Retinal Microperimetry: A New Tool for Identifying Patients With Type 2 Diabetes at Risk for Developing Alzheimer Disease.
Andreea CiudinOlga Simó-ServatCristina HernándezGabriel ArcosSusana DiegoÁngela SanabriaÓscar SotolongoIsabel HernándezMercè BoadaRafael SimòPublished in: Diabetes (2017)
Type 2 diabetes is associated with a high risk of cognitive impairment and dementia. Therefore, strategies are needed to identify patients who are at risk for dementia. Given that the retina is a brain-derived tissue, it may provide a noninvasive way to examine brain pathology. The aims of this study were to evaluate whether retinal sensitivity 1) correlates with the specific parameters of brain imaging related to cognitive impairment and 2) discriminates patients with diabetes with mild cognitive impairment (MCI) from those with normal cognition and those with Alzheimer disease (AD). For this purpose, a prospective, nested case-control study was performed and included 35 patients with type 2 diabetes without cognitive impairment, 35 with MCI, and 35 with AD. Retinal sensitivity was assessed by Macular Integrity Assessment microperimetry, and a neuropsychological evaluation was performed. Brain neurodegeneration was assessed by MRI and fludeoxyglucose-18 positron emission tomography (18FDG-PET). A significant correlation was found between retinal sensitivity and the MRI and 18FDG-PET parameters related to brain neurodegeneration. Retinal sensitivity was related to cognitive status (normocognitive > MCI > AD; P < 0.0001). Our results suggest that retinal sensitivity assessed by microperimetry is related to brain neurodegeneration and could be a useful biomarker for identifying patients with type 2 diabetes who are at risk for developing AD.
Keyphrases
- mild cognitive impairment
- positron emission tomography
- cognitive impairment
- diabetic retinopathy
- optical coherence tomography
- cognitive decline
- white matter
- resting state
- computed tomography
- pet ct
- type diabetes
- optic nerve
- pet imaging
- functional connectivity
- cerebral ischemia
- multiple sclerosis
- newly diagnosed
- end stage renal disease
- magnetic resonance
- adipose tissue
- mass spectrometry
- metabolic syndrome
- prognostic factors
- clinical evaluation