Assessment of cardiac autonomic neuropathy (CAN) in Type I diabetic mice

Diabetic cardiovascular autonomic neuropathy (DCAN) is common in patients with diabetes mellitus, and causes abnormalities in heart rate control as well as central and peripheral nervous system dynamics. A good understanding of DCAN is not established yet. An effective way to detect diabetes mellitus at an early stage is still undiscovered, which method is highly desired by researchers and patients. One reason why the pathogenesis of DCAN is unclear is that non- invasive assessment of DCAN in humans and animals has been problematic. The non-stationary and non- linear natures of the interested physiological signals have placed great limitation on traditionally algorithms. To overcome this limitation, this work proposes a series of time- varying, nonlinear and non-invasive methods to assess cardiac autonomic dysregulation from ECG and PPG records. Including a non-stationary method called PDM, which is based on principal dynamic mode (PDM) analysis of heart rate variability (HRV), nonstationary power spectral density called TVOPS-VFCDM and also standard spectrum analysis method of HRV. We are also able to study and analyze a series of long term and short term ECG and PPG data. In a pilot study, ECG was measured via telemetry in conscious 4 month old C57/Bl6 controls and in Akita mice, a model of insulin- dependent type I diabetes, while PPG was measured via tail pulse oximetry system from 2 month old to 4 month old. The results indicate significant cardiac autonomic impairment in the diabetic mice in comparison to the controls at 4 month old and such impairment start to present at 3 month old. Further, both immunohistochemistry and Western blot analyses show a reduction in nerve density in Akita mice as compared to the control mice, thus, corroborating our data analysis records