Failing Heart Transplants and Rejection—A Cellular Perspective

Hurskainen, Maria; Ainasoja, O.H.; Lemström, Karl

doi:10.3390/jcdd8120180

Cited by 5 publications

(2 citation statements)

References 109 publications

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“…Damage to endothelial cells (EC) leads to reduced myocardial perfusion resulting in further hypoxia in affected areas. Hypoxia, in turn, has been shown to induce phenotypic changes consistent with endothelial-tomesenchymal transition (EndMT), in which ECs undergo phenotypic changes and transdifferentiate into myofibroblast-like cells with increased extracellular matrix protein production, contributing to fibrosis [12]. Also, by secreting cytokines, adaptive immune cells (such as B and CD4+ T cells) and innate immunity cells (such as neutrophils and innate lymphoid cells) contribute to the trans differentiation of 10 recipient-derived macrophages to myofibroblasts, which leads to transplanted organ fibrosis [13].…”

Section: Resultsmentioning

confidence: 99%

Reduction in myocardial fibrosis in MDX mice on oral consumption ofAureobasidium Pullulansproduced Neu REFIX Beta-glucans; holds potential as an adjuvant in managing post-transplantation organ fibrosis

Preethy,

Yamamoto,

Cherian

et al. 2023

Preprint

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Organ fibrosis is one of the major causes of morbidity and mortality globally. Though fibrosis in genetic diseases such as Duchenne muscular dystrophy (DMD) may be attributed to the genetic defect, chronic microinflammation remains a key mechanism underlying such fibrosis, which also precedes both other organ fibrosis and post-organ transplant fibrosis. Having proven the anti-inflammatory, anti-fibrotic effects of Beta-1,3-1,6-glucan (Neu-REFIX) produced by N-163 strain ofAureobasidium Pullulansin earlier clinical and pre-clinical studies, we performed the current study to evaluate its effects on myocardial fibrosis. N-163 beta-glucan was administered to 45 mice in three groups, each fifteen animals, Gr. 1, normal mice, Gr.2, mdx mice as vehicle, Gr.3, mdx mice which were administered Neu REFIX beta-glucan orally. Evaluation of Collagen Type I (Col-I) in myocardium was performed by immunohistochemistry. Percentage of myocardium Col-I positive area of 6.42 ± 2.67 significantly decreased in the Neu-REFIX group (4.32 ± 1.78) (p-value < 0.01). As myocardial fibrosis has been shown to be reduced following treatment with N-163 beta glucan in a genetic, muscle structure anomaly disease such as DMD, in addition to adding value to DMD patients, in whom myocardial failure occurs in the advanced stages leading to pre-mature death, Neu-REFIX beta-glucan adjuvant treatment in the setting of solid organ transplantation may be of value to reduce the incidence of fibrosis which is a known feature of chronic allograft rejection leading to graft loss.

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Section: Resultsmentioning

confidence: 99%

Reduction in myocardial fibrosis in MDX mice on oral consumption ofAureobasidium Pullulansproduced Neu REFIX Beta-glucans; holds potential as an adjuvant in managing post-transplantation organ fibrosis

Preethy,

Yamamoto,

Cherian

et al. 2023

Preprint

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“…Discovering biomarkers crucial in cardiac rejection may aid in the development of targeted therapies and improve heart transplantation outcomes. Allograft rejection involves both antibody and T cell responses [4]. Cytotoxic T lymphocytes and natural killer (NK) cells play a pivotal role in the immune response including in organ transplantation [5,6].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Acute Cardiac Rejection Based on Gene Expression Profiles

Abdrakhimov,

Kayewa,

Wang

2024

JPM

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Acute cardiac rejection remains a significant challenge in the post-transplant period, necessitating meticulous monitoring and timely intervention to prevent graft failure. Thus, the goal of the present study was to identify novel biomarkers involved in acute cardiac rejection, paving the way for personalized diagnostic, preventive, and treatment strategies. A total of 809 differentially expressed genes were identified in the GSE150059 dataset. We intersected genes selected by analysis of variance, recursive feature elimination, least absolute shrinkage and selection operator, and random forest classifier to identify the most relevant genes involved in acute cardiac rejection. Thus, HCP5, KLRD1, GZMB, PLA1A, GNLY, and KLRB1 were used to train eight machine learning models: random forest, logistic regression, decision trees, support vector machines, gradient boosting machines, K-nearest neighbors, XGBoost, and neural networks. Models were trained, tested, and validated on the GSE150059 dataset (MMDx-based diagnosis of rejection). Eight algorithms achieved great performance in predicting acute cardiac rejection. However, all machine learning models demonstrated poor performance in two external validation sets that had rejection diagnosis based on histology: merged GSE2596 and GSE4470 dataset and GSE9377 dataset, thus highlighting differences between these two methods. According to SHAP and LIME, KLRD1 and HCP5 were the most impactful genes.

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