Dataset Information

Comparison of Circulating Biomarkers in Predicting Diabetic Kidney Disease Progression With Autoantibodies to Erythropoietin Receptor.

ABSTRACT:

Introduction

Several circulating markers, including autoantibodies to erythropoietin receptor (anti-EPOR antibodies), have been identified as useful biomarkers in predicting diabetic kidney disease progression. However, a direct comparison of their utility is lacking. We aimed to validate and to compare the prognostic value of anti-EPOR antibodies with that of other known biomarkers, using the ADVANCE trial and its long-term follow-up, ADVANCE-ON, cohorts.

Methods

In this nested case-control study from the ADVANCE trial cohort, we included 165 case participants who had the composite kidney outcome (renal replacement therapy, renal death, or doubling of serum creatinine to ≥200 μmol/l) and 330 matched controls. We compared the associations of baseline plasma levels of anti-EPOR antibodies, tumor necrosis factor receptor (TNFR)-1 and -2, and bone morphogenetic protein (BMP)-7 with kidney outcomes.

Results

Cases had higher baseline plasma levels of anti-EPOR antibodies than controls (median 1.7 vs. 0.6 enzyme-linked immunosorbent assay unit, P < 0.001). Higher levels of anti-EPOR antibodies were associated with an increased risk of kidney outcome (odds ratio 2.16 [95% confidence interval 1.51, 3.08], per 1 SD of log-transformed levels) after adjusting for conventional markers. Elevated circulating TNFR1 and TNFR2 levels, and lower BMP-7 levels at baseline, were associated with poor kidney outcome (odds ratios 2.06 [1.29, 3.30], 1.66 [1.13, 2.43], and 0.45 [0.32, 0.65], respectively). The addition of anti-EPOR antibodies into the model improved the prediction of kidney outcome, regardless of other biomarkers.

Conclusion

Anti-EPOR antibodies provide a promising biomarker, as with TNFR1, TNFR2, and BMP-7, in predicting kidney disease progression in people with type 2 diabetes mellitus.

SUBMITTER: Oshima M

PROVIDER: S-EPMC7879109 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Comparison of Circulating Biomarkers in Predicting Diabetic Kidney Disease Progression With Autoantibodies to Erythropoietin Receptor.

Oshima Megumi M Hara Akinori A Toyama Tadashi T Jun Min M Pollock Carol C Jardine Meg M Harrap Stephen S Poulter Neil N Cooper Mark E ME Woodward Mark M Chalmers John J Perkovic Vlado V Wong Muh Geot MG Wada Takashi T

Kidney international reports 20201110 2

<h4>Introduction</h4>Several circulating markers, including autoantibodies to erythropoietin receptor (anti-EPOR antibodies), have been identified as useful biomarkers in predicting diabetic kidney disease progression. However, a direct comparison of their utility is lacking. We aimed to validate and to compare the prognostic value of anti-EPOR antibodies with that of other known biomarkers, using the ADVANCE trial and its long-term follow-up, ADVANCE-ON, cohorts.<h4>Methods</h4>In this nested c ...[more]

PMID: 33615053

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Project description:BackgroundDNA methylation differences are associated with kidney function and diabetic kidney disease (DKD), but prospective studies are scarce. Therefore, we aimed to study DNA methylation in a prospective setting in the Finnish Diabetic Nephropathy Study type 1 diabetes (T1D) cohort.MethodsWe analysed baseline blood sample-derived DNA methylation (Illumina's EPIC array) of 403 individuals with normal albumin excretion rate (early progression group) and 373 individuals with severe albuminuria (late progression group) and followed-up their DKD progression defined as decrease in eGFR to <60 mL/min/1.73m2 (early DKD progression group; median follow-up 13.1 years) or end-stage kidney disease (ESKD) (late DKD progression group; median follow-up 8.4 years). We conducted two epigenome-wide association studies (EWASs) on DKD progression and sought methylation quantitative trait loci (meQTLs) for the lead CpGs to estimate genetic contribution.ResultsAltogether, 14 methylation sites were associated with DKD progression (P<9.4×10-8). Methylation at cg01730944 near CDKN1C and at other CpGs associated with early DKD progression were not correlated with baseline eGFR, whereas late progression CpGs were strongly associated. Importantly, 13 of 14 CpGs could be linked to a gene showing differential expression in DKD or chronic kidney disease. Higher methylation at the lead CpG cg17944885, a frequent finding in eGFR EWASs, was associated with ESKD risk (HR [95% CI] = 2.15 [1.79, 2.58]). Additionally, we replicated meQTLs for cg17944885 and identified ten novel meQTL variants for other CpGs. Furthermore, survival models including the significant CpG sites showed increased predictive performance on top of clinical risk factors.ConclusionsOur EWAS on early DKD progression identified a podocyte-specific CDKN1C locus. EWAS on late progression proposed novel CpGs for ESKD risk and confirmed previously known sites for kidney function. Since DNA methylation signals could improve disease course prediction, a combination of blood-derived methylation sites could serve as a potential prognostic biomarker.

Project description:Rationale & objectiveMost circulating biomarkers of chronic kidney disease (CKD) progression focus on factors reflecting glomerular filtration. Few biomarkers capture nonglomerular pathways of kidney injury or damage, which may be particularly informative in populations at high risk for CKD progression such as individuals with diabetes.Study designCohort study.Setting & participants594 participants (mean age, 70 years; 53% women) of the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study who had diabetes and an estimated glomerular filtration rate (eGFR)<60mL/min/1.73m2 at baseline.ExposuresPlasma biomarkers of inflammation/fibrosis (TNFR1 and TNFR2, suPAR, MCP-1, YKL-40) and tubular injury (KIM-1) measured at the baseline visit.OutcomesIncident kidney failure with replacement therapy (KFRT).Analytical approachCox proportional hazards regression and least absolute shrinkage and selection operator regression adjusted for established risk factors for kidney function decline, baseline eGFR, and urinary albumin-creatinine ratio (UACR).ResultsA total of 98 KFRT events were observed over a mean of 6.2±3.5 (standard deviation) years of follow-up. Plasma biomarkers were modestly associated with baseline eGFR (correlation coefficients ranging from-0.08 to-0.65) and UACR (0.14 to 0.56). In individual biomarker models adjusted for eGFR, UACR, and established risk factors, hazard ratios for incident KFRT per 2-fold higher biomarker concentrations were 1.52 (95% CI, 1.25-1.84) for plasma KIM-1, 1.54 (95% CI, 1.08-2.21) for TNFR1, 1.91 (95% CI, 1.16-3.14) for TNFR2, and 1.39 (95% CI, 1.05-1.84) for YKL-40. In least absolute shrinkage and selection operator regression models accounting for biomarkers in parallel, plasma KIM-1 and TNFR1 remained associated with incident KFRT.LimitationsSingle biomarker measurement, lack of follow-up eGFR assessments.ConclusionsIndividual plasma markers of inflammation/fibrosis (TNFR1, TNFR2, YKL-40) and tubular injury (KIM-1) were associated with risk of incident KFRT in adults with diabetes and an eGFR<60mL/min/1.73m2 after adjustment for established risk factors.

Dataset Information

Comparison of Circulating Biomarkers in Predicting Diabetic Kidney Disease Progression With Autoantibodies to Erythropoietin Receptor.

Introduction

Methods

Results

Conclusion

Publications

Comparison of Circulating Biomarkers in Predicting Diabetic Kidney Disease Progression With Autoantibodies to Erythropoietin Receptor.

Similar Datasets

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