You are here: vision-research.eu » Vision Research » Visionary of the Quarter » Frank G. Holz (Q03-2020)
Age-related macular degeneration (AMD) is a leading cause for global blindness. Despite a major therapeutic breakthrough in neovascular disease states, the advanced atrophic late-stage manifestation (geographic atrophy - GA), with exponential increase in prevalence with age, represents a major unmet need. Earlier stages of the disease including intermediate AMD not only lack a treatment for halting or slowing progression, but also an approvable endpoint for testing efficacy of potential interventions. A multidisciplinary approach with both basic and clinical science is needed to better understand the underlying pathophysiology, to identify treatment targets and ultimately to develop efficacious therapies. This was the starting point when we early on established a DFG (German Research Council) priority research program (SPP 1088) “age-related macular degeneration” encompassing multifaceted disciplines. A base was formed for many subsequent collaborations both nationally and internationally as well as for later research funding.
Fundus autofluorescence (FAF) imaging using confocal scanning laser ophthalmoscopy (cSLO) allows for topographic mapping of naturally or pathologically occurring intrinsic fluorophores. The dominant sources are fluorophores accumulating in the lysosomal compartment of postmitotic retinal pigment epithelium cells as well as other fluorophores that may occur with disease in the outer retina and subretinal space. FAF imaging has been shown to be useful with regard to understanding of pathophysiological mechanisms, diagnostics, phenotype-genotype correlation, identification of prognostic markers for disease progression, and novel outcome parameters to assess efficacy of interventional strategies in retinal diseases. More recently, the spectrum of FAF imaging has been expanded with use of green FAF, introduction of spectrally-resolved FAF, near-infrared FAF, and quantitative FAF imaging.
We have shown that FAF imaging is one of the most reliable imaging modalities to detect, delineate, reproducibly quantify, and monitor progression of outer retinal atrophy. The loss of RPE and its inherent fluorophores in GA correlates with well-defined areas of decreased autofluorescence, allowing for precise manual, semi-automatic or automatic GA segmentation methods based on FAF imaging. Hereby, the semi-automatic region-growing image analysis approach has been integrated in a now commercially available software (RegionFinderTM Heidelberg Engineering).
Based on various natural history studies including the FAM-study conducted by our team GA lesion growth based on FAF imaging has become an accepted primary structural outcome measure by the regulatory authorities including FDA in prospective interventional GA-trials.
A striking finding of FAF imaging in GA is the frequent presence of areas of relative increased FAF in the junctional zone surrounding atrophic patches. Looking at larger patient groups with longer review periods, the significance of increased junctional FAF for foreshadowing atrophy enlargement has been demonstrated Distinct patterns of abnormal FAF in the junctional zone of atrophy and a high degree of intraindividual symmetry between fellow eyes have subsequently been described by our group. A classification system of abnormal FAF patterns in the junctional zone of atrophy in GA patients has been developed, used as inclusion criterion for patient selection in GA-trials (fast progressors). Furthermore, studies of retinal sensitivity have underscored the relevance of FAF surrounding areas of GA
In addition to FAF patterns in the junctional zone we showed that several other factors can inform an individual’s disease prognosis including baseline lesion size, lesion location, multifocality, presence of reticular pseudodrusen and fellow eye status. Correlations with other imaging modalities has subsequently been sought by the international CAM-group (Classification of Atrophy Meeting) who also addressed the sequence from incomplete to complete outer retinal atrophy in the context of AMD.
FAF imaging is now widely used also in the context of other complex and monogenetic retinal degenerations. As an example in a rare disease our group found a abnormally increased FAF signal in the macular area to a variable degree with blue-light FAF imaging in eyes with macular telangiectasia (MacTel) type 2 due to deficiencies in trafficking and storage of luteal pigment. This is now considered a hallmark phenotypic feature in this slowly progressive neurodegenerative disease of the central retina and also serves as a prognostic biomarker.
To probe potential genetic factors various studies have been conducted with Bernhard Weber’s group (University of Regensburg). Recently, in 935 patients with longitudinal GA progression data were analyzed to determine the contribution of common genetic variants to GA lesion growth. Two gene loci with conservative genome-wide significance were identified. Each minor allele of the genome-wide associated variants increased the GA growth rate by a mean of about 15% or 0.05 mm per year. Gene prioritization within each locus suggested the protein arginine methyltransferase 6 gene (PRMT6) and the lanosterol synthase gene (LSS) as the most likely progression-associated genes.
Artificial intelligence (AI)/deep learning offers a new horizon for analyzing digital images and personalized medicine based on these analyses. Human visual grading of retinal images is inherently limited, e.g. by the required time/ressources and limited visual resolution of humans. We are particularly interested in automated quantifications of AMD features on OCT such as different phenotypes of drusen, focal high-risk pigmentary changes quantification as well as in mapping retinal function de novo in order to provide an en-face high-resolution map of predicted retinal sensitivity (“inferred sensitivity”) based on structural information. Hereby machine learning algorithms are applied to predict functional impairment based on multimodal imaging. This may be applicable in future interventional trials to allow for refined investigation of treatment effect superior to standard functional testing without the need for psychophysical examinations such as mesopic and scotopic microperimetry. AI-based quantifications recently also allowed the demonstration of the protective effect of type 1 CNV on the RPE and overlying neurosensory retina in eyes with geographic atrophy with clinical implications for the management of CNV and new therapeutic strategies to prevent atrophy progression.
Preventing late-stage disease by therapeutic intervention may be considered the holy grail in AMD. However, currently, no outcome measures are clinically validated and accepted as clinical endpoints by regulatory agencies for drug development in intermediate age-related macular degeneration. The MACUSTAR consortium, a public-private research group funded by the European Innovative Medicines Initiative, intends to close this gap. A large natural history study across 20 clinical sites in Europe currently ongoing will address structural and functional and patient outcome aspects of intermediate AMD including machine-learning approaches for identifying prognostic biomarkers. This observational study consists of a cross-sectional and a longitudinal part. Functional outcome measures assessed under low contrast and low luminance have the potential to detect progression of visual deficit within iAMD and to late AMD. Structural outcome measures will be multimodal and investigate topographical relationships with function. As clinical endpoints currently accepted by regulators cannot detect functional loss or patient-relevant impact in iAMD, we will clinically validate novel candidate endpoints for iAMD.
FEBO, FARVO
University of Bonn
Deptartment of Ophthalmology
Ernst-Abbe-Straße 2
D-53127 Bonn
Germany
Phone: +49 (0)228 / 287 - 15646
E-mail: Frank.Holz[at]ukbonn.de
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