Author Identifier

Lois Balmer

https://orcid.org/0000-0001-5618-0555

Document Type

Journal Article

Publication Title

NPJ Regenerative Medicine

Publisher

Springer Nature in partnership with Australian Regenerative Medicine Institute

School

School of Medical and Health Sciences

RAS ID

28287

Funders

...This work was supported by National Health and Medical Research Council (NHMRC) Australia Fellowship (546133, N.A.R.), Australian Research Council (ARC) Stem Cells Australia (SR1100102, N.A.R.), NHMRC/Heart Foundation Career Development Fellowship (1049980, M.R.), a trampoline grant from the Association Française contre les Myopathies (17822, K.J.N.), an Australian Research Council Future Fellowship (FT100100734, K.J.N.), an NHMRC Program Grant (1037321, G.M.), an NHMRC Project Grant (1069173, G.M.), and the Diabetes Research Foundation of WA (G.M.), a United States National Institutes of Health Research Grant (R01HL116449, J.W.H.).

Grant Number

NHMRC Number : 1037321

Comments

Salimova, E., Nowak, K. J., Estrada, A. C., Furtado, M. B., McNamara, E., Nguyen, Q., ... Rosenthal, N. A. (2019). Variable outcomes of human heart attack recapitulated in genetically diverse mice. Nature Partner Journals Regenerative Medicine, 4(1), Article 5. Available here

Abstract

Clinical variation in patient responses to myocardial infarction (MI) has been difficult to model in laboratory animals. To assess the genetic basis of variation in outcomes after heart attack, we characterized responses to acute MI in the Collaborative Cross (CC), a multi-parental panel of genetically diverse mouse strains. Striking differences in post-MI functional, morphological, and myocardial scar features were detected across 32 CC founder and recombinant inbred strains. Transcriptomic analyses revealed a plausible link between increased intrinsic cardiac oxidative phosphorylation levels and MI-induced heart failure. The emergence of significant quantitative trait loci for several post-MI traits indicates that utilizing CC strains is a valid approach for gene network discovery in cardiovascular disease, enabling more accurate clinical risk assessment and prediction.

DOI

10.1038/s41536-019-0067-6

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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