We use cookies to improve your experience. By continuing to browse this site, you accept our cookie policy.×
Skip main navigation
Aging Health
Bioelectronics in Medicine
Biomarkers in Medicine
Breast Cancer Management
CNS Oncology
Colorectal Cancer
Concussion
Epigenomics
Future Cardiology
Future Medicine AI
Future Microbiology
Future Neurology
Future Oncology
Future Rare Diseases
Future Virology
Hepatic Oncology
HIV Therapy
Immunotherapy
International Journal of Endocrine Oncology
International Journal of Hematologic Oncology
Journal of 3D Printing in Medicine
Lung Cancer Management
Melanoma Management
Nanomedicine
Neurodegenerative Disease Management
Pain Management
Pediatric Health
Personalized Medicine
Pharmacogenomics
Regenerative Medicine

The genomic landscape of CYP2D6 variation in the Indian population

    Ambily Sivadas

    *Author for correspondence:

    E-mail Address: ambily.s@sjri.res.in

    Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bangalore, Karnataka, 560034, India

    ,
    Surabhi Rathore

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    ,
    S Sahana

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    ,
    Bani Jolly

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    ,
    Rahul C Bhoyar

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    ,
    Abhinav Jain

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    ,
    Disha Sharma

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    ,
    Mohamed Imran

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    ,
    Vigneshwar Senthilvel

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    ,
    Mohit Kumar Divakar

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    ,
    Anushree Mishra

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    ,
    Sridhar Sivasubbu

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    Vishwanath Cancer Care Foundation, B 702, 7th Floor, Neelkanth Business Park Kirol Village, Vidya Vihar, West Mumbai, 400086, India

    &
    Vinod Scaria

    **Author for correspondence:

    E-mail Address: vinod.scaria@vishwanathcancercare.org

    CSIR Institute of Genomics & Integrative Biology, Mathura Road, New Delhi, 110025, India

    Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    Vishwanath Cancer Care Foundation, B 702, 7th Floor, Neelkanth Business Park Kirol Village, Vidya Vihar, West Mumbai, 400086, India

    Published Online:https://doi.org/10.2217/pgs-2023-0233

    Aim: The CYP2D6 gene is highly polymorphic, causing large interindividual variability in the metabolism of several clinically important drugs. Materials & methods: The authors investigated the diversity and distribution of CYP2D6 alleles in Indians using whole genome sequences (N = 1518). Functional consequences were assessed using pathogenicity scores and molecular dynamics simulations. Results: The analysis revealed population-specific CYP2D6 alleles (*86, *7, *111, *112, *113, *99) and remarkable differences in variant and phenotype frequencies with global populations. The authors observed that one in three Indians could benefit from a dose alteration for psychiatric drugs with accurate CYP2D6 phenotyping. Molecular dynamics simulations revealed large conformational fluctuations, confirming the predicted reduced function of *86 and *113 alleles. Conclusion: The findings emphasize the utility of comprehensive CYP2D6 profiling for aiding precision public health.

    References

    • 1. Nelson DR, Kamataki T, Waxman DJ et al. The P450 superfamily: update on new sequences, gene mapping, accession numbers, early trivial names of enzymes, and nomenclature. DNA Cell Biol. 12, 1–51 (1993).
    • 2. Gaedigk A, Ingelman-Sundberg M, Miller NA, Leeder JS, Whirl-Carrillo M, Klein TE. The Pharmacogene Variation (PharmVar) Consortium: incorporation of the human cytochrome P450 (CYP) allele nomenclature database. Clin. Pharmacol. Ther. 103, 399–401 (2018).
    • 3. Kimura S, Umeno M, Skoda RC, Meyer UA, Gonzalez FJ. The human debrisoquine 4-hydroxylase (CYP2D) locus: sequence and identification of the polymorphic CYP2D6 gene, a related gene, and a pseudogene. Am. J. Hum. Genet. 45, 889 (1989).
    • 4. Gaedigk A, Blum M, Gaedigk R, Eichelbaum M, Meyer UA. Deletion of the entire cytochrome P450 CYP2D6 gene as a cause of impaired drug metabolism in poor metabolizers of the debrisoquine/sparteine polymorphism. Am. J. Hum. Genet. 48, 943 (1991).
    • 5. Kagimoto M, Heim M, Kagimoto K, Zeugin T, Meyer UA. Multiple mutations of the human cytochrome P450IID6 gene (CYP2D6) in poor metabolizers of debrisoquine. Study of the functional significance of individual mutations by expression of chimeric genes. J. Biol. Chem. 265, 17209–17214 (1990).
    • 6. Bertilsson L, Dahl ML, Dalén P, Al-Shurbaji A. Molecular genetics of CYP2D6: clinical relevance with focus on psychotropic drugs. Br. J. Clin. Pharmacol. 53, 111 (2002).
    • 7. Daly AK. Pharmacogenetics of drug metabolizing enzymes in the United Kingdom population: review of current knowledge and comparison with selected European populations. Drug Metab. Pers Ther. 30, 165–174 (2015).
    • 8. Gaedigk A, Sangkuhl K, Whirl-Carrillo M, Klein T, Steven Leeder J. Prediction of CYP2D6 phenotype from genotype across world populations. Genet. Med. 19, 69 (2017).
    • 9. Sistonen J, Sajantila A, Lao O, Corander J, Barbujani G, Fuselli S. CYP2D6 worldwide genetic variation shows high frequency of altered activity variants and no continental structure. Pharmacogenet. Genomics 17, 93–101 (2007).
    • 10. Llerena A, Dorado P, Ramírez R et al. CYP2D6 genotype and debrisoquine hydroxylation phenotype in Cubans and Nicaraguans. Pharmacogenomics J. 12, 176–183 (2012).
    • 11. Zhou Y, Ingelman-Sundberg M, Lauschke VM. Worldwide distribution of cytochrome P450 alleles: a meta-analysis of population-scale sequencing projects. Clin. Pharmacol. Ther. 102, 688 (2017).
    • 12. Del Tredici AL, Malhotra A, Dedek M et al. Frequency of CYP2D6 alleles including structural variants in the United States. Front. Pharmacol. 9, 305 (2018).
    • 13. Naveen AT, Adithan C, Soya SS, Gerard N, Krishnamoorthy R. CYP2D6 genetic polymorphism in South Indian populations. Biol. Pharm. Bull. 29, 1655–1658 (2006).
    • 14. Adithan C, Gerard N, Naveen AT, Koumaravelou K, Shashindran CH, Krishnamoorthy R. Genotype and allele frequency of CYP2D6 in Tamilian population. Eur. J. Clin. Pharmacol. 59, 517–520 (2003).
    • 15. Umamaheswaran G, Krishna Kumar D, Adithan C. Distribution of genetic polymorphisms of genes encoding drug metabolizing enzymes & drug transporters – a review with Indian perspective. Indian J. Med. Res. 139, 27 (2014).
    • 16. Choudhury S, Akam E, Mastana S. Genetic analysis of CYP2D6 polymorphism in Indian populations and its pharmacogenetic implications. Curr. Pharmacogenomics Person. Med. 12, 123–132 (2015).
    • 17. Paradkar MU, Shah SAV, Dherai AJ, Shetty D, Ashavaid TF. Distribution of CYP2D6 genotypes in the Indian population – preliminary report. Drug Metab. Pers. Ther. 33, 141–151 (2018).
    • 18. Lamba V, Lamba JK, Dilawari JB, Kohli KK. Genetic polymorphism of CYP2D6 in North Indian subjects. Eur. J. Clin. Pharmacol. 54, 787–791 (1998).
    • 19. Abraham BK, Adithan C, Usha Kiran P, Asad M, Koumaravelou K. Genetic polymorphism of CYP2D6 in Karnataka and Andhra Pradesh population in India. Acta Pharmacol. Sin. 21, 494–498 (2000).
    • 20. Jain A, Bhoyar RC, Pandhare K et al. IndiGenomes: a comprehensive resource of genetic variants from over 1000 Indian genomes. Nucleic Acids Res. 49, D1225–D1232 (2021).
    • 21. 1000 Genomes Project Consortium A, Auton A, Brooks LD et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).
    • 22. Chen X, Shen F, Gonzaludo N et al. Cyrius: accurate CYP2D6 genotyping using whole-genome sequencing data. Pharmacogenomics J. 21, 251–261 (2021).
    • 23. Whirl-Carrillo M, McDonagh EM, Hebert JM et al. Pharmacogenomics knowledge for personalized medicine. Clin. Pharmacol. Ther. 92, 414–417 (2012).
    • 24. Preeprem T, Gibson G. SDS, a structural disruption score for assessment of missense variant deleteriousness. Front. Genet. 5, 82 (2014).
    • 25. Dehouck Y, Kwasigroch JM, Gilis D, Rooman M. PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality. BMC Bioinformatics 12, 1–12 (2011).
    • 26. van Durme J, Delgado J, Stricher F, Serrano L, Schymkowitz J, Rousseau F. A graphical interface for the FoldX forcefield. Bioinformatics 27, 1711–1712 (2011).
    • 27. Kuznetsov IB, McDuffie M. FlexPred: a web-server for predicting residue positions involved in conformational switches in proteins. Bioinformation 3, 134–136 (2008).
    • 28. Wass MN, Kelley LA, Sternberg MJE. 3DLigandSite: predicting ligand-binding sites using similar structures. Nucleic Acids Res. 38, W469 (2010).
    • 29. Nimrod G, Glaser F, Steinberg D, Ben-Tal N, Pupko T. In silico identification of functional regions in proteins. Bioinformatics 21(Suppl. 1), i328–i337 (2005).
    • 30. Chang X, Wang K. wANNOVAR: annotating genetic variants for personal genomes via the web. J. Med. Genet. 49, 433 (2012).
    • 31. Grantham R. Amino acid difference formula to help explain protein evolution. Science (80-) 185, 862–864 (1974).
    • 32. Rowland P, Blaney FE, Smyth MG et al. Crystal structure of human cytochrome P450 2D6. J. Biol. Chem. 281, 7614–7622 (2006).
    • 33. Šali A, Blundell TL. Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol. 234, 779–815 (1993).
    • 34. Shapovalov MV, Dunbrack RL. A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions. Structure 19, 844 (2011).
    • 35. Wang A, Savas U, Hsu MH, Stout CD, Johnson EF. Crystal structure of human cytochrome P450 2D6 with prinomastat bound. J. Biol. Chem. 287, 10834 (2012).
    • 36. Malde AK, Zuo L, Breeze M et al. An automated force field topology builder (ATB) and repository: version 1.0. J. Chem. Theory Comput. 7, 4026–4037 (2011).
    • 37. Angélil R, Diemand J, Tanaka KK, Tanaka H. Homogeneous SPC/E water nucleation in large molecular dynamics simulations. J. Chem. Phys. 143(6), 64507 (2015).
    • 38. Schmid N, Eichenberger AP, Choutko A et al. Definition and testing of the GROMOS force-field versions 54A7 and 54B7. Eur. Biophys. J. 40, 843–856 (2011).
    • 39. Maciej S, Becker FG, Cleary M et al. LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472 (1997).
    • 40. Parrinello M, Rahman A. Polymorphic transitions in single crystals: a new molecular dynamics method. J. Appl. Phys 52, 7182 (1998).
    • 41. Pettersen EF, Goddard TD, Huang CC et al. UCSF ChimeraX: structure visualization for researchers, educators, and developers. Protein Sci. 30, 70 (2021).
    • 42. Fukuyoshi S, Kometani M, Watanabe Y et al. Molecular dynamics simulations to investigate the influences of amino acid mutations on protein three-dimensional structures of cytochrome P450 2D6.1, 2, 10, 14A, 51, and 62. PLOS ONE 11(4), e0152946 (2016).
    • 43. Montané Jaime LK, Paul J, Lalla A, Legall G, Gaedigk A. Impact of CYP2D6 on venlafaxine metabolism in Trinidadian patients with major depressive disorder. Pharmacogenomics 19, 197–212 (2018).
    • 44. Dodgen TM, Hochfeld WE, Fickl H et al. Introduction of the AmpliChip CYP450 test to a South African cohort: a platform comparative prospective cohort study. BMC Med. Genet. 14, 1–15 (2013).
    • 45. Evert B, Griese EU, Eichelbaum M. A missense mutation in exon 6 of the CYP2D6 gene leading to a histidine 324 to proline exchange is associated with the poor metabolizer phenotype of sparteine. Naunyn Schmiedeberg'sArch. Pharmacol. 350, 434–439 (1994).
    • 46. Lek M, Karczewski KJ, Minikel EV et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).
    • 47. Don CG, Smieško M. Microsecond MD simulations of human CYP2D6 wild-type and five allelic variants reveal mechanistic insights on the function. PLOS ONE 13(8), e0202534 (2018).
    • 48. Handa K, Nakagome I, Yamaotsu N, Gouda H, Hirono S. In silico study on the inhibitory interaction of drugs with wild-type CYP2D6.1 and the natural variant CYP2D6.17. Drug Metab. Pharmacokinet. 29, 52–60 (2014).
    • 49. Muroi Y, Saito T, Takahashi M et al. Functional characterization of wild-type and 49 CYP2D6 allelic variants for N-desmethyltamoxifen 4-hydroxylation activity. Drug Metab. Pharmacokinet. 29, 360–366 (2014).
    • 50. Stern S, Hyland PL, Pacanowski M, Schuck R. Leveraging in vitro models for clinically relevant rare CYP2D6 variants in pharmacogenomics. Drug Metab. Dispos. 52(3), 159–170 (2024).
    • 51. Lauschke VM, Ingelman-Sundberg M. Emerging strategies to bridge the gap between pharmacogenomic research and its clinical implementation. NPJ Genomic Med. 5, 9 (2020).
    • 52. Nakatsuka N, Moorjani P, Rai N et al. The promise of discovering population-specific disease-associated genes in South Asia. Nat. Genet. 49, 1403–1407 (2017).