Drilling for Insight: Forecasting Phenotype from Genotype

Individualized management of genetic diversity in Niemann-Pick C1 through modulation of the Hsp70 chaperone system

Genetic diversity provides a rich repository for understanding the role of proteostasis in the management of the protein fold in human biology. Failure in proteostasis can trigger multiple disease states, affecting both human health and lifespan. Niemann-Pick C1 (NPC1) disease is a rare genetic disorder triggered by mutations in NPC1, a multi-spanning transmembrane protein that is trafficked through the exocytic pathway to late endosomes (LE) and lysosomes (Ly) (LE/Ly) to globally manage cholesterol homeostasis. Defects triggered by >300 NPC1 variants found in the human population inhibit export of NPC1 protein from the endoplasmic reticulum (ER) and/or function in downstream LE/Ly, leading to cholesterol accumulation and onset of neurodegeneration in childhood. We now show that the allosteric inhibitor JG98, that targets the cytosolic Hsp70 chaperone/co-chaperone complex, can significantly improve the trafficking and post-ER protein level of diverse NPC1 variants. Using a new approach to model genetic diversity in human disease, referred to as variation spatial profiling, we show quantitatively how JG98 alters the Hsp70 chaperone/co-chaperone system to adjust the spatial covariance (SCV) tolerance and set-points on an amino acid residue-by-residue basis in NPC1 to differentially regulate variant trafficking, stability, and cholesterol homeostasis, results consistent with the role of BCL2-associated athanogene family co-chaperones in managing the folding status of NPC1 variants. We propose that targeting the cytosolic Hsp70 system by allosteric regulation of its chaperone/co-chaperone based client relationships can be used to adjust the SCV tolerance of proteostasis buffering capacity to provide an approach to mitigate systemic and neurological disease in the NPC1 population.

Quantitating the epigenetic transformation contributing to cholesterol homeostasis using Gaussian process

To understand the impact of epigenetics on human misfolding disease, we apply Gaussian-process regression (GPR) based machine learning (ML) (GPR-ML) through variation spatial profiling (VSP). VSP generates population-based matrices describing the spatial covariance (SCV) relationships that link genetic diversity to fitness of the individual in response to histone deacetylases inhibitors (HDACi). Niemann-Pick C1 (NPC1) is a Mendelian disorder caused by >300 variants in the NPC1 gene that disrupt cholesterol homeostasis leading to the rapid onset and progression of neurodegenerative disease. We determine the sequence-to-function-to-structure relationships of the NPC1 polypeptide fold required for membrane trafficking and generation of a tunnel that mediates cholesterol flux in late endosomal/lysosomal (LE/Ly) compartments. HDACi treatment reveals unanticipated epigenomic plasticity in SCV relationships that restore NPC1 functionality. GPR-ML based matrices capture the epigenetic processes impacting information flow through central dogma, providing a framework for quantifying the effect of the environment on the healthspan of the individual.