Introduction: The aim of this study was to describe the design and the participants’ baseline characteristics of a prospective natural history study of geographic atrophy (GA) secondary to age-related macular degeneration. Methods: The optical coherence tomography (OCT) and microperimetry biomarker evaluation in patients with GA (OMEGA) study was conducted at a tertiary referral center (ClinicalTrials.gov identifier: NCT05963646). Participants were followed for 12 months during 4 visits (baseline and follow-up exams at weeks 12, 24, and 48) with best-corrected Early Treatment of Diabetic Retinopathy Study visual acuity, low-luminance visual acuity (LLVA), and quick contrast sensitivity function testing. Further, participants underwent spectral-domain OCT, OCT angiography, fundus autofluorescence imaging, and mesopic microperimetry testing. Results: Thirty participants (median [IQR] age of 79 [77, 84] years) and 37 study eyes were included with a (median [IQR]) GA area of 1.40 mm2 (0.49, 5.24) at baseline. Out of 37 study eyes, six developed macular neovascularizations (16%). The study-eye best-corrected visual acuity was (median [IQR]) 0.18 logarithm of the minimum angle of resolution (logMAR) (0.06, 0.26), LLVA 0.66 logMAR (0.36, 0.88), and the microperimetry mean sensitivity 18.4 dB (9.21, 20.9). The highest correlation between square root GA area and a visual function test was evident for LLVA (R2 of 0.578), followed by area under the log contrast sensitivity function curve (0.519) and microperimetral retinal sensitivity (0.487). Conclusion: This report lays out the design and baseline characteristics of the OMEGA study, which aims to contribute to the understanding of the natural history of GA. The OMEGA study will provide estimates of the ability to detect change and retest reliability for a panel of structure and functional assessments.

Geographic atrophy (GA), the nonexudative late-stage manifestation of age-related macular degeneration (AMD), is among the leading causes of irreversible blindness in the developed world [1]. GA is characterized by progressive loss of photoreceptors, choriocapillaris, and retinal pigment epithelium. GA lesions mostly form initially in the parafovea, sparing the fovea itself [2, 3]. Eventually, the foci of GA expand and involve the fovea. This results in a marked loss of best-corrected visual acuity (BCVA) and impairment of daily activities, including driving, reading, and recognizing faces [4, 5].

To date, no therapy with a (demonstrated) patient-relevant treatment effect, such as preservation or improvement in BCVA, is available for GA. The US Food and Drug Administration has recently approved intravitreal pegcetacoplan and avacincaptad pegol for slowing GA progression. Despite slowing GA progression in fundus autofluorescence (FAF) imaging, both drugs yet failed to improve BCVA [6‒9]. It is unclear whether this lack of concordance between the structure and function is attributable to the selection of visual function tests or the nonefficaciousness of the drugs. The former possibility highlights the need for a more refined understanding of the ability to detect change of visual function tests in GA [6‒9].

Previously applied visual function tests in AMD include BCVA, low-luminance visual acuity (LLVA) [10], and microperimetry (i.e., fundus-controlled perimetry) testing [11]. In terms of imaging, FAF-delineated GA is the predominantly used endpoint in clinical trials [4, 12]. Recently, a panel of candidate structural and functional endpoints became available that might improve the ability to detect change. This includes quick contrast sensitivity function (qCSF) testing [13]. Future candidate endpoints include refined microperimetry paradigms such as patient-tailored perimetry [14] or perilesional sensitivity loss [15‒17] and new structural endpoints such as the change in perilesional photoreceptor integrity [18‒20]. In addition, optical coherence tomography angiography (OCTA)-based outcome measure might provide insight into early changes driving GA progression [21].

The current OCT and microperimetry biomarker evaluation in patients with GA (OMEGA) study aimed to systematically compare a multimodal panel of established and novel visual function and structural outcome measures for monitoring GA progression. These may provide insights into GA pathophysiology to facilitate the assessment of the safety and efficacy of upcoming treatments.

Participants

This prospective, natural history study was performed at a tertiary referral center (University Hospital Basel, P.I.: Prof. Dr. med. Hendrik P.N. Scholl, ClinicalTrials.gov identifier: NCT05963646). Thirty participants were recruited between March 2021 and July 2022. In patients with two eligible eyes (n = 7), both eyes were included, leading to a total of 37 study eyes. The study was approved by the Ethics Committee (BASEC ID: 2019-02003 [https://raps.swissethics.ch/]) and adhered to the Declaration of Helsinki. All participants were informed of the study’s nature and gave written informed consent before study-related examinations. This study included a baseline visit and follow-up visits at weeks 12, 24, and 48.

Main inclusion criteria were (1) well-demarcated GA areas detected in autofluorescence imaging, which were secondary to AMD. No evidence of prior or active macular neovascularization in at least one eye, (2) in individuals older than 60 years, (3) with one focus of GA having a diameter ≥250 µm was mandatory [22]. The ocular media had to be sufficiently clear for retinal imaging (based on the investigator’s judgment).

Exclusion criteria were evidence of monogenic macular dystrophies, e.g., late-onset Stargardt disease, cone-rod dystrophies, or toxic maculopathies. History of vitreoretinal surgery or any other interventions for AMD in the study eye were additional exclusion criteria. Online supplementary Table 1 (for all online suppl. material, see https://doi.org/10.1159/000535375) describes all inclusion and exclusion criteria. Systolic and diastolic blood pressure was measured at baseline and all follow-up visits.

Chart-Based Vision Testing

BCVA was tested using Early Treatment of Diabetic Retinopathy Study (ETDRS) charts at a distance of 4 m. In addition, we tested LLVA using a 2.0-log-unit neutral density filter [10]. Visual acuity was recorded per eye and converted to the logarithm of the minimum angle of resolution (logMAR). The low-luminance deficit was calculated by subtracting LLVA from BCVA. All exams were conducted by trained and certified BCVA examiners.

Vision-Related Quality of Life

At baseline and final visit, the 14-item National Eye Institute Visual Function Index (VF-14) was administered. Baseline scores were obtained as described before [23].

Contrast Sensitivity

CSFs were obtained with the participant’s best refraction using the qCSF method (Manifold Platform, Adaptive Sensory Technology, Lübeck, Germany). The qCSF method uses Bayesian adaptive testing to estimate the four parameters defining the participant’s CSF in a time-efficient manner [24‒26]. The test estimates a CSF curve after 25 CSF trials, generating the area under the log contrast sensitivity function curve (AULCSF), integrated from 1 to 18 cycles per degree [24‒26].

Spectral-Domain OCT and Autofluorescence Imaging

Figure 1 shows imaging and functional testing data for an exemplary patient. SD-OCT imaging of the macula was obtained with a Heidelberg Spectralis device (Heidelberg Engineering, Heidelberg, Germany) with a 20° × 20° (193 B-scans, HS mode, enhanced Automatic Real Time-Function was 16, covering an area of 6 mm × 6 mm. Short-wavelength FAF images (30° × 30°, HS mode, Automatic Real Time-Function 20) were performed using the same device.

Fig. 1.

Exemplary patient with GA. This figure shows imaging and functional testing data for an exemplary patient. a A wide field color fundus photograph. b A wide field green FAF photograph. c An OCT scan. d A 30° blue FAF. e The results of a microperimetry examination. f, g The en-face projection of the OCTA scan at the level of the superficial vascular complex and choriocapillaris.

Fig. 1.

Exemplary patient with GA. This figure shows imaging and functional testing data for an exemplary patient. a A wide field color fundus photograph. b A wide field green FAF photograph. c An OCT scan. d A 30° blue FAF. e The results of a microperimetry examination. f, g The en-face projection of the OCTA scan at the level of the superficial vascular complex and choriocapillaris.

Close modal

Image Grading

GA regions were semiautomatically annotated in FAF and infrared reflectance images (co-acquired as part of SD-OCT imaging) using the RegionFinder software (Heidelberg Engineering, Heidelberg, Germany). The software enables joint analysis of FAF and infrared reflectance images to delineate foveal sparing. Grading was performed individually by three graders per study eye. The median value of the number of foci and GA area was used for subsequent analyses [27, 28].

OCT Angiography

A PLEX Elite 9000 swept-source OCT device (Carl Zeiss Meditec AG, Jena, Germany) was used for OCTA imaging. Participants were imaged using an Angio 6 mm × 6 mm scan pattern.

Color Fundus Photography

Color fundus photography was obtained using a Clarus 700 imaging device (Carl Zeiss Meditec AG, Jena, Germany) centered on the macula.

Microperimetry

Retinal sensitivity of the posterior pole was examined using the microperimetry device MAIA (CentreVue, Padova, Italy). Microperimetry was performed with a mesopic background using a 4-2 staircase strategy and a pattern of 24 stimuli centered in the fovea and covering the central 10° degrees (in terms of diameter).

Statistical Analysis

Statistical analyses were performed in R using the add-on packages tidyverse [29], ggplot2 [30], Table 1 [31], lme4, and sjPlot [32]. Continuous demographic data were summarized in terms of the median and IQR.

Table 1.

Demographic characteristics of participants

Total (N = 30)
Age, years 
 Median (IQR) 79.0 (77.0, 84.3) 
Sex, n (%) 
 Female 14 (46.7) 
 Male 16 (53.3) 
Ethnicity, n (%) 
 Caucasian 30 (100) 
Smoking status, n (%) 
 Ex-smoker 13 (43.3) 
 Never 12 (40.0) 
 Smoker 5 (16.7) 
Diagnosis of nonstudy eyes (n = 23), n (%) 
 dAMD 1 (4.3) 
 GA 8 (34.8) 
 iAMD 5 (21.7) 
 nAMD 9 (39.1) 
Total (N = 30)
Age, years 
 Median (IQR) 79.0 (77.0, 84.3) 
Sex, n (%) 
 Female 14 (46.7) 
 Male 16 (53.3) 
Ethnicity, n (%) 
 Caucasian 30 (100) 
Smoking status, n (%) 
 Ex-smoker 13 (43.3) 
 Never 12 (40.0) 
 Smoker 5 (16.7) 
Diagnosis of nonstudy eyes (n = 23), n (%) 
 dAMD 1 (4.3) 
 GA 8 (34.8) 
 iAMD 5 (21.7) 
 nAMD 9 (39.1) 

dAMD, dry nonexsudative age-related macular degeneration; GA, geographic atrophy; iAMD, intermediate age-related macular degeneration; nAMD, neovascular age-related macular degeneration.

We applied linear mixed-effects models to assess the cross-sectional relationship of visual function tests among each other and in dependence of the square root of GA area. The patient ID was considered a random effect term. The GA area was transformed to the square root of the GA area to decrease the skew of distribution. The coefficient of determination (marginal R2 [proportion of variance explained by the fixed effects]) was computed as a unitless measure to compare the strengths of the association. The relationship between square root GA area and VF-14 questionnaire was calculated using the better eye (i.e., with the smaller GA area), if both eyes were included as study eyes.

Participants

Thirty participants were enrolled in the study between March 2021 and July 2022 (16 male, 14 female, median [IQR] age of 79 years [77, 84]). The demographic data are summarized in Table 1, and online supplementary Table 2 summarizes the cohort characteristics of the enrolled participants. Out of the thirty participants, 37 study eyes were selected. Table 2 summarizes the ocular characteristics of the study eyes. In addition, ocular baseline characteristics in dependence of lens status are provided in online supplementary Table 3. All study eyes were diagnosed with GA with one focus of GA having a diameter ≥250 µm. One female participant was excluded during the screening visit due to fixation instability hindering retinal imaging. The clinical study flowchart is described in online supplementary Figure 1. Six out of the 37 study eyes (16.2%) developed macular neovascularization over the period of observation. Reticular pseudodrusen were present in 24 (64.9%) of the study eyes.

Table 2.

Ocular baseline characteristics of study eyes

Total (N = 37)Fovea spared (N = 26)Fovea affected (N = 11)
BCVA (logMAR)] 
 Mean (min, max) 0.20 (−0.10, 0.74) 0.14 (−0.10, 0.58) 0.33 (0.12, 0.74) 
 Median (IQR) 0.18 (0.06, 0.26) 0.14 (0.01, 0.22) 0.26 (0.23, 0.42) 
LLVA (logMAR) 
 Mean (min, max) 0.66 (0.10, 1.42) 0.65 (0.10, 1.42) 0.70 (0.46, 1.02) 
 Median (IQR) 0.66 (0.36, 0.88) 0.66 (0.29, 0.96) 0.66 (0.57, 0.85) 
AULCSF (logCS*logCPD) 
 Mean (min, max) 0.82 (0.19, 1.55) 0.86 (0.19, 1.55) 0.67 (0.21, 1.08) 
 Median (IQR) 0.82 (0.63, 1.04) 0.91 (0.63, 1.08) 0.74 (0.44, 0.91) 
 Missing, n (%) 7 (18.9) 3 (11.5) 4 (36.4) 
CSF acuity (logCPD) 
 Mean (min, max) 1.09 (0.58, 1.47) 1.13 (0.62, 1.47) 0.96 (0.58, 1.27) 
 Median (IQR) 1.08 (0.99, 1.26) 1.16 (1.01, 1.29) 1.07 (0.78, 1.12) 
 Missing, n (%) 7 (18.9) 3 (11.5) 4 (36.4) 
GA area, mm2 
 Mean (min, max) 3.00 (0.07, 11.7) 3.07 (0.07, 11.7) 2.83 (0.42, 10.7) 
 Median (IQR) 1.40 (0.49, 5.24) 1.06 (0.35, 5.27) 1.69 (1.37, 2.40) 
Number of GA Foci 
 Mean (min, max) 2.76 (1.00, 13.00) 3.08 (1.00, 13.0) 2.00 (1.00, 4.00) 
 Median (IQR) 2.00 (1.00, 3.00) 2.00 (1.00, 3.00) 1.00 (1.00, 3.00) 
Microperimetry retinal sensitivity, dB 
 Mean (min, max) 15.9 (1.58, 23.8) 14.8 (1.58, 23.8) 18.5 (7.58, 22.5) 
 Median (IQR) 18.4 (9.21, 20.9) 16.8 (7.95, 21.8) 19.5 (18.2, 20.4) 
Reticular pseudodrusen, n (%) 
 Absent 13 (35.1) 8 (30.8) 5 (45.5) 
 Present 24 (64.9) 18 (69.2) 6 (54.5) 
Type of drusen, n (%) 
 Mixed soft drusen and reticular pseudodrusen 18 (48.6) 12 (46.2) 6 (54.5) 
 Predominantly reticular pseudodrusen 6 (16.2) 6 (23.1) 0 (0) 
 Soft drusen 13 (35.1) 8 (30.8) 5 (45.5) 
Lens status, n (%) 
 Immature cataract 4 (10.8) 2 (7.7) 2 (18.2) 
 Mild cataract 6 (16.2) 6 (23.1) 0 (0) 
 Pseudophakic 27 (73.0) 18 (69.2) 9 (81.8) 
Total (N = 37)Fovea spared (N = 26)Fovea affected (N = 11)
BCVA (logMAR)] 
 Mean (min, max) 0.20 (−0.10, 0.74) 0.14 (−0.10, 0.58) 0.33 (0.12, 0.74) 
 Median (IQR) 0.18 (0.06, 0.26) 0.14 (0.01, 0.22) 0.26 (0.23, 0.42) 
LLVA (logMAR) 
 Mean (min, max) 0.66 (0.10, 1.42) 0.65 (0.10, 1.42) 0.70 (0.46, 1.02) 
 Median (IQR) 0.66 (0.36, 0.88) 0.66 (0.29, 0.96) 0.66 (0.57, 0.85) 
AULCSF (logCS*logCPD) 
 Mean (min, max) 0.82 (0.19, 1.55) 0.86 (0.19, 1.55) 0.67 (0.21, 1.08) 
 Median (IQR) 0.82 (0.63, 1.04) 0.91 (0.63, 1.08) 0.74 (0.44, 0.91) 
 Missing, n (%) 7 (18.9) 3 (11.5) 4 (36.4) 
CSF acuity (logCPD) 
 Mean (min, max) 1.09 (0.58, 1.47) 1.13 (0.62, 1.47) 0.96 (0.58, 1.27) 
 Median (IQR) 1.08 (0.99, 1.26) 1.16 (1.01, 1.29) 1.07 (0.78, 1.12) 
 Missing, n (%) 7 (18.9) 3 (11.5) 4 (36.4) 
GA area, mm2 
 Mean (min, max) 3.00 (0.07, 11.7) 3.07 (0.07, 11.7) 2.83 (0.42, 10.7) 
 Median (IQR) 1.40 (0.49, 5.24) 1.06 (0.35, 5.27) 1.69 (1.37, 2.40) 
Number of GA Foci 
 Mean (min, max) 2.76 (1.00, 13.00) 3.08 (1.00, 13.0) 2.00 (1.00, 4.00) 
 Median (IQR) 2.00 (1.00, 3.00) 2.00 (1.00, 3.00) 1.00 (1.00, 3.00) 
Microperimetry retinal sensitivity, dB 
 Mean (min, max) 15.9 (1.58, 23.8) 14.8 (1.58, 23.8) 18.5 (7.58, 22.5) 
 Median (IQR) 18.4 (9.21, 20.9) 16.8 (7.95, 21.8) 19.5 (18.2, 20.4) 
Reticular pseudodrusen, n (%) 
 Absent 13 (35.1) 8 (30.8) 5 (45.5) 
 Present 24 (64.9) 18 (69.2) 6 (54.5) 
Type of drusen, n (%) 
 Mixed soft drusen and reticular pseudodrusen 18 (48.6) 12 (46.2) 6 (54.5) 
 Predominantly reticular pseudodrusen 6 (16.2) 6 (23.1) 0 (0) 
 Soft drusen 13 (35.1) 8 (30.8) 5 (45.5) 
Lens status, n (%) 
 Immature cataract 4 (10.8) 2 (7.7) 2 (18.2) 
 Mild cataract 6 (16.2) 6 (23.1) 0 (0) 
 Pseudophakic 27 (73.0) 18 (69.2) 9 (81.8) 

BCVA, best-corrected visual acuity; logMAR, logarithm of the minimum angle of resolution; LLVA, low-luminance visual acuity; AULCSF, area under the log contrast sensitivity function curve; logCS, logarithm of the contrast sensitivity; logCPD, logarithm of the cycles per degree; CSF, contrast sensitivity function; GA, geographic atrophy; dB, decibel.

Visual Function at Baseline

BCVA at baseline was (median [IQR]) 76.0 ETDRS letters [72.0, 82.0] (logMAR 0.18 [0.06, 0.26]). LLVA at baseline was (median [IQR]) 52.0 ETDRS letters (41.0, 67.0) (logMAR 0.66, [0.36, 0.88]). At baseline, qCSF measurements were available for 30 out of 37 eyes. The AULCSF was (median [IQR]) 0.82 logCS*logCPD (0.63, 1.04) at baseline, and CSF acuity 1.08 logCPD (0.99, 1.26). The mean sensitivity in microperimetry was (median [IQR]) 18.4 dB (9.21, 20.9).

Correlation among Visual Function Tests

Figure 2 shows the cross-sectional association of the visual function test results. The linear mixed-effects models describing their relationships are presented in Table 3. LLVA and AULCSF exhibited the strongest association between visual function tests (R2 of 0.768) with a slope (coefficient [95% CI]) of −0.88 logMAR/(logCS*logCPD) (−1.07 to −0.69). The association between BCVA and AULCSF had the second highest strength of association (R2 of 0.559) with a slope (coefficient [95% CI]) of −0.35 logMAR/(logCS*logCPD) (−0.44 to −0.26). BCVA and microperimetry mean sensitivity showed the weakest association (R2 of 0.044) with a slope (coefficient [95% CI]) of −0.01 logMAR/dB (−0.02 to 0.00).

Fig. 2.

Cross-sectional (baseline) association between visual function tests. The panel shows linear mixed-effects plots between different visual function tests in dependence of patient. The dashed line shows the calculated mean random intercept and random slope models. BCVA, best-corrected visual acuity; logMAR, logarithm of the minimum angle of resolution; LLVA, low-luminance visual acuity; AULCSF, area under the log contrast sensitivity function curve; logCS, logarithm of the contrast sensitivity; logCPD, logarithm of the cycles per degree; dB, decibel.

Fig. 2.

Cross-sectional (baseline) association between visual function tests. The panel shows linear mixed-effects plots between different visual function tests in dependence of patient. The dashed line shows the calculated mean random intercept and random slope models. BCVA, best-corrected visual acuity; logMAR, logarithm of the minimum angle of resolution; LLVA, low-luminance visual acuity; AULCSF, area under the log contrast sensitivity function curve; logCS, logarithm of the contrast sensitivity; logCPD, logarithm of the cycles per degree; dB, decibel.

Close modal
Table 3.

Cross-section (baseline) of structural and functional ocular biomarkers in GA

Dependent variableExplanatory variableCoefficient estimates95% CIp valueMarginal R2/conditional R2
BCVA (logMAR) Intercept −0.06 −0.16 to 0.04 0.215  
LLVA (ETDRS) 0.40 0.27–0.53 <0.001 0.483/0.921 
BCVA (logMAR) Intercept 0.46 0.38–0.55 <0.001  
AULCSF (logCS*logCPD) −0.35 −0.44 to −0.26 <0.001 0.559/0.975 
LLVA (logMAR) Intercept 1.35 1.18–1.52 <0.001  
AULCSF (logCS*logCPD) −0.88 −1.07 to −0.69 <0.001 0.768/0.904 
BCVA (logMAR) Intercept 0.31 0.12–0.49 0.002  
Retinal sensitivity, dB −0.01 −0.02 to 0.00 0.243 0.044/0.858 
LLVA (logMAR) Intercept 1.13 0.87–1.39 <0.001  
Retinal sensitivity, dB −0.03 −0.05 to −0.01 <0.001 0.336/0.738 
LLVA (logMAR) Intercept 0.34 −0.03 to 0.72 0.072  
Retinal sensitivity, dB 0.03 0.01–0.05 0.014 0.229/0.772 
Dependent variableExplanatory variableCoefficient estimates95% CIp valueMarginal R2/conditional R2
BCVA (logMAR) Intercept −0.06 −0.16 to 0.04 0.215  
LLVA (ETDRS) 0.40 0.27–0.53 <0.001 0.483/0.921 
BCVA (logMAR) Intercept 0.46 0.38–0.55 <0.001  
AULCSF (logCS*logCPD) −0.35 −0.44 to −0.26 <0.001 0.559/0.975 
LLVA (logMAR) Intercept 1.35 1.18–1.52 <0.001  
AULCSF (logCS*logCPD) −0.88 −1.07 to −0.69 <0.001 0.768/0.904 
BCVA (logMAR) Intercept 0.31 0.12–0.49 0.002  
Retinal sensitivity, dB −0.01 −0.02 to 0.00 0.243 0.044/0.858 
LLVA (logMAR) Intercept 1.13 0.87–1.39 <0.001  
Retinal sensitivity, dB −0.03 −0.05 to −0.01 <0.001 0.336/0.738 
LLVA (logMAR) Intercept 0.34 −0.03 to 0.72 0.072  
Retinal sensitivity, dB 0.03 0.01–0.05 0.014 0.229/0.772 

The table shows the calculated linear mixed-effects model values. Association between different visual function tests and between each other was calculated in dependence of patients.

CI, 95% confidence interval; logMAR, logarithm of the minimum angle of resolution; LLVA, low-luminance visual acuity; AULCSF, area under the log contrast sensitivity function curve; logCS, logarithm of the contrast sensitivity; logCPD, logarithm of the cycles per degree; dB, decibel.

Fundus Autofluorescence

Eleven (29.7%) examined eyes presented with GA affecting the fovea, while 26 (70.3%) eyes showed GA with foveal sparing. The median (IQR) number of GA loci was 2.00 (1.00, 3.00). The median (IQR) area of GA per eye was 1.40 mm2 (0.49, 5.24).

Visual Function in Dependence of GA Area

Figure 3 shows the cross-sectional association of visual function tests and structural GA area. The calculated values are depicted in Table 4. LLVA function and square root GA area exhibited the strongest association (R2 of 0.578) with a slope (coefficient [95% CI]) of 0.28 (logMAR/mm) (0.20–0.36). The linear mixed-effects model with AULCSF as a function of square root GA area yielded the second highest R2 with 0.519 (coefficient estimates [95% CI] −0.28 (logCS*logCPD)/mm [−0.38 to −0.18]). The association between microperimetry retinal sensitivity and GA area was also strong (R2 of 0.487) with a slope of −4.44 (dB/mm) (−5.87 to −3.01). In contrast, the association between BCVA and GA area was weak (R2 of 0.154) with a slope of 0.08 logMAR/mm (0.02–0.15).

Fig. 3.

Relationship between GA area and visual function. The panel shows linear mixed-effects plots between structural and functional ocular biomarkers in GA in dependence of patient. The dashed line shows the calculated mean random intercept and random slope models. BCVA, best-corrected visual acuity; logMAR, logarithm of the minimum angle of resolution; LLVA, low-luminance visual acuity; AULCSF, area under the log contrast sensitivity function curve; logCS, logarithm of the contrast sensitivity; logCPD, logarithm of the cycles per degree; dB, decibel; GA, geographic atrophy.

Fig. 3.

Relationship between GA area and visual function. The panel shows linear mixed-effects plots between structural and functional ocular biomarkers in GA in dependence of patient. The dashed line shows the calculated mean random intercept and random slope models. BCVA, best-corrected visual acuity; logMAR, logarithm of the minimum angle of resolution; LLVA, low-luminance visual acuity; AULCSF, area under the log contrast sensitivity function curve; logCS, logarithm of the contrast sensitivity; logCPD, logarithm of the cycles per degree; dB, decibel; GA, geographic atrophy.

Close modal
Table 4.

Cross-section (baseline) of structural and functional ocular biomarkers in GA

Dependent variableExplanatory variableCoefficient estimates95% CIp valueMarginal R2/conditional R2
BCVA (logMAR) Intercept 0.08 −0.04 to 0.20 0.167  
Square root GA area, mm 0.08 0.02 to 0.15 0.011 0.154/0.886 
LLVA (logMAR) Intercept 0.26 0.11–0.40 <0.001  
Square root GA area, mm 0.28 0.20–0.36 <0.001 0.578/0.897 
AULCSF (logCS*logCPD) Intercept 1.17 0.99–1.34 <0.001  
Square root GA area, mm −0.28 −0.38 to −0.18 <0.001 0.519/0.902 
Retinal sensitivity, dB Intercept 22.15 19.49–24.81 <0.001  
Square root GA area, mm −4.44 −5.87 to −3.01 <0.001 0.487/0.944 
Dependent variableExplanatory variableCoefficient estimates95% CIp valueMarginal R2/conditional R2
BCVA (logMAR) Intercept 0.08 −0.04 to 0.20 0.167  
Square root GA area, mm 0.08 0.02 to 0.15 0.011 0.154/0.886 
LLVA (logMAR) Intercept 0.26 0.11–0.40 <0.001  
Square root GA area, mm 0.28 0.20–0.36 <0.001 0.578/0.897 
AULCSF (logCS*logCPD) Intercept 1.17 0.99–1.34 <0.001  
Square root GA area, mm −0.28 −0.38 to −0.18 <0.001 0.519/0.902 
Retinal sensitivity, dB Intercept 22.15 19.49–24.81 <0.001  
Square root GA area, mm −4.44 −5.87 to −3.01 <0.001 0.487/0.944 

The table shows the calculated linear mixed-effects model values of different functional biomarkers in association to the GA area conditioned on the patient.

CI, 95% confidence interval; BCVA, best-corrected visual acuity; logMAR, logarithm of the minimum angle of resolution; LLVA, low-luminance visual acuity; AULCSF, area under the log contrast sensitivity function curve; logCS, logarithm of the contrast sensitivity; logCPD, logarithm of the cycles per degree; dB, decibel.

Linear mixed-effects models with age and sex as additional covariates are shown in online supplementary Table 4. Across models, sex and age showed no association with visual function. Online supplementary Figure 2 shows the cross-sectional association VF-14 questionnaire score and structural GA area. VF-14 score and square root GA area exhibited a strong association (R2 of 0.422) with a slope (coefficient [95% CI]) of −3.75 (score-points/mm) (−5.45 to −2.05).

GA is a common, chronic disease leading to irreversible and often bilateral loss of central vision. Although pegcetacoplan and avacincaptad pegol demonstrated to reduce structural GA progression, no current treatment exists for central visual acuity preservation [8, 9]. Also, the proposed GA treatment was associated with an increased rate of macular neovascularization of 12% using a monthly administration regime [6]. Conflicting results in recent clinical trials (i.e., benefits in terms of surrogate measures but not patient-relevant measures) highlight the critical importance of precisely understanding the natural history of GA. Thus, natural history studies probing novel visual function tests, such as the now-presented OMEGA study, will be critical for designing the next generation of interventional trials.

Natural history study settings regarding GA in AMD have been established previously, most notably the Baltimore natural history study [5], the FAF imaging in AMD study (ClinicalTrials.gov Identifier: NCT00393692) [33], the Directional Spread in GA study (NCT02051998) [18, 34], and Proxima A and B studies (NCT02479386, NCT02399072) [35]. In addition, extensive data on GA progression are available for the age-related eye disease studies 2 study [36]. Compared to Proxima A and B, the baseline GA area is markedly smaller in OMEGA [35]. Only age-related eye disease studies 2 study patients had similar small GA areas with a mean (SD) of 3.4 mm2 (4.2) in the prevalence cohort and 1.7 mm2 (2.5) in the incidence cohort [36].

LLVA has been previously described to be more translatable to everyday tasks such as driving at night than BCVA, and is therefore considered to be a surrogate for patient-relevant visual function [37]. It has also been shown to be prognostic for AMD progression [10]. In our baseline data, LLVA showed the strongest association with the GA area.

To the best of our knowledge, the qCSF testing is yet to be evaluated in a prospective study of GA progression. The AULCSF showed a high correlation with the mean sensitivity. Notably, the correlation coefficient between the GA area and qCSF AULCSF is higher than between the GA area and BCVA. This implies that AULCSF is more reflective of the overall disease burden compared to BCVA. As reported previously, BCVA can remain stable over a long time in eyes with foveal sparing [34]. However, contrast sensitivity testing at low spatial frequencies (large optotypes) likely reveals dysfunction due to parafoveal scotomata, similar to the phenomenon of reading difficulties with large print sizes [38‒40]. In contrast, considering that most of our GA patients presented with an intact fovea, a weak correlation between BCVA and GA area is expected.

Limitations

This study has a limited sample size compared to previous natural history studies of GA. Also, the OMEGA cohort is variable regarding baseline characteristics such as the GA areas (range of 0.07–11.7 mm2). Critical advantages of the study are the comprehensive imaging and functional testing protocol, longitudinal evaluation of new functional tests, and frequent follow-up tests (12, 24, and 48 weeks). The latter will enable us to identify short-term fluctuations and early biomarkers of disease progression. Longitudinal analysis of this prospective, natural history study will deepen our understanding of GA progression and the ability to detect change for novel visual function assessments.

The study was reviewed and approved by the Swiss Ethics Committees on research involving humans (BASEC ID: 2019-02003 [https://raps.swissethics.ch/]) and adhered to the World Medical Association Declaration of Helsinki. All participants were informed of the study’s nature and written informed consent was obtained from participants before study-related examinations.

Georg Ansari and Chrysoula Gabrani: none. Nils Schärer: consultant of Boehringer Ingelheim Pharma GmbH & Co. Hanna Camenzind Zuche: recipient of Bayer and Apellis. Philipp Anders: financial support of Bayer; grant support by the foundation “Freiwillige Akademische Gesellschaft Basel” and the foundation “OPOS zugunsten von Wahrnehmungsbehinderten” (project funding: “Validation of novel microperimetry metrics as functional outcome parameters for clinical trials targeting macular diseases”). Kristina Pfau: consultant of Daiichi Sankyo. Philippe Valmaggia: recipient of Heidelberg Engineering, funding from Swiss National Science Foundation (Grant 323530_199395) and Janggen-Pöhn Foundation. Andrea Giani, Marieh Esmaeelpour, and Taffeta Chingning Yamaguchi: emloyees of Boehringer Ingelheim. Christian F. Prünte: consultant of Alcon, Bayer, Novartis, and Oertli; recipient of Alcon, Bayer, Novartis, and Oertli. Peter M. Maloca: consultant at Roche (Basel, Switzerland), Zeiss Forum, and holds intellectual property for machine learning at MIMO AG and VisionAI, Switzerland. Leopold Schmetterer: consultant of Boehringer Ingelheim Pharma GmbH & Co., Thea Pharma, Centervue Spa, funding from Johnson & Johnson. Hendrik P.N. Scholl: Swiss National Science Foundation (project funding: “Developing novel outcomes for clinical trials in Stargardt disease using the structure/function relationship and deep learning” #310030_201165, National Center of Competence in Research Molecular Systems Engineering: “NCCR MSE: Molecular Systems Engineering (phase II)” #51NF40-182895), the Wellcome Trust (PINNACLE study), and the Foundation Fighting Blindness Clinical Research Institute (ProgStar study). Member of the Scientific Advisory Board of: Boehringer Ingelheim Pharma GmbH & Co.; Claris Biotherapeutics Inc.; Eluminex Biosciences; Gyroscope Therapeutics Ltd.; Janssen Research and Development, LLC (Johnson & Johnson); Novartis Pharma AG (CORE); Okuvision GmbH; ReVision Therapeutics Inc.; and Saliogen Therapeutics Inc. Consultant of Alnylam Pharmaceuticals Inc.; Gerson Lehrman Group Inc.; Guidepoint Global, LLC; and Intergalactic Therapeutics Inc. Member of: Data Monitoring and Safety Board/Committee of Belite Bio (CT2019-CTN-04690-1), F. Hoffmann-La Roche Ltd. (VELODROME trial, NCT04657289; DIAGRID trial, NCT05126966; HUTONG trial), Steering Committee of Novo Nordisk (FOCUS trial; NCT03811561). All arrangements have been reviewed and approved by the University of Basel (Universitätsspital Basel, USB) and the Board of Directors of the Institute of Molecular and Clinical Ophthalmology Basel (IOB) in accordance with their conflict of interest policies. Compensation is being negotiated and administered as grants by USB, which receives them on its proper accounts. Dr. Scholl is the co-director of the Institute of Molecular and Clinical Ophthalmology Basel (IOB), which is constituted as a nonprofit foundation and receives funding from the University of Basel, the University Hospital Basel, Novartis, and the government of Basel-Stadt. Maximilian Pfau: recipient of Novartis, consultant of Janssen Pharmaceutica, Apellis, and Daiichi Sankyo, and funding from Apellis.

This study was funded by Boehringer Ingelheim Pharma GmbH & Co.KG (Ingelheim, Rheinland-Pfalz, Germany).

Georg Ansari: analysis and interpretation of data and manuscript drafting, review. Nils Schärer, Hanna Camenzind Zuche, Chrysoula Gabrani, Philipp Anders, Kristina Pfau, and Philippe Valmaggia: data acquisition and analysis and interpretation of data, review. Andrea Giani, Marieh Esmaeelpour, Taffeta Chingning Yamaguchi, and Christian F. Prünte: conception and design of the study, review. Peter M. Maloca and Leopold Schmetterer: conception and design of the study, interpretation of data, review. Hendrik P.N. Scholl and Maximilian Pfau: conception and design of the study, acquisition of data, interpretation of data, manuscript drafting, review.

Additional Information

H.P.N.S. and M.P. contributed equally to the work presented here and should therefore be regarded as equivalent authors.

All data generated or analyzed during this study are included in this article and its online supplementary material. Further inquiries can be directed to the corresponding author.

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