Principal Investigator: Professor Jonathan Flint
Department: University of California, Semel Institute, Department of Psychiatry, Los Angeles, United States
1) Dr Na Cai
2) Professor Richard Mott
Collaborating Institutions and Addresses:
1) European Bioinformatics Institute, Stegle Group, European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cabridge
2) University College London, UCL Genetics Institute, Gower Street, LondonTags: 24129, featured, interaction, Metabolism, mitochondria, physiology, psychiatric, variants
1a: We aim to identify what genetic, physiological and metabolic measures mtDNA copy number is associated with, and how this relationship varies with disease. We have previously shown that psychological stress increases the amount of mtDNA. In this project, we will explore how mtDNA variation is determined by nuclear genetic variants and examine its interaction with psychological, physiological and environmental factors. We will focus on medical records and self-reported outcomes of internalising psychiatric disorders and co-morbid health conditions (including autoimmune disorders, like rheumatoid arthritis, and non-immune traits including type2 diabetes, migraine, chronic pain, obesity and body-mass index).
1b: This proposed research project investigates the relationship between mtDNA copy number and disease states, and asks how this may be affected by genetic variation. The research will shed light on the link between environmental and physiological stress, cellular metabolism, and diseases (primarily psychiatric illness). It will further the understanding of the mechanisms of these diseases and has the potential to help diagnosis, and potentially guide treatment choice.
1c: We will quantify the amount of mtDNA based on the relative genotyping array intensities at mitochondrial probes and nuclear DNA probes. We will then test for associations between the quantified amount of mtDNA and disease status and physiological traits in the dataset to identify relationships between them
1d: full cohort