Kuan-Han Wu

I’d like to acknowledge the mentorship of @XuShiBiostat and @cristenw and thank our @umichmedicine collaborators @Douville_NJ and @Michael__Mathis and the contribution of @LabWiller and @umichsph colleagues including Xianshi Yu, @SarahEGraham1, Ida Surakka, and @whitneyhornsby.

This work reveals the power of integrating PRS and ClinRS to enhance disease prediction and the potential to inform heart failure prevention efforts.

We are glad to share our latest preprint on integrating large scale genetic and clinical information to predict cases of heart failure, using polygenic risk score (PRS) and clinical risk score (ClinRS).

Huge thanks to the whole GBMI team, especially @weizhouw and participating biobanks. This research is the combined effort of several @UMich colleagues including @Douville_NJ, @bnwolford, Ida Surakka, @SarahEGraham1, @whitneyhornsby, @cristenw, and @LabWiller.

Predicting susceptibility to heart failure with preserved ejection fraction is going to be a harder problem to solve!

Our hearts are glad to share our preprint on using genetic information to uncover susceptibility to heart failure, as part of the Global Biobank Meta-analysis Initiative (GBMI) @GlobalBiobanks.