Background Inherited retinal diseases (IRDs) are a leading cause of blindness in children and working age adults in the United Kingdom and other countries, with an appreciable socioeconomic impact. However, by definition, IRD data are individually rare, and as a result, this patient group has been underserved by research. Researchers need larger amounts of these rare data to make progress in this field, for example, through the development of gene therapies. The challenge has been how to find and make these data available to researchers in the most productive way. MyEyeSite is a research collaboration aiming to design and develop a digital platform (the MyEyeSite platform) for people with rare IRDs that will enable patients, doctors, and researchers to aggregate and share specialist eye health data. A crucial component of this platform is the MyEyeSite patient application, which will provide the means for patients with IRD to interact with the system and, in particular, to collate, manage, and share their personal specialist IRD data both for research and their own health care. Objective This study aims to test the acceptability and feasibility of the MyEyeSite platform in the target IRD population through a collaborative patient-centered study. Methods Qualitative data were generated through focus groups and workshops, and quantitative data were obtained through a survey of patients with IRD. Participants were recruited through clinics at Moorfields Eye Hospital National Health Service (NHS) Foundation Trust and the National Institute for Health Research (NIHR) Moorfields Biomedical Research Centre through their patient and public involvement databases. Results Our IRD focus group sample (n=50) highlighted the following themes: frustration with the current system regarding data sharing within the United Kingdom’s NHS; positive expectations of the potential benefits of the MyEyeSite patient application, resulting from increased access to this specialized data; and concerns regarding data security, including potentially unethical use of the data outside the NHS. Of the surveyed 80 participants, 68 (85%) were motivated to have a more active role in their eye care and share their data for research purposes using a secure technology, such as a web application or mobile app. Conclusions This study demonstrates that patients with IRD are highly motivated to be actively involved in managing their own data for research and their own eye care. It demonstrates the feasibility of involving patients with IRD in the detailed design of the MyEyeSite platform exemplar, with input from the patient with IRD workshops playing a key role in determining both the functionality and accessibility of the designs and prototypes. The development of a user-centered technological solution to the problem of rare health data has the potential to benefit not only the patient with IRD community but also others with rare diseases.

As high-throughput sequencing is increasingly applied to the molecular diagnosis of rare Mendelian disorders, a large number of patients with diverse phenotypes have their genetic and phenotypic data pooled together to uncover new gene-phenotype relations. We introduce Phenogenon, a statistical tool that combines, Human Phenotype Ontology (HPO) annotated patient phenotypes, gnomAD allele population frequency, and Combined Annotation Dependent Depletion (CADD) score for variant pathogenicity, in order to jointly predict the mode of inheritance and gene-phenotype associations. We ran Phenogenon on our cohort of 3,290 patients who had undergone whole exome sequencing. Among the top associations, we recapitulated previously known, such as "SRD5A3-Abnormal full-field electroretinogram-recessive" and "GRHL2-Nail dystrophy-recessive", and discovered one potentially novel, "RRAGA-Abnormality of the skin-dominant". We also developed an interactive web interface available at https://phenogenon.phenopolis.org to visualise and explore the results.

IntroductionInherited retinal diseases (IRD) are a leading cause of visual impairment and blindness in the working age population. Mutations in over 300 genes have been found to be associated with IRDs and identifying the affected gene in patients by molecular genetic testing is the first step towards effective care and patient management. However, genetic diagnosis is currently slow, expensive and not widely accessible. The aim of the current project is to address the evidence gap in IRD diagnosis with an AI algorithm, Eye2Gene, to accelerate and democratise the IRD diagnosis service.Methods and analysisThe data-only retrospective cohort study involves a target sample size of 10 000 participants, which has been derived based on the number of participants with IRD at three leading UK eye hospitals: Moorfields Eye Hospital (MEH), Oxford University Hospital (OUH) and Liverpool University Hospital (LUH), as well as a Japanese hospital, the Tokyo Medical Centre (TMC). Eye2Gene aims to predict causative genes from retinal images of patients with a diagnosis of IRD. For this purpose, 36 most common causative IRD genes have been selected to develop a training dataset for the software to have enough examples for training and validation for detection of each gene. The Eye2Gene algorithm is composed of multiple deep convolutional neural networks, which will be trained on MEH IRD datasets, and externally validated on OUH, LUH and TMC.Ethics and disseminationThis research was approved by the IRB and the UK Health Research Authority (Research Ethics Committee reference 22/WA/0049) ‘Eye2Gene: accelerating the diagnosis of IRDs’ Integrated Research Application System (IRAS) project ID: 242050. All research adhered to the tenets of the Declaration of Helsinki. Findings will be reported in an open-access format.

Introduction Co-use of tobacco and cannabis is highly prevalent among cannabis users and is associated with poorer tobacco cessation outcomes. This study explored the barriers and enablers influencing stop smoking practitioners’ ability to provide optimal support to co-users. Methods Online semi-structured interviews were audio recorded. Interviewees (n = 20) were UK-based certified stop smoking practitioners. An interview schedule informed by the ‘capability’, ‘opportunity’, ‘motivation’ (COM-B) model was designed to explore participants’ perceived barriers and enablers in better supporting co-users to achieve abstinence of both substances or tobacco harm reduction. The transcripts were analysed using framework analysis. Results Capability: practitioners’ lack of knowledge and skills undermines their delivery of smoking cessation interventions to co-users. Interestingly, when cannabis is used for medicinal reasons, practitioners feel unable to provide adequate support. Opportunity: service recording systems play an important role in screening for co-use and supporting co-users. When responding to clients’ specific needs and practitioners’ uncertainties, a positive therapeutic relationship and a support network of peers and other healthcare professionals are needed. Motivation: supporting co-users is generally perceived as part of practitioners’ roles but there are concerns that co-users are less likely to successfully stop smoking. Conclusions Practitioners are willing to support co-users, but their lack of knowledge and access to an appropriate recording system are barriers to doing so. Having a supportive team and a positive therapeutic relationship are perceived as important. Identified barriers can be mostly addressed with further training to improve tobacco cessation outcomes for co-users. Implications Supporting cannabis-related abstinence or harm reduction among co-users constitutes an essential part of stop smoking practitioners’ role. In order to offer adequate support, practitioners need appropriate recording, referral systems, as well as comprehensive training. By prioritizing these measures, practitioners shoud be able to better assist co-users and improve tobacco cessation outcome.