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 901–1,000 of 1,027
Serdarević, F., Tiemeier, H. W., Jansen, P. R., Alemany, S., Xerxa, Y., Neumann, A., Robinson, E., Hillegers, M. H. J., Verhulst, F. C., & Ghassabian, A. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.06.006 · Cited by 47
Kowalec, K., Lu, Y., Sariaslan, A., Song, J., Ploner, A., Dalman, C., Hultman, C. M., Larsson, H., Lichtenstein, P., & Sullivan, P. F. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0575-1 · Cited by 44
Gooch, H. M., Cui, X., Anggono, V., Trzaskowski, M., Tan, M. C., Eyles, D. W., Burne, T. H. J., Jang, S. E., Mattheisen, M., HOUGAARD, D. M., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0626-z · Cited by 47
Yoshihara, Y., Lisi, G., Yahata, N., Fujino, J., Matsumoto, Y., Miyata, J., Sugihara, G., Urayama, S.-I., Kubota, M., Yamashita, M., et al. (2020) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaa021 · Cited by 42
Akula, N., Marenco, S., Johnson, K. R., Feng, N., Zhu, K., Schulmann, A., Corona, W., Jiang, X., Cross, J., England, B. K., et al. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-020-00949-5 · Cited by 43
McGrath, L. M., Braaten, E. B., Doty, N. D., Willoughby, B. L., Wilson, H. K., O'Donnell, E. H., Colvin, M. K., Ditmars, H. L., Blais, J. E., Hill, E. N., et al. (2016) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12463 · Cited by 43
Narayanan, B., Soh, P., Calhoun, V. D., Ruaño, G., Kocherla, M., Windemuth, A., Clementz, B. A., Tamminga, C. A., Sweeney, J. A., Keshavan, M. S., et al. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.76 · Cited by 45
Koenen, K. C., Duncan, L. E., Liberzon, I., & Ressler, K. J. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.08.022 · Cited by 47
Cellular and circuit models of increased resting-state network gamma activity in schizophrenia
White, R. S., & Siegel, S. J. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.11.011 · Cited by 44
Dunn, D. W., Besag, F., Caplan, R., Aldenkamp, A. P., Gobbi, G., & Sillanpää, M. L. (2016) · Epileptic Disorders · doi:10.1684/epd.2016.0813 · Cited by 43
Wingo, A. P., Almli, L. M., Stevens, J. S., Jovanović, T., Wingo, T. S., Tharp, G. K., Li, Y., Lori, A., Briscione, M. A., Jin, P., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.143 · Cited by 43
Schneider, M., Walter, H., Moessnang, C., Schäfer, A., Erk, S., Mohnke, S., Romund, L., Garbusow, M., Dixson, L., Heinz, A., et al. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx001 · Cited by 44
Sepp, M., Vihma, H., Nurm, K., Urb, M., Page, S. C., Roots, K., Hark, A., Maher, B. J., Pruunsild, P., & Timmusk, T. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.1151-17.2017 · Cited by 45
Sample Size for Successful Genome-Wide Association Study of Major Depressive Disorder
Nishino, J., Ochi, H., Kochi, Y., Tsunoda, T., & Matsui, S. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00227 · Cited by 49
Tracing Early Neurodevelopment in Schizophrenia with Induced Pluripotent Stem Cells
Ahmad, R., Sportelli, V., Ziller, M. J., Spengler, D., & Hoffmann, A. (2018) · Cells · doi:10.3390/cells7090140 · Cited by 42
Pornpattananangkul, N., Leibenluft, E., Pine, D. S., & Stringaris, A. K. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.0020 · Cited by 44
RetractedRecent Advances in the Genetics of Fractures in Osteoporosis
Koromani, F., Trajanoska, K., Rivadeneira, F., & Oei, L. (2019) · Frontiers in Endocrinology · doi:10.3389/fendo.2019.00337 · Cited by 43
Andlauer, T. F. M., Parra, J. G., Streit, F., Strohmaier, J., González, M. J., Flores, S. G., Cabaleiro, F., Noriega, F. D. R., Pérez, F., González, J. H., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0558-2 · Cited by 46
Aberrant Resting-State Brain Function in Adolescent Depression
Mao, N., Che, K., Chu, T., Li, Y., Wang, Q., Liu, M., Ma, H., Wang, Z., Lin, F., Wang, B., et al. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01784 · Cited by 43
Evaluating the informativeness of deep learning annotations for human complex diseases
Dey, K. K., van de Geijn, B., Kim, S. S., Hormozdiari, F., Kelley, D. R., & Price, A. L. (2020) · Nature Communications · doi:10.1038/s41467-020-18515-4 · Cited by 42
Childhood attention-deficit/hyperactivity disorder
Verkuijl, N., Perkins, M., & Fazel, M. S. (2015) · BMJ · doi:10.1136/bmj.h2168 · Cited by 45
Morris, D. W., Pearson, R. D., Cormican, P., Kenny, E. M., O'Dushlaine, C. T., Perreault, L.-P. L., Giannoulatou, E., Tropea, D., Maher, B. S., Wormley, B., et al. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu025 · Cited by 42
White Matter Alterations in Depressive Disorder
He, E., Liu, M., Gong, S., Fu, X., Han, Y., & Deng, F. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.826812 · Cited by 44
Cattarinussi, G., Giorgio, A. D., Moretti, F., Bondi, E., & Sambataro, F. (2023) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2023.110827 · Cited by 52
Genetic liability for schizophrenia predicts risk of immune disorders
Stringer, S., Kahn, R. S., de Witte, L. D., Ophoff, R. A., & Derks, E. M. (2014) · Schizophrenia Research · doi:10.1016/j.schres.2014.09.004 · Cited by 42
Анатольевич, П. И., Cline, B. H., Anthony, D. C., Steinbusch, H. W. M., Lesch, K., & Strekalova, T. V. (2014) · Behavioural Brain Research · doi:10.1016/j.bbr.2014.04.049 · Cited by 45
Cariaga-Martínez, A. E., Sáiz-Ruiz, J., & Alelú‐Paz, R. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00202 · Cited by 48
Hiroi, N. (2018) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.12641 · Cited by 43
Schizophrenia polygenic risk score predicts mnemonic hippocampal activity
Chen, Q., Ursini, G., Romer, A. L., Knodt, A. R., Mezeivtch, K., Xiao, E., Pergola, G., Blasi, G., Straub, R. E., Callicott, J. H., et al. (2018) · Brain · doi:10.1093/brain/awy004 · Cited by 40
Relationships between substance abuse/dependence and psychiatric disorders based on polygenic scores
Gurriarán, X., Rodriguez‐Lopez, J. A., Flórez, G., Pereiro, C., Fernández, J. M., Fariñas, E., Estévez, V., Arrojo, M., Costas, J., & the GenPol Study Group (2018) · Genes Brain & Behavior · doi:10.1111/gbb.12504 · Cited by 44
Sudre, G. P., Frederick, J., Sharp, W. S., Ishii‐Takahashi, A., Mangalmurti, A., Choudhury, S., & Shaw, P. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0350-3 · Cited by 42
Steen, N. E., Dieset, I., Hope, S., Vedal, T. S. J., Smeland, O. B., Matson, W. R., Kaddurah‐Daouk, R., Agartz, I., Melle, I. S., Djurovic, S., et al. (2019) · Psychological Medicine · doi:10.1017/s0033291719000400 · Cited by 43
Hammerschlag, A. R., de Leeuw, C., Middeldorp, C. M., & Polderman, T. J. C. (2019) · Psychological Medicine · doi:10.1017/s0033291719001776 · Cited by 43
Runge, K., Mathieu, R., Bugeon, S., Lafi, S., Beurrier, C., Sahu, S., Schaller, F., Loubat, A., Hérault, L., Gaillard, S., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01179-x · Cited by 49
Comorbidity of depression and anxiety disorders in patients with hypertension
Graham, N., & Smıth, D. J. (2016) · Journal of Hypertension · doi:10.1097/hjh.0000000000000850 · Cited by 46
Liang, J., Cade, B. E., Wang, H., Chen, H., Gleason, K. J., Larkin, E. K., Saxena, R., Lin, X., Redline, S., & Zhu, X. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21957 · Cited by 41
Menke, A. (2018) · Pharmacogenomics and Personalized Medicine · doi:10.2147/pgpm.s146110 · Cited by 41
Attention deficit hyperactivity disorder
Antshel, K. M., & Barkley, R. A. (2020) · Handbook of clinical neurology · doi:10.1016/b978-0-444-64148-9.00003-x · Cited by 50
Chang, S., Fang, K., Zhang, K., & Wang, J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0133404 · Cited by 41
Reading and Language Disorders: The Importance of Both Quantity and Quality
Newbury, D. F., Monaco, A. P., & Paracchini, S. (2014) · Genes · doi:10.3390/genes5020285 · Cited by 43
Microbial Origins of Chronic Diseases
Gargano, L. M., & Hughes, J. M. (2013) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-032013-182426 · Cited by 42
Chen, J., Wang, M., Khan, R. A. W., He, K., Wang, Q., Li, Z., Shen, J., Song, Z., Li, W., Wen, Z., et al. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.06.040 · Cited by 41
An eMERGE Clinical Center at Partners Personalized Medicine
Smoller, J. W., Karlson, E. W., Green, R. C., Kathiresan, S., MacArthur, D. G., Talkowski, M. E., Murphy, S. N., & Weiss, S. T. (2016) · Journal of Personalized Medicine · doi:10.3390/jpm6010005 · Cited by 41
Chen, J., Calhoun, V. D., Perrone‐Bizzozero, N. I., Pearlson, G. D., Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Du, Y.-X., & Liu, J. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.96 · Cited by 40
Balanced translocation linked to psychiatric disorder, glutamate, and cortical structure/function
Thomson, P. A., Duff, B. J., Blackwood, D., Romaniuk, L., Watson, A., Whalley, H. C., Li, X., Dauvermann, M. R., Moorhead, T. W. J., Bois, C., et al. (2016) · Schizophrenia · doi:10.1038/npjschz.2016.24 · Cited by 41
Biophysical and functional characterization of hippocalcin mutants responsible for human dystonia
Helassa, N., Antonyuk, S. V., Lian, L., Haynes, L. P., & Burgoyne, R. D. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx133 · Cited by 41
Feng, Y. A., Discovery, B., (ELLIPSE), E. L. I. I. P. C. S., Cho, K., Lindström, S., Kraft, P. L., Cormack, J. B., Liang, L., & Driver, J. A. (2017) · Human Genetics · doi:10.1007/s00439-017-1831-6 · Cited by 43
Michels, S., Ganjam, G. K., Martins, H. C., Schratt, G. M., Wöhr, M., Schwarting, R. K. W., & Culmsee, C. (2018) · Cell Death Discovery · doi:10.1038/s41420-018-0061-6 · Cited by 43
Ranlund, S. M., Rosa, M. J., de Jong, S., Cole, J. H., Kyriakopoulos, M., Fu, C. H. Y., Mehta, M. A., & Dima, D. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.10.008 · Cited by 42
Qi, G., & Chatterjee, N. (2018) · PLoS Genetics · doi:10.1371/journal.pgen.1007549 · Cited by 38
Global Deep-Sea Biodiversity Research Trends Highlighted by Science Mapping Approach
Costa, C., Fanelli, E., Marini, S., Danovaro, R., & Aguzzi, J. (2020) · Frontiers in Marine Science · doi:10.3389/fmars.2020.00384 · Cited by 42
Kirkpatrick, R. H., Munoz, D. P., Khalid-Khan, S., & Booij, L. (2021) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2020.11.023 · Cited by 41
Jin, T., Rehani, P. R., Ying, M., Huang, J., Liu, S., Roussos, P., & Wang, D. (2021) · Genome Medicine · doi:10.1186/s13073-021-00908-9 · Cited by 42
Inferring Causal Relationships between Risk Factors and Outcomes Using Genetic Variation
Burgess, S., Foley, C. N., & Zuber, V. (2019) · Wiley eBooks · doi:10.1002/9781119487845.ch23 · Cited by 40
Sadeghi, I., Gispert, J. D., Palumbo, E., Muñoz-Aguirre, M., Wucher, V., D’Argenio, V., Santpere, G., Navarro, A., Guigó, R., & Vilor‐Tejedor, N. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.08.037 · Cited by 42
Evaluation of genetic susceptibility of common variants in CACNA1D with schizophrenia in Han Chinese
Guan, F., Li, L., Qiao, C., Chen, G., Yan, T., Li, T., Zhang, T., & Liu, X. (2015) · Scientific Reports · doi:10.1038/srep12935 · Cited by 40
Posttraumatic Stress Disorder and Comorbidity: Untangling the Gordian Knot
Lockwood, E., & Forbes, D. (2014) · Psychological Injury and Law · doi:10.1007/s12207-014-9189-8 · Cited by 44
Drug development in schizophrenia
GOFF, D. C. (2015) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000152 · Cited by 40
The study of psychiatric disease genes and drugs in zebrafish
Haesemeyer, M., & Schier, A. F. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.12.002 · Cited by 41
Kochunov, P., Chiappelli, J., Wright, S. N., Rowland, L. M., Patel, B., Wijtenburg, S. A., Nugent, K. L., McMahon, R. P., Carpenter, W. T., Muellerklein, F., et al. (2014) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2014.05.004 · Cited by 42
Kotlar, A., Mercer, K. B., Zwick, M. E., & Mullé, J. G. (2015) · European Journal of Medical Genetics · doi:10.1016/j.ejmg.2015.10.008 · Cited by 42
Watmuff, B., Berkovitch, S. S., Huang, J., Iaconelli, J., Toffel, S., & Karmacharya, R. (2016) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2016.01.003 · Cited by 40
Common variants in CACNA1C and MDD susceptibility: A comprehensive meta‐analysis
Rao, S., Yao, Y., Zheng, C., Ryan, J. L., Mao, C., Zhang, F., Meyre, D., & Xu, Q. (2016) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32466 · Cited by 43
GW-SEM: A Statistical Package to Conduct Genome-Wide Structural Equation Modeling
Verhulst, B., MAES, H. H. M., & Neale, M. C. (2017) · Behavior Genetics · doi:10.1007/s10519-017-9842-6 · Cited by 38
Network Analysis as a Grand Unifier in Biomedical Data Science
McGillivray, P. D., Clarke, D., Meyerson, W. U., Zhang, J., Lee, D., Gu, M., Kumar, S., Zhou, H., & Gerstein, M. (2018) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-080917-013444 · Cited by 41
Clozapine Pharmacogenetic Studies in Schizophrenia: Efficacy and Agranulocytosis
Numata, S., Umehara, H., Ohmori, T., & Hashimoto, R. (2018) · Frontiers in Pharmacology · doi:10.3389/fphar.2018.01049 · Cited by 39
Genetic risk scores for major psychiatric disorders and the risk of postpartum psychiatric disorders
Bauer, A. E., Liu, X., Byrne, E. M., Sullivan, P. F., Wray, N. R., Agerbo, E., Nyegaard, M., Grove, J., Musliner, K. L., Ingstrup, K. G., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0629-9 · Cited by 42
Bakulski, K. M., Dou, J., Thompson, R. C., Lee, C., Middleton, L. Y. M., Perera, B. P. U., Ferris, S. P., Jones, T. R., Neier, K. E., Zhou, X. Y., et al. (2020) · Toxicological Sciences · doi:10.1093/toxsci/kfaa069 · Cited by 42
Neurological Disorders and Risk of Arrhythmia
Bernardi, J., Aromolaran, K. A., & Aromolaran, A. S. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms22010188 · Cited by 40
Novel approaches in schizophrenia-from risk factors and hypotheses to novel drug targets
Ľupták, M., Michaličková, D., Fišar, Z., Kitzlerová, E., & Hroudová, J. (2021) · World Journal of Psychiatry · doi:10.5498/wjp.v11.i7.277 · Cited by 41
Schizophrenia Research: A Progress Report.
Buckley, P. F., & Miller, B. J. (2015) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2015.05.001 · Cited by 110
Single-case experimental research designs.
Kazdin, A. E. (2015) · Methodological issues and strategies in clinical research (4th ed.). · doi:10.1037/14805-029 · Cited by 39
Psychiatric Genetics in Child Custody Proceedings: Ethical, Legal, and Social Issues
Sabatello, M., & Appelbaum, P. S. (2016) · Current Genetic Medicine Reports · doi:10.1007/s40142-016-0093-2 · Cited by 41
Genetic Variants Associated With Resilience in Human and Animal Studies
Cahill, S., Chandola, T., & Hager, R. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.840120 · Cited by 52
Examining the shared etiology of psychopathology with genome-wide association studies
Mallard, T. T., Grotzinger, A. D., & Smoller, J. W. (2023) · Physiological Reviews · doi:10.1152/physrev.00016.2022 · Cited by 38
Genetic analysis of SNPs in CACNA1C and ANK3 gene with schizophrenia: A comprehensive meta‐analysis
Nie, F., Wang, X., Zhao, P., Yang, H., Zhu, W., Zhao, Y., Chen, B., Valenzuela, R. K., Zhang, R., Gallitano, A. L., et al. (2015) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32348 · Cited by 39
Addressing the lack of studies in attention-deficit/hyperactivity disorder in adults
Ramos‐Quiroga, J. A., Nasillo, V., Fernández‐Aranda, F., & Casas, M. (2014) · Expert Review of Neurotherapeutics · doi:10.1586/14737175.2014.908708 · Cited by 44
Cline, B. H., Anthony, D. C., Lysko, A., Dolgov, O., Anokhin, K. V., Schroeter, C. A., Malin, D., Kubatiev, A. A., Steinbusch, H. W. M., Lesch, K., et al. (2014) · Behavioural Brain Research · doi:10.1016/j.bbr.2014.04.037 · Cited by 42
Port, R. G., Gandal, M. J., Roberts, T. P. L., Siegel, S. J., & Carlson, G. C. (2014) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2014.00414 · Cited by 41
Kong, S. W., Shimizu‐Motohashi, Y., Campbell, M. G., Lee, I., Collins, C. D., Brewster, S. J., Holm, I. A., Rappaport, L., Kohane, I. S., & Kunkel, L. M. (2013) · Neurogenetics · doi:10.1007/s10048-013-0363-z · Cited by 37
Russell, T. A., Blizinsky, K. D., Cobia, D. J., Cahill, M. E., Xie, Z., Sweet, R. A., Duan, J., Gejman, P. V., Wang, L., Csernansky, J. G., et al. (2014) · Nature Communications · doi:10.1038/ncomms5858 · Cited by 37
Developmental vitamin D deficiency and schizophrenia: the role of animal models
Schoenrock, S. A., & Tarantino, L. M. (2015) · Genes Brain & Behavior · doi:10.1111/gbb.12271 · Cited by 39
Hertzberg, L., Katsel, P., Roussos, P., Haroutunian, V. H., & Domany, E. (2015) · Schizophrenia Research · doi:10.1016/j.schres.2015.02.001 · Cited by 39
Bigdeli, T. B., Ripke, S., Bacanu, S., Lee, S., Wray, N. R., Gejman, P. V., Rietschel, M., Cichon, S., Clair, D. S., Corvin, A. P., et al. (2015) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32402 · Cited by 40
A network of synaptic genes associated with schizophrenia and bipolar disorder
Forero, D. A., Herteleer, L., Zutter, S. D., Norrback, K., Nilsson, L., Adolfsson, R., Callaerts, P., & Del‐Favero, J. (2016) · Schizophrenia Research · doi:10.1016/j.schres.2016.02.012 · Cited by 35
Mitchell, E. J., Klein, S. L., Argyropoulos, K. V., Sharma, A., Chan, R., Toth, J. G., Barboza, L., Bavley, C. C., Bortolozzi, A. A., Chen, Q., et al. (2016) · Nature Communications · doi:10.1038/ncomms11492 · Cited by 38
Balakrishnan, P., Vaidya, D. M., Franceschini, N., Voruganti, V. S., Gribble, M. O., Haack, K., Laston, S., Umans, J. G., Francesconi, K. A., Goessler, W., et al. (2016) · Environmental Health Perspectives · doi:10.1289/ehp251 · Cited by 39
Matsuda, K. (2017) · Neurosciences research · doi:10.1016/j.neures.2016.11.004 · Cited by 38
Wangler, M. F., Hu, Y., & Shulman, J. M. (2017) · Disease Models & Mechanisms · doi:10.1242/dmm.027680 · Cited by 41
Dimensional thinking in psychiatry in the era of the Research Domain Criteria (RDoC)
Kelly, J. R., Clarke, G. A., Cryan, J. F., & Dinan, T. G. (2017) · Irish Journal of Psychological Medicine · doi:10.1017/ipm.2017.7 · Cited by 39
Ronald, A., & Pain, O. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy157 · Cited by 40
Polygenic risk scoring and prediction of mental health outcomes
Anderson, J. S., Shade, J., DiBlasi, E., Shabalin, A. A., & Docherty, A. R. (2018) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2018.09.002 · Cited by 38
Chang, M., Edmiston, E. K., Womer, F. Y., Zhou, Q., Wei, S., Jiang, X., Zhou, Y., Ye, Y., Huang, H., Zuo, X., et al. (2019) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.170226 · Cited by 39
Endogenous Retroviruses Activity as a Molecular Signature of Neurodevelopmental Disorders
Balestrieri, E., Matteucci, C., Cipriani, C., Grelli, S., Ricceri, L., Calamandrei, G., & Vallebona, P. S. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20236050 · Cited by 38
Nigg, J. T. (2016) · Wiley eBooks · doi:10.1002/9781119125556.devpsy314 · Cited by 41
CACNA1C-Related Channelopathies
Herold, K., Hussey, J. W., & Dick, I. E. (2023) · Handbook of experimental pharmacology · doi:10.1007/164_2022_624 · Cited by 38
Zheng, F., Zhang, Y., Xie, W., Li, W., Jin, C., Mi, W., Wang, F., Ma, W., Ma, C., Yang, Y., et al. (2013) · Schizophrenia Research · doi:10.1016/j.schres.2013.12.003 · Cited by 38
Erk, S., Meyer‐Lindenberg, A., Linden, D. E. J., Lancaster, T. M., Mohnke, S., Grimm, O., Degenhardt, F., Holmans, P., Pocklington, A. J., Schmierer, P., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.007 · Cited by 38
Zhang, J., Kendrick, K. M., Lu, G., & Feng, J. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu173 · Cited by 37
The best-laid plans go oft awry: synaptogenic growth factor signaling in neuropsychiatric disease
Williams, A. J., & Umemori, H. (2014) · Frontiers in Synaptic Neuroscience · doi:10.3389/fnsyn.2014.00004 · Cited by 38
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