In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms

Scientific Reports

Volumn 6, Issue , 2016, Pages

  Hao, Ling ^a   Greer, Tyler ^a   Page, David ^a   Shi, Yatao ^a   Vezina, Chad M ^a,b   Macoska, Jill A ^a,c   Marker, Paul C ^a   Bjorling, Dale E ^a,b   Bushman, Wade ^a   Ricke, William A ^a   Li, Lingjun ^a  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b UNIVERSITY OF WISCONSIN MADISON   (United States)

^c UNIVERSITY OF MASSACHUSETTS BOSTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID; BIOLOGICAL MARKER; COLLAGEN;

AREA UNDER THE CURVE; ELECTROSPRAY MASS SPECTROMETRY; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; HUMAN; LOWER URINARY TRACT SYMPTOM; MACHINE LEARNING; MALE; METABOLISM; METABOLOME; METABOLOMICS; PATHOLOGY; PROSTATE; QUALITY CONTROL; RECEIVER OPERATING CHARACTERISTIC; STANDARDS; URINE;

AMINO ACIDS; AREA UNDER CURVE; BIOMARKERS; CHROMATOGRAPHY, HIGH PRESSURE LIQUID; COLLAGEN; HUMANS; LOWER URINARY TRACT SYMPTOMS; MACHINE LEARNING; MALE; METABOLOME; METABOLOMICS; PROSTATE; QUALITY CONTROL; ROC CURVE; SPECTROMETRY, MASS, ELECTROSPRAY IONIZATION;

EID: 84981156500     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep30869     Document Type: Article

References (60)

1. Abrams, P. et al. The standardisation of terminology of lower urinary tract function: Report from the of the International Standardisation Sub-Committee Continence Society. Neurourol Urodynam 21, 167-178, doi: 10.1002/Nau.10052 (2002).
2. Chapple, C. R. & Roehrborn, C. G. A shifted paradigm for the further understanding, evaluation, and treatment of lower urinary tract symptoms in men: Focus on the bladder. Eur Urol 49, 651-659, doi: 10.1016/j.eururo.2006.02.018 (2006).
3. Ma, J. J. et al. Prostatic Fibrosis is Associated with Lower Urinary Tract Symptoms. Journal Of Urology 188, 1375-1381, doi: 10.1016/j.juro.2012.06.007 (2012).
4. Lee, S., Yang, G. & Bushman, W. Prostatic Inflammation Induces Urinary Frequency in Adult Mice. Plos One 10, doi: UNSP e011682710.1371/journal.pone.0116827 (2015)
5. Rodriguez-Nieves, J. A. & Macoska, J. A. Prostatic fibrosis, lower urinary tract symptoms, and BPH. Nat Rev Urol 10, 546-550, doi: 10.1038/nrurol.2013.149 (2013).
6. OMalley, K. J. et al. The Expression of Androgen-Responsive Genes Is Up-Regulated in the Epithelia of Benign Prostatic Hyperplasia. Prostate 69, 1716-1723, doi: 10.1002/pros.21034 (2009).
7. OMalley, K. J. et al. Proteomic analysis of patient tissue reveals PSA protein in the stroma of benign prostatic hyperplasia. Prostate 74, 892-900, doi: 10.1002/pros.22807 (2014).
8. Juliao, A. A., Plata, M., Kazzazi, A., Bostanci, Y. & Djavan, B. American Urological Association and European Association of Urology guidelines in the management of benign prostatic hypertrophy: revisited. Curr Opin Urol 22, 34-39, doi: 10.1097/Mou.0b013e32834d8e87 (2012).
9. Nicholson, J. K. & Wilson, I. D. Understanding global systems biology: Metabonomics and the continuum of metabolism. Nat Rev Drug Discov 2, 668-676, doi: 10.1038/nrd1157 (2003).
10. Schmidt, C. Metabolomics takes its place as latest up-And-coming "omic" science. J Natl Cancer I 96, 732-734 (2004).
11. Patti, G. J., Yanes, O. & Siuzdak, G. Metabolomics: The apogee of the omics trilogy. Nat Rev Mol Cell Bio 13, 263-269, doi: 10.1038/nrm3314 (2012).
12. Nicholson, J. K. & Lindon, J. C. Systems biology-Metabonomics. Nature 455, 1054-1056, doi: 10.1038/4551054a (2008).
13. Mamas, M., Dunn, W. B., Neyses, L. & Goodacre, R. The role of metabolites and metabolomics in clinically applicable biomarkers of disease. Arch Toxicol 85, 5-17, doi: 10.1007/s00204-010-0609-6 (2011).
14. Nicholson, J. K. et al. Metabolic phenotyping in clinical and surgical environments. Nature 491, 384-392, doi: 10.1038/nature11708 (2012).
15. Kim, K. et al. Urine Metabolomic Analysis Identifies Potential Biomarkers and Pathogenic Pathways in Kidney Cancer. Omics-A Journal Of Integrative Biology 15, 293-303, doi: 10.1089/omi.2010.0094 (2011).
16. Peng, J., Chen, Y. T., Chen, C. L. & Li, L. Development of a Universal Metabolome-Standard Method for Long-Term LC-MS Metabolome Profiling and Its Application for Bladder Cancer Urine-Metabolite-Biomarker Discovery. Anal Chem 86, 6540-6547, doi: 10.1021/ac5011684 (2014).
17. Shaham, O. et al. Metabolic profiling of the human response to a glucose challenge reveals distinct axes of insulin sensitivity. Mol Syst Biol 4, doi: Artn 21410.1038/Msb.2008.50 (2008)
18. Swan, A. L., Mobasheri, A., Allaway, D., Liddell, S. & Bacardit, J. Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology. Omics 17, 595-610, doi: 10.1089/omi.2013.0017 (2013).
19. Nanni, L., Lumini, A. & Brahnam, S. Advanced machine learning techniques for microarray spot quality classification. Neural Comput Appl 19, 471-475, doi: 10.1007/s00521-010-0342-3 (2010).
20. Gaul, D. A. et al. Highly-Accurate metabolomic detection of early-stage ovarian cancer. Scientific reports 5, 16351, doi: 10.1038/srep16351 (2015).
21. Van, A. H. T., Saeys, Y., Wehenkel, L. & Geurts, P. Statistical interpretation of machine learning-based feature importance scores for biomarker discovery. Bioinformatics 28, 1766-1774, doi: 10.1093/bioinformatics/bts238 (2012).
22. Wale, N. Machine Learning in Drug Discovery and Development. Drug Develop Res 72, 112-119, doi: 10.1002/Ddr.20407 (2011).
23. Mahadevan, S., Shah, S. L., Marrie, T. J. & Slupsky, C. M. Analysis of metabolomic data using support vector machines. Anal Chem 80, 7562-7570, doi: 10.1021/ac800954c (2008).
24. Schilling, J. et al. Compartment Proteomics Analysis of White Perch (Morone americana) Ovary Using Support Vector Machines. J Proteome Res 13, 1515-1526, doi: 10.1021/Pr401067g (2014).
25. Hawkridge, A. M. & Muddiman, D. C. Mass Spectrometry-Based Biomarker Discovery: Toward a Global Proteome Index of Individuality. Annu Rev Anal Chem 2, 265-277, doi: 10.1146/annurev.anchem.1.031207.112942 (2009).
26. Smith, R. D. Mass Spectrometry in Biomarker Applications: From Untargeted Discovery to Targeted Verification, and Implications for Platform Convergence and Clinical Application. Clin Chem 58, 528-530, doi: 10.1373/clinchem.2011.180596 (2012).
27. Fu, Q. et al. An Empirical Approach to Signature Peptide Choice for Selected Reaction Monitoring: Quantification of Uromodulin in Urine. Clin Chem, doi: 10.1373/clinchem.2015.242495 (2015).
28. Rifai, N., Gillette, M. A. & Carr, S. A. Protein biomarker discovery and validation: The long and uncertain path to clinical utility. Nat Biotechnol 24, 971-983, doi: 10.1038/nbt1235 (2006).
29. Vapnik, V. The Support Vector method of function estimation. Nonlinear Modeling 55-85 (1998).
30. Nickel, J. C., Downey, J., Young, I. & Boag, S. Asymptomatic inflammation and/or infection in benign prostatic hyperplasia. Bju Int 84, 976-981 (1999).
31. Bauman, T. M. et al. Characterization of Fibrillar Collagens and Extracellular Matrix of Glandular Benign Prostatic Hyperplasia Nodules. Plos One 9, doi: ARTN e10910210.1371/journal.pone.0109102 (2014)
32. He, Q. et al. Metabolic syndrome, inflammation and lower urinary tract symptoms: possible translational links. Prostate Cancer P D 19, 7-13, doi: 10.1038/pcan.2015.43 (2016).
33. Finerman, G. A., Downing, S. & Rosenber, Le. Amino Acid Transport in Bone.2. Regulation of Collagen Synthesis by Perturbation of Proline Transport. Biochim Biophys Acta 135, 1008, doi: 10.1016/0005-2736(67)90071-5 (1967).
34. Bygd, H. C., Akilbekova, D., Munoz, A., Forsmark, K. D. & Bratlie, K. M. Poly-L-Arginine based materials as instructive substrates for fibroblast synthesis of collagen. Biomaterials 63, 47-57, doi: 10.1016/j.biomaterials.2015.05.045 (2015).
35. Barbul, A. Proline precursors to sustain mammalian collagen synthesis. J Nutr 138, 2021s-2024s (2008).
36. Grasemann, H., Schwiertz, R., Matthiesen, S., Racke, K. & Ratjen, F. Increased arginase activity in cystic fibrosis airways. Am J Resp Crit Care 172, 1523-1528, doi: 10.1164/rccm.200502-253OC (2005).
37. Coffino, P. Regulation of cellular polyamines by antizyme. Nat Rev Mol Cell Bio 2, 188-194, doi: 10.1038/35056508 (2001).
38. Dunzendorfer, U. & Russell, D. H. Altered Polyamine Profiles In Prostatic Hyperplasia And In Kidney Tumors. Cancer Res 38, 2321-2324 (1978).
39. Andersson, K. E. & Arner, A. Urinary bladder contraction and relaxation: Physiology and pathophysiology. Physiol Rev 84, 935-986, doi: 10.1152/physrev.00038.2003 (2004).
40. Esteller, M. Cancer epigenomics: DNA methylomes and histone-modification maps. Nat Rev Genet 8, 286-298, doi: 10.1038/Nrg2005 (2007).
41. Li, L. C., Carroll, P. R. & Dahiya, R. Epigenetic changes in prostate cancer: Implication for diagnosis and treatment. J Natl Cancer I 97, 103-115, doi: 10.1093/Jnci/Dji010 (2005).
42. Kim, J., Jia, L., Tilley, W. D. & Coetzee, G. A. Dynamic methylation of histone H3 at lysine 4 in transcriptional regulation by the androgen receptor. Nucleic Acids Res 31, 6741-6747, doi: 10.1093/Nar/Gkg909 (2003).
43. Frazier, E. P., Peters, S. L. M., Braverman, A. S., Ruggieri, M. R. & Michel, M. C. Signal transduction underlying the control of urinary bladder smooth muscle tone by muscarinic receptors and beta-Adrenoceptors. N-S Arch Pharmacol 377, 449-462, doi: 10.1007/s00210-007-0208-0 (2008).
44. Vishnevsky, E. L. et al. Role of the impairment of oxidative metabolism in pathogenesis of lower urinary tract symptoms with benign prostatic hyperplasia and their treatment by alpha(1)-Adrenoblocker alfuzosin. Mitochondrion 3, 67-73, doi: 10.1016/S1567-7249(03)00061-8 (2003).
45. Greer, T. et al. Custom 4-Plex DiLeu Isobaric Labels Enable Relative Quantification of Urinary Proteins in Men with Lower Urinary Tract Symptoms (LUTS). Plos One 10, doi: ARTN e013541510.1371/journal.pone.0135415 (2015)
46. Ganti, S. et al. Kidney Tumor Biomarkers Revealed by Simultaneous Multiple Matrix Metabolomics Analysis. Cancer Res 72, 3471-3479, doi: 10.1158/0008-5472.Can-11-3105 (2012).
47. Ganti, S. et al. Urinary acylcarnitines are altered in human kidney cancer. Int J Cancer 130, 2791-2800, doi: 10.1002/ijc.26274 (2012).
48. Elkahwaji, J. E., Zhong, W. X., Hopkins, W. J. & Bushman, W. Chronic bacterial infection and inflammation incite reactive hyperplasia in a mouse model of chronic prostatitis. Prostate 67, 14-21, doi: 10.1002/pros.20445 (2007).
49. Bjorling, D. E., Wang, Z. Y. & Bushman, W. Models of Inflammation of the Lower Urinary Tract. Neurourol Urodynam 30, 673-682, doi: 10.1002/nau.21078 (2011).
50. Ricke, W. A. et al. Prostatic hormonal carcinogenesis is mediated by in situ estrogen production and estrogen receptor alpha signaling. Faseb J 22, 1512-1520, doi: 10.1096/fj.07-9526com (2008).
51. Robinson, D., Staskin, D., Laterza, R. M. & Koelbl, H. Defining female voiding dysfunction: ICI-RS 2011. Neurourol Urodyn 31, 313-316, doi: 10.1002/nau.22213 (2012).
52. Stewart, W. F. et al. Prevalence and burden of overactive bladder in the United States. World J Urol 20, 327-336, doi: 10.1007/s00345-002-0301-4 (2003).
53. Milsom, I. Lower urinary tract symptoms in women. Curr Opin Urol 19, 337-341, doi: 10.1097/MOU.0b013e32832b659d (2009).
54. Dabney, A., Storey, J. D. & Warnes, G. qvalue: Q-value estimation for false discovery rate control. R package version 1 (2010).
55. Hall, M., Eibe Frank, Geoffrey, Holmes, Bernhard, Pfahringer, Peter, Reutemann & Ian H., Witten. The WEKA Data Mining Software: An Update. SIGKDD Explorations 11, 11 (2009).
56. Hunt, E. B., Marin, J. & Stone, P. J. Experiments in induction (Academic Press, 1966).
57. Zhou, B., Wang, J. L. & Ressom, H. W. MetaboSearch: Tool for Mass-Based Metabolite Identification Using Multiple Databases. Plos One 7, doi: ARTN e4009610.1371/journal.pone.0040096 (2012)
58. Wolf, S., Schmidt, S., Muller-Hannemann, M. & Neumann, S. In silico fragmentation for computer assisted identification of metabolite mass spectra. Bmc Bioinformatics 11, doi: Artn 148 10.1186/1471-2105-11-148 (2010).
59. Xia, J. G., Mandal, R., Sinelnikov, I. V., Broadhurst, D. & Wishart, D. S. MetaboAnalyst 2.0-A comprehensive server for metabolomic data analysis. Nucleic Acids Res 40, W127-W133, doi: 10.1093/Nar/Gks374 (2012).
60. Ogata, H. et al. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 27, 29-34, doi: 10.1093/nar/27.1.29 (1999).