Genetic burden of MS risk variants distinguish patients from healthy individuals but are not associated with disease activity

Whole-blood methylation signatures are associated with and accurately classify multiple sclerosis disease severity

BACKGROUND

The variation in multiple sclerosis (MS) disease severity is incompletely explained by genetics, suggesting genetic and environmental interactions are involved. Moreover, the lack of prognostic biomarkers makes it difficult for clinicians to optimise care. DNA methylation is one epigenetic mechanism by which gene-environment interactions can be assessed. Here, we aimed to identify DNA methylation patterns associated with mild and severe relapse-onset MS (RMS) and to test the utility of methylation as a predictive biomarker.

METHODS

We conducted an epigenome-wide association study between 235 females with mild (n = 119) or severe (n = 116) with RMS. Methylation was measured with the Illumina methylationEPIC array and analysed using logistic regression. To generate hypotheses about the functional consequence of differential methylation, we conducted gene set enrichment analysis using ToppGene. We compared the accuracy of three machine learning models in classifying disease severity: (1) clinical data available at baseline (age at onset and first symptoms) built using elastic net (EN) regression, (2) methylation data using EN regression and (3) a weighted methylation risk score of differentially methylated positions (DMPs) from the main analysis using logistic regression. We used a conservative 70:30 test:train split for classification modelling. A false discovery rate threshold of 0.05 was used to assess statistical significance.

RESULTS

Females with mild or severe RMS had 1472 DMPs in whole blood (839 hypermethylated, 633 hypomethylated in the severe group). Differential methylation was enriched in genes related to neuronal cellular compartments and processes, and B-cell receptor signalling. Whole-blood methylation levels at 1708 correlated CpG sites classified disease severity more accurately (machine learning model 2, AUC = 0.91) than clinical data (model 1, AUC = 0.74) or the wMRS (model 3, AUC = 0.77). Of the 1708 selected CpGs, 100 overlapped with DMPs from the main analysis at the gene level. These overlapping genes were enriched in neuron projection and dendrite extension, lending support to our finding that neuronal processes, rather than immune processes, are implicated in disease severity.

CONCLUSION

RMS disease severity is associated with whole-blood methylation at genes related to neuronal structure and function. Moreover, correlated whole-blood methylation patterns can assign disease severity in females with RMS more accurately than clinical data available at diagnosis.

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.

Effects of Vitamin D and Body Mass Index on Disease Risk and Relapse Hazard in Multiple Sclerosis: A Mendelian Randomization Study

Background and Objectives

Decreased vitamin D levels and obesity are associated with an increased risk for multiple sclerosis (MS). However, whether they also affect the disease course after onset remains unclear. With larger data sets now available, we used Mendelian randomization (MR) to determine whether serum 25-hydroxyvitamin D (25OHD) and body mass index (BMI) are causally associated with MS risk and, moving beyond susceptibility toward heterogeneity, with relapse hazard.

Methods

We used genetic variants from 4 distinct genome-wide association studies (GWASs) for serum 25OHD in up to 416,247 individuals and for BMI from a GWAS in 681,275 individuals. Applying 2-sample MR, we examined associations of 25OHD and BMI with the risk of MS, with summary statistics from the International Multiple Sclerosis Genetics Consortium GWAS in 14,802 MS cases and 26,703 controls. In addition, we examined associations with relapse hazard, with data from our GWAS in 506 MS cases.

Results

A 1-SD increase in genetically predicted natural-log transformed 25OHD levels decreased odds of MS up to 28% (95% CI: 12%–40%, p = 0.001) and decreased hazard for a relapse occurring up to 43% (95% CI: 15%–61%, p = 0.006). A 1-SD increase in genetically predicted BMI, corresponding to roughly 5 kg/m², increased risk for MS with 30% (95% CI: 15%–47%, p = 3.76 × 10⁻⁵). On the contrary, we did not find evidence for a causal role of higher BMI with an increased hazard for occurrence of a relapse.

Discussion

This study supports causal effects of genetically predicted serum 25OHD concentrations and BMI on risk of MS. In contrast, serum 25OHD but not BMI is significantly associated with relapse hazard after onset. These findings might offer clinical implications for both prevention and treatment.

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.

Genetic and gene expression signatures in multiple sclerosis

Multiple sclerosis (MS) exhibits a well-documented increased incidence in individuals with respective family history, that is, is a heritable disease. In the last decade, genome-wide association studies have enabled the agnostic interrogation of the whole genome at a large scale. To date, over 200 genetic associations have been described at the strict level of genome-wide significance. Our current understanding of MS genetics can explain up to half of the disease's heritability, raising the important question of whether this is enough information to leverage toward improving diagnosis in MS. Parallel advancements in technologies that allow the characterization of the full transcriptome down to the single-cell level have enabled the generation of an unprecedented wealth of information. Transcriptional changes of putative causal cells could be utilized to identify early signs of disease onset. These recent findings in genetics and genomics, coupled with new technologies and deeply phenotyped cohorts, have the potential to improve the diagnosis of MS.

Multiple sclerosis: disease modifying therapy and the human leukocyte antigen

OBJECTIVE

To investigate the potential relationship between the human leukocyte antigen (HLA) type (class I and II) and the response to several disease-modifying therapies (DMTs) in patients with multiple sclerosis (MS).

METHODS

We analyzed clinical data of 87 patients with MS at the beginning and end of each type of DMT including the disease duration, Expanded Disability Status Scale and Multiple Sclerosis Severity Score (MSSS). Genotyping of HLA-DRB1, HLA-DPB1, HLA-DQB1, HLA-A, HLA-B and HLA-C alleles were identified using high-resolution techniques. Statistical correlation between the HLA type and response to DMTs was done using the initial and final MSSS.

RESULTS

Statistical relationships (p < 0.05) were found for only 15 of 245 alleles tested. There was a reduction in the MSSS for patients treated with corticosteroids (DRB1*15:01, DPB1*04:01, DQB1*02:01 and DQB1*03:01), azathioprine (DRB1*03:01, DPB1*04:01, DQB1*03:02, DQB1*06:02, HLA-C*07:02), interferon β-1a 22 mcg (DRB1*11:04, DQB1*03:01 and DQB1*03:02), interferon β-1a 30 mcg (DPB1*02:01, HLA-C*05:01) and interferon β-1b (DQB1*02:01).

CONCLUSION

These findings suggest a few relationships between the HLA and response to DMTs in the disability for some types of HLA class I and II alleles in a specific subset of MS patients.

Genotype and Phenotype in Multiple Sclerosis-Potential for Disease Course Prediction?

PURPOSE OF REVIEW

This review will examine the current evidence that genetic and/or epigenetic variation may influence the multiple sclerosis (MS) clinical course, phenotype, and measures of MS severity including disability progression and relapse rate.

RECENT FINDINGS

There is little evidence that MS clinical phenotype is under significant genetic control. There is increasing evidence that there may be genetic determinants of the rate of disability progression. However, studies that can analyse disability progression and take into account all the confounding variables such as treatment, clinical characteristics, and environmental factors are by necessity longitudinal, relatively small, and generally of short duration, and thus do not lend themselves to the assessment of hundreds of thousands of genetic variables obtained from GWAS. Despite this, there is recent evidence to support the association of genetic loci with relapse rate. Recent progress suggests that genetic variations could be associated with disease severity, but not MS clinical phenotype, but these findings are not definitive and await replication. Pooling of study results, application of other genomic techniques including epigenomics, and analysis of biomarkers of progression could functionally validate putative severity markers.

Genetic basis for relapse rate in multiple sclerosis: Association with LRP2 genetic variation

BACKGROUND

In contrast to successes for multiple sclerosis (MS) susceptibility, the genetic basis for clinical heterogeneity remains largely unresolved.

OBJECTIVES

We investigate the first reported genetic association with relapse rate.

METHODS

We genotyped variant rs12988804 in LRP2 in a homogeneous study population of 527 Belgian MS patients with 970 documented relapses.

RESULTS

The rs12988804*T allele is associated with a 1.16-fold increased hazard rate for a relapse occurring ( P = 0.0078) and a higher baseline relapse rate prior to immunomodulatory treatment ( P = 0.044).

CONCLUSION

Variant rs12988804 in LRP2, the first example of a genome-wide significant association with relapse rate in MS, is replicated in an independent study.