Analyses of frequency profiles of markers on disease or drug-response related genes in diverse populations are important for the dissection of common diseases. We report the results of analyses of data on 405 SNPs from 75 such genes and a 5.2 Mb chromosome, 22 genomic region in 1871 individuals from diverse 55 endogamous Indian populations. These include 32 large (>10 million individuals) and 23 isolated populations, representing a large fraction of the people of India. We observe high levels of genetic divergence between groups of populations that cluster largely on the basis of ethnicity and language. Indian populations not only overlap with the diversity of HapMap populations, but also contain population groups that are genetically distinct. These data and results are useful for addressing stratification and study design issues in complex traits especially for heterogeneous populations.

With the advent of next-generation sequencing, large-scale initiatives for mining whole genomes and exomes have been employed to better understand global or population-level genetic architecture. India encompasses more than 17% of the world population with extensive genetic diversity, but is under-represented in the global sequencing datasets. This gave us the impetus to perform and analyze the whole genome sequencing of 1029 healthy Indian individuals under the pilot phase of the ‘IndiGen’ program. We generated a compendium of 55,898,122 single allelic genetic variants from geographically distinct Indian genomes and calculated the allele frequency, allele count, allele number, along with the number of heterozygous or homozygous individuals. In the present study, these variants were systematically annotated using publicly available population databases and can be accessed through a browsable online database named as ‘IndiGenomes’ http://clingen.igib.res.in/indigen/. The IndiGenomes database will help clinicians and researchers in exploring the genetic component underlying medical conditions. Till date, this is the most comprehensive genetic variant resource for the Indian population and is made freely available for academic utility. The resource has also been accessed extensively by the worldwide community since it's launch.

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Background: Host adhesion molecules play a significant role in the pathogenesis of Plasmodium falciparum malaria and changes in their structure or levels in individuals can influence the outcome of infection. The aim of this study was to investigate the association of SNPs of three adhesion molecule genes, ICAM1, PECAM1 and CD36, with severity of falciparum malaria in a malaria-endemic and a non-endemic region of India.

Polymorphic variants of DNA repair and damage response genes play major role in carcinogenesis. These variants are suspected as predisposition factors to Oral Squamous Cell Carcinoma (OSCC). For identification of susceptible variants affecting OSCC development in Indian population, the “maximally informative” method of SNP selection from HapMap data to non-HapMap populations was applied. Three hundred twenty-five SNPs from 11 key genes involved in double strand break repair, mismatch repair and DNA damage response pathways were genotyped on a total of 373 OSCC, 253 leukoplakia and 535 unrelated control individuals. The significantly associated SNPs were validated in an additional cohort of 144 OSCC patients and 160 controls. The rs12515548 of MSH3 showed significant association with OSCC both in the discovery and validation phases (discovery P-value: 1.43E-05, replication P-value: 4.84E-03). Two SNPs (rs12360870 of MRE11A, P-value: 2.37E-07 and rs7003908 of PRKDC, P-value: 7.99E-05) were found to be significantly associated only with leukoplakia. Stratification of subjects based on amount of tobacco consumption identified SNPs that were associated with either high or low tobacco exposed group. The study reveals a synergism between associated SNPs and lifestyle factors in predisposition to OSCC and leukoplakia.

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Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug–gene (pharmacogenetic), drug–drug and drug–drug–gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug–drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.

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