80 research outputs found

    SCN5A mutations and the role of genetic background in the pathophysiology of Brugada syndrome.

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    International audienceBACKGROUND: Mutations in SCN5A are identified in approximately 20% to 30% of probands affected by Brugada syndrome (BrS). However, in familial studies, the relationship between SCN5A mutations and BrS remains poorly understood. The aim of this study was to investigate the association of SCN5A mutations and BrS in a group of large genotyped families. METHODS AND RESULTS: Families were included if at least 5 family members were carriers of the SCN5A mutation, which was identified in the proband. Thirteen large families composed of 115 mutation carriers were studied. The signature type I ECG was present in 54 mutation carriers (BrS-ECG+; 47%). In 5 families, we found 8 individuals affected by BrS but with a negative genotype (mutation-negative BrS-ECG+). Among these 8 mutation-negative BrS-ECG+ individuals, 3, belonging to 3 different families, had a spontaneous type I ECG, whereas 5 had a type I ECG only after the administration of sodium channel blockers. One of these 8 individuals had also experienced syncope. Mutation carriers had, on average, longer PR and QRS intervals than noncarriers, demonstrating that these mutations exerted functional effects. CONCLUSIONS: Our results suggest that SCN5A mutations are not directly causal to the occurrence of a BrS-ECG+ and that genetic background may play a powerful role in the pathophysiology of BrS. These findings add further complexity to concepts regarding the causes of BrS, and are consistent with the emerging notion that the pathophysiology of BrS includes various elements beyond mutant sodium channels

    Novel Association of the NOTCH Pathway Regulator MIB1 Gene With the Development of Bicuspid Aortic Valve.

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    IMPORTANCE Nonsyndromic bicuspid aortic valve (nsBAV) is the most common congenital heart valve malformation. BAV has a heritable component, yet only a few causative genes have been identified; understanding BAV genetics is a key point in developing personalized medicine. OBJECTIVE To identify a new gene for nsBAV. DESIGN, SETTING, AND PARTICIPANTS This was a comprehensive, multicenter, genetic association study based on candidate gene prioritization in a familial cohort followed by rare and common association studies in replication cohorts. Further validation was done using in vivo mice models. Study data were analyzed from October 2019 to October 2022. Three cohorts of patients with BAV were included in the study: (1) the discovery cohort was a large cohort of inherited cases from 29 pedigrees of French and Israeli origin; (2) the replication cohort 1 for rare variants included unrelated sporadic cases from various European ancestries; and (3) replication cohort 2 was a second validation cohort for common variants in unrelated sporadic cases from Europe and the US. MAIN OUTCOMES AND MEASURES To identify a candidate gene for nsBAV through analysis of familial cases exome sequencing and gene prioritization tools. Replication cohort 1 was searched for rare and predicted deleterious variants and genetic association. Replication cohort 2 was used to investigate the association of common variants with BAV. RESULTS A total of 938 patients with BAV were included in this study: 69 (7.4%) in the discovery cohort, 417 (44.5%) in replication cohort 1, and 452 (48.2%) in replication cohort 2. A novel human nsBAV gene, MINDBOMB1 homologue MIB1, was identified. MINDBOMB1 homologue (MIB1) is an E3-ubiquitin ligase essential for NOTCH-signal activation during heart development. In approximately 2% of nsBAV index cases from the discovery and replication 1 cohorts, rare MIB1 variants were detected, predicted to be damaging, and were significantly enriched compared with population-based controls (2% cases vs 0.9% controls; P = .03). In replication cohort 2, MIB1 risk haplotypes significantly associated with nsBAV were identified (permutation test, 1000 repeats; P = .02). Two genetically modified mice models carrying Mib1 variants identified in our cohort showed BAV on a NOTCH1-sensitized genetic background. CONCLUSIONS AND RELEVANCE This genetic association study identified the MIB1 gene as associated with nsBAV. This underscores the crucial role of the NOTCH pathway in the pathophysiology of BAV and its potential as a target for future diagnostic and therapeutic intervention.This study was supported in part by grants PID2019-104776RB-I00 and CB16/ 11/00399 (Dr de la Pompa) from the Spanish Ministerio de Ciencia e Innovación (MCIN/ AEI/ 10.13039/501100011033/); a grant from Hadassah France Association (Drs Gilon and Tessler); a grant from the Center for Interdisciplinary Data Science Research of the Hebrew University of Jerusalem (Dr Tessler); grant R35 CA220340 from the National Institutes of Health (Dr Blacklow), and grants R21HL150373, R01HL114823 (Dr Body); BSF grants 2013269 and 2017245 (Drs. Sprinzak and Blacklow); a consolidator grant from the European Research Council (Genomia – ERC-COG-2017-771945; Dr Loeys); the European Reference Network on rare multisystemic vascular disorders (VASCERN - project ID: 769036 partly cofunded by the European Union Third Health Programme (Drs Loeys and Verstraeten); funding from the Outreach project (Dutch Heart Foundation; Dr Luyckx); funding from Heart and Stroke Foundation of Canada/Robert M Freedom Chair of Cardiovascular Science (Dr Mital); sample biobanking and sequencing from Canada were supported by grants from the Leducq Foundation Transatlantic Networks of Excellence grant, and the Ted Rogers Centre for Heart Research; ISF grant 1053/12 (Dr Durst); and grant R01HL150401 from National Heart, Lung, and Blood Institute (Dr Muehlschlegel).S

    Candidate gene resequencing in a large bicuspid aortic valve-associated thoracic aortic aneurysm cohort: SMAD6 as an important contributor

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    Bicuspid aortic valve (BAV) is the most common congenital heart defect. Although many BAV patients remain asymptomatic, at least 20% develop thoracic aortic aneurysm (TAA). Historically, BAV-related TAA was considered as a hemodynamic consequence of the valve defect. Multiple lines of evidence currently suggest that genetic determinants contribute to the pathogenesis of both BAV and TAA in affected individuals. Despite high heritability, only very few genes have been linked to BAV or BAV/TAA, such as NOTCH1, SMAD6, and MAT2A. Moreover, they only explain a minority of patients. Other candidate genes have been suggested based on the presence of BAV in knockout mouse models (e.g., GATA5, NOS3) or in syndromic (e.g., TGFBR1/2, TGFB2/3) or non-syndromic (e.g., ACTA2) TAA forms. We hypothesized that rare genetic variants in these genes may be enriched in patients presenting with both BAV and TAA. We performed targeted resequencing of 22 candidate genes using Haloplex target enrichment in a strictly defined BAV/TAA cohort (n = 441; BAV in addition to an aortic root or ascendens diameter = 4.0 cm in adults, or a Z-score = 3 in children) and in a collection of healthy controls with normal echocardiographic evaluation (n = 183). After additional burden analysis against the Exome Aggregation Consortium database, the strongest candidate susceptibility gene was SMAD6 (p = 0.002), with 2.5% (n = 11) of BAV/TAA patients harboring causal variants, including two nonsense, one in-frame deletion and two frameshift mutations. All six missense mutations were located in the functionally important MH1 and MH2 domains. In conclusion, we report a significant contribution of SMAD6 mutations to the etiology of the BAV/TAA phenotype

    A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

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    Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

    Application des stratégies combinées utilisant le séquençage d'exome dans les maladies vasculaires rares

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    Identifying genes of Mendelian disorders has started within the eighties. The pace of new genes discovery has been dramatically accelerated by the availability of the human genome sequence in the 2000s, and the next-generation sequencing technologies in the 2010s. However, a majority of the elucidated conditions so far correspond to relatively simplified situations, where the prevalence and the penetrance of the condition are high and the genetic heterogeneity is low. Nowadays, geneticists meet more and more situations where gene identification in unknown disorders can be tricky. Heritable conditions that are very rare, heterogenous or with imperfect Mendelian transmission can only be elucidated using large cohorts of patients, with a very well-characterized phenotype. This requires clinical, financial and logistical efforts to be made by the research teams. Generally, using exome sequencing alone is not efficient enough to elucidate these types of conditions. The power of recently developed strategies comes from its association with other genetic analysis tools, that have been specifically developed in the context of rare, heterogenous, or polygenic disorders. I employed exome sequencing in the identification of cardiovascular genetic conditions, using three different strategies. In the first condition, called hereditary xerocytosis, using linkage analysis together with exome sequencing of distant relatives was successful in identifying the causative gene. This was made possible by the identification of a reliable endophenotype, and the relative genetic homogeneity of the disorder. The second condition I studied is the abdominal aortic aneurysm (AAA), a common disorder with a strong hereditary component and rare situations of fully penetrant, dominant inheritance. I combined exome sequencing in a family with dominant inheritance with rare variants analysis of the candidate gene in a large cohort of sporadic AAA. This analysis is more complex and can be hazardous in the context of a candidate gene approach. The third strategy was developed for the study of fibromuscular dysplasia (FMD) which is a very heterogenous condition with low penetrance and no specific endophenotype. I combined exome sequencing in a group of 30 cases and relatives with filtering strategies for any type of Mendelian inheritance. I also used available bioinformatics tools and databases for refining the candidate genes filtering. This strategy provided promising results, probably due to the genetic characteristics of this condition. In each of these examples, I adapted the analysis strategy to the peculiarities of the disorder. The results presented here enable to evaluate the efficiency of combined approaches using exome sequencing. Their specificities, limits, and the optimization that need to be done to elucidate the remaining unsolved genetic conditions are discussed.L’identification des gĂšnes de maladies Mendeliennes Ă©tĂ© rendue possible dans les annĂ©es 1980. Le sĂ©quençage du gĂ©nome humain dans les annĂ©es 2000, et l’arrivĂ©e du sĂ©quençage haut dĂ©bit dans les annĂ©es 2010 ont permis une progression phĂ©nomĂ©nale du rythme de ces dĂ©couvertes gĂ©nĂ©tiques. Cependant, ces techniques ont permis d’élucider les maladies les plus accessibles, de par leur homogĂ©nĂ©itĂ© gĂ©nĂ©tique, leur forte pĂ©nĂ©trance pour les maladies dominantes, et leur prĂ©valence Ă©levĂ©e. Aujourd’hui, la communautĂ© gĂ©nĂ©tique se heurte Ă  des difficultĂ©s de plus en plus nombreuses pour identifier les maladies non monogĂ©niques, hĂ©tĂ©rogĂšnes, ou trĂšs rares : recruter des familles porteuses d’une maladie trĂšs rare et cliniquement bien caractĂ©risĂ©e, ou de grandes cohortes de patients atteints de maladies communes Ă  composante gĂ©nĂ©tique, nĂ©cessite un effort clinique, logistique et financier important. De plus, le sĂ©quençage d’exome pris isolĂ©ment ne permet gĂ©nĂ©ralement pas l’élucidation de ces pathologies. Cet outil bien que puissant trouve ses limites dans les modĂšles gĂ©nĂ©tiques sus-citĂ©s. La rĂ©ussite des approches rĂ©centes vient de son utilisation en association avec d’autres techniques, adaptĂ©es aux caractĂ©ristiques des maladies comme la raretĂ©, la dimension polygĂ©nique, ou l’hĂ©tĂ©rogĂ©nĂ©itĂ© gĂ©nĂ©tique. J’ai utilisĂ© le sĂ©quençage d’exome dans l’identification de gĂšnes de maladies cardiovasculaires rares, par trois stratĂ©gies combinĂ©es diffĂ©rentes. La premiĂšre pathologie appelĂ©e stomatocytose hĂ©rĂ©ditaire, est rare, relativement homogĂšne mais prĂ©sente des difficultĂ©s de phĂ©notypage. Elle a Ă©tĂ© caractĂ©risĂ©e par sĂ©quençage d’exome en association avec une analyse de liaison traditionnelle et l’identification d’une endophĂ©notype fiable. Cette approche a Ă©tĂ© appliquĂ©e avec succĂšs dans ce modĂšle relativement peu complexe de maladie. La seconde pathologie Ă©tudiĂ©e, l’anĂ©vrysme de l’aorte abdominale (AAA), est une maladie commune Ă  forte composante hĂ©rĂ©ditaire, avec de rares formes dominantes Ă  pĂ©nĂ©trance Ă©levĂ©e. J’ai associĂ© sĂ©quençage d’exome en modĂšle dominant et recherche de variants rares dans une cohorte de cas sporadiques afin d’identifier un gĂšne de susceptibilitĂ© Ă  la pathologie. Cette approche s’est rĂ©vĂ©lĂ©e plus complexe Ă  mettre en place, et son efficacitĂ© peut ĂȘtre discutĂ©e dans le cas d'une Ă©tude d'association centrĂ©e sur un gĂšne candidat. Enfin, la troisiĂšme partie de ce travail est consacrĂ©e Ă  la dysplasie fibromusculaire (DFM), maladie trĂšs hĂ©tĂ©rogĂšne sur le plan gĂ©nĂ©tique, peu pĂ©nĂ©trante, et d’endophĂ©notype peu accessible. J’ai appliquĂ© dans cette troisiĂšme Ă©tape le sĂ©quençage d’exome Ă  plus grande Ă©chelle (30 individus), en association Ă  des stratĂ©gies de filtres sophistiquĂ©s exploitant tous les types de transmission MendĂ©lienne. J'y ai aussi associĂ© l'utilisation des outils bioinformatiques et bases de donnĂ©es biologiques accessibles Ă  la communautĂ© scientifique. Les rĂ©sultats obtenus par cette derniĂšre approche sont prometteurs, probablement du fait des caractĂ©ristiques inhĂ©rentes de cette pathologie. L’utilisation de ces trois stratĂ©gies trĂšs diffĂ©rentes, adaptĂ©es aux contraintes de chaque pathologie, permet d’évaluer la puissance et l’efficacitĂ© des approches combinĂ©es utilisant le sĂ©quençage d’exome. Leurs difficultĂ©s inhĂ©rentes, leur inadaptation Ă  certaines situations gĂ©nĂ©tiques, ainsi que les pistes d’amĂ©lioration nĂ©cessaires pour l’élucidation des maladies gĂ©nĂ©tiques de cause inconnue sont aussi abordĂ©s

    Combined genetic strategies using exome sequencing in rare vascular disorders

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    L’identification des gĂšnes de maladies Mendeliennes Ă©tĂ© rendue possible dans les annĂ©es 1980. Le sĂ©quençage du gĂ©nome humain dans les annĂ©es 2000, et l’arrivĂ©e du sĂ©quençage haut dĂ©bit dans les annĂ©es 2010 ont permis une progression phĂ©nomĂ©nale du rythme de ces dĂ©couvertes gĂ©nĂ©tiques. Cependant, ces techniques ont permis d’élucider les maladies les plus accessibles, de par leur homogĂ©nĂ©itĂ© gĂ©nĂ©tique, leur forte pĂ©nĂ©trance pour les maladies dominantes, et leur prĂ©valence Ă©levĂ©e. Aujourd’hui, la communautĂ© gĂ©nĂ©tique se heurte Ă  des difficultĂ©s de plus en plus nombreuses pour identifier les maladies non monogĂ©niques, hĂ©tĂ©rogĂšnes, ou trĂšs rares : recruter des familles porteuses d’une maladie trĂšs rare et cliniquement bien caractĂ©risĂ©e, ou de grandes cohortes de patients atteints de maladies communes Ă  composante gĂ©nĂ©tique, nĂ©cessite un effort clinique, logistique et financier important. De plus, le sĂ©quençage d’exome pris isolĂ©ment ne permet gĂ©nĂ©ralement pas l’élucidation de ces pathologies. Cet outil bien que puissant trouve ses limites dans les modĂšles gĂ©nĂ©tiques sus-citĂ©s. La rĂ©ussite des approches rĂ©centes vient de son utilisation en association avec d’autres techniques, adaptĂ©es aux caractĂ©ristiques des maladies comme la raretĂ©, la dimension polygĂ©nique, ou l’hĂ©tĂ©rogĂ©nĂ©itĂ© gĂ©nĂ©tique. J’ai utilisĂ© le sĂ©quençage d’exome dans l’identification de gĂšnes de maladies cardiovasculaires rares, par trois stratĂ©gies combinĂ©es diffĂ©rentes. La premiĂšre pathologie appelĂ©e stomatocytose hĂ©rĂ©ditaire, est rare, relativement homogĂšne mais prĂ©sente des difficultĂ©s de phĂ©notypage. Elle a Ă©tĂ© caractĂ©risĂ©e par sĂ©quençage d’exome en association avec une analyse de liaison traditionnelle et l’identification d’une endophĂ©notype fiable. Cette approche a Ă©tĂ© appliquĂ©e avec succĂšs dans ce modĂšle relativement peu complexe de maladie. La seconde pathologie Ă©tudiĂ©e, l’anĂ©vrysme de l’aorte abdominale (AAA), est une maladie commune Ă  forte composante hĂ©rĂ©ditaire, avec de rares formes dominantes Ă  pĂ©nĂ©trance Ă©levĂ©e. J’ai associĂ© sĂ©quençage d’exome en modĂšle dominant et recherche de variants rares dans une cohorte de cas sporadiques afin d’identifier un gĂšne de susceptibilitĂ© Ă  la pathologie. Cette approche s’est rĂ©vĂ©lĂ©e plus complexe Ă  mettre en place, et son efficacitĂ© peut ĂȘtre discutĂ©e dans le cas d'une Ă©tude d'association centrĂ©e sur un gĂšne candidat. Enfin, la troisiĂšme partie de ce travail est consacrĂ©e Ă  la dysplasie fibromusculaire (DFM), maladie trĂšs hĂ©tĂ©rogĂšne sur le plan gĂ©nĂ©tique, peu pĂ©nĂ©trante, et d’endophĂ©notype peu accessible. J’ai appliquĂ© dans cette troisiĂšme Ă©tape le sĂ©quençage d’exome Ă  plus grande Ă©chelle (30 individus), en association Ă  des stratĂ©gies de filtres sophistiquĂ©s exploitant tous les types de transmission MendĂ©lienne. J'y ai aussi associĂ© l'utilisation des outils bioinformatiques et bases de donnĂ©es biologiques accessibles Ă  la communautĂ© scientifique. Les rĂ©sultats obtenus par cette derniĂšre approche sont prometteurs, probablement du fait des caractĂ©ristiques inhĂ©rentes de cette pathologie. L’utilisation de ces trois stratĂ©gies trĂšs diffĂ©rentes, adaptĂ©es aux contraintes de chaque pathologie, permet d’évaluer la puissance et l’efficacitĂ© des approches combinĂ©es utilisant le sĂ©quençage d’exome. Leurs difficultĂ©s inhĂ©rentes, leur inadaptation Ă  certaines situations gĂ©nĂ©tiques, ainsi que les pistes d’amĂ©lioration nĂ©cessaires pour l’élucidation des maladies gĂ©nĂ©tiques de cause inconnue sont aussi abordĂ©s.Identifying genes of Mendelian disorders has started within the eighties. The pace of new genes discovery has been dramatically accelerated by the availability of the human genome sequence in the 2000s, and the next-generation sequencing technologies in the 2010s. However, a majority of the elucidated conditions so far correspond to relatively simplified situations, where the prevalence and the penetrance of the condition are high and the genetic heterogeneity is low. Nowadays, geneticists meet more and more situations where gene identification in unknown disorders can be tricky. Heritable conditions that are very rare, heterogenous or with imperfect Mendelian transmission can only be elucidated using large cohorts of patients, with a very well-characterized phenotype. This requires clinical, financial and logistical efforts to be made by the research teams. Generally, using exome sequencing alone is not efficient enough to elucidate these types of conditions. The power of recently developed strategies comes from its association with other genetic analysis tools, that have been specifically developed in the context of rare, heterogenous, or polygenic disorders. I employed exome sequencing in the identification of cardiovascular genetic conditions, using three different strategies. In the first condition, called hereditary xerocytosis, using linkage analysis together with exome sequencing of distant relatives was successful in identifying the causative gene. This was made possible by the identification of a reliable endophenotype, and the relative genetic homogeneity of the disorder. The second condition I studied is the abdominal aortic aneurysm (AAA), a common disorder with a strong hereditary component and rare situations of fully penetrant, dominant inheritance. I combined exome sequencing in a family with dominant inheritance with rare variants analysis of the candidate gene in a large cohort of sporadic AAA. This analysis is more complex and can be hazardous in the context of a candidate gene approach. The third strategy was developed for the study of fibromuscular dysplasia (FMD) which is a very heterogenous condition with low penetrance and no specific endophenotype. I combined exome sequencing in a group of 30 cases and relatives with filtering strategies for any type of Mendelian inheritance. I also used available bioinformatics tools and databases for refining the candidate genes filtering. This strategy provided promising results, probably due to the genetic characteristics of this condition. In each of these examples, I adapted the analysis strategy to the peculiarities of the disorder. The results presented here enable to evaluate the efficiency of combined approaches using exome sequencing. Their specificities, limits, and the optimization that need to be done to elucidate the remaining unsolved genetic conditions are discussed

    Exploration du gĂšne de la plakophiline dans le syndrome de Brugada familial

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    Le syndrome de Brugada est une affection hĂ©rĂ©ditaire associant un risque accru de troubles du rythme et de mort subite Ă  un profil Ă©lectrogardiographique particulier. Cette maladie est caractĂ©risĂ©e par une atteinte fonctionnelle et parfois structurale du ventricule droit, et partage des Ă©lĂ©ments cliniques et histologiques avec une autre affection gĂ©nĂ©tique : la Dysplasie ArythmogĂšne du Ventricule Droit (ou DAVD). Cette derniĂšre est majoritairement liĂ©e Ă  un dĂ©faut de la structure du myocarde impliquant les desmosomes. PKP2, gĂšne de protĂ©ine desmosomale, est le gĂšne majeur de cette affection. Le syndrome de Brugada est gĂ©nĂ©tiquement hĂ©tĂ©rogĂšne, transmis sur un mode autosomique dominant, et sa pĂ©nĂ©trance est incomplĂšte : SCN5A, codant le canal sodique spĂ©cifique du myocarde, est le seul gĂšne responsable que l on connaisse. Il n est mutĂ© que chez 20% des patients. La dĂ©couverte de l implication de SCN5A dans cette maladie n a pas pour autant permis d Ă©claircir sa physiopathologie complexe. L hypothĂšse d un dĂ©faut de la structure myocardique, sous-tendu par le chevauchement phĂ©notypique qui existe avec la DAVD, est ici explorĂ©e. Dans cette thĂšse sont prĂ©sentĂ©s les rĂ©sultats de l Ă©tude du gĂšne PKP2 dans une cinquantaine de cas de syndrome de Brugada familial. Les rĂ©sultats de cette analyse montrent que ces deux entitĂ©s sont distinctes sur le plan gĂ©nĂ©tique, mais n excluent pas totalement qu un dĂ©faut de structure puisse ĂȘtre Ă  l origine de ce syndrome. Les hypothĂšses actuelles proposĂ©es pour Ă©lucider la physiopathologie de ce syndrome sont discutĂ©es, ainsi que les causes potentielles du dĂ©faut de pĂ©nĂ©trance qui y est associĂ©.PARIS6-Bibl.PitiĂ©-SalpĂȘtrie (751132101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF
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