GWAS Summary-level Data for Cardiovascular Disease

Summary-level GWAS data of Cardiovascular Disease from UKBB (n = 459,324, case fraction = 0.319)^{35 (link)} were generated by BOLT-LMM based on the Bayesian linear mixed model per SNP^{63 (link)} with assessment centered, sex, age, and squared age as covariates. Although BOLT-LMM was derived based on a quantitative trait model, it can be applied to analyze case–control traits and has a well-controlled false-positive rate when the trait is sufficiently balanced with a case fraction ≥10% and samples are of the same ancestry. The tested dichotomous cardiovascular disease phenotype includes a list of sub-phenotypes: hypertension, heart/cardiac problem, peripheral vascular disease, venous thromboembolic disease, stroke, transient ischemic attack (tia), subdural hemorrhage/hematoma, cerebral aneurysm, high cholesterol, and other venous/lymphatic diseases.

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Dai Q., Zhou G., Zhao H., Võsa U., Franke L., Battle A., Teumer A., Lehtimäki T., Raitakari O.T., Esko T., Epstein M.P, & Yang J. (2023). OTTERS: a powerful TWAS framework leveraging summary-level reference data. Nature Communications, 14, 1271.

Publication 2023

Cardiac Cardiovascular disease Cerebral aneurysm Gwas Hematoma Hemorrhage High cholesterol Hypertension Lymphatic diseases Peripheral vascular disease Phenotypes Stroke Subdural hemorrhage Thromboembolic disease Transient ischemic attack Venous

Corresponding Organization : Emory University

Other organizations : Yale University, University of Tartu, University of Groningen, Oncode Institute, University Medical Center Groningen, Johns Hopkins University, Universitätsmedizin Greifswald, Fimlab (Finland), Tampere University, Turku University Hospital, University of Turku

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Variable analysis

dependent variables

Cardiovascular Disease
Hypertension
Heart/Cardiac Problem
Peripheral Vascular Disease
Venous Thromboembolic Disease
Stroke
Transient Ischemic Attack (TIA)
Subdural Hemorrhage/Hematoma
Cerebral Aneurysm
High Cholesterol
Other Venous/Lymphatic Diseases

control variables

Squared Age

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