Annotation of functional variation within non-MHC MS susceptibility loci through bioinformatics analysis

Mining Complex Genetic Patterns Conferring Multiple Sclerosis Risk

(1) Background: Complex genetic relationships, including gene-gene (G × G; epistasis), gene(n), and gene-environment (G × E) interactions, explain a substantial portion of the heritability in multiple sclerosis (MS). Machine learning and data mining methods are promising approaches for uncovering higher order genetic relationships, but their use in MS have been limited. (2) Methods: Association rule mining (ARM), a combinatorial rule-based machine learning algorithm, was applied to genetic data for non-Latinx MS cases (n = 207) and controls (n = 179). The objective was to identify patterns (rules) amongst the known MS risk variants, including HLA-DRB1*15:01 presence, HLA-A*02:01 absence, and 194 of the 200 common autosomal variants. Probabilistic measures (confidence and support) were used to mine rules. (3) Results: 114 rules met minimum requirements of 80% confidence and 5% support. The top ranking rule by confidence consisted of HLA-DRB1*15:01, SLC30A7-rs56678847 and AC093277.1-rs6880809; carriers of these variants had a significantly greater risk for MS (odds ratio = 20.2, 95% CI: 8.5, 37.5; p = 4 × 10⁻⁹). Several variants were shared across rules, the most common was INTS8-rs78727559, which was in 32.5% of rules. (4) Conclusions: In summary, we demonstrate evidence that specific combinations of MS risk variants disproportionately confer elevated risk by applying a robust analytical framework to a modestly sized study population.

Genetic Variants and Multiple Sclerosis Risk Gene SLC9A9 Expression in Distinct Human Brain Regions

A recent genome-wide association study reported a significant association between rs9828519 (G) and nonresponsiveness to interferon-beta (IFN-β) treatment and dysregulation of SLC9A9 expression in multiple sclerosis (MS) cases. We hypothesize that disease-relevant tissues are necessary to detect the effects of rs9828519-tagged SNPs on SLC9A9 expression. Here, we investigated whether SLC9A9 expression is regulated by rs9828519-tagged SNPs in human brain tissue. We used HaploReg to identify the proxy SNPs of the rs9828519 variant based on linkage disequilibrium information from the 1000 Genomes Project. We evaluated the potential association between these SNPs and SLC9A9 expression using multiple expression quantitative trait loci datasets including 10 brain regions of 134 individuals from Braineac, 2 brain regions of 773 samples from brain expression GWAS datasets, and 12 brain regions from the GTEx. We discovered differential SLC9A9 expression in different brain regions and identified 15 rs9828519-tagged SNPs that significantly regulated SLC9A9 expression only in occipital cortex, intralobular white matter, and substantia nigra. Our results advance the understanding of the involvement of SLC9A9 and rs9828519 mechanisms in MS.

Meta-Analysis of Differential Connectivity in Gene Co-Expression Networks in Multiple Sclerosis

Differential gene expression analyses to investigate multiple sclerosis (MS) molecular pathogenesis cannot detect genes harboring genetic and/or epigenetic modifications that change the gene functions without affecting their expression. Differential co-expression network approaches may capture changes in functional interactions resulting from these alterations. We re-analyzed 595 mRNA arrays from publicly available datasets by studying changes in gene co-expression networks in MS and in response to interferon (IFN)-β treatment. Interestingly, MS networks show a reduced connectivity relative to the healthy condition, and the treatment activates the transcription of genes and increases their connectivity in MS patients. Importantly, the analysis of changes in gene connectivity in MS patients provides new evidence of association for genes already implicated in MS by single-nucleotide polymorphism studies and that do not show differential expression. This is the case of amiloride-sensitive cation channel 1 neuronal (ACCN1) that shows a reduced number of interacting partners in MS networks, and it is known for its role in synaptic transmission and central nervous system (CNS) development. Furthermore, our study confirms a deregulation of the vitamin D system: among the transcription factors that potentially regulate the deregulated genes, we find TCF3 and SP1 that are both involved in vitamin D3-induced p27Kip1 expression. Unveiling differential network properties allows us to gain systems-level insights into disease mechanisms and may suggest putative targets for the treatment.

Allelic imbalance of multiple sclerosis susceptibility genes IKZF3 and IQGAP1 in human peripheral blood

Background

Multiple sclerosis is a chronic inflammatory, demyelinating disease of the central nervous system. Recent genome-wide studies have revealed more than 110 single nucleotide polymorphisms as associated with susceptibility to multiple sclerosis, but their functional contribution to disease development is mostly unknown.

Results

Consistent allelic imbalance was observed for rs907091 in IKZF3 and rs11609 in IQGAP1, which are in strong linkage disequilibrium with the multiple sclerosis associated single nucleotide polymorphisms rs12946510 and rs8042861, respectively. Using multiple sclerosis patients and healthy controls heterozygous for rs907091 and rs11609, we showed that the multiple sclerosis risk alleles at IKZF3 and IQGAP1 are expressed at higher levels as compared to the protective allele. Furthermore, individuals homozygous for the multiple sclerosis risk allele at IQGAP1 had a significantly higher total expression of IQGAP1 compared to individuals homozygous for the protective allele.

Conclusions

Our data indicate a possible regulatory role for the multiple sclerosis-associated IKZF3 and IQGAP1 variants. We suggest that such cis-acting mechanisms may contribute to the multiple sclerosis association of single nucleotide polymorphisms at IKZF3 and IQGAP1.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0367-4) contains supplementary material, which is available to authorized users.

Epstein-Barr virus and multiple sclerosis. From evidence to therapeutic strategies

Multiple sclerosis is caused by a complex interaction between genetic predisposition and environmental factors. Epstein-Barr virus (EBV) is an environmental risk factor that is strongly related to multiple sclerosis (MS), since EBV seropositivity is linked to a significant risk of developing MS. EBV may be involved in the pathogenesis of the disease and it is possibly a prerequisite for the development of MS. EBV infection persists in B-cells during the lifetime of the host and can modulate their function. In addition, MS patients might have a deficient capacity to eliminate latent EBV infection in the central nervous system and this would promote the accumulation of infected B cells. Several mechanisms of pathogenesis, including a direct and indirect function of infected B cells, have been postulated in inflammation and neurodegeneration. A relationship between EBV and human endogenous retroviruses in the pathogenesis of MS has also been reported. If EBV is important in the pathogenesis of MS, different therapeutic strategies seem possible for MS treatment.

Role of socioeconomic position in multiple sclerosis etiology

Multiple sclerosis (MS) is a debilitating autoimmune disease with a prominent inflammatory component. There have been strides identifying genetic and environmental MS risk factors, though much of the disease risk remains unknown. Recent large observational studies suggest adverse socioeconomic position increases the risk for MS, however the mediating biological processes are not understood. We hypothesize a prominent role for stress response, both the autonomic nervous system and the hypothalamic–pituitary–adrenal axis, which become maladaptive under frequent or chronic stimulation resulting in a proinflammatory phenotype. Thus, adverse SEP and chronic stress may predispose individuals for MS.