Alzheimer's disease (AD) is the most common cause of dementia, characterized by memory loss, cognitive decline, personality changes, and various neurological symptoms. The role of blood-brain barrier (BBB) injury, extracellular matrix (ECM) abnormalities, and oligodendrocytes (ODCs) dysfunction in AD has gained increasing attention, yet the detailed pathogenesis remains elusive. This study integrates single-cell sequencing of AD patients' cerebrovascular system with a genome-wide association analysis. It aims to elucidate the associations and potential mechanisms behind pericytes injury, ECM disorder, and ODCs dysfunction in AD pathogenesis. Finally, we identified that abnormalities in the pericyte PI3K-AKT-FOXO signaling pathway may be involved in the pathogenic process of AD. This comprehensive approach sheds new light on the complex etiology of AD and opens avenues for advanced research into its pathogenesis and therapeutic strategies.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11385648 | PMC |
http://dx.doi.org/10.1038/s41598-024-71888-0 | DOI Listing |
Background: Alzheimer's Disease and Related dementias (ADRD) are disproportionately underdiagnosed, misdiagnosed, and undertreated in Latino/a/e/x populations living in the U.S. Latino/a/e/x families also experience low access to ADRD caregiver support services and high levels of depression.
View Article and Find Full Text PDFBackground: The associations of PM mass and various adverse health outcomes have been widely investigated. However, fewer studies focused on the potential health impacts of PM components, especially for dementia and Alzheimer's diseases (AD).
Methods: We constructed a nationwide population-based open cohort study among Medicare beneficiaries aged 65 or older during 2000-2018.
Motivation: This study aims to develop an AI-driven framework that leverages large language models (LLMs) to simulate scientific reasoning and peer review to predict efficacious combinatorial therapy when data-driven prediction is infeasible.
Results: Our proposed framework achieved a significantly higher accuracy (0.74) than traditional knowledge-based prediction (0.
Transcriptome- and proteome-wide association studies (TWAS/PWAS) have proven successful in prioritizing genes and proteins whose genetically regulated expression modulates disease risk, but they ignore potential co-expression and interaction effects. To address this limitation, we introduce the co-expression-wide association study (COWAS) method, which can identify pairs of genes or proteins whose genetically regulated co-expression is associated with complex traits. COWAS first trains models to predict expression and co-expression conditional on genetic variation, and then tests for association between imputed co-expression and the trait of interest while also accounting for direct effects from each exposure.
View Article and Find Full Text PDFGenetic risk variants for common diseases are predominantly located in non-coding regulatory regions and modulate gene expression. Although bulk tissue studies have elucidated shared mechanisms of regulatory and disease-associated genetics, the cellular specificity of these mechanisms remains largely unexplored. This study presents a comprehensive single-nucleus multi-ancestry atlas of genetic regulation of gene expression in the human prefrontal cortex, comprising 5.
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