Gareth Baynam

Background: An estimated 1 in 12 individuals across the world have a rare disease. The Undiagnosed Diseases Network International (UDNI) recommend Undiagnosed Disease Programs (UDPs) as the best approach to facilitate diagnosis and support for those affected. The Australian Undiagnosed Diseases Network (UDN-Aus) was the first National Australian UDP initiative funded by the Medical Research Future Fund’s Genomics Health Futures Mission (MRFF2007567). Aims: UDN-Aus brings together an unprecedented national collaborative network for rare disease, aiming to improve the rate of genomic diagnoses for those with undiagnosed rare genetic conditions, enabling precise, personalised care to individuals throughout Australia. Methods: The research program recruited Australians who were seen through a clinical genetics service and remained undiagnosed following clinically available genomic testing. This paper outlines the approach taken to establish a national research project at 12 clinical recruitment sites. The methods detail the funding, aims, governance, study design, population and participation process, health economic research and preliminary results, and recommendations for future sustainability and implementation. Results: The study was approved by the Royal Children’s Hospital Human Research Ethics Committee on 19 November 2021 (RCH79712), with relevant site-specific approvals at local recruitment sites. Key benefits and barriers in the establishment of UDN-Aus are outlined. Conclusion: The successful establishment of this program required several components, including meaningful and ongoing community and stakeholder engagement, strategic appointment of key operational staff, and a tailored approach to facilitate more equitable enrolment. It also highlighted several crucial areas for consideration to ensure future sustainable implementation of a national UDP. These include continued investment in Australia’s national genomic data transfer policy and infrastructure, and research ethics and governance procedures imperative for the sustainable delivery of genomic research for rare disease.

Background: As part of Singapore’s effort towards precision medicine tailored to Asian diversity, we describe the implementation of a nationwide reproductive carrier screening program. Using a customised 112-gene panel, targeting population-specific recessive genetic diseases, we outline the overall program design, and initial efforts of community and stakeholder engagement to inform culturally appropriate implementation. Methods: Participants receive culturally tailored online education regarding our reproductive screening program and are provided results with genetic counselling and reproductive options. Engagement with religious leaders indicated support for the program. Community and stakeholder perspectives were assessed through questionnaires. Results: Recruitment is nation-wide, and since initiation of our pilot phase in September 2024, 1,619 couples have registered interest, with 60% uptake of those deemed eligible. Among the 550 couples that have received results to date, six couples (1.0%) were identified to be at increased risk. Community questionnaire responses ( n = 1,002), involving couples who participated in the program as well as the general public, indicated interest was high (59%) across the cohort but awareness, intent to participate and implications for reproductive options differed by sociodemographic factors such as ancestry and religion. Healthcare professional respondents ( n = 113) acknowledged carrier screening will be routine in medical care, but report limited confidence and resources. Conclusions: These early program outcomes and community engagement are guiding the implementation of expanding population-based carrier screening in Singapore, contingent on addressing practical challenges through equitable outreach and professional training.

Background: People living with rare diseases (PLWRD) often face significant challenges in receiving timely and accurate diagnoses, leading to what is known as a diagnostic odyssey. Digital phenotyping (DP) offers a promising solution by leveraging advanced technology to capture unique digital signatures associated with various rare diseases. This innovative approach not only aids in the identification of these conditions but also facilitates the detection of digital biomarkers (DBM). By utilizing DP and DBMs, we can improve both the diagnosis and management of RDs, ultimately leading to better health outcomes for affected participants. Objective: To identify whether DBMs can be identified by DP utilizing 3D facial imaging techniques in outpatient settings in participants with RDs. Design, setting, and participants: This multicentre observational study was conducted in 3 hospitals in Singapore. The eligible participants were male and female RD participants of various age groups. The study duration was 4 years and 8 months. Interventions: Twenty participants of Chinese genetic ancestry were photographed using a 3D camera. Additionally, two participants with hereditary angioedema (HAE) were photographed during acute stages of disease flare-ups. Main outcomes and measures: The obtained facial scans of participants (that included participants with HAE in non-acute phase) were plotted using Artificial Intelligence-powered software - Cliniface. The growth curves and facial landmarks obtained were compared against the growth curves of normal RD-unaffected individuals of Chinese genetic ancestry. The two participants with HAE were photographed qualitatively over a longer period of time, and their scans were plotted, yielding growth curves. Results: Distinct facial markers such as periorbital swelling were identified in two qualitatively assessed HAE participants during flare-up stages. This provides an opportunity to explore and validate whether these facial signatures in a disease condition can be assigned as DBM for HAE. Conclusions: and relevance: This study explores the utility of 3D facial analysis as a DBM in rare diseases such as HAE. These findings offer preliminary objective evidence that supports existing subjective reports of facial features in the literature. Additionally, while DP's diagnostic capabilities may be limited, it successfully identified DBM, which could facilitate disease monitoring in conditions such as HAE.

In this literature review conducted by EURORDIS, we examine the psychological and psychosocial needs of people living with a rare condition and their families. The findings highlight that people living with a rare condition and their families face common and persistent challenges. These include chronic uncertainty, limited access to reliable information, stigma, social isolation, and difficulties navigating fragmented healthcare systems. Many individuals and caregivers also take on the role of coordinating care themselves, often without adequate support. The report emphasises that psychological needs evolve over time, particularly at key stages such as diagnosis, disease progression, and transition to adult care. Despite this, psychological and psychosocial support remains a major unmet need across the rare disease community. In response, the report calls for more integrated, family-centred and multidisciplinary care, with psychological support embedded throughout the care pathway and stronger links with patient organisations to better support individuals and families.

In this EURORDIS paper, we explore the importance of psychological support to live will with a rare disease. The literature review highlights the importance of integrating psychological and psychosocial support into rare disease care pathways, particularly at key stages such as diagnosis and disease progression, when emotional distress and uncertainty are often highest. The findings demonstrate that family-centred and community-based approaches improve wellbeing. Interventions that strengthen coping strategies, such as acceptance, resilience, and self-efficacy, are associated with better mental health outcomes and quality of life. Access to peer support, social networks, and clear, reliable information also plays a key role in helping individuals and families manage the challenges of living with a rare condition. The paper calls for more holistic, multidisciplinary and psychologically informed care models, with psychological support embedded throughout care pathways. It also calls for stronger policy action to address gaps in provision and ensure equitable access to mental health and psychosocial support across rare disease systems.

Importance: Digital Phenotyping (DP) utilizes digital technologies to assess observable phenotypic traits, enhancing our understanding of various disease states. It aims to support equitable interventions through diverse digital data, fostering inclusivity by integrating various digital devices. Central to DP is identifying digital biomarkers (DBMs), which offer real-time health monitoring and personalized insights into disease conditions. Applying machine learning (ML) techniques on non-invasive signals sets the ideal platform for precision medicine application, especially in rare diseases (RDs). People living with rare diseases (PLWRD) often face significant challenges in receiving timely and accurate diagnoses, leading to what is known as a diagnostic odyssey. Digital phenotyping (DP) offers a promising solution by leveraging advanced technology, such as 3D facial photography, to capture unique digital signatures associated with various rare diseases. This innovative approach not only aids in the identification of these conditions but also facilitates the detection of digital biomarkers (DBM). These biomarkers enable healthcare providers to monitor the progression of the disease over time, enhancing patient care and potentially shortening the duration of the diagnostic odyssey. By utilizing DP and DBMs, we can improve both the diagnosis and management of RDs, ultimately leading to better health outcomes for affected participants. Objective: To identify whether DBMs can be identified by DP utilizing 3D facial imaging techniques in outpatient settings in participants with RDs. The primary objective of this study was to determine if specific facial measurements in participants with RD who experience transient episodes of facial swelling (oedema) differ from established ethnically matched norms. The secondary objective was to assess peri-orbital and/or facial swelling as a potential biomarker for identifying flare-ups in hereditary angioedema (HAE). Design, setting, and participants: This multicentre observational study was conducted in 3 hospitals in Singapore. The eligible participants were male and female RD participants of various age groups. The study duration was 4 years and 8 months. Interventions: Twenty participants of Chinese genetic ancestry were photographed using a 3D camera. Additionally, two participants with hereditary angioedema (HAE) were photographed during acute stages of disease flare-ups. Main outcomes and measures: The obtained facial scans of participants (that included participants with HAE in non-acute phase) were plotted using Artificial Intelligence-powered software - Cliniface. The growth curves and facial landmarks obtained were compared against the growth curves of normal RD-unaffected individuals of Chinese genetic ancestry. The two participants with HAE were photographed qualitatively over a longer period of time, and their scans were plotted, yielding growth curves. Results: Distinct facial markers such as periorbital swelling were identified in two qualitatively assessed HAE participants during flare-up stages. This provides an opportunity to explore and validate further if these facial signatures in a disease condition can be assigned as DBM for HAE. Conclusions and relevance: This study explores the utility of 3D facial analysis as a DBM in rare diseases such as HAE. Applying non-invasive signals coupled with AI may open new vistas for precision medicine in real-world settings. The individual measurements that yielded small p-values demonstrate significant relevance and potential utility. These findings offer preliminary objective evidence that supports existing subjective reports of facial features in the literature. Additionally, while DP’s diagnostic capabilities may be limited, it successfully identified DBM, which could facilitate disease monitoring in conditions such as HAE. Author Summary: Rare diseases pose a significant challenge to all stakeholders, including clinicians, patients’ families, care providers, and the healthcare system. Diagnostic delays are integral and impose a massive financial and emotional burden on everyone involved in care delivery, beyond the patients themselves. A universally acceptable, scalable, and replicable non-invasive mechanism to detect distinct biomarkers associated with a rare disease can help identify the disease’s signs and symptoms far earlier and ease the burden. An easy-to-deploy approach could be 3D facial imaging of patients with rare diseases, which are associated with distinct or subtle facial changes at different stages of disease progression. A rare disease, such as hereditary angioedema, which is known to exhibit facial swelling in patients during the acute disease state, is a prime example. The facial changes can be identified and assigned as specific disease markers, also known as facial biomarkers. These facial biomarkers can be identified and measured using 3D facial imaging when patients present to the clinic. Subsequently, these initial signs can be correlated clinically to establish a firm diagnosis earlier than traditional approaches.

Multi-omics in combination with advanced computational methodologies synthesizes diverse omics data to provide deeper insights into molecular interactions

Artificial intelligence (AI) can transform rare disease care when organized around the patient journey. We outline a patient–clinician–AI triad spanning early detection, diagnosis, clinical trials, and individualized therapies.

Introduction: The promise of precision medicine lies in its ability to provide greater diagnostic accuracy and customized therapy by filtering out patients less likely to benefit from it. Our study focuses on the importance of reducing uncertainty in interpretation of individuals 3D facial data to support more equitable precision medicine applications. The Human Genome Project and subsequent advances in sequencing have led to the creation of vast genetic datasets, predominantly representing individuals of European origin. However, there is a significant underrepresentation of individuals of African, Asian, and Indigenous ancestries. Methods: The study involved 1,218 participants from various genetic ancestries backgrounds, with a focus on the paediatric population of Chinese genetic ancestry. The study subjects underwent 3D facial photogrammetry in outpatient department setting and with the aid of Cliniface software growth curves were obtained to produce reference statistics of 3D facial norms. Results: The results showed measurable and distinct facial differences in children with Chinese genetic ancestry when compared with other groups representing different genetic ancestries highlighting the need for population diversity and inclusion enrichment in genetic databases. Also, these facial differences and markers are uniquely poised to be correlated in clinic as disease specific digital biomarkers with further investigation and validation in conditions such as hereditary angioedema. Discussion: The study underscores the importance of creating larger datasets involving more diverse genetic ancestry groups to enhance the evidence base for advanced and equitable disease diagnosis, treatment monitoring, prognostication and customized drug development.