Evidence map›Paper›PMID 35338580›Full record

ArticleClinical and translational science2022

Pharmacogenomic landscape of Indian population using whole genomes.

S Sahana, Rahul C Bhoyar, Ambily Sivadas, Abhinav Jain, Mohamed Imran, Mercy Rophina, Vigneshwar Senthivel, Mohit Kumar Diwakar, Disha Sharma, Anushree Mishra and 2 more

Open access · goldAbstract read
In one paragraph

Article in Clinical and translational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
4.2field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Pharmacogenomic heterogeneity ofAnnals of medicine · 2025
    Observational
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
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  10. Article
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  12. Review
  13. Article
  14. Genetic Variation among Pharmacogenes in the Sardinian Population.International journal of molecular sciences · 2022
    Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

S SahanaCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Rahul C BhoyarCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Ambily SivadasDivision of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bangalore, India.
Abhinav JainCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Mohamed ImranCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Mercy RophinaCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Vigneshwar SenthivelCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Mohit Kumar DiwakarCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Disha SharmaCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Anushree MishraCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Sridhar SivasubbuCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Vinod ScariaCSIR Institute of Genomics and Integrative Biology, New Delhi, India.
Institute of Genomics and Integrative Biology · INAcademy of Scientific and Innovative Research · INSt. John's National Academy of Health Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Genome, HumanPharmacogeneticsAsian PeopleGene FrequencyGenetics, PopulationGenotypeHumans

Identifiers

PMID35338580
PMCPMC9010271
OpenAlexW4220988545

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.