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基于血浆蛋白的器官特异性衰老和死亡率模型揭示疾病是机体系统的加速衰老。

Plasma protein-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems.

作者信息

Goeminne Ludger J E, Vladimirova Anastasiya, Eames Alec, Tyshkovskiy Alexander, Argentieri M Austin, Ying Kejun, Moqri Mahdi, Gladyshev Vadim N

机构信息

Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.

出版信息

Cell Metab. 2025 Jan 7;37(1):205-222.e6. doi: 10.1016/j.cmet.2024.10.005. Epub 2024 Nov 1.

DOI:10.1016/j.cmet.2024.10.005
PMID:39488213
Abstract

Aging is a complex process manifesting at molecular, cellular, organ, and organismal levels. It leads to functional decline, disease, and ultimately death, but the relationship between these fundamental biomedical features remains elusive. By applying elastic net regularization to plasma proteome data of over 50,000 human subjects in the UK Biobank and other cohorts, we report interpretable organ-specific and conventional aging models trained on chronological age, mortality, and longitudinal proteome data. These models predict organ/system-specific disease and indicate that men age faster than women in most organs. Accelerated organ aging leads to diseases in these organs, and specific diets, lifestyles, professions, and medications influence organ aging rates. We then identify proteins driving these associations with organ-specific aging. Our analyses reveal that age-related chronic diseases epitomize accelerated organ- and system-specific aging, modifiable through environmental factors, advocating for both universal whole-organism and personalized organ/system-specific anti-aging interventions.

摘要

衰老 是一个在分子、细胞、器官和机体水平上表现出来的复杂过程。它会导致功能衰退、疾病,并最终导致死亡,但这些基本生物医学特征之间的关系仍然难以捉摸。通过将弹性网络正则化应用于英国生物银行和其他队列中超过50000名人类受试者的血浆蛋白质组数据,我们报告了基于实足年龄、死亡率和纵向蛋白质组数据训练的可解释的器官特异性和传统衰老模型。这些模型预测器官/系统特异性疾病,并表明在大多数器官中男性比女性衰老得更快。器官加速衰老会导致这些器官发生疾病,特定的饮食、生活方式、职业和药物会影响器官衰老速度。然后,我们确定驱动这些与器官特异性衰老相关联的蛋白质。我们的分析表明,与年龄相关的慢性疾病是器官和系统特异性加速衰老的典型表现,可通过环境因素进行调节,这提倡进行普遍的全机体和个性化的器官/系统特异性抗衰老干预。

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