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Renal ischemia-reperfusion injury (IRI) predictably causes acute kidney injury after shock and major cardiovascular procedures in all kidneys procured for transplantation. The earliest events of IRI are triggered by molecules released from injured cells, damage-associated molecular patterns (DAMPs), that bind pattern recognition receptors (PRRs) constitutively expressed on many cells within the kidney. Activation of PRR signaling leads to production of proinflammatory molecules, which incite a cascade of inflammatory events leading to acute kidney injury. Renal tubular epithelial cells (RTECs) are particularly susceptible to ischemic injury, and proximal RTEC injury is pathognomonic of renal IRI. To better understand how injured RTECs contribute to the cycle of deleterious inflammation in the setting of renal IRI, this study asked whether DAMPs released from injured RTECs induced PRR signals in healthy RTECs.Human RTECs were necrosed ex vivo to release intracellular DAMPs and resulting necrotic supernatant used to stimulate healthy RTECs, T lymphocytes, and monocytes.DAMPs released from necrosed RTECs upregulated PRRs known to be associated with renal IRI and activated mitogen-activated protein kinase signaling pathways. Proinflammatory cytokines were upregulated in response to necrotic supernatant, and this upregulation was abrogated by MEK-1 inhibition. The RTEC-derived DAMPs were also potent inducers of T-cell activation/proliferation and monocyte migration.This is the first study to our knowledge to show that endogenous DAMPs released from injured RTECs directly activate PRR signaling in healthy RTECs. These findings provide new insights directed to therapeutics for renal IRI.

Background and objectives Subclinical acute rejection is associated with poor outcomes in kidney transplant recipients. As an alternative to surveillance biopsies, noninvasive screening has been established with a blood gene expression profile. Donor-derived cellfree DNA (cfDNA) has been used to detect rejection in patients with allograft dysfunction but not tested extensively in stable patients. We hypothesized that we could complement noninvasive diagnostic performance for subclinical rejection by combining a donor-derived cfDNA and a gene expression profile assay. Design, setting, participants, & measurements We performed a post hoc analysis of simultaneous blood gene expression profile and donor-derived cfDNA assays in 428 samples paired with surveillance biopsies from 208 subjects enrolled in an observational clinical trial (Clinical Trials in Organ Transplantation-08). Assay results were analyzed as binary variables, and then, their continuous scores were combined using logistic regression. The performance of each assay alone and in combination was compared. Results For diagnosing subclinical rejection, the gene expression profile demonstrated a negative predictive value of 82%, a positive predictive value of 47%, a balanced accuracy of 64%, and an area under the receiver operating curve of 0.75. The donor-derived cfDNA assay showed similar negative predictive value (84%), positive predictive value (56%), balanced accuracy (68%), and area under the receiver operating curve (0.72). When both assays were negative, negative predictive value increased to 88%. When both assays were positive, positive predictive value increased to 81%. Combining assays using multivariable logistic regression, area under the receiver operating curve was 0.81, significantly higher than the gene expression profile (P Conclusions A combination of blood-based biomarkers can improve detection and provide less invasive monitoring for subclinical rejection. In this study, the gene expression profile detected more cellular rejection, whereas donor-derived cfDNA detected more antibody-mediated rejection.

Yttrium-90 (Y-90) radioembolization for the treatment of hepatocellular carcinoma can present safety challenges when transplanting recently treated Y-90 patients. To reduce surgeons' contact with radioactive tissue and remain within occupational dose limits, current guidelines recommend delaying transplants at least 14 days, if possible. We wanted to determine the level of radiation exposure to the transplant surgeon when explanting an irradiated liver before the recommended decay period. Anex-vivoradiation exposure analysis was conducted on the explanted liver of a patient who received Y-90 therapy 46 h prior to orthotopic liver transplant. To estimate exposure to the surgeon's hands, radiation dosimeter rings were placed inside three different surgical glove configurations and exposed to the explanted liver. Estimated radiation doses corrected for Y-90 decay were calculated. Radiation safety gloves performed best, with an average radiation exposure rate of 5.36 mSV h-1in the static hand position, an 83% reduction in exposure over controls with no glove (31.31 mSv h-1). Interestingly, non-radiation safety gloves also demonstrated reduced exposure rates, well below occupational regulation limits. Handling of Y-90 radiated organs within the immediate post-treatment period can be done safely and does not exceed federal occupational dose limits if appropriate gloves and necessary precautions are exercised.

BACKGROUND In transplant medicine, clinical decision making largely relies on histology of biopsy specimens. However, histology suffers from low specificity, sensitivity, and reproducibility, leading to suboptimal stratification of patients. We developed a histology-independent immune framework of kidney graft homeostasis and rejection. METHODS We applied tailored RNA deconvolution for leukocyte enumeration and coregulated gene network analysis to published bulk human kidney transplant RNA transcriptomes as input for unsupervised, high-dimensional phenotype clustering. We used framework-based graft survival analysis to identify a biomarker that was subsequently characterized in independent transplant biopsy specimens. RESULTS We found seven immune phenotypes that confirm known rejection types and uncovered novel signatures. The molecular phenotypes allow for improved graft survival analysis compared with histology, and identify a high-risk group in nonrejecting transplants. Two fibrosis-related phenotypes with distinct immune features emerged with reduced graft survival. We identified lysyl oxidase-like 2 (LOXL2)-expressing peritubular CD68+ macrophages as a framework-derived biomarker of impaired allograft function. These cells precede graft fibrosis, as demonstrated in longitudinal biopsy specimens, and may be clinically useful as a biomarker for early fibrogenesis. CONCLUSIONS This study provides a comprehensive, data-driven atlas of human kidney transplant phenotypes and demonstrates its utility to identify novel clinical biomarkers.

Although interest in the role of donor-specific antibodies (DSAs) in kidney transplant rejection, graft survival, and histopathological outcomes is increasing, their impact on steroid avoidance or minimization in renal transplant populations is poorly understood. Primary outcomes of graft survival, rejection, and histopathological findings were assessed in 188 patients who received transplants between 2012 and 2015 at the Scripps Center for Organ Transplantation, which follows a steroid avoidance protocol. Analyses were performed using data from the United Network for Organ Sharing. Cohorts included kidney transplant recipients with de novo DSAs (dnDSAs; n = 27), preformed DSAs (pfDSAs; n = 15), and no DSAs (nDSAs; n = 146). Median time to dnDSA development (classes I and II) was shorter (102 days) than in previous studies. Rejection of any type was associated with DSAs to class I HLA (P .05) and class II HLA (P .01) but not with graft loss. Although mean fluorescence intensity (MFI) independently showed no association with rejection, an MFI5000 showed a trend toward more antibody-mediated rejection (P .06), though graft loss was not independently associated. Banff chronic allograft nephropathy scores and a modified chronic injury score were increased in the dnDSA cohort at 6 months, but not at 2 years (P .001 and P .08, respectively). Our data suggest that dnDSAs and pfDSAs impact short-term rejection rates but do not negatively impact graft survival or histopathological outcomes at 2 years. Periodic protocol post-transplant DSA monitoring may preemptively identify patients who develop dnDSAs who are at a higher risk for rejection.

Mood disorders (depression, bipolar disorders) are prevalent and disabling. They are also highly co-morbid with other psychiatric disorders. Currently there are no objective measures, such as blood tests, used in clinical practice, and available treatments do not work in everybody. The development of blood tests, as well as matching of patients with existing and new treatments, in a precise, personalized and preventive fashion, would make a significant difference at an individual and societal level. Early pilot studies by us to discover blood biomarkers for mood state were promising [1], and validated by others [2]. Recent work by us has identified blood gene expression biomarkers that track suicidality, a tragic behavioral outcome of mood disorders, using powerful longitudinal within-subject designs, validated them in suicide completers, and tested them in independent cohorts for ability to assess state (suicidal ideation), and ability to predict trait (future hospitalizations for suicidality) [3–6]. These studies showed good reproducibility with subsequent independent genetic studies [7]. More recently, we have conducted such studies also for pain [8], for stress disorders [9], and for memory/Alzheimer’s Disease [10]. We endeavored to use a similar comprehensive approach to identify more definitive biomarkers for mood disorders, that are transdiagnostic, by studying mood in psychiatric disorders patients. First, we used a longitudinal within-subject design and whole-genome gene expression approach to discover biomarkers which track mood state in subjects who had diametric changes in mood state from low to high, from visit to visit, as measured by a simple visual analog scale that we had previously developed (SMS-7). Second, we prioritized these biomarkers using a convergent functional genomics (CFG) approach encompassing in a comprehensive fashion prior published evidence in the field. Third, we validated the biomarkers in an independent cohort of subjects with clinically severe depression (as measured by Hamilton Depression Scale, (HAMD)) and with clinically severe mania (as measured by the Young Mania Rating Scale (YMRS)). Adding the scores from the first three steps into an overall convergent functional evidence (CFE) score, we ended up with 26 top candidate blood gene expression biomarkers that had a CFE score as good as or better than SLC6A4, an empirical finding which we used as a de facto positive control and cutoff. Notably, there was among them an enrichment in genes involved in circadian mechanisms. We further analyzed the biological pathways and networks for the top candidate biomarkers, showing that circadian, neurotrophic, and cell differentiation functions are involved, along with serotonergic and glutamatergic signaling, supporting a view of mood as reflecting energy, activity and growth. Fourth, we tested in independent cohorts of psychiatric patients the ability of each of these 26 top candidate biomarkers to assess state (mood (SMS-7), depression (HAMD), mania (YMRS)), and to predict clinical course (future hospitalizations for depression, future hospitalizations for mania). We conducted our analyses across all patients, as well as personalized by gender and diagnosis, showing increased accuracy with the personalized approach, particularly in women. Again, using SLC6A4 as the cutoff, twelve top biomarkers had the strongest overall evidence for tracking and predicting depression after all four steps: NRG1, DOCK10, GLS, PRPS1, TMEM161B, GLO1, FANCF, HNRNPDL, CD47, OLFM1, SMAD7, and SLC6A4. Of them, six had the strongest overall evidence for tracking and predicting both depression and mania, hence bipolar mood disorders. There were also two biomarkers (RLP3 and SLC6A4) with the strongest overall evidence for mania. These panels of biomarkers have practical implications for distinguishing between depression and bipolar disorder. Next, we evaluated the evidence for our top biomarkers being targets of existing psychiatric drugs, which permits matching patients to medications in a targeted fashion, and the measuring of response to treatment. We also used the biomarker signatures to bioinformatically identify new/repurposed candidate drugs. Top drugs of interest as potential new antidepressants were pindolol, ciprofibrate, pioglitazone and adiphenine, as well as the natural compounds asiaticoside and chlorogenic acid. The last 3 had also been identified by our previous suicidality studies. Finally, we provide an example of how a report to doctors would look for a patient with depression, based on the panel of top biomarkers (12 for depression and bipolar, one for mania), with an objective depression score, risk for future depression, and risk for bipolar switching, as well as personalized lists of targeted prioritized existing psychiatric medications and new potential medications. Overall, our studies provide objective assessments, targeted therapeutics, and monitoring of response to treatment, that enable precision medicine for mood disorders.

Transplant candidates can be listed at multiple transplant centers to increase the probability of receiving an organ. We evaluated the association between multilisting (ML) status and access to a deceased donor kidney transplant (DDKT) to determine if ML provides a long-term advantage regarding wait-list mortality and recipient outcomes.Candidates between January 2010 and October 2017 were identified as either singly or multiply listed using Organ Procurement and Transplantation Network data and cohorts before and after implementation of the Kidney Allocation System (KAS). Cross-sectional logistic regression was used to assess relationships between candidate factors and ML prevalence (5.4%).Factors associated with ML pre-KAS included having blood type B (reference, type O; odds ratio [OR], 1.20; P .001), having private insurance (OR, 1.5; P .001), wait time (OR, 1.28; P .001), and increasing calculated panel-reactive antibody (cPRA) (reference, cPRA 0-100; OR for cPRA 80-98, 2.83; OR for cPRA 99, 3.47; OR for cPRA 100, 5.18; P .001). Transplant rates were double for multilisted vs singly listed recipients (adjusted hazard ratio [aHR], 2.16; P .001). Extra-donor service area ML candidates received transplants 2.5 years quicker than single-listing (SL) candidates, conferring a 42% wait-list advantage. Recipient death (aHR, 0.94; P = .122) and graft failure (aHR, 0.91; P = .006) rates were also lower for ML recipients.In the KAS era, ML continues to increase the likelihood of receiving a DDKT and lower the incidence of wait-list mortality, and it confers a survival advantages over SL.

Long-term survival of transplant recipients is significantly impacted by malignancy. We aimed to determine whether calcineurin inhibitor (CNI)-treated recipients converted to and weaned off molecular target of rapamycin inhibitor (mTOR-I) therapy have favorable changes in their molecular profiles in regard to malignancy risk. We performed gene expression profiling from liver biopsy and blood (PBMC) specimens followed by network analysis of key dysregulated genes, associated diseases and disorders, molecular and cellular functions using IPA software. Twenty non-immune, non-viremic patients were included, and 8 of them achieved tolerance. Two comparisons were performed: (1) tolerance time point vs tacrolimus monotherapy and (2) tolerance time point vs sirolimus monotherapy. Upon achieving tolerance, IPA predicted significant activation of DNA damage response (p = 5.40e-04) and inhibition of DNA replication (p = 7.56e-03). Conversion from sirolimus to tolerance showed decrease in HCC (p = 1.30e-02), hepatic steatosis (p = 5.60e-02) and liver fibrosis (p = 2.91e-02) associated genes. In conclusion, this longitudinal study of patients eventually achieving tolerance reveals an evolving molecular profile associated with decreased cancer risk and improved hepatic steatosis and liver fibrosis. This provides a biological rationale for attempting conversion to mTOR-I therapy and tolerance following liver transplantation particularly in patients at higher risk of cancer incidence and progression post-transplant.

Early elimination of tacrolimus in favor of everolimus can improve renal function in liver transplant recipients. However, as this approach increases the risk of acute rejection, it may benefit from predictive biomarkers guiding weaning. We enrolled 20 recipients on stable tacrolimus + everolimus to undergo tacrolimus withdrawal early post-liver transplant. Blood samples were collected at month 3 (withdrawal initiation), 4 (withdrawal completion), 4.5 and 6 (both everolimus alone). 15 patients did not reject and 5 had mild rejection responding to tacrolimus resumption. Before tacrolimus withdrawal, eventual rejecters had higher percentages of CD56+ NK cells and CD19+CD27+CD24+ memory B cells, and lower levels of T cells expressing the exhaustion marker PD-1. Over time, memory B cells, Ki-67+CD3+ (proliferating) cells and CD4+CD127-CD25HIGH FOXP3+ Tregs increased in rejecters. Tregs also increased in non-rejecters over time. The number of differentially expressed genes progressively increased in rejecters, particularly in mTOR, Eukaryotic Initiation Factor 2, and Neuroinflammation signaling pathways. There was no difference in anti-HLA antibodies between the groups. In summary, blood mononuclear cell and gene expression may predict successful vs. failed early tacrolimus withdrawal in liver transplant recipients. While needing validation, these preliminary findings highlight the potential for cellular and molecular biomarkers to guide decision-making during tacrolimus weaning.

The human microbiome encompasses a variety of microorganisms that change dynamically and are in close contact with the body. The microbiome influences health and homeostasis, as well as the immune system, and any significant change in this equilibrium (dysbiosis) triggers both acute and chronic health conditions. Microbiome research has surged, in part, due to advanced sequencing technologies enabling rapid, accurate, and cost-effective identification of the microbiome. A major prerequisite for stool sample collection to study the gut microbiome in longitudinal prospective studies requires standardized protocols that can be easily replicated. However, there are still significant bottlenecks to stool specimen collection that contribute to low patient retention rates in microbiome studies. These barriers are further exacerbated in solid organ transplant recipients where diarrhea is estimated to occur in up to half the patient population. We sought to test two relatively easy sample collection methods (fecal swab and wipes) and compare them to the more cumbersome "gold" standard collection method (scoop) using two different sequencing technologies (16S ribosomal RNA sequencing and shotgun metagenomics). Our comparison of the collection methods shows that both the swabs and the wipes are comparable to the scoop method in terms of bacterial abundance and diversity. The swabs, however, were closer in representation to the scoop and were easier to collect and process compared to the wipes. Potential contamination of the swab and the wipe samples by abundant skin commensals was low in our analysis. Comparison of the two sequencing technologies showed that they were complementary, and that 16S sequencing provided enough coverage to detect and differentiate between bacterial species identified in the collected samples. Our pilot study demonstrates that alternative collection methods for stool sampling are a viable option in clinical applications, such as organ transplant studies. The use of these methods may result in better patient retention recruitment rates in serial microbiome studies.

Noninvasive biomarker profiles of acute rejection (AR) could affect the management of liver transplant (LT) recipients. Peripheral blood was collected following LT for discovery (Northwestern University [NU]) and validation (National Institute of Allergy and Infectious Diseases Clinical Trials in Organ Transplantation [CTOT]‐14 study). Blood gene profiling was paired with biopsies showing AR or ADNR (acute dysfunction no rejection) as well as stable graft function samples (Transplant eXcellent—TX). CTOT‐14 subjects had serial collections prior to AR, ADNR, TX, and after AR treatment. NU cohort gene expression (46 AR, 45 TX) was analyzed using random forest models to generate a classifier training set (36 gene probe) distinguishing AR vs TX (area under the curve 0.92). The algorithm and threshold were locked and tested on the CTOT‐14 validation cohort (14 AR, 50 TX), yielding an accuracy of 0.77, sensitivity 0.57, specificity 0.82, positive predictive value (PPV) 0.47, and negative predictive value (NPV) 0.87 for AR vs TX. The probability score line slopes were positive preceding AR, and negative preceding TX and non‐AR (TX + ADNR) (P ≤ .001) and following AR treatment. In conclusion, we have developed a blood biomarker diagnostic for AR that can be detected prior to AR‐associated graft injury as well a normal graft function (non‐AR). Further studies are needed to evaluate its utility in precision‐guided immunosuppression optimization following LT., This study reports on a novel peripheral blood gene signature intended to distinguish acute rejection from other causes and healthy graft function in liver transplant recipients and provide early detection to inform and enhance immunosuppression management.

Short-term memory dysfunction is a key early feature of Alzheimer’s disease (AD). Psychiatric patients may be at higher risk for memory dysfunction and subsequent AD due to the negative effects of stress and depression on the brain. We carried out longitudinal within-subject studies in male and female psychiatric patients to discover blood gene expression biomarkers that track short term memory as measured by the retention measure in the Hopkins Verbal Learning Test. These biomarkers were subsequently prioritized with a convergent functional genomics approach using previous evidence in the field implicating them in AD. The top candidate biomarkers were then tested in an independent cohort for ability to predict state short-term memory, and trait future positive neuropsychological testing for cognitive impairment. The best overall evidence was for a series of new, as well as some previously known genes, which are now newly shown to have functional evidence in humans as blood biomarkers: RAB7A, NPC2, TGFB1, GAP43, ARSB, PER1, GUSB, and MAPT. Additional top blood biomarkers include GSK3B, PTGS2, APOE, BACE1, PSEN1, and TREM2, well known genes implicated in AD by previous brain and genetic studies, in humans and animal models, which serve as reassuring de facto positive controls for our whole-genome gene expression discovery approach. Biological pathway analyses implicate LXR/RXR activation, neuroinflammation, atherosclerosis signaling, and amyloid processing. Co-directionality of expression data provide new mechanistic insights that are consistent with a compensatory/scarring scenario for brain pathological changes. A majority of top biomarkers also have evidence for involvement in other psychiatric disorders, particularly stress, providing a molecular basis for clinical co-morbidity and for stress as an early precipitant/risk factor. Some of them are modulated by existing drugs, such as antidepressants, lithium and omega-3 fatty acids. Other drug and nutraceutical leads were identified through bioinformatic drug repurposing analyses (such as pioglitazone, levonorgestrel, salsolidine, ginkgolide A, and icariin). Our work contributes to the overall pathophysiological understanding of memory disorders and AD. It also opens new avenues for precision medicine- diagnostics (assement of risk) as well as early treatment (pharmacogenomically informed, personalized, and preventive).

Background TruGraf v1 is a well-validated DNA microarray-based test that analyzes blood gene expression profiles as an indicator of immune status in kidney transplant recipients with stable renal function. Methods In this study, investigators assessed clinical utility of the TruGraf test in patient management. In a retrospective study, simultaneous blood tests and clinical assessments were performed in 192 patients at 7 transplant centers, and in a prospective observational study they were performed in 45 subjects at 5 transplant centers. Results When queried regarding whether or not the TruGraf test result impacted their decision regarding patient management, in 168 of 192 (87.5%) cases the investigator responded affirmatively. The prospective study indicated that TruGraf results supported physicians' decisions on patient management 87% (39/45) of the time, and in 93% of cases physicians indicated that they would use serial TruGraf testing in future patient management. A total of 21 of 39 (54%) reported results confirmed their decision that no intervention was needed, and 17 of 39 (44%) reported that results specifically informed them that a decision not to perform a surveillance biopsy was correct. Conclusions TruGraf is the first and only noninvasive test to be evaluated for clinical utility in determining rejection status of patients with stable renal function and shows promise of providing support for clinical decisions to avoid unnecessary surveillance biopsies with a high degree of confidence. TruGraf is an invaluable addition to the transplant physician's tool kit for managing patient health by avoiding painful and invasive biopsies, reducing health care costs, and enabling frequent assessment of patients with stable renal function to confirm immune quiescence.

TruGraf v1 is a laboratory-developed DNA microarray-based gene expression blood test to enable proactive noninvasive serial assessment of kidney transplant recipients with stable renal function. It has been previously validated in patients identified as Transplant eXcellence (TX: stable serum creatinine, normal biopsy results, indicative of immune quiescence), and not-TX (renal dysfunction and/or rejection on biopsy results). TruGraf v1 is intended for use in subjects with stable renal function to measure the immune status as an alternative to invasive, expensive, and risky surveillance biopsies. Materials and Methods In this study, simultaneous blood tests and clinical assessments were performed in 192 patients from 7 transplant centers to evaluate TruGraf v1. The molecular testing laboratory was blinded to renal function and biopsy results. Results Overall, TruGraf v1 accuracy (concordance between TruGraf v1 result and clinical and/or histologic assessment) was 74% (142/192), and a result of TX was accurate in 116 of 125 (93%). The negative predictive value for TruGraf v1 was 90%, with a sensitivity 74% and specificity of 73%. Results did not significantly differ in patients with a biopsy-confirmed diagnosis vs those without a biopsy. Conclusions TruGraf v1 can potentially support a clinical decision enabling unnecessary surveillance biopsies with high confidence, making it an invaluable addition to the transplant physician's tool kit for managing patients. TruGraf v1 testing can potentially avoid painful and risky invasive biopsies, reduce health care costs, and enable frequent assessment of patients with stable renal function to confirm the presence of immune quiescence in the peripheral blood.

Delayed graft function (DGF) after kidney transplantation is associated with higher rates of acute rejection and poor graft survival and outcomes. Current DGF definitions based on posttransplant need for dialysis are not standardized and there are no objective methodologies for quantifying DGF severity.Using Organ Procurement and Transplantation Network data, we examined DGF, and used recipient serum creatinine at discharge as a correlate of renal function and DGF severity (mild:2.5 mg/dL; severe: ≥2.5 mg/dL). The associations between donor and recipient factors and DGF severity were quantified using logistic regression. We also examined the associations between DGF severity and long-term recipient outcomes, adjusting for potential confounders.A predictive model using donor and recipient factors had a reasonably good ability to discriminate mild (low creatinine) versus severe (high creatinine) DGF (c-statistic of 0.70). In Cox regression, DGF and creatinine at discharge were both independently associated with long-term outcomes, yet their effects differed depending on the outcome (graft function, death-censored graft function, recipient mortality). Our findings suggest that having DGF, but with relatively good renal function (creatinine2.5) at discharge, may be less deleterious on graft and recipient survival compared with severe, prolonged DGF, which was associated with a decreased median graft survival of ~2.6 y compared with no DGF with low creatinine at discharge.Our novel DGF severity stratification identified unique factors associated with DGF severity, along with DGF's association with long-term graft and patient survival. The adverse cost and outcome implications of severe DGF warrant additional investigation to improve kidney transplantation practice.

Noninvasive biomarkers distinguishing early immune activation before acute rejection (AR) could more objectively inform immunosuppression management in liver transplant recipients (LTRs). We previously reported a genomic profile distinguishing LTR with AR versus stable graft function. This current study includes key phenotypes with other causes of graft dysfunction and uses a novel random forest approach to augment the specificity of predicting and diagnosing AR.Gene expression results in LTRs with AR versus non-AR (combination of other causes of graft dysfunction and normal function) were analyzed from single and multicenter cohorts. A 70:30 approach (61 ARs; 162 non-ARs) was used for training and testing sets. Microarray data were normalized using a LT-specific vector.Random forest modeling on the training set generated a 59-probe classifier distinguishing AR versus non-AR (area under the curve 0.83; accuracy 0.78, sensitivity 0.70, specificity 0.81, positive predictive value 0.54, negative predictive value [NPV] 0.89; F-score 0.61). Using a locked threshold, the classifier performed well on the testing set (accuracy 0.72, sensitivity 0.67, specificity 0.73, positive predictive value 0.48, NPV 0.86; F-score 0.56). Probability scores increased in samples preceding AR versus non-AR, when liver function tests were normal, and decreased following AR treatment (P 0.001). Ingenuity pathway analysis of the genes revealed a high percentage related to immune responses and liver injury.We have developed a blood-based biologically relevant biomarker that can be detected before AR-associated graft injury distinct from LTR never developing AR. Given its high NPV ("rule out AR"), the biomarker has the potential to inform precision-guided immunosuppression minimization in LTRs.

BackgroundSuccessful containment strategies for SARS-CoV-2, the causative virus of the COVID-19 pandemic, have involved widespread population testing that identifies infections early and enables rapid contact tracing. In this study, we developed a rapid and inexpensive RT- qPCR testing pipeline for population-level SARS-CoV-2 detection, and used this pipeline to establish a clinical laboratory dedicated to COVID-19 testing at the University of California San Diego (UCSD) with a processing capacity of 6,000 samples per day and next-day result turnaround times.Methods and findingsUsing this pipeline, we screened 6,786 healthcare workers and first responders, and 21,220 students, faculty, and staff from UCSD. Additionally, we screened 6,031 preschool-grade 12 students and staff from public and private schools across San Diego County that remained fully or partially open for in-person teaching during the pandemic. Between April 17, 2020 and February 5, 2021, participants provided 161,582 nasal swabs that were tested for the presence of SARS-CoV-2. Overall, 752 positive tests were obtained, yielding a test positivity rate of 0.47%. While the presence of symptoms was significantly correlated with higher viral load, most of the COVID-19 positive participants who participated in symptom surveys were asymptomatic at the time of testing. The positivity rate among preschool-grade 12 schools that remained open for in-person teaching was similar to the positivity rate at UCSD and lower than that of San Diego County, with the children in private schools being less likely to test positive than the adults at these schools.ConclusionsMost schools across the United States have been closed for in-person learning for much of the 2020-2021 school year, and their safe reopening is a national priority. However, as there are no vaccines against SARS-CoV-2 currently available to the majority of school-aged children, the traditional strategies of mandatory masking, physical distancing, and repeated viral testing of students and staff remain key components of risk mitigation in these settings. The data presented here suggest that the safety measures and repeated testing actions taken by participating healthcare and educational facilities were effective in preventing outbreaks, and that a similar combination of risk-mitigation strategies and repeated testing may be successfully adopted by other healthcare and educational systems.

Purpose of review Organ transplantation research has led to the discovery of several interesting individual mechanistic pathways, molecules and potential drug targets but there are still no comprehensive studies that have addressed how these varied mechanisms work in unison to regulate the posttransplant immune response that drives kidney rejection and dysfunction. Recent findings Systems biology is a rapidly expanding field that aims to integrate existing knowledge of molecular concepts and large-scale genomic and clinical datasets into networks that can be used in cutting edge computational models to define disease mechanisms in a holistic manner. Systems biology approaches have brought a paradigm shift from a reductionist view of biology to a wider agnostic assessment of disease from several lines of evidence. Although the complex nature of the posttransplant immune response makes it difficult to pinpoint mechanisms, systems biology is enabling discovery of unknown biological interactions using the cumulative power of genomic data sets, clinical data and endpoints, and improved computational methods for the systematic deconvolution of this response. Summary An integrative systems biology approach that leverages genomic data from varied technologies, such as DNA sequencing, copy number variation, RNA sequencing, and methylation profiles along with long-term clinical follow-up data has the potential to define a framework that can be mined to provide novel insights for developing therapeutic interventions in organ transplantation.

Immunoglobulin A (IgA) Nephropathy (IgAN) is one of the most common recurrent glomerulopathies associated with graft loss and patient survival after kidney transplantation (KT). Steroid withdrawal regimens in KT have been associated with improvements of patient outcomes. The Scripps Center for Organ Transplantation (SCOT) utilizes a rapid low-dose steroid withdrawal immunosuppression (IS) protocol for KT maintenance. We assessed the impact of our protocol on IgAN recurrence over a 10-year period to reassess our steroid withdrawal and IS protocols to see if outcomes diverged from available UNOS data. Therefore, we used IS and induction matched retrospective data from UNOS to investigate patient and graft survival for IgAN. SCOT recurrence rates for IgAN was 13.6%. Overall outcomes of graft failure and recipient death did not differ between SCOT patients and data obtained from steroid free transplants from UNOS. Our results differ from earlier studies showing IgAN was associated with a higher risk of graft loss, perhaps due to selection of a SCOT IS matched dataset. Based on our analysis, we believe that it is safe to continue the steroid avoidance protocols at SCOT and think that it may be beneficial, given the adverse effects and toxicities associated with steroid use.

Highlights • San Diego healthcare worker seroconversion was, Coronavirus Disease 2019 infections among healthcare workers were widely reported in China and Europe as the pandemic expanded to the United States. In order to examine the infection rate among these essential workers, we combined results of SARS-CoV-2 serology testing offered free to healthcare workers at two large San Diego health systems when the antibody assays first became available.

We endeavored to identify objective blood biomarkers for pain, a subjective sensation with a biological basis, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We studied psychiatric patients, a high risk group for co-morbid pain disorders and increased perception of pain. For discovery, we used a powerful within-subject longitudinal design. We were successful in identifying blood gene expression biomarkers that were predictive of pain state, and of future emergency department (ED) visits for pain, more so when personalized by gender and diagnosis. MFAP3, which had no prior evidence in the literature for involvement in pain, had the most robust empirical evidence from our discovery and validation steps, and was a strong predictor for pain in the independent cohorts, particularly in females and males with PTSD. Other biomarkers with best overall convergent functional evidence for involvement in pain were GNG7, CNTN1, LY9, CCDC144B, and GBP1. Some of the individual biomarkers identified are targets of existing drugs. Moreover, the biomarker gene expression signatures were used for bioinformatic drug repurposing analyses, yielding leads for possible new drug candidates such as SC-560 (an NSAID), and amoxapine (an antidepressant), as well as natural compounds such as pyridoxine (vitamin B6), cyanocobalamin (vitamin B12), and apigenin (a plant flavonoid). Our work may help mitigate the diagnostic and treatment dilemmas that have contributed to the current opioid epidemic.

Noninvasive biomarkers are needed to monitor stable patients after kidney transplant (KT), because subclinical acute rejection (subAR), currently detectable only with surveillance biopsies, can lead to chronic rejection and graft loss. We conducted a multicenter study to develop a blood‐based molecular biomarker for subAR using peripheral blood paired with surveillance biopsies and strict clinical phenotyping algorithms for discovery and validation. At a predefined threshold, 72% to 75% of KT recipients achieved a negative biomarker test correlating with the absence of subAR (negative predictive value: 78%‐88%), while a positive test was obtained in 25% to 28% correlating with the presence of subAR (positive predictive value: 47%‐61%). The clinical phenotype and biomarker independently and statistically correlated with a composite clinical endpoint (renal function, biopsy‐proved acute rejection, ≥grade 2 interstitial fibrosis, and tubular atrophy), as well as with de novo donor-specific antibodies. We also found that

Kidney transplant recipients given donor hematopoietic stem cells from their HLA-identical living related donors have now been followed between 5 and 9 ½ years post-operatively. Recipients who were designated as tolerant (Tol) have remained so since the last report when the 5 year (biopsy associated) milestone was reached. There has been 1 mortality of a Tol patient, unrelated to the study protocol, while 5 (of 15) have remained Tol between 7 & 8 ½ years post-operatively. There has been continuing elevated T-regulatory (CD4(+)CD25(High)CD127(−)FOXP3(+)) cells in PBMC previously reported on. Ten year renal transplant biopsies are tentatively planned.

We performed orthogonal technology comparisons of concurrent peripheral blood and biopsy tissue samples from 69 kidney transplant recipients who underwent comprehensive algorithm-driven clinical phenotyping. The sample cohort included patients with normal protocol biopsies and stable transplant (sTx) function (n = 25), subclinical acute rejection (subAR, n = 23), and clinical acute rejection (cAR, n = 21). Comparisons between microarray and RNA sequencing (RNA-seq) signatures were performed and demonstrated a strong correlation between the blood and tissue compartments for both technology platforms. A number of shared differentially expressed genes and pathways between subAR and cAR in both platforms strongly suggest that these two clinical phenotypes form a continuum of alloimmune activation. SubAR is associated with fewer or less expressed genes than cAR in blood, whereas in biopsy tissues, this clinical phenotype demonstrates a more robust molecular signature for both platforms. The discovery work done in this study confirms a clear ability to detect gene expression profiles for sTx, subAR, and cAR in both blood and biopsy tissue, yielding equivalent predictive performance that is agnostic to both technology and platform. Our data also provide strong biological insights into the molecular mechanisms underlying these signatures, underscoring their logistical potential as molecular diagnostics to improve clinical outcomes following kidney transplantation.

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a 'liquid biopsy' approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator.

Background and aims As conversion from calcineurin inhibitor to sirolimus (SRL), a mechanistic target of rapamycin inhibitor (mTOR-I), has been shown to enhance immunoregulatory profiles in liver transplant (LT) recipients (LTRs), mTOR-I therapy might allow for increased success of immunosuppression (IS) withdrawal. Our aim was to determine if operational tolerance could be observed in LTRs withdrawn from SRL and if blood/graft tolerance biomarkers were predictive of successful withdrawal. Approach and results We performed a prospective trial of SRL monotherapy withdrawal in nonimmune, nonviremic LTRs > 3 years post-LT. SRL was weaned over ~6 months, and biopsies were performed 12 months postweaning or at concern for acute rejection. Twenty-one LTRs consented; 6 were excluded due to subclinical acute rejection on baseline biopsy or other reasons, and 15 underwent weaning (age 61.3 ± 8.8 years; LT to SRL weaning 6.7 ± 3 years). Eight (53%) achieved operational tolerance (TOL). Of the 7 who were nontolerant (non-TOL), 6 had mild acute rejection on biopsy near the end of weaning or at study end; 1 was removed from the trial due to liver cancer recurrence. At baseline preweaning, there were statistically increased blood tolerogenic dendritic cells and cell phenotypes correlating with chronic antigen presentation in the TOL versus non-TOL groups. A previously identified biopsy gene signature accurately predicted TOL versus non-TOL in 12/14 LTRs before weaning. At study end, biopsy staining revealed statistically significant increases in antigen-presenting cell:leukocyte pairings, FOXP3+ /CD4+ T cells, Tbet+ /CD8+ T cells, and lobular dendritic cells in the non-TOL group. Conclusions This study evaluated IS withdrawal directly from mTOR-I therapy in LTRs and achieved > 50% operational tolerance. Preweaning gene expression and peripheral blood mononuclear cell profiling may be useful as predictors of successful mTOR-I therapy withdrawal. NCT02062944.

Background Focal segmental glomerulosclerosis (FSGS) is a common recurrent glomerulopathy associated with graft loss and patient survival after kidney transplantation (KT). However, its natural history, clinical predictors, and treatment response are still poorly understood. Steroid withdrawal regimens in KT have been associated with improvements in cardiovascular risk and patient outcomes. The Scripps Center for Organ Transplantation (SCOT) uses a rapid low-dose steroid withdrawal immunosuppression (IS) protocol for KT maintenance. Methods We assessed the impact of our protocol on FSGS disease recurrence over a 10-y period to reassess our steroid and IS protocols and to evaluate if our patient outcomes diverge from published data. We compared 4 groups: steroids always, steroid free, steroid switch on, and steroid weaned off. We used IS and induction-matched retrospective data from United Network for Organ Sharing (UNOS) to investigate patient and graft survival for FSGS at SCOT. Results Our analysis results differ from earlier studies showing that FSGS was associated with a higher risk of graft loss, perhaps because of selection of a UNOS data set filtered to match the SCOT IS protocol for making direct comparisons. Overall outcomes of graft failure and recipient death did not differ between SCOT patients and steroid-free transplant patient data from the UNOS data for FSGS. SCOT recurrence rate for FSGS was 7.5%, which was lower than in most published single-center studies. Conclusions Based on our results, we believe that it is safe to continue the steroid avoidance protocols at SCOT and the steroid-free protocol may not be detrimental when the adverse effects and toxicities associated with steroid use are considered.

BACKGROUND: Early diagnosis of familial transthyretin (TTR) amyloid diseases remains challenging because of variable disease penetrance. Currently, patients must have an amyloid positive tissue biopsy to be eligible for disease-modifying therapies. Endomyocardial biopsies are typically amyloid positive when cardiomyopathy is suspected, but this disease manifestation is generally diagnosed late. Early diagnosis is often difficult because patients exhibit apparent symptoms of polyneuropathy, but have a negative amyloid biopsy. Thus, there is a pressing need for an additional early diagnostic strategy for TTR-aggregation-associated polyneuropathy and cardiomyopathy. METHODS AND FINDINGS: Global peripheral blood cell mRNA expression profiles from 263 tafamidis-treated and untreated V30M Familiar Amyloid Neuropathy patients, asymptomatic V30M carriers, and healthy, age- and sex-matched controls without TTR mutations were used to differentiate symptomatic from asymptomatic patients. We demonstrate that blood cell gene expression patterns reveal sex-independent, as well as male- and female-specific inflammatory signatures in symptomatic FAP patients, but not in asymptomatic carriers. These signatures differentiated symptomatic patients from asymptomatic V30M carriers with >80% accuracy. There was a global downregulation of the eIF2 pathway and its associated genes in all symptomatic FAP patients. We also demonstrated that the molecular scores based on these signatures significantly trended toward normalized values in an independent cohort of 46 FAP patients after only 3 months of tafamidis treatment. CONCLUSIONS: This study identifies novel molecular signatures that differentiate symptomatic FAP patients from asymptomatic V30M carriers as well as affected males and females. We envision using this approach, initially in parallel with amyloid biopsies, to identify individuals who are asymptomatic gene carriers that may convert to FAP patients. Upon further validation, peripheral blood cell mRNA expression profiling could become an independent early diagnostic. This quantitative gene expression signature for symptomatic FAP could also become a biomarker to demonstrate significant disease-modifying effects of drugs and drug candidates. For example, when new disease modifiers are being evaluated in a FAP clinical trial, such surrogate biomarkers have the potential to provide an objective, quantitative and mechanistic molecular diagnostic of disease response to therapy. We acknowledge the following sources of research funding: NIH U19 A1063603 (DRS, SMK), NIH DK46335 (JWK) and NIH R01AG19259 (JNB) info:eu-repo/semantics/publishedVersion

Interstitial fibrosis and tubular atrophy (IFTA) is found in approximately 25% of 1-year biopsies posttransplant. It is known that IFTA correlates with decreased graft survival when histological evidence of inflammation is present. Identifying the mechanistic etiology of IFTA is important to understanding why long-term graft survival has not changed as expected despite improved immunosuppression and dramatically reduced rates of clinical acute rejection (AR) (Services UDoHaH. http://www.ustransplant.org/annual_reports/current/509a_ki.htm). Gene expression profiles of 234 graft biopsy samples were obtained with matching clinical and outcome data. Eighty-one IFTA biopsies were divided into subphenotypes by degree of histological inflammation: IFTA with AR, IFTA with inflammation, and IFTA without inflammation. Samples with AR (n = 54) and normally functioning transplants (TX; n = 99) were used in comparisons. A novel analysis using gene coexpression networks revealed that all IFTA phenotypes were strongly enriched for dysregulated gene pathways and these were shared with the biopsy profiles of AR, including IFTA samples without histological evidence of inflammation. Thus, by molecular profiling we demonstrate that most IFTA samples have ongoing immune-mediated injury or chronic rejection that is more sensitively detected by gene expression profiling. These molecular biopsy profiles correlated with future graft loss in IFTA samples without inflammation.

Reactivation of latent human cytomegalovirus is a significant infectious complication of organ transplantation and current therapies target viral replication once reactivation of latent virus has already occurred. The specific molecular pathways that activate viral gene expression in response to transplantation are not well understood. Our studies aim to identify these factors, with the goal of developing novel therapies that prevent transcriptional reactivation in transplant recipients. Murine cytomegalovirus (MCMV) is a valuable model for studying latency and reactivation of CMV in vivo. We previously demonstrated that transplantation of MCMV-latently infected kidneys into allogeneic recipients induces reactivation of immediate early (IE) gene expression and epigenetic reprogramming of the major immediate early promoter (MIEP) within 48 h. We hypothesize that these events are mediated by activation of signalling pathways that lead to binding of transcription factors to the MIEP, including AP-1 and NF-κB. Here we show that transplantation induces rapid activation of several members of the AP-1 and NF-κB transcription factor family and we demonstrate that canonical NF-κB (p65/p50), the junD component of AP-1, and nucleosome remodelling complexes are recruited to the MIEP following transplantation. Proteomic analysis of recipient plasma and transcriptome analysis of kidney RNA identified five extracellular ligands, including TNF, IL-1β, IL-18, CD40L and IL-6, and three intracellular signalling pathways associated with reactivation of IE gene expression. Identification of the factors that mediate activation of these signalling pathways may eventually lead to new therapies to prevent reactivation of CMV and its sequelae.

Long-term renal allograft rejection is the most common outcome in kidney transplantation. Continuing the crusade to extend allograft function after the first year post-transplantation, we attempted to associate genetic factors that might contribute to long-term allograft outcomes by sequencing the exomes of patients diagnosed with chronic allograft nephropathy/interstitial fibrosis and tubular atrophy. A variety of association analyses were employed, but these analyses failed to identify statistically significant associations. The study was underpowered to detect the association of rare genomic variants with small effect sizes. However, it confirmed previous reports of the absence of large effects from common variants. We have made both the study data and analysis workflow available for public use, and we hope that these resources will help to power future meta-analyses that may detect smaller effects.

DNA polymerase θ (POLQ) plays an important role in alternative nonhomologous end joining or microhomology-mediated end joining (alt-NHEJ/MMEJ). Here, we show that POLQ is not only required for MMEJ to repair DNA double-strand breaks (DSBs) generated by endonucleases such as I-SceI or Cas9, but is also needed for repair of DSBs derived from DNA nicks generated by Cas9 nickase. Consistently, we found that POLQ deficiency leads to sensitivity to topoisomerase inhibitors that cause DNA single-strand break (SSB) accumulation at replication forks and to ATR inhibitors that induce replication fork collapse. These studies support the function of POLQ in coping with replication stress and repairing DSBs upon fork collapse. POLQ overexpression is present in many cancer types and is associated with poor prognosis, including breast cancer regardless of BRCA1 status. We provide proof-of-concept evidence to support a novel cancer treatment strategy that combines POLQ inhibition with administration of topoisomerase or ATR inhibitors, which induces replication stress and fork collapse. Given the prevalence of POLQ overexpression in tumors, such strategy may have a significant impact on developing targeted cancer treatment.

The biological fingerprint of environmental adversity may be key to understanding health and disease, as it encompasses the damage induced as well as the compensatory reactions of the organism. Metabolic and hormonal changes may be an informative but incomplete window into the underlying biology. We endeavored to identify objective blood gene expression biomarkers for psychological stress, a subjective sensation with biological roots. To quantify the stress perception at a particular moment in time, we used a simple visual analog scale for life stress in psychiatric patients, a high-risk group. Then, using a stepwise discovery, prioritization, validation, and testing in independent cohort design, we were successful in identifying gene expression biomarkers that were predictive of high-stress states and of future psychiatric hospitalizations related to stress, more so when personalized by gender and diagnosis. One of the top biomarkers that survived discovery, prioritization, validation, and testing was FKBP5, a well-known gene involved in stress response, which serves as a de facto reassuring positive control. We also compared our biomarker findings with telomere length (TL), another well-established biological marker of psychological stress and show that newly identified predictive biomarkers such as NUB1, APOL3, MAD1L1, or NKTR are comparable or better state or trait predictors of stress than TL or FKBP5. Over half of the top predictive biomarkers for stress also had prior evidence of involvement in suicide, and the majority of them had evidence in other psychiatric disorders, providing a molecular underpinning for the effects of stress in those disorders. Some of the biomarkers are targets of existing drugs, of potential utility in patient stratification, and pharmacogenomics approaches. Based on our studies and analyses, the biomarkers with the best overall convergent functional evidence (CFE) for involvement in stress were FKBP5, DDX6, B2M, LAIR1, RTN4, and NUB1. Moreover, the biomarker gene expression signatures yielded leads for possible new drug candidates and natural compounds upon bioinformatics drug repurposing analyses, such as calcium folinate and betulin. Our work may lead to improved diagnosis and treatment for stress disorders such as PTSD, that result in decreased quality of life and adverse outcomes, including addictions, violence, and suicide.

Worldwide, one person dies every 40 seconds by suicide, a potentially preventable tragedy. A limiting step in our ability to intervene is the lack of objective, reliable predictors. We have previously provided proof of principle for the use of blood gene expression biomarkers to predict future hospitalizations due to suicidality, in male bipolar disorder participants. We now generalize the discovery, prioritization, validation, and testing of such markers across major psychiatric disorders (bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) in male participants, to understand commonalities and differences. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation and high suicidal ideation states (n=37 participants out of a cohort of 217 psychiatric participants followed longitudinally). We then used a convergent functional genomics (CFG) approach with existing prior evidence in the field to prioritize the candidate biomarkers identified in the discovery step. Next, we validated the top biomarkers from the prioritization step for relevance to suicidal behavior, in a demographically matched cohort of suicide completers from the coroner's office (n=26). The biomarkers for suicidal ideation only are enriched for genes involved in neuronal connectivity and schizophrenia, the biomarkers also validated for suicidal behavior are enriched for genes involved in neuronal activity and mood. The 76 biomarkers that survived Bonferroni correction after validation for suicidal behavior map to biological pathways involved in immune and inflammatory response, mTOR signaling and growth factor regulation. mTOR signaling is necessary for the effects of the rapid-acting antidepressant agent ketamine, providing a novel biological rationale for its possible use in treating acute suicidality. Similarly, MAOB, a target of antidepressant inhibitors, was one of the increased biomarkers for suicidality. We also identified other potential therapeutic targets or biomarkers for drugs known to mitigate suicidality, such as omega-3 fatty acids, lithium and clozapine. Overall, 14% of the top candidate biomarkers also had evidence for involvement in psychological stress response, and 19% for involvement in programmed cell death/cellular suicide (apoptosis). It may be that in the face of adversity (stress), death mechanisms are turned on at a cellular (apoptosis) and organismal level. Finally, we tested the top increased and decreased biomarkers from the discovery for suicidal ideation (CADM1, CLIP4, DTNA, KIF2C), prioritization with CFG for prior evidence (SAT1, SKA2, SLC4A4), and validation for behavior in suicide completers (IL6, MBP, JUN, KLHDC3) steps in a completely independent test cohort of psychiatric participants for prediction of suicidal ideation (n=108), and in a future follow-up cohort of psychiatric participants (n=157) for prediction of psychiatric hospitalizations due to suicidality. The best individual biomarker across psychiatric diagnoses for predicting suicidal ideation was SLC4A4, with a receiver operating characteristic (ROC) area under the curve (AUC) of 72%. For bipolar disorder in particular, SLC4A4 predicted suicidal ideation with an AUC of 93%, and future hospitalizations with an AUC of 70%. SLC4A4 is involved in brain extracellular space pH regulation. Brain pH has been implicated in the pathophysiology of acute panic attacks. We also describe two new clinical information apps, one for affective state (simplified affective state scale, SASS) and one for suicide risk factors (Convergent Functional Information for Suicide, CFI-S), and how well they predict suicidal ideation across psychiatric diagnoses (AUC of 85% for SASS, AUC of 89% for CFI-S). We hypothesized a priori, based on our previous work, that the integration of the top biomarkers and the clinical information into a universal predictive measure (UP-Suicide) would show broad-spectrum predictive ability across psychiatric diagnoses. Indeed, the UP-Suicide was able to predict suicidal ideation across psychiatric diagnoses with an AUC of 92%. For bipolar disorder, it predicted suicidal ideation with an AUC of 98%, and future hospitalizations with an AUC of 94%. Of note, both types of tests we developed (blood biomarkers and clinical information apps) do not require asking the individual assessed if they have thoughts of suicide, as individuals who are truly suicidal often do not share that information with clinicians. We propose that the widespread use of such risk prediction tests as part of routine or targeted healthcare assessments will lead to early disease interception followed by preventive lifestyle modifications and proactive treatment.

Our aim was to determine outcomes with transplanting kidneys from deceased donors with acute kidney injury, defined as a donor with terminal serum creatinine ≥2.0 mg/dL, or a donor requiring acute renal replacement therapy. We included all patients who received deceased donor kidney transplant from June 2004 to October 2013. There were 162 AKI donor transplant recipients (21% of deceased donor transplants): 139 in the standard criteria donor (SCD) and 23 in the expanded criteria donor (ECD) cohort. 71% of the AKI donors had stage 3 (severe AKI), based on acute kidney injury network (AKIN) staging. Protocol biopsies were done at 1, 4, and 12 months posttransplant. One and four month formalin-fixed paraffin embedded (FFPE) biopsies from 48 patients (24 AKI donors, 24 non-AKI) underwent global gene expression profiling using DNA microarrays (96 arrays). DGF was more common in the AKI group but eGFR, graft survival at 1 year and proportion with IF/TA>2 at 1 year were similar for the two groups. At 1 month, there were 898 differentially expressed genes in the AKI group (p-value

Kidney transplantation is the optimal treatment for many patients with end-stage kidney disease. The short-term outcomes of kidney transplantation have improved in the past few decades as a result of development of newer immunosuppressive drugs, more effective anti-microbial prophylaxis, and improved surgical techniques; however, long-term outcomes remain suboptimal. Routine posttransplant monitoring consists of the measurement of serum creatinine (SCr) and immunosuppressive drug levels. However, both are insensitive and non-specific markers of graft damage.

Early hepatic allograft dysfunction (EAD) manifests posttransplantation with high serum transaminases, persistent cholestasis, and coagulopathy. The biological mechanisms are poorly understood. This study investigates the molecular mechanisms involved in EAD and defines a gene expression signature revealing different biological pathways in subjects with EAD from those without EAD, a potential first step in developing a molecular classifier as a potential clinical diagnostic. Global gene expression profiles of 30 liver transplant recipients of deceased donor grafts with EAD and 26 recipients without graft dysfunction were investigated using microarrays of liver biopsies performed at the end of cold storage and after graft reperfusion prior to closure. Results reveal a shift in inflammatory and metabolic responses between the two time points and differences between EAD and non-EAD. We identified relevant pathways (PPARα and NF-κB) and targets (such as CXCL1, IL1, TRAF6, TIPARP, and TNFRSF1B) associated with the phenotype of EAD. Preliminary proof of concept gene expression classifiers that distinguish EAD from non-EAD patients, with Area Under the Curve (AUC) >0.80 were also identified. This data may have mechanistic and diagnostic implications for EAD.

Immunosuppression after solid organ transplantation is a delicate balance of the immune response and is a complex phenomenon with many factors involved. Despite advances in the care of patients receiving organ transplants the adverse effects associated with immunosuppressive agents and the risks of long-term immunosuppression present a series of challenges and the need to weigh the risks and benefits of either over or under-immunosuppression. Ideally, if all transplant recipients could develop donor-specific immunological tolerance, it could drastically improve long-term graft survival without the need for immunosuppressive agents. In the absence of this ideal situation, the next best approach would be to develop tools to determine the adequacy of immunosuppression in each patient, in a manner that would individualize or personalize therapy. Despite current genomics-based studies of tolerance biomarkers in transplantation there are currently, no clinically validated tools to safely increase or decrease the level of IS that is beneficial to the patient. However, the successful identification of biomarkers and/or mechanisms of tolerance that have implications on long-term graft survival and outcomes depend on proper integration of study design, experimental protocols, and data-driven hypotheses. The objective of this article is to first, discuss the progress made on genomic biomarkers of immunological tolerance and the future avenues for the development of such biomarkers specifically in kidney transplantation. Secondly, we provide a set of guiding principles and identify the pitfalls, advantages, and drawbacks of studies that generate genomic data aimed at understanding transplant tolerance that is applicable to all solid transplants.

Liver regeneration is a complex process that restores functional tissue after resection or injury, and it is accompanied by transient adenosine triphosphate depletion and metabolic stress in hepatic parenchymal cells. Heat shock protein 70 (Hsp70) functions as a chaperone during periods of cellular stress and induces the expression of several inflammatory cytokines identified as key players during early liver regeneration. We, therefore, hypothesized that Hsp70 is required for the initiation of regeneration. Investigations were carried out in a 70% partial hepatectomy mouse model with mice lacking inducible Hsp70 (Hsp70(-/-)). Liver regeneration was assessed postoperatively with the liver weight/body weight (LW/BW) ratio, and sera and tissues were collected for analysis. In addition, the expression of Hsp-related genes was assessed in a cohort of 23 human living donor liver transplantation donors. In mice, the absence of Hsp70 was associated with a reduced postoperative LW/BW ratio, Ki-67 staining, and tumor necrosis factor α (TNF-α) expression in comparison with wild-type mice. TNF-α expression was also reduced in livers from Hsp70(-/-) mice after induction with lipopolysaccharide (1 mg/kg). Clinically, the transcription of multiple Hsp genes (especially Hsp70 family members) was up-regulated after donor hepatectomy. Together, these results suggest that the early phase of successful liver regeneration requires the presence of Hsp70 to induce TNF-α. Further studies are required to determine whether Hsp70 contributes to liver regeneration as a chaperone by stabilizing specific interactions required for growth signaling or as a paracrine inflammatory signal, as can occur in models of shock.

The ability to achieve immunologic tolerance after transplantation is a therapeutic goal. Here, we report interim results from an ongoing trial of tolerance in HLA-identical sibling renal transplantation. The immunosuppressive regimen included alemtuzumab induction, donor hematopoietic stem cells, tacrolimus/mycophenolate immunosuppression converted to sirolimus, and complete drug withdrawal by 24 months post-transplantation. Recipients were considered tolerant if they had normal biopsies and renal function after an additional 12 months without immunosuppression. Of the 20 recipients enrolled, 10 had at least 36 months of follow-up after transplantation. Five of these 10 recipients had immunosuppression successfully withdrawn for 16-36 months (tolerant), 2 had disease recurrence, and 3 had subclinical rejection in protocol biopsies (nontolerant). Microchimerism disappeared after 1 year, and CD4(+)CD25(high)CD127(-)FOXP3(+) regulatory T cells and CD19(+)IgD/M(+)CD27(-) B cells were increased through 5 years post-transplantation in both tolerant and nontolerant recipients. Immune/inflammatory gene expression pathways in the peripheral blood and urine, however, were differentially downregulated between tolerant and nontolerant recipients. In summary, interim results from this trial of tolerance in HLA-identical renal transplantation suggest that predictive genomic biomarkers, but not immunoregulatory phenotyping, may be able to discriminate tolerant from nontolerant patients.