<HashMap><database>EGA</database><scores/><additional><omics_type>Genomics</omics_type><dataset_type>Illumina HumanExome-12v1_A</dataset_type><full_dataset_link>https://ega-archive.org/datasets/EGAD00010000758</full_dataset_link><sample_count>906</sample_count><description>EGA dataset EGAD00010000758</description><repository>EGA</repository><title>Title not provided</title><pubmed_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&lt;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.</pubmed_abstract><pubmed_title>Search for new loci and low-frequency variants influencing glioma risk by exome-array analysis.</pubmed_title><pubmed_authors>Kinnersley Ben B, Kamatani Yoichiro Y, Labussière Marianne M, Wang Yufei Y, Galan Pilar P, Mokhtari Karima K, Delattre Jean-Yves JY, Gousias Konstantinos K, Schramm Johannes J, Schoemaker Minouk J MJ, Swerdlow Anthony A, Fleming Sarah J SJ, Herms Stefan S, Heilmann Stefanie S, Nöthen Markus M MM, Simon Matthias M, Sanson Marc M, Lathrop Mark M, Houlston Richard S RS</pubmed_authors></additional><is_claimable>false</is_claimable><name>Glioma_Exome_FRE_CASES - samples</name><description>French glioma case germline genotypes using Illumina HumanExome-12v1_A array</description><dates><updated>2017-07-26 15:39:26</updated></dates><accession>EGAD00010000758</accession><cross_references><TAXONOMY>9606</TAXONOMY><pubmed>26264438</pubmed><EGA>EGAC00001000345</EGA><EGA>EGAS00001001258</EGA></cross_references></HashMap>