In the spirit of the popular “get organized” new year’s resolution, scientists at Baylor College of Medicine have discovered a new way to declutter brain proteins for 2023.
Working for the Jan and Dan Duncan Neurological Research Institute, Kim et al. have identified genes in mice that, when shut off, lead to a decrease in the plaque-forming protein tau (2023).
Out of the 20,000 identified human genes, around 6,600 are candidates for gene therapy through non-invasive treatments using small drug compounds. Scientists predict (and really hope) that these “druggable genes” offer potential avenues for treating diseases, including those that manifest late in life.
One terrifying neurodegenerative disease that can come later in life is the taupathology Alzheimer’s Disease. The researchers at Baylor screened the potentially druggable genes for those responsible for tau production and degradation.
The ‘C-terminus of Hsc70-interacting protein’ or CHIP is a helpful enzyme that dooms other proteins for degradation by marking them with a ubiquitin. One of CHIPs targets is the notorious tau. In addition to knocking down the apostrophe “s” at the end of “Alzheimer’s,” researchers here cut the transcription of three genes whose proteins like to rough up CHIP.
The protein from the USP7 gene likes to suppress CHIP activity, thus increasing tau aggregation in neurons. There are also the RNF130 and RNF149 proteins that mark the stalwart CHIP for degradation. Perhaps members of the same functional complex, the former two proteins gang up on CHIP to stabilize the presence of tau.
In adult tauopathy mice, knocking-down these genes rescued the mice from their usual memory deficits. These knockdowns also had less microgliosis and protopathic tau seeding/spreading activities. The next step to decluttering our tau-tangled brains is to identify small molecules that might hinder the expression of these newly identified genes.
Druggable genes that have yet to have drugs specially designed for them can be identified through mathematical models of the resulting protein’s binding site. The number of genes in this group is likely to grow with our knowledge of pharmacological technology and protein modeling. Research has already doubled in the last 16 years.