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Enregistrement W3184253966 · doi:10.1016/j.ymthe.2021.07.007

Genetic diseases in the omics era

2021· letter· en· W3184253966 sur OpenAlexaboutno aff
Jean‐Baptiste Dupont

Notice bibliographique

RevueMolecular Therapy · 2021
Typeletter
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueMuscle Physiology and Disorders
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOmicsComputational biologyProteomicsBiologyEpigenomicsDiseaseTranscriptomeBioinformaticsGeneGeneticsMedicineGene expressionPathologyDNA methylation

Résumé

récupéré en direct d'OpenAlex

Accurate quantification of gene expression at RNA and protein levels has provided invaluable insight into the mechanisms of biological processes in health and disease. The so-called “-omics” technologies (transcriptomics, proteomics, but also epigenomics, etc.) enabled researchers to detect expression changes specifically associated with given biological states and, more recently, to establish their dynamics at a single-cell resolution in stem cell-based models. In this issue of Molecular Therapy, Djeddi et al.1Djeddi S. Reiss D. Menuet A. Freismuth S. de Carvalho Neves J. Djerroud S. Massana-Muñoz X. Sosson A.S. Kretz C. Raffelsberger W. et al.Multi-omics comparisons of different forms of centronuclear myopathies and the effects of several therapeutic strategies.Mol. Ther. 2021; 29: 2514-2534Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar report a meta-analysis of multi-omic data to define a common molecular signature between three forms of centronuclear myopathy (CNM), a subfamily of inherited muscle disease. They highlighted patterns of gene dysregulation associated with each mutation in well-defined mouse models, extracted the lists of common genes and ontologies, and used this information to discover new biomarkers that respond to disease correction. The study demonstrates how the power of -omics technologies can shed light on complex processes of disease initiation, progression, and correction at the molecular level. CNMs are a group of inherited muscle disorders sharing similar clinical features and histological hallmarks. Patients suffer from muscle weakness and hypotonia, which evolves more or less severely depending on the mutation.2Jungbluth H. Treves S. Zorzato F. Sarkozy A. Ochala J. Sewry C. Phadke R. Gautel M. Muntoni F. Congenital myopathies: disorders of excitation-contraction coupling and muscle contraction.Nat. Rev. Neurol. 2018; 14: 151-167Crossref PubMed Scopus (117) Google Scholar Muscle fibers typically show a hypotrophic phenotype with nuclei abnormally located in the center of the cell instead of at the periphery. Several genes have been associated with CNMs and are linked with specific modes of inheritance, including MTM1 (X-linked myotubular myopathy, XLMTM), DNM2 (autosomal dominant), and BIN1 (autosomal recessive). These genes establish a complex interplay in skeletal muscle cells, as MTM1 deficiency can be compensated either by DNM2 downregulation or BIN1 overexpression, suggesting that all three proteins are involved in common biological processes. The myotubularin 1 (MTM1), dynamin 2 (DNM2), and amphiphysin 2 (BIN1) proteins are known to participate in complex membrane remodeling processes between the sarcolemma, transverse tubules, and the endomembrane system. However, the pathological mechanisms of CNMs remain unclear at cellular and molecular levels. Several preclinical therapeutic strategies have been validated in small animal models of CNMs, including the mice employed in the Djeddi et al.1Djeddi S. Reiss D. Menuet A. Freismuth S. de Carvalho Neves J. Djerroud S. Massana-Muñoz X. Sosson A.S. Kretz C. Raffelsberger W. et al.Multi-omics comparisons of different forms of centronuclear myopathies and the effects of several therapeutic strategies.Mol. Ther. 2021; 29: 2514-2534Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar study and in a larger Labrador model of XLMTM.3Tasfaout H. Cowling B.S. Laporte J. Centronuclear myopathies under attack: A plethora of therapeutic targets.J. Neuromuscul. Dis. 2018; 5: 387-406Crossref PubMed Scopus (24) Google Scholar,4Childers M.K. Joubert R. Poulard K. Moal C. Grange R.W. Doering J.A. Lawlor M.W. Rider B.E. Jamet T. Danièle N. et al.Gene therapy prolongs survival and restores function in murine and canine models of myotubular myopathy.Sci. Transl. Med. 2014; 6: 220ra10Crossref PubMed Scopus (105) Google Scholar The latter was recently employed in a dose-finding study for the clinical translation of a recombinant adeno-associated virus (rAAV) expressing therapeutic MTM1 in XLMTM patients.5Mack D.L. Poulard K. Goddard M.A. Latournerie V. Snyder J.M. Grange R.W. Elverman M.R. Denard J. Veron P. Buscara L. et al.Systemic AAV8-Mediated Gene Therapy Drives Whole-Body Correction of Myotubular Myopathy in Dogs.Mol. Ther. 2017; 25: 839-854Abstract Full Text Full Text PDF PubMed Scopus (60) Google Scholar In parallel, we published a detailed description of the muscle transcriptome in affected dogs and how it was corrected after gene transfer by inventing specific RNA-based metrics and complementary visualization tools.6Dupont J.-B. Guo J. Renaud-Gabardos E. Poulard K. Latournerie V. Lawlor M.W. Grange R.W. Gray J.T. Buj-Bello A. Childers M.K. Mack D.L. AAV-Mediated Gene Transfer Restores a Normal Muscle Transcriptome in a Canine Model of X-Linked Myotubular Myopathy.Mol. Ther. 2020; 28: 382-393Abstract Full Text Full Text PDF PubMed Scopus (10) Google Scholar We showed that rAAV8-MTM1 gene transfer led to molecular rescue of the transcriptome in two muscle types and that it has the potential to predict treatment efficiency and identify potential biomarkers. Djeddi et al.1Djeddi S. Reiss D. Menuet A. Freismuth S. de Carvalho Neves J. Djerroud S. Massana-Muñoz X. Sosson A.S. Kretz C. Raffelsberger W. et al.Multi-omics comparisons of different forms of centronuclear myopathies and the effects of several therapeutic strategies.Mol. Ther. 2021; 29: 2514-2534Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar built on and extended this methodology to compare different CNMs in different species so as to extract the “common molecular signature” (i.e., specific lists of differentially expressed genes [DEGs] detected in all conditions) (Figure 1A). For instance, they compared XLMTM manifestations on the transcriptome in Mtm1−/y mice with those previously found in dogs6Dupont J.-B. Guo J. Renaud-Gabardos E. Poulard K. Latournerie V. Lawlor M.W. Grange R.W. Gray J.T. Buj-Bello A. Childers M.K. Mack D.L. AAV-Mediated Gene Transfer Restores a Normal Muscle Transcriptome in a Canine Model of X-Linked Myotubular Myopathy.Mol. Ther. 2020; 28: 382-393Abstract Full Text Full Text PDF PubMed Scopus (10) Google Scholar and patients.7Noguchi S. Fujita M. Murayama K. Kurokawa R. Nishino I. Gene expression analyses in X-linked myotubular myopathy.Neurology. 2005; 65: 732-737Crossref PubMed Scopus (16) Google Scholar This resulted in five common DEGs, among which the acetylcholine receptor subunits CHRNA1, CHRND, and the myogenic regulatory factor MYOG, are particularly relevant to the pathology. Importantly, the identification of these “core XLMTM genes” in an unbiased manner gives further credit to the data and the new biology discovered by the authors. Next, they conducted a rigorous comparison of the muscle transcriptome in their mouse models of CNM carrying Mtm1, Bin1, or Dnm2 mutations and highlighted 155 genes that were dysregulated in all cohorts. Interestingly, the gene ontology analysis performed on this list suggested that muscles from CNM mouse models suffer from inflammation and macrophage infiltration, which was further confirmed by immunofluorescence experiments. This unequivocally shows the interest of transcriptomics to move beyond our current understanding of pathophysiological mechanisms. Multi-omics can also bring precious knowledge on how diseases are rescued at the molecular level. We previously introduced a battery of new metrics based on RNA-sequencing data to define genes with a “rescued” expression profile from those “resistant” to the treatment, “worsened,” or “partially rescued.”6Dupont J.-B. Guo J. Renaud-Gabardos E. Poulard K. Latournerie V. Lawlor M.W. Grange R.W. Gray J.T. Buj-Bello A. Childers M.K. Mack D.L. AAV-Mediated Gene Transfer Restores a Normal Muscle Transcriptome in a Canine Model of X-Linked Myotubular Myopathy.Mol. Ther. 2020; 28: 382-393Abstract Full Text Full Text PDF PubMed Scopus (10) Google Scholar In the present study, Djeddi et al.1Djeddi S. Reiss D. Menuet A. Freismuth S. de Carvalho Neves J. Djerroud S. Massana-Muñoz X. Sosson A.S. Kretz C. Raffelsberger W. et al.Multi-omics comparisons of different forms of centronuclear myopathies and the effects of several therapeutic strategies.Mol. Ther. 2021; 29: 2514-2534Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar extended this concept to define the specific CNM rescue profiles in mice. Different modes of disease correction were compared, from genetic crosses to a pharmacological treatment with tamoxifen or antisense oligonucleotides. Here, it can be argued that the constitutive expression of a transgene resulting from a genetic cross does not represent a viable therapeutic strategy and remains hard to compare with postnatal interventions such as tamoxifen treatment or MTM1 gene therapy (not included in this study). However, it might also help unveil core mechanisms of disease rescue independent from the correction strategy (Figure 1B). The authors were able to rank therapeutic strategies based on the degree of transcriptome rescue and identified Bin1 transgenic overexpression as the most efficient. How much of this is recapitulated by Mtm1 gene therapy was not investigated but could be an interesting follow-up study. The authors detected 42 genes commonly rescued by all correction strategies that were subsequently tested for their potential to serve as new therapeutic targets and circulating biomarkers. For the latter, proteomic data obtained by mass spectrometry on murine serum samples, but also from public databases, were integrated into the analysis, and the most promising candidates were further validated by conventional molecular biology techniques, including ELISA and western blot. Overall, this helped identify annexin A2 (ANXA2) as a circulating biomarker common to several CNM forms that responded to disease correction. This gene was not identified as a biomarker candidate in our previous XLMTM dog study, which did not include proteomics and complementary ELISA experiments. This suggests that inter-species differences can be a source of variability, and comparison of biomarker lists between different models might be a powerful way to isolate the most promising genes to be used to monitor disease progression and rescue in patients. The study by Djeddi et al.1Djeddi S. Reiss D. Menuet A. Freismuth S. de Carvalho Neves J. Djerroud S. Massana-Muñoz X. Sosson A.S. Kretz C. Raffelsberger W. et al.Multi-omics comparisons of different forms of centronuclear myopathies and the effects of several therapeutic strategies.Mol. Ther. 2021; 29: 2514-2534Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar offers global gene expression profiling for CNMs by combining multi-omic data analysis with database mining and downstream validation. This is one convincing example of how -omics technologies can be used to improve our understanding of genetic diseases, both their progression and their correction, and how they are perceived in the community. Mutations in specific loci have broad consequences on a cell’s state and isolated phenotypes must be considered in this larger picture. Further emphasis should be placed on data from diversified sources (e.g., the epigenome, the interactome, or the metabolome) and different species. Future efforts should aim to better integrate this data using, for example, machine learning, to fully appreciate their complexity. In addition, the development of more versatile computer analysis pipelines and even better visualization tools should be encouraged. Altogether, this will help researchers and clinicians build more faithful disease models and accelerate clinical translation of the most promising treatments. Multi-omics comparisons of different forms of centronuclear myopathies and the effects of several therapeutic strategiesDjeddi et al.Molecular TherapyApril 30, 2021In BriefA multi-omics analysis is performed on transgenic mouse lines faithfully modeling different forms of centronuclear myopathies treated or not with several therapeutic approaches. The common disease and therapy signatures are described at the molecular level. Potential circulating biomarkers are identified and await confirmation in patients. Full-Text PDF

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,648
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,009
Tête enseignante GPT0,232
Écart entre enseignants0,223 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

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