The superoxide dismutase 1 knock out (SOD1 KO) mouse develops age-dependent auto reactivity to ocular antigens

Abstract

Purpose : We have evidence that sera from AMD patients exhibit increased levels of auto-antibodies (AAbs) against macular antigens (PLOS One 2015; 10:e0145323). Here we have tested the hypothesis that the SOD1 KO mouse model, analogously to patients with AMD, develops an age-dependent increase in auto-reactivity against ocular antigens, and that this phenotype develops earlier and more severely in the SOD1/APOE double knock out (DKO) on high fat diet (HFD).

Methods : Wild type (WT), SOD1 KO and DKO mice were aged up to 14 months. For the WT, and the DKO genotypes a subgroup of animals were maintained on HFD for 3 months before collection of sera and ocular tissues. At 9, 12, and 14 months sera and ocular tissues were collected for all animal groups. Sera were used to test for auto reactivity against a pool of ocular proteins from WT mice. Autoreactive bands were detected by immunoblotting and fluorescence imaging.

Results : Our preliminary data suggest that the SOD1 KO and the DKO exhibit similar, increased autoreactivities against ocular antigens starting at 9 months of age as compared to WT. We found no significant differences in the number of detected autoreactive bands between animals kept on regular diet as compared to animals on HFD. The strongest autoreactivity was observed against ocular antigens in the 17 to 35 kDa molecular weight range.

Conclusions : We have obtained preliminary evidence that animals with impaired antioxidative defense mechanisms display an age-dependent increase in autoreactivity against ocular antigens. The observed phenotype was not worsened in the DKO on HFD, suggesting that oxidative stress might play a more prominent role in AMD than impaired lipid metabolism and/or diet. Further investigation of our animal models will focus on the characterization of other retinal phenotypic differences and on identification of the ocular proteins targeted by the AAbs.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.