American Diabetes Association
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Proteomic predictors of incident diabetes: Results from the Atherosclerosis Risk in Communities (ARIC) Study

Version 2 2023-01-27, 19:23
Version 1 2023-01-27, 18:24
posted on 2023-01-27, 19:23 authored by Mary R. Rooney, Jingsha Chen, Justin B. Echouffo-Tcheugui, Keenan A. Walker, Pascal Schlosser, Aditya Surapaneni, Olive Tang, Jinyu Chen, Christie M. Ballantyne, Eric Boerwinkle, Chiadi E. Ndumele, Ryan T. Demmer, James S. Pankow, Pamela L. Lutsey, Lynne Wagenknecht, Yujian Liang, Xueling Sim, Rob van Dam, E Shyong Tai, Morgan E. Grams, Elizabeth Selvin, Josef Coresh


Introduction: The plasma proteome preceding diabetes can improve our understanding of diabetes pathogenesis.

Methods: In 8,923 Atherosclerosis Risk in Communities (ARIC) Study participants (aged 47-70 years, 55% women, 20% Black), we conducted discovery and internal validation for associations of 4,955 plasma proteins with incident diabetes. We externally validated results in the Singapore Multiethnic Cohort (MEC) nested case-control (624 cases, 1,214 controls). 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). Forty-seven of the 63 (75%) available proteins were validated in MEC. Twenty-two of the 47 proteins had novel associations with diabetes. Prediction models (27 proteins selected by elastic net) developed in discovery had a C-statistic of 0.731 in internal validation with ∆C-statistic=0.011 (p=0.04) beyond 13 risk factors including fasting glucose and HbA1c. Inflammation and lipid metabolism pathways were over-represented 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 three proteins, and identified diabetes-associated inflammation and lipid pathways with potential implications for diagnosis and therapy.  


The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services (contract numbers 75N92022D00001, 75N92022D00002, 75N92022D00003, 75N92022D00004, 75N92022D00005), R01HL087641, R01HL086694; National Human Genome Research Institute contract U01HG004402; and NIH contract HHSN268200625226C. Dr. Echouffo Tcheugui was supported by NIH/NHLBI grant K23 HL153774. Dr. Selvin was supported by NIH/NHLBI grant K24 HL152440 and NIH/NIDDK grant R01 DK089174. Dr. Tang is funded by NIH/NHLBI T32 HL007024. Dr. Grams was supported by NIH/NHLBI K24 HL155861. This research was also supported by NIH/NIDDK R01 DK124399. The Singapore Multi-Ethnic Cohort (MEC) study is supported by individual research and clinical scientist award schemes from the Singapore National Medical Research Council (NMRC, including MOH-000271-00) and the Singapore Biomedical Research Council (BMRC), the Singapore Ministry of Health (MOH), the National University of Singapore (NUS) and the Singapore National University Health System (NUHS). We thank all ARIC Study and MEC participants, study team and investigators for their contributions to research. Dr. Rooney takes full responsibility for the work as a whole, including the study design, access to data, and the decision to submit and publish the manuscript.


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