Understanding Barriers to Diagnosis in a Rare, Genetic Disease: Delays and Errors Diagnosing Schwannomatosis

Diagnosis of rare, genetic diseases is challenging, but conceptual frameworks of the diagnostic process can be used to guide benchmarking and process improvement initiatives. Using the National Academy of Medicine diagnostic framework, we assessed the extent of, and reasons for, diagnostic delays and errors in schwannomatosis, a neurogenetic syndrome characterized by nerve sheath tumors and chronic pain. We reviewed the medical records of 97 patients with confirmed or probable schwannomatosis seen in two U.S. tertiary care clinics from 2005-2016. Survival analysis revealed a median time from first symptom to diagnosis of 16.7 years (95% CI, 7.5-26.0 years) and median time from first medical consultation to diagnosis of 9.8 years (95% CI, 3.5-16.2 years). Factors associated with longer times to diagnosis included initial signs/symptoms that were intermittent, non-specific, or occurred at younger ages (p<0.05). Thirty-six percent of patients experienced a misdiagnosis of underlying genetic condition (18.6%), pain etiology (16.5%) and/or tumor imaging/pathology (11.3%). One-fifth (19.6%) of patients had a clear missed opportunity for appropriate workup that could have led to an earlier schwannomatosis diagnosis. These results suggest that interventions in clinician education, genetic testing availability, expert review of pathology findings, and automatic triggers for genetics referrals may improve diagnosis in schwannomatosis.

Experienced fatigue in people with rare disorders: a scoping review on characteristics of existing research

Background Experienced fatigue is an under-recognized and under-researched feature in persons with many different rare diseases. A better overview of the characteristics of existing research on experienced fatigue in children and adults with rare diseases is needed. The purpose of this review was to map and describe characteristics of existing research on experienced fatigue in a selection of rare diseases in rare developmental defects or anomalies during embryogenesis and rare genetic diseases. Furthermore, to identify research gaps and point to research agendas. Methods We applied a scoping review methodology, and performed a systematic search in March 2020 in bibliographic databases. References were sorted and evaluated for inclusion using EndNote and Rayyan. Data were extracted on the main research questions concerning characteristics of research on experienced fatigue (definition and focus on fatigue, study populations, research questions investigated and methods used). Results This review included 215 articles on ten different rare developmental defects/anomalies during embryogenesis and 35 rare genetic diseases. Of the 215 articles, 82 had investigation of experienced fatigue as primary aim or outcome. Included were 9 secondary research articles (reviews) and 206 primary research articles. A minority of articles included children. There were large differences in the number of studies in different diseases. Only 29 of 215 articles gave a description of how they defined the concept of experienced fatigue. The most common research-question reported on was prevalence and/ -or associations to fatigue. The least common was diagnostics (development or validation of fatigue assessment methods for a specific patient group). A large variety of methods were used to investigate experienced fatigue, impeding comparisons both within and across diagnoses. Conclusion This scoping review on the characteristics of fatigue research in rare diseases found a large variety of research on experienced fatigue. However, the minority of studies had investigation of experienced fatigue as a primary aim. There was large variation in how experienced fatigue was defined and also in how it was measured, both within and across diagnoses. More research on experienced fatigue is needed, both in children and adults with rare diseases. This review offers a basis for further research.

Heterogeneity in biomarkers, mitogenome and genetic disorders of Arab population with special emphasis on large-scale whole-exome sequencing

More than 25 million DNA variations were discovered as novel including major alleles from Arab population. Exome studies on Arabs discovered >3000 novel nucleotide variants associated with >1200 rare genetic disorders. Reclassification of many pathogenic variant into benign through the Arab database enhance building a detailed and comprehensive map of Arab morbid genome. Intellectual disability stands first with the combined and observed carrier frequency. Genome studies and advanced computational biology discovered interesting novel candidate disease marker variations in many genes from consanguineous families with intellectual disability, neurogenetic disorders, blood and bleeding disorder and rare genetic diseases. Pathogenic variants in C12orf57 gene are prominently associated with the etiology of developmental delay/intellectual impairment. Arab mitogenome exposed hundreds of variations in mtDNA genome and its association with obesity. Further study is needed in genomics to fully comprehend the molecular abnormalities and associated pathogenesis that cause inherited disorders in Arab ancestries.

Use of Zebrafish Models to Boost Research in Rare Genetic Diseases

Rare genetic diseases are a group of pathologies with often unmet clinical needs. Even if rare by a single genetic disease (from 1/2000 to 1/more than 1,000,000), the total number of patients concerned account for approximatively 400 million peoples worldwide. Finding treatments remains challenging due to the complexity of these diseases, the small number of patients and the challenge in conducting clinical trials. Therefore, innovative preclinical research strategies are required. The zebrafish has emerged as a powerful animal model for investigating rare diseases. Zebrafish combines conserved vertebrate characteristics with high rate of breeding, limited housing requirements and low costs. More than 84% of human genes responsible for diseases present an orthologue, suggesting that the majority of genetic diseases could be modelized in zebrafish. In this review, we emphasize the unique advantages of zebrafish models over other in vivo models, particularly underlining the high throughput phenotypic capacity for therapeutic screening. We briefly introduce how the generation of zebrafish transgenic lines by gene-modulating technologies can be used to model rare genetic diseases. Then, we describe how zebrafish could be phenotyped using state-of-the-art technologies. Two prototypic examples of rare diseases illustrate how zebrafish models could play a critical role in deciphering the underlying mechanisms of rare genetic diseases and their use to identify innovative therapeutic solutions.

Ocular manifestations in a case of progeroid syndrome

Progeria syndromes are very rare genetic diseases characterized by premature aging changes. There are several phenotypes and variables noted in literature in some cases difficult to specifically classify a specific syndrome. It occurs due to mutation in DNA repair genes. The most common ocular findings are loss of eyebrow and eyelashes, brow ptosis, lid margin changes, entropion, Meibomian gland dysfunction, severe dry eye, corneal opacity, cataract, poor mydriasis, and rod-cone dystrophy. We report this case with all the above ocular manifestations in 19year old teenager with additional finding being retinal detachment.

Medical genetics workforce in Brazil: practitioners, services, and disease distribution

Purpose In anticipation of the implementation of personalized medicine (PM) in Brazil we assessed the demographic characteristics of its medical genetics workforce together with the distribution of rare genetic diseases (RGD) and hereditary cancer syndromes (HCS) across municipalities in the country. Methods We used demographic data from an earlier report on medical specialties, and open databases providing summarized data on the public and private healthcare systems, for the years 2019 and 2020. In the public system we considered RGD live births and hospitalizations, and HCS mortality. In the private system we obtained data on RGD, HCS and genetic counselling appointments. Results The 332 registered medical geneticists (MGs) were mostly female, attended a public medical school, and were predominantly registered in the Southeast. The distribution of MGs overlapped the country-wise distribution of all types of genetic disease and service examined, indicating that ~30% of the patient population has access to a MG specialist. Conclusion The Brazilian MG workforce is concentrated in the richest and most populated areas and while it covers a significant proportion of the population there are vast regions with very limited services. The public health system should address these inequalities for a successful transition to PM.

Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases

Background Clinical interpretation of genetic variants in the context of the patient’s phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed genome interpretation by integrating predictive methods with the growing knowledge of genetic disease. Here we assess the diagnostic performance of Fabric GEM, a new, AI-based, clinical decision support tool for expediting genome interpretation. Methods We benchmarked GEM in a retrospective cohort of 119 probands, mostly NICU infants, diagnosed with rare genetic diseases, who received whole-genome or whole-exome sequencing (WGS, WES). We replicated our analyses in a separate cohort of 60 cases collected from five academic medical centers. For comparison, we also analyzed these cases with current state-of-the-art variant prioritization tools. Included in the comparisons were trio, duo, and singleton cases. Variants underpinning diagnoses spanned diverse modes of inheritance and types, including structural variants (SVs). Patient phenotypes were extracted from clinical notes by two means: manually and using an automated clinical natural language processing (CNLP) tool. Finally, 14 previously unsolved cases were reanalyzed. Results GEM ranked over 90% of the causal genes among the top or second candidate and prioritized for review a median of 3 candidate genes per case, using either manually curated or CNLP-derived phenotype descriptions. Ranking of trios and duos was unchanged when analyzed as singletons. In 17 of 20 cases with diagnostic SVs, GEM identified the causal SVs as the top candidate and in 19/20 within the top five, irrespective of whether SV calls were provided or inferred ab initio by GEM using its own internal SV detection algorithm. GEM showed similar performance in absence of parental genotypes. Analysis of 14 previously unsolved cases resulted in a novel finding for one case, candidates ultimately not advanced upon manual review for 3 cases, and no new findings for 10 cases. Conclusions GEM enabled diagnostic interpretation inclusive of all variant types through automated nomination of a very short list of candidate genes and disorders for final review and reporting. In combination with deep phenotyping by CNLP, GEM enables substantial automation of genetic disease diagnosis, potentially decreasing cost and expediting case review.

Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm

Over 7,000 rare genetic diseases have been identified, and millions of newborns are affected by severe rare genetic diseases each year. A variety of Human Phenotype Ontology (HPO)-based clinical decision support systems (CDSS) and patient repositories have been developed to support clinicians in diagnosing patients with suspected rare genetic diseases. In September 2017, we released PubCaseFinder (https://pubcasefinder.dbcls.jp), a web-based CDSS that provides ranked lists of genetic and rare diseases using HPO-based phenotypic similarities, where top-listed diseases represent the most likely differential diagnosis. We also developed a Matchmaker Exchange (MME) application programming interface (API) to query PubCaseFinder, which has been adopted by several patient repositories. In this paper, we describe notable updates regarding PubCaseFinder, the GeneYenta matching algorithm implemented in PubCaseFinder, and the PubCaseFinder API. The updated GeneYenta matching algorithm improves the performance of the CDSS automated differential diagnosis function. Moreover, the updated PubCaseFinder and new API empower patient repositories participating in MME and medical professionals to actively use HPO-based resources.

Current and Future Prospects for Gene Therapy for Rare Genetic Diseases Affecting the Brain and Spinal Cord

In recent years, gene therapy has been raising hopes toward viable treatment strategies for rare genetic diseases for which there has been almost exclusively supportive treatment. We here review this progress at the pre-clinical and clinical trial levels as well as market approvals within diseases that specifically affect the brain and spinal cord, including degenerative, developmental, lysosomal storage, and metabolic disorders. The field reached an unprecedented milestone when Zolgensma® (onasemnogene abeparvovec) was approved by the FDA and EMA for in vivo adeno-associated virus-mediated gene replacement therapy for spinal muscular atrophy. Shortly after EMA approved Libmeldy®, an ex vivo gene therapy with lentivirus vector-transduced autologous CD34-positive stem cells, for treatment of metachromatic leukodystrophy. These successes could be the first of many more new gene therapies in development that mostly target loss-of-function mutation diseases with gene replacement (e.g., Batten disease, mucopolysaccharidoses, gangliosidoses) or, less frequently, gain-of-toxic-function mutation diseases by gene therapeutic silencing of pathologic genes (e.g., amyotrophic lateral sclerosis, Huntington's disease). In addition, the use of genome editing as a gene therapy is being explored for some diseases, but this has so far only reached clinical testing in the treatment of mucopolysaccharidoses. Based on the large number of planned, ongoing, and completed clinical trials for rare genetic central nervous system diseases, it can be expected that several novel gene therapies will be approved and become available within the near future. Essential for this to happen is the in depth characterization of short- and long-term effects, safety aspects, and pharmacodynamics of the applied gene therapy platforms.