Aims: The aim of this project is to elucidate the involvement of mitochondria (energy-producing centres in cells) with the risk of metabolic diseases such as obesity and diabetes and their associated complications. Specifically, we will determine the association between mtDNA-CN and mtDNA damage with obesity and related co-morbidities and we will determine the associated clinical, physiological and demographic risk factors which contribute to disease.
Scientific Rationale: Although there are increasing studies reporting mitochondrial dysfunction in metabolic disease, the exact role of mitochondrial function and dysfunction in the risk of obesity and its related complications, including diabetes and cardiovascular disease, remain poorly understood. MtDNA copy number (mtDNA-CN) has emerged as a biomarker of mitochondrial function and disease associated alterations in mtDNA-CN have been widely reported in the context of metabolic disease. We propose to test the theory that changes in mtDNA-CN and damage to mtDNA are involved in obesity related complications. We will investigate large sets of genetic data from different participants available within the UK biobank. We’ll use this data to see how much MtDNA each person has and if there are any variations in it. We will combine the genetic information with available health records to see if there are any connections between mitochondrial DNA and disease status and identify related risk markers.
Project duration: this project is funded for 5 years in total, ending on 30th April 2028
Public Health Impact. The project is part of the recently funded EU project PASGRAS “(DE-RISKING METABOLIC, ENVIRONMENTAL AND BEHAVIORAL DETERMINANTS OF OBESITY IN CHILDREN, ADOLESCENTS AND YOUNG ADULTS”. Determination of the risk factors for obesity related complications in the UKBB will assist with the PASGRAs project goal of development of a personalised risk assessment tool to prevent obesity and its related complication. Understanding the genetic factors involved in metabolic diseases could lead to the development of more personalized and targeted therapies, improving treatment outcomes for individuals affected by these conditions. Additionally, this knowledge could guide the development of new diagnostic tools for early detection, enabling healthcare professionals to intervene sooner and potentially prevent the progression of metabolic diseases and their associated complications. Moreover, insights gained from this research could lead to the design of public health programs focused on promoting healthier lifestyles and reducing the prevalence of metabolic diseases in communities.