Personalized transcriptome signatures in a cardiomyopathy stem cell biobank
Personalized transcriptome signatures in a cardiomyopathy stem cell biobank
Abstract BACKGROUNDThere is growing evidence that pathogenic mutations do not fully explain hypertrophic (HCM) or dilated (DCM) cardiomyopathy phenotypes. We hypothesized that if a patient’s genetic background was influencing cardiomyopathy this should be detectable as signatures in gene expression. We built a cardiomyopathy biobank resource for interrogating personalized genotype phenotype relationships in human cell lines. METHODSWe recruited 308 diseased and control patients for our cardiomyopathy stem cell biobank. We successfully reprogrammed PBMCs (peripheral blood mononuclear cells) into induced pluripotent stem cells (iPSCs) for 300 donors. These iPSCs underwent whole genome sequencing and were differentiated into cardiomyocytes for RNA-seq. In addition to annotating pathogenic variants, mutation burden in a panel of cardiomyopathy genes was assessed for correlation with echocardiogram measurements. Line-specific co-expression networks were inferred to evaluate transcriptomic subtypes. Drug treatment targeted the sarcomere, either by activation with omecamtiv mecarbil or inhibition with mavacamten, to alter contractility. RESULTSWe generated an iPSC biobank from 300 donors, which included 101 individuals with HCM and 88 with DCM. Whole genome sequencing of 299 iPSC lines identified 78 unique pathogenic or likely pathogenic mutations in the diseased lines. Notably, only DCM lines lacking a known pathogenic or likely pathogenic mutation replicated a finding in the literature for greater nonsynonymous SNV mutation burden in 102 cardiomyopathy genes to correlate with lower left ventricular ejection fraction in DCM. We analyzed RNA-sequencing data from iPSC-derived cardiomyocytes for 102 donors. Inferred personalized co-expression networks revealed two transcriptional subtypes of HCM. The first subtype exhibited concerted activation of the co-expression network, with the degree of activation reflective of the disease severity of the donor. In contrast, the second HCM subtype and the entire DCM cohort exhibited partial activation of the respective disease network, with the strength of specific gene by gene relationships dependent on the iPSC-derived cardiomyocyte line. ADCY5 was the largest hubnode in both the HCM and DCM networks and partially corrected in response to drug treatment. CONCLUSIONSWe have a established a stem cell biobank for studying cardiomyopathy. Our analysis supports the hypothesis the genetic background influences pathologic gene expression programs and support a role for ADCY5 in cardiomyopathy.
Snyder Michael P.、Furihata Takaaki、Guevara Julio Vicente、Wei Eric、Cheng Xun、Zhuge Yan、Dagan-Rosenfeld Orit、Karakikes Ioannis、Wu Joseph C.、Black Katelyn、Wang Guangwen、Mercola Mark、Maguire Peter、Mares Rene、Serrano Ricardo、Chaib Hassan、Nair Ramesh、Monte Emma、Perea-Gil Isaac
Department of Genetics, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineCardiovascular Institute, Stanford University School of Medicine||Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineCardiovascular Institute, Stanford University School of Medicine||Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineCardiovascular Institute, Stanford University School of Medicine||Department of Cardiothoracic Surgery, Stanford University School of MedicineCardiovascular Institute, Stanford University School of Medicine||Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of MedicineCardiovascular Institute, Stanford University School of Medicine||Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineCardiovascular Institute, Stanford University School of Medicine||Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineCardiovascular Institute, Stanford University School of Medicine||Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineDepartment of Genetics, Stanford University School of MedicineCardiovascular Institute, Stanford University School of Medicine||Department of Cardiothoracic Surgery, Stanford University School of Medicine
医学研究方法基础医学遗传学
Snyder Michael P.,Furihata Takaaki,Guevara Julio Vicente,Wei Eric,Cheng Xun,Zhuge Yan,Dagan-Rosenfeld Orit,Karakikes Ioannis,Wu Joseph C.,Black Katelyn,Wang Guangwen,Mercola Mark,Maguire Peter,Mares Rene,Serrano Ricardo,Chaib Hassan,Nair Ramesh,Monte Emma,Perea-Gil Isaac.Personalized transcriptome signatures in a cardiomyopathy stem cell biobank[EB/OL].(2025-03-28)[2025-07-16].https://www.biorxiv.org/content/10.1101/2024.05.10.593618.点此复制
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