Characteristics of age-dependent changes in urine proteome in healthy men
Tóm tắt
This paper studies the age dynamics of the proteomic profile of urine in healthy volunteers. The proteome composition was determined by chromatography-mass-spectrometry based on a nanostream highly efficient liquid chromatograph (Agilent 1100), and mass-spectra were obtained with a LTQ-FT hybrid mass-spectrometer. The urine samples obtained from 52 healthy men aged 19–54 years were found to contain 259 various proteins. According to the TiGER database, the tissue origin was established for 141 of them, and 715 biological processes in which they participate were identified. A significant positive correlation of the number (R = 0.566, p-value = 1.24E–05) and weight of proteins (R = 0.45; p-value = 8.17E–04) with age was found. We identified 23 proteins that are significantly more frequent in urine with increasing age of the subjects (p < 0.05) and only one protein, RGSL1, that is a regulator of signal transmission through receptors connected with G-protein (MW 125.69), which becomes less frequent with increasing age.
Tài liệu tham khảo
Valeeva, O.A., Pastushkova, L.K., Pakharukova, N.A., Dobrokhotov, I.V., and Larina, I.M., Variability of urine proteome in healthy humans during a 105-day isolation in a pressurized compartment, Hum. Physiol., 2011, vol. 37, no. 3, pp. 351–354.
Trizno, M.N., Asfandiyarov, F.R., and Kafarov, E.S., Changes of volumes of arteries and veins of cortical and medullar substances of a kidney during aging, Sarat. Med. Zh., 2009, vol. 5, no. 1, pp. 15–16.
Bakun, M., Senatorski, G., Rubel, T., et al., Urine proteomes of healthy aging humans reveal extracellular matrix (ECM) alterations and immune system dysfunction, Age (Dordrecht), 2014, vol. 36, no. 1, pp. 299–311.
Coon, J.J., Zurbig, P., Dakna, M., et al., CE-MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics, Proteomics Clin. Appl., 2008, vol. 2, nos. 7–8, pp. 964–973.
Duan, Z.H., Hughes, B., Reichel, L., et al., The relationship between protein sequences and their gene ontology functions, BMC Bioinf., 2006, vol. 12, no. 7, suppl. 4, p. 11.
Fulladosa, X., Moreso, F., Narváez, J.A., et al., Estimation of total glomerular number in stable renal transplants, J. Am. Soc. Nephrol., 2003, vol. 14, no. 10, pp. 2662–2668.
Glassock, R.J. and Rule, A.D., The implications of anatomical and functional changes of the aging kidney: with an emphasis on the glomeruli, Kidney Int., 2012, vol. 82, no. 3, pp. 270–277.
Guo, X., Liu, R., Shriver, C.D., et al., Assessing semantic similarity measures for the characterization of human regulatory pathways, Bioinformatics, 2006, vol. 22, no. 8, pp. 967–973.
Hoy, W.E., Douglas-Denton, R.N., Hughson, M.D., et al., A stereological study of glomerular number and volume: preliminary findings in a multiracial study of kidneys at autopsy, Kidney Int., 2003, vol. 83, suppl., pp. 31–37.
Ishihama, Y., Rappsilber, J., Andersen, J.S., and Mann, M., Microcolumns with self-assembled particle frits for proteomics, J. Chromatogr., 2002, vol. 979, pp. 233–239.
Lei, Z. and Dai, Y., Assessing protein similarity with Gene Ontology and its use in subnuclear localization prediction, BMC Bioinf., 2006, vol. 7, no. 7, p. 491.
Mancilla, E., Avila-Casado, C., Uribe-Uribe, N., et al., Timezero renal biopsy in living kidney transplantation: a valuable opportunity to correlate predonation clinical data with histological abnormalities, Transplantation, 2008, vol. 86, no. 12, pp. 1684–1688.
Nyengaard, J.R. and Bendtsen, T.F., Glomerular number and size in relation to age, kidney weight, and body surface in normal man, Anat. Rec., 1992, vol. 232, no. 2, pp. 194–201.
Oeseburg, H., De Boer, R.A., van Gilst, W.H., and van der Harst, P., Telomere biology in healthy aging and disease, Pflügers Arch., 2010, vol. 459, no. 2, pp. 259–268.
Pannarale, G., Carbone, R., Del Mastro, G., et al., The aging kidney: structural changes, J. Nephrol., 2010, vol. 23, suppl. 15, pp. 37–40.
Rule, A.D., Amer, H., Cornell, L.D., et al., The association between age and nephrosclerosis on renal biopsy among healthy adults, Ann. Int. Med., 2010, vol. 152, no. 9, pp. 561–567.
Soltow, Q.A., Jones, D.P., and Promislow, D.E., A network perspective on metabolism and aging, Integr. Comp. Biol., 2010, vol. 50, no. 5, pp. 844–854.
Thongboonkerd, V., Practical points in urinary proteomics, J. Proteome Res., 2007, vol. 6, no. 10, pp. 3881–3890.
Wu, X., Zhu, L., Guo, J., et al., Prediction of yeast protein- protein interaction network: insights from the Gene Ontology and annotations, Nucleic Acids Res., 2006, vol. 34, no. 7, pp. 2137–2150.
Zürbig, P., Decramer, S., Dakna, M., et al., The human urinary proteome reveals high similarity between kidney aging and chronic kidney disease, Proteomics, 2009, vol. 9, no. 8, pp. 2108–2117.