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多利时钟:一种基于脂质的衰老时钟揭示了神经疾病中的加速衰老。

DoliClock: a lipid-based aging clock reveals accelerated aging in neurological disorders.

作者信息

Latumalea Djakim, Unfried Maximilian, Barardo Diogo, Gruber Jan, Kennedy Brian K

机构信息

Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.

Institute for Life Sciences and Technology, Hanze University of Applied Sciences, Groningen, The Netherlands.

出版信息

Aging (Albany NY). 2025 Jun 4;17(6):1405-1428. doi: 10.18632/aging.206266.

Abstract

Aging is a multifaceted process influenced by intrinsic and extrinsic factors, with lipid alterations playing a critical role in brain aging and neurological disorders. This study introduces DoliClock, a lipid-based biological aging clock designed to predict the age of the prefrontal cortex using post-mortem lipidomic data. Significant age acceleration was observed in autism, schizophrenia, and Down syndrome. Additionally, an increase in entropy around age 40 suggests dysregulation of the mevalonate pathway and dolichol accumulation. Dolichol, a lipid integral to N-glycosylation and intracellular transport, emerged as a potential aging biomarker, with specific variants such as dolichol-19 and dolichol-20 showing unique age-related associations. These findings suggest that lipidomics can provide valuable insights into the molecular mechanisms of brain aging and neurological disorders. By linking dolichol levels and entropy changes to accelerated aging, this study highlights the potential of lipid-based biomarkers for understanding and predicting biological age, especially in conditions associated with premature aging.

摘要

衰老 是一个受内在和外在因素影响的多方面过程,脂质改变在大脑衰老和神经疾病中起着关键作用。本研究介绍了DoliClock,这是一种基于脂质的生物衰老时钟,旨在利用死后脂质组学数据预测前额叶皮质的年龄。在自闭症、精神分裂症和唐氏综合征中观察到显著的年龄加速。此外,40岁左右熵的增加表明甲羟戊酸途径失调和多萜醇积累。多萜醇是N-糖基化和细胞内运输所必需的一种脂质,成为一种潜在的衰老生物标志物,多萜醇-19和多萜醇-20等特定变体显示出独特的与年龄相关的关联。这些发现表明,脂质组学可以为大脑衰老和神经疾病的分子机制提供有价值的见解。通过将多萜醇水平和熵变化与加速衰老联系起来,本研究突出了基于脂质的生物标志物在理解和预测生物年龄方面的潜力,特别是在与早衰相关的情况下。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9119/12245196/69549ce73de8/aging-17-206266-g001.jpg

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