There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection ...(ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi‐array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one‐by‐one analysis strategy to model the real clinical application of this test. Multiple three‐way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction.
This study of kidney transplantation describes a three‐way classifier based on global gene expression profiling of peripheral blood and the blood signatures of patients with excellent functioning grafts that can be used in the setting of acute kidney transplant dysfunction to accurately distinguish between biopsy‐proven acute rejection and acute dysfunction with no rejection.
The 8th Banff Conference on Allograft Pathology was held in Edmonton, Canada, 15–21 July 2005. Major outcomes included the elimination of the non‐specific term ‘chronic allograft nephropathy’ (CAN) ...from the Banff classification for kidney allograft pathology, and the recognition of the entity of chronic antibody‐mediated rejection. Participation of B cells in allograft rejection and genomics markers of rejection were also major subjects addressed by the conference.
The Banff consensus process has now eliminated the use of the term “chronic allograft nephropathy” (CAN) and replaced it with specific terms that distinguish non‐specific atrophy and fibrosis from specific entities such as slow antibody‐mediated rejection.
There are to date no objective clinical laboratory blood tests for psychotic disease states. We provide proof of principle for a convergent functional genomics (CFG) approach to help identify and ...prioritize blood biomarkers for two key psychotic symptoms, one sensory (hallucinations) and one cognitive (delusions). We used gene expression profiling in whole blood samples from patients with schizophrenia and related disorders, with phenotypic information collected at the time of blood draw, then cross-matched the data with other human and animal model lines of evidence. Topping our list of candidate blood biomarkers for hallucinations, we have four genes decreased in expression in high hallucinations states (Fn1, Rhobtb3, Aldh1l1, Mpp3), and three genes increased in high hallucinations states (Arhgef9, Phlda1, S100a6). All of these genes have prior evidence of differential expression in schizophrenia patients. At the top of our list of candidate blood biomarkers for delusions, we have 15 genes decreased in expression in high delusions states (such as Drd2, Apoe, Scamp1, Fn1, Idh1, Aldh1l1), and 16 genes increased in high delusions states (such as Nrg1, Egr1, Pvalb, Dctn1, Nmt1, Tob2). Twenty-five of these genes have prior evidence of differential expression in schizophrenia patients. Predictive scores, based on panels of top candidate biomarkers, show good sensitivity and negative predictive value for detecting high psychosis states in the original cohort as well as in three additional cohorts. These results have implications for the development of objective laboratory tests to measure illness severity and response to treatment in devastating disorders such as schizophrenia.
There are to date no objective clinical laboratory blood tests for mood disorders. The current reliance on patient self-report of symptom severity and on the clinicians' impression is a rate-limiting ...step in effective treatment and new drug development. We propose, and provide proof of principle for, an approach to help identify blood biomarkers for mood state. We measured whole-genome gene expression differences in blood samples from subjects with bipolar disorder that had low mood vs those that had high mood at the time of the blood draw, and separately, changes in gene expression in brain and blood of a mouse pharmacogenomic model. We then integrated our human blood gene expression data with animal model gene expression data, human genetic linkage/association data and human postmortem brain data, an approach called convergent functional genomics, as a Bayesian strategy for cross-validating and prioritizing findings. Topping our list of candidate blood biomarker genes we have five genes involved in myelination (Mbp, Edg2, Mag, Pmp22 and Ugt8), and six genes involved in growth factor signaling (Fgfr1, Fzd3, Erbb3, Igfbp4, Igfbp6 and Ptprm). All of these genes have prior evidence of differential expression in human postmortem brains from mood disorder subjects. A predictive score developed based on a panel of 10 top candidate biomarkers (five for high mood and five for low mood) shows sensitivity and specificity for high mood and low mood states, in two independent cohorts. Our studies suggest that blood biomarkers may offer an unexpectedly informative window into brain functioning and disease state.
An unbalanced microbiome may lead to disease by creating aberrant immune responses. A recent association of cellular rejection with the development of interstitial fibrosis and tubular atrophy (IFTA) ...suggests the role of immune‐mediated tissue injury. We hypothesized that developing IFTA correlates with altered urinary tract microbiomes (UMBs). UMBs at two serial time points, 1 and 6–8 months posttransplant, were assessed by 16S microbial ribosomal gene sequencing in 25 patients developing biopsy‐proven IFTA compared to 23 transplant patients with normal biopsies and excellent function (TX) and 20 healthy nontransplant controls (HC). Streptococcus, the dominant genera in HC males, was lower in IFTA and TX males at 1 month compared to HCs. At 6–8 months, Streptococcus was further decreased in IFTA males, but normalized in TX. IFTA males and females had increases in number of genera per sample at 6–8 months. UMB composition varied substantially between individuals in all groups. Despite the wide variation in UMBs between individuals, IFTA was associated with a loss in dominant resident urinary microbes in males, and a parallel increase in nonresident, pathogenic bacteria in males and females. UMB changes may contribute to IFTA development by alteration of the host immune response.
The authors assess urinary microbiomes at 1 and 6–8 months posttransplant in 25 patients who developed biopsy‐proven interstitial fibrosis and tubular atrophy (IFTA), 23 transplant patients with normal biopsies and excellent function, and 20 healthy controls, and find an association of the development of IFTA with a loss in dominant resident urinary microbes in males, and a parallel increase in nonresident, pathogenic bacteria in males and females.
We previously reported that tacrolimus (TAC) trough blood concentrations for African American (AA) kidney allograft recipients were lower than those observed in white patients. Subtherapeutic TAC ...troughs may be associated with acute rejection (AR) and AR-associated allograft failure. This variation in TAC troughs is due, in part, to differences in the frequency of the cytochrome P450 CYP3A5*3 allele (rs776746, expresses nonfunctional enzyme) between white and AA recipients; however, even after accounting for this variant, variability in AA-associated troughs is significant. We conducted a genomewide association study of TAC troughs in AA kidney allograft recipients to search for additional genetic variation. We identified two additional CYP3A5 variants in AA recipients independently associated with TAC troughs: CYP3A5*6 (rs10264272) and CYP3A5*7 (rs41303343). All three variants and clinical factors account for 53.9% of the observed variance in troughs, with 19.8% of the variance coming from demographic and clinical factors including recipient age, glomerular filtration rate, anticytomegalovirus drug use, simultaneous pancreas–kidney transplant and antibody induction. There was no evidence of common genetic variants in AA recipients significantly influencing TAC troughs aside from the CYP3A gene. These results reveal that additional and possibly rare functional variants exist that account for the additional variation.
With the increase in patients having impaired renal function at liver transplant due to MELD, accurate predictors of posttransplant native renal recovery are needed to select candidates for ...simultaneous liver–kidney transplantation (SLK). Current UNOS guidelines rely on specific clinical criteria for SLK allocation. To examine these guidelines and other variables predicting nonrecovery, we analyzed 155 SLK recipients, focusing on a subset (n = 78) that had post‐SLK native GFR (nGFR) determined by radionuclide renal scans. The 77 patients not having renal scans received a higher number of extended criteria donor organs and had worse posttransplant survival. Of the 78 renal scan patients, 31 met and 47 did not meet pre‐SLK UNOS criteria. The UNOS criteria were more predictive than our institutional criteria for all nGFR recovery thresholds (20–40 mL/min), although at the most conservative cut‐off (nGFR ≤ 20) it had low sensitivity (55.3%), specificity (75%), PPV (67.6%) and NPV (63.8%) for predicting post‐SLK nonrecovery. On multivariate analysis, the only predictor of native renal nonrecovery (nGFR ≤ 20) was abnormal pre‐SLK renal imaging (OR 3.85, CI 1.22–12.5). Our data support the need to refine SLK selection utilizing more definitive biomarkers and predictors of native renal recovery than current clinical criteria.
This analysis of radionuclide imaging following simultaneous liver–kidney transplantation demonstrates the need for more definitive predictors of native renal recovery than current clinical criteria to better guide the selection of acceptable candidates for this procedure versus liver transplant alone. See editorial by Feng and Trotter on page 2869.
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.
The American Society of Transplantation (AST) and American Society of Transplant Surgeons (ASTS) convened a workshop on June 2–3, 2014, to explore increasing both living and deceased organ donation ...in the United States. Recent articles in the lay press on illegal organ sales and transplant tourism highlight the impact of the current black market in kidneys that accompanies the growing global organ shortage. We believe it important not to conflate the illegal market for organs, which we reject in the strongest possible terms, with the potential in the United States for concerted action to remove all remaining financial disincentives for donors and critically consider testing the impact and acceptability of incentives to increase organ availability in the United States. However, we do not support any trials of direct payments or valuable considerations to donors or families based on a process of market‐assigned values of organs. This White Paper represents a summary by the authors of the deliberations of the Incentives Workshop Group and has been approved by both AST and ASTS Boards.
The authors present the output of a recent AST/ASTS workshop focusing on challenges facing organ donation in the US, specifically introducing an operational “arc of change” strategy to address removal of all disincentives for living donors and exploring the potential of highly controlled pilot studies of incentives for donation. Read two related viewpoints on pages 1180 and 1187.
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 <0.005; FDR <10%), but by 4 months there were no differences. Transplanting selected kidneys from deceased donors with AKI is safe and has excellent outcomes.
The authors show that transplanting select kidneys from deceased donors with severe acute injury results in excellent outcomes, including graft survival, and resolution of early differences in allograft gene expression for tissue damage, cell death, and inflammation.
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