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Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis
Open accessAbstract
Background Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia.Methods We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33,332 cases and 27,888 controls of European ancestory. To characterise allelic effects on each disorder, we applied a multinomial logistic regression procedure with model selection to identify the best-fitting model of relations between genotype and phenotype. We examined cross-disorder effects of genome-wide significant loci previously identified for bipolar disorder and schizophrenia, and used polygenic risk-score analysis to examine such effects from a broader set of common variants. We undertook pathway analyses to establish the biological associations underlying genetic overlap for the five disorders. We used enrichment analysis of expression quantitative trait loci (eQTL) data to assess whether SNPs with cross-disorder association were enriched for regulatory SNPs in post-mortem brain-tissue samples.Findings SNPs at four loci surpassed the cutoff for genome-wide significance (p<5×10(-8)) in the primary analysis: regions on chromosomes 3p21 and 10q24, and SNPs within two L-type voltage-gated calcium channel subunits, CACNA1C and CACNB2. Model selection analysis supported effects of these loci for several disorders. Loci previously associated with bipolar disorder or schizophrenia had variable diagnostic specificity. Polygenic risk scores showed cross-disorder associations, notably between adult-onset disorders. Pathway analysis supported a role for calcium channel signalling genes for all five disorders. Finally, SNPs with evidence of cross-disorder association were enriched for brain eQTL markers.Interpretation Our findings show that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset. In particular, variation in calcium-channel activity genes seems to have pleiotropic effects on psychopathology. These results provide evidence relevant to the goal of moving beyond descriptive syndromes in psychiatry, and towards a nosology informed by disease cause.Funding National Institute of Mental Health.
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“Interestingly, common genetic factors contributing to depression and autism have been reported (45, 46).”
From Gene × Environment Interactions in Autism Spectrum Disorders: Role of Epigenetic Mechanisms (2014) · cites this paper as [46]
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“On the basis of data from genomewide association studies (GWAS), approximately 40% of the heritability of ADHD can be attributed to numerous common genetic variants 37 .”
From Attention-deficit/hyperactivity disorder (2015) · cites this paper as [37]
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“They include unhealthy lifestyle, poorer (self)care adherence, medication side effects, shared pathophysiology including e.g. upregulation of immune-endocrine stress systems and genetic pleiotropy (see 39, 247 for a review that gives more details).”
From Major depressive disorder (2016) · cites this paper as [39]
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“Furthermore, combined GWAS of ADHD, autism spectrum disorders, depression, bipolar disorder and schizophrenia identified four genome-wide significant loci shared by these disorders 37 .”
From Attention-deficit/hyperactivity disorder (2015) · cites this paper as [37]
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In the citing paper
“We suggest that although selfmedication plays a part in the co-occurrence of mental health disorders and substance-related disorders, a shared liability between the disorders likewise plays a role.”
From Childhood Psychiatric Disorders as Risk Factor for Subsequent Substance Abuse: A Meta-Analysis. (2017) · cites this paper as [64]
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“Given the significant genetic overlap between various psychiatric conditions and ASD, heritability likely contributes to these relationships (53–55).”
From Maternal Psychiatric Conditions, Treatment With Selective Serotonin Reuptake Inhibitors, and Neurodevelopmental Disorders (2021) · cites this paper as [54]
In the citing paper
“Recent findings suggest the possibility that not only single, but also aggregate molecular genetic risk factors, linked in particular to alterations in calcium-channel signaling, are shared between autism and four other psychiatric disorders (schizophrenia, attention-deficit hyperactivity disorder, bipolar disorder, and major depressive disorder) (45, 46).”
From Gene × Environment Interactions in Autism Spectrum Disorders: Role of Epigenetic Mechanisms (2014) · cites this paper as [46]
In the citing paper
“Studies with full genomic analyses of tens or even hundreds of thousands of participants sometimes identify cumulatively meaningful genetic risk factors, but they involve hundreds if not thousands of alleles, the specific functions of which are often not understood (Crespi, 2020; Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013).”
From A process-based approach to psychological diagnosis and treatment:The conceptual and treatment utility of an extended evolutionary meta model (2020) · cites this paper as Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013
In the citing paper
“High levels of psychiatric comorbidity and heterogeneity, fluid symptom trajectories, cross-diagnostic overlap in genetic and neurobiological factors, and the limited efficacy of many psychiatric treatments restrict our understanding of the neurobiology of mental illness based on categorical diagnoses [3–6].”
From Toward a neurocircuit-based taxonomy to guide treatment of obsessive-compulsive disorder (2021) · cites this paper as [4]
In the citing paper
“We note that the most significant pathway identified from the PGC cross-disorder analysis3 (GO:0005262, calcium channel activity) also showed nominally significant enrichment in our analysis, confirming a role for calcium channel activity in these disorders.”
From Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways (2015) · cites this paper as [3]
In the citing paper
“has also shown clear evidence of shared genetic risk at individual loci3”
From Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways (2015) · cites this paper as [3]
In the citing paper
“the most significant pathway (GO:0005262, calcium channel activity) from the previous PGC Cross Disorder group SNP-based meta-analysis GWAS3 across the five disorders was found to show nominally significant association in our pathway level meta-analysis across all five disorders (P = 3.13 × 10−3) and also in SCZ, MDD and BIP (P = 8.07 × 10−3).”
From Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways (2015) · cites this paper as [3]
In the citing paper
“Stringent and standardized quality control procedures were applied as previously described3.”
From Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways (2015) · cites this paper as [3]
In the citing paper
“However, evidence is increasing that inflammation and specifically cytokine signaling play a role in the pathophysiology of psychiatric disorders.”
From Cytokine Research in Depression: Principles, Challenges, and Open Questions (2019) · cites this paper as [118]
In the citing paper
“There is considerable evidence that genetic risk factors for psychiatric disorders are closely related to cytokines or other functions of the immune system.”
From Cytokine Research in Depression: Principles, Challenges, and Open Questions (2019) · cites this paper as [118]
In the citing paper
“Genome-wide association studies (GWAS) have identified immune pathway genes that significantly contribute to the risk of psychiatric disorders (118).”
From Cytokine Research in Depression: Principles, Challenges, and Open Questions (2019) · cites this paper as [118]
In the citing paper
“Alterations in other genes implicated in E/T coupling have been observed before in ASD individuals and include Ca2+ signaling components such as the voltage-dependent channels Cav1.2 (CACNA1C), Cav1.3 (CACNA1D) and the α-δ auxiliary subunit of L-type voltage-gated Ca2+ channels (CACNA2D3) [102, 103].”
In the citing paper
“Several reports have now confirmed an association between the LTCC CACNA1C gene and neurodevelopmental disorders25,58.”
From Neuronal defects in a human cellular model of 22q11.2 deletion syndrome (2020) · cites this paper as [25]
In the citing paper
“Biological links such as single nucleotide polymorphisms (4,5), brain structure (6,7), or functional connectivity (8,9) to specific disorders are limited.”
From Methods and challenges for assessing heterogeneity (2020) · cites this paper as [5]
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Citations
Cites
Model selection and multimodel inference: a practical information-theoretic approach.
Guthery, F. S., Burnham, K. P., & Anderson, D. R. (2003) · The Journal of Wildlife Management · doi:10.2307/3802723 · Cited by 41,495
Common polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
Lichtenstein, P., Yip, B. H., Björk, C., Pawitan, Y., Cannon, T. D., Sullivan, P. F., & Hultman, C. M. (2009) · The Lancet · doi:10.1016/s0140-6736(09)60072-6 · Cited by 2,125
Genome-wide association study identifies five new schizophrenia loci
The Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (2011) · Nature Genetics · doi:10.1038/ng.940 · Cited by 1,919
Psychiatric GWAS Consortium Bipolar Disorder Working Group, Sklar, P., Ripke, S., Scott, L. J., Andreassen, O. A., Cichon, S., Craddock, N., Edenberg, H. J., Nurnberger, J. I., Rietschel, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.943 · Cited by 1,344
Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS
Nicolae, D. L., Gamazon, E., Zhang, W., Duan, S., Dolan, M. E., & Cox, N. J. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000888 · Cited by 1,292
Wellcome Trust Case Control Consortium, Ferreira, M. A. R., O'Donovan, M. C., Meng, Y. A., Jones, I. R., Ruderfer, D. M., Jones, L., Fan, J., Kirov, G., Perlis, R. H., et al. (2008) · Nature Genetics · doi:10.1038/ng.209 · Cited by 1,237
Population genomics of human gene expression
Stranger, B. E., Nica, A. C., Forrest, M. S., Dimas, A. S., Bird, C., Beazley, C., Ingle, C., Dunning, M., Flicek, P., Koller, D., et al. (2007) · Nature Genetics · doi:10.1038/ng2142 · Cited by 1,153
A mega-analysis of genome-wide association studies for major depressive disorder
Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, Ripke, S., Wray, N. R., Lewis, C. M., Hamilton, S. P., Weissman, M. M., Breen, G., Byrne, E. M., Blackwood, D. H. R., Boomsma, D. I., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.21 · Cited by 1,120
Identification of loci associated with schizophrenia by genome-wide association and follow-up
Molecular Genetics of Schizophrenia Collaboration, O'Donovan, M. C., Craddock, N., Norton, N., Williams, H., Peirce, T., Moskvina, V., Nikolov, I., Hamshere, M., Carroll, L., et al. (2008) · Nature Genetics · doi:10.1038/ng.201 · Cited by 1,070
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Munafo, M. R., Zammit, S., & Jonathan Flint, C. (2014) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12261 · Cited by 51
Does Biology Transcend the Symptom-based Boundaries of Psychosis?
Pearlson, G. D., Clementz, B. A., Sweeney, J. A., Keshavan, M. S., & Tamminga, C. A. (2016) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2016.01.001 · Cited by 51
Srivastava, R., Faust, T. E., Ramos, A., Ishizuka, K., & Sawa, A. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.01.007 · Cited by 52
Vinberg, M., Ottesen, N. M., Meluken, I., Sørensen, N., Pedersen, O. B., Kessing, L. V., & Miskowiak, K. W. (2018) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.12976 · Cited by 50
Recent Advances in Understanding the Genetic Architecture of Autism
Dias, C., & Walsh, C. A. (2020) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-121219-082309 · Cited by 56
MAOA Variants and Genetic Susceptibility to Major Psychiatric Disorders
Liu, Z., Huang, L., Luo, X., Wu, L., & Li, M. (2015) · Molecular Neurobiology · doi:10.1007/s12035-015-9374-0 · Cited by 51
Lee, P. H., Anttila, V., Won, H., Feng, Y. A., Rosenthal, J., Zhu, Z., Tucker–Drob, E. M., Nivard, M. G., Grotzinger, A. D., Posthuma, D., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/528117 · Cited by 51
Demontis, D., Walters, R. K., Rajagopal, V. M., Waldman, I. D., Grove, J., Als, T. D., Dalsgaard, S., Ribasés, M., Bybjerg-Grauholm, J., Bækvad-Hansen, M., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-20443-2 · Cited by 50
Emsell, L., Chaddock, C., Forde, N. J., Hecke, W. V., Barker, G. J., Leemans, A., Sunaert, S. G., Walshe, M., Bramon, E., Cannon, D. M., et al. (2013) · Psychological Medicine · doi:10.1017/s0033291713002845 · Cited by 50
Polygenic Risk Scores: What Are They Good For?
Zheutlin, A. B., & Ross, D. A. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.04.007 · Cited by 49
Namkung, H., Yukitake, H., Fukudome, D., Lee, B. J., Tian, M., Ursini, G., Saito, A., Lam, S., Kannan, S., Srivastava, R., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.10.031 · Cited by 51
Grezenko, H., Ekhator, C., Nwabugwu, N. U., Ganga, H., Affaf, M., Abdelaziz, A., Rehman, A., Shehryar, A., Abbasi, F. A., Bellegarde, S. B., et al. (2023) · Cureus · doi:10.7759/cureus.43960 · Cited by 55
Implications of pleiotropy: challenges and opportunities for mining Big Data in biomedicine
Yang, C., Li, C., Wang, Q., Chung, D., & Zhao, H. (2015) · Frontiers in Genetics · doi:10.3389/fgene.2015.00229 · Cited by 51
A comprehensive meta-analysis of common genetic variants in autism spectrum conditions
Warrier, V., Chee, V., Smith, P. L., Chakrabarti, B., & Baron‐Cohen, S. (2015) · Molecular Autism · doi:10.1186/s13229-015-0041-0 · Cited by 55
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Donaldson, Z. R., & Hen, R. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.02.004 · Cited by 52
Koiliari, E., Roussos, P., Pasparakis, E., Lencz, T., Malhotra, A., Siever, L., Giakoumaki, S., & Bitsios, P. (2014) · Schizophrenia Research · doi:10.1016/j.schres.2014.02.017 · Cited by 52
Sakamoto, K., & Crowley, J. J. (2017) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32554 · Cited by 52
Clementz, B. A., Trotti, R. L., Pearlson, G. D., Keshavan, M. S., Gershon, E. S., Keedy, S., Ivleva, E. I., McDowell, J. E., & Tamminga, C. A. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.03.011 · Cited by 49
Lancaster, T. M., Linden, D. E., Tansey, K. E., Banaschewski, T., Bokde, A. L. W., Bromberg, U., Büchel, C., Cattrell, A., Conrod, P. J., Flor, H., et al. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2016.1135 · Cited by 49
Breitenkamp, A. F. S., Matthes, J., Nass, R. D., Sinzig, J., Lehmkuhl, G., Nürnberg, P., & Herzig, S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095579 · Cited by 49
Ryan, J. L., Artéro, S., Carrière, I., Maller, J. J., Meslin, C., Ritchie, K. A., & Ancelin, M. (2015) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2015.08.022 · Cited by 49
Identifying common genome-wide risk genes for major psychiatric traits
Liu, S., Rao, S., Xu, Y. J., Li, J., Huang, H., Zhang, X., Fu, H. Q., Wang, Q., Cao, H., Baranova, A. V., et al. (2019) · Human Genetics · doi:10.1007/s00439-019-02096-4 · Cited by 49
Explicit Modeling of Ancestry Improves Polygenic Risk Scores and BLUP Prediction
Chen, C., Han, J., Hunter, D. J., Kraft, P. L., & Price, A. L. (2015) · Genetic Epidemiology · doi:10.1002/gepi.21906 · Cited by 46
GWAS meta analysis identifies TSNARE1 as a novel Schizophrenia / Bipolar susceptibility locus
Abou‐Sleiman, P. M., Wang, D., Glessner, J., Hadley, D., Gur, R. E., Cohen, N., Li, Q. S., Hakonarson, H. H., the Janssen-CHOP Neuropsychiatric Genomics Working Group, Abou‐Sleiman, P. M., et al. (2013) · Scientific Reports · doi:10.1038/srep03075 · Cited by 49
Excitation-Inhibition Discoordination in Rodent Models of Mental Disorders
Fenton, A. A. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.03.013 · Cited by 49
Schizophrenia biomarkers: Translating the descriptive into the diagnostic
Pickard, B. S. (2015) · Journal of Psychopharmacology · doi:10.1177/0269881114566631 · Cited by 52
Zhang, B., Seigneur, E. M., Wei, P., Gökçe, Ö., Morgan, J., & Südhof, T. C. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.157 · Cited by 49
The Yin and Yang of Autism Genetics: How Rare De Novo and Common Variations Affect Liability
Chaste, P., Roeder, K., & Devlin, B. (2017) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-083115-022647 · Cited by 54
Hackinger, S., Trajanoska, K., Styrkársdóttir, U., Zengini, E., Steinberg, J., Ritchie, G. R. S., Hatzikotoulas, K., Gilly, A., Εvangelou, Ε., Kemp, J. P., et al. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx285 · Cited by 53
Garcez, M. L., Jacobs, K. R., & Guillemin, G. J. (2019) · Neurotoxicity Research · doi:10.1007/s12640-019-00057-3 · Cited by 51
Imamura, A., Morimoto, Y., Ono, S., Kurotaki, N., Kanegae, S., Yamamoto, N., Kinoshita, H., Tsujita, T., Okazaki, Y., & Ozawa, H. (2020) · Journal of Neural Transmission · doi:10.1007/s00702-020-02188-w · Cited by 53
Kember, R. L., Merikangas, A. K., Verma, S. S., Verma, A., Judy, R., Abecasis, G. R., Baras, A., Cantor, M., Coppola, G., Economides, A. N., et al. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.06.026 · Cited by 48
Transdiagnostic time‐varying dysconnectivity across major psychiatric disorders
Li, C. R., Dong, M., Womer, F. Y., Han, S., Yin, Y., Jiang, X., Wei, Y., Duan, J., Feng, R., Zhang, L., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25285 · Cited by 49
Genome-wide association studies of suicidal behaviors: a review
Sokolowski, M., Wasserman, J., & Wasserman, D. (2014) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2014.08.006 · Cited by 48
Photoperiodic and circadian bifurcation theories of depression and mania
Kripke, D. F., Elliott, J. A., Welsh, D. K., & Youngstedt, S. D. (2015) · F1000Research · doi:10.12688/f1000research.6444.1 · Cited by 48
Genetic architecture for human aggression: A study of gene–phenotype relationship in OMIM
Zhang‐James, Y., & Faraone, S. V. (2016) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32363 · Cited by 48
Genetics of eating disorders in the genome-wide era
Watson, H. J., Palmos, A. B., Hunjan, A. K., Baker, J. H., Yılmaz, Z., & Davies, H. L. (2021) · Psychological Medicine · doi:10.1017/s0033291720005474 · Cited by 52
Genetic Moderation of Stress Effects on Corticolimbic Circuitry
Bogdan, R., Pagliaccio, D., Baranger, D. A. A., & Hariri, A. R. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.216 · Cited by 53
McOmish, C. E., Burrows, E. L., & Hannan, A. J. (2014) · British Journal of Pharmacology · doi:10.1111/bph.12783 · Cited by 48
Challenges in understanding psychiatric disorders and developing therapeutics: a role for zebrafish
McCammon, J. M., & Sive, H. L. (2015) · Disease Models & Mechanisms · doi:10.1242/dmm.019620 · Cited by 51
Kim, Y. S., & State, M. W. (2014) · International Journal of Epidemiology · doi:10.1093/ije/dyu037 · Cited by 50
Transcriptomics analysis of iPSC-derived neurons and modeling of neuropsychiatric disorders
Lin, M., Lachman, H. M., & Zheng, D. (2015) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2015.11.009 · Cited by 48
GWIS: Genome-Wide Inferred Statistics for Functions of Multiple Phenotypes
Nieuwboer, H. A., Pool, R., Dolan, C. V., Boomsma, D. I., & Nivard, M. G. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.07.020 · Cited by 44
Effects of environmental risks and polygenic loading for schizophrenia on cortical thickness
Neilson, E., Bois, C., Gibson, J., Duff, B. J., Watson, A., Roberts, N., Brandon, N. J., Dunlop, J., Hall, J., McIntosh, A. M., et al. (2016) · Schizophrenia Research · doi:10.1016/j.schres.2016.12.011 · Cited by 48
Molecular mechanisms underlying noncoding risk variations in psychiatric genetic studies
Xiao, X., Chang, H., & Li, M. (2017) · Molecular Psychiatry · doi:10.1038/mp.2016.241 · Cited by 51
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Ling, T.-Y., Wang, X.-L., Chai, Q., Lü, T., Stulak, J. M., Joyce, L. D., Daly, R. C., Greason, K. L., Wu, L.-Q., Shen, W.-K., et al. (2017) · BBA Clinical · doi:10.1016/j.bbacli.2017.02.002 · Cited by 49
Hopp, S. C. (2020) · Journal of Neuroscience Research · doi:10.1002/jnr.24585 · Cited by 50
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van den Oord, E. J. C. G., Clark, S. L., Xie, L. Y., Shabalin, A. A., Dozmorov, M. G., Kumar, G., Swedish Schizophrenia Consortium, Vladimirov, V. I., Magnusson, P. K. E., & Aberg, K. A. (2016) · Schizophrenia Bulletin · doi:10.1093/schbul/sbv182 · Cited by 47
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Osborne, A. J., Pearson, J. F., Noble, A. J., Gemmell, N. J., Horwood, L. J., Boden, J. M., Benton, M. C., Macartney-Coxson, D. P., & Kennedy, M. A. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0800-3 · Cited by 47
SNAP25 Is Associated With Schizophrenia and Major Depressive Disorder in the Han Chinese Population
Wang, Q., Wang, Y., Ji, W., Zhou, G., He, K., Li, Z., Chen, J., Li, W., Wen, Z., Shen, J., et al. (2015) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.13m08962 · Cited by 48
The XY gene hypothesis of psychosis: Origins and current status
Crow, T. J. (2013) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32202 · Cited by 47
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Gariup, M., González, A., Lázaro, L., Torres, F., Serra‐Pages, C., & Morer, Á. (2015) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2015.08.017 · Cited by 47
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Modai, S., & Shomron, N. (2016) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2016.01.006 · Cited by 48
Personality as an intermediate phenotype for genetic dissection of alcohol use disorder
Oreland, L., Lagravinese, G., Toffoletto, S., Nilsson, K. W., Harro, J., Cloninger, C. R., & Comasco, E. (2017) · Journal of Neural Transmission · doi:10.1007/s00702-016-1672-9 · Cited by 49
Fabbri, C., Corponi, F., Albani, D., Raimondi, I., Forloni, G., Schruers, K. R. J., Kasper, S. F., Kautzky, A., Zohar, J., Souery, D., et al. (2017) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2017.10.005 · Cited by 48
Song, J., Kuja‐Halkola, R., Sjölander, A., Bergen, S. E., Larsson, H., Landén, M., & Lichtenstein, P. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.11.014 · Cited by 48
Zhu, Z., Anttila, V., Smoller, J. W., & Lee, P. H. (2018) · PLOS ONE · doi:10.1371/journal.pone.0193256 · Cited by 47
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Common gray and white matter abnormalities in schizophrenia and bipolar disorder
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A structural brain network of genetic vulnerability to psychiatric illness
Taquet, M., Smith, S. M., Prohl, A. K., Peters, J. M., Warfield, S. K., Scherrer, B., & Harrison, P. J. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0723-7 · Cited by 49
Hinney, A., Albayrak, Ö., Antel, J., Volckmar, A., Sims, R., Chapman, J., Harold, D., Gerrish, A., Heid, I. M., Winkler, T. W., et al. (2014) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32234 · Cited by 46
Marta Ribasés, A., Mitjans, M., Hartman, C. A., Artigas, M. S., Demontis, D., Larsson, H., Ramos‐Quiroga, J. A., Kuntsi, J., Faraone, S. V., Ad, B., et al. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105313 · Cited by 49
Jeppesen, P., Larsen, J. T., Clemmensen, L., Munkholm, A., Rimvall, M. K., Rask, C. U., van Os, J., Petersen, L. V., & Skovgaard, A. M. (2014) · Schizophrenia Bulletin · doi:10.1093/schbul/sbu167 · Cited by 48
Genetic psychophysiology: Advances, problems, and future directions
Anokhin, A. P. (2014) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2014.04.003 · Cited by 49
Gene X Environment Interactions in Schizophrenia and Bipolar Disorder: Evidence from Neuroimaging
Geoffroy, P. A., Étain, B., & Houenou, J. (2013) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2013.00136 · Cited by 47
Higgins, G. A., Allyn-Feuer, A., Barbour, E., & Athey, B. D. (2015) · Pharmacogenomics · doi:10.2217/pgs.15.106 · Cited by 46
Evidence-based psychotherapies II: changes in models of treatment and treatment delivery
Kazdin, A. E. (2014) · South African Journal of Psychology · doi:10.1177/0081246314538733 · Cited by 52
Garn, H., Bahn, S., Baune, B. T., Binder, E. B., Bisgaard, H. F., Chatila, T. A., Chavakis, T., Culmsee, C., Dannlowski, U., Gay, S., et al. (2016) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2016.02.046 · Cited by 46
Steen, V. M., Skrede, S., Polushina, T. V., López, M., Andreassen, O. A., Fernø, J., & Hellard, S. L. (2016) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2016.07.011 · Cited by 48
Foley, S. F., Bracher‐Smith, M., Tansey, K. E., Harrison, J. R., Parker, G. D., & Caseras, X. (2018) · The British Journal of Psychiatry · doi:10.1192/bjp.2018.101 · Cited by 46
Gene × Environment Interaction in Developmental Disorders: Where Do We Stand and What’s Next?
Esposito, G., Azhari, A., & Borelli, J. L. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.02036 · Cited by 48
McCarthy, M. J. (2018) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000215 · Cited by 49
Jiang, X., Detera‐Wadleigh, S. D., Akula, N., Mallon, B. S., Hou, L., Xiao, T., Felsenfeld, G., Gu, X., & McMahon, F. J. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0207-1 · Cited by 47
Domingue, B. W., Liu, H., Okbay, A., & Belsky, D. W. (2017) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2017.16111209 · Cited by 48
Ghoshal, A., Uygun, D. S., Yang, L., McNally, J. M., López-Huerta, V. G., Arias-García, M. A., Báez-Nieto, D., Allen, A., Fitzgerald, M. L., Choi, S., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0685-1 · Cited by 44
Neuronal α2δ proteins and brain disorders
Ablinger, C., Geisler, S. M., Stanika, R. I., Klein, C., & Obermair, G. J. (2020) · Pflügers Archiv - European Journal of Physiology · doi:10.1007/s00424-020-02420-2 · Cited by 48
Gleason, K. J., Yang, F., Pierce, B. L., He, X., & Chen, L. (2020) · Genome biology · doi:10.1186/s13059-020-02125-w · Cited by 45
Harrison, P. J., Husain, S. M., Lee, H., Angeles, A. D. L., Colbourne, L., Mould, A. W., Hall, N., Haerty, W., & Tunbridge, E. M. (2022) · Neuropharmacology · doi:10.1016/j.neuropharm.2022.109262 · Cited by 45
Knott, S., Forty, L., Craddock, N. J., & Thomas, R. H. (2015) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2015.07.003 · Cited by 50
López‐Solà, C., Fontenelle, L. F., Bui, M., Hopper, J. L., Pantelis, C., Yücel, M., Menchón, J. M., Alonso, P., & Harrison, B. J. (2015) · The British Journal of Psychiatry · doi:10.1192/bjp.bp.114.156281 · Cited by 45
Sense and specificity in neuronal calcium signalling
Burgoyne, R. D., & Haynes, L. P. (2014) · Biochimica et Biophysica Acta (BBA) - Molecular Cell Research · doi:10.1016/j.bbamcr.2014.10.029 · Cited by 46
Lee, H., Dvořák, D., & Fenton, A. A. (2014) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2014.00015 · Cited by 45
Heterogeneity and Individuality: microRNAs in Mental Disorders
Hommers, L. G., Domschke, K., & Deckert, J. (2014) · Journal of Neural Transmission · doi:10.1007/s00702-014-1338-4 · Cited by 45
Larimore, J. L., Ryder, P. V., Kim, K., Ambrose, L. A., Chapleau, C. A., Calfa, G. D., Groß, C., Bassell, G. J., Pozzo‐Miller, L. D., Smith, Y., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0065069 · Cited by 45
Genome-wide association study of paliperidone efficacy
Li, Q. S., Wineinger, N. E., Fu, D., Libiger, O., Alphs, L. D., Savitz, A. J., Gopal, S., Cohen, N., & Schork, N. J. (2016) · Pharmacogenetics and Genomics · doi:10.1097/fpc.0000000000000250 · Cited by 45
The contribution of alternative splicing to genetic risk for psychiatric disorders
Reble, E., Dineen, A., & Barr, C. L. (2017) · Genes Brain & Behavior · doi:10.1111/gbb.12430 · Cited by 47
Heritability of obsessive–compulsive trait dimensions in youth from the general population
Burton, C. L., Park, L. S., Corfield, E. C., Forget‐Dubois, N., Dupuis, A., Sinopoli, V. M., Shan, J., Goodale, T., Shaheen, S. ‐., Crosbie, J., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0249-9 · Cited by 48
Caly, H., Rabiei, H., Coste-Mazeau, P., Sébastien, H., Alain, S., Eyraud, J., Chianéa, T., Caly, C., Makowski, D., Hadjikhani, N. K., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-86320-0 · Cited by 48
Genetics of age-at-onset in major depression
Harder, A., Nguyen, T.-D., Pasman, J. A., Mosing, M. A., Hägg, S., & Lu, Y. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-01888-z · Cited by 50
Kaufman, J., Gelernter, J. E., Hudziak, J. J., Tyrka, A. R., & Coplan, J. D. (2015) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2015.06.001 · Cited by 46
Martin, A. K., Robinson, G. A., Dzafic, I., Reutens, D. C., & Mowry, B. J. (2013) · Genes Brain & Behavior · doi:10.1111/gbb.12066 · Cited by 52
A rare WNT1 missense variant overrepresented in ASD leads to increased Wnt signal pathway activation
Martin, P.-M., Yang, X., Robin, N. C., Lam, E. T., Rabinowitz, J. S., Erdman, C. A., Quinn, J. F., Weiss, L. A., Hamilton, S. P., Kwok, P.-Y., et al. (2013) · Translational Psychiatry · doi:10.1038/tp.2013.75 · Cited by 44
New Developments in the Genetics of Bipolar Disorder
Shinozaki, G., & Potash, J. B. (2014) · Current Psychiatry Reports · doi:10.1007/s11920-014-0493-5 · Cited by 52
Robinson, E., Kirby, A. W., Ruparel, K., Yang, J., McGrath, L. M., Anttila, V., Neale, B. M., Merikangas, K. R., Lehner, T., Abou‐Sleiman, P. M., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2014.65 · Cited by 43
Specific Roles of NMDA Receptor Subunits in Mental Disorders
Yamamoto, H., Hagino, Y., Kasai, S., & Ikeda, K. (2015) · Current Molecular Medicine · doi:10.2174/1566524015666150330142807 · Cited by 48
Shared functional defect in IP3R-mediated calcium signaling in diverse monogenic autism syndromes
Schmunk, G., Boubion, B., Smith, I. F., Parker, I., & Gargus, J. J. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.123 · Cited by 44
Kim, M. J., Biag, J. D., Fass, D. M., Lewis, M. C., Zhang, Q., Fleishman, M., Gangwar, S. P., Machius, M., Fromer, M., Purcell, S., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.98 · Cited by 43
Schmunk, G., Nguyen, R. L., Ferguson, D. L., Kumar, K., Parker, I., & Gargus, J. J. (2017) · Scientific Reports · doi:10.1038/srep40740 · Cited by 44
Kim, D. S., Burt, A., Ranchalis, J., Wilmot, B., Smith, J. D., Patterson, K., Coe, B. P., Li, Y. K., Bamshad, M. J., Nikolas, M. A., et al. (2017) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32527 · Cited by 45
First episode psychosis and comorbid ADHD, autism and intellectual disability
Strålin, P., & Hetta, J. E. (2018) · European Psychiatry · doi:10.1016/j.eurpsy.2018.09.007 · Cited by 46
Metadata
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2013-04
- Volume
- 381
- Issue
- 9875
- Pages
- 1371-1379
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- PMC
- PMC3714010
- OpenAlex
- W2139852368
- Cited by
- 3,010
- References
- 52
- Citations by year
- 2026: 70 · 2025: 104 · 2024: 141 · 2023: 117 · 2022: 166 · 2021: 223 · 2020: 249 · 2019: 235 · 2018: 282 · 2017: 317 · 2016: 288 · 2015: 322 · 2014: 303 · 2013: 176
- FWCI
- 240.86
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The Lancet (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- DuEPublico (University of Duisburg-Essen) (submittedVersion)
- TSpace (University of Toronto) (submittedVersion, cc-by-nc-nd)
- UNSWorks (UNSW Sydney) (submittedVersion, cc-by-nc-nd)
- Research Publications (Maastricht University) (submittedVersion, cc-by-nc)
- ePrints Soton (University of Southampton) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- VBN Forskningsportal (Aalborg Universitet) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- VU Research Portal (submittedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- Hirsla (Landspítali University Hospital) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- National Institutes of Health
- National Institute on Alcohol Abuse and Alcoholism (K05AA017688)
- National Institute of Mental Health (R01MH077139, U01MH085520, R01MH100027, R01MH094400, U01MH094421, K99MH101367, MH085520, R01MH083094, K24MH094614, R01MH106595)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Keywords
- mental illness, genetic susceptibility loci, autism spectrum disorder, attention deficit hyperactivity disorder, bipolar disorder, major depressive disorder, schizophrenia, CACNA1C, CACNB2, L-type calcium channels, polygenic risk score, expression quantitative trait loci, pleiotropy, disease classification, childhood-onset disorders
- MeSH terms
- Adult, Attention Deficit Disorder with Hyperactivity, Bipolar Disorder, Child, Child Development Disorders, Pervasive, Depressive Disorder, Major, Major Depressive Disorder, Humans, Schizophrenia, Logistic Models, Age of Onset, Polymorphism, Single Nucleotide, Calcium Channels, L-Type, Genome-Wide Association Study, Genetic Loci
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