Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/23918
Title: Identification of Potential Biomarkers of Chronic Kidney Disease in Individuals with Diabetes: Protocol for a Cross-sectional Observational Study.
Austin Authors: Lecamwasam, Ashani R ;Mohebbi, Mohammadreza;Ekinci, Elif I ;Dwyer, Karen M;Saffery, Richard
Affiliation: School of Medicine, Faculty of Health, Deakin University, Victoria, Australia
Biostatistics Unit, Faculty of Health, Deakin University, Victoria, Australia
Department of Medicine, The University of Melbourne, Victoria, Australia
Endocrinology
Department of Paediatrics, The University of Melbourne, Victoria, Australia
Epigenetics Research, Murdoch Children's Research Institute, Victoria, Australia
Issue Date: 31-Jul-2020
Date: 2020
Publication information: JMIR Research Protocols 2020; 9(7): e16277
Abstract: The importance of identifying people with diabetes and progressive kidney dysfunction relates to the excess morbidity and mortality of this group. Rates of cardiovascular disease are much higher in people with both diabetes and kidney dysfunction than in those with only one of these conditions. By the time these people are identified in current clinical practice, proteinuria and renal dysfunction are already established, limiting the effectiveness of therapeutic interventions. The identification of an epigenetic or blood metabolite signature or gut microbiome profile may identify those with diabetes at risk of progressive chronic kidney disease, in turn providing targeted intervention to improve patient outcomes. This study aims to identify potential biomarkers in people with diabetes and chronic kidney disease (CKD) associated with progressive renal injury and to distinguish between stages of chronic kidney disease. Three sources of biomarkers will be explored, including DNA methylation profiles in blood lymphocytes, the metabolomic profile of blood-derived plasma and urine, and the gut microbiome. The cross-sectional study recruited 121 people with diabetes and varying stages (stages 1-5) of chronic kidney disease. Single-point data collection included blood, urine, and fecal samples in addition to clinical data such as anthropometric measurements and biochemical parameters. Additional information obtained from medical records included patient demographics, medical comorbidities, and medications. Data collection commenced in January 2018 and was completed in June 2018. At the time of submission, 121 patients had been recruited, and 119 samples remained after quality control. There were 83 participants in the early diabetes-associated CKD group with a mean estimated glomerular filtration rate (eGFR) of 61.2 mL/min/1.73 m2 (early CKD group consisting of stage 1, 2, and 3a CKD), and 36 participants in the late diabetic CKD group with a mean eGFR of 23.9 mL/min/1.73 m2 (late CKD group, consisting of stage 3b, 4, and 5), P<.001. We have successfully obtained DNA for methylation and microbiome analyses using the biospecimens collected via this protocol and are currently analyzing these results together with the metabolome of this cohort of individuals with diabetic CKD. Recent advances have improved our understanding of the epigenome, metabolomics, and the influence of the gut microbiome on the incidence of diseases such as cancers, particularly those related to environmental exposures. However, there is a paucity of literature surrounding these influencers in renal disease. This study will provide insight into the fundamental understanding of the pathophysiology of CKD in individuals with diabetes, especially in novel areas such as epigenetics, metabolomics, and the kidney-gut axis. DERR1-10.2196/16277.
URI: https://ahro.austin.org.au/austinjspui/handle/1/23918
DOI: 10.2196/16277
ORCID: 0000-0002-1960-2242
0000-0001-9713-7211
0000-0003-2372-395X
0000-0002-4376-9720
0000-0002-9510-4181
Journal: JMIR Research Protocols
PubMed URL: 32734931
ISSN: 1929-0748
Type: Journal Article
Subjects: chronic kidney disease
diabetes
epigenetics
gut microbiome
metabolomics
Appears in Collections:Journal articles

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