WP 1: Advancing the global registry of mitochondrial diseases

We will increase the number of sites, networks and countries in the registry and will continue to recruit patients for follow-up visits (cohort study). The value of the registry and cohort study will be increased by linking the physician documented data with patient-reported outcome measures. This work will be done in close relationship to patient organisations, such as IMP (International Mito Patients).

WP1 is lead and coordinated by Friedrich-Baur-Institute of LMU Munich (Germany, german national network mitoNET) and the University of Pisa (Italy, italian national network Mitocon). It also includes the contributions of data by the partners and the national networks of Austria, Italy, Hungary, Japan, United Kingdom, Spain and patient organisations.

WP2 – Development of algorithms increasing diagnostic rates

The multi-omics algorithms developed during previous GENOMIT periods will be improved by implementation of AI-tools and screening of polygenic risk factors, which will improve the diagnostic rates of complex inheritance patterns associated with clinical phenotypes of mitochondrial diseases (MD).

WP2 is coordinated by the Institute of Human Genetics at Klinikum rechts der Isar TUM (MRI, Munich, Germany) and the Fondazione IRCCS Istituto Neurologico C. Besta (BESTA, Milan, Italy).

WP3 – Identifying metabolic biomarkers signatures

Metabolic changes reflect pathophysiological processes preceding clinical manifestation and treatment response. Metabolomic data analysis will be analysed to identify markers and signatures predicting the severety, progression and treatment response of MD. In addition to analysis of untargeted metabolomic data, we performe studies covering central metabolic pathways in specific phenotypes as Leigh syndrome, MELAS spectrum and PDHA1 deficiency.

WP3 is coordinated by Reference Center for Hereditary Metabolic Disorders (MetabERN, CIBERER Hospital, Madrid, Spain) and the Luxembourg Centre for Systems Biomedicine (LCSB, Luxembourg). Animal and human bioprobes for validation are analysed by the partners Department of Biomedical Sciences University of Padova (Italy) and BESTA (Milan, Italy). Biosamples from patients are provided by several partners.

WP4 - Determination of environmental and lifestyle factors from metabolic profiles

Using untargeted metabolomics data we will assess the role of environment and lifestyle factors in MD. Existing data will be analysed with cheminformatics/exposomics open science workflows and the results will be verified by newly measured data from independent samples.

WP4 is coordinated by LCSB (Luxembourg). The national network contributions are managed by BESTA and University of Pisa (Italy), Friedrich-Baur-Institut of LMU and Klinikum rechts der Isar TUM (Germany), SALK (Austria), Semmelweis University (Hungary), CIBERER Hospital (Madrid, Spain), Chiba Hospital (Japan) and Wellcome Centre for Mitochondrial Research, Newcastle University (United Kingdom).

WP5 – Improvement of prediction of the natural history of MD

We will train serveral machine learning and deep learning algorithms integrating multi-omics data, data of pharmacology, environment, lifestyle and clinical and patient reported outcomes. We will develop novel scoring systems and multi-omics-guided patient stratification.

WP5 is lead by Klinikum rechts der Isar TUM (Munich, Germany).