Large and rare copy number variants (CNVs) at several loci have been shown to increase risk for schizophrenia. Aiming to discover novel susceptibility CNV loci, we analyzed 6882 cases and 11 255 controls genotyped on Illumina arrays, most of which have not been used for this purpose before. We identified genes enriched for rare exonic CNVs among cases, and then attempted to replicate the findings in additional 14 568 cases and 15 274 controls. In a combined analysis of all samples, 12 distinct loci were enriched among cases with nominal levels of significance (P < 0.05); however, none would survive correction for multiple testing. These loci include recurrent deletions at 16p12.1, a locus previously associated with neurodevelopmental disorders (P = 0.0084 in the discovery sample and P = 0.023 in the replication sample). Other plausible candidates include non-recurrent deletions at the glutamate transporter gene SLC1A1, a CNV locus recently suggested to be involved in schizophrenia through linkage analysis, and duplications at 1p36.33 and CGNL1. A burden analysis of large (>500 kb), rare CNVs showed a 1.2% excess in cases after excluding known schizophrenia-associated loci, suggesting that additional susceptibility loci exist. However, even larger samples are required for their discovery.
Previous studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.
Abstract We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05–21.6; P =1 × 10 −4 ) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS ( P =8.4 × 10 −7 ). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08–1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.
Objective: Family studies have suggested that postpartum mood symptoms might have a partly genetic etiology. The authors used a genome-wide linkage analysis to search for chromosomal regions that harbor genetic variants conferring susceptibility for such symptoms. The authors then fine-mapped their best linkage regions, assessing single nucleotide polymorphisms (SNPs) for genetic association with postpartum symptoms. Method: Subjects were ascertained from two studies: the NIMH Genetics Initiative Bipolar Disorder project and the Genetics of Recurrent Early-Onset Depression. Subjects included women with a history of pregnancy, any mood disorder, and information about postpartum symptoms. In the linkage study, 1,210 women met criteria (23% with postpartum symptoms), and 417 microsatellite markers were analyzed in multipoint allele sharing analyses. For the association study, 759 women met criteria (25% with postpartum symptoms), and 16,916 SNPs in the regions of the best linkage peaks were assessed for association with postpartum symptoms. Results: The maximum linkage peak for postpartum symptoms occurred on chromosome 1q21.3-q32.1, with a chromosome-wide significant likelihood ratio Z score (Z LR ) of 2.93 (permutation p=0.02). This was a significant increase over the baseline Z LR of 0.32 observed at this locus among all women with a mood disorder (permutation p=0.004). Suggestive linkage was also found on 9p24.3-p22.3 (Z LR =2.91). In the fine-mapping study, the strongest implicated gene was HMCN1 (nominal p=0.00017), containing four estrogen receptor binding sites, although this was not region-wide significant. Conclusions: This is the first study to examine the genetic etiology of postpartum mood symptoms using genome-wide data. The results suggest that genetic variations on chromosomes 1q21.3-q32.1 and 9p24.3-p22.3 may increase susceptibility to postpartum mood symptoms.
Objective: The authors carried out a genetic association study of 14 schizophrenia candidate genes ( RGS4, DISC1, DTNBP1, STX7, TAAR6, PPP3CC, NRG1, DRD2, HTR2A, DAOA, AKT1, CHRNA7, COMT , and ARVCF ). This study tested the hypothesis of association of schizophrenia with common single nucleotide polymorphisms (SNPs) in these genes using the largest sample to date that has been collected with uniform clinical methods and the most comprehensive set of SNPs in each gene. Method: The sample included 1,870 cases (schizophrenia and schizoaffective disorder) and 2,002 screened comparison subjects (i.e. controls), all of European ancestry, with ancestral outliers excluded based on analysis of ancestry-informative markers. The authors genotyped 789 SNPs, including tags for most common SNPs in each gene, SNPs previously reported as associated, and SNPs located in functional domains of genes such as promoters, coding exons (including nonsynonymous SNPs), 3′ untranslated regions, and conserved noncoding sequences. After extensive data cleaning, 648 SNPs were analyzed for association of single SNPs and of haplotypes. Results: Neither experiment-wide nor gene-wide statistical significance was observed in the primary single-SNP analyses or in secondary analyses of haplotypes or of imputed genotypes for additional common HapMap SNPs. Results in SNPs previously reported as associated with schizophrenia were consistent with chance expectation, and four functional polymorphisms in COMT, DRD2 , and HTR2A did not produce nominally significant evidence to support previous evidence for association. Conclusions: It is unlikely that common SNPs in these genes account for a substantial proportion of the genetic risk for schizophrenia, although small effects cannot be ruled out.
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