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.

We undertook a two-stage genome-wide association study of Alzheimer's disease involving over 16,000 individuals. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the APOE locus (most significant SNP: rs2075650, p= 1.8×10−157) and observed genome-wide significant association with SNPs at two novel loci: rs11136000 in the CLU or APOJ gene (p= 1.4×10−9) and rs3851179, a SNP 5′ to the PICALM gene (p= 1.9×10−8). Both novel associations were supported in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with AD in the combined dataset (rs11136000: p= 8.5×10−10, odds ratio= 0.86; rs3851179: p= 1.3×10−9, odds ratio= 0.86). We also observed more variants associated at p< 1×10−5 than expected by chance (p=7.5×10−6), including polymorphisms at the BIN1, DAB1 and CR1 loci.

BACKGROUND Homozygous loss-of-function mutations in TREM2, encoding the triggering receptor expressed on myeloid cells 2 protein, have previously been associated with an autosomal recessive form of early-onset dementia. METHODS We used genome, exome, and Sanger sequencing to analyze the genetic variability in TREM2 in a series of 1092 patients with Alzheimer's disease and 1107 controls (the discovery set). We then performed a meta-analysis on imputed data for the TREM2 variant rs75932628 (predicted to cause a R47H substitution) from three genomewide association studies of Alzheimer's disease and tested for the association of the variant with disease. We genotyped the R47H variant in an additional 1887 cases and 4061 controls. We then assayed the expression of TREM2 across different regions of the human brain and identified genes that are differentially expressed in a mouse model of Alzheimer's disease and in control mice. RESULTS We found significantly more variants in exon 2 of TREM2 in patients with Alzheimer's disease than in controls in the discovery set (P = 0.02). There were 22 variant alleles in 1092 patients with Alzheimer's disease and 5 variant alleles in 1107 controls (P<0.001). The most commonly associated variant, rs75932628 (encoding R47H), showed highly significant association with Alzheimer's disease (P<0.001). Meta-analysis of rs75932628 genotypes imputed from genomewide association studies confirmed this association (P = 0.002), as did direct genotyping of an additional series of 1887 patients with Alzheimer's disease and 4061 controls (P<0.001). Trem2 expression differed between control mice and a mouse model of Alzheimer's disease. CONCLUSIONS Heterozygous rare variants in TREM2 are associated with a significant increase in the risk of Alzheimer's disease. (Funded by Alzheimer's Research UK and others.)

Background Genome-wide association studies (GWASs) in Parkinson's disease (PD) have increased the scope of biological knowledge about the disease over the past decade. We sought to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into disease etiology. Methods We performed the largest meta-GWAS of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases (having a first degree relative with PD), and 1.4M controls. We carried out a meta-analysis of this GWAS data to nominate novel loci. We then evaluated heritable risk estimates and predictive models using this data. We also utilized large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type and biological pathway enrichments for the identified risk factors. Additionally we examined shared genetic risk between PD and other phenotypes of interest via genetic correlations followed by Mendelian randomization. Findings We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of PD depending on prevalence. Integrating methylation and expression data within a Mendelian randomization framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested PD loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. Mendelian randomization between cognitive performance and PD risk showed a robust association. Interpretation These data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified. Funding See supplemental materials (Text S2). lead to earlier detection and refined diagnostics, which may help improve clinical trials (4). The generation of copious amounts of public summary statistics created by this effort relating to both the GWAS and subsequent analyses of gene expression and methylation patterns may be of use to investigators planning follow-up functional studies in stem cells or other cellular screens, allowing them to prioritize targets more efficiently using our data as additional evidence. We hope our findings may have some downstream clinical impact in the future such as improved patient stratification for clinical trials and genetically informed drug targets.