The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Proteomic analysis for the assessment of diabetic renal damage in humans
Abstract
Renal disease in patients with Type II diabetes is the leading cause of terminal renal failure and a major healthcare problem. Hence early identification of patients prone to develop this complication is important. Diabetic renal damage should be reflected by a change in urinary polypeptide excretion at a very early stage. To analyse these changes, we used an online combination of CE/MS (capillary electrophoresis coupled with MS), allowing fast and accurate evaluation of up to 2000 polypeptides in urine. Employing this technology, we have examined urine samples from 39 healthy individuals and from 112 patients with Type II diabetes mellitus and different degrees of albumin excretion rate. We established a ‘normal’ polypeptide pattern in the urine of healthy subjects. In patients with Type II diabetes and normal albumin excretion rate, the polypeptide pattern in urine differed significantly from normal, indicating a specific ‘diabetic’ pattern of polypeptide excretion. In patients with higher grade albuminuria, we were able to detect a polypeptide pattern indicative of ‘diabetic renal damage’. We also found this pattern in 35% of those patients who had low-grade albuminuria and in 4% of patients with normal albumin excretion. Moreover, we could identify several of the indicative polypeptides using MS/MS sequencing. We conclude that proteomic analysis with CE/MS permits fast and accurate identification and differentiation of polypeptide patterns in urine. Longitudinal studies should explore the potential of this powerful diagnostic tool for early detection of diabetic renal damage.
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Brenner, B. M., Cooper, M. E., de Zeeuw, D., Keane, W. F., Mitch, W. E., Parving, H.-H., Remuzzi, G., Snapinn, S. M., Zhang, Z., & Shahinfar, S. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa011161 · Cited by 7,493
Lewis, E. J., Hunsicker, L. G., Clarke, W. R., Berl, T., Pohl, M. A., Lewis, J. B., Ritz, E., Atkins, R. C., Rohde, R., & Raz, I. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa011303 · Cited by 5,987
Use of proteomic patterns in serum to identify ovarian cancer
Petricoin, E. F., Ardekani, A. M., Hitt, B. A., Levine, P. J., Fusaro, V. A., Steinberg, S. M., Mills, G. B., Simone, C., Fishman, D. A., Kohn, E. C., et al. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07746-2 · Cited by 3,236
The effect of irbesartan on the development of diabetic nephropathy in patients with type 2 diabetes
Parving, H.-H., Lehnert, H., Bröchner-Mortensen, J., Gomis, R., Andersen, S., & Arner, P. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa011489 · Cited by 2,873
Thongboonkerd, V., Mcleish, K. R., Arthur, J. M., & Klein, J. B. (2002) · Kidney International · doi:10.1111/j.1523-1755.2002.kid565.x · Cited by 359
Cited by
Advances in Urinary Proteome Analysis and Biomarker Discovery
Fliser, D., Novak, J., Thongboonkerd, V., Argile[Combining Acute Accent]s, A. G. A., Jankowski, V., Girolami, M. A., Jankowski, J., & Mischak, H. (2007) · Journal of the American Society of Nephrology · doi:10.1681/asn.2006090956 · Cited by 286
Self-citationQuantitative Urinary Proteome Analysis for Biomarker Evaluation in Chronic Kidney Disease
Jantos-Siwy, J., Schiffer, E., Brand, K., Schumann, G., Rossing, K., Delles, C., Mischak, H., & Metzger, J. (2009) · Journal of Proteome Research · doi:10.1021/pr800401m · Cited by 259
Self-citationMischak, H., Coon, J. J., Novak, J., Weissinger, E. M., Schanstra, J. P., & Dominiczak, A. F. (2009) · Mass Spectrometry Reviews · doi:10.1002/mas.20205 · Cited by 193
Self-citationCapillary electrophoresis–mass spectrometry for the analysis of intact proteins
Haselberg, R., de Jong, G. J., & Somsen, G. W. (2007) · Journal of Chromatography A · doi:10.1016/j.chroma.2007.05.048 · Cited by 185
Mapping of molecular pathways, biomarkers and drug targets for diabetic nephropathy
Fechete, R., Heinzel, A., Perco, P., Mönks, K., Söllner, J., Stelzer, G., Eder, S., Lancet, D., Oberbauer, R., Mayer, G., et al. (2011) · PROTEOMICS – Clinical Applications · doi:10.1002/prca.201000136 · Cited by 45
Metadata
- Authors
- MISCHAK, H., KAISER, T., WALDEN, M., HILLMANN, M., WITTKE, S., HERRMANN, A., KNUEPPEL, S., HALLER, H., & FLISER, D.
- Venue
- Clinical Science
- Publisher
- Portland Press Ltd.
- Published
- 2004-10-26
- Volume
- 107
- Issue
- 5
- Pages
- 485-495
- ISSN
- 0143-5221 (ISSN-L)
- 1470-8736
- OpenAlex
- W2054801022
- Cited by
- 176
- References
- 5
- FWCI
- 12.45
- Type
- journal article
- Language
- en
- Open access
- closed
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- MISCHAK, H., KAISER, T., WALDEN, M., HILLMANN, M., WITTKE, S., HERRMANN, A., KNUEPPEL, S., HALLER, H., & FLISER, D. (2004). Proteomic analysis for the assessment of diabetic renal damage in humans. Clinical Science. https://doi.org/10.1042/cs20040103
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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