Almramhi Mona M, Storm Catherine S, Kia Demis A, Coneys Rachel, Chhatwal Burleen K, Wood Nicholas W
Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK/Department of Medical Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.
Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK.
Mult Scler. 2022 Oct;28(11):1673-1684. doi: 10.1177/13524585221092644. Epub 2022 May 14.
The objective of this study was to explore the potential causal associations of body mass index, height, weight, fat mass, fat percentage and non-fat mass in the whole body, arms, legs and trunk (henceforth, 'anthropometric measures') with multiple sclerosis (MS) risk and severity. We also investigated the potential for reverse causation between anthropometric measures and MS risk.
We conducted a two-sample univariable, multivariable and bidirectional Mendelian randomisation (MR) analysis.
A range of features linked to obesity (body mass index, weight, fat mass and fat percentage) were risk factors for MS development and worsened the disease's severity in MS patients. Interestingly, we were able to demonstrate that height and non-fat mass have no association with MS risk or MS severity. We demonstrated that the association between anthropometric measures and MS is not subject to bias from reverse causation.
Our findings provide evidence from human genetics that a range of features linked to obesity is an important contributor to MS development and MS severity, but height and non-fat mass are not. Importantly, these findings also identify a potentially modifiable factor that may reduce the accumulation of further disability and ameliorate MS severity.
本研究的目的是探讨全身、手臂、腿部和躯干的体重指数、身高、体重、脂肪量、脂肪百分比和非脂肪量（以下简称“人体测量指标”）与多发性硬化症（MS）风险及严重程度之间的潜在因果关联。我们还研究了人体测量指标与MS风险之间反向因果关系的可能性。
我们进行了两样本单变量、多变量和双向孟德尔随机化（MR）分析。
一系列与肥胖相关的特征（体重指数、体重、脂肪量和脂肪百分比）是MS发病的危险因素，并会加重MS患者的疾病严重程度。有趣的是，我们能够证明身高和非脂肪量与MS风险或MS严重程度无关。我们证明了人体测量指标与MS之间的关联不受反向因果关系的偏差影响。
我们的研究结果提供了来自人类遗传学的证据，表明一系列与肥胖相关的特征是MS发病和严重程度的重要因素，但身高和非脂肪量并非如此。重要的是，这些发现还确定了一个潜在的可改变因素，该因素可能减少进一步残疾的积累并改善MS严重程度。
