Identification of potential biomarkers for predicting the early onset of diabetic cardiomyopathy
Type 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 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 identified a biomarker profile that could potentially detect the early onset of DCM. Differential expression of Lysyl Oxidase Like 2 (LOXL2) and Mitochondria protein dehydrogenase (MPD), in both serum and heart tissue of 6-16-week-old db/db mice, confirmed cardiac dysfunction and correlated with a reduced LVDD as assessed by high-resolution Doppler echocardiography.
Principal component analysis of the combined biomarkers, LOXL2 and MTB, further displayed a significant difference between wild type and db/db mice from as early as 9 weeks of age. Knockdown experiments, utilising siRNA of either LOXL2 or MTB, revealed a decrease in the expression of Collagen Type I Alpha1 (COL1A1), a marker that contributes to enhanced myocardial fibrosis. Additionally, receiver-operating curve (ROC) analysis of the proposed diagnostic profile showed that the combination of LOXL2 and MTB resulted in an area under the curve (AUC) of 0.813, with a cutoff point of 0.824, suggesting the favorable positive predictive power of the model and further supporting the use of LOXL2 and MTB as possible early predictive DCM biomarkers.
In conclusion, we propose that the identified genes might be able to detect DCM asymptomatically and a follow up study is required using human serum with established DCM to confirm such findings.