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使用一小部分 DNA 甲基化位点和基于队列的机器学习算法从血液中准确预测年龄。

Accurate age prediction from blood using a small set of DNA methylation sites and a cohort-based machine learning algorithm.

机构信息

School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel; The Center for Computational Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.

School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel; Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.

出版信息

Cell Rep Methods. 2023 Sep 25;3(9):100567. doi: 10.1016/j.crmeth.2023.100567. Epub 2023 Aug 28.

DOI:10.1016/j.crmeth.2023.100567
PMID:37751697
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10545910/
Abstract

Chronological age prediction from DNA methylation sheds light on human aging, health, and lifespan. Current clocks are mostly based on linear models and rely upon hundreds of sites across the genome. Here, we present GP-age, an epigenetic non-linear cohort-based clock for blood, based upon 11,910 methylomes. Using 30 CpG sites alone, GP-age outperforms state-of-the-art models, with a median accuracy of ∼2 years on held-out blood samples, for both array and sequencing-based data. We show that aging-related changes occur at multiple neighboring CpGs, with implications for using fragment-level analysis of sequencing data in aging research. By training three independent clocks, we show enrichment of donors with consistent deviation between predicted and actual age, suggesting individual rates of biological aging. Overall, we provide a compact yet accurate alternative to array-based clocks for blood, with applications in longitudinal aging research, forensic profiling, and monitoring epigenetic processes in transplantation medicine and cancer.

摘要

从 DNA 甲基化预测年龄有助于了解人类衰老、健康和寿命。目前的时钟主要基于线性模型,并依赖于基因组中数百个位点。在这里,我们提出了基于血液的表观遗传非线性基于队列的时钟 GP-age,它基于 11910 个甲基组。仅使用 30 个 CpG 位点,GP-age 的性能优于最先进的模型,在保留的血液样本中,对于基于阵列和测序的数据,中位数准确性约为 2 年。我们表明,与衰老相关的变化发生在多个相邻的 CpG 上,这对使用测序数据的片段水平分析在衰老研究中具有重要意义。通过训练三个独立的时钟,我们表明,在预测年龄和实际年龄之间存在一致偏差的供体富集,这表明存在个体生物学衰老率。总的来说,我们为血液提供了一种紧凑而准确的替代基于阵列的时钟,可应用于纵向衰老研究、法医分析以及监测移植医学和癌症中的表观遗传过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/b9caf831eef7/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/1385d929ee3c/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/a1f6b99c0b3c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/9be60ffa6566/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/96f5fee46a68/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/fe1b1c9d88f9/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/f41840133b14/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/b3c43562739c/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/b9caf831eef7/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/1385d929ee3c/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/a1f6b99c0b3c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/9be60ffa6566/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/96f5fee46a68/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/fe1b1c9d88f9/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/f41840133b14/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/b3c43562739c/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63da/10545910/b9caf831eef7/gr7.jpg

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