73 research outputs found

    Myasthenia gravis and pregnancy: clinical implications and neonatal outcome

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    BACKGROUND: The myasthenia gravis is twice as common in women as in men and frequently affects young women in the second and third decades of life, overlapping with the childbearing years. Generally, during pregnancy in one third of patients the disease exacerbates, whereas in two thirds it remains clinically unchanged. Complete remission can occur in some patients. METHODS: To describe the clinical course, delivery and neonatal outcome of 18 pregnant women with the diagnosis of myasthenia gravis. Retrospective chart review of pregnant patients with myasthenia gravis, followed at the National Institute of Perinatology in Mexico City over an 8-year period. Data was abstracted from the medical records on the clinical course during pregnancy, delivery and neonatal outcome. RESULTS: From January 1, 1996 to December 31, 2003 18 patients with myasthenia gravis were identified and included in the study. The mean ± SD maternal age was 27.4 ± 4.0 years. During pregnancy 2 women (11%) had an improvement in the clinical symptoms of myasthenia gravis, 7 women (39%) had clinical worsening of the condition of 9 other patients (50%) remained clinically unchanged. Nine patients delivered vaginally, 8 delivered by cesarean section and 1 pregnancy ended in fetal loss. Seventeen infants were born at mean ± SD gestational age of 37.5 ± 3.0 weeks and a mean birth weight of 2710 ± 73 g. Only one infant presented with transient neonatal myasthenia gravis. No congenital anomalies were identified in any of the newborns. CONCLUSIONS: The clinical course of myasthenia gravis during pregnancy is variable, with a significant proportion of patients experiencing worsening of the clinical symptoms. However, neonatal transient myasthenia was uncommon in our patient population

    A genome-wide association study of myasthenia gravis

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    IMPORTANCE: Myasthenia gravis is a chronic, autoimmune, neuromuscular disease characterized by fluctuating weakness of voluntary muscle groups. Although genetic factors are known to play a role in this neuroimmunological condition, the genetic etiology underlying myasthenia gravis is not well understood. OBJECTIVE: To identify genetic variants that alter susceptibility to myasthenia gravis, we performed a genome-wide association study. DESIGN, SETTING, AND PARTICIPANTS: DNA was obtained from 1032 white individuals from North America diagnosed as having acetylcholine receptor antibody–positive myasthenia gravis and 1998 race/ethnicity-matched control individuals from January 2010 to January 2011. These samples were genotyped on Illumina OmniExpress single-nucleotide polymorphism arrays. An independent cohort of 423 Italian cases and 467 Italian control individuals were used for replication. MAIN OUTCOMES AND MEASURES: We calculated P values for association between 8114394 genotyped and imputed variants across the genome and risk for developing myasthenia gravis using logistic regression modeling. A threshold P value of 5.0 × 10(−8) was set for genome-wide significance after Bonferroni correction for multiple testing. RESULTS: In the over all case-control cohort, we identified association signals at CTLA4 (rs231770; P = 3.98 × 10(−8); odds ratio, 1.37; 95% CI, 1.25–1.49), HLA-DQA1 (rs9271871; P = 1.08 × 10(−8); odds ratio, 2.31; 95% CI, 2.02 – 2.60), and TNFRSF11A (rs4263037; P = 1.60 × 10(−9); odds ratio, 1.41; 95% CI, 1.29–1.53). These findings replicated for CTLA4 and HLA-DQA1 in an independent cohort of Italian cases and control individuals. Further analysis revealed distinct, but overlapping, disease-associated loci for early- and late-onset forms of myasthenia gravis. In the late-onset cases, we identified 2 association peaks: one was located in TNFRSF11A (rs4263037; P = 1.32 × 10(−12); odds ratio, 1.56; 95% CI, 1.44–1.68) and the other was detected in the major histocompatibility complex on chromosome 6p21 (HLA-DQA1; rs9271871; P = 7.02 × 10(−18); odds ratio, 4.27; 95% CI, 3.92–4.62). Association within the major histocompatibility complex region was also observed in early-onset cases (HLA-DQA1; rs601006; P = 2.52 × 10(−11); odds ratio, 4.0; 95% CI, 3.57–4.43), although the set of single-nucleotide polymorphisms was different from that implicated among late-onset cases. CONCLUSIONS AND RELEVANCE: Our genetic data provide insights into aberrant cellular mechanisms responsible for this prototypical autoimmune disorder. They also suggest that clinical trials of immunomodulatory drugs related to CTLA4 and that are already Food and Drug Administration approved as therapies for other autoimmune diseases could be considered for patients with refractory disease

    CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

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    Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research

    Associating mutations causing cystinuria with disease severity with the aim of providing precision medicine

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    Background Cystinuria is an inherited disease that results in the formation of cystine stones in the kidney, which can have serious health complications. Two genes (SLC7A9 and SLC3A1) that form an amino acid transporter are known to be responsible for the disease. Variants that cause the disease disrupt amino acid transport across the cell membrane, leading to the build-up of relatively insoluble cystine, resulting in formation of stones. Assessing the effects of each mutation is critical in order to provide tailored treatment options for patients. We used various computational methods to assess the effects of cystinuria associated mutations, utilising information on protein function, evolutionary conservation and natural population variation of the two genes. We also analysed the ability of some methods to predict the phenotypes of individuals with cystinuria, based on their genotypes, and compared this to clinical data. Results Using a literature search, we collated a set of 94 SLC3A1 and 58 SLC7A9 point mutations known to be associated with cystinuria. There are differences in sequence location, evolutionary conservation, allele frequency, and predicted effect on protein function between these mutations and other genetic variants of the same genes that occur in a large population. Structural analysis considered how these mutations might lead to cystinuria. For SLC7A9, many mutations swap hydrophobic amino acids for charged amino acids or vice versa, while others affect known functional sites. For SLC3A1, functional information is currently insufficient to make confident predictions but mutations often result in the loss of hydrogen bonds and largely appear to affect protein stability. Finally, we showed that computational predictions of mutation severity were significantly correlated with the disease phenotypes of patients from a clinical study, despite different methods disagreeing for some of their predictions. Conclusions The results of this study are promising and highlight the areas of research which must now be pursued to better understand how mutations in SLC3A1 and SLC7A9 cause cystinuria. The application of our approach to a larger data set is essential, but we have shown that computational methods could play an important role in designing more effective personalised treatment options for patients with cystinuria

    Associating mutations causing cystinuria with disease severity with the aim of providing precision medicine

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    Background Cystinuria is an inherited disease that results in the formation of cystine stones in the kidney, which can have serious health complications. Two genes (SLC7A9 and SLC3A1) that form an amino acid transporter are known to be responsible for the disease. Variants that cause the disease disrupt amino acid transport across the cell membrane, leading to the build-up of relatively insoluble cystine, resulting in formation of stones. Assessing the effects of each mutation is critical in order to provide tailored treatment options for patients. We used various computational methods to assess the effects of cystinuria associated mutations, utilising information on protein function, evolutionary conservation and natural population variation of the two genes. We also analysed the ability of some methods to predict the phenotypes of individuals with cystinuria, based on their genotypes, and compared this to clinical data. Results Using a literature search, we collated a set of 94 SLC3A1 and 58 SLC7A9 point mutations known to be associated with cystinuria. There are differences in sequence location, evolutionary conservation, allele frequency, and predicted effect on protein function between these mutations and other genetic variants of the same genes that occur in a large population. Structural analysis considered how these mutations might lead to cystinuria. For SLC7A9, many mutations swap hydrophobic amino acids for charged amino acids or vice versa, while others affect known functional sites. For SLC3A1, functional information is currently insufficient to make confident predictions but mutations often result in the loss of hydrogen bonds and largely appear to affect protein stability. Finally, we showed that computational predictions of mutation severity were significantly correlated with the disease phenotypes of patients from a clinical study, despite different methods disagreeing for some of their predictions. Conclusions The results of this study are promising and highlight the areas of research which must now be pursued to better understand how mutations in SLC3A1 and SLC7A9 cause cystinuria. The application of our approach to a larger data set is essential, but we have shown that computational methods could play an important role in designing more effective personalised treatment options for patients with cystinuria

    Seronegative myasthenia gravis (SNMG): treatment with semiselective immunoadsorption columns”.

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    trattamento dei pazienti affetti da miastenia grave attraverso l'impiego di plasmaferesi con colonna immunoassorbente anticorpi antiacetilcolina
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