Proteomic Predictors of Incident Diabetes: Results From the Atherosclerosis Risk in Communities (ARIC) Study

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.

Plasma proteins and onset of type 2 diabetes and diabetic complications: Proteome-wide Mendelian randomization and colocalization analyses

“…Our study corroborated some previously identified protein-diabetes associations, such as the associations of diabetes with TYRO3 (tyrosine-protein kinase receptor TYRO3), ARG1, SHBG, MANSC4, HP, MANBA, ABO, angiotensin-converting enzyme (ACE), ERO1-like protein beta (ERO1LB), MICB, and GSTA1. 8 , 14 The associations of some well-studied proteins, like GCKR, 5 SHBG, 16 ABO, 17 and ACE 18 with the risk of developing type 2 diabetes were also identified, which indicated a good validity of data sources used in the current analysis. However, except for ABO, ARG1, ERO1LB, GSTA1, and TYRO3, we observed weak colocalization support of the associations for other above-mentioned proteins, which implies that these associations may be influenced by linkage disequilibrium.…”

“… 7 Another study with a larger sample size identified 47 proteins associated with incident type 2 diabetes after 19 years of follow-up. 8 Still, merely three associations were confirmed by Mendelian randomization (MR) analysis. 8 These findings may convey that observational studies on proteomic research in type 2 diabetes are prone to be influenced by reverse causation, as well as confounding given that the factors influencing proteomic profiles remain unestablished.…”

“… 6 Because of the development of high-throughput detection and quantification of serum proteins, an increasing number of studies were also conducted to explore the associations of proteins with the risk of type 2 diabetes aiming at revealing molecular pathological basis. 7 , 8 A population-based study found 24 plasma proteins consistently associated with prevalent type 2 diabetes in discovery and replication studies; however, only 3 proteins were found to be associated with incident type 2 diabetes. 7 Another study with a larger sample size identified 47 proteins associated with incident type 2 diabetes after 19 years of follow-up.…”

Circulating proteomic profiles are associated with the onset of type 2 diabetes in a multi-ethnic Asian population — a longitudinal study

“…Among the 522 proteins identified in our study, 316 (60.64%) proteins were not previously reported to be associated with T2D risk (Supplementary Figure 6). We compared our findings to four published studies on proteomics and T2D incidence in European and African populations [12,13,15,16]. Of the 530 proteins that were significant at a Bonferroni threshold (approximately 1x10 -5 ) or had an FDR q-value less than 0.05 in at least one other study, 479 (90.38%) were present in our data.…”

“…Proteins, as products of gene transcription, function as dynamic biomarkers reflecting genetic regulation and environmental changes, which can aid in pinpointing the perturbed proteins and pathways in T2D pathogenesis [10]. Large-scale population proteomic studies on plasma proteins and complex diseases, including T2D, have become possible in recent years as high-throughput proteomic profiling technologies improve [11][12][13][14][15][16]. Using the genome, Mendelian randomization (MR) uses genetic variants to assess causality and has been used to integrate the genome and proteome to reveal causal proteins and potential T2D therapeutic targets [12,13,16,17].…”