Bhat, Mamatha

The Ajmera Transplant Center and Mayo Clinic hosted the third annual Transplant Artificial Intelligence (AI) Symposium in Toronto, Canada, bringing together expert clinicians, researchers, scientists, and trainees to discuss the current role of AI in transplant medicine. This paper summarizes the third annual Transplant AI Symposium proceedings and talks. Presentations covered a wide range of topics across the transplant continuum, highlighting numerous benefits of AI in transplantation such as organ matching, human-AI collaboration, and survival/risk prediction. Artificial intelligence is most useful when linked to specific clinical problems, especially those involving multimodal or longitudinal data. However, speakers also emphasized ongoing limitations in data quality, generalizability, workflow integration, and fairness. Multiple presentations highlighted the importance of clinician oversight. Overall, the symposium highlighted that the future of transplant AI will depend on careful validation, clinically meaningful implementation, and attention to patient outcomes ( Figure 1 ).

Machine learning (ML) utilizes artificial intelligence to generate predictive models efficiently and more effectively than conventional methods through detection of hidden patterns within large data sets. With this in mind, there are several areas within hepatology where these methods can be applied. In this review, we examine the literature pertaining to machine learning in hepatology and liver transplant medicine. We provide an overview of the strengths and limitations of ML tools and their potential applications to both clinical and molecular data in hepatology. ML has been applied to various types of data in liver disease research, including clinical, demographic, molecular, radiological, and pathological data. We anticipate that use of ML tools to generate predictive algorithms will change the face of clinical practice in hepatology and transplantation. This review will provide readers with the opportunity to learn about the ML tools available and potential applications to questions of interest in hepatology.

The International Liver Transplantation Society (ILTS) 2019 Annual Congress was held in Toronto, Canada, in May 2019. Members of the ILTS Basic and Translational Research Committee attended all sessions of the meeting and selected the most promising, innovative, and novel research presented. A total of 900 abstracts were presented at the meeting. The percentage of abstracts presented at the ILTS Congress that contains basic or translational research continues to increase, accounting for 15% of all the abstracts in 2019, up from 10% in 2018. Here, we summarize the “what’s hot what’s new” in 5 main themes: liver immunobiology and tolerance, ischemia/reperfusion injury and organ preservation, bioengineering and liver regeneration, hepatic primary tumor biology, and pathophysiology of liver failure.

Background. Posttransplant diabetes mellitus (PTDM) affects up to 50% of solid organ transplant recipients and compromises long-term outcomes. The goal of this study was to investigate how immunosuppressants affect gene expression in a manner that increases diabetes risk, by performing integrative analysis on publicly available, high-throughput gene expression data. Methods. All high-throughput gene expression datasets of solid organ transplant recipients were retrieved from the Gene Expression Omnibus. Significantly dysregulated genes and pathways were determined, and those in common with type 2 diabetes were identified. THP-1 and HepG2 cells were exposed in vitro to tacrolimus, and validation of genes involved in insulin signaling and glucose metabolism was performed using specific arrays. These cells were then treated with the hypoglycemic agents, metformin, and insulin to assess for appropriate reversion of specific diabetogenic genes. Results. Insulin signaling and secretion were the most commonly dysregulated pathways that overlapped with diabetes in transplant recipients. KRAS, GRB2, PCK2, BCL2L1, INSL3, DOK3, and PTPN1 were among the most significantly upregulated genes in both immunosuppression and diabetes subsets and were appropriately reverted by metformin as confirmed in vitro. Conclusions. We discovered that the significantly dysregulated genes in the context of immunosuppression are implicated in insulin signaling and insulin secretion, as a manifestation of pancreatic β-cell function. In vitro validation confirmed key diabetes-related genes in the context of immunosuppression. Further analysis and in vitro validation revealed that metformin optimally reverts diabetogenic genes dysregulated in the context of immunosuppression. The optimal therapeutic management of posttransplant diabetes mellitus needs to be further investigated, taking into account the mechanistic impact of immunosuppressants.

The 24th Joint Annual Congress of the International Liver Transplantation Society in association with European Liver and Intestine Transplant Association and Liver Intensive Care Group of Europe was held in Lisbon, Portugal from May 23 to 26, 2018. More than 1200 participants from over 60 countries including surgeons, hepatologists, anesthesiologists and critical care intensivists, radiologists, pathologists, organ procurement personnel, and research scientists came together with the common aim of improving care and outcomes for liver transplant recipients. Over 600 scientific abstracts were presented. The principal themes were living donation, use of marginal liver donors, machine preservation, disease-specific immunosuppressive regimen, malignancies, and advances in pediatric liver transplantation and liver transplant anesthesia. This report presents excerpts from invited lectures and select abstracts from scientific sessions, which add to current knowledge, and will drive clinical practice and future research.

Background Malignancy after liver transplant (LT) is a leading cause of mortality, but data is limited. The aim of this study was to identify patients at higher risk for de novo malignancies after LT in a large multicenter database. Methods The Scientific Registry of Transplant Recipients database comprising all 108 412 LT recipients across the United States between 1987 and March 2015 was analyzed with a median follow-up of 6.95 years. Potential risk factors for malignancies after LT were assessed using Cox regression analysis for the outcome of time to first malignancy. Results Mean age 51.9 ± 10.8 years, 64.6% male, 74.5% white, and 15.8% with previous malignancy. Malignancies during follow-up were 4,483 (41.3%) skin, 1519 (14.0%) hematologic, and 4842 (44.7%) solid organ. The 10-year probability of de novo malignancy was 11.5% (11.3-11.8%). On multivariable analysis, age by decade (hazard ratio [HR], 1.52; P < 0.001), male sex (HR, 1.28; P < 0.001), white race (compared with other races: HR, 1.45-2.04; P < 0.001), multiorgan transplant (HR, 1.35; P < 0.001), previous malignancy (HR, 1.34; P < 0.001), and alcoholic liver disease, autoimmune, nonalcoholic steatohepatitis (HR, 1.35; P < 0.001), and primary sclerosing cholangitis pre-LT (compared with hepatitis C virus, P < 0.001) were associated with higher risk of post-LT malignancy, but type of immunosuppression was not (P = NS). Conclusions This large data set demonstrates the effects of ethnicity/race and etiologies of liver disease, particularly nonalcoholic steatohepatitis as additional risk factors for cancer after LT. Patients with these high-risk characteristics should be more regularly and diligently screened.