Capturing India’s phenotypic diversity: Health insights from the GenomeIndia project

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Abstract Background India represents 18% of the global population yet remains underrepresented in health research. Moreover, existing national surveys miss critical variation across its 4,600 ethnolinguistic groups. We present a comprehensive phenotypic characterisation of 81 populations from the GenomeIndia project. Methods We analysed 67 sociodemographic, anthropometric, and blood biochemistry variables from 17,777 individuals sampled across 81 ethnolinguistic populations from India, examining population-level variation, disease reporting fractions, and age- and sex-specific life-course trends. Findings Ethnolinguistic identity predicted health outcomes independently of administrative state, improving phenotypic variance explained by an average of 7·4%. 95% of participants had at least one abnormal biochemical or anthropometric marker, driven by low HDL (52·2%) and elevated triglycerides (43·6%). Metabolic risk, however, was highly stratified: adjusted prevalence for low HDL ranged four-fold across ancestry groups from 17·2% to 67·7%. We also identified an “awareness gap”; only 17·6% of people with hypertension and 2·2% of people with dyslipidemia were aware of their condition. This awareness gap was higher in tribal populations, in which women did not show the higher HDL levels typically seen compared to men, pointing to distinct metabolic profiles and healthcare access barriers across India. Interpretation The Indian phenotypic landscape is highly structured along ethnolinguistic lines, where ancestry and environment both influence risk. The high systemic burden of abnormalities necessitates population-specific reference intervals. GenomeIndia provides a foundational map for precision public health, shifting the focus from state-level averages to population-specific risk profiles.

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