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Significant Concordance of Genetic Variation That Increases Both the Risk The British Journal of Psychiatry (2018) 213, 430–436. doi: 10.1192/bjp.2018.62 Significant concordance of genetic variation that increases both the risk for obsessive–compulsive disorder and the volumes of the nucleus accumbens and putamen Derrek P. Hibar, Joshua W. Cheung, Sarah E. Medland, Mary S. Mufford, Neda Jahanshad, Shareefa Dalvie, Raj Ramesar, Evelyn Stewart, Odile A. van den Heuvel, David L. Pauls, James A. Knowles, Dan J. Stein, Paul M. Thompson, Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA) Consortium and International Obsessive Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC)* Background accumbens and putamen volumes. When conditioning OCD risk Many studies have identified changes in the brain associated variants on brain volume, variants influencing putamen, amyg- with obsessive–compulsive disorder (OCD), but few have dala and thalamus volumes were associated with risk for OCD. examined the relationship between genetic determinants of OCD and brain variation. Conclusions Aims These results are consistent with current OCD neurocircuitry models. Further evidence will clarify the relationship between We present the first genome-wide investigation of overlapping putamen volume and OCD risk, and the roles of the detected genetic risk for OCD and genetic influences on subcortical brain variants in this disorder. structures. Method Declaration of interest Using single nucleotide polymorphism effect concordance ana- The authors have declared that no competing interests exist. lysis, we measured genetic overlap between the first genome- wide association study (GWAS) of OCD (1465 participants with OCD, 5557 controls) and recent GWASs of eight subcortical brain Keywords volumes (13 171 participants). Genetic overlap; neuroimaging; obsessive–compulsive disorder. Results We found evidence of significant positive concordance between Copyright and usage OCD risk variants and variants associated with greater nucleus © The Royal College of Psychiatrists 2018. Obsessive–compulsive disorder (OCD) is a highly debilitating psy- subcortical brain structures. We combined data from the chiatric disorder characterised by persistent thoughts, urges and International OCD Foundation Genetics Collaborative (IOCDF- repetitive behaviours. The lifetime prevalence of OCD is estimated GC) GWAS14 and the ENIGMA GWAS of brain structure12 to to be between 1 and 3%,1 and it is thought to be among the most assess: (a) whether the same single nucleotide polymorphism impairing non-fatal illnesses in the world.2 Current neurobiological (SNP) influences both OCD and subcortical brain volume pheno- models of OCD emphasise the role of cortico–striatal–thalamic cir- types (pleiotropy), (b) whether the same SNP has the same direction cuitry in this disorder.3,4 Twin and family studies have established a of effect on OCD risk as its effect on subcortical brain volume (con- strong genetic effect in susceptibility to childhood-onset OCD (45– cordance), and (c) whether genetic variants associated with specific – 65% heritable) and in adult-onset OCD (27–47% heritable).5 8 subcortical brain volumes are significantly associated with OCD Twin studies have also indicated specific genetic contributions risk. to brain changes in OCD, although the relevant contributing – genes have not been identified.9 11 Work such as that undertaken by the Enhancing Neuro Imaging through Meta Analysis Method (ENIGMA) Consortium has, however, provided methods to identify specific genetic contributors to brain alterations. For example, a Description of original association studies recent large-scale genome-wide association study (GWAS) of mea- We obtained summary statistics from the IOCDF-GC GWAS of sures derived from structural brain magnetic resonance imaging OCD,14 which comprised three case-control populations (totalling scans of 30 717 individuals from 50 cohorts identified genetic var- 12 1465 cases of OCD and 5557 controls) combined with 299 complete iants associated with the putamen and caudate nucleus volumes. trios (which includes both parents and their OCD-diagnosed child, Few studies have integrated neurogenetic and brain imaging henceforth referred to as the proband). After removing the ancestral methods to study OCD. Prior studies mostly examined candidate 13 outliers (101 non-European trios were removed), all remaining par- genes rather than using a genome-wide approach. Here we ticipants were of European ancestry. GWAS summary statistics present the first genome-wide investigation of the overlap between were genome controlled to account for residual inflation factors the genetic risk for OCD and genetic influences on the volumes of (see Methods in Stewart et al., 201314 for complete details). Additionally, we used GWAS summary statistics from a recent, * A full author list, including all affiliations, is available as supplementary large-scale meta-analysis by the ENIGMA Consortium of subcor- material at https://doi.org/10.1192/bjp.2018.62. tical brain volumes across 50 cohorts worldwide.12 These cohorts 430 Downloaded from https://www.cambridge.org/core. 30 Sep 2021 at 07:55:05, subject to the Cambridge Core terms of use. Genetic overlap between risk of obsessive–compulsive disorder and brain structure consist of healthy controls as well as participants diagnosed with brain volume GWAS to all levels of the OCD GWAS (144 compar- neuropsychiatric disorders (including anxiety, Alzheimer’s isons in total). We tallied the number of comparisons with evidence disease, attention-deficit hyperactivity disorder, major depression, of overlap at a nominally significant level of P ≤ 0.05. To evaluate bipolar disorder, epilepsy and schizophrenia). These data further the global level of pleiotropy, we generated 10 000 permuted data comprised separate GWASs of seven subcortical brain volumes sets – containing all the possible combinations for a given brain (nucleus accumbens, amygdala, caudate nucleus, hippocampus, volume v. OCD comparison – and determined if the number of sig- globus pallidus, putamen and thalamus) and total intracranial nificance thresholds with genetic overlap was significantly greater volume (ICV) in 13 171 participants from the GWAS discovery than chance. sample. Brain volume data were extracted following a harmonised Similarly, we estimated concordance using SECA. We deter- protocol that uses validated, robust segmentation algorithms15 to mined whether or not there was a significant (P ≤ 0.05) positive ensure maximum cross-site comparability. All participants were or negative trend in the effect of the overlapping SNPs at each of of European ancestry as verified by multidimensional scaling ana- the 12 P-value thresholds using a two-sided Fisher’s exact test. lysis and GWAS test statistics were genome controlled to adjust The direction of effect for each SNP was determined by the sign for spurious inflation factors. Prior to these analyses we verified of the beta (β) of the SNP regression coefficient from each meta- that there were no participants diagnosed with OCD included in analysis. In the OCD GWAS, a positive β value for a SNP was asso- the brain volume GWASs from the ENIGMA Consortium (see ciated with an increased risk of developing OCD (a negative β value Methods in Hibar et al., 201512 and Supplementary Table 1 available indicates a protective variant). A positive β value for a SNP in a brain at https://doi.org/10.1192/bjp.2018.62). All studies were approved volume GWAS indicates that that SNP is associated with an increase by a local ethics board prior to the recruitment of participants in brain volume (a negative β value indicates a SNP is associated and all participants gave written, informed consent before with a reduction in brain volume). We estimated the global level participating. of concordance between a given brain volume phenotype and OCD by generating 10 000 permuted data sets, repeating the Post-processing of genetic data Fisher’s exact test procedure, and determined if the number of sig- nificant overlapping thresholds was significantly greater than would After applying quality control and filtering rules to the imputed be expected by chance (see Nyholt et al., 201417 for details of the OCD GWAS data, 7 658 445 SNPs remained (see supplementary SECA analysis). materials in Stewart et al., 201314 for imputation, the statistical We tested for pleiotropy and concordance between OCD and inference of SNPs that were not directly genotyped and quality all eight brain structures. Given the number of tests performed, control details). Similarly, 8 398 366 SNPs were consistently avail- we set a Bonferroni-corrected significance level at P* = 0.05/(2 * 8) = able for all eight brain structures after applying quality control − 3.13 × 10 3. and filtering rules to the imputed brain volume GWAS data (see Methods in Hibar et al., 201512 for imputation and quality control details). To statistically compare the OCD and eight brain volume Conditional false discovery rate to detect OCD risk GWASs, we used the 6 946 379 overlapping SNPs that passed variants quality control and filtering rules in all data sets. We also examined if conditioning the OCD GWAS results on With these data, we performed a clumping procedure in genetic variants that influence brain volume could improve our PLINK16 to identify an independent SNP from every linkage dis- ability to detect variants associated with OCD.18 For a given equilibrium (LD) block across the genome. The clumping procedure brain-volume phenotype, we selected subsets of SNPs at 14 false dis- − − was performed separately for each of the eight brain volume GWASs covery rate (FDR) thresholds with q-values ≤ (1 × 10 5,1×10 4, − using an 800 kb window, with SNPs in LD (r2 > 0.25), in the 1×10 3, 0.01, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1) and looked European reference samples from the 1000 Genomes Project up the corresponding P-values for each SNP subset in the OCD (Phase 1, version 3) (http://www.internationalgenome.org/). The GWAS. We then applied the FDR method19 to each subset of SNP with the lowest P-value within each LD block was selected as P-values in the OCD GWAS.
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