September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
A comparison of retinal layer changes in diabetic mouse models using spectral-domain optical coherence tomography (SDOCT)
Author Affiliations & Notes
  • Justin Elstrott
    Biomedical Imaging, Genentech, South San Francisco, California, United States
  • Yann Malato
    Translational Immunology, Genentech, South San Francisco, California, United States
  • Tom Truong
    Translational Immunology, Genentech, South San Francisco, California, United States
  • Menno Van Lookeren Campagne
    Immunology, Genentech, South San Francisco, California, United States
  • Brent McKenzie
    Translational Immunology, Genentech, South San Francisco, California, United States
  • Robby Weimer
    Biomedical Imaging, Genentech, South San Francisco, California, United States
  • Footnotes
    Commercial Relationships   Justin Elstrott, Genentech (E); Yann Malato, Genentech (E); Tom Truong, Genentech (E); Menno Van Lookeren Campagne, Genentech (E); Brent McKenzie, Genentech (E); Robby Weimer, Genentech (E)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 2192. doi:
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    • Get Citation

      Justin Elstrott, Yann Malato, Tom Truong, Menno Van Lookeren Campagne, Brent McKenzie, Robby Weimer; A comparison of retinal layer changes in diabetic mouse models using spectral-domain optical coherence tomography (SDOCT). Invest. Ophthalmol. Vis. Sci. 2016;57(12):2192.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Robust, preclinical models of diabetic retinopathy are essential for the development of new therapies. In humans, diabetic retinopathy (DR) is induced by a hyperglycemic environment combined with hypoxic-ischemic conditions that result in changes of the thickness of specific retina layers. Here we use high resolution SDOCT to compare the in vivo effects of hypoxia and common carotid artery (CCA) ligation on segmented retinal layer thicknesses in control and diet-induced obesity (DIO) mouse models.

Methods : 7 week old male C57Bl6J mice were given normal chow and water (control group) or high fat chow (60% kcal from fat) and 50% glucose water ad libitum (DIO group) for 25 weeks prior to imaging. The right eyes of anesthetized mice were imaged using a high-resolution Envisu SDOCT system (Leica, 1000x100x5 pixel scan, 1.8x1.8 mm field, 1 µm axial resolution) before and after CCA ligation and/or 7-14 days in hypoxic conditions (9-10% O2). The five B-scans were registered and averaged for each mouse, and the retinal layers were automatically segmented providing 8 layer measurements (Leica Diver software).

Results : DIO mice have thinner overall retinas compared to control mice (222.1±1.5 vs 217.2±1.6 µm, mean±95% CI, p<0.05, N=8 control, 14 DIO). 7 days exposure to 9% O2 hypoxia thickened the retinal nerve fiber layer (RNFL) in DIO mice, with even greater thickening after 14 days exposure (20.3±0.8 vs 22.3±1.0 vs 24.2±0.8 µm , p<0.05, N=14 baseline DIO, 14 7d hypoxia DIO, 12 14d hypoxia DIO). Conversely, the outer segment (OS) of the photoreceptor layer was thinner in DIO mice after 7d hypoxia compared to baseline (31.0±0.9 vs 27.8±0.5 µm, p<0.05, N=14 baseline DIO, 14 7d hypoxia DIO). Lastly, 14 days of 9% O2 hypoxia alone caused similar overall reductions in total retinal thickness in DIO mice as 14 days of 10% O2 hypoxia with CCA ligation (217.2±2.3 vs 209.5±2.7 vs 212.5±3.2 µm , p<0.05, N=9 baseline DIO, 12 9% O2 hypoxia DIO, 10 10% O2 hypoxia + CCA ligation DIO).

Conclusions : The DIO retinas are thinner overall compared to controls and more sensitive to hypoxia and CCA ligation. Hypoxia thickens the nerve fiber layer while thinning other layers, especially the photoreceptor layers. 9% hypoxia alone showed similar effects as 10% hypoxia + CCA ligation. Future studies will determine whether these deficits can be rescued with therapeutic interventions.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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