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Yob, J. M.

Publications and source records attributed to Yob, J. M..

2 recordsLinked to original sources

Effects of Sodium Glucose Co-Transporter Inhibitors on Work in Human Hypertrophic Cardiomyopathy Living Myocardial Slices

BackgroundDisease modifying therapies for hypertrophic cardiomyopathy (HCM) remain a prevailing unmet need. Human-based experimental platforms capable of controlled manipulation of preload and afterload can distinguish direct myocardial and systemic effects and facilitate development of targeted cardiac therapeutics. Sodium glucose cotransporter inhibitors (SGLTi) may directly affect cardiac contractility, potentially related to increased ketone availability. These effects have not been adequately studied in human HCM myocardium under defined loading conditions. AimsWe sought to establish human living myocardial slices (LMS) as a platform to interrogate load-dependent myocardial mechanics in HCM and to quantify the acute effects of metabolic and pharmacologic interventions--including SGLTi--on myocardial work under physiologic loading conditions. MethodsHuman myocardial tissue was procured from non-failing donor hearts or individuals with HCM undergoing septal myectomy. Freshly prepared human LMS were mechanically tested to generate biomimetic work loops across a range of physiologic preloads and afterloads in either glucose-only fuel or glucose supplemented with ketone. Following baseline measurements, slices were loaded with drug (isoproterenol, mavacamten, sotagliflozin, or empagliflozin) or vehicle (DMSO) and work loop analysis was repeated, allowing each slice to serve as its own control. Mixed effects linear regression models incorporating random effects for heart and slice and fixed effects for clinical characteristics evaluated determinants of myocardial work and drug response across loading conditions. ResultsA total of 120 LMS from 32 individuals (16 non-failing and 16 HCM) were analyzed. At baseline, myocardial work was positively associated with younger age, hypertension, and ejection fraction. Ketone supplementation augmented work and work-strain slope particularly in HCM LMS at high afterloads. We validated our drug testing methodology by demonstrating increased work with known positive inotrope isoproterenol, decreased work with negative inotrope mavacamtem most pronounced in HCM LMS, and a null effect of DMSO. Acute exposure to SGLTi sotagliflozin and empagliflozin directly reduced myocardial work, with increased potency of sotagliflozin at high afterloads. ConclusionsOur LMS platform enables assessment of myocardial mechanics across controlled loading conditions and is an ideal platform to rigorously phenotype human myocardial tissue and interrogate direct effects of pharmacologic intervention. We demonstrate that SGLTi and ketones have distinct and discordant effects on human myocardial contractility.

physiology↗

Investigating the role of long non-coding RNA in hypertrophic cardiomyopathy

Long non-coding RNA (lncRNA) are transcripts that do not typically code for protein but have essential roles in the regulation of transcription and translation in health and disease. The objective of this study was to identify potential lncRNAs that could play a role in the pathophysiology of hypertrophic cardiomyopathy (HCM). We analyzed RNA-Seq data for lncRNA expression from a mouse model of HCM and cross-referenced transcripts to a published human HCM tissue dataset. We identified a total of 9,140 lncRNA transcripts in the mouse dataset, of which 35 were differentially expressed between transgenic TNNT2 {Delta}160 mice (TG) and non-transgenic mice (nTG, p-adj < 0.05). Of these, 13 had a human ortholog as predicted by ortho2align. We used the computational tools MiPepid, AlphaFold, and PhyloCSF to predict potential micropeptides that could be coded for by these 13 mouse lncRNAs. We found that predicted micropeptides from 3 of these lncRNAs-G730003C15Rik, 9830004L10Rik, and Gm45012-have higher AlphaFold folding confidence metrics than random peptides or truly non-coding lncRNA negative controls (p < 0.05). Another 2 of these lncRNAs, 6330403L08Rik and 2900072N19Rik, have positive PhyloCSF scores, also indicating micropeptide coding potential. In summary, we developed a computational workflow to identify differentially expressed lncRNAs in a mouse model of HCM that can be prioritized for future experimental studies based on their cross-species conservation and micropeptide coding potential. NEW & NOTEWORTHYThis is the first analysis of RNA-Seq data for lncRNA expression in an HCM mouse model and the first cross-species analysis of HCM lncRNA RNA-Seq data. Additionally, this study demonstrated a novel computational pipeline that combines several tools-RNA-Seq, MiPepid, AlphaFold, and PhyloCSF-to identify potential lncRNAs of interest from RNA-Seq data.

bioinformatics↗