Parkinson’s disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson’s disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson’s disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson’s disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson’s disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson’s disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson’s disease drug development.
Common neurodegenerative diseases are thought to arise from a combination of environmental and genetic exposures. Mendelian randomization is a powerful way to leverage existing genetic data to investigate causal relationships between risk factors and disease. In recent years, Mendelian randomization has gathered considerable traction in neurodegenerative disease research, providing valuable insights into the aetiology of these conditions. This review aims to evaluate the impact of Mendelian randomization studies on translational medicine for neurodegenerative diseases, highlighting the advances made and challenges faced. We will first describe the fundamental principles and limitations of Mendelian randomization and then discuss the lessons from Mendelian randomization studies of environmental risk factors for neurodegeneration. We will illustrate how Mendelian randomization projects have used novel resources to study molecular pathways of neurodegenerative disease and discuss the emerging role of Mendelian randomization in drug development. Finally, we will conclude with our view of the future of Mendelian randomization in these conditions, underscoring unanswered questions in this field.
Objective: 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. Methods: We conducted a two-sample univariable, multivariable and bidirectional Mendelian randomisation (MR) analysis. Results: 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. Conclusions: 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.
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