Discovery and clinical translation of novel glaucoma biomarkers

Abstract

Glaucoma and other optic neuropathies are characterized by progressive dysfunction and loss of retinal ganglion cells and their axons. Given the high prevalence of glaucoma-related blindness and the availability of treatment options, improving the diagnosis and precise monitoring of progression in these conditions is paramount. Here we review recent progress in the development of novel biomarkers for glaucoma in the context of disease pathophysiology and we propose future steps for the field, including integration of exploratory biomarker outcomes into prospective therapeutic trials. We anticipate that, when validated, some of the novel glaucoma biomarkers discussed here will prove useful for clinical diagnosis and prediction of progression, as well as monitoring of clinical responses to standard and investigational therapies.

Keywords: Axonal degeneration; Glaucoma; Nerve fiber layer; Retinal ganglion cell; Retinal imaging.

Fig. 1.

Schematic model of RGC injury and recovery. RGCs may enter a ‘comatose’ state, where functional impairment occurs following cellular insults in glaucoma. Relief of RGC stress may allow for RGC functional recovery, however injuries of a sufficient magnitude, duration or quantity may trigger irreversible cell death. Figure and legend reproduced with permission from Elsevier (Fry et al., 2018).

Fig. 2.

Punctate backscattering/reflectivity changes in the innermost surface of the RNFL in a healthy control as seen in confocal reflectance adaptive optics ophthalmoscopy images captured a few seconds apart. Scale bar, 50 μm.

Fig. 3.

The sdOCT results for an eye with widespread cpRNFL damage. (A) An image from a circumpapillary scan. (B) The cpRNFL thickness plot (black, magenta, and light blue curve). The SVZ is shown as the green line. (C) An en-face slab image of the 9 * 12 mm scan. (D) An en-face slab image of a 3 * 3 mm scan of disc. (E) AO-SLO image. The yellow and white arrows are approximately the same locations in panels (C), (D), and (E). Figure and legend reproduced with permission and modified from Elsevier (Hood et al., 2017).

Fig. 4.

Structural brain MRI in early and advanced glaucoma. (A, B) Anatomical MRI of the intraorbital optic nerve (A) and optic chiasm (B) in sagittal view (left) and coronal view (right) at the level of the green or red slab. (C–F) Zoomed images of the intraorbital optic nerve (green arrows) (C, D) and optic chiasm (red arrows) (E, F) from the blue boxes in A, B in early E) and advanced glaucoma (D, F). Note the reduction in size in both structures as the disease progresses. Figure and legend reproduced with permission and modified from Wolters Kluwer - Medknow Publications (Kasi et al., 2019).

Fig. 5.

(A) RGC-type specific lamination patterns in the ON- and OFF- sublaminae. (B) Dendritic rearrangements of OFF-transient RGCs have been implicated as among the earliest responses to elevated IOP in mice. Figure and legend reproduced with permission and modified from Society for Neuroscience (El-Danaf and Huberman, 2015).

Fig. 6.

IPL reflectivity maps captured using near infrared OCT in a normal control, a few minutes apart. The changes in intensity near the foveal pit and the top left quadrant suggest that poor repeatability might limit the potential for using IPL intensity in OCT images as a glaucoma biomarker. Scale bar, 1 mm.

Fig. 7.

Visible light OCT cross-sectional images reveal a reflectivity pattern corresponding to inner plexiform layer (IPL) lamination in humans (A) and mice (B). Cell-type specific lamination patterns previously described for ON- and OFF-RGC sublaminae correspond well with the reflectivity pattern (C).

Fig. 8.

DARC counts are increased in affected glaucoma patients compared to healthy controls. ANX776 injections revealed single neuronal cell apoptosis in the retina of study subjects. Representative retinal images are shown from glaucoma patients following intravenous injections of 0.4 (A and B), 0.2 (C and D) and 0.5 (E and F) mg ANX776 at 240 min. Panels show unmarked (A, C and E) and marked (B, D and F) ANX776-positive spots with yellow rings highlighting individual spots. DARC counts were defined as new, unique individual ANX776-labeled spots, at their first appearance in the retina. Analysis of DARC counts in glaucoma and healthy controls for each ANX776 dosing cohort showed that at each dose, the number of DARC spot counts was consistently higher in glaucoma patients compared to healthy controls, and this reached significance at the 0.4 mg (P < 0.005) dose (G). The spread of the individual data points is shown in Tukey’s box plots (G). Horizontal lines indicate medians and interquartile ranges with the continuous line across doses showing the means. Asterisks indicate the level of significance by Bonferroni multiple comparison test between groups (P < 0.01) with two-way ANOVA across the doses showing a significant effect of glaucoma status (P = 0.0033) and time point (P = 0.0011). Multivariable analysis indicated that the total DARC count across 6 h was 2.37-fold higher in patients with glaucoma (95% CI: 1.4–4.03, P = 0.003) at any dose. Different fluorescent intensity profiles were seen for individual labeled spots (H–P). Low (I, K, M and O) and high (J, L, N and P) magnification (scale bars indicated) retinal images at different time points are shown from the same patient as in A at baseline (I and J, 0 min), 60 (K and L), 120 (M and N) and 240 (O and P) min. Marked, colour-coded spots are shown in adjacent panels (J, L, N and P) with fluorescent intensity profiles illustrated in H, identified by corresponding coloured lines. Figure and legend reproduced with permission from Oxford University Press (Cordeiro et al., 2017).

Fig. 9.

(A) Original C-mode of adaptive optics OCT taken from a 56-year-old Caucasian woman with glaucoma. (B) Automated segmentation of the corresponding slice, with the beams labeled in green and pores in red. (C) 3D view en-face of the LC beams. (D) rotated 3D view of the same LC beams. Figure and legend reproduced with permission from Elsevier (Dong et al., 2017).

Fig. 10.

Densely packed macular INL micro cystoid spaces (red arrows) in a primary open-angle glaucoma patient as seen with non-confocal split-detection AO ophthalmoscopy. The scale bar is 100 μm across. This retinal area, highlighted as a red square in the wider field of view image (top right), shows early signs of vision loss as illustrated by the superimposed visual field test results. The stimulus locations and size are shown by the black circles (24-2 visual field test points, Goldmann III), with the color denoting deviation from normal on the total deviation map (green ≤4 points, yellow 4–12 points and red ≥12 points).

Fig. 11.

Sparse INL micro cystoid spaces in a primary open-angle glaucoma patient as seen with non-confocal split-detection adaptive optics ophthalmoscopy, with its location highlighted in red in the wider field of view image (bottom left). The scale bar is 100 μm across. These micro cystoid spaces have irregular shapes and sizes as large as 40 μm, which is substantially larger than the bodies of cells in this layer (see legend box).

Fig. 12.

INL microcystoid spaces progression (black circle) and regression (yellow ellipse) in a glaucoma patient over a four-week period, as seen with non-confocal split-detection adaptive optics ophthalmoscopy. Scale bar, 100 μm.

Fig. 13.

(A) Schematic illustration of stimulus array used to measure increment responses (left panel) and decrement responses (right panel). Array elements are scaled to account for cortical magnification. (B) Scalp topography of the most reliable response component is similar for increments (left panel) and decrements (right panel). Components measured using Reliable Components Analysis (Dmochowski et al., 2015). (C) Waveform of the most reliable component evoked by 2.7 Hz incremental (left) or decremental (right) sawtooth waveforms. Response to decrements is larger than for increments (n = 14; healthy 18–22 age observers).