6 CHAPTER 6 118 fulfilling the screening criteria were asked to complete an extended questionnaire that focused on signs and symptoms of CH as outlined in the International Classification of Headache Disorders III (ICHD-III) criteria for CH.5 Individual diagnoses were made upon visiting the outpatient clinic or using an validated algorithm (positive predictive value: ∼92%) based on ICHD criteria.15 CH cases were diagnosed in specialized headache centers to minimize misclassification. Controls (n = 1,671) were obtained from the Netherlands Epidemiology of Obesity Study (NEO) study,16 a population-based sample that includes individuals aged 45-65 years living in a nearby municipality (Leiderdorp, The Netherlands) recruited between 2008 and 2012. Most cases and all controls originated from the same geographical region, in the Western part of the Netherlands. All participants were unrelated and of European ancestry. The local ethics committees approved the study. Written informed consent was obtained from all participants. Genotyping, quality control, and imputation in the discovery stage Genomic DNA was extracted from peripheral blood leukocytes according to standard protocols and genotyping of both cases and controls was performed using the Illumina Infinium CoreExome-24 v1.1 array according to the protocol from the manufacturer. Cases were genotyped at the GenomicsCore Facility at the Norwegian University of Science and Technology (Trondheim, Norway) and controls at the Centre National de Génotypage (Paris, France). For the cases, variant calling was performed with Genome Studio 2.0 following a standard quality protocol,17 and the CHARGE best practice calling of the HumanExome Bead chip.18 For the controls, calling was performed using the GenCall algorithm using standard settings as provided by Illumina. Quality control (QC) was performed according to standard procedures.19 Markers with high missingness rates (≥ 2%), monomorphic variants and those failing the Hardy-Weinberg equilibrium were excluded. Individuals were excluded if they had a high proportion of missing genotype data (≥ 2%), inconsistent sex information, were related (PI-HAT ≥ 0.2), or were heterozygosity outliers. Principal component analysis (PCA) was performed on the pruned data set (with a 50-kb sliding window, r2 > 0.2) using PLINK and population outliers were excluded. No overt population substructure between cases and controls was observed (data not shown). After combining the genotyped SNP information from LUCA and NEO, imputation was performed on the Michigan Imputation Server (https:// imputationserver.sph.umich.edu/) using Haplotype Reference Consortium (HRC v1.1 2016) as a reference panel after phasing by Eagle (v2.3),20 using the default parameters. In total 345,064 SNPs from 2,297 individuals (840 cases and 1,457 controls) were available for imputation. Prior to analyses, variants with MAF ≤ 0.01 or imputation INFO score ≤ 0.6 were excluded, resulting in 7,578,399 SNPs available for analysis. Statistical analysis in the discovery stage Case-control SNP association analysis was performed using a logistic regression model implemented in SNPTEST (v2.5.2) for autosomal variants, with case-control status as outcome and assuming
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