Childhood obesity and multiple sclerosis: a Mendelian randomization study

Adil Harroud*, Ruth E Mitchell, Tom G Richardson, John A Morris, Vincenzo Forgetta, George Davey Smith, Sergio E Baranzini, J Brent Richards*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Abstract

Background:
Higher childhood body mass index (BMI) has been associated with an increased risk of multiple sclerosis (MS).

Objective:
To evaluate whether childhood BMI has a causal influence on MS, and whether this putative effect is independent from early adult obesity and pubertal timing.

Methods:
We performed Mendelian randomization (MR) using summary genetic data on 14,802 MS cases and 26,703 controls. Large-scale genome-wide association studies provided estimates for BMI in childhood (n = 47,541) and adulthood (n = 322,154). In multivariable MR, we examined the direct effects of each timepoint and further adjusted for age at puberty. Findings were replicated using the UK Biobank (n = 453,169).

Results:
Higher genetically predicted childhood BMI was associated with increased odds of MS (odds ratio (OR) = 1.26/SD BMI increase, 95% confidence interval (CI): 1.07–1.50). However, there was little evidence of a direct effect after adjusting for adult BMI (OR = 1.03, 95% CI: 0.70–1.53). Conversely, the effect of adult BMI persisted independent of childhood BMI (OR = 1.43; 95% CI: 1.01–2.03). The addition of age at puberty did not alter the findings. UK Biobank analyses showed consistent results. Sensitivity analyses provided no evidence of pleiotropy.

Conclusion:
Genetic evidence supports an association between childhood obesity and MS susceptibility, mediated by persistence of obesity into early adulthood but independent of pubertal timing.
Original languageEnglish
Number of pages9
JournalMultiple Sclerosis Journal
Early online date22 Mar 2021
DOIs
Publication statusE-pub ahead of print - 22 Mar 2021

Keywords

  • Multiple sclerosisv
  • obesity
  • Mendelian randomization
  • genetic epidemiology

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