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Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes.

ABSTRACT: AIMS/HYPOTHESIS:We examined whether candidate biomarkers in serum or urine can improve the prediction of renal disease progression in type 1 diabetes beyond prior eGFR, comparing their performance with urinary albumin/creatinine ratio (ACR). METHODS:From the population-representative Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) we sampled 50% and 25% of those with starting eGFR below and above 75 ml min-1 [1.73 m]-2, respectively (N?=?1629), and with median 5.1 years of follow-up. Multiplexed ELISAs and single molecule array technology were used to measure nine serum biomarkers and 13 urine biomarkers based on our and others' prior work using large discovery and candidate studies. Associations with final eGFR and with progression to <30 ml min-1 [1.73] m-2, both adjusted for baseline eGFR, were tested using linear and logistic regression models. Parsimonious biomarker panels were identified using a penalised Bayesian approach, and their performance was evaluated through tenfold cross-validation and compared with using urinary ACR and other clinical record data. RESULTS:Seven serum and seven urine biomarkers were strongly associated with either final eGFR or progression to <30 ml min-1 [1.73 m]-2, adjusting for baseline eGFR and other covariates (all at p<2.3?×?10-3). Of these, associations of four serum biomarkers were independent of ACR for both outcomes. The strongest associations with both final eGFR and progression to <30 ml min-1 [1.73 m]-2 were for serum TNF receptor 1, kidney injury molecule 1, CD27 antigen, ?-1-microglobulin and syndecan-1. These serum associations were also significant in normoalbuminuric participants for both outcomes. On top of baseline covariates, the r2 for prediction of final eGFR increased from 0.702 to 0.743 for serum biomarkers, and from 0.702 to 0.721 for ACR alone. The area under the receiver operating characteristic curve for progression to <30 ml min-1 [1.73 m]-2 increased from 0.876 to 0.953 for serum biomarkers, and to 0.911 for ACR alone. Other urinary biomarkers did not outperform ACR. CONCLUSIONS/INTERPRETATION:A parsimonious panel of serum biomarkers easily measurable along with serum creatinine may outperform ACR for predicting renal disease progression in type 1 diabetes, potentially obviating the need for urine testing.

SUBMITTER: Colombo M

PROVIDER: S-EPMC7054370 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes.

Colombo Marco M McGurnaghan Stuart J SJ Blackbourn Luke A K LAK Dalton R Neil RN Dunger David D Bell Samira S Petrie John R JR Green Fiona F MacRury Sandra S McKnight John A JA Chalmers John J Collier Andrew A McKeigue Paul M PM Colhoun Helen M HM

Diabetologia 20200108 4

<h4>Aims/hypothesis</h4>We examined whether candidate biomarkers in serum or urine can improve the prediction of renal disease progression in type 1 diabetes beyond prior eGFR, comparing their performance with urinary albumin/creatinine ratio (ACR).<h4>Methods</h4>From the population-representative Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) we sampled 50% and 25% of those with starting eGFR below and above 75 ml min<sup>-1</sup> [1.73 m]<sup>-2</sup>, respectively (N = 162 ...[more]

PMID: 31915892

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Project description:ImportanceAlthough cumulative evidence suggests that elevated urinary albumin-to-creatinine ratio (UACR) in the normal range (<30 mg/g) may be associated with an increased risk of mortality, few studies have investigated whether cardiovascular health (CVH) modifies the harmful outcomes of high-normal UACR.ObjectiveTo investigate associations of traditionally normal UACR and CVH with all-cause mortality.Design, setting, and participantsThis cohort study used National Health and Nutrition Examination Survey data from 2005 through 2018 and linked mortality information until 2019. Data were analyzed from March 1 through October 31, 2023. The study included adult participants aged 20 to 79 years with a normal UACR (<30 mg/g) based on Kidney Disease: Improving Global Outcomes criteria.ExposuresThe UACR was treated as a continuous variable and categorized into tertiles delineated as low (<4.67 mg/g), medium (4.67-7.67 mg/g), and high (7.68 to <30 mg/g). Cardiovascular health was assessed using Life's Essential 8 scores and grouped as poor (0-49 points), moderate (50-79 points), and ideal (80-100 points).Main outcomes and measuresMultivariable Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% CIs for associations of UACR with all-cause mortality in total participants and as stratified by CVH groups.ResultsThe study included 23 697 participants (mean [SD] age, 45.58 [15.44] years; 11 806 women [49.7%] and 11 891 men [50.3%]). During the median 7.8 years (range, 4.5-11.1 years) of follow-up, 1403 deaths were recorded. Near-linear associations were observed for continuous UACR and CVH with all-cause mortality. Compared with the low UACR group, high UACR in the normal range showed an increased mortality risk in the moderate and poor CVH groups (CVH [50-79]: HR, 1.54 [95% CI, 1.26-1.89]; CVH [0-49]: HR, 1.56 [95% CI, 1.10-2.20]), with a significant multiplicative interaction of UACR and CVH (P < .001).Conclusions and relevanceThe findings suggest that high UACR within the normal range is associated with a significantly increased risk of all-cause mortality, with the association more pronounced in adults with poor CVH status. These findings highlight the importance of risk management for early kidney dysfunction, particularly among individuals with poor CVH.

Dataset Information

Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes.

Publications

Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes.

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