Skip to main content
SpringerLink
Log in

Relationships between accelerometer-measured and multiple sclerosis: a 2-sample Mendelian randomization study

  • Original Article
  • Published:
Neurological Sciences Aims and scope Submit manuscript

Abstract

Background

Observational studies suggest that physical activity (PA) can independently modify the risk of developing multiple sclerosis (MS).

Objective

To investigate the causal effect of PA on MS by Mendelian randomization (MR) approaches.

Methods

Through a genome-wide association study including 91,105 participants from UK Biobank, we obtained 5 single-nucleotide polymorphisms (SNPs) associated with accelerometer-measured PA (P < 5 × 10−8). Summary-level data for MS were obtained from a meta-analysis, incorporating 14,802 subjects with MS and 26,703 healthy controls of European ancestry. MR analyses were performed using the inverse-variance-weighted method, weighted median estimator, and MR-PRESSO method. Additional analyses were further performed using MR-Egger intercept and Cochran’s Q statistic to verify the robustness of our findings.

Results

We failed to detect a causal effect of PA on MS (OR, 0.60; 95% confidence interval [CI], 0.30–1.20; P = 0.15) per in the random-effects IVW analysis. Additional MR methods yielded consistent results. MR-Egger regression suggested no evidence of horizontal pleiotropy (Intercept = 0.14, P = 0.21) and there seemed no substantial heterogeneity (I2 = 29.8%, P = 0.22) among individual SNPs.

Conclusion

Our findings suggest that enhancing PA might not modify the risk of developing MS independent of established risk factors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Goldenberg MM (2012) Multiple sclerosis review. P T 37(3):175–184

    PubMed  PubMed Central  Google Scholar 

  2. Reich DS, Lucchinetti CF, Calabresi PA (2018) Multiple sclerosis. N Engl J Med 378(2):169–180

    Article  CAS  Google Scholar 

  3. Lo J, Chan L, Flynn S (2020) A systematic review of the incidence, prevalence, costs, and activity/work limitations of amputation, osteoarthritis, rheumatoid arthritis, back pain, multiple sclerosis, spinal cord injury, stroke, and traumatic brain injury in the United States: A 2019 Update. Arch Phys Med Rehabil. https://doi.org/10.1016/j.apmr.2020.04.001

  4. Noonan CW, Williamson DM, Henry JP, Indian R, Lynch SG, Neuberger JS, Schiffer R, Trottier J, Wagner L, Marrie RA (2010) The prevalence of multiple sclerosis in 3 US communities. Prev Chronic Dis 7(1):A12

    PubMed  Google Scholar 

  5. Nocon M, Hiemann T, Müller-Riemenschneider F, Thalau F, Roll S, Willich SN (2008) Association of physical activity with all-cause and cardiovascular mortality: a systematic review and meta-analysis. Eur J Cardiovasc Prev Rehabil 15(3):239–246

    Article  Google Scholar 

  6. Warburton DE, Nicol CW, Bredin SS (2006) Health benefits of physical activity: the evidence. CMAJ. 174(6):801–809

    Article  Google Scholar 

  7. Sivaramakrishnan A, Madhavan S (2019) Recumbent stepping aerobic exercise in amyotrophic lateral sclerosis: a pilot study. Neurol Sci 40:971–978

    Article  Google Scholar 

  8. Castelli L, De Giglio L, Haggiag S, Traini A, De Luca F, Ruggieri S, Prosperini L (2020) Premorbid functional reserve modulates the effect of rehabilitation in multiple sclerosis. Neurol Sci 41:1251–1257

    Article  Google Scholar 

  9. Grubić KT, Babić M, Kauzlarić-Živković T, Gulić T (2020) Combined upper limb and breathing exercise programme for pain management in ambulatory and non-ambulatory multiple sclerosis individuals: part II analyses from feasibility study. Neurol Sci 41:65–74

    Article  Google Scholar 

  10. Wesnes K, Myhr KM, Riise T, Cortese M, Pugliatti M, Boström I, Landtblom AM, Wolfson C, Bjørnevik K (2018) Physical activity is associated with a decreased multiple sclerosis risk: the EnvIMS study. Mult Scler 24:150–157

    Article  Google Scholar 

  11. Dorans KS, Massa J, Chitnis T, Ascherio A, Munger KL (2016) Physical activity and the incidence of multiple sclerosis. Neurology 87:1770–1776

    Article  Google Scholar 

  12. Smith GD, Ebrahim S (2003) ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease. Int J Epidemiol 32:1–22

    Article  Google Scholar 

  13. Zhang H, Wang T, Han Z, Liu G (2020) Mendelian randomization study to evaluate the effects of interleukin-6 signaling on four neurodegenerative diseases. Neurol Sci 41:2875–2882

    Article  Google Scholar 

  14. Smith GD, Lawlor DA, Harbord R, Timpson N, Day I, Ebrahim S (2007) Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology. PLoS Med 4(12):e352

    Article  Google Scholar 

  15. Davies NM, Holmes MV, Davey SG (2018) Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 362:k601

    Article  Google Scholar 

  16. Doherty A, Smith-Byrne K, Ferreira T, Holmes MV, Holmes C, Pulit SL, Lindgren CM (2018) GWAS identifies 14 loci for device-measured physical activity and sleep duration. Nat Commun 9:5257

    Article  Google Scholar 

  17. Klimentidis YC, Raichlen DA, Bea J, Garcia DO, Wineinger NE, Mandarino LJ, Alexander GE, Chen Z, Going SB (2018) Genome-wide association study of habitual physical activity in over 377,000 UK Biobank participants identifies multiple variants including CADM2 and APOE. Int J Obes 42:1161–1176

    Article  CAS  Google Scholar 

  18. International Multiple Sclerosis Genetics Consortium (2019) Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility. Science 365(6460):eaav7188

  19. Zhong VW, Kuang A, Danning RD, Kraft P, van Dam RM, Chasman DI, Cornelis MC (2019) A genome-wide association study of bitter and sweet beverage consumption. Hum Mol Genet 28:2449–2457

    Article  CAS  Google Scholar 

  20. Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R, Tan VY, Yarmolinsky J, Shihab HA, Timpson NJ, Evans DM, Relton C, Martin RM, Davey Smith G, Gaunt TR, Haycock PC (2018) The MR-base platform supports systematic causal inference across the human phenome. Elife 7

  21. Verbanck M, Chen CY, Neale B, Do R (2018) Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet 50:693–698

    Article  CAS  Google Scholar 

  22. Brion MJ, Shakhbazov K, Visscher PM (2013) Calculating statistical power in Mendelian randomization studies. Int J Epidemiol 42:1497–1501

    Article  Google Scholar 

  23. Mokry LE, Ross S, Timpson NJ, Sawcer S, Davey SG, Richards JB (2016) Obesity and multiple sclerosis: a Mendelian randomization study. PLoS Med 13:e1002053

    Article  Google Scholar 

  24. Mokry LE, Ross S, Ahmad OS, Forgetta V, Smith GD, Goltzman D, Leong A, Greenwood CM, Thanassoulis G, Richards JB (2015) Vitamin D and risk of multiple sclerosis: a Mendelian randomization study. PLoS Med 12:e1001866

    Article  Google Scholar 

  25. Gunnarsson M, Udumyan R, Bahmanyar S, Nilsagård Y, Montgomery S (2015) Characteristics in childhood and adolescence associated with future multiple sclerosis risk in men: cohort study. Eur J Neurol 22:1131–1137

    Article  CAS  Google Scholar 

  26. Ghadirian P, Dadgostar B, Azani R, Maisonneuve P (2001) A case-control study of the association between socio-demographic, lifestyle and medical history factors and multiple sclerosis. Can J Public Health 92:281–285

    Article  CAS  Google Scholar 

  27. Warren SA, Warren KG, Greenhill S, Paterson M (1982) How multiple sclerosis is related to animal illness, stress and diabetes. Can Med Assoc J 126:377–382 385

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Sharif K, Watad A, Bragazzi NL, Lichtbroun M, Amital H, Shoenfeld Y (2018) Physical activity and autoimmune diseases: get moving and manage the disease. Autoimmun Rev 17:53–72

    Article  CAS  Google Scholar 

Download references

Author information

Author notes

  1. Hui Lu and Peng-fei Wu contributed equally to this work.

Authors and Affiliations

  1. Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China

    Hui Lu

  2. Hunan Provincial Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China

    Peng-Fei Wu

  3. Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA

    Peng-Fei Wu & Wan Zhang

  4. Department of Ultrasonography, Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, China

    Rui-Zhuo Li

  5. Biology Department, College of Arts and Sciences, Boston University, Boston, MA, USA

    Wan Zhang

  6. Department of Neurology, Affiliated Hospital of Nantong University, Nantong, China

    Guo-Xiang Huang

Authors
  1. Hui Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peng-Fei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rui-Zhuo Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Guo-Xiang Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hui Lu.

Ethics declarations

Conflict of interest

The authors declare that they have no potential conflicts of interest.

Ethical approval

This MR study is based on publicly shared databases and no additional participant ethical consent is required.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

ESM 1

(DOCX 13 kb)

ESM 2

(DOCX 14 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, H., Wu, PF., Li, RZ. et al. Relationships between accelerometer-measured and multiple sclerosis: a 2-sample Mendelian randomization study. Neurol Sci 42, 3337–3341 (2021). https://doi.org/10.1007/s10072-020-04953-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10072-020-04953-x

Keywords

Search

Navigation