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Non-invasive Biomarkers with regard to Cardiovascular Disorder Developed in Men Kids of Adverse Pregnancy.
High pharmacokinetic variability of voriconazole is mainly explained by CYP2C19 phenotype, but there are still unknown factors affecting the variability. In this study, the effect of solute carrier organic anion transporter family member 2B1 (SLCO2B1) genotype on the pharmacokinetics (PKs) of voriconazole was evaluated in 12 healthy CYP2C19 poor metabolizers after a single administration of voriconazole 200 mg intravenously and orally. In addition, the influence of CYP3A4 enzyme activity was also explored. The oral absorption of voriconazole was decreased and delayed in the subjects with the SLCO2B1 c.*396T>C variant compared to the subjects with wild type. However, the CYP3A activity markers measured in this study did not show significant association with metabolism of voriconazole. The results suggest that the SLCO2B1 c.*396T>C may be associated with the decreased function of intestinal OATP2B1, and it could contribute to interindividual PK variability of voriconazole.Genetic variations in DNA base excision repair (BER) genes may affect tumor sensitivity to chemotherapy and radiotherapy. Thus, we investigated the effects of single-nucleotide polymorphisms (SNPs) in key BER pathway genes on clinical outcomes in male patients who received concurrent chemoradiotherapy (CCRT). Seven SNPs from XRCC1, OGG1, APEX1, and MUTYH were genotyped using the Sequenom iPLEX MassARRAY system in samples from 319 men with advanced oral squamous cell carcinoma. The disease-free survival (DFS) rates of the MUTYH rs3219489 genotypes and those of the other genotypes differed significantly (log-rank test p = 0.027). Multivariate Cox proportional hazard analysis showed that the MUTYH rs3219489 GG genotype was associated with poor DFS (recessive model hazard ratio [HR] = 2.01, 95% confidence interval [CI] = 1.31-3.10; p = 0.002). The CT + TT genotypes of XRCC1 rs1799782 (dominant model HR = 0.65, 95% CI = 0.43-0.99; p = 0.044) and GG genotype of APEX1 rs1760944 (recessive model HR = 1.64, 95% CI = 1.00-2.70; p = 0.050) were associated with overall survival (OS). Carrying the two risk genotypes, CC and GG of XRCC1 rs1799782 and APEX1 rs1760944, respectively, (HR = 2.95, 95% CI = 1.47-5.88; p = 0.002) increased mortality risk. Our findings showed that carrying the two risk genotypes of XRCC1 rs1799782 and APEX1 rs1760944 was associated with poor OS, while the GG genotype of MUTYH rs3219489 was associated with poor DFS. Patients carrying the risk genotypes may not benefit from CCRT; therefore, they will need alternative treatments.The acceleration of DNA sequencing in samples from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD)1, we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the 'proportion expressed across transcripts', which quantifies isoform expression for variants. We calculate this metric using 11,70ses, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies.Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which loss-of-function variants are not tolerated, can be highly successful as targets of inhibitory drugs. Second, in most genes, loss-of-function variants are sufficiently rare that genotype-based ascertainment of homozygous or compound heterozygous 'knockout' humans will await sample sizes that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous individuals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development.Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. buy T-DM1 As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6.
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