Xin Ruomin, Kim Elizabeth, Li Wei Tse, Wang-Rodriguez Jessica, Ongkeko Weg M
Department of Otolaryngology-Head and Neck Surgery, University of California, La Jolla, San Diego, CA 92093, USA.
Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA.
Biomolecules. 2025 Jun 3;15(6):806. doi: 10.3390/biom15060806.
Alzheimer's disease (AD) is a leading cause of dementia worldwide. As current diagnostic approaches remain limited in sensitivity and accessibility, there is a critical need for novel, non-invasive biomarkers aiding early detection. Non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs), PIWI-interacting RNAs (piRNAs), and small nucleolar RNAs (snoRNAs), have emerged as promising candidates due to their regulatory roles in gene expression and association with diseases. In this study, we systematically profiled ncRNA expression from RNA sequencing data of 48 AD and 22 control blood tissue samples, aiming to evaluate their utility as biomarkers for AD classification. Differential expression analysis revealed widespread dysregulation of lncRNAs and piRNAs, with over 5000 lncRNAs and nearly 1000 piRNAs significantly upregulated in AD. Weighted gene co-expression network analysis (WGCNA) identified multiple ncRNA modules associated with the AD phenotype. Using supervised machine learning approaches, we evaluated the diagnostic potential of ncRNA expression profiles, including single-gene, multi-gene, and module-level models. Random Forest models trained on individual genes identified 121 ncRNAs with AUROC > 0.8. Feature importance analysis emphasized ncRNAs such as lnc-MYEF2-3, lnc-PRKACB2, and HBII-115 as major contributors to diagnostic accuracy. These findings support the potential of ncRNA signatures as reliable and non-invasive biomarkers for AD diagnosis.
阿尔茨海默病（AD）是全球痴呆症的主要病因。由于目前的诊断方法在敏感性和可及性方面仍然有限，因此迫切需要新的非侵入性生物标志物来辅助早期检测。非编码RNA（ncRNA），包括长链非编码RNA（lncRNA）、PIWI相互作用RNA（piRNA）和小核仁RNA（snoRNA），因其在基因表达中的调控作用以及与疾病的关联，已成为有前景的候选生物标志物。在本研究中，我们从48例AD和22例对照血液组织样本的RNA测序数据中系统地分析了ncRNA表达，旨在评估它们作为AD分类生物标志物的效用。差异表达分析显示lncRNA和piRNA广泛失调，超过5000种lncRNA和近1000种piRNA在AD中显著上调。加权基因共表达网络分析（WGCNA）确定了多个与AD表型相关的ncRNA模块。使用监督机器学习方法，我们评估了ncRNA表达谱的诊断潜力，包括单基因、多基因和模块水平模型。基于单个基因训练的随机森林模型识别出121种AUROC>0.8的ncRNA。特征重要性分析强调lnc-MYEF2-3、lnc-PRKACB2和HBII-115等ncRNA是诊断准确性的主要贡献者。这些发现支持了ncRNA特征作为AD诊断可靠且非侵入性生物标志物的潜力。
