. 2025 Aug 17:12:20543581251363126.

doi: 10.1177/20543581251363126. eCollection 2025.

Cardiometabolic Biomarkers and Prediction of Kidney Disease Progression: The eGFR Cohort Study

Elizabeth L M Barr^{1

2}, Federica Barzi^{1

3}, Phillip Mills Kulkalgal⁴, Maria Nickels¹, Sian Graham¹, Odette Pearson⁵, Varuni Obeyesekere⁶, Wendy E Hoy⁷, Graham R D Jones^{8

9}, Paul D Lawton^{1

10}, Alex D H Brown^{11

12}, Mark Thomas¹³, Ashim Sinha¹⁴, Alan Cass¹, Richard J MacIsaac^{6

15

16}, Louise J Maple-Brown^{1

17}, Jaquelyne T Hughes Wagadagam^{1

17

18}

Affiliations

¹ Menzies School of Health Research, Charles Darwin University, Casuarina, NT, Australia.
² Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
³ UQ Poche Centre, The University of Queensland, Brisbane, Australia.
⁴ James Cook University, Cairns, QLD, Australia.
⁵ South Australian Health and Medical Research Institute, Adelaide, Australia.
⁶ Department of Endocrinology & Diabetes, St Vincent's Hospital Melbourne, Fitzroy, VIC, Australia.
⁷ The University of Queensland, Brisbane, Australia.
⁸ St Vincent's Hospital, SydPath, Sydney, NSW, Australia.
⁹ Department of Medicine, University of New South Wales, Sydney, Australia.
¹⁰ Monash University, Melbourne, VIC, Australia.
¹¹ Indigenous Genomics, Telethon Kids Institute, Adelaide, SA, Australia.
¹² National Centre for Indigenous Genomics, Australian National University, Adelaide, SA, Australia.
¹³ Royal Perth Hospital, Perth, WA, Australia.
¹⁴ Diabetes and Endocrinology, Cairns Base Hospital, Cairns, QLD, Australia.
¹⁵ Department of Medicine, University of Melbourne, Fitzroy, VIC, Australia.
¹⁶ Australian Centre for Accelerating Diabetes Innovations, University of Melbourne, Parkville, VIC, Australia.
¹⁷ Royal Darwin Hospital, Tiwi, NT, Australia.
¹⁸ Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Tiwi, NT, Australia.

PMID: 40831908
PMCID: PMC12358709
DOI: 10.1177/20543581251363126

Cardiometabolic Biomarkers and Prediction of Kidney Disease Progression: The eGFR Cohort Study

Elizabeth L M Barr et al. Can J Kidney Health Dis. 2025.

. 2025 Aug 17:12:20543581251363126.

doi: 10.1177/20543581251363126. eCollection 2025.

Authors

Affiliations

¹ Menzies School of Health Research, Charles Darwin University, Casuarina, NT, Australia.
² Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
³ UQ Poche Centre, The University of Queensland, Brisbane, Australia.
⁴ James Cook University, Cairns, QLD, Australia.
⁵ South Australian Health and Medical Research Institute, Adelaide, Australia.
⁶ Department of Endocrinology & Diabetes, St Vincent's Hospital Melbourne, Fitzroy, VIC, Australia.
⁷ The University of Queensland, Brisbane, Australia.
⁸ St Vincent's Hospital, SydPath, Sydney, NSW, Australia.
⁹ Department of Medicine, University of New South Wales, Sydney, Australia.
¹⁰ Monash University, Melbourne, VIC, Australia.
¹¹ Indigenous Genomics, Telethon Kids Institute, Adelaide, SA, Australia.
¹² National Centre for Indigenous Genomics, Australian National University, Adelaide, SA, Australia.
¹³ Royal Perth Hospital, Perth, WA, Australia.
¹⁴ Diabetes and Endocrinology, Cairns Base Hospital, Cairns, QLD, Australia.
¹⁵ Department of Medicine, University of Melbourne, Fitzroy, VIC, Australia.
¹⁶ Australian Centre for Accelerating Diabetes Innovations, University of Melbourne, Parkville, VIC, Australia.
¹⁷ Royal Darwin Hospital, Tiwi, NT, Australia.
¹⁸ Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Tiwi, NT, Australia.

PMID: 40831908
PMCID: PMC12358709
DOI: 10.1177/20543581251363126

Abstract
in English, French

Background: Traditional markers modestly predict chronic kidney disease progression in Aboriginal and Torres Strait Islander people. Therefore, we assessed associations of cardiometabolic and inflammatory clinical biomarkers with kidney disease progression among Aboriginal and Torres Strait Islander people with and without diabetes.

Objectives: To identify cardiometabolic and inflammatory clinical biomarkers that predict kidney disease progression in Aboriginal and Torres Strait Islander people.

Design: Prospective observational cohort study.

Setting: Northern Territory, Australia.

Participants: Aboriginal and Torres Strait Islander participants of the estimated glomerular filtration rate (eGFR) study with (n = 218) and without diabetes (n = 278).

Measurements: Baseline biomarkers (expressed as 1 standard deviation increase in logarithmic scale), plasma kidney injury molecule-1 (pKIM-1) (pg/ml), high-sensitivity troponin-T (hs-TnT) (ng/L), troponin-I (hs-TnI) (ng/L), and soluble tumor necrosis factor receptor-1 (sTNFR-1) (pg/ml) were assessed in 496 adults. Annual change in eGFR (ml/min/1.73 m²) and a composite kidney outcome (first of ≥30% eGFR decline with follow-up eGFR <60 ml/min/1.73 m², initiation of kidney replacement therapy or kidney disease-related death) over a median of 3 years.

Methods: Linear regression estimated annual change in eGFR (ml/min/1.73 m²). Cox proportional hazards regression estimated hazard ratio (HR) and 95% CI for developing a combined kidney health outcome.

Results: In individuals with diabetes, but not those without diabetes, higher baseline hs-TnT (-2.1 [-4.1 to -0.2], P = .033) and sTNFR-1 (-1.8 [-3.5 to -0.1], P = .039) predicted mean (95% CI) eGFR change, after adjusting for age, gender, baseline eGFR, and urinary albumin-to-creatinine ratio. Baseline variables explained 11% of eGFR decline variance; increasing to 27% (P < .001) with biomarkers. In diabetes, hs-TnT and hs-TnI were significantly associated with increased risk of kidney health outcomes.

Limitations: Limitations included potential chronic kidney disease misclassification from single creatinine and albumin measurements, limited adjustment for covariates due to a small sample size, and short follow-up restricting long-term outcome assessment.

Conclusions: Cardiovascular, kidney, and inflammatory biomarkers are likely associated with kidney function loss in diabetes, with particularly prominent associations for cardiac injury markers.

Contexte: Les marqueurs traditionnels sont des prédicteurs modérés de la progression de l’insuffisance rénale chronique (IRC) chez les Aborigènes et les Insulaires du Détroit de Torres. Nous avons évalué les associations de biomarqueurs cliniques cardiométaboliques et inflammatoires avec la progression de l’IRC dans ces populations, auprès d’individus atteints ou non de diabète.

Objectif: Identifier les biomarqueurs cliniques cardiométaboliques et inflammatoires qui prédisent la progression de l’insuffisance rénale chez les Aborigènes et les Insulaires du Détroit de Torres.

Conception: Étude de cohorte observationnelle prospective.

Cadre: Territoire du Nord, Australie.

Sujets: Les Aborigènes et Insulaires du Détroit de Torres, diabétiques (n=218) ou non (n=278), participant à l’étude « eGFR cohort study ».

Mesures: Les biomarqueurs initiaux (exprimés par une augmentation de l’écart-type de 1 échelle logarithmique), la protéine KIM-1 plasmatique (pKIM-1 — plasma Kidney Injury Molecule-1) en pg/ml, la troponine-T de haute sensibilité (hs-TnT) en ng/l, la troponine-I (hs-TnI) en ng/l et le récepteur-1 soluble du facteur de nécrose tumorale (sTNFR-1) en pg/ml ont été évalués chez 496 adultes. On a également examiné la variation annuelle du débit de filtration glomérulaire estimé (DFGe) (ml/min/1,73 m²) et d’un résultat clinique composite de santé rénale (premier déclin du DFGe ≥30 % avec DFGe de suivi < 60 ml/min/1,73 m², amorce d’un traitement de substitution rénale ou décès lié à une néphropathie) sur une durée médiane de 3 ans.

Méthodologie: La variation annuelle du DFGe (ml/min/1,73 m²) a été estimée par régression linéaire. Le rapport de risque (RR) a été estimé par régression des risques proportionnels de Cox avec IC à 95 % pour le développement d’un résultat clinique composite de santé rénale.

Résultats: Chez les sujets diabétiques, des valeurs initiales plus élevées du hs-TnT (-2,1 [-4,1 à -0,2], p=0,033) et du sTNFR-1 (-1,8 [-3,5 à -0,1], p=0,039) ont prédit une variation moyenne (IC à 95 %) du DFGe, après correction selon l’âge, le sexe, le DFGe initial et le rapport albumine/créatinine urinaire, ce qui n’était pas le cas de sujets non-diabétiques. Les variables initiales pouvaient expliquer 11 % de la variation du déclin du DFGe; cette proportion augmentait à 27 % (p<0,001) avec les biomarqueurs. Chez les diabétiques, le hs-TnT et le hs-TnI ont été significativement associés à un risque accru d’issues de santé rénale.

Limites: La possible erreur de classification de l’IRC à partir de mesures uniques de créatinine et d’albumine, la correction limitée des covariables en raison de la petite taille de l’échantillon et la courte durée du suivi qui a empêché l’évaluation des résultats cliniques à long terme.

Conclusion: Les biomarqueurs cardiovasculaires, rénaux et inflammatoires sont probablement associés au déclin de la fonction rénale chez les diabétiques, et cette association serait particulièrement importante pour les marqueurs de lésions cardiaques.

Keywords: First Nations; epidemiology; inflammatory markers; kidney disease progression; novel biomarkers.

PubMed Disclaimer

Conflict of interest statement

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: MT, in the last 5 years, has received lecture fees and advisory board payments for cardiometabolic topics from AstraZeneca, Bayer, Boehringer Ingelheim, and Eli Lilly. RM reports no direct conflicts of interest to the work reported in this paper. However, RM has received research grants from Novo Nordisk, Servier, Medtronic, The Rebecca Cooper Medical Research Foundation, St Vincent’s Research Foundation, The Juvenile Diabetes Research Foundation, Gray Innovations, The Diabetes Australia Research Trust/Program, and The National Health and Medical Research Council of Australia. RM also received honoraria for lectures from Eli Lilly, Novo Nordisk, Sanofi Aventis, AstraZeneca, Merck Sharp & Dohme, Norvartis, and Boehringer Ingelheim and has been or is on the advisory boards for Novo Nordisk, Boehringer Ingelheim-Eli Lilly Diabetes Alliance, AstraZeneca and Merck Shape and Dohme. Travel support for RM has been supplied by Novo Nordisk, Sanofi, Boehringer Ingelheim, and AstraZeneca. RM has been a principal investigator for industry-sponsored clinical trials run by Novo Nordisk, Sanofi, Bayer, Johnson-Cilag and Abbive. All other authors declare no conflict of interest to disclose.

Figures

Use this as context data: “Annual decline in CKD-EPI eGFR over 3 years for pKIM-1, hs-TnT, and hs-TnI levels in diabetics and non-diabetics” — **Figure 1.**
Annual CKD-EPI eGFR decline over a median of 3 years according to baseline levels of pKIM-1, hs-TnT and hs-TnI for participants with and without diabetes at baseline: the eGFR study.

Increased eGFR decline in those without diabetes and those with diabetes, adjusted for pKIM-1, hs-TnT, hs-TnI, sTNFR-1 and CKD-EPI eGFR rate by uACR and uPCR — **Figure 2.**
Adjusted associations for pKIM-1, hs-TnT, hs-TnI, and sTNFR-1 with CKD-EPI eGFR decline: the eGFR study.

add the description — **Figure 3.**
Risk of combined kidney health outcome for pKIM-1, hs-TnT, hs-TnI, and sTNFR-1 in those with and without diabetes: the eGFR study.

See this image and copyright information in PMC

References

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Cardiometabolic Biomarkers and Prediction of Kidney Disease Progression: The eGFR Cohort Study

Affiliations

Cardiometabolic Biomarkers and Prediction of Kidney Disease Progression: The eGFR Cohort Study

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Abstract
in English, French

Conflict of interest statement

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Abstract
in English, French