원문정보
Epigenetic Age Prediction of Alzheimer's Disease Patients Using the Aging Clock
초록
영어
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.
목차
1. 서론
2. 재료 및 방법
2.1. 데이터세트 수집
2.2 데이터 전처리
2.3 후성유전학적 연령 계산
2.4 후성유전학적 연령 가속 계산
2.5 Differential Methylation Position Analysis
2.6 Pathway Analysis
2.7 통계 분석 및 데이터 시각화
3. 결과 및 고찰
3.1 샘플 특성
3.2 해마 조직의 후성유전학적 연령
3.3 내후각피질 조직의 후성유전학적 연령
3.4 후성유전학적 연령 가속도
3.5 DMPA
3.6 Pathway analysis
4. 결론
5. 참고문헌
