Two sample Mendelian Randomisation using an outcome from a multilevel model of disease progression.

ABSTRACT: Identifying factors that are causes of disease progression, especially in neurodegenerative diseases, is of considerable interest. Disease progression can be described as a trajectory of outcome over time-for example, a linear trajectory having both an intercept (severity at time zero) and a slope (rate of change). A technique for identifying causal relationships between one exposure and one outcome in observational data whilst avoiding bias due to confounding is two sample Mendelian Randomisation (2SMR). We consider a multivariate approach to 2SMR using a multilevel model for disease progression to estimate the causal effect an exposure has on the intercept and slope. We carry out a simulation study comparing a naïve univariate 2SMR approach to a multivariate 2SMR approach with one exposu

SUBMITTER: Lawton M 

PROVIDER: S-EPMC11219432 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature