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Background: Adiposity is a key modulator for Insulin resistance (IR); a strong risk factor for type 2 diabetes and cardiovascular diseases. The blood proteome is a crucial indicator of biological processes associated with complex disorders. In this study, we investigate the associations between plasma proteomics and visceral adipose tissue volume (VAT), and their intersection with phenotypic and genomic data to identify critical proteins for adiposity linked to IR.

Methods: We examined UK biobank participants with proteomic data generated using the Olink proximity extension antibody assay (PEA). Interactions between, polygenic scores, biomarkers, socio-behavioral, and fitness factors were investigated to identify the most important proteins associated with VAT (Figure). Multi-step machine learning algorithms including separate models for each feature type, followed by a combined model were employed. We used …