Lutte contre l’errance diagnostique dans les maladies mitochondriales.
Projet de constitution d’une cohorte de patients atteints de maladies mitochondriales.

Les maladies mitochondriales, sont un ensemble de maladies, le plus souvent héréditaires, caractérisées par un dysfonctionnement des mitochondries, des organites présents dans toutes les cellules. Les mitochondries jouent un rôle indispensable dans le fonctionnement cellulaire puisqu’elles permettent la production d’énergie, grâce auprocessus de respiration cellulaire. Les maladies mitochondriales sont dues à des mutations sur les gènes impliqués dans les fonctions mitochondriales qui impactent la production d’énergie des cellules. La compréhension des causes des maladies mitochondriales est d’autant plus complexe que le génome mitochondrial n’est pas suffisant pour assurer le bon fonctionnement desmitochondries, et que ce dernier est associé au génome de la cellule (génome nucléaire). Ainsiles maladies mitochondriales peuvent être dues à des mutations dans le génomemitochondrial ou nucléaire. Ce sont les maladies métaboliques les plus courantes, très hétérogènes tant sur le plan clinique que biochimique ou génétique. Le diagnostic des maladies mitochondriales a été complètement transformé par l'émergence des technologies de séquençage de nouvelle génération (NGS : Next Generation Sequencing)qui ont permis d'augmenter rapidement le diagnostic génétique de 10% à 20% à plus de 50% dans certaines cohortes mettant en évidence de nombreux variants (pathogènes ou dont la signification est actuellement inconnue). Le réseau Français des Laboratoires de Diagnostic des Maladies Mitochondriale, MITODIAG, travaille en étroite collaboration avec les deux Centres Nationaux de Référence, CARAMMEL et CALISSON, et la filière FILNEMUS, afin d'améliorer le diagnostic et la prise en charge des patients.
Le projet COMMI consiste à rassembler une cohorte de 400 patients testés par séquençage haut débit, avec description clinique et génétique, dans les laboratoires du réseau MITODIAG.Ce groupe de patients possède un diagnostic moléculaire confirmé par l'identification d'un ou plusieurs variants pathogènes dans des gènes nucléaires. Les données de cette étude seront anonymisées. L’objectif de ce projet est de mieux définir les spectres cliniques associés aux différents gènes impliqués, d'établir des corrélations génotypes/phénotypes et ainsi d'améliorer l'interprétation des analyses génétiques de plus en plus complexes avec un nombre de variants de signification incertaine grandissant.
L’enjeu est de réduire l'errance diagnostique et d’obtenir un diagnostic fiable par l'interprétation de l'impact clinique de ces nouveaux variants rares. Cela permettra également d’améliorer la prise en charge et faciliter l'accès aux essais cliniques des patients et de perfectionner les stratégies de diagnostic moléculaire. Les informations complémentaires sont disponibles sur demande auprès du coordinateur. De même, les patients sont libres de refuser que leurs données soient utilisées pour ce projet surles maladies mitochondriales et de décider à tout moment de changer d’avis.

Coordination Réseau MitoDiag :
Cécile Rouzier, rouzier.c(at)chu-nice.fr; Vincent Procaccio, viprocaccio(at)chu-angers.fr
Projet_COMMI _Maladies_mitochondriales_origine_nucleaire_Mitodiag.pdf

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 3000 patients with mitochondrial disease and 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, and (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.

Charte_utilisation_mitomatcher_20211119.pdf

BACKGROUND :
The advent of high throughput sequencing (NGS) techniques has revolutionized the genetic diagnosis of mitochondrial diseases with an increase in the amount of data generated but also in their complexity, particularly with the identification of many variants of unknown significance (VSI) in nuclear and mitochondrial genomes (mtDNA). The objective of the MitoDiag network, 11 French hospital laboratories specializing in the diagnosis of mitochondrial diseases and supported by the Filnemus sector, was therefore to create a French clinical-biological database, MitoMatcher, which collects for each patient the set of variants mtDNA, clinical and demographic data to facilitate exchanges between the various network laboratories and NGS data analysis.

METHODS :
The MitoMatcher database was designed around 3 modules: a clinical database, a genetic database of mtDNA variants and a query interface. The clinical database is provided by PhenoTIPS, specialized in the collection and analysis of phenotypic information from patients with genetic diseases and using the terminology HPO. The genetic database contains, for each patient, all the information contained in the VCF file as well as metadata (nature of the sample, type of analysis). For the query and information sharing interface between the labs, CafeVariome was set up in collaboration with Anthony Brookes coordinating the European project GEN2PHEN.

RESULTS :
As a first step, the MitoMatcher project focused on the analysis of the NGS data of the mtDNA. After developing the structure of the database of genetic variants, it was tested by integrating the data of nearly 800 patients from a previous study conducted by the laboratories of the network. Interoperability between clinical information from PHENOTIPS and the genetic database was made possible by the integration of CafeVariome into MitoMatcher. The interface has been developed to allow information sharing between laboratories and the extraction of new knowledge through the "elastic search" technology.

CONCLUSION AND PERSPECTIVES :
Mitomatcher is a French clinical-biological database that simplifies the sharing of genetic and phenotypic information between laboratories and facilitates the interpretation of mtDNA VSIs. The deployment of the tool within the network is planned for the year 2020. In a second time, its use is envisaged for more complex queries (co-occurrence of variants, influence of mitochondrial haplogroups ...). Finally, in the medium term, the tool can be extended to variants of nuclear genes involved in mitochondrial diseases, and the Mitomatcher architecture used for other pathologies.

MitoMatcher has got a poster award at the congress "10ème Assises de Génétique humaine et médicale" by the Association BioinfoDiag.

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.