3009-LB: Annotation-Informed Soft Clustering Identifies Biologically Interpretable Factors Underlying Type 2 Diabetes Heterogeneity

Introduction and Objective: Type 2 diabetes (T2D) is polygenic and heterogeneous. Clustering of genome-wide association study (GWAS) signals has identified variant clusters underlying T2D trait heterogeneity but has not resolved them to genes and pathways. We tested whether clustering diabetes-associated SNPs by gene and functional annotation could resolve T2D genetic signals to pathways. Methods: We developed PIGEAN, a Bayesian method inferring SNP-to-gene/annotation associations from GWAS summary statistics, and EAGGL, a soft-clustering method using non-negative matrix factorization on PIGEAN outputs. We applied both to meta-analyzed T2D GWAS SNPs to define pathway clusters (factors). Factor polygenic scores (FPS) were made from each factor to test associations with T2D traits in 4 models, with or without T2D polygenic adjustment and using joint or individual factors, in AMP-T2D Knowledge Portal GWAS summary statistics and individual-level data from the United Kingdom Biobank. Results: PIGEAN identified 149 genes with >50% likelihood of T2D involvement by annotation; 67 were factor-specific. EAGGL clustered these into 11 annotation-derived factors. These factors overlapped T2D SNP-trait clusters, but aggregated liver clusters, resolved additional beta cell and lipid clusters, and introduced 2 novel insulin-response clusters. FPS trait associations were concordant, notably CRP with Adipocyte Hypertrophy p = 2.0 × 10-3, NAFLD with Hepatic Steatosis p = 7.0 × 10-3, LPA with Non-Leptin Adipokine Signaling p = 9.4 × 10-4, BMI with Leptin Signaling p = 3.3 × 10-3 and Obesity p < 10-300, and ALT with Adipose Failure p = 6.2 × 10-5. Of PIGEAN-identified genes, 58% (86) were novel findings, including PDE8B. Conclusion: Annotation-informed clustering identified biologically interpretable factors spanning pancreatic, adipose, hepatic, and mixed dysmetabolic pathways. This approach refines our understanding of T2D heterogeneity by mapping signals to genes and pathways. Disclosure S.D. Gage: None. K. Smith: None. A.J. Deutsch: None. M. Udler: Advisory Panel; Ended; Novo Nordisk. Research Support; Current; Novo Nordisk. J. Flannick: None. Funding NIDDK (U54 DK118612)