Abstract
Purpose :
To evaluate inner- and outer-retina dysfunction in the 5xFAD mouse model of Alzheimer’s disease using the full-field electroretinogram (ERG).
Methods :
Dark- and light-adapted flash ERGs were recorded from 11 5xFAD transgenic mice and 9 wild-type (WT) mice at 3 months of age. Dark-adapted ERGs were recorded after 2 hours of dark adaptation in response to achromatic flashes of 0.01 to 25 cd-s-m2. Light-adapted ERGs were obtained for the same flash luminances against a 30 cd/m2 adapting field. Amplitude and implicit time (IT) of the a- and b-waves were calculated according to convention. Oscillatory potentials (OPs) were extracted from the responses by bandpass filtering; the amplitude and IT of the three resulting OPs were summed to provide a single measure of OP amplitude and IT. In addition, the amplitude and IT of the photopic negative response (PhNR), a measure of inner-retina function, was extracted from the light-adapted recordings.
Results :
Two-way repeated measures analysis of variance (ANVOA) indicated significant differences between the groups (WT vs. 5xFAD) in dark-adapted OP timing (F = 7.31, p = 0.015) and PhNR amplitude (F = 20.40, p < 0.001). Pairwise comparisons indicated that the dark-adapted OP IT was delayed significantly for luminances of 0.10 cd-s-m2 and higher. Similarly, pairwise comparisons indicated that the PhNR amplitude was reduced significantly for luminances of 3.0 cd-s-m2 and higher. No other statistically significant differences between groups were observed, but there was a marginally significant reduction in b-wave amplitude for the 5xFAD group compared to the WT group under dark-adapted conditions (F = 3.46; p = 0.079).
Conclusions :
Photoreceptor and bipolar cell function appear to be less affected than measures of inner-retina function in the 5xFAD mouse model of Alzheimer’s disease. These findings are consistent with previously reported pattern ERG deficits in 5xFAD mice, indicating that inner-retina dysfunction may be an early marker of Alzheimer’s disease.
This is a 2020 ARVO Annual Meeting abstract.