A unified health algorithm that teaches itself to improve health outcomes for every individual: How far into the future is it?

The single biggest factor driving health outcomes is patient behavior. The CHR Model (County Health Rankings Model) weights socioeconomic factors, lifestyle behaviors, and physical environment factors collectively at 80% in driving impact on health outcomes, to the 20% weight for access to and quality of clinical care. Commercial determinants of health affect everyone today and unhealthy choices worsen pre-existing economic, social, and racial inequities. Yet there is a disproportionate focus on therapeutic intervention to the exclusion of shaping patient behaviors to improve healthcare. If the recent pandemic taught us a critically important lesson, it is the imperative to look beyond clinical care. According to the Centers for Disease Control and Prevention (CDC), long-standing systemic health and social inequities put various groups of people at higher risk of getting sick and dying from COVID-19, including many racial and ethnic minority groups. The virus was simply more efficient in detecting such vulnerabilities than the guardians of these physiologies. These insights from the pandemic come at the heel of a confluence of three major accelerants that may radically reshape our approaches to hot-spotting vulnerabilities and managing them before they manifest in a derangement or disease. They are the recent strides in behavioral economics and behavior science; advances in remote monitoring and personal health technologies; and developments in artificial intelligence and data sciences. These accelerants allow us to imagine a previously impossible vision-we can now build and maintain a unified health algorithm for every individual that can dynamically track the two interdependent streams of risk, clinical and behavioral.

Alternate exon insertion controls selective ubiquitination and degradation of different AUF1 protein isoforms.

The A+U-rich element (ARE) in the 3' non-coding region (3' NCR) of short-lived cytokine mRNAs binds several regulatory proteins, including hnRNP D/AUF1, which comprises four isoforms of 37, 40, 42 and 45 kDa. ARE-mRNA degradation involves ubiquitin-proteasome activity, and one or more AUF1 proteins are thought to be ubiquitinated. Here we have characterized the mechanism for differential ubiquitination and degradation of the different AUF1 protein isoforms. We demonstrate in an in vitro ubiquitination system that the p37, followed by the p40 protein, are strongly ubiquitinated, whereas the p42 and p45 forms are not. Over expression in cells of enzymes that control the ubiquitin cycle were found to control p37 and p40 AUF1 protein levels through ubiquitination and proteasome activity, but not p42 and p45 forms. The p42 and p45 AUF1 proteins share a C-terminal exon 7 that is not found in the p37/p40 isoforms. Our studies show that exon 7 blocks ubiquitination and rapid degradation of AUF1 proteins, whereas its deletion permits ubiquitination to occur and promotes rapid turnover of AUF1 proteins. Thus, the stabilities of AUF1 isoforms are differentially controlled by insertion of an alternate exon that regulates ubiquitin targeting activity.

Ubiquitin-dependent mechanism regulates rapid turnover of AU-rich cytokine mRNAs.

An AU rich element (ARE) in the 3' noncoding region promotes the rapid degradation of mammalian cytokine and proto-oncogene mRNAs, such as tumor necrosis factor-alpha, granulocyte-macrophage colony-stimulating factor (GM-CSF) and c-fos. Destabilization of ARE-mRNAs involves the association of ARE-binding proteins tristetraprolin or AUF1 and proteasome activity, of which the latter has not been characterized. Here, we show that the stability of a model short-lived mRNA containing the GM-CSF ARE was regulated by the level of ubiquitin-conjugating activity in the cell, which links ARE-mRNA decay to proteasome activity. Increased expression of a cytokine-inducible deubiquitinating protein (DUB) that impairs addition of ubiquitin to proteins fully blocked ARE-mRNA decay, whereas increased expression of a DUB that promotes ubiquitin addition to proteins strongly accelerated ARE-mRNA decay. ARE-mRNA turnover was found to be activated by the ubiquitin-addition reaction and blocked by the ubiquitin-removal reaction. Saturation of the ARE-mRNA decay machinery by high levels of ARE-mRNA, which is well established but not understood, was found to be relieved by increased expression of a DUB that promotes ubiquitin addition to proteins. Finally, inhibition of proteasome activity also blocked accelerated ARE-mRNA decay that is mediated by increased ubiquitin recycling. These results demonstrate that both ubiquitinating activity and proteasome activity are essential for rapid turnover of a model cytokine ARE-mRNA containing the GM-CSF ARE.