A proper interpretation of the pathogenicity of rare variants is crucial before clinical translation. Ongoing addition of new data may modify previous variant classifications; however, how often a reanalysis is necessary remains undefined. We aimed to extensively reanalyze rare variants associated with inherited channelopathies originally classified 5 years ago and its clinical impact. In 2016, rare variants identified through genetic analysis were classified following the American College of Medical Genetics and Genomics’ recommendations. Five years later, we have reclassified the same variants following the same recommendations but including new available data. Potential clinical implications were discussed. Our cohort included 49 cases of inherited channelopathies diagnosed in 2016. Update show that 18.36% of the variants changed classification mainly due to improved global frequency data. Reclassifications mostly occurred in minority genes associated with channelopathies. Similar percentage of variants remain as deleterious nowadays, located in main known genes (SCN5A, KCNH2 and KCNQ1). In 2016, 69.38% of variants were classified as unknown significance, but now, 53.06% of variants are classified as such, remaining the most common group. No management was modified after translation of genetic data into clinics. After 5 years, nearly 20% of rare variants associated with inherited channelopathies were reclassified. This supports performing periodic reanalyses of no more than 5 years since last classification. Use of newly available data is necessary, especially concerning global frequencies and family segregation. Personalized clinical translation of rare variants can be crucial to management if a significant change in classification is identified.
A B S T R A C TBackground: Accurate interpretation of rare genetic variants is a challenge for clinical translation. Updates in recommendations for rare variant classification require the reanalysis and reclassification. We aim to perform an exhaustive re-analysis of rare variants associated with inherited arrhythmogenic syndromes, which were classified ten years ago, to determine whether their classification aligns with current standards and research findings. Methods: In 2010, the rare variants identified through genetic analysis were classified following recommendations available at that time. Nowadays, the same variants have been reclassified following current American College of Medical Genetics and Genomics recommendations. Findings: Our cohort included 104 cases diagnosed with inherited arrhythmogenic syndromes and 17 postmortem cases in which inherited arrhythmogenic syndromes was cause of death. 71.87% of variants change their classification. While 65.62% of variants were classified as likely pathogenic in 2010, after reanalysis, only 17.96% remain as likely pathogenic. In 2010, 18.75% of variants were classified as uncertain role but nowadays 60.15% of variants are classified of unknown significance. Interpretation: Reclassification occurred in more than 70% of rare variants associated with inherited arrhythmogenic syndromes. Our results support the periodical reclassification and personalized clinical translation of rare variants to improve diagnosis and adjust treatment.
The left ventricular (LV) ejection fraction (EF) is key to prognosis in dilated cardiomyopathy (DCM). Circulating microRNAs have emerged as reliable biomarkers for heart diseases, included DCM. Clinicians need improved tools for greater clarification of DCM EF categorization, to identify high-risk patients. Thus, we investigated whether microRNA profiles can categorize DCM patients based on their EF. 179-differentially expressed circulating microRNAs were screened in two groups: (1) non-idiopathic DCM; (2) idiopathic DCM. Then, 26 microRNAs were identified and validated in the plasma of ischemic-DCM (n = 60), idiopathic-DCM (n = 55) and healthy individuals (n = 44). We identified fourteen microRNAs associated with echocardiographic variables that differentiated idiopathic DCM according to the EF degree. A predictive model of a three-microRNA (miR-130b-3p, miR-150-5p and miR-210-3p) combined with clinical variables (left bundle branch block, left ventricle end-systolic dimension, lower systolic blood pressure and smoking habit) was obtained for idiopathic DCM with a severely reduced-EF. The receiver operating characteristic curve analysis supported the discriminative potential of the diagnosis. Bioinformatics analysis revealed that miR-150-5p and miR-210-3p target genes might interact with each other with a high connectivity degree. In conclusion, our results revealed a three-microRNA signature combined with clinical variables that highly discriminate idiopathic DCM categorization. This is a potential novel prognostic biomarker with high clinical value.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.