Estimating the causal influence of body mass index on risk of Parkinson disease: A Mendelian randomisation study.


Noyce, AJ; Kia, DA; Hemani, G; Nicolas, A; Price, TR; De Pablo-Fernandez, E; Haycock, PC; Lewis, PA; Foltynie, T; Davey Smith, G; International Parkinson Disease Genomics Consortium, ; Schrag, A; Lees, AJ; Hardy, J; Singleton, A; Nalls, MA; Pearce, N; Lawlor, DA; Wood, NW; (2017) Estimating the causal influence of body mass index on risk of Parkinson disease: A Mendelian randomisation study. PLoS medicine, 14 (6). e1002314. ISSN 1549-1277 DOI: 10.1371/journal.pmed.1002314

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Abstract

Both positive and negative associations between higher body mass index (BMI) and Parkinson disease (PD) have been reported in observational studies, but it has been difficult to establish causality because of the possibility of residual confounding or reverse causation. To our knowledge, Mendelian randomisation (MR)-the use of genetic instrumental variables (IVs) to explore causal effects-has not previously been used to test the effect of BMI on PD. Two-sample MR was undertaken using genome-wide association (GWA) study data. The associations between the genetic instruments and BMI were obtained from the GIANT consortium and consisted of the per-allele difference in mean BMI for 77 independent variants that reached genome-wide significance. The per-allele difference in log-odds of PD for each of these variants was estimated from a recent meta-analysis, which included 13,708 cases of PD and 95,282 controls. The inverse-variance weighted method was used to estimate a pooled odds ratio (OR) for the effect of a 5-kg/m2 higher BMI on PD. Evidence of directional pleiotropy averaged across all variants was sought using MR-Egger regression. Frailty simulations were used to assess whether causal associations were affected by mortality selection. A combined genetic IV expected to confer a lifetime exposure of 5-kg/m2 higher BMI was associated with a lower risk of PD (OR 0.82, 95% CI 0.69-0.98). MR-Egger regression gave similar results, suggesting that directional pleiotropy was unlikely to be biasing the result (intercept 0.002; p = 0.654). However, the apparent protective influence of higher BMI could be at least partially induced by survival bias in the PD GWA study, as demonstrated by frailty simulations. Other important limitations of this application of MR include the inability to analyse non-linear associations, to undertake subgroup analyses, and to gain mechanistic insights. In this large study using two-sample MR, we found that variants known to influence BMI had effects on PD in a manner consistent with higher BMI leading to lower risk of PD. The mechanism underlying this apparent protective effect warrants further study.

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Medical Statistics
PubMed ID: 28609445
URI: http://researchonline.lshtm.ac.uk/id/eprint/3962407

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