Visual Function and Central Retinal Structure in Choroideremia

Abstract

Purpose: To define the clinical phenotype of a cohort of patients affected with choroideremia.

Methods: A retrospective study of patients with choroideremia included two centers. Data collected included age, visual acuity, refractive error, color vision, kinetic perimetry, optical coherence tomography (OCT), and genotype information.

Results: Sixty male participants were recruited. Genotype information was available for 58 cases, and nonsense mutations were most commonly observed. Eight novel mutations were identified including a missense mutation. The mean age at the first visit was 30.1 years (range, 5–65 years) and thirty-seven patients (61%) had more than one visit with a mean follow-up period of 10.3 years (range, 1–23 years). Visual acuity was not associated with age for patients younger than 30 years (P = 0.46) but significantly associated with age for the age group above 30 years (P < 0.0001). Central retinal thickness was significantly associated with visual acuity (P = 0.03) and with age (P = 0.0014). The extent of visual field documented by kinetic perimetry showed a negative correlation with age to tested stimuli; the smallest target used (I-4e) showed the earliest and most rapid deterioration below the age of 20 years (P = 0.0032). Color vision was abnormal in 46.7% of cases (mean age, 36.3 years; range, 18–61 years), which was associated with older age (P = 0.0039). Central OCT images were abnormal in all cases, as early as age 10 years. Outer retinal tubulations were observed in all but five patients. No genotype–phenotype correlation was observed.

Conclusions: This comprehensive structural and functional characterization of a large cohort of patients with molecularly confirmed choroideremia indicates that certain parameters are not changing significantly with time while others are. The latter warrants a prospective natural history study, ultimately to be considered as outcome measures for interventional clinical trials.

Choroideremia (CHM) is a monogenic X-linked (Xq21) condition characterized by progressive night blindness and constriction of visual fields due to mutations in the CHM (REP1) gene.^1–3 The progressive degeneration of the photoreceptors, retinal pigment epithelium (RPE), and choroid leads to severe peripheral field loss by adulthood and central visual acuity loss after 50 years of age.⁴ It is unclear whether the primary insult is at the level of the choroid and RPE or the photoreceptors. Our studies in patients support a primary photoreceptor disease, but analysis of a CHM mouse model suggests that mutations of CHM affect the integrity of photoreceptors and RPE independently.^5–7 The degenerative process of CHM is progressive, irreversible, and not treatable at this time. 

Recent success in retinal gene transfer (GT) therapy has generated much enthusiasm and hope to make conditions such as CHM treatable.^8–10 Lessons learned from the early GT studies⁸ highlight the important role of patient selection and choosing the right outcome measures in order to understand better the short- and long-term results of trialed interventions. As clinical trials of gene therapy for CHM have been initiated,^9,11–17 a better understanding of the structural and functional changing features of the CHM-retina is needed. In the present study, a large cohort of men affected with molecularly proven CHM was characterized with noninvasive tests, including cross-sectional data and serial measurements, to gain insight into the disease's natural history. 

Methods

This was a retrospective study involving two sites: the Hospital for Sick Children in Toronto (site 1) and the Scheie Eye Institute in Philadelphia (site 2). This work was approved by our Institutional Ethics Review Boards and respected the tenets of the Declaration of Helsinki. Patients were identified through our respective internal databases. Inclusion criteria were (1) unequivocal clinical diagnosis of CHM, (2) molecular diagnosis of CHM when possible, and (3) availability of phenotype information (visual acuity, Goldmann kinetic visual field [GVF], color vision, and spectral-domain optical coherence tomography [SD-OCT]) for at least one visit. 

Data collected included deidentified demographic information, best-corrected visual acuity (BCVA) in logMAR,¹⁸ color vision (Farnsworth D15 panel), GVF, and OCT. Any color vision anomaly was defined as abnormal. At site 1, OCT was performed with the Cirrus (Carl Zeiss Meditec, Dublin, CA, USA), while site 2 used the RTVue-100 (Optovue, Inc., Fremont, CA, USA). At both sites, the OCT quantitative analysis focused on the central retinal area (central subfield 1 mm) as defined by the Early Treatment Diabetic Retinopathy Study.^19–21 At both sites, normal values were obtained from individuals with normal vision without ocular pathology, by measuring the central subfield thickness, from the Bruch's membrane to the vitreoretinal interface.¹⁹ Site 1 had 22 normal individuals (mean age: 30 ± 23.6 years) and site 2 measured 35 normal individuals (mean age: 33.1 ± 15.1 years). The data were averaged at each site (site 1: 259 μm ± 22.37 μm; site 2 mean: 260.07 μm ± 23.37 μm). In cases and controls, only scans with a clear foveal dip were included to measure central retinal thickness (CRT). 

In a subset of patients, data from en face imaging with a confocal scanning laser ophthalmoscope (Spectralis HRA; Heidelberg Engineering, Heidelberg, Germany) using near-infrared (815 nm) illumination was analyzed. Regions of relatively low reflectance within the macula on these images represent the remaining extent of melanized RPE.²² A nonlinear gamma transformation (power = 0.7) was applied to gray levels in order to allow simultaneous visualization of features both within darker and brighter regions of the images. 

The GVF data were presented in percentage of residual field of vision compared to age-matched controls for specific isopters.²³ The visual field (VF) areas were quantified by using a previously published computer-based algorithm.²⁴ Test points of the Goldmann field were digitized and mapped as points on a VF hemisphere. Their sequence defined a curvilinear polygon, and the solid angle (in steradians) subtended by it was calculated. The entire field of vision was accounted for as the solid angles associated with scotomas were subtracted from the seeing areas. For easier interpretation, solid angle measurements are reported as a percentage of the mean normal “visual field extent” for the corresponding target. The annual rate of change for V-4e and I-4e test targets was calculated from a subset of patients with serial data as previously described.^25,26 Both sites had a practice of adapting the patient to the perimeter environment for approximately 5 minutes. 

Statistical Analysis

Statistical analyses were completed by using SAS 9.4 (SAS Institute, Inc., Cary, NC, USA). 

For descriptive statistics, a two sample t-test was used to compare patient age in the two sites. For visual acuity we only included the vision of the better eye and because visual acuity was not normally distributed, a Wilcoxon two-sample test was used to compare patient visual acuity. We analyzed the association between visual acuity and age by using linear spline mixed model. This model took into account the correlation within a subject over repeated measures and examined association between age and visual acuity for younger patients (<30 years) and older patients (≥30 years) separately. 

Repeated measure ANOVA (RM-ANOVA) was used to investigate the association between age and VF for each stimulus (V-4e, IV-4e, III-4e, and I-4e). These RM-ANOVA models accounted for the doubly repeated measures in VF over time on the same subject and in VF tested on both eyes on the same subject at each visit. A two-piecewise RM-ANOVA model was built for stimuli I-4e. Normality of residuals of the four models were checked and met. Bonferroni correction technique was used to adjust for the effect of multiple testing. Furthermore, logistic regression was used to examine the association between outcome color vision and predictors including age and visual acuity. Mixed models were used to examine the association between outcome CRT and predictors, including acuity and age, separately. 

Results

Sixty male CHM patients were included in this study. Thirty-seven patients (61%) had more than one visit with a mean follow-up period of 10.3 years (range, 1–23 years). The data of patients at both sites were similar (Table 1) and analyzed together. Although we could not capture age at diagnosis, the mean age at the first visit was 30.1 years (range, 5–65 years; Table 1). 

Table 1

 

General Characteristics of the Populations Studied

 

The Correlation With Age Differs Between Visual Fields and Visual Acuity

The mean refractive error in spherical equivalent was −2.75 D ± 3.5 D. Although BCVA appeared to decrease with age (Table 2; Fig.1), a beta regression analysis of the visual acuity over time did not show any significant relationship between age and visual acuity (P = 0.63). However, although there was no correlation between BCVA and age when younger than 30 years (β = −0.00174, P = 0.46), for patients older than 30 years, visual acuity declined significantly as age increased (β = 0.008871, P < 0.0001). The estimated visual acuity between birth and 30 years was not significantly different from normal. However, the estimated vision at 50 years of age was significantly worse at 0.21 (P < 0.0001). There was no loss of light perception in this cohort. 

Table 2

 

Summary of Data Goldmann Visual Field

 

Goldmann kinetic visual fields were measurable for 57 individuals. Examples of the different patterns of progressive visual field loss of four representative patients are shown (Fig. 2A); P29 lost most of his I-4e field throughout 7 years (ages 11–18 years), while fields to the V-4e target remained relatively full during that period. P43 had a very small field to the I-4e target at age 17 years and this decreased further throughout 7 years. The midperipheral scotomas (to the V-4e target) also expanded during the 7-year period depicted (ages 17–24 years). P42 at age 31 years had a very small field to the I-4e target, which got smaller during the 12-year period. He also showed an altitudinal (superior) loss of visual field (to the V-4e target) and the beginning of an inferior scotomatous region in the near midperiphery. During the subsequent 12 years, the scotoma encircled fixation and by age 43 years, the central island was isolated from a residual far temporal peripheral island. P28—at a more advanced stage for his age than the other patients shown—only had a small central island and peripheral inferior temporal islands of perception with the V-4e target at age 33 years. The peripheral islands became nondetectable at age 51 years but the central island remained detectable (<5°) with the I-4e target and further decreased in size at the latest age. 

Figure 1

 

Best-corrected visual acuity in CHM. The better visual acuity of each patient (n = 60) is shown at age of testing. When serial data are available (n = 37), visual acuities from the same eye at the first and the latest evaluation are plotted and connected by lines. Thicker line represents the linear spline mixed model (fit by excluding the datum from the patient with hand-motion acuity) described in text.

Figure 2

 

Kinetic visual fields in CHM. (A) Serial visual field drawings (using the V-4e and I-4e stimuli) from four patients, representing different disease stages at different time points, illustrate progression of visual field loss in CHM. (B) Quantified field extents to five different targets are plotted on a linear scale, with serial data connected by lines for cases with more than one measurement. Data points from the four selected patients in (A) are marked (P28, P29, P32, P43). (C, D) In a subset of patients with serial data, the annual rate of change was estimated for V-4e (C) and I-4e (D). Data were arranged as time after onset of decline in field extent; the annual rate of decline (dashed gray line) is the average of the slopes fit to the log-linear data for individuals.

Visual field extent from the entire cohort of patients, using a number of different stimuli (Table 2), is plotted in Figure 2B. The field of vision to the I-4e stimulus showed the earliest (first decade) and most rapid decline in extent, while the fields in response to the V-4e stimulus could be measured ∼30 years longer. Two types of analyses were used to interpret the visual fields changes. Analysis 1 based on the two-piecewise RM-ANOVA model showed that the visual field area loss correlated with age for the I-4e isopter for patients 20 years or younger (P = 0.0032). The correlation of visual field area loss with age for the V-4e (P < 0.0001) and III-4e (P = 0.018) isopters was also significant. The pattern of visual field loss was symmetric and independent of the class of the mutation (nonsense, frameshift, or missense). Practically, by 20 years of age there was approximately 1% of the I-4e field left, while 50% of the V-4e field was maintained until reaching the 40s. 

In analysis 2, we studied a subset of 17 patients with available longitudinal data (n = 10 for V-4e; n = 9 for I-4e) and assumed a model wherein the disease progresses exponentially after its onset.^27–32 The estimated rates of visual field constriction were 8.3% (±4.7%) per year for the large target and 27.7% (±19.2%) per year for the small target (Figs. 2C, 2D). 

Color vision results were available for 60 cases (Table 2, Fig. 3) of which 28 were abnormal (46.7%); 17.5% of this subgroup had normal visual acuity (mean age, 36.3 years; range, 18–61 years). Five patients had no measurable color vision despite a BCVA of 0.3 or better (Table 2; cases 12, 14, 20, 24). Visual acuity was not associated with abnormal color vision (P = 0.11) but older age was (P = 0.0039). Mean age of patients with abnormal color vision was 43 years (range, 12–65 years) while that of cases with normal color vision was 27 years (range, 6–53 years). Each additional year increased the risk of developing abnormal color vision by 6% (OR = 1.06, 95% CI = 1.02–1.11). 

Figure 3

 

Color vision defects can occur early and progress with age. The horizontal axis reflects three age groups: 5 to 20 years, 20 to 35 years, and 35 to 65 years.

Optical Coherence Tomography: Early Central Retinal Changes Despite Good Vision

The OCT images were available for 39 cases (61 eyes). The CRT was within normal limits until the 40s, followed by significant thinning in some patients between 40 and 60 years of age, while others maintained normal thickness in this age group (Fig. 4). Mixed-model analyses of the mean CRT (259.2 μm ± 52.70 μm) showed an association with age (P = 0.0045) as well as an association with visual acuity: the older the patient, the thinner the CRT (β = −1.73, P = 0.0014) and the worse the eye vision, the thinner the CRT (β = −22.68, P = 0.0321). 

Figure 4

 

Central retinal thickness of CHM patients as a function of age; CRT in choroideremia. Scatter plot of CRT values from patients as a function of age from both sites (site 1 [pink] used the Cirrus OCT, while site 2 [blue] used the Optovue). Mean retinal thickness values by age were estimated by using local polynomial regression fitting. The shaded areas show the sample variation (±1.96 standard deviations) of CRT normal values for each site. The retina appeared to be initially on the thicker end of normal followed by a slow thinning after the age of 50 years.

Paramacular retinal disorganization was also a significant feature observed early (Fig. 5A). Outer retinal tubulations (ORTs) were observed in all but five patients (Tables 2, 3; Fig. 5). Thirteen patients had ORTs in one eye, while in 22 cases ORTs were observed in both eyes. The presence or absence of ORTs did not correlate with age or visual acuity. We used en face OCT imaging to determine the branching patterns of the ORTs as has been demonstrated in age-related macular degeneration (AMD).^32–36 Two patients, one at age 12 years and the other at age 37 years, showed differently sized central islands of RPE on near-infrared reflectance images (Figs. 5B, 5C). En face and cross-sectional imaging of the central, normally pigmented region is also shown (right). Both patients showed branching structures evident at the edges of the preserved RPE and extending to further eccentricities. Insets adjacent to the en face images (Fig. 5) are drawings of the branching patterns. Although this warrants further investigation, the caliber of the tubular structures seemed to be wider in the younger patient. An OCT cross-section at one location in each patient showed correspondence between the branched structures and the ORTs. 

Figure 5

 

Retinal structural features in CHM. (A) The SD-OCT scans along the horizontal meridian through the fovea are shown from six different patients. Black arrows show ORTs. White arrows show schisis in the ganglion cell layer. White-filled arrowheads of black arrows point to cystic lesions. (B, C) The NIR reflectance images are shown for comparison with an OCT en face image in 12-year-old and 37-year-old CHM patients. Retinal regions of low reflectance correspond to pigmented RPE, whereas those with high reflectance likely correspond to RPE atrophy. Thus, hyperreflective ORTs border the retained pigmented RPE and extend out into the atrophied area as small tubular structures. An OCT cross-section, selected from the many individual scans used to derive the en face image (white line indicates where section was taken), illustrates that the hyperreflective features correspond to ORTs. Insets: Diagram of central pigmented RPE (filled-in gray) with surrounding tubular structures (lines).

Table 3

 

Summary of Outer Retinal Tubulation Correlation

 

In our cohort only one eye displayed cystoid macular edema. However, in 20% of eyes imaged there were mild degenerative cystic changes in the inner retina, unrelated to age, suggestive of a schisis (Fig. 5A). The OCT imaging of the central retina also showed other previously described features,^7,37,38 such as interlaminar bridges, loss of the outer retina, cystic spaces, focal RPE hyperplasia, all of which were independent of each other. The thinning of RPE/Bruch's membrane complex increased with age but could still be seen in some individuals 60 years of age. Although we did not measure the choroidal thickness, paramacular choroidal thinning was obvious by late teens (P17) and slowly progressed centrally. Choroidal changes also included increased size of choroidal lacunae and progressive collapse. The choroid was barely perceptible by the age of 60 years. Choroidal excavation³⁹ was noted in at least three eyes (P3, P5, and P12) at ages 54, 64, and 65 years, the significance of which has not been determined (Table 2). 

The Phenotype of Missense Mutations Is Not Different From That of Truncating Variants

Mutations (n = 37) were identified in 58 cases (Tables 2, 4), most of which were private. There were eight novel mutations including one missense mutation in two distantly related individuals, which is rarely documented. The phenotype of individuals with the missense mutation did not appear different from that of CHM patients with other mutation types, but this may reflect a limitation due to sample size. In fact, no phenotype–genotype correlations were observed at large. As documented in previous studies, the nonsense mutations were most common (40%) followed by the frameshift, splice site, and large deletion variants in equal proportion (19%). Novel mutations were validated, using information from the literature and various mutation databases (https://grenada.lumc.nl/LOVD2/Usher_montpellier/variants.php?select_db=CHM&action=view_unique; provided in the public domain by the Leiden Open Variation Database). The potential effect of novel variants was predicted by using Polyphen-2⁴⁰ and SIFT⁴¹ followed by segregation analysis and determination of allele frequency in a specific ethnic background if indicated. 

Table 4

 

Summary of Mutations Identified by Mutation Type

 

Discussion

Extending Previous Observations About Vision in CHM

There is a long history of clinical description of patients with the diagnosis of CHM as well as some reports that include postmortem eye donor retina histopathology.^42–46 Most of the original literature has preceded molecular confirmation but the distinctive fundus appearance and X-linked inheritance make those reports relevant.⁴⁷ The current work provided a comprehensive documentation of functional and OCT structural phenotype as a consequence of REP1 mutations, some of which are novel. Limitations of the current study included the retrospective nature of the data and the lack of regular serial follow-up intervals. Strengths included relatively large number of patients from two centers with overlapping approaches and relatively long-term follow-up period. 

For patients with REP1 mutations, it is clear that the central visual acuity and central retinal thickness by OCT are usually well preserved until the fourth decade of life and sometimes longer. Although central visual acuity changes did not correlate with age younger than 30 years (P = 0.46), it did for those older than 30 years (P < 0.0001), therefore a measure of disease progression only for that age group. Because the visual acuity changes observed were not linear, we could not determine a reliable time-related rate of vision loss unlike previous studies.^48–50 It has been reported that 33% of patients older than 60 years have 20/200 or worse vision.⁴⁹ In our cohort of patients older than 60 years (n = 4), the average visual acuity was 0.22 logMAR with one individual having normal vision. 

Color vision was abnormal in half of the patients studied, as early as 12 years of age, and this correlated with age. Abnormal color vision parallels the observation that the cone mosaic is disturbed on adaptive optics scanning laser ophthalmoscopy (AOSLO) imaging despite an often normal cone density and normal central visual acuity.⁵¹ The youngest case to have abnormal color vision was 12 years of age (P52; visual acuity: 0.3 logMAR and GVF I4e: 0.5% of normal), while the oldest to maintain normal color vision was 53 years of age (P56; visual acuity: 0 logMAR). The color vision was often maintained until the late 50s (Table 2; Fig. 3). Studies of color vision assessment in patients with CHM have yielded variable results with the most recent studies documenting some anomalies.^52–55 Unlike the recent study of Jolly et al.,⁵⁴ we did not observe any correlation with visual acuity (P = 0.11) but saw a correlation with age (P = 0.003). Our work supports that of Jolly et al.⁵⁴ in that the color vision changes did not follow any specific axis. These early functional changes in color vision reflect early cone dysfunction, which provides insight in the CHM-related degeneration and an additional potential outcome measure. The findings in the current work and that of Jolly et al.⁵⁴ indicate that a standardized but practical and sensitive measure of color vision should be included in the workups of patients with CHM. 

Kinetic perimetry has been a traditional outcome measure for peripheral visual field measurement and there have been many examples of fields shown in CHM studies.^{42–45,47,56} To our knowledge, there has not been an attempt to date to quantify and characterize the rate of change of perimetry with age in CHM. We reviewed kinetic perimetry results of 57 patients (33 had data from two or more visits) and showed that the changes observed for the I-4e, III-4e, and V-4e isopters were related to age. The changes observed with the I-4e isopter were the earliest and the fastest (Fig. 2). This is consistent with most other such studies of RP using comparable methods.^{25,26,29,57–62} For the V-4e target, the CHM visual field change of 8.3% per year is within the lower rates published by previous retinitis pigmentosa studies, other than specifically adRP (ranging from approximately 5%–10% per year).^61,63,64 Usher syndrome studies have tended to report higher rates of decline per year for V-4e (ranging from 11%–14%^28,29). The rate of change related to the I-4e target, 27.7% per year, was higher than for the V-4e rate in this cohort of CHM patients and results were generally similar, albeit with slightly faster progression, to those reported for other forms of RP.^28,58 

The kinetic perimetry data we presented allow for prediction of field loss in CHM and will be useful for guiding patients inquiring about a prognosis. Measures of intervisit variability were not performed and this would be required if kinetic perimetry was considered for disease monitoring. Results of static threshold perimetry would be very valuable to monitor patients in clinical trials. Such data have not been reported for the CHM peripheral field, either as dark- or light-adapted threshold perimetry. Ongoing GT trials of CHM are mainly subretinal injections directed at the central retina.⁹ The use of fundus perimetry (also called microperimetry) has been very helpful to date to understand central retinal function and would be useful in assessing CHM patients. Future trials, whether GT or other treatment modalities, may target extracentral retina in which case threshold data for change in peripheral function will then be required to decide the most favorable treatment sites and to monitor posttreatment changes. 

Retinal Structure Following the Effects of REP1 Mutations

Retinal structural changes using OCT have been observed to involve different layers of the retina in CHM patients.^{7,37,50,65,66} Thinner CRT was significantly associated with worse visual acuity and older age. An important observation was that ORTs were observed in 34 of the 39 cases (87%) imaged; there was no obvious relation to age or the type of mutation involved. Outer retinal tubulations have also been noted in a number of other inherited retinal degenerations,^67–69 but only Bietti crystalline retinopathy seems to show ORTs frequently.^70,71 Other studies have reported ORTs in CHM,^{7,37,51,69,72} but the high frequency of this pathologic finding in our cohort leads to the suggestion that ORTs may be an expected part of the CHM phenotype. The presence of ORTs in patients at early ages suggests the effect is not simply a late-stage abnormality. Our en face OCT imaging technique, as has been used in studies investigating ORTs in AMD,^33,35 revealed many branched structures surrounding the area of retina with residual photoreceptors and RPE. Correlative OCT cross-sections indicate that these branched structures are the ORTs, as has also been shown in AMD images.^33,35,36 

What is the histopathologic basis of these features and how do they relate to the pathophysiology of CHM? Human postmortem retinal histopathology in CHM has noted rosette-like structures formed by abnormal photoreceptors^4,46 and these may be the ORTs seen with OCT. The rosette-like structures were documented in a postmortem retina of a 19-year-old CHM patient,⁴⁶ indicating that our observations of ORTs in younger patients has a morphologic basis. Our comparison between OCT en face and cross-sections showed that the ORTs in CHM are also in the outer nuclear layer (ONL), which is similar to the well described histopathologic studies of ORTs in AMD.^34,73 Whether the ORTs of CHM represent tubes of degenerating cone photoreceptors, as in AMD,^34,73 is uncertain. In donor studies of RP, there have been rare reports of rosettes comprised of S-cones but not rods or L/M-cones⁷⁴ and rosettes comprised of mostly rods but not cones.⁷⁵ Considering that the ORTs in CHM were adjacent to but not within preserved areas of ONL, it can be speculated that they are a sequela leading from photoreceptor degeneration, as an unusual form of retinal remodeling. The phases of retinal remodeling have been studied in great detail for more than a decade in many murine models of retinal degeneration and to our knowledge, there is no specific description of a structure resembling an ORT.^5,6,76 The pseudorosettes widely seen in mouse retinopathy models,⁷⁷ as well as other types of rosettes, have been considered different than ORTs.³⁴ Further en face imaging, extending as far as the OCT will permit, should at least answer questions about the more peripheral extent of the tubular structures and whether they stop or continue beyond borders of more viable-appearing RPE and ONL. 

What Is the Clinical Relevance of the Current Results?

As gene augmentation clinical trials have started in CHM,^{6,9,13–15,17,78,79} it becomes important that molecular testing be available to any patient with a CHM-like phenotype and that the CHM phenotype be thoroughly characterized. Defining the phenotype as a function of time is important to accurately stage the disease process and understand outcomes. From the ongoing gene therapy clinical trials, it is acknowledged that the initially selected participants were at different disease stages, which challenges the interpretation of results.¹⁰ 

It is now apparent that central visual acuity is not a good parameter of the disease stage for CHM patients younger than 30 years, while the OCT, color vision, and visual fields could provide more useful information. An understanding of the natural history of CHM-related retinal degeneration, the characteristics of the phenotype, and the correlation between surrogate measures will assist in properly staging the disease severity. Accuracy in defining a “stage” of retinal degeneration, similar to what is done for tumors,^80,81 is becoming increasingly important to optimize the design and selection of interventions and candidates. 

Phenotyping of CHM and other retinal dystrophies merits the development of some guidelines that would include the structural and functional measures of retinal degeneration. This would allow a better interpretation of larger sets of data from different centers, and most likely better reflect the natural history of disease as well as allow an optimal selection of outcome measures and patient management. 

Acknowledgments

The authors are grateful for assistance in figure design by Thomas Wright, PhD, Alejandro J. Roman, MSc, and Alexander Sumaroka, PhD. 

Supported by the Mira Godard Research Fund, the Brendan Eye Research fund (EH), and Foundation Fighting Blindness (SGJ, AVC). The authors alone are responsible for the content and writing of the paper. 

Disclosure: E. Heon, None; T. Alabduljalil, None; D.B. McGuigan III, None; A.V. Cideciyan, None; S. Li, None; S. Chen, None; S.G. Jacobson, None