Portrait de Julien St-Pierre

Julien St-Pierre

julien.st-pierre@mila.quebec
Postdoctorat - UdeM
Superviseur⋅e principal⋅e
Marc-André Legault
Sujets de recherche
Causalité
Génétique
Statistiques
Statistiques en haute dimension
Google Scholar
GitHub

Publications

Revisiting the genetic support of leukotriene pathway drug targets in atherosclerotic cardiovascular disease
Tristan St-Laurent
Julien St.-Pierre
Julien Quang Le Van
Marc‐André Legault
Arachidonate 5-lipoxygenase (5-LO) and its activating protein, encoded by ALOX5 and ALOX5AP respectively, are two leukotriene pathway protei… (voir plus)ns suspected to play a role in atherosclerotic cardiovascular disease (ASCVD) through inflammatory mechanisms. Prior genetic association studies linking ALOX5 and ALOX5AP to ASCVD have motivated clinical trials of 5-LO inhibitors, such as atreleuton, which was associated with reduced atherosclerotic plaque progression in patients with a recent acute coronary syndrome in a phase II trial. However, the effect of 5-LO inhibition on ASCVD clinical outcomes remains unclear. Using data from the UK Biobank, we revisit previously reported genetic associations of ALOX5 and ALOX5AP with ASCVD using a multi-ancestry meta-analysis including data from 378,962 participants. We characterize ancestral differences in previously studied ALOX5 and ALOX5AP polymorphisms which could have led to population stratification. When adequately accounting for ancestry, these previous associations were not replicated. In addition to our replication efforts, we used association scans and transcriptome-wide association studies to test the involvement of leukotriene pathway genes with ASCVD. Overall, our results do not support a role for genetic variation in ALOX5 or its activating protein in ASCVD risk.
2026-10-13
Frontiers in Genetics (publié)
doi.org
Robust Mendelian Randomization Estimation using Weighted Quantile Regression
Julien St-Pierre
Archer Y. Yang
Mireille E. Schnitzer
Marc-André Legault
In Mendelian randomization (MR) studies, genetic variants are used as instrumental variables (IVs) to investigate causal relationships betwe… (voir plus)en exposures and outcomes based on observational data. However, numerous genetic studies have shown the pervasive pleiotropy of genetic variants, meaning that many, if not most, variants are associated with multiple traits, potentially violating the core assumptions of IV estimation. Uncorrelated pleiotropy occurs when genetic variants have a direct effect on the outcome that is not mediated by the exposure, while correlated pleiotropy occurs when genetic variants affect the exposure and outcome via shared heritable confounders. In this work, we propose a novel MR method, called MR-Quantile, based on weighted quantile regression (WQR) that is robust to both correlated and uncorrelated pleiotropy. We propose a procedure for selecting the optimal quantile of the ratio estimates through a likelihood-based formulation of WQR using the asymmetric Laplace distribution. Monte Carlo simulations demonstrate the empirical performance of the proposed method, especially in settings with many invalid IVs with weak pleiotropic effects. Finally, we apply our method to study the causal effect of resting heart rate on atrial fibrillation. Genetic variants associated with heart rate were identified in a genome-wide association study of 425,748 individuals from the VA Million Veteran Program, and used as instruments in a two-sample MR analysis with summary statistics from a genetic meta-analysis of 228,926 AF cases across eight studies.
2026-04-07
arXiv (prépublication)
doi.org
arxiv.org