Liu G, Zhang F, Jiang Y, Hu Y, Gong Z, Liu S, et al. Integrating genome-wide association studies and gene expression data highlights dysregulated multiple sclerosis risk pathways. Mult Scler. 2017;23:205–12.

Article  CAS  Google Scholar 

Munger KL, Zhang SM, O’Reilly E, Hernan MA, Olek MJ, Willett WC, et al. Vitamin D intake and incidence of multiple sclerosis. Neurology 2004;62:60–65.

Article  CAS  Google Scholar 

Munger KL, Hongell K, Aivo J, Soilu-Hanninen M, Surcel HM, Ascherio A. 25-Hydroxyvitamin D deficiency and risk of MS among women in the Finnish Maternity Cohort. Neurology 2017;89:1578–83.

Article  CAS  Google Scholar 

Salzer J, Hallmans G, Nystrom M, Stenlund H, Wadell G, Sundstrom P. Vitamin D as a protective factor in multiple sclerosis. Neurology 2012;79:2140–5.

Article  CAS  Google Scholar 

Munger KL, Levin LI, Hollis BW, Howard NS, Ascherio A. Serum 25-hydroxyvitamin D levels and risk of multiple sclerosis. JAMA 2006;296:2832–8.

Article  CAS  Google Scholar 

Harroud A, Richards JB. Mendelian randomization in multiple sclerosis: A causal role for vitamin D and obesity? Mult Scler. 2018;24:80–85.

Article  CAS  Google Scholar 

Mokry LE, Ross S, Ahmad OS, Forgetta V, Smith GD, Goltzman D, et al. Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study. PLoS Med. 2015;12:e1001866.

Article  Google Scholar 

Rhead B, Baarnhielm M, Gianfrancesco M, Mok A, Shao X, Quach H, et al. Mendelian randomization shows a causal effect of low vitamin D on multiple sclerosis risk. Neurol Genet. 2016;2:e97.

Article  Google Scholar 

Gianfrancesco MA, Stridh P, Rhead B, Shao X, Xu E, Graves JS, et al. Evidence for a causal relationship between low vitamin D, high BMI, and pediatric-onset MS. Neurology 2017;88:1623–9.

Article  CAS  Google Scholar 

Jacobs BM, Noyce AJ, Giovannoni G, Dobson R. BMI and low vitamin D are causal factors for multiple sclerosis: A Mendelian Randomization study. Neurol Neuroimmunol Neuroinflamm. 2020;7:e662.

Article  Google Scholar 

Harroud A, Manousaki D, Butler-Laporte G, Mitchell RE, Davey Smith G, Richards JB, et al. The relative contributions of obesity, vitamin D, leptin, and adiponectin to multiple sclerosis risk: A Mendelian randomization mediation analysis. Mult Scler. 2021;27:1994–2000.

Article  CAS  Google Scholar 

Bouillon R, Manousaki D, Rosen C, Trajanoska K, Rivadeneira F, Richards JB. The health effects of vitamin D supplementation: Evidence from human studies. Nat Rev Endocrinol. 2022;18:96–110.

Article  CAS  Google Scholar 

Wang R. Mendelian randomization study updates the effect of 25-hydroxyvitamin D levels on the risk of multiple sclerosis. J Transl Med. 2022;20:3.

Article  Google Scholar 

Vandebergh M, Dubois B, Goris A. Effects of Vitamin D and body mass index on disease risk and relapse hazard in multiple sclerosis: A mendelian randomization study. Neurol Neuroimmunol Neuroinflamm. 2022;9:e1165.

Article  Google Scholar 

Zheng JS, Imamura F, Sharp SJ, van der Schouw YT, Sluijs I, Gundersen TE, et al. Association of plasma vitamin D metabolites with incident type 2 diabetes: EPIC-InterAct case-cohort study. J Clin Endocrinol Metab. 2019;104:1293–303.

Article  Google Scholar 

Steingrimsdottir L, Gunnarsson O, Indridason OS, Franzson L, Sigurdsson G. Relationship between serum parathyroid hormone levels, vitamin D sufficiency, and calcium intake. JAMA. 2005;294:2336–41.

Article  CAS  Google Scholar 

Arnold A, Dennison E, Kovacs CS, Mannstadt M, Rizzoli R, Brandi ML, et al. Hormonal regulation of biomineralization. Nat Rev Endocrinol. 2021;17:261–75.

Article  CAS  Google Scholar 

Kern J, Kern S, Blennow K, Zetterberg H, Waern M, Guo X, et al. Calcium supplementation and risk of dementia in women with cerebrovascular disease. Neurology 2016;87:1674–80.

Article  CAS  Google Scholar 

Zhang FF, Barr SI, McNulty H, Li D, Blumberg JB. Health effects of vitamin and mineral supplements. BMJ. 2020;369:m2511.

Article  Google Scholar 

Harvey NC, D’Angelo S, Paccou J, Curtis EM, Edwards M, Raisi-Estabragh Z, et al. Calcium and Vitamin D supplementation are not associated with risk of incident ischemic cardiac events or death: Findings from the UK biobank cohort. J Bone Min Res. 2018;33:803–11.

Article  CAS  Google Scholar 

Jian Z, Huang Y, He Y, Jin X, Li H, Li S, et al. Genetically predicted lifelong circulating 25(OH)D levels are associated with serum calcium levels and kidney stone risk. J Clin Endocrinol Metab. 2022;107:e1159–e1166.

Article  Google Scholar 

Revez JA, Lin T, Qiao Z, Xue A, Holtz Y, Zhu Z, et al. Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration. Nat Commun. 2020;11:1647.

Article  Google Scholar 

Zheng JS, Luan J, Sofianopoulou E, Sharp SJ, Day FR, Imamura F, et al. The association between circulating 25-hydroxyvitamin D metabolites and type 2 diabetes in European populations: A meta-analysis and Mendelian randomisation analysis. PLoS Med. 2020;17:e1003394.

Article  CAS  Google Scholar 

Young WJ, Warren HR, Mook-Kanamori DO, Ramirez J, van Duijvenboden S, Orini M, et al. Genetically determined serum calcium levels and markers of ventricular repolarization: a mendelian randomization study in the UK Biobank. Circ Genom Precis Med. 2021;14:e003231.

Article  CAS  Google Scholar 

Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility. Science 2019; 365(6460):eaav7188.

Liu G, Zhao Y, Jin S, Hu Y, Wang T, Tian R, et al. Circulating vitamin E levels and Alzheimer’s disease: A Mendelian randomization study. Neurobiol Aging. 2018;72:189 e181–189 e189.

Article  Google Scholar 

Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32:377–89.

Article  Google Scholar 

Bowden J, Davey, Smith G, Haycock PC, Burgess S. Consistent estimation in mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40:304–14.

Article  Google Scholar 

Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50:693–8.

Article  CAS  Google Scholar 

Burgess S, Foley CN, Allara E, Staley JR, Howson JMM. A robust and efficient method for Mendelian randomization with hundreds of genetic variants. Nat Commun. 2020;11:376.

Article  CAS  Google Scholar 

Bowden J, Holmes MV. Meta-analysis and Mendelian randomization: A review. Res Synth Methods. 2019;10:486–96.

Article  Google Scholar 

Yavorska OO, Burgess S. MendelianRandomization: An R package for performing Mendelian randomization analyses using summarized data. Int J Epidemiol. 2017;46:1734–9.

Article  Google Scholar 

Shim H, Chasman DI, Smith JD, Mora S, Ridker PM, Nickerson DA, et al. A multivariate genome-wide association analysis of 10 LDL subfractions, and their response to statin treatment, in 1868 Caucasians. PLoS One. 2015;10:e0120758.

Article  Google Scholar 

Pierce BL, Ahsan H, Vanderweele TJ. Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol. 2011;40:740–52.

Article  Google Scholar 

Palmer TM, Lawlor DA, Harbord RM, Sheehan NA, Tobias JH, Timpson NJ, et al. Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res. 2012;21:223–42.

Article  Google Scholar 

Burgess S, Thompson SG. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011;40:755–64.

Article  Google Scholar 

Brion MJ, Shakhbazov K, Visscher PM. Calculating statistical power in Mendelian randomization studies. Int J Epidemiol. 2013;42:1497–501.

Article  Google Scholar 

Ward LD, Kellis M. HaploReg: A resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 2012;40:D930–934.

Article  CAS  Google Scholar 

Maretzke F, Bechthold A, Egert S, Ernst JB, Melo van Lent D, Pilz S, et al. Role of Vitamin D in preventing and treating selected extraskeletal diseases-an umbrella review. Nutrients. 2020;12:969.

Article  CAS  Google Scholar 

Boltjes R, Knippenberg S, Gerlach O, Hupperts R, Damoiseaux J. Vitamin D supplementation in multiple sclerosis: An expert opinion based on the review of current evidence. Expert Rev Neurother. 2021;21:715–25.

Article  CAS  Google Scholar 

Feige J, Moser T, Bieler L, Schwenker K, Hauer L, Sellner J. Vitamin D supplementation in multiple sclerosis: A critical analysis of potentials and threats. Nutrients. 2020;12:783.

Article  CAS  Google Scholar 

Fatima M, Lamis A, Siddiqui SW, Ashok T, Patni N, Fadiora OE. Therapeutic role of Vitamin D in multiple sclerosis: An essentially contested concept. Cureus 2022;14:e26186.

Google Scholar 

Dorr J, Backer-Koduah P, Wernecke KD, Becker E, Hoffmann F, Faiss J, et al. High-dose vitamin D supplementation in multiple sclerosis - results from the randomized EVIDIMS (efficacy of vitamin D supplementation in multiple sclerosis) trial. Mult Scler J Exp Transl Clin. 2020;6:2055217320903474.

Google Scholar 

Backer-Koduah P, Bellmann-Strobl J, Scheel M, Wuerfel J, Wernecke KD, Dorr J, et al. Vitamin D and disease severity in multiple sclerosis-baseline data from the randomized controlled trial (EVIDIMS). Front Neurol. 2020;11:129.

Article  Google Scholar 

McLaughlin L, Clarke L, Khalilidehkordi E, Butzkueven H, Taylor B, Broadley SA. Vitamin D for the treatment of multiple sclerosis: A meta-analysis. J Neurol. 2018;265:2893–905.

Article  CAS  Google Scholar 

Galoppin M, Kari S, Soldati S, Pal A, Rival M, Engelhardt B, et al. Full spectrum of vitamin D immunomodulation in multiple sclerosis: Mechanisms and therapeutic implications. Brain Commun. 2022;4:fcac171.

Article  CAS  Google Scholar 

Mao D, Yuen LY, Ho CS, Wang CC, Tam CH, Chan MH, et al. Maternal and Neonatal 3-epi-25-hydroxyvitamin D concentration and factors influencing their concentrations. J Endocr Soc. 2022;6:bvab170.

Article