Identification of potential biomarkers for predicting the early onset of diabetic cardiomyopathy in a mouse model

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dc.contributor.authorJohnson, R.
dc.contributor.authorNxele, X.
dc.contributor.authorCour, M.
dc.contributor.authorSangweni, N.
dc.contributor.authorJooste, T.
dc.contributor.authorHadebe, N.
dc.contributor.authorSamodien, E.
dc.contributor.authorBenjeddou, M.
dc.contributor.authorMazino, M.
dc.contributor.authorLouw, J.
dc.contributor.authorLecour, S.
dc.contributor.departmentRabia Johnson: Biomedical Research and Innovation Platform (BRIP), South African Medical Research Councilen_US
dc.date.accessioned2023-04-17T12:58:44Z
dc.date.available2023-04-17T12:58:44Z
dc.date.epub2020-07-23
dc.date.issued2020-07-23
dc.description.abstractType 2 diabetes (T2D) is characterized by metabolic derangements that cause a shift in substrate preference, inducing cardiac interstitial fibrosis. Interstitial fibrosis plays a key role in aggravating left ventricular diastolic dysfunction (LVDD), which has previously been associated with the asymptomatic onset of heart failure. The latter is responsible for 80% of deaths among diabetic patients and has been termed diabetic cardiomyopathy (DCM). Through in silico prediction and subsequent detection in a leptin receptor-deficient db/db mice model (db/db), we confirmed the presence of previously identified potential biomarkers to detect the early onset of DCM. Differential expression of Lysyl Oxidase Like 2 (LOXL2) and Electron Transfer Flavoprotein Beta Subunit (ETFβ), in both serum and heart tissue of 6-16-week-old db/db mice, correlated with a reduced left-ventricular diastolic dysfunction as assessed by high-resolution Doppler echocardiography. Principal component analysis of the combined biomarkers, LOXL2 and ETFβ, further displayed a significant difference between wild type and db/db mice from as early as 9 weeks of age. Knockdown in H9c2 cells, utilising siRNA of either LOXL2 or ETFβ, revealed a decrease in the expression of Collagen Type I Alpha1 (COL1A1), a marker known to contribute to enhanced myocardial fibrosis. Additionally, receiver-operating curve (ROC) analysis of the proposed diagnostic profile showed that the combination of LOXL2 and ETFβ resulted in an area under the curve (AUC) of 0.813, with a cut-off point of 0.824, thus suggesting the favorable positive predictive power of the model and further supporting the use of LOXL2 and ETFβ as possible early predictive DCM biomarkers.en_US
dc.description.sponsorshipThe work reported herein was made possible through funding by the South Africa Medical Research Council’s Biomedical Research and Innovation Platform baseline funding as well as Division of Research Capacity Development Internship Scholarship and Intra-mural Post-doctoral Program, South African Rooibos Council and the National Research Foundation (NRF) Thuthuka Programme Grant 107261. NRF echocardiograph large equipment Grant at the University of Cape Town. We would like to thank Charna Chapman, Desmond Linden, Samira Ghoor, Ruzayda van Aarde and Joritha van Heerden for technical support.en_US
dc.identifier.citationJohnson R, Nxele X, Cour M, et al. Identification of potential biomarkers for predicting the early onset of diabetic cardiomyopathy in a mouse model. Sci Rep. 2020 Jul 23;10(1):12352.en_US
dc.identifier.doi10.1038/s41598-020-69254-x
dc.identifier.journalScientific Reportsen_US
dc.identifier.urihttps://www.nature.com/articles/s41598-020-69254-x
dc.identifier.urihttps://infospace.mrc.ac.za/handle/11288/595307
dc.language.isoenen_US
dc.publisherNature Publishing Groupen_US
dc.research.unitBiomedical Research and Innovation Platformen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectBiomarkersen_US
dc.subjectDiabetic cardiomyopathyen_US
dc.subjectMouse modelen_US
dc.subjectBlooden_US
dc.subjectAnimalsen_US
dc.subjectMiceen_US
dc.subjectDiabetesen_US
dc.titleIdentification of potential biomarkers for predicting the early onset of diabetic cardiomyopathy in a mouse modelen_US
dc.typeArticleen_US
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