[논문]노화 시계를 이용한 알츠하이머병 환자의 후성유전학적 연령 예측

김진영; 조광원

doi:10.13160/ricns.2023.16.2.61

Abstract ▼ AI-Helper

Human body ages differently due to environmental, genetic and pathological factors. DNA methylation patterns also differs depending on various factors such as aging and several other diseases. The aging clock model, which uses these differences to predict age, analyzes DNA methylation patterns, reco...

Human body ages differently due to environmental, genetic and pathological factors. DNA methylation patterns also differs depending on various factors such as aging and several other diseases. The aging clock model, which uses these differences to predict age, analyzes DNA methylation patterns, recognizes age-specific patterns, predicts age, and grasps the speed and degree of aging. Aging occurs in everyone and causes various problems such as deterioration of physical ability and complications. Alzheimer's disease is a disease associated with aging and the most common brain degenerative disease. This disease causes various cognitive functions disabilities such as dementia and impaired judgment to motor functions, making daily life impossible. It has been reported that the incidence and progression of this disease increase with aging, and that increased phosphorylation of Aβ and tau proteins, which are overexpressed in this disease and accelerates epigenetic aging. It has also been reported that DNA methylation is significantly increased in the hippocampus and entorhinal cortex of Alzheimer's disease patients. Therefore, we calculated the biological age using the Epi clock, a pan-tissue aging clock model, and confirmed that the epigenetic age of patients suffering from Alzheimer's disease is lower than their actual age. Also, it was confirmed to slow down aging.

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표 Table. 1. Cleaning up the collected dataset (Alzheimer's disease & Control).
그림 Fig. 1. Comparison of epigenetic age between Alzheimer's and Control in hippocampal tissue. (A) Control group of Alzheimer's disease graph. It shows the trend of the epigenetic age of normal people on the Epi clock. Also used to check the accuracy of hippocampal tissue in the Epi clock. (B) Graph of Alzheimer's disease patients. The epigenetic age of patients with Alzheimer's disease shows the trend of the Epi clock. (A,B) By comparing the two groups, it is possible to confirm the difference in epigenetic age between normal people and Alzheimer's patients in the hippocampus.
표 Table. 2. Sample characteristics of Alzheimer's disease and Control.
표 Table. 3. Hippocampal tissue accuracy in Alzheimer's and Control.
그림 Fig. 2. Comparison of epigenetic age between Alzheimer's and Control in entorhinal cortex tissue. (A) Control of Alzheimer's disease graph. The epigenetic age trend of normal people is shown in Epi clock. It is also used to check the accuracy of entorhinal cortex tissue in the Epi clock. (B) Alzheimer's disease patients Graph. The epigenetic age trend of Alzheimer's disease patients is shown in Epi clock. (A,B) By comparing the two groups, the difference in epigenetic age between normal people and patients with Alzheimer's disease can be confirmed in the entorhinal cortex.
그림 Fig. 3. Epigenetic age acceleration in the hippocampus and entorhinal cortex. (A) Epigenetic age acceleration in the hippocampus. Showing differences in age acceleration between Alzheimer's and normal subjects in hippocampal tissue. (B) Accelerated epigenetic age in the entorhinal cortex. Differences in age acceleration between Alzheimer's and normal subjects in the entorhinal cortex tissue
표 Table. 4. Entorhinal cortex tissue accuracy in Alzheimer's and Control.
그림 Fig. 4. Analysis of pathways in the hippocampus and entorhinal cortex. (A) Pathways represented by genes associated with the top 10 CpG sites significantly altered in the hippocampus (B) Pathways represented by genes associated with the top 10 CpG sites significantly altered in the entorhinal cortex

참고문헌 (10)

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노화 시계를 이용한 알츠하이머병 환자의 후성유전학적 연령 예측
Epigenetic Age Prediction of Alzheimer's Disease Patients Using the Aging Clock 원문보기

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노화 시계를 이용한 알츠하이머병 환자의 후성유전학적 연령 예측 Epigenetic Age Prediction of Alzheimer's Disease Patients Using the Aging Clock 원문보기

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노화 시계를 이용한 알츠하이머병 환자의 후성유전학적 연령 예측
Epigenetic Age Prediction of Alzheimer's Disease Patients Using the Aging Clock 원문보기

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