Dataset Information

Mendelian randomization.

ABSTRACT: Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and give methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The difference between the assumptions required for MR analysis and other forms of non-interventional epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference.

SUBMITTER: Sanderson E

PROVIDER: S-EPMC7614635 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Publications

Mendelian randomization.

Sanderson Eleanor E Glymour M Maria MM Holmes Michael V MV Kang Hyunseung H Morrison Jean J Munafò Marcus R MR Palmer Tom T Schooling C Mary CM Wallace Chris C Zhao Qingyuan Q Smith George Davey GD

Nature reviews. Methods primers 20220201

Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the met ...[more]

PMID: 37325194

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Project description:Parkinson's disease (PD) is the second most common neurodegenerative disorder, characterized by a complex pathogenesis involving the interplay of multiple molecular and cellular pathways. In recent years, metabolic dysregulation and neuroinflammation have been recognized as key contributors to PD onset and progression, potentially mediating neurodegenerative changes by affecting dopaminergic neuron survival, synaptic function, and neural network homeostasis. However, conventional observational studies are limited in establishing causal relationships between these metabolites and inflammatory mediators, highlighting the urgent need for systematic identification using genetic approaches.MeathodsUsing Mendelian randomization, this study systematically elucidates, for the first time, the causal roles of key metabolites and inflammatory mediators in PD. These findings provide critical genetic evidence for the identification of early biomarkers and the development of potential therapeutic targets, while also offering novel insights into the mechanistic interplay between metabolic dysregulation and inflammation in neurodegenerative diseases.ResultA total of 722 differential metabolites were identified, of which three had corresponding genetic information in GWAS datasets. In addition, 14 caffeine-related metabolites and 91 inflammatory mediators were included in the MR analysis. The results showed that 1-Methylnicotinamide, Flt3L, IL-13, and ST1A1 were negatively associated with PD, suggesting potential protective effects, whereas FGF-5, IL-4, and CCL13 exhibited positive causal associations, indicating potential risk-promoting roles. These findings highlight the central role of inflammatory pathways in PD pathogenesis and progression and suggest a potential interplay between metabolic dysregulation and inflammatory responses.ConclusionThis study, using Mendelian randomization, systematically elucidates for the first time the causal roles of key metabolites and inflammatory mediators in PD, providing critical theoretical evidence for the identification of early biomarkers and the development of potential therapeutic targets, while also offering novel genetic insights into the mechanistic interplay between metabolic dysregulation and inflammation in neurodegenerative diseases.

Dataset Information

Mendelian randomization.

Publications

Mendelian randomization.

Similar Datasets

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