Deciphering the Plasma Proteome of Type 2 Diabetes.
Mohamed A ElhadadChristian JonassonCornelia HuthRory WilsonChristian GiegerPamela MatiasHarald GrallertJohannes GraumannValerie Gailus-DurnerWolfgang RathmannChristine von ToerneStefanie M HauckWolfgang KoenigMoritz F SinnerTudor I OpreaKarsten SuhreBarbara ThorandKristian HveemAnnette PetersMelanie WaldenbergerPublished in: Diabetes (2020)
With an estimated prevalence of 463 million affected, type 2 diabetes represents a major challenge to health care systems worldwide. Analyzing the plasma proteomes of individuals with type 2 diabetes may illuminate hitherto unknown functional mechanisms underlying disease pathology. We assessed the associations between type 2 diabetes and >1,000 plasma proteins in the Cooperative Health Research in the Region of Augsburg (KORA) F4 cohort (n = 993, 110 cases), with subsequent replication in the third wave of the Nord-Trøndelag Health Study (HUNT3) cohort (n = 940, 149 cases). We computed logistic regression models adjusted for age, sex, BMI, smoking status, and hypertension. Additionally, we investigated associations with incident type 2 diabetes and performed two-sample bidirectional Mendelian randomization (MR) analysis to prioritize our results. Association analysis of prevalent type 2 diabetes revealed 24 replicated proteins, of which 8 are novel. Proteins showing association with incident type 2 diabetes were aminoacylase-1, growth hormone receptor, and insulin-like growth factor-binding protein 2. Aminoacylase-1 was associated with both prevalent and incident type 2 diabetes. MR analysis yielded nominally significant causal effects of type 2 diabetes on cathepsin Z and rennin, both known to have roles in the pathophysiological pathways of cardiovascular disease, and of sex hormone-binding globulin on type 2 diabetes. In conclusion, our high-throughput proteomics study replicated previously reported type 2 diabetes-protein associations and identified new candidate proteins possibly involved in the pathogenesis of type 2 diabetes.
Keyphrases
- type diabetes
- cardiovascular disease
- glycemic control
- healthcare
- insulin resistance
- high throughput
- blood pressure
- mental health
- public health
- magnetic resonance imaging
- metabolic syndrome
- computed tomography
- risk assessment
- climate change
- adipose tissue
- mass spectrometry
- weight gain
- health information
- growth hormone
- high speed