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MskAge——一种源自遗传算法岛屿模型的肌肉骨骼年龄的表观遗传生物标志物。

MskAge-An Epigenetic Biomarker of Musculoskeletal Age Derived From a Genetic Algorithm Islands Model.

作者信息

Green Daniel C, Reynard Louise N, Henstock James R, Reppe Sjur, Gautvik Kaare, Peffers Mandy J, Shanley Daryl P, Clegg Peter D, Canty-Laird Elizabeth G

机构信息

Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK.

The Medical Research Council Versus Arthritis Centre for Integrated Research Into Musculoskeletal Ageing (CIMA), University of Liverpool, Liverpool, UK.

出版信息

Aging Cell. 2025 Sep;24(9):e70149. doi: 10.1111/acel.70149. Epub 2025 Jun 19.

DOI:10.1111/acel.70149
PMID:40538142
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12419849/
Abstract

Age is a significant risk factor for functional decline and disease of the musculoskeletal system, yet few biomarkers exist to facilitate ageing research in musculoskeletal tissues. Multivariate models based on DNA methylation, termed epigenetic clocks, have shown promise as markers of biological age. However, the accuracy of existing epigenetic clocks in musculoskeletal tissues are no more, and often less accurate than a randomly sampled baseline model. We developed a highly accurate epigenetic clock, MskAge, that is specific to tissues and cells of the musculoskeletal system. MskAge was built using a penalised genetic algorithm islands model that addresses multi-tissue clock bias. The final model was trained on the transformed principal components of CpGs selected by the genetic algorithm. We show that MskAge tracks epigenetic ageing ex vivo and in vitro. Epigenetic age estimates are rejuvenated with cellular reprogramming and are accelerated at a rate of 0.45 years per population doubling. MskAge explains more variance associated with in vitro ageing of fibroblasts than the purpose-developed skin and blood clock. The precision of MskAge and its ability to capture perturbations in biological ageing make it a promising research tool for musculoskeletal and ageing biologists.

摘要

年龄是肌肉骨骼系统功能衰退和疾病的一个重要风险因素,但用于促进肌肉骨骼组织衰老研究的生物标志物却很少。基于DNA甲基化的多变量模型,即表观遗传时钟,已显示出有望成为生物年龄的标志物。然而,现有表观遗传时钟在肌肉骨骼组织中的准确性并不比随机抽样的基线模型更高,而且往往更低。我们开发了一种高度准确的表观遗传时钟MskAge,它对肌肉骨骼系统的组织和细胞具有特异性。MskAge是使用一种惩罚遗传算法岛屿模型构建的,该模型解决了多组织时钟偏差问题。最终模型是在由遗传算法选择的CpG的转换主成分上进行训练的。我们表明,MskAge在体外和体内都能追踪表观遗传衰老。表观遗传年龄估计值会随着细胞重编程而恢复活力,并且以每细胞群体倍增0.45年的速度加速。与专门开发的皮肤和血液时钟相比,MskAge能解释更多与成纤维细胞体外衰老相关的方差。MskAge的精确性及其捕捉生物衰老过程中扰动的能力使其成为肌肉骨骼和衰老生物学家的一个有前途的研究工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/87dec3ec9f7a/ACEL-24-e70149-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/1be6d3eb4475/ACEL-24-e70149-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/3ffcd2038d04/ACEL-24-e70149-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/dbf3b21b53d7/ACEL-24-e70149-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/2fb3f3328af8/ACEL-24-e70149-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/44cb73ad5f60/ACEL-24-e70149-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/87dec3ec9f7a/ACEL-24-e70149-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/1be6d3eb4475/ACEL-24-e70149-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/3ffcd2038d04/ACEL-24-e70149-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/dbf3b21b53d7/ACEL-24-e70149-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/2fb3f3328af8/ACEL-24-e70149-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/44cb73ad5f60/ACEL-24-e70149-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9713/12419849/87dec3ec9f7a/ACEL-24-e70149-g004.jpg

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