Context: Hypothesis-free approaches such as proteomic analysis may identify novel biomarkers for disease. Objective: The objective of the study was to compare the plasma proteome of patients presenting with the polycystic ovary syndrome (PCOS) with that of women without hyperandrogenism. Design: This was a case-control study. Settings: The study was conducted at an academic hospital. Patients: Patients included 12 PCOS patients and 12 women without hyperandrogenism. Interventions: Interventions included basal blood sampling. Main Outcome Measures: Two-dimensional difference in-gel electrophoresis, matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry, Western blot, and ELISA analyses were measured. Results: Two-dimensional difference in-gel electrophoresis and matrix-assisted laser desorption/ ionization-time-of-flight mass spectrometry analyses identified haptoglobin β-chain and α2-macroglobulin as proteins underexpressed in PCOS samples, whereas transferrin and κ-free light chain were overexpressed. We were able to confirm only the underexpression of haptoglobin β-chain in subsequent Western blot and ELISA analyses. Conclusions: Proteomic analysis of plasma from PCOS patients revealed changes in protein expression in several acute-phase response proteins including isoforms of plasma haptoglobin, α2-macroglobulin, and transferrin and in κ-free light chain. In addition to their role as inflammatory markers, some of these molecules play major roles in iron metabolism, further suggesting that iron metabolism and low-grade chronic inflammation may be involved in the pathogenesis of insulin-resistant disorders such as PCOS. Copyright © 2010 by The Endocrine Society.
CITATION STYLE
Insenser, M., Martínez-García, M. Á., Montes, R., San-Millán, J. L., & Escobar-Morreale, H. F. (2010). Proteomic analysis of plasma in the polycystic ovary syndrome identifies novel markers involved in iron metabolism, acute-phase response, and inflammation. Journal of Clinical Endocrinology and Metabolism, 95(8), 3863–3870. https://doi.org/10.1210/jc.2010-0220
Mendeley helps you to discover research relevant for your work.