表观遗传学
脂质代谢
生物
内质网
表型
DNA甲基化
细胞生物学
线粒体
DNA损伤
遗传学
基因
生物化学
DNA
基因表达
作者
Xin Li,Jiaqiang Wang,LeYun Wang,Yuanxu Gao,Guihai Feng,Gen Li,Jun Zou,Meixin Yu,Yu Fei Li,Chao Liu,Xue Wei Yuan,Ling Zhao,Hong Ouyang,Jian‐Kang Zhu,Wei Li,Qi Zhou,Kang Zhang
标识
DOI:10.1038/s41392-022-00964-6
摘要
Abstract Epigenetic alterations and metabolic dysfunction are two hallmarks of aging. However, the mechanism of how their interaction regulates aging, particularly in mammals, remains largely unknown. Here we show ELOVL fatty acid elongase 2 (Elovl2), a gene whose epigenetic alterations are most highly correlated with age prediction, contributes to aging by regulating lipid metabolism. We applied artificial intelligence to predict the protein structure of ELOVL2 and the interaction with its substrate. Impaired Elovl2 function disturbs lipid synthesis with increased endoplasmic reticulum stress and mitochondrial dysfunction, leading to key aging phenotypes at both cellular and physiological level. Furthermore, restoration of mitochondrial activity can rescue age-related macular degeneration (AMD) phenotypes induced by Elovl2 deficiency in human retinal pigmental epithelial (RPE) cells; this indicates a conservative mechanism in both human and mouse. Taken together, we revealed an epigenetic-metabolism axis contributing to aging and illustrate the power of an AI-based approach in structure-function studies.
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