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Dombroski, B.

Publications and source records attributed to Dombroski, B..

2 recordsLinked to original sources

TSC1 loss-of-function increases risk for tauopathy by inducing tau acetylation and preventing autophagy-mediated tau clearance

Age-associated neurodegenerative disorders demonstrating tau-laden intracellular inclusions, including Alzheimers disease (AD), frontotemporal lobar degeneration (FTLD) and progressive supranuclear palsy (PSP), are collectively known as tauopathies. The vast majority of human tauopathies accumulate non-mutant tau rather than mutant forms of the protein, yet cell and animal models for non-mutant tauopathies are lacking. We previously linked a monoallelic mutation in the TSC1 gene to tau accumulation and FTLD. Now, we have identified new variants in TSC1 that predisposed to other tauopathies such as AD and PSP. These new TSC1 risk variants significantly decreased the half-life of TSC1/hamartin in vitro. Cellular and murine models of TSC1 haploinsufficiency (TSC1+/-) accumulated tau protein that exhibited aberrant acetylation on six lysine residues. Tau acetylation hindered its lysosomal degradation via chaperone-mediated autophagy leading to neuronal tau accumulation. Enhanced tau acetylation in TSC1+/- models was achieved through both an increase in p300 acetyltransferase activity and a decrease in SIRT1 deacetylase levels. Pharmacological modulation of either enzyme restored tau levels. Together, these studies substantiate TSC1 as a novel tauopathy risk gene and advance TSC1 haploinsufficiency as a new genetic model for tauopathy. In addition, these results promote acetylated tau as a rational target for diagnostic and therapeutic modalities in multiple tauopathies.

neuroscience↗

Inferring the molecular mechanisms of noncoding Alzheimer’s disease-associated genetic variants

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSWe set out to characterize the causal variants, regulatory mechanisms, tissue contexts, and target genes underlying noncoding late-onset Alzheimers Disease (LOAD)-associated genetic signals.\n\nMETHODSWe applied our INFERNO method to the IGAP genome-wide association study (GWAS) data, annotating all potentially causal variants with tissue-specific regulatory activity. Bayesian co-localization analysis of GWAS summary statistics and eQTL data was performed to identify tissue-specific target genes.\n\nRESULTSINFERNO identified enhancer dysregulation in all 19 tag regions analyzed, significant enrichments of enhancer overlaps in the immune-related blood category, and co-localized eQTL signals overlapping enhancers from the matching tissue class in ten regions (ABCA7, BIN1, CASS4, CD2AP, CD33, CELF1, CLU, EPHA1, FERMT2, ZCWPW1). We validated the allele-specific effects of several variants on enhancer function using luciferase expression assays.\n\nDISCUSSIONIntegrating functional genomics with GWAS signals yielded insights into the regulatory mechanisms, tissue contexts, and genes affected by noncoding genetic variation associated with LOAD risk.

bioinformatics↗