Back

The Alzheimer's disease risk factor APOE4 drives pro-inflammation in human astrocytes via HDAC-dependent repression of TAGLN3

Arnaud, L.; Benech, P.; Greetham, L.; Stephan, D.; Jimenez, A.; Jullien, N.; Garcia-Gonzalez, L.; Tsvetkov, P. O.; Devred, F.; Sancho-Martinez, I.; Belmonte, J. C. I.; Baranger, K.; Rivera, S.; Nivet, E.

2021-04-16 neuroscience
10.1101/2021.04.16.440108 bioRxiv
Show abstract

The Apolipoprotein E4 (APOE4) is the major allelic risk factor for late-onset Alzheimers disease (AD). APOE4 associates with a pro-inflammatory phenotype increasingly considered as critical in AD initiation and progression. Yet, the mechanisms driving an APOE4-dependent neuroinflammation remain unelucidated. Leveraging patient specific human induced Pluripotent Stem Cells (iPSCs) we demonstrate inflammatory chronicity and hyperactivated responses upon cytokines in human APOE4 astrocytes via a novel mechanism. We uncovered that APOE4 represses Transgelin 3 (TAGLN3), a new interacting partner of I{kappa}B, thus increasing the NF-kB activity. The transcriptional repression of TAGLN3 was shown to result from an APOE4-dependent histone deacetylase (HDAC) activity. The functional relevance of TAGLN3 was demonstrated by the attenuation of APOE4-driven neuroinflammation after TAGLN3 supplementation. Importantly, TAGLN3 downregulation was confirmed in the brain of AD patients. Our findings highlight the APOE4-TAGLN3 axis as a new pathogenic pathway that paves the way for the development of therapeutics to prevent maladaptive inflammatory responses in APOE4 carriers, while placing TAGLN3 downregulation as a potential biomarker of AD. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=98 HEIGHT=200 SRC="FIGDIR/small/440108v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1036557org.highwire.dtl.DTLVardef@1f245bdorg.highwire.dtl.DTLVardef@c07c4aorg.highwire.dtl.DTLVardef@1200396_HPS_FORMAT_FIGEXP M_FIG C_FIG

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.