Validation of Candidate Phospholipid Biomarkers of Chronic Kidney Disease in Hyperglycemic Individuals and Their Organ-Specific Exploration in Leptin Receptor-Deficient db/db Mouse
Authors:
- Jialing HuangJialing Huang
- Marcela CovicMCMarcela Covic
- Cornelia HuthCHCornelia Huth
- Martina RommelMRMartina Rommel
- Jonathan AdamJAJonathan Adam
- Sven ZukunftSZSven Zukunft
- Cornelia PrehnCornelia Prehn
- Li WangLWLi Wang
- Jana NanoJana Nano
- Markus F. ScheererMSMarkus F. Scheerer
- Susanne NeschenSNSusanne Neschen
- Gabi KastenmüllerGKGabi Kastenmüller
Open Access
- 3 February 2021
- journal article
- research article
- Published by MDPI AG in Metabolites
- Vol. 11 (2) , 89
Abstract
Biological exploration of early biomarkers for chronic kidney disease (CKD) in (pre)diabetic individuals is crucial for personalized management of diabetes. Here, we evaluated two candidate biomarkers of incident CKD (sphingomyelin (SM) C18:1 and phosphatidylcholine diacyl (PC aa) C38:0) concerning kidney function in hyperglycemic participants of the Cooperative Health Research in the Region of Augsburg (KORA) cohort, and in two biofluids and six organs of leptin receptor-deficient (db/db) mice and wild type controls. Higher serum concentrations of SM C18:1 and PC aa C38:0 in hyperglycemic individuals were found to be associated with lower estimated glomerular filtration rate (eGFR) and higher odds of CKD. In db/db mice, both metabolites had a significantly lower concentration in urine and adipose tissue, but higher in the lungs. Additionally, db/db mice had significantly higher SM C18:1 levels in plasma and liver, and PC aa C38:0 in adrenal glands. This cross-sectional human study confirms that SM C18:1 and PC aa C38:0 associate with kidney dysfunction in pre(diabetic) individuals, and the animal study suggests a potential implication of liver, lungs, adrenal glands, and visceral fat in their systemic regulation. Our results support further validation of the two phospholipids as early biomarkers of renal disease in patients with (pre)diabetes.Keywords
Funding Information
- Horizon 2020 Framework Programme (19076 & 20679 iPDM-GO)
This publication has 57 references indexed in Scilit:
- Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 DiabetesDiabetes, 2020
- Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017The Lancet, 2020
- Sodium–Glucose Cotransporter 2 Inhibition and Diabetic Kidney DiseaseDiabetes, 2019
- Risk Prediction for Early CKD in Type 2 DiabetesClinical Journal of the American Society of Nephrology, 2015
- Lipid biology of the podocyte—new perspectives offer new opportunitiesNature Reviews Nephrology, 2014
- Novel biomarkers for pre‐diabetes identified by metabolomicsMolecular Systems Biology, 2012
- Human metabolic individuality in biomedical and pharmaceutical researchNature, 2011
- Population based screening for chronic kidney disease: cost effectiveness studyBMJ, 2010
- Genetics Meets Metabolomics: A Genome-Wide Association Study of Metabolite Profiles in Human SerumPLOS Genetics, 2008
- Understanding 'Global' Systems Biology: Metabonomics and the Continuum of MetabolismNature Reviews Drug Discovery, 2003