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Background: Endomyocardial Biopsy ( EMB) is the standard method to diagnose allograft rejection post HTx. While it is used to support medical decisions, insufficient diagnostic accuracy constitutes a fundamental limitation. The aim of this study is to develop a methodology that improves the classification of the EMB through a non-supervised evaluation of intramyocardial gene expression. Methods: Sixty-four heart tissues from 47 HTx recipients were subjected to genome wide mRNA sequencing. An unsupervised algorithm using optimal transport to mitigate batch effects and to filter confounding sources of variability was developed to identify molecular signatures of rejection. Linear Mixed Model identified genes statistically significant among the histology defined rejection groups. Weighted Gene Correlation Network Analysis (WGCNA) was used to establish 13 eigengene modules and module-clinical phenotype relationships. Gene Ontology was used for interpretation of the modules in their biological context. Results: O ur algorithm best classified the EMBs into 4 unsupervised clusters solely based on their gene expression. Statistical analysis showed a set of genes differentially expressed among groups defined by histology criteria. Top ranked genes were CLNK, TNFRSF10A, TRADD, CD2, and HLA-A. WGCNA revealed best trait-module correlation was observed between the classes defined by the unsupervised algorithm developed in this study followed by Histology. Figure 1 shows Module-Trait relationships, strength of association, significance and enriched biological process. Conclusion: We have developed an unsupervised algorithm that classifies the EMBs into 4 functionally distinctive categories. These categories are highly correlated with genomic modules defined by WGCNA and with the clinical phenotypes. To our knowledge, this is the first unsupervised classification of the EMBs. Further validation and performance will be provided at the time of presentation.
Background: The neuro-endocrino-immunological (NEI) pathophysiology associated with advanced heart failure (AdHF) progression and arrythmogenesis is not well understood. While it has been shown that mechanical circulatory support device (MCSD) implantation rapidly restores normal hemodynamics, it is unknown as to whether NEI mechanisms also normalize rapidly. We hypothesized that transcriptional activity in PBMC reflecting NEI normalizes shortly after MCSD implantation. Methods: We collected PBMC samples from 25 MCSD patients and 4 healthy controls (CTRL). Samples were obtained at 1 day before, and 1, 3, 5 and 8 days after MCSD. Purified mRNA was subjected to whole-genome NGS analysis. Statistically significant genes, dysregulated between AdHF patients and CTRLs, were subjected to time dependent bioinformatics analysis. Results: We identified 1226 dysregulated gene-transcripts between AdHF patients and CRTLs at baseline. Time dependent analysis provided 344 dysregulated transcripts in AdHF patients across all time-points. An analysis of enriched molecular pathways by dysregulated genes showed 52 pathways with NEI annotations at baseline. The Endothelin pathway, one of the most significant of the 52 pathways, had 17/60 dysregulated transcripts in AdHF patients at baseline and through day 8 after implantation (Fig.1A). Within the Endothelin pathway we found that expression of EDNRB, a gene central to ET1 clearance and ECE-inhibition, is persistently elevated through day 8 after MCSD (Fig.1B). Conclusion: Transcriptional NEI dysregulation is persistent in PBMC 8 days after MCSD implantation. Neuromodulatory strategies targeted at NEI dysregulation and implemented after MCSD implantation may be a mechanism to improve perioperative outcomes. Further studies including validation methods to objectively assess NEI activity are warranted.
Background: The lack of consent to organ donation is the main limiting factor for heart transplantation in the United States. Limited knowledge is available about using social media to change health behavior. Social and parasocial interactions are highly effective in increasing engagement with audiences by appropriate public influencers. We hypothesized that a Social Network (SN) intervention that engages members with short, specific content through public influencers is effective in improving attitudes about organ donation. Method: We disseminated public information related to organ donation to assess efficacy of engagement in social media sources through paid and organic campaigns. We used Facebook as a social media platform to engage audiences using three different methods of content delivery. The paid campaign ran for seven days without any other active intervention, followed by a one month organic phase where an audience was created and content delivered by engaging public influencers. Effectiveness was measured by click-through rates (CTR), and engagement. We analyzed each phase of the intervention and compared them against the industry averages. Results: The first campaign used emotionally driven content and resulted in 140 clicks in a population of 24,574 people, with a unique people reach of 127. The CTR (number of clicks/number of times shown) was 0.253% and unique (u) uCTR 0.517%. This campaign resulted in a 23% increase in engagement. In the organic phase, emotionally driven content resulted in 21.1% uCTR, Infographics 33.2%, and short educational videos 7.6%. All results performed exceptionally well above the industry average within the non-profit sector which was 0.21%. Computing engagement, emotionally driven stories and infographic driven content resulted in very high engagements, 12.3% and 14.6% respectively. The average engagement as determined by Salesforce Facebook Data Analytics within the same industry had a range of 0.5%-0.1%. Conclusion: Establishing a community on a social network before tailoring content resulted in the best engagement. Combined with identifying peer influencers, it is a highly effective strategy in engaging populations to stimulate a dialogue for higher consent rates than traditional campaigns.
Introduction Endomyocardial biopsy is the standard surveillance method to detect cardiac allograft rejection. While microRNAs (miRNA) play a major role in regulating mRNA, their nature and role in the biology is not well understood. We hypothesized that specific mRNA-miRNA networks can be identified underlying the clinical phenotypes of different forms of cardiac allograft rejection. Method Twenty one tissue samples from 14 post-HTx patients were subjected to genome wide miRNA sequencing. A non-parametric empirical Bayes framework removed batch effect and filtered genes with low variability. Weighted Gene Correlation Network Analysis (WGCNA) clustered genes into related eigengene modules based on their gene expression. Identified miRNAs were subjected to target prediction and compared with mRNA expression profiles previously identified on the same biopsies. Gene Ontology (GO) was used for biological interpretation of selected genes. Results 1270 miRNAs were used to construct 9 eigengene modules. Module-Trait relationship were then investigated as shown in Figure. The top ten miRNA probe sets filtered by the highest intra-module correlation and statistical significance were hsa-miR-141-3p, hsa-miR-150-5p, hsa-miR-605, hsa-miR-582-5p, hsa-miR-3150b-3p, hsa-miR-508-3p, hsa-miR-652-5p, hsa-miR-26a-1-3p, hsa-miR-3667-3p and hsa-miR-3911. Target prediction analysis resulted in 724 gene targets. GO analysis revealed 184 categories enriched by these genes including regulation of protein kinase activity, cardiac muscle cell differentiation and epithelial cell migration among others. Compared to mRNA previously identified in the same heart biopsies showed 685 overlapping gene targets. Conclusion WGCNA identified miRNA modules correlated with different clinical phenotypes of rejection. MRNA-miRNA pairs were identified to help understand the biology of rejection and as interesting candidates for diagnostic or therapeutic applications.
Objective We previously demonstrated thattransient repetitive pressure overload (RPO) in swine leads to myocardial interstitial fibrosis and reduced diastolic left ventricular (LV) compliance. While this phenotype is similar to that found in some patients with heart failure with preserved ejection fraction (HFpEF), it occurs in the absence of anatomic LV hypertrophy, persistent hypertension, or comorbidities. The present study was designed to determine if reduced LV diastolic distensibility alters the acute transcriptional response to transient pressure overload. Methods A total of 21 swine were studied. Hemodynamic assessment, echocardiography, and blood sampling were performed before and after a 60 minute intravenous infusion of phenylephrine (PE; 300 μg/min) to elevate LV end-diastolic pressure (EDP) to ~30 mmHg. Myocardial RNA from control animals (n=7) was compared to tissue isolated 24 hours after a single episode of pressure overload (n=6) or after 14 days of RPO (n=8). We assessed LV diastolic strain and compliance via echocardiography and quantified interstitial fibrosis with picrosirius red staining. Genes previously demonstrated to be altered after pressure overload including natriuretic peptides (ANP and BNP), inflammatory mediators (CD68 and CCR2) and pro-fibrotic factors (LOXL2 and Fibronectin) were assessed with quantitative PCR and normalized to β2 microglobulin. Results Transient PE infusion increased LV EDP from 14 ± 1 to 30 ± 1 mmHg and systolic arterial pressure from 120 ± 6 to 205 ± 6 mmHg (both p<0.01). The hemodynamic response to PE was similar during a single episode of pressure overload and after 14 days of RPO. There was concentric LV remodeling (LV mass/EDV: 1.3 ± 0.1 vs. 1.1 ± 0.1 g/mL; p<0.05) without anatomic hypertrophy after RPO (LV mass/body mass: 2.4 ± 0.1 vs. 2.3 ± 0.1 g/kg; p=0.37), yet interstitial fibrosis increased from 6.6 ± 0.7% to 12.9 ± 1.8% (p<0.05) and LV diastolic compliance (∆EDV/∆EDP) decreased from 1.7 ± 0.2 to 0.6 ± 0.2 mL/mmHg (p<0.05). As a result, myocardial diastolic circumferential strain after RPO was markedly reduced in comparison to a single episode of pressure overload in the normal heart (1.5 ± 2.7% after RPO vs. 11.1 ± 3.0% in controls; p<0.05). The reduction in diastolic circumferential strain after RPO markedly attenuated the transcriptional response to acute pressure overload (Figure). In normal myocardium, transient pressure overload upregulated natriuretic peptides (ANP 26-fold and BNP 12-fold; both p<0.01), pro-inflammatory genes (CD68 2.3-fold and CCR2 4-fold; p=0.06), and pro-fibrotic genes (LOXL2 3.4-fold and fibronectin 3.9-fold; p<0.05). In contrast, the reduction in diastolic strain after RPO prevented any increase in gene expression despite a similar magnitude of transient pressure overload. Conclusions These results dissociate the effects of myocardial strain from systolic and end-diastolic pressure on the transcriptional response to LV pressure overload. The dependence of gene expression on diastolic strain rather than LV pressure may explain observations such as the frequent absence of natriuretic peptide elevation in patients with HFpEF.
