Background
Human mitochondria play a vital role in regulating key biological processes throughout the body, especially in high-energy tissues like the brain. Mitochondrial dysfunction has been linked to several common neurological disorders, such as Parkinson’s Disease, Alzheimer’s Disease and ALS, but it is unclear whether this dysfunction is a cause or consequence of disease. Using large-scale genetic and gene expression data from human brain regions, we will employ advanced machine learning techniques to model the genetic mechanisms affecting mitochondrial function and integrate protein and metabolite data to assess the downstream effects. These models will then be applied to disease cohorts and electronic health records to explore whether tissue- and cell-type-specific mitochondrial processes contribute to the risk and progression of neurological disorders.
Novelty and Importance
This project addresses a fundamental question in neurodegenerative research: are mitochondria part of the disease pathway or a response to disease? Understanding this will highlight specific biological pathways and cell types that can be targeted therapeutically to reduce disease risk and progression.
Aims and Objectives
Aim 1: Identify genetic changes in mitochondrial and nuclear genomes that influence mitochondrial processes across different brain cell types, using bulk and single-cell RNA sequencing data.
Aim 2: Develop machine learning models to predict mitochondrial processes based on genetic data, and then validate these models with protein and metabolite data.
Aim 3: Apply validated models to large cohort datasets, such as UK Biobank, and electronic health records to identify mitochondrial processes causally linked to neurological disorders, guiding future therapeutic interventions.”