Quantitating the epigenetic transformation contributing to cholesterol homeostasis using Gaussian process.

Area of Science:

• Genetics and Epigenetics
• Neurodegenerative Diseases
• Computational Biology

Background:

• Niemann-Pick C1 (NPC1) disease is a Mendelian disorder caused by genetic variants disrupting cholesterol homeostasis and leading to neurodegeneration.
• Understanding the interplay between genetic mutations, protein structure, and cellular function is crucial for developing therapeutic strategies.
• Epigenetic modifications, such as those influenced by histone deacetylase inhibitors (HDACi), represent a potential avenue for modulating disease progression.

Purpose of the Study:

• To investigate the impact of epigenetics on human misfolding diseases using a machine learning approach.
• To determine the sequence-to-function-to-structure relationships of the NPC1 protein and how they are affected by epigenetic factors.
• To explore the potential of HDACi in restoring NPC1 functionality and mitigating disease phenotypes.

Main Methods:

• Application of Gaussian-process regression (GPR) based machine learning (ML) combined with variation spatial profiling (VSP).
• VSP generates population-based matrices to describe spatial covariance (SCV) relationships linking genetic diversity to individual fitness.
• Analysis of NPC1 variants and their impact on cholesterol flux within late endosomal/lysosomal compartments.

Main Results:

• HDACi treatment demonstrated an unexpected epigenomic plasticity in SCV relationships, leading to the restoration of NPC1 functionality.
• GPR-ML based matrices successfully captured epigenetic processes influencing information flow through the central dogma.
• The study provides a framework for quantifying environmental effects on individual healthspan.

Conclusions:

• Epigenetic plasticity offers a novel therapeutic target for NPC1 and potentially other misfolding diseases.
• Machine learning, particularly GPR-ML and VSP, provides powerful tools for dissecting complex genotype-phenotype-environment interactions.
• This research opens new possibilities for understanding and intervening in diseases influenced by both genetic and epigenetic factors.