Proteomic Signatures of 3-Year Progression From Impaired Fasting Glucose to Diabetes: The Atherosclerosis Risk in Communities (ARIC) Study

OBJECTIVE: To identify proteomic signatures underlying 3-year progression from impaired fasting glucose (IFG) to diabetes. RESEARCH DESIGN AND METHODS: We examined IFG progression in the Atherosclerosis Risk in Communities (ARIC) study from visit 2 (1990-1992) to visit 3 (1993-1995). We tested associations of 4,955 plasma proteins (SomaScan version 4.0) with ∼3-year progression from IFG (FG 100-125 mg/dL without diabetes) to diabetes (diagnosis, medication, or FG ≥126 mg/dL) using logistic regression models adjusted for demographics, cardiometabolic risk factors, and baseline glucose with Bonferroni correction (P < 10-5). We explored biological pathways enriched among the top proteins and calculated improvements in prediction (ΔAUC and net reclassification using 3-year risk thresholds of 6% and 15% in 80% training and 20% internal validation subsamples). We validated results in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. RESULTS: There were 3,786 ARIC participants with IFG (mean [SD] age 57 [6] years, 52% female, 28% Black individuals). The 3-year cumulative incidence of diabetes was 6%. Six proteins were associated with ∼3-year progression to diabetes, namely lower receptor-type tyrosine-protein phosphatase S (PTPRS), anthrax toxin receptor 2 (ANTXR2), adiponectin (ADIPOQ), ciliary neurotrophic factor receptor subunit α (CNTFR), transmembrane protein 132C (TMEM132C), and higher ADAMTS-like protein 2 (ADAMTSL2). Altered carbohydrate metabolism and glycolysis were key pathways. Adding the six proteins to covariates improved discrimination (optimism-corrected AUC 0.81, ΔAUC 0.03, P = 0.005) and net reclassification (training 12.2%, internal validation 12.0%) with predicted diabetes risk quintiles spanning <1% to ∼20%. Two of the six proteins were validated in MESA (P < 0.008). CONCLUSIONS: We identified proteins associated with 3-year IFG progression, with improvements in diabetes risk stratification.