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

Bipolar disorder (BP) is a disabling and often life-threatening disorder that affects approximately 1% of the population worldwide. To identify genetic variants that increase the risk of BP, we genotyped on the Illumina HumanHap550 Beadchip 2,076 bipolar cases and 1,676 controls of European ancestry from the National Institute of Mental Health Human Genetics Initiative Repository, and the Prechter Repository and samples collected in London, Toronto, and Dundee. We imputed SNP genotypes and tested for SNP-BP association in each sample and then performed meta-analysis across samples. The strongest association P value for this 2-study meta-analysis was 2.4 x 10(-6). We next imputed SNP genotypes and tested for SNP-BP association based on the publicly available Affymetrix 500K genotype data from the Wellcome Trust Case Control Consortium for 1,868 BP cases and a reference set of 12,831 individuals. A 3-study meta-analysis of 3,683 nonoverlapping cases and 14,507 extended controls on >2.3 M genotyped and imputed SNPs resulted in 3 chromosomal regions with association P approximately 10(-7): 1p31.1 (no known genes), 3p21 (>25 known genes), and 5q15 (MCTP1). The most strongly associated nonsynonymous SNP rs1042779 (OR = 1.19, P = 1.8 x 10(-7)) is in the ITIH1 gene on chromosome 3, with other strongly associated nonsynonymous SNPs in GNL3, NEK4, and ITIH3. Thus, these chromosomal regions harbor genes implicated in cell cycle, neurogenesis, neuroplasticity, and neurosignaling. In addition, we replicated the reported ANK3 association results for SNP rs10994336 in the nonoverlapping GSK sample (OR = 1.37, P = 0.042). Although these results are promising, analysis of additional samples will be required to confirm that variant(s) in these regions influence BP risk.

BackgroundFor the most part, genome-wide association studies (GWAS) have only partially explained the heritability of complex diseases. One of their limitations is to assume independent contributions of individual variants to the phenotype. Many tools have therefore been developed to investigate the interactions between distant loci, or epistasis. Among them, the recently proposed EpiGWAS models the interactions between a target variant and the rest of the genome. However, applying this approach to studying interactions along all genes of a disease map is not straightforward. Here, we propose a pipeline to that effect, which we illustrate by investigating a multiple sclerosis GWAS dataset from the Wellcome Trust Case Control Consortium 2 through 19 disease maps from the MetaCore pathway database.ResultsFor each disease map, we build an epistatic network by connecting the genes that are deemed to interact. These networks tend to be connected, complementary to the disease maps and contain hubs. In addition, we report 4 epistatic gene pairs involving missense variants, and 25 gene pairs with a deleterious epistatic effect mediated by eQTLs. Among these, we highlight the interaction of GLI-1 and SUFU, and of IP10 and NF-kappaB, as they both match known biological interactions. The latter pair is particularly promising for therapeutic development, as both genes have known inhibitors.ConclusionsOur study showcases the ability of EpiGWAS to uncover biologically interpretable epistatic interactions that are potentially actionable for the development of combination therapy.

Background Multiple sclerosis is an autoimmune condition that affects the spinal cord and brain which is categorized by demyelination, swelling, and axonal loss. The meta-analysis rationale was to determine the correlation between TNFα gene polymorphism and multiple sclerosis risk. Methods We conducted a systematic literature mining in the major electronic databases, including PubMed, Embase, Medline Scopus, and to look up for relevant studies published up to December 2024. We executed the meta-analysis to assess the correlation between TNFα gene (rs361525) SNP and multiple sclerosis. This meta-analysis was executed using the MetaGenyo and RevMan V-5.0 software to estimate the odds ratio along with 95% confidence interval. Results Our results indicated a positive association of TNFα with OR = 1.03, (95% CI [0.530–1.980]), p = 0.04 in the dominant genetic model. These findings support the evidence that TNFα rs361525 polymorphism was found to be linked with MS risk. However, case–control studies with large sample size from Caucasian and Asian ethnicity are required to investigate the functional role of TNFα polymorphism in the multiple sclerosis pathogenesis.

Smoking and multiple sclerosis, cause or coincidence?

Parvalbumin (PV) and calretinin (CR) are calcium binding proteins (CBP's) expressed in discrete GABAergic interneuron populations in the human cortex. CBP's are known to buffer calcium concentrations and protect neurons from increases in intracellular calcium. Perturbations in intracellular calcium can activate proteolytic enzymes including calpain, leading to deleterious effects to axons. Ca++-mediated mechanisms have been found to be associated with axonal pathology in MS and the restructuring of calcium channels has been shown to occur in experimental autoimmune encephalomyelitis (EAE) as well as multiple sclerosis tissue. Previous data indicates a reduction in the expression of the parvalbumin gene as well as reduced extension of neurites on parvalbumin expressing interneurons within multiple sclerosis normal appearing grey matter (NAGM). Modifications in interneuron parvalbumin or calretinin levels could change calcium buffering capacity, as well as the way these cells respond to neuronal insults. The present study was designed to compare CBP immunoreactive neurons in normal and multiple sclerosis post-mortem NAGM. To this end, we utilized immunofluorescent staining and high resolution confocal microscopy to map regions of the human motor cortex, and characterize layer specific CBP distribution in the normal and multiple sclerosis motor cortex. Our results indicate a significant reduction in the number of PV interneurons within layer 2 of the multiple sclerosis primary motor cortex with no concurrent change in number of calretinin positive neurons.

ABSTRACTBackgroundEpstein–Barr Virus (EBV) and its clinical manifestation, infectious mononucleosis (IM), are strongly linked to MS risk. A recent in vitro study suggests that HLA‐E*01:03, in contrast to HLA‐E*01:01, may protect against MS through more effective immune responses against EBV‐infected B cells. However, the role of HLA‐E*01 in MS remains unclear.MethodsWe investigated if HLA‐E*01:01 was significantly associated with higher MS risk in individuals with a history of IM diagnosis, using 487,144 individuals from the UK Biobank's cohort. We estimated the interaction between HLA‐E*01:01 and IM using Cox proportional hazard models, adjusting for demographics, smoking, childhood body size, older siblings, and MS‐related HLA alleles (e.g., HLA‐DRB1*15:01).ResultsHLA‐E*01:01 allele alone was not significantly associated with IM or MS (p > 0.05). However, a significant interaction between HLA‐E*01:01 and IM history was observed in relation to MS risk (p < 0.001). Specifically, MS risk was significantly higher in both HLA‐E*01:01 heterozygotes (HR = 1.74 [95% CI: 1.36, 1.97], p < 0.001) and homozygotes (HR = 3.01 [95% CI: 1.81, 3.88], p < 0.001) with IM history, compared to HLA‐E*01:03 homozygotes. Conversely, these associations were non‐significant in individuals without IM history (p > 0.05). The estimated proportion of the combined risk attributable to interaction effects was 40% in HLA‐E*01:01 heterozygotes and 65% in HLA‐E*01:01 homozygotes.ConclusionsHLA‐E*01:01 carriers diagnosed with IM are at significantly increased risk of MS, independently from other MS‐related HLA alleles. This supports the hypothesis that HLA‐E*01:01 may contribute to MS susceptibility due to weaker immune control over EBV infection. Incorporating HLA‐E*01:01 into existing MHC‐based MS risk models could then enhance personalized risk assessments in individuals with IM history.

ABSTRACTMultiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system. Matrix metalloproteinases (MMPs) play an important role in breakdown of blood–brain barrier, transmigration, and invasion of immune cells and formation of MS lesions. The aim of present study was to investigate the influence of MMP-2 C-735T and MMP-9 C-1562T variants and their synergism with MMP-7 A-181G on susceptibility to MS. In a case–control study 125 MS patients and 235 healthy individuals from Western Iran were investigated. The various genotypes of MMP-2, MMP-9, and MMP-7 were detected using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). In females the presence of MMP-2 C allele was associated with an increased risk of MS (OR = 1.69, p = 0.041). No significant difference was detected between the frequency of MMP-9 T allele in MS patients (8.2%) and controls (12.8%, p = 0.068). The concomitant presence of both MMP-2 C and MMP-7 G alleles was associated with 1.82-fold increased risk of MS (p = 0.002). Also, a synergism was detected between MMP-9 C and MMP-7 G alleles that elevated the risk of MS by 1.5-times (p = 0.035). The presence of haplotype MMP-9 T, MMP-7 G, and MMP-2 C (TGC) compared to haplotype CAG increased the risk of MS by 3.13-fold (p = 0.16). The present study suggests that gene–gene interactions and variants of more genes instead of single gene might play a role in susceptibility to MS. We indicated that synergism between variants of MMP-2, MMP-7, and MMP-9 genes might increase the risk of MS.

Penalized Multiple Regression (PMR) can be used to discover novel disease associations in GWAS datasets. In practice, proposed PMR methods have not been able to identify well-supported associations in GWAS that are undetectable by standard association tests and thus these methods are not widely applied. Here, we present a combined algorithmic and heuristic framework for PUMA (Penalized Unified Multiple-locus Association) analysis that solves the problems of previously proposed methods including computational speed, poor performance on genome-scale simulated data, and identification of too many associations for real data to be biologically plausible. The framework includes a new minorize-maximization (MM) algorithm for generalized linear models (GLM) combined with heuristic model selection and testing methods for identification of robust associations. The PUMA framework implements the penalized maximum likelihood penalties previously proposed for GWAS analysis (i.e. Lasso, Adaptive Lasso, NEG, MCP), as well as a penalty that has not been previously applied to GWAS (i.e. LOG). Using simulations that closely mirror real GWAS data, we show that our framework has high performance and reliably increases power to detect weak associations, while existing PMR methods can perform worse than single marker testing in overall performance. To demonstrate the empirical value of PUMA, we analyzed GWAS data for type 1 diabetes, Crohns's disease, and rheumatoid arthritis, three autoimmune diseases from the original Wellcome Trust Case Control Consortium. Our analysis replicates known associations for these diseases and we discover novel etiologically relevant susceptibility loci that are invisible to standard single marker tests, including six novel associations implicating genes involved in pancreatic function, insulin pathways and immune-cell function in type 1 diabetes; three novel associations implicating genes in pro- and anti-inflammatory pathways in Crohn's disease; and one novel association implicating a gene involved in apoptosis pathways in rheumatoid arthritis. We provide software for applying our PUMA analysis framework.

By means of age specific incidence and death rates for MS, plus age specific death rates all causes, the risk of multiple sclerosis in Denmark has been calculated with a modified life-table method. the cumulative lifetime risk of MS from birth is estimated at 201 per 100,000 (180 in males and 223 in females) - or one chance in 500. the cumulative risk remains about the same from birth until age 25 when it begins to decline toward 0 which is reached at age 60. Period cumulative risks from various ages and for periods ranging from 5 to 30 years were also calculated. Thus, at age 20, the risk of MS within 10 years is 74 per 100,000 and within twenty years, 142, for both sexes combined. With the likely equivalence of the duration of the illness throughout the world, and with little major variation expected for most regions for death rates, all causes, within the ages of concern, we may then estimate the risk of MS for parts of the world considered as high frequency MS (like Denmark), medium frequency (like Italy), or low frequency (like Japan). By applying to these regions the factors of 1.0, 0.3, and 0.04 respectively, as reflecting the ratios of their likely prevalence rates, the cumulative lifetime and period risks may be approximated from the Danish data. Thus in 20 years, a group of 100,000 Japanese migrating to Denmark at age 10 would be expected to contain 4 MS if they retained the low risk of their homeland, as opposed to 92 MS if they acquired the high risk of Denmark.

Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis

BackgroundAdmittedly, little is known about the epidemiological signatures of familial multiple sclerosis (FMS) in different geographical regions of Iran.ObjectiveTo determine the epidemiology and the risk of FMS incidence in several provinces of Iran with a different ethnic population including, Fars, Tehran, Isfahan (Persians), and Mazandaran (Mazanis), Kermanshah (Kurds), and Chaharmahal and Bakhtiari (Lors).MethodsThis cross-sectional registry-based study was performed on nationwide MS registry of Iran (NMSRI) data collected from 2018 to 2021. This system, registers baseline characteristics, clinical presentations and symptoms, diagnostic and treatments at regional and national levels.ResultsA total of 9200 patients including, 7003 (76.1%) female and 2197 (23.9%) male, were participated. About 19% of patients reported a family history of MS; the order from highest to lowest FMS prevalence was as follows: Fars (26.5%), Chaharmahal and Bakhtiari (21.1%), Tehran (20.5%), Isfahan (20.3%), Mazandaran (18.0%), and Kermanshah (12.5%). Of all FMS cases, 74.7% (1308 cases) were female and 25.3% (442 cases) were male. FMS occurrence was much more common in females than males (P-value = 0.001). Further, the mean age at onset was 30 years among FMS cases. A substantially higher probability of relapsing-remitting MS and secondary-progressive MS was found among FMS cases than sporadic MS (SMS) (P_value = 0.001). There was no significant difference in Expanded Disability Status Scale (EDSS) scores between FMS and SMS. The majority of FMS cases were observed among first-degree relatives, with the highest rate in siblings. There was a significant association between MS risk and positive familial history in both maternal and paternal aunt/uncle (P_value = 0.043 and P_value = 0.019, respectively). Multiple sclerosis occurrence among offspring of females was higher than males (P_value = 0.027).ConclusionsIn summary, our findings imply a noteworthy upward trend of FMS in Iran, even more than the global prevalence, which suggests a unique Atlas of FMS prevalence in this multi-ethnic population. Despite the highest rate of FMS within Persian and Lor ethnicities, no statistically significant difference was observed among the provinces.

Genetic biomarkers in multiple sclerosis: An umbrella review of meta-analyses of observational studies

Multiple sclerosis (MS) is an inflammatory neurodegenerative disease of the CNS. Recent advances in whole-genome screening tools have enabled discovery of several MS risk genes, the majority of which have known immune-related functions. However, disease heterogeneity and low tissue accessibility hinder functional studies of established MS risk genes. For this reason, the MS model experimental autoimmune encephalomyelitis (EAE) is often used to study neuroinflammatory disease mechanisms. In this study, we performed high-resolution linkage analysis in a rat advanced intercross line to identify an EAE-regulating quantitative trait locus, Eae29, on rat chromosome 1. Eae29 alleles from the resistant strain both conferred milder EAE and lower production of proinflammatory molecules in macrophages, as demonstrated by the congenic line, DA.PVG-Eae29 (Dc1P). The soluble IL-22R α2 gene (Il-22ra2) lies within the Eae29 locus, and its expression was reduced in Dc1P, both in activated macrophages and splenocytes from immunized rats. Moreover, a single nucleotide polymorphism located at the end of IL-22RA2 associated with MS risk in a combined Swedish and Norwegian cohort comprising 5019 subjects, displaying an odds ratio of 1.26 (p = 8.0 × 10(-4)). IL-22 and its receptors have been implicated in chronic inflammation, suggesting that IL-22RA2 regulates a central immune pathway. Through a combined approach including genetic and immunological investigation in an animal model and large-scale association studies of MS patients, we establish IL-22RA2 as an MS risk gene.

BackgroundMultiple sclerosis (MS) is a major demyelinating disorder that affects the central nervous system. A growing body of evidence has revealed the involvement of coagulation pathway in the pathogenesis of MS. However, the causal association between coagulation factors and MS is still unclear.MethodA two-sample Mendelian randomization (MR) analysis was conducted. Genetic variants for plasma coagulation factors were identified as instrumental variables. Summary-level statistics for MS were collected from a large-scale genome-wide association study, including 47,429 cases and 68,374 controls. Primary MR analysis was performed using the inverse-variance weighting (IVW) approach. False discovery rate (FDR)-adjusted method was applied to adjust for multiple testing. MR-Egger, weighted median, simple mode, weighted mode, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods were used as sensitivity analysis approaches.ResultsA causal effect of higher plasma tissue factor (TF) levels on the risk of MS onset was identified using IVW method (OR: 1.215, 95% CI 1.108–1.333, P < 0.001, PFDR < 0.001). Complementary analysis using weighted median (OR: 1.262, 95% CI: 1.119–1.423, P < 0.001), weighted mode (OR: 1.238, 95% CI: 1.100–1.394, P = 0.012), and MR-PRESSO (OR: 1.215, 95% CI: 1.125–1.313, P = 0.003) methods yielded consistent results. Null associations were found for other plasma coagulation factors with MS.ConclusionsThe study demonstrates a suggestive association between TF and MS. Increasing plasma TF was associated with an increase in MS risk. TF should be a promising biomarker and new target for MS.

Vitamin D status modulates the immune response to Epstein Barr virus: Synergistic effect of risk factors in multiple sclerosis