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Research Article

The Human Urine Metabolome

Affiliation Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada

Affiliation Department of Computing Sciences, University of Alberta, Edmonton, Alberta, Canada

Affiliation Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America

Affiliation BIOCRATES Life Sciences AG, Innsbruck, Austria

•  [ ... ],

* E-mail: [email protected]

Affiliations Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada, Department of Computing Sciences, University of Alberta, Edmonton, Alberta, Canada, National Institute for Nanotechnology, Edmonton, Alberta, Canada

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• Souhaila Bouatra, 
• Farid Aziat, 
• Rupasri Mandal, 
• An Chi Guo, 
• Michael R. Wilson, 
• Craig Knox, 
• Trent C. Bjorndahl, 
• Ramanarayan Krishnamurthy, 
• Fozia Saleem, 

• Published: September 4, 2013
• https://doi.org/10.1371/journal.pone.0073076
• Reader Comments

Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca .

Citation: Bouatra S, Aziat F, Mandal R, Guo AC, Wilson MR, Knox C, et al. (2013) The Human Urine Metabolome. PLoS ONE 8(9): e73076. https://doi.org/10.1371/journal.pone.0073076

Editor: Petras Dzeja, Mayo Clinic, United States of America

Received: June 7, 2013; Accepted: July 9, 2013; Published: September 4, 2013

Copyright: © 2013 Bouatra et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: Funding for this research has been provided by Genome Canada, Genome Alberta, The Canadian Institutes of Health Research, Alberta Innovates BioSolutions, Alberta Innovates Health Solutions, The National Research Council, The National Institute of Nanotechnology. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: Ralf Bogumil and Cornelia Roehring are employed by BIOCRATES Life Sciences AG. This company produces kits for targeted metabolomic analyses. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

Introduction

Metabolomics is a relatively young branch of “omics” science concerned with the systematic study of the chemical products or metabolites that cells and organisms generate. Because metabolites are the downstream products of numerous genome-wide or proteome-wide interactions, the metabolome (the sum of all metabolites in an organism) can be a very sensitive measure of an organism’s phenotype. This fact has made metabolomics particularly useful in the study of environment-gene interactions [1] , [2] , [3] , [4] , the identification of disease biomarkers [5] , [6] , [7] , [8] , [9] and the discovery of drugs [10] . Unlike its older “omics” cousins, where complete or near-complete coverage of the genome or proteome is fairly routine, metabolomics still struggles to cover even a tiny fraction of the metabolome. Indeed, most human metabolomic studies published today, even those exploiting the latest and most sensitive LC-MS/MS technologies, typically succeed in identifying or characterizing fewer than 100 compounds [11] , [12] , [13] , [14] . This corresponds to less than 1% of the known human metabolome [15] , [16] . In an effort to help improve this situation, we (and others) have started to undertake the systematic characterization of various human biofluid metabolomes. This includes the human cerebrospinal fluid metabolome [17] , [18] , the human saliva metabolome [19] , and the human serum metabolome [20] . We have now turned our attention to characterizing the human urine metabolome.

Urine, as produced by mammals, is a transparent, sterile, amber-colored fluid generated by the kidneys. The kidneys extract the soluble wastes from the bloodstream, as well as excess water, sugars, and a variety of other compounds. The resulting urine contains high concentrations of urea (from amino acid metabolism), inorganic salts (chloride, sodium, and potassium), creatinine, ammonia, organic acids, various water-soluble toxins and pigmented products of hemoglobin breakdown, including urobilin, which gives urine its characteristic color. Urination is the primary route by which the body eliminates water-soluble waste products. The average adult generates between 1.5–2.0 liters of urine per day, which over the course of their lifetime would be enough to fill a small backyard swimming pool (5 X 8 X 1.5 m).

While largely viewed as a waste product, urine has considerable value as a diagnostic biofluid. Indeed the analysis of urine for medical purposes dates back to ancient Egypt [21] , [22] , [23] , [24] . Hippocrates largely legitimized the medical practice of uroscopy (the study of urine for medical diagnostics) where examination of the color, cloudiness, smell and even the taste of urine was used to identify a variety of diseases. Throughout the Byzantine era and well into the Middle Ages, urine color wheels (a diagram that linked the color of urine to a particular disease) were commonly used by physicians to make diagnoses [21] , [25] . A brownish color would indicate jaundice, a red hue (blood) might indicate urinary tract tumors, absence of color would be indicative of diabetes and foamy urine would indicate proteinuria. With the advent of modern clinical techniques in the middle of the 19 th century, uroscopy largely disappeared. However, urine has continued to be an important cornerstone to modern medical practice. In fact, it was the first biofluid to be used to clinically diagnose a human genetic disease - alkaptonuria [26] . Even today urine analysis is routinely performed with dipstick tests that can readily measure urinary glucose, bilirubin, ketone bodies, nitrates, leukocyte esterase, specific gravity, hemoglobin, urobilinogen and protein. More detailed urinalysis can be also used to study a variety of renal conditions, such as bladder, ovarian and kidney diseases [27] , [28] , [29] , [30] .

Being an important and easily accessible biological fluid, urine has been the subject of detailed chemical analysis for more than 100 years [31] , [32] . Extensive tables of normal reference ranges have been published for more than 100 urine ions and metabolites [33] , [34] , [35] , [36] , [37] . In addition to these referential clinical chemistry studies, several groups have applied various “global” metabolomic or metabolite profiling methods to urine, such as high resolution nuclear magnetic resolution (NMR) spectroscopy [38] , [39] , [40] , high performance liquid chromatography (HPLC) [41] , high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) [42] , ultra high performance liquid chromatography-high resolution orbitrap mass spectrometry (UHPLC-HRMS) [43] , ultra high performance liquid chromatography (UPLC-RP) [31] , [44] , fast atom bombardment ionization coupled with mass spectroscopy (FAB-MS) [35] , two-dimensional gas chromatography coupled to quadrupole mass spectrometry (GCxGC-MS) [32] or time-of-flight mass spectrometry (GCxGC-TOF-MS) [37] , nanoflow liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) [33] and liquid chromatography coupled with electrospray quadruple time-of-flight mass spectrometry (LC/QTOF-MS) [36] . A combination of two or more profiling methods has also been used by many research groups to help improve metabolite coverage [34] , [40] .

A comprehensive list of methods used to analyze urine and the numbers of metabolites identified and/or quantified by these methods (along with references) is provided in Table 1 . As seen from this table, it is possible to (tentatively) identify up to 294 different metabolites in human urine. However, quantification is somewhat more difficult, with the largest number of quantified metabolites ever reported in human urine being slightly less than 100. In addition to these global metabolomic studies, hundreds of other “targeted” or single-metabolite studies have been conducted on human urine that have led to the identification and quantification of hundreds of other urine metabolites. Unfortunately, this information is not located in any central repository. Instead it is highly dispersed across numerous textbooks and periodicals [16] .

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https://doi.org/10.1371/journal.pone.0073076.t001

To facilitate future research into urine chemistry and urine metabolomics, we believe it is critical to establish a comprehensive, electronically accessible database of the detectable metabolites in human urine. This document describes just such a database, one that contains the metabolites that can, with today’s technology, be detected in human urine along with their respective concentrations and disease associations. This resource was assembled using a combination of both our own experimental and literature-based research. Experimentally, we used high-resolution NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection tandem mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) with ultraviolet (UV) or fluorescence detection (FD) techniques performed on multiple human urine samples to identify 445 metabolites or metabolite species and quantify 378 of these compounds. To complement these “global” metabolic profiling efforts, our team also surveyed and extracted metabolite and disease-association data from more than 3000 books and journal articles that had been identified through computer-aided literature and in-house developed text-mining software. This “bibliomic” effort yielded data for another 2206 metabolites. The resulting Urine Metabolome Database (UMDB - http://www.urinemetabolome.ca ) is a comprehensive, web-accessible resource containing a total of 2651 confirmed urine metabolites or metabolite species (corresponding to 3079 defined structures), their corresponding concentrations and their disease associations that were revealed or identified from these combined experimental and literature mining efforts.

Results and Discussion

The content of the human urine metabolome – the urine metabolome database.

The Urine Metabolome Database (UMDB: http://www.urinemetabolome.ca ) contains a complete list of all (to the best of our knowledge) possible metabolites that have been detected in human urine using current technologies. The UMDB is freely available, easily queried, web-enabled database which provides a list of the metabolite names, level of verification (confirmed or probable), normal and disease-associated concentration ranges, associated diseases and corresponding literature references for all human urine metabolites that have ever been detected and/or quantified in the literature. The UMDB also contains concentration data compiled from the experimental studies described here. Each urine metabolite entry in this database is linked to a MetaboCard button [15] , [16] that, when clicked, brings up detailed information about that particular entry. This detailed information includes nomenclature, chemical, clinical and molecular/biochemical data. Each MetaboCard entry contains up to 120 data fields many of which are hyperlinked to other databases (KEGG [45] , PubChem [46] , MetaCyc [47] , ChEBI [48] , PDB [49] , UniProt [50] , and GenBank [51] as well as to GeneCard IDs [52] , GeneAtlas IDs [53] and HGNC IDs [54] for each of the corresponding enzymes or proteins known to act on that metabolite). Additionally, the UMDB through its MetaboCard/HMDB links includes nearly 450 hand-drawn, zoomable and fully hyperlinked human metabolic pathway maps (SMPDB: http://www.smpdb.ca/ ). These maps are intended to help users visualize the chemical structures on metabolic pathways and to get detailed information about metabolic processes [55] . These UMDB pathway maps are quite specific to human metabolism and explicitly show the subcellular compartments where specific reactions are known to take place.

The UMDB’s simple text query (TextQuery) supports general text queries including names, synonyms, conditions and disorders. Clicking on the Browse button (on the UMDB navigation panel) generates a tabular view that allows users to casually scroll through the database or re-sort its contents by compound name or by concentration. Users can choose either the “Metabolite View”, “Concentration View” or “Diseases View” to facilitate their browsing or searching. Clicking on a given MetaboCard button brings up the full data content (from the HMDB) for the corresponding metabolite. Users may also search the database using a variety of options listed uner the “Search” menu. For instance, the ChemQuery button allows users to draw or write (using a SMILES string) a chemical compound to search the UMDB for chemicals similar or identical to the query compound. ChemQuery also supports chemical formula and molecular weight searches. The Sequence Search button allows users to conduct BLAST sequence searches of the 4075 protein sequences contained in the UMDB. Both single and multiple sequence BLAST queries are supported. “Advanced Search” which is also located under the “Search” menu is the most sophisticated search tool in the UMDB and opens an easy-to-use query search tool that allows users to select or search over various combinations of subfields. The UMDB’s “MS Search” allows users to submit mass spectral peak lists that will be searched against the Human Metabolome Database (HMDB)’s library of MS/MS spectra. This potentially allows facile identification of urine metabolites from mixtures via MS/MS spectroscopy. UMDB’s NMR Search allows users to submit peak lists from 1 H or 13 C NMR spectra (both pure and mixtures) and have these peak lists compared to the NMR libraries contained in the HMDB. This allows the identification of metabolites from mixtures via NMR spectral data. The Download button provides links to collected sequence, image and text files associated with the UMDB. In the About menu, the “Data Fields Explained” button lists source data used to assemble the UMDB.

Currently the UMDB contains information on 2651 detectable metabolites or metabolite species (which corresponds to 3079 metabolites with precisely defined structures) and 3832 concentration ranges or values associated with 220 different conditions, diseases and disorders. The number of metabolites in the UMDB is not a number that will remain unchanged. Rather it reflects the total number of metabolites – most of which are endogenous - that have ever been detected and/or quantified by ourselves and others. Certainly as technology improves, we anticipate this number will increase as other, lower abundance, metabolites are detected and added to future versions of the UMDB. Likewise, if the list was expanded to include intermittent, exogenous compounds such as all possible drugs or drug metabolites or rare food additives and food-derived phytochemicals, the database could be substantially larger.

Inspection of the on-line tables in UMDB generally shows that human urine contains a substantial number of hydrophilic molecules. This is further reiterated in Table 2 , which provides a listing of the chemical “superclasses” (using the HMDB definitions) in human urine and the number of representative compounds that can be found in this biofluid. Excluding lipids (which are in very low concentration), human urine is dominated by amino acids and derivatives, carbohydrates and carbohydrate conjugates. This simply reinforces the fact that urine is a key carrier of hydrophilic waste products. Other small molecule components found in high abundance in urine include hydroxy acids and derivatives (such as citric acid), urea, ammonia, creatinine and hippuric acid. A more detailed description of both our literature and experimental findings is given in the following 7 sections covering: 1) Literature Review/Text Mining; 2) NMR; 3) DFI/LC-MS/MS; 4) GC-MS; 5) ICP-MS; 6) HPLC/UV and 7) HPLC/FD.

https://doi.org/10.1371/journal.pone.0073076.t002

Metabolite Concentration in Urine – Literature Survey

In addition to the experimentally derived values obtained for this study, the urine metabolome database (UMDB) also presents literature-derived concentrations of urine metabolites with references to either PubMed IDs or clinical textbooks. In many cases, multiple concentration values are given for “normal” conditions. This is done to provide users/readers with a better estimate of the potential concentration variations that different technologies or laboratories may measure. As a general rule, there is good agreement between most laboratories and methods. However, the literature results presented in the UMDB do not reflect the true state of the raw literature. A number of literature-derived concentration values were eliminated through the curation process after being deemed mistaken, disproven (by subsequent published studies), mis-typed or physiologically impossible. Much of the curation process involved having multiple curators carefully reading and re-reading the primary literature to check for unit type, unit conversion and typographical inconsistencies.

Other than the inorganic ions and gases such as sodium (14.7 ± 9.0 mM/mM creatinine – average value), chlorine (8.8 ± 6.2 mM/mM creatinine), potassium (4.6 ± 0.1 mM/mM creatinine), ammonia (2.8 ± 0.9 mM/mM creatinine), the 4 most abundant organic metabolites found in urine (based on average values) are urea (22.5 ± 4.4 mM/mM creatinine), creatinine (10.4 ± 2.0 mM), hippuric acid (298.5 ± 276.8 µM/mM creatinine) and citric acid (280.6 ± 115.2 µM/mM creatinine). The least abundant (detectable) metabolites in urine include oxytocin (0.9 ± 0.1 pM/mM creatinine), angiotensin II (1.2 ± 0.2 pM/mM creatinine), 15-deoxy-d-12,14-PGJ2 (2.3 ± 1.0 pM/mM creatinine) and melatonin (3.3 ± 2.7 pM/mM creatinine). This shows that the current lower limit of detection for metabolites in urine is in the low pM/mM creatinine range and that the concentration range of analytes in urine spans nearly 11 orders of magnitude.

One point that is particularly interesting is the fact that the concentration (scaled to creatinine) of the average metabolite in normal urine varies by about ± 50%, with some metabolites varying by as much as ± 350% (such as normetanephrine (0.00085 ± 0.00317 µM/mM creatinine), pipecolic acid (0.03 ± 0.07 µM/mM creatinine), enterodiol (0.032 ± 0.072 µM/mM creatinine), tungsten (0.010 ± 0.022 µM/mM creatinine) and chlorogenic acid (0.0014 ± 0.0029 µM/mM creatinine). Therefore, drawing conclusions about potential disease biomarkers without properly taking into account this variation would be ill-advised. We believe that these relatively large metabolite concentration ranges are due to a number of factors, including age, gender, genetic background, diurnal variation, health status, activity level and diet [56] , [57] , [58] , [59] . Indeed, some UMDB entries explicitly show such variations based on the populations (age, gender) from which these metabolite concentrations were derived. Clearly more study on the contributions to the observed variations in urine is warranted, although with thousands of metabolites to measure for dozens of conditions, these studies will obviously require significant technical and human resources.

Experimental Quantification and Identification of Urine Metabolites – NMR

A representative high-resolution NMR spectrum of urine from a healthy individual is shown in Figure 1 . As can be readily seen from this figure, urine NMR spectra are very information-rich and surprisingly complex, with thousands of resolved peaks. From the 22 healthy control urine samples analyzed, we could identify a total of 209 unique compounds with an average of 167 ± 19 compounds being identified per sample. Every compound was unequivocally identified and quantified using spectral fitting (via Chenomx) and/or spike-in experiments with authentic standards. The concentration of each metabolite was normalized to each urine sample’s corresponding creatinine value to compensate for variations in urine volume (the concentration of metabolites is expressed as µM/mM creatinine).

Numbers indicates the following metabolites: 1: creatinine; 2: citric acid; 3: glycine; 4: formic acid; 5: methanol; 6: guanidoacetic acid; 7: acetic acid; 8: L-cysteine; 9: glycolic acid; 10: creatine; 11: isocitric acid; 12: hippuric acid; 13: L-glutamine; 14: L-alanine; 15: L-lysine; 16: gluconic acid; 17∶2- hydroxyglutaric acid; 18: D-glucose; 19: indoxyl sulfate; 20: trimethyl-N-oxide; 21: ethanolamine; 22: L-lactic acid; 23: taurine; 24: L-threonine; 25: dimethylamine; 26: pyroglutamic acid; 27: trigonelline; 28: sucrose; 29: trimethylamine; 30: mannitol; 31: L-serine; 32: acetone; 33: L-cystine; 34: adipic acid; 35: L-histidine; 36: L-tyrosine; 37: imidazole; 38: mandelic acid; 39: dimethylglycine; 40: Cis-aconitic acid; 41: urea; 42∶3-(3-hydroxyphenyl)-3-hydroxypropanoic acid (HPHPA); 43: phenol; 45: isobutyric acid; 46: methylsuccinic acid; 47∶3-aminoisobutyric acid; 48: L-fucose; 49: N-acetylaspartic acid; 50: N-acetylneuraminic acid; 51: acetoacetic acid; 52: Alpha-aminoadipic acid; 53: methylguanidine; 54: phenylacetylglutamine.

https://doi.org/10.1371/journal.pone.0073076.g001

The 209 compounds identified and quantified from these NMR studies represent a “high-water” mark for NMR-based metabolomics. Previous studies have reported up to 70 compounds being identified and/or quantified in human urine [40] . Indeed, compared to other platforms previously used to analyze human urine ( Table 1 ), it appears that NMR may currently be the most comprehensive and certainly the most quantitative approach to characterizing this biofluid. Based on the fitted area under each urinary NMR spectrum and the number of unidentified peaks we estimate that more than 96% of the spectral area and more than 92% of all NMR-detectable compounds in our human urine samples are listed in Table 3 . In other words, for NMR-based metabolomics, human urine is essentially “solved”. The same “solved” status has already been achieved for human serum (with 49 definitive compounds, [20] ) and for human cerebrospinal fluid (with 53 definitive compounds, [17] ). Knowing the expected or detectable composition of these biofluids should open the door to automated NMR-based metabolomics [60] .

https://doi.org/10.1371/journal.pone.0073076.t003

Based on these NMR studies, the most abundant constituents (based on average values) of urine from a healthy individual are urea (12.3 ± 14.5 mM/mM creatinine), creatinine (14.7 ± 9.8 mM), hippuric acid (229 ± 160 µM/mM creatinine) and citric acid (203 ± 129 µM/mM creatinine). The least abundant compounds were trans-ferulic acid (1.2 µM/mM creatinine), phosphorylcholine (1.1 ± 0.7 µM/mM creatinine), 4-ethylphenol (0.9 ± 0.1 µM/mM creatinine), 2-methylglutaric acid (0.8 ± 0.4 µM/mM creatinine). The lowest concentrations that could be reliably detected using NMR were 0.4 ± 0.1 µM/mM creatinine (for maleic acid), 0.5 ± 0.2 µM/mM creatinine (for alpha-ketoisovaleric acid and N-acetylputrescine) and 0.7 ± 0.4 µM/mM creatinine (for fumaric acid). The complete list of average compound concentrations (including their range), literature-reported concentrations (for healthy adult) and the frequency of their occurrence is shown in Table 3 . In general, there is good agreement between the NMR-measured concentrations and those reported in the literature (often obtained by other analytical techniques).

However, not all of the NMR-derived urine concentrations agree with literature-derived values. A total of 34 compounds had average concentrations somewhat higher (>1 SD) than previously reported values (for example, 1, 3-dimethyluric acid, glucaric acid, L-aspartic acid, mannitol), while 21 compounds had average concentrations lower (<1 SD) than previously reported (for example, 1-methylhistidine, phenol, dihydrothymine, thymidine). Another 7 metabolites also exhibited somewhat greater range in concentrations than those previously reported in the literature. These included: acetic acid, butyric acid, isovaleric acid, lactose, phenylglyoxylic acid, proline-betaine and trans-ferulic acid. Some of these discrepancies are likely due to differences in diet, physiological status, pharmacological effects and the age of the different cohorts that were analyzed. Other differences may be due to storage effects, sample preparation methods and the analytical methods being used. As a rule, NMR concentration determinations are very accurate since they involve direct measurement of the compound, as opposed to an indirect measurement of a derivative compound. Therefore we are quite confident in the NMR concentration values reported in Table 3 and would tend to view these as more reliable than those measured via other technologies.

A number of the compounds exhibiting higher-than or lower-than-reported concentrations appear to be associated with dietary intake. For example, mannitol is a sugar alcohol that is poorly absorbed by humans but its presence in urine can be explained by its occurrence in commonly consumed foods such as apples, pineapples, asparagus and carrots. Likewise, the urinary excretion of trans-ferulic acid (a polyphenolic derivative) increases after the ingestion of breakfast cereals [61] and chocolate. The relatively low value we measured is likely due to the fact that the literature value of trans-ferulic acid reported in Table 3 was measured for people on a special diet [62] . Also, the low level of proline-betaine we measured in urine may be due to a lower frequency of exposure to dietary citrus fruits in our population sample [63] . Proline-betaine is an osmoprotectant found in citrus fruit and urinary excretion of this metabolite is increased after consumption of fruits such as orange juice [64] . Similarly the higher levels of dimethyl sulfone we detected in urine could be attributed to dietary sources that contain DMSO [65] . For example, onions contain many sulfoxides including DMSO which can be oxidized in the liver and kidneys to produce dimethyl sulfone [66] , [67] . The consumption of meat could also significantly increase the concentration of some metabolites in urine as reported in the case of 1-methylhistidine [68] . 1-methylhistidine is produced from the metabolism of anserine (a dipeptide) which is commonly found in meats [69] , [70] . In addition to diet, metabolite levels in urine can also be affected by physiological status. For instance, the level of 3-hydroxybutyric acid in urine increases during fasting and can range from 0 to 200 µM/mM creatinine, with the maximum level reported in the literature (200 µM/mM creatinine) corresponding to healthy male after 35 h of fasting [50] .

Some of the metabolites we measured by NMR did not have any previously reported literature values. For example, glucuronic acid is usually reported as total glucuronic acid (the free acid plus glucuronide conjugates) after hydrolysis [71] , [72] . Here we report the concentration of free glucuronic acid, as indicated in Table 3 . Another example, 2-methylerythritol, was previously detected in human urine but no concentration was reported [73] . The urinary excretion of 2-methylerythritol is most likely a result of dietary consumption of fruits or vegetables containing 2-methylerythritol and/or 2-methylerythritol-4-phosphate. 2-methylerythritol-4-phosphate is an intermediate in isoprenoid biosynthesis [74] and has been found to be quite abundant in certain plants [75] .

A number of compounds we measured by NMR appear to be normal constituents of human urine but seem not to have been previously reported as being detectable by NMR (a total of 42 compounds) or reported as detected but not-quantified by any other method (a total of 8 compounds). The identification of these “NMR-novel” compounds was aided by their prior identification by GC-MS and DI-MS (see following sections) and through a careful literature analysis of compounds that had previously been detected in human urine via other methods. The list of detected but not previously quantified by NMR compounds includes: 2-hydroxy-3-methylpentanoic acid, 2-methyl-3-ketovaleric acid, 2-methylerythritol, glucuronic acid, monomethyl glutaric acid, N-methylhydantoin, phosphorylcholine and scyllitol. All of these compounds were confirmed using authentic standards.

This NMR study also revealed a number of common identification errors made in previously published NMR-based human urine metabolomic studies. In particular, several earlier reports identified phenylacetylglycine [76] , N-acetylglutamic acid [77] , cresol [78] , isonicotinic acid [78] , yellow 7.1 [79] , meta-hydroxyphenylpropionic acid [80] , 2-oxoisocaproic acid [81] , urocanic acid, glycylproline and ornithine [80] as being detectable by NMR in human urine. Using our NMR instrument and the samples available to us, we were unable to detect any of these compounds, even after performing multiple spike-in experiments using authentic compounds. While some of these metabolites have been previously reported to be in human urine, they were reported at concentrations far below the lower limit of detection of modern NMR instruments (which is ∼ 1 µM). Due to their chemical shift similarity, phenylacetylglycine (which is found only in rats and mice) and N-acetylglutamic acid appear to be commonly mistaken for phenylacetylglutamine. We also noticed that, isonicotinic acid (a breakdown product of isoniazid and hydrazine derivatives, which is found only in individuals that have taken isoniazid and other hydrazine derivatives as a drug) appears to be mistaken for trigonelline. Likewise cresol (water-insoluble) appears to be frequently mistaken for cresol-sulfate (water-soluble), while the compounds yellow 7.1, meta-hydroxyphenylpropionic acid and 3-(p-hydroxyphenyl)-propionic acid appear to be commonly mistaken for 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid (HPHPA).

In addition to correcting these compound identification errors, we also observed some significant gender-related effects on creatinine levels in our urine samples. Since males generally have a greater mass of skeletal muscle than females, they tend to have higher urinary levels of creatinine than women. This was clearly evident in our samples as the average male creatinine level was 20 mM while the average female creatinine level was 11 mM. In addition, increased dietary intake of creatine or a protein-rich diet can increase daily creatinine excretion [82] .

Quantification and Identification of Urine Metabolites – GC-MS

As seen in Table 1 , GC-MS methods have long been used to comprehensively characterize the chemical content of human urine. For our studies a total of 4 different GC-MS analyses were performed. The first method employed polar solvent extraction and derivatization to achieve broad metabolite coverage of polar metabolites, the second was more selective and targeted organic acids, the third targeted volatiles, while the fourth targeted bile acids. Representative high-resolution GC-MS total ion chromatograms are shown in Figures 2 – 4 for each of these analyses (except for the bile acids). Combined, the 4 GC-MS methods allowed us to identify 179 and quantify a total of 85 compounds. Table 4 shows the identified polar, organic acid extracts and bile acids (127 in total), Table 5 shows the identified volatile metabolites (52 in total) while Table 6 shows the 85 fully quantified compounds from all 4 techniques. These numbers actually represent the highest number of urine metabolites both identified and quantified by GC-MS to date. As seen in Table 1 , previous GC-MS studies have reported up to 258 unique compounds being identified (but none quantified) [83] and approximately 95 compounds quantified in human urine [84] . Relative to NMR (see previous section) and other methods used to analyze human urine ( Table 1 ), it appears that a multi-pronged GC-MS analysis is an excellent approach to characterize this biofluid. However, unlike NMR where nearly all detectable peaks are identifiable, metabolite coverage by GC-MS tends to be relatively incomplete. As seen in Figure 2 , only 60% of the peaks could be identified using as reference the 2008 NIST library and other home-made GC-MS metabolite libraries. Likewise, in Figure 3 , we see that only 65% of the organic acid peaks could be identified while in Figure 4 , just 60% of the volatile compound peaks could be identified.

Numbers indicate the following metabolites (quantified compounds): 1: L-valine; 2: oxalic acid; 3∶3-hydroxyisobutyric acid; 4: L-serine; 5: glycine; 6: succinic acid; 7: glyceric acid; 8∶4-deoxythreonic acid; 9∶2,4-dihydroxybutanoic acid; 10∶3,4-dihydroxybutanoic acid; 11: adipic acid; 12: creatinine; 13: threonic acid; 14: L-phenylalanine; 15: p-hydroxyphenylacetic acid; 16: L-ornithine; 17: L-asparagine; 18: L-arabinose; 19: D-xylitol; 20: D-xylulose; 21: Cis/Trans-aconitic acid; 22: hippuric acid; 23: isocitric acid; 24: D-galactose; 25: D-glucose; 26: L- tyrosine; 27: sorbitol; 28: gluconic acid; 29: scyllitol; 30: myoinositol; 31: uric acid; 32: pseudouridine.

https://doi.org/10.1371/journal.pone.0073076.g002

Numbers indicate the following metabolites (quantified compounds): 1: pyruvic acid; 2: L-lactic acid; 3: alpha-hydroxyisobutyric acid; 4: glycolic acid; 5: levulinic acid; 6∶3-hydroxyisovaleric acid; 7∶2-hydroxy-2-methylbutyric acid; 8: hydroxypropionic acid; 9∶2-methyl-3-hydroxybutyric acid; 10: malonic acid; 11∶3-hydroxyisovaleric acid; 12: methylmalonic acid; 13∶2-ethylhydracrylic acid; 14: benzoic acid; 15: phosphoric acid; 16: ethylmalonic acid; 17: succinic acid; 18: methylsuccinic acid; 19∶4-deoxythreonic acid; 20∶5-hydroxyhexanoic acid; 21: citraconic acid; 22: glutaric acid; 23: m-chlorobenzoic acid; 24; 3,4-dihydroxybutanoic acid; 25∶3-methylglutaconic acid; 26: adipic acid; 27: pyroglutamic acid; 28∶3-methyladipic acid; 29: sumiki’s acid; 30: o-hydroxyphenylacetic acid; 31: oxoglutaric acid; 32: pimelic acid; 33∶3-hydroxymethylglutaric acid; 34∶3-hydroxyphenylacetic acid; 35∶4-hydroxybenzoic acid; 36∶2-furoylglycine; 37: suberic acid; 38: quinolinic acid; 39: Cis/Trans-aconitic acid; 40: homovanillic acid; 41: azelaic acid; 42: hippuric acid; 43∶3,4-dihydroxybenzeneacetic acid; 44∶3-(3-hydroxyphenyl)-3-hydroxypropanoic acid (HPHPA); 45: vanillylmandelic acid; 46∶4-hydroxyphenyllactic acid; 47: indoleacetic acid; 48: palmitic acid; 49: kynurenic acid; 50∶3-hydroxyhippuric acid; 51∶3-hydroxysebacic acid; 52: Trans-ferulic acid; 53∶5-hydroxyindoleacetic acid; 54: stearic acid.

https://doi.org/10.1371/journal.pone.0073076.g003

Numbers indicate the following metabolites: 1∶3-methyl sulfolane; 2∶3-hexanone; 3∶2-pentanone; 4∶1-hydroxy-2-pentanone; 5: allyl methylsulphide; 6: dimethyl disulfide; 7∶4-heptanone; 8∶1-methylcyclohexanol; 9; 2-hexanone; 10∶3,4-dimethylthiophene; 11: diallyl sulphide; 12∶5-methyl-2-hexanone; 13∶1,3-dithio cyclohexane; 14: dimethyl trisulfide; 15: phenol; 16: o-cymene; 17: p-cymene; 18: m-cymene; 19∶1,4-cineol; 20: p-cresol; 21: linalool oxide; 22: iso-menthol; 23: Alpha-p-dimethylstyrene; 24: L-menthol; 25: undecane; 26: ledene oxide (II); 27: salicylic acid methyl ester; 28: Beta-carvone; 29: piperitone; 30: o-thymol; 31: Beta-cyclocitrol; 32∶4,7-dimethyl-benzofuran; 33: cuminal: 34∶2,6,10,10 Tetramethyl-oxa-spiro-4,5-dec-6-ene; 35∶4-(2,6,6-trimethyl-1-cyclohexen-1-yl)-2-butanone; 36∶1,2,3,4-tetrahydro-1,1,6-trimethyl naphthalene; 37: Alpha-cedrene; 38∶1,2,3,4-tetrahydro-1,5,7-trimethylnapthalene; 39∶1,2-diydro-1,1,6-trimethyl-napthalene; 40: Beta-guaiene; 41: Beta-damascenone; 42∶2,5-cyclohexadiene-1,4-dione-2,6-di-tert-butyl; 43: himachalene; 44∶4-(2,6,6-trimethylcyclohexa-1,3-dienyl)-but-3-en-2-one: 45∶1-(2,6,6-trimethyl-1-cyclohexen-1-yl)-1-penten-3-one; 46∶2,4-Bis (1,1-dimethylethyl)-phenol; 47∶1-(2,3,6-trimethyl phenyl)-3-buten-2-one; 48: L-calamenene; 49: Beta-vatirenene; 50∶1,6,7-trimethylnaphthalene; 51: azulol; 52∶3,3,5,6-tetramethyl-1-indanone.

https://doi.org/10.1371/journal.pone.0073076.g004

https://doi.org/10.1371/journal.pone.0073076.t004

https://doi.org/10.1371/journal.pone.0073076.t005

https://doi.org/10.1371/journal.pone.0073076.t006

Incomplete compound identification is a common problem with global or untargeted GC-MS metabolomics. This may be due to any number of factors including spectral overlap due to incomplete separation, poor signal to noise for low intensity peaks, the lack of reference GC-MS spectral data for certain metabolites (especially unusual dietary sources), or the presence of spectral artefacts such as derivatization by-products or degraded metabolites in the GC-MS spectrum. For our GC-MS studies we used the NIST library supplemented with a home-made GC-MS reference library of known urine compounds assembled from the Human Metabolome Library [16] . No doubt the use of other commercially available reference GC-MS libraries such as the Fiehn GC-MS library from Agilent or the GOLM metabolome database library [85] might have allowed us to further increase our coverage. Likewise the use of a faster scan rate and/or a more sensitive GC-TOF instrument (instead of a slower scanning quadrupole GC-MS) certainly would have increased overall coverage.

Nearly all of the non-volatile metabolites (87) identified by our GC-MS analyses were also identified by NMR. Some of the exceptions were oxalic acid, phosphate and uric acid, each of which was detected by GC-MS but not by NMR. These compounds do not have NMR-detectable protons at physiological pH, making them essentially “NMR invisible”. Other compounds seen by GC-MS but not by NMR included metabolites that were generally below the detection limit of NMR (∼2 µM/mM creatinine) such as indolelactic acid and 2,4-dihydroxybutanoic acid. For our non-targeted GC-MS analysis, the lower limit of detection was 1 µM/mM creatinine (for 2,4-dihydroxybutanoic acid), while for our targeted organic acid GC-MS analysis the lower limit of detection was 0.7 µM/mM creatinine (for m-chlorobenzoic acid). Overall, our data suggests that the sensitivity of a standard single quadrupole GC-MS instrument is perhaps 1.5–2X better than a 500 MHz NMR instrument for water-soluble metabolites. It is also important to note that the level of water-soluble, non-volatile metabolite coverage obtained by GC-MS is not as great as seen with NMR (127 cmpds vs. 209 cmpds). The limited coverage of GC-MS is partly due to the fact that not all compounds can be readily extracted, easily derivatized or routinely separated on a GC column. Furthermore, when analyzing urine by GC-MS there is a need to pretreat the sample with urease (to reduce urea levels) that can diminish the abundance of some metabolites [86] . While GC-MS may not be the best method for analyzing water-soluble metabolites, it certainly excels at the detection of volatile metabolites. Indeed, only one of the volatile metabolites identified by GC-MS is identified by NMR (phenol). This certainly underlines a key strength of GC-MS relative to other metabolomics platforms. When comparing NMR to GC-MS we found that NMR is capable of detecting 121 compounds that the 4 combined GC-MS methods cannot detect while the combined GC-MS methods can detect 91 compounds that NMR cannot routinely detect. Overall, these data suggest that GC-MS and NMR appear to be complementary methods for the identification and quantification of small molecules in urine.

Among the 58 metabolites quantified by both GC-MS and NMR we found very good overall agreement, with the majority of measured concentration values falling within 20 ± 11% of each other. The concentration patterns and rankings of the most abundant to the least abundant compounds were also largely identical for the two platforms. A total of 12 metabolites exhibited somewhat larger concentration discrepancies between GC-MS and NMR (i.e; L-arabinose, L-serine (lower in GC-MS vs. NMR), 4-hydroxybenzoic acid and tyrosine (higher in GC-MS vs NMR). Some of these concentration differences may be due to the extraction or derivatization process needed to conduct GC-MS analyses. This can lead to unspecified compound losses, unusual derivatives or unrecognized fragmentation patterns. Therefore we would have expected at least a few GC-MS concentration values to be slightly lower than those seen by NMR. Likewise, it is important to remember that there are inherent errors (5–10%) in measuring peak areas (i.e. compound concentrations) both in GC-MS and NMR due to peak overlap, uneven baselines and spectral noise.

Nearly all of the compounds we detected or quantified in human urine by GC-MS have been previously described or mentioned in the GC-MS literature. One compound (scyllitol), however, appears not to have been previously detected by GC-MS. The identification of this compound by our GC-MS method was aided by its prior identification by NMR (see previous section). Additionally, a careful literature analysis also indicated the scyllitol is a normal constituent of human urine and has previously been detected in human urine via other methods.

As we noted with our NMR studies earlier, there are a few previously reported GC-MS detectable metabolites in human urine that appear to be artefacts. These artefactual metabolites may arise from extractions with different solvents, pre-treatment with urease, and chemical derivatization. For example, Shoemaker et al [84] , reported the presence of bisethane in human urine. We also detected bisethane, but it appears to be artefact of chemical derivatization and is not a urine metabolite.

Quantification and Identification of Urine Metabolites – Combined Direct Flow Injection and LC-MS/MS Assay

Direct flow injection (DFI) MS/MS or DFI-MS/MS is another commonly used global metabolic profiling method [87] . When isotopic standards are used along with multiple reactions monitoring (MRM), it is also possible to perform targeted metabolomics with very accurate concentration measurements. For our urine studies, we employed a combined DFI/LC-MS/MS approach, based on the commercially available AbsoluteIDQ p180 Kit (BIOCRATES Life Sciences AG, Innsbruck). When applied to urine, we were able to identify and quantify a total of 127 metabolites or metabolite species, including 34 acylcarnitines, 21 amino acids, 15 biogenic amines, creatinine, hexose, 35 phospatidylcholines, 15 sphingomyelins and 5 lysophosphatidylcholines. The amino acids and biogenic amines are analyzed by an LC-MS/MS method, whereas all other metabolites are analyzed by DFI-MS/MS as indicated in Table 7 . DFI-MS/MS identifies lipid species (as opposed to specific lipids) using their total acyl/alkyl chain content (i.e. PC (38∶4)) rather than their unique structure. Therefore each lipid species identified by the BIOCRATES kit typically corresponds to 5–10 possible unique lipid structures. Consequently, the total number of phosphatidylcholines, sphingolipids and lysophosphatidylcholines structures identified by this method was 458, 19 and 6, respectively. Therefore, combining these probable lipid structures (483 in total, based on the known fatty acid and lipid composition in human serum) with the other 72 confirmed non-lipid metabolites, the DFI-MS/MS method yields 555 confirmed and probable metabolites or metabolite structures. All of these compounds, along with their corresponding estimated concentrations have all been entered into the UMDB.

https://doi.org/10.1371/journal.pone.0073076.t007

Our results show very good agreement with the previous studies conducted by BIOCRATES on human urine samples (Biocrates Application Note 1005-1). We found that the lower limit of quantification by DFI MS/MS based on the Absolute IDQ kit was 0.1 nM/mM creatinine for certain phosphatidylcholine species (i.e. PC aa C40∶3) and 0.1 nM/mM creatinine for certain sphingomyelin species (i.e. SM 26∶1). Comparison of our lipid results with literature data was difficult as relatively few papers report urine lipid concentration data. Indeed, the presence of lipids in urine is a little unexpected, but not entirely unreasonable. It is likely that urea, a well known chaotrope, facilitates the dissolution of small amounts of fatty acids and other lipid species in urine.

Many of the compounds we measured with this kit assay appear to be normal constituents of human urine but have not been previously reported (quantified and/or detected) in the scientific literature (with the exception of the BIOCRATES Application Note). In total, 53 compounds are being reported here for the first time as being normal constituents of human urine, while 68 compounds are being robustly quantified in human urine for the first time. The vast majority of these compounds are lipids.

Based on our results, the combined DFI/LC-MS/MS method detected 98 compounds or compound species that GC-MS and NMR methods could not detect, while GC-MS detected 161 compounds and NMR detected 181 compounds that DFI/LC-MS/MS could not detect. The 3 methods were able to detect a common set of 17 compounds including creatinine, L-glutamine, L-tryptophan, L-tyrosine and L-valine. Interestingly, the concentrations measured by DFI/LC-MS/MS, NMR and GC-MS (across the shared set of 17 compounds) showed generally good agreement (within 19 ± 7% of each other). The relatively small overlap, in terms of compound coverage, between the 3 platforms is a bit of a surprise and certainly serves to emphasize the tremendous chemical diversity that must exist in urine. Overall, by combining these 3 platforms, we were able to identify 295 and quantify 231 unique or non-overlapping metabolites or metabolite species. These data suggest that DFI/LC-MS/MS, GC-MS and NMR are highly complementary techniques for the identification and quantification of metabolites in human urine.

Quantification and Identification of Urinary Trace Metals – ICP-MS

To determine the trace elemental composition of urine, we used inductively coupled plasma mass spectrometry (ICP-MS). ICP-MS is widely considered to be one of the best techniques for the characterization of the trace element composition of biological samples [88] , [89] . Indeed, none of the other methods ( 1 H-NMR, GC-MS and DFI/LC-MS/MS) are suited for measuring trace element composition or concentrations. Our multi-elemental analysis of urine using ICP-MS provided quantitative results for a total of 40 metals or trace minerals ( Table 8 ). Based on their frequency of occurrence and overall abundance, all 40 trace elements appear to be normal constituents of human urine. Of these, 2 have previously not been quantified for healthy adults.

https://doi.org/10.1371/journal.pone.0073076.t008

As far as we are aware, this is the first multi-elemental study of urine that has been performed by ICP-MS. As seen in Table 8 , there is generally good agreement between the values measured by ICP-MS and those previously reported in literature, with differences generally being less than 22 ± 10%. Larger differences are seen for gallium (Ga), lead (Pb), Neodymium (Nd), titanium (Ti) and vanadium (V), but these may be due to the effects of age, diet, local environment (minerals in local water) or diurnal variation. Alternately they may reflect real differences in the sensitivity or accuracy of the instruments being used. As a general rule, ICP-MS is considered as a gold standard for the identification and quantification of trace metals [18] , so we would tend to place higher confidence in the values derived via ICP-MS over those measured by other technologies. By our measurements, the most abundant metals/salts are sodium (Na) (12.5 ± 10.6 mM/mM creatinine) and potassium (K) (3.6 ± 2.5 mM/mM creatinine) – as expected, while the least abundant was rhenium (Re) with a lower limit of quantification by ICP-MS of 96 pM/mM creatinine.

Quantification and Identification of Urine Metabolites – Targeted HPLC Assays

The inventory of metabolites we detected and quantified by 1 H NMR, GC-MS, DFI/LC-MS/MS and ICP-MS covers a significant portion of all chemical classes. However, these methods sometimes lack the necessary sensitivity, the appropriate instrumental configuration or detection capabilities and therefore fail to detect/quantify a variety of important compound classes. This includes a number of molecules that are normal constituents of urine such as thiols and isoflavones. To identify and quantify these 2 classes of metabolites we decided to employ High Performance Liquid Chromatography (HPLC). HPLC assays are the method of choice for detecting isoflavones and thiols as they are sensitive, precise and can be easily coupled with sensitive detection methodologies such as fluorescence and ultraviolet detection. In our studies, fluorescence and ultraviolet detection were used for the identification and quantification of urinary thiols and isoflavones, respectively.

Biological thiols, or mercaptans, are very active metabolic products of sulfur and play a central role in redox metabolism, cellular homeostasis and a variety of physiological and pathological processes. In urine, the most important thiols are L-cysteine and L-cysteinylglycine [90] , [91] , [92] , [93] . Isoflavones or phytoestrogens form or constitute another important class of urinary metabolites [90] . Humans are exposed to these biologically active phytochemicals mainly through food intake via vegetables, fruit and wheat/bread products [94] . For the detection of thiols we developed assays to measure L-cysteine, L-cysteineglycine, L-glutathione and L-homocysyeine, while for isoflavones we developed assays to measure biochanin A, coumesterol, daidzein, equol, formonentin and genistein. Using these HPLC assays, we measured a total of 4 thiols and 6 isoflavones in urine ( Table 9 ).

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As seen in Table 9 , there is generally good agreement between the values measured by these targeted HPLC assays and those previously reported in literature, with differences generally being less than ∼30%. Only one of these metabolites (L-cysteine) was measured independently on one of our other platforms (NMR) and the NMR concentration was found to be 25% lower than the HPLC assay. A possible explanation for this discrepancy is that cysteine measured by HPLC-FD yields total L-cysteine including the free form and L-cystine reduced to L-cysteine during the reaction [95] . On the other hand, NMR can distinguish between L-cysteine and L-cystine.

The Composition of Human Urine – Comparison with Other Biofluids

By combining a systematic computer-aided literature survey with an extensive, quantitative multiplatform metabolomic analysis we have been able to comprehensively characterize the human urine metabolome. Our data suggests that there are at least 3079 detectable metabolites in human urine, of which 1350 have been quantified. At least 72 of these compounds are of microbial origin, 1453 are endogenous while 2282 are considered exogenous (note some compounds can be both exogenous and endogenous), coming from diet, drugs, cosmetics or environmental exposure. Using a chemical classification system developed for the HMDB [15] we found that human urinary metabolites fall into 230 different chemical classes (25 “super classes”, Table 2 ). Given that there are only 356 chemical classes in the entire human metabolome [16] , this certainly demonstrates the enormous chemical diversity found in urine. As might be expected, most urinary metabolites are very hydrophilic, although there are clearly trace amounts of lipids and fatty acids that contribute a significant number of chemicals to the urinary metabolome (836 fatty acids and lipids). This is in rather striking contrast to the composition of serum [20] which is particularly rich in lipids (i.e. >17000 lipids and fatty acids). Relative to other biofluids such as CSF [18] or saliva [19] , urine contains significantly more compounds (5–10X) and exhibits significantly more chemical diversity (2–3X). On the other hand, we know that every compound that is found in human urine is also found in human blood. In other words, the human urine metabolome is a subset of the human serum metabolome, both in terms of composition and chemical diversity [20] . However, more than 484 compounds we identified in urine (either experimentally or via literature review) were not previously reported to be in blood. The fact that so many compounds seem to be unique to urine likely has to do with the fact that the kidneys do an extraordinary job of concentrating certain metabolites from the blood. Consequently compounds that are far below the limit of detection in blood (using today’s instrumentation) are well above the detection limit in urine. In fact, concentration differences between the two biofluids sometimes exceed 1000X for certain compounds, such as histamine, androsterone, normetanephrine, testosterone 13, 14-dihydro-15-keto-PGE2, m-tyramine and aldosterone. So, while the number of water-soluble compounds in blood and urine may be almost identical, the concentrations of these compounds are often profoundly different. This difference, combined with the ability of the kidney to handle abnormally high or abnormally low concentrations of metabolites, makes urine a particularly useful biofluid for medical diagnostics. In fact, according to our data in the UMDB, urinary metabolites have been used to characterize nearly 220 diseases. Furthermore, the ability of the kidneys to filter toxins or xenobiotics makes urine a particularly useful biofluid for diet and drug monitoring and for assessing chemical or pollutant exposure [96] .

Method Comparison

One of the central motivations behind this work was to ascertain the strengths and weaknesses of several common metabolomic platforms for characterizing human urine. We employed 6 different analytical platforms: NMR; GC-MS; DFI/LC-MS/MS; HPLC/UV; HPLC/FD and ICP-MS. Using our literature-derived knowledge about the composition of human urine, along with custom-derived spectral libraries and targeted assays we were able to “push the limits” in terms of number of compounds that could be identified and/or quantified via each platform. In total, we identified 445 and quantified 378 distinct metabolites using these 6 different systems. According to Table 1 , this is the largest number of urine metabolites ever identified and/or quantified in a single study. NMR spectroscopy was able to identify and quantify 209 compounds; GC-MS was able to identify 179 and quantify 85 compounds; DFI/LC-MS/MS identified and quantified 127 compounds; ICP-MS identified and quantified 40 compounds; while customized HPLC assays (with UV or FD detection) identified and quantified 10 compounds. The number of urinary metabolites we identified/quantified for NMR, GC-MS, DFI/LC-MS/MS and ICP-MS all represent “records” for these platforms.

In terms of platform overlap and compound complementarity, NMR and GC-MS were able to identify a common set of 88 metabolites; NMR and DFI/LC-MS/MS were able to identify and quantify a common set of 28 metabolites, while NMR, GC-MS and DFI/LC-MS/MS were able to identify a common set of 17 metabolites (15 amino acids, creatinine and hexose/glucose). All of these results are summarized in a Venn diagram ( Figure 5 ). As might be expected, metabolite coverage differs from one analytical technique to another. These are difference mostly due to the intrinsic nature of the devices or platforms used. In particular, significant differences exist between these platforms in terms of their sensitivity or separation and/or extraction efficiency. Likewise the use of targeted vs. non-targeted methods along with issues related to compound stability, solubility and volatility led to some significantly different platform-dependent results.

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Given that the known, quantifiable urine metabolome consists of ∼2651 known metabolites and metabolite species (corresponding to 3079 distinct structures), we can calculate that NMR is able to measure ∼8% (209/2651) of the human urine metabolome; GC-MS is able to measure ∼7% (179/2651); DFI/LC-MS/MS is able to measure ∼5% (127/2651); ICP-MS/MS is able to measure ∼1.5% (40/2651); HPLC/UV is able to measure ∼0.2% (6/2651); while HPLC/FD is able to measure ∼0.15% (4/2651) of the urine metabolome. When combined, the 6 analytical techniques are able to cover >16% of the known urinary metabolome (>445/2651). If we re-evaluate this fraction in terms of total metabolite structures (corresponding to known and highly probable metabolites), the urine metabolome consists of 3079 compounds. From this total we can calculate that NMR is able to measure ∼7% (209/3079) of the human urine metabolome; GC-MS is able to measure ∼6% (179/3079); DFI/LC-MS/MS is able to measure ∼18% (555/3079); ICP-MS/MS is able to measure ∼1.3% (40/3079); HPLC/UV is able to measure ∼0.2% (6/3079); while HPLC/FD is able to measure ∼0.13% (4/3079) of the urine metabolome. When combined, the 6 analytical techniques are able to cover >28% of the known and probable or putative urinary metabolome (>873/3079). In terms of chemical class coverage, NMR detects compounds from 15 of the 25 major chemical superclasses in urine, GC-MS detects compounds from 14 of the 25, DFI/LC-MS/MS detects 6 of the 25, ICP-MS detects 1 of the 25 while the targeted methods for thiols and isoflavones detect just 1 of each.

From these data we can conclude that NMR is currently the best method for identifying and quantifying urinary compounds. Not only does it permit measurement of the largest number of metabolites (209) but it also yields the greatest chemical diversity. Furthermore, NMR is non-destructive so that the same sample can be subsequently re-used for GC-MS, LC-MS or ICP-MS analyses. The minimal sample preparation and relatively rapid data collection for NMR also make it much more appealing for urine metabolomics, although the spectral analysis can be quite slow (∼1–2 hours per sample). While GC-MS is a close second in terms of overall coverage (179 metabolites, 14 chemical superclasses), these numbers represents the result of 4 different analyses performed on 2 different GC-MS instruments. Many labs would not have these multiple configurations available or the resources to routinely run these types of analyses. Likewise each sample required many hours of preparation, sample collection and data analysis. In this regard, multi-platform GC-MS is definitely not a high-throughput metabolomics technique. Relative to NMR and GC-MS, DFI/LC-MS/MS also performs well, with 127 compounds being quantified. However, DFI/LC-MS/MS provides very limited chemical diversity (only 6 chemical superclasses). On the other hand, DFI/LC-MS/MS requires very little sample volume (10 µL) and it is a very low-cost, largely automated, high-throughput route for measuring metabolites. The other techniques (HPLC, ICP-MS) we employed in this study, while useful, do not come close to matching the coverage or diversity of NMR, GC-MS or DFI/LC-MS/MS.

While we certainly went to considerable lengths to use current or cutting edge technologies to characterize the urine metabolome, it is also important to note that there is always potential for future improvement. Using higher field (900–950 MHz) NMR instruments, employing newer model GC-MS instruments or more sensitive GC-TOF instruments, using more than 3 derivatization or extraction steps for our GC-MS analyses, employing the latest version of the NIST database or a larger collection of GC-MS databases, implementing more sophisticated or targeted detection and separation techniques, using various commercial immunodetection kits or employing the latest LC-MS/MS techniques coupled to FT-MS or orbitraps – all of these could have added to the quantity and diversity of metabolites detected or quantified. However, like many laboratories, our resources are somewhat limited. Furthermore, in this study we wanted to address the question of how well a cross-section of commonly accessible metabolomic methods or platforms could perform in identifying and quantifying metabolites in urine.

While being able to quantitatively compare metabolite coverage and chemical diversity amongst the major metabolomics platforms (NMR, GC-MS and DFI/LC-MS/MS) is important, it is also useful to compare their consistency or reproducibility in terms of metabolite quantification. In particular we decided to assess the 3 major platforms in terms of their ability to identify and quantify a common group of compounds, namely the amino acids. Overall we found that the measured concentrations are in relatively good agreement ( Table 10 ). However, a few exceptions are evident. For example, the NMR and DFI/LC-MS/MS concentrations of glycine and serine are higher than the GC-MS values (note that glycine exhibits the highest concentration among urinary amino acids). For serine, after the silylation reaction using MSTFA, we obtained serine-2TMS (13.9 min) and serine-3TMS derivatives (16.6 min). The chromatographic peak corresponding to serine-2TMS is weak and overlaps slightly with the urea peak. This overlap and the corresponding difficulty in peak integration may explain the quantitation differences compared to other analytical assays. Neither L-glutamine nor L-glutamic acid could be accurately quantified or identified by GC-MS. In our case, the glutamine peak co-elutes with glycerol-3-phosphate. Other investigators have noted that glutamine can also be hydrolyzed and converted to glutamic acid [97] , or to pyroglutamic acid during derivatization [95] . As a result, only pyroglutamic acid could be identified in our GC-MS assay. The identification of glutamic acid and pyroglutamic acid can be complicated [97] , which explains our failure to identify glutamic acid by GC-MS. L-arginine could not be detected by GC-MS, because it is converted to ornithine during derivatization [98] , which probably explains the slightly higher concentration of ornithine measured by GC-MS, compared to the one determined by DFI/LC-MS/MS. Finally, L-cysteine and L-cystine can only be identified and quantified by NMR and targeted HPLC/FD because the identification and quantification of theses metabolites is not possible with the Biocrates kit. With GC-MS it has often been noted that L-cystine can be converted to L-cysteine during derivatization, while L-cysteine might be oxidized to L-cystine during prolonged storage of the standard solution [95] , confounding the identification of L-cystine and L-cysteine.

https://doi.org/10.1371/journal.pone.0073076.t010

Using a combination of multiple experimental assays supplemented with an extensive computer–assisted literature survey we were able to identify a total of 2651 metabolites or metabolite species (corresponding to 3079 distinct structures) that can be or have been identified and/or quantified in human urine using today’s technology. This information, which includes both normal and abnormal (disease or exposure-associated) metabolites has been placed into a publicly accessible web-enabled database called the Urine Metabolome Database (UMDB). To assess the validity of the literature data and to further investigate the capabilities of existing metabolomics technologies we conducted a comprehensive, quantitative analysis of human urine from 22 healthy volunteers. A total of 6 different platforms: NMR, GC-MS, DFI/LC-MS/MS, ICP-MS, HPLC/UV and HPLC/FD were used in this analysis. From this experimental work we were able to identify a total of 445 and quantify 378 metabolites or metabolite species. This corresponds to 873 unique structures (identified) and 806 unique structures (quantified). A total of 53 compounds or compound species are being reported here for the first time as being normal constituents of human urine, while 77 compounds or compound species are being robustly quantified in human urine for the first time. All of the metabolites that we experimentally identified and/or quantified have been added to the UMDB. Based on the information in the UMDB, our experimentally acquired data corresponds to 16% of the human urine metabolome (or 28% if we include probable or putative metabolites).

Considering the level of coverage, the diversity of chemical species and the ease with which analyses can be performed, we have determined that NMR spectroscopy appears to be the method of choice for global or untargeted metabolomic analysis of urine. On the other hand, the kit-based combined DFI/LC-MS/MS methods appear to be optimal for a targeted metabolomic approach. Using a multi-pronged GC-MS approach for urine metabolomics appears to be very promising in terms of coverage, but is not ideal for high-throughput analyses. All methods used in this study appear to be quite complementary with relatively little compound overlap. This strongly suggests that if sufficient time and resources are available, multiple methods should be used in urine metabolomic studies.

If additional resources had been available, we would have liked to assess other technologies (GCxGC-MS, FT-MS, isotope labeled-LC-MS) and to compare the level of metabolite coverage and chemical diversity attainable with these methods. However, this study is not intended to be the “final” word on urine or urine metabolome. Rather, it should be viewed as a starting point for future studies and future improvements in this field. Indeed, our primary objective for undertaking these studies and compiling this data was to help advance the fields of quantitative metabolomics, especially with regard to clinically important biofluids such as urine. Experimentally, our data should serve as a useful benchmark from which to compare other technologies and to assess coming methodological improvements in human urine characterization. From a clinical standpoint, we think the information contained in the human urine metabolome database (UMDB) should provide metabolomic researchers as well as clinicians and clinical chemists with a convenient, centralized resource from which to learn more about human urine and its unique chemical constituents.

Ethics Statement

All samples were collected in accordance with the ethical guidelines mandated by the University of Alberta as approved by the University’s Health Research Ethics Board. All individuals were over 18 years of age. All were approached using approved ethical guidelines and those who agreed to participate in this study were required to sign consent forms. All participants provided written consent.

Collection of Urine Samples

Human urine samples (first pass, morning) were collected from 22 healthy adult volunteers (14 male, 8 female) in 120 mL sterile urine specimen cups. The average age of the volunteers was 30 (range 19–65) for females, and 32 (range 21–67) for males. Upon receipt (typically within 1 hour of collection), all samples were immediately treated with sodium azide to a final concentration of 2.5 mM. After centrifugation at 4000 rpm for 10 min to remove particulate matter, the urine samples were stored in 2 mL aliquots in falcon tube at −20°C until further use. Prior to each analysis, the samples were thawed at room temperature for 30 minutes and filtered for a second time via centrifugation.

NMR Compound Identification and Quantification

All 1 H-NMR spectra were collected on a 500 MHz Inova (Varian Inc., Palo Alto, CA) spectrometer using the first transient of the tnnoesy-presaturation pulse sequence. The resulting 1 H-NMR spectra were processed and analyzed using the Chenomx NMR Suite Professional software package version 7.0 (Chenomx Inc., Edmonton, AB), as previously described [17] . Additional NMR spectra for 39 compounds were added to the Chenomx Spectral Reference Library using the company’s recommended spectral acquisition and formatting protocols. Further details on the NMR sample preparation, NMR data acquisition and the customized spectral library are provided in Method S1 .

GC-MS Compound Identification and Quantification

Twenty-two urine samples were extracted separately to obtain separate pools of polar, organic acid, bile acid (3 of the 22 urine samples were chosen for analysis and aliquots from these provided an additional “pooled normal” sample) and volatile metabolites using different protocols. The polar metabolites were extracted with cold HPLC grade methanol and double-distilled water after pretreatment with urease, followed by derivatization with MSTFA (N-Methyl-N-trifluoroacetamide) with 1% TMCS (trimethylchlorosilane). For organic acids, the ketoacids were converted first to methoxime derivatives, followed by derivatization with BSTFA (N,O-Bis(trimethylsilyl)trifluoroacetamide) after two successive extractions by ethyl acetate and diethyl ether. The bile acids were eluted with methanol through a SPE column (Bond Elute C18), followed by two different derivatization steps. First the bile acid extracts were esterified using 2% sulfuric acid in methanol, then after phase separation, the esterified bile acids were converted to the corresponding methyl ester-trimethylsilyl ether derivatives using MSTFA with 1% TMCS. Each set of extracted/derivatized metabolites (polar metabolites, organic acids, bile acids) was separated and analyzed using an Agilent 5890 Series II GC-MS operating in electron impact (EI) ionization mode.

The volatile compound extraction and analysis by GC-MS was far different from the other protocols. The pooled urine samples were acidified using HCl and transferred to a SPME (solid phase microextraction) vial (75 µm Carboxen/PDMS from Supelco), and then introducing the SPME fiber assembly into the GC-MS injector port according to procedures described elsewhere [99] , [100] . The fibers were conditioned prior to use according to the manufacturer’s instructions by inserting them into the GC injector port. Further details on the extraction, derivatization, separation and GC-MS data analysis for the 4 separate groups of urine metabolites are provided in Method S2 .

Direct Flow Injection/LC-MS/MS Compound Identification and Quantification

To assess the performance of direct flow injection DFI-MS/MS methods in urine metabolomics and to determine the concentration ranges of a number of metabolites not measurable by other methods, we used the commercially available Absolute-IDQ p180 Kit (BIOCRATES Life Sciences AG - Austria). The kit, in combination with an ABI 4000 Q-Trap (Applied Biosystems/MDS Sciex) mass spectrometer, can be used for the targeted identification and quantification of 187 different metabolites or metabolite species including amino acids, biogenic amines, creatinine, acylcarnitines, glycerophospholipids, sphingolipids and hexoses. This method involves derivatization and extraction of analytes from the biofluid of interest, along with selective mass spectrometric detection and quantification via multiple reactions monitoring (MRM). Isotope-labeled internal standards are integrated into the kit plate filter to facilitate metabolite quantification. Metabolite concentrations were expressed as ratios relative to creatinine to correct for dilution, assuming a constant rate creatinine excretion for each urine sample (see Method S3 for additional information).

Trace Element Analysis Using ICP-MS

Before trace elemental analysis by ICP-MS was performed, 22 urine samples were processed as described previously [101] . The concentrations of trace elements were determined on a Perkin-Elmer Sciex Elan 6000 quadrupole ICP-MS operating in a dual detector mode. Blank subtraction was applied after internal standard correction (see Method S4 for additional information). The accuracy of the ICP-MS analytical protocol was periodically evaluated via the analysis of certified reference standard materials (whole rock powders) BE-N and DR-N available from the SARM laboratory at the CRPG (Centre de Recherches Pétrographiques et Géologiques).

Characterization of Isoflavones from Urine

We processed 22 urine samples as described previously [102] , [103] . The isoflavones were isolated and concentrated by solid-phase extraction (Bond Elut C18 column). The elutes were hydrolyzed enzymatically as the urinary isoflavones occur predominantly as glucuronate and sulfate conjugates. The analysis were performed on an Agilent 1100 HPLC system using NovaPak C18 reversed-phase column connected to Agilent G1315B diode array detector with signals scanned between 190 and 400 nm (see Method S5 for additional information).

Characterization of Thiols from Urine

To extract urinary thiols, we derivatized all 22 urine samples as described previously [104] . A mixture of reagent was used for the reduction and derivatization (with bromobimane) of thiols. The derivatized thiols were injected immediately into a hypersil-ODS HPLC Column connected to Agilent fluorometer operating at an excitation wavelength of 485 nm and emission wavelength of 510 nm (see Method S6 for additional information).

Supporting Information

NMR Compound Identification and Quantification.

https://doi.org/10.1371/journal.pone.0073076.s001

GC-MS Compound Identification and Quantification.

https://doi.org/10.1371/journal.pone.0073076.s002

Direct Flow Injection/LC-MS/MS Compound Identification and Quantification.

https://doi.org/10.1371/journal.pone.0073076.s003

Trace Element Analysis Using ICP-MS.

https://doi.org/10.1371/journal.pone.0073076.s004

Characterization of Isoflavones from Urine.

https://doi.org/10.1371/journal.pone.0073076.s005

Characterization of Thiols from Urine.

https://doi.org/10.1371/journal.pone.0073076.s006

Acknowledgments

The authors wish to thank Kruti Chaudhary and Hetal Chaudhary for adding concentration values from the literature to the UMDB, Rolando Perez-Pineiro for the synthesis of HPHPA and Beomsoo Han for converting all figures to high resolution images.

Author Contributions

Conceived and designed the experiments: SB FA RM RK DSW. Performed the experiments: SB FA RM RK ZTD NP RB CR. Analyzed the data: SB FA RM RK ACG ZTD DSW. Contributed reagents/materials/analysis tools: ACG MRW CK TCB FS PL ZTD JP JH FSY ED RB CR DSW. Wrote the paper: SB FA RM RK TCB FS PL NP DSW.

• View Article
• Google Scholar
• 24. Rigby D, Gray K (2005) Understanding urine testing. 60–62 p.
• 72. Dutton GJ ( 1966) Glucuronic Acid, Free and Combined: Chemistry, Biochemistry, Pharmacology, and Medicine. Madison: Academic Press. 629.
• 82. Taylor EH (1989) Clinical Chemistry. New York: John Wiley and Sons. 293 p.
• 87. Röhring C, Bogumil R, Dammeier S. Analysis of human urine using the absolute IDQ™ Kit Application Note 1003–1 Innsbruck, Austria: Biocrates Life Sciences Available At: http://wwwbiocratescom/images/stories/pdf/biocrates_applnote_1005-1pdf Accessed Accessed 2013 May 24.
• 90. Harborne JB (1988) The Flavonoids. London: Chapman & Hall. 531 p.
• 105. David FP (1971) Composition and concentrative properties of human urine. Washington: National Aeronautics and Space Administration. 107 p.

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Urine Tests

A Case-Based Guide to Clinical Evaluation and Application

• Victoria J.A. Sharp 0 ,
• Lisa M. Antes 1 ,
• M. Lee Sanders 2 ,
• Gina M. Lockwood 3

Department of Urology and Department of Family Medicine, University of Iowa, Iowa City, USA

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Department of Internal Medicine Division of Nephrology, University of Iowa, Iowa City, USA

Department of urology, university of iowa, iowa city, usa.

• Is the first-of-its-kind comprehensive text on the evaluation and applications of urine tests
• Is written by primary care and specialists
• Includes best practices and national guidelines from a variety of specialty associations

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Table of contents (17 chapters)

Front matter, urine: the golden elixir of life.

• M. Lee Sanders, Lisa M. Antes

Follow the Money: Costs, Reimbursement and Regulations of Urine Based Testing

• Matthew A. Uhlman, Victoria J. A. Sharp, Nora Kopping, Mark S. Uhlman

Going with the Flow: Proper Urine Testing Methods for Clinical Practice

• Gina M. Lockwood, Victoria J. A. Sharp

Urine Dipstick: Blood – The Spectrum of Red

• Alexandra J. Sharp, Victoria J. A. Sharp

Urine Dipstick: Proteinuria – Causes, Consequences and Diagnostic Approach

• Lewis Mann, Lisa M. Antes, M. Lee Sanders

Urine Dipstick: Urinary Nitrites and Leukocyte Esterase – Dipping into Murky Waters

• A. Ben Appenheimer, Bradley Ford

Urine Dipstick: An Approach to Glucosuria, Ketonuria, pH, Specific Gravity, Bilirubin and Urobilinogen – Undeniable Chemistry

• Puja T. Pape, Victoria J. A. Sharp, Jessica Rockafellow

Urine Microscopy: The Burning Truth – White Blood Cells in the Urine

• Andrew M. Vitale, Gina M. Lockwood

Urine Microscopy: Seeing Red – Understanding Blood in the Urine

• Christopher Meier, Gina M. Lockwood

Urine Microscopy: The Utility of Urinary Casts in Patient Care – Practical and Useful Tips for Busy Clinicians

• Stephanie J. Houston, M. Lee Sanders, Lyndsay A. Harshman

Urine Microscopy: Clouding Over – Bacteria, Yeast, Parasites and Zika

• Bradley Ford, Wendy Fiordellisi, Victoria J. A. Sharp, A. Ben Appenheimer

Urine Microscopy – Urine Made Crystal Clear

• Courtney Yong, Chad R. Tracy, Lisa M. Antes

Urine Testing in Children: Little People, Big Challenges

• Gina M. Lockwood, Douglas W. Storm

Urine Based Tests in the Diagnosis of Genitourinary Cancers

• Morgan Schubbe, Laila Dahmoush, KennethG. Nepple

Kidney Excretions: The Lyter Side of Urine

• Jeremy Steinman, Carly Kuehn, Lisa M. Antes

Other Common Uses for Urine Screening in Clinical Practice: Substance Use Disorders, Antipsychotic Adherence, Sexually Transmitted Infections

• Aubrey Chan, Puja T. Pape, M. Lee Sanders

Urine Tests: Solidifying Concepts – Questions and Answers

• M. Lee Sanders, Lisa M. Antes, Victoria J. A. Sharp, Gina M. Lockwood

Back Matter

Urine tests are used by a variety of primary care providers and specialists in order to diagnose, monitor and treat patients with various medical conditions. This first-of-its-kind text is a comprehensive clinical guide to the evaluation and application of urine tests. Clinical cases are used to highlight important aspects of urine testing. Further evaluation and management are then discussed based on the results of the urine tests.

Topics covered include financial considerations, regulations, proper collection, testing methods, dipstick analysis, microscopy as well as cancer and drug screening tests, among others. Each chapter contains specific objectives for focus of study. Pertinent images, algorithms and board style review questions for important topics are also included.

Written by nephrologists, urologists, other specialists and primary care physicians, Urine Tests uses a comprehensive approach to the clinical use of both common and uncommon urinetesting. Primarily appealing to practicing primary care physicians, this book is also a useful resource for specialists, nurse practitioners, physician assistants, physician fellows, residents and medical students alike.    

• urine dipstick
• Urine Electrolytes
• urine tests

Victoria J.A. Sharp

Lisa M. Antes, M. Lee Sanders

Gina M. Lockwood

Dr. M Lee Sanders obtained his MD degree from the University of Tennessee Health Science Center after completion of a PhD in Pharmaceutical Sciences. He completed internal medicine residency and chief residency at the University of Iowa Hospitals and Clinics followed by completion of both a general nephrology and transplant nephrology fellowship at Vanderbilt University Medical Center. He is Board Certified in both Internal Medicine and Nephrology, and his current medical practice incorporates internal medicine, generalnephrology, and transplant nephrology. His academic interests include medical education and kidney transplant outcomes. 

Dr. Gina Lockwood obtained her MD degree from Southern Illinois University School of Medicine. She completed urology residency at the Medical College of Wisconsin. She completed her pediatric urology fellowship at Connecticut Children’s Medical Center and obtained her Master of Science degree in Clinical and Translational Research at University of Connecticut. She is Board certified in Urology. She currently practices pediatric urology and has research interests in patient and parent education and quality improvement.

Book Title : Urine Tests

Book Subtitle : A Case-Based Guide to Clinical Evaluation and Application

Editors : Victoria J.A. Sharp, Lisa M. Antes, M. Lee Sanders, Gina M. Lockwood

DOI : https://doi.org/10.1007/978-3-030-29138-9

Publisher : Springer Cham

eBook Packages : Medicine , Medicine (R0)

Copyright Information : Springer Nature Switzerland AG 2020

Softcover ISBN : 978-3-030-29137-2 Published: 20 July 2020

eBook ISBN : 978-3-030-29138-9 Published: 19 July 2020

Edition Number : 1

Number of Pages : XXI, 389

Number of Illustrations : 6 b/w illustrations, 71 illustrations in colour

Topics : General Practice / Family Medicine , Primary Care Medicine , Urology

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Review article, urine analysis has a very broad prospect in the future.

• 1 School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
• 2 Institute of National Medicine, Beijing University of Chinese Medicine, Beijing, China

Medical tests are playing an increasingly important role in the diagnosis and treatment of diseases. Urine tests, blood tests and stool tests together constitute the three major routine examination items of modern medicine and are an important part of medical tests. Urine is a body fluid normally metabolized by the human body. Compared with using blood as a test sample, using urine as a medical test sample has many advantages, such as non-invasiveness and convenient collection. This article discusses the advantages of urine test compared with blood test, the understanding and application of urine in traditional medicine, the application of urine test in social life, the current dilemma and the future urine test may play a greater role The value and advantages are discussed, aiming to increase people’s attention to urine testing by explaining the advantages of urine testing, and to discover more functions of urine testing, thereby optimizing medical testing methods and reducing the pain and fear of patients. Improve inspection efficiency, reduce national and personal medical inspection expenditures, and save medical resources.

Introduction

Urine is the liquid excretion excreted through the urinary system and urinary tract for the needs of humans and vertebrates for metabolism. It contains key information about human health, dietary intake and exposure to environmental pollutants ( Zha and Huang, 2019 ). Urine is the normal metabolic water of the human body, and the normal acquisition of urine will not have an adverse effect on the body, which is convenient for multiple sampling and dynamic observation and analysis of the patient’s treatment status. Both urine and blood contain rich physiological and pathological information of the human body, but due to the particularity of blood itself, the use of blood as a medical test sample will cause more or less harm to the human body. With the continuous development of testing technology, some diseases in which urine is used to find markers are slowly being discovered. This will allow more diseases in the future to be easily and quickly tested through urine, and even at home, to be able to make diagnosis and assessment of the prognosis of treatment, and to make up for the inconvenience or delay of blood testing and pathological section examination. If the urine test can be used to diagnose the disease more accurately, it will save more medical costs, reduce the mental and economic burden of patients, and have important clinical practical significance. It is currently known that every compound found in urine can also be found in blood. More than 484 compounds have been identified in urine (either through experiments or through literature reviews), and have not been previously found in blood reported. Urine contains all the compounds in the blood, and at the same time has what the blood does not have. This may be related to the extraordinary work done by the kidneys in concentrating certain metabolites in the blood. For certain compounds, such as histamine, androsterone, norepinephrine, metatyramine, and aldosterone, the concentration difference between the two biological fluids is sometimes even more than 1,000 times. Therefore, although the amounts of water-soluble compounds in blood and urine are almost the same, the concentrations of these compounds are often very different. This difference, combined with the ability of the kidneys to process abnormally high or low concentrations of metabolites, makes urine a particularly useful biological fluid for medical diagnosis. According to data in UMDB (Urine Metabolome Database), urine metabolites have been used to describe nearly 220 diseases. In addition, the kidney’s ability to filter toxins or foreign biological substances makes urine a particularly useful biological fluid for diet and drug monitoring, and to assess exposure to chemicals or pollutants ( Bouatra et al., 2013 ). As shown in the figure below, Figures 1 - 3 introduce a concise summary of the urinalysis.

FIGURE 1 . Urine can be observed macroscopically from many aspects, which is convenient for healthy people or patients to check their physical condition in time.

FIGURE 2 . Advantages of urine testing compared with blood testing.

FIGURE 3 . Some of the markers or metabolites found in the urine that have diagnostic significance for the disease.

Compared With Blood Tests, Urine Tests Have the Following Advantages

The collection is simple and non-invasive.

The urine can be collected completely non-invasively and continuously during the collection process, and the operation is simple, which is convenient for timely observation and analysis of the dynamics and prognosis of the disease. The blood collection is invasive, and the time for collecting blood samples, the operation process and even the position of blood collection have relatively strict requirements ( Zhang and Liang, 2016 ). Blood is one of the most important tissues in the human body ( Fan, 2020 ). A large amount of blood sampling will have adverse effects on the patient’s body, and multiple blood sampling in a short period of time will affect the patient’s physical and mental health, especially for children, the elderly, and patients with physical weakness. It is not conducive to timely assessment of the disease. Urine dynamic analysis is more convenient and safer than blood.

Less Affected by the Regulation of Internal Mechanisms

The human body has a tendency to maintain stability, and blood, as one of the important components of the human body, also has this characteristic. A biomarker is essentially a variable. Variables in the blood, liver, kidney, lung, skin and other organs will use various mechanisms to reduce this variable in the blood ( Gao, 2013 ). Most of the changed information does not stay in the blood for a long time, but the changed information it is also the essence of disease markers. Urine does not have the necessary and mechanism to maintain stability. More types of disease information can be accumulated in urine, and many changes in the body can be reflected in urine, which is more conducive to finding markers in urine ( Zha and Huang, 2019 ).

Facilitate Continuous Monitoring

Because of the research on Drosophila circadian clock genes and molecular regulation mechanisms, the three scientists won the Nobel Prize. Biological rhythms and time biological rhythms have once again attracted widespread attention. As early as 1959, the famous American physiologist Franz Halberg proposed the use of “circa-dian clock” to define a biological clock with a 24 h rhythm, and the term “chronobiology” to define interbiology. He tested the level of hormones in his urine by a friend of his for the past 30 years. It is found that the human body has a particularly obvious circadian rhythm, that is, a 24-h cycle of change, and it also has a clear 7-days rhythm. Rhythm changes in urine will also provide the possibility and convenience of disease dynamic monitoring. Blood and urine are rich in disease biological information. The requirements for obtaining urine and testing conditions are lower than those of blood, so if you use urine the continuous detection of liquid can control the disease, and it will be more convenient to observe and analyze the dynamics and prognosis of the disease in time ( Yuan et al., 2018 ).

Suitable for People who are Inconvenient to Draw Blood for Testing

For children, people with special beliefs who are inconvenient to collect blood, and people who need long-term monitoring of diseases, the way of urine sampling and testing is much more friendly. Urine Legionella (Lp) antigen test card is used in the clinic to detect Legionella pneumophila in the urine of children, which can quickly diagnose the child as Legionella pneumophila infection, shorten the diagnosis time, improve the treatment efficiency, and reduce the number of children Resistance in routine testing ( Qiu et al., 2020 ).

Urine can be Collected in Large Quantities

Urine can be collected continuously in large quantities and will not cause harm to the human body. Under suitable storage conditions, the stability of a variety of compounds in the urine is better. A large amount of urine can be collected to solve the problem that the content of certain components is too low and it is inconvenient to detect ( Wang and Bao, 2019 ; Zha and Huang, 2019 ).

The Samples are Easy to Store, Handle and Transport

Compared with blood samples, urine samples have relatively low requirements for storage, transportation and processing conditions. Relatively reduce the consumption of manpower and material resources. The protein group in the urine can be stored for a long time without significant changes. Someone has proposed whether it is possible to save the urine information of the patient as a case by preserving the protein group in the urine ( Zha and Huang, 2019 ). This may be it provides a new idea for the innovation of future case preservation. At the same time, the content of other proteins in the urine is low, and the detection background is low, which is conducive to the separation of DNA.

It can be Monitored Macroscopically

Because urine can be visually observed, it is convenient to make timely judgments of diseases that can be detected from the macroscopic changes in urine, such as: the appearance or change of urine foam, turbidity, and sediment. Have a preliminary understanding of one’s own situation, draw attention to it, and conduct timely examination, diagnosis and treatment of physical conditions to prevent the appearance or further aggravation of the disease. With the improvement of the level of health awareness, people’s attention to urine is gradually increasing. In the theory of Chinese medicine, the color of urine is closely related to the cold and heat conditions in the body. People can understand their physical conditions through awareness of their own physical conditions and changes in urine. If you have not reached the disease state, through subjective feelings and objective urine-assisted observations, you can adjust your diet or living habits in a timely manner, and you can perform self-regulation simply and easily, which is convenient for keeping the body in a good state.

Reduce the Risk of Medical Staff as Occupational Exposure

For the blood collection of some patients with infectious diseases, urine testing can relatively reduce the risk of medical workers. Traditional blood test methods require invasive collection of samples, and there is a risk of needle stick injuries. Investigations and studies have found that the main types of exposure of medical staff are sharp object injuries, which mainly occur when sorting out medical equipment, medical waste and blood sampling ( Zhang et al., 2020 ). It has been confirmed that more than 20 pathogens can enter the body through damaged skin and mucous membranes and cause infections of medical staff, such as Treponema pallidum , hepatitis B and C viruses, human immunodeficiency virus, etc., ( Tang et al., 2020 ). Clinically, a large number of blood samples will increase the risk of infection among medical staff.

Saving Medical Staff Time and Improving Medical Efficiency

With the continuous development of urine testing automation technology and the emergence of automated urine instruments, the time for urine testing has been greatly reduced ( Carrera and Bueno, 2020 ), because most patients can complete sample collection independently or with the assistance of family members. The workload of medical workers is reduced, the time cost of medical workers is saved, and the efficiency of medical inspection is improved.

Test for HIV Through Urine

In addition to HIV antibodies in the blood of HIV-infected persons, HIV antibodies can be detected in their urine, saliva, tears and other body fluids or secretions. The concentration of HIV-1 antibodies (mainly IgG) in urine and serum The antibody concentration in parallel ( Dai et al., 2003 ). In a HIV blood and urine test of 203 people, it was found that the sensitivity and specificity of urine specimens to detect HIV-1 antibodies were similar to those of blood specimens (the sensitivity of blood specimens was 99.9%, and the specificity was 99.9%; urine specimens had a sensitivity of 99.9% and specificity of 99.9%. The sensitivity of the specimen is 98.7%, and the specificity is 99.1%). Many studies have also reflected that the urine test for HIV also has good specificity and sensitivity ( Ye et al., 2019 ; Ren, 2020 ). Studies have shown that in the HIV test of patients, the acceptance rate of urine test is higher than that of blood test and oral mucosal collection test. Urine test reduces patients’ fear of medical tests ( Gao, 2013 ). Compared with blood, it is easy to operate and suitable for large-scale screening and monitoring.

Food Safety Testing in Urine

With the development of social productivity, people’s material life has become richer, but the food safety problem has become more and more serious. The people’s pursuit of a healthy diet and the insecurity of the food consumer market constitute a pair of important contradictions in the market today. Hormones and tranquilizers are used in poultry to sedative and hypnotize poultry, gain weight, and use antibiotics in violation of regulations, so as to achieve illegal benefits. Large doses of drugs remaining in animal products enter the human body after being eaten. Serious harm to the human body, precocious puberty in children, obesity, and many chronic physical and mental diseases are becoming more and more serious, which are closely related to these food problems. In this regard, it is very important to strengthen the supervision of food safety. There have been many studies on children’s urine testing and found that a variety of commonly used antibiotics and those limited to livestock and poultry can be detected in children’s urine. For example: There was a survey of more than 1,000 children and found that 580 human urine has antibiotics, and some children even contain 6 kinds of antibiotics. Enrofloxacin and tylosin, which are generally restricted to livestock and poultry, were also detected in children ( Hexing et al., 2015 ; Li et al., 2017 ; Wang et al., 2018 ). Strengthening supervision at the source link can not only reduce the chance of illness, but also reduce the use of medical resources and save social resources. At present, experiments have proved that the use of glucocorticoid drugs, diazepam and meat essence, antibiotics and their metabolites can be detected in the urine of pigs, and the urine is used to monitor poultry meat problems before slaughter, to avoid damage to the animal body and secondary infections and other problems.

Urine Biomarkers Have the Advantage of Early Diagnosis of Diseases

Urine biomarkers have the advantage of early diagnosis of diseases, because in the case of no obvious pathological symptoms in the early stage of the disease, the homeostasis mechanism effectively maintains the stability of the body’s internal environment and removes harmful ones from the body through various methods. Keep the composition and characteristics of body fluids (especially blood) unchanged or within the normal range. Therefore, the early characteristics of many diseases are difficult to reflect in the blood. Compared with blood, urine has no homeostasis mechanism, and urine can adapt to subtle and comprehensive changes, especially in the early stages of the disease. Many early disease markers in urine appear earlier than in the blood, and even earlier than the patient’s symptoms, signs, and imaging pathology examinations. With the latest advances in the discovery of nano-scale extracellular vesicles called vesicles, urine vesicles have become a new source for screening and characterizing potential biomarkers. At present, a new on-disk laboratory platform has been developed. It is used to quickly and effectively isolate exosomes from urine, and potential biomarkers have been discovered, which can be used for early screening of bladder cancer. In the near future, further research on urine biomarkers will greatly promote the early diagnosis, prevention, treatment and prognosis of various diseases. Compared with plasma biomarkers, urine biomarkers are used as disease biomarkers. The early stage showed many advantages and deserves more attention and further research ( Li, 2014 ; Jian and Youhe, 2018 ).

Abundant Amount of Biological Information

Urine is the mid-terminal metabolite produced by the blood after glomerular filtration, renal tubules and collecting duct reabsorption and excretion. Its composition and characteristics can reflect the body’s metabolism and organ functional status. With the development of biotechnology, the rich biological information contained in urine is gradually being discovered. Millions of chemical urine tests are performed every day to identify metabolic diseases in newborns, diagnose diabetes, monitor kidney function, confirm bladder infections, detect illegal drug use, and more. At present, it is well known that the urine of normal people contains water, inorganic salts, urea, uric acid, etc., and abnormal urine can detect proteins, sugar, amino acids and ketone bodies, but the substances contained in urine are much more than these ( Zha and Huang, 2019 ).

The David Wischett research team at the University of Alberta in Canada found a total of 3,079 chemical substances in urine. In addition to water and inorganic salts, the composition of urine also includes proteins, enzymes, nucleic acids, vitamins, hormones, amino acids and their derivatives, mesothelin, β-microglobulin, antibiotics, hormones, urokinase, mycomycin, and the final product of metabolism in the body, etc. Professor David Wischert pointed out: “Urine is an extremely complex biological fluid. We did not expect so many different chemicals to enter the urine.” He said that the current urine test can only detect 16 or 7 chemicals. Ingredients, most medical textbooks only list 50–100 chemical ingredients in urine, and this study expanded the list by 30 times ( Zha and Huang, 2019 ). The discovery of this result makes urine testing a more important method. It provides the possibility to be a test that precedes the blood test or pathological tissue section.

At present, urine biomarkers in lung cancer, cardiovascular disease, blood coagulation system, kidney cancer and other kidney diseases, bladder cancer, prostate cancer, Alzheimer’s disease and autoimmune diseases have been found in the study of urine biomarkers ( Huang et al., 2018 ). Some of the diagnostic markers or metabolites found in urine are as follows:

Mesothelin is a cell surface glycoprotein and a biomarker of early pancreatic cancer. It is found in blood and urine. It has the characteristics of small molecular weight and good stability. It can also appear in cells of normal tissues, but due to its it has limited distribution in normal tissues and is highly expressed in some tumor tissues, and is expected to be used for specific treatment of tumors. Studies have shown that mesothelin is easily filtered through the glomerulus and is not easily affected by serum proteins and degrading enzymes. It is highly expressed in ovarian cancer, lung cancer, AIDS and other diseases ( Wang et al., 2019 ).

β2-Microglobulin

β2-microglobulin is produced by nucleated cells such as lymphocytes. It is widely distributed in human urine, plasma, cerebrospinal fluid, saliva and colostrum. Under normal circumstances, the synthesis and release of β2-microglobulin in the human body are relatively constant, which can be filtered by the glomerulus, but 99.9% will be absorbed by the proximal renal tubules, and will be degraded into amino acids in the renal tubular epithelial cells. It is used by the body and no longer flows back into the blood. Therefore, under normal circumstances, the excretion of β2-microglobulin in urine is very small. The proximal tubule is the only place where β2-microglobulin is processed in the body, and it is negatively correlated with tubule reabsorption rate. Therefore, it is a specific and sensitive index to evaluate the proximal tubule, and it can reflect the degree of damage. In clinical practice, the differential diagnosis, condition estimation, and prognostic judgment of kidney disease by measuring the content of β2-microglobulin in blood and urine can provide valuable reference data, and β2-microspheres can also be caused in some special clinical situations. A variety of tumors, such as chronic lymphocytic leukemia, lung cancer, kidney cancer, breast cancer, liver cancer, gastric cancer, colon cancer, rectal cancer, and lymphoma can cause β2-microglobulin to increase in varying degrees. Fever and the use of certain drugs may also lead to different degrees of elevation, which is of reference value for the diagnosis and differential diagnosis of various diseases ( Huang et al., 2018 ).

At present, clinical monitoring of hormone levels in urine is often used in the detection of human chorionic pheromone in urine to detect pregnancy. Because it is convenient to test at home, it is convenient and saves the trouble of going to the hospital. Many studies now show that breast, uterus, and organs affected by hormone levels have a clear relationship between canceration and estrogen overstimulation. The metabolites of hormones are still active and have various biological effects. Some of these metabolites can inhibit the growth of cancer, and some can induce the production of cancer. When the level of hormonal metabolites exceeds that of good metabolites, it is easy to induce cancer. Therefore, monitor the level of estrogen and the level of metabolites is of great significance for the prevention of breast, ovarian, and uterine cancers. Hormones can be detected in urine using high-performance liquid chromatography-tandem technology, but for more precise detection, further improvements in testing technology are needed ( Zhao, 2013 ).

At the same time, it has now been discovered that occupational stress hormones can be detected in urine. Occupational stress is one of the important factors leading to many diseases. It belongs to the psychological range. The evaluation of occupational stress is determined by the subjective description of patients. It is difficult to determine occupational stress. For objective quantification, some studies focused on shooters and analyzed the changes in urine indicators of shooters. It was found that vanilla mandelic acid in the urine increased significantly after stress. After studying the changes in urine indicators after exams and normal classes, it is found that vanilla mandelic acid in the urine of students after the exam has also increased ( Zha and Huang, 2019 ). The discovery of stress markers in urine provides the possibility for future psychological diagnosis and objective quantification of occupational stress determination, which will be of great help to psychological diagnosis.

Diacetylspermine

Polyamines are low-molecular-weight aliphatic amine compounds produced in the process of metabolism. They are widely present in organisms and participate in regulating various life activities of the body, such as gene expression and translation, cell proliferation, cell apoptosis and organ development, etc. Polyamines in organisms are further divided into putrescine, cadaverine, spermidine and spermine. Diacetylspermine is a diacetylated derivative of spermine. Studies have shown that the level of diacetylspermine in the urine of a variety of cancers will be higher than normal people to different degrees. At present, it has shown a certain direction in the early diagnosis, treatment, prognosis and monitoring of recurrence of cancer ( Li et al., 2019 ).

Bisphenol A

At present, people are exposed to bisphenol A (BPA) in large amounts in daily life. Animal studies have found that BPA can cause prostate cancer, but human research data is still lacking. In a study of bisphenol A in the urine of men, it was found that patients with prostate cancer had higher levels of BPA in their urine than those without prostate cancer. Urinary bisphenol levels are associated with prostate cancer and may have prognostic value ( Prins et al., 2014 ; Tarapore et al., 2014 ).

Pluripotent Stem Cells in Urine

Using exogenous factors to transform somatic cells into induced pluripotent stem cells (iPSCs), also known as reprogramming, can be used for personalized regenerative medicine. Human induced pluripotent stem cells come from many sources, including skin (fibroblasts and keratinocytes), extra-embryonic tissues or cord blood. The reprogramming of these tissues has been achieved at different frequencies, which indicates that the cell of origin is an important determinant. The ideal cell source should be easy to obtain, susceptible and universal (any age, gender, race, and physical condition). Although human urine is a kind of biological waste, it contains a small amount of cells with self-renewal ability and differentiation potential. Urine-derived stem cells (UDSC) derived from the tortuous tubules of nephron, renal pelvis, ureter, bladder and urethra have a phenotype similar to mesenchymal stromal cells (MSC) and can be reprogrammed into induced pluripotent stem cells (iPSC). Some data indicate that urine may be the preferred source of iPSCs ( Zhou et al., 2011 ; Bento et al., 2020 ).

Urinary 8-Hydroxy-Deoxyguanosine

Urine 8-hydroxy-deoxyguanosine (8-OHdG) is a marker of DNA oxidative damage. It is mainly caused by a series of chemical processes in the body caused by ionizing radiation and chemical carcinogens, which lead to DNA oxidative damage. The markers produced are excreted in the urine through the kidneys and can only be formed through DNA oxidative damage. The content reflects the degree of oxidative damage in the body. 8-OHdG is not only a biomarker of systemic oxidative stress, but also a risk factor for atherosclerosis, tumors, and diabetes. In clinical practice, urine 8-OHdG levels are usually used to evaluate DNA oxidative damage and oxidative stress. Studies have shown that urine The change of 8-OHdG level may have a certain correlation with Parkinson’s disease, which is not yet clear ( Huang et al., 2018 ).

Gene Fragments of Cancer

So far, some disease markers have been found that can be found through urine tests. For example, researchers use a technology called Capp-Seq (Deep Sequencing for Cancer Individualization) to find bladder cancer DNA fragments in the urine of patients. By testing urine, they can effectively identify patients with early-stage bladder cancer, so that they can be treated in time. This new detection technology can accurately identify 83% of early-stage bladder cancer patients, while the current clinical urine cytology test can only identify 14% of bladder cancer patients ( CJCOR, 2019 ). And the latest research shows that for the diagnosis and treatment of prostate cancer, a highly accurate and non-invasive biopsy method that has been developed and verified is to use 25 genomes for urine testing as a follow-up fluid for the diagnosis and treatment of prostate cancer. Which can improve the diagnosis and treatment of prostate cancer ( Johnson et al., 2020 ).

8-Dihydroguanosine (8-oxo Gsn)

A study showed that as people grow older, 8-oxo Gsn, a substance in urine, can indicate cell damage during oxidation. A simple urine test can be used. Revealing the true age of the body, that is, showing its biological age, is expected to become a new marker of aging. The detection of such markers is more accurate than just judging by age, and may be beneficial to predict the risk of age-related diseases ( Liu and Xue, 2018 ).

Polypeptide Combination in Urine

Some scholars have used capillary electrophoresis-mass spectrometry (CE-MS) to compare the urine proteome of patients with coronary heart disease and normal people, and found that multiple combinations of urine peptides can identify coronary heart disease, with a sensitivity and specificity of 98 and 83%. This reflects to a certain extent that the biological information carried by urine can not only directly reflect the functional state of the urinary system, but also reflect the state of blood and the entire body to a certain extent ( Zha and Huang, 2019 ).

The Understanding and Application of Urine Test in Traditional Medicine

The microscopic analysis of urine has been one of the most routine inspection methods in modern hospitals at all levels, and it has developed to advanced microscopic technology and digital stage, but for the macroscopic characteristics of urine color, turbidity, odor, sediment and foam, etc. There are still not many ways to analyze it. Traditional urinary diagnosis is still worthy of being the most distinctive, simplest and most effective diagnostic method for Tibetan medicine, Mongolian medicine and Chinese medicine.

Due to the convenient availability of urine, Urinary diagnosishas an important position in traditional medicine. In the consultation of traditional Chinese medicine, the consultation of urine status is an indispensable link, as reflected in the “Ten Questions” of Chinese medicine. Traditional Chinese medicine believes that urine is one of the final products of body fluid metabolism. Water enters the body, transports and transforms through the spleen and stomach, and is transferred to the lungs. Through lung qi disseminate and liquefy, the esseatence part of it is used to nourish the whole body, and the turbid fluid in the metabolism of the viscera is transferred to the kidney or bladder. Under the action of the transpiration and gasification of the kidney qi, the clearer is dispersed throughout the body. Turbidity turns into urine. Urine contains the turbid fluid of various viscera metabolism and is regulated by multiple viscera. If the urine is abnormal, it reflects the abnormal function of the internal organs. The excrement of the human body is the messenger of physiological and pathological changes in the body. Su Weng, Zhi Zheng, Yao Da Lun records: “the body has an antagonist reflex, and the water is turbid, which is related to heat in the body. The body fluids in the course of the disease are cold and clear, which is a manifestation of body cold,” in other words, the cold and hot nature of the disease can be determined by the effluent ( Yang et al., 2016 ). For some exogenous diseases, it is sometimes difficult to distinguish whether the pathogen is on the outside or inside at this time. Zhongjing Zhang pointed out in Shang Hang Lun that it can be distinguished by urine conditions, such as Article 56: “Patients with Febrile Diseases and no bowel movements for six or 7 days, headache and fever syndrome, should be given Chengqi Decoction. If the patient has cold urine and knows that the patient’s pathogen is not in the body but still outside the body, sweating should be given. If the headache is accompanied by nose bleeding, Suitable for taking Guizhi Tang.” By judging whether the urine is hot or cold. Identify whether the disease is on the outside or on the inside ( Li and Guo, 1997 ), and the profit and loss of body fluid in the body can be judged by changes in urine output and urinary patency. During the development of the disease, the change from unfavorable urination to good urination also marks the transformation of the disease to the better, and the prognosis is good ( Wang et al., 2009 ). Combining the information of the other four medical examinations to make the dialectic of the outside and inside, cold and heat, deficiency and excess, yin and yang, through the observation and analysis of the patient’s internal and external conditions, to determine the location of the patient’s disease, its stage and prognosis, etc., ( Zhang et al., 2020 ). Tibetan doctors also have unique insights on urinary diagnosis and have summarized a set of relatively complete urine collection, observation and diagnosis methods. Among the various traditional medical systems in the world, there is no other medical system whose urinary consultation content and the degree of detailed observation can compare with the urinary consultation of Tibetan medicine ( Yang et al., 2016 ). The Tibetan medicine urinary clinic has also been included in the first batch of intangible cultural heritage lists of the country. In the History of World Civilization, it was recorded: “Urinalysis was a popular method at the time. The doctors in Tibet believe that there is no need to observe any other parts of the patient, just check the patients urine to treat the patient.” It can be seen that urinary diagnosis plays a pivotal role in Tibetan medicine ( Tang et al., 2020 ). Tibetology believes that urine belongs to the category of metabolites. It is the dregs of water throughout the body. It is formed by continuous differentiation after the human body consumes food ( Wang et al., 2009 ; Renqing, 2016 ). The source of urine is mainly produced by the five vital and six vessel organs. Urine the changes are related to living environment, diet and disease. The contents of Tibetan medicine urinary consultation mainly include smelling smell, observing color, how quickly the steam disappears, the size of steam, floating matter on the surface of urine, urine sediment, flocculent and foam in the middle layer of urine. For frail patients, Tibetans sometimes put the patient’s urine in a special container for Tibetan doctors to diagnose, so as to save the patient from the hardships of traveling on the road. The urinary clinic has a good reputation and practice foundation among the Tibetan people ( Bu and Ram, 2011 ; Shaoju, 2019 ).

The Application of Urine Testing Technology in Social Production and Life

Urine testing technology is also widely used in social life. In daily life, urine can be tested by pregnancy test sticks to determine whether pregnancy or not. The principle is to detect whether the urine contains human chorionic gonadotropin (HCG). The urine can be used to monitor whether you are pregnant or not, and the results can be obtained within a few minutes, eliminating the need to go to the hospital to queue for blood tests, and you can easily operate at home, which is safe and non-invasive. The test can go to the hospital for related examinations after a positive result is made for further confirmation, saving manpower, material resources and financial resources, and improving efficiency.

Since 1968, the International Olympic Committee has been using urine tests to detect whether athletes are taking stimulants. Urine tests are the main method and blood tests are supplemented. By collecting blood for testing, there may be discomfort after blood sampling or secondary adverse reactions, which may affect the results of the game. Urine tests are used to identify whether or not to take doping, which reduces the risk of exposure of athletes, improves the efficiency of testing, and minimizes the probability of these adverse events caused by invasive testing. It is a simple, effective and highly accurate method to detect whether athletes are taking doping through urine testing ( CSC, 1995 ; Zhou et al., 2015 ). In the past, it was impossible to find out after 2 weeks of stopping doping. With the advent of high-resolution mass spectrometers, the detection technology has made a great leap and development. Now even if the interval is 50–60 days, it can be detected relatively easily.

My country as a major drug ban country, it is also one of the methods of anti-drug inspection to test whether the urine contains drug metabolites to detect whether drugs have been used. Compared with blood tests, urine tests are more convenient for large-scale screening. Among drug users, the probability of carrying AIDS is relatively high, and the use of urine tests also reduces the risk of exposure of medical staff and related staff to a certain extent.

There is also the use of HP-ELISA diagnostic reagent urine test for the diagnosis of HP ( Helicobacter pylori ) infection ( Yixin and Jinbo, 2014 ). Urine tests are used to assess whether there has been recent alcohol consumption. By using uEtG as a biomarker of alcohol, it can help predict alcohol intake and overcome the deficiencies of self-reported. It can be used to help people who quit alcohol or researchers. Observation research during the experiment ( Grodin et al., 2020 ). There is also the use of commercial kits to extract and determine human DNA from urine. Urine may be successfully genotyped even if it is stored at 20°C for several months, and urine can be collected at many times of the day. To, this has important implications for public health research ( Bali et al., 2014 ). In the current use situation, there is also the use of test paper to detect albumin in the urine to monitor the occurrence and progress of cardiovascular disease and kidney disease ( Smink et al., 2012 ; Aiumtrakul et al., 2021 ). It is believed that there will be more urine testing technologies in the future to improve the convenience of people’s production and life and promote social development.

The Advantages and Disadvantages of the Common Urine Testing Technologies

At present, the clinically common urine detection techniques include microscopy, urine analyzer detection and urine dry chemical detection. The advantage of microscopy is that the detection accuracy is relatively high, but the detection time is long and the work efficiency is lower, and the requirements for the inspection personnel’s operating technology and inspection skills are also relatively high ( Shaoju, 2019 ). The advantages of urine dry chemical analysis and detection are simple and fast operation, and only a small amount of urine is needed to obtain a number of experimental parameters. However, it has strong randomness, many interference factors, and more frequent shortcomings of false positives and false negatives ( Jingzhi, 2007 ). The principle of analysis and detection of urine sediment analyzer is basically similar to the principle of manual microscopy. Both are intuitive observations of the constituents in the urine. However, the urine sediment analyzer undergoes strict timing, fixed speed, and quantification to quantify the test results, but the disadvantage is that the automatic urine sediment analyzer is susceptible to the influence of bacteria, myoglobin, and heat-prone enzyme factors, which reduces the specificity ( Yuhang et al., 2021 ).

Difficulties Faced by the Development of Urine Testing Technology

With the development of science and technology and the advancement of human understanding, the technology of urine testing has made great breakthroughs, but there is still a large distance from the ideal test target. In the urine collection process, it is also affected by many factors such as the patient’s collection time and improper operation during the collection process, resulting in test errors ( Shi, 2020 ; Zhou, 2020 ). The complexity and diversity of urine components and the susceptibility of urine to various factors make the research of urine still a great challenge at present. The more factors that affect urine, the more samples are needed for research and analysis, the amount is larger. At present, people are more enthusiastic about blood research than urine. From the perspective of the number of papers published, urine biomarkers only account for 7% of blood ( Zha and Huang, 2019 ), which also reflects the impact on urine. The research investment is far less than the research on blood. These are the problems currently facing the further development of urine testing technology. Therefore, opportunities and challenges coexist.

Prospects and Foreground for the Future Development of Urine Testing

Urine is rich in biological information. In the era of rapid development of bioanalysis technology and big data processing information, the human health code contained in the complex urine components will also be continuously decrypted. Some researchers believe that the method of searching for cancer DNA in body fluids rather than blood may be more widely used. Now for colon cancer, prostate cancer and other new generation urine diagnostic technologies, and some signs of finding signs in urine the better than the markers in the blood has also been initially recognized and explored by people. The technology of detecting cancer information markers through urine has entered the development process or will soon enter the hospital ( Li et al., 2020 ). Some scholars also want to use urine to detect volatile organic compounds to achieve the purpose of distinguishing cancer types ( Bannaga et al., 2020 ). Some experiments have proved that the health of athletes can be monitored through urine observation and analysis, so as to protect the health of athletes and improve their physical fitness ( Pero et al., 2020 ), which also indicates whether ordinary healthy people can also perform health self-examination through urine. Accessibility makes it easier for people to monitor their physical health ( Liu et al., 2020 ; Liu et al., 2021 ). Today, with the continuous development of medical inspection technology, these are all possible ideas. If more researchers can participate in the mining of the potential gold mine of urine testing, it may greatly accelerate the development of medical laboratory science and change the face of medical research and medical practice in the next century.

Author Contributions

HZ and XR contributed to conception and supervised the project. ZZ, JL, YC, and JC contributed in doing literature searches and wrote the manuscript draft. HZ, XR, ZZ, JL, YC, and JC equally revised and approved the manuscript. All authors have read and approved the final draft manuscript.

This work was supported by National Natural Science Foundation of China (81973697), project leader: HZ and National Natural Science Foundation of China (81774448), project leader: XR.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Aiumtrakul, N., Phichedwanichskul, K., Saravutthikul, S., Ottasat, K., Visuthitepkul, K., Jaruthiti, T., et al. (2021). Urine Albumin Dipstick Independently Predicts Cardiovascular and Renal Outcomes Among Rural Thai Population: a 14-year Retrospective Cohort Study. BMC Nephrol. 22 (1), 18. doi:10.1186/s12882-020-02215-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Bali, L. E., Diman, A., Bernard, A., Roosens, N. C. H., and Keersmaecker, S. J. D. E. (2014). Comparative Study of Seven Commercial Kits for Human DNA Extraction from Urine Samples Suitable for DNA Biomarker-Based Public Health Studies. J. Biomol. Tech. : JBT 25 (4), 96-110. doi:10.7171/jbt.14-2504-002

CrossRef Full Text | Google Scholar

Bannaga, A. S. I., Kvasnik, F., Persaud, K. C., and Arasaradnam, R. (2020). Differentiating Cancer Types Using a Urine Test for Volatile Organic Compounds. J. Breath Res. 15, 2–10. doi:10.1088/1752-7163/abc36b

Bento, G., Shafigullina, A. K., Rizvanov, A. A., Sardão, V. A., Macedo, M. P., and Oliveira, P. J. (2020). Urine-Derived Stem Cells: Applications in Regenerative and Predictive Medicine. Cells 9 (3), 573. doi:10.3390/cells9030573

Bouatra, S., Aziat, F., Mandal, R., Guo, A. C., Wilson, M. R., Knox, C., et al. (2013). The Human Urine Metabolome. PLOS ONE 8 (9), e73076. doi:10.1371/journal.pone.0073076

Bu, L., and Ram, L. (2011). On the Urinary Diagnosis of Tibetan Medicine[J]. Med. Inf. 24 (03), 862–863. doi:10.3969/j.issn.1006-1959.2011.03.065

Carrera, Ó. H., and Bueno, M. D. M. J. (2020). Cost Analysis of the Automated Examination of Urine with the Sysmex UN-series in a Spanish Population. PharmacoEconomics Open 4, 605–613. doi:10.1007/s41669-020-00200-3

CJCOR The Birth of a New Urine Detection Technology for Bladder Cancer[J]. Chin. J. Clin. Oncol. Rehabil. 2019, 26 (12), 1516.

Google Scholar

CSC (1995). Urine Test and Blood Test [J]. China Sports Coach 01, 36.

Dai, J., Li, Q., Qin, S., Qin, S., Zhang, L., Min, M., et al. (2003). Comparative Analysis of HIV Antibody Test Results in Blood and Urine of 203 Drug Addicts [J]. China AIDS and STDs (05), 278–279. doi:10.3969/j.issn.1672-5662.2003.05.009

Fan, X. (2020). Influencing Factors and Control Measures of Blood Test Results [J]. Guide China Med. 18 (31), 120.

Gao, Y. (2013). Urine May Be a Better Source of Biomarkers than blood[R] . Shandong, China: Qingdao .

Grodin, E. N., Nguyen, X. T., Ho, D., Bujarski, S., and Ray, L. A. (2020). Sensitivity and Specificity of a Commercial Urinary Ethyl Glucuronide (ETG) Test in Heavy Drinkers. Addict. Behav. Rep. 11, 100249. (prepublish). doi:10.1016/j.abrep.2020.100249

Hexing, W., Bin, W., Qi, Z., Zhao, Y., Fu, C., Femg, X., et al. (2015). Antibiotic Body burden of Chinese School Children: a Multisite Biomonitoring-Based Study. Environ. Sci. Technol. 49 (8), 5070–5079. doi:10.1021/es5059428

Huang, S., Xiaobin, T., Hui, C., and Zha, Y. (2018). Urine Marker Science[M] , 6. Beijing, China: Science Press , 77.

Jian, J., and Youhe, G. (2018). Urine Biomarkers in the Early Stages of Diseases: Current Status and Perspective. [J]. Discov. Med. 25 (136).

Jingzhi, M. (2007). Clinical Evaluation of the Comprehensive Application of Multiple Methods in 600 Urine Tests[J]. Cliniques (19), 1435.

Johnson, H., Guo, J., Zhang, X., Zhang, H., Simoulis, A., Wu, A. H. B., et al. (2020). Development and Validation of a 25-Gene Panel Urine Test for Prostate Cancer Diagnosis and Potential Treatment Follow-Up. BMC Med. 18, 376. doi:10.1186/s12916-020-01834-0

Li, S., and Guo, S. (1997). Significance of Clinical Application of "Treatise on Febrile Diseases" [J]. Guangming Traditional Chin. Med. 12 (73), 5–6.

Li, N., Ho, K. W. K., Ying, G.-G., and Deng, W.-J. (2017). Veterinary Antibiotics in Food, Drinking Water, and the Urine of Preschool Children in Hong Kong. Environ. Int. 108, 246–252. doi:10.1016/j.envint.2017.08.014

Li, J., Yang, M., Cheng, Y., Sun, T., and Liu, J. (2019). The Clinical Value of N∼1,N∼(12)-diacetylspermine as a New Tumor Marker[J]. Tianjin Sci. Technol. 46 (12), 85–88. doi:10.14099/j.cnki.tjkj.2019.12.026

Li, F., Chen, M., Zhang, Y., Yan, B., and Zheng, J. (2020). Multi-factor Analysis of Urine NMP22 Positive and Urine Routine Examination and Blood Examination in Zhoupu Area of ​​Shanghai. Lab. Med. Clin. 17 (11), 1515.

Li, M. (2014). Urine Is an Ideal Source of Disease Markers [D] . Beijing, China: Peking Union Medical College .

Liu, X., and Xue, H. (2018). Disease-related Information Is Hidden in Urine [J]. Basic Med. Clin. 38 (12), 1748. doi:10.16352/j.issn.1001-6325.2018.12.020

Liu, J. N., Tidwell, T., Zhao, H. H., Ren, Q. J., Mao, M., Li, J. L., et al. (2020). Theoretical Characteristics of Tibetan Medicine. World J. Tradit Chin. Med. 6, 490–499. doi:10.4103/wjtcm.wjtcm_21_20

Liu, J., Zhang, Z., Pang, X., Cheng, Y., Man, D., He, X., et al. (2021). Analysis of the Distribution of Urine Color and Its Relationship With Urine Dry Chemical Parameters Among College Students in Beijing, China - A Cross-Sectional Study. Front. Nutr. 8, 719260. doi:10.3389/fnut.2021.719260

Pero, R., Brancaccio, M., Mennitti, C., Gentile, L., Arpino, S., De Falco, R., et al. (2020). Urinary Biomarkers: Diagnostic Tools for Monitoring Athletes' Health Status. Int. J. Environ. Res. Public Health 17, 2–14. doi:10.3390/ijerph17176065

Prins, G. S., Hu, W.-Y., Shi, G.-B., Hu, D.-P., Majumdar, S., Li, G., et al. (2014). Bisphenol A Promotes Human Prostate Stem-Progenitor Cell Self-Renewal and Increases In Vivo Carcinogenesis in Human Prostate Epithelium. Endocrinology 155 (3), 805–817. doi:10.1210/en.2013-1955

Qiu, W., Long, W., and Luo, H. (2020). Clinical Application of Urine Test in the Diagnosis of Acute Fever Caused by Legionella pneumophila in Children. Heilongjiang Med. . 9 (44), 1252. doi:10.3969/j.issn.1004-5775.2020.09.033

Ren, Y. (2020). Feasibility Study of HIV Antibody Rapid Detection Method for Self-Detection [D] . Beijing, China: Chinese Center for Disease Control and Prevention .

Renqing, W. M. (2016). Discussion on the Application of Metabolomics Technology in the Urinary Diagnosis of Tibetan Medicine [J]. Chin. J. Ethnic Med. 22 (09), 39–50. doi:10.16041/j.cnki.cn15-1175.2016.09.027

Shaoju, S. (2019). Analysis of the Application Value of Urine Analyzer and Microscopy in Urine Testing[J]. China Med. Device Inf. 25 (09), 160–161. doi:10.3969/j.issn.1006-6586.2019.09.075

Shi, G. (2020). How Much Do You Know about Urine Tests [N] . Nanning City: Guangxi Zhuang Autonomous Region , 033.

Smink, P. A., Lambers Heerspink, H. J., Gansevoort, R. T., de Jong, P. E., Hillege, H. L., Bakker, S. J., et al. (2012). Albuminuria, Estimated GFR, Traditional Risk Factors, and Incident Cardiovascular Disease: the PREVEND (Prevention of Renal and Vascular Endstage Disease) Study. Am. J. Kidney Dis. 60 (5), 804–811. doi:10.1053/j.ajkd.2012.06.017

Tang, Z., Wu, A., Huang, X., Xiong, X., Li, C., Gong, R., et al. (2020). Investigation on Infectious Occupational Exposure of Medical Staff in Xiangya Hospital [J]. Chin. J. Nosocomial Infect. 30 (18), 2864. doi:10.11816/cn.ni.2020-192881

Tarapore, P., Ying, J., Ouyang, B., Burke, B., Bracken, B., and Ho, S. M. (2014). Exposure to Bisphenol A Correlates with Early-Onset Prostate Cancer and Promotes Centrosome Amplification and anchorage-independent Growth In Vitro . PLOS ONE 9 (3), e90332. doi:10.1371/journal.pone.0090332

Wang, H., and Bao, Z. (2019). Preliminary Study and Application of Hormone Analysis Methods in Urine of Diapers[J]. Environ. Occup. Med. 36 (11), 1001–1006. doi:10.13213/j.cnki.jeom.2019.19324

Wang, J., Gu, S., Zang, Y., Chen, B., and Shao, L. (2009). Looking at the Potential Value of Metabolomics in the Standardization of TCM Syndromes from Traditional Medical Urinary Diagnosis [J]. World Sci. Technol. 11 (01), 24–35. doi:10.3969/j.issn.1674-3849.2009.01.010

Wang, H., Tang, C., Yang, J., Wang, N., Jiang, F., Xia, Q., et al. (2018). Predictors of Urinary Antibiotics in Children of Shanghai and Health Risk Assessment. Environ. Int. 121 (Pt 1), 507–514. doi:10.1016/j.envint.2018.09.032

Wang, Y., Wang, J., Zhang, Z., and Chen, B. (2019). Urine Mesothelin Combined with Human Epididymal Protein in Patients with Ovarian Tumors and its Clinical Significance[J]. Shaanxi Med. J. 48 (8), 1088–1090.

Yang, M., Duan, X., and Shou, H. (2016). The Role of Urine Appearance in the Diagnosis of Traditional Chinese Medicine [J]. Guide Chin. Med. 22 (15), 114–116. doi:10.13862/j.cnki.cn43-1446/r.2016.15.040

Ye, L., Chen, X., Su, L., Liang, S., Yang, H., Yuan, D., et al. (2019). Comparison of the Performance of HIV Antibody Non-invasive (Oral Mucosal Exudate and Urine) Testing Reagents and Invasive (Blood) Testing Reagents[ J]. Int. J. Lab. Med. 40 (10), 1169–1173. doi:10.3969/j.issn.1673-4130.2019.10.005

Yixin, S., and Jinbo, Q. (2014). Evaluation of Non-invasive Laboratory Diagnosis Methods for Helicobacter pylori Infection[J]. Chin. J. Endemic Dis. Control. 29 (S2), 116.

Yuan, L., Li, Y. R., and Xu, X. D. (2018). Chronobiology -2017 Nobel Prize in Physiology or Medicine. Yi Chuan 40 (01), 1–11. doi:10.16288/j.yczz.17-397

Yuhang, C., Mingqin, F., and Hong, H. (2021). Application of Automatic Urine Sediment Analyzer and Microscope Detection Method in Routine Urine Inspection[J]. Med. Equipment 34 (17), 59–63.

Zha, Y., and Huang, S. (2019). Urine Biochemistry and Inspection[M] . Beijing, China: People's Medical Publishing House , 5–815.

Zhang, D., and Liang, Y. (2016). Blood[M] . Wuhan, China: Hubei Science and Technology Press , 11–12.

Zhang, Y., Bai, J., and Zhou, Y. (2020). Characteristics of Occupational Exposure to Blood-Borne Pathogens in a Hospital in Southwest China from 2015 to 2019 [J]. Chin. J. Infect. Control. 19 (12), 1054. doi:10.12138/j.issn.1671-9638.20206169

Zhao, H. (2013) Study on the Correlation Between Estrogen Metabolites in Liquid and Endometrial Cancer [J] . Hebei Medical University .

Zhou, T., Benda, C., Duzinger, S., Huang, Y., Li, X., Li, Y., et al. (2011). Generation of Induced Pluripotent Stem Cells from Urine. Jasn 22 (7), 1221–1228. doi:10.1681/asn.2011010106

Zhou, T., Wang, M., Fang, H., Cui, J., Zhang, J., Zhuo, Z., et al. (2015). Research and Implementation of Doping Detection Methods[J]. Rev. Develop. Sci. Technol. Award China Assoc. Anal. Test. 9.

Zhou, T. (2020). What Is in Your Urine? [J]. Healthy Home 11, 57.

Keywords: urine test, blood test, medical test, traditional Chinese medicine urinary examination, Tibetan medicine urinary examination

Citation: Zhang Z, Liu J, Cheng Y, Chen J, Zhao H and Ren X (2022) Urine Analysis has a Very Broad Prospect in the Future. Front. Anal. Sci. 1:812301. doi: 10.3389/frans.2021.812301

Received: 17 November 2021; Accepted: 29 December 2021; Published: 02 February 2022.

Reviewed by:

Copyright © 2022 Zhang, Liu, Cheng, Chen, Zhao and Ren. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Huihui Zhao, [email protected] ; Xiaoqiao Ren, [email protected]

† These authors have contributed equally to this work and share first authorship

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Lough, Patricia Schechter. "Use of urine samples for ethanol analysis." CSUSB ScholarWorks, 1989. https://scholarworks.lib.csusb.edu/etd-project/446.

Abdelrazig, Salah M. A. "Mass spectrometry for high-throughput metabolomics analysis of urine." Thesis, University of Nottingham, 2015. http://eprints.nottingham.ac.uk/30600/.

Cooper, Mark Thomas. "A chromatographic method for detecting phenolic metabolites of carbosulfan in urine." Thesis, Queensland University of Technology, 1989. https://eprints.qut.edu.au/35977/1/35977_Cooper_1989.pdf.

Kirk, Jayne Marie. "Mass Spectrometric Analysis of Steroid Hormones for Application in Analysis of Bovine Urine." Thesis, University of York, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.485830.

Couchman, Lewis. "LC-MS/MS analysis of buprenorphine and norbuprenorphine in urine." Thesis, Queen Mary, University of London, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511397.

Hassan, Syed Saeed-Ul. "Rapid immunological methods for analysis of dexamethasone in equine urine." Thesis, University of Sunderland, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.245822.

Allen, Robert Douglas III. "Development of an assay for the detection of cytomegalovirus in urine." Thesis, Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/25410.

Chen, Hui-Chuen. "The urinary excretion of mercapturic acids in free-living adult males." Thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-12052009-020010/.

Hoang, Tiffany Truc. "Speciation and identification of low molecular weight organoselenium metabolites in human urine." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/30671.

Stubbs, Christopher. "High performance liquid chromatographic analysis of erythromycin in serum and urine." Thesis, Rhodes University, 1985. http://hdl.handle.net/10962/d1004581.

West, Robert E. 1952. "Confirmation of urinary benzodiazepines by gas chromatography/mass spectrometry." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277228.

Rocha, Diogo Librandi da. "Desenvolvimento de procedimento analítico em fluxo com multicomutação para a determinação espectofotométrica de ácido úrico em urina." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/46/46133/tde-05102009-105307/.

Hannon, Sarrah. "Analysis of cocaine adulterants and their metabolites in real patient urine samples." Thesis, Boston University, 2013. https://hdl.handle.net/2144/12114.

Kelly, Barbara M. "The analysis of biological fluids for acylcarnitines." Thesis, Open University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326566.

Dumitrescu, Vlad Andrei. "Comparative analysis of biogas slurry and urine as sustainable nutrient sources for hydroponic vertical farming." Thesis, Linköpings universitet, Tema vatten i natur och samhälle, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-96368.

De, Kock Neil. "The development of direct infusion mass spectrometry method for analysis of small metabolites in urine." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/80213.

Wu, Ruige, and 吴瑞阁. "Microchip-capillary electrophoresis with two-dimensional separation and isotachophoresis preconcentration for determining low abundanceproteins in human urine and dairy products." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46506044.

Shreeram, Devesh Dadhich. "Electrochemical Analysis of Genetically Engineered Bacterial Strains in a Urine-Based Microbial Fuel Cell." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1458814734.

Low, Ann Stewart. "An evaluation of analytical procedures for detection of drug abuse with particular reference to opiates." Thesis, Robert Gordon University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242985.

Kim, Yuni T. "The effects of broccoli on the excretion of urinary conjugates." Diss., Virginia Tech, 1992. http://hdl.handle.net/10919/38535.

Diaz, Sílvia de Oliveira. "Pregnancy and newborns disorders followed by urine metabolomics." Doctoral thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/13110.

Troster, Charles Micah Smolkin. "Trace analysis of cyclophosphamide and its metabolites in urine by liquid chromatography-tandem mass spectrometry." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/29263.

Cromwell, Wyn Zhang. "An Analysis of the Loops of Henle and Urine Concentrating Mechanisms in the Kangaroo Rat." Thesis, The University of Arizona, 2011. http://hdl.handle.net/10150/144330.

Fong, Ka-wah Martin, and 方家華. "Adaptation of a simplified method for urinary iodine for studying the iodine status of local Chinese." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31971726.

Härmä, Johan. "Validation of a method for analyzing urinary Cystatin C and analysis of ULSAM-77 urine samples." Thesis, Uppsala universitet, Institutionen för medicinsk biokemi och mikrobiologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-177342.

Bulusu, Sudha. "Analysis of organic acids by high performance liquid chromatography in urine and plasma and its applications." Thesis, University of Southampton, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.280405.

Li, Xin. "Comparative evaluation of the extraction and analysis of urinary phospholipids and lysophospholipids using MALDI-TOF/MS." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/265182.

Van, Buynder Paul G. "The epidemiology of renal disease in Aboriginal Australians." Thesis, The University of Sydney, 1991. https://hdl.handle.net/2123/26311.

Yap, Bin Kiat. "Exercise-stress responses of urinary hormones." Thesis, The University of Sydney, 1994. https://hdl.handle.net/2123/26858.

Silva, Júnior Jarbas Miguel da. "Excreção urinária de derivados de purinas e de compostos nitrogenados de zebuínos em pastejo." Universidade Federal de Viçosa, 2014. http://locus.ufv.br/handle/123456789/5825.

Li, Jiufeng. "Determination and evaluation of endocrine disrupting chemicals in urine samples of pregnant women by liquid chromatography-tandem mass spectrometry." HKBU Institutional Repository, 2020. https://repository.hkbu.edu.hk/etd_oa/757.

Wiens, Kristy. "Design of an optical uroflowmeter and assessing bladder pressure through video analysis of the male urine stream." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/43722.

Buist, Neil R. M. "Fifty years in inborn errors of metabolism : from urine ferric chloride to mass spectrometry and gene analysis." Thesis, University of St Andrews, 2014. http://hdl.handle.net/10023/12724.

Avery, Thomas W. "Further characterization of the direct injection nebulizer for flow injection analysis and liquid chromatography with inductively coupled plasma spectrometric detection." Virtual Press, 1988. http://liblink.bsu.edu/uhtbin/catkey/539620.

Lugogo, Rita de Nicolo. "Quantitative assessment of daily urinary conjugates in an adult male population." Diss., This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-06062008-171211/.

Bordin, Keliani. "Avaliação de biomarcadores da exposição humana à fumonisina B1 nos alimentos em municípios dos estados de São Paulo e Santa Catarina, Brasil." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/74/74132/tde-23042015-140349/.

McBride, M. B. "The development and evaluation of an HPLC method of analysis for nicotine and its major metabolites in urine." Thesis, University of Bristol, 1988. http://hdl.handle.net/1983/9268fc8e-2d95-426e-b6a3-7cdfd849fc15.

Wood, Jennifer. "A study of the development of the adrenal gland in very low birthweight babies by gas chromatographic analysis of urinary steroid profiles." Thesis, The University of Sydney, 1995. https://hdl.handle.net/2123/26836.

Shadbolt, Sheila. "The use of ¹H-NMR analysis of urine to discriminate between calcium oxalate kidney stone patients and healthy controls." Master's thesis, University of Cape Town, 2001. http://hdl.handle.net/11427/6362.

Lange, Tim Verfasser], Karlhans [Akademischer Betreuer] [Endlich, Karlhans Gutachter] Endlich, and Sebastian [Gutachter] [Bachmann. "Identification and analysis of urine-derived exosomal miRNAs and BDNF / Tim Lange ; Gutachter: Karlhans Endlich, Sebastian Bachmann ; Betreuer: Karlhans Endlich." Greifswald : Universität Greifswald, 2020. http://nbn-resolving.de/urn:nbn:de:gbv:9-opus-35795.

Lange, Tim Verfasser], Karlhans [Akademischer Betreuer] [Endlich, Karlhans [Gutachter] Endlich, and Sebastian [Gutachter] Bachmann. "Identification and analysis of urine-derived exosomal miRNAs and BDNF / Tim Lange ; Gutachter: Karlhans Endlich, Sebastian Bachmann ; Betreuer: Karlhans Endlich." Greifswald : Universität Greifswald, 2020. http://d-nb.info/1206688335/34.

Lange, Tim [Verfasser], Karlhans [Akademischer Betreuer] Endlich, Karlhans [Gutachter] Endlich, and Sebastian [Gutachter] Bachmann. "Identification and analysis of urine-derived exosomal miRNAs and BDNF / Tim Lange ; Gutachter: Karlhans Endlich, Sebastian Bachmann ; Betreuer: Karlhans Endlich." Greifswald : Universität Greifswald, 2020. http://d-nb.info/1206688335/34.

Dinh, Nancy Vien. "An analysis of the accuracy and function of three presumptive methods used in forensic science for the detection of urine." Thesis, Boston University, 2012. https://hdl.handle.net/2144/12349.

Tsai, Mon-Yo, and 蔡孟祐. "Analysis of Phenol In Water and In Urine." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/63672126858091467266.

Ncube, Somandla. "Liquid phase microextraction of hallucinogenic compounds from human urine samples based on single hollow fibre followed by chromatographic determination." Thesis, 2016. http://hdl.handle.net/10539/21207.

Fu-Ren and 江福仁. "Mass Spectrometric Analysis of Benzodiazepins In Urine and Hair." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/40151268630350543257.

Lin, Shih-Shan, and 林詩珊. "Analysis of cathinones in urine by chromatography/mass spectrometry." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/35g9tu.

Liu, Hsu-Che, and 劉旭哲. "Patent Analysis of Urine Sensing Technologies for Kidney Disease." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/n9wnar.

Chia-HungHsia and 夏嘉鴻. "Development of Home Health Checkup System for Urine Analysis." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/yj2xar.

Lung, Su-Yi, and 蘇意隆. "Evaluation of Bioeletrical Impedance Analysis for Intravesical Urine Volume Assessment." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/97654111336974928193.

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Urinalysis articles from across Nature Portfolio

Urinalysis is the examination of urine using laboratory techniques and procedures. The composition of urine can provide information regarding hydration status, infection, kidney function, hormones and urogenital diseases.

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Urinary concentrations of neonicotinoid insecticides were related to renal tubular dysfunction and neuropsychological complaints in Dry-zone of Sri Lanka

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Comparison of questionnaire-based estimation of pesticide residue intake from fruits and vegetables with urinary concentrations of pesticide biomarkers

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Assessing the conundrum of microscopic haematuria

The compliance of physicians to current guidelines for asymptomatic microhaematuria is limited and the evidence supporting asymptomatic microhaematuria as an effective screening tool for the early detection of bladder cancer is weak. Medical or surgical treatment is indicated in 13–35% of patients with asymptomatic microhaematuria, albeit mostly for benign conditions, which are more commonly the cause. The high prevalence of asymptomatic microhaematuria in the general population means that this condition poses a considerable challenge to the health-care system.

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Clinical profile of urinary tract infections in diabetics and non-diabetics

Affiliations.

• 1 Department of Internal Medicine, Kasturba Medical College, Manipal University, Manipal, India.
• 2 Former Associate Professor, Department of Internal Medicine, Kasturba Medical College, Manipal University, Manipal, India.
• PMID: 24567764
• PMCID: PMC3920469
• DOI: 10.4066/AMJ.2014.1906

Background: The risk of urinary tract infection (UTI) is higher in diabetics compared to non-diabetics. The aetiology and the antibiotic resistance of uropathogens have been changing over the past years. Hence the study was undertaken to determine if there are differences in clinical and microbiological features of UTI between diabetic and non-diabetic subjects, to study the influence of diabetes mellitus on the uropathogens and antibiotic sensitivity pattern in patients with UTI.

Method: A total of 181 diabetics (83 males and 98 females) and 124 non-diabetic subjects (52 males and 72 females) with culture positive UTI were studied. Patients with negative urine culture (n= 64), those diagnosed and treated outside (n= 83) and not willing to participate in the study (n= 24) were excluded.

Results: Almost 30 per cent of the patients (both diabetics and nondiabetics) presented with asymptomatic bacteriuria and the prevalence of pyelonephritis was significantly higher (p= 0.04) in diabetics compared to non-diabetic patients. The majority of the diabetics with UTI (87.14 per cent) had glycosylated haemoglobin (HbA1c) > 6.5 per cent with p < 0.001. The isolation rate of Escherichia coli (E. coli) from urine culture was higher (64.6 per cent) among diabetic patients followed by Klebsiella (12.1 per cent) and Enterococcus (9.9 per cent). The prevalence of extendedspectrum beta-lactamase (ESBL) producing E.coli was significantly higher in diabetics (p= 0.001) compared to nondiabetics. E.coli showed maximum sensitivity to carbapenems in both diabetic and non-diabetic subjects and least susceptibility to ampicillin.

Conclusion: The prevalence of pyelonephritis is significantly higher in diabetics than in non-diabetic subjects, with E. coli being the most common isolate. Elevated glycosylated hemoglobin (HbA1c) predisposes diabetics to UTI. Investigation of bacteriuria in diabetic patients for urinary tract infection is important for treatment and prevention of renal complications.

Keywords: Asymptomatic bacteriuria; Diabetic patients; E. coli; Urinary tract infection; Uropathogens.

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• Introduction

Around 6,000 years ago, laboratory medicine began with the analysis of human urine as uroscopy, which later became termed urinalysis . The word "uroscopy" derives from two Greek words: " ouron," which means urine and " skopeoa," which means to 'behold, contemplate, examine, inspect'. Ancient physicians spoke of urine as a window to the body's inner workings and reflected different diseases. For instance, Hindu civilizations recognized a "sweetness" in certain people's urine, which attracted black ants. [1]  Hippocrates (460–355 BC) hypothesized that urine was a filtrate of the humors in the body, originating from the blood filtered through the kidneys. In Aphorisms, he described bubbles on the surface of fresh urine as a sign of long-term kidney disease and associated urinary sediment with fever. [2]  Galen used the phrase " diarrhea of the urine" to describe excessive urination. [3]  Theophilus Protospatharius, a seventh-century physician who wrote the first manuscript focused exclusively on urine called " De Urinis" , determined heating urine would precipitate proteins, documenting proteinuria as a disease state. [4]  Ismail of Jurjani, an eleventh-century physician, acknowledged food and aging altered urine composition and was the first to propose 24 hours urine collection.

By the late 12th-century, a French scholar named Gilles de Corbeil taught and classified 20 different types of urine, recording differences in urine sediment and color. De Corbeil also introduced the " matula," a glass vessel in which a physician could assess color, consistency, and clarity. [5] In 1630, Nicolas Fabricius de Peiresc, a French astronomer and naturalist, did the first microscopic description of urine crystals as "a heap of rhomboidal bricks." [6]  Posteriorly, in the early-mid 1800s, Richard Bright, an English physician, pioneered the field of kidney research leading him to be ultimately recognized as the "father of nephrology." These few examples illustrate how urinalysis was the first laboratory test developed in the history of medicine, how it has been persistently used for several thousand years, and how it continues to be a formidable and cost-effective tool to obtain crucial information for diagnostic purposes. [7]

• Specimen Requirements and Procedure

Urine is an unstable fluid; it changes composition as soon as it is eliminated through micturition. [7] Accurate collection, storage, and handling are crucial to maintaining the sample’s integrity. 

Urine samples collected from the first void or “morning urine” are considered the best representative for testing. The urine accumulated overnight in the bladder is more concentrated, thus provides an insight into the kidneys’ concentrating capacities and allows for the detection of trace amounts of substances that may not be present in more diluted samples. [7] [8]  However, other types of urine specimens may be ordered according to specific purposes (randomly, 2-hours postprandial, 24-hour collection). Furthermore, urine should be ideally examined within the first hour after the collection due to the instability of some urinary components (cells, casts, and crystals). If not possible, the sample should be refrigerated at 4 degrees C for up to 24 hours, which will slow down the decomposition process. Any specimen older than 24 hours cannot be used for urinalysis. [7] [8]

There are two methods to obtain a urine specimen: non-invasive and invasive techniques . Spontaneous voiding is the main non-invasive technique, although other strategies may be used in children who cannot yet control their voiding (i.e., bag urine). In contrast, urethral catheterization and suprapubic bladder puncture are the two invasive procedures described to date. The fundamental principle of either technique is to obtain a specimen without external contamination. 

Non-invasive Techniques 

Spontaneous voiding is the simplest and most commonly used method in clinical practice. Before collecting the sample, health personnel should be provided clear instructions to patients in order to minimize the chance of contamination from penile/vaginal microbiota (“clean-catch” method). Most urine collection kits include a sterile container with a lid and sterile moist towels to wipe the urethral area before collection; if not, cotton wool or toilet tissue and/or tap water with soap may be used. Traditionally, male patients are instructed to retract the foreskin and clean the glans of the penis before urinating. Consequently, females should clean the labia and urethral meatus as well before collection. Currently, it is under debate the need for these standard precautions, and even many areas no longer perform them. [7] [8] [9]

Subsequently, the patient should first void a small amount of urine into the toilet and afterward position the container mid-stream in the flow of urine. Approximately, only 15 mL to 30 mL of urine is sufficient for accurate analysis, so, in most cases, patients should be advised not to fill the containers to their full capacity. Finally, the container is closed with careful precautions not to contaminate its lid or rim, and the patient may finish urinating in the toilet, bedpan, etc. The sample must be labeled before or immediately following collection, and it should not be on the lid. [7] [8]   

Invasive Techniques

Invasive urine collection is warranted when patients cannot cooperate, have urinary incontinence or external urethral ulceration that increases contamination risk. Both of these techniques pose a risk for the inoculation of pathogens, thus causing urinary tract infections. 

Urethral catheterization involves a small French urinary catheter passed through the urethral meatus after the previous cleansing with proper equipment. Depending on the catheter, personnel may or may not need a sterile syringe. In cases where patients already have a urinary catheter placed, the specimen should never be taken from the catheter bag as it is considered contaminated. 

Suprapubic needle aspiration of the bladder is both the most invasive and uncomfortable procedure of all previously mentioned and may generate false-positive results (protein, red and white cells) as a consequence of blood contamination. They are generally reserved for situations where samples may not be obtained or are persistently contaminated through previous methods, which usually occurs in small children. The main advantage is that, by bypassing the urethra, it minimizes the risk of obtaining a contaminated sample. 

Before the procedure, trained personnel must identify the bladder by examination. If not distinguished, it is recommended to hydrate the patient and wait until correct identification or use ultrasound guidance if available. After proper cleaning with an antiseptic solution and anesthetizing the skin located approximately 5 cm above the pubic symphysis, a small needle (i.e., 22-gauge spinal needle x 10 cm in adults) is inserted approximately at 60 degrees at the point identified previously. The needle is directed slightly caudal or cephalic in adults or children, respectively, according to the anatomic location. Usually, the needle will enter the abdominal bladder after advancing it approximately 5 cm in adults. Finally, attempt to aspirate using a sterile syringe. If a sample is not obtained, advance the needle applying continuous suction on the syringe. If unsuccessful after an additional 5 cm in adults, withdraw the needle and repeat the procedure. If unsuccessful, personnel should seek help from a specialist or use ultrasound guidance if not previously done. [7] [8] [10]

• Diagnostic Tests

A complete urinalysis consists of three components or examinations: physical , chemical , and microscopical . 

• Physical examination describes the volume, color, clarity, odor, and specific gravity.
• Chemical examination identifies pH, red blood cells, white blood cells, proteins, glucose, urobilinogen, bilirubin, ketone bodies, leukocyte esterase, and nitrites.
• Microscopic examination encompasses the detection of casts, cells, crystals, and microorganisms.
• Interfering Factors

The following factors may alter the results of a urine sample analysis:

• Light and Temperature: If exposed for a considerable period of time, bilirubin and urobilinogen may decompose due to their instability under these conditions. Additionally, room temperature favors the growth of microorganisms, such as bacteria.
• Bacterial Growth: Contamination of the sample or pathogenic bacteria may produce a variety of inaccurate results. For example, they may produce a false-positive blood reaction and affect the specimen's pH towards acidity or alkaline. 
• Alkaline pH: This concentration may show false-positive results regarding the presence of protein.
• Glucose: If present in the sample, it may be metabolized by microorganisms and cause a decrease in the sample's pH.
• Contrast Agents: May produce false-positive results of specific gravity.
• Exercise: May alter the specific gravity and electrolyte concentration of the sample.
• Foods and Drugs: May alter the urine's color, odor, or pH value. Examples include, but are not limited to, red beets, blackberries, rhubarb, food coloring (e.g., aniline), ibuprofen, chloroquine, metronidazole, deferoxamine, nitrofurantoin, phenytoin, rifampicin, phenolphthalein, phenothiazines, and imipenem/cilastatin.
• Thymol: May generate false-positive reactions for albumin.
• Formaldehyde: May cause false-positive results for leukocyte esterase, peroxidase reaction, urobilinogen, and glucose if strips are used.
• Hydrochloric Acid: Although used to preserve cell structures and determine steroid concentrations, it affects the sample's pH. 
• Mercury Salts: May produce false-negative results for leukocyte esterase reaction. 
• Boric Acid: While commonly used to preserve bacteria present in urine, this substance may reduce the sensitivity of the leukocyte reagent on dipsticks and alter initial pH values. Moreover, excessive concentrations may prevent bacterial growth in samples reserved for culture. [11] [12] [13]
• Results, Reporting, and Critical Findings

Physical Examination

Only in a few instances, the color, odor, and/or appearance are of clinical significance; nonetheless, any abnormal finding should be noted.

• Normal: Yellow (light/pale to dark/deep amber)
• Amber: Bile pigments
• Brown/Black (Tea-colored): Bile pigments, cascara, chloroquine, fava beans, homogentisic acid (alkaptonuria), levodopa, melanin or oxidized melanogen, methemoglobin, methyldopa, metronidazole, myoglobin, nitrofurantoin, primaquine, rhubarb, riboflavin, senna
• Dark Yellow: Concentrated specimen (dehydration, exercise)
• Green/Blue: Amitriptyline, asparagus, biliverdin, cimetidine, clorets (breath mint), indicans, indigo carmine, indomethacin, methocarbamol, methylene blue, promethazine, propofol, pseudomonal UTI, triamterene
• Orange: Bile pigments, carrots, coumadin, nitrofurantoin, phenothiazines, phenazopyridine, rifampin, vitamin C
• Pink/Red: Beets, blackberries, chlorpromazine, food dyes, hematuria, hemoglobinuria, menstrual contamination, myoglobinuria, phenolphthalein, porphyrins, rifampin, rhubarb, senna, thioridazine, uric acid crystals. [7] [14]  A urine sample that turns red on standing suggests the presence of porphobilinogen, which is increased in acute porphyrias.
• Normal: Clear or translucent
• Associations: Bacteria, blood clots, contrast media, a diet high in purine-rich foods, fecal contamination or material (i.e., gastrointestinal-bladder fistula), lipids such as chyluria (chylomicrons in the urine), lymph fluid, mucus, precipitation of cells (red blood cells (RBC), white blood cells (WBC), squamous and non-squamous epithelial cells), casts or crystals (calcium phosphate, calcium oxalate, uric acid), pyuria, semen, small calculi, talcum powder, vaginal creams or secretions, yeast or non-specific/normal. [7] [14]  
• Not routinely reported
• Normal: "Urinoid"
• Cystine Decomposition: Sulfuric smell
• Dehydration/Prolonged Room Temperature: Strong smell
• Diabetes Mellitus: Honey
• Diabetic Ketoacidosis: Fruity/sweet
• Gastrointestinal-bladder Fistula: Fecal smell
• Maple-syrup Urine Disease: "Burnt sugar."
• Prolonged Bladder Retention: Ammoniacal
• Urinary Tract Infection: Pungent or fetid
• Medications and Diet: Onions, garlic, asparagus [7] [14]

Specific Gravity (USG)/Osmolality (O)

The urinary specific gravity (USG) and osmolality are of special importance because they indicate the kidney's capacity to dilute or concentrate urine. USG is defined as the ratio between the density of urine and the density of an equal volume of pure distilled water. Normal values are lab-dependent since there are multiple methods to calculate this parameter (hydrometer, dipstick reagent pad, refractometer, and harmonic oscillation or urinometry). As it depends primarily on mass, it is not a truly reliable measure for quantifying the exact number of solute particles. Thus, USG is commonly used to rapidly estimate screen urine concentration, employing the term hyposthenuric and hypersthenuric depending on whether the USG is diminished, or elevated. Isosthenuria connotes urine with a fixed specific gravity and portends renal disease. Conversely, osmolality is a measure of the sum of all dissolved particles in urine. It is more reliable and accurate than USG for evaluating kidney function. Urine osmolality ranges from 50-1200 mOsmol/kg; the key is to always compare to serum osmolality to establish a pathological condition. Both parameters directly correlate; for example, a USG of 1.010 approximates to a urine osmolality of 300 mOsm/kg. [7] [15]

• Normal: USG = 1.002-1.035 (usually 1.016 to 1.022). O = 50-1200 mOsm/kg (usually 275-900 mOsm/kg) [Both parameters are lab dependent]
• Variations according to the patient’s diet, health, hydration status, and physical activity.
• High Values: Contrast media, dehydration, decreased renal blood flow (shock, heart failure, renal artery stenosis), diarrhea, emesis, excessive sweating, glycosuria, hepatic failure, syndrome of inappropriate antidiuretic hormone (SIADH)
• Low Values: Acute tubular necrosis, acute adrenal insufficiency, aldosteronism, diuretic use, diabetes insipidus, excessive fluid intake (psychogenic polydipsia), impaired renal function, interstitial nephritis, hypercalcemia, hypokalaemia, pyelonephritis
• False Elevation: Dextran solutions, intravenous (IV) radiopaque contrast media, proteinuria
• False Depression: Alkaline urine [7] [11] [14] [15]
• Normal: 0.5 to 1.5 cc/kg/hour or 600 and 2,000 mL daily in adults (typically 1,000– 1,600 mL/day)
• Anuria (less than 100 cc/day) and oliguria (less than 500 cc/day): Severe dehydration from vomiting, diarrhea, hemorrhage or excessive sweating; renal disease, renal obstruction, renal ischemia secondary to heart failure or hypotension
• Polyuria (greater than 2,500 - 3,000 cc/day): Alcohol or caffeine consumption, diabetes mellitus, diabetes insipidus, diuretics, increased water intake, saline or glucose intravenous therapy [7]
• Normal: Appears upon agitation and dissipates readily on standing
• Associations: Proteinuria, bile pigments, retrograde ejaculation, medications (phenazopyridine, etc.), non-specific/unexplained [7] [11] [14]

Chemical Examination

Urine pH is a vital piece of information and provides insight into tubular function. Normally, urine is slightly acidic because of metabolic activity. A urinary pH greater than 5.5 in the presence of systemic acidemia (serum pH less than 7.35) suggests renal dysfunction related to an inability to excrete hydrogen ions. On the contrary, the most common cause of alkaline urine is a stale urine sample due to the growth of bacteria and the breakdown of urea releasing ammonia. Determination of urinary pH is helpful for the diagnosis and management of urinary tract infections and crystals/calculi formation. [7] [11] [14]

• Normal: 4.5 to 8 (usually 5.5 to 6.5)
• High Values (alkaline): Stale/old urine specimens (most common), hyperventilation, presence of urease-producing bacteria, renal tubular acidosis, vegetarian diet, vomiting.
• Low Values (acid): Cranberry juice, dehydration, diabetes mellitus, diabetic ketoacidosis, diarrhea, emphysema, high protein diet, starvation, potassium depletion, medications (methionine, mandelic acid, etc.), and a possible predisposition to the formation of renal or bladder calculi. [7] [11] [14] [15]

Proteinuria is another critical finding. In normal conditions, the glomerular capillary wall is permeable to molecules of less than 20,000 Daltons. Most of the small fraction of filtered proteins are reabsorbed and metabolized by the proximal tubule cells. Thus, proteins are normally present in urine in trace amounts. From the total urinary proteins, approximately one-third of the total is albumin, another third is a protein secreted by the tubular cells called Tamm–Horsfall glycoprotein, and the rest is made up of plasma proteins such as globulins. Proteinuria can be classified into a transient or persistent, with the first one typically been a benign condition (i.e., orthostatic proteinuria due to prolonged standing). For the latter, persistent proteinuria can my categorized as a glomerular pattern, a tubular pattern, and an overflow pattern. The first occurs when proteins that are not normally filtered (i.e., albumin, transferrin) pass by a damaged glomerular capillary wall. Thus, this pattern may be seen with low serum albumin, secondary generalized edema, and high serum lipids as in nephrotic syndrome. Usually, protein excretion is greater than 3.0 g/day to 3.5 g/day. The tubular pattern results from the tubular cells' inability to reabsorb filtered proteins. Consequently, small serum proteins are typically seen in the microscopic examination, and proteinuria is not relatively high (approximately 1 g/day to 2 g/day). Finally, overflow proteinuria occurs when excessive concentrations of small proteins in plasma are filtered, and tubular cells reabsorption's capacity is surpassed, which occurs in conditions such as rhabdomyolysis (myoglobin) and multiple myeloma (Bence Jones light chains). This phenomenon harms tubular cells, and they may be seen on microscopic examination.   Qualitative assessment of minimal amounts of proteinuria serves as a marker for glomerular injury and risk of progression of renal disease. Normal albumin excretion is less than or equal to 29 mg/g creatinine. It is best to express albuminuria per gram of creatinine. According to the Kidney Disease Improving Global Outcomes (KDIGO) guidelines, albuminuria can be classified into three stages: A1 (less than 30 mg/g creatinine; normal to mildly increased), A2 (30 mg/g to 300 mg/g creatinine; moderately increased, formerly termed as "microalbuminuria"), and A3 (greater than 300 mg/g creatinine; severely increased). [7] [14] [16] [17]

Normal: Proteinuria  less than or equal to 150 mg/day (typically albuminuria less than 30 mg/day) or 10 mg/dL

• Albuminuria of 30 mg/day to 300 mg/day is an indicator of early renal disease, glomerular injury, and risk of progression of renal disease
• Other Associations: Multiple myeloma, congestive heart failure, Fanconi syndrome, Wilson disease, pyelonephritis, and physiological conditions (strenuous exercise, fever, hypothermia, emotional distress, orthostatic proteinuria, and dehydration)
• False-positive: Alkaline or concentrated urine, phenazopyridine, quaternary ammonia compounds
• False-negative: Acid or dilute urine, primary protein is not albumin [7] [11] [14] [15]

Blood Cells

• Dipstick test for blood detects primarily the peroxidase activity of erythrocytes, but myoglobin and hemoglobin can also catalyze this reaction. Thus, a positive test result indicates hematuria, myoglobinuria, or hemoglobinuria.
• Normal: Negative (usually) or less than or equal to 5 RBCs per mL (lab-dependent value)
• Hematuria: Renal calculi, glomerulonephritis, pyelonephritis, tumors, trauma, anticoagulants, strenuous exercise, exposure to toxic chemicals
• Hemoglobinuria: Hemolytic anemias, RBC trauma, strenuous exercise, transfusion reactions, severe burns, infections (i.e., malaria)
• Myoglobinuria: Muscle trauma eg, rhabdomyolysis, prolonged coma, convulsions, drug abuse, extensive exertion, alcoholism/overdose, muscle wasting diseases
• False-positive: Dehydration, exercise, hemoglobinuria, menstrual blood, myoglobinuria
• False-negative: Captopril, elevated specific gravity, acid urine, proteinuria, vitamin C [7] [11] [14] [15]

Glycosuria occurs when the filtered load of glucose exceeds the tubular cells' ability to reabsorb it, which normally happens at a glucose serum concentration of around 180  mg per dL. Furthermore, nitrites are not normally found in urine, and it is highly specific for urinary tract infection. However, due to its low sensitivity, a negative result does not rule out infection. [14]

• Normal: Negative
• Associations: Diabetes mellitus, Cushing syndrome, Fanconi syndrome, glucose infusion, pregnancy.
• Glucosuria with normal plasma glucose without other features of Fanconi syndrome is due to a benign condition referred to as renal glycosuria and is due to a mutation in the sodium-glucose linked transporter 2
• False-positive: Ketones, levodopa
• False-negative: Elevated specific gravity, uric acid, vitamin C [7] [11] [14] [15]

Bilirubin (conjugated)

• Normal: There is no bilirubin in normal urine 
• Associations: Liver dysfunction, biliary obstruction, congenital hyperbilirubinemia, viral or drug-induced hepatitis, cirrhosis
• False-positive: medications such as phenazopyridine that have a similar color at the low pH of the reagent pad
• False-negative: stale/old urine specimens, chlorpromazine, selenium [7] [11] [14] [15]

Urobilinogen

• The degradation product of bilirubin metabolism from bacteria in the intestine
• Normal: 0.1 mg/dL to 1 mg/dL in random samples or up to 4 mg/daily
• Elevation: Hemolysis, liver disease (cirrhosis, hepatitis), sickle cell disease, thalassemia
• Decrease: Antibiotic use, bile duct obstruction
• False-positive: Elevated nitrite levels, phenazopyridine, porphobilinogen, sulfonamides, and aminosalicylic acid
• False-negative: Prolonged exposition to daylight, formaldehyde, high levels of nitrites [7] [11] [14] [15]

Ketone Bodies

• Products of body fat metabolism
• Normal: Negative
• Associations: Uncontrolled diabetes mellitus (diabetic ketoacidosis), pregnancy, carbohydrate-free diets, starvation, febrile illness.
• False-positive: Acid urine, elevated specific gravity, mesna, phenolphthalein, some drug metabolites (e.g., levodopa, captopril)
• False-negative: Stale/old urine specimens.
• Remember : Reagent strips do not detect beta-hydroxy-butyric acid, only acetoacetic acid and acetone [7] [11] [14] [15]
• Products originating from the reduction of urinary nitrates
• Associations: Urinary tract infection (UTI) from a nitrate reductase-positive bacteria ( E. coli, Proteus, Enterobacter, Klebsiella, Streptococcus faecalis and Staphylococcus aureus )
• False-positive: Contamination, exposure of dipstick to air, pigmented materials, phenazopyridine
• False-negative: elevated specific gravity, elevated urobilinogen levels, nitrate reductase-negative bacteria, acid urine, vitamin C, urine with less than 4 hours of bladder resting, absent dietary nitrates
• Remember : A negative result does not rule out UTI [7] [11] [14] [15]

Leukocyte Esterase

• An enzyme present in certain WBCs (except lymphocytes)
• Associations: Inflammation of the urinary tract, sterile pyuria (balanitis, urethritis, tuberculosis, bladder tumors, nephrolithiasis, foreign bodies, exercise, glomerulonephritis, corticosteroids, and cyclophosphamide), fever, glomerulonephritis, pelvic inflammation
• False-positive: Contamination, highly pigmented urine, strong oxidizing agents, Trichomonas
• False-negative: Elevated specific gravity, glycosuria, ketonuria, proteinuria, some oxidizing drugs (cephalexin, nitrofurantoin, tetracycline, gentamicin), vitamin C [7] [14] [15]

Microscopic examination

Casts are a coagulum composed of the trapped contents of tubule lumen and Tamm-Horsfall mucoprotein. They originate in the lumen the distal convoluted tubule or collecting duct with pH alterations or long periods of urinary concentration or stasis. The casts preserve the cylindrical shape of the tubule in which they were formed. Only a few hyaline or finely granular casts may be seen under normal physiological conditions. Cellular casts can dissolve within 30 to 10 minutes depending on the pH of the urine sample, thus promptly testing is mandatory for appropriate testing. 

• Normal: Absent
• Associations: Glomerulonephritis, vasculitis, intrinsic renal disease (tubulointerstitial nephritis, acute tubular injury/necrosis), strenuous exercise (see image attached) [7] [14] [15]
• Associations: Pyelonephritis, interstitial nephritis, glomerulonephritis, renal inflammatory processes (see image attached) [7] [14] [15]
• Normal: Absent
• Associations: Acute tubular injury/necrosis, interstitial nephritis, glomerulonephritis, eclampsia, nephritic syndrome, transplant rejection, heavy metal ingestion, renal disease [7] [14] [15]
• Associations: Glomerular or tubular disease, pyelonephritis, advanced renal disease, viral infections, stress/exercise, non-specific [7] [14] [15]
• Associations: Advanced renal failure (dilated tubules with decreased flow) [7] [14] [15]
• Normal: Up to 5 casts/low-power field
• Associations: Normal finding in concentrated urine, fever, exercise, diuretics, pyelonephritis, chronic renal disease [7] [14] [15]
• Associations: Heavy proteinuria (nephrotic syndrome), renal disease, hypothyroidism, acute tubular necrosis, diabetes mellitus, severe crush injuries [7] [14] [15]
• Normal: 0-5 cells/high-power field
• Associations: UTI, inflammation [7] [14] [15]
• Associations: Interstitial nephritis, acute tubular necrosis, UTI, kidney transplant rejection, hepatorenal syndrome [7] [14] [15]
• Squamous, transitional, or renal tubular cells 
• Type of cell encountered depends on the location of the disease process
• Normal: Less than or equal to 15-20 squamous epithelial cells/high-power field
• Squamous (most common): Contamination
• Transitional: Normal, UTI
• Renal Tubular: Heavy metal poisoning, drug-induced toxicity, viral infections, pyelonephritis, malignancy, acute tubular necrosis [7] [14] [15]
• Associations: UTI, contamination [7] [14] [15]

End products of metabolism are found highly concentrated in the urine and can precipitate in the form of crystals. The presence of crystals is not necessarily associated with pathological states, although several types of crystals are associated with certain diseases. For example, cholesterol crystals are seen in polycystic renal disease and nephrotic syndrome and polycystic renal disease; leucine and tyrosine crystals are associated with severe liver disease. [7] [14]

• Yellow to orange-brown, diamond- or barrel-shaped crystals
• Associations: Acid urine, hyperuricosuria, uric acid nephropathy, normal (see image attached) [7] [14]
• Most commonly encountered crystal in human urine
• Refractile square "envelope" shape
• Associations: Ethylene glycol poisoning, acid urine, hyperoxaluria, normal (see image attached) [7] [14]
• Associations: Alkaline urine, decreased urine volume, a diet rich in calcium, prolonged immobilization, overactive parathyroid glands, bone metastases, normal [7] [14]
• "Coffin lid" appearance crystals
• Associations: Alkaline urine, decreased urine volume, UTI from urease-producing bacteria ( Proteus, Klebsiella ) [7] [14]
• Colorless crystals with a hexagonal shape
• Associations: Cystinuria [7] [14]
• Associations: Antibiotics containing sulfa [7] [14]
• Clinical Significance

Urinalysis is an ancient diagnostic screening test that has stood the test of time and is still useful in clinical laboratories since it plays a critical role in the health assessment process. [11] [13]  For some, a urinalysis is considered as the most common, simple, and relevant screening exam that provides clinicians with valuable information about the general health status of a patient, including hydration, urinary tract infection, diabetes mellitus, and liver or renal disease. [8]

• Quality Control and Lab Safety

Multiple reagent strips and tablets are used for several semiquantitative and qualitative tests, which allow the analysis of diverse parameters such as glucose, albumin, specific gravity, hydrogen ions, electrolytes, leukocytes, leukocyte esterase, nitrite, ketones, blood, bilirubin, urobilinogen, and heme. Most reagent strips are narrow bands of plastic 4 mm to 6 mm wide and 11 cm to 12 cm long with a series of absorbent pads. Each pad contains reagents for different reactions, so various tests can be carried out simultaneously. The reagent strip method comprises multiple complex chemical reactions. A color change on the pad demonstrates a reaction which can be compared to a color chart provided by the manufacturer for result interpretation. When using this method, it is essential to test the urine promptly, understand the advantages and limitations of each test, and establish controls. [7]

Reagent strips are designed to react progressively, modifying color for positive reactions along the strip at specific periods. The fundamental principle corresponds to read the strip at the specified time from the manufacturer to obtain accurate results. These times are established on the label of the bottle containing the particular strip. Furthermore, the reagent trips should never be stored in alternative containers because they have a relatively short shelf life. Expired strips may produce inaccurate results, the expiration date is also located on the bottle. [11]

Additionally, some computerized urine analyzers are available for reading reagent strips. They show the analysis on a small screen and print them out to include in the patient’s records. These analyzers comprise greater accuracy, convenience, simplicity, and time savings. However, they may not be able at many facilities due to financial limits. [11]

• Enhancing Healthcare Team Outcomes

A urinalysis is a valuable test commonly used in clinical practice. Depending on the technique and hospital, most samples are usually collected by nurses or phlebotomists who must determine whether or not the specimen meets the minimum requirements for proper analysis. They should be familiar with each method of collection and educate patients for appropriate sampling in the outpatient setting. In addition, as many conditions may alter the sample analysis (food, drugs, exercise, intercourse, room temperature, daylight, etc.), adequate recording and communication between the interprofessional team ensure discarding possible false-positive or false-negative results. Accurate collections provide key information for screening multiple systemic diseases and monitor treatment progress.

Finally, careful consideration of current guidelines must be done at all times. For example, the American Academy of Pediatrics no longer recommends performing routine screening urinalysis for asymptomatic children and adolescents. [18]  However, in adults, it is an excellent cost-effective screening test in primary care to screen for certain diseases.

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Triple Phosphate Crystals, Urine Contributed by RWTH Aachen (CC by 2.0) https://creativecommons.org/licenses/by/2.0/

Uric acid Crystals in Urine Contributed by Iqbal Osman (CC by 2.0) https://creativecommons.org/licenses/by/2.0/

Example of red cell cast. Contributed by Rian Kabir, MD

White Blood Cell Cast Contributed by Bharat Sachdeva MD

Disclosure: Daniel Queremel Milani declares no relevant financial relationships with ineligible companies.

Disclosure: Ishwarlal Jialal declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Queremel Milani DA, Jialal I. Urinalysis. [Updated 2023 May 1]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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NICHD Urinary Tract Health Research Information

NICHD is one of several NIH institutes that conduct and support research to advance understanding of urinary tract health in women, men, children, and those with disabilities. The institute also works with the National Institute of Diabetes and Digestive and Kidney Diseases, other NIH institutes, and other agencies and organizations to study different aspects of urinary tract health, including UTIs and UI, among specific populations.

NICHD Research Goals

The NICHD’s research goals for urinary tract health are part of its overall mission to advance affordable health and quality of life maintenance for men, women, and children. The research conducted and supported by the NICHD focuses on the diagnosis and prevention of urinary tract problems.

Specifically, the institute promotes research to advance understanding, focusing on the following areas:

• Examining factors that contribute to the development of UI, including labor and delivery
• Evaluating the impact of obesity on UTIs
• Managing UTIs in vulnerable populations, including pregnant women, individuals with disabilities or neurological conditions, and children with  Turner syndrome
• Assessing new treatments for UI
• Evaluating prevention methods to maintain and improve urinary tract health

Research Activities and Advances

Through its intramural and extramural organizational units, the NICHD supports and conducts research on urinary tract health. Short descriptions of this research appear below.

Institute Activities and Advances

Other activities and advances.

The NICHD's research efforts focus on the diagnosis and prevention of urinary tract infections (UTIs) and urinary incontinence (UI).

The Gynecologic Health and Disease Branch (GHDB) funds research on pelvic floor disorders (PFDs). These occur when the muscles and connective tissues of the pelvic area weaken or are injured and include UI. Branch research on UI is:

• Evaluating the effectiveness of a new treatment for urge UI, myofascial physical therapy, which aims to release tension in muscle tissue. Myofascial therapy is commonly used to relieve soft tissue restrictions that cause pain.
• Investigating how incontinence develops after vaginal delivery to develop and test treatments and prevention methods for stress UI
• Determining the potential of stem cell therapy to increase elastin content of lower urinary tract tissues, which could facilitate recovery after vaginal delivery and prevent UI

Researchers also are examining the impact of obesity on UTIs. They have found that elevated body mass index (BMI) increases the risk for UTI and pyelonephritis, a kidney infection caused by bacteria traveling to the kidney from the bladder. Their results can help guide weight loss treatment to prevent UTIs, but more studies are needed to determine a causal relationship between obesity and UTI. (Source: Semins, M. J., Shore, A. D, Makary, M. A, Weiner, J., Matlaga, B. R.(2012). The impact of obesity on urinary tract infection risk. Urology , 79: 266-–269. PMID: 22130358 )

In addition, the Section on Epigenetics and Development, part of the Division of Intramural Research (DIR) , conducts research that includes the study of girls and women with Turner Syndrome (TS) , a condition in which a female is partially or completely missing an X chromosome. Congenital malformations of the urinary tract are found in up to 30% of patients with TS. Many of these abnormalities are not clinically significant, but some may result in increased risk of UTIs.

The NICHD participated in a consensus workshop to develop recommendations for diagnosing and managing TS. The resulting recommendations of an independent panel of experts called for patients to be evaluated for renal abnormalities after receiving a TS diagnosis. Women found to have such abnormalities should then receive a renal ultrasound study and urine culture every 3 to 5 years. They may also need to be screened for UTIs more often. (Source: Saenger, P., Wikland, K. A., Conway, G. S., Davenport, M., Gravholt, C. H., Hintz, R., et al. (2001). Recommendations for the diagnosis and management of Turner syndrome. Journal of Clinical Endocrinology & Metabolism, 86: 3061–3069. PMID: 11443168 )

NICHD’s National Center for Medical Rehabilitation Research is studying individuals with neurogenic bladder after spinal cord injuries (SCI) and recurrent UTIs in these patients. In one SMAD Program-supported project, researchers seeded the bladder with benign bacteria ( Escherichia coli HU2117) to out-compete pathogenic strains and prevent their growth. Follow-up studies are ongoing, but preliminary results show that the E. coli safely reduces the risk of UTI in patients with SCI. (Source: Darouiche, R. O., et al. (2011). Multicenter randomized controlled trial of bacterial interference for prevention of urinary tract infection in patients with neurogenic bladder. Urology, Aug;78(2):341-6. PMID: 21683991 )

• The Ambulatory Treatments for Leakage Associated with Stress (ATLAS) study, a randomized controlled trial of nonsurgical treatment for stress urinary incontinence, provided information on the relative efficacy of (and satisfaction with) pessaries, training and exercise of the pelvic floor muscles, and the two treatments combined.
• The Colpopexy and Urinary Reduction Efforts (CARE) and Outcomes Following Vaginal Prolapse Repair and Mid Urethral Sling (OPUS) studies evaluated the addition of a procedure used to treat stress incontinence at the time of surgery for pelvic organ prolapse in women without symptoms of stress incontinence. The studies found that the procedure helped prevent stress incontinence after surgery.
• The Anticholinergic vs.Botox Comparison Study (ABC) was a double-blind, double-placebo-controlled randomized trial that provided much-need data comparing these two commonly prescribed treatments for urgency urinary incontinence. The trial found that the medications equally reduced the frequency of daily urinary incontinence but had different side effect profiles. A journal article describing these findings can be found at: https://pubmed.ncbi.nlm.nih.gov/23036134/ (In January, 2013, the FDA expanded the approved use of Botox to include adults who do not respond to anticholinergics for overactive bladder. News release: https://wayback.archive-it.org/7993/20170112032338/http:/www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm336101.htm )
• In 2010, the NICHD sponsored the 2-day workshop on Pregnancy in Women with Disabilities to review the current body of evidence on the management of pregnancy in women with physical disabilities. The Workshop identified key gaps in knowledge and recommendations for priority avenues for future research and included a discussion of UTIs as a common complication of such pregnancies. For example, according to scientists who took part in the workshop, 46% of women with spinal cord injuries develop UTIs during pregnancy. Broad-spectrum antibiotics appear to provide effective treatment, but some questions about prevention techniques remain unresolved. A journal article that resulted from the workshop is available at https://pubmed.ncbi.nlm.nih.gov/21422868/ .
• Evidence about the treatment of UTIs in preterm and low birth weight infants was also evaluated as part of a 2010 Cochrane Review supported by the NICHD. The study specifically examined treatments to compensate for the underdeveloped immune systems of preterm infants and low birth weight infants as a way to prevent infection.

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