Biology subjects

Olivotto, I.

Publications and source records attributed to Olivotto, I..

4 recordsLinked to original sources

bioRxiv2025

Long-term mavacamten exposure reduces force and sarcomere density in a hiPSC model of hypertrophic cardiomyopathy

BackgroundMavacamten, a first-in-class allosteric myosin inhibitor, has demonstrated efficacy and safety in obstructive hypertrophic cardiomyopathy (oHCM), notably reducing symptoms, left ventricular outflow obstruction, and wall thickness over 30 weeks. We recently reported that the MYBPC3:c.772G>A variant causes HCM through cMyBP-C haploinsufficiency, leading to accelerated sarcomere kinetics and higher energy consumption in patient myocardium and hiPSC- derived cardiomyocytes (hiPSC-CMs). These effects are counterbalanced by prolonged action potentials and slower Ca{superscript 2} transients, which preserve twitch duration but may increase arrhythmic risk. Mavacamten may reduce myocardial energetic defects in HCM. ObjectivesTo investigate the long-term effects of Mavacamten on sarcomere structure, contractility, and transcriptional remodeling using patient-specific and CRISPR-corrected isogenic hiPSC-derived cardiomyocyte models of HCM. MethodsHiPSC-CMs and engineered heart tissues (EHTs) derived from a MYBPC3:c.772G>A patient and its CRISPR-corrected line were first exposed to increasing concentrations of Mavacamten to assess acute dose-response relationships and determine IC50 values. Based on these data, chronic treatments (0.3- 0.75 M for 20 days) were performed mechanical, structural, electrophysiological, and transcriptomic adaptations. ResultsAcute exposure produced a rapid and fully reversible reduction in active force, while chronic treatment for 20 days induced a sustained decrease in contractility with incomplete recovery after 4 days of washout, indicating a two-phase mechanism of action. Long-term force reduction was paralleled by decreased cell area and sarcomere density, indicating that structural disassembly contributes to sustained functional depression and re-assembly after washout. Electrophysiological analysis confirmed the specific alterations of the MYBPC3:c.772G>A mutation previously observed, with no detectable effects following treatment with Mavacamten. In addition, transcriptome analysis was used to study the molecular mechanisms underlying the long-term effect. ConclusionsMavacamten induces a biphasic, persistent-to-reversible, reduction of sarcomeric force associated with structural remodeling, providing mechanistic insight into its capacity to promote favorable cardiac remodeling in oHCM.

physiology↗

bioRxiv2020

Computational prediction of protein subdomain stability in MYBPC3 enables clinical risk stratification in hypertrophic cardiomyopathy and enhances variant interpretation.

PurposeVariants in MYBPC3 causing loss-of-function are the most common cause of HCM. However, a substantial number of patients carry missense variants of uncertain significance (VUS) in MYBPC3. We hypothesize that a structural-based algorithm, STRUM, which estimates the effect of missense variants on protein folding, will improve clinical risk stratification of patients with HCM and a MYBPC3 VUS. MethodsAmong 7,963 patients in the multi-center Sarcomeric Human Cardiomyopathy Registry, 120 unique missense VUSs in MYBPC3 were identified. Variants were evaluated for their effect on subdomain folding and a stratified time-to-event analysis for an overall composite endpoint (first occurrence of ventricular arrhythmia, heart failure, all-cause mortality, atrial fibrillation, and stroke) was performed for patients with HCM and a MYBPC3 missense VUS. ResultsWe demonstrated that patients carrying a MYBPC3 VUS predicted to cause subdomain misfolding (STRUM +, {Delta}{Delta}G [≤]-1.2 kcal/mol) exhibited a higher rate of adverse events compared to those with a STRUM-VUS (Hazard Ratio=2.29, P=0.0282). In silico saturation mutagenesis of MYBPC3 identified 4,943/23,427 (21%) missense variants that were predicted to cause subdomain misfolding. ConclusionsSTRUM enables clinical risk stratification of patients with HCM and a MYBPC3 VUS and has the capacity to improve prognostic predictions and clinical decision making.

genetics↗

bioRxiv2020

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

BackgroundAccurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning tools are useful for genome-wide variant prioritisation but remain imprecise. Since the relationship between molecular consequence and likelihood of pathogenicity varies between genes with distinct molecular mechanisms, we hypothesised that a disease-specific classifier may outperform existing genome-wide tools. MethodsWe present a novel disease-specific variant classification tool, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias, trained with variants of known clinical effect. To benchmark against state-of-the-art genome-wide pathogenicity classification tools, we assessed classification of hold-out test variants using both overall performance metrics, and metrics of high-confidence (>90%) classifications relevant to variant interpretation. We further evaluated the prioritisation of variants associated with disease and patient clinical outcomes, providing validations that are robust to potential mis-classification in gold-standard reference datasets. ResultsCardioBoost has higher discriminating power than published genome-wide variant classification tools in distinguishing between pathogenic and benign variants based on overall classification performance measures with the highest area under the Precision-Recall Curve as 91% for cardiomyopathies and as 96% for inherited arrhythmias. When assessed at high-confidence (>90%) classification thresholds, prediction accuracy is improved by at least 120% over existing tools for both cardiomyopathies and arrhythmias, with significantly improved sensitivity and specificity. Finally, CardioBoost improves prioritisation of variants significantly associated with disease, and stratifies survival of patients with cardiomyopathies, confirming biologically relevant variant classification. ConclusionsWe demonstrate that a disease-specific variant pathogenicity prediction tool outperforms state-of-the-art genome-wide tools for the classification of rare missense variants of uncertain significance for inherited cardiac conditions. To facilitate evaluation of CardioBoost, we provide pre-computed pathogenicity scores for all possible rare missense variants in genes associated with cardiomyopathies and arrhythmias (https://www.cardiodb.org/cardioboost/). Our results also highlight the need to develop and evaluate variant classification tools focused on specific diseases and clinical application contexts. Our proposed model for assessing variants in known disease genes, and the use of application-specific evaluations, is broadly applicable to improve variant interpretation across a wide range of Mendelian diseases.

genetics↗

bioRxiv2018

Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: The case of hypertrophic cardiomyopathy

BackgroundInternational guidelines for variant interpretation in Mendelian disease set stringent criteria to report a variant as (likely) pathogenic, prioritising control of false positive rate over test sensitivity and diagnostic yield. Genetic testing is also more likely informative in individuals with well-characterised variants from extensively studied European-ancestry populations. Inherited cardiomyopathies are relatively common Mendelian diseases that allow empirical calibration and assessment of this framework.\n\nResultsWe compared rare variants in large hypertrophic cardiomyopathy (HCM) cohorts to reference populations to identify variant classes with high prior likelihoods of pathogenicity, as defined by etiological fraction (EF). Analysis of variant distribution identified regions in which variants are significantly enriched in cases and variant location was a better discriminator of pathogenicity than generic computational functional prediction algorithms. Non-truncating variant classes with an EF[≥]0.95, and therefore clinically actionable, were identified in 5 established HCM genes. Applying this approach leads to an estimated 14-20% increase in cases with actionable HCM variants.\n\nConclusionsWhen found in a patient confirmed to have disease, novel variants in some genes and regions are empirically shown to have a sufficiently high probability of pathogenicity to support a \"likely pathogenic\" classification, even without additional segregation or functional data. This could increase the yield of high confidence actionable variants, consistent with the framework and recommendations of current guidelines. The techniques outlined offer a consistent, unbiased and equitable approach to variant interpretation for Mendelian disease genetic testing. We propose adaptations to ACMG/AMP guidelines to incorporate such evidence in a quantitative and transparent manner.

genetics↗