Targeting gut microbial signatures to personalize obesity treatment: Integrating microbiome-based stratification into precision medicine

Abstract

Obesity is a chronic heterogenous metabolic disease that is on the rise in low- and middle-income countries like sub-Saharan Africa, where they are experiencing an urbanisation and westernisation of the diet, transforming the nutrition environment. Although microbiome-based stratification of obesity treatment has been suggested as a global solution, there are no African-specific structures. The current communication introduces the first Africa-adapted, conceptual and evidence-informed, enterotype-based model, combining recent African microbiome data. Unique microbial signatures of the gut e.g., a greater occurrence of Succinivibria, Treponema, and Methanobrevibacter are likely to affect nutritional response patterns and responses to interventions among Africans. The four-step conceptual model includes (1) gut profiling, (2) enterotype-matched diets, (3) metabolite tracking and (4) digital feedback loops, which are enabled by culturally adapted, low-cost diagnostics (e.g., portable quantitative polymerase chain reaction (qPCR) kits, lateral-flow short-chain fatty acid (SCFA)/lipopolysaccharide (LPS) assays), and mobile health platforms. We clarified that this is a hypothesis-driven framework, conceptually informed by existing evidence but not empirically validated. A randomised controlled trial (RCT) design proposal to use permutational multivariate analysis of variance (PERMANOVA) to test microbiome composition and multivariate regression to test the diet-microbiome body mass index (BMI) association. This methodology provides solutions to some of the main translational gaps in precision obesity care by incorporating African-specific microbial data, culturally specific diets, and scalable technology.