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ESR8: ABCA4 transcript analysis of retinal cells derived from mono-allelic STGD1 cases

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Partner
NewCells Biotech Ltd, Newcastle, United Kingdom (newcellsbiotech.co.uk)
Supervisor
Prof. Dr. M. Lako
Avril Watson
My name is Avril, I’m originally from Dublin, Ireland. I achieved both my Bachelor in Genetics and my Masters in Immunology at Trinity College Dublin, which allowed me to apply for the fantastic StarT Marie Curie ITN Programme to carry out my PhD research. I was fortunate enough to spend 3.5 years under the supervision of Prof. Majlinda Lako and her fantastic team at Newcastle University in the UK, modelling the spectrum of Stargardt disease (late onset & classic forms) using pluripotent stem cells and retinal organoid technology. During this project, we were able to identify several altered molecular pathways in matured retinal organoids indicative of photoreceptor degeneration in STGD1, even in the absence of diseased RPE tissue. We published a review article based on the work done in the Lako lab during my PhD, and a primary research article is in editing and will soon be submitted based on my own PhD work.
I had a fantastic experience during my PhD in both my host lab at Newcastle University and with my fellow ESRs in StarT. It was an amazing opportunity to network and meet well-established researchers in the vision field. The StarT network allowed me to gain confidence in my scientific skills and communication, form lifelong connections and allowed me to contribute to a research field I have been passionate about since my undergraduate degree in 2018.
I obtained my PhD in November 2023 with my thesis; ‘Modelling Stargardt Disease Using iPSC-Derived Retinal Organoids: Insights into Pathology and Genotype/Phenotype Correlations’. I moved back to Ireland last year and I’m currently working as a Postdoctoral researcher with Prof. Sarah Doyle in Trinity College Dublin. My current work is focused on the immunobiology of retinal degeneration with a focus on developing an in vitro ‘fibrosis on a chip’ model for the study of age-related macular degeneration (AMD). I bring a wealth of skills from my PhD research in this endeavour and have plans to continue my stem-cell-derived retinal organoid modelling in collaboration with my previous mentor Prof. Lako.
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Abstract
In this study, we generated iPSC lines from two monoallelic (PT1 & PT2), late-onset STGD1 cases with the heterozygous complex allele - c.[5461-10T>C;5603A>T]. We differentiated these cells alongside a biallelic affected control (AC) - c.4892T>C, and c.4539+2001G>A, to retinal organoids (ROs) allowing us to investigate cellular and molecular characteristics associated with STGD1. We hypothesised that the missing inheritance in our monoallelic cases is due to an RNA defect. Consequently, we utilised a myriad of sequencing strategies including WGS, single-cell RNA sequencing (scRNAseq) and long-read RNA sequencing (LRS) to address this. 
ROs were grown for 230 days and developed all key retinal neurons with photoreceptor outer segments capable of ABCA4 expression. We observed patient-specific disruption to lamination with OPN1MW/LW+ cone photoreceptor retention in the RO centre during differentiation. Retention was more severe in the AC case affecting both cones and rods, suggesting a genotype/phenotype correlation. scRNAseq suggests retention may be due to the induction of apoptosis in photoreceptors. WGS successfully identified the missing alleles in both cases; PT1 reported c. 5603A>T in homozygous state and PT2 uncovered a rare hypomorph - c.4685T>C. Furthermore, ROs were able to recapitulate the retina-specific splicing defect in PT1 as shown by LRS data.
Collectively, these results highlight the suitability of ROs in STGD1 modelling. Their ability to display genotype-phenotype correlations enhances their utility as a platform for therapeutic development. Importantly, both PT1 and PT2 cases were genetically resolved in this study, providing two more individuals with their confirmed genetic diagnosis.
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This project has received funding from the European Union's Horizon 2020 research and innovation programme Marie Sklodowska-Curie Innovative Training Networks (ITN) under grant No.
813490
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