The chromosome 9p21 amyotrophic lateral sclerosis-frontotemporal dementia (ALS-FTD) locus contains one of the last major unidentified autosomal dominant genes underlying these common neurodegenerative diseases. We have previously shown that a founder haplotype, covering the MOBKL2b, IFNK and C9ORF72 genes, is present in the majority of cases linked to this region. Here we show that there is a large hexanucleotide (GGGGCC) repeat expansion in the first intron of C9ORF72 on the affected haplotype. This repeat expansion segregates perfectly with disease in the Finnish population, underlying 46.0% of familial ALS and 21.1% of sporadic ALS in that population. Taken together with the D90A SOD1 mutation, 87% of familial ALS in Finland is now explained by a simple monogenic cause. The repeat expansion is also present in one third of familial ALS cases of outbred European descent making it the most common genetic cause of these fatal neurodegenerative diseases identified to date.
Schizophrenia (SCZ) is a severe mental disorder with a lifetime risk of
about 1%, characterized by hallucinations, delusions and cognitive
deficits with heritability estimated at up to 80%1,2. We adopted two analytic approaches to determine the
extent to which common genetic variation underlies risk of SCZ using genome-wide
association study (GWAS) data from 3,322 European individuals with SCZ and 3,587
controls. First, we implicate the major histocompatibility complex (MHC).
Second, we provide molecular genetic evidence for a substantial polygenic
component to risk of SCZ involving thousands of common alleles of very small
effect. We show that this component also contributes to risk of bipolar disorder
(BPD), but not to multiple non-psychiatric diseases.
Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.
We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 × 10−11) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 × 10−9), ANK3 (rs10994359, P = 2.5 × 10−8) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 × 10−9).
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Heritability and polygenic predictionIn the EUR sample, the SNP-based heritability (h 2 SNP ) (that is, the proportion of variance in liability attributable to all measured SNPs)
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