Pharmacogenomic landscape of Indian population using whole genomes

Abstract

Ethnic differences in pharmacogenomic (PGx) variants have been well documented in literature and could significantly impact variability in response and adverse events to therapeutics. India is a large country with diverse ethnic populations of distinct genetic architecture. India's national genome sequencing initiative (IndiGen) provides a unique opportunity to explore the landscape of PGx variants using population-scale whole genome sequences. We have analyzed the IndiGen variation dataset (N = 1029 genomes) along with global population scale databases to map the most prevalent clinically actionable and potentially deleterious PGx variants among Indians. Differential frequencies for the known and novel variants were studied and interaction of the disrupted PGx genes affecting drug responses were analyzed by performing a pathway analysis. We have highlighted significant differences in the allele frequencies of clinically actionable PGx variants in Indians when compared to the global populations. We identified 134 mostly common (allele frequency [AF] > 0.1) potentially deleterious PGx variants that could alter or inhibit the function of 102 pharmacogenes in Indians. We also estimate that on, an average, each Indian individual carried eight PGx variants (single nucleotide variants) that have a direct impact on the choice of treatment or drug dosing. We have also highlighted clinically actionable PGx variants and genes for which preemptive genotyping is most recommended for the Indian population. The study has put forward the most comprehensive PGx landscape of the Indian population from whole genomes that could enable optimized drug selection and genotype-guided prescriptions for improved therapeutic outcomes and minimizing adverse events.

FIGURE 1

(a) Comparison of Indian allele frequencies of clinically relevant PGx single nucleotide variants with populations in 1KGP3 dataset, gnomAD database, and GME database. PGx variants in Indians which yielded significant p value (p < 0.05) in Fisher’s exact test comparing Indian allele frequency with other databases are highlighted in green outer circle. (b) Comparison of Indian allele frequencies of clinically relevant PGx haplotype variants with populations in the 1KGP3 dataset. AFR, African/African American; AMI, Amish; AMR, Admixed American/Latino; ASJ, Ashkenazi Jewish; CA, Central Asia; EAS, East Asian; EUR, European; FIN, Finnish; GME, Greater Middle East; gnomAD, Genome Aggregation Database; IKGP3, 1000 Genomes Phase 3; NEA, Northeast Africa; NWA, Northwest Africa; OTH, Other (population not assigned); PGx, pharmacogenomic; SAS, South Asian; SD, Syrian Desert; TP, Turkish Peninsula

FIGURE 2

Allele frequencies of most common potentially deleterious nonsynonymous variants (AF > 0.1) in Indians involved drug transport, metabolism and target. Allele frequencies are compared with 1KGP3 database, gnomAD database, and GME database. Y‐axis represents the variant [gene name] and X‐axis represents the population and subpopulation. Gene function category is color coded on the left with the number of drugs associated with each gene. AF, allele frequency; AFR, African/African American; AMI, Amish; AMR, Admixed American/Latino; AP, Arabian Peninsula; ASJ, Ashkenazi Jewish; CA, Central Asia; EAS, East Asian; EUR, European; FIN, Finnish; GME, Greater Middle East; gnomAD, Genome Aggregation Database; IKGP3, 1000 Genomes Phase 3; NEA, Northeast Africa; NFE, Non‐Finnish European; NWA, Northwest Africa; OTH, Other (population not assigned); PGx, pharmacogenomic; SAS, South Asian; SD, Syrian Desert; TP, Turkish Peninsula

FIGURE 3

Sankey diagram. Drug pathway map representing the pharmacogenes functionally disrupted in more than 10 percent of the Indian population. The first column represents the broad drug category associated with the potentially deleterious variants in the Indian population. The second, third, and fourth columns represent the pharmacogenes belonging to the classes: transporter/carriers, enzymes, and targets, respectively. The link width represents the degree of functional loss of the given drug in terms of the pharmacogene classes