Mendelian Randomization Reveals Potential Drug Targets for Multiple Sclerosis Targeting Ferroptosis.

Multiple sclerosis is a complex autoimmune disease, and several therapies for multiple sclerosis have been developed and widely used. However, existing medications for multiple sclerosis were far from satisfactory due to their failure to suppress relapses and alleviate disease progression. Novel drug targets for multiple sclerosis prevention are still needed.We performed Mendelian randomization to explore potential drug targets for multiple sclerosis using summary statistics from the International Multiple Sclerosis Genetics Consortium (nCase = 47 429, nControl = 68 374) and further replicated in UK Biobank (nCase = 1356, nControl = 395 209) and FinnGen cohorts (nCase = 1326, nControl = 359 815). Genetic instruments for 734 plasma and 154 CSF proteins were obtained from recently published genome-wide association studies. The reverse causality detection using bidirectional Mendelian randomization analysis and Steiger filtering, Bayesian co-localization, and phenotype scanning that searched previously reported genetic variant–trait associations were implemented to consolidate the Mendelian randomization findings further. In addition, the protein–protein interaction network was performed to reveal potential associations among proteins and/or present multiple sclerosis medications.At Bonferroni significance (P < 5.63 × 10−5), Mendelian randomization analysis revealed six protein–multiple sclerosis pairs. In plasma, per standard deviation increase in FCRL3, TYMP and AHSG had a protective effect. Odds ratios for the proteins above were 0.83 (95% CI, 0.79–0.89), 0.59 (95% CI, 0.48–0.71) and 0.88 (95% CI, 0.83–0.94), respectively. In CSF, per 10-fold increase in MMEL1 (OR, 5.03; 95% CI, 3.42–7.41) increased the risk of multiple sclerosis, while SLAMF7 (OR, 0.42; 95% CI, 0.29–0.60) and CD5L (OR, 0.30; 95%CI, 0.18–0.52) decreased the risk. None of the six proteins had reverse causality. Bayesian co-localization suggested that FCRL3 [coloc.abf-posterior probability of hypothesis 4 (PPH4) = 0.889], TYMP (coloc.susie-PPH4 = 0.896), AHSG (coloc.abf-PPH4 = 0.957, coloc.susie-PPH4 = 0.973), MMEL1 (coloc.abf-PPH4 = 0.930) and SLAMF7 (coloc.abf-PPH4 = 0.947) shared the same variant with multiple sclerosis. FCRL3, TYMP and SLAMF7 interacted with target proteins of current multiple sclerosis medications. MMEL1 was replicated in both UK Biobank and FinnGen cohorts.Our integrative analysis suggested that genetically determined levels of circulating FCRL3, TYMP, AHSG, CSF MMEL1 and SLAMF7 had causal effects on multiple sclerosis risk. These findings suggested those five proteins might be promising drug targets for multiple sclerosis and warrant further clinical investigation, especially FCRL3 and SLAMF7.

There has been considerable interest in statins because of their pleiotropic effects beyond their lipid-lowering properties. Many of these pleiotropic effects are predominantly ascribed to Rho small guanosine triphosphatases (Rho GTPases) proteins. We aimed to genetically investigate the role of lipids and statin interventions on multiple sclerosis (MS) risk and severity. We used two-sample Mendelian randomization (MR) to investigate (1) the causal role of genetically mimic both cholesterol-dependent (through low-density lipoprotein cholesterol (LDL-C) and cholesterol biosynthesis pathway) and cholesterol-independent (through Rho GTPases) effects of statins on MS risk and MS severity, (2) the causal link between lipids (high-density lipoprotein cholesterol [HDL-C] and triglycerides [TG]) levels and MS risk and severity, and (3) the reverse causation between lipid fractions and MS risk. We used summary statistics from the Global Lipids Genetics Consortium (GLGC), eQTLGen Consortium, and the International MS Genetics Consortium (IMSGC) for lipids, expression quantitative trait loci, and MS, respectively (GLGC: n = 188,577; eQTLGen: n = 31,684; IMSGC (MS risk): n = 41,505; IMSGC (MS severity): n = 7,069). The results of MR using the inverse-variance weighted method show that genetically predicted RAC2, a member of cholesterol-independent pathway (OR 0.86 [95% CI 0.78-0.95], p-value 3.80E-03), is implicated causally in reducing MS risk. We found no evidence for the causal role of LDL-C and the member of cholesterol biosynthesis pathway on MS risk. The MR results also show that lifelong higher HDL-C (OR 1.14 [95% CI 1.04-1.26], p-value 7.94E-03) increases MS risk but TG was not. Furthermore, we found no evidence for the causal role of lipids and genetically mimicked statins on MS severity. There is no evidence of reverse causation between MS risk and lipids. Evidence from this study suggests that RAC2 is a genetic modifier of MS risk. Because RAC2 has been reported to mediate some of the pleiotropic effects of statins, we suggest that statins may reduce MS risk through a cholesterol-independent pathway (that is, RAC2-related mechanism(s)). MR analyses also support a causal effect of HDL-C on MS risk.

Observational studies suggest an association between immune responses to Epstein-Barr virus nuclear antigen 1 (EBNA1) and multiple sclerosis (MS) risk. Nevertheless, a causal effect cannot be established, as confounding and reverse causation cannot be excluded. We performed a bidirectional two-sample Mendelian randomization (MR) to test whether higher anti-EBNA1 IgG levels causally influence MS risk, or vice versa. Genetic associations for anti-EBNA1 IgG were obtained from 7972 UK Biobank participants, and for MS from 115,803 individuals in the International MS Genetics Consortium. Given that most anti-EBNA1 IgG instruments lie in the pleiotropic major histocompatibility complex, we applied a robust cis-MR framework, sensitivity analyses, and external validation using genetic association from anti-EBNA1 IgG levels obtained from 914 French individuals. A one standard deviation increase in genetically predicted anti-EBNA1 IgG levels was causally associated with a 69% higher MS risk (OR = 1.69 [95% CI: 1.28; 2.23], p < 0.001). Results were consistent across sensitivity analyses and showed no directional pleiotropy. External validation supported these findings. Reverse MR provided no evidence that MS influences anti-EBNA1 IgG levels (p > 0.05). These results support a unidirectional causal effect of elevated anti-EBNA1 IgG levels on MS risk, reinforcing the role of EBV-related immune responses in MS pathogenesis.

Objective Based on the principles of Predictive, Preventive, and Personalized Medicine (PPPM), this study aimed to identify ferroptosis-related genes associated with multiple sclerosis (MS) and to explore the underlying mechanisms through genetic approaches. Materials and Methods Summary statistics of circulating proteins were obtained from the UK Biobank Pharma Proteomics Project (UKB-PPP), ferroptosis-related genes were curated from the FerrDb database, and MS genome-wide association study (GWAS) data were sourced from the International Multiple Sclerosis Genetics Consortium (IMSGC). Two-sample Mendelian randomization (MR) analyses were performed to assess the causal relationships between proteins, ferroptosis-related genes, and MS risk. Mediation MR analysis was conducted to explore the potential mediating role of ferroptosis-related genes. The primary analytical method was inverse variance weighting (IVW), supplemented by MR-Egger and weighted median approaches. Results After Bonferroni correction, one ferroptosis-related gene (Ferritin Mitochondrial, FTMT) and 21 circulating proteins were significantly associated with MS. Eleven protein-gene pairs were identified. Mediation analysis further revealed that FTMT mediated the effects of several proteins on MS risk, including CD8A (17.6%), CFB (9.0%), ENPP6 (9.5%), GZMA (22.9%), KIR2DL2 (17.4%), KIR2DL3 (16.9%), and TNXB (13.2%). Conclusions This study highlights the critical role of FTMT in linking circulating proteins to MS pathogenesis through ferroptosis regulation, providing novel insights into predictive, preventive, and personalized medicine strategies for MS management.

Several observational studies have explored the relationships between multiple sclerosis (MS) and breast cancer; however, whether an association exists remains unknown. We conducted a meta-analysis of observational studies and Mendelian randomization (MR) based on genetic variants to identify the relationship between MS and breast cancer. The observational studies were searched from PubMed, Embase, Web of Science, and Scopus to assess the relationship between MS and breast cancer from inception to 07 Nov 2022. Moreover, we explored the association between genetically pre-disposed MS and breast cancer risk based on an MR study. The summary analysis for MS from two separate databases [International Multiple Sclerosis Genetics Consortium (IMSGC), FinnGen] and the summary analysis for breast cancer from Breast Cancer Association Consortium. Fifteen cohort studies involving 173,565 female MS patients were included in this meta-analysis. The correlation between MS and breast cancer was not statistically significant [relative ratio (RR) = 1.08, 95% confidence interval (CI) = 0.99-1.17]. In the MR analysis, we did not observe causal associations of genetically determined MS with breast cancer and its subtypes from both the IMSGC and FinnGen datasets. The meta-analysis of observational and MR based on genetic variants does not support the correlation between MS and breast cancer.

BackgroundObservational studies have reported an association between obesity, as measured by elevated body mass index (BMI), in early adulthood and risk of multiple sclerosis (MS). However, bias potentially introduced by confounding and reverse causation may have influenced these findings. Therefore, we elected to perform Mendelian randomization (MR) analyses to evaluate whether genetically increased BMI is associated with an increased risk of MS.Methods and FindingsEmploying a two-sample MR approach, we used summary statistics from the Genetic Investigation of Anthropometric Traits (GIANT) consortium and the International MS Genetics Consortium (IMSGC), the largest genome-wide association studies for BMI and MS, respectively (GIANT: n = 322,105; IMSGC: n = 14,498 cases and 24,091 controls). Seventy single nucleotide polymorphisms (SNPs) were genome-wide significant (p < 5 x 10−8) for BMI in GIANT (n = 322,105) and were investigated for their association with MS risk in the IMSGC. The effect of each SNP on MS was weighted by its effect on BMI, and estimates were pooled to provide a summary measure for the effect of increased BMI upon risk of MS. Our results suggest that increased BMI influences MS susceptibility, where a 1 standard deviation increase in genetically determined BMI (kg/m2) increased odds of MS by 41% (odds ratio [OR]: 1.41, 95% CI 1.20–1.66, p = 2.7 x 10−5, I2 = 0%, 95% CI 0–29). Sensitivity analyses, including MR-Egger regression, and the weighted median approach provided no evidence of pleiotropic effects. The main study limitations are that, while these sensitivity analyses reduce the possibility that pleiotropy influenced our results, residual pleiotropy is difficult to exclude entirely.ConclusionGenetically elevated BMI is associated with risk of MS, providing evidence for a causal role for obesity in MS etiology. While obesity has been associated with many late-life outcomes, these findings suggest an important consequence of childhood and/or early adulthood obesity.

ObjectiveTo investigate the causal relationships between inflammatory proteins, iron metabolism, blood/CSF metabolites, and multiple sclerosis (MS) risk using genetic evidence.MethodsWe performed a two-sample, two-step Mendelian randomization (MR) analysis using European-ancestry genome-wide association study data. The exposures comprised 91 inflammatory proteins, while potential mediators included 1091 blood metabolites, 309 metabolite ratios, 233 circulating metabolic traits, and 338 cerebrospinal fluid metabolites. For the outcome, we assessed MS risk using two independent datasets: International Multiple Sclerosis Genetics Consortium (IMSGC) and UK Biobank. Our primary analysis utilized inverse-variance weighted regression. To ensure robust results, we conducted comprehensive sensitivity analyses including MR-Egger, weighted median, MR-PRESSO, and Bayesian Weighted MR approaches to evaluate potential pleiotropy and strengthen causal inference.ResultsWe observed a statistically significant but modest elevation in MS risk associated with interleukin-7 (IL-7; OR = 1.40, 95% CI: 1.07–1.83, p = 0.016) in the IMSGC cohort, with a weaker effect in the UK Biobank (OR = 1.001, 95% CI: 1.000–1.002, p = 0.047). The IL-7 was causally linked to six blood metabolic traits (taurocholenate sulfate, anthranilate, taurodeoxycholate, albumin, sphingomyelin (d18:1/24:1, d18:2/24:0), leucine-to-phosphate ratio), all influencing MS risk. No significant interactions between iron metabolism and inflammatory proteins were found.ConclusionsThis MR study establishes IL-7 as a potential causal risk factor for MS, partially mediated by blood metabolites. The findings prioritize IL-7 and associated metabolic pathways (bile acids/kynurenine) for therapeutic targeting.

Observational studies associate Epstein-Barr virus (EBV) with multiple sclerosis (MS), but causality across autoimmune neuroinflammatory diseases (ANDs) remains uncertain. This study aimed to assess the causal effects of 5 EBV antibodies on ANDs using Mendelian randomization (MR). Bidirectional, two-sample MR was performed using generalized summary-data-based MR (GSMR). Genetic instruments for EBV antibodies (anti-EBNA-1, VCA p18, ZEBRA, EA-D, IgG) were sourced from UK Biobank (UKB). Outcome data for ANDs (multiple sclerosis [MS], neuromyelitis optica [NMO], myasthenia gravis [MG], Guillain-Barré syndrome [GBS], and chronic inflammatory demyelinating polyneuropathy [CIDP]) were from FinnGen (discovery), UKB, and International Multiple Sclerosis Genetics Consortium (replication). Applying an evidence-tiered interpretation, we found a high-confidence, protective causal effect of increased ZEBRA antibody levels on MS risk (odds ratio [OR] = 0.705, P = 2.967 × 10-6), which was robust to multiple testing nominally supported in an independent cohort (IMSGC). In contrast, the association between EBNA-1 antibodies and increased MS risk (OR = 1.284, P = 2.450 × 10-4) was graded as suggestive as it showed nominal support only in one of 2 validation cohorts (UKB) and was substantially attenuated after excluding HLA-region single nucleotide polymorphisms, indicating shared genetic architecture rather than direct causation. Steiger directionality tests confirmed the primary causal direction was from antibodies to MS. Results for NMO, MG, GBS, and CIDP were inconclusive due to limited statistical power, and thus no definitive conclusions can be drawn regarding EBV antibodies and these diseases. This study provides high-confidence genetic evidence for a protective role of ZEBRA antibodies in MS, which was robust to multiple testing and nominally supported in an independent cohort [International MS Genetics Consortium (IMSGC)], and suggestive evidence for an HLA-mediated link between EBV-encoded nuclear antigen-1 (EBNA-1) and MS which showed nominal support only in one of 2 validation cohorts. The role of EBV in other ANDs warrants investigation in larger, well-powered cohorts.

Oxidative stress (OS) is linked to the development of multiple sclerosis (MS), but the causal relationship in terms of genetic pathophysiology remains ambiguous. We employed Mendelian randomization (MR) and colocalization analysis to explore the relationship between OS genes and MS, utilizing an integrative multi-omics approach. We obtained data from a genome-wide association study (GWAS) of MS from the International Multiple Sclerosis Genetics Consortium (Discovery phase) and the FinnGen study (Replication phase). Mendelian randomization analyses were conducted using summary data to evaluate the association between molecular features of OS-related genes and MS. Additional colocalization analyses were undertaken to ascertain whether the identified signal pairs shared causal genetic variants. Integration of multi-omics data, including mQTL-eQTL and eQTL-pQTL, revealed that the STAT3 gene is associated with MS, supported by Level 1 evidence. The CR1 gene shows an association with MS risk, evidenced by Level 3 support. Methylation at cg24718015 and cg17833746 in the STAT3 gene correlates with reduced expression of STAT3. At the protein level, high circulating levels of STAT3 are inversely associated with MS risk (OR: 0.43, 95% CI, 0.33-0.54). Elevated levels of TNFRSF1A are also linked with a decreased risk of MS (OR: 0.21; 95% CI, 0.12-0.37), while higher levels of CR1 are positively associated with an increased risk of MS (OR: 1.17; 95% CI, 1.08-1.27). This study identifies specific OS genes that are associated with MS and enhances our understanding of its pathogenesis.

BackgroundObservational studies have demonstrated an association between decreased vitamin D level and risk of multiple sclerosis (MS); however, it remains unclear whether this relationship is causal. We undertook a Mendelian randomization (MR) study to evaluate whether genetically lowered vitamin D level influences the risk of MS.Methods and FindingsWe identified single nucleotide polymorphisms (SNPs) associated with 25-hydroxyvitamin D (25OHD) level from SUNLIGHT, the largest (n = 33,996) genome-wide association study to date for vitamin D. Four SNPs were genome-wide significant for 25OHD level (p-values ranging from 6 × 10−10 to 2 × 10−109), and all four SNPs lay in, or near, genes strongly implicated in separate mechanisms influencing 25OHD. We then ascertained their effect on 25OHD level in 2,347 participants from a population-based cohort, the Canadian Multicentre Osteoporosis Study, and tested the extent to which the 25OHD-decreasing alleles explained variation in 25OHD level. We found that the count of 25OHD-decreasing alleles across these four SNPs was strongly associated with lower 25OHD level (n = 2,347, F-test statistic = 49.7, p = 2.4 × 10−12). Next, we conducted an MR study to describe the effect of genetically lowered 25OHD on the odds of MS in the International Multiple Sclerosis Genetics Consortium study, the largest genetic association study to date for MS (including up to 14,498 cases and 24,091 healthy controls). Alleles were weighted by their relative effect on 25OHD level, and sensitivity analyses were performed to test MR assumptions. MR analyses found that each genetically determined one-standard-deviation decrease in log-transformed 25OHD level conferred a 2.0-fold increase in the odds of MS (95% CI: 1.7–2.5; p = 7.7 × 10−12; I2 = 63%, 95% CI: 0%–88%). This result persisted in sensitivity analyses excluding SNPs possibly influenced by population stratification or pleiotropy (odds ratio [OR] = 1.7, 95% CI: 1.3–2.2; p = 2.3 × 10−5; I2 = 47%, 95% CI: 0%–85%) and including only SNPs involved in 25OHD synthesis or metabolism (ORsynthesis = 2.1, 95% CI: 1.6–2.6, p = 1 × 10−9; ORmetabolism = 1.9, 95% CI: 1.3–2.7, p = 0.002). While these sensitivity analyses decreased the possibility that pleiotropy may have biased the results, residual pleiotropy is difficult to exclude entirely.ConclusionsA genetically lowered 25OHD level is strongly associated with increased susceptibility to MS. Whether vitamin D sufficiency can delay, or prevent, MS onset merits further investigation in long-term randomized controlled trials.

A metabolome-wide Mendelian randomization study prioritizes potential causal circulating metabolites for multiple sclerosis

Coffee consumption is not associated with risk of multiple sclerosis: A Mendelian randomization study

BackgroundThe DNA methylation-based epigenetic clocks are increasingly recognized for their precision in predicting aging and its health implications. Although prior research has identified connections between accelerated epigenetic aging and multiple sclerosis, the chronological and causative aspects of these relationships are yet to be elucidated. Our research seeks to clarify these potential causal links through a bidirectional Mendelian randomization study.MethodsThis analysis employed statistics approaches from genome-wide association studies related to various epigenetic clocks (GrimAge, HannumAge, PhenoAge, and HorvathAge) and multiple sclerosis, utilizing robust instrumental variables from the Edinburgh DataShare (n = 34,710) and the International Multiple Sclerosis Genetics Consortium (including 24,091 controls and 14,498 cases). We applied the inverse-variance weighted approach as our main method for Mendelian randomization, with additional sensitivity analyses to explore underlying heterogeneity and pleiotropy.ResultsUsing summary-based Mendelian randomization, we found that HannumAge was associated with multiple sclerosis (OR = 1.071, 95%CI:1.006–1.140, p = 0.033, by inverse-variance weighted). The results suggest that an increase in epigenetic age acceleration of HannumAge promotes the risk of multiple sclerosis. In reverse Mendelian randomization analysis, no evidence of a clear causal association of multiple sclerosis on epigenetic age acceleration was identified.ConclusionsOur Mendelian randomization analysis revealed that epigenetic age acceleration of HannumAge was causally associated with multiple sclerosis, and provided novel insights for further mechanistic and clinical studies of epigenetic age acceleration-mediated multiple sclerosis.

Results from observational studies indicate an association between circulating levels of mammalian target of rapamycin (mTOR)-dependent circulating proteins and the risk of multiple sclerosis (MS). However, a causal association has not been fully elucidated. Mendelian randomization (MR) is used to overcome limitations inherent to observational studies, assess the causal association, and minimize bias due to confounding and reverse causation. To explore the causal association between seven mTOR-dependent proteins (AKT, RP-S6K, eIF4E-BP, eIF4A, eIF4E, eIF4G, and PKC-α) and MS, we obtained summary statistics from the genome-wide association study (GWAS) meta-analysis of the International Multiple Sclerosis Genetics Consortium (47,429 patients and 68,374 controls) and the INTERVAL study (genetic associations with 2994 plasma proteins from 3301 healthy individuals). MR analyses were conducted using inverse variance weighted, weighted median estimator, and MR-Egger regression methods/models. Sensitivity analyses were performed to ensure the reliability of the findings. Single nucleotide polymorphisms (SNPs) that are independent (r2 < 0.01) and strongly associated to minerals (p < 1e-5) were selected as instrumental variables. The results of the MR analyses revealed that among the seven mTOR-dependent proteins selected for study, the circulating level of PKC-α (odds ratio [OR] 0.90, 95% confidence interval [CI] 0.82-0.98; P = 0.017) and RP-S6K (OR 1.12, 95% CI 1.00-1.25; P = 0.045) were associated with MS risk and that there was no sign of pleiotropy or heterogeneity. PKC-α was negatively related to MS, while RP-S6K was positively related to MS. No significant causation was found between the other proteins studied (AKT, eIF4E-BP, eIF4A, eIF4E, eIF4G) and MS. Molecules in the mTOR signaling pathway may bidirectionally regulate the occurrence and development of MS. PKC-α is a protective factor, while RP-S6K is a risk factor. Further explorations of pathways underlying the association between mTOR-dependent proteins and MS are required. PKC-α and RP-S6K might be used as future therapeutic targets for screening high-risk individuals and potentially improving opportunities for targeted prevention strategies.

BackgroundPrevious research have implicated critical roles of systemic inflammation in the development of Multiple Sclerosis (MS). But the causal relationship between interleukins (ILs) and MS has not been fully elucidated.ObjectiveIn this study, we applied Mendelian randomization (MR) approaches to address the causal associations between genetically determined circulating levels of ILs and the risk of MS.MethodsGenetic instruments for circulating IL-1 receptor antagonist (IL-1Ra), IL-2 receptor α subunit (IL-2Rα), IL-6, IL-16, IL-17, and IL-18 were obtained from recently published genome-wide association studies (GWAS). Summary-level data for MS were obtained from the International Multiple Sclerosis Genetics Consortium. MR analyses were performed using the R software (version 3.6.1, The R Foundation) and the TwoSampleMR package.ResultsGenetic predisposition to higher circulating levels of IL-2Rα were significantly associated with MS risk. The odds ratio (OR) was 1.22 (95% confidence interval [CI], 1.12–1.32; p < 0.001) per one standard deviation increase in circulating IL-2Rα levels. There was a suggestive association of circulating IL-1Ra with MS risk (OR, 0.94; 95% CI, 0.88–0.99; p = 0.027). The other ILs were not associated with the outcome.ConclusionOur results indicated that circulating IL-2Rα was causally associated with risk of MS.