The DOI matches its Crossref record; 55 of the 56 references it cites were found in a registry or an index.
Biological insights from 108 schizophrenia-associated genetic loci
Open accessAbstract
Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.
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 source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Conservative estimates are that 10 -20% of people with ASD harbour a de novo rare point mutation or CNV contributing to their presentation (34, 49,50).”
From Autism spectrum disorder (2020) · cites this paper as [50]
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
“In ASD, a single de novo more risk than the cumulative effect of the top decile of polygenic risk for schizophrenia 47,50”
From Autism spectrum disorder (2020) · cites this paper as [50]
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
“Large-scale genome-wide association studies (GWAS) have identified approximately 160 regions of the genome harboring common variants robustly associated with the diagnosis of schizophrenia, with evidence for a substantial polygenic component in signals that individually fall below genome-wide levels of significance (Pardiñas et al., 2018; Ripke et al., 2014)”
From DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia (2021) · cites this paper as Ripke et al., 2014
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
“Significant correlations were found for several traits including schizophrenia 15 ( 𝑟 𝐺 = 0.211, p = 1.03 x 10 -5 ) and measures of cognitive ability, especially educational attainment 20 ( 𝑟 𝐺 = 0.199, p = 2.56 x 10 -9 )”
From Identification of common genetic risk variants for autism spectrum disorder (2019) · cites this paper as [15]
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
“The scientific basis of this imbalance has been demonstrated theoretically, in simulations, and empirically across many traits and diseases11–22.”
From Clinical use of current polygenic risk scores may exacerbate health disparities (2019) · cites this paper as [18]
Experimental — accuracy not yet measured
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Mounting evidence suggests a link between GRAMD1b and various neurodevelopmental disorders, including schizophrenia and intellectual disability (Schizophrenia Working Group of the Psychiatric Genomics C, 2014; Reuter et al, 2017; Santos‐Cortez et al, 2018; Thyme et al, 2019).”
From Molecular basis of accessible plasma membrane cholesterol recognition by the GRAM domain of GRAMD1b (2021) · cites this paper as Schizophrenia Working Group of the Psychiatric Genomics C, 2014
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Genetic association studies (Ripke et al., 2014) as well as epidemiological studies addressing the impact of the environment (van Os, Kenis, & Rutten, 2010) on disease burden, have not yet explained the non-complete genetic correlation between monozygotic twins in conditions such as schizophrenia (SCZ) (41–65%), Bipolar Disorder (BD) (~60%) (Craddock, O'Donovan, & Owen, 2005) or Major Depression (”
From Can epigenetics shine a light on the biological pathways underlying major mental disorders? (2022) · cites this paper as Ripke et al., 2014
The cited source says what the claim attributes to it.
In the citing paper
“large consortia that have discovered and successfully replicated genome-wide associations of common gene variants (single nucleotide polymorphisms, SNPs) for several disorders including schizophrenia [2] and major depression [3–6].”
From Neandertal introgression partitions the genetic landscape of neuropsychiatric disorders and associated behavioral phenotypes (2022) · cites this paper as [2]
The cited source says what the claim attributes to it.
In the citing paper
“A relevant example is evident in genomics research, in which data pooling has, e.g., enabled knowledge of disease-related loci to be expanded substantially [e.g.Lambert et al. (2013); Manolio et al. (2008); Schizophrenia Working Group of the Psychiatric Genomics (2014)], findings which would not have been possible without the sample sizes offered through data-sharing.”
From New directions in hypnosis research: strategies for advancing the cognitive and clinical neuroscience of hypnosis (2017) · cites this paper as Schizophrenia Working Group 2014
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“However, the absolute number of cannabis users needed to stop using cannabis in order to prevent one case of schizophrenia per year has been estimated at approximately 5000 for heavy users among men, and 10,000 to 15,000 among women (67).”
From Association Between Cannabis and Psychosis: Epidemiologic Evidence (2016) · cites this paper as [67]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Research in other fields has benefited substantially from datasharing initiatives.”
From New directions in hypnosis research: strategies for advancing the cognitive and clinical neuroscience of hypnosis (2017) · cites this paper as Schizophrenia Working Group 2014
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“However, the major ethical and scientific challenge surrounding clinical implementation is that they are many-fold more accurate in European ancestry individuals than others.”
From Clinical use of current polygenic risk scores may exacerbate health disparities (2019) · cites this paper as [18]
Experimental — accuracy not yet measuredIn the citing paper
“Additionally, associations have been found between schizophrenia and the arginine and serine rich coiled-coil 1 (RSRC1) 28 and myocyte enhancer factor 2C (MEF2C) 21 genes, both of which we found to be putatively associated with depression.”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [21]
In the citing paper
“many high-risk SZ genes identified by GWAS studies are highly enriched in mid-frontal lobe 161”
From Mechanisms of synaptic transmission dysregulation in the prefrontal cortex: pathophysiological implications (2022) · cites this paper as [161]
In the citing paper
“Converging lines of genetic, post-mortem, and pre-clinical evidence suggest immune dysregulation may play a role in the pathogenesis of both schizophrenia 63–67 and depression, 68, 69 and it is hypothesised that immune alterations are seen only in a proportion of these patients (immune/inflammatory subgroups) and are linked to poor treatment response. 67, 70–72”
From Treatment resistance in psychiatry: state of the art and new directions (2022) · cites this paper as [64]
In the citing paper
“one association (rs3768644; chr2:72.3Mb) is no longer supported11”
From Mapping genomic loci implicates genes and synaptic biology in schizophrenia (2022) · cites this paper as [11]
In the citing paper
“Large-scale genome-wide association studies have also identified associations between immune system-related genes and psychiatric conditions [15, 16].”
From Inflammatory ratios as predictors of length of hospitalization in psychiatric patients: A multicenter study (2025) · cites this paper as [15]
In the citing paper
“It is true that a large number of risk alleles are involved, and that the explanatory power of currently available polygenic risk scores for addictive disorders lags behind those for e.g., schizophrenia or major depression [47,48].”
From Addiction as a brain disease revised: why it still matters, and the need for consilience (2021) · cites this paper as [47]
In the citing paper
“Power analyses indicate that additional SNPs associated with AD are likely to have small effect sizes, smaller than schizophrenia47 and more consistent with more common psychiatric disorders (e.g. major depression48).”
From Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders (2018) · cites this paper as [47]
In the citing paper
“Schizophrenia GWAS also identified a common variant at GRIN2A (OR = 1.057,P = 1.57x 10 - 10 ), providing an allelic series in which different perturbation of gene function results in severity of disease risk (Figure 3A) 5 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [5]
In the citing paper
“Efforts in the past decade are beginning to generate a more comprehensive view of the genetic architecture for schizophrenia, composed of common variants of small effects, large CNVs with elevated frequencies driven by genomic instability, and now, URVs of large effect implicating individual genes (Figure 6A) 5,7 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [5]
In the citing paper
“Following earlier reports studying heritability enrichment in GTEx tissues 5,30 , we found that genes with the highest specific expression in brain regions showed the strongest enrichment of risk URVs, most significantly in the human frontal cortex (P = 1.63 x 10 -8 ) and with limited signal in the other tissue types (Figure S19, Table S8, S9).”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [5]
In the citing paper
“Schizophrenia GWAS also identified a common variant at GRIN2A (OR = 1.057, P = 1.57 × 10−10), providing an allelic series in which different perturbation of gene function results in severity of disease risk (Figure 3A)8.”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [8]
In the citing paper
“It is well-established that schizophrenia has a substantial genetic component with contributions from across the allele frequency spectrum8–11.”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [8]
In the citing paper
“Pathway analyses of common variants have prioritized disease-relevant tissues and cell types, and in some cases, independently recapitulating known biology8,30,31.”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [8]
In the citing paper
“Efforts in the past decade are beginning to generate a more comprehensive view of the genetic architecture for schizophrenia, composed of common variants of small effects, large CNVs with elevated frequencies driven by genomic instability, and now, URVs of large effect implicating individual genes (Figure 6A)8,10.”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [8]
In the citing paper
“Following earlier reports studying heritability enrichment in GTEx tissues8,31, we found that genes with the highest specific expression in brain regions showed the strongest enrichment of risk URVs, most significantly in the human frontal cortex (P = 1.63 × 10−8) and with limited signal in the other tissue types (Extended Data Figure 4, Table S8, S9).”
From Rare coding variants in ten genes confer substantial risk for schizophrenia (2022) · cites this paper as [8]
In the citing paper
“We identified two loci (Supplementary Fig. 14) with statistically significant associations (p<10−6) replicating a couple of common variants associations previously observed for this cohort50: a single variant rs281766 on chromosome 2 in the UTR5 of genes TYW5 and C2orf47”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [24]
In the citing paper
“We observed a nominally significant enrichment in genes overlapping regions near common variants associated with schizophrenia24 (OR=1.37; 95% CI=1.09–1.73; P = 0.027) (Fig. 2) hinting at some degree of convergence.”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [24]
In the citing paper
“Similarly to rare variants enrichment, common variants associated with schizophrenia are localized near XLID genes CNKSR2 and NLGN4X, both of which escape X inactivation, as well as non-XLID gene PJA124.”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [24]
In the citing paper
“While a predictor based on common variants24,109 explained 15% of the variance in schizophrenia liability in this cohort”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [24]
In the citing paper
“as exemplified by a study by the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC) which identified 108 independent schizophrenia associated loci 14.”
From Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects (2017) · cites this paper as [14]
In the citing paper
“including rare copy number variants2 and >100 common variants3.”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“Indeed, GWAS SNPs associated with SCZ risk occur more often than expected by chance in cis-regulatory functional genomic elements, such as enhancers or eQTL SNPs3,21–24.”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“As expected3, SCZ cases inherited an increased number of common variant alleles previously associated with SCZ risk (P = 1.6 × 10−8, Supplementary Fig. 1D).”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“Of the 108 SCZ GWAS loci previously reported3, 73 harbor cis-eQTL SNPs for one or more genes (FDR ≤ 5%).”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“For that gene, the expected magnitude of differential expression fold change will be on the order of the allele frequency differences seen in the recent large Psychiatric Genomic Consortium SCZ genetic association study (~1–2%)3, precisely what is observed in the CMC data.”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“We also slightly modified the Sherlock source code, omitting the exclusion criterion for SNPs (and genes whose expression is associated with those SNPs) that could not be found in the 1000 Genomes data, which encompassed only 49,612 [4.4%] of the 1,127,447 eSNPs also found in the PGC SCZ2 GWAS data 3.”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“Over 100 genetic loci harbor schizophrenia associated variants”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“Of the 108 SCZ GWAS loci previously reported3, 73 harbor cis-eQTL SNPs for one or more genes (FDR ≤ 5%).”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“As expected3, SCZ cases inherited an increased number of common variant alleles previously associated with SCZ risk (P = 1.6 × 10−8, Supplementary Fig. 1D).”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“only recently have specific genetic risk factors been conclusively identified, including rare copy number variants2 and >100 common variants3”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“Indeed, GWAS SNPs associated with SCZ risk occur more often than expected by chance in cis-regulatory functional genomic elements, such as enhancers or eQTL SNPs3,21–24.”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“Prior analyses using brain eQTL datasets derived from older technologies have pointed to less than a handful of such associations3.”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“For that gene, the expected magnitude of differential expression fold change will be on the order of the allele frequency differences seen in the recent large Psychiatric Genomic Consortium SCZ genetic association study (~1–2%)3, precisely what is observed in the CMC data.”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [3]
In the citing paper
“In addition, recently reported genetic vulnerabilities for CSPG genes, including PTPRZ1 and neurocan (Buxbaum et al., 2008; Muhleisen et al., 2012; Ripke and Schizophrenia Working Group of the Psychiatric Genomics, 2014), may contribute to decrease CSPG synthesis in SZ.”
From Losing the sugar coating: Potential impact of perineuronal net abnormalities on interneurons in schizophrenia (2015) · cites this paper as Ripke and Schizophrenia Working Group of the Psychiatric Genomics, 2014
In the citing paper
“Due to overlapping samples between the ASD and PGC GWAS, INRICH analyses against the PGC schizophrenia study [19] was restricted to the noSWM3 ASD GWAS including the worldwide dataset minus the Swedish PAGES sample. This set was analysed in isolation and exceeded the experiment-wise correction (P = .008), with 19 of the 82 blocks included in the analysis overlapping these annotations.”
In the citing paper
“Previously, when comparing the results of an early iteration of the PGC schizophrenia GWAS (PGC1) [40], which is of similar size to that of reported here for the PGC ASD GWAS, to more recent and larger PGC schizophrenia GWAS (PGC2) [19], we noted that of the association signals 5 × 10−8 ≤ P < 10−4 in the schizophrenia PGC1 study, over 10% (20 of 183 independent loci) were subsequently reported as”
In the citing paper
“We again observe evidence of an overlap with schizophrenia, with a 2.5-fold enrichment in heritability for those markers within the PGC schizophrenia GWS loci (P = 0.021).”
In the citing paper
“After removing significant loci (+/−1 Mb) previously reported in the PGC schizophrenia analyses, we observed 12 new GWS loci (see Table 3; Additional file 14 and Additional file 15).”
In the citing paper
“A PGC schizophrenia GWAS [40], which was of comparable size to this, yielded 5 GWS loci and 183 non-GWS loci at P < 10−4. In a follow-up study [19], 20 of these markers were elevated beyond GWS; these were not limited to the most highly ranked markers, as the newly GWS markers ranged from 7 to 188 in the original study.”
In the citing paper
“When considering the GWS loci reported in the PGC schizophrenia GWAS, 118 of the markers pass QC in the ASD WWW GWAS sample. Eleven of these 118 schizophrenia-associated markers are also associated with ASD at P ≤ .05 (Pr(K > = 11/118) = 0.035).”
In the citing paper
“Due to overlapping samples between the ASD and PGC GWAS, INRICH analyses against the PGC schizophrenia study [19] was restricted to the noSWM3 ASD GWAS including the worldwide dataset minus the Swedish PAGES sample.”
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 [58]
In the citing paper
“We found that noncoding SNVs associated with schizophrenia38 (n = 80, P < 5 × 10−8, see Supplementary Methods) preferentially colocalize with class 3 loops anchored by activity-decommissioned enhancers”
From Three-dimensional genome restructuring across timescales of activity-induced neuronal gene expression (2020) · cites this paper as [38]
In the citing paper
“A recent genome-wide association study (GWAS) implicated serine racemase (SRR) and GRIN2A as risk genes for schizophrenia 21 as well as other genes functionally up-and downstream of NMDAR activity 21,22 .”
From Linking early-life NMDAR hypofunction and oxidative stress in schizophrenia pathogenesis (2016) · cites this paper as [21]
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
Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005) · Cell · doi:10.1016/j.cell.2004.12.035 · Cited by 11,855
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., & Wang, P. (2010) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.09091379 · Cited by 7,067
Effectiveness of Antipsychotic Drugs in Patients with Chronic Schizophrenia
Lieberman, J. A., Stroup, T. S., McEvoy, J. P., Swartz, M. S., Rosenheck, R. A., Perkins, D. O., Keefe, R. S. E., Davis, S. M., Davis, C. E., Lebowitz, B. D., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa051688 · Cited by 5,892
The Endophenotype Concept in Psychiatry: Etymology and Strategic Intentions
Gottesman, I. I., & Gould, T. D. (2003) · American Journal of Psychiatry · doi:10.1176/appi.ajp.160.4.636 · Cited by 5,615
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
Self-citationCommon polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease
The International IBD Genetics Consortium (IIBDGC), Jostins, L., Ripke, S., Weersma, R. K., Duerr, R. H., McGovern, D. P., Hui, K. Y., Lee, J. C., Philip Schumm, L., Sharma, Y., et al. (2012) · Nature · doi:10.1038/nature11582 · Cited by 4,722
Self-citationSystematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716
(2013) · The Lancet · doi:10.1016/s0140-6736(12)62129-1 · Cited by 3,010
Flagged first, then by citations
1 of the 56 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- World Health Organization. The Global Burden of Disease: 2004 Update (WHO Press, 2008)
Cited by
Sorted by citations
Items 801–900 of 1,121
The Relationship Between Polygenic Risk Scores and Cognition in Schizophrenia
Richards, A. L., Pardiñas, A. F., Frizzati, A., Tansey, K. E., Lynham, A. J., Holmans, P., Legge, S. E., Savage, J. E., Agartz, I., Andreassen, O. A., et al. (2019) · Schizophrenia Bulletin · doi:10.1093/schbul/sbz061 · Cited by 112
Brain-derived neurotrophic factor and schizophrenia
Di Carlo, P., Punzi, G., & Ursini, G. (2019) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000237 · Cited by 110
Goldsmith, D. R., & Rapaport, M. H. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00046 · Cited by 115
Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits
Yao, C., Joehanes, R., Johnson, A. D., Huan, T., Liu, C., Freedman, J. E., Munson, P. J., Hill, D. E., Vidal, M., & Levy, D. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.02.003 · Cited by 106
Lin, M., Pedrosa, E., Hrabovsky, A., Chen, J., Puliafito, B. R., Gilbert, S. R., Zheng, D., & Lachman, H. M. (2016) · BMC Systems Biology · doi:10.1186/s12918-016-0366-0 · Cited by 111
The Major Histocompatibility Complex (MHC) in Schizophrenia: A Review
Mokhtari, R., & Lachman, H. M. (2016) · Journal of Clinical & Cellular Immunology · doi:10.4172/2155-9899.1000479 · Cited by 117
Biological Insights Into Muscular Strength: Genetic Findings in the UK Biobank
Tikkanen, E., Gustafsson, S., Amar, D., Shcherbina, A., Waggott, D. M., Ashley, E. A., & Ingelsson, E. (2018) · Scientific Reports · doi:10.1038/s41598-018-24735-y · Cited by 108
Zhu, X., & Stephens, M. (2018) · Nature Communications · doi:10.1038/s41467-018-06805-x · Cited by 103
Deciphering the Emerging Complexities of Molecular Mechanisms at GWAS Loci
Cannon, M. E., & Mohlke, K. L. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.10.001 · Cited by 111
Dong, Z., Chen, W., Chen, C., Wang, H., Cui, W., Tan, Z., Robinson, H., Gao, N., Luo, B., Zhang, L., et al. (2020) · Neuron · doi:10.1016/j.neuron.2019.10.035 · Cited by 109
Increased Macrophages and C1qA, C3, C4 Transcripts in the Midbrain of People With Schizophrenia
Purves-Tyson, T. D., Robinson, K., Brown, A. M., Boerrigter, D., Cai, H. Q., Weissleder, C., Owens, S. J., Rothmond, D. A., & Weickert, C. S. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.02002 · Cited by 114
Pardiñas, A. F., Smart, S. E., Willcocks, I. R., Holmans, P., Dennison, C. A., Lynham, A. J., Legge, S. E., Baune, B. T., Bigdeli, T. B., Cairns, M. J., et al. (2022) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2021.3799 · Cited by 105
Musliner, K. L., Mortensen, P. B., McGrath, J. J., Suppli, N. P., Hougaard, D. M., Bybjerg-Grauholm, J., Bækvad-Hansen, M., Andreassen, O., Pedersen, C. B., Pedersen, M. G., et al. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2018.4166 · Cited by 108
Self-citationSomatic Comorbidity in Schizophrenia: Some Possible Biological Mechanisms Across the Life Span
Dieset, I., Andreassen, O. A., & Haukvik, U. K. (2016) · Schizophrenia Bulletin · doi:10.1093/schbul/sbw028 · Cited by 110
Köhler‐Forsberg, O., Petersen, L. V., Mors, O. N., Mortensen, P. B., Yolken, R. H., Gasse, C., & Benros, M. E. (2016) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.12671 · Cited by 109
The genetics of neuropsychiatric disorders
Bray, N. J., & O’Donovan, M. C. (2018) · Brain and Neuroscience Advances · doi:10.1177/2398212818799271 · Cited by 113
Maternal immune activation, central nervous system development and behavioral phenotypes
Minakova, E., & Warner, B. B. (2018) · Birth Defects Research · doi:10.1002/bdr2.1416 · Cited by 114
Brown, A. A., Viñuela, A., Delaneau, O., Spector, T. D., Small, K. S., & Dermitzakis, E. T. (2017) · Nature Genetics · doi:10.1038/ng.3979 · Cited by 102
Endres, D., Leypoldt, F., Bechter, K., Hasan, A., Steiner, J. H., Domschke, K., Wandinger, K., Falkai, P., Arolt, V., Stich, O., et al. (2020) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-020-01113-2 · Cited by 109
Disrupted sleep and circadian rhythms in schizophrenia and their interaction with dopamine signaling
Ashton, A., & Jagannath, A. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00636 · Cited by 106
Paquette, M., Chong, M., Thériault, S., Dufour, R., Paré, G., & Baass, A. (2017) · Journal of Clinical Lipidology · doi:10.1016/j.jacl.2017.03.019 · Cited by 115
The role of Th17 cells in auto-inflammatory neurological disorders
Tahmasebinia, F., & Pourgholaminejad, A. (2017) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2017.07.023 · Cited by 111
Defects in Bioenergetic Coupling in Schizophrenia
Sullivan, C. R., O'Donovan, S. M., McCullumsmith, R. E., & Ramsey, A. J. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.10.014 · Cited by 108
B-1a lymphocytes promote oligodendrogenesis during brain development
Tanabe, S., & Yamashita, T. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0106-4 · Cited by 109
Comprehensive integrative analyses identify GLT8D1 and CSNK2B as schizophrenia risk genes
Yang, C., Li, X., Wu, Y., Shen, Q., Zeng, Y., Xiong, Q., Wei, M., Chen, C., Liu, J., Huo, Y., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03247-3 · Cited by 106
A decade in psychiatric GWAS research
Horwitz, T. B., Lam, K., Chen, Y., Xia, Y., & Liu, C. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0055-z · Cited by 108
Gallego, J. A., Blanco, E. A., Husain-Krautter, S., Fagen, E. M., Moreno-Merino, P., del Ojo-Jiménez, J. A., Ahmed, A. O., Rothstein, T. L., Lencz, T., & Malhotra, A. K. (2018) · Schizophrenia Research · doi:10.1016/j.schres.2018.07.019 · Cited by 107
Electronic health records and polygenic risk scores for predicting disease risk
Li, R., Chen, Y., Ritchie, M. D., & Moore, J. H. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0224-1 · Cited by 106
Mammalian brain glycoproteins exhibit diminished glycan complexity compared to other tissues
Williams, S., Noël, M., Lehoux, S. D., Çetinbaş, M., Xavier, R. J., Sadreyev, R. I., Scolnick, E. M., Smoller, J. W., Cummings, R. D., & Mealer, R. G. (2022) · Nature Communications · doi:10.1038/s41467-021-27781-9 · Cited by 107
What genes are differentially expressed in individuals with schizophrenia? A systematic review
Merikangas, A. K., Shelly, M., Knighton, A., Kotler, N., Tanenbaum, N., & Almasy, L. A. (2022) · Molecular Psychiatry · doi:10.1038/s41380-021-01420-7 · Cited by 110
Kember, R. L., Vickers‐Smith, R., Xu, H., Toikumo, S., Niarchou, M., Zhou, H., Hartwell, E. E., Crist, R. C., Rentsch, C. T., Program, M. V., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01160-z · Cited by 104
Thorup, A. A. E., Jepsen, J. R. M., Ellersgaard, D., Burton, B. K., Christiani, C. J., Hemager, N., Skjærbæk, M., Ranning, A., Spang, K. S., Gantriis, D. L., et al. (2015) · BMC Psychiatry · doi:10.1186/s12888-015-0616-5 · Cited by 111
Substantial DNA methylation differences between two major neuronal subtypes in human brain
Kozlenkov, A., Wang, M., Roussos, P., Rudchenko, S., Barbu, M., Bibikova, M. V., Klotzle, B., Dwork, A. J., Zhang, B., Hurd, Y. L., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1304 · Cited by 130
Ludwig, K. U., Böhmer, A. C., Bowes, J., Nikolić, M., Ishorst, N., Wyatt, N., Hammond, N. L., Gölz, L., Thieme, F., Barth, S., et al. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx012 · Cited by 106
Fraguas, D., Díaz‐Caneja, C. M., Rodríguez-Quiroga, A., & Arango, C. (2017) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyx015 · Cited by 106
Classics in Chemical Neuroscience: Ketamine
Tyler, M. W., Yourish, H. B., Ionescu, D. F., & Haggarty, S. J. (2017) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.7b00074 · Cited by 108
Immune-inflammatory markers and psychosis risk: A systematic review and meta-analysis
Misiak, B., Bartoli, F., Carrà, G., Stańczykiewicz, B., Gładka, A., Frydecka, D., Samochowiec, J., Jarosz, K., Hadryś, T., & Miller, B. J. (2021) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2021.105200 · Cited by 107
Chen, C., Zhang, C., Cheng, L., Reilly, J. L., Bishop, J. R., Sweeney, J. A., Chen, H., Gershon, E. S., & Liu, C. (2014) · Bipolar Disorders · doi:10.1111/bdi.12255 · Cited by 105
Rannals, M. D., Hamersky, G. R., Page, S. C., Campbell, M. N., Briley, A., Gallo, R. A., Phan, B. N., Hyde, T. M., Kleinman, J. E., Shin, J. H., et al. (2016) · Neuron · doi:10.1016/j.neuron.2016.02.021 · Cited by 106
Gialluisi, A., Andlauer, T. F. M., Mirza‐Schreiber, N., Moll, K., Becker, J., Hoffmann, P., Ludwig, K. U., Czamara, D., Pourcain, B. S., Brandler, W. M., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0402-0 · Cited by 111
Challenges and Future Prospects of Precision Medicine in Psychiatry
Manchia, M., Pisanu, C., Squassina, A., & Carpiniello, B. (2020) · Pharmacogenomics and Personalized Medicine · doi:10.2147/pgpm.s198225 · Cited by 109
Epigenomic Dysregulation in Schizophrenia: In Search of Disease Etiology and Biomarkers
Khavari, B., & Cairns, M. J. (2020) · Cells · doi:10.3390/cells9081837 · Cited by 115
The Microbiota–Gut–Brain Axis: Psychoneuroimmunological Insights
Marano, G., Mazza, M., Lisci, F. M., Ciliberto, M., Traversi, G., Kotzalidis, G. D., Berardis, D. D., Laterza, L., Sani, G., Gasbarrini, A., et al. (2023) · Nutrients · doi:10.3390/nu15061496 · Cited by 116
Liu, C. H., Keshavan, M. S., Tronick, E., & Seidman, L. J. (2015) · Schizophrenia Bulletin · doi:10.1093/schbul/sbv047 · Cited by 104
Duan, J., Shi, J., Fiorentino, A., Leites, C., Chen, X., Moy, W., Chen, J., Alexandrov, B. S., Usheva, A., S, D. H. B., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.11.001 · Cited by 107
Homann, O. R., Misura, K. M. S., Lamas, E., Sandrock, R. W., Nelson, P., McDonough, S. I., & DeLisi, L. E. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.24 · Cited by 105
Collste, K., Plavén‐Sigray, P., Fatouros‐Bergman, H., Victorsson, P. I., Schain, M., Forsberg, A., Amini, N., Aeinehband, S., Farde, L., Flyckt, L., et al. (2017) · Molecular Psychiatry · doi:10.1038/mp.2016.247 · Cited by 104
Levchenko, А., Kanapin, A. A., Samsonova, A. A., & Gainetdinov, R. R. (2017) · Genome Biology and Evolution · doi:10.1093/gbe/evx240 · Cited by 107
Forrest, M. P., Hill, M., Kavanagh, D. H., Tansey, K. E., Waite, A. J., & Blake, D. J. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx164 · Cited by 107
Transcriptome analysis in whole blood reveals increased microbial diversity in schizophrenia
Loohuis, L. M. O., Mangul, S., Ori, A. P. S., Jospin, G., Koslicki, D., Yang, H. T., Wu, T., Boks, M. P., Lomen‐Hoerth, C., Wiedau‐Pazos, M., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0107-9 · Cited by 106
Childhood adversity and psychosis: a systematic review of bio-psycho-social mediators and moderators
Sideli, L., Murray, R. M., Schimmenti, A., Corso, M., Barbera, D. L., Trotta, A., & Fisher, H. L. (2020) · Psychological Medicine · doi:10.1017/s0033291720002172 · Cited by 119
COVID-19 and psychosis risk: real or delusional concern?
Watson, C. J., Thomas, R. H., Solomon, T., Michael, B. D., Nicholson, T. R., & Pollak, T. A. (2021) · Neuroscience Letters · doi:10.1016/j.neulet.2020.135491 · Cited by 103
Analyzing the Role of MicroRNAs in Schizophrenia in the Context of Common Genetic Risk Variants
Hauberg, M. E., Roussos, P., Grove, J., Børglum, A. D., & Mattheisen, M. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.3018 · Cited by 105
Fernández-Egea, E., Vértes, P. E., Flint, S. M., Turner, L., Mustafa, S. J., Hatton, A., Smith, K. G. C., Lyons, P., & Bullmore, E. T. (2016) · PLoS ONE · doi:10.1371/journal.pone.0155631 · Cited by 106
SorCS2 is required for BDNF-dependent plasticity in the hippocampus
Glerup, S., Bølcho, U., Mølgaard, S., Boggild, S., Vægter, C. B., Smith, A. H., Nieto-González, J. L., Ovesen, P. L., Pedersen, L. F., Fjorback, A. N., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.108 · Cited by 99
Associations between Polygenic Risk for Psychiatric Disorders and Substance Involvement
Carey, C. E., Arpana Agrawal, A., Bucholz, K. K., Hartz, S. M., Lynskey, M. T., Nelson, E. C., Bierut, L. J., & Bogdan, R. (2016) · Frontiers in Genetics · doi:10.3389/fgene.2016.00149 · Cited by 107
High-resolution genetic mapping of putative causal interactions between regions of open chromatin
Kumasaka, N., Knights, A. J., & Gaffney, D. J. (2018) · Nature Genetics · doi:10.1038/s41588-018-0278-6 · Cited by 103
Neurobiological functions of transcriptional enhancers
Nord, A. S., & West, A. E. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0538-5 · Cited by 106
Meta‐analysis of total and differential white blood cell counts in schizophrenia
Jackson, A. J., & Miller, B. J. (2019) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13140 · Cited by 105
Potential Roles of Redox Dysregulation in the Development of Schizophrenia
Perkins, D. O., Jeffries, C. D., & Do, K. Q. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.03.016 · Cited by 103
Li, K. W., Gonzalez‐Lozano, M. A., Koopmans, F., & Smit, A. B. (2020) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2020.564446 · Cited by 104
Parellada, E., & Gassó, P. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01385-9 · Cited by 108
Munawar, N., Ahsan, K., Muhammad, K., Ahmad, A., Anwar, M. A., Shah, I., Ameri, A. A., & Mughairbi, F. A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22147671 · Cited by 107
Immuno-Modulatory Effects of Intervertebral Disc Cells
Bermudez‐Lekerika, P., Crump, K. B., Tseranidou, S., Nüesch, A., Kanelis, E., Alminnawi, A., Baumgartner, L., Muñoz‐Moya, E., Compte, R., Gualdi, F., et al. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.924692 · Cited by 103
Phenotype-Specific Enrichment of Mendelian Disorder Genes near GWAS Regions across 62 Complex Traits
Freund, M. K., Burch, K. S., Shi, H., Mancuso, N., Kichaev, G., Garske, K. M., Pan, D. Z., Miao, Z., Mohlke, K. L., Laakso, M., et al. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.08.017 · Cited by 102
HDAC1 links early life stress to schizophrenia-like phenotypes
Bahari-Javan, S., Varbanov, H., Halder, R., Benito, E., Kaurani, L., Burkhardt, S., Anderson-Schmidt, H., Anghelescu, I., Budde, M., Stilling, R. M., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1613842114 · Cited by 101
Kočovská, E., Gaughran, F., Krivoy, A., & Meier, U. (2017) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2017.00047 · Cited by 107
Kinetics of Cytokine Levels during Antipsychotic Treatment in Schizophrenia: A Meta-Analysis
Roméo, B., Brunet-Lecomte, M., Martelli, C., & Benyamina, A. (2018) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyy062 · Cited by 104
Hill, W. D., Weiß, A., Liewald, D. C. M., Davies, G., Porteous, D. J., Hayward, C., McIntosh, A. M., Galé, C. R., & Deary, I. J. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0387-3 · Cited by 104
Mongan, D., Föcking, M., Healy, C., Susai, S. R., Heurich, M., Wynne, K. J., Nelson, B., McGorry, P. D., Amminger, G. P., Nordentoft, M., et al. (2020) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2020.2459 · Cited by 102
Kraepelin revisited: schizophrenia from degeneration to failed regeneration
Falkai, P., Rossner, M. J., Schulze, T. G., Hasan, A., Brzózka, M. M., Malchow, B., Honer, W. G., & Schmitt, A. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.35 · Cited by 106
Ruzicka, W. B., Subburaju, S., & Benes, F. M. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.49 · Cited by 101
Disciplined approach to drug discovery and early development
Plenge, R. M. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aaf2608 · Cited by 102
Heilmann‐Heimbach, S., Herold, C., Hochfeld, L. M., Hillmer, A. M., Nyholt, D. R., Hecker, J., Javed, A., Chew, E. G. Y., Pechlivanis, S., Drichel, D., et al. (2017) · Nature Communications · doi:10.1038/ncomms14694 · Cited by 101
Common Variant Burden Contributes to the Familial Aggregation of Migraine in 1,589 Families
Gormley, P., Kurki, M., Hiekkala, M. E., Veerapen, K., Häppölä, P., Mitchell, A. A., Lal, D., Palta, P., Surakka, I. L., Kaunisto, M. A., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.04.014 · Cited by 102
The association between neonatal vitamin D status and risk of schizophrenia
Eyles, D. W., Trzaskowski, M., Vinkhuyzen, A. A. E., Mattheisen, M., Meier, S. M., Gooch, H. M., Anggono, V., Cui, X., Tan, M. C., Burne, T. H. J., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-35418-z · Cited by 104
Reus, L. M., Shen, X., Gibson, J., Wigmore, E. M., Ligthart, L., Adams, M. J., Davies, G., Cox, S. R., Hagenaars, S. P., Bastin, M. E., et al. (2017) · Scientific Reports · doi:10.1038/srep42140 · Cited by 98
Sanchez‐Roige, S., Fontanillas, P., Elson, S. L., The 23andMe Research Team, Gray, J. C., de Wit, H., Davis, L. K., MacKillop, J., & Palmer, A. A. (2019) · Addiction Biology · doi:10.1111/adb.12574 · Cited by 101
Fakhfouri, G., Rahimian, R., Dyhrfjeld‐Johnsen, J., Zirak, M. R., & Beaulieu, J. (2019) · Pharmacological Reviews · doi:10.1124/pr.118.015487 · Cited by 105
Breen, M. S., Dobbyn, A. L., Li, Q., Roussos, P., Hoffman, G. E., Stahl, E. A., Chess, A. J., Sklar, P. B., Li, J. B., Devlin, B., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0463-7 · Cited by 107
Romero-García, R., Seidlitz, J., Whitaker, K. J., Morgan, S. E., Fonagy, P., Dolan, R. J., Jones, P. B., Goodyer, I. M., Suckling, J., Bullmore, E. T., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.12.005 · Cited by 104
Dissecting polygenic signals from genome-wide association studies on human behaviour
Abdellaoui, A., & Verweij, K. J. H. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01110-y · Cited by 104
Dedic, N., Dworak, H., Zeni, C. M., Rutigliano, G., & Howes, O. D. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222413185 · Cited by 104
MacDonald, H. J., Kleppe, R., Szigetvari, P. D., & Haavik, J. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1492126 · Cited by 124
Antipsychotic treatment of schizophrenia: An update
Bruijnzeel, D. M., Suryadevara, U., & Tandon, R. (2014) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2014.08.002 · Cited by 105
Social and non-social autism symptoms and trait domains are genetically dissociable
Warrier, V., Toro, R., Won, H., Leblond, C. S., Cliquet, F., Delorme, R., De Witte, W., Bralten, J., Chakrabarti, B., Børglum, A. D., et al. (2019) · Communications Biology · doi:10.1038/s42003-019-0558-4 · Cited by 94
Atypical Lateralization in Neurodevelopmental and Psychiatric Disorders: What Is the Role of Stress?
Berretz, G., Wolf, O. T., Güntürkün, O., & Ocklenburg, S. (2020) · Cortex · doi:10.1016/j.cortex.2019.12.019 · Cited by 100
Bulik, C. M., Blake, L. E., & Austin, J. (2019) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2018.10.007 · Cited by 129
Zhao, D., Lin, M., Chen, J., Pedrosa, E., Hrabovsky, A., Fourcade, H. M., Zheng, D., & Lachman, H. M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0132387 · Cited by 108
Lenzenweger, M. F. (2015) · Schizophrenia Bulletin · doi:10.1093/schbul/sbu184 · Cited by 102
Li, J., Wilkinson, B., Clementel, V. A., Hou, J., O’Dell, T. J., & Coba, M. P. (2016) · Science Signaling · doi:10.1126/scisignal.aaf6716 · Cited by 95
Ganna, A., Genovese, G., Howrigan, D. P., Byrnes, A., Kurki, M., Zekavat, S. M., Whelan, C. W., Kals, M., Nivard, M. G., Bloemendal, A., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4404 · Cited by 89
Klein, M., Onnink, A. M. H., van Eijk, K. R., Wolfers, T., Harich, B., Shi, Y., Dammers, J. T., Vásquez, A. A., Hoogman, M., & Franke, B. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.01.013 · Cited by 116
Comes, A. L., Papiol, S., Müeller, T., Geyer, P. E., Mann, M., & Schulze, T. G. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0219-2 · Cited by 107
DiPrete, T. A., Burik, C. A. P., & Koellinger, P. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707388115 · Cited by 100
Reynolds, R. H., Botía, J. A., Nalls, M. A., Noyce, A. J., Nicolas, A., Cookson, M., Bandrés‐Ciga, S., Gibbs, J. R., Hernandez, D. G., Singleton, A., et al. (2019) · npj Parkinson s Disease · doi:10.1038/s41531-019-0076-6 · Cited by 101
Smeland, O. B., Shadrin, A. A., Bahrami, S., Broce, I., Tesli, M., Frei, O., Wirgenes, K. V., O’Connell, K. S., Krull, F., Bettella, F., et al. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.01.026 · Cited by 98
Jaffe, A. E., Hoeppner, D. J., Saito, T., Blanpain, L. T., Ukaigwe, J., Burke, E. E., Collado‐Torres, L., Tao, R., Tajinda, K., Maynard, K. R., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0604-z · Cited by 96
Detection of Circulating miRNA Levels in Schizophrenia
Wei, H., Yuan, Y., Liu, S., Wang, C., Yang, F., Lu, Z. F., Wang, C., Deng, H., Zhao, J., Shen, Y., et al. (2015) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2015.14030273 · Cited by 100
Epigenetics and depressive disorders: a review of current progress and future directions
Januar, V., Saffery, R., & Ryan, J. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyu273 · Cited by 99
Metadata
- Authors
- Schizophrenia Working Group of the Psychiatric Genomics Consortium
- Venue
- Nature
- Published
- 2014-07
- Volume
- 511
- Issue
- 7510
- Pages
- 421-427
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4112379
- OpenAlex
- W2101357408
- Semantic Scholar
- 4d7a4017e4ebdf3380f5f84f759a51ffd3cba04d
- Cited by
- 7,577
- References
- 56
- Citations by year
- 2026: 196 · 2025: 336 · 2024: 452 · 2023: 497 · 2022: 657 · 2021: 763 · 2020: 826 · 2019: 856 · 2018: 767 · 2017: 812 · 2016: 713 · 2015: 563 · 2014: 133
- FWCI
- 566.07
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- PubMed Central (acceptedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- Lirias (KU Leuven) (submittedVersion, other-oa)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- Arrow@dit (Dublin Institute of Technology) (submittedVersion, cc-by-nc-sa)
- ARAN (University of Galway Research Repository) (Ollscoil na Gaillimhe – University of Galway) (submittedVersion, cc-by-nc-nd)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- University of Regensburg Publication Server (University of Regensburg) (submittedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Institutional Research Information System (Università degli Studi di Trento) (submittedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- GRO (submittedVersion, cc-by)
- Pure Amsterdam UMC (submittedVersion)
- Research Portal (Queen's University Belfast) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
- University of Galway Research Repository (submittedVersion, cc-by-nc)
- Trinity's Access to Research Output (TARA) (Trinity College Dublin) (submittedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Hirsla (Landspítali University Hospital) (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- UNC Libraries
- Funders
- U.S. Department of Veterans Affairs (I01BX001356, I01BX002395)
- Eli Lilly and Company
- Pfizer
- Massachusetts General Hospital
- Emory University
- Aarhus Universitet
- Virginia Commonwealth University
- Wellcome Trust
- Broad Institute
- National Institute for Health and Care Research (PDA/02/06/016)
- King's College London
- Cardiff University
- Trinity College Dublin
- Lundbeckfonden (R155-2014-1724)
- Karolinska Institutet
- Danmarks Tekniske Universitet
- Universitetet i Oslo
- Diakonhjemmet
- H. Lundbeck A/S
- National Institutes of Health (5u01mh094432-04)
- Stanley Center for Psychiatric Research, Broad Institute
- Medical Research Council (MR/L010305/1)
- National Institute of Mental Health (U01MH096296, R01MH077139, U01 MH094432, MH094421, R01MH100141, U01MH094421, K99MH101367, R01MH085548, R01MH040799, T32MH020030)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- schizophrenia, genetic susceptibility loci, genome-wide association study, polygenic inheritance, brain-expressed genes, glutamatergic neurotransmission, DRD2, immune system, etiology of schizophrenia, therapeutic target
- MeSH terms
- Alleles, Brain, Enhancer Elements, Genetic, Humans, Immunity, Mutation, Synaptic Transmission, Schizophrenia, Odds Ratio, Glutamic Acid, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, 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