歯学ジャーナル
オープンアクセス

概要

Inner Retinal Layers as Biomarkers of Disease in Patients with Mild Cognitive Impairment

Demirtzoglou Iordanis*, Tsolaki Magda, Gougoulias Kyriakos, Oikonomidis Panagiotis, Karampatakis Vasileios

Purpose: To investigate whether inner retinal thickness can be used as a reliable biomarker in patients with mild cognitive impairment (MCI) for early diagnosis and correlate these changes with cognitive decline.

Material and methods: Using spectral domain optical coherence tomography (SD-OCT) in MCI and control subjects we assess peripapillary Retinal Nerve Fiber Layer (RNFL) thickness, macular thickness and volume and macular Ganglion Cell Complex (mGCC was defined as the combination of retinal fiber, ganglion cell and inner plexiform layers) thickness, Ganglion Cell Complex Global Volume Loss (GCC GVL%) and Ganglion Cell Complex Focal Volume Loss (GCC FVL%). We assessed cognitive function using Mini Mental State Examination (MMSE) score. A database was created with the use of the Statistical Program for Social Sciences (SPSS® ver12). Descriptive Statistics were utilized to find means, medians, standard deviations and interquantile ranges. Statistical significance was set to 95%. Independent t-tests were used to compare means between patients and control group when variables reached normal distribution. Mann-Whitney U test was used to compare medians between patients and control group when variables did not reach normal distribution.

Results: In MCI patients there was found a statistically significant decrease in overall RNFL thickness (Mann-Whitney test, p: 0.009) and temporal RNFL thickness (T-test, p: 0.013) and increased macular GCC FVL% (Mann-Whitney test, p: 0.001) compared to the controls. There was found no significant correlation between retinal thickness and cognitive decline in MCI patients.

Conclusion: Our study showed decreased inner retinal thickness in MCI patients. The potential use of inner retina thickness as a reliable biomarker in early diagnosis needs to be further explored in longitudinal studies with large cohorts.