Variante genética del síndrome de Stickler

Cabrera, Pedro Rocha; Dorta, L. Cordovés; García, Miguel Ángel Serrano; Castillo, M. J. Losada; Reyes, José Augusto Abreu; Resa, M. Gómez

doi:10.1016/j.oftal.2017.07.003

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…Entretanto, o diagnóstico é bastante complexo, pois esta doença se assemelha a outras síndromes e apresenta variabilidade genética pouco específica. Apesar de não haver cura, o diagnóstico precoce e uma rápida intervenção médica torna-se fundamental e essencial para um melhor prognóstico e acompanhamento das possíveis complicações associadas à síndrome (CABRERA et al, 2018;.…”

Section: Manifestaçõesunclassified

Síndrome de Stickler

Oliveira¹,

Oliveira²,

Ramos³

et al. 2022

Braz. J. Hea. Rev.

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INTRODUÇÃO: A Síndrome Stickler é uma colagenopatia, rara, hereditária e caráter autossômica dominante, sua incidência é de 1/7500 nascimentos. APRESENTAÇÃO CASO: GPS, sexo masculino, 5 anos, admitido no Hospital das Clínicas de Goiânia, portador de miopia importante e fissura palatina desde o nascimento, queixava-se de baixa acuidade visual há 3meses. Durante a inspeção, foram evidenciados face plana, maxilar curto, olhos proeminentes e pregas epicantais. DISCUSSÃO: A síndrome é caracterizada por um artro-oftalmopatia, ou seja, anormalidades esqueléticas, anomalias orofaciais, perda auditiva, osteoartrite prematura, perda neuro-sensorial,fenda palatina, miopatia grave e cegueira. É classificada de acordo com a mutação em Tipo I, II e III. CONCLUSÃO: Por se tratar de uma síndrome genética rara, é de difícil diagnóstico, necessita de uma análise fenotípica, um quadro clínico favorável e história familiar. Não existe um tratamento curativo. Portanto, quanto mais precoce seu diagnóstico, a intervenção será mais rápida e melhor será o prognóstico.

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Section: Manifestaçõesunclassified

Síndrome de Stickler

Oliveira¹,

Oliveira²,

Ramos³

et al. 2022

Braz. J. Hea. Rev.

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“…There are disorders having a great overlap of clinical signs with MFS and collected under the definition of Marfan-like phenotype [8]: e.g. Loeys-Dietz Syndrome (LDS), Ehlers-Danlos Syndrome [9] (EDS), and Familial Thoracic Aortic Aneurysm and Dissection [10] (TAAD), Ectopia Lentis Syndrome [11] (ELS), Beals Syndrome [12] (BS), Sticler Syndrome [13] (SS), Bicuspid Aortic Valve [14] (BAV) and MASS phenotype [15] (Mitral valve, myopia, Aorta, Skin and Skeletal features of the disorder). The complexity of MFS clinical picture and its unpredictable course were extensively studied in the last decades, especially trying to elucidate the genotype-phenotype correlations of MFS and Marfan-like habitus .…”

Section: Introductionmentioning

confidence: 99%

NGS analysis in Marfan syndrome spectrum: Combination of rare and common genetic variants to improve genotype-phenotype correlation analysis

et al. 2019

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The diagnosis of Marfan spectrum includes a large number of clinical criteria. Although the identification of pathogenic variants contributes to the diagnostic process, its value to the prediction of clinical outcomes is still limited. An important novelty of the present study is represented by the statistical approach adopted to investigate genotype-phenotype correlation. The analysis has been improved considering the extended genetic information obtained by Next Generation Sequencing (NGS) and combining the effects of both rare and common genetic variants in an inclusive model. To this aim a cohort of 181 patients were analyzed with a NGS panel including 11 genes associated with Marfan spectrum. The genotype-phenotype correlation was also investigated considering the possibility to predict presence of a pathological mutation in Marfan syndrome (MFS) main genes based only on the analysis of phenotypic traits. Results obtained indicate that information about clinical traits can be summarized in a new variable that resulted significantly associated with the probability to find a pathological mutation in MFS main genes. This is important since the choice of the genetic test is often influenced by the phenotypic characterization of patients. Moreover, both rare and common variants were found to significantly contribute to clinical spectrum and their combination allowed to increase the percentage of phenotype variability that could be explained based on genetic factors. Results highlight the opportunity to take advantage of the overall genetic information obtained by NGS data to have a better clinical classification of patients.

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