Publications by authors named "Jean-Marie Ravel"

5 Publications

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Expanding the clinical spectrum of STIP1 homology and U-box containing protein 1-associated ataxia.

J Neurol 2021 Jan 8. Epub 2021 Jan 8.

Service de Génétique Médicale, Hôpitaux de Brabois, CHRU de Nancy, Rue du Morvan, 54500, Vandoeuvre-lès-Nancy, France.

Background: STUB1 has been first associated with autosomal recessive (SCAR16, MIM# 615768) and later with dominant forms of ataxia (SCA48, MIM# 618093). Pathogenic variations in STUB1 are now considered a frequent cause of cerebellar ataxia.

Objective: We aimed to improve the clinical, radiological, and molecular delineation of SCAR16 and SCA48.

Methods: Retrospective collection of patients with SCAR16 or SCA48 diagnosed in three French genetic centers (Montpellier, Strasbourg and Nancy).

Results: Here, we report four SCAR16 and nine SCA48 patients from two SCAR16 and five SCA48 unrelated French families. All presented with slowly progressive cerebellar ataxia. Additional findings included cognitive decline, dystonia, parkinsonism and swallowing difficulties. The age at onset was highly variable, ranging from 14 to 76 years. Brain MRI showed marked cerebellar atrophy in all patients. Phenotypic findings associated with STUB1 pathogenic variations cover a broad spectrum, ranging from isolated slowly progressive ataxia to severe encephalopathy, and include extrapyramidal features. We described five new pathogenic variations, two previously reported pathogenic variations, and two rare variants of unknown significance in association with STUB1-related disorders. We also report the first pathogenic variation associated with both dominant and recessive forms of inheritance (SCAR16 and SCA48).

Conclusion: Even though differences are observed between the recessive and dominant forms, it appears that a continuum exists between these two entities. While adding new symptoms associated with STUB1 pathogenic variations, we insist on the difficulty of genetic counselling in STUB1-related pathologies. Finally, we underscore the usefulness of DAT-scan as an additional clue for diagnosis.
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http://dx.doi.org/10.1007/s00415-020-10348-xDOI Listing
January 2021

Comprehensive Map of the Regulated Cell Death Signaling Network: A Powerful Analytical Tool for Studying Diseases.

Cancers (Basel) 2020 Apr 17;12(4). Epub 2020 Apr 17.

Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, 75005 Paris, France.

The processes leading to, or avoiding cell death are widely studied, because of their frequent perturbation in various diseases. Cell death occurs in three highly interconnected steps: Initiation, signaling and execution. We used a systems biology approach to gather information about all known modes of regulated cell death (RCD). Based on the experimental data retrieved from literature by manual curation, we graphically depicted the biological processes involved in RCD in the form of a seamless comprehensive signaling network map. The molecular mechanisms of each RCD mode are represented in detail. The RCD network map is divided into 26 functional modules that can be visualized contextually in the whole seamless network, as well as in individual diagrams. The resource is freely available and accessible via several web platforms for map navigation, data integration, and analysis. The RCD network map was employed for interpreting the functional differences in cell death regulation between Alzheimer's disease and non-small cell lung cancer based on gene expression data that allowed emphasizing the molecular mechanisms underlying the inverse comorbidity between the two pathologies. In addition, the map was used for the analysis of genomic and transcriptomic data from ovarian cancer patients that provided RCD map-based signatures of four distinct tumor subtypes and highlighted the difference in regulations of cell death molecular mechanisms.
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http://dx.doi.org/10.3390/cancers12040990DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226067PMC
April 2020

[Narcolepsy: From the discovery of a wake promoting peptide to autoimmune T cell biology and molecular mimicry with flu epitopes].

Biol Aujourdhui 2019 12;213(3-4):87-108. Epub 2019 Dec 12.

Stanford Center for Sleep Sciences and Medicine, Department of Psychiatry and Behavioral Medicine, Stanford University, 3615 Porter Drive, Palo Alto, CA, USA.

Narcolepsy-cataplexy was first described in the late 19th century in Germany and France. Prevalence was established to be 0.05 % and a canine model was discovered in the 1970s. In 1983, a Japanese study found that all patients carried HLA-DR2, suggesting autoimmunity as the cause of the disease. Studies in the canine model established that dopaminergic stimulation underlies anti-narcoleptic action of psychostimulants, while antidepressants were found to suppress cataplexy through adrenergic reuptake inhibition. No HLA association was found in canines. A linkage study initiated in 1988 revealed in hypocretin (orexin) receptor two mutations as the cause of canine narcolepsy in 1999. In 1992, studies on African Americans showed that DQ0602 was a better marker than DR2 across all ethnic groups. In 2000, hypocretin-1/orexin A levels were measured in the cerebrospinal fluid (CSF) and found to be undetectable in most patients, establishing hypocretin deficiency as the cause of narcolepsy. Decreased CSF hypocretin-1 was then found to be secondary to the loss of the 70,000 neurons producing hypocretin in the hypothalamus, suggesting immune destruction of these cells as the cause of the disease. Additional genetic studies, notably genome wide associations (GWAS), found multiple genetic predisposing factors for narcolepsy. These were almost all involved in other autoimmune diseases, although a strong and unique association with T cell receptor (TCR) alpha and beta loci were observed. Nonetheless, all attempts to demonstrate presence of autoantibodies against hypocretin cells in narcolepsy failed, and the presumed autoimmune cause remained unproven. In 2009, association with strep throat infections were found, and narcolepsy onsets were found to occur more frequently in spring and summer, suggesting upper away infections as triggers. Following reports that narcolepsy cases were triggered by vaccinations and infections against influenza A 2009 pH1N1, a new pandemic strain that erupted in 2009, molecular mimicry with influenza A virus was suggested in 2010. This hypothesis was later confirmed by peptide screening showing higher activity of CD4 T cell reactivity to a specific post-translationally amidated segment of hypocretin (HCRT-) and cross-reactivity of specific TCRs with a pH1N1-specific segment of hemagglutinin that shares homology with HCRT-. Strikingly, the most frequent TCR recognizing these antigens was found to carry sequences containing TRAJ24 or TRVB4-2, segments modulated by narcolepsy-associated genetic polymorphisms. Cross-reactive CD4 T cells with these cross-reactive TCRs likely subsequently recruit CD8 T cells that are then involved in hypocretin cell destruction. Additional flu mimics are also likely to be discovered since narcolepsy existed prior to 2009. The work that has been conducted over the years on narcolepsy offers a unique perspective on the conduct of research on the etiopathogeny of a specific disease.
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http://dx.doi.org/10.1051/jbio/2019026DOI Listing
May 2020

Application of Atlas of Cancer Signalling Network in preclinical studies.

Brief Bioinform 2019 03;20(2):701-716

Institut Curie, PSL Research University, F-75005 Paris, France, INSERM, U900, F-75005 Paris, France and MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, F-75006 Paris, France.

Cancer initiation and progression are associated with multiple molecular mechanisms. The knowledge of these mechanisms is expanding and should be converted into guidelines for tackling the disease. Here, we discuss the formalization of biological knowledge into a comprehensive resource: the Atlas of Cancer Signalling Network (ACSN) and the Google Maps-based tool NaviCell, which supports map navigation. The application of ACSN for omics data visualization, in the context of signalling maps, is possible via the NaviCell Web Service module and through the NaviCom tool. It allows generation of network-based molecular portraits of cancer using multilevel omics data. We review how these resources and tools are applied for cancer preclinical studies. Structural analysis of the maps together with omics data helps to rationalize the synergistic effects of drugs and allows design of complex disease stage-specific druggable interventions. The use of ACSN modules and maps as signatures of biological functions can help in cancer data analysis and interpretation. In addition, they empowered finding of associations between perturbations in particular molecular mechanisms and the risk to develop a specific type of cancer. These approaches are helpful, among others, to study the interplay between molecular mechanisms of cancer. It opens an opportunity to decipher how gene interactions govern the hallmarks of cancer in specific contexts. We discuss a perspective to develop a flexible methodology and a pipeline to enable systematic omics data analysis in the context of signalling network maps, for stratifying patients and suggesting interventions points and drug repositioning in cancer and other diseases.
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http://dx.doi.org/10.1093/bib/bby031DOI Listing
March 2019

HLA-DPB1 and HLA class I confer risk of and protection from narcolepsy.

Am J Hum Genet 2015 Jan;96(1):136-46

Stanford University Center for Sleep Sciences, Palo Alto, CA 94304, USA. Electronic address:

Type 1 narcolepsy, a disorder caused by a lack of hypocretin (orexin), is so strongly associated with human leukocyte antigen (HLA) class II HLA-DQA1(∗)01:02-DQB1(∗)06:02 (DQ0602) that very few non-DQ0602 cases have been reported. A known triggering factor for narcolepsy is pandemic 2009 influenza H1N1, suggesting autoimmunity triggered by upper-airway infections. Additional effects of other HLA-DQ alleles have been reported consistently across multiple ethnic groups. Using over 3,000 case and 10,000 control individuals of European and Chinese background, we examined the effects of other HLA loci. After careful matching of HLA-DR and HLA-DQ in case and control individuals, we found strong protective effects of HLA-DPA1(∗)01:03-DPB1(∗)04:02 (DP0402; odds ratio [OR] = 0.51 [0.38-0.67], p = 1.01 × 10(-6)) and HLA-DPA1(∗)01:03-DPB1(∗)04:01 (DP0401; OR = 0.61 [0.47-0.80], p = 2.07 × 10(-4)) and predisposing effects of HLA-DPB1(∗)05:01 in Asians (OR = 1.76 [1.34-2.31], p = 4.71 × 10(-05)). Similar effects were found by conditional analysis controlling for HLA-DR and HLA-DQ with DP0402 (OR = 0.45 [0.38-0.55] p = 8.99 × 10(-17)) and DP0501 (OR = 1.38 [1.18-1.61], p = 7.11 × 10(-5)). HLA-class-II-independent associations with HLA-A(∗)11:01 (OR = 1.32 [1.13-1.54], p = 4.92 × 10(-4)), HLA-B(∗)35:03 (OR = 1.96 [1.41-2.70], p = 5.14 × 10(-5)), and HLA-B(∗)51:01 (OR = 1.49 [1.25-1.78], p = 1.09 × 10(-5)) were also seen across ethnic groups in the HLA class I region. These effects might reflect modulation of autoimmunity or indirect effects of HLA class I and HLA-DP alleles on response to viral infections such as that of influenza.
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http://dx.doi.org/10.1016/j.ajhg.2014.12.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4289679PMC
January 2015