CEREBRAL VASOREGULATION IN DIABETES

这个子项目是众多研究子项目之一

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The goal of this study is to assess the impact of diabetic autonomic neuropathy with orthostatic hypotension (OH) on cerebral vasoregulation and determine the factors indicative of silent cerebrovascular disease in diabetes. OH is the most severe feature of autonomic neuropathy and increases the risk for stroke. To quantify the effects of diabetic autonomic neuropathy with OH on cerebral vasoregulation, a comparative experimental study will evaluate vasomotor reactivity of cerebral arteries using transcranial Doppler (TCD) ultrasonography in non-randomized diabetic patients with and without OH and 40 non-diabetic controls. Cerebral vasoregulation will be measured from blood flow velocities measured by TCD during hypo- and hypercapnia, tilt-up and rapid blood pressure changes. The range of effective vasoregulation will be determined to identity the OH patients who might be at risk for hypoperfusion during orthostatic stress if vasoregulation fails or blood pressure declines below autoregulated range. An arterial spin labeling (ASL) will be used, as well as a T2 weighted (FLAIR) MRI at 3 Tesla to determine and quantify the distribution of white matter changes (WMC) in diabetic autonomic neuropathy with OH indicative of silent hypoperfusion. Models will be developed distinguishing OH-associated WMC on MRI from non-specific age-related changes, based on indices of cerebral vasoregulation adjusting for blood pressure decline during tilt and clinical factors. Data obtained from subjects who complete the study will be analyzed per protocol. This study may have potential clinical impact and it may help to identify the population of elderly diabetic patients at risk for stroke.