Plasma cell-free RNA profiling of Vietnamese Alzheimer's patients reveals a linkage with chronic inflammation and apoptosis: a pilot study.
Plasma cell-free RNA profiling of Vietnamese Alzheimer's patients reveals a linkage with chronic inflammation and apoptosis: a pilot study.
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DOI：
10.3389/fnmol.2023.1308610
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发表时间：
2023
影响因子：
4.8
通讯作者：
Ha, Huong Thi Thanh
中科院分区：
文献类型：
--
作者：
Cao, Thien Hoang Minh;Le, Anh Phuc Hoang;Tran, Tai Tien;Huynh, Vy Kim;Pham, Bao Hoai;Le, Thao Mai;Nguyen, Quang Lam;Tran, Thang Cong;Tong, Trang Mai;Than, The Ha Ngoc;Nguyen, Tran Tran To;Ha, Huong Thi Thanh
关键词：
循环游离 RNA (cfRNA) 是阿尔茨海默病 (AD) 早期诊断的潜在标志，因为它可以解释基因表达水平，从一开始就可以洞察病理进展。白种人 AD 患者的 cfRNA 概况已得到彻底研究，但尚无在东盟群体中探索 cfRNA 的报道。这项研究探讨了这一差距，希望能够支持 AD 即时诊断的发展。对 20 个越南血浆样本（10 个可能的 AD 样本和 10 个年龄匹配的对照样本）进行了 cfRNA 谱特征分析。 RNA 读数进行差异表达 (DE) 分析。进行加权基因相关网络分析（WGCNA）来识别显着共表达的基因模块。然后将这些模块的表达谱与 AD 状态相关联，以识别相关模块。选择具有最高模块内连接性（模块成员资格）的基因作为中心基因。将差异表达基因的转录本计数与关键 AD 指标（MMSE 和 MTA 评分）相关联，以识别潜在的生物标志物。 136 个基因被确定为显着的 AD 标志（p < 0.05），其中 AD 队列中 52 个基因下调，84 个基因上调。其中45.6%的基因在海马、小脑和大脑皮层中高表达。值得注意的是，所有与慢性炎症相关的标记物均上调，并且所有凋亡标记物均发生显着变化。发现三个共表达模块与阿尔茨海默病状态显着相关（p < 0.05；R2> 0.5）。对这些模块的功能富集分析揭示了与粘着斑、核细胞质转运和导致细胞凋亡的金属离子反应的关联，表明这些通路在 AD 病理学中的潜在参与。发现47个显着的枢纽基因是连通性最高的差异表达基因。六个重要的枢纽基因（CREB1、YTHDC1、IL1RL1、PHACTR2、ANKRD36B、RNF213）被发现与 MTA 和 MMSE 评分显着相关。其他重要的转录本（XRN1、UBB、CHP1、THBS1、S100A9）被发现与炎症和神经元死亡有关。总体而言，我们已经确定了血浆 cf-RNA 中存在差异表达并与炎症和细胞凋亡相关的候选转录本，这可以启动在越南和东盟国家应用 cf-RNA 作为 AD 生物标志物的进一步研究。
Circulating cell-free RNA (cfRNA) is a potential hallmark for early diagnosis of Alzheimer's Disease (AD) as it construes the genetic expression level, giving insights into the pathological progress from the outset. Profiles of cfRNA in Caucasian AD patients have been investigated thoroughly, yet there was no report exploring cfRNAs in the ASEAN groups. This study examined the gap, expecting to support the development of point-of-care AD diagnosis. cfRNA profiles were characterized from 20 Vietnamese plasma samples (10 probable AD and 10 age-matched controls). RNA reads were subjected to differential expression (DE) analysis. Weighted gene correlation network analysis (WGCNA) was performed to identify gene modules that were significantly co-expressed. These modules' expression profiles were then correlated with AD status to identify relevant modules. Genes with the highest intramodular connectivity (module membership) were selected as hub genes. Transcript counts of differentially expressed genes were correlated with key AD measures—MMSE and MTA scores—to identify potential biomarkers. 136 genes were identified as significant AD hallmarks (p < 0.05), with 52 downregulated and 84 upregulated in the AD cohort. 45.6% of these genes are highly expressed in the hippocampus, cerebellum, and cerebral cortex. Notably, all markers related to chronic inflammation were upregulated, and there was a significant shift in all apoptotic markers. Three co-expressed modules were found to be significantly correlated with Alzheimer's status (p < 0.05; R2> 0.5). Functional enrichment analysis on these modules reveals an association with focal adhesion, nucleocytoplasmic transport, and metal ion response leading to apoptosis, suggesting the potential participation of these pathways in AD pathology. 47 significant hub genes were found to be differentially expressed genes with the highest connectivity. Six significant hub genes (CREB1, YTHDC1, IL1RL1, PHACTR2, ANKRD36B, RNF213) were found to be significantly correlated with MTA and MMSE scores. Other significant transcripts (XRN1, UBB, CHP1, THBS1, S100A9) were found to be involved in inflammation and neuronal death. Overall, we have identified candidate transcripts in plasma cf-RNA that are differentially expressed and are implicated in inflammation and apoptosis, which can jumpstart further investigations into applying cf-RNA as an AD biomarker in Vietnam and ASEAN countries.
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影响因子：
2.1
作者：
Bai Z;Stamova B;Xu H;Ander BP;Wang J;Jickling GC;Zhan X;Liu D;Han G;Jin LW;DeCarli C;Lei H;Sharp FR
通讯作者：
Sharp FR
影响因子：
12.7
作者：
Ashton NJ;Pascoal TA;Karikari TK;Benedet AL;Lantero-Rodriguez J;Brinkmalm G;Snellman A;Schöll M;Troakes C;Hye A;Gauthier S;Vanmechelen E;Zetterberg H;Rosa-Neto P;Blennow K
通讯作者：
Blennow K
影响因子：
4.8
作者：
通讯作者：
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影响因子：
4.8
作者：
通讯作者：
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影响因子：
--
作者：
Guttula SV;Allam A;Gumpeny RS
通讯作者：
Gumpeny RS