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Luo, H. ; Bauer, A. ; Nano, J. ; Petrera, A. ; Rathmann, W.* ; Herder, C.* ; Hauck, S.M. ; Sun, B.B.* ; Hoyer, A.* ; Peters, A. ; Thorand, B.

Associations of plasma proteomics with type 2 diabetes and related traits: Results from the longitudinal KORA S4/F4/FF4 Study.

Diabetologia 66, 1655-1668 (2023)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
AIMS/HYPOTHESIS: This study aimed to elucidate the aetiological role of plasma proteins in glucose metabolism and type 2 diabetes development. METHODS: We measured 233 proteins at baseline in 1653 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort study (median follow-up time: 13.5 years). We used logistic regression in the cross-sectional analysis (n=1300), and Cox regression accounting for interval-censored data in the longitudinal analysis (n=1143). We further applied two-level growth models to investigate associations with repeatedly measured traits (fasting glucose, 2 h glucose, fasting insulin, HOMA-B, HOMA-IR, HbA1c), and two-sample Mendelian randomisation analysis to investigate causal associations. Moreover, we built prediction models using priority-Lasso on top of Framingham-Offspring Risk Score components and evaluated the prediction accuracy through AUC. RESULTS: We identified 14, 24 and four proteins associated with prevalent prediabetes (i.e. impaired glucose tolerance and/or impaired fasting glucose), prevalent newly diagnosed type 2 diabetes and incident type 2 diabetes, respectively (28 overlapping proteins). Of these, IL-17D, IL-18 receptor 1, carbonic anhydrase-5A, IL-1 receptor type 2 (IL-1RT2) and matrix extracellular phosphoglycoprotein were novel candidates. IGF binding protein 2 (IGFBP2), lipoprotein lipase (LPL) and paraoxonase 3 (PON3) were inversely associated while fibroblast growth factor 21 was positively associated with incident type 2 diabetes. LPL was longitudinally linked with change in glucose-related traits, while IGFBP2 and PON3 were linked with changes in both insulin- and glucose-related traits. Mendelian randomisation analysis suggested causal effects of LPL on type 2 diabetes and fasting insulin. The simultaneous addition of 12 priority-Lasso-selected biomarkers (IGFBP2, IL-18, IL-17D, complement component C1q receptor, V-set and immunoglobulin domain-containing protein 2, IL-1RT2, LPL, CUB domain-containing protein 1, vascular endothelial growth factor D, PON3, C-C motif chemokine 4 and tartrate-resistant acid phosphatase type 5) significantly improved the predictive performance (ΔAUC 0.0219; 95% CI 0.0052, 0.0624). CONCLUSIONS/INTERPRETATION: We identified new candidates involved in the development of derangements in glucose metabolism and type 2 diabetes and confirmed previously reported proteins. Our findings underscore the importance of proteins in the pathogenesis of type 2 diabetes and the identified putative proteins can function as potential pharmacological targets for diabetes treatment and prevention.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Cohort Study ; Mendelian Randomisation ; Proteomics ; Traits Of Glucose And Insulin ; Type 2 Diabetes; Insulin Sensitivity; Biomarkers; Monica/kora; Population; Metabolism; Prediction; Mellitus; Improves; Risk; Bone
ISSN (print) / ISBN 0012-186X
e-ISSN 1432-0428
Zeitschrift Diabetologia
Quellenangaben Band: 66, Heft: 9, Seiten: 1655-1668 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin ; Heidelberg [u.a.]
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Förderungen Helmholtz Zentrum Munchen - German Research Center for Environmental Health
German Federal Ministry of Education and Research (BMBF)
State of Bavaria
Helmholtz Institute for Metabolic, Obesity and Vascular Research - Project Initiative 2018 (HI-MAG)
German Federal Ministry of Health (Berlin, Germany)
Ministry of Culture and Science of the state North Rhine-Westphalia (Dusseldorf, Germany)
German Federal Ministry of Education and Research (BMBF) through the German Center for Diabetes Research (DZD e.V.)
Alnylam Pharmaceuticals
Amgen
China Scholarship Council
Biogen
Bristol-Myers Squibb
Calico
Genentech
Glaxo Smith Klein
Janssen Pharmaceuticals
Novo Nordisk
Pfizer
Regeneron
Takeda
AstraZeneca