The variant allele HLA‐B*15:02 is strongly associated with greater risk of Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) in patients treated with carbamazepine or oxcarbazepine. ...The variant allele HLA‐A*31:01 is associated with greater risk of maculopapular exanthema, drug reaction with eosinophilia and systemic symptoms, and SJS/TEN in patients treated with carbamazepine. We summarize evidence from the published literature supporting these associations and provide recommendations for carbamazepine and oxcarbazepine use based on HLA genotypes.
Our purpose was to characterize the clinical influences, genetic risk factors, and gene mechanisms contributing to persistent cisplatin-induced peripheral neuropathy (CisIPN) in testicular cancer ...survivors (TCSs).
TCS given cisplatin-based therapy completed the validated EORTC QLQ-CIPN20 questionnaire. An ordinal CisIPN phenotype was derived, and associations with age, smoking, excess drinking, hypertension, body mass index, diabetes, hypercholesterolemia, cumulative cisplatin dose, and self-reported health were examined for 680 TCS. Genotyping was performed on the Illumina HumanOmniExpressExome chip. Following quality control and imputation, 5.1 million SNPs in 680 genetically European TCS formed the input set. GWAS and PrediXcan were used to identify genetic variation and genetically determined gene expression traits, respectively, contributing to CisIPN. We evaluated two independent datasets for replication: Vanderbilt's electronic health database (BioVU) and the CALGB 90401 trial.
Eight sensory items formed a subscale with good internal consistency (Cronbach α = 0.88). Variables significantly associated with CisIPN included age at diagnosis (OR per year, 1.06;
= 2 × 10
), smoking (OR, 1.54;
= 0.004), excess drinking (OR, 1.83;
= 0.007), and hypertension (OR, 1.61;
= 0.03). CisIPN was correlated with lower self-reported health (OR, 0.56;
= 2.6 × 10
) and weight gain adjusted for years since treatment (OR per Δkg/m
, 1.05;
= 0.004). PrediXcan identified lower expressions of
and
and higher
expression as associated with CisIPN (
value for each < 5 × 10
) with replication of
meeting significance criteria (Fisher combined
= 0.0089).
CisIPN is associated with age, modifiable risk factors, and genetically determined expression level of
Further study of implicated genes could elucidate the pathophysiologic underpinnings of CisIPN.
.
The BioBank Japan (BBJ) Project was launched in 2003 with the aim of providing evidence for the implementation of personalized medicine by constructing a large, patient-based biobank (BBJ). This ...report describes the study design and profile of BBJ participants who were registered during the first 5-year period of the project.
The BBJ is a registry of patients diagnosed with any of 47 target common diseases. Patients were enrolled at 12 cooperative medical institutes all over Japan from June 2003 to March 2008. Clinical information was collected annually via interviews and medical record reviews until 2013. We collected DNA from all participants at baseline and collected annual serum samples until 2013. In addition, we followed patients who reported a history of 32 of the 47 target diseases to collect survival data, including cause of death.
During the 5-year period, 200,000 participants were registered in the study. The total number of cases was 291,274 at baseline. Baseline data for 199,982 participants (53.1% male) were available for analysis. The average age at entry was 62.7 years for men and 61.5 years for women. Follow-up surveys were performed for participants with any of 32 diseases, and survival time data for 141,612 participants were available for analysis.
The BBJ Project has constructed the infrastructure for genomic research for various common diseases. This clinical information, coupled with genomic data, will provide important clues for the implementation of personalized medicine.
•The BioBank Japan Project (BBJ) enrolled 200,000 patients with 47 target diseases.•The BBJ is one of the largest patient-based biobanks in the world.•The BBJ may allow for personalized medicine in the future.
Tamoxifen has been widely used for the prevention of recurrence in patients with hormone receptor-positive breast cancer. Tamoxifen requires metabolic activation by cytochrome P450 (CYP) enzymes for ...formation of active metabolites, 4-hydroxytamoxifen and endoxifen, which have 30- to 100fold greater affinity to the estrogen receptor and the potency to suppress estrogen-dependent breast cancer cell proliferation. CYP2D6 is a key enzyme in this metabolic activation and it has been suggested that the genetic polymorphisms of CYP2D6 influence the plasma concentrations of active tamoxifen metabolites and clinical outcomes for breast cancer patients treated with tamoxifen. The genetic polymorphisms in the other drug-metabolizing enzymes, including other CYP isoforms, sulfotransferases and UDP-glucuronosyl-transferases might contribute to individual differences in the tamoxifen metabolism and clinical outcome of tamoxifen therapy although their contributions would be small. Recently, involvement of a drug transporter in the disposition of active tamoxifen metabolites was identified. The genetic polymorphisms of transporter genes have the potential to improve the prediction of clinical outcome for the treatment of hormone receptor-positive breast cancer. This review summarizes current knowledge on the roles of polymorphisms in the drug-metabolizing enzymes and transporters in tamoxifen pharmacogenomics.
Trastuzumab has been administered to patients with human epidermal growth factor receptor 2 (HER2)-positive cancer, however, the cardiotoxicity is identified as one of the life-threatening ...toxicities. Clinically useful biomarker for trastuzumab-induced cardiotoxicity has been expected to be developed. To identify a novel genetic marker(s) determining the risk of trastuzumab-induced cardiotoxicity, we performed a first genome-wide association study (GWAS) in Japanese population. We enrolled 481 patients who had been treated with trastuzumab and carried out a GWAS using 11 cases (with cardiotoxicity) and 257 controls (without cardiotoxicity). Top 100 single nucleotide polymorphisms (SNPs) which revealed the smallest p values in GWAS (p = 7.60 × 10−7 − 2.01 × 10−4) were further examined using replication samples consisted of 14 cases and 199 controls. The combined analysis of the GWAS and replication study indicated possible association of five loci with trastuzumab-induced cardiotoxicity (rs9316695 on chromosome 13q14.3, rs28415722 on chromosome 15q26.3, rs7406710 on chromosome 17q25.3, rs11932853 on chromosome 4q25, and rs8032978 on chromosome 15q26.3, Pcombined = 6.00 × 10−6, 8.88 × 10−5, 1.07 × 10−4, 1.42 × 10−4, 1.60 × 10−4, respectively). Furthermore, we developed a risk prediction model for trastuzumab-induced cardiotoxicity using the five marker SNPs. The incidence of trastuzumab-induced cardiotoxicity in patients with risk score ≥5 was significantly higher (42.5%) compared to that in patients with score ≤ 4 (1.8%) (p = 7.82 × 10−15, odds ratio = 40.0). These findings suggest the potential to improve the ability of physicians to avoid the trastuzumab-induced cardiotoxicity for patients with HER2-positive cancer.
In the design of whole-genome sequencing (WGS) studies, sequencing depth is a crucial parameter to define variant calling accuracy and study cost, with no standard recommendations having been ...established. We empirically evaluated the variant calling accuracy of the WGS pipeline using ultra-deep WGS data (approximately 410×). We randomly sampled sequence reads and constructed a series of simulation WGS datasets with a variety of gradual depths (n = 54; from 0.05× to 410×). Next, we evaluated the genotype concordances of the WGS data with those in the SNP microarray data or the WGS data using all the sequence reads. In addition, we assessed the accuracy of HLA allele genotyping using the WGS data with multiple software tools (PHLAT, HLA-VBseq, HLA-HD, and SNP2HLA). The WGS data with higher depths showed higher concordance rates, and >13.7× depth achieved as high as >99% of concordance. Comparisons with the WGS data using all the sequence reads showed that SNVs achieved >95% of concordance at 17.6× depth, whereas indels showed only 60% concordance. For the accuracy of HLA allele genotyping using the WGS data, 13.7× depth showed sufficient accuracy while performance heterogeneity among the software tools was observed (the highest concordance of 96.9% was observed with HLA-HD). Improvement in HLA genotyping accuracy by further increasing the depths was limited. These results suggest a medium degree of the WGS depth setting (approximately 15×) to achieve both accurate SNV calling and cost-effectiveness, whereas relatively higher depths are required for accurate indel calling.
Genetic variation in pharmacokinetics (PK)-related genes encoding drug metabolizing enzymes or drug transporters is one of the most practical pharmacogenetic biomarkers for the prediction or ...explanation of an individual’s response to drugs. Many pharmacogenomic variations are identified using targeted, whole-exome, and whole-genome sequencing, and the number of known novel variations and alleles in PK-related genes is increasing. The high homology of sequences among PK-related genes is suspected to lead to potential read misalignment and genotyping errors when short-read sequencing was performed. Therefore, highly efficient and accurate next generation sequencing (NGS) platforms for the sequencing of PK-related genes are needed. We have developed PKseq, a targeted sequencing panel based on multiplex PCR, which targets the coding regions of 37 drug transporters, 30 cytochrome P450 isoforms, 10 UDP-glucuronosyltransferases, 5 flavin-containing monooxygenases, 4 glutathione S-transferases, 4 sulfotransferases, and 10 other genes. In this review, we describe the current NGS platforms for the sequencing of PK-related genes. The NGS platforms, including the PKseq panel, will be useful not only for the identification of all the variants of PK-related genes associated with adverse drug reactions and drug efficacy, but also for clinical sequencing to achieve pharmacogenomics-based stratified medicine.
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