Schizophrenia (SZ) and autism spectrum disorders (ASDs) are complex neurodevelopmental disorders that may share an underlying pathology suggested by shared genetic risk variants. We sequenced the ...exonic regions of 215 genes in 147 ASD cases, 273 SZ cases and 287 controls, to identify rare risk mutations. Genes were primarily selected for their function in the synapse and were categorized as: (1) Neurexin and Neuroligin Interacting Proteins, (2) Post-synaptic Glutamate Receptor Complexes, (3) Neural Cell Adhesion Molecules, (4) DISC1 and Interactors and (5) Functional and Positional Candidates. Thirty-one novel loss-of-function (LoF) variants that are predicted to severely disrupt protein-coding sequence were detected among 2 861 rare variants. We found an excess of LoF variants in the combined cases compared with controls (P=0.02). This effect was stronger when analysis was limited to singleton LoF variants (P=0.0007) and the excess was present in both SZ (P=0.002) and ASD (P=0.001). As an individual gene category, Neurexin and Neuroligin Interacting Proteins carried an excess of LoF variants in cases compared with controls (P=0.05). A de novo nonsense variant in GRIN2B was identified in an ASD case adding to the growing evidence that this is an important risk gene for the disorder. These data support synapse formation and maintenance as key molecular mechanisms for SZ and ASD.
Prior to the genome-wide association era, candidate gene studies were a major approach in schizophrenia genetics. In this invited review, we consider the current status of 25 historical candidate ...genes for schizophrenia (for example, COMT, DISC1, DTNBP1 and NRG1). The initial study for 24 of these genes explicitly evaluated common variant hypotheses about schizophrenia. Our evaluation included a meta-analysis of the candidate gene literature, incorporation of the results of the largest genomic study yet published for schizophrenia, ratings from informed researchers who have published on these genes, and ratings from 24 schizophrenia geneticists. On the basis of current empirical evidence and mostly consensual assessments of informed opinion, it appears that the historical candidate gene literature did not yield clear insights into the genetic basis of schizophrenia. A likely reason why historical candidate gene studies did not achieve their primary aims is inadequate statistical power. However, the considerable efforts embodied in these early studies unquestionably set the stage for current successes in genomic approaches to schizophrenia.
The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt ...to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10
). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.
Bipolar disorder and schizophrenia are two often severe disorders with high heritabilities. Recent studies have demonstrated a large overlap of genetic risk loci between these disorders but ...diagnostic and molecular distinctions still remain. Here, we perform a combined genome-wide association study (GWAS) of 19 779 bipolar disorder (BP) and schizophrenia (SCZ) cases versus 19 423 controls, in addition to a direct comparison GWAS of 7129 SCZ cases versus 9252 BP cases. In our case-control analysis, we identify five previously identified regions reaching genome-wide significance (CACNA1C, IFI44L, MHC, TRANK1 and MAD1L1) and a novel locus near PIK3C2A. We create a polygenic risk score that is significantly different between BP and SCZ and show a significant correlation between a BP polygenic risk score and the clinical dimension of mania in SCZ patients. Our results indicate that first, combining diseases with similar genetic risk profiles improves power to detect shared risk loci and second, that future direct comparisons of BP and SCZ are likely to identify loci with significant differential effects. Identifying these loci should aid in the fundamental understanding of how these diseases differ biologically. These findings also indicate that combining clinical symptom dimensions and polygenic signatures could provide additional information that may someday be used clinically.
We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data ...with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology.
The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to ...analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.
Schizophrenia is a serious psychiatric disorder with a broadly undiscovered genetic etiology. Recent studies of de novo mutations (DNMs) in schizophrenia and autism have reinforced the hypothesis ...that rare genetic variation contributes to risk. We carried out exome sequencing on 57 trios with sporadic or familial schizophrenia. In sporadic trios, we observed a ~3.5-fold increase in the proportion of nonsense DNMs (0.101 vs 0.031, empirical P=0.01, Benjamini-Hochberg-corrected P=0.044). These mutations were significantly more likely to occur in genes with highly ranked probabilities of haploinsufficiency (P=0.0029, corrected P=0.006). DNMs of potential functional consequence were also found to occur in genes predicted to be less tolerant to rare variation (P=2.01 × 10(-)(5), corrected P=2.1 × 10(-)(3)). Genes with DNMs overlapped with genes implicated in autism (for example, AUTS2, CHD8 and MECP2) and intellectual disability (for example, HUWE1 and TRAPPC9), supporting a shared genetic etiology between these disorders. Functionally CHD8, MECP2 and HUWE1 converge on epigenetic regulation of transcription suggesting that this may be an important risk mechanism. Our results were consistent in an analysis of additional exome-based sequencing studies of other neurodevelopmental disorders. These findings suggest that perturbations in genes, which function in the epigenetic regulation of brain development and cognition, could have a central role in the susceptibility to, pathogenesis and treatment of mental disorders.
The Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC) highlighted 81 single-nucleotide polymorphisms (SNPs) with moderate evidence for association to schizophrenia. After ...follow-up in independent samples, seven loci attained genome-wide significance (GWS), but multi-locus tests suggested some SNPs that did not do so represented true associations. We tested 78 of the 81 SNPs in 2640 individuals with a clinical diagnosis of schizophrenia attending a clozapine clinic (CLOZUK), 2504 cases with a research diagnosis of bipolar disorder, and 2878 controls. In CLOZUK, we obtained significant replication to the PGC-associated allele for no fewer than 37 (47%) of the SNPs, including many prior GWS major histocompatibility complex (MHC) SNPs as well as 3/6 non-MHC SNPs for which we had data that were reported as GWS by the PGC. After combining the new schizophrenia data with those of the PGC, variants at three loci (ITIH3/4, CACNA1C and SDCCAG8) that had not previously been GWS in schizophrenia attained that level of support. In bipolar disorder, we also obtained significant evidence for association for 21% of the alleles that had been associated with schizophrenia in the PGC. Our study independently confirms association to three loci previously reported to be GWS in schizophrenia, and identifies the first GWS evidence in schizophrenia for a further three loci. Given the number of independent replications and the power of our sample, we estimate 98% (confidence interval (CI) 78-100%) of the original set of 78 SNPs represent true associations. We also provide strong evidence for overlap in genetic risk between schizophrenia and bipolar disorder.
A recent genome-wide association study (GWAS) reported evidence for association between rs1344706 within ZNF804A (encoding zinc-finger protein 804A) and schizophrenia (P=1.61 × 10(-7)), and stronger ...evidence when the phenotype was broadened to include bipolar disorder (P=9.96 × 10(-9)). In this study we provide additional evidence for association through meta-analysis of a larger data set (schizophrenia/schizoaffective disorder N=18 945, schizophrenia plus bipolar disorder N=21 274 and controls N=38 675). We also sought to better localize the association signal using a combination of de novo polymorphism discovery in exons, pooled de novo polymorphism discovery spanning the genomic sequence of the locus and high-density linkage disequilibrium (LD) mapping. The meta-analysis provided evidence for association between rs1344706 that surpasses widely accepted benchmarks of significance by several orders of magnitude for both schizophrenia (P=2.5 × 10(-11), odds ratio (OR) 1.10, 95% confidence interval 1.07-1.14) and schizophrenia and bipolar disorder combined (P=4.1 × 10(-13), OR 1.11, 95% confidence interval 1.07-1.14). After de novo polymorphism discovery and detailed association analysis, rs1344706 remained the most strongly associated marker in the gene. The allelic association at the ZNF804A locus is now one of the most compelling in schizophrenia to date, and supports the accumulating data suggesting overlapping genetic risk between schizophrenia and bipolar disorder.
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