A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

Mitochondrial DNA sequence variation in multiple sclerosis

Objective: To assess the influence of common mitochondrial DNA (mtDNA) sequence variation on multiple sclerosis (MS) risk in cases and controls part of an international consortium. Methods: We analyzed 115 high-quality mtDNA variants and common haplogroups from a previously published genome-wide association study among 7,391 cases from the International Multiple Sclerosis Genetics Consortium and 14,568 controls from the Wellcome Trust Case Control Consortium 2 project from 7 countries. Significant single nucleotide polymorphism and haplogroup associations were replicated in 3,720 cases and 879 controls from the University of California, San Francisco. Results: An elevated risk of MS was detected among haplogroup JT carriers from 7 pooled clinic sites (odds ratio [OR] = 1.15, 95% confidence interval [CI] = 1.07-1.24, p = 0.0002) included in the discovery study. The increased risk of MS was observed for both haplogroup T (OR = 1.17, 95% CI = 1.06-1.29, p = 0.002) and haplogroup J carriers (OR = 1.11, 95% CI = 1.01-1.22, p = 0.03). These haplogroup associations with MS were not replicated in the independent sample set. An elevated risk of primary progressive (PP) MS was detected for haplogroup J participants from 3 European discovery populations (OR = 1.49, 95% CI = 1.10-2.01, p = 0.009). This elevated risk was borderline significant in the US replication population (OR = 1.43, 95% CI = 0.99-2.08, p = 0.058) and remained significant in pooled analysis of discovery and replication studies (OR = 1.43, 95% CI = 1.14-1.81, p = 0.002). No common individual mtDNA variants were associated with MS risk. Conclusions: Identification and validation of mitochondrial genetic variants associated with MS and PPMS may lead to new targets for treatment and diagnostic tests for identifying potential responders to interventions that target mitochondria

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

Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available.status: publishe