Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Yu LR

PROVIDER: S-EPMC6127416 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Yu Li-Rong LR Sun Jinchun J Daniels Jaclyn R JR Cao Zhijun Z Schnackenberg Laura L Choudhury Devasmita D Palevsky Paul M PM Ma Jennie Z JZ Beger Richard D RD Portilla Didier D

Kidney international reports 20180503 5

<h4>Introduction</h4>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.<h4>Methods</h4>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 ...[more]

PMID: 30197987

Similar Datasets

Project description:Nonalcoholic steatohepatitis (NASH) is a major cause of liver-related morbidity and mortality worldwide. Liver fibrosis stage, a key component of NASH, has been linked to the risk of mortality and liver-related clinical outcomes. Currently there are no validated noninvasive diagnostics that can differentiate between fibrosis stages in patients with NASH; many existing tests do not reflect underlying disease pathophysiology. Noninvasive biomarkers are needed to identify patients at high-risk of NASH with advanced fibrosis. This was a retrospective study of patients with histologically proven NASH with fibrosis stages 0-4. The SOMAscan proteomics platform was used to quantify 1,305 serum proteins in a discovery cohort (n = 113). In patients with advanced (stages 3-4) versus early fibrosis (stages 0-2), 97 proteins with diverse biological functions were differentially expressed. Next, fibrosis-stage classification models were explored using a machine learning-based approach to prioritize the biomarkers for further evaluation. A four-protein model differentiated patients with stage 0-1 versus stage 2-4 fibrosis (area under the receiver operating characteristic curve [AUROC] = 0.74), while a 12-protein classifier differentiated advanced versus early fibrosis (AUROC = 0.83). Subsequently, the model's performance was validated in two independent cohorts (n = 71 and n = 32) with similar results (AUROC = 0.74-0.78). Our advanced fibrosis model performed similarly to or better than Fibrosis-4 index, aspartate aminotransferase-to-platelet ratio index, and nonalcoholic fatty liver disease (NAFLD) fibrosis score-based models for all three cohorts. Conclusion: A SOMAscan proteomics-based exploratory classifier for advanced fibrosis, consisting of biomarkers that reflect the complexity of NASH pathophysiology, demonstrated similar performance in independent validation cohorts and performed similarly or better than Fibrosis-4 index, aspartate aminotransferase-to-platelet ratio index, and NAFLD fibrosis score. Further studies are warranted to evaluate the clinical utility of these biomarker panels in patients with NAFLD.

Project description:BackgroundAKI 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.MethodsSerum 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.ResultsDifferential 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.ConclusionsThese 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.

Project description:BackgroundSerum phosphorus (SP) level is closely associated with overall mortality and cardiovascular events, while the role of SP controlled duration is not fully recognized. Here, we conducted a retrospective cohort study in our department to identify the relationship of SP controlled duration with clinical outcomes in patients undergoing peritoneal dialysis (PD).MethodsPD patients in our center from January 1, 2009, to June 30, 2019, were followed up at 2-month (the first year) or 5-month (the next follow-up period) intervals, and until death, until PD withdrawal, or until June 30, 2019. Data at each follow-up point were collected from their medical records. SP levels, changed degree of SP over baseline, and SP controlled duration were analyzed with overall mortality, PD withdrawal (including death, transferred to hemodialysis, and received renal transplantation), and combined endpoint (including death, acute heart failure, cardiovascular event, and stroke).ResultsA total of 530 patients entered the analysis. Of them, 456 (86.0%) had hyperphosphatemia before dialysis, and the SP levels decreased soon after dialysis. The degree of SP change over baseline was the maximum at the 3rd month after dialysis (-31.0%), and lower degree was associated with higher overall mortality (hazard ratio [HR], 1.012; 95% CI, 1.004-1.020; p = 0.003). The median SP controlled duration was 13 (5-28) months, and longer duration was significantly associated with lower overall mortality (HR, 0.968; 95% CI, 0.956-0.981; p < 0.001). After categorization, duration more than 12 months greatly improved overall mortality with a HR of 0.197 (0.082-0.458; p < 0.001 vs. SP never controlled group) and 0.329 (0.150-0.724; p = 0.006 vs. duration <12 months group). Longer SP controlled duration also improved PD withdrawal and combined endpoint.ConclusionsIn summary, both degree and duration of SP control were tightly associated with overall mortality. We should control SP levels as early, as possible, and as long as we could.

Project description:BackgroundAutoantibodies against tumor associated antigens are highly related to cancer progression. Autoantibodies could serve as indicators of tumor burden, and have the potential to monitor the response of treatment and tumor recurrence. However, how the autoantibody repertoire changes in response to cancer treatment are largely unknown.MethodsSera of five lung adenocarcinoma patients before and after surgery, were collected longitudinally. These sera were analyzed on a human proteome microarray of 20,240 recombinant proteins to acquire dynamic autoantibody repertoire in response to surgery, as well as to identify the antigens with decreased antibody response after tumor excision or surgery, named as surgery-associated antigens. The identified candidate antigens were then used to construct focused microarray and validated by longitudinal sera collected from a variety of time points of the same patient and a larger cohort of 45 sera from lung adenocarcinoma patients.FindingsThe autoantibody profiles are highly variable among patients. Meanwhile, the autoantibody profiles of the sera from the same patient were surprisingly stable for at least 3 months after surgery. Six surgery-associated antigens were identified and validated. All the five patients have at least one surgery-associated antigen, demonstrating this type of biomarkers is prevalent, while specific antigens are poorly shared among individuals. The prevalence of each antigen is 2%-14% according to the test with a larger cohort.InterpretationTo our knowledge, this is the first study of dynamically profiling of autoantibody repertoires before/after surgery of cancer patients. The high prevalence of surgery-associated antigens implies the possible broad application for monitoring of tumor recurrence in population, while the low prevalence of specific antigens allows personalized medicine. After the accumulation and analysis of more longitudinal samples, the surgery-associated serum biomarkers, combined as a panel, may be applied to alarm the recurrence of tumor in a personalized manner.FundingResearch supported by grants from National Key Research and Development Program of China Grant (No. 2016YFA0500600), National Natural Science Foundation of China (No. 31970130, 31600672, 31670831, and 31370813), Open Foundation of Key Laboratory of Systems Biomedicine (No. KLSB2017QN-01), Science and Technology Commission of Shanghai Municipality Medical Guidance Science &Technology Support Project (16411966100), Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (20172005), Shanghai Municipal Commission of Health and Family Planning Outstanding Academic Leaders Training Program (2017BR055) and National Natural Science Foundation of China (81871882).

Dataset Information

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

Introduction

Methods

Results

Conclusions

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets