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. 2023 Jul 19;11(1):17.
doi: 10.1007/s40203-023-00154-4. eCollection 2023.

In-silico mining to glean SNPs of pharmaco-clinical importance: an investigation with reference to the Indian populated SNPs

Anamika Yadav  1 , Shivani Srivastava  1   2 , Shivani Tyagi  1 , Neelam Krishna  1 , Pramod Katara  1
Affiliations

In-silico mining to glean SNPs of pharmaco-clinical importance: an investigation with reference to the Indian populated SNPs

Anamika Yadav et al. In Silico Pharmacol. .

Abstract

Drugs pharmacology is defined by pharmacokinetics and pharmacodynamics and both of them are affected by genetic variability. Genetic variability varies from population to population, and sometimes even within the population, it exists. Single nucleotide polymorphisms (SNPs) are one of the major genetic variability factors which are found to be associated with the pharmacokinetics and pharmacodynamics process of a drug and are responsible for variable drug response and clinical phenotypes. Studies of SNPs can help to perform genome-wide association studies for their association with pharmacological and clinical events, at the same time; their information can direct genome-wide association studies for their use as biomarkers. With the aim to mine and characterize Indian populated SNPs of pharmacological and clinical importance. Two hundred six candidate SNPs belonging to 43 genes were retrieved from Indian Genome Variation Database. The distribution pattern of considered SNPs was observed against all five world super-populations (AFR, AMR, EAS, EUR, and SAS). Further, their annotation was done through SNP-nexus by considering Human genome reference builds - hg38, pharmacological and clinical information was supplemented by PharmGKB and ClinVar database. At last, to find out the association between SNPs linkage disequilibrium was observed in terms of r2. Overall, the study reported 53 pharmaco-clinical active SNPs and found 24 SNP-pairs as potential markers, and recommended their clinical and experimental validation.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-023-00154-4.

Keywords: Drug response; Haplotype; Linkage disequilibrium; Molecular marker; Single nucleotide polymorphisms.

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Conflict of interest statement

Competing interestsThe authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Column chart shows physical annotation (consequences) of SNPs variants
Fig. 2
Fig. 2
Range wise comparative representation of LD in SNP-pairs among world super-population (AFR: African, AMR: Ad Mixed American, EAS: East Asian, EUR: European, SAS: South Asian)
Fig. 3
Fig. 3
Range wise comparative representation of LD sharing among SAS subpopulations (BEB: Bengali from Bangladesh, GIH: Gujrati Indian from Houston, Texas, ITU: Indian Telugu from the UK, STU: Sri Lankan Tamil from the UK, PJL: Punjabi from Lahore, Pakistan)
Fig. 4
Fig. 4
Synopsis of overall analysis of Indian populated SNPs belongs to pharmacokinetics genes
See this image and copyright information in PMC

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