2622-P: Multiomics-Based Molecular Subtyping of Obesity

Introduction and Objective: Obesity, defined by a BMI >30 kg/m², is a heterogeneous condition with variable clinical outcomes. Current treatment strategies yield inconsistent benefits at the individual level. Identifying biologically distinct subtypes is critical for precision interventions; however, existing approaches have been insufficient to uncover actionable molecular targets. Methods: We applied a novel pseudotime trajectory analysis (PTA) using Monocle to bulk adipose and muscle transcriptomic data from a densely phenotyped cohort of 256 non-diabetic African American individuals. PTA inferred continuous molecular trajectories based on the top 2,000 transcripts with the greatest variance in each tissue, enabling classification of obesity subtypes. Results: PTA integrated adipose and muscle expression profiles to define ten molecular states. States 4, 6, and 10 (N=18, 32, and 24), located near the trajectory root, were enriched for lean individuals (59-75%). In contrast, states 1, 11 (N=32 and 27), and 9 (N=41) were strongly depleted for lean individuals (0-9%). Compared to lean state 4, obese states 9 and 11 exhibited significant activation (Z>2) of neutrophil degranulation, extracellular matrix organization, and macrophage pathways, alongside repression (Z<-2) of LXR/RXR and SREBF-mediated gene regulation in adipose tissue. In muscle, nonsense-mediated decay and EIF2AK4 (GCN2) response to amino acid deficiency were suppressed. Obese state 11 showed higher WHR, triglycerides, and lower HDL-C compared to state 9, and demonstrated repression of protein biosynthesis (e.g., EIF2 signaling), exosome signaling, and fatty acyl-CoA biosynthesis pathways. Conclusion: PTA revealed phenotypically and molecularly distinct obesity subtypes in African Americans, highlighting pathways that may inform precision treatment strategies.