Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Heritability and polygenic predictionIn the EUR sample, the SNP-based heritability (h 2 SNP ) (that is, the proportion of variance in liability attributable to all measured SNPs)

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Background: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies (GWASs). PGS methods differ in which DNA variants are included and the weights assigned

Several groups have reported weak evidence for linkage between schizophrenia and genetic markers located on chromosome 22q using the lod score method of analysis. However these findings involved different genetic markers and methods of analysis, and so were not directly comparable. To resolve this issue we have performed a combined analysis of genotypic data from the marker D22S278 in multiply affected schizophrenic families derived from 11 independent research groups worldwide. This marker was chosen because it showed maximum evidence for linkage in three independent datasets (Vallada et al., Am J Med Genet 60:139‐146, 1995; Polymeropoulos et al., Neuropsychiatr Genet 54:93‐99, 1994; Lasseter et al., Am J Med Genet, 60:172‐173, 1995). Using the affected sib‐pair method as implemented by the program ESPA, the combined dataset showed 252 alleles shared compared with 188 alleles not shared (chi‐square 9.31, 1df, P = 0.001) where parental genotype data was completely known. When sib‐pairs for whom parental data was assigned according to probability were included the number of alleles shared was 514.1 compared with 437.8 not shared (chi‐square 6.12, 1df, P = 0.006). Similar results were obtained when a likelihood ratio method for sib‐pair analysis was used. These results indicate that there may be a susceptibility locus for schizophrenia at 22q12. © 1996 Wiley‐Liss, Inc.

Evidence for suggestive linkage to schizophrenia with chromosome 6q markers was previously reported from a two-stage approach. Using nonparametric affected sib pairs (ASP) methods, nominal p-values of 0.00018 and 0.00095 were obtained in the screening (81 ASPs; 63 independent) and the replication (109 ASPs; 87 independent) data sets, respectively. Here, we report a follow-up study of this 50cM 6q region using 12 microsatellite markers to test for linkage to schizophrenia. We increased the replication sample size by adding an independent sample of 43 multiplex pedigrees (66 ASPs; 54 independent). Pairwise and multipoint nonparametric linkage analyses conducted in this third data set showed evidence consistent with excess sharing in this 6q region, though the statistical level is weaker (p=0.013). When combining both replication data sets (total of 141 independent ASPs), an overall nominal p-value=0.000014 (LOD=3. 82) was obtained. The sibling recurrence risk (lambdas) attributed to this putative 6q susceptibility locus is estimated to be 1.92. The linkage region could not be narrowed down since LOD score values greater than three were observed within a 13cM region. The length of this region was only slightly reduced (12cM) when using the total sample of independent ASPs (204) obtained from all three data sets. This suggests that very large sample sizes may be needed to narrow down this region by ASP linkage methods. Study of the etiological candidate genes in this region is ongoing.

and the Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances (STRATA) Consortium and the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC) IMPORTANCE About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts.OBJECTIVE To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples.DESIGN, SETTING, AND PARTICIPANTS Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]).MAIN OUTCOMES AND MEASURES GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. RESULTSThe study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r 2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r 2 = 1.09%; P = .04). CONCLUSIONS AND RELEVANCEIn this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patie...

Objective: Schizophrenia is associated with widespread brain-morphological alterations, believed to be shaped by the underlying connectome architecture. This study tests whether large-scale structural reorganization in schizophrenia relates to normative network architecture, in particular regional centrality/hubness and connectivity patterns. We examine network effects in schizophrenia across different disease stages, and transdiagnostically explore consistency of such relationships in patients with bipolar and major depressive disorder. Methods: We studied anatomical MRI scans from 2,439 adults with schizophrenia and 2,867 healthy controls from 26 ENIGMA sites. Case-control patterns of structural alterations were evaluated against two network susceptibility models: 1) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; 2) epicenter models, which identify regions whose typical connectivity profile most closely resembles the disease-related morphological alteration patterns. Both susceptibility models were tested across schizophrenia disease stages and compared to meta-analytic bipolar and major depressive disorder case-control maps. Results: In schizophrenia, regional gray matter reductions co-localized with interconnected hubs, in both the functional (r=0.58, pspin<0.0001) and structural connectome (r=0.32, pspin=0.01). Epicenters were identified in temporo-paralimbic regions, extending to frontal areas. We found unique epicenters for first-episode and early stages, and a shift from occipital to temporal-frontal epicenters in chronic stages. Transdiagnostic comparisons revealed shared epicenters in schizophrenia and bipolar, but not major depressive disorders. Conclusions: Cortical reorganization over the course of schizophrenia closely reflects brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters. The observed overlapping epicenters for schizophrenia and bipolar disorder furthermore suggest shared pathophysiological processes within the schizophrenia-bipolar-spectrum.

Numerous studies have reported association between variants in the dystrobrevin binding protein 1 (dysbindin) gene (DTNBP1) and schizophrenia. However, the pattern of results is complex and to date, no specific risk marker or haplotype has been consistently identified. The number of single nucleotide polymorphisms (SNPs) tested in these studies has ranged from 5 to 20. We attempted to replicate previous findings by testing 16 SNPs in samples of 41 Australian pedigrees, 194 Australian cases and 180 controls, and 197 Indian pedigrees. No globally significant evidence for association was observed in any sample, despite power calculations indicating sufficient power to replicate several previous findings. Possible explanations for our results include sample differences in background linkage dis-equilibrium and/or risk allele effect size, the presence of multiple risk alleles upon different haplotypes, or the presence of a single risk allele upon multiple haplotypes. Some previous associations may also represent false positives. Examination of Caucasian HapMap phase II genotype data spanning theDTNBP1region indicates upwards of 40 SNPs are required to satisfactorily assess all nonredundant variation withinDTNBP1and its potential regulatory regions for association with schizophrenia. More comprehensive studies in multiple samples will be required to determine whether specificDTNBP1variants function as risk factors for schizophrenia.