Novel biomarkers useful in surveillance of graft rejection after heart transplantation

An Update on Myocarditis in Forensic Pathology

In forensic medicine, myocarditis is a complicated topic in the context of sudden death and medical malpractice. A good knowledge of the etiopathology, histopathology, and available literature are both indispensable and essential for the correct management and evaluation of the causal link. Some agents, which are rarely lethal for humans, are not necessarily related to death from myocarditis, even if an infection in other organs such as the gastrointestinal tract is documented. The diagnosis of the causes of death is often difficult and confusing. In some cases, the hypothetical diagnosis of myocarditis as the cause of death is formulated by deduction, causing error and misleading the correct temporal evaluation of pathological events. We reviewed the literature realizing that histomorphological data are scarce and often poorly documented. Only after COVID-19 have the histomorphological aspects of myocarditis been better documented. This is due to poor autopsy practice and poor accuracy in identifying the specific histotype of myocarditis with identification of the responsible agent. We believe that four points are essential for a better understanding and complete diagnosis of the disease: (1) clinical classification of myocarditis; (2) etiological classification of myocarditis; (3) pathophysiology of viral and bacterial infections with host response; and (4) histopathological diagnosis with precise identification of the histotype and pathogen. In the review we provide histological images from authoritative scientific references with the aim of providing useful information and food for thought to readers.

Towards Allograft Longevity: Leveraging Omics Technologies to Improve Heart Transplant Outcomes

PURPOSE OF REVIEW

Heart transplantation (HT) remains the optimal therapy for patients living with end-stage heart disease. Despite recent improvements in peri-transplant management, the median survival after HT has remained relatively static, and complications of HT, including infection, rejection, and allograft dysfunction, continue to impact quality of life and long-term survival.

RECENT FINDINGS

Omics technologies are becoming increasingly accessible and can identify novel biomarkers for, and reveal the underlying biology of, several disease states. While some technologies, such as gene expression profiling (GEP) and donor-derived cell-free DNA (dd-cfDNA), are routinely used in the clinical care of HT recipients, a number of emerging platforms, including pharmacogenomics, proteomics, and metabolomics, hold great potential for identifying biomarkers to aid in the diagnosis and management of post-transplant complications. Omics-based assays can improve patient and allograft longevity by facilitating a personalized and precision approach to post-HT care. The following article is a contemporary review of the current and future opportunities to leverage omics technologies, including genomics, transcriptomics, proteomics, and metabolomics in the field of HT.

Artificial intelligence, big data and heart transplantation: Actualities

BACKGROUND

As diagnostic and prognostic models developed by traditional statistics perform poorly in real-world, artificial intelligence (AI) and Big Data (BD) may improve the supply chain of heart transplantation (HTx), allocation opportunities, correct treatments, and finally optimize HTx outcome. We explored available studies, and discussed opportunities and limits of medical application of AI to the field of HTx.

METHOD

A systematic overview of studies published up to December 31st, 2022, in English on peer-revied journals, have been identified through PUBMED-MEDLINE-WEB of Science, referring to HTx, AI, BD. Studies were grouped in 4 domains based on main studies' objectives and results: etiology, diagnosis, prognosis, treatment. A systematic attempt was made to evaluate studies by the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD).

RESULTS

Among the 27 publications selected, none used AI applied to BD. Of the selected studies, 4 fell in the domain of etiology, 6 in the domain of diagnosis, 3 in the domain of treatment, and 17 in that of prognosis, as AI was most frequently used for algorithmic prediction and discrimination of survival, but in retrospective cohorts and registries. AI-based algorithms appeared superior to probabilistic functions to predict patterns, but external validation was rarely employed. Indeed, based on PROBAST, selected studies showed, to some extent, significant risk of bias (especially in the domain of predictors and analysis). In addition, as example of applicability in the real-world, a free-use prediction algorithm developed through AI failed to predict 1-year mortality post-HTx in cases from our center.

CONCLUSIONS

While AI-based prognostic and diagnostic functions performed better than those developed by traditional statistics, risk of bias, lack of external validation, and relatively poor applicability, may affect AI-based tools. More unbiased research with high quality BD meant for AI, transparency and external validations, are needed to have medical AI as a systematic aid to clinical decision making in HTx.

Extracellular Vesicles: The Future of Diagnosis in Solid Organ Transplantation?

Solid organ transplantation (SOT) is a life-saving treatment for end-stage organ failure, but it comes with several challenges, the most important of which is the existing gap between the need for transplants and organ availability. One of the main concerns in this regard is the lack of accurate non-invasive biomarkers to monitor the status of a transplanted organ. Extracellular vesicles (EVs) have recently emerged as a promising source of biomarkers for various diseases. In the context of SOT, EVs have been shown to be involved in the communication between donor and recipient cells and may carry valuable information about the function of an allograft. This has led to an increasing interest in exploring the use of EVs for the preoperative assessment of organs, early postoperative monitoring of graft function, or the diagnosis of rejection, infection, ischemia-reperfusion injury, or drug toxicity. In this review, we summarize recent evidence on the use of EVs as biomarkers for these conditions and discuss their applicability in the clinical setting.

"Transplantomics" for predicting allograft rejection: real-life applications and new strategies from Network Medicine

Although decades of the reductionist approach achieved great milestones in optimizing the immunosuppression therapy, traditional clinical parameters still fail in predicting both acute and chronic (mainly) rejection events leading to higher rates across all solid organ transplants. To clarify the underlying immune-related cellular and molecular mechanisms, current biomedical research is increasingly focusing on "transplantomics" which relies on a huge quantity of big data deriving from genomics, transcriptomics, epigenomics, proteomics, and metabolomics platforms. The AlloMap (gene expression) and the AlloSure (donor-derived cell-free DNA) tests represent two successful examples of how omics and liquid biopsy can really improve the precision medicine of heart and kidney transplantation. One of the major challenges in translating big data in clinically useful biomarkers is the integration and interpretation of the different layers of omics datasets. Network Medicine offers advanced bioinformatic-molecular strategies which were widely used to integrate large omics datasets and clinical information in end-stage patients to prioritize potential biomarkers and drug targets. The application of network-oriented approaches to clarify the complex nature of graft rejection is still in its infancy. Here, we briefly discuss the real-life clinical applications derived from omics datasets as well as novel opportunities for establishing predictive tests in solid organ transplantation. Also, we provide an original "graft rejection interactome" and propose network-oriented strategies which can be useful to improve precision medicine of solid organ transplantation.

Multifaceted role of cardiovascular biomarkers

Cardiovascular diseases, a global health issue, claim the lives of many every year. Lifestyle changes and genetic predisposition are the key drivers for the development of CVDs. In many of the patients, the disease is detected at the end stage making heart transplantation the only treatment option. Hence every attempt should be made to identify the risk at an early stage and initiate preventive measures to improve the quality of their life. Biomarkers are one of the critical factors that aid in the early diagnosis of CVDs. More specific and highly sensitive biomarkers have been discovered lately and have been employed for prognosis and diagnosis of CVDs. The present review briefs about the various categories of cardiovascular biomarkers with emphasis on novel biomarkers and discusses the biomarkers employed for different purposes in CVDs. The biomarkers have also helped in identifying COVID-19 patients with increased risk for developing cardiovascular complications. Being non-invasive makes biomarkers advantageous over other methods for evaluating the pathophysiological status of CVDs.

Novel insights in the clinical management of hyperimmune patients before and after transplantation

Despite improvements in anti-Human Leucocyte Antigens antibody detection, identification, and characterization offer a better in peri-operative management techniques, antibodies remain a serious cause of morbidity and mortality for patients both before and after organ transplantation. Hyperimmune patients are disadvantaged by having to wait longer to receive an organ from a suitably matched donor. They could benefit from desensitization protocols in both pre- and post-transplantation period. Clinical studies are underway to highlight which best desensitization strategies could be assure the best outcome in both heart and kidney transplantation. Although most clinical evidence about desensitization strategies by using anti-CD20 monoclonal antibodies, proteasome inhibitors, anti-CD38 monoclonal antibodies, interleukin-6 blockade, cysteine protease and complement inhibitors, comes from kidney transplantation studies, many of the debated novel concepts can be easily applied to desensitization also in heart transplantation. Here, we discuss the candidates and recipients' management by using most common standard of care and novel therapeutics, desensitization endpoints, and strategies for future studies.