Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder.

paper Primary Public

Authors: Strom, Nora I; Gerring, Zachary F; Galimberti, Marco; Yu, Dongmei; Halvorsen, Matthew W; Abdellaoui, Abdel; Rodriguez-Fontenla, Cristina; Sealock, Julia M; Bigdeli, Tim; Coleman, Jonathan R; Mahjani, Behrang; Thorp, Jackson G; Bey, Katharina; Burton, Christie L; Luykx, Jurjen J; Zai, Gwyneth; Alemany, Silvia; Andre, Christine; Askland, Kathleen D; Bäckman, Julia; Banaj, Nerisa; Barlassina, Cristina; Nissen, Judith Becker; Bienvenu, O Joseph; Black, Donald; Bloch, Michael H; Børte, Sigrid; Bosch, Rosa; Breen, Michael; Brennan, Brian P; Brentani, Helena; Buxbaum, Joseph D; Bybjerg-Grauholm, Jonas; Byrne, Enda M; Cabana-Dominguez, Judit; Camarena, Beatriz; Camarena, Adrian; Cappi, Carolina; Carracedo, Angel; Casas, Miguel; Cavallini, Maria Cristina; Ciullo, Valentina; Cook, Edwin H; Crosby, Jesse; Cullen, Bernadette A; De Schipper, Elles J; Delorme, Richard; Djurovic, Srdjan; Elias, Jason A; Estivill, Xavier; Falkenstein, Martha J; Fundin, Bengt T; Garner, Lauryn; Gironda, Christina; Goes, Fernando S; Grados, Marco A; Grove, Jakob; Guo, Wei; Haavik, Jan; Hagen, Kristen; Harrington, Kelly; Havdahl, Alexandra; Höffler, Kira D; Hounie, Ana G; Hucks, Donald; Hultman, Christina; Janecka, Magdalena; Jenike, Eric; Karlsson, Elinor K; Kelley, Kara; Klawohn, Julia; Krasnow, Janice E; Krebs, Kristi; Lange, Christoph; Lanzagorta, Nuria; Levey, Daniel; Lindblad-Toh, Kerstin; Macciardi, Fabio; Maher, Brion; Mathes, Brittany; McArthur, Evonne; McGregor, Nathaniel; McLaughlin, Nicole C; Meier, Sandra; Miguel, Euripedes C; Mulhern, Maureen; Nestadt, Paul S; Nurmi, Erika L; O'Connell, Kevin S; Osiecki, Lisa; Ousdal, Olga Therese; Palviainen, Teemu; Pedersen, Nancy L; Piras, Fabrizio; Piras, Federica; Potluri, Sriramya; Rabionet, Raquel; Ramirez, Alfredo; Rauch, Scott; Reichenberg, Abraham; Riddle, Mark A; Ripke, Stephan; Rosário, Maria C; Sampaio, Aline S; Schiele, Miriam A; Skogholt, Anne Heidi; Sloofman, Laura G; Smit, Jan; Artigas, María Soler; Thomas, Laurent F; Tifft, Eric; Vallada, Homero; van Kirk, Nathanial; Veenstra-VanderWeele, Jeremy; Vulink, Nienke N; Walker, Christopher P; Wang, Ying; Wendland, Jens R; Winsvold, Bendik S; Yao, Yin; Zhou, Hang; Estonian Biobank; 23andMe Inc.; Agrawal, Arpana; Alonso, Pino; Berberich, Götz; Bucholz, Kathleen K; Bulik, Cynthia M; Cath, Danielle; Denys, Damiaan; Eapen, Valsamma; Edenberg, Howard; Falkai, Peter; Fernandez, Thomas V; Fyer, Abby J; Gaziano, J M; Geller, Dan A; Grabe, Hans J; Greenberg, Benjamin D; Hanna, Gregory L; Hickie, Ian B; Hougaard, David M; Kathmann, Norbert; Kennedy, James; Lai, Dongbing; Landén, Mikael; Hellard, Stéphanie Le; Leboyer, Marion; Lochner, Christine; McCracken, James T; Medland, Sarah E; Mortensen, Preben B; Neale, Benjamin M; Nicolini, Humberto; Nordentoft, Merete; Pato, Michele; Pato, Carlos; Pauls, David L; Piacentini, John; Pittenger, Christopher; Posthuma, Danielle; Ramos-Quiroga, Josep Antoni; Rasmussen, Steven A; Richter, Margaret A; Rosenberg, David R; Ruhrmann, Stephan; Samuels, Jack F; Sandin, Sven; Sandor, Paul; Spalletta, Gianfranco; Stein, Dan J; Stewart, S Evelyn; Storch, Eric A; Stranger, Barbara E; Turiel, Maurizio; Werge, Thomas; Andreassen, Ole A; Børglum, Anders D; Walitza, Susanne; Hveem, Kristian; Hansen, Bjarne K; Rück, Christian; Martin, Nicholas G; Milani, Lili; Mors, Ole; Reichborn-Kjennerud, Ted; Ribasés, Marta; Kvale, Gerd; Mataix-Cols, David; Domschke, Katharina; Grünblatt, Edna; Wagner, Michael; Zwart, John-Anker; Breen, Gerome; Nestadt, Gerald; Kaprio, Jaakko; Arnold, Paul D; Grice, Dorothy E; Knowles, James A; Ask, Helga; Verweij, Karin J; Davis, Lea K; Smit, Dirk J; Crowley, James J; Scharf, Jeremiah M; Stein, Murray B; Gelernter, Joel; Mathews, Carol A; Derks, Eske M; Mattheisen, Manuel
Year: 2025
Journal: Nature genetics
PMID: 40360802
DOI: 10.1038/s41588-025-02189-z
PMCID: PMC12165847
Preprint: Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder. (2025)

Fig. 1

Manhattan plot of OCD GWAS meta-analysis.The y axis represents −log10 (P values) (two sided, not adjusted for multiple testing) for the association of variants with OCD using an inverse-variance-weighted fixed-effects model (ncases = 53,660 and ncontrols = 2,044,417). The x axis shows chromosomes 1–22. The horizontal red line represents the threshold for genome-wide significance (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P=5\times {10}^{-8})$$\end{document}P=5×10−8). Index variants of genome-wide significant loci are highlighted as green diamonds.

LLM interpretation

This is a Manhattan plot showing the association of genetic variants with OCD across chromosomes 1–22. The y-axis represents $-\log_{10}(P\text{ values})$, with a horizontal red line indicating the genome-wide significance threshold of $P=5\times10^{-8}$. Several peaks exceed this threshold, with index variants of significant loci highlighted as green diamonds, most notably on chromosomes 3, 6, 11, and 12.

Fig. 2

Gene-based, tissue and cell type enrichment analyses.a, List of 25 genes that were implicated in at least two of the five different gene-based tests (significance indicated by gray dots) and passed the TWAS colocalization and/or SMR-HEIDI filters (significance indicated by orange dots). Conditionally independent (cond. ind.) genes within each locus are indicated by blue dots. b, Enrichment of OCD GWAS signal in human brain-related tissues from GTEx (version 8). No significant enrichment was observed in the peripheral tissues (not included in the figure). The horizontal bar size represents the significance of the enrichment measured using the MAGMA gene set enrichment test or partitioned LDSC. c, Top 20 groups of brain cell types (n = 35 total tested) enriched with OCD GWAS signal using MAGMA. Dots represent −log10(P values) from MAGMA gene set enrichment tests of individual neuronal cell types from Zeisel et al.30. Vertical crosses represent the mean −log10(P value) observed for each brain cell type group. Blue crosses represent a significant enrichment of OCD GWAS signals (FDR across 35 groups, FDR < 0.05), while pink crosses indicate nonsignificant enrichment. Gray points represent the association (−log10(P value)) for each single cell cluster (‘level 5’ analysis defined by Zeisel et al.30) in a given cell type (for example, excitatory neurons, cerebral cortex). CCK, cholecystokinin-expressing; R-LM, stratum radiatum-stratum lacunosum-moleculare.

LLM interpretation

This figure consists of three panels analyzing gene and cell-type enrichment for OCD GWAS signals. Panel **a** is a dot plot listing 25 genes across various genomic loci, with colored dots indicating significance across different gene-based tests (mBAT-combo, TWAS, SMR, PWAS, PsyOPS) and filters (TWAS-COLOC, SMR-HEIDI). Panel **b** is a horizontal bar chart showing the $-\log_{10}(P)$ enrichment of OCD signals in brain tissues, with the Anterior cingulate cortex showing the highest significance. Panel **c** is a scatter plot with mean markers showing the $-\log_{10}(P)$ enrichment across 35 brain cell types, where blue crosses indicate significant enrichment (FDR < 0.05), notably in several excitatory and inhibitory neuron groups.

Fig. 3

Genetic correlations (rG) between OCD and 112 phenotypes.This includes psychiatric, substance use, cognition–socioeconomic status (SES), personality, psychological, neurological, autoimmune, cardiovascular (cardiovasc.), anthropomorphic–diet, fertility and other phenotypes. References and sample sizes of the corresponding summary statistics of the GWAS studies can be found in Supplementary Table 18. The OCD summary statistics are of the main meta-analysis (ncases = 53,660 and ncontrols = 2,044,417). Error bars represent the 95% confidence intervals for the genetic correlation estimates (rG). Red circles indicate significant associations with a P value adjusted for multiple testing with the Benjamini–Hochberg procedure to control the FDR (<0.05). Black circles indicate associations that are not significant. a., after; ADHD, attention-deficit hyperactivity disorder; ALS, amyotrophic lateral sclerosis; BMI, body mass index; embarras., embarrassment; freq, frequency; fr., from; HDL, high-density lipoprotein; IQ, intelligence quotient; LDL, low-density lipoprotein; neurot., neuroticism; nr., number; PTSD, post-traumatic stress disorder; sat., satisfaction; VN, verbal-numerical.

LLM interpretation

This figure consists of two forest plots showing genetic correlations ($r_G$) between OCD and 112 phenotypes categorized into groups such as psychiatric, substance use, and neurological. The x-axis represents the genetic correlation coefficient ($r_G$), with error bars indicating 95% confidence intervals. Red circles denote associations that remain significant after Benjamini–Hochberg FDR correction ($P < 0.05$), while black circles indicate non-significant associations. Most significant positive correlations are observed within the psychiatric and personality categories.

#	Section	Preview
60	Methods — SNP and gene findings in the context of previous analyses — Overlap of previous rare coding variants in OCD and GWAS gene findings	We performed a bidirectional lookup, assessing (1) whether gene findings from our GWAS showed…
61	Methods — SNP and gene findings in the context of previous analyses — Overlap of previous rare coding variants in OCD and GWAS gene findings	First, we comprehensively assessed the overlap between 251 genes that we highlighted in our study as…
62	Methods — SNP and gene findings in the context of previous analyses — Overlap of previous rare coding variants in OCD and GWAS gene findings	Second, as Halvorsen et al.88 describe an overall excess of loss-of-function variants in OCD cases…
63	Methods — Reporting summary	Further information on research design is available in the Nature Portfolio Reporting Summary linked…
64	Online content	Any methods, additional references, Nature Portfolio reporting summaries, source data, extended…
65	Supplementary information	Supplementary InformationSupplementary Notes 1–10 and Figs. 1–43 Reporting Summary Supplementary…

Citation	PMID	DOI	Status
Adams, DM et al., Psychol. Med., 2023, Multiomic prioritisation of risk genes for anorexia nervosa	36803885	10.1017/S0033291723000235	Cited
Ahmari, SE et al., Neuropsychopharmacology, 2022, The prefrontal cortex and OCD	34400778	10.1038/s41386-021-01130-2	Cited
Ahmari, SE, Science, 2013, Repeated cortico–striatal stimulation generates persistent OCD-like behavior	23744948	10.1126/science.1234733	Cited
Als, TD, Nat. Med., 2023, Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses	37464041	10.1038/s41591-023-02352-1	Cited
Altshuler, DM, Nature, 2010, Integrating common and rare genetic variation in diverse human populations	20811451	10.1038/nature09298	Cited
Baselmans, BML, Nat. Genet., 2019, Multivariate genome-wide analyses of the well-being spectrum	30643256	10.1038/s41588-018-0320-8	Cited
Benjamini, Y et al., J. R. Stat. Soc. B, 1995, Controlling the false discovery rate: a practical and powerful approach to multiple testing	—	10.1111/j.2517-6161.1995.tb02031.x	Cited
Benner, C, Bioinformatics, 2016, FINEMAP: efficient variable selection using summary data from genome-wide association studies	26773131	10.1093/bioinformatics/btw018	Cited
Blanco-Vieira, T, Transl. Psychiatry, 2023, The genetic epidemiology of obsessive–compulsive disorder: a systematic review and meta-analysis	37380645	10.1038/s41398-023-02433-2	Cited
Boedhoe, PSW, Am. J. Psychiatry, 2018, Cortical abnormalities associated with pediatric and adult obsessive–compulsive disorder: findings from the ENIGMA Obsessive–Compulsive Disorder Working Group	29377733	10.1176/appi.ajp.2017.17050485	Cited
Bruin, WB, Transl. Psychiatry, 2020, Structural neuroimaging biomarkers for obsessive–compulsive disorder in the ENIGMA-OCD consortium: medication matters	33033241	10.1038/s41398-020-01013-y	Cited
Bryois, J, Nat. Genet., 2020, Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease	32341526	10.1038/s41588-020-0610-9	Cited
Bulik-Sullivan, BK, Nat. Genet., 2015, LD Score regression distinguishes confounding from polygenicity in genome-wide association studies	25642630	10.1038/ng.3211	Cited
Buniello, A, Nucleic Acids Res., 2019, The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019	30445434	10.1093/nar/gky1120	Cited
Burton, CL, Transl. Psychiatry, 2018, Heritability of obsessive–compulsive trait dimensions in youth from the general population	30228290	10.1038/s41398-018-0249-9	Cited
Cai, N, Nat. Genet., 2020, Minimal phenotyping yields genome-wide association signals of low specificity for major depression	32231276	10.1038/s41588-020-0594-5	Cited
Cappi, C, Biol. Psychiatry, 2020, De novo damaging DNA coding mutations are associated with obsessive–compulsive disorder and overlap with Tourette’s disorder and autism	31771860	10.1016/j.biopsych.2019.09.029	Cited
Chen, W, Genetics, 2015, Fine mapping causal variants with an approximate Bayesian method using marginal test statistics	25948564	10.1534/genetics.115.176107	Cited
Daniel, JM et al., Mol. Cell. Biol., 1999, The catenin p120ctn interacts with Kaiso, a novel BTB/POZ domain zinc finger transcription factor	10207085	10.1128/MCB.19.5.3614	Cited
Davis, LK, PLoS Genet., 2013, Partitioning the heritability of Tourette syndrome and obsessive compulsive disorder reveals differences in genetic architecture	24204291	10.1371/journal.pgen.1003864	Primary
Davis, MA et al., J. Cell Biol., 2003, A core function for p120-catenin in cadherin turnover	14610055	10.1083/jcb.200307111	Cited
de Klein, N, Nat. Genet., 2023, Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases	36823318	10.1038/s41588-023-01300-6	Cited
de Leeuw, CA et al., PLoS Comput. Biol., 2015, MAGMA: generalized gene-set analysis of GWAS data	25885710	10.1371/journal.pcbi.1004219	Cited
Debnath, M et al., Curr. Behav. Neurosci. Rep., 2018, The MHC/HLA gene complex in major psychiatric disorders: emerging roles and implications	—	10.1007/s40473-018-0155-8	Cited
Demontis, D, Nat. Genet., 2019, Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder	30478444	10.1038/s41588-018-0269-7	Cited
Demontis, D, Nat. Genet., 2023, Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains	36702997	10.1038/s41588-022-01285-8	Cited
Derks, EM et al., Nat. Genet., 2022, Ten challenges for clinical translation in psychiatric genetics	36138228	10.1038/s41588-022-01174-0	Cited
DSM-5. Diagnostic and Statistical Manual of Mental Disorders: DSM-5 237–242 (American Psychiatric Association, 2013).	—	—	—
Elsworth, B. et al. The MRC IEU OpenGWAS data infrastructure. Preprint at bioRxiv10.1101/2020.08.10.244293 (2020).	—	—	—
Fawcett, EJ et al., J. Clin. Psychiatry, 2020, Women are at greater risk of OCD than men: a meta-analytic review of OCD prevalence worldwide	32603559	10.4088/JCP.19r13085	Cited
Fernández de la Cruz, L, Mol. Psychiatry, 2017, Suicide in obsessive–compulsive disorder: a population-based study of 36 788 Swedish patients	27431293	10.1038/mp.2016.115	Cited
Finucane, HK, Nat. Genet., 2015, Partitioning heritability by functional annotation using genome-wide association summary statistics	26414678	10.1038/ng.3404	Cited
Gandal, MJ, Science, 2018, Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap	29439242	10.1126/science.aad6469	Cited
Giambartolomei, C, PLoS Genet., 2014, Bayesian test for colocalisation between pairs of genetic association studies using summary statistics	24830394	10.1371/journal.pgen.1004383	Cited
Grotzinger, AD et al., Biol. Psychiatry, 2023, Pervasive downward bias in estimates of liability-scale heritability in genome-wide association study meta-analysis: a simple solution	35973856	10.1016/j.biopsych.2022.05.029	Cited
Grotzinger, AD, Nat. Hum. Behav., 2019, Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits	30962613	10.1038/s41562-019-0566-x	Cited
Grotzinger, AD, Psychol. Med., 2021, Shared genetic architecture across psychiatric disorders	33729112	10.1017/S0033291721000829	Cited
Gusev, A, Nat. Genet., 2016, Integrative approaches for large-scale transcriptome-wide association studies	26854917	10.1038/ng.3506	Cited
Haber, SN, Dialogues, 2016, Corticostriatal circuitry	27069376	10.31887/DCNS.2016.18.1/shaber	Cited
Hall, LS, Transl. Psychiatry, 2018, Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank	29317602	10.1038/s41398-017-0034-1	Cited
Halvorsen, M, Nat. Neurosci., 2021, Exome sequencing in obsessive–compulsive disorder reveals a burden of rare damaging coding variants	34183866	10.1038/s41593-021-00876-8	Cited
Higgins, JPT et al., B, 2003, Measuring inconsistency in meta-analyses	12958120	10.1136/bmj.327.7414.557	Cited
Higgins, JPT et al., Stat. Med., 2002, Quantifying heterogeneity in a meta-analysis	12111919	10.1002/sim.1186	Cited
Hindley, G, Am. J. Psychiatry, 2022, Charting the landscape of genetic overlap between mental disorders and related traits beyond genetic correlation	36069018	10.1176/appi.ajp.21101051	Cited
Holland, D, PLoS Genet., 2020, Beyond SNP heritability: polygenicity and discoverability of phenotypes estimated with a univariate Gaussian mixture model	32427991	10.1371/journal.pgen.1008612	Cited
International Obsessive Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC) and OCD Collaborative Genetics Association Studies (OCGAS). Revealing the complex genetic architecture of obsessive–compulsive disorder using meta-analysis. Mol. Psychiatry 23, 1181–1188 (2018).10.1038/mp.2017.154PMC666015128761083	—	—	—
Ishiyama, N, Cell, 2010, Dynamic and static interactions between p120 catenin and E-cadherin regulate the stability of cell–cell adhesion	20371349	10.1016/j.cell.2010.01.017	Cited
Kia, DA, JAMA Neurol., 2021, Identification of candidate Parkinson disease genes by integrating genome-wide association study, expression, and epigenetic data sets	33523105	10.1001/jamaneurol.2020.5257	Cited
Kichaev, G et al., Am. J. Hum. Genet., 2015, Leveraging functional-annotation data in trans-ethnic fine-mapping studies	26189819	10.1016/j.ajhg.2015.06.007	Cited
Kichaev, G, PLoS Genet., 2014, Integrating functional data to prioritize causal variants in statistical fine-mapping studies	25357204	10.1371/journal.pgen.1004722	Cited
Knox, C, Nucleic Acids Res., 2024, DrugBank 6.0: the DrugBank Knowledgebase for 2024	37953279	10.1093/nar/gkad976	Cited
Lam, M, Bioinformatics, 2020, RICOPILI: Rapid Imputation for Consortias Pipeline	31393554	10.1093/bioinformatics/btz633	Cited
Lee, PH, Cell, 2019, Genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders	31835028	10.1016/j.cell.2019.11.020	Primary
Lek, M, Nature, 2016, Analysis of protein-coding genetic variation in 60,706 humans	27535533	10.1038/nature19057	Cited
Lentini, JM et al., Nat. Commun., 2020, DALRD3 encodes a protein mutated in epileptic encephalopathy that targets arginine tRNAs for 3-methylcytosine modification	32427860	10.1038/s41467-020-16321-6	Cited
Li, A, Am. J. Hum. Genet., 2023, mBAT-combo: a more powerful test to detect gene–trait associations from GWAS data	36608683	10.1016/j.ajhg.2022.12.006	Cited
Mahjani, B, Am. J. Psychiatry, 2022, The genetic architecture of obsessive–compulsive disorder: contribution of liability to OCD from alleles across the frequency spectrum	34789012	10.1176/appi.ajp.2021.21010101	Cited
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium., Cell, 2025, Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies	39814019	10.1016/j.cell.2024.12.002	Cited
Mataix-Cols, D, Mol. Psychiatry, 2018, A total-population multigenerational family clustering study of autoimmune diseases in obsessive–compulsive disorder and Tourette’s/chronic tic disorders	29133949	10.1038/mp.2017.215	Cited
Mattheisen, M, Mol. Psychiatry, 2015, Genome-wide association study in obsessive–compulsive disorder: results from the OCGAS	24821223	10.1038/mp.2014.43	Cited
Mattheisen, M. PGC OCD3 code. Figshare10.6084/m9.figshare.28451894.v1 (2025).	—	—	—
McCarthy, S, Nat. Genet., 2016, A reference panel of 64,976 haplotypes for genotype imputation	27548312	10.1038/ng.3643	Cited
Meier, SM, JAMA Psychiatry, 2016, Mortality among persons with obsessive–compulsive disorder in Denmark	26818216	10.1001/jamapsychiatry.2015.3105	Cited
Nagel, M et al., Nat. Commun., 2018, Item-level analyses reveal genetic heterogeneity in neuroticism	29500382	10.1038/s41467-018-03242-8	Cited
Olislagers, M et al., Mol. Psychiatry, 2022, Comprehensive analyses of RNA-seq and genome-wide data point to enrichment of neuronal cell type subsets in neuropsychiatric disorders	34719691	10.1038/s41380-021-01324-6	Cited
Pardiñas, AF, Nat. Genet., 2018, Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection	29483656	10.1038/s41588-018-0059-2	Cited
Pauls, DL, Am. J. Med. Genet. C Semin. Med. Genet., 2008, The genetics of obsessive compulsive disorder: a review of the evidence	18412099	10.1002/ajmg.c.30168	Cited
Piantadosi, SC, Transl. Psychiatry, 2021, Transcriptome alterations are enriched for synapse-associated genes in the striatum of subjects with obsessive–compulsive disorder	33723209	10.1038/s41398-021-01290-1	Cited
Qi, T, Nat. Commun., 2018, Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood	29891976	10.1038/s41467-018-04558-1	Cited
Romero, C, Nat. Genet., 2022, Exploring the genetic overlap between twelve psychiatric disorders	36471075	10.1038/s41588-022-01245-2	Cited
Savage, JE, Nat. Genet., 2018, Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence	29942086	10.1038/s41588-018-0152-6	Cited
Schaffer, AE, Cell, 2014, CLP1 founder mutation links tRNA splicing and maturation to cerebellar development and neurodegeneration	24766810	10.1016/j.cell.2014.03.049	Cited
Sharma, E, Front. Psychiatry, 2021, Comorbidities in obsessive–compulsive disorder across the lifespan: a systematic review and meta-analysis	34858219	10.3389/fpsyt.2021.703701	Cited
Shephard, E, Mol. Psychiatry, 2021, Toward a neurocircuit-based taxonomy to guide treatment of obsessive–compulsive disorder	33414496	10.1038/s41380-020-01007-8	Cited
Stewart, SE, Mol. Psychiatry, 2013, Genome-wide association study of obsessive–compulsive disorder	22889921	10.1038/mp.2012.85	Cited
Strom, N. I. et al. Genome-wide association study identifies new loci associated with OCD. Preprint at medRxiv10.1101/2024.03.06.24303776 (2024).	—	—	—
Strom, N. I. et al. Genome-wide association study identifies new locus associated with OCD. Preprint at medRxiv10.1101/2021.10.13.21261078 (2021).	—	—	—
Strom, N. I. et al. Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling. Preprint at medRxiv10.1101/2024.07.03.24309466 (2024).	—	—	—
Sullivan, PF, Am. J. Psychiatry, 2018, Psychiatric genomics: an update and an agenda	28969442	10.1176/appi.ajp.2017.17030283	Cited
Swedo, SE, Am. J. Psychiatry, 1998, Pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections: clinical description of the first 50 cases	9464208	10.1176/ajp.155.2.264	Cited
The 1000 Genomes Project Consortium., Nature, 2015, A global reference for human genetic variation	26432245	10.1038/nature15393	Cited
Trubetskoy, V, Nature, 2022, Mapping genomic loci implicates genes and synaptic biology in schizophrenia	35396580	10.1038/s41586-022-04434-5	Cited
Turley, P, Nat. Genet., 2018, Multi-trait analysis of genome-wide association summary statistics using MTAG	29292387	10.1038/s41588-017-0009-4	Cited
Tylee, DS, Am. J. Med. Genet. B Neuropsychiatr. Genet., 2018, Genetic correlations among psychiatric and immune-related phenotypes based on genome-wide association data	30325587	10.1002/ajmg.b.32652	Cited
van den Heuvel, OA, Eur. Neuropsychopharmacol., 2016, Brain circuitry of compulsivity	26711687	10.1016/j.euroneuro.2015.12.005	Cited
van den Heuvel, OA, Hum., 2022, An overview of the first 5 years of the ENIGMA obsessive–compulsive disorder working group: the power of worldwide collaboration	32154629	10.1002/hbm.24972	Cited
van Grootheest, DS et al., Twin Res. Hum. Genet., 2005, Twin studies on obsessive–compulsive disorder: a review	16212834	10.1375/twin.8.5.450	Cited
Vandervore, LV, Am. J. Hum. Genet., 2019, TMX2 is a crucial regulator of cellular redox state, and its dysfunction causes severe brain developmental abnormalities	31735293	10.1016/j.ajhg.2019.10.009	Cited
Virtanen, S, JAMA Netw. Open, 2022, Association of obsessive–compulsive disorder and obsessive–compulsive symptoms with substance misuse in 2 longitudinal cohorts in Sweden	35666504	10.1001/jamanetworkopen.2022.14779	Cited
Võsa, U, Nat. Genet., 2021, Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression	34475573	10.1038/s41588-021-00913-z	Cited
Wainberg, M et al., Mol. Psychiatry, 2022, Predicting causal genes from psychiatric genome-wide association studies using high-level etiological knowledge	35411039	10.1038/s41380-022-01542-6	Cited
Wallace, C, PLoS Genet., 2020, Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses	32310995	10.1371/journal.pgen.1008720	Cited
Walters, RK, Nat. Neurosci., 2018, Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders	30482948	10.1038/s41593-018-0275-1	Primary
Wang, D, Science, 2018, Comprehensive functional genomic resource and integrative model for the human brain	30545857	10.1126/science.aat8464	Cited
Wang, J, Nucleic Acids Res., 2020, CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies	31691819	10.1093/nar/gkz1026	Cited
Watanabe, K, Nat. Genet., 2019, A global overview of pleiotropy and genetic architecture in complex traits	31427789	10.1038/s41588-019-0481-0	Cited
Westwell-Roper, C, J. Child Adolesc. Psychopharmacol., 2019, Immune-related comorbidities in childhood-onset obsessive compulsive disorder: lifetime prevalence in the Obsessive Compulsive Disorder Collaborative Genetics Association Study	31170001	10.1089/cap.2018.0140	Cited
Wilbur, C, Paediatr. Child Health, 2019, PANDAS/PANS in childhood: controversies and evidence	30996598	10.1093/pch/pxy145	Cited
Willer, CJ et al., Bioinformatics, 2010, METAL: fast and efficient meta-analysis of genomewide association scans	20616382	10.1093/bioinformatics/btq340	Cited
Willsey, AJ, Neuron, 2017, De novo coding variants are strongly associated with Tourette disorder	28472652	10.1016/j.neuron.2017.04.024	Cited
Wingo, TS, Nat. Neurosci., 2021, Brain proteome-wide association study implicates novel proteins in depression pathogenesis	33846625	10.1038/s41593-021-00832-6	Cited
World Health Organization. The Global Burden of Disease: 2004 Update (WHO Press, 2008).	—	—	—
Wray, NR, Nat. Genet., 2018, Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression	29700475	10.1038/s41588-018-0090-3	Cited
Wu, J et al., Dev. Biol., 2022, Planar cell polarity and the pathogenesis of Tourette disorder: new hypotheses and perspectives	35644250	10.1016/j.ydbio.2022.05.017	Cited
Xie, X et al., Mol. Cell. Biochem., 2007, Association of LKB1 with a WD-repeat protein WDR6 is implicated in cell growth arrest and p27Kip1 induction	17216128	10.1007/s11010-006-9402-5	Cited
Yanagisawa, M, J. Biol. Chem., 2008, A p120 catenin isoform switch affects Rho activity, induces tumor cell invasion, and predicts metastatic disease	18407999	10.1074/jbc.M801192200	Cited
Yang, J et al., Am. J. Hum. Genet., 2011, GCTA: a tool for genome-wide complex trait analysis	21167468	10.1016/j.ajhg.2010.11.011	Cited
Zeisel, A, Cell, 2018, Molecular architecture of the mouse nervous system	30096314	10.1016/j.cell.2018.06.021	Cited
Zhang, T, Biol. Psychiatry, 2023, Prenatal and early childhood infections and subsequent risk of obsessive–compulsive disorder and tic disorders: a nationwide, sibling-controlled study	36155699	10.1016/j.biopsych.2022.07.004	Cited
Zhang, Y, Front. Cell Dev. Biol., 2021, Potential role of S-palmitoylation in cancer stem cells of lung adenocarcinoma	34621750	10.3389/fcell.2021.734897	Cited
Zhao, X, DNA Cell Biol., 2020, A whole-exome sequencing study of Tourette disorder in a Chinese population	31855460	10.1089/dna.2019.4746	Cited
Zhu, Z, Nat. Genet., 2016, Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets	27019110	10.1038/ng.3538	Cited

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External

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