Fighting Diagnostic Odyssey in Mitochondrial Diseases.
Project for the Establishment of a Cohort of Patients with Mitochondrial Diseases.
Mitochondrial diseases are a group of disorders, most often hereditary, characterized by mitochondrial dysfunction. Mitochondria are organelles present in all cells and play an essential role in cellular function by enabling energy production through the process of cellular respiration. Mitochondrial diseases are caused by mutations in genes involved in mitochondrial functions, impacting the cells' energy production. Understanding the causes of mitochondrial diseases is particularly complex because the mitochondrial genome alone is not sufficient to ensure proper mitochondrial function, as it is also linked to the nuclear genome. Thus, mitochondrial diseases can be caused by mutations in either the mitochondrial or nuclear genome. These are the most common metabolic diseases, highly heterogeneous in clinical, biochemical, and genetic aspects.
The diagnosis of mitochondrial diseases has been completely transformed by the emergence of Next-Generation Sequencing (NGS) technologies, which have rapidly increased the genetic diagnosis rate from 10-20% to over 50% in some cohorts, revealing numerous variants (either pathogenic or of currently unknown significance). The French Network of Mitochondrial Disease Diagnostic Laboratories, MITODIAG, collaborates closely with the two National Reference Centers, CARAMMEL and CALISSON, as well as the FILNEMUS network, to improve patient diagnosis and care.
The COMMI project aims to assemble a cohort of 400 patients tested by high-throughput sequencing, with clinical and genetic descriptions, within the MITODIAG network laboratories. This patient group has a confirmed molecular diagnosis through the identification of one or more pathogenic variants in nuclear genes. The study data will be anonymized. The objective of this project is to better define the clinical spectrum associated with the different nuclear genes, establish genotype-phenotype correlations, and thus improve the interpretation of increasingly complex genetic analyses, given the growing number of genetic variants of unknown significance.
The challenge is to reduce the diagnostic odyssey and achieve a reliable diagnosis by interpreting the clinical impact of these new rare variants. This will also help improve patient care, facilitate access to clinical trials, and refine molecular diagnostic strategies. Additional information is available upon request from the coordinator. Likewise, patients are free to refuse the use of their data for this project on mitochondrial diseases and may change their decision at any time.

Mitochondrial Disease database: An integrated multi-OMICS approach
Mitochondrial diseases are rare, clinically and genetically extremely heterogeneous, caused by a deficit of energy production via the mitochondria. Mitochondria are dependent on 2 genomes mitochondrial DNA (mtDNA) and nuclear DNA, and many pathogenic variants carried by these 2 genomes are responsible for mitochondrial diseases. There is a cross talk and regulatory mechanisms between both genomes, which are still poorly understood, involved in the control and maintenance of mitochondrial biogenesis. All of these mechanisms play an important role in the clinical and genetic heterogeneities presented by patients suffering from mitochondrial disease and are difficult to identify by "classical" high-throughput mtDNA, whole exome (WES) or genome (WGS) sequencing approaches.
Mitomatcher is the first French database collecting genetic and clinical data for patients with mitochondrial diseases, implemented by the national mitochondrial laboratory network MITODIAG in conjunction with the reference centres (CARAMMEL and CALISSON) and FILNEMUS the rare disease network.

Mitomatcher comprises 3 different modules:

i) HPO related phenotypic data module

ii) genetic module currently containing mtDNA variants from more than 5000 patients with mitochondrial disease

iii) query and cross-reference module for the clinical-biological data.

The MITOMICS project aims to better understand the molecular mechanisms responsible for the clinical-genetic heterogeneity of mitochondrial diseases. The integration of multi-OMICS data (transcriptomics/proteomics/metabolomics) combined with clinical and genomic data (WES, WGS) in the Mitomatcher database should help to unravel the complexity of these diseases. Societal implications (ethics, juridics) of genomics research will be investigated and guidelines will be defined.
The cross analysis of these data requires the development of in silico tools. Different approaches will be developed to :

i) identify co-occurrences of mtDNA and/or nuclear DNA variants responsible for mitochondrial diseases in order to reveal new genotype/phenotype correlations

ii) characterise the mitochondrial and nuclear crosstalk

iii) identify OMICS signatures specific to mitochondrial dysfunction.

The study will be divided into 4 WPs starting with data collection and mitomatcher implementation (WP1) and from WP2-4 with the development of algorithms and data integration with increasing complexity with sequential data implementation starting with mtDNA variants alone, then combined with nuclear variants and finally multi-OMICs.
Innovative machine learning, neural networks and artificial intelligence approaches will be developed such as Ruche a multi-layeR mUlti-omics maCHine learning intEgration tool or ABEILLE (ABerrant Expression Identification empLoying machine LEarning), an autoencoder-based method for the identification of aberrant gene expression from RNA-seq which will be applied to other OMICs. The identification of combinations of variants or affected signaling pathways from homogeneous groups of patients will be further verified by laboratory experiments. This project will also allow further development of in silico tools for the analysis of mtDNA variants such as Eklipse to detect mtDNA rearrangements.
Mitomatcher database will be accessible, already following international standards (Fast Healthcare Interoperability Resources, HPO), interoperable with other national or international databases and reusable for the development of ancillary studies for these disorders.
In the long term, the results obtained will allow the identification of new genotype/phenotype correlations and a better understanding of the pathophysiological mechanisms of mitochondrial diseases. The identification of specific signatures via an integrated multi-OMICs approach through Mitomics should also target specific pathways, thus enabling the development of new therapeutic strategies for mitochondrial diseases.
This current work resulted in a publication:
["Mitochondrial medicine" in the light of the fourth national plan for rare diseases (PNMR4): The example of the MITOMICS project] Clémence Guillermain, Stéphane Tirard, Sylvie Bannwarth, Vincent Procaccio médecine/sciences 2025 ; 41 : 000-000 PubMed

BACKGROUND :
Mitochondrial DNA (mtDNA) diseases are rare disorders whose prevalence is estimated around 1 in 5000. Patients are usually tested only for deletions and for common mutations of mtDNA which account for 5-40% of cases, depending on the study. However, the prevalence of rare mtDNA mutations is not known.

METHODS :
We analysed the whole mtDNA in a cohort of 743 patients suspected of manifesting a mitochondrial disease, after excluding deletions and common mutations. Both heteroplasmic and homoplasmic variants were identified using two complementary strategies (Surveyor and MitoChip). Multiple correspondence analyses followed by hierarchical ascendant cluster process were used to explore relationships between clinical spectrum, age at onset and localisation of mutations.

RESULTS :
7.4% of deleterious mutations and 22.4% of novel putative mutations were identified. Pathogenic heteroplasmic mutations were more frequent than homoplasmic mutations (4.6% vs 2.8%). Patients carrying deleterious mutations showed symptoms before 16 years of age in 67% of cases. Early onset disease (< 1 year) was significantly associated with mutations in protein coding genes (mainly in complex I) while late onset disorders (>16 years) were associated with mutations in tRNA genes. MTND5 and MTND6 genes were identified as 'hotspots' of mutations, with Leigh syndrome accounting for the large majority of associated phenotypes.

CONCLUSIONS :
Rare mitochondrial DNA mutations probably account for more than 7.4% of patients with respiratory chain deficiency. This study shows that a comprehensive analysis of mtDNA is essential, and should include young children, for an accurate diagnosis that is now accessible with the development of next generation sequencing technology.

BACKGROUND :
The A3243G mutation in the tRNALeu gene (UUR), is one of the most common pathogenic mitochondrial DNA (mtDNA) mutations in France, and is associated with highly variable and heterogeneous disease phenotypes. To define the relationships between the A3243G mutation and mtDNA backgrounds, we determined the haplogroup affiliation of 142 unrelated French patients - diagnosed as carriers of the A3243G mutation - by control-region sequencing and RFLP survey of their mtDNAs.

RESULTS :
The analysis revealed 111 different haplotypes encompassing all European haplogroups, indicating that the 3243 site might be a mutational hot spot. However, contrary to previous findings, we observed a statistically significant underepresentation of the A3243G mutation on haplogroup J in patients (p = 0.01, OR = 0.26, C.I. 95%: 0.08-0.83), suggesting that might be due to a strong negative selection at the embryo or germ line stages.

CONCLUSION :
Thus, our study supports the existence of mutational hotspot on mtDNA and a "haplogroup J paradox," a haplogroup that may increase the expression of mtDNA pathogenic mutations, but also be beneficial in certain environmental contexts.