29 research outputs found

    MTMR4 SNVs modulate ion channel degradation and clinical severity in congenital long QT syndrome: insights in the mechanism of action of protective modifier genes

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    Abstract Aims In long QT syndrome (LQTS) patients, modifier genes modulate the arrhythmic risk associated with a disease-causing mutation. Their recognition can improve risk stratification and clinical management, but their discovery represents a challenge. We tested whether a cellular-driven approach could help to identify new modifier genes and especially their mechanism of action. Methods and results We generated human-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) from two patients carrying the same KCNQ1-Y111C mutation, but presenting opposite clinical phenotypes. We showed that the phenotype of the iPSC-CMs derived from the symptomatic patient is due to impaired trafficking and increased degradation of the mutant KCNQ1 and wild-type human ether-a-go-go-related gene. In the iPSC-CMs of the asymptomatic (AS) patient, the activity of an E3 ubiquitin-protein ligase (Nedd4L) involved in channel protein degradation was reduced and resulted in a decreased arrhythmogenic substrate. Two single-nucleotide variants (SNVs) on the Myotubularin-related protein 4 (MTMR4) gene, an interactor of Nedd4L, were identified by whole-exome sequencing as potential contributors to decreased Nedd4L activity. Correction of these SNVs by CRISPR/Cas9 unmasked the LQTS phenotype in AS cells. Importantly, the same MTMR4 variants were present in 77% of AS Y111C mutation carriers of a separate cohort. Thus, genetically mediated interference with Nedd4L activation seems associated with protective effects. Conclusion Our finding represents the first demonstration of the cellular mechanism of action of a protective modifier gene in LQTS. It provides new clues for advanced risk stratification and paves the way for the design of new therapies targeting this specific molecular pathway

    Transethnic Genome-Wide Association Study Provides Insights in the Genetic Architecture and Heritability of Long QT Syndrome

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    BACKGROUND: Long QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility. METHODS: We conducted genome-wide association studies followed by transethnic meta-analysis in 1656 unrelated patients with LQTS of European or Japanese ancestry and 9890 controls to identify susceptibility single nucleotide polymorphisms. We estimated the common variant heritability of LQTS and tested the genetic correlation between LQTS susceptibility and other cardiac traits. Furthermore, we tested the aggregate effect of the 68 single nucleotide polymorphisms previously associated with the QT-interval in the general population using a polygenic risk score. RESULTS: Genome-wide association analysis identified 3 loci associated with LQTS at genome-wide statistical significance (P&lt;5×10-8) near NOS1AP, KCNQ1, and KLF12, and 1 missense variant in KCNE1(p.Asp85Asn) at the suggestive threshold (P&lt;10-6). Heritability analyses showed that ≈15% of variance in overall LQTS susceptibility was attributable to common genetic variation (h2SNP 0.148; standard error 0.019). LQTS susceptibility showed a strong genome-wide genetic correlation with the QT-interval in the general population (rg=0.40; P=3.2×10-3). The polygenic risk score comprising common variants previously associated with the QT-interval in the general population was greater in LQTS cases compared with controls (P&lt;10-13), and it is notable that, among patients with LQTS, this polygenic risk score was greater in patients who were genotype negative compared with those who were genotype positive (P&lt;0.005). CONCLUSIONS: This work establishes an important role for common genetic variation in susceptibility to LQTS. We demonstrate overlap between genetic control of the QT-interval in the general population and genetic factors contributing to LQTS susceptibility. Using polygenic risk score analyses aggregating common genetic variants that modulate the QT-interval in the general population, we provide evidence for a polygenic architecture in genotype negative LQTS.</p

    mromanello/ADA-DHOxSS: ADA-DHOxSS2023

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    Teaching materials for the ADA 2023 strand at the Digital Humanities Oxford Summer School, co-taught with Nilo Pedrazzini

    Radiological exposure of patients undergoing transcatheter aortic valve implantation in contemporary practice

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    BACKGROUND Radiological exposure associated with transcatheter aortic valve implantation (TAVI) is unknown and might impact on broadening indications to lower risk patients. Radiological exposure of TAVI patients and its predictors are herein reported. METHODS Radiological exposure derived from exams/procedures performed within 30 days preceding/following TAVI were acquired and converted into effective-dose. Total effective-dose was defined as the sum of each single dose derived from diagnostic/therapeutic sources. Univariable and multivariable analyses were performed to recognize correlates of exposure. RESULTS Seventy-five patients aged 82.6 ± 6.0 years with a median Euroscore II 3.6 [IQR 1.93-6.65] were analysed. Median total effective-dose was 41.39 mSv [IQR 27.93-60.88], with TAVI accounting for 47% of it. Age (coefficient -0.031, 95% CI -0.060 to -0.002; P = 0.031) and previous history of cerebrovascular accidents (CVA; coefficient -0.545; 95% CI -1.039 to -0.010; P = 0.046) resulted as inversely correlated to total effective-dose (log-transformed), whereas left ventricular ejection fraction (LVEF) less than 50% (coefficient 0.430, 95% CI 0.031-0.828; P = 0.035) was directly associated. CONCLUSION Multiple radiological sources are responsible for the observed exposure, with TAVI being the prominent source. Age is inversely related to the radiological exposure

    Sostenibilità in sanità

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    In un mondo in cui la crescita economica è stata per lungo tempo l’obiettivo primario in ogni ambito industriale, emerge con forza la necessità di integrare la sostenibilità ambientale e sociale nelle strategie e attività aziendali. La necessità di operare in modo sempre più sostenibile è trasversale a tutti i settori ma assume un carattere particolare nei settori che sono naturalmente connessi al benessere sociale e ambientale della società nel suo complesso. È il caso delle aziende attive nel settore sanitario, le quali con il proprio operato contribuiscono direttamente ad assicurare la salute e il benessere all’intera popolazione, rivestendo un ruolo ad alto impatto sociale per la natura delle attività svolte. Nell’ambito della propria missione ad alto valore sociale, come operano le aziende sanitarie nei confronti dei propri stakeholder? Quale è l’impatto di tali attività e processi sull’ambiente naturale? Come e quanto le aziende della sanità stanno integrando la sostenibilità sociale e ambientale nelle proprie strategie

    <i>JAK2</i> Exon 14 Skipping in Patients with Primary Myelofibrosis: A Minor Splice Variant Modulated by the JAK2-V617F Allele Burden

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    <div><p>Background</p><p>Primary myelofibrosis (PMF) is an acquired clonal disease of the hematopoietic stem cell compartment, characterized by bone marrow fibrosis, anemia, splenomegaly and extramedullary hematopoiesis. About 60% of patients with PMF harbor a somatic mutation of the <i>JAK2</i> gene (JAK2-V617F) in their hematopoietic lineage. Recently, a splicing isoform of <i>JAK2</i>, lacking exon 14 (JAK2Δ14) was described in patients affected by myeloproliferative diseases.</p><p>Materials and Methods</p><p>By using a specific RT-qPCR method, we measured the ratio between the splicing isoform and the <i>JAK2</i> full-length transcript (JAK2+14) in granulocytes, isolated from peripheral blood, of forty-four patients with PMF and nine healthy donors.</p><p>Results</p><p>We found that JAK2Δ14 was only slightly increased in patients and, at variance with published data, the splicing isoform was also detectable in healthy controls. We also found that, in patients bearing the JAK2-V617F mutation, the percentage of mutated alleles correlated with the observed increase in JAK2Δ14. Homozygosity for the mutation was also associated with a higher level of JAK2+14. Bioinformatic analysis indicates the possibility that the G>T transversion may interfere with the correct splicing of exon 14 by modifying a splicing regulatory sequence.</p><p>Conclusions</p><p>Increased levels of <i>JAK2</i> full-length transcript and a small but significant increase in <i>JAK2</i> exon 14 skipping, are associated with the JAK2-V617F allele burden in PMF granulocytes. Our data do not confirm a previous claim that the production of the JAK2Δ14 isoform is related to the pathogenesis of PMF.</p></div

    Eight short notes on the parallel tables

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    The paper contains the comments of the chairs who coordinated the eight parallel tables that took place during the conference. The organization of the tables started from the three main tracks (track A: genealogy/Poetic; track B: Metamprphosis/Actions; track C: Multiplicity/Communication), but it has undergone decisive variations according to some thematic and/or interpretative affinities and/ or divergences. These variations were identified among some papers that do not necessarily adhere to the same track and which were presented by the authors who participated in the parallel sessions

    Regression analysis.

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    <p>Shows that the proportion of mutated alleles in the genomic DNA corresponds to the proportion of mutated transcripts (Y = 0.293 + 1.012 * <i>x</i>, <i>R</i><sup>2</sup> = 0.983).</p
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