Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients.

BACKGROUND: AKI requiring dialysis (AKI-D) is associated with prolonged hospitalization, mortality, and progressive CKD among survivors. Previous studies have examined only select urine or serum biomarkers for predicting kidney recovery from AKI. METHODS: Serum samples collected on day 8 of randomized RRT from 72 patients enrolled in the Veteran's Affairs/National Institutes of Health Acute Renal Failure Trial Network study were analyzed by the SOMAscan proteomic platform to profile 1305 proteins in each sample. Of these patients, 38 recovered kidney function and dialysis was discontinued, whereas another 34 patients remained on dialysis by day 28. RESULTS: Differential serum levels of 119 proteins, with 53 higher and 66 lower, were detected in samples from patients who discontinued dialysis, compared with patients who remained on dialysis by day 28. Patients were classified into tertiles on the basis of SOMAscan protein measurements for the 25 proteins most differentially expressed. The association of serum levels of each protein with kidney recovery was further evaluated using logistic regression analysis. Higher serum levels of CXCL11, CXCL2/CXCL3, CD86, Wnt-7a, BTK, c-Myc, TIMP-3, CCL5, ghrelin, PDGF-C, survivin, CA2, IL-9, EGF, and neuregulin-1, and lower levels of soluble CXCL16, IL1RL1, stanniocalcin-1, IL-6, and FGF23 when classified in tertiles were significantly associated with better kidney recovery. This significant association persisted for each of these proteins after adjusting for potential confounding risk factors including age, sex, cardiovascular SOFA score, congestive heart failure, diabetes, modality of intensive dialysis treatment, cause of AKI, baseline serum creatinine, day 8 urine volume, and estimated 60-day mortality risk. CONCLUSIONS: These results suggest concerted changes between survival-related proteins and immune-regulatory chemokines in regulating angiogenesis, endothelial and epithelial remodeling, and kidney cell regeneration, illustrating potential mechanisms of kidney recovery. Thus, this study identifies potential novel predictive biomarkers of kidney recovery in patients with AKI-D.

Stability of the Human Plasma Proteome to Pre-analytical Variability as Assessed by an Aptamer-Based Approach.

Variable processing and storage of whole blood and/or plasma are potential confounders in biomarker development and clinical assays. The goal of the study was to investigate how pre-analytical variables impact the human plasma proteome. Whole blood obtained from 16 apparently healthy individuals was collected in six EDTA tubes and processed randomly under six pre-analytical variable conditions including blood storage at 0 °C or RT for 6 h (B6h0C or B6hRT) before processing to plasma, plasma storage at 4 °C or RT for 24 h (P24h4C or P24hRT), low centrifugal force at 1300 × g, (Low×g), and immediate processing to plasma under 2500 × g (control) followed by plasma storage at -80 °C. An aptamer-based proteomic assay was performed to identify significantly changed proteins (fold change ≥1.2, P < 0.05, and false discovery rate < 0.05) relative to the control from a total of 1305 proteins assayed. Pre-analytical conditions Low×g and B6h0C resulted in the most plasma proteome changes with 200 and 148 proteins significantly changed, respectively. Only 36 proteins were changed under B6hRT. Conditions P24h4C and P24hRT yielded changes of 28 and 75 proteins, respectively. The complement system was activated in vitro under the conditions B6hRT, P24h4C, and P24hRT. The results suggest that particular pre-analytical variables should be controlled for clinical measurement of specific biomarkers.

An Integrated Analysis of Metabolites, Peptides, and Inflammation Biomarkers for Assessment of Preanalytical Variability of Human Plasma.

Discrepancies in blood sample collection and processing could have a significant impact on levels of metabolites, peptides, and protein biomarkers of inflammation in the blood; thus, sample quality control is critical for successful biomarker identification and validation. In this study, we analyzed the effects of several preanalytical processing conditions, including different storage times and temperatures for blood or plasma samples and different centrifugation forces on the levels of metabolites, peptides, and inflammation biomarkers in human plasma samples using ethylenediaminetetraacetic acid (EDTA) as an anticoagulant. Temperature was found to be the major factor for metabolite variation, and both time and temperature were identified as major factors for peptide variation. For inflammation biomarkers, temperature played different roles depending on the sample type (blood or plasma). Low temperature affected inflammation biomarkers in blood, while room temperature impacted inflammation biomarkers in plasma.

Aptamer-Based Proteomics Identifies Mortality-Associated Serum Biomarkers in Dialysis-Dependent AKI Patients.

INTRODUCTION: Currently, no effective therapies exist to reduce the high mortality associated with dialysis-dependent acute kidney injury (AKI-D). Serum biomarkers may be useful in understanding the pathophysiological processes involved with AKI and the severity of injury, and point to novel therapeutic targets. METHODS: Study day 1 serum samples from 100 patients and day 8 samples from 107 patients enrolled in the Veteran's Affairs/National Institutes of Health Acute Renal Failure Trial Network study were analyzed by the slow off-rate modified aptamers scan proteomic platform to profile 1305 proteins in each sample. Patients in each cohort were classified into tertiles based on baseline biomarker measurements. Cox regression analyses were performed to examine the relationships between serum levels of each biomarker and mortality. RESULTS: Changes in the serum levels of 54 proteins, 33 of which increased and 21 of which decreased, were detected when comparing samples of patients who died in the first 8 days versus patients who survived >8 days. Among the 33 proteins that increased, higher serum levels of fibroblast growth factor-23 (FGF23), tissue plasminogen activator (tPA), neutrophil collagenase (matrix metalloproteinase-8), and soluble urokinase plasminogen activator receptor, when stratified by tertiles, were associated with higher mortality. The association with mortality persisted for each of these proteins after adjusting for other potential risk factors, including age, sex, cardiovascular sequential organ failure assessment score, congestive heart failure, and presence of diabetes. Upper tertile levels of FGF23, tPA, and interleukin-6 on day 8 were associated with increased mortality; however, FGF23 barely lost significance after multivariable adjustment. CONCLUSIONS: Our results underscore an emerging proteomics tool capable of identifying low-abundance serum proteins important not only in the pathogenesis of AKI-D, but which is also helpful in discriminating AKI-D patients with high mortality.

Immune response proteins as predictive biomarkers of doxorubicin-induced cardiotoxicity in breast cancer patients.

Cancer treatment with doxorubicin (DOX) can induce cumulative dose-dependent cardiotoxicity. Currently, there are no specific biomarkers that can identify patients at risk during the initial doses of chemotherapy. The aim of this study was to examine plasma cytokines/chemokines and potential cardiovascular biomarkers for the prediction of DOX-induced cardiotoxicity. Plasma samples were collected before (T0), and after the first (T1) and the second (T2) cycles of DOX-based chemotherapy of 27 breast cancer patients, including five patients who presented with >10% decline of left ventricular ejection fraction (LVEF), five patients with LVEF decline of 5-10%, and 17 patients who maintained normal LVEF at the end of chemotherapy (240 mg/m2 cumulative dose of DOX from four cycles of treatment). Multiplex immunoassays were used to screen plasma samples for 40 distinct chemokines, nine matrix metalloproteinases, 33 potential markers of cardiovascular diseases, and the fourth-generation cardiac troponin T assay. The results showed that the patients with abnormal decline of LVEF (>10%) had lower levels of CXCL6 and sICAM-1 and higher levels of CCL23 and CCL27 at T0; higher levels of CCL23 and lower levels of CXCL5, CCL26, CXCL6, GM-CSF, CXCL1, IFN-γ, IL-2, IL-8, CXCL11, CXCL9, CCL17, and CCL25 at T1; and higher levels of MIF and CCL23 at T2 than the patients who maintained normal LVEF. Patients with LVEF decline of 5-10% had lower plasma levels of CXCL1, CCL3, GDF-15, and haptoglobin at T0; lower levels of IL-16, FABP3, and myoglobin at T1; and lower levels of myoglobin and CCL23 at T2 as compared to the patients who maintained normal LVEF. This pilot study identified potential biomarkers that may help predict which patients are vulnerable to DOX-induced cardiotoxicity although further validation is needed in a larger cohort of patients. Impact statement Drug-induced cardiotoxicity is one of the major concerns in drug development and clinical practice. It is critical to detect potential cardiotoxicity early before onset of symptomatic cardiac dysfunction or heart failure. Currently there are no qualified clinical biomarkers for the prediction of cardiotoxicity caused by cancer treatment such as doxorubicin (DOX). By using multiplex immunoassays, we identified proteins with significantly changed plasma levels in a group of breast cancer patients who were treated with DOX-based chemotherapy and produced cardiotoxicity. These proteins were associated with immune response and were identified before DOX treatment or at early doses of treatment, thus they could be potential predictive biomarkers of cardiotoxicity although further validation is required to warrant their clinical values.