Genome-Wide Association Study of Multiplex Schizophrenia Pedigrees

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.

Genome-wide association analysis identifies 13 new risk loci for schizophrenia

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder.

No major schizophrenia locus detected on chromosome 1q in a large multicenter sample

Reports of substantial evidence for genetic linkage of schizophrenia to chromosome 1q were evaluated by genotyping 16 DNA markers across 107 centimorgans of this chromosome in a multicenter sample of 779 informative schizophrenia pedigrees. No significant evidence was observed for such linkage, nor for heterogeneity in allele sharing among the eight individual samples. Separate analyses of European-origin families, recessive models of inheritance, and families with larger numbers of affected cases also failed to produce significant evidence for linkage. If schizophrenia susceptibility genes are present on chromosome 1q, their population-wide genetic effects are likely to be small.

CNV analysis in a large schizophrenia sample implicates deletions at 16p12.1 and SLC1A1 and duplications at 1p36.33 and CGNL1

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 analysed 6,882 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 an 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 (P500kb), 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.

Literature Focus

Literature focus is a feature consisting of short abstracts highlighting recent developments of interest in the literature selected
by postgraduate researchers.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

Defining the role of common variation in the genomic and biological architecture of adult human height

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated 1/42,000, 1/43,700 and 1/49,500 SNPs explained 1/421%, 1/424% and 1/429% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/I 2-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.