Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer's disease.
Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer's disease.
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DOI：
10.1371/journal.pone.0248375
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发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
Radhakrishna U
中科院分区：
文献类型：
--
作者：
Bahado-Singh RO;Vishweswaraiah S;Aydas B;Yilmaz A;Metpally RP;Carey DJ;Crist RC;Berrettini WH;Wilson GD;Imam K;Maddens M;Bisgin H;Graham SF;Radhakrishna U
我们评估了白细胞表观基因组生物标志物用于阿尔茨海默病（AD）检测的效用，并阐明了其分子发病机制。使用Infinium MethylationEPIC BeadChip阵列对24名迟发性AD（LOAD）和24名认知健康受试者进行全基因组DNA甲基化分析。使用六种人工智能（AI）方法分析数据，包括深度学习（DL），然后使用不相容性途径分析（IPA）进行AD预测。与对照组相比，我们在AD患者的171个不同基因中鉴定了152个显著（FDR p<0.05）差异甲基化的基因内CpG。所有AI平台使用283，143个基因内和244，246个基因间/基因外CpG准确预测了AUC ≥0.93的AD。使用基因内CpG，DL的AUC = 0.99，灵敏度和特异性均为97%。使用基因间/基因外CpG位点也实现了高AD预测（DL显著性值为AUC = 0.99，灵敏度和特异性为97%）。表观遗传学改变的基因包括CR 1 L和CTSV（大脑皮质异常形态），S1 PR 1（CNS炎症）和LTB 4 R（炎症反应）。这些基因以前与AD和痴呆症有关。差异甲基化的基因CTSV和PRMT 5（心室肥大和扩张）与心血管疾病相关，并且考虑到脑血流受损、心血管疾病和AD之间的已知关联而引起关注。我们报告了一种新的，微创的方法，使用外周血白细胞表观基因组学，AI分析检测AD和阐明其发病机制。
We evaluated the utility of leucocyte epigenomic-biomarkers for Alzheimer’s Disease (AD) detection and elucidates its molecular pathogeneses. Genome-wide DNA methylation analysis was performed using the Infinium MethylationEPIC BeadChip array in 24 late-onset AD (LOAD) and 24 cognitively healthy subjects. Data were analyzed using six Artificial Intelligence (AI) methodologies including Deep Learning (DL) followed by Ingenuity Pathway Analysis (IPA) was used for AD prediction. We identified 152 significantly (FDR p<0.05) differentially methylated intragenic CpGs in 171 distinct genes in AD patients compared to controls. All AI platforms accurately predicted AD with AUCs ≥0.93 using 283,143 intragenic and 244,246 intergenic/extragenic CpGs. DL had an AUC = 0.99 using intragenic CpGs, with both sensitivity and specificity being 97%. High AD prediction was also achieved using intergenic/extragenic CpG sites (DL significance value being AUC = 0.99 with 97% sensitivity and specificity). Epigenetically altered genes included CR1L & CTSV (abnormal morphology of cerebral cortex), S1PR1 (CNS inflammation), and LTB4R (inflammatory response). These genes have been previously linked with AD and dementia. The differentially methylated genes CTSV & PRMT5 (ventricular hypertrophy and dilation) are linked to cardiovascular disease and of interest given the known association between impaired cerebral blood flow, cardiovascular disease, and AD. We report a novel, minimally invasive approach using peripheral blood leucocyte epigenomics, and AI analysis to detect AD and elucidate its pathogenesis.
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影响因子：
10.6
作者：
Bazan NG
通讯作者：
Bazan NG
DOI：
10.1186/1478-7547-1-8
发表时间：
2003-12-19
期刊：
Cost effectiveness and resource allocation : C/E
影响因子：
--
作者：
Hutubessy, Raymond;Chisholm, Dan;Edejer, Tessa Tan-Torres
通讯作者：
Edejer, Tessa Tan-Torres
影响因子：
3.7
作者：
Bahado-Singh, Ray Oliver;Yilmaz, Ali;Graham, Stewart F.
通讯作者：
Graham, Stewart F.
影响因子：
14
作者：
通讯作者：
--
影响因子：
2.9
作者：
Bahado-Singh, Ray O.;Vishweswaraiah, Sangeetha;Radhakrishna, Uppala
通讯作者：
Radhakrishna, Uppala