👤 Bratati Kahali

Cardiometabolic risks affect cognition during aging, yet genetic basis for both remain understudied in Indians. This study constructs an ancestry-matched Indian haplotype reference panel for genotype imputation of 5111 rural Indians. Single-locus, gene-based, conditional genome-wide association analyses are performed on 20 cognitive and 10 cardiometabolic traits, with subsequent follow-up of identified associations through multimodal functional annotation. Furthermore, causal interrelationships between cardiometabolic and cognitive phenotypes by Mendelian randomization are investigated. One novel memory-associated and 17 novel cardiometabolic phenotypes-associated (high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], triglycerides [TG], total cholesterol [TC], TG:HDL, and visceral adiposity index [VAI]) genome-wide significant loci, and multiple genes are identified. AMIGO1 (delayed-recall) and ZPR1-APOA5 (metabolic syndrome) exhibit distinct haplotype structure compared to other populations. Causal roles of cardiometabolic traits on various cognitive domains are identified via genetic instruments in APOC3-APOA4-APOA5-ZPR1-BUD13 among others. These findings illustrate the impact of cardiometabolic factors on cognition in a rural socioeconomically disadvantaged population, advancing efforts to address health disparities. Our newly constructed ancestry-matched haplotype reference panel gives better genotype imputation accuracy for the Indian population. One and 17 novel genome-wide significant single-loci were identified to be associated with cognitive and cardiometabolic traits, respectively. Several subgenome-wide hits for all phenotypes were identified. Collapsing protein truncating variants (PTVs), there were two genes identified to be associated with cardiometabolic traits at a genome-wide level of significance, correcting for multiple phenotypes tested. Haplotypic differences were identified compared to 1000 Genomes superpopulations for genes influencing delayed recall and metabolic syndrome. Adverse causal roles of cardiometabolic traits on cognition were uncovered via genetic instruments in APOC3-APOA4-APOA5-ZPR1-BUD13, among others, through Mendelian randomization. Show less

Genome wide association studies (GWAS) have focused on elucidating the genetic architecture of complex traits by assessing single variant effects in additive genetic models, albeit explaining a fraction of the trait heritability. Epistasis has recently emerged as one of the intrinsic mechanisms that could explain part of this missing heritability. We conducted epistasis analysis for genome-wide body mass index (BMI) associated SNPs in Alzheimer's Disease Neuroimaging Initiative (ADNI) and followed up top significant interacting SNPs for replication in the UK Biobank imputed genotype dataset. We report two pairwise epistatic interactions, between rs2177596 (RHBDD1) and rs17759796 (MAPK1), rs1121980 (FTO) and rs6567160 (MC4R), obtained from a consensus of nine different epistatic approaches. Gene interaction maps and tissue expression profiles constructed for these interacting loci highlights co-expression, co-localisation, physical interaction, genetic interaction, and shared pathways emphasising the neuronal influence in obesity and implicating concerted expression of associated genes in liver, pancreas, and adipose tissues insinuating to metabolic abnormalities characterized by obesity. Detecting epistasis could thus be a promising approach to understand the effect of simultaneously interacting multiple genetic loci in disease aetiology, beyond single locus effects. Show less

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity. Show less