The DOI matches its Crossref record; 50 of the 52 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source doesn’t support the claim as written.
In the citing paper
“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]
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
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]
The cited source says what the claim attributes to it.
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]
The check wasn’t confident either way, so it gives no verdict — never disputed.
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]
Experimental — accuracy not yet measuredIn the citing paper
“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
“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].”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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
Cited by
Sorted by citations
Items 1,001–1,027 of 1,027
Addressing the Genetics of Human Mental Health Disorders in Model Organisms
McCammon, J. M., & Sive, H. L. (2015) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-090314-050048 · Cited by 42
Ames, J. L., Ladd-Acosta, C., Fallin, M. D., Qian, Y., Schieve, L. A., DiGuiseppi, C., Lee, L.-C., Kasten, E. P., Zhou, G., Pinto-Martin, J., et al. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2021.04.002 · Cited by 36
Prescription Stimulant Use and Hospitalization for Psychosis or Mania: A Population-Based Study
Cressman, A. M., Macdonald, E. M., Huang, A., Gomes, T., Paterson, M. J., Kurdyak, P. A., Mamdani, M. M., & Juurlink, D. N. (2015) · Journal of Clinical Psychopharmacology · doi:10.1097/jcp.0000000000000406 · Cited by 37
Gstir, R., Schafferer, S., Scheideler, M., Misslinger, M., Griehl, M., Daschil, N., Humpel, C., Obermair, G. J., Schmuckermair, C., Striessnig, J., et al. (2014) · RNA · doi:10.1261/rna.047225.114 · Cited by 36
Qi, S., Bustillo, J., Turner, J. A., Jiang, R., Zhi, D., Fu, Z., Deramus, T. P., Vergara, V., Ma, X., Yang, X., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0834-6 · Cited by 32
Meta-Analyses of Genome-Wide Association Data Hold New Promise for Addiction Genetics
Agrawal, A., Edenberg, H. J., & Gelernter, J. (2016) · Journal of Studies on Alcohol and Drugs · doi:10.15288/jsad.2016.77.676 · Cited by 32
Mathias, S. R., Knowles, E. E. M., Kent, J. W., McKay, D. R., Curran, J. E., de Almeida, M. A. A., Dyer, T. D., Göring, H. H. H., Olvera, R. L., Duggirala, R., et al. (2016) · Human Brain Mapping · doi:10.1002/hbm.23025 · Cited by 28
Sokolowski, M., Wasserman, J., & Wasserman, D. (2018) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32694 · Cited by 30
Genome-wide association analysis identifies common variants influencing infant brain volumes
Xia, K., Zhang, J., Ahn, M., Jha, S., Crowley, J. J., Szatkiewicz, J., Li, T., Zou, F., Zhu, H., Hibar, D., et al. (2017) · Translational Psychiatry · doi:10.1038/tp.2017.159 · Cited by 30
Mansell, W., & McEvoy, P. M. (2017) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2016.06.008 · Cited by 30
Kennedy, H. L., Dinkler, L., Kennedy, M. A., Bulik, C. M., & Jordan, J. (2022) · Journal of Eating Disorders · doi:10.1186/s40337-022-00578-x · Cited by 29
Chromatin regulators, phenotypic robustness, and autism risk
Suliman, R., Ben-David, E., & Shifman, S. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00081 · Cited by 28
Mental distress through the prism of predictive processing theory
Van de Cruys, S., & Van Dessel, P. (2021) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2021.07.006 · Cited by 28
Novikova, G., Kapoor, M., TCW, J., Abud, E. M., Efthymiou, A. G., Cheng, H., Fullard, J. F., Bendl, J., Roussos, P., Poon, W. W., et al. (2019) · doi:10.1101/694281 · Cited by 27
SanGiovanni, J. P., & Lee, P. H. (2013) · PLoS ONE · doi:10.1371/journal.pone.0071239 · Cited by 26
Autism-related behavioral phenotypes in an inbred rat substrain
Zhang-James, Y., Yang, L., Middleton, F. A., Yang, L., Patak, J., & Faraone, S. V. (2014) · Behavioural Brain Research · doi:10.1016/j.bbr.2014.04.035 · Cited by 26
Lithium Treatment in Children and Adolescents
Duffy, A., & Grof, P. (2018) · Pharmacopsychiatry · doi:10.1055/a-0575-4179 · Cited by 22
Leopold, K., Bauer, M., Bechdolf, A., Correll, C. U., Holtmann, M., Juckel, G., Lambert, M., Meyer, T. D., Pfeiffer, S., Kittel‐Schneider, S., et al. (2020) · Bipolar Disorders · doi:10.1111/bdi.12894 · Cited by 23
Chen, X., Cao, H., Saraf, A., Zweifel, L. S., & Storm, D. R. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.2478-14.2015 · Cited by 21
Deserno, M. K., Bathelt, J., Groenman, A. P., & Geurts, H. M. (2023) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-022-01986-9 · Cited by 22
Van Assche, E., Moons, T., Cinar, O., Viechtbauer, W., Oldehinkel, A. J., Van Leeuwen, K., Verschueren, K., Colpin, H., Lambrechts, D., Van den Noortgate, W., et al. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12766 · Cited by 19
Jones, S. E., Hees, V. T. V., Mazzotti, D. R., Marques-Vidal, P., Sabia, S., der Spek, A. V., Dashti, H. S., Engmann, J., Kocevska, D., Tyrrell, J., et al. (2018) · doi:10.1101/303925 · Cited by 14
Weng, W., Chen, Y., Wang, M., Zhuang, Y., & Behnisch, T. (2016) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2016.00247 · Cited by 14
Uchino, T., Okubo, R., Takubo, Y., Aoki, A., Wada, I., Hashimoto, N., Ikezawa, S., & Nemoto, T. (2023) · Journal of Personalized Medicine · doi:10.3390/jpm13040683 · Cited by 12
Putative contributions of the sex chromosome proteins SOX3 and SRY to neurodevelopmental disorders
Tahira, A. C., Barbosa, A. R., Feltrin, A. S., Gastaldi, V. D., de Toledo, V. H. C., de Carvalho Pereira, J. G., Lisboa, B. C. G., de Souza Reis, V. N., dos Santos, A. C. F., Maschietto, M., et al. (2019) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32704 · Cited by 11
Genis-Mendoza, A., Gallegos-Silva, I., Tovilla-Zarate, C. A., López-Narvaez, L., González-Castro, T. B., Hernández-Díaz, Y., López-Casamichana, M., Nicolini, H., & Morales-Mulia, S. (2018) · Journal of Molecular Neuroscience · doi:10.1007/s12031-017-1013-y · Cited by 6
CYFIP1 governs the development of cortical axons by modulating calcium availability
Ricci, C., Midroit, M. J., Caicci, F., Achsel, T., Domínguez-Iturza, N., & Bagni, C. (2025) · Nature Communications · doi:10.1038/s41467-025-65801-0 · Cited by 1
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review