Language
English
Publication Date
4-1-2023
Journal
Diabetes Care
DOI
10.2337/dc22-1830
PMID
36706097
PMCID
PMC10090896
PubMedCentral® Posted Date
1-27-2023
PubMedCentral® Full Text Version
Post-print
Abstract
Objective: The plasma proteome preceding diabetes can improve our understanding of diabetes pathogenesis.
Research design and methods: In 8,923 Atherosclerosis Risk in Communities (ARIC) Study participants (aged 47-70 years, 57% women, 19% Black), we conducted discovery and internal validation for associations of 4,955 plasma proteins with incident diabetes. We externally validated results in the Singapore Multi-Ethnic Cohort (MEC) nested case-control (624 case subjects, 1,214 control subjects). We used Cox regression to discover and validate protein associations and risk-prediction models (elastic net regression with cardiometabolic risk factors and proteins) for incident diabetes. We conducted a pathway analysis and examined causality using genetic instruments.
Results: There were 2,147 new diabetes cases over a median of 19 years. In the discovery sample (n = 6,010), 140 proteins were associated with incident diabetes after adjustment for 11 risk factors (P < 10-5). Internal validation (n = 2,913) showed 64 of the 140 proteins remained significant (P < 0.05/140). Of the 63 available proteins, 47 (75%) were validated in MEC. Novel associations with diabetes were found for 22 the 47 proteins. Prediction models (27 proteins selected by elastic net) developed in discovery had a C statistic of 0.731 in internal validation, with ΔC statistic of 0.011 (P = 0.04) beyond 13 risk factors, including fasting glucose and HbA1c. Inflammation and lipid metabolism pathways were overrepresented among the diabetes-associated proteins. Genetic instrument analyses suggested plasma SHBG, ATP1B2, and GSTA1 play causal roles in diabetes risk.
Conclusions: We identified 47 plasma proteins predictive of incident diabetes, established causal effects for 3 proteins, and identified diabetes-associated inflammation and lipid pathways with potential implications for diagnosis and therapy.
Keywords
Humans, Female, Male, Proteomics, Diabetes Mellitus, Atherosclerosis, Risk Factors, Inflammation, Incidence
Published Open-Access
yes
Recommended Citation
Rooney, Mary R; Chen, Jingsha; Echouffo-Tcheugui, Justin B; et al., "Proteomic Predictors of Incident Diabetes: Results From the Atherosclerosis Risk in Communities (ARIC) Study" (2023). Faculty and Staff Publications. 4261.
https://digitalcommons.library.tmc.edu/baylor_docs/4261