Association of Body Mass Index and Parkinson Disease
Cloé Domenighetti, Pierre‐Emmanuel Sugier, Ashwin Ashok Kumar Sreelatha, Claudia Schulte, Sandeep Grover, Berta Portugal, Pei‐Chen Lee, Patrick May, Dheeraj Reddy Bobbili, Milena Radivojkov Blagojevic, Peter Lichtner, Andrew Singleton, Dena Hernández, Connor Edsall, George D. Mellick, Alexander Zimprich, Walter Pirker, Ekaterina Rogaeva, Anthony E. Lang, Sulev Kõks, Pille Taba, Suzanne Lesage, Alexis Brice, Jean‐Christophe Corvol, Marie‐Christine Chartier‐Harlin, Eugénie Mutez, Kathrin Brockmann, Angela Deutschländer, Georgios M. Hadjigeorgiou, Efthimios Dardiotis, Leonidas Stefanis, Athina Maria Simitsi, Enza Maria Valente, Simona Petrucci, Letizia Straniero, Anna Zecchinelli, Gianni Pezzoli, Laura Brighina, Carlo Ferrarese, Grazia Annesi, Andrea Quattrone, Monica Gagliardi, Hirotaka Matsuo, Akiyoshi Nakayama, Nobutaka Hattori, Kenya Nishioka, Sun Ju Chung, Yun Joong Kim, Pierre Kolber, Bart P.C. van de Warrenburg, Bastiaan R. Bloem, Mathias Toft, Lasse Pihlstrøm, Leonor Correia Guedes, Joaquim J. Ferreira, Soraya Bardien, Jonathan Carr, Eduardo Tolosa, Mario Ezquerra, Pau Pástor, Mónica Díez-Fairén, Karin Wirdefeldt, Nancy L. Pedersen, Caroline Ran, Andrea Carmine Belin, Andreas Puschmann, Clara Hellberg, Carl E Clarke, Karen Morrison, Manuela Tan, Dimitri Krainc, Lena F. Burbulla, Matthew J. Farrer, Rejko Krüger, Thomas Gasser, Manu Sharma, Alexis Elbaz
Abstract
BACKGROUND AND OBJECTIVES: The role of body mass index (BMI) in Parkinson disease (PD) is unclear. Based on the Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in PD (Courage-PD) consortium, we used 2-sample Mendelian randomization (MR) to replicate a previously reported inverse association of genetically predicted BMI with PD and investigated whether findings were robust in analyses addressing the potential for survival and incidence-prevalence biases. We also examined whether the BMI-PD relation is bidirectional by performing a reverse MR. METHODS: [95% CI]) of PD and additional pleiotropy robust methods. We performed analyses stratified by age, disease duration, and sex. For reverse MR, we used SNPs associated with PD from 2 iPDGC GWAS to assess the effect of genetic liability toward PD on BMI. RESULTS: -interaction = 0.48). In reverse MR, there was evidence for pleiotropy, but pleiotropy robust methods showed a significant inverse association. DISCUSSION: Using an independent data set (Courage-PD), we replicate an inverse association of genetically predicted BMI with PD, not explained by survival or incidence-prevalence biases. Moreover, reverse MR analyses support an inverse association between genetic liability toward PD and BMI, in favor of a bidirectional relation.