Smoking and multiple sclerosis risk: a Mendelian randomization study

Applying a genetic risk score model to enhance prediction of future multiple sclerosis diagnosis at first presentation with optic neuritis

Optic neuritis (ON) is associated with numerous immune-mediated inflammatory diseases, but 50% patients are ultimately diagnosed with multiple sclerosis (MS). Differentiating MS-ON from non-MS-ON acutely is challenging but important; non-MS ON often requires urgent immunosuppression to preserve vision. Using data from the United Kingdom Biobank we showed that combining an MS-genetic risk score (GRS) with demographic risk factors (age, sex) significantly improved MS prediction in undifferentiated ON; one standard deviation of MS-GRS increased the Hazard of MS 1.3-fold (95% confidence interval 1.07-1.55, P < 0.01). Participants stratified into quartiles of predicted risk developed incident MS at rates varying from 4% (95%CI 0.5-7%, lowest risk quartile) to 41% (95%CI 33-49%, highest risk quartile). The model replicated across two cohorts (Geisinger, USA, and FinnGen, Finland). This study indicates that a combined model might enhance individual MS risk stratification, paving the way for precision-based ON treatment and earlier MS disease-modifying therapy.

Modifiable risk factors for multiple sclerosis have consistent directions of effect across diverse ethnic backgrounds: a nested case-control study in an English population-based cohort

BACKGROUND

Multiple sclerosis is a leading cause of non-traumatic neurological disability among young adults worldwide. Prior studies have identified modifiable risk factors for multiple sclerosis in cohorts of White ethnicity, such as infectious mononucleosis, smoking, and obesity during adolescence/early adulthood. It is unknown whether modifiable exposures for multiple sclerosis have a consistent impact on risk across ethnic groups.

AIM

To determine whether modifiable risk factors for multiple sclerosis have similar effects across diverse ethnic backgrounds.

METHODS

We conducted a nested case-control study using data from the UK Clinical Practice Research Datalink. Multiple sclerosis cases diagnosed from 2001 until 2022 were identified from electronic healthcare records and matched to unaffected controls based on year of birth. We used stratified logistic regression models and formal statistical interaction tests to determine whether the effect of modifiable risk factors for multiple sclerosis differed by ethnicity.

RESULTS

We included 9662 multiple sclerosis cases and 118,914 age-matched controls. The cohort was ethnically diverse (MS: 277 South Asian [2.9%], 251 Black [2.6%]; Controls: 5043 South Asian [5.7%], 4019 Black [4.5%]). The age at MS diagnosis was earlier in the Black (40.5 [SD 10.9]) and Asian (37.2 [SD 10.0]) groups compared with White cohort (46.1 [SD 12.2]). There was a female predominance in all ethnic groups; however, the relative proportion of males was higher in the South Asian population (proportion of women 60.3% vs 71% [White] and 75.7% [Black]). Established modifiable risk factors for multiple sclerosis-smoking, obesity, infectious mononucleosis, low vitamin D, and head injury-were consistently associated with multiple sclerosis in the Black and South Asian cohorts. The magnitude and direction of these effects were broadly similar across all ethnic groups examined. There was no evidence of statistical interaction between ethnicity and any tested exposure, and no evidence to suggest that differences in area-level deprivation modifies these risk factor-disease associations. These findings were robust to a range of sensitivity analyses.

CONCLUSIONS AND RELEVANCE

Established modifiable risk factors for multiple sclerosis are applicable across diverse ethnic backgrounds. Efforts to reduce the population incidence of multiple sclerosis by tackling these risk factors need to be inclusive of people from diverse ethnicities.

Characterizing causal relationships of visceral fat and body shape on multiple sclerosis risk

BACKGROUND

Epidemiologic studies have established obesity as a risk factor for multiple sclerosis (MS). These studies relied on body-mass index (BMI) and body size silhouettes as the primary measures of obesity. Unfortunately, the causal mechanisms through which obesity confers MS risk are not yet known.

OBJECTIVES

To investigate the causal effects of multiple specific measures of body fat on MS risk in populations of European descent, using Mendelian randomization (MR).

METHODS

MR is a genetic instrumental variable analysis utilizing genome-wide association (GWA) summary statistics to infer causality between phenotypes. MR analyses were performed to investigate the relationships between seven measures of body fat (BMI, waist-hip ratio, visceral adipose tissue [VAT], subcutaneous adipose tissue, and arm-, leg-, and trunk-fat to total body fat ratio) and MS risk.

RESULTS

Only BMI and VAT were significantly associated with MS risk in separate MR analyses (βBMI=0.27, pBMI<0.001; βVAT=0.28, pVAT=0.006). High correlation between BMI and VAT instruments suggest that two-sample MR associations for BMI and VAT likely capture the same causal mechanisms.

CONCLUSIONS

BMI and VAT were causally associated with MS risk in European populations, though their effects do not appear independent, suggesting overlap in the role of overall body mass and visceral obesity in MS pathogenesis.

A systematic review of Mendelian randomization studies on multiple sclerosis

Mendelian randomization (MR) is a powerful approach for assessing the causal effect of putative risk factors on an outcome, using genetic variants as instrumental variables. The methodology and application developed in the framework of MR have been dramatically improved, taking advantage of the many public genome-wide association study (GWAS) data. The availability of summary-level data allowed to perform numerous MR studies especially for complex diseases, pinpointing modifiable exposures causally related to increased or decreased disease risk. Multiple sclerosis (MS) is a complex multifactorial disease whose aetiology involves both genetic and non-genetic risk factors and their interplay. Previous observational studies have revealed associations between candidate modifiable exposures and MS risk; although being prone to confounding, and reverse causation, these studies were unable to draw causal conclusions. MR analysis addresses the limitations of observational studies and allows to establish reliable and accurate causal conclusions. Here, we systematically reviewed the studies evaluating the causal effect, through MR, of genetic and non-genetic exposures on MS risk. Among 107 papers found, only 42 were eligible for final evaluation and qualitative synthesis. We found that, above all, low vitamin D levels and high adult body mass index (BMI) appear to be uncontested risk factors for increased MS risk.

Mendelian randomization as a tool to gain insights into the mosaic causes of autoimmune diseases

Autoimmune diseases (ADs) are a broad range of disorders which are characterized by long-term inflammation and tissue damage arising from an immune response against one's own tissues. It is now widely accepted that the causes of ADs include environmental factors, genetic susceptibility and immune dysregulation. However, the exact etiology of ADs has not been fully elucidated to date. Because observational studies are plagued by confounding factors and reverse causality, no firm conclusions can be drawn about the etiology of ADs. Over the years, Mendelian randomization (MR) analysis has come into focus, offering unique perspectives and insights into the etiology of ADs and promising the discovery of potential therapeutic interventions. In MR analysis, genetic variation (alleles are randomly dispensed during meiosis, usually irrespective of environmental or lifestyle factors) is used instead of modifiable exposure to explore the link between exposure factors and disease or other outcomes. Therefore, MR analysis can provide a valuable method for exploring the causal relationship between different risk factors and ADs when its inherent assumptions and limitations are fully considered. This review summarized the recent findings of MR in major ADs, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), multiple sclerosis (MS), and type 1 diabetes mellitus (T1DM), focused on the effects of different risk factors on ADs risks. In addition, we also discussed the opportunities and challenges of MR methods in ADs research.

Towards a global view of multiple sclerosis genetics

Multiple sclerosis (MS) is a neuroimmunological disorder of the CNS with a strong heritable component. The genetic architecture of MS susceptibility is well understood in populations of European ancestry. However, the extent to which this architecture explains MS susceptibility in populations of non-European ancestry remains unclear. In this Perspective article, we outline the scientific arguments for studying MS genetics in ancestrally diverse populations. We argue that this approach is likely to yield insights that could benefit individuals with MS from all ancestral groups. We explore the logistical and theoretical challenges that have held back this field to date and conclude that, despite these challenges, inclusion of participants of non-European ancestry in MS genetics studies will ultimately be of value to all patients with MS worldwide.

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.

Appraising the causal role of smoking in multiple diseases: A systematic review and meta-analysis of Mendelian randomization studies

BACKGROUND

The causal association between cigarette smoking and several diseases remains equivocal. The purpose of this study was to appraise the causal role of smoking in a wide range of diseases by summarizing the evidence from Mendelian randomization (MR) studies.

METHODS

MR studies on genetic liability to smoking initiation or lifetime smoking (composite of smoking initiation, heaviness, duration, and cessation) in relation to circulatory system, digestive system, nervous system, musculoskeletal system, endocrine, metabolic, and eye diseases, and neoplasms published until February 15, 2022, were identified in PubMed. De novo MR analyses were performed using summary statistics data from genome-wide association studies. Meta-analysis was applied to combine study-specific estimates.

FINDINGS

Meta-analyses of findings of 29 published MR studies and 123 de novo MR analyses of 57 distinct primary outcomes showed that genetic liability to smoking (smoking initiation or lifetime smoking) was associated with increased risk of 13 circulatory system diseases, several digestive system diseases (including diverticular, gallstone, gastroesophageal reflux, and Crohn's disease, acute pancreatitis, and periodontitis), epilepsy, certain musculoskeletal system diseases (including fracture, osteoarthritis, and rheumatoid arthritis), endocrine (polycystic ovary syndrome), metabolic (type 2 diabetes) and eye diseases (including age-related macular degeneration and senile cataract) as well as cancers of the lung, head and neck, esophagus, pancreas, bladder, kidney, cervix, and ovaries, and myeloid leukemia. Smoking liability was associated with decreased risk of Parkinson's disease and prostate cancer.

INTERPRETATION

This study found robust evidence that cigarette smoking causes a wide range of diseases.

FUNDING

This work was supported by research grants from the Swedish Cancer Society (Cancerfonden), the Swedish Heart Lung Foundation (Hjärt-Lungfonden, 20210351), the Swedish Research Council for Health, Working Life and Welfare (Forte, 2018-00123), and the Swedish Research Council (Vetenskapsrådet, 2019-00977). Stephen Burgess is supported by Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (204623/Z/16/Z) and the National Institute for Health Research Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care.

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.

Environmental risk factors in multiple sclerosis: bridging Mendelian randomization and observational studies

Multiple sclerosis (MS) is a complex disease with both genetic variants and environmental factors involved in disease susceptibility. The main environmental risk factors associated with MS in observational studies include obesity, vitamin D deficiency, Epstein-Barr virus infection and smoking. As modifying these environmental and lifestyle factors may enable prevention, it is important to pinpoint causal links between these factors and MS. Leveraging genetics through the Mendelian randomization (MR) paradigm is an elegant way to inform prevention strategies in MS. In this review, we summarize MR studies regarding the impact of environmental factors on MS susceptibility, thereby paying attention to quality criteria which will aid readers in interpreting any MR studies. We draw parallels and differences with observational studies and randomized controlled trials and look forward to the challenges that such work presents going forward.

Body Mass Index, Interleukin-6 Signaling and Multiple Sclerosis: A Mendelian Randomization Study

Objectives

We explored whether genetically predicted increased body mass index (BMI) modulates multiple sclerosis (MS) risk through interleukin-6 (IL-6) signaling.

Methods

We performed a two-sample Mendelian randomization (MR) study using multiple genome-wide association studies (GWAS) datasets for BMI, IL-6 signaling, IL-6 levels and c-reactive protein (CRP) levels as exposures and estimated their effects on risk of MS from GWAS data from the International Multiple Sclerosis Genetics Consortium (IMSGC) in 14,802 MS cases and 26,703 controls.

Results

In univariable MR analyses, genetically predicted increased BMI and IL-6 signaling were associated with higher risk of MS (BMI: odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.15-1.47, p = 3.76 × 10-5; IL-6 signaling: OR = 1.51, 95% CI = 1.11-2.04, p = 0.01). Furthermore, higher BMI was associated with increased IL-6 signaling (β = 0.37, 95% CI = 0.32,0.41, p = 1.58 × 10-65). In multivariable MR analyses, the effect of IL-6 signaling on MS risk remained after adjusting for BMI (OR = 1.36, 95% CI = 1.11-1.68, p = 0.003) and higher BMI remained associated with an increased risk for MS after adjustment for IL-6 signaling (OR = 1.16, 95% CI =1.00-1.34, p = 0.046). The proportion of the effect of BMI on MS mediated by IL-6 signaling corresponded to 43% (95% CI = 25%-54%). In contrast to IL-6 signaling, there was little evidence for an effect of serum IL-6 levels or CRP levels on risk of MS.

Conclusion

In this study, we identified IL-6 signaling as a major mediator of the association between BMI and risk of MS. Further explorations of pathways underlying the association between BMI and MS are required and will, together with our findings, improve the understanding of MS biology and potentially lead to improved opportunities for targeted prevention strategies.

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.

Genetics and functional genomics of multiple sclerosis

Multiple sclerosis (MS) is an inflammatory neurodegenerative disease with genetic predisposition. Over the last decade, genome-wide association studies with increasing sample size led to the discovery of robustly associated genetic variants at an exponential rate. More than 200 genetic loci have been associated with MS susceptibility and almost half of its heritability can be accounted for. However, many challenges and unknowns remain. Definitive studies of disease progression and endophenotypes are yet to be performed, whereas the majority of the identified MS variants are not yet functionally characterized. Despite these shortcomings, the unraveling of MS genetics has opened up a new chapter on our understanding MS causal mechanisms.

Role of environmental factors in multiple sclerosis

INTRODUCTION

Environmental factors play a significant role in the pathogenesis and progression of multiple sclerosis (MS), either acting alone or by interacting with other environmental or genetic factors. This cumulative exposure to external risk factors is highly complex and highly variable between individuals.

AREAS COVERED

We narratively review the current evidence on the role of environment-specific risk factors in MS onset and progression, as well as the effect of gene-environment interactions and the timing of exposure We have reviewed the latest literature, by Ovid Medline, retrieving the most recently published systematic reviews and/or meta-analyses and more recent studies not previously included in meta-analyses or systematic reviews.

EXPERT OPINION

There is some good evidence supporting the impact of some environmental risk factors in increasing the risk of developing MS. Tobacco smoking, low vitamin D levels and/or low sun exposure, Epstein Barr Virus (EBV) seropositivity and a history of infectious mononucleosis may increase the risk of developing MS. Additionally, there is some evidence that gene-smoking, gene-EBV, and smoking-EBV interactions additively affect the risk of MS onset. However, the evidence for a role of other environmental factors in MS progression is limited. Finally, there is some evidence that tobacco smoking, insufficient vitamin D levels and/or sun exposure have impacts on MS phenotypes and various markers of disease activity including relapse, disability progression and MRI findings. Clearly the effect of environmental factors on MS disease course is an area that requires significantly more research.

Little evidence for an effect of smoking on multiple sclerosis risk: A Mendelian Randomization study

The causes of multiple sclerosis (MS) remain unknown. Smoking has been associated with MS in observational studies and is often thought of as an environmental risk factor. We used two-sample Mendelian randomization (MR) to examine whether this association is causal using genetic variants identified in genome-wide association studies (GWASs) as associated with smoking. We assessed both smoking initiation and lifetime smoking behaviour (which captures smoking duration, heaviness, and cessation). There was very limited evidence for a meaningful effect of smoking on MS susceptibility as measured using summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) meta-analysis, including 14,802 cases and 26,703 controls. There was no clear evidence for an effect of smoking on the risk of developing MS (smoking initiation: odds ratio [OR] 1.03, 95% confidence interval [CI] 0.92-1.61; lifetime smoking: OR 1.10, 95% CI 0.87-1.40). These findings suggest that smoking does not have a detrimental consequence on MS susceptibility. Further work is needed to determine the causal effect of smoking on MS progression.