Abstract
PurposeTo determine the relationship between longitudinal in vivo measurements of retinal nerve fiber layer thickness (RNFLT) and retinal ganglion cell (RGC) density after unilateral optic nerve transection (ONT).MethodsNineteen adult Brown-Norway rats were studied; N = 10 ONT plus RGC label, N = 3 ONT plus vehicle only (sans label), N = 6 sham ONT plus RGC label. RNFLT was measured by spectral domain optical coherence tomography (SD-OCT) at baseline then weekly for 1 month. RGCs were labeled by retrograde transport of fluorescently conjugated cholera toxin B (CTB) from the superior colliculus 48 hours prior to ONT or sham surgery. RGC density measurements were obtained by confocal scanning laser ophthalmoscopy (CSLO) at baseline and weekly for 1 month. RGC density and reactivity of microglia (anti-Iba1) and astrocytes (anti-GFAP) were determined from post mortem fluorescence microscopy of whole-mount retinae.ResultsRNFLT decreased after ONT by 17% (p<0.05), 30% (p<0.0001) and 36% (p<0.0001) at weeks 2, 3 and 4. RGC density decreased after ONT by 18%, 69%, 85% and 92% at weeks 1, 2, 3 and 4 (p<0.0001 each). RGC density measured in vivo at week 4 and post mortem by microscopy were strongly correlated (R = 0.91, p<0.0001). In vivo measures of RNFLT and RGC density were strongly correlated (R = 0.81, p<0.0001). In ONT- CTB labeled fellow eyes, RNFLT increased by 18%, 52% and 36% at weeks 2, 3 and 4 (p<0.0001), but did not change in fellow ONT-eyes sans CTB. Microgliosis was evident in the RNFL of the ONT-CTB fellow eyes, exceeding that observed in other fellow eyes.Conclusions In vivo measurements of RNFLT and RGC density are strongly correlated and can be used to monitor longitudinal changes after optic nerve injury. The strong fellow eye effect observed in eyes contralateral to ONT, only in the presence of CTB label, consisted of a dramatic increase in RNFLT associated with retinal microgliosis.
Highlights
Glaucoma is the most common optic neuropathy and is the second leading cause of blindness worldwide [1]
We have developed methods for in vivo assay of axonal transport in retinal ganglion cell (RGC) based on confocal scanning laser ophthalmoscopy (CSLO) imaging of a fluorescent tracer and have begun to apply the techniques in conjunction with spectral domain optical coherence tomography (SD-optical coherence tomography (OCT)) imaging to study experimental models of optic nerve injury [26,39]
retinal nerve fiber layer thickness (RNFLT) decreased steadily in the weeks after optic nerve transection (ONT), somewhat surprisingly, there was a substantial increase in RNFLT in the fellow eye during the second, third and fourth weeks of post-operative follow-up
Summary
Glaucoma is the most common optic neuropathy and is the second leading cause of blindness worldwide [1]. Though intraocular pressure (IOP) is the most important treatable risk factor and currently the only target for treatment, the mechanisms by which IOP damages optic nerve axons remain unclear [2,3]. Experimental models of glaucoma are critical for elucidating details of pathophysiological mechanisms as well as for testing new avenues of therapy. Experimental models of glaucoma are commonly based on elevated IOP, often induced unilaterally, for example in non-human primates or rodents; or in the case of heritable models such as the DBA/2J mouse, IOP becomes chronically elevated in both eyes during the course of aging [4,5,6,7,8,9]. Common outcome measures for experimental glaucoma models include anatomical counts of retinal ganglion cell (RGC) soma and/or orbital optic nerve axons, which require sacrifice of the animal for histological processing. The ability to visualize RGCs in vivo has raised the possibility of longitudinal evaluation within animals, which could help to both reduce the number of animals required to adequately power a scientific study (instead of sacrificing a different set of animals at each time point) and to minimize the possibility of errors arising when inferences about longitudinal time course and inter-relationships are drawn from cross-sectional data [10,11,12,13]
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