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

Low-frequency and rare genetic variants associated with rheumatoid arthritis risk

Rheumatoid arthritis (RA) has an estimated heritability of nearly 50%, which is particularly high in seropositive RA. HLA alleles account for a large proportion of this heritability, in addition to many common single-nucleotide polymorphisms with smaller individual effects. Low-frequency and rare variants, such as those captured by next-generation sequencing, can also have a large role in heritability in some individuals. Rare variant discovery has informed the development of drugs such as inhibitors of PCSK9 and Janus kinases. Some 34 low-frequency and rare variants are currently associated with RA risk. One variant (19:10352442G>C in TYK2) was identified in five separate studies, and might therefore represent a promising therapeutic target. Following a set of best practices in future studies, including studying diverse populations, using large sample sizes, validating RA and serostatus, replicating findings, adjusting for other variants and performing functional assessment, could help to ensure the relevance of identified variants. Exciting opportunities are now on the horizon for genetics in RA, including larger datasets and consortia, whole-genome sequencing and direct applications of findings in the management, and especially treatment, of RA.

MicroRNAs targeting TGF-β signaling exacerbate central nervous system autoimmunity by disrupting regulatory T cell development and function

Transforming growth factor beta (TGF-β) signaling is essential for a balanced immune response by mediating the development and function of regulatory T cells (Tregs) and suppressing autoreactive T cells. Disruption of this balance can result in autoimmune diseases, including multiple sclerosis (MS). MicroRNAs (miRNAs) targeting TGF-β signaling have been shown to be upregulated in naïve CD4 T cells in MS patients, resulting in a limited in vitro generation of human Tregs. Utilizing the murine model experimental autoimmune encephalomyelitis, we show that perinatal administration of miRNAs, which target the TGF-β signaling pathway, enhanced susceptibility to central nervous system (CNS) autoimmunity. Neonatal mice administered with these miRNAs further exhibited reduced Treg frequencies with a loss in T cell receptor repertoire diversity following the induction of experimental autoimmune encephalomyelitis in adulthood. Exacerbated CNS autoimmunity as a result of miRNA overexpression in CD4 T cells was accompanied by enhanced Th1 and Th17 cell frequencies. These findings demonstrate that increased levels of TGF-β-associated miRNAs impede the development of a diverse Treg population, leading to enhanced effector cell activity, and contributing to an increased susceptibility to CNS autoimmunity. Thus, TGF-β-targeting miRNAs could be a risk factor for MS, and recovering optimal TGF-β signaling may restore immune homeostasis in MS patients.

Next-generation sequencing of host genetics risk factors associated with COVID-19 severity and long-COVID in Colombian population

Coronavirus disease 2019 (COVID-19) was considered a major public health burden worldwide. Multiple studies have shown that susceptibility to severe infections and the development of long-term symptoms is significantly influenced by viral and host factors. These findings have highlighted the potential of host genetic markers to identify high-risk individuals and develop target interventions to reduce morbimortality. Despite its importance, genetic host factors remain largely understudied in Latin-American populations. Using a case-control design and a custom next-generation sequencing (NGS) panel encompassing 81 genetic variants and 74 genes previously associated with COVID-19 severity and long-COVID, we analyzed 56 individuals with asymptomatic or mild COVID-19 and 56 severe and critical cases. In agreement with previous studies, our results support the association between several clinical variables, including male sex, obesity and common symptoms like cough and dyspnea, and severe COVID-19. Remarkably, thirteen genetic variants showed an association with COVID-19 severity. Among these variants, rs11385942 (p < 0.01; OR = 10.88; 95% CI = 1.36-86.51) located in the LZTFL1 gene, and rs35775079 (p = 0.02; OR = 8.53; 95% CI = 1.05-69.45) located in CCR3 showed the strongest associations. Various respiratory and systemic symptoms, along with the rs8178521 variant (p < 0.01; OR = 2.51; 95% CI = 1.27-4.94) in the IL10RB gene, were significantly associated with the presence of long-COVID. The results of the predictive model comparison showed that the mixed model, which incorporates genetic and non-genetic variables, outperforms clinical and genetic models. To our knowledge, this is the first study in Colombia and Latin-America proposing a predictive model for COVID-19 severity and long-COVID based on genomic analysis. Our study highlights the usefulness of genomic approaches to studying host genetic risk factors in specific populations. The methodology used allowed us to validate several genetic variants previously associated with COVID-19 severity and long-COVID. Finally, the integrated model illustrates the importance of considering genetic factors in precision medicine of infectious diseases.

Gene-environment interactions: Epstein-Barr virus infection and risk of pediatric-onset multiple sclerosis

BACKGROUND AND OBJECTIVE

Prior Epstein-Barr virus (EBV) infection is associated with an increased risk of pediatric-onset multiple sclerosis (POMS) and adult-onset multiple sclerosis (MS). It has been challenging to elucidate the biological mechanisms underlying this association. We examined the interactions between candidate human leukocyte antigen (HLA) and non-HLA variants and childhood EBV infection as it may provide mechanistic insights into EBV-associated MS.

METHODS

Cases and controls were enrolled in the Environmental and Genetic Risk Factors for Pediatric MS study of the US Network of Pediatric MS Centers. Participants were categorized as seropositive and seronegative for EBV-viral capsid antigen (VCA). The association between prior EBV infection and having POMS was estimated with logistic regression. Interactions between EBV serostatus, major HLA MS risk factors, and non-HLA POMS risk variants associated with response to EBV infection were also evaluated with logistic regression. Models were adjusted for sex, age, genetic ancestry, and the mother's education. Additive interactions were calculated using relative risk due to interaction (RERI) and attributable proportions (APs).

RESULTS

A total of 473 POMS cases and 702 controls contributed to the analyses. Anti-VCA seropositivity was significantly higher in POMS cases compared to controls (94.6% vs 60.7%, p < 0.001). There was evidence for additive interaction between childhood EBV infection and the presence of the HLA-DRB1*15 allele (RERI = 10.25, 95% confidence interval (CI) = 3.78 to 16.72; AP = 0.61, 95% CI = 0.47 to 0.75). There was evidence for multiplicative interaction (p < 0.05) between childhood EBV infection and the presence of DRB1*15 alleles (odds ratio (OR) = 3.43, 95% CI = 1.06 to 11.07). Among the pediatric MS variants also associated with EBV infection, we detected evidence for additive interaction (p = 0.02) between prior EBV infection and the presence of the GG genotype in risk variant (rs2255214) within CD86 (AP = 0.30, 95% CI = 0.03 to 0.58).

CONCLUSION

We report evidence for interactions between childhood EBV infection and DRB1*15 and the GG genotype of CD86 POMS risk variant. Our results suggest an important role of antigen-presenting cells (APCs) in EBV-associated POMS risk.

The regulation and differentiation of regulatory T cells and their dysfunction in autoimmune diseases

The discovery of FOXP3+ regulatory T (Treg) cells as a distinct cell lineage with a central role in regulating immune responses provided a deeper understanding of self-tolerance. The transcription factor FOXP3 serves a key role in Treg cell lineage determination and maintenance, but is not sufficient to enable the full potential of Treg cell suppression, indicating that other factors orchestrate the fine-tuning of Treg cell function. Moreover, FOXP3-independent mechanisms have recently been shown to contribute to Treg cell dysfunction. FOXP3 mutations in humans cause lethal fulminant systemic autoinflammation (IPEX syndrome). However, it remains unclear to what degree Treg cell dysfunction is contributing to the pathophysiology of common autoimmune diseases. In this Review, we discuss the origins of Treg cells in the periphery and the multilayered mechanisms by which Treg cells are induced, as well as the FOXP3-dependent and FOXP3-independent cellular programmes that maintain the suppressive function of Treg cells in humans and mice. Further, we examine evidence for Treg cell dysfunction in the context of common autoimmune diseases such as multiple sclerosis, inflammatory bowel disease, systemic lupus erythematosus and rheumatoid arthritis.

Differential Runx3, Eomes, and T-bet expression subdivides MS-associated CD4+ T cells with brain-homing capacity

Multiple sclerosis (MS) is a common and devastating chronic inflammatory disease of the CNS. CD4+ T cells are assumed to be the first to cross the blood-central nervous system (CNS) barrier and trigger local inflammation. Here, we explored how pathogenicity-associated effector programs define CD4+ T cell subsets with brain-homing ability in MS. Runx3- and Eomes-, but not T-bet-expressing CD4+ memory cells were diminished in the blood of MS patients. This decline reversed following natalizumab treatment and was supported by a Runx3+ Eomes+ T-bet- enrichment in cerebrospinal fluid samples of treatment-naïve MS patients. This transcription factor profile was associated with high granzyme K (GZMK) and CCR5 levels and was most prominent in Th17.1 cells (CCR6+ CXCR3+ CCR4-/dim ). Previously published CD28- CD4 T cells were characterized by a Runx3+ Eomes- T-bet+ phenotype that coincided with intermediate CCR5 and a higher granzyme B (GZMB) and perforin expression, indicating the presence of two separate subsets. Under steady-state conditions, granzyme Khigh Th17.1 cells spontaneously passed the blood-brain barrier in vitro. This was only found for other subsets including CD28- cells when using inflamed barriers. Altogether, CD4+ T cells contain small fractions with separate pathogenic features, of which Th17.1 seems to breach the blood-brain barrier as a possible early event in MS.

mRNA expression profile reveals differentially expressed genes in splenocytes of experimental autoimmune encephalomyelitis model

Experimental autoimmune encephalomyelitis (EAE) is a mouse model that can be used to investigate aetiology, pathogenesis, and treatment approaches for multiple sclerosis (MS). A novel integrated bioinformatics approach was used to understand the involvement of differentially expressed genes (DEGs) in the spleen of EAE mice through data mining of existing microarray and RNA-seq datasets. We screened differentially expressed mRNAs using mRNA expression profile data of EAE spleens taken from Gene Expression Omnibus (GEO). Functional and pathway enrichment analyses of DEGs were performed by Database for Annotation, Visualization, and Integrated Discovery (DAVID). Subsequently, the DEGs-encoded protein-protein interaction (PPI) network was constructed. The 784 DEGs in GSE99300 A.SW PP-EAE mice spleen mRNA profiles, 859 DEGs in GSE151701 EAE mice spleen mRNA profiles, and 646 DEGs in GSE99300 SJL/J PP-EAE mice spleen mRNA profiles were explored. Functional enrichment of 55 common DEGs among 3 sub-datasets revealed several immune-related terms, such as neutrophil extravasation, leucocyte migration, antimicrobial humoral immune response mediated by an antimicrobial peptide, toll-like receptor 4 bindings, IL-17 signalling pathway, and TGF-beta signalling pathway. In the screening of 10 hub genes, including MPO, ELANE, CTSG, LTF, LCN2, SELP, CAMP, S100A9, ITGA2B, and PRTN3, and in choosing and validating the 5 DEGs, including ANK1, MBOAT2, SLC25A21, SLC43A1, and SOX6, the results showed that SLC43A1 and SOX6 were significantly decreased in EAE mice spleen. Thus this study offers a list of genes expressed in the spleen that might play a key role in the pathogenesis of EAE.

Decision trees to evaluate the risk of developing multiple sclerosis

Introduction

Multiple sclerosis (MS) is a persistent neurological condition impacting the central nervous system (CNS). The precise cause of multiple sclerosis is still uncertain; however, it is thought to arise from a blend of genetic and environmental factors. MS diagnosis includes assessing medical history, conducting neurological exams, performing magnetic resonance imaging (MRI) scans, and analyzing cerebrospinal fluid. While there is currently no cure for MS, numerous treatments exist to address symptoms, decelerate disease progression, and enhance the quality of life for individuals with MS.

Methods

This paper introduces a novel machine learning (ML) algorithm utilizing decision trees to address a key objective: creating a predictive tool for assessing the likelihood of MS development. It achieves this by combining prevalent demographic risk factors, specifically gender, with crucial immunogenetic risk markers, such as the alleles responsible for human leukocyte antigen (HLA) class I molecules and the killer immunoglobulin-like receptors (KIR) genes responsible for natural killer lymphocyte receptors.

Results

The study included 619 healthy controls and 299 patients affected by MS, all of whom originated from Sardinia. The gender feature has been disregarded due to its substantial bias in influencing the classification outcomes. By solely considering immunogenetic risk markers, the algorithm demonstrates an ability to accurately identify 73.24% of MS patients and 66.07% of individuals without the disease.

Discussion

Given its notable performance, this system has the potential to support clinicians in monitoring the relatives of MS patients and identifying individuals who are at an increased risk of developing the disease.

Cellular and Molecular Evidence of Multiple Sclerosis Diagnosis and Treatment Challenges

Multiple sclerosis (MS) is a chronic autoimmune disease that impacts the central nervous system and can result in disability. Although the prevalence of MS has increased in India, diagnosis and treatment continue to be difficult due to several factors. The present study examines the difficulties in detecting and treating multiple sclerosis in India. A lack of MS knowledge among healthcare professionals and the general public, which delays diagnosis and treatment, is one of the significant issues. Inadequate numbers of neurologists and professionals with knowledge of MS management also exacerbate the situation. In addition, MS medications are expensive and not covered by insurance, making them inaccessible to most patients. Due to the absence of established treatment protocols and standards for MS care, India's treatment techniques vary. In addition, India's population diversity poses unique challenges regarding genetic variations, cellular and molecular abnormalities, and the potential for differing treatment responses. MS is more difficult to accurately diagnose and monitor due to a lack of specialized medical supplies and diagnostic instruments. Improved awareness and education among healthcare professionals and the general public, as well as the development of standardized treatment regimens and increased investment in MS research and infrastructure, are required to address these issues. By addressing these issues, it is anticipated that MS diagnosis and treatment in India will improve, leading to better outcomes for those affected by this chronic condition.

Genetic Basis of Inflammatory Demyelinating Diseases of the Central Nervous System: Multiple Sclerosis and Neuromyelitis Optica Spectrum

Demyelinating diseases alter myelin or the coating surrounding most nerve fibers in the central and peripheral nervous systems. The grouping of human central nervous system demyelinating disorders today includes multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) as distinct disease categories. Each disease is caused by a complex combination of genetic and environmental variables, many involving an autoimmune response. Even though these conditions are fundamentally similar, research into genetic factors, their unique clinical manifestations, and lesion pathology has helped with differential diagnosis and disease pathogenesis knowledge. This review aims to synthesize the genetic approaches that explain the differential susceptibility between these diseases, explore the overlapping clinical features, and pathological findings, discuss existing and emerging hypotheses on the etiology of demyelination, and assess recent pathogenicity studies and their implications for human demyelination. This review presents critical information from previous studies on the disease, which asks several questions to understand the gaps in research in this field.

In silico prioritisation of microRNA-associated common variants in multiple sclerosis

BACKGROUND

Genome-wide association studies (GWAS) have highlighted over 200 autosomal variants associated with multiple sclerosis (MS). However, variants in non-coding regions such as those encoding microRNAs have not been explored thoroughly, despite strong evidence of microRNA dysregulation in MS patients and model organisms. This study explores the effect of microRNA-associated variants in MS, through the largest publicly available GWAS, which involved 47,429 MS cases and 68,374 controls.

METHODS

We identified SNPs within the coordinates of microRNAs, ± 5-kb microRNA flanking regions and predicted 3'UTR target-binding sites using miRBase v22, TargetScan 7.0 RNA22 v2.0 and dbSNP v151. We established the subset of microRNA-associated SNPs which were tested in the summary statistics of the largest MS GWAS by intersecting these datasets. Next, we prioritised those microRNA-associated SNPs which are among known MS susceptibility SNPs, are in strong linkage disequilibrium with the former or meet a microRNA-specific Bonferroni-corrected threshold. Finally, we predicted the effects of those prioritised SNPs on their microRNAs and 3'UTR target-binding sites using TargetScan v7.0, miRVaS and ADmiRE.

RESULTS

We have identified 30 candidate microRNA-associated variants which meet at least one of our prioritisation criteria. Among these, we highlighted one microRNA variant rs1414273 (MIR548AC) and four 3'UTR microRNA-binding site variants within SLC2A4RG (rs6742), CD27 (rs1059501), MMEL1 (rs881640) and BCL2L13 (rs2587100). We determined changes to the predicted microRNA stability and binding site recognition of these microRNA and target sites.

CONCLUSIONS

We have systematically examined the functional, structural and regulatory effects of candidate MS variants among microRNAs and 3'UTR targets. This analysis allowed us to identify candidate microRNA-associated MS SNPs and highlights the value of prioritising non-coding RNA variation in GWAS. These candidate SNPs could influence microRNA regulation in MS patients. Our study is the first thorough investigation of both microRNA and 3'UTR target-binding site variation in multiple sclerosis using GWAS summary statistics.

A gene regulatory network approach harmonizes genetic and epigenetic signals and reveals repurposable drug candidates for multiple sclerosis

Multiple sclerosis (MS) is a complex dysimmune disorder of the central nervous system. Genome-wide association studies (GWAS) have identified 233 genetic variations associated with MS at the genome-wide significant level. Epigenetic studies have pinpointed differentially methylated CpG sites in MS patients. However, the interplay between genetic risk factors and epigenetic regulation remains elusive. Here, we employed a network model to integrate GWAS summary statistics of 14 802 MS cases and 26 703 controls with DNA methylation profiles from 140 MS cases and 139 controls and the human interactome. We identified differentially methylated genes by aggregating additive effects of differentially methylated CpG sites within promoter regions. We reconstructed a gene regulatory network (GRN) using literature-curated transcription factor knowledge. Colocalization of the MS GWAS and methylation quantitative trait loci (mQTL) was performed to assess the GRN. The resultant MS-associated GRN highlighted several single nucleotide polymorphisms with GWAS-mQTL colocalization: rs6032663, rs6065926 and rs2024568 of CD40 locus, rs9913597 of STAT3 locus, and rs887864 and rs741175 of CIITA locus. Moreover, synergistic mQTL and expression QTL signals were identified in CD40, suggesting gene expression alteration was likely induced by epigenetic changes. Web-based Cell-type Specific Enrichment Analysis of Genes (WebCSEA) indicated that the GRN was enriched in T follicular helper cells (P-value = 0.0016). Drug target enrichment analysis of annotations from the Therapeutic Target Database revealed the GRN was also enriched with drug target genes (P-value = 3.89 × 10-4), revealing repurposable candidates for MS treatment. These candidates included vorinostat (HDAC1 inhibitor) and sivelestat (ELANE inhibitor), which warrant further investigation.

Rare and low-frequency coding genetic variants contribute to pediatric-onset multiple sclerosis

BACKGROUND

Rare genetic variants are emerging as important contributors to the heritability of multiple sclerosis (MS). Whether rare variants also contribute to pediatric-onset multiple sclerosis (POMS) is unknown.

OBJECTIVE

To test whether genes harboring rare variants associated with adult-onset MS risk (PRF1, PRKRA, NLRP8, and HDAC7) and 52 major histocompatibility complex (MHC) genes are associated with POMS.

METHODS

We analyzed DNA samples from 330 POMS cases and 306 controls from the US Network of Pediatric MS Centers and Kaiser Permanente Northern California for which Illumina ExomeChip genotypes were available. Using the gene-based method "SKAT-O," we tested the association between candidate genes and POMS risk.

RESULTS

After correction for multiple comparisons, one adult-onset MS gene (PRF1, p = 2.70 × 10^-3) and two MHC genes (BRD2, p = 5.89 × 10^-5 and AGER, p = 7.96 × 10^-5) were significantly associated with POMS. Results suggest these are independent of HLA-DRB1*1501.

CONCLUSION

Findings support a role for rare coding variants in POMS susceptibility. In particular, rare minor alleles within PRF1 were more common among individuals with POMS compared to controls while the opposite was true for rare variants within significant MHC genes, BRD2 and AGER. These genes would not have been identified by common variant studies, emphasizing the merits of investigating rare genetic variation in complex diseases.

Intrinsic blood-brain barrier dysfunction contributes to multiple sclerosis pathogenesis

Blood-brain barrier (BBB) breakdown and immune cell infiltration into the CNS are early hallmarks of multiple sclerosis (MS). The mechanisms leading to BBB dysfunction are incompletely understood and generally thought to be a consequence of neuroinflammation. Here, we have challenged this view and asked if intrinsic alterations in the BBB of MS patients contribute to MS pathogenesis. To this end, we made use of human induced pluripotent stem cells derived from healthy controls and MS patients and differentiated them into brain microvascular endothelial cell (BMEC)-like cells as in vitro model of the BBB. MS-derived BMEC-like cells showed impaired junctional integrity, barrier properties and efflux pump activity when compared to healthy controls. Also, MS-derived BMEC-like cells displayed an inflammatory phenotype with increased adhesion molecule expression and immune cell interactions. Activation of Wnt/β-catenin signalling in MS-derived endothelial progenitor cells enhanced barrier characteristics and reduced the inflammatory phenotype. Our study provides evidence for an intrinsic impairment of BBB function in MS patients that can be modelled in vitro. Human iPSC-derived BMEC-like cells are thus suitable to explore the molecular underpinnings of BBB dysfunction in MS and will assist in the identification of potential novel therapeutic targets for BBB stabilization.

A Whole-Genome Sequencing Study Implicates GRAMD1B in Multiple Sclerosis Susceptibility

While the role of common genetic variants in multiple sclerosis (MS) has been elucidated in large genome-wide association studies, the contribution of rare variants to the disease remains unclear. Herein, a whole-genome sequencing study in four affected and four healthy relatives of a consanguineous Italian family identified a novel missense c.1801T > C (p.S601P) variant in the GRAMD1B gene that is shared within MS cases and resides under a linkage peak (LOD: 2.194). Sequencing GRAMD1B in 91 familial MS cases revealed two additional rare missense and two splice-site variants, two of which (rs755488531 and rs769527838) were not found in 1000 Italian healthy controls. Functional studies demonstrated that GRAMD1B, a gene with unknown function in the central nervous system (CNS), is expressed by several cell types, including astrocytes, microglia and neurons as well as by peripheral monocytes and macrophages. Notably, GRAMD1B was downregulated in vessel-associated astrocytes of active MS lesions in autopsied brains and by inflammatory stimuli in peripheral monocytes, suggesting a possible role in the modulation of inflammatory response and disease pathophysiology.

Progressive multifocal leukoencephalopathy genetic risk variants for pharmacovigilance of immunosuppressant therapies

Background

Progressive multifocal leukoencephalopathy (PML) is a rare and often lethal brain disorder caused by the common, typically benign polyomavirus 2, also known as JC virus (JCV). In a small percentage of immunosuppressed individuals, JCV is reactivated and infects the brain, causing devastating neurological defects. A wide range of immunosuppressed groups can develop PML, such as patients with: HIV/AIDS, hematological malignancies (e.g., leukemias, lymphomas, and multiple myeloma), autoimmune disorders (e.g., psoriasis, rheumatoid arthritis, and systemic lupus erythematosus), and organ transplants. In some patients, iatrogenic (i.e., drug-induced) PML occurs as a serious adverse event from exposure to immunosuppressant therapies used to treat their disease (e.g., hematological malignancies and multiple sclerosis). While JCV infection and immunosuppression are necessary, they are not sufficient to cause PML.

Methods

We hypothesized that patients may also have a genetic susceptibility from the presence of rare deleterious genetic variants in immune-relevant genes (e.g., those that cause inborn errors of immunity). In our prior genetic study of 184 PML cases, we discovered 19 candidate PML risk variants. In the current study of another 152 cases, we validated 4 of 19 variants in both population controls (gnomAD 3.1) and matched controls (JCV+ multiple sclerosis patients on a PML-linked drug ≥ 2 years).

Results

The four variants, found in immune system genes with strong biological links, are: C8B, 1-57409459-C-A, rs139498867; LY9 (alias SLAMF3), 1-160769595-AG-A, rs763811636; FCN2, 9-137779251-G-A, rs76267164; STXBP2, 19-7712287-G-C, rs35490401. Carriers of any one of these variants are shown to be at high risk of PML when drug-exposed PML cases are compared to drug-exposed matched controls: P value = 3.50E-06, OR = 8.7 [3.7-20.6]. Measures of clinical validity and utility compare favorably to other genetic risk tests, such as BRCA1 and BRCA2 screening for breast cancer risk and HLA-B^*15:02 pharmacogenetic screening for pharmacovigilance of carbamazepine to prevent Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis.

Conclusion

For the first time, a PML genetic risk test can be implemented for screening patients taking or considering treatment with a PML-linked drug in order to decrease the incidence of PML and enable safer use of highly effective therapies used to treat their underlying disease.

Exonic variants of the P2RX7 gene in familial multiple sclerosis

INTRODUCTION

Several studies have analysed the presence of P2RX7 variants in patients with MS, reporting diverging results.

METHODS

Our study analyses P2RX7 variants detected through whole-exome sequencing (WES).

RESULTS

We analysed P2RX7, P2RX4, and CAMKK2 gene variants detected by whole-exome sequencing in all living members (n = 127) of 21 families including at least 2 individuals with multiple sclerosis. P2RX7 gene polymorphisms previously associated with autoimmune disease. Although no differences were observed between individuals with and without multiple sclerosis, we found greater polymorphism of gain-of-function variants of P2RX7 in families with individuals with multiple sclerosis than in the general population. Copresence of gain-of-function and loss-of-function variants was not observed to reduce the risk of presenting the disease. Three families displayed heterozygous gain-of-function SNPs in patients with multiple sclerosis but not in healthy individuals. We were unable to determine the impact of copresence of P2RX4 and CAMKK2 variants with P2RX7 variants, or the potential effect of the different haplotypes described in the gene. No clinical correlations with other autoimmune diseases were observed in our cohort.

CONCLUSIONS

Our results support the hypothesis that the disease is polygenic and point to a previously unknown mechanism of genetic predisposition to familial forms of multiple sclerosis. P2RX7 gene activity can be modified, which suggests the possibility of preventive pharmacological treatments for families including patients with familial multiple sclerosis.

Whole Exome Sequencing Study Identifies Novel Rare Risk Variants for Habitual Coffee Consumption Involved in Olfactory Receptor and Hyperphagia

Habitual coffee consumption is an addictive behavior with unknown genetic variations and has raised public health issues about its potential health-related outcomes. We performed exome-wide association studies to identify rare risk variants contributing to habitual coffee consumption utilizing the newly released UK Biobank exome dataset (n = 200,643). A total of 34,761 qualifying variants were imported into SKAT to conduct gene-based burden and robust tests with minor allele frequency <0.01, adjusting the polygenic risk scores (PRS) of coffee intake to exclude the effect of common coffee-related polygenic risk. The gene-based burden and robust test of the exonic variants found seven exome-wide significant associations, such as OR2G2 (PSKAT = 1.88 × 10−9, PSKAT-Robust = 2.91 × 10−17), VEZT1 (PSKAT = 3.72 × 10−7, PSKAT-Robust = 1.41 × 10−7), and IRGC (PSKAT = 2.92 × 10−5, PSKAT-Robust = 1.07 × 10−7). These candidate genes were verified in the GWAS summary data of coffee intake, such as rs12737801 (p = 0.002) in OR2G2, and rs34439296 (p = 0.008) in IRGC. This study could help to extend genetic insights into the pathogenesis of coffee addiction, and may point to molecular mechanisms underlying health effects of habitual coffee consumption.

Investigating the role of common and rare variants in multiplex multiple sclerosis families reveals an increased burden of common risk variation

Many multiple sclerosis (MS)-associated common risk variants as well as candidate low-frequency and rare variants have been identified; however, approximately half of MS heritability remains unexplained. We studied seven multiplex MS families, six of which with parental consanguinity, to identify genetic factors that increase MS risk. Candidate genomic regions were identified through linkage analysis and homozygosity mapping, and fully penetrant, rare, and low-frequency variants were detected by exome sequencing. Weighted sum score and polygenic risk score (PRS) analyses were conducted in MS families (24 affected, 17 unaffected), 23 sporadic MS cases, 63 individuals in 19 non-MS control families, and 1272 independent, ancestry-matched controls. We found that familial MS cases had a significantly higher common risk variation burden compared with population controls and control families. Sporadic MS cases tended to have a higher PRS compared with familial MS cases, suggesting the presence of a higher rare risk variation burden in the families. In line with this, score distributions among affected and unaffected family members within individual families showed that known susceptibility alleles can explain disease development in some high-risk multiplex families, while in others, additional genetic contributors increase MS risk.

Whole Exome Sequencing in Multi-Incident Families Identifies Novel Candidate Genes for Multiple Sclerosis

Multiple sclerosis (MS) is a degenerative disease of the central nervous system in which auto-immunity-induced demyelination occurs. MS is thought to be caused by a complex interplay of environmental and genetic risk factors. While most genetic studies have focused on identifying common genetic variants for MS through genome-wide association studies, the objective of the present study was to identify rare genetic variants contributing to MS susceptibility. We used whole exome sequencing (WES) followed by co-segregation analyses in nine multi-incident families with two to four affected individuals. WES was performed in 31 family members with and without MS. After applying a suite of selection criteria, co-segregation analyses for a number of rare variants selected from the WES results were performed, adding 24 family members. This approach resulted in 12 exonic rare variants that showed acceptable co-segregation with MS within the nine families, implicating the genes MBP, PLK1, MECP2, MTMR7, TOX3, CPT1A, SORCS1, TRIM66, ITPR3, TTC28, CACNA1F, and PRAM1. Of these, three genes (MBP, MECP2, and CPT1A) have been previously reported as carrying MS-related rare variants. Six additional genes (MTMR7, TOX3, SORCS1, ITPR3, TTC28, and PRAM1) have also been implicated in MS through common genetic variants. The proteins encoded by all twelve genes containing rare variants interact in a molecular framework that points to biological processes involved in (de-/re-)myelination and auto-immunity. Our approach provides clues to possible molecular mechanisms underlying MS that should be studied further in cellular and/or animal models.

Genetics of multiple sclerosis: lessons from polygenicity

Large-scale mapping studies have identified 236 independent genetic variants associated with an increased risk of multiple sclerosis. However, none of these variants are found exclusively in patients with multiple sclerosis. They are located throughout the genome, including 32 independent variants in the MHC and one on the X chromosome. Most variants are non-coding and seem to act through cell-specific effects on gene expression and splicing. The likely functions of these variants implicate both adaptive and innate immune cells in the pathogenesis of multiple sclerosis, provide pivotal biological insight into the causes and mechanisms of multiple sclerosis, and some of the variants implicated in multiple sclerosis also mediate risk of other autoimmune and inflammatory diseases. Genetics offers an approach to showing causality for environmental factors, through Mendelian randomisation. No single variant is necessary or sufficient to cause multiple sclerosis; instead, each increases total risk in an additive manner. This combined contribution from many genetic factors to disease risk, or polygenicity, has important consequences for how we interpret the epidemiology of multiple sclerosis and how we counsel patients on risk and prognosis. Ongoing efforts are focused on increasing cohort sizes, increasing diversity and detailed characterisation of study populations, and translating these associations into an understanding of the biology of multiple sclerosis.

Association of rare variants in genes of immune regulation with pediatric autoimmune CNS diseases

Background

There is a gap in the literature regarding genetic underpinnings of pediatric autoimmune CNS diseases. This study explored rare gene variants implicated in immune dysregulation within these disorders.

Methods

This was a single-center observational study of children with inflammatory CNS disorder who had genetic testing through next generation focused exome sequencing targeting 155 genes associated with innate or adaptive immunity. For in silico prediction of functional effects of single-nucleotide variants, Polymorphism Phenotyping v2, and Sorting Intolerant from Tolerant were used, and Combined Annotation Dependent Depletion (CADD) scores were calculated. Identified genes were analyzed using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.

Results

Of 54 patients, 42 (77.8%) carried variant(s), among which 12 (22.2%) had 3–8 variants. Eighty-eight unique single-nucleotide variants of 55 genes were identified. The most variants were detected in UNC13D, LRBA, LYST, NOD2, DOCK8, RNASEH2A, STAT5B, and AIRE. The majority of variants (62, 70.4%) had CADD > 10. KEGG pathway analysis revealed seven genes associated with primary immunodeficiency (Benjamini 1.40E − 06), six genes with NOD-like receptor signaling (Benjamini 4.10E − 04), five genes with Inflammatory Bowel Disease (Benjamini 9.80E − 03), and five genes with NF-kappa B signaling pathway (Benjamini 1.90E − 02).

Discussion

We observed a high rate of identification of rare and low-frequency variants in immune regulatory genes in pediatric neuroinflammatory CNS disorders. We identified 88 unique single-nucleotide variants of 55 genes with pathway analysis revealing an enrichment of NOD2-receptor signaling, consistent with involvement of the pathway within other autoinflammatory conditions and warranting further investigation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-022-11325-2.

Dissection of multiple sclerosis genetics identifies B and CD4+ T cells as driver cell subsets

Background

Multiple sclerosis (MS) is an autoimmune condition of the central nervous system with a well-characterized genetic background. Prior analyses of MS genetics have identified broad enrichments across peripheral immune cells, yet the driver immune subsets are unclear.

Results

We utilize chromatin accessibility data across hematopoietic cells to identify cell type-specific enrichments of MS genetic signals. We find that CD4 T and B cells are independently enriched for MS genetics and further refine the driver subsets to T_h17 and memory B cells, respectively. We replicate our findings in data from untreated and treated MS patients and find that immunomodulatory treatments suppress chromatin accessibility at driver cell types. Integration of statistical fine-mapping and chromatin interactions nominate numerous putative causal genes, illustrating complex interplay between shared and cell-specific genes.

Conclusions

Overall, our study finds that open chromatin regions in CD4 T cells and B cells independently drive MS genetic signals. Our study highlights how careful integration of genetics and epigenetics can provide fine-scale insights into causal cell types and nominate new genes and pathways for disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02694-y.

The Effect of Peripheral Immune Cell Counts on the Risk of Multiple Sclerosis: A Mendelian Randomization Study

Objectives

Multiple sclerosis (MS) is a complex central nervous system (CNS) demyelinating disease, the etiology of which involves the interplay between genetic and environmental factors. We aimed to determine whether genetically predicted peripheral immune cell counts may have a causal effect on MS.

Methods

We used genetic variants strongly associated with cell counts of circulating leukocyte, lymphocyte, monocyte, neutrophil, eosinophil, and basophil, in addition to some subpopulations of T and B lymphocyte, as instrumental variables (IVs) to perform Mendelian randomization (MR) analyses. The effect of immune cell counts on MS risk was measured using the summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) genome-wide association studies (GWAS).

Results

Our findings indicated that higher leucocyte count [odds ratio (OR), 1.24; 95% confidence interval (CI), 1.07 - 1.43; p = 0.0039] and lymphocyte count (OR, 1.17; 95% CI, 1.01 – 1.35; p = 0.0317) were causally associated with MS susceptibility. In addition, we also found that increase of genetically predicted natural killer T (NKT) cell count is also associated with an increase MS risk (OR, 1.24; 95% CI, 1.06 - 1.45; p = 0.0082).

Conclusions

These findings show that the genetic predisposition to higher peripheral immune cell counts can exert a causal effect on MS risk, which confirms the crucial role played by peripheral immunity in MS. Particularly, the causal association between NKT cell count and MS underscores the relevance of exploring the functional roles of NKT cells in disease pathogenesis in future.

Natural Killer Cells in Multiple Sclerosis: Entering the Stage

Studies investigating the immunopathology of multiple sclerosis (MS) have largely focused on adaptive T and B lymphocytes. However, in recent years there has been an increased interest in the contribution of innate immune cells, amongst which the natural killer (NK) cells. Apart from their canonical role of controlling viral infections, cell stress and malignancies, NK cells are increasingly being recognized for their modulating effect on the adaptive immune system, both in health and autoimmune disease. From different lines of research there is now evidence that NK cells contribute to MS immunopathology. In this review, we provide an overview of studies that have investigated the role of NK cells in the pathogenesis of MS by use of the experimental autoimmune encephalomyelitis (EAE) animal model, MS genetics or through ex vivo and in vitro work into the immunology of MS patients. With the advent of modern hypothesis-free technologies such as single-cell transcriptomics, we are exposing an unexpected NK cell heterogeneity, increasingly blurring the boundaries between adaptive and innate immunity. We conclude that unravelling this heterogeneity, as well as the mechanistic link between innate and adaptive immune cell functions will lay the foundation for the use of NK cells as prognostic tools and therapeutic targets in MS and a myriad of other currently uncurable autoimmune disorders.

Twin study reveals non-heritable immune perturbations in multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory disorder of the central nervous system underpinned by partially understood genetic risk factors and environmental triggers and their undefined interactions1,2. Here we investigated the peripheral immune signatures of 61 monozygotic twin pairs discordant for MS to dissect the influence of genetic predisposition and environmental factors. Using complementary multimodal high-throughput and high-dimensional single-cell technologies in conjunction with data-driven computational tools, we identified an inflammatory shift in a monocyte cluster of twins with MS, coupled with the emergence of a population of IL-2 hyper-responsive transitional naive helper T cells as MS-related immune alterations. By integrating data on the immune profiles of healthy monozygotic and dizygotic twin pairs, we estimated the variance in CD25 expression by helper T cells displaying a naive phenotype to be largely driven by genetic and shared early environmental influences. Nonetheless, the expanding helper T cells of twins with MS, which were also elevated in non-twin patients with MS, emerged independent of the individual genetic makeup. These cells expressed central nervous system-homing receptors, exhibited a dysregulated CD25-IL-2 axis, and their proliferative capacity positively correlated with MS severity. Together, our matched-pair analysis of the extended twin approach allowed us to discern genetically and environmentally determined features of an MS-associated immune signature.

Predicting Multiple Sclerosis: Challenges and Opportunities

Determining effective means of preventing Multiple Sclerosis (MS) relies on testing preventive strategies in trial populations. However, because of the low incidence of MS, demonstrating that a preventive measure has benefit requires either very large trial populations or an enriched population with a higher disease incidence. Risk scores which incorporate genetic and environmental data could be used, in principle, to identify high-risk individuals for enrolment in preventive trials. Here we discuss the concepts of developing predictive scores for identifying individuals at high risk of MS. We discuss the empirical efforts to do so using real cohorts, and some of the challenges-both theoretical and practical-limiting this work. We argue that such scores could offer a means of risk stratification for preventive trial design, but are unlikely to ever constitute a clinically-helpful approach to predicting MS for an individual.

Contribution of Rare and Low-Frequency Variants to Multiple Sclerosis Susceptibility in the Italian Continental Population

Genome-wide association studies identified over 200 risk loci for multiple sclerosis (MS) focusing on common variants, which account for about 50% of disease heritability. The goal of this study was to investigate whether low-frequency and rare functional variants, located in MS-established associated loci, may contribute to disease risk in a relatively homogeneous population, testing their cumulative effect (burden) with gene-wise tests. We sequenced 98 genes in 588 Italian patients with MS and 408 matched healthy controls (HCs). Variants were selected using different filtering criteria based on allelic frequency and in silico functional impacts. Genes showing a significant burden (n = 17) were sequenced in an independent cohort of 504 MS and 504 HC. The highest signal in both cohorts was observed for the disruptive variants (stop-gain, stop-loss, or splicing variants) located in EFCAB13, a gene coding for a protein of an unknown function (p < 10^-4). Among these variants, the minor allele of a stop-gain variant showed a significantly higher frequency in MS versus HC in both sequenced cohorts (p = 0.0093 and p = 0.025), confirmed by a meta-analysis on a third independent cohort of 1298 MS and 1430 HC (p = 0.001) assayed with an SNP array. Real-time PCR on 14 heterozygous individuals for this variant did not evidence the presence of the stop-gain allele, suggesting a transcript degradation by non-sense mediated decay, supported by the evidence that the carriers of the stop-gain variant had a lower expression of this gene (p = 0.0184). In conclusion, we identified a novel low-frequency functional variant associated with MS susceptibility, suggesting the possible role of rare/low-frequency variants in MS as reported for other complex diseases.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Brain Barriers and Multiple Sclerosis: Novel Treatment Approaches from a Brain Barriers Perspective

Multiple sclerosis (MS) is considered a prototypic organ specific autoimmune disease targeting the central nervous system (CNS). Blood-brain barrier (BBB) breakdown and enhanced immune cell infiltration into the CNS parenchyma are early hallmarks of CNS lesion formation. Therapeutic targeting of immune cell trafficking across the BBB has proven a successful therapy for the treatment of MS, but comes with side effects and is no longer effective once patients have entered the progressive phase of the disease. Beyond the endothelial BBB, epithelial and glial brain barriers establish compartments in the CNS that differ in their accessibility to the immune system. There is increasing evidence that brain barrier abnormalities persist during the progressive stages of MS. Here, we summarize the role of endothelial, epithelial, and glial brain barriers in maintaining CNS immune privilege and our current knowledge on how impairment of these barriers contributes to MS pathogenesis. We discuss how therapeutic stabilization of brain barriers integrity may improve the safety of current therapeutic regimes for treating MS. This may also allow for the development of entirely novel therapeutic approaches aiming to restore brain barriers integrity and thus CNS homeostasis, which may be specifically beneficial for the treatment of progressive MS.

Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis

Background

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) mediated by autoimmunity. No objective clinical indicators are available for the diagnosis and prognosis of MS. Extracellular proteins are most glycosylated and likely to enter into the body fluid to serve as potential biomarkers. Our work will contribute to the in-depth study of the functions of extracellular proteins and the discovery of disease biomarkers.

Methods

MS expression profiling data of the human brain was downloaded from the Gene Expression Omnibus (GEO). Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases. GO and KEGG were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Key EP-DEGs levels were detected in the CSF of MS patients. ROC curve and survival analysis were used to evaluate the diagnostic and prognostic ability of key EP-DEGs.

Results

We screened 133 EP-DEGs from DEGs. EP-DEGs were enriched in the collagen-containing extracellular matrix, signaling receptor activator activity, immune-related pathways, and PI3K-Akt signaling pathway. The PPI network of EP-DEGs had 85 nodes and 185 edges. We identified 4 key extracellular proteins IL17A, IL2, CD44, IGF1, and 16 extracellular proteins that interacted with IL17A. We clinically verified that IL17A levels decreased, but Del-1 and resolvinD1 levels increased. The diagnostic accuracy of Del-1 (AUC: 0.947) was superior to that of IgG (AUC: 0.740) with a sensitivity of 82.4% and a specificity of 100%. High Del-1 levels were significantly associated with better relapse-free and progression-free survival.

Conclusion

IL17A, IL2, CD44, and IGF1 may be key extracellular proteins in the pathogenesis of MS. IL17A, Del-1, and resolvinD1 may co-regulate the development of MS and Del-1 is a potential biomarker of MS. We used bioinformatics methods to explore the biomarkers of MS and validated the results in clinical samples. The study provides a theoretical and experimental basis for revealing the pathogenesis of MS and improving the diagnosis and prognosis of MS.

Specific hypomethylation programs underpin B cell activation in early multiple sclerosis

Epigenetic changes have been consistently detected in different cell types in multiple sclerosis (MS). However, their contribution to MS pathogenesis remains poorly understood partly because of sample heterogeneity and limited coverage of array-based methods. To fill this gap, we conducted a comprehensive analysis of genome-wide DNA methylation patterns in four peripheral immune cell populations isolated from 29 MS patients at clinical disease onset and 24 healthy controls. We show that B cells from new-onset untreated MS cases display more significant methylation changes than other disease-implicated immune cell types, consisting of a global DNA hypomethylation signature. Importantly, 4,933 MS-associated differentially methylated regions in B cells were identified, and this epigenetic signature underlies specific genetic programs involved in B cell differentiation and activation. Integration of the methylome to changes in gene expression and susceptibility-associated regions further indicates that hypomethylated regions are significantly associated with the up-regulation of cell activation transcriptional programs. Altogether, these findings implicate aberrant B cell function in MS etiology.

Estimating prevalence of human traits among populations from polygenic risk scores

The genetic basis of phenotypic variation across populations has not been well explained for most traits. Several factors may cause disparities, from variation in environments to divergent population genetic structure. We hypothesized that a population-level polygenic risk score (PRS) can explain phenotypic variation among geographic populations based solely on risk allele frequencies. We applied a population-specific PRS (psPRS) to 26 populations from the 1000 Genomes to four phenotypes: lactase persistence (LP), melanoma, multiple sclerosis (MS) and height. Our models assumed additive genetic architecture among the polymorphisms in the psPRSs, as is convention. Linear psPRSs explained a significant proportion of trait variance ranging from 0.32 for height in men to 0.88 for melanoma. The best models for LP and height were linear, while those for melanoma and MS were nonlinear. As not all variants in a PRS may confer similar, or even any, risk among diverse populations, we also filtered out SNPs to assess whether variance explained was improved using psPRSs with fewer SNPs. Variance explained usually improved with fewer SNPs in the psPRS and was as high as 0.99 for height in men using only 548 of the initial 4208 SNPs. That reducing SNPs improves psPRSs performance may indicate that missing heritability is partially due to complex architecture that does not mandate additivity, undiscovered variants or spurious associations in the databases. We demonstrated that PRS-based analyses can be used across diverse populations and phenotypes for population prediction and that these comparisons can identify the universal risk variants.

De novo germline mutation in the dual specificity phosphatase 10 gene accelerates autoimmune diabetes

Insulin-dependent or type 1 diabetes (T1D) is a polygenic autoimmune disease. In humans, more than 60 loci carrying common variants that confer disease susceptibility have been identified by genome-wide association studies, with a low individual risk contribution for most variants excepting those of the major histocompatibility complex (MHC) region (40 to 50% of risk); hence the importance of missing heritability due in part to rare variants. Nonobese diabetic (NOD) mice recapitulate major features of the human disease including genetic aspects with a key role for the MHC haplotype and a series of Idd loci. Here we mapped in NOD mice rare variants arising from genetic drift and significantly impacting disease risk. To that aim we established by selective breeding two sublines of NOD mice from our inbred NOD/Nck colony exhibiting a significant difference in T1D incidence. Whole-genome sequencing of high (H)- and low (L)-incidence sublines (NOD/Nck^H and NOD/Nck^L) revealed a limited number of subline-specific variants. Treating age of diabetes onset as a quantitative trait in automated meiotic mapping (AMM), enhanced susceptibility in NOD/Nck^H mice was unambiguously attributed to a recessive missense mutation of Dusp10, which encodes a dual specificity phosphatase. The causative effect of the mutation was verified by targeting Dusp10 with CRISPR-Cas9 in NOD/Nck^L mice, a manipulation that significantly increased disease incidence. The Dusp10 mutation resulted in islet cell down-regulation of type I interferon signature genes, which may exert protective effects against autoimmune aggression. De novo mutations akin to rare human susceptibility variants can alter the T1D phenotype.

An Investigation of the Role of Common and Rare Variants in a Large Italian Multiplex Family of Multiple Sclerosis Patients

Known multiple sclerosis (MS) susceptibility variants can only explain half of the disease's estimated heritability, whereas low-frequency and rare variants may partly account for the missing heritability. Thus, here we sought to determine the occurrence of rare functional variants in a large Italian MS multiplex family with five affected members. For this purpose, we combined linkage analysis and next-generation sequencing (NGS)-based whole exome and whole genome sequencing (WES and WGS, respectively). The genetic burden attributable to known common MS variants was also assessed by weighted genetic risk score (wGRS). We found a significantly higher burden of common variants in the affected family members compared to that observed among sporadic MS patients and healthy controls (HCs). We also identified 34 genes containing at least one low-frequency functional variant shared among all affected family members, showing a significant enrichment in genes involved in specific biological processes-particularly mRNA transport-or neurodegenerative diseases. Altogether, our findings point to a possible pathogenic role of different low-frequency functional MS variants belonging to shared pathways. We propose that these rare variants, together with other known common MS variants, may account for the high number of affected family members within this MS multiplex family.

Investigating rare pathogenic/likely pathogenic exonic variation in bipolar disorder

Bipolar disorder (BD) is a serious mental illness with substantial common variant heritability. However, the role of rare coding variation in BD is not well established. We examined the protein-coding (exonic) sequences of 3,987 unrelated individuals with BD and 5,322 controls of predominantly European ancestry across four cohorts from the Bipolar Sequencing Consortium (BSC). We assessed the burden of rare, protein-altering, single nucleotide variants classified as pathogenic or likely pathogenic (P-LP) both exome-wide and within several groups of genes with phenotypic or biologic plausibility in BD. While we observed an increased burden of rare coding P-LP variants within 165 genes identified as BD GWAS regions in 3,987 BD cases (meta-analysis OR = 1.9, 95% CI = 1.3-2.8, one-sided p = 6.0 × 10-4), this enrichment did not replicate in an additional 9,929 BD cases and 14,018 controls (OR = 0.9, one-side p = 0.70). Although BD shares common variant heritability with schizophrenia, in the BSC sample we did not observe a significant enrichment of P-LP variants in SCZ GWAS genes, in two classes of neuronal synaptic genes (RBFOX2 and FMRP) associated with SCZ or in loss-of-function intolerant genes. In this study, the largest analysis of exonic variation in BD, individuals with BD do not carry a replicable enrichment of rare P-LP variants across the exome or in any of several groups of genes with biologic plausibility. Moreover, despite a strong shared susceptibility between BD and SCZ through common genetic variation, we do not observe an association between BD risk and rare P-LP coding variants in genes known to modulate risk for SCZ.

HLA Class II Polymorphisms Modulate Gut Microbiota and Experimental Autoimmune Encephalomyelitis Phenotype

Multiple sclerosis (MS) is an autoimmune disease of the CNS in which the interaction between genetic and environmental factors plays an important role in disease pathogenesis. Although environmental factors account for 70% of disease risk, the exact environmental factors associated with MS are unknown. Recently, gut microbiota has emerged as a potential missing environmental factor linked with the pathobiology of MS. Yet, how genetic factors, such as HLA class II gene(s), interact with gut microbiota and influence MS is unclear. In the current study, we investigated whether HLA class II genes that regulate experimental autoimmune encephalomyelitis (EAE) and MS susceptibility also influence gut microbiota. Previously, we have shown that HLA-DR3 transgenic mice lacking endogenous mouse class II genes (AE-KO) were susceptible to myelin proteolipid protein (91-110)-induced EAE, an animal model of MS, whereas AE-KO.HLA-DQ8 transgenic mice were resistant. Surprisingly, HLA-DR3.DQ8 double transgenic mice showed higher disease prevalence and severity compared with HLA-DR3 mice. Gut microbiota analysis showed that HLA-DR3, HLA-DQ8, and HLA-DR3.DQ8 double transgenic mice microbiota are compositionally different from AE-KO mice. Within HLA class II transgenic mice, the microbiota of HLA-DQ8 mice were more similar to HLA-DR3.DQ8 than HLA-DR3. As the presence of DQ8 on an HLA-DR3 background increases disease severity, our data suggests that HLA-DQ8-specific microbiota may contribute to disease severity in HLA-DR3.DQ8 mice. Altogether, our study provides evidence that the HLA-DR and -DQ genes linked to specific gut microbiota contribute to EAE susceptibility or resistance in a transgenic animal model of MS.

Liver kinase B1 rs9282860 polymorphism and risk for multiple sclerosis in White and Black Americans

BACKGROUND

We previously reported that the single nucleotide polymorphism (SNP) rs9282860 in serine threonine kinase 11 (STK11) gene which codes for liver kinase B1 (LKB1) has higher prevalence in White relapsing-remitting multiple sclerosis (RRMS) patients than controls. However it is not known if this SNP is a risk factor for MS in other populations.

METHODS

We assessed the prevalence of the STK11 SNP in samples collected from African American (AA) persons with MS (PwMS) and controls at multiple Veterans Affairs (VA) Medical Centers and from a network of academic MS centers. Genotyping was carried out using a specific Taqman assay. Comparisons of SNP frequencies were made using Fisher's exact test to determine significance and odds ratios. Group means were compared by appropriate t-tests based on normality and variance using SPSS V27.

RESULTS

There were no significant differences in average age at first symptom onset, age at diagnosis, disease duration, or disease severity between RRMS patients recruited from VAMCs versus non-VAMCs. The SNP was more prevalent in AA than White PwMS, however only in secondary progressive MS (SPMS) patients was that difference statistically significant. AA SPMS patients had higher STK11 SNP prevalence than controls; and in that cohort the SNP was associated with older age at symptom onset and at diagnosis.

CONCLUSIONS

The results suggest that the STK11 SNP represents a risk factor for SPMS in AA patients, and can influence both early (onset) and later (conversion to SPMSS) events.

Genetic contributors to risk of schizophrenia in the presence of a 22q11.2 deletion

Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n = 35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (padj = 6.73 × 10-6). Novel reciprocal case-control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to the deletion conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present.

Host Genetics and Gut Microbiome: Perspectives for Multiple Sclerosis

As a complex disease, Multiple Sclerosis (MS)'s etiology is determined by both genetic and environmental factors. In the last decade, the gut microbiome has emerged as an important environmental factor, but its interaction with host genetics is still unknown. In this review, we focus on these dual aspects of MS pathogenesis: we describe the current knowledge on genetic factors related to MS, based on genome-wide association studies, and then illustrate the interactions between the immune system, gut microbiome and central nervous system in MS, summarizing the evidence available from Experimental Autoimmune Encephalomyelitis mouse models and studies in patients. Finally, as the understanding of influence of host genetics on the gut microbiome composition in MS is in its infancy, we explore this issue based on the evidence currently available from other autoimmune diseases that share with MS the interplay of genetic with environmental factors (Inflammatory Bowel Disease, Rheumatoid Arthritis and Systemic Lupus Erythematosus), and discuss avenues for future research.

The CD8 T Cell-Epstein-Barr Virus-B Cell Trialogue: A Central Issue in Multiple Sclerosis Pathogenesis

The cause and the pathogenic mechanisms leading to multiple sclerosis (MS), a chronic inflammatory disease of the central nervous system (CNS), are still under scrutiny. During the last decade, awareness has increased that multiple genetic and environmental factors act in concert to modulate MS risk. Likewise, the landscape of cells of the adaptive immune system that are believed to play a role in MS immunopathogenesis has expanded by including not only CD4 T helper cells but also cytotoxic CD8 T cells and B cells. Once the key cellular players are identified, the main challenge is to define precisely how they act and interact to induce neuroinflammation and the neurodegenerative cascade in MS. CD8 T cells have been implicated in MS pathogenesis since the 80's when it was shown that CD8 T cells predominate in MS brain lesions. Interest in the role of CD8 T cells in MS was revived in 2000 and the years thereafter by studies showing that CNS-recruited CD8 T cells are clonally expanded and have a memory effector phenotype indicating in situ antigen-driven reactivation. The association of certain MHC class I alleles with MS genetic risk implicates CD8 T cells in disease pathogenesis. Moreover, experimental studies have highlighted the detrimental effects of CD8 T cell activation on neural cells. While the antigens responsible for T cell recruitment and activation in the CNS remain elusive, the high efficacy of B-cell depleting drugs in MS and a growing number of studies implicate B cells and Epstein-Barr virus (EBV), a B-lymphotropic herpesvirus that is strongly associated with MS, in the activation of pathogenic T cells. This article reviews the results of human studies that have contributed to elucidate the role of CD8 T cells in MS immunopathogenesis, and discusses them in light of current understanding of autoreactivity, B-cell and EBV involvement in MS, and mechanism of action of different MS treatments. Based on the available evidences, an immunopathological model of MS is proposed that entails a persistent EBV infection of CNS-infiltrating B cells as the target of a dysregulated cytotoxic CD8 T cell response causing CNS tissue damage.

Exome sequencing reveals novel rare variants in Iranian familial multiple sclerosis: The importance of POLD2 in the disease pathogenesis

The prevalence of familial multiple sclerosis (FMS) is increasing worldwide which endorses the heritability of the disease. Given that many genome variations are ethnicity-specific and consanguineous marriage could affect genetic diseases, hereditary disease gene analysis among FMS patients from Iran, a country with high rates of parental consanguinity, could be highly effective in finding mutations underlying disease pathogenesis. To examine rare genetic mutations, we selected three Iranian FMS cases with ≥3 MS patients in more than one generation and performed whole exome sequencing. We identified a homozygous rare missense variant in POLD2 (p. Arg141Cys; rs372336011). Molecular dynamics analysis showed reduced polar dehydration energy and conformational changes in POLD2 mutant. Further, we found a heterozygote rare missense variant in NBFP1 (p. Gly487Asp; rs778806175). Our study revealed the possible role of novel rare variants in FMS. Molecular dynamic simulation provided the initial evidence of the structural changes behind POLD2 mutant.

Genes and environment in multiple sclerosis: Impact of temporal changes in the sex ratio on recurrence risks

Objective:

To evaluate the impact of temporal increase of female to male (F:M) sex ratio for persons with multiple sclerosis (MS) on the familial risk (empiric recurrence risks or RRs) for biological relatives of affected individuals.

Methods:

Detailed family histories were systematically obtained from people with MS attending the University of British Columbia Hospital MS Clinic. The study cohort was born in 1970 or more recently. Data were collected from 1 September 2015 to 31 January 2019. The study was designed to allow only one proband per family. Age-corrected RRs for biological relatives of probands were calculated based on a modification of the maximum-likelihood approach.

Results:

Data analyses were possible for 746 unique probands (531 females; 215 males) and 19,585 of their biological relatives. RRs were temporally impacted.

Conclusion:

Both genetic sharing and environmental factors are important in determining RRs. It appears that there is an increase in MS risk due to environmental factors in later life (i.e. not shared family environment). Environmental exposures in genetically predisposed individuals might be driving the MS risk. The increase in F:M ratio of RRs for sisters/brothers of female probands over time is likely due to environmental differences.

Distinct effect of prenatal and postnatal brain expression across 20 brain disorders and anthropometric social traits: a systematic study of spatiotemporal modularity

Different spatiotemporal abnormalities have been implicated in different neuropsychiatric disorders and anthropometric social traits, yet an investigation in the temporal network modularity with brain tissue transcriptomics has been lacking. We developed a supervised network approach to investigate the genome-wide association study (GWAS) results in the spatial and temporal contexts and demonstrated it in 20 brain disorders and anthropometric social traits. BrainSpan transcriptome profiles were used to discover significant modules enriched with trait susceptibility genes in a developmental stage-stratified manner. We investigated whether, and in which developmental stages, GWAS-implicated genes are coordinately expressed in brain transcriptome. We identified significant network modules for each disorder and trait at different developmental stages, providing a systematic view of network modularity at specific developmental stages for a myriad of brain disorders and traits. Specifically, we observed a strong pattern of the fetal origin for most psychiatric disorders and traits [such as schizophrenia (SCZ), bipolar disorder, obsessive-compulsive disorder and neuroticism], whereas increased co-expression activities of genes were more strongly associated with neurological diseases [such as Alzheimer's disease (AD) and amyotrophic lateral sclerosis] and anthropometric traits (such as college completion, education and subjective well-being) in postnatal brains. Further analyses revealed enriched cell types and functional features that were supported and corroborated prior knowledge in specific brain disorders, such as clathrin-mediated endocytosis in AD, myelin sheath in multiple sclerosis and regulation of synaptic plasticity in both college completion and education. Our study provides a landscape view of the spatiotemporal features in a myriad of brain-related disorders and traits.

Genomic and functional evaluation of TNFSF14 in multiple sclerosis susceptibility

Among multiple sclerosis (MS) susceptibility genes, the strongest non-human leukocyte antigen (HLA) signal in the Italian population maps to the TNFSF14 gene encoding LIGHT, a glycoprotein involved in dendritic cell (DC) maturation. Through fine-mapping in a large Italian dataset (4,198 patients with MS and 3,903 controls), we show that the TNFSF14 intronic SNP rs1077667 is the primarily MS-associated variant in the region. Expression quantitative trait locus (eQTL) analysis indicates that the MS risk allele is significantly associated with reduced TNFSF14 messenger RNA levels in blood cells, which is consistent with the allelic imbalance in RNA-Seq reads (P < 0.0001). The MS risk allele is associated with reduced levels of TNFSF14 gene expression (P < 0.01) in blood cells from 84 Italian patients with MS and 80 healthy controls (HCs). Interestingly, patients with MS are lower expressors of TNFSF14 compared to HC (P < 0.007). Individuals homozygous for the MS risk allele display an increased percentage of LIGHT-positive peripheral blood myeloid DCs (CD11c⁺, P = 0.035) in 37 HCs, as well as in in vitro monocyte-derived DCs from 22 HCs (P = 0.04). Our findings suggest that the intronic variant rs1077667 alters the expression of TNFSF14 in immune cells, which may play a role in MS pathogenesis.

Autoimmune Disorders of the Nervous System: Pathophysiology, Clinical Features, and Therapy

Remarkable discoveries over the last two decades have elucidated the autoimmune basis of several, previously poorly understood, neurological disorders. Autoimmune disorders of the nervous system may affect any part of the nervous system, including the brain and spinal cord (central nervous system, CNS) and also the peripheral nerves, neuromuscular junction and skeletal muscle (peripheral nervous system, PNS). This comprehensive overview of this rapidly evolving field presents the factors which may trigger breakdown of self-tolerance and development of autoimmune disease in some individuals. Then the pathophysiological basis and clinical features of autoimmune diseases of the nervous system are outlined, with an emphasis on the features which are important to recognize for accurate clinical diagnosis. Finally the latest therapies for autoimmune CNS and PNS disorders and their mechanisms of action and the most promising research avenues for targeted immunotherapy are discussed.

Genetic Variation in WNT9B Increases Relapse Hazard in Multiple Sclerosis

OBJECTIVE

Many multiple sclerosis (MS) genetic susceptibility variants have been identified, but understanding disease heterogeneity remains a key challenge. Relapses are a core feature of MS and a common primary outcome of clinical trials, with prevention of relapses benefiting patients immediately and potentially limiting long-term disability accrual. We aim to identify genetic variation associated with relapse hazard in MS by analyzing the largest study population to date.

METHODS

We performed a genomewide association study (GWAS) in a discovery cohort and investigated the genomewide significant variants in a replication cohort. Combining both cohorts, we captured a total of 2,231 relapses occurring before the start of any immunomodulatory treatment in 991 patients. For assessing time to relapse, we applied a survival analysis utilizing Cox proportional hazards models. We also investigated the association between MS genetic risk scores and relapse hazard and performed a gene ontology pathway analysis.

RESULTS

The low-frequency genetic variant rs11871306 within WNT9B reached genomewide significance in predicting relapse hazard and replicated (meta-analysis hazard ratio (HR) = 2.15, 95% confidence interval (CI) = 1.70-2.78, p = 2.07 × 10^-10 ). A pathway analysis identified an association of the pathway "response to vitamin D" with relapse hazard (p = 4.33 × 10^-6 ). The MS genetic risk scores, however, were not associated with relapse hazard.

INTERPRETATION

Genetic factors underlying disease heterogeneity differ from variants associated with MS susceptibility. Our findings imply that genetic variation within the Wnt signaling and vitamin D pathways contributes to differences in relapse occurrence. The present study highlights these cross-talking pathways as potential modulators of MS disease activity. ANN NEUROL 2021;89:884-894.

PLCG2 rs72824905 Variant Reduces the Risk of Alzheimer's Disease and Multiple Sclerosis

We aimed to evaluate the association of PLCG2 rs72824905 variant with Alzheimer's disease (AD) and multiple sclerosis (MS) using large-scale genetic association study datasets. We selected 50,024 AD cases and 467,330 controls, and 32,367 MS cases and 36,012 controls. We found moderate heterogeneity of rs72824905 in different studies. We found significant association between rs72824905 G allele and reduced AD risk (OR = 0.66, 95% CI 0.59-0.74, p = 5.91E-14). Importantly, rs72824905 G allele could also significantly reduce the risk of MS with OR = 0.94, p = 3.63E-05. Hence, the effects of rs72824905 on AD and MS are consistent.

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.