Multiple Sclerosis Journal - October 2017 - 1461

681196
research-article2016

MSJ0010.1177/1352458516681196Multiple Sclerosis JournalJ Devorak, LE Mokry

MULTIPLE
SCLEROSIS
JOURNAL

MSJ

Original Research Paper

Large differences in adiponectin levels
have no clear effect on multiple sclerosis
risk: A Mendelian randomization study

Multiple Sclerosis Journal
2017, Vol. 23(11) 1461-1468
DOI: 10.1177/
https://doi.org/10.1177/1352458516681196
1352458516681196
https://doi.org/10.1177/1352458516681196
© The Author(s), 2016.
Reprints and permissions:
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Julia Devorak, Lauren E Mokry, John A Morris, Vincenzo Forgetta,
George Davey Smith, Stephen Sawcer and J Brent Richards

Abstract
Background: Mendelian randomization (MR) studies have demonstrated strong support for an association between genetically increased body mass index and risk of multiple sclerosis (MS). The adipokine
adiponectin may be a potential mechanism linking body mass to risk of MS.
Objective: To evaluate whether genetically increased adiponectin levels influence risk of MS.
Methods: Using genome-wide significant single nucleotide polymorphisms (SNPs) for adiponectin, we
undertook an MR study to estimate the effect of adiponectin on MS. This method prevents bias due to
reverse causation and minimizes bias due to confounding. Sensitivity analyses were performed to evaluate the assumptions of MR.
Results: MR analyses did not support a role for genetically elevated adiponectin in risk of MS (odds ratio
(OR) = 0.93 per unit increase in natural-log-transformed adiponectin, equivalent to a two-standard deviation increase in adiponectin on the absolute scale; 95% confidence interval (CI) = 0.66-1.33; p = 0.61).
Further MR analysis suggested that genetic variation at the adiponectin gene, which influences adiponectin level, does not impact MS risk. Sensitivity analyses, including MR-Egger regression, suggested no
bias due to pleiotropy.
Conclusion: Lifelong genetically increased adiponectin levels in humans have no clear effect on risk of
MS. Other biological factors driving the association between body mass and MS should be investigated.
Keywords: Multiple sclerosis, adiponectin, Mendelian randomization analysis, genetic epidemiology
Date received: 13 July 2016; revised: 19 October 2016; accepted: 1 November 2016
Introduction
Multiple sclerosis (MS) is the most common chronic
inflammatory disease of the central nervous system
(CNS),1 affecting an estimated 2.3 million people
worldwide.2 MS is thought to be initiated by T-cells
which target self-antigens in the CNS, resulting in
demyelination and progressive neuroaxonal injury
and degeneration.1 Disease onset usually occurs in
early adulthood, and prognosis is variable; however,
the disease is often progressively debilitating.3
Both genetic and environmental factors have been
implicated in the etiology of MS.4 Genetic risk profiles in individuals with MS are often complex, and
many non-genetic factors have been associated with
the disease,4 including body weight. High body mass

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index (BMI) during childhood and early adolescence
has been associated with a 1.15- to 1.18-fold
increased risk of MS in adulthood,5 and overweight
and obesity in late adolescence and early adulthood
have been associated with an approximate two-fold
increased risk of MS in adulthood.6,7 Furthermore,
childhood overweight and obesity have been associated with an approximate 1.5- to 3.75-fold increased
odds of pediatric-onset MS, depending on the extent
of overweight or obesity.8 In addition, recent
Mendelian randomization (MR) analyses have demonstrated support for a causal association between
BMI and MS, whereby an increase in BMI by
approximately 5 kg/m2 increased the odds of MS by
40%.9 However, the underlying biological mechanisms linking BMI to MS are unclear.

Correspondence to:
JB Richards
Centre for Clinical
Epidemiology, Department
of Epidemiology, Lady
Davis Institute for Medical
Research, Jewish General
Hospital, H-413.1, 3755
Chemin de la Côte-SteCatherine, Montréal, QC
H3T 1E2, Canada.
brent.richards@mcgill.ca
Julia Devorak
Vincenzo Forgetta
Centre for Clinical
Epidemiology, Department
of Epidemiology, Lady
Davis Institute for Medical
Research, Jewish General
Hospital, Montréal, QC,
Canada
Lauren E Mokry
Department of Epidemiology,
Biostatistics and
Occupational Health, McGill
University, Montréal, QC,
Canada
John A Morris
Department of Human
Genetics, McGill University,
Montréal, QC, Canada
George Davey Smith
MRC Integrative
Epidemiology Unit, School
of Social and Community
Medicine, University of
Bristol, Bristol, UK
Stephen Sawcer
Department of Clinical
Neurosciences, Cambridge
Biomedical Campus,
University of Cambridge,
Cambridge, UK
J Brent Richards
Centre for Clinical
Epidemiology, Department
of Epidemiology, Lady
Davis Institute for Medical
Research, Jewish General
Hospital, Montréal, QC,
Canada/Department of
Epidemiology, Biostatistics
and Occupational Health,
McGill University, Montréal,
QC, Canada/Department of
Human Genetics, McGill
University, Montréal,

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