Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs

Abstract

Schizophrenia is a complex disorder caused by both genetic and environmental factors. Using 9,087 affected individuals, 12,171 controls and 915,354 imputed SNPs from the Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (PGC-SCZ), we estimate that 23% (s.e. = 1%) of variation in liability to schizophrenia is captured by SNPs. We show that a substantial proportion of this variation must be the result of common causal variants, that the variance explained by each chromosome is linearly related to its length (r = 0.89, P = 2.6 × 10(-8)), that the genetic basis of schizophrenia is the same in males and females, and that a disproportionate proportion of variation is attributable to a set of 2,725 genes expressed in the central nervous system (CNS; P = 7.6 × 10(-8)). These results are consistent with a polygenic genetic architecture and imply more individual SNP associations will be detected for this disease as sample size increases.

Figure 1

Genomic partitioning of schizophrenia. a) By chromosome: Estimated proportion of the variance in liability to schizophrenia explained bySNPs on individual chromosomes from a joint analysis of all chromosomes simultaneously or separate analyses for each chromosome The sum of the h² is 0.23 for the joint analysis and 0.26 for the separate analyses. b) By annotation; the total variance explained by SNPs ( h² ) in CNS+ genes, other genes and by those not in genes totals 0.23. Of this, a proportion 0.31 is attributed to SNPs in brain genes, which is greater than expected by chance (p = 7.6 × 10⁻⁸) given that the brain genes cover 0.20 of the length of the genome (Mb) and represent 0.21 of the SNP count (N SNPs). Error bars represent the 95% confidence intervals of the estimates. c) By MAF bin from analyses fitting MAF bins jointly or each separately d) By MAF bin compared to simulation under a rare variants only model. The variance explained by SNPs in each MAF bin (when MAF bins are fitted in separate analyses) as a proportion of the variance explained by all SNPs. Error bars represent 95% confidence intervals, for the simulations (right graph) these are calculated using the standard deviation across simulation replicates.

Figure 1

Genomic partitioning of schizophrenia. a) By chromosome: Estimated proportion of the variance in liability to schizophrenia explained bySNPs on individual chromosomes from a joint analysis of all chromosomes simultaneously or separate analyses for each chromosome The sum of the h² is 0.23 for the joint analysis and 0.26 for the separate analyses. b) By annotation; the total variance explained by SNPs ( h² ) in CNS+ genes, other genes and by those not in genes totals 0.23. Of this, a proportion 0.31 is attributed to SNPs in brain genes, which is greater than expected by chance (p = 7.6 × 10⁻⁸) given that the brain genes cover 0.20 of the length of the genome (Mb) and represent 0.21 of the SNP count (N SNPs). Error bars represent the 95% confidence intervals of the estimates. c) By MAF bin from analyses fitting MAF bins jointly or each separately d) By MAF bin compared to simulation under a rare variants only model. The variance explained by SNPs in each MAF bin (when MAF bins are fitted in separate analyses) as a proportion of the variance explained by all SNPs. Error bars represent 95% confidence intervals, for the simulations (right graph) these are calculated using the standard deviation across simulation replicates.

Figure 1

Genomic partitioning of schizophrenia. a) By chromosome: Estimated proportion of the variance in liability to schizophrenia explained bySNPs on individual chromosomes from a joint analysis of all chromosomes simultaneously or separate analyses for each chromosome The sum of the h² is 0.23 for the joint analysis and 0.26 for the separate analyses. b) By annotation; the total variance explained by SNPs ( h² ) in CNS+ genes, other genes and by those not in genes totals 0.23. Of this, a proportion 0.31 is attributed to SNPs in brain genes, which is greater than expected by chance (p = 7.6 × 10⁻⁸) given that the brain genes cover 0.20 of the length of the genome (Mb) and represent 0.21 of the SNP count (N SNPs). Error bars represent the 95% confidence intervals of the estimates. c) By MAF bin from analyses fitting MAF bins jointly or each separately d) By MAF bin compared to simulation under a rare variants only model. The variance explained by SNPs in each MAF bin (when MAF bins are fitted in separate analyses) as a proportion of the variance explained by all SNPs. Error bars represent 95% confidence intervals, for the simulations (right graph) these are calculated using the standard deviation across simulation replicates.