ObjectiveThe objective of this study was to aggregate data for the first genomewide association study meta-analysis of cluster headache, to identify genetic risk variants, and gain biological... Show moreObjectiveThe objective of this study was to aggregate data for the first genomewide association study meta-analysis of cluster headache, to identify genetic risk variants, and gain biological insights.MethodsA total of 4,777 cases (3,348 men and 1,429 women) with clinically diagnosed cluster headache were recruited from 10 European and 1 East Asian cohorts. We first performed an inverse-variance genomewide association meta-analysis of 4,043 cases and 21,729 controls of European ancestry. In a secondary trans-ancestry meta-analysis, we included 734 cases and 9,846 controls of East Asian ancestry. Candidate causal genes were prioritized by 5 complementary methods: expression quantitative trait loci, transcriptome-wide association, fine-mapping of causal gene sets, genetically driven DNA methylation, and effects on protein structure. Gene set and tissue enrichment analyses, genetic correlation, genetic risk score analysis, and Mendelian randomization were part of the downstream analyses.ResultsThe estimated single nucleotide polymorphism (SNP)-based heritability of cluster headache was 14.5%. We identified 9 independent signals in 7 genomewide significant loci in the primary meta-analysis, and one additional locus in the trans-ethnic meta-analysis. Five of the loci were previously known. The 20 genes prioritized as potentially causal for cluster headache showed enrichment to artery and brain tissue. Cluster headache was genetically correlated with cigarette smoking, risk-taking behavior, attention deficit hyperactivity disorder (ADHD), depression, and musculoskeletal pain. Mendelian randomization analysis indicated a causal effect of cigarette smoking intensity on cluster headache. Three of the identified loci were shared with migraine. Show less
Dumont, M.; Weber-Lassalle, N.; Joly-Beauparlant, C.; Ernst, C.; Droit, A.; Feng, B.J.; ... ; Simard, J. 2022
Simple Summary Genetic variants explaining approximately 40% of familial breast cancer risk have been identified, thus leaving a significant fraction of the heritability of this disease still... Show moreSimple Summary Genetic variants explaining approximately 40% of familial breast cancer risk have been identified, thus leaving a significant fraction of the heritability of this disease still unexplained. The exact nature of this missing fraction is unknown; more extensive sequencing efforts could potentially identify new moderate-penetrance breast cancer risk alleles. The aim of this study was to perform a large-scale whole-exome sequencing study, followed by a targeted validation, in breast cancer patients and healthy women of European descent. We identified 20 novel genes with modest evidence of association (p-value < 0.05) for either overall or subtype-specific breast cancer; however, much larger studies are needed to confirm the exact role of these genes in susceptibility to breast cancer. Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes. Show less
