Exploring miRNA-target gene pair detection in disease with coRmiT.

A wide range of approaches can be used to detect micro RNA (miRNA)-target gene pairs (mTPs) from expression data, differing in the ways the gene and miRNA expression profiles are calculated, combined and correlated. However, there is no clear consensus on which is the best approach across all datasets. Here, we have implemented multiple strategies and applied them to three distinct rare disease datasets that comprise smallRNA-Seq and RNA-Seq data obtained from the same samples, obtaining mTPs related to the disease pathology. All datasets were preprocessed using a standardized, freely available computational workflow, DEG_workflow. This workflow includes coRmiT, a method to compare multiple strategies for mTP detection. We used it to investigate the overlap of the detected mTPs with predicted and validated mTPs from 11 different databases. Results show that there is no clear best strategy for mTP detection applicable to all situations. We therefore propose the integration of the results of the different strategies by selecting the one with the highest odds ratio for each miRNA, as the optimal way to integrate the results. We applied this selection-integration method to the datasets and showed it to be robust to changes in the predicted and validated mTP databases. Our findings have important implications for miRNA analysis. coRmiT is implemented as part of the ExpHunterSuite Bioconductor package available from https://bioconductor.org/packages/ExpHunterSuite.

Human Neutrophils Couple Nitric Oxide Production and Extracellular Traps Formation in Allergic Asthma.

RATIONALE: Nitric oxide (NO) is elevated in the airways and serum of allergic asthmatic patients, suggesting an important role in asthma. NO production has been widely attributed to the canonical inducible nitric oxide synthase (iNOS). Much effort has been made to inhibit this enzyme with two outcomes: no asthma improvement; and partial NO reduction, suggesting the involvement of an iNOS-independent source. OBJECTIVES: Neutrophils produce NO under inflammatory conditions and their role in asthma has been overlooked. The present study analyzes their possible role as source of NO. METHODS: Our hypothesis was tested in 99 allergic patients with intermittent bronchial asthma and 26 healthy donors. NO production by blood and sputum neutrophils in response to allergens, anti-IgE, and anti-IgE receptors Abs was assessed by Griess, flow cytometry and confocal microscopy. Extracellular traps (ETs) formation, as a possible consequence of NO production, was quantified by western blot and confocal microscopy, and reactive oxygen species by luminol-enhanced chemiluminescence. RESULTS: Among blood and sputum granulocytes from allergic asthmatic patients, only neutrophils, produce NO by an IgE-dependent mechanism. This production is independent of NOS, but dependent on a reaction between L-arginine and reactive oxygen species from NOX2. NO and ETosis are induced in parallel, and NO amplifies ETs formation, which is a key mediator in asthma. CONCLUSIONS: Our findings reveal a novel role of neutrophils as the unique allergen/IgE-dependent NO source in allergic asthma enhancing ETs formation. These results suggest that NO produced by neutrophils needs further consideration in the treatment of allergic asthma.

Pediatric priority in kidney allocation after the age of 18 years.

Children registered for kidney transplants prior to the age of 18 years retain "pediatric" allocation status after their 18th birthday. There are no data on the impact of this policy. We performed a retrospective cohort study of 7097 candidates listed for kidney transplant prior to 18 years of age who remained on the waitlist after their 18th birthday between January 1, 2015, and April 1, 2022, using United Network for Organ Sharing data. A total of 1193 candidates remained on the waitlist after their 18th birthday. The median age at listing was 17 years (IQR: 17-17 years). A total of 588 candidates (8% of 7097 pediatric candidates) received a kidney transplant with pediatric status at the age of 18 years or older; 465 (79%) were deceased-donor transplants. The median age at deceased-donor transplants was 18 years (IQR: 18-19 years); 97% were performed before the age of 21 years. In the 7.25 years of the study, 12 adults aged 21 years and older received a deceased-donor kidney transplant with pediatric allocation priority. Deceased-donor transplants with pediatric priority after the age of 18 years are rare, comprising an estimated 0.4% of all adult deceased-donor transplants. Candidates with pediatric priority after 18 years of age typically progress to transplant within 3 years. Ongoing monitoring of this population is important to fully understand the allocation policy.

Risk for graft loss in pediatric and young adult kidney transplant recipients due to recurrent IgA nephropathy.

IgA nephropathy (IgAN) is associated with a risk for posttransplant recurrence. Data are limited regarding graft loss attributable to recurrence of IgAN among pediatric and young adult kidney transplant (KT) recipients. This was a retrospective cohort study of patients aged 0 to 25 years from the Scientific Registry of Transplant Recipients who received a primary KT for IgAN. Patients with history of KT attributable to renal dysplasia were comparators. Outcomes included the incidence of graft loss attributable to IgAN recurrence, association with donor type, and posttransplant corticosteroid use. In total, 5475 transplant recipients were included, with 1915 patients with IgAN and 3560 patients with renal dysplasia. In a multivariable Cox proportional hazards model, IgAN was associated with higher risk of graft loss (adjusted hazard ratio [aHR], 1.35; 95% CI, 1.21-1.50; P < .001) compared with dysplasia. Graft loss was attributed to recurrent disease in 5.4% of patients with IgAN. In a multivariable competing risks analysis, patients with IgAN receiving a parental living-donor kidney were more likely to report graft loss from recurrent disease compared with patients with a nonparental living donor (aHR, 0.52; 95% CI, 0.31-0.91; P = .02). Posttransplant prednisone use was not associated with improved graft survival (P = .2). These data challenge existing paradigms in posttransplant management of patients with IgAN.

A retrospective cohort study of socioeconomic deprivation and post-liver transplant survival in adults.

The Area Deprivation Index is a granular measure of neighborhood socioeconomic deprivation. The relationship between neighborhood socioeconomic deprivation and recipient survival following liver transplantation (LT) is unclear. To investigate this, the authors performed a retrospective cohort study of adults who underwent LT at the University of Washington Medical Center from January 1, 2004, to December 31, 2020. The primary exposure was a degree of neighborhood socioeconomic deprivation as determined by the Area Deprivation Index score. The primary outcome was posttransplant recipient mortality. In a multivariable Cox proportional analysis, LT recipients from high-deprivation areas had a higher risk of mortality than those from low-deprivation areas (HR: 1.81; 95% CI: 1.03-3.18, p =0.04). Notably, the difference in mortality between area deprivation groups did not become statistically significant until 6 years after transplantation. In summary, LT recipients experiencing high socioeconomic deprivation tended to have worse posttransplant survival. Further research is needed to elucidate the extent to which neighborhood socioeconomic deprivation contributes to mortality risk and identify effective measures to improve survival in more socioeconomically disadvantaged LT recipients.

The road less taken: Dihydroflavonol 4-reductase inactivation and delphinidin anthocyanin loss underpins a natural intraspecific flower colour variation.

Visual cues are of critical importance for the attraction of animal pollinators, however, little is known about the molecular mechanisms underpinning intraspecific floral colour variation. Here, we combined comparative spectral analysis, targeted metabolite profiling, multi-tissue transcriptomics, differential gene expression, sequence analysis and functional analysis to investigate a bee-pollinated orchid species, Glossodia major with common purple- and infrequent white-flowered morphs. We found uncommon and previously unreported delphinidin-based anthocyanins responsible for the conspicuous and pollinator-perceivable colour of the purple morph and three genetic changes underpinning the loss of colour in the white morph - (1) a loss-of-function (LOF; frameshift) mutation affecting dihydroflavonol 4-reductase (DFR1) coding sequence due to a unique 4-bp insertion, (2) specific downregulation of functional DFR1 expression and (3) the unexpected discovery of chimeric Gypsy transposable element (TE)-gene (DFR) transcripts with potential consequences to the genomic stability and post-transcriptional or epigenetic regulation of DFR. This is one of few known cases where regulatory changes and LOF mutation in an anthocyanin structural gene, rather than transcription factors, are important. Furthermore, if TEs prove to be a frequent source of mutation, the interplay between environmental stress-induced TE evolution and pollinator-mediated selection for adaptive colour variation may be an overlooked mechanism maintaining floral colour polymorphism in nature.

Kidney retransplantation outcomes in adults aged 70 and older: Analysis of risk factors and survival.

BACKGROUND: An increasing number of older patients are undergoing kidney transplant. Because of a finite longevity, more patients will be faced with failing allografts. At present there is a limited understanding of the benefits and risks associated with kidney retransplantation in this challenging population. METHODS: We performed a retrospective analysis of the Organ Procurement and Transplantation Network database of all adults ≥70 undergoing kidney retransplant from January 1, 2014 to December 31, 2022. We examined patient and graft survival of retransplanted patients compared to first time transplants. We also analyzed the risk factors that impacted the survival. RESULTS: During the study period there has been a significant rise in the number of retransplants performed, with 631 patients undergoing the procedure. Although clinically insignificant, overall graft, and patient survival rates were slightly lower in the retransplant group compared to the primary transplant group. With retransplant, patient survival was 91.3%, 75.6%, and 56.9% compared to 93.4%, 81.4%, and 64.4% with primary transplant at 1, 3, and 5 years, respectively. With retransplant, graft survival was 89.5%, 73.5%, 57.4% compared to 91.5%, 79.0%, and 63.6% in a primary transplant group at 1, 3, and 5 years, respectively. Multivariable analysis showed that factors predicting poor survival included longer time on dialysis before retransplantation and decreased functional capacity. No survival difference was noted between recipients of deceased versus living donor kidneys. Patients who underwent retransplantation before initiating dialysis had better patient and graft survival. CONCLUSION: Patients aged ≥70 achieve satisfactory outcomes following kidney retransplantation, highlighting that chronologic age should not preclude this medically complex population from this life-saving procedure. Improvement in functional status and timely retransplantation are the key factors to successful outcome.

Optimizing pediatric liver transplantation: Evaluating the impact of donor age and graft type on patient survival outcome.

BACKGROUND: We examined the combined effects of donor age and graft type on pediatric liver transplantation outcomes with an aim to offer insights into the strategic utilization of these donor and graft options. METHODS: A retrospective analysis was conducted using a national database on 0-2-year-old (N = 2714) and 3-17-year-old (N = 2263) pediatric recipients. These recipients were categorized based on donor age (≥40 vs <40 years) and graft type. Survival outcomes were analyzed using the Kaplan-Meier and Cox proportional hazards models, followed by an intention-to-treat (ITT) analysis to examine overall patient survival. RESULTS: Living and younger donors generally resulted in better outcomes compared to deceased and older donors, respectively. This difference was more significant among younger recipients (0-2 years compared to 3-17 years). Despite this finding, ITT survival analysis showed that donor age and graft type did not impact survival with the exception of 0-2-year-old recipients who had an improved survival with a younger living donor graft. CONCLUSIONS: Timely transplantation has the largest impact on survival in pediatric recipients. Improving waitlist mortality requires uniform surgical expertise at many transplant centers to provide technical variant graft (TVG) options and shed the conservative mindset of seeking only the "best" graft for pediatric recipients.

The volatile chemistry of orchid pollination.

Covering: up to September 2022Orchids are renowned not only for their diversity of floral forms, but also for their many and often highly specialised pollination strategies. Volatile semiochemicals play a crucial role in the attraction of a wide variety of insect pollinators of orchids. The compounds produced by orchid flowers are as diverse as the pollinators they attract, and here we summarise some of the chemical diversity found across orchid taxa and pollination strategies. We focus on compounds that have been experimentally demonstrated to underpin pollinator attraction. We also highlight the structural elucidation and synthesis of a select subset of important orchid pollinator attractants, and discuss the ecological significance of the discoveries, the gaps in our current knowledge of orchid pollination chemistry, and some opportunities for future research in this field.

Integrating differential expression, co-expression and gene network analysis for the identification of common genes associated with tumor angiogenesis deregulation.

Angiogenesis is essential for tumor growth and cancer metastasis. Identifying the molecular pathways involved in this process is the first step in the rational design of new therapeutic strategies to improve cancer treatment. In recent years, RNA-seq data analysis has helped to determine the genetic and molecular factors associated with different types of cancer. In this work we performed integrative analysis using RNA-seq data from human umbilical vein endothelial cells (HUVEC) and patients with angiogenesis-dependent diseases to find genes that serve as potential candidates to improve the prognosis of tumor angiogenesis deregulation and understand how this process is orchestrated at the genetic and molecular level. We downloaded four RNA-seq datasets (including cellular models of tumor angiogenesis and ischaemic heart disease) from the Sequence Read Archive. Our integrative analysis includes a first step to determine differentially and co-expressed genes. For this, we used the ExpHunter Suite, an R package that performs differential expression, co-expression and functional analysis of RNA-seq data. We used both differentially and co-expressed genes to explore the human gene interaction network and determine which genes were found in the different datasets that may be key for the angiogenesis deregulation. Finally, we performed drug repositioning analysis to find potential targets related to angiogenesis inhibition. We found that that among the transcriptional alterations identified, SEMA3D and IL33 genes are deregulated in all datasets. Microenvironment remodeling, cell cycle, lipid metabolism and vesicular transport are the main molecular pathways affected. In addition to this, interacting genes are involved in intracellular signaling pathways, especially in immune system and semaphorins, respiratory electron transport and fatty acid metabolism. The methodology presented here can be used for finding common transcriptional alterations in other genetically-based diseases.

Phenotype-genotype comorbidity analysis of patients with rare disorders provides insight into their pathological and molecular bases.

Genetic and molecular analysis of rare disease is made difficult by the small numbers of affected patients. Phenotypic comorbidity analysis can help rectify this by combining information from individuals with similar phenotypes and looking for overlap in terms of shared genes and underlying functional systems. However, few studies have combined comorbidity analysis with genomic data. We present a computational approach that connects patient phenotypes based on phenotypic co-occurence and uses genomic information related to the patient mutations to assign genes to the phenotypes, which are used to detect enriched functional systems. These phenotypes are clustered using network analysis to obtain functionally coherent phenotype clusters. We applied the approach to the DECIPHER database, containing phenotypic and genomic information for thousands of patients with heterogeneous rare disorders and copy number variants. Validity was demonstrated through overlap with known diseases, co-mention within the biomedical literature, semantic similarity measures, and patient cluster membership. These connected pairs formed multiple phenotype clusters, showing functional coherence, and mapped to genes and systems involved in similar pathological processes. Examples include claudin genes from the 22q11 genomic region associated with a cluster of phenotypes related to DiGeorge syndrome and genes related to the GO term anterior/posterior pattern specification associated with abnormal development. The clusters generated can help with the diagnosis of rare diseases, by suggesting additional phenotypes for a given patient and potential underlying functional systems. Other tools to find causal genes based on phenotype were also investigated. The approach has been implemented as a workflow, named PhenCo, which can be adapted to any set of patients for which phenomic and genomic data is available. Full details of the analysis, including the clusters formed, their constituent functional systems and underlying genes are given. Code to implement the workflow is available from GitHub.

Assigning protein function from domain-function associations using DomFun.

BACKGROUND: Protein function prediction remains a key challenge. Domain composition affects protein function. Here we present DomFun, a Ruby gem that uses associations between protein domains and functions, calculated using multiple indices based on tripartite network analysis. These domain-function associations are combined at the protein level, to generate protein-function predictions. RESULTS: We analysed 16 tripartite networks connecting homologous superfamily and FunFam domains from CATH-Gene3D with functional annotations from the three Gene Ontology (GO) sub-ontologies, KEGG, and Reactome. We validated the results using the CAFA 3 benchmark platform for GO annotation, finding that out of the multiple association metrics and domain datasets tested, Simpson index for FunFam domain-function associations combined with Stouffer's method leads to the best performance in almost all scenarios. We also found that using FunFams led to better performance than superfamilies, and better results were found for GO molecular function compared to GO biological process terms. DomFun performed as well as the highest-performing method in certain CAFA 3 evaluation procedures in terms of [Formula: see text] and [Formula: see text] We also implemented our own benchmark procedure, Pathway Prediction Performance (PPP), which can be used to validate function prediction for additional annotations sources, such as KEGG and Reactome. Using PPP, we found similar results to those found with CAFA 3 for GO, moreover we found good performance for the other annotation sources. As with CAFA 3, Simpson index with Stouffer's method led to the top performance in almost all scenarios. CONCLUSIONS: DomFun shows competitive performance with other methods evaluated in CAFA 3 when predicting proteins function with GO, although results vary depending on the evaluation procedure. Through our own benchmark procedure, PPP, we have shown it can also make accurate predictions for KEGG and Reactome. It performs best when using FunFams, combining Simpson index derived domain-function associations using Stouffer's method. The tool has been implemented so that it can be easily adapted to incorporate other protein features, such as domain data from other sources, amino acid k-mers and motifs. The DomFun Ruby gem is available from https://rubygems.org/gems/DomFun . Code maintained at https://github.com/ElenaRojano/DomFun . Validation procedure scripts can be found at https://github.com/ElenaRojano/DomFun_project .

Deceased donor kidneys are discarded at higher rates when labeled as high kidney donor profile index.

The kidney donor risk index (KDRI) and percentile conversion, kidney donor profile index (KDPI), provide a continuous measure of donor quality. Kidneys with a KDPI >85% (KDPI85 ) are referred to as "high KDPI." The KDPI85 cutoff changes every year, impacting which kidneys are labeled as KDPIHIGH . We examine kidney utilization around the KDPI85 cutoff and explore the "high KDPI" labeling effect. KDRI to KDPI Mapping Tables from 2012 to 2020 were used to determine the yearly KDRI85 value. Organ Procurement and Transplantation Network data was used to calculate discard rates and model organ use. KDRI85 varied between 1.768 and 1.888. In a multivariable analysis, kidney utilization was lower for KDPI 86% compared with KDPI 85% kidneys (p = .046). Kidneys with a KDRI between 1.785-1.849 were classified as KDPIHIGH in the years 2015-2017 and KDPILOW in the years 2018-2020. The discard rate was 44.9% when labeled as KDPIHIGH and 39.1% when labeled as KDPILOW (p < .01). For kidneys with the same KDRI, the high KDPI label is associated with increased discard. We should reconsider the appropriateness of the "high KDPI" label.

Acute Graft-Versus-Host Disease After Orthotopic Liver Transplantation: Predicting This Rare Complication Using Machine Learning.

Acute graft-versus-host disease (GVHD) is a rare complication after orthotopic liver transplantation (OLT) that carries high mortality. We hypothesized that machine-learning algorithms to predict rare events would identify patients at high risk for developing GVHD. To develop a predictive model, we retrospectively evaluated the clinical features of 1938 donor-recipient pairs at the time they underwent OLT at our center; 19 (1.0%) of these recipients developed GVHD. This population was divided into training (70%) and test (30%) sets. A total of 7 machine-learning classification algorithms were built based on the training data set to identify patients at high risk for GVHD. The C5.0, heterogeneous ensemble, and generalized gradient boosting machine (GGBM) algorithms predicted that 21% to 28% of the recipients in the test data set were at high risk for developing GVHD, with an area under the receiver operating characteristic curve (AUROC) of 0.83 to 0.86. The 7 algorithms were then evaluated in a validation data set of 75 more recent donor-recipient pairs who underwent OLT at our center; 2 of these recipients developed GVHD. The logistic regression, heterogeneous ensemble, and GGBM algorithms predicted that 9% to 11% of the validation recipients were at high risk for developing GVHD, with an AUROC of 0.93 to 0.96 that included the 2 recipients who developed GVHD. In conclusion, we present a practical model that can identify patients at high risk for GVHD who may warrant additional monitoring with peripheral blood chimerism testing.

Systematic identification of genetic systems associated with phenotypes in patients with rare genomic copy number variations.

Copy number variation (CNV) related disorders tend to show complex phenotypic profiles that do not match known diseases. This makes it difficult to ascertain their underlying molecular basis. A potential solution is to compare the affected genomic regions for multiple patients that share a pathological phenotype, looking for commonalities. Here, we present a novel approach to associate phenotypes with functional systems, in terms of GO categories and KEGG and Reactome pathways, based on patient data. The approach uses genomic and phenomic data from the same patients, finding shared genomic regions between patients with similar phenotypes. These regions are mapped to genes to find associated functional systems. We applied the approach to analyse patients in the DECIPHER database with de novo CNVs, finding functional systems associated with most phenotypes, often due to mutations affecting related genes in the same genomic region. Manual inspection of the ten top-scoring phenotypes found multiple FunSys connections supported by the previous studies for seven of them. The workflow also produces reports focussed on the genes and FunSys connected to the different phenotypes, alongside patient-specific reports, which give details of the associated genes and FunSys for each individual in the cohort. These can be run in "confidential" mode, preserving patient confidentiality. The workflow presented here can be used to associate phenotypes with functional systems using data at the level of a whole cohort of patients, identifying important connections that could not be found when considering them individually. The full workflow is available for download, enabling it to be run on any patient cohort for which phenotypic and CNV data are available.

Regulatory variants: from detection to predicting impact.

Variants within non-coding genomic regions can greatly affect disease. In recent years, increasing focus has been given to these variants, and how they can alter regulatory elements, such as enhancers, transcription factor binding sites and DNA methylation regions. Such variants can be considered regulatory variants. Concurrently, much effort has been put into establishing international consortia to undertake large projects aimed at discovering regulatory elements in different tissues, cell lines and organisms, and probing the effects of genetic variants on regulation by measuring gene expression. Here, we describe methods and techniques for discovering disease-associated non-coding variants using sequencing technologies. We then explain the computational procedures that can be used for annotating these variants using the information from the aforementioned projects, and prediction of their putative effects, including potential pathogenicity, based on rule-based and machine learning approaches. We provide the details of techniques to validate these predictions, by mapping chromatin-chromatin and chromatin-protein interactions, and introduce Clustered Regularly Interspaced Short Palindromic Repeats-Associated Protein 9 (CRISPR-Cas9) technology, which has already been used in this field and is likely to have a big impact on its future evolution. We also give examples of regulatory variants associated with multiple complex diseases. This review is aimed at bioinformaticians interested in the characterization of regulatory variants, molecular biologists and geneticists interested in understanding more about the nature and potential role of such variants from a functional point of views, and clinicians who may wish to learn about variants in non-coding genomic regions associated with a given disease and find out what to do next to uncover how they impact on the underlying mechanisms.

Association of Donor and Recipient Cytomegalovirus Serostatus on Graft and Patient Survival in Liver Transplant Recipients.

Among solid organ transplant recipients, donor cytomegalovirus (CMV) seropositive (D+) and recipient seronegative (R-) status are associated with an increased risk of graft loss and mortality after kidney or lung transplantation. Whether a similar relationship exists among liver transplant recipients (LTR) is unknown. We assessed graft loss and mortality among adult LTRs from January 1, 2010, to March 14, 2020, in the Organ Procurement and Transplantation Network database. We used multivariable mixed Cox proportional hazards regression to analyze the association of donor and recipient CMV serostatus group with graft loss and mortality, with donor seronegative (D-) and recipient seronegative (R-) as the reference group. Among 54,078 LTRs, the proportion of D-R-, D- and recipient seropositive (R+), D+R-, and D+R+ was 13.4%, 22.5%, 22%, and 42%, respectively. By unadjusted Kaplan-Meier survival curve estimates, survival by the end of follow-up was 73.3%, 73.5%, 70.1%, and 69.7%, among the D-R-, D-R+, D+R-, and D+R+ groups, respectively. By multivariable Cox regression, the CMV D+R- serogroup, but not other serogroups, was independently associated with increased risks of graft loss (adjusted hazard ratio [aHR], 1.13; 95% confidence interval [CI], 1.05-1.22) and mortality (aHR, 1.13; 95% CI, 1.05-1.22). The magnitude of the association of the CMV D+R- serostatus group with mortality was similar when the Cox regression analysis was restricted to the first year after transplant and beyond the first year after transplant: aHR, 1.13 (95% CI, 1.01-1.27) and aHR, 1.13 (95% CI, 1.02-1.25), respectively. Even in an era of CMV preventive strategies, CMV D+R- serogroup status remains independently associated with increased graft loss and mortality in adult LTRs. Factors in addition to direct CMV-associated short-term mortality are likely, and studies to define the underlying mechanism(s) are warranted.

Do funding sources influence long-term patient survival in pediatric liver transplantation?

BACKGROUND: Socioeconomic status has been associated with inferior outcomes after multiple surgical procedures, but has not been well studied with respect to pediatric liver transplantation. This study evaluated the impact of insurance status (as a proxy for socioeconomic status) on patient and allograft survival in pediatric first-time liver transplant recipients. METHODS: Our retrospective analysis of the UNOS data base from January 2002 through September 2017 revealed 6997 pediatric patients undergoing first-time isolated liver transplantation. A mixed Cox proportional hazards model adjusted for donor, recipient, and program characteristics determined the RR of insurance status on allograft and patient survival. All results were considered significant at P < .05. All statistical results were obtained using R version 3.5.1 and coxme version 2.2-10. RESULTS: Medicaid status had a significant negative impact on long-term survival after controlling for multiple covariates. Pediatric patients undergoing first-time isolated liver transplantation with Medicaid insurance had a RR of 1.42 [confidence interval: 1.18-1.60] of post-transplant death. CONCLUSION: Pediatric patients undergoing first-time isolated liver transplantation have multiple risk factors that may impact long-term survival. Having Medicaid insurance almost doubles the chances of dying post-liver transplant. This patient population may require more global support post-transplant to improve long-term survival.

End-of-Life Care among US Adults with ESKD Who Were Waitlisted or Received a Kidney Transplant, 2005-2014.

BACKGROUND: The care of patients in the United States who have ESKD is often shaped by their hopes and prognostic expectations related to kidney transplant. Little is known about how patients' engagement in the transplant process might relate to patterns of end-of-life care. METHODS: We compared six measures of intensity of end-of-life care among adults in the United States with ESKD who died between 2005 and 2014 after experiencing differing exposure to the kidney transplant process. RESULTS: Of 567,832 decedents with ESKD, 27,633 (5%) had a functioning kidney transplant at the time of death, 14,653 (3%) had a failed transplant, 16,490 (3%) had been removed from the deceased donor waitlist, 17,010 (3%) were inactive on the waitlist, 11,529 (2%) were active on the waitlist, and 480,517 (85%) had never been waitlisted for or received a transplant (reference group). In adjusted analyses, compared with the reference group, patients exposed to the transplant process were significantly more likely to have been admitted to an intensive care unit and to have received an intensive procedure in the last 30 days of life; they were also significantly more likely to have died in the hospital. Those who died on the transplant waitlist were also less likely than those in the reference group to have been enrolled in hospice and to have discontinued dialysis before death. CONCLUSIONS: Patients who had engaged in the kidney transplant process received more intensive patterns of end-of-life care than other patients with ESKD. These findings support the relevance of advance care planning, even for this relatively healthy segment of the ESKD population.

Livers From Pediatric Donation After Circulatory Death Donors Represent a Viable and Underutilized Source of Allograft.

Despite increased numbers of donation after circulatory death (DCD) donors, pediatric DCD livers are underused. To investigate possible reasons for this discrepancy, we conducted a retrospective cohort study using 2 data sets from the Organ Procurement and Transplantation Network for all deceased liver donors and for all recipients of DCD liver transplants from March 8, 1993, to June 30, 2018. Pediatric (0-12 years) and adolescent (13-17 years) DCD donors were compared with those aged 18-40 years. We found that pediatric DCD allografts are recovered at a significantly lower rate than from 18-to-40-year-old donors (27.3% versus 56.3%; P < 0.001). However, once recovered, these organs are transplanted at a similar rate to those from the 18-to-40-year-old donor cohort (74.7% versus 74.2%). Significantly more pediatric DCD livers (odds ratio [OR], 3.75; confidence interval [CI], 3.14-4.47) were not recovered compared with adult organs, which were most commonly not recovered due to organ quality (10.2% versus 7.1%; P < 0.001). The 10-year relative risks (RRs) for graft failure and patient death were similar between pediatric and adult DCD donors, with adolescent DCD livers demonstrating improved outcomes. DCD livers transplanted into pediatric donors were protective against graft failure (RR, 0.46; 95% confidence interval [CI], 0.21-0.99) and patient death (RR, 0.16; 95% CI, 0.04-0.69). In conclusion, despite lower rates of recovery, pediatric DCD livers represent a viable organ source for certain adults and children.