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The global spectrum of protein-coding pharmacogenomic diversity.

ABSTRACT: Differences in response to medications have a strong genetic component. By leveraging publically available data, the spectrum of such genomic variation can be investigated extensively. Pharmacogenomic variation was extracted from the 1000 Genomes Project Phase 3 data (2504 individuals, 26 global populations). A total of 12?084 genetic variants were found in 120 pharmacogenes, with the majority (90.0%) classified as rare variants (global minor allele frequency <0.5%), with 52.9% being singletons. Common variation clustered individuals into continental super-populations and 23 pharmacogenes contained highly differentiated variants (FST>0.5) for one or more super-population comparison. A median of three clinical variants (PharmGKB level 1A/B) was found per individual, and 55.4% of individuals carried loss-of-function variants, varying by super-population (East Asian 60.9%>African 60.1%>South Asian 60.3%>European 49.3%>Admixed 39.2%). Genome sequencing can therefore identify clinical pharmacogenomic variation, and future studies need to consider rare variation to understand the spectrum of genetic diversity contributing to drug response.

SUBMITTER: Wright GEB

PROVIDER: S-EPMC5817389 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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The global spectrum of protein-coding pharmacogenomic diversity.

Wright G E B GEB Carleton B B Hayden M R MR Ross C J D CJD

The pharmacogenomics journal 20161025 1

Differences in response to medications have a strong genetic component. By leveraging publically available data, the spectrum of such genomic variation can be investigated extensively. Pharmacogenomic variation was extracted from the 1000 Genomes Project Phase 3 data (2504 individuals, 26 global populations). A total of 12 084 genetic variants were found in 120 pharmacogenes, with the majority (90.0%) classified as rare variants (global minor allele frequency <0.5%), with 52.9% being singletons. ...[more]

PMID: 27779249

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Project description:BACKGROUND: Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel. RESULTS: 43 SNPs were found significantly associated (FDR<0.005) with paclitaxel response, with 10 belonging to protein-coding genes (CFTR, ROBO1, PTPRD, BTBD12, DCT, SNTG1, SGCD, LPHN2, GRIK1, ZNF607). SNPs in GRIK1, DCT, SGCD and CFTR were predicted to be intronic enhancers, altering gene expression, while SNPs in ZNF607 and BTBD12 cause conservative missense mutations. mRNA expression analysis supported these findings as GRIK1, DCT, SNTG1, SGCD and CFTR showed significantly (p<0.05) increased expression among sensitive cell lines. Haplotypes found in GRIK1, SGCD, ROBO1, LPHN2, and PTPRD were more strongly associated with response than their individual SNPs. CONCLUSIONS: Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.

Project description:BACKGROUND:In structural bioinformatics, there is an increasing interest in identifying and understanding the evolution of local protein structures regarded as key structural or functional protein building blocks. A central need is then to compare these, possibly short, fragments by measuring efficiently and accurately their (dis)similarity. Progress towards this goal has given rise to scores enabling to assess the strong similarity of fragments. Yet, there is still a lack of more progressive scores, with meaningful intermediate values, for the comparison, retrieval or clustering of distantly related fragments. RESULTS:We introduce here the Amplitude Spectrum Distance (ASD), a novel way of comparing protein fragments based on the discrete Fourier transform of their C(?) distance matrix. Defined as the distance between their amplitude spectra, ASD can be computed efficiently and provides a parameter-free measure of the global shape dissimilarity of two fragments. ASD inherits from nice theoretical properties, making it tolerant to shifts, insertions, deletions, circular permutations or sequence reversals while satisfying the triangle inequality. The practical interest of ASD with respect to RMSD, RMSDd, BC and TM scores is illustrated through zinc finger retrieval experiments and concrete structure examples. The benefits of ASD are also illustrated by two additional clustering experiments: domain linkers fragments and complementarity-determining regions of antibodies. CONCLUSIONS:Taking advantage of the Fourier transform to compare fragments at a global shape level, ASD is an objective and progressive measure taking into account the whole fragments. Its practical computation time and its properties make ASD particularly relevant for applications requiring meaningful measures on distantly related protein fragments, such as similar fragments retrieval asking for high recalls as shown in the experiments, or for any application taking also advantage of triangle inequality, such as fragments clustering. ASD program and source code are freely available at: http://www.irisa.fr/dyliss/public/ASD/.

Project description:BackgroundIndividuals with intellectual disability (ID) and autism spectrum disorder (ASD) often receive psychotropic medications such as antipsychotics and antidepressants to treat aberrant behaviors and mood symptoms, frequently resulting in polypharmacy and drug-related adverse effects. Pharmacogenomic (PGx) studies with ASD and/or ID (ASD/ID) have been scarce despite the promise of optimizing treatment outcomes. We reviewed the literature on PGx studies with antipsychotics and antidepressants (e.g., treatment response and adverse effects) in ASD/ID.MethodsWe performed a systematic review using MEDLINE, Embase, and PsycINFO, including peer-reviewed original articles in English referring to PGx in the treatment of ASD/ID in any age groups (e.g., treatment response and adverse effects).ResultsA total of 28 PGx studies using mostly candidate gene approaches were identified across age groups. Notably, only 3 studies included adults with ASD/ID while the other 25 studies focused specifically on children/adolescents with ASD/ID. Twelve studies primarily investigated treatment response, of which 5 and 6 studies included patients treated with antipsychotics and antidepressants, respectively. Most interesting results for response were reported for 2 sets of candidate gene studies, namely: (1) The DRD3 Ser9Gly (rs6280) polymorphism was examined in patients treated with risperidone in 3 studies, 2 of which reported an association with risperidone treatment response and (2) the SLC6A4 5-HTTLPR polymorphism and treatment response to antidepressants which was investigated in 4 studies, 3 of which reported significant associations. In regard to side effects, 9 of 15 studies focused on hyperprolactinemia in patients treated with risperidone. Among them, 7 and 5 studies examined the impact of CYP2D6 and DRD2 Taq1A polymorphisms, respectively, yielding mostly negative study findings.ConclusionsThere is limited data available on PGx in individuals with ASD/ID and in particular in adults. Given the potential for PGx testing in improving treatment outcomes, additional PGx studies for psychotropic treatment in ASD/ID across age groups are warranted.

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The global spectrum of protein-coding pharmacogenomic diversity.

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The global spectrum of protein-coding pharmacogenomic diversity.

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