Clinical phenomapping and outcomes after heart transplantation

Recipient Pericardial Apolipoprotein Levels Might Be an Indicator of Worse Outcomes after Orthotopic Heart Transplantation

BACKGROUND

End-stage heart failure (ESHF) leads to hypoperfusion and edema formation throughout the body and is accompanied by neurohormonal and immunological alterations. Orthotopic heart transplantation (HTX) has been used as a beneficial option for ESHF. Due to the shortage of donor hearts, the ideal matching and timing of donors and recipients has become more important.

PURPOSE

In this study, our aim was to explore the relationship between the clinical outcomes of HTX and the cytokine and apolipoprotein profiles of the recipient pericardial fluid obtained at heart transplantation after opening the pericardial sac.

MATERIALS AND METHODS

The clinical data and the interleukin, adipokine, and lipoprotein levels in the pericardial fluid of twenty HTX recipients were investigated. Outcome variables included primer graft dysfunction (PGD), the need for post-transplantation mechanical cardiac support (MCS), International Society for Heart and Lung Transplantation grade ≥2R rejection, and mortality. Recipient risk scores were also investigated.

RESULTS

Leptin levels were significantly lower in patients with PGD than in those without PGD (median: 6.36 (IQR: 5.55-6.62) versus 7.54 (IQR = 6.71-10.44); p = 0.029). Higher ApoCII levels (median: 14.91 (IQR: 11.55-21.30) versus 10.31 (IQR = 10.02-13.07); p = 0.042) and ApoCIII levels (median: 60.32 (IQR: 43.00-81.66) versus 22.84 (IQR = 15.84-33.39); p = 0.005) were found in patients (n = 5) who died in the first 5 years after HTX. In patients who exhibited rejection (n = 4) in the first month after transplantation, the levels of adiponectin (median: 74.48 (IQR: 35.51-131.70) versus 29.96 (IQR: 19.86-42.28); p = 0.039), ApoCII (median: 20.11 (IQR: 13.06-23.54) versus 10.32 (IQR: 10.02-12.84); p = 0.007), and ApoCIII (median: 70.97 (IQR: 34.72-82.22) versus 26.33 (IQR: 17.18-40.17); p = 0.029) were higher than in the nonrejection group. Moreover, the pericardial thyroxine (T4) levels (median: 3.96 (IQR: 3.49-4.46) versus 4.69 (IQR: 4.23-5.77); p = 0.022) were lower in patients with rejection than in patients who did not develop rejection.

CONCLUSION

Our results indicate that apolipoproteins can facilitate the monitoring of rejection and could be a useful tool in the forecasting of early and late complications.

Insights and perspectives into clinical biomarker discovery in pediatric heart failure and congenital heart disease-a narrative review

Background and Objective

Heart failure (HF) in the pediatric population is a multi-factorial process with a wide spectrum of etiologies and clinical manifestations, that are distinct from the adult HF population, with congenital heart disease (CHD) as the most common cause. CHD has high morbidity/mortality with nearly 60% developing HF during the first 12 months of life. Hence, early discovery and diagnosis of CHD in neonates is pivotal. Plasma B-type natriuretic peptide (BNP) is an increasingly popular clinical marker in pediatric HF, however, in contrast to adult HF, it is not yet included in pediatric HF guidelines and there is no standardized reference cut-off value. We explore the current trends and prospects of biomarkers in pediatric HF, including CHD that can aid in diagnosis and management.

Methods

As a narrative review, we will analyze biomarkers with respect to diagnosis and monitoring in specific anatomical types of CHD in the pediatric population considering all English PubMed publications till June 2022.

Key Content and Findings

We present a concise description of our own experience in applying plasma BNP as a clinical biomarker in pediatric HF and CHD (tetralogy of fallot vs. ventricular septal defect) in the context of surgical correction, as well as untargeted metabolomics analyses. In the current age of Information Technology and large data sets we also explored new biomarker discovery using Text Mining of 33M manuscripts currently on PubMed.

Conclusions

(Multi) Omics studies from patient samples as well as Data Mining can be considered for the discovery of potential pediatric HF biomarkers useful in clinical care. Future research should focus on validation and defining evidence-based value limits and reference ranges for specific indications using the most up-to-date assays in parallel to commonly used studies.

DCAF12 and HSPA1A May Serve as Potential Diagnostic Biomarkers for Myasthenia Gravis

Background

Myasthenia gravis (MG) is an autoimmune disease that severely affects the life quality of patients. This study explores the differences in immune cell types between MG and healthy control and the role of immune-related genes in the diagnosis of MG.

Methods

The GSE85452 dataset was downloaded from the Gene Expression Omnibus (GEO) database and analyzed using the limma package to determine differentially expressed genes (DEGs) between patients with MG and the control group. Differentially expressed immune cells were analyzed using single-sample gene set enrichment analysis (GSEA), while immune cell-associated modules were identified by weighted gene coexpression network analysis (WGCNA). Then, the expression of the identified hub genes was confirmed by RT-PCR in peripheral blood mononuclear cells (PBMCs) of MG patients. The R package pROC was used to plot the receiver operating characteristics (ROC) curves.

Results

The modules related to CD56^bright natural killer cells were identified by GSEA and WGCNA. The proportion of CD56^bright natural killer cells in the peripheral blood of MG patients is low. The results of RT-PCR showed that the levels of DDB1- and CUL4-associated factor 12 (DCAF12) and heat shock protein family A member 1A (HSPA1A) were significantly decreased in peripheral blood mononuclear cells of MG patients compared with healthy controls. The ROC curve results of DCAF12 and HSPA1A mRNA in MG diagnosis were 0.780 and 0.830, respectively.

Conclusions

CD56^bright NK cell is lower in MG patients and may affect MG occurrence. DCAF12 and HSPA1A are lowly expressed in PBMCs of MG patients and may serve as the diagnostic biomarkers of MG.

CRL4-DCAF12 Ubiquitin Ligase Controls MOV10 RNA Helicase during Spermatogenesis and T Cell Activation

Multisubunit cullin-RING ubiquitin ligase 4 (CRL4)-DCAF12 recognizes the C-terminal degron containing acidic amino acid residues. However, its physiological roles and substrates are largely unknown. Purification of CRL4-DCAF12 complexes revealed a wide range of potential substrates, including MOV10, an "ancient" RNA-induced silencing complex (RISC) complex RNA helicase. We show that DCAF12 controls the MOV10 protein level via its C-terminal motif in a proteasome- and CRL-dependent manner. Next, we generated Dcaf12 knockout mice and demonstrated that the DCAF12-mediated degradation of MOV10 is conserved in mice and humans. Detailed analysis of Dcaf12-deficient mice revealed that their testes produce fewer mature sperms, phenotype accompanied by elevated MOV10 and imbalance in meiotic markers SCP3 and γ-H2AX. Additionally, the percentages of splenic CD4+ T and natural killer T (NKT) cell populations were significantly altered. In vitro, activated Dcaf12-deficient T cells displayed inappropriately stabilized MOV10 and increased levels of activated caspases. In summary, we identified MOV10 as a novel substrate of CRL4-DCAF12 and demonstrated the biological relevance of the DCAF12-MOV10 pathway in spermatogenesis and T cell activation.

Hierarchical Clustering Analysis for Predicting 1-Year Mortality After Starting Hemodialysis

Introduction

For patients with end-stage renal disease (ESRD), due to the heterogeneity of the population, appropriate risk assessment approaches and strategies for further follow-up remain scarce. We aimed to conduct a pilot study for better risk stratification, applying machine learning–based classification to patients with ESRD who newly started maintenance hemodialysis.

Methods

We prospectively studied 101 patients with ESRD, who were new to maintenance hemodialysis therapy, between August 2016 and March 2018. Baseline values of variables such as blood and urine tests were obtained before the initiation of hemodialysis. Agglomerative hierarchical clustering was conducted with the collected continuous data. The resulting clusters were followed up for the primary outcome of 1-year mortality, as analyzed by the Kaplan-Meier survival curve with log-rank test and the Cox proportional hazard model.

Results

The participants were divided into 3 clusters (cluster 1, n = 62; cluster 2, n = 15; cluster 3, n = 24) by hierarchical clustering, using 46 clinical variables. Patients in cluster 3 showed lower systolic blood pressures, and lower serum creatinine and urinary liver-type fatty acid-binding protein levels, before the initiation of hemodialysis. Consequently, cluster 3 was associated with the highest 1-year mortality in the study cohort (P < 0.001), and the difference was significant after adjustment for age and sex (hazard ratio: 10.2; 95% confidence interval: 2.94–46.8, cluster 1 as reference).

Conclusion

In this proof-of-concept study, hierarchical clustering discovered a subgroup with a higher 1-year mortality at the initiation of hemodialysis. Applying machine learning–derived classification to patients with ESRD may contribute to better risk stratification.

Recent advances in precision medicine for individualized immunosuppression

PURPOSE OF REVIEW

The current tools to proactively guide and individualize immunosuppression in solid organ transplantation are limited. Despite continued improvements in posttransplant outcomes, the adverse effects of over-immunosuppression or under-immunosuppression are common. The present review is intended to highlight recent advances in individualized immunosuppression.

RECENT FINDINGS

There has been a great focus on genomic information to predict drug dose requirements, specifically on single nucleotide polymorphisms of CYP3A5 and ABCB1. Furthermore, biomarker studies have developed ways to better predict clinical outcomes, such as graft rejection.

SUMMARY

The integration of advanced computing tools, such as artificial neural networks and machine learning, with genome sequencing has led to intriguing findings on individual or group-specific dosing requirements. Rapid computing allows for processing of data and discovering otherwise undetected clinical patterns. Genetic polymorphisms of CYP3A5 and ABCB1 have yielded results to suggest varying dose requirements correlated with race and sex. Newly proposed biomarkers offer precise and noninvasive ways to monitor patient's status. Cell-free DNA quantitation is increasingly explored as an indicator of allograft injury and rejection, which can help avoid unneeded biopsies and more frequently monitor graft function.

Noteworthy Literature Published in 2018 for Thoracic Organ Transplantation

Publications of note from 2018 are reviewed for the cardiothoracic transplant anesthesiologist. Strategies to expand the availability of donor organs were highlighted, including improved donor management, accumulating experience with increased-risk donors, ex vivo perfusion techniques, and donation after cardiac death. A number of reports examined posttransplant outcomes, including outcomes other than mortality, with new data-driven risk models. Use of extracorporeal support in cardiothoracic transplantation was a prominent theme. Major changes in adult heart allocation criteria were implemented, aiming to improve objectivity and transparency in the listing process. Frailty and prehabilitation emerged as targets of comprehensive perioperative risk mitigation programs.