Childhood rare diseases and the UN convention on the rights of the child

Purpose

The aim of this case control study was to evaluate the prognostic value of automatically quantified retinal vessel tortuosity from fundus images and vessel density from OCT-A in Fabry disease and to evaluate the correlation of these with systemic disease parameters.

Methods

Automatically quantified perimacular retinal vessel tortuosity (MONA REVA software), acquired by fundus imaging, and perifoveal retinal vessel density, acquired by optic coherence tomography angiography (OCT-A) were compared between 26 FD patients and 26 controls. Gender and FD phenotype were analyzed to the obtained retinovascular data and correlated to the Mainz severity score index (MSSI) and plasma lyso-Gb3.

Results

Automatically quantified retinal vessel tortuosity indices of FD patients were significantly lower, reflecting an increased vessel tortuosity, compared to controls (p = 0.008). Males with a classical phenotype showed significantly lower retinal vessel tortuosity indices compared to males with an oligosymptomatic phenotype and females with a classical or oligosymptomatic phenotype (p < 0.001). The retinal vessel tortuosity index correlated significantly with systemic disease severity parameters [global MSSI (r = − 0.5; p < 0.01), cardiovascular MSSI (r = − 0.5; p < 0.01), lyso-Gb3 (r = − 0.6; p < 0.01)].

Conclusion

We advocate fundus imaging based automatically quantified retinal vessel tortuosity index over OCT-A imaging as it is a quick, non-invasive, easily assessable, objective and reproducible marker.

     

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000 rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available.     

Modeling 3D Facial Shape from DNA

Human facial diversity is substantial, complex, and largely scientifically unexplained. We used spatially dense quasi-landmarks to measure face shape in population samples with mixed West African and European ancestry from three locations (United States, Brazil, and Cape Verde). Using bootstrapped response-based imputation modeling (BRIM), we uncover the relationships between facial variation and the effects of sex, genomic ancestry, and a subset of craniofacial candidate genes. The facial effects of these variables are summarized as response-based imputed predictor (RIP) variables, which are validated using self-reported sex, genomic ancestry, and observer-based facial ratings (femininity and proportional ancestry) and judgments (sex and population group). By jointly modeling sex, genomic ancestry, and genotype, the independent effects of particular alleles on facial features can be uncovered. Results on a set of 20 genes showing significant effects on facial features provide support for this approach as a novel means to identify genes affecting normal-range facial features and for approximating the appearance of a face from genetic markers.     

Dispelling myths about rare disease registry system development

Rare disease registries (RDRs) are an essential tool to improve knowledge and monitor interventions for rare diseases. If designed appropriately, patient and disease related information captured within them can become the cornerstone for effective diagnosis and new therapies. Surprisingly however, registries possess a diverse range of functionality, operate in different, often-times incompatible, software environments and serve various, and sometimes incongruous, purposes. Given the ambitious goals of the International Rare Diseases Research Consortium (IRDiRC) by 2020 and beyond, RDRs must be designed with the agility to evolve and efficiently interoperate in an ever changing rare disease landscape, as well as to cater for rapid changes in Information Communication Technologies. In this paper, we contend that RDR requirements will also evolve in response to a number of factors such as changing disease definitions and diagnostic criteria, the requirement to integrate patient/disease information from advances in either biotechnology and/or phenotypying approaches, as well as the need to adapt dynamically to security and privacy concerns. We dispel a number of myths in RDR development, outline key criteria for robust and sustainable RDR implementation and introduce the concept of a RDR Checklist to guide future RDR development.     

Focus: Rare Disease: mEDUrare: Supporting Integrated Care for Rare Diseases by Better Connecting Health and Education Through Policy

Rare diseases affect an estimated 6-10% of the Australian population, a prevalence similar to that seen in other regions worldwide. These multi-system conditions are often severely debilitating and affect multiple domains of a person’s life. A salient necessity for effective care provision thus, is holistic care, achieved by appropriate and continual multi-disciplinary and cross-sectoral collaboration. Synonymous with this priority for collaborative care, is the need for increased partnerships between the health and education sectors. This partnership has the potential to benefit people with rare disease of all educational ages, but in particular, school-aged children and young adults. More than 70% of rare diseases affect children, and this population often experiences difficulties with overall well-being and functioning, including impaired school performance and confounding mental and social comorbidities. Ensuring adequate schooling needs and experiences along with provision of adequate medical care, is crucial in ensuring overall well-being for this population. For this, effective partnerships between the health and education sectors are paramount. This article highlights fundamental elements of health and education priorities, ingrained in current strategic documents, to build a policy foundation that informs and supports increased inter-sectoral partnerships between health and education services. Shared priorities identified in both sectors’ guidelines, co-developed with those with lived experience of rare diseases, build a strong policy base for future advocative initiatives to mold better integration between the sectors, a partnership which is vital to improving the overall quality of life, experiences and journeys of people living with rare disease.