Identification of pharmacogenetic variants from large scale next generation sequencing data in the Saudi population

被引:13
|
作者
Goljan, Ewa [1 ,2 ]
Abouelhoda, Mohammed [3 ]
ElKalioby, Mohamed M. [2 ,3 ]
Jabaan, Amjad [2 ]
Alghithi, Nada [2 ]
Meyer, Brian F. [1 ,2 ]
Monies, Dorota [1 ,2 ]
机构
[1] King Faisal Specialist Hosp & Res Ctr, Ctr Genom Med, Clin Genom, Riyadh, Saudi Arabia
[2] King Abdulaziz City Sci & Technol, Saudi Human Genome Program, Riyadh, Saudi Arabia
[3] King Faisal Specialist Hosp & Res Ctr, Ctr Genom Med, Computat Biosci, Riyadh, Saudi Arabia
来源
PLOS ONE | 2022年 / 17卷 / 01期
关键词
IMPLEMENTATION CONSORTIUM; GENETIC-VARIATION; GUIDELINES; GENOTYPE; ASSOCIATION; REQUIREMENT; GENOMICS; OUTCOMES; DRUG;
D O I
10.1371/journal.pone.0263137
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
It is well documented that drug responses are related to Absorption, Distribution, Metabolism, and Excretion (ADME) characteristics of individual patients. Several studies have identified genetic variability in pharmacogenes, that are either directly responsible for or are associated with ADME, giving rise to individualized treatments. Our objective was to provide a comprehensive overview of pharmacogenetic variation in the Saudi population. We mined next generation sequencing (NGS) data from 11,889 unrelated Saudi nationals, to determine the presence and frequencies of known functional SNP variants in 8 clinically relevant pharmacogenes (CYP2C9, CYP2C19, CYP3A5, CYP4F2, VKORC1, DPYD, TPMT and NUDT15), recommended by the Clinical Pharmacogenetics Implementation Consortium (CPIC), and collectively identified 82 such star alleles. Functionally significant pharmacogenetic variants were prevalent especially in CYP genes (excluding CYP3A5), with 10-44.4% of variants predicted to be inactive or to have decreased activity. In CYP3A5, inactive alleles (87.5%) were the most common. Only 1.8%, 0.7% and 0.7% of NUDT15, TPMT and DPYD variants respectively, were predicted to affect gene activity. In contrast, VKORC1 was found functionally, to be highly polymorphic with 53.7% of Saudi individuals harboring variants predicted to result in decreased activity and 31.3% having variants leading to increased metabolic activity. Furthermore, among the 8 pharmacogenes studied, we detected six rare variants with an aggregated frequency of 1.1%, that among several other ethnicities, were uniquely found in Saudi population. Similarly, within our cohort, the 8 pharmacogenes yielded forty-six novel variants predicted to be deleterious. Based upon our findings, 99.2% of individuals from the Saudi population carry at least one actionable pharmacogenetic variant.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] SNVHMM: predicting single nucleotide variants from next generation sequencing
    Bian, Jiawen
    Liu, Chenglin
    Wang, Hongyan
    Xing, Jing
    Kachroo, Priyanka
    Zhou, Xiaobo
    BMC BIOINFORMATICS, 2013, 14
  • [42] SNVHMM: predicting single nucleotide variants from next generation sequencing
    Jiawen Bian
    Chenglin Liu
    Hongyan Wang
    Jing Xing
    Priyanka Kachroo
    Xiaobo Zhou
    BMC Bioinformatics, 14
  • [43] VarB: a variation browsing and analysis tool for variants derived from next-generation sequencing data
    Preston, Mark D.
    Manske, Magnus
    Horner, Neil
    Assefa, Samuel
    Campino, Susana
    Auburn, Sarah
    Zongo, Issaka
    Ouedraogo, Jean-Bosco
    Nosten, Francois
    Anderson, Tim
    Clark, Taane G.
    BIOINFORMATICS, 2012, 28 (22) : 2983 - 2985
  • [44] NDesign: software for study design for the detection of rare variants from next-generation sequencing data
    Yuki Sugaya
    Yasuaki Akazawa
    Akira Saito
    Shigeo Kamitsuji
    Journal of Human Genetics, 2012, 57 : 676 - 678
  • [45] A study on fast calling variants from next-generation sequencing data using decision tree
    Li, Zhentang
    Wang, Yi
    Wang, Fei
    BMC BIOINFORMATICS, 2018, 19
  • [46] Detection of somatic structural variants from short-read next-generation sequencing data
    Gong, Tingting
    Hayes, Vanessa M.
    Chan, Eva K. F.
    BRIEFINGS IN BIOINFORMATICS, 2021, 22 (03)
  • [47] A study on fast calling variants from next-generation sequencing data using decision tree
    Zhentang Li
    Yi Wang
    Fei Wang
    BMC Bioinformatics, 19
  • [48] NDesign: software for study design for the detection of rare variants from next-generation sequencing data
    Sugaya, Yuki
    Akazawa, Yasuaki
    Saito, Akira
    Kamitsuji, Shigeo
    JOURNAL OF HUMAN GENETICS, 2012, 57 (10) : 676 - 678
  • [49] Using population data for assessing next-generation sequencing performance
    Houniet, Darren T.
    Rahman, Thahira J.
    Al Turki, Saeed
    Hurles, Matthew E.
    Xu, Yaobo
    Goodship, Judith
    Keavney, Bernard
    Santibanez Koref, Mauro
    BIOINFORMATICS, 2015, 31 (01) : 56 - 61
  • [50] Identification of variants in 94 Chinese patients with hereditary spherocytosis by next-generation sequencing
    Wang, Wen-Juan
    Xie, Jun-dan
    Yao, Hong
    Ding, Zi-xuan
    Jiang, Ai-rui
    Ma, Liang
    Shen, Hong-jie
    Chen, Su-ning
    CLINICAL GENETICS, 2023, 103 (01) : 67 - 78