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Protein markers and risk of type 2 diabetes and prediabetes: A targeted proteomics approach in the KORA F4/FF4 study.

Eur. J. Epidemiol. 34, 409-422 (2019)
DOI PMC
Postprint online available 01/2020 Open Access Green as soon as is submitted to ZB.
The objective of the present study was to identify proteins that contribute to pathophysiology and allow prediction of incident type 2 diabetes or incident prediabetes. We quantified 14 candidate proteins using targeted mass spectrometry in plasma samples of the prospective, population-based German KORA F4/FF4 study (6.5-year follow-up). 892 participants aged 42-81years were selected using a case-cohort design, including 123 persons with incident type 2 diabetes and 255 persons with incident WHO-defined prediabetes. Prospective associations between protein levels and diabetes, prediabetes as well as continuous fasting and 2h glucose, fasting insulin and insulin resistance were investigated using regression models adjusted for established risk factors. The best predictive panel of proteins on top of a non-invasive risk factor model or on top of HbA1c, age, and sex was selected. Mannan-binding lectin serine peptidase (MASP) levels were positively associated with both incident type 2 diabetes and prediabetes. Adiponectin was inversely associated with incident type 2 diabetes. MASP, adiponectin, apolipoprotein A-IV, apolipoprotein C-II, C-reactive protein, and glycosylphosphatidylinositol specific phospholipase D1 were associated with individual continuous outcomes. The combination of MASP, apolipoprotein E (apoE) and adiponectin improved diabetes prediction on top of both reference models, while prediabetes prediction was improved by MASP plus CRP on top of the HbA1c model. In conclusion, our mass spectrometric approach revealed a novel association of MASP with incident type 2 diabetes and incident prediabetes. In combination, MASP, adiponectin and apoE improved type 2 diabetes prediction beyond non-invasive risk factors or HbA1c, age and sex.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Type 2 Diabetes ; Prediabetes ; Population-based ; Biomarker ; Proteomics ; Prediction; Mannan-binding Lectin; Pattern-recognition Molecules; Serum-levels; Biomarkers; Complement; Prediction; Adiponectin; Lipoprotein; Metabolism; Masp-1
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