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.
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ABSTRACT: Objective: Clinically, attention-deficit/hyperactivity disorder (ADHD) is characterized by hyperactivity, impulsivity, and inattention and is among the most common childhood disorders. These same traits that define ADHD are variable in the general population, and the clinical diagnosis may represent the extreme end of a continuous distribution of inattentive and hyperactive behaviors. This hypothesis can be tested by assessing the predictive value of polygenic risk scores derived from a discovery sample of ADHD patients in a target sample from the general population with continuous scores of inattention and hyperactivity. In addition, the genetic overlap between ADHD and continuous ADHD scores can be tested across rater and age. Method: The Psychiatric Genomics Consortium has performed the largest genome-wide analysis (GWA) study of ADHD so far, including 5,621 clinical patients and 13,589 controls. The effects sizes of single nucleotide polymorphisms (SNPs) estimated in this meta-analysis were used to obtain individual polygenic risk scores in an independent population-based cohort of 2,437 children from the Netherlands Twin Register. The variance explained in Attention Problems scale scores by the polygenic risk scores was estimated by linear mixed modeling. Results: The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of attention problems in preschool and school-age children. Conclusion: These results indicate genetic overlap between a diagnosis of ADHD and Attention Problems scale scores across raters and age groups and provides evidence for a dimensional model of ADHD. Future GWA studies on ADHD can likely benefit from the inclusion of population-based cohorts and the analysis of continuous scores.Journal of the American Academy of Child & Adolescent Psychiatry 08/2014; · 6.35 Impact Factor
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ABSTRACT: Biomarkers are biological measures that are indicative of a specific disorder, its severity or response to treatment. They are widely used in many areas of medicine, but biomarker development for brain-based disorders lags behind. Using examples from the field of psychiatry, this article reviews the concepts of biomarkers, challenges to their development and the recent progress along those lines. In addition to discussing historical biomarker candidates such as cortisol or catecholamine levels, we include progress from recent genetic, epigenetic, proteomic, neuroimaging and EEG studies. Successful identification of biomarkers will advance the field of psychiatry towards the goal of biological tests for diagnosis, symptom management and treatment response.Journal of Comparative Neurology and Psychology 11/2013; 1(2):7.
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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; · 4.43 Impact Factor