Ioanna Tzoulaki
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Articles (19)
Year:
2024
Year:
2024
Year:
2024
Year:
2024
Year:
2024
Year:
2024
Year:
2024
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2024
Year:
2023
BACKGROUND Mendelian randomization (MR) offers a powerful approach to study potential causal associations between exposures and health outcomes by using genetic variants associated with an exposure as instrumental variables. In this systematic review, we aimed to summarize previous MR studies and to evaluate the evidence for causality for a broad range of exposures in relation to coronary artery disease and stroke. METHODS AND RESULTS MR studies investigating the association of any genetically predicted exposure with coronary artery disease or stroke were identified. Studies were classified into 4 categories built on the significance of the main MR analysis results and its concordance with sensitivity analyses, namely, robust, probable, suggestive, and insufficient. Studies reporting associations that did not perform any sensitivity analysis were classified as nonevaluable. We identified 2725 associations eligible for evaluation, examining 535 distinct exposures. Of them, 141 were classified as robust, 353 as probable, 110 as suggestive, and 926 had insufficient evidence. The most robust associations were observed for anthropometric traits, lipids, and lipoproteins and type 2 diabetes with coronary artery; disease and clinical measurements with coronary artery disease and stroke; and thrombotic factors with stroke. CONCLUSIONS Despite the large number of studies that have been conducted, only a limited number of associations were supported by robust evidence. Approximately half of the studies reporting associations presented an MR sensitivity analysis along with the main analysis that further supported the causality of associations. Future research should focus on more thorough assessments of sensitivity MR analyses and further assessments of mediation effects or nonlinearity of associations.
Year:
2023
Year:
2023
Year:
2023
Year:
2023
Year:
2022
Year:
2022
Year:
2022
Year:
2022
Year:
2021
Year:
2021
Collaborators (18)
Marie-Joe Dib
Imperial College London
Fotios Koskeridis
University of Ioannina
Abbas Dehghan
Reader in cardiometabolic diseases
Imperial College London
Álvaro Hernáez
Associate Lecturer
Blanquerna Universitat Ramon Llull Facultat de Ciències de la Salut
Benjamin Woolf
University of Bristol
James Yarmolinsky
Imperial College London
Tom G. Richardson
-
Marc Chadeau-Hyam
Professor in Computational Epidemiology and Biostatistics
Imperial College London
Christos V. Chalitsios
University of Oxford
Sofia Cividini
External consultant for the Global Cancer Update Programme (CUP Global). Collaboration with Prof. Konstantinos (Kostas) Tsilidis, Dr Doris SM Chan, and the CUP Global Team/Research Associate in Biostatistics
Imperial College London
Jaume Marrugat
Senior Consultant 3 in the professional degree
Institut Hospital del Mar d'Investigacions Mèdiques
Camille Lassale
Assistant Professor
Barcelona Institute for Global Health
Paul Elliott
Imperial College London
Manyi Jia
Graduate teaching assistant
Imperial College London
Christopher Papandreou
-
Dipender Gill
Imperial College London
ROBERTO ELOSUA
Full Professor
Universitat de Vic - Universitat Central de Catalunya
Héléne Toinét Cronjé
Københavns Universitet
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