Cellular heterogeneity of pluripotent stem cell-derived cardiomyocyte grafts is mechanistically linked to treatable arrhythmias.
Dinesh SelvakumarZoe E ClaytonAndrew ProwseSteve DingwallSul Ki KimLeila ReyesJacob GeorgeHaisam ShahSiqi ChenHalina H L LeungRobert D HumeLaurentius TjahjadiSindhu IgoorRhys J P SkeltonAlfred HingHugh PatersonSheryl L FosterLachlan PearsonEmma WilkieAlan D MarcusPrajith JeyaprakashZhixuan WuHan Shen ChiuCherica Felize J OngtengcoOnkar MulayJeffrey R McArthurTony BarryJuntang LuVu TranRichard BennettYasuhito KotakeTimothy G CampbellTimothy CampbellAnunay GuptaQuan H NguyenGuiyan NiStuart M GrieveNathan J PalpantFaraz PathanEddy KizanaSaurabh KumarPeter P GrayJames J H ChongPublished in: Nature cardiovascular research (2024)
Preclinical data have confirmed that human pluripotent stem cell-derived cardiomyocytes (PSC-CMs) can remuscularize the injured or diseased heart, with several clinical trials now in planning or recruitment stages. However, because ventricular arrhythmias represent a complication following engraftment of intramyocardially injected PSC-CMs, it is necessary to provide treatment strategies to control or prevent engraftment arrhythmias (EAs). Here, we show in a porcine model of myocardial infarction and PSC-CM transplantation that EAs are mechanistically linked to cellular heterogeneity in the input PSC-CM and resultant graft. Specifically, we identify atrial and pacemaker-like cardiomyocytes as culprit arrhythmogenic subpopulations. Two unique surface marker signatures, signal regulatory protein α (SIRPA) + CD90 - CD200 + and SIRPA + CD90 - CD200 - , identify arrhythmogenic and non-arrhythmogenic cardiomyocytes, respectively. Our data suggest that modifications to current PSC-CM-production and/or PSC-CM-selection protocols could potentially prevent EAs. We further show that pharmacologic and interventional anti-arrhythmic strategies can control and potentially abolish these arrhythmias.
Keyphrases
- congenital heart disease
- clinical trial
- heart failure
- endothelial cells
- high glucose
- electronic health record
- left ventricular
- single cell
- big data
- atrial fibrillation
- transcription factor
- stem cells
- machine learning
- cell therapy
- randomized controlled trial
- angiotensin ii
- artificial intelligence
- gene expression
- small molecule
- bone marrow
- data analysis
- induced pluripotent stem cells
- inferior vena cava