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Laroche, V.

Publications and source records attributed to Laroche, V..

2 recordsLinked to original sources

Systemic infections alter cortical transcriptional signatures in Alzheimer's disease

Alzheimers disease (AD) is characterized by neuroinflammation, yet the impact of concurrent systemic infections on the AD brain remains poorly understood. We investigated the molecular mechanisms underlying the central nervous system response to systemic infections in AD by analyzing RNA sequencing data generated in the prefrontal cortex from 202 post-mortem donors (113 AD, 89 controls), where we stratified by the presence of a respiratory infection at the time of death. We identified 763 significantly differentially expressed genes (DEGs) between AD and controls without infection, which were enriched for oxidative phosphorylation and neurodegenerative pathways. In contrast, 122 DEGs distinguished AD from controls during infection, with 57 genes uniquely altered in AD in the presence of infection, including MAPK4, VAV3, and POU3F4, implicating infection-dependent mechanisms of vascular and immune regulation. Pathway activity analysis revealed that infection in AD suppresses some immune and vascular pathways, while enhancing transcriptional and developmental programs. Weighted gene co-expression network analysis uncovered three key modules: one module strongly associated with AD, enriched for aging and signal transduction; one module linked to both AD and infection, highlighting cytoskeletal remodelling and host-pathogen interactions; and one module specific to infection, enriched in astrocytes, pericytes, and endothelial cells, implicating blood-brain barrier dysfunction. These findings suggest that systemic respiratory infections reshape transcriptional programs in the AD brain, dampening immune effector pathways and engaging vascular and host-pathogen processes in blood-brain-barrier-associated cell types. Our results highlight the complex interplay between systemic infection, neuroinflammation, and vascular responses in AD.

neuroscience↗

A Cell Type Enrichment Analysis Tool for Brain DNA Methylation Data (CEAM)

DNA methylation signatures are highly cell type-specific, yet most epigenome-wide association studies (EWAS) are performed on bulk tissue, potentially obscuring critical cell type-specific patterns. Existing computational tools for detecting cell type-specific DNAm changes are often limited by the accuracy of cell type deconvolution algorithms. Here, we introduce CEAM (Cell-type Enrichment Analysis for Methylation), a robust and interpretable framework for cell type enrichment analysis in DNA methylation data. CEAM applies over-representation analysis with cell type-specific CpG panels from Illumina EPIC arrays derived from nuclei-sorted cortical post-mortem brains from neurologically healthy aged individuals. The constructed CpG panels were systematically evaluated using both simulated datasets and published EWAS results from Alzheimers disease, Lewy body disease, and multiple sclerosis. CEAM demonstrated resilience to shifts in cell type composition, a common confounder in EWAS, and remained accurate across a wide range of differentially methylated positions, underscoring its flexibility. Application to existing EWAS findings generated in neurodegenerative diseases revealed enrichment patterns concordant with established disease biology, confirming CEAMs biological relevance. The workflow is publicly available as an interactive Shiny app (https://um-dementia-systems-biology.shinyapps.io/CEAM/) enabling rapid, interpretable analysis of cell type-specific DNAm changes from bulk EWAS.

genomics↗