Coronin1A regulates the trafficking of alpha synuclein in microglia.

Microglia respond to cytotoxic protein aggregates associated with the progression of neurodegenerative disease. Pathological protein aggregates activate the microglial NLRP3 inflammasome resulting in proinflammatory signaling, secretion, and potentially pyroptotic cell death. We characterized mixed sex primary mouse microglia exposed to microbial stressors and alpha synuclein preformed fibrils (αsyn PFFs) to identify cellular mechanisms related to Parkinson's disease.

Inhibiting the Cholesterol Storage Enzyme ACAT1/SOAT1 in Aging Apolipoprotein E4 Mice Alters Their Brains' Inflammatory Profiles.

Aging and apolipoprotein E4 () are the two most significant risk factors for late-onset Alzheimer's disease (LOAD). Compared to , disrupts cholesterol homeostasis, increases cholesteryl esters (CEs), and exacerbates neuroinflammation in brain cells, including microglia. Targeting CEs and neuroinflammation could be a novel strategy to ameliorate -dependent phenotypes.

The association of GNB5 with Alzheimer disease revealed by genomic analysis restricted to variants impacting gene function.

Disease-associated variants identified from genome-wide association studies (GWASs) frequently map to non-coding areas of the genome such as introns and intergenic regions. An exclusive reliance on gene-agnostic methods of genomic investigation could limit the identification of relevant genes associated with polygenic diseases such as Alzheimer disease (AD). To overcome such potential restriction, we developed a gene-constrained analytical method that considers only moderate- and high-risk variants that affect gene coding sequences.

Ancestry-specific high-risk gene variant profiling unmasks diabetes-associated genes.

How ancestry-associated genetic variance affects disparities in the risk of polygenic diseases and influences the identification of disease-associated genes warrants a deeper understanding. We hypothesized that the discovery of genes associated with polygenic diseases may be limited by the overreliance on single-nucleotide polymorphism (SNP)-based genomic investigation, as most significant variants identified in genome-wide SNP association studies map to introns and intergenic regions of the genome. To overcome such potential limitations, we developed a gene-constrained, function-based analytical method centered on high-risk variants (hrV) that encode frameshifts, stopgains or splice site disruption.