Skip to main content

Advertisement

SpringerLink
Log in

Defining screening panel of functional variants of CYP1A1, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 genes in Serbian population

  • Original Article
  • Published:
International Journal of Legal Medicine Aims and scope Submit manuscript

Abstract

Plethora of drugs and toxic substances is metabolized by cytochrome P450 enzymes (CYP450). These enzymes are coded by highly variable genes abundant with single nucleotide variants (SNVs) and small insertions/deletions (indels) that affect the functionality of the enzymes, increasing or decreasing their activity. CYP genes genotyping, followed by haplotype inference, provides substrate specific metabolic phenotype prediction. This is crucial in pharmacogenetics and applicable in molecular autopsy. However, high number of alleles in CYP450 superfamily and interethnic variability in frequency distribution require precise gene panel customization. To estimate informativeness of SNVs and alleles in CYP gene families 1, 2, and 3, associated with metabolic alterations, 500 unrelated individuals from 5 regions of Serbia were genotyped using TaqMan assays to determine frequencies of CYP2C9 *2 and *3, CYP2C19 *2 and *17 alleles, four variants in CYP2D6 (rs3892097, rs1065852, rs28371725, rs28371706) gene, and CYP3A4*1B allele. In addition, CYP1A1 rs4646903 and rs1048943 (m1 and m2) variants were genotyped by RFLP. Our results showed that frequencies of tested variants in Serbian population corresponded to general European population and somewhat differed from neighboring populations. SNV rs1065852, the main contributor to non-functional CYP2D6 *4, significantly departed from Hardy-Weinberg equilibrium. With the exception of rs28371706 in CYP2D6 and rs2740574 in CYP3A4, which were very rare in our sample, all other tested variants in CYP2 family are informative and appropriate for pharmacogenetic testing, molecular autopsy, and medico-legal genetic analyses.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Ackerman MJ, Tester DJ, Driscoll DJ (2001) Molecular autopsy of sudden unexplained death in the young. Am J Forensic Med Pathol 22:105–111. https://doi.org/10.1097/00000433-200106000-00001

    Article  CAS  PubMed  Google Scholar 

  2. van Driel B, Michels M, van der Velden J (2018) Molecular autopsy. Neth Hear J 26:471–472. https://doi.org/10.1007/s12471-018-1157-6

    Article  Google Scholar 

  3. Sajantila A, Budowle B (2016) Molecular autopsy. In: Handbook of Forensic Genetics. World scientific, Europe, pp 377–413. https://doi.org/10.1142/9781786340788_0016

    Google Scholar 

  4. Bush WS, Crosslin DR, Owusu-Obeng A, Wallace J, Almoguera B, Basford MA, Bielinski SJ, Carrell DS, Connolly JJ, Crawford D, Doheny KF, Gallego CJ, Gordon AS, Keating B, Kirby J, Kitchner T, Manzi S, Mejia AR, Pan V, Perry CL, Peterson JF, Prows CA, Ralston J, Scott SA, Scrol A, Smith M, Stallings SC, Veldhuizen T, Wolf W, Volpi S, Wiley K, Li R, Manolio T, Bottinger E, Brilliant MH, Carey D, Chisholm RL, Chute CG, Haines JL, Hakonarson H, Harley JB, Holm IA, Kullo IJ, Jarvik GP, Larson EB, McCarty C, Williams MS, Denny JC, Rasmussen-Torvik LJ, Roden DM, Ritchie MD (2016) Genetic variation among 82 pharmacogenes: the PGRNseq data from the eMERGE network. Clin Pharmacol Ther 100:160–163. https://doi.org/10.1002/cpt.350

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Zanger UM, Schwab M (2013) Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation. Pharmacol Ther 138:103–141. https://doi.org/10.1016/j.pharmthera.2012.12.007

    Article  CAS  PubMed  Google Scholar 

  6. Anwar-Mohamed A, Elbekai RH, El-Kadi AO (2009) Regulation of CYP1A1 by heavy metals and consequences for drug metabolism. Expert Opin Drug Metab Toxicol 5:501–521. https://doi.org/10.1517/17425250902918302

    Article  CAS  PubMed  Google Scholar 

  7. Resnik DB, MacDougall DR, Smith EM (2018) Ethical dilemmas in protecting susceptible subpopulations from environmental health risks: liberty, utility, fairness, and accountability for reasonableness. Am J Bioeth 18:29–41. https://doi.org/10.1080/15265161.2017.1418922

    Article  PubMed  PubMed Central  Google Scholar 

  8. Marchant GE (2000) Genetic susceptibility and biomarkers in toxic injury litigation. SSRN Electron J. https://doi.org/10.2139/ssrn.248461

  9. Niinuma Y, Saito T, Takahashi M, Tsukada C, Ito M, Hirasawa N, Hiratsuka M (2014) Functional characterization of 32 CYP2C9 allelic variants. Pharm J 14:107–114. https://doi.org/10.1038/tpj.2013.22

    Article  CAS  Google Scholar 

  10. Schwarz UI (2003) Clinical relevance of genetic polymorphisms in the human CYP2C9 gene. Eur J Clin Investig 33:23–30. https://doi.org/10.1046/j.1365-2362.33.s2.6.x

    Article  CAS  Google Scholar 

  11. Caudle KE, Rettie AE, Whirl-Carrillo M, Smith LH, Mintzer S, Lee MT, Klein TE, Callaghan JT, Clinical Pharmacogenetics Implementation Consortium (2014) Clinical pharmacogenetics implementation consortium guidelines for CYP2C9 and HLA-B genotypes and phenytoin dosing. Clin Pharmacol Ther 96:542–548. https://doi.org/10.1038/clpt.2014.159

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Teichert M, Eijgelsheim M, Uitterlinden AG et al (2011) Dependency of phenprocoumon dosage on polymorphisms in the VKORC1, CYP2C9, and CYP4F2 genes. Pharmacogenet Genomics 21:26–34. https://doi.org/10.1097/FPC.0b013e32834154fb

    Article  CAS  PubMed  Google Scholar 

  13. Paré G, Mehta SR, Yusuf S, Anand SS, Connolly SJ, Hirsh J, Simonsen K, Bhatt DL, Fox KA, Eikelboom JW (2010) Effects of CYP2C19 genotype on outcomes of clopidogrel treatment. N Engl J Med 363:1704–1714. https://doi.org/10.1056/nejmoa1008410

    Article  PubMed  Google Scholar 

  14. Brøsen K (2004) Some aspects of genetic polymorphism in the biotransformation of antidepressants. Therapie 59:5–12. https://doi.org/10.2515/therapie:2004003

    Article  PubMed  Google Scholar 

  15. Martínez C, Blanco G, Ladero JM, García-Martín E, Taxonera C, Gamito FG, Diaz-Rubio M, Agúndez JA (2004) Genetic predisposition to acute gastrointestinal bleeding after NSAIDs use. Br J Pharmacol 141:205–208. https://doi.org/10.1038/sj.bjp.0705623

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Musumba CO, Jorgensen A, Sutton L, van Eker D, Zhang E, O’Hara N, Carr DF, Pritchard DM, Pirmohamed M (2013) CYP2C19*17 gain-of-function polymorphism is associated with peptic ulcer disease. Clin Pharmacol Ther 93:195–203. https://doi.org/10.1038/clpt.2012.215

    Article  CAS  PubMed  Google Scholar 

  17. Baumann P (2014) CYP2D6: genetics, pharmacology and clinical relevance. Future Medicine Ltd, Unitec House, 2 Albert Place, London N3 1QB, UK. pp 2–6. https://doi.org/10.2217/9781780844626

  18. Kirchheiner J, Keulen JTHA, Bauer S, Roots I, Brockmöller J (2008) Effects of the CYP2D6 gene duplication on the pharmacokinetics and pharmacodynamics of tramadol. J Clin Psychopharmacol 28:78–83. https://doi.org/10.1097/JCP.0b013e318160f827

    Article  CAS  PubMed  Google Scholar 

  19. Zackrisson AL, Lindblom B, Ahlner J (2010) High frequency of occurrence of CYP2D6 gene duplication/multiduplication indicating ultrarapid metabolism among suicide cases. Clin Pharmacol Ther 88:354–359. https://doi.org/10.1038/clpt.2009.216

    Article  CAS  PubMed  Google Scholar 

  20. Stingl (formerly Kirchheiner) JC, Viviani R (2011) CYP2D6 in the brain: impact on suicidality. Clin Pharmacol Ther 89:352–353. https://doi.org/10.1038/clpt.2010.239

    Article  Google Scholar 

  21. LLerena A, Naranjo MEG, Rodrigues-Soares F, Penas-LLedó EM, Fariñas H, Tarazona-Santos E (2014) Interethnic variability of CYP2D6 alleles and of predicted and measured metabolic phenotypes across world populations. Expert Opin Drug Metab Toxicol 10:1569–1583. https://doi.org/10.1517/17425255.2014.964204

    Article  CAS  PubMed  Google Scholar 

  22. Zhou Y, Ingelman-Sundberg M, Lauschke VM (2017) Worldwide distribution of cytochrome P450 alleles: a meta-analysis of population-scale sequencing projects. Clin Pharmacol Ther 102:688–700. https://doi.org/10.1002/cpt.690

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Zalma A, Von Moltke LL, Granda BW et al (2000) In vitro metabolism of trazodone by CYP3A: inhibition by ketoconazole and human immunodeficiency viral protease inhibitors. Biol Psychiatry 47:655–661. https://doi.org/10.1016/S0006-3223(99)00176-6

    Article  CAS  PubMed  Google Scholar 

  24. Ohno Y, Hisaka A, Ueno M, Suzuki H (2008) General framework for the prediction of oral drug interactions caused by CYP3A4 induction from in vivo information. Clin Pharmacokinet 47:669–680. https://doi.org/10.2165/00003088-200847100-00004

    Article  CAS  PubMed  Google Scholar 

  25. Jin M, Gock SB, Jannetto PJ, Jentzen JM, Wong SH (2005) Pharmacogenomics as molecular autopsy for forensic toxicology: genotyping cytochrome P450 3A4*1B and 3A5*3 for 25 fentanyl cases. J Anal Toxicol 29:590–598. https://doi.org/10.1093/jat/29.7.590

    Article  CAS  PubMed  Google Scholar 

  26. Amirimani B, Ning B, Deitz AC, Weber BL, Kadlubar FF, Rebbeck TR (2003) Increased transcriptional activity of the CYP3A4* 1B promoter variant. Environ Mol Mutagen 42:299–305. https://doi.org/10.1002/em.10199

    Article  CAS  PubMed  Google Scholar 

  27. Spurdle AB, Goodwin B, Hodgson E, Hopper JL, Chen X, Purdie DM, McCredie M, Giles GG, Chenevix-Trench G, Liddle C (2002) The CYP3A4* 1B polymorphism has no functional significance and is not associated with risk of breast or ovarian cancer. Pharmacogenetics 12:355–366. https://doi.org/10.1097/00008571-200207000-00003

    Article  CAS  PubMed  Google Scholar 

  28. Verbelen M, Weale ME, Lewis CM (2017) Cost-effectiveness of pharmacogenetic-guided treatment: are we there yet? Pharm J 17:395–402. https://doi.org/10.1038/tpj.2017.21

    Article  CAS  Google Scholar 

  29. Sistonen J, Sajantila A, Lao O, Corander J, Barbujani G, Fuselli S (2007) CYP2D6 worldwide genetic variation shows high frequency of altered activity variants and no continental structure. Pharmacogenet Genomics 17:93–101. https://doi.org/10.1097/01.fpc.0000239974.69464.f2

    Article  CAS  PubMed  Google Scholar 

  30. Polimanti R, Piacentini S, Manfellotto D, Fuciarelli M (2012) Human genetic variation of CYP450 superfamily: analysis of functional diversity in worldwide populations. Pharmacogenomics 13:1951–1960. https://doi.org/10.2217/pgs.12.163

    Article  CAS  PubMed  Google Scholar 

  31. Haahr M (2012) True random number service. https://www.Random.org. Accessed 01 Sept 2019

  32. Feldman DN, Feldman JG, Greenblatt R, Anastos K, Pearce L, Cohen M, Gange S, Leanza S, Burk R (2009) CYP1A1 genotype modifies the impact of smoking on effectiveness of HAART among women. AIDS Educ Prev 21:81–93. https://doi.org/10.1521/aeap.2009.21.3_supp.81

    Article  PubMed  PubMed Central  Google Scholar 

  33. Šidák Z (1967) Rectangular confidence regions for the means of multivariate normal distributions. J Am Stat Assoc 62:626–633. https://doi.org/10.1080/01621459.1967.10482935

    Article  Google Scholar 

  34. R CoreTeam DC (2017) A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.r-project.org/. Accessed 26 Apr 2019

  35. Stephens M, Smith NJ, Donnelly P (2001) A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 68:978–989. https://doi.org/10.1086/319501

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Excoffier L, Lischer HEL (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour. https://doi.org/10.1111/j.1755-0998.2010.02847.x

    Article  Google Scholar 

  38. Matei MC, Negură L, Liliac L et al (2012) Validation of PCR-RFLP techniques for the evaluation of codon 72 of p53 and CYP1A1 gene’s polymorphisms in relation with ovarian cancer in a Romanian population. Romanian J Morphol Embryol 53:47–54

    Google Scholar 

  39. Pašalić D, Marinković N (2017) Genetic polymorphisms of the CYP1A1, GSTM1, and GSTT1 enzymes and their influence on cardiovascular risk and lipid profile in people who live near a natural gas plant. Arch Ind Hyg Toxicol 68:46–52. https://doi.org/10.1515/aiht-2017-68-2772

    Article  CAS  Google Scholar 

  40. Szanyi I, Ráth G, Móricz P et al (2012) Effects of cytochrome P450 1A1 and uridine-diphosphate-glucuronosyltransferase 1A1 allelic polymorphisms on the risk of development and the prognosis of head and neck cancers. Eur J Cancer Prev 21:560–568. https://doi.org/10.1097/CEJ.0b013e328350b04c

    Article  CAS  PubMed  Google Scholar 

  41. Kiss I, Orsós Z, Gombos K et al (2007) Association between allelic polymorphisms of metabolizing enzymes (CYP 1A1, CYP 1A2, CYP 2E1, mEH) and occurrence of colorectal cancer in Hungary. Anticancer Res 27:2931–2937

  42. Krasniqi V, Dimovski A, Bytyqi HQ et al (2017) Genetic polymorphisms of CYP2C9, CYP2C19, and CYP3A5 in Kosovar population. Arch Ind Hyg Toxicol 68:180–184. https://doi.org/10.1515/aiht-2017-68-2998

    Article  CAS  Google Scholar 

  43. Saraeva RB, Paskaleva ID, Doncheva E, Eap CB, Ganev VS (2007) Pharmacogenetics of acenocoumarol: CYP2C9, CYP2C19, CYP1A2, CYP3A4, CYP3A5 and ABCB1 gene polymorphisms and dose requirements. J Clin Pharm Ther 32:641–649. https://doi.org/10.1111/j.1365-2710.2007.00870.x

    Article  CAS  PubMed  Google Scholar 

  44. Buzoianu AD, Militaru FC, Vesa ŞC et al (2013) The impact of the CYP2C9 and VKORC1 polymorphisms on acenocoumarol dose requirements in a Romanian population. Blood Cells Mol Dis 50:166–170. https://doi.org/10.1016/j.bcmd.2012.10.010

    Article  CAS  PubMed  Google Scholar 

  45. Ganoci L, Božina T, Mirošević Skvrce N et al (2017) Genetic polymorphisms of cytochrome P450 enzymes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 in the Croatian population. Drug Metab Pers Ther 32. https://doi.org/10.1515/dmpt-2016-0024

  46. Sipeky C, Lakner L, Szabo M et al (2009) Interethnic differences of CYP2C9 alleles in healthy Hungarian and Roma population samples: relationship to worldwide allelic frequencies. Blood Cells Mol Dis 43:239–242. https://doi.org/10.1016/j.bcmd.2009.05.005

    Article  CAS  PubMed  Google Scholar 

  47. Jakovski K, Nestorovska AK, Labacevski N, Dimovski AJ (2013) Characterization of the most common CYP2C9 and CYP2C19 allelic variants in the population from the Republic of Macedonia. An Int J Pharm Sci 68:893–898. https://doi.org/10.1691/ph.2013.3579

    Article  CAS  Google Scholar 

  48. Pendicheva D, Tzveova R, Kaneva R, Duhlenski I (2017) Is pharmacogenetics of antidepressant-related metabolic genes applicable to clinical reality of recurrent depression? Clin Ther 39:e6. https://doi.org/10.1016/j.clinthera.2017.07.033

    Article  Google Scholar 

  49. Kiss ÁF, Vaskó D, Déri MT et al (2018) Combination of CYP2C19 genotype with non-genetic factors evoking phenoconversion improves phenotype prediction. Pharmacol Rep 70:525–532. https://doi.org/10.1016/j.pharep.2017.12.001

    Article  CAS  PubMed  Google Scholar 

  50. Kuzmanovska M, Dimishkovska M, Maleva Kostovska I, Noveski P, Sukarova Stefanovska E, Plaseska-Karanfilska D (2015) CYP2D6 allele distribution in Macedonians, Albanians and Romanies in the Republic of Macedonia. Balkan J Med Genet 18:49–58. https://doi.org/10.1515/bjmg-2015-0086

    Article  CAS  PubMed  Google Scholar 

  51. Mizzi C, Dalabira E, Kumuthini J, Dzimiri N, Balogh I, Başak N, Böhm R, Borg J, Borgiani P, Bozina N, Bruckmueller H, Burzynska B, Carracedo A, Cascorbi I, Deltas C, Dolzan V, Fenech A, Grech G, Kasiulevicius V, Kádaši Ľ, Kučinskas V, Khusnutdinova E, Loukas YL, Macek M Jr, Makukh H, Mathijssen R, Mitropoulos K, Mitropoulou C, Novelli G, Papantoni I, Pavlovic S, Saglio G, Setric J, Stojiljkovic M, Stubbs AP, Squassina A, Torres M, Turnovec M, van Schaik R, Voskarides K, Wakil SM, Werk A, del Zompo M, Zukic B, Katsila T, Lee MT, Motsinger-Rief A, Mc Leod HL, van der Spek P, Patrinos GP (2016) A European spectrum of pharmacogenomic biomarkers: implications for clinical pharmacogenomics. PLoS One 11:e0162866. https://doi.org/10.1371/journal.pone.0162866

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Weber A, Szalai R, Sipeky C et al (2015) Increased prevalence of functional minor allele variants of drug metabolizing CYP2B6 and CYP2D6 genes in Roma population samples. Pharmacol Rep 67:460–464. https://doi.org/10.1016/j.pharep.2014.11.006

    Article  CAS  PubMed  Google Scholar 

  53. Rajeevan H, Cheung K-H, Gadagkar R et al (2017) ALFRED: an allele frequency database for microevolutionary studies. Evol Bioinforma 1:1–10. https://doi.org/10.1177/117693430500100006

    Article  Google Scholar 

  54. McGinty SA (2007) Toxicogenetics and nutrigenetics: biomarkers in occupational medicine and litigation. Biomark Med 1:567–573. https://doi.org/10.2217/17520363.1.4.567

    Article  CAS  PubMed  Google Scholar 

  55. Johnson J, Caudle K, Gong L, Whirl-Carrillo M, Stein CM, Scott SA, Lee MT, Gage BF, Kimmel SE, Perera MA, Anderson JL, Pirmohamed M, Klein TE, Limdi NA, Cavallari LH, Wadelius M (2017) Clinical pharmacogenetics implementation consortium (CPIC) guideline for pharmacogenetics-guided warfarin dosing: 2017 update. Clin Pharmacol Ther 102:397–404. https://doi.org/10.1002/cpt.668

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Mega JL, Close SL, Wiviott SD, Shen L, Hockett RD, Brandt JT, Walker JR, Antman EM, Macias W, Braunwald E, Sabatine MS (2008) Cytochrome P-450 polymorphisms and response to clopidogrel. N Engl J Med 360:354–362. https://doi.org/10.1056/nejmoa0809171

    Article  PubMed  Google Scholar 

  57. Scott SA, Sangkuhl K, Stein CM, Hulot JS, Mega JL, Roden DM, Klein TE, Sabatine MS, Johnson JA, Shuldiner AR, Clinical Pharmacogenetics Implementation Consortium (2013) Clinical pharmacogenetics implementation consortium guidelines for CYP2C19 genotype and clopidogrel therapy: 2013 update. Clin Pharmacol Ther 94:317–323. https://doi.org/10.1038/clpt.2013.105

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Bijl MJ, Visser LE, Hofman A, Vulto AG, van Gelder T, Stricker BH, van Schaik R (2008) Influence of the CYP2D6*4 polymorphism on dose, switching and discontinuation of antidepressants. Br J Clin Pharmacol 65:558–564. https://doi.org/10.1111/j.1365-2125.2007.03052.x

    Article  CAS  PubMed  Google Scholar 

  59. Gaedigk A, Sangkuhl K, Whirl-Carrillo M, Klein T, Leeder JS (2017) Prediction of CYP2D6 phenotype from genotype across world populations. Genet Med 19:69–76. https://doi.org/10.1038/gim.2016.80

    Article  PubMed  Google Scholar 

  60. Haufroid V, Hantson P (2015) CYP2D6 genetic polymorphisms and their relevance for poisoning due to amfetamines, opioid analgesics and antidepressants. Clin Toxicol 53:501–510. https://doi.org/10.3109/15563650.2015.1049355

    Article  CAS  Google Scholar 

  61. Peñas-Lledó E, Guillaume S, Naranjo MEG, Delgado A, Jaussent I, Blasco-Fontecilla H, Courtet P, LLerena A (2015) A combined high CYP2D6-CYP2C19 metabolic capacity is associated with the severity of suicide attempt as measured by objective circumstances. Pharm J 15:172–176. https://doi.org/10.1038/tpj.2014.42

    Article  CAS  Google Scholar 

  62. Ahlner J, Zackrisson A-L, Lindblom B, Bertilsson L (2010) CYP2D6, serotonin and suicide. Pharmacogenomics 11:903–905. https://doi.org/10.2217/pgs.10.84

    Article  CAS  PubMed  Google Scholar 

  63. Gaedigk A, Frank D, Fuhr U (2009) Identification of a novel non-functional CYP2D6 allele, CYP2D6*69, in a Caucasian poor metabolizer individual. Eur J Clin Pharmacol 65:97–100. https://doi.org/10.1007/s00228-008-0559-6

    Article  PubMed  Google Scholar 

  64. Tavira B, Coto E, Diaz-Corte C, Alvarez V, López-Larrea C, Ortega F (2013) A search for new CYP3A4 variants as determinants of tacrolimus dose requirements in renal-transplanted patients. Pharmacogenet Genomics 23:445–448. https://doi.org/10.1097/FPC.0b013e3283636856

    Article  CAS  PubMed  Google Scholar 

  65. Blanchard J, Anand N, Meshkin B et al (2016) (200) opioids and genetics: rs2740574 in CYP3A4 may impact the risk of opioid abuse, misuse, and/or addiction. J Pain 17:S25–S26. https://doi.org/10.1016/j.jpain.2016.01.103

    Article  Google Scholar 

  66. Lamba JK, Lin YS, Schuetz EG, Thummel KE (2012) Genetic contribution to variable human CYP3A-mediated metabolism. Adv Drug Deliv Rev 64:256–269. https://doi.org/10.1016/j.addr.2012.09.017

    Article  Google Scholar 

  67. Zhou L-P, Yao F, Luan H, Wang YL, Dong XH, Zhou WW, Wang QH (2013) CYP3A4*1B polymorphism and cancer risk: a HuGE review and meta-analysis. Tumor Biol 34:649–660. https://doi.org/10.1007/s13277-012-0592-z

    Article  CAS  Google Scholar 

  68. García-Martín E (2002) CYP3A4 variant alleles in white individuals with low CYP3A4 enzyme activity. Clin Pharmacol Ther 71:196–204. https://doi.org/10.1067/mcp.2002.121371

    Article  PubMed  Google Scholar 

  69. Werk AN, Cascorbi I (2014) Functional gene variants of CYP3A4. Clin Pharmacol Ther 96:340–348. https://doi.org/10.1038/clpt.2014.129

    Article  CAS  PubMed  Google Scholar 

  70. Elens L, van Gelder T, Hesselink DA, Haufroid V, van Schaik R (2013) CYP3A4*22 : promising newly identified CYP3A4 variant allele for personalizing pharmacotherapy. Pharmacogenomics 14:47–62. https://doi.org/10.2217/pgs.12.187

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This work was supported by the Ministry of Education, Science and Technological Development, of the Republic of Serbia [grant no. 175093].

Author information

Authors and Affiliations

  1. Institute for Forensic Medicine, Faculty of Medicine, University of Belgrade, Belgrade, 11000, Serbia

    Ivan Skadrić & Oliver Stojković

Authors
  1. Ivan Skadrić
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Oliver Stojković
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Oliver Stojković.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving human participants

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Ethical Committee of Faculty of Medicine, University of Belgrade, no. 2650/XII-15 and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Highlights

CYP450 variants are applicable in postmortem analysis in Serbian population.

Functional variants frequencies of CYP450 genes in Serbian population are similar to European.

CYP2D6 variant rs12248560 (1847G>A) is highly frequent in Serbian population.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Skadrić, I., Stojković, O. Defining screening panel of functional variants of CYP1A1, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 genes in Serbian population. Int J Legal Med 134, 433–439 (2020). https://doi.org/10.1007/s00414-019-02234-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00414-019-02234-7

Keywords

Search

Navigation