Mendelian randomisation with proxy exposures: challenges and opportunities
medRxiv
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
A key challenge in human genetics is the discovery of modifiable causal risk factors for complex traits and diseases. Mendelian randomisation (MR) using molecular traits as exposures is a particularly promising approach for identifying such risk factors. Despite early successes with low-density lipoprotein (LDL) cholesterol and C-reactive protein, recent studies have revealed a more nuanced picture, with widespread horizontal pleiotropy. Here, using data from the UK Biobank, we illustrate the issue of horizontal pleiotropy with two case studies involving glycolysis and vitamin D synthesis pathways. In both cases, we demonstrate that, although the measured metabolites (pyruvate or histidine) do not have a direct causal effect on the outcomes of interest (red blood cell count or vitamin D level), we can still use variants’ effects on these metabolites to infer how they perturb protein function in different gene regions. This allows us to use variant effects on metabolite levels as proxy exposures in the cis-MR framework, thus rediscovering the causal roles of histidine ammonia lyase (HAL) in vitamin D synthesis and glycolysis pathway in red blood cell survival. We also highlight the assumptions that need to be satisfied for cis-MR with proxy exposures to yield valid inferences and discuss the practical challenges of meeting these assumptions.
Bibliographic Details
Cold Spring Harbor Laboratory
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