Data Sheet 2_Investigating the biomarkers of diabetic-cardiomyopathy with the high mobility group box-1 as a potential anti-inflammatory therapeutic target: Systematic Review and meta-analysis.pdf

AimThe aim was to carry out a preliminary investigation to identify new biomarkers and test the suitability of the pro-inflammatory nuclear protein, HMGB1, as a potential diagnostic or treatment target for DCM.
BackgroundDiabetic cardiomyopathy (DCM) is a complex metabolic disease group which manifests in persons diagnosed with poorly managed Diabetes mellitus. This study investigates whether HMGB1 is capable of attenuating the inflammation that manifests from DCM in pre-clinical models of mouse and rat combined.
MethodologyA systematic review and a meta-analysis were performed by searching 5 electronic databases and retrieving 2979 articles from which 29 qualified as included studies for reporting 37 biomarkers that were grouped into 8 preclinical DCM biomarker models. The standardized mean difference (SMD or the effect size), non-parametric Mann Whitney U test, ROC, correlation coefficient and coefficient of determination were carried out in this evaluation.
Results28 heterogeneous proinflammatory biomarkers were identified as carrying a significantly high risk of developing DCM out of the total of 37 biomarkers evaluated in forest plots in which, the highest SMD was produced by cardiac troponin (CTPN). 8 significantly high biomarkers (HMGB1, HW/BW, EF%, FS%, BG, TC, TG, NF-kB) were identified out of 37 in the non-parametric Mann Whitney U test in the DCM group compared to the HC. The correlation coefficient between HMGB1 as the independent variable produced a significant negative (ecological) correlation with HR, EF% and TLR4 at p < 0.05.
ConclusionThe ability of HMGB1 in downregulating inflammation or the direct inhibition of HMGB1 using small molecules or blocking of HMGB1/TLR4/NF-kB signalling pathway could be a novel potential mechanism to resolving DCM which requires further investigations.
Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42024597641.