The AGM CSF miRNome is substantially conserved with the human miRNome but also contains 3′-terminal isomiRs and unclassified miRNA candidates and reveals challenges related to species-specific sequence variation and reduced cross-platform concordance for isomiRs.
Abstract
Background The African green monkey (AGM) is increasingly used as a model for early-stage Alzheimer’s disease (AD), with cerebrospinal fluid (CSF) targeted for biomarker discovery and longitudinal disease monitoring of shifts in the central nervous system. MicroRNAs (miRNAs) are particularly informative indicators of early neuropathological change. Despite the complementary value of an early-stage disease model and a molecular marker capable of capturing early change, the miRNA composition (miRNome) of AGM remains undefined. We established the AGM CSF miRNome from antemortem samples using miRNA sequencing and a qRT-PCR-based array. We also developed a hierarchical annotation pipeline to classify miRNAs as either family-conserved or unclassified and to assess sequence alignment across humans and other species. Results We used untargeted miRNA sequencing to characterize the AGM CSF miRNome and identified 205 miRNAs that could be classified into three family-conserved categories: canonical, noncanonical, and 3′-terminal variants. Of these, 150 were also detected using a human-targeted qRT-PCR array, providing independent support for the sequence-derived miRNome. Sequencing abundance and qRT-PCR array Ct values showed significant cross-platform concordance overall, although concordance was lower for 3′-terminal isomiRs than for canonical miRNAs. Comparison with human GTEx tissue-expression data indicated that several human homologs of AGM CSF miRNAs exhibited brain-preferential expression. Notably, predicted targets of many of these miRNAs were enriched for pathways implicated in neurodegenerative disease. Finally, we identified 20 unclassified candidates that could not be assigned to established miRNA families, two of which we propose as putatively novel miRNAs. Conclusion The AGM CSF miRNome is substantially conserved with the human miRNome but also contains 3′-terminal isomiRs and unclassified miRNA candidates. AGM CSF contains miRNAs homologous to human miRNAs associated with AD and other neuropathologies, highlighting the translational potential of this model. However, our study also reveals challenges related to species-specific sequence variation and reduced cross-platform concordance for isomiRs. Thus, comparative studies will be needed to validate the functional and biomarker relevance of these miRNAs across species. More generally, this initial miRNome provides a reference resource for future studies of miRNAs in AGM across disease-related, physiological, experimental, and evolutionary contexts.
Background: Frontotemporal dementia (FTD) is a neurodegenerative disease that shares numerous clinical features with other forms of dementia. In this context, non-coding RNAs, specifically microRNAs (miRNAs), represent a promising tool for differential diagnosis. Since these miRNAs can be isolated from circulating extracellular vesicles (EVs) in peripheral blood, they provide a direct insight into FTD-specific molecular processes. Consequently, while EV-contained miRNAs hold potential as disease-specific biomarkers, investigating their relative target genes can help elucidate their precise functional roles. Aim: This work aimed to identify a specific miRNA signature to better characterize FTD pathology. Methods: Building on a previous Next-Generation Sequencing (NGS) analysis, three candidate miRNAs were selected for validation in both EVs and peripheral blood mononuclear cells (PBMCs) of FTD patients. Subsequently, the predicted target genes of two of these miRNAs were validated in PBMCs to assess their expression levels. Results: Our findings revealed that miR-365a-3p and miR-212 were significantly down-regulated in FTD. Conclusions: Together with their target genes, these miRNAs are involved in cell cycle and apoptotic pathways, suggesting a potential role in the pathological mechanisms of the disease.
Evelyne Minucchi, F. Dragoni, R. Di Gerlando et al.· Genes· 0 citations
Abstract Dementia is a syndrome caused by various diseases including Alzheimer's disease (AD) and frontotemporal dementia (FTD) with an estimated global prevalence of 60 million individuals. Recently, therapeutic development in the dementia field has accelerated, with the introduction of monoclonal antibody therapeutics such as Lecanemab and Donanemab. However, AD and FTD patients are still either diagnosed too late to benefit from available therapies or are misdiagnosed due to the clinical overlap between dementia subgroups making therapeutic intervention challenging. This highlights a real need to improve early diagnostic tools of neurodegenerative disease (ND) biomarkers. A potential source of such biomarkers come from small extracellular vesicles (sEVs), groups of cell-derived, lipid-bound assemblies with the capability to cross the blood–brain barrier (BBB) and known to carry pathogenic proteins associated with AD and FTD. A known cargo of sEVs is microRNA (miRNA), regulatory molecules that post-transcriptionally silence gene expression including transcripts of autophagic systems, processes which dysfunction in dementia-causing diseases leading to toxic aggregate build-up, causing neurodegeneration. The targeting of functional machineries in macroautophagy (MA) and chaperone-mediated autophagy (CMA) by different miRNA may vary between AD and FTD mutations, leading to potential biomarkers of disease being highlighted. Through isolating sEVs from the frontal cortex of post-mortem brain tissue of AD, FTD-MAPT, FTD-C9orf72, FTD-GRN and no-disease control patients (Manchester Brain Bank), miRNA cargoes were analysed and compared using real-time quantitative PCR (RT-qPCR). Seven autophagy-associated miRNA candidates (MA: miR-124-3p, miR-30a-5p, miR-128-3p; and CMA: miR-224-5p, miR-373-5p, miR-106a-3p and miR-26b-5p) were tested to identify dementia sub-group variations, used alongside small RNA-sequencing to explore broader miRNA variation within sEV populations. Of the miRNA tested miR-224-5p (P = 1.76 × 10−5) and miR-106a-3p (P = 0.033) showed significant group differences, and further significant pairwise comparison differences [miR-224-5p: AD fold change (FC) = 4.29, MAPT FC = 7.62; miR-106a-5p: AD FC = 5.59] when compared with no disease controls and other dementia subgroups, potentially showing initial diagnostic and differentiating potential. Small RNA-sequencing results revealed 8 AD, 2 FTD-GRN, 52 FTD-MAPT and 12 FTD-C9orf72 differentially expressed sEV-miRNAs when compared with no disease controls. Further direct comparisons between AD versus FTD mutation-derived sEV cargoes, and even FTD mutation versus FTD mutation-derived sEV cargoes, identified additional miRNA with differentiating capabilities. These findings demonstrate sEV-derived miRNA signatures vary across dementia sub-types and suggest potential roles of sEV cargoes in both disease diagnostics and identifying drivers of ND, such as autophagic impairments and signalling pathways.
Joseph Morgan, Toby Aarons, Arijit Mukhopadhyay et al.· Brain Communications· 0 citations
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the leading cause of late-life dementia. As pathology spreads through the brain, affected individuals experience devastating cognitive decline, linguistic impairments, mood changes, and behavioral issues. Developing effective disease-modifying therapies remains a persistent challenge because diagnosis typically occurs at a late stage, long after extensive, irreversible neuronal and synaptic loss has taken place. To overcome these diagnostic and therapeutic bottlenecks, attention has shifted to microRNAs (miRNAs), the most prominent class of abundant, small non-coding RNAs that post-transcriptionally regulate eukaryotic gene expression networks. This review delineates the critical functions of specific miRNAs in orchestrating the three primary pathological pillars of AD: amyloid-β (Aβ) buildup, chronic neuroinflammation, and systemic oxidative stress. Unraveling these complex epigenetic interactions contributes fundamentally to understanding AD’s pathology, offering highly sensitive avenues for early blood-based biomarker discovery and highlighting promising targets for innovative, RNA-targeted clinical therapeutics.
Manivannan Subramanian, Aditi Singh, Amit Singh· Journal of Dementia and Alzh...· 0 citations
Alzheimer’s disease (AD) and HIV-associated neurocognitive disorder (HAND) share progressive cognitive decline. Their common molecular mechanisms remain poorly understood. Current therapeutic approaches lack effective biomarkers for early diagnosis and intervention. We integrated transcriptomic profiles from multiple independent cohorts across brain tissues and blood. We systematically evaluated diagnostic performance using machine learning algorithms including Random Forest, Support Vector Machine, and XGBoost. Notably, FOXO3 emerged as the top cross-disease biomarker. FOXO3 achieved diagnostic accuracy in AD temporal cortex (area under the curve [AUC] = 0.922, 95% CI: 0.885–0.959). FOXO3 showed diagnostic performance in HAND frontal cortex (AUC = 0.771, 95% CI: 0.724–0.818). FOXO3 expression positively correlated with APP (R = 0.558). FOXO3 expression negatively correlated with MAPT (R = −0.690) and SORL1 (R = −0.856). ACE showed strong positive correlation with FOXO3 (R = 0.685), suggesting vascular involvement. STAT3 and ZNF341 were identified from 21 transcription factor candidates. STAT3 ranked first in HAND integrated cohort (n = 107, AUC = 0.759). STAT3 may function as an inflammatory mediator through JAK-STAT signaling. ZNF341 showed strongest transcriptional association with disease status (β = 5.09 in AD, β = 4.85 in HAND). The two-gene panel (FOXO3-ZNF341) achieved diagnostic accuracy in blood samples (AUC = 0.764, n = 329). This performance approaches clinical utility thresholds. Blood-based detection offers non-invasive diagnostic potential. Saturation analysis identified three molecules as optimal panel size. Marginal AUC gains declined below 0.02 beyond this threshold. FOXO3, STAT3, and ZNF341 showed stable selection frequency (97%, 65%, and 100%, respectively). PI3K-Akt and FoxO signaling pathways were enriched, which are known to regulate apoptosis and cell survival. Taken together, these computational findings indicate FOXO3 transcriptional regulatory activity in neurodegeneration. The three-molecule panel represents candidate blood-based diagnostic biomarkers. These candidate biomarkers warrant further investigation in independent clinical cohorts.
