InsightRP2
Exploring
New Research Paths
Towards Modern Therapies
The InsightRP2 consortium embodies a groundbreaking and exceptionally innovative research approach that integrates complementary expertise to understand the complex pathophysiological aspects of RP2-associated retinitis pigmentosa and to develop new therapeutic options.
What distinguishes the consortium is its cohesive structure; it functions not as a collection of isolated, parallel research lines, but as a tightly woven framework that actively and systematically links the various research areas. To achieve this, we bring together highly motivated experts in ophthalmology, human genetics, data science, cell biology and gene therapy. InsightRP2 enables us to feed clinical observations into mechanistic studies, to use bioinformatics approaches for variant interpretation and experimental design, and to translate (patho)physiological findings into therapeutic strategies.
Digital ophthalmology
Digital ophthalmology
Using custom-developed AI algorithms, we analyse retinal imaging data including fundus images and OCT scans from patients with RP2-associated RP, detecting and decoding even subtle structural changes in the retina. Through this approach, we aim to describe disease progression based on objective morphologic criteria and to enhance clinical diagnostics, progression monitoring and assessment of treatment efficacy.
In Depth
RP2-associated retinitis pigmentosa is characterized by progressive photoreceptor loss and substantial structural remodeling of the retina. These phenotypic changes present as distinct biomarkers across different imaging modalities: color fundus photography captures characteristic vessel attenuation and the accumulation of pigment clumps on the retinal surface, while optical coherence tomography (OCT) provides cross-sectional views of retinal layer alterations (e.g. outer segment thinning), disruption of microstructures due to photoreceptor loss, macular changes and microvessel alterations. Additionally, fundus autofluorescence images can identify disturbed metabolic activity within the retinal tissue, presenting as hyperautofluorescent or hypoautofluorescent areas of the retina.
To transform these complex visual features into meaningful and quantifiable data, we train specialized models for each imaging modality. This process allows us to identify key indicators of specific disease stages, ranging from known clinical markers to subtle patterns that only computer models can detect. The information from these different imaging data will then be combined into a single, high-dimensional digital map. This unified dataset acts as a foundation for high precision retinal segmentation, objective disease grading, and disease progression modeling. We expect to define a digital morphology atlas of the natural course of RP2-associated retinitis pigmentosa.
By integrating digital morphology profiles with genetic and clinical information, we seek to better characterize inter-individual variability in disease progression and explore potential genotype–phenotype correlations. Finally, the RP2-specific digital morphology atlas may facilitate the development of standardized inclusion criteria and clinically relevant endpoints for future therapeutic trials.
Variant scanning
Variant scanning
By means of advanced digital high-throughput technologies and experimental functional assays, we systematically identify all theoretically possible variants in the RP2 gene and investigate their functional implications. This allows us to evaluate variants of uncertain significance in a more differentiated manner and to make them amenable to molecular interpretation.
In Depth
Functional mapping of RP2 variants
More than half of the missense variants in the RP2 gene listed in ClinVar are currently classified as variants of uncertain significance (VUS). The lack of functional evidence substantially hampers molecular genetic diagnosis in many individuals with suspected RP2-associated retinitis pigmentosa and limits the identification of suitable candidates for future clinical trials. To address this gap, we pursue an integrative strategy for the systematic prioritization and functional characterization of RP2 missense variants.
In our research, we combine several complementary in silico approaches that capture distinct aspects of potential variant effects. We use AlphaFold-based protein structure modeling to assess possible consequences of amino acid substitutions on RP2 protein folding, stability, and functional domains. In parallel, evolution-based models such as EVE/PoPEVE are applied to evaluate the functional relevance of individual amino acid changes by leveraging statistical protein sequence models and population genetic data. AlphaMissense is employed to predict the probability of pathogenicity for missense variants using a protein language model trained on large-scale protein sequence datasets. In addition, we use SpliceAI to test whether ostensibly missense variants may also alter pre-mRNA splicing. The outputs of these analyses are integrated into a combined prioritization score that jointly considers structural, evolutionary, and splicing-related features.
Variants with high prioritization scores are subsequently analyzed in cellular model systems using a panel of functional assays. These include measurements of RP2 protein expression and stability, assessment of subcellular localization, and assays probing RP2 activity and interactions with known binding partners.
In a platform-like approach, our long-term goal is to interrogate all biologically possible RP2 missense variants and consolidate the resulting information into a comprehensive functional dataset. This dataset will be made available as a resource to support more precise interpretation of RP2 variants in the molecular genetic diagnostics of RP2-associated disease. Ultimately, our work aims to increase the diagnostic yield in individuals with suspected RP2-associated retinitis pigmentosa and, in turn, to provide a larger proportion of patients with a definitive molecular diagnosis and access to targeted clinical care.
Mechanistic insights
Mechanistic insights
To further characterise the role of RP2, we introduce patient-relevant mutations into induced pluripotent stem cells and differentiate them into retinal tissues and organoids. Using HighEnd multi-omics technologies and integrative data analysis, we study cell type-specific
alterations and identify potential therapeutic targets.
In Depth
iPSC-based RP2 disease modeling
A central component of the InsightRP2 project is the establishment of human iPSC-based models reflecting patient genotypes to enable controlled, mechanistic studies of disease-relevant RP2 variants. Induced pluripotent stem cells (iPSCs) are generated from patient-derived cells and further engineered using CRISPR/Cas9-based genome editing. This allows defined RP2 variants to be introduced into an otherwise healthy genetic background or corrected in patient-derived iPSC lines. Such isogenic pairs of cell lines are particularly valuable, as disease-associated phenotypes can be directly attributed to the respective genetic change without confounding effects from inter-individual genetic variation.
From these iPSC lines, we first derive 2D retinal cell models to systematically investigate early, cell-autonomous effects of RP2 variants. These reductionist model systems offer a high degree of experimental control and are well suited for quantitative assays, including analyses of ciliary organization, protein localization, intracellular transport processes, cellular stress responses, photoreceptor-specific differentiation markers, and early degeneration signatures. By directly comparing mutant, corrected, and isogenic control lines, primary disease mechanisms can be identified and functionally validated. Complementary to 2D models, 3D retinal organoids are used to capture RP2-associated retinal degeneration in a more complex, tissue-like context. Retinal organoids comprise multiple retinal cell types and allow longitudinal analysis of developmental, maturation, and degeneration processes. This enables us to dissect cell type–specific alterations, particularly in photoreceptors, as well as interactions between distinct retinal cell populations. High-resolution imaging, transcriptomics, proteomics, and other multi-omics approaches are employed to identify disease-relevant signaling pathways, vulnerable cellular states, and mechanisms that are amenable to therapeutic targeting.
In addition, the iPSC-derived 2D and 3D models serve as an early-stage preclinical platform for testing therapeutic strategies. Candidate small molecules, gene replacement concepts, and genome editing approaches can first be assessed in robust 2D assays for efficacy, dose–response relationships, and cellular tolerability and subsequently validated under more tissue-like conditions in retinal organoids. In this way, the iPSC platform directly links mechanistic disease elucidation with translational therapy development and supports a rational prioritization of the most promising treatment strategies for RP2-associated retinitis pigmentosa.
Drug discovery
Drug discovery
Based on elucidated signalling pathways and cellular mechanisms, we systematically and specifically search for compounds that can stabilise or correct dysregulated processes. Our goal is to identify candidate substances that can be further evaluated in preclinical models and, in the longer term, in clinical studies.
In Depth
Identification of novel therapeutic compounds
RP2 functions as a GTPase-activating protein (GAP) for the small GTPase ARL3 and thereby indirectly participates in ciliary and vesicular trafficking processes controlled by ARL3. By binding to ARL3, RP2 contributes additional catalytic side chains to the active site of the ARL3 GTPase and accelerates the otherwise very slow GTP hydrolysis by a factor of approximately 90,000. Loss of RP2 leads to accumulation of ARL3‑GTP and mislocalization of cargo within the photoreceptor cilium.
Using state-of-the-art AI-based methods and the available crystal structure of the RP2–ARL3 complex, we aim to design molecules that directly complement the ARL3 active site and enhance its GTP hydrolysis. Based on the known ARL3‑GTP–RP2 structures, we will identify protein pockets that could accommodate a “synthetic finger” ligand. In this concept, small molecules or peptides would bind specifically to ARL3 and functionally mimic an arginine or lysine finger that stabilizes the transition state of GTP hydrolysis. In analogy to therapeutic strategies targeting RAS GTPases, we will also explore conformational modulation of the ARL3 switch regions to promote its intrinsic GTP hydrolysis independently of RP2. In addition, inhibition of ARL13B or ARL3 GTP loading may reduce ARL3‑GTP levels such that the remaining intrinsic hydrolysis becomes sufficient to lower the steady-state GTP fraction. Newly identified compounds and their effects on ARL3 GTP hydrolysis will first be evaluated in our cellular model systems.
Beyond direct modulation of ARL3, multi-omics profiling of retinal organoids will be used to uncover additional signaling pathways involved in RP2-associated retinal degeneration. We will investigate the cell-type-specific roles of these pathways in different retinal cell populations, with the goal of identifying new targets for mechanism-based pharmacological intervention.
Gene therapy
Gene therapy
We are establishing gene replacement strategies and genome editing approaches with the aim of developing a clinically applicable gene therapy for RP2-associated retinitis pigmentosa. The comparatively small RP2 gene is particularly well suited for gene transfer and thus opens up promising therapeutic opportunities.
In Depth
Since most known disease-causing RP2 variants result in a loss of RP2 protein function, gene addition represents a particularly promising therapeutic strategy, further facilitated by the relatively short coding sequence of the RP2 gene (1053 nucleotides). However, to our knowledge, no gene-based therapeutic approach for RP2 has yet entered clinical development.
Within InsightRP2, we are developing strategies for local RP2 gene addition. For this, we use adeno-associated viral (AAV) vectors and optimize vector design to achieve efficient and targeted restoration of RP2 function in affected photoreceptors and retinal ganglion cells. Because transgene expression efficiency can differ substantially between species, we plan to evaluate AAV-based gene therapy not only in differentiated photoreceptors but also in retinal organoids, providing a physiologically relevant context to assess vector performance prior to validation in animal models. Additional key aspects include comparing the efficacy of photoreceptor-specific versus ubiquitous promoters and assessing the transduction efficiency of different capsids across retinal cell types.
Beyond gene addition, in vivo delivery of base and prime editors offers the potential for mutation-specific correction of selected RP2 variants and may represent an alternative therapeutic strategy in the future.