Mendelian Randomization with longitudinal exposure data: simulation study and real data application

Background and aim Mendelian Randomization (MR) is a widely used tool to estimate causal effects using genetic variants as instrumental variables. MR is limited to cross-sectional summary statistics of different samples and time points to analyse time-varying effects. We aimed at using longitudinal summary statistics for an exposure in a multivariable MR setting and validating the effect estimates for the mean, slope and within-individual variability. Simulation study We tested our approach in twelve scenarios for power and type I error, depending on shared instruments between the mean, slope and variability, and regression model specifications. We observed high power to detect causal effects of the mean and slope throughout the simulation, but the variability effect was low powered in case of shared SNPs between the mean and variability. Mis-specified regression models led to lower power and increased the type I error. Real data application We applied our approach to two real data sets (POPS, UK Biobank). We detected significant causal estimates for both the mean and the slope in both cases, but no independent effect of the variability. However, we only had weak instruments in both data sets.

We used a new approach to test a time-varying exposure for causal effects of the exposure’s mean, slope and variability. The simulation with strong instruments seems promising but also highlights three crucial points: 1) the difficulty to define the correct exposure regression model, 2) the dependency on the genetic correlation, and 3) the lack of strong instruments in real data. Taken together, this demands a cautious evaluation of the results, accounting for known biology and the trajectory of the exposure. Competing Interest Statement JKB has received research funding for unrelated work from F. Hoffmann-La Roche Ltd. Funding Statement JP was supported by grants from the Wellcome Trust (225790/Z/22/Z) and the United Kingdom Research and Innovation Medical Research Council (MC_UU_00002/7) to SB. MP was supported by the MRC grant "Looking beyond the mean: what within-person variability can tell us about dementia, cardiovascular disease and cystic fibrosis" (MR/V020595/1) and his research is currently supported by the Ulverscroft Vision Research Group (UCL). JKB was supported by MRC Unit Programme MC_UU_00002/5 and MRC Unit Theme MC_UU_00040/02 (Precision Medicine). POPS was supported by the Women's Health theme of the NIHR Cambridge Biomedical Research Centre. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Pregnancy Outcome Prediction Study (POPS) study is approved by the Cambridge Local Research Ethics Committee. Written informed consent including agreement with genetic analyses was obtained by research midwifes from all participants. UK Biobank has approval from the North West Multi-centre Research Ethics Committee (MREC) as a Research Tissue Bank (RTB) approval. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes We updated the simulation section to clarify the workflow and the different scenarios. We revised and restructured the discussion. Data Availability All data produced are available online at doi:10.5281/ZENODO.17634559