Genome-Wide Association Study of Multiplex Schizophrenia Pedigrees
ABSTRACT OBJECTIVE The authors used a genome-wide association study (GWAS) of multiply affected families to investigate the association of schizophrenia to common single-nucleotide polymorphisms (SNPs) and rare copy number variants (CNVs). METHOD The family sample included 2,461 individuals from 631 pedigrees (581 in the primary European-ancestry analyses). Association was tested for single SNPs and genetic pathways. Polygenic scores based on family study results were used to predict case-control status in the Schizophrenia Psychiatric GWAS Consortium (PGC) data set, and consistency of direction of effect with the family study was determined for top SNPs in the PGC GWAS analysis. Within-family segregation was examined for schizophrenia-associated rare CNVs. RESULTS No genome-wide significant associations were observed for single SNPs or for pathways. PGC case and control subjects had significantly different genome-wide polygenic scores (computed by weighting their genotypes by log-odds ratios from the family study) (best p=10-17, explaining 0.4% of the variance). Family study and PGC analyses had consistent directions for 37 of the 58 independent best PGC SNPs (p=0.024). The overall frequency of CNVs in regions with reported associations with schizophrenia (chromosomes 1q21.1, 15q13.3, 16p11.2, and 22q11.2 and the neurexin-1 gene [NRXN1]) was similar to previous case-control studies. NRXN1 deletions and 16p11.2 duplications (both of which were transmitted from parents) and 22q11.2 deletions (de novo in four cases) did not segregate with schizophrenia in families. CONCLUSIONS Many common SNPs are likely to contribute to schizophrenia risk, with substantial overlap in genetic risk factors between multiply affected families and cases in large case-control studies. Our findings are consistent with a role for specific CNVs in disease pathogenesis, but the partial segregation of some CNVs with schizophrenia suggests that researchers should exercise caution in using them for predictive genetic testing until their effects in diverse populations have been fully studied.
- SourceAvailable from: Andrew Mcquillin
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- "CNVs in COS vs healthy siblings and vs adult onset SCZ and did not therefore represent a straight forward case control study design. Likewise the study Levinson et al. (2012) was also excluded because their study was not a case control study, and the Grozeva et al. (2010) study was excluded because they had focused their analysis on a healthy control group compared with historical results in patients with SCZ. In our pre-quality control meta-analysis, we utilized a fixed effect (M-H) method and found a pooled OR "
ABSTRACT: Background In the last 5 years an increasing number of studies have found that individuals who have micro-duplications at 16p11.2 may have an increased risk of mental disorders including psychotic syndromes. Objective Our main aim was to review all the evidence in the literature for the association between copy number variants (CNVs) at 16p11.2 and psychosis. Methods We have conducted a systematic review and a meta-analysis utilising the PRISMA statement criteria. We included all original studies (published in English) which presented data on CNVs at 16p11.2 in patients affected by schizophrenia, schizoaffective disorder or bipolar disorder. Results We retrieved 15 articles which fulfilled our inclusion criteria. Eleven articles were subsequently selected for a meta-analysis that showed a 10 fold increased risk of psychosis in patients with proximal 16p11.2 duplications. We conducted a second meta-analysis of those studies with low risk of overlap in order to obtain the largest possible sample with the lowest risk of repeated results: 5 studies were selected and we found an odds ratio (OR) of 14.4 (CI = 5.2–39.8; p < 0.001) for psychosis with proximal 16p11.2 duplications. The results were not significant for micro-deletions in the same region. Finally extracting only those studies that included patients with schizophrenia we found an OR = 16.0 (CI = 5.4–47.3: p < 0.001) Conclusions There is a fourteen fold-increased risk of psychosis and a sixteen fold increased risk of schizophrenia in individuals with micro-duplication at proximal 16p11.2.Schizophrenia Research 10/2014; 159(2-3). DOI:10.1016/j.schres.2014.09.025 · 4.43 Impact Factor
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- "The molecular elements other than LCRs favoring CNV formation are poorly understood, and therefore, a good starting point would be to study regions prone to a relatively high CNV frequency, like the NRXN1 locus previously associated with schizophrenia [Kirov et al., 2008; Walsh et al., 2008; Rujescu et al., 2009; Levinson et al., 2012], autism [Kim et al., 2008; Marshall et al., 2008; Bucan et al., 2009; Glessner et al., 2009; Wis´niowiecka-Kowalnik et al., 2010], and epilepsy [Møller et al., 2013]. The high frequency of deletions found in the NRXN1 locus raises the possibility that genomic instability events in this region are commonly driven by a single mechanism. "
ABSTRACT: Genome instability plays fundamental roles in human evolution and phenotypic variation within our population. This instability leads to genomic rearrangements that are involved in a wide variety of human disorders, including congenital and neurodevelopmental disorders, and cancers. Insight into the molecular mechanisms governing such genomic rearrangements may increase our understanding of disease pathology and evolutionary processes. Here we analyse 17 carriers of non-recurrent deletions in the NRXN1 gene, which have been associated with neurodevelopmental disorders, e.g. schizophrenia, autism and epilepsies. 17 non-recurrent NRXN1 deletions identified by GWA were sequenced to map the breakpoints of each. Meme … etc. was used to identify shared patterns between the deletions and compare these were previously studies on non-recurrent deletions. We discovered two novel sequence motifs shared between all 17 NRXN1 deletions and a significantly higher AT nucleotide content at the breakpoints, compared to the overall nucleotide content on chromosome 2. We found different alteration of sequence at the breakpoint; small insertions and duplications giving rise to short microhomology sequences. No single mechanism seems to be implicated in the deletion events, but the results suggest that NHEJ, FoSTeS or MMBIR is implicated. The two novel sequence motifs together with a high AT content in all in NRXN1 deletions may lead to increased instability leading to a increase susceptibility to a single stranded structures. This favours potentially repaired by NHEJ mechanism of double strand breaks or may leading to replication errors. © 2013 Wiley Periodicals, Inc.American Journal of Medical Genetics Part B Neuropsychiatric Genetics 04/2014; 165(1):52-61. DOI:10.1002/ajmg.b.32204 · 3.27 Impact Factor
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- "miR137 (Alkelai et al., 2011, 2012; Athanasiu et al., 2010; Bergen et al., 2012; Betcheva et al., 2013; Chen et al., 2011; Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013; Ikeda et al., 2011; Irish Schizophrenia Genomics Consor- tium & Wellcome Trust Case Control Consortium 2 , 2012 ; Kirov et al . , 2009 ; Lencz et al . , 2007 ; Levinson et al . , 2012 ; Ma et al . , 2011 ; O ' Donovan et al . , 2008 ; Purcell et al . , 2009 ; Rietschel et al . , 2011 ; Ripke et al 624 E . Walton et al . for schizophrenia . We found an overall positive cor - relation between cumulative genetic risk for schizo - phrenia and WkM - related activity in the DLPFC ."
ABSTRACT: Abstract Complex, polygenic phenotypes in psychiatry hamper our understanding of the underlying molecular pathways and mechanisms of many diseases. The unknown aetiology, together with symptoms which often show a large variability both across individuals and over time and also tend to respond comparatively slowly to medication, can be a problem for patient treatment and drug development. We argue that neuroimaging has the potential to improve psychiatric treatment in two ways. First, by reducing phenotypic complexity, neuroimaging intermediate phenotypes can help to identify disease-related genes and can shed light into the biological mechanisms of known risk genes. Second, quantitative neuroimaging markers - reflecting the spectrum of impairment on a brain-based level - can be used as a more sensitive, reliable and immediate treatment response biomarker. In the end, enhancing both our understanding of the pathophysiology of psychiatric disorders and the prediction of treatment success could eventually optimise current therapy plans.International Review of Psychiatry 10/2013; 25(5):619-31. DOI:10.3109/09540261.2013.816659 · 1.80 Impact Factor