Typical differential single-nucleus gene expression (snRNA-seq) analyses in Alzheimer's disease (AD) provide fixed snapshots of cellular alterations, making the accurate detection of temporal cell changes challenging. To characterize the dynamic cellular and transcriptomic differences in AD neuropathology, we apply the novel concept of RNA velocity to the study of single-nucleus RNA from the cortex of 60 subjects with varied levels of AD pathology. RNA velocity captures the rate of change of gene expression by comparing intronic and exonic sequence counts. We performed differential analyses to find the significant genes driving both cell type-specific RNA velocity and expression differences in AD, extensively compared these two transcriptomic metrics, and clarified their associations with multiple neuropathologic traits. The results were cross-validated in an independent dataset. Comparison of AD pathology-associated RNA velocity with parallel gene expression differences reveals sets of genes and molecular pathways that underlie the dynamic and static regimes of cell type-specific dysregulations underlying the disease. Differential RNA velocity and its linked progressive neuropathology point to significant dysregulations in synaptic organization and cell development across cell types. Notably, most of the genes underlying this synaptic dysregulation showed increased RNA velocity in AD subjects compared to controls. Accelerated cell changes were also observed in the AD subjects, suggesting that the precocious depletion of precursor cell pools might be associated with neurodegeneration. Overall, this study uncovers active molecular drivers of the spatiotemporal alterations in AD and offers novel insights towards gene- and cell-centric therapeutic strategies accounting for dynamic cell perturbations and synaptic disruptions.
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http://dx.doi.org/10.1038/s41598-024-57918-x | DOI Listing |
RNA velocities and generalizations emerge as powerful approaches for extracting time-resolved information from high-throughput snapshot single-cell data. Yet, several inherent limitations restrict applying the approaches to genes not suitable for RNA velocity inference due to complex transcriptional dynamics, low expression, or lacking splicing dynamics, or data of non-transcriptomic modality. Here, we present GraphVelo, a graph-based machine learning procedure that uses as input the RNA velocities inferred from existing methods and infers velocity vectors lying in the tangent space of the low-dimensional manifold formed by the single cell data.
View Article and Find Full Text PDFEur J Pharmacol
January 2025
Department of Basic Medicine, Institute of Respiratory Diseases Xiamen Medical College, Xiamen Medical College, Xiamen, Fujian 361023, P. R. China; State Key Laboratory of Frigid Zone Cardiovascular Diseases (SKLFZCD), Harbin Medical University, Harbin, Heilongjiang 150081, P. R. China. Electronic address:
ITFG2 is an intracellular protein known to modulate the immune response of T-cells. Our previous investigation revealed that ITFG2 specifically targets ATP5b to regulate ATP energy metabolism and maintain mitochondrial function, thereby protecting the heart from ischemic injury. However, the role of ITFG2 in ischemic ventricular arrhythmias and its underlying mechanisms have not been previously reported.
View Article and Find Full Text PDFInt J Pharm
January 2025
Université Paris-Saclay, Inserm, Maladies et hormones du système nerveux, 94276 Le Kremlin-Bicêtre, France. Electronic address:
Small interfering RNA (siRNA) has shown promising results for the treatment of Charcot-Marie-Tooth disease 1A (CMT1A) caused by overexpression of peripheral myelin protein (PMP22), leading to myelin dysfunction and axonal damage. Recently, we developed siRNA PMP22-squalene (SQ) nanoparticles (NPs) for intravenous use. Three consecutive injections of siRNA PMP22-SQ NPs at a cumulative dose of 1.
View Article and Find Full Text PDFPLoS One
January 2025
Bio Bureau Biotechnology, Rio de Janeiro, Rio de Janeiro, Brazil.
Monitoring biodiversity on a large scale, such as in hydropower reservoirs, poses scientific challenges. Conventional methods such as passive fishing gear are prone to various biases, while the utilization of environmental DNA (eDNA) metabarcoding has been restricted. Most eDNA studies have primarily focused on replicating results from traditional methods, which themselves have limitations regarding representativeness and bias.
View Article and Find Full Text PDFAm J Clin Nutr
January 2025
Department of Nutrition, Center for Big Data and Population Health of IHM, The Second Affiliated Hospital of Anhui Medical University, School of Public Health, Anhui Medical University, Hefei, China. Electronic address:
Background: Hippuric acid (HA), a host-microbe co-metabolite, normally derives from gut microbial catabolism of dietary polyphenols.
Objectives: We investigated the potential interplay between dietary polyphenols and gut microbiota on circulating HA levels, and examined the associations between serum concentrations of HA and cardiometabolic risk markers.
Methods: In a 1-year cohort of 754 community-dwelling adults, serum HA and its precursor [benzoic acid (BA)] and fecal microbiota were assayed using liquid chromatography-tandem mass spectrometry and 16S ribosomal RNA sequencing, respectively.
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