Integrative Multi-Omics Study of Emirati Patients with Diabetes and Prediabetes Undergoing Bariatric Surgery: A P4 Medicine-Guided Approach

Abstract

Integrating advancements in systems medicine that are predictive, preventive, personalized, and participatory (P4) is expected to support the prevention of chronic diseases such as diabetes and obesity. Bariatric surgery is a promising intervention for managing obesity-related metabolic disorders; however, its effects on the development of cardiovascular disease (CVD) in individuals with type 2 diabetes (T2D) remain poorly understood. To address this knowledge gap, a multi-omics approach was utilized to investigate the impact of bariatric surgery on Emirati individuals with T2D and prediabetes, with a focus on identifying early signs of CVD development. During a 9-month period, longitudinal data were prospectively collected, including whole-genome sequencing (WGS) for genomic profiling, protein immunoassays for proteomic analysis, untargeted metabolomics for metabolic profiling, and gut microbiome composition through 16S rRNA sequencing. By integrating these datasets, a correlation network was constructed which identified distinct communities of interrelated analytes associated with physiological processes and disease progression. This systems-level analysis uncovered biomarkers, pathways, and molecular mechanisms linked to cardiometabolic risk and post-surgical outcomes. Through this longitudinal study, I showed that bariatric surgery reduced CVD risk and inflammatory biomarkers in T2D patients while inducing changes in the gut microbiome and metabolomic profiles. I identified four inflammatory biomarkers (FGF-basic, TNFSF13, IL-8, and IL-1Ra) that were significantly (p < 0.05) influenced by bariatric surgery. In addition, I identified 98 metabolites with significant changes post-surgery that were involved in folate biosynthesis, glycerophospholipid metabolism, and retinol metabolism. Eighteen microbial genera were also found to differentiate between the pre- and post-surgery states. The association analysis revealed four microbial genera (Enterobacter, Enterococcus, Gemella, and Erysipelotrichaceae UCG-003) associated with two T2D SNPs (rs11830243 and rs6978118) and three CVD-related SNPs (rs9490306, 62207434, and rs34606058). These genera formed the network’s central hub, connecting host genetic variants, metabolic pathways, and clinical data, highlighting their broader role in host-microbiome interactions. These findings emphasize the proactive potential of P4 medicine by leveraging multi-omics data in the UAE population. This study adopts a different approach from previous research by promoting the development of personalized medicine protocols tailored to the UAE population. Furthermore, the research quantifies the impact of phenotypic factors on CVD progression among UAE nationals, contributing to a deeper understanding of cardiometabolic health in this specific population.