Endomyocardial biopsy (EMB) is currently considered the gold standard for diagnosing cardiac allograft rejection. However, significant limitations related to histological interpretation variability ...are well-recognized. We sought to develop a methodology to evaluate EMB solely based on gene expression, without relying on histology interpretation.
Sixty-four EMBs were obtained from 47 post-heart transplant recipients, who were evaluated for allograft rejection. EMBs were subjected to mRNA sequencing, in which an unsupervised classification algorithm was used to identify the molecular signatures that best classified the EMBs. Cytokine and natriuretic peptide peripheral blood profiling was also performed. Subsequently, we performed gene network analysis to identify the gene modules and gene ontology to understand their biological relevance. We correlated our findings with the unsupervised and histological classifications.
Our algorithm classifies EMBs into three categories based solely on clusters of gene expression: unsupervised classes 1, 2, and 3. Unsupervised and histological classifications were closely related, with stronger gene module-phenotype correlations for the unsupervised classes. Gene ontology enrichment analysis revealed processes impacting on the regulation of cardiac and mitochondrial function, immune response, and tissue injury response. Significant levels of cytokines and natriuretic peptides were detected following the unsupervised classification.
We have developed an unsupervised algorithm that classifies EMBs into three distinct categories, without relying on histology interpretation. These categories were highly correlated with mitochondrial, immune, and tissue injury response. Significant cytokine and natriuretic peptide levels were detected within the unsupervised classification. If further validated, the unsupervised classification could offer a more objective EMB evaluation.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
2.
PKC and PKN in heart disease Marrocco, Valeria; Bogomolovas, Julius; Ehler, Elisabeth ...
Journal of molecular and cellular cardiology,
03/2019, Volume:
128
Journal Article
Peer reviewed
Open access
The protein kinase C (PKC) and closely related protein kinase N (PKN) families of serine/threonine protein kinases play crucial cellular roles. Both kinases belong to the AGC subfamily of protein ...kinases that also include the cAMP dependent protein kinase (PKA), protein kinase B (PKB/AKT), protein kinase G (PKG) and the ribosomal protein S6 kinase (S6K). Involvement of PKC family members in heart disease has been well documented over the years, as their activity and levels are mis-regulated in several pathological heart conditions, such as ischemia, diabetic cardiomyopathy, as well as hypertrophic or dilated cardiomyopathy.
This review focuses on the regulation of PKCs and PKNs in different pathological heart conditions and on the influences that PKC/PKN activation has on several physiological processes. In addition, we discuss mechanisms by which PKCs and the closely related PKNs are activated and turned-off in hearts, how they regulate cardiac specific downstream targets and pathways, and how their inhibition by small molecules is explored as new therapeutic target to treat cardiomyopathies and heart failure.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The cohort of long-term survivors of heart transplant is expanding, and the assessment of these patients requires specific knowledge of the surgical techniques employed to implant the donor heart, ...the physiology of the transplanted heart, complications of invasive tests routinely performed to detect graft rejection (GR), and the specific pathologies that may affect the transplanted heart. A joint EACVI/Brazilian cardiovascular imaging writing group committee has prepared these recommendations to provide a practical guide to echocardiographers involved in the follow-up of heart transplant patients and a framework for standardized and efficient use of cardiovascular imaging after heart transplant. Since the transplanted heart is smaller than the recipient's dilated heart, the former is usually located more medially in the mediastinum and tends to be rotated clockwise. Therefore, standard views with conventional two-dimensional (2D) echocardiography are often difficult to obtain generating a large variability from patient to patient. Therefore, in echocardiography laboratories equipped with three-dimensional echocardiography (3DE) scanners and specific expertise with the technique, 3DE may be a suitable alternative to conventional 2D echocardiography to assess the size and the function of cardiac chambers. 3DE measurement of left (LV) and right ventricular (RV) size and function are more accurate and reproducible than conventional 2D calculations. However, clinicians should be aware that cardiac chamber volumes obtained with 3DE cannot be compared with those obtained with 2D echocardiography. To assess cardiac chamber morphology and function during follow-up studies, it is recommended to obtain a comprehensive echocardiographic study at 6 months from the cardiac transplantation as a baseline and make a careful quantitation of cardiac chamber size, RV systolic function, both systolic and diastolic parameters of LV function, and pulmonary artery pressure. Subsequent echocardiographic studies should be interpreted in comparison with the data obtained from the 6-month study. An echocardiographic study, which shows no change from the baseline study, has a high negative predictive value for GR. There is no single systolic or diastolic parameter that can be reliably used to diagnose GR. However, in case several parameters are abnormal, the likelihood of GR increases. When an abnormality is detected, careful revision of images of the present and baseline study (side-by-side) is highly recommended. Global longitudinal strain (GLS) is a suitable parameter to diagnose subclinical allograft dysfunction, regardless of aetiology, by comparing the changes occurring during serial evaluations. Evaluation of GLS could be used in association with endomyocardial biopsy (EMB) to characterize and monitor an acute GR or global dysfunction episode. RV size and function at baseline should be assessed using several parameters, which do not exclusively evaluate longitudinal function. At follow-up echocardiogram, all these parameters should be compared with the baseline values. 3DE may provide a more accurate and comprehensive assessment of RV size and function. Moreover, due to the unpredictable shape of the atria in transplanted patients, atrial volume should be measured using the discs' summation algorithm (biplane algorithm for the left atrium) or 3DE. Tricuspid regurgitation should be looked for and properly assessed in all echocardiographic studies. In case of significant changes in severity of tricuspid regurgitation during follow-up, a 2D/3D and colour Doppler assessment of its severity and mechanisms should be performed. Aortic and mitral valves should be evaluated according to current recommendations. Pericardial effusion should be serially evaluated regarding extent, location, and haemodynamic impact. In case of newly detected pericardial effusion, GR should be considered taking into account the overall echocardiographic assessment and patient evaluation. Dobutamine stress echocardiography might be a suitable alternative to routine coronary angiography to assess cardiac allograft vasculopathy (CAV) at centres with adequate experience with the methodology. Coronary flow reserve and/or contrast infusion to assess myocardial perfusion might be combined with stress echocardiography to improve the accuracy of the test. In addition to its role in monitoring cardiac chamber function and in diagnosis the occurrence of GR and/or CAV, in experienced centres, echocardiography might be an alternative to fluoroscopy to guide EMB, particularly in children and young women, since echocardiography avoids repeated X-ray exposure, permits visualization of soft tissues and safer performance of biopsies of different RV regions. Finally, in addition to the indications about when and how to use echocardiography, the document also addresses the role of the other cardiovascular imaging modalities during follow-up of heart transplant patients. In patients with inadequate acoustic window and contraindication to contrast agents, pharmacological SPECT is an alternative imaging modality to detect CAV in heart transplant patients. However, in centres with adequate expertise, intravascular ultrasound (IVUS) in conjunction with coronary angiography with a baseline study at 4-6 weeks and at 1 year after heart transplant should be performed to exclude donor coronary artery disease, to detect rapidly progressive CAV, and to provide prognostic information. Despite the fact that coronary angiography is the current gold-standard method for the detection of CAV, the use of IVUS should also be considered when there is a discrepancy between non-invasive imaging tests and coronary angiography concerning the presence of CAV. In experienced centres, computerized tomography coronary angiography is a good alternative to coronary angiography to detect CAV. In patients with a persistently high heart rate, scanners that provide high temporal resolution, such as dual-source systems, provide better image quality. Finally, in patients with insufficient acoustic window, cardiac magnetic resonance is an alternative to echocardiography to assess cardiac chamber volumes and function and to exclude acute GR and CAV in a surveillance protocol.
In the field of heart transplantation, the ability to accurately and promptly diagnose cardiac allograft rejection is crucial. This comprehensive review explores the transformative role of digital ...pathology and computational pathology, especially through machine learning, in this critical domain. These methodologies harness large datasets to extract subtle patterns and valuable information that extend beyond human perceptual capabilities, potentially enhancing diagnostic outcomes. Current research indicates that these computer-based systems could offer accuracy and performance matching, or even exceeding, that of expert pathologists, thereby introducing more objectivity and reducing observer variability. Despite promising results, several challenges such as limited sample sizes, diverse data sources, and the absence of standardized protocols pose significant barriers to the widespread adoption of these techniques. The future of digital pathology in heart transplantation diagnostics depends on utilizing larger, more diverse patient cohorts, standardizing data collection, processing, and evaluation protocols, and fostering collaborative research efforts. The integration of various data types, including clinical, demographic, and imaging information, could further refine diagnostic precision. As researchers address these challenges and promote collaborative efforts, digital pathology has the potential to become an integral part of clinical practice, ultimately improving patient care in heart transplantation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Background: Cardiac allograft rejection (AR) remains a significant complication following heart transplantation. The primary objective of our study is to gain a comprehensive understanding of the ...fundamental mechanisms involved in AR and identify possible therapeutic targets.
Methods: We acquired the GSE87301 dataset from the Gene Expression Omnibus database. In GSE87301, a comparison was conducted on blood samples from patients with and without cardiac allograft rejection (AR and NAR) to detect differentially expressed genes (DEGs). Enrichment analysis was conducted to identify the pathways that show significant enrichment during AR. Machine learning techniques, including the least absolute shrinkage and selection operator regression (LASSO) and random forest (RF) algorithms, were employed to identify potential genes for the diagnosis of AR. The diagnostic value was evaluated using a nomogram and receiver operating characteristic (ROC) curve. Additionally, immune cell infiltration was analyzed to explore any dysregulation of immune cells in AR.
Results: A total of 114 DEGs were identified from the GSE87301 dataset. These DEGs were mainly found to be enriched in pathways related to the immune system. To identify the signature genes, the LASSO and RF algorithms were used, and four genes, namely ALAS2, HBD, EPB42, and FECH, were identified. The performance of these signature genes was evaluated using the receiver operating characteristic curve (ROC) analysis, which showed that the area under the curve (AUC) values for ALAS2, HBD, EPB42, and FECH were 0.906, 0.881, 0.900, and 0.856, respectively. These findings were further confirmed in the independent datasets and clinical samples. The selection of these specific genes was made to construct a nomogram, which demonstrated excellent diagnostic ability. Additionally, the results of the single-sample gene set enrichment analysis (ssGSEA) revealed that these genes may be involved in immune cell infiltration.
Conclusion: We identified four signature genes (ALAS2, HBD, EPB42, and FECH) as potential peripheral blood diagnostic candidates for AR diagnosis. Additionally, a nomogram was constructed to aid in the diagnosis of heart transplantation. This study offers valuable insights into the identification of candidate genes for heart transplantation using peripheral blood samples.
•Discovery of four potential blood biomarkers (ALAS2, HBD, EPB42, and FECH) for the accurate diagnosis of cardiac allograft rejection.•Development of a predictive nomogram based on signature genes with high AUC values.•Elucidation of the immune infiltration landscape in cardiac allograft rejection, offering new insights into the immune dysregulation associated with heart transplantation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Despite novel immunosuppressive (IS) protocols, adverse effects of IS drugs continue to have notable negative impact on patient and cardiac allograft survival after heart transplantation (HTx). ...Therefore, IS regimens with less toxic side effects are sorely needed. We aimed to evaluate the efficacy of extracorporeal photopheresis (ECP) in combination with tacrolimus-based maintenance IS therapy in the treatment of allograft rejection in adult HTx recipients. Indications for ECP included acute moderate-to-severe or persistent mild cellular rejection, or mixed rejection. Twenty-two patients underwent a median of 22(2–44) ECP treatments after HTx. Median duration of ECP course was 173.5(2–466) days. No relevant adverse effects of ECP were noted. Reduction of methylprednisolone doses was safe throughout the ECP course. ECP, used in conjunction with pharmacological anti-rejection therapy, had a successful reversal of cardiac allograft rejection, decreased the rates of subsequential rejection episodes and normalized the allograft function in patients completing the ECP course. Short- and long-term survivals were excellent (91% at 1 and 5 years post-ECP) and comparable to International Society for Heart and Lung Transplantation registry data on HTx recipient overall survival. In conclusion, ECP can be safely used for the treatment and prevention of cardiac allograft rejection in conjunction with traditional IS regimen.
•ECP could be applied effectively and safely in a variety of clinical scenarios.•Patients treated for rejection with ECP are eligible for reduced immunosuppression.•Mean daily dose of tacrolimus could be significantly reduced besides ECP therapy.•Mean daily dose of methylprednisolone could be significantly decreased besides ECP.•Patient treated for rejection with ECP has similar survival as average HTx patients.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Aims
Current non-invasive screening methods for cardiac allograft rejection have shown limited discrimination and are yet to be broadly integrated into heart transplant care. Given ...electrocardiogram (ECG) changes have been reported with severe cardiac allograft rejection, this study aimed to develop a deep-learning model, a form of artificial intelligence, to detect allograft rejection using the 12-lead ECG (AI-ECG).
Methods and results
Heart transplant recipients were identified across three Mayo Clinic sites between 1998 and 2021. Twelve-lead digital ECG data and endomyocardial biopsy results were extracted from medical records. Allograft rejection was defined as moderate or severe acute cellular rejection (ACR) based on International Society for Heart and Lung Transplantation guidelines. The extracted data (7590 unique ECG-biopsy pairs, belonging to 1427 patients) was partitioned into training (80%), validation (10%), and test sets (10%) such that each patient was included in only one partition. Model performance metrics were based on the test set (n = 140 patients; 758 ECG-biopsy pairs). The AI-ECG detected ACR with an area under the receiver operating curve (AUC) of 0.84 95% confidence interval (CI): 0.78–0.90 and 95% (19/20; 95% CI: 75–100%) sensitivity. A prospective proof-of-concept screening study (n = 56; 97 ECG-biopsy pairs) showed the AI-ECG detected ACR with AUC = 0.78 (95% CI: 0.61–0.96) and 100% (2/2; 95% CI: 16–100%) sensitivity.
Conclusion
An AI-ECG model is effective for detection of moderate-to-severe ACR in heart transplant recipients. Our findings could improve transplant care by providing a rapid, non-invasive, and potentially remote screening option for cardiac allograft function.
Graphical Abstract
Graphical abstract
An artificial intelligence enabled ECG can effectively detect cardiac allograft rejection among heart transplant recipients. AI, artificial intelligence; AUC, area under the receiver operating characteristic curve; ECG, electrocardiogram; ISHLT, International Society for Heart and Lung Transplantation; NPV, negative predictive value; PPV, positive predictive value.
PURPOSE OF REVIEWRecent years have seen advances in the early detection of cardiac graft rejection.
RECENT FINDINGSWe review the possibilities offered by tissue Doppler imaging and speckle tracking ...echocardiography, cardiac magnetic resonance, cardiac computed tomography, single positron emission tomography, gene expression profiling, and quantitation of donor-derived cell-free DNA, and microRNAs.
SUMMARYNoninvasive monitoring of acute and chronic rejection after cardiac transplantation is an unmet need and remains a challenge. Imaging techniques and peripheral blood biomarkers are the most commonly used approaches, and in recent years there has been great progress. Gene expression profiling seems to be useful for ruling out the presence of a moderate to severe acute cellular rejection in stable, low-risk patients. Newer monitoring tools, like donor-derived cell-free DNA or microRNA, seem to be promising for individualizing immunosuppressive therapies and better understanding the mechanisms of rejection.
Long-term success of heart transplantation is limited by allograft rejection and cardiac allograft vasculopathy (CAV). Classic management has relied on frequent invasive testing to screen for early ...features of rejection and CAV to allow for early treatment. In this review, we discuss new developments in the screening and prevention of allograft rejection and CAV.
Newer noninvasive screening techniques show excellent sensitivity and specificity for the detection of clinically significant rejection. New biomarkers and treatment targets continue to be identified and await further studies regarding their utility in preventing allograft vasculopathy.
Noninvasive imaging and biomarker testing continue to show promise as alternatives to invasive testing for allograft rejection. Continued validation of their effectiveness may lead to new surveillance protocols with reduced frequency of invasive testing. Furthermore, these noninvasive methods will allow for more personalized strategies to reduce the complications of long-term immunosuppression whereas continuing the decline in the overall rate of allograft rejection.