Development of a Clinical Prediction Model for Diabetes in Chronic Pancreatitis: The PREDICT3c Study.

OBJECTIVE: Diabetes that arises from chronic pancreatitis (CP) is associated with increased morbidity and mortality. Methods to predict which patients with CP are at greatest risk for diabetes are urgently needed. We aimed to examine independent risk factors for diabetes in a large cohort of patients with CP. RESEARCH DESIGN AND METHODS: This cross-sectional study comprised 645 individuals with CP enrolled in the PROCEED study, of whom 276 had diabetes. We conducted univariable and multivariable regression analyses of potential risk factors for diabetes. Model performance was assessed by area under the receiver operating characteristic curve (AUROC) analysis, and accuracy was evaluated by cross validation. Exploratory analyses were stratified according to the timing of development of diabetes relative to the diagnosis of pancreatitis. RESULTS: Independent correlates of diabetes in CP included risk factors for type 2 diabetes (older age, overweight/obese status, male sex, non-White race, tobacco use) as well as pancreatic disease-related factors (history of acute pancreatitis complications, nonalcoholic etiology of CP, exocrine pancreatic dysfunction, pancreatic calcification, pancreatic atrophy) (AUROC 0.745). Type 2 diabetes risk factors were predominant for diabetes occurring before pancreatitis, and pancreatic disease-related factors were predominant for diabetes occurring after pancreatitis. CONCLUSIONS: Multiple factors are associated with diabetes in CP, including canonical risk factors for type 2 diabetes and features associated with pancreatitis severity. This study lays the groundwork for the future development of models integrating clinical and nonclinical data to identify patients with CP at risk for diabetes and identifies modifiable risk factors (obesity, smoking) on which to focus for diabetes prevention.

Noninvasive biomarkers for prediction and diagnosis of heart transplantation rejection.

For most patients with end-stage heart failure, heart transplantation is the treatment of choice. Allograft rejection is one of the major post-transplantation complications affecting graft outcome and survival. Recent advancements in science and technology offer an opportunity to integrate genomic and other omics-based biomarkers into clinical practice, facilitating noninvasive evaluation of allograft for diagnostic and prognostic purposes. Omics, including gene expression profiling (GEP) of blood immune cell components and donor-derived cell-free DNA (dd-cfDNA) are of special interest to researchers. Several studies have investigated levels of dd-cfDNA and miroRNAs in blood as potential markers for early detection of allograft rejection. One of the achievements in the field of transcriptomics is AlloMap, GEP of peripheral blood mononuclear cells (PBMC), which can identify 11 differentially expressed genes and help with detection of moderate and severe acute cellular rejection in stable heart transplant recipients. In recent years, the utilization of GEP of PBMC for identifying differentially expressed genes to diagnose acute antibody-mediated rejection and cardiac allograft vasculopathy has yielded promising results. Advancements in the field of metabolomics and proteomics as well as their potential implications have been further discussed in this paper.

Rejection-associated Mitochondrial Impairment After Heart Transplantation.

BACKGROUND: Mitochondrial dysfunction is associated with poor allograft prognosis. Mitochondrial-related gene expression (GE) in endomyocardial biopsies (EMBs) could be useful as a nonimmune functional marker of rejection. We hypothesize that acute cardiac allograft rejection is associated with decreased mitochondrial-related GE in EMBs. METHODS: We collected 64 routines or clinically indicated EMB from 47 patients after heart transplant. The EMBs were subjected to mRNA sequencing. We conducted weighted gene coexpression network analysis to construct module-derived eigengenes. The modules were assessed by gene ontology enrichment and hub gene analysis. Modules were correlated with the EMBs following the International Society of Heart and Lung Transplantation histology-based criteria and a classification based on GE alone; we also correlated with clinical parameters. RESULTS: The modules enriched with mitochondria-related and immune-response genes showed the strongest correlation to the clinical traits. Compared with the no-rejection samples, rejection samples had a decreased activity of mitochondrial-related genes and an increased activity of immune-response genes. Biologic processes and hub genes in the mitochondria-related modules were primarily involved with energy generation, substrate metabolism, and regulation of oxidative stress. Compared with International Society of Heart and Lung Transplantation criteria, GE-based classification had stronger correlation to the weighted gene coexpression network analysis-derived functional modules. The brain natriuretic peptide level, ImmuKnow, and Allomap scores had negative relationships with the expression of mitochondria-related modules and positive relationships with immune-response modules. CONCLUSIONS: During acute cardiac allograft rejection, there was a decreased activity of mitochondrial-related genes, related to an increased activity of immune-response genes, and depressed allograft function manifested by brain natriuretic peptide elevation. This suggests a rejection-associated mitochondrial impairment.

Association of pro-inflammatory cytokines and monocyte subtypes in older and younger patients on clinical outcomes after mechanical circulatory support device implantation.

Noninvasive immunologic analysis of peripheral blood holds promise for explaining the mechanism of development of adverse clinical outcomes, and may also become a method for patient risk stratification before or after mechanical circulatory support device (MCSD) implantation. Dysregulation of the innate immune system is associated with increased patient age but has yet to be evaluated in the older patient with advanced heart failure undergoing MCSD surgery. Patients pre- and post-MCSD implantation had peripheral blood mononuclear cells (PBMC) and serum isolated. Multiparameter flow cytometry was used to analyze markers of innate cell function, including monocyte subtypes. Multiplex cytokine analysis was performed. MELD-XI and SOFA scores were utilized as surrogate markers of outcomes. Increased levels of pro-inflammatory cytokines including IL-15, TNF-α, and IL-10 were associated with increased MELD-XI and SOFA scores. IL-8, TNF- α, and IL-10 were associated with risk of death after MCSD implantation, even with correction for patient age. Increased frequency of 'classical' monocytes (CD14 + CD16-) were associated with increased MELD-XI and SOFA scores. This suggests that inflammation and innate immune system activation contribute to progression to multiorgan system failure and death after MCSD surgery. Development of noninvasive monitoring of peripheral blood holds promise for biomarker development for candidate selection and patient risk stratification.

Clinical phenomapping and outcomes after heart transplantation.

BACKGROUND: Survival after heart transplantation (HTx) is limited by complications related to alloreactivity, immune suppression, and adverse effects of pharmacologic therapies. We hypothesize that time-dependent phenomapping of clinical and molecular data sets is a valuable approach to clinical assessments and guiding medical management to improve outcomes. METHODS: We analyzed clinical, therapeutic, biomarker, and outcome data from 94 adult HTx patients and 1,557 clinical encounters performed between January 2010 and April 2013. Multivariate analyses were used to evaluate the association between immunosuppression therapy, biomarkers, and the combined clinical end point of death, allograft loss, retransplantation, and rejection. Data were analyzed by K-means clustering (K = 2) to identify patterns of similar combined immunosuppression management, and percentile slopes were computed to examine the changes in dosages over time. Findings were correlated with clinical parameters, human leucocyte antigen antibody titers, and peripheral blood mononuclear cell gene expression of the AlloMap (CareDx, Inc., Brisbane, CA) test genes. An intragraft, heart tissue gene coexpression network analysis was performed. RESULTS: Unsupervised cluster analysis of immunosuppressive therapies identified 2 groups, 1 characterized by a steeper immunosuppression minimization, associated with a higher likelihood for the combined end point, and the other by a less pronounced change. A time-dependent phenomap suggested that patients in the group with higher event rates had increased human leukocyte antigen class I and II antibody titers, higher expression of the FLT3 AlloMap gene, and lower expression of the MARCH8 and WDR40A AlloMap genes. Intramyocardial biomarker-related coexpression network analysis of the FLT3 gene showed an immune system-related network underlying this biomarker. CONCLUSIONS: Time-dependent precision phenotyping is a mechanistically insightful, data-driven approach to characterize patterns of clinical care and identify ways to improve clinical management and outcomes.

T cell dysfunction and patient age are associated with poor outcomes after mechanical circulatory support device implantation.

Immunologic impairment may contribute to poor outcomes after implantation of mechanical circulatory support device (MCSD), with infection often as a terminal event. The study of immune dysfunction is of special relevance given the growing numbers of older patients with heart disease. The aim of the study was to define which immunologic characteristics are associated with development of adverse clinical outcomes after MCSD implantation. We isolated peripheral blood mononuclear cells (PBMC) from patients pre- and up to 20 days post-MCSD implantation and analyzed them by multiparameter flow cytometry for T cell dysfunction, including terminal differentiation, exhaustion, and senescence. We used MELD-XI and SOFA scores measured at each time point as surrogate markers of clinical outcome. Older patients demonstrated increased frequencies of terminally differentiated T cells as well as NKT cells. Increased frequency of terminally differentiated and immune senescent T cells were associated with worse clinical outcome as measured by MELD-XI and SOFA scores, and with progression to infection and death. In conclusion, our data suggest that T cell dysfunction, independently from age, is associated with poor outcomes after MCSD implantation, providing a potential immunologic mechanism behind patient vulnerability to multiorgan dysfunction and death. This noninvasive approach to PBMC evaluation holds promise for candidate evaluation and patient monitoring.

Association between preoperative peripheral blood mononuclear cell gene expression profiles, early postoperative organ function recovery potential and long-term survival in advanced heart failure patients undergoing mechanical circulatory support.

BACKGROUND: Multiorgan dysfunction syndrome contributes to adverse outcomes in advanced heart failure (AdHF) patients after mechanical circulatory support (MCS) implantation and is associated with aberrant leukocyte activity. We tested the hypothesis that preoperative peripheral blood mononuclear cell (PBMC) gene expression profiles (GEP) can predict early postoperative improvement or non-improvement in patients undergoing MCS implantation. We believe this information may be useful in developing prognostic biomarkers. METHODS & DESIGN: We conducted a study with 29 patients undergoing MCS-surgery in a tertiary academic medical center from 2012 to 2014. PBMC samples were collected one day before surgery (day -1). Clinical data was collected on day -1 and day 8 postoperatively. Patients were classified by Sequential Organ Failure Assessment score and Model of End-stage Liver Disease Except INR score (measured eight days after surgery): Group I = improving (both scores improved from day -1 to day 8, n = 17) and Group II = not improving (either one or both scores did not improve from day -1 to day 8, n = 12). RNA-sequencing was performed on purified mRNA and analyzed using Next Generation Sequencing Strand. Differentially expressed genes (DEGs) were identified by Mann-Whitney test with Benjamini-Hochberg correction. Preoperative DEGs were used to construct a support vector machine algorithm to predict Group I vs. Group II membership. RESULTS: Out of 28 MCS-surgery patients alive 8 days postoperatively, one-year survival was 88% in Group I and 27% in Group II. We identified 28 preoperative DEGs between Group I and II, with an average 93% prediction accuracy. Out of 105 DEGs identified preoperatively between year 1 survivors and non-survivors, 12 genes overlapped with the 28 predictive genes. CONCLUSIONS: In AdHF patients following MCS implantation, preoperative PBMC-GEP predicts early changes in organ function scores and correlates with long-term outcomes. Therefore, gene expression lends itself to outcome prediction and warrants further studies in larger longitudinal cohorts.

Integrative model of leukocyte genomics and organ dysfunction in heart failure patients requiring mechanical circulatory support: a prospective observational study.

BACKGROUND: The implantation of mechanical circulatory support devices in heart failure patients is associated with a systemic inflammatory response, potentially leading to death from multiple organ dysfunction syndrome. Previous studies point to the involvement of many mechanisms, but an integrative hypothesis does not yet exist. Using time-dependent whole-genome mRNA expression in circulating leukocytes, we constructed a systems-model to improve mechanistic understanding and prediction of adverse outcomes. METHODS: We sampled peripheral blood mononuclear cells from 22 consecutive patients undergoing mechanical circulatory support device (MCS) surgery, at 5 timepoints: day -1 preoperative, and postoperative days 1, 3, 5, and 8. Clinical phenotyping was performed using 12 clinical parameters, 2 organ dysfunction scoring systems, and survival outcomes. We constructed a strictly phenotype-driven time-dependent non-supervised systems-representation using weighted gene co-expression network analysis, and annotated eigengenes using gene ontology, pathway, and transcription factor binding site enrichment analyses. Genes and eigengenes were mapped to the clinical phenotype using a linear mixed-effect model, with Cox models also fit at each timepoint to survival outcomes. RESULTS: We inferred a 19-module network, in which most module eigengenes correlated with at least one aspect of the clinical phenotype. We observed a response of advanced heart failure patients to surgery orchestrated into stages: first, activation of the innate immune response, followed by anti-inflammation, and finally reparative processes such as mitosis, coagulation, and apoptosis. Eigengenes related to red blood cell production and extracellular matrix degradation became predictors of survival late in the timecourse corresponding to multiorgan dysfunction and disseminated intravascular coagulation. CONCLUSIONS: Our model provides an integrative representation of leukocyte biology during the systemic inflammatory response following MCS device implantation. It demonstrates consistency with previous hypotheses, identifying a number of known mechanisms. At the same time, it suggests novel hypotheses about time-specific targets.

From Impairment to Empowerment: A Longitudinal Medical School Curriculum on Disabilities.

PROBLEM: All physicians will care for individuals with disabilities; however, education about disabilities is lacking at most medical schools. Most of the schools that do include such education exclusively teach the medical model, in which disability is viewed as an impairment to be overcome. Disability advocates contest this approach because it overlooks the social and societal contexts of disability. A collaboration between individuals with disabilities, educators, and physicians to design a medical school curriculum on disabilities could overcome these differences. APPROACH: A curriculum on disabilities for first- and second-year medical students was developed during the 2013-2014 academic year and involved a major collaboration between a medical student, medical educators, disability advocates, and academic disability specialists. The guiding principle of the project was the Disability Rights Movement motto, "Nothing about us without us." Two small-group sessions were created, one for each medical school class. They included discussions about different models of disability, video and in-person narratives of individuals with disabilities, and explorations of concepts central to social perceptions of disability, such as power relationships, naming and stigmatization, and disability as identity. OUTCOMES: According to evaluations conducted after each session, students reported positive feedback about both sessions. NEXT STEPS: Through this curriculum, first- and second-year medical students learned about the obstacles faced by individuals with disabilities and became better equipped to understand and address the concerns, hopes, and societal challenges of their future patients. This inclusive approach may be used to design additional curricula about disabilities for the clinical and postgraduate years.

Comparison of whole blood and peripheral blood mononuclear cell gene expression for evaluation of the perioperative inflammatory response in patients with advanced heart failure.

BACKGROUND: Heart failure (HF) prevalence is increasing in the United States. Mechanical Circulatory Support (MCS) therapy is an option for Advanced HF (AdHF) patients. Perioperatively, multiorgan dysfunction (MOD) is linked to the effects of device implantation, augmented by preexisting HF. Early recognition of MOD allows for better diagnosis, treatment, and risk prediction. Gene expression profiling (GEP) was used to evaluate clinical phenotypes of peripheral blood mononuclear cells (PBMC) transcriptomes obtained from patients' blood samples. Whole blood (WB) samples are clinically more feasible, but their performance in comparison to PBMC samples has not been determined. METHODS: We collected blood samples from 31 HF patients (57±15 years old) undergoing cardiothoracic surgery and 7 healthy age-matched controls, between 2010 and 2011, at a single institution. WB and PBMC samples were collected at a single timepoint postoperatively (median day 8 postoperatively) (25-75% IQR 7-14 days) and subjected to Illumina single color Human BeadChip HT12 v4 whole genome expression array analysis. The Sequential Organ Failure Assessment (SOFA) score was used to characterize the severity of MOD into low (≤ 4 points), intermediate (5-11), and high (≥ 12) risk categories correlating with GEP. RESULTS: Results indicate that the direction of change in GEP of individuals with MOD as compared to controls is similar when determined from PBMC versus WB. The main enriched terms by Gene Ontology (GO) analysis included those involved in the inflammatory response, apoptosis, and other stress response related pathways. The data revealed 35 significant GO categories and 26 pathways overlapping between PBMC and WB. Additionally, class prediction using machine learning tools demonstrated that the subset of significant genes shared by PBMC and WB are sufficient to train as a predictor separating the SOFA groups. CONCLUSION: GEP analysis of WB has the potential to become a clinical tool for immune-monitoring in patients with MOD.