Nonlinear ageing gero-marker dynamics of transcriptomic profile during calcific aortic valve mouse modeling

Abstract

The prevention and management of degenerative heart disease remain challenging and could potentially be significantly improved by understanding of ageing biomarker dynamics. In this study, we constructed the calcific aortic valve mouse model at different age points, measured valve function degeneration along with valve calcification, and investigated the nonlinear dynamics using sequencing data and deep learning models. In C57BL/6 N mouse model, the older mice had higher levels of peak transvalvular jet velocity in terms of valve function. Regarding valve calcification, collagen and elastic fiber calcification in the middle layer increased significantly at 48-week-old (p < 0.001), and the calcification spread to the inner endothelial cells at 72-week-old (p < 0.0001). RNA sequencing illustrated that 30 genes, including Acadsb, L2hgdh, and Cpped1, showed increased expression with age. Among them, four genes, namely Hipk2, 9430069I07Rik, Peli3, and Slc22a12, increased more than threefold in aortic tissues in 72-week-old mice compared to 6-week-old mice. Moreover, a large proportion of genes changed in a nonlinear pattern (6,325 out of 12,160, 52%). In conclusion, both linear and nonlinear gero-markers were found in the calcific aortic valve mouse modeling, which highlighted specific periods of significant wave with accelerated ageing (48-week-old in mice).