Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk.

Multiple sclerosis is a complex neurological disease, with ∼20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFNγ biology, and NFκB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS

Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility.

We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects and established a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 variants within the extended MHC. We used an ensemble of methods to prioritize 551 putative susceptibility genes that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we observed enrichment for MS genes in these brain-resident immune cells, suggesting that these may have a role in targeting an autoimmune process to the central nervous system, although MS is most likely initially triggered by perturbation of peripheral immune responses.Cambridge NIHR Biomedical Research Centre UK MS Societ

Author Correction: A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Peer reviewe

Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Peer reviewe

A robust clustering algorithm for identifying problematic samples in genome-wide association studies

Summary: High-throughput genotyping arrays provide an efficient way to survey single nucleotide polymorphisms (SNPs) across the genome in large numbers of individuals. Downstream analysis of the data, for example in genome-wide association studies (GWAS), often involves statistical models of genotype frequencies across individuals. The complexities of the sample collection process and the potential for errors in the experimental assay can lead to biases and artefacts in an individual's inferred genotypes. Rather than attempting to model these complications, it has become a standard practice to remove individuals whose genome-wide data differ from the sample at large. Here we describe a simple, but robust, statistical algorithm to identify samples with atypical summaries of genome-wide variation. Its use as a semi-automated quality control tool is demonstrated using several summary statistics, selected to identify different potential problems, and it is applied to two different genotyping platforms and sample collections

A second major histocompatibility complex susceptibility locus for multiple sclerosis

Objective: Variation in the major histocompatibility complex (MHC) on chromosome 6p21 is known to influence susceptibility to multiple sclerosis with the strongest effect originating from the HLA-DRB1 gene in the class II region. The possibility that other genes in the MHC independently influence susceptibility to multiple sclerosis has been suggested but remains unconfirmed. Methods: Using a combination of microsatellite, single nucleotide polymorphism, and human leukocyte antigen (HLA) typing, we screened the MHC in trio families looking for evidence of residual association above and beyond that attributable to the established DRB1*1501 risk haplotype. We then refined this analysis by extending the genotyping of classical HLA loci into independent cases and control subjects. Results: Screening confirmed the presence of residual association and suggested that this was maximal in the region of the HLA-C gene. Extending analysis of the classical loci confirmed that this residual association is partly due to allelic heterogeneity at the HLA-DRB1 locus, but also reflects an independent effect from the HLA-C gene. Specifically, the HLA-C*05 allele, or a variant in tight linkage disequilibrium with it, appears to exert a protective effect (p = 3.3 × 10−5). Interpretation: Variation in the HLA-C gene influences susceptibility to multiple sclerosis independently of any effect attributable to the nearby HLA-DRB1 gene

The complex genetics of multiple sclerosis: pitfalls and prospects

The genetics of complex disease is entering a new and exciting era. The exponentially growing knowledge and technological capabilities emerging from the human genome project have finally reached the point where relevant genes can be readily and affordably identified. As a result, the last 12 months has seen a virtual explosion in new knowledge with reports of unequivocal association to relevant genes appearing almost weekly. The impact of these new discoveries in Neuroscience is incalculable at this stage but potentially revolutionary. In this review, an attempt is made to illuminate some of the mysteries surrounding complex genetics. Although focused almost exclusively on multiple sclerosis all the points made are essentially generic and apply equally well, with relatively minor addendums, to any other complex trait, neurological or otherwise

The novel endosomal membrane protein Ema interacts with the class C Vps–HOPS complex to promote endosomal maturation

Defective attenuation of BMP signaling causes synapses to overgrow in Drosophila Ema mutants due to impaired endosomal maturation