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Search for new loci and low-frequency variants influencing glioma risk by exome-array analysis.

ABSTRACT: To identify protein-altering variants (PAVs) for glioma, we analysed Illumina HumanExome BeadChip exome-array data on 1882 glioma cases and 8079 controls from three independent European populations. In addition to single-variant tests we incorporated information on the predicted functional consequences of PAVs and analysed sets of genes with a higher likelihood of having a role in glioma on the basis of the profile of somatic mutations documented by large-scale sequencing initiatives. Globally there was a strong relationship between effect size and PAVs predicted to be damaging (P=2.29 × 10(-49)); however, these variants which are most likely to impact on risk, are rare (MAF<5%). Although no single variant showed an association which was statistically significant at the genome-wide threshold a number represented promising associations - BRCA2:c.9976A>T, p.(Lys3326Ter), which has been shown to influence breast and lung cancer risk (odds ratio (OR)=2.3, P=4.00 × 10(-4) for glioblastoma (GBM)) and IDH2:c.782G>A, p.(Arg261His) (OR=3.21, P=7.67 × 10(-3), for non-GBM). Additionally, gene burden tests revealed a statistically significant association for HARS2 and risk of GBM (P=2.20 × 10(-6)). Genome scans of low-frequency PAVs represent a complementary strategy to identify disease-causing variants compared with scans based on tagSNPs. Strategies to lessen the multiple testing burden by restricting analysis to PAVs with higher priors affords an opportunity to maximise study power.

SUBMITTER: Kinnersley B

PROVIDER: S-EPMC4677454 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Genome-wide association studies (GWASs) have identified loci contributing to total serum bilirubin level. However, no exome-wide approaches have been performed to address this question. Using exome-wide approach, we assessed the influence of protein-coding variants on unconjugated, conjugated, and total serum bilirubin levels in a well-characterized cohort of 773 ambulatory elderly subjects from Italy. Coding variants were replicated in 227 elderly subjects from the same area. We identified 4 missense rare (minor allele frequency, MAF?<?0.5%) and low-frequency (MAF, 0.5%-5%) coding variants located in the first exon of the UGT1A1 gene, which encodes for the substrate-binding domain (rs4148323 [MAF?=?0.06%; p.Gly71Arg], rs144398951 [MAF?=?0.06%; p.Ile215Val], rs35003977 [MAF?=?0.78%; p.Val225Gly], and rs57307513 [MAF?=?0.06%; p.Ser250Pro]). These variants were in strong linkage disequilibrium with 3 intronic UGT1A1 variants (rs887829, rs4148325, rs6742078), which were significantly associated with total bilirubin level (P?=?2.34?×?10(-34), P?=?7.02?×?10(-34), and P?=?8.27?×?10(-34)), as well as unconjugated, and conjugated bilirubin levels. We also identified UGT1A6 variants in association with total (rs6759892, p.Ser7Ala, P?=?1.98?×?10(-26); rs2070959, p.Thr181Ala, P?=?2.87?×?10(-27); and rs1105879, p.Arg184Ser, P?=?3.27?×?10(-29)), unconjugated, and conjugated bilirubin levels. All UGT1A1 intronic variants (rs887829, rs6742078, and rs4148325) and UGT1A6 coding variants (rs6759892, rs2070959, and rs1105879) were significantly associated with gallstone-related cholecystectomy risk. The UGT1A6 variant rs2070959 (p.Thr181Ala) was associated with the highest risk of gallstone-related cholecystectomy (OR, 4.58; 95% CI, 1.58-13.28; P?=?3.21?×?10(-3)). Using an exome-wide approach we identified coding variants on UGT1A1 and UGT1A6 genes in association with serum bilirubin level and hyperbilirubinemia risk in elderly subjects. UGT1A1 intronic single-nucleotide polymorphisms (SNPs) (rs6742078, rs887829, rs4148324) serve as proxy markers for the low-frequency and rare UGT1A1 variants, thereby providing mechanistic explanation to the relationship between UGT1A1 intronic SNPs and the UGT1A1 enzyme activity. UGT1A1 and UGT1A6 variants might be potentially associated with gallstone-related cholecystectomy risk.

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Search for new loci and low-frequency variants influencing glioma risk by exome-array analysis.

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