How many rare diseases are there?

Trends from two decades of orphan designations in paediatric rare neuromuscular diseases

Rare diseases are characterized by substantial unmet need mostly because the majority have limited, or no treatment options and a large number also affect children. Since the inception of EU orphan regulation in 2000 the European Medicines Agency Committee for Orphan Medicinal Products has received several applications for paediatric rare neuromuscular diseases (PERAN) however treatment options remain limited. Here we discuss the results form an observational, retrospective, cross-sectional study to characterize the currently authorised orphan medicinal products (OMP) and orphan designations (OD) given to products for PERAN in the last two decades. In the EU about half of PERAN diseases have at least one active OD approved since 2000, and about half of these are for Duchenne muscular dystrophy (DMD). The large majority of PERAN diseases do not have an authorised medicine with only 6 OMP currently authorised for Spinal muscular atrophy (3); DMD (1) and Myasthenia gravis (2). One in five products have inactive or discontinued regulatory development but clinical trials are ongoing for the vast majority of PERAN diseases, and more than half are in the final stage of clinical research with significantly more products with medical plausibility based in clinical data reaching advanced stages in clinical development.

Patient experiences of interprofessional collaboration and intersectoral communication in rare disease healthcare in Germany - a mixed-methods study

BACKGROUND

Rare diseases are often complex, chronic and many of them life-shortening. In Germany, healthcare for rare diseases is organized in expert centers for rare diseases. Most patients additionally have regional general practicioners and specialists for basic medical care. Thus, collaboration and information exchange between sectors is highly relevant. Our study focuses on the patient and caregiver perspective on intersectoral and interdisciplinary care between local healthcare professionals (HCPs) and centers for rare diseases in Germany. The aims were (1) to investigate patients' and caregivers' general experience of healthcare, (2) to analyse patients' and caregivers' perception of collaboration and cooperation between local healthcare professionals and expert centers for rare diseases and (3) to investigate patients' and caregivers' satisfaction with healthcare in the expert centers for rare diseases.

RESULTS

In total 299 individuals of whom 176 were patients and 123 were caregivers to pediatric patients participated in a survey using a questionnaire comprising several instruments and constructs. Fifty participants were additionally interviewed using a semistructured guideline. Most patients reported to receive written information about their care, have a contact person for medical issues and experienced interdisciplinary exchange within the centers for rare diseases. Patients and caregivers in our sample were mainly satisfied with the healthcare in the centers for rare diseases. The qualitative interviews showed a rather mixed picture including experiences of uncoordinated care, low engagement and communication difficulties between professionals of different sectors. Patients reported several factors that influenced the organization and quality of healthcare e.g. engagement and health literacy in patients or engagement of HCPs.

CONCLUSIONS

Our findings indicate the high relevance of transferring affected patients to specialized care as fast as possible to provide best medical treatment and increase patient satisfaction. Intersectoral collaboration should exceed written information exchange and should unburden patients of being and feeling responsible for communication between sectors and specialists. Results indicate a lack of inclusion of psychosocial aspects in routine care, which suggests opportunities for necessary improvements.

Advance Care Planning for Children With Rare Diseases: A Pilot RCT

BACKGROUND AND OBJECTIVE

Pediatric rare diseases are often life-limiting conditions and/or require constant caregiving. Investigators assessed the initial efficacy of the FAmily CEntered (FACE) pediatric advance care planning (pACP), FACE-Rare, intervention on families' quality of life.

METHODS

A pilot-phase, single-blinded, intent-to-treat, randomized controlled clinical trial enrolled families from 1 pediatric quaternary hospital between 2021 and 2023. Intervention families received 3 weekly 60-minute (FACE-Rare pACP) sessions: (1) Carer Support Needs Assessment Tool or Action Plan, (2) Carer Support Needs Assessment Tol Action Plan Review, and (3) Pediatric Next Steps: Respecting Choices pACP. Controls received treatment as usual (TAU). Outcome measures were Beck Anxiety Inventory, Family Appraisal of Caregiving, Functional Assessment of Chronic Illness Therapy (FACIT)-Spirituality, and health care utilization. Generalized mixed effect models with γ response assessed the intervention effect at 3-month follow-up.

RESULTS

Children (n = 21) were aged 1 to 10 years, 48% male, 24% Black; and 100% technology dependent. Primary family caregivers (n = 21) were aged 30 to 43 years, 19% male, 19% Black; and 27% household income below the Federal poverty level. Dyads underwent 1:1 randomization: 9 to FACE-Rare and 12 to TAU. TAU caregivers reported statistically lower meaning and peace than FACE-Rare caregivers (0.9, P = .03, confidence interval [CI]: 0.75-0.99). Black caregivers reported significantly less caregiver distress (0.7, P = .04, CI: 0.47-0.98) than non-Black caregivers. Poor families reported more anxiety (3.5, P = .002, CI: 1.62-7.94), more caregiver strain (1.2, P = .006, CI: 1.07-1.42); and less family well-being (0.8, P = .02, CI: 0.64-0.95).

CONCLUSIONS

FACE®-Rare was feasible, acceptable, safe, and demonstrated initial efficacy, providing greater feelings of meaning and peace to caregivers. Poverty impacted well-being. A multisite trial is needed to determine generalizability.

Health-related quality of life and associated risk factors in patients with Multiple Osteochondromas: a cross-sectional study

PURPOSE

To evaluate the health-related quality of life and associated risk factors for Multiple Osteochondromas patients.

METHODS

A cross-sectional, observational study was conducted from May to December 2022 during the routine visit to the referral center for rare skeletal disorders. All patients with Multiple Osteochondromas aged ≥ 3 years were included. EuroQol 5-dimension questionnaires, and demographic, clinical, and surgical history data were collected. Descriptive statistics, Fisher's exact test, One-sample t-test, Spearman's correlation, and multiple linear and logistic regression were performed to analyze the data. Results are reported following STROBE guidelines.

RESULTS

A total of 128 patients were included in the study, with a mean age of 14 [SD, 10] years. The mean EQ-5D Index Value was 0.863 [SD, 0.200] and the EQ-VAS was 84 [SD, 19] with a positive correlation between two scores [r = 0.541, p < 0.001]. Patients frequently referred problems in pain/discomfort [78.8%], anxiety/depression [50%], and usual activities [38.8%] dimensions. Increasing age was the common risk factor for health-related quality of life [p < 0.000], as well as Index Value and VAS scores were significantly lower in surgical patients [p = 0.001 and p < 0.001, respectively].

CONCLUSION

Increasing age and surgical procedures were found highly associated with reduced health-related quality of life in Multiple Osteochondromas patients. Our findings provide relevant information to support the establishment of patient-centered healthcare pathways and pave the way for further research into medical and non-medical therapeutic strategies for these patients.

Longitudinal natural history studies based on real-world data in rare diseases: Opportunity and a novel approach

Growing interest in therapeutic development for rare diseases necessitate a systematic approach to the collection and curation of natural history data that can be applied consistently across this group of heterogenous rare diseases. In this study, we discuss the challenges facing natural history studies for leukodystrophies and detail a novel standardized approach to creating a longitudinal natural history study using existing medical records. Prospective studies are uniquely challenging for rare diseases. Delays in diagnosis and overall rarity limit the timely collection of natural history data. When feasible, prospective studies are often cross-sectional rather than longitudinal and are unlikely to capture pre- or early- symptomatic disease trajectories, limiting their utility in characterizing the full natural history of the disease. Therapeutic development in leukodystrophies is subject to these same obstacles. The Global Leukodystrophy Initiative Clinical Trials Network (GLIA-CTN) comprises of a network of research institutions across the United States, supported by a multi-center biorepository protocol, to map the longitudinal clinical course of disease across leukodystrophies. As part of GLIA-CTN, we developed Standard Operating Procedures (SOPs) that delineated all study processes related to staff training, source documentation, and data sharing. Additionally, the SOP detailed the standardized approach to data extraction including diagnosis, clinical presentation, and medical events, such as age at gastrostomy tube placement. The key variables for extraction were selected through face validity, and common electronic case report forms (eCRF) across leukodystrophies were created to collect analyzable data. To enhance the depth of the data, clinical notes are extracted into "original" and "imputed" encounters, with imputed encounter referring to a historic event (e.g., loss of ambulation 3 months prior). Retrospective Functional Assessments were assigned by child neurologists, using a blinded dual-rater approach and score discrepancies were adjudicated by a third rater. Upon completion of extraction, data source verification is performed. Data missingness was evaluated using statistics. The proposed methodology will enable us to leverage existing medical records to address the persistent gap in natural history data within this unique disease group, allow for assessment of clinical trajectory both pre- and post-formal diagnosis, and promote recruitment of larger cohorts.

Between hope and reality: treatment of genetic diseases through nucleic acid-based drugs

Rare diseases (RD) affect a small number of people compared to the general population and are mostly genetic in origin. The first clinical signs often appear at birth or in childhood, and patients endure high levels of pain and progressive loss of autonomy frequently associated with short life expectancy. Until recently, the low prevalence of RD and the gatekeeping delay in their diagnosis have long hampered research. The era of nucleic acid (NA)-based therapies has revolutionized the landscape of RD treatment and new hopes arise with the perspectives of disease-modifying drugs development as some NA-based therapies are now entering the clinical stage. Herein, we review NA-based drugs that were approved and are currently under investigation for the treatment of RD. We also discuss the recent structural improvements of NA-based therapeutics and delivery system, which overcome the main limitations in their market expansion and the current approaches that are developed to address the endosomal escape issue. We finally open the discussion on the ethical and societal issues that raise this new technology in terms of regulatory approval and sustainability of production.

'Integrating Ethics and Equity with Economics and Effectiveness for newborn screening in the genomic age: A qualitative study protocol of stakeholder perspectives

BACKGROUND

Newborn bloodspot screening is a well-established population health initiative that detects serious, childhood-onset, treatable conditions to improve health outcomes. With genomic technologies advancing rapidly, many countries are actively discussing the introduction of genomic assays into newborn screening programs. While adding genomic testing to Australia's newborn screening program could improve outcomes for infants and families, it must be considered against potential harms, ethical, legal, equity and social implications, and economic and health system impacts. We must ask not only 'can' we use genomics to screen newborns?' but 'should we'?' and 'how much should health systems invest in genomic newborn screening?'.

METHODS

This study will use qualitative methods to explore understanding, priorities, concerns and expectations of genomic newborn screening among parents/carers, health professionals/scientists, and health policy makers across Australia. In-depth, semi-structured interviews will be held with 30-40 parents/carers recruited via hospital and community settings, 15-20 health professionals/scientists, and 10-15 health policy makers. Data will be analysed using inductive content analysis. The Sydney Children's Hospital Network Human Research Ethics Committee approved this study protocol [2023/ETH02371]. The Standards for Reporting Qualitative Research will guide study planning, conduct and reporting.

DISCUSSION

Few studies have engaged a diverse range of stakeholders to explore the implications of genomics in newborn screening in a culturally and genetically diverse population, nor in a health system underpinned by universal health care. As the first study within a multi-part research program, findings will be used to generate new knowledge on the risks and benefits and importance of ethical, legal, social and equity implications of genomic newborn screening from the perspective of key stakeholders. As such it will be the foundation on which child and family centered criteria can be developed to inform health technology assessments and drive efficient and effective policy decision-making on the implementation of genomics in newborn screening.

Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders

BACKGROUND

In the process of finding the causative variant of rare diseases, accurate assessment and prioritization of genetic variants is essential. Previous variant prioritization tools mainly depend on the in-silico prediction of the pathogenicity of variants, which results in low sensitivity and difficulty in interpreting the prioritization result. In this study, we propose an explainable algorithm for variant prioritization, named 3ASC, with higher sensitivity and ability to annotate evidence used for prioritization. 3ASC annotates each variant with the 28 criteria defined by the ACMG/AMP genome interpretation guidelines and features related to the clinical interpretation of the variants. The system can explain the result based on annotated evidence and feature contributions.

RESULTS

We trained various machine learning algorithms using in-house patient data. The performance of variant ranking was assessed using the recall rate of identifying causative variants in the top-ranked variants. The best practice model was a random forest classifier that showed top 1 recall of 85.6% and top 3 recall of 94.4%. The 3ASC annotates the ACMG/AMP criteria for each genetic variant of a patient so that clinical geneticists can interpret the result as in the CAGI6 SickKids challenge. In the challenge, 3ASC identified causal genes for 10 out of 14 patient cases, with evidence of decreased gene expression for 6 cases. Among them, two genes (HDAC8 and CASK) had decreased gene expression profiles confirmed by transcriptome data.

CONCLUSIONS

3ASC can prioritize genetic variants with higher sensitivity compared to previous methods by integrating various features related to clinical interpretation, including features related to false positive risk such as quality control and disease inheritance pattern. The system allows interpretation of each variant based on the ACMG/AMP criteria and feature contribution assessed using explainable AI techniques.

Oral conditions of children with microcephaly associated with congenital Zika syndrome: a cross-sectional study

The aim of the present study was to compare the oral conditions of children with congenital Zika syndrome (CZS)-associated microcephaly, non-CZS-associated microcephaly, and normotypical children, as well as to characterize their sociodemographic aspects and medical history. A paired cross-sectional study was carried out on 14 children with CZS-associated microcephaly and 24 age-matched controls, in Belo Horizonte, in southeastern Brazil. Children's oral conditions were assessed: dental caries experience (dmft/DMFT indices); developmental defects of enamel (DDE) index; dental anomalies; mucosal changes; lip sealing, and malocclusion (overjet, overbite, and/or posterior crossbite alterations). The quality of oral hygiene was analyzed by the simplified oral hygiene index. The children's mothers also answered a questionnaire about sociodemographic and medical history data. The variables were analyzed descriptively. Female participants were more prevalent (60.5%), and the mean age of the participants was 4.9 years (±1.4) (range: 2-8 years) and 92.1% of their exhibited some oral condition. All participants with CZS-associated microcephaly showed absence of lip sealing and had malocclusion (100.0%). When compared to the other groups, children with CZS had a higher percentage of dental anomalies (35.7%), mucosal changes (71.4%), and unsatisfactory oral hygiene (64.3%). In a sample composed mainly of female participants aged less than 5 years, the prevalence of oral conditions and unsatisfactory oral hygiene was higher in the group with CZS-associated microcephaly, followed by the group with non-CZS-associated microcephaly. Normotypical children had the highest percentage of dental caries experience.

Exome and genome sequencing in a heterogeneous population of patients with rare disease: Identifying predictors of a diagnosis

PURPOSE

Exome (ES) and genome sequencing (GS) are increasingly being utilized for individuals with rare and undiagnosed diseases; however, guidelines on their use remain limited. This study aimed to identify factors associated with diagnosis by ES and/or GS in a heterogeneous population of patients with rare and undiagnosed diseases.

METHODS

In this case control study, we reviewed data from 400 diagnosed and 400 undiagnosed randomly selected participants in the Undiagnosed Diseases Network, all of whom had undergone ES and/or GS. We analyzed factors associated with receiving a diagnosis by ES and/or GS.

RESULTS

Factors associated with a decreased odds of being diagnosed included adult symptom onset, singleton sequencing, and having undergone ES and/or GS before acceptance to the Undiagnosed Diseases Network (48%, 51%, and 32% lower odds, respectively). Factors that increased the odds of being diagnosed by ES and/or GS included having primarily neurological symptoms and having undergone prior chromosomal microarray testing (44% and 59% higher odds, respectively).

CONCLUSION

We identified several factors that were associated with receiving a diagnosis by ES and/or GS. This will ideally inform the utilization of ES and/or GS and help manage expectations of individuals and families undergoing these tests.

Mowat-Wilson Syndrome: Case Report and Review of ZEB2 Gene Variant Types, Protein Defects and Molecular Interactions

Mowat-Wilson syndrome (MWS) is a rare genetic neurodevelopmental congenital disorder associated with various defects of the zinc finger E-box binding homeobox 2 (ZEB2) gene. The ZEB2 gene is autosomal dominant and encodes six protein domains including the SMAD-binding protein, which functions as a transcriptional corepressor involved in the conversion of neuroepithelial cells in early brain development and as a mediator of trophoblast differentiation. This review summarizes reported ZEB2 gene variants, their types, and frequencies among the 10 exons of ZEB2. Additionally, we summarized their corresponding encoded protein defects including the most common variant, c.2083 C>T in exon 8, which directly impacts the homeodomain (HD) protein domain. This single defect was found in 11% of the 298 reported patients with MWS. This review demonstrates that exon 8 encodes at least three of the six protein domains and accounts for 66% (198/298) of the variants identified. More than 90% of the defects were due to nonsense or frameshift changes. We show examples of protein modeling changes that occurred as a result of ZEB2 gene defects. We also report a novel pathogenic variant in exon 8 in a 5-year-old female proband with MWS. This review further explores other genes predicted to be interacting with the ZEB2 gene and their predicted gene-gene molecular interactions with protein binding effects on embryonic multi-system development such as craniofacial, spine, brain, kidney, cardiovascular, and hematopoiesis.

ASACO: Automatic and Serial Analysis of CO-expression to discover gene modifiers with potential use in drug repurposing

Massive gene expression analyses are widely used to find differentially expressed genes under specific conditions. The results of these experiments are often available in public databases that are undergoing a growth similar to that of molecular sequence databases in the past. This now allows novel secondary computational tools to emerge that use such information to gain new knowledge. If several genes have a similar expression profile across heterogeneous transcriptomics experiments, they could be functionally related. These associations are usually useful for the annotation of uncharacterized genes. In addition, the search for genes with opposite expression profiles is useful for finding negative regulators and proposing inhibitory compounds in drug repurposing projects. Here we present a new web application, Automatic and Serial Analysis of CO-expression (ASACO), which has the potential to discover positive and negative correlator genes to a given query gene, based on thousands of public transcriptomics experiments. In addition, examples of use are presented, comparing with previous contrasted knowledge. The results obtained propose ASACO as a useful tool to improve knowledge about genes associated with human diseases and noncoding genes. ASACO is available at http://www.bioinfocabd.upo.es/asaco/.

Automatically pre-screening patients for the rare disease aromatic l-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population

OBJECTIVES

Electronic health record (EHR) data may facilitate the identification of rare diseases in patients, such as aromatic l-amino acid decarboxylase deficiency (AADCd), an autosomal recessive disease caused by pathogenic variants in the dopa decarboxylase gene. Deficiency of the AADC enzyme results in combined severe reductions in monoamine neurotransmitters: dopamine, serotonin, epinephrine, and norepinephrine. This leads to widespread neurological complications affecting motor, behavioral, and autonomic function. The goal of this study was to use EHR data to identify previously undiagnosed patients who may have AADCd without available training cases for the disease.

MATERIALS AND METHODS

A multiple symptom and related disease annotated dataset was created and used to train individual concept classifiers on annotated sentence data. A multistep algorithm was then used to combine concept predictions into a single patient rank value.

RESULTS

Using an 8000-patient dataset that the algorithms had not seen before ranking, the top and bottom 200 ranked patients were manually reviewed for clinical indications of performing an AADCd diagnostic screening test. The top-ranked patients were 22.5% positively assessed for diagnostic screening, with 0% for the bottom-ranked patients. This result is statistically significant at P < .0001.

CONCLUSION

This work validates the approach that large-scale rare-disease screening can be accomplished by combining predictions for relevant individual symptoms and related conditions which are much more common and for which training data is easier to create.

Impact of the COVID-19 Pandemic on People Living With Rare Diseases and Their Families: Results of a National Survey

BACKGROUND

With more than 103 million cases and 1.1 million deaths, the COVID-19 pandemic has had devastating consequences for the health system and the well-being of the entire US population. The Rare Diseases Clinical Research Network funded by the National Institutes of Health was strategically positioned to study the impact of the pandemic on the large, vulnerable population of people living with rare diseases (RDs).

OBJECTIVE

This study was designed to describe the characteristics of COVID-19 in the RD population, determine whether patient subgroups experienced increased occurrence or severity of infection and whether the pandemic changed RD symptoms and treatment, and understand the broader impact on respondents and their families.

METHODS

US residents who had an RD and were <90 years old completed a web-based survey investigating self-reported COVID-19 infection, pandemic-related changes in RD symptoms and medications, access to care, and psychological impact on self and family. We estimated the incidence of self-reported COVID-19 and compared it with that in the US population; evaluated the frequency of COVID-19 symptoms according to self-reported infection; assessed infection duration, complications and need for hospitalization; assessed the influence of the COVID-19 pandemic on RD symptoms and treatment, and whether the pandemic influenced access to care, special food and nutrition, or demand for professional psychological assistance.

RESULTS

Between May 2, 2020, and December 15, 2020, in total, 3413 individuals completed the survey. Most were female (2212/3413, 64.81%), White (3038/3413, 89.01%), and aged ≥25 years (2646/3413, 77.53%). Overall, 80.6% (2751/3413) did not acquire COVID-19, 2.08% (71/3413) acquired it, and 16.58% (566/3413) did not know. Self-reported cases represented an annual incidence rate of 2.2% (95% CI 1.7%-2.8%). COVID-19 cases were more than twice the expected (71 vs 30.3; P<.001). COVID-19 was associated with specific symptoms (loss of taste: odds ratio [OR] 38.9, 95% CI 22.4-67.6, loss of smell: OR 30.6, 95% CI 17.7-53.1) and multiple symptoms (>9 symptoms vs none: OR 82.5, 95% CI 29-234 and 5-9: OR 44.8, 95% CI 18.7-107). Median symptom duration was 16 (IQR 9-30) days. Hospitalization (7/71, 10%) and ventilator support (4/71, 6%) were uncommon. Respondents who acquired COVID-19 reported increased occurrence and severity of RD symptoms and use or dosage of select medications; those who did not acquire COVID-19 reported decreased occurrence and severity of RD symptoms and use of medications; those who did not know had an intermediate pattern. The pandemic made it difficult to access care, receive treatment, get hospitalized, and caused mood changes for respondents and their families.

CONCLUSIONS

Self-reported COVID-19 was more frequent than expected and was associated with increased prevalence and severity of RD symptoms and greater use of medications. The pandemic negatively affected access to care and caused mood changes in the respondents and family members. Continued surveillance is necessary.

Enabling personalised disease diagnosis by combining a patient's time-specific gene expression profile with a biomedical knowledge base

BACKGROUND

Recent developments in the domain of biomedical knowledge bases (KBs) open up new ways to exploit biomedical knowledge that is available in the form of KBs. Significant work has been done in the direction of biomedical KB creation and KB completion, specifically, those having gene-disease associations and other related entities. However, the use of such biomedical KBs in combination with patients' temporal clinical data still largely remains unexplored, but has the potential to immensely benefit medical diagnostic decision support systems.

RESULTS

We propose two new algorithms, LOADDx and SCADDx, to combine a patient's gene expression data with gene-disease association and other related information available in the form of a KB, to assist personalized disease diagnosis. We have tested both of the algorithms on two KBs and on four real-world gene expression datasets of respiratory viral infection caused by Influenza-like viruses of 19 subtypes. We also compare the performance of proposed algorithms with that of five existing state-of-the-art machine learning algorithms (k-NN, Random Forest, XGBoost, Linear SVM, and SVM with RBF Kernel) using two validation approaches: LOOCV and a single internal validation set. Both SCADDx and LOADDx outperform the existing algorithms when evaluated with both validation approaches. SCADDx is able to detect infections with up to 100% accuracy in the cases of Datasets 2 and 3. Overall, SCADDx and LOADDx are able to detect an infection within 72 h of infection with 91.38% and 92.66% average accuracy respectively considering all four datasets, whereas XGBoost, which performed best among the existing machine learning algorithms, can detect the infection with only 86.43% accuracy on an average.

CONCLUSIONS

We demonstrate how our novel idea of using the most and least differentially expressed genes in combination with a KB can enable identification of the diseases that a patient is most likely to have at a particular time, from a KB with thousands of diseases. Moreover, the proposed algorithms can provide a short ranked list of the most likely diseases for each patient along with their most affected genes, and other entities linked with them in the KB, which can support health care professionals in their decision-making.

Defining priorities in the transition from paediatric to adult healthcare for rare bone disease patients: a dialogic approach

The Italian patient association for Multiple Osteochondromas, Ollier Disease, and Maffucci Syndrome, Associazione Conto Alla Rovescia-ACAR Aps, conducted a mixed-methods study at its 2023 annual conference. The study included the Open Dialogue Approach and a feedback survey to identify the main priorities in the transitioning process from paediatric to adult healthcare for patients with Multiple Osteochondromas, Ollier Disease, and Maffucci Syndrome. The common needs identified by patients, families, caregivers, and healthcare professionals were coordination and continuity of care, patient empowerment and communication, social and practical support, and transition planning and support. This experience fostered a sense of collaboration and cooperation among stakeholders, helping to build trust and create a shared vision for improving the quality of care for these patients. Furthermore, it could be considered a starting point for other patient associations interested in using different approaches to identify the needs of their members and actively involve all stakeholders.

Artificial Intelligence for Drug Discovery: Are We There Yet?

Drug discovery is adapting to novel technologies such as data science, informatics, and artificial intelligence (AI) to accelerate effective treatment development while reducing costs and animal experiments. AI is transforming drug discovery, as indicated by increasing interest from investors, industrial and academic scientists, and legislators. Successful drug discovery requires optimizing properties related to pharmacodynamics, pharmacokinetics, and clinical outcomes. This review discusses the use of AI in the three pillars of drug discovery: diseases, targets, and therapeutic modalities, with a focus on small-molecule drugs. AI technologies, such as generative chemistry, machine learning, and multiproperty optimization, have enabled several compounds to enter clinical trials. The scientific community must carefully vet known information to address the reproducibility crisis. The full potential of AI in drug discovery can only be realized with sufficient ground truth and appropriate human intervention at later pipeline stages.

Drug repurposing for rare: progress and opportunities for the rare disease community

Repurposing is one of the key opportunities to address the unmet rare diseases therapeutic need. Based on cases of drug repurposing in small population conditions, and previous work in drug repurposing, we analyzed the most important lessons learned, such as the sharing of clinical observations, reaching out to regulatory scientific advice at an early stage, and public-private collaboration. In addition, current upcoming trends in the field of drug repurposing in rare diseases were analyzed, including the role these trends could play in the rare diseases' ecosystem. Specifically, we cover the opportunities of innovation platforms, the use of real-world data, the use of artificial intelligence, regulatory initiatives in repurposing, and patient engagement throughout the repurposing project. The outcomes from these emerging activities will help progress the field of drug repurposing for the benefit of patients, public health and medicines development.

Perry Disease: Bench to Bedside Circulation and a Team Approach

With technological applications, especially in genetic testing, new diseases have been discovered and new disease concepts have been proposed in recent years; however, the pathogenesis and treatment of these rare diseases are not as well established as those of common diseases. To demonstrate the importance of rare disease research, in this paper we focus on our research topic, Perry disease (Perry syndrome). Perry disease is a rare autosomal dominant neurodegenerative disorder clinically characterized by parkinsonism, depression/apathy, weight loss, and respiratory symptoms including central hypoventilation and central sleep apnea. The pathological classification of Perry disease falls under TAR DNA-binding protein 43 (TDP-43) proteinopathies. Patients with Perry disease exhibit DCTN1 mutations, which is the causative gene for the disease; they also show relatively uniform pathological and clinical features. This review summarizes recent findings regarding Perry disease from both basic and clinical perspectives. In addition, we describe technological innovations and outline future challenges and treatment prospects. We discuss the expansion of research from rare diseases to common diseases and the importance of collaboration between clinicians and researchers. Here, we highlight the importance of researching rare diseases as it contributes to a deeper understanding of more common diseases, thereby opening up new avenues for scientific exploration.

Attaining Diagnostic Excellence: How the Structure and Function of a Rare Disease Service Contribute to Ending the Diagnostic Odyssey

Patients with rare or otherwise undiagnosed disorders frequently find themselves on a diagnostic odyssey, the often-prolonged journey toward diagnosis that can be characterized by significant physical, emotional, and financial hardship, as well as by diagnostic errors and delays. The wider availability of clinical exome sequencing has helped end many diagnostic odysseys, though diagnostic success rates of around 35% for exome sequencing leave many patients undiagnosed. Diagnostic yields can be improved via the implementation of advanced genetic testing modalities, though both these modalities and exome sequencing perform significantly better when paired with high-quality phenotypic data. Diagnostic centers of excellence can improve outcomes for patients on a diagnostic odyssey by providing a process and environment that address shortfalls in diagnostic access while providing high-quality phenotyping. Features of successful undiagnosed and rare disease evaluation teams are discussed and an illustrative case is provided.

Determining Commonalities in the Experiences of Patients with Rare Diseases: A Qualitative Analysis of US Food and Drug Administration Patient Engagement Sessions

BACKGROUND

Rare diseases are estimated to affect more than one in ten Americans. However, most patients with a rare disease face significant emotional, physical, and social challenges. To better understand the burden of disease and unmet needs, the US Food and Drug Administration (FDA) conducts and supports multiple patient engagement platforms. We analyzed summaries from these discussions to identify commonalities among patients with disparate rare diseases, the results of which could inform priorities for cross-disease policies and medical product development.

METHODS

We conducted a qualitative analysis of patient engagement session summaries to investigate shared experiences across rare diseases. Cross-disease similarities were identified within four dimensions: product development/regulatory, clinical/physical, social/psychological, and economic/financial. Summaries from 29 rare diseases were included in our analyses.

RESULTS

Within the product development/regulatory dimension, we observed that patients and caregivers across rare diseases shared the desire for development of medical products that cured their disease or improved their overall quality of life. In the clinical/physical dimension, we found that patients had numerous common symptoms, including pain and fatigue. In the social/psychological dimension, we observed significant negative impact on mental health. Within the economic/financial dimension, patients and caregivers shared that disease burden caused significant financial hardships.

CONCLUSION

We found remarkable similarities among patients with rare diseases across all four dimensions. Our results indicate that, even among rare diseases with diverse etiologies, patients share numerous commonalties due to their diseases: a lack of effective treatment options, certain physical symptoms, mental health challenges, and financial concerns.

Ultra-rare ultra-care: Assessing the impact of caring for children with ultra rare diseases

BACKGROUND

We sought to assesses the impact of caring for children with ultra rare diseases (URDs) on family carers and to analyse the way these experiences differ among the caregivers of children diagnosed through prenatal or newborn screening, and those with symptom-based diagnosis.

METHODS

A total of 200 caregivers of 219 URDs children completed an on-line survey regarding the challenges and experiences of caregivers of URDs children.

RESULTS

The majority of URD caregivers felt burdened by their children's health problems, emotional and behavioural changes. 46.5% reported feelings of care overload, 43% coped poorly with the stress, and many experienced a variety of feelings of distress towards the role of caregiver. While most caregivers struggled with the diagnostic odyssey and were dissatisfied with the healthcare services for URD children, caregivers of children diagnosed through prenatal or newborn screening were significantly less burdened than the parents of children with symptom-based diagnoses.

CONCLUSION

Although caregivers of URDs children experience physical and emotional strain, they are often neglected by the healthcare system. A bio-psychosocial approach to URDs should therefore also include family caregivers' physical and psychosocial needs. Apart from financial and emotional support, enhancing access to genetic testing and newborn screening should be prioritised.

Clustering rare diseases within an ontology-enriched knowledge graph

OBJECTIVE

Identifying sets of rare diseases with shared aspects of etiology and pathophysiology may enable drug repurposing. Toward that aim, we utilized an integrative knowledge graph to construct clusters of rare diseases.

MATERIALS AND METHODS

Data on 3242 rare diseases were extracted from the National Center for Advancing Translational Science Genetic and Rare Diseases Information center internal data resources. The rare disease data enriched with additional biomedical data, including gene and phenotype ontologies, biological pathway data, and small molecule-target activity data, to create a knowledge graph (KG). Node embeddings were trained and clustered. We validated the disease clusters through semantic similarity and feature enrichment analysis.

RESULTS

Thirty-seven disease clusters were created with a mean size of 87 diseases. We validate the clusters quantitatively via semantic similarity based on the Orphanet Rare Disease Ontology. In addition, the clusters were analyzed for enrichment of associated genes, revealing that the enriched genes within clusters are highly related.

DISCUSSION

We demonstrate that node embeddings are an effective method for clustering diseases within a heterogenous KG. Semantically similar diseases and relevant enriched genes have been uncovered within the clusters. Connections between disease clusters and drugs are enumerated for follow-up efforts.

CONCLUSION

We lay out a method for clustering rare diseases using graph node embeddings. We develop an easy-to-maintain pipeline that can be updated when new data on rare diseases emerges. The embeddings themselves can be paired with other representation learning methods for other data types, such as drugs, to address other predictive modeling problems.

Digital child health: opportunities and obstacles. A joint statement of European Academy of Paediatrics and European Confederation of Primary Care Paediatricians

The advancement of technology and the increasing digitisation of healthcare systems have opened new opportunities to transform the delivery of child health services. The importance of interoperable electronic health data in enhancing healthcare systems and improving child health care is evident. Interoperability ensures seamless data exchange and communication among healthcare entities, providers, institutions, household and systems. Using standardised data formats, coding systems, and terminologies is crucial in achieving interoperability and overcoming the barriers of different systems, formats, and locations. Paediatricians and other child health stakeholders can effectively address data structure, coding, and terminology inconsistencies by promoting interoperability and improving data quality and accuracy of children and youth, according to guidelines of the World Health Organisation. Thus, ensure comprehensive health assessments and screenings for children, including timely follow-up and communication of results. And implement effective vaccination schedules and strategies, ensuring timely administration of vaccines and prompt response to any concerns or adverse events. Developmental milestones can be continuously monitored. This can improve care coordination, enhance decision-making, and optimise health outcomes for children. In conclusion, using interoperable electronic child health data holds great promise in advancing international child healthcare systems and enhancing the child's care and well-being. By promoting standardised data exchange, interoperability enables timely health assessments, accurate vaccination schedules, continuous monitoring of developmental milestones, coordination of care, and collaboration among child healthcare professionals and the individual or their caregiver. Embracing interoperability is essential for creating a person-centric and data-driven healthcare ecosystem where the potential of digitalisation and innovation can be fully realized.

The Medical Action Ontology: A tool for annotating and analyzing treatments and clinical management of human disease

BACKGROUND

Navigating the clinical literature to determine the optimal clinical management for rare diseases presents significant challenges. We introduce the Medical Action Ontology (MAxO), an ontology specifically designed to organize medical procedures, therapies, and interventions.

METHODS

MAxO incorporates logical structures that link MAxO terms to numerous other ontologies within the OBO Foundry. Term development involves a blend of manual and semi-automated processes. Additionally, we have generated annotations detailing diagnostic modalities for specific phenotypic abnormalities defined by the Human Phenotype Ontology (HPO). We introduce a web application, POET, that facilitates MAxO annotations for specific medical actions for diseases using the Mondo Disease Ontology.

FINDINGS

MAxO encompasses 1,757 terms spanning a wide range of biomedical domains, from human anatomy and investigations to the chemical and protein entities involved in biological processes. These terms annotate phenotypic features associated with specific disease (using HPO and Mondo). Presently, there are over 16,000 MAxO diagnostic annotations that target HPO terms. Through POET, we have created 413 MAxO annotations specifying treatments for 189 rare diseases.

CONCLUSIONS

MAxO offers a computational representation of treatments and other actions taken for the clinical management of patients. Its development is closely coupled to Mondo and HPO, broadening the scope of our computational modeling of diseases and phenotypic features. We invite the community to contribute disease annotations using POET (https://poet.jax.org/). MAxO is available under the open-source CC-BY 4.0 license (https://github.com/monarch-initiative/MAxO).

FUNDING

NHGRI 1U24HG011449-01A1 and NHGRI 5RM1HG010860-04.

What can GPT-4 do for Diagnosing Rare Eye Diseases? A Pilot Study

INTRODUCTION

Generative pretrained transformer-4 (GPT-4) has gained widespread attention from society, and its potential has been extensively evaluated in many areas. However, investigation of GPT-4's use in medicine, especially in the ophthalmology field, is still limited. This study aims to evaluate GPT-4's capability to identify rare ophthalmic diseases in three simulated scenarios for different end-users, including patients, family physicians, and junior ophthalmologists.

METHODS

We selected ten treatable rare ophthalmic disease cases from the publicly available EyeRounds service. We gradually increased the amount of information fed into GPT-4 to simulate the scenarios of patient, family physician, and junior ophthalmologist using GPT-4. GPT-4's responses were evaluated from two aspects: suitability (appropriate or inappropriate) and accuracy (right or wrong) by senior ophthalmologists (> 10 years' experiences).

RESULTS

Among the 30 responses, 83.3% were considered "appropriate" by senior ophthalmologists. In the scenarios of simulated patient, family physician, and junior ophthalmologist, seven (70%), ten (100%), and eight (80%) responses were graded as "appropriate" by senior ophthalmologists. However, compared to the ground truth, GPT-4 could only output several possible diseases generally without "right" responses in the simulated patient scenarios. In contrast, in the simulated family physician scenario, 50% of GPT-4's responses were "right," and in the simulated junior ophthalmologist scenario, the model achieved a higher "right" rate of 90%.

CONCLUSION

To our knowledge, this is the first proof-of-concept study that evaluates GPT-4's capacity to identify rare eye diseases in simulated scenarios involving patients, family physicians, and junior ophthalmologists. The results indicate that GPT-4 has the potential to serve as a consultation assisting tool for patients and family physicians to receive referral suggestions and an assisting tool for junior ophthalmologists to diagnose rare eye diseases. However, it is important to approach GPT-4 with caution and acknowledge the need for verification and careful referrals in clinical settings.

Qualified placebo for trials of herbal medicine treatment in rare diseases? A cross-sectional analysis

BACKGROUND

While substantial placebos have been used in herbal medicine (HM) clinical trials for rare diseases, the use and quality of reporting of HM-placebo remain unclear. We aim to describe the use of HM-placebo in clinical trials for rare diseases and determine the quality of reporting in these trials.

METHODS

This is a cross-sectional study. We searched PubMed, Embase, Web of Science, SinoMed, China National Knowledge Infrastructure, WanFang database, China Science and Technology Journal Database, National Institute of Informatics Support Academic Information Services, ClinicalTrials.gov and Chinese Clinical Trials Registry from their inception date to 14 February 2023 to identify registered and published trials that use placebos as a comparator in rare diseases. We collected data on placebo use reporting and the efficacy and safety of placebo. Descriptive statistics, the Chi-square test, and Binary multivariable logistic regression analysis were used to determine the placebo characteristics of the HM trial and its effect on reporting.

RESULTS

Among the 55 studies, we included that with a median administration time of placebo of 84 days (IQR 42-180) and a median placebo sample size of 30 (IQR 24-54). About half of the trials (27, 49.1%) did not provide their ethical approvals, and one trial had details of informed consent. None of the studies were fully reported and more than half of the items reported less than 50%. A total of 10 trials (18.2%) of placebo has active ingredients even though none of them performed pharmacological inert tests. Of the 29 studies with available data on adverse events, 5 (17.2%) trials did not show a better safety profile in the placebo group. Under the context that a relatively high-quality report is defined as a report with more than 9 items, there was a statistically significant difference between the two groups in the rate of relatively high-quality reports of the administration time (p = 0.047, OR 0.10, 95% CI 0.01 to 0.90), but the results are not representative.

CONCLUSION

The overall situation of HM-placebo in the field of rare diseases was poor. In particular, the placebo is tied to the quality of trials, and poor placebo hinders the generation of high-quality evidence for herbal clinical trials in the field of rare diseases. We summarize the current methods of assessment involved in the use of placebos and propose various considerations for placebos in different contexts. Our study can greatly promote rare disease researchers to review the quality of their placebo and clinical trials. It is imperative to guarantee that meticulously conducted research generates clinical evidence of the highest caliber. We also expect that in the future, more rigorous relevant standards about the reporting and design of HM-placebo will be developed. High-quality clinical trials are the prerequisite for the wide clinical application of herbal medicines for rare diseases.

Genetic newborn screening and digital technologies: A project protocol based on a dual approach to shorten the rare diseases diagnostic path in Europe

Since 72% of rare diseases are genetic in origin and mostly paediatrics, genetic newborn screening represents a diagnostic "window of opportunity". Therefore, many gNBS initiatives started in different European countries. Screen4Care is a research project, which resulted of a joint effort between the European Union Commission and the European Federation of Pharmaceutical Industries and Associations. It focuses on genetic newborn screening and artificial intelligence-based tools which will be applied to a large European population of about 25.000 infants. The neonatal screening strategy will be based on targeted sequencing, while whole genome sequencing will be offered to all enrolled infants who may show early symptoms but have resulted negative at the targeted sequencing-based newborn screening. We will leverage artificial intelligence-based algorithms to identify patients using Electronic Health Records (EHR) and to build a repository "symptom checkers" for patients and healthcare providers. S4C will design an equitable, ethical, and sustainable framework for genetic newborn screening and new digital tools, corroborated by a large workout where legal, ethical, and social complexities will be addressed with the intent of making the framework highly and flexibly translatable into the diverse European health systems.

Role of pharmacists in the context of rare diseases: a scoping review protocol

INTRODUCTION

Rare diseases are chronic conditions, generally incurable, progressive and disabling, which may result in early death. Access to therapeutic products, both medicines and appropriate medical devices, is essential to prevent the progression of the disease and maintain the patients' quality of life. Pharmacists can be part of health teams, in charge of guiding patients' journey, monitoring pharmacotherapy and identifying risks. This scoping review aims to identify and summarise evidence on the role of pharmacists and its impact in the field of rare diseases.

METHODS AND ANALYSIS

The searches will be conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline for protocols. Three electronic databases will be consulted. Studies reporting on qualitative and/or quantitative data from any world region will be considered. There will be no language or initial time limit for studies inclusion, until December 2022. To be eligible for inclusion, studies must focus on the role pharmacists in clinical services aimed at promote the access to medicines, prevention and resolution of problems related to pharmacotherapy. No assessments of items' quality will be made, as the purpose of this scoping review is to synthesise and describe the coverage of the evidence. Clinical, humanistic or economic outcomes from studies that meet the inclusion criteria will be included in the review. The analysis will synthesise the available evidence and may be able to push pharmaceutical practice forward, aiding professionals, educators and managers in the implementation of new approaches to better meet the needs of rare diseases and providing opportunities for future research.

ETHICS AND DISSEMINATION

Primary data will not be collected in this study and formal ethical approval is not required. The findings of this study will be disseminated through peer-reviewed publications and conference presentations.

A mouse model of ZTTK syndrome reveals indispensable SON functions in organ development and hematopoiesis

Rare diseases are underrepresented in biomedical research, leading to insufficient awareness. Zhu-Tokita-Takenouchi-Kim (ZTTK) syndrome is a rare disease caused by genetic alterations that result in heterozygous loss-of-function of SON. While ZTTK syndrome patients suffer from numerous symptoms, the lack of model organisms hamper our understanding of both SON and this complex syndrome. Here, we developed Son haploinsufficiency (Son+/-) mice as a model of ZTTK syndrome and identified the indispensable roles of Son in organ development and hematopoiesis. Son+/- mice recapitulated clinical symptoms of ZTTK syndrome, including growth retardation, cognitive impairment, skeletal abnormalities, and kidney agenesis. Furthermore, we identified hematopoietic abnormalities in Son+/- mice, similar to those observed in human patients. Surface marker analyses and single-cell transcriptome profiling of hematopoietic stem and progenitor cells revealed that Son haploinsufficiency inclines cell fate toward the myeloid lineage but compromises lymphoid lineage development by reducing key genes required for lymphoid and B cell lineage specification. Additionally, Son haploinsufficiency causes inappropriate activation of erythroid genes and impaired erythroid maturation. These findings highlight the importance of the full gene dosage of Son in organ development and hematopoiesis. Our model serves as an invaluable research tool for this rare disease and related disorders associated with SON dysfunction.

DDX3X Syndrome Behavioral Manifestations with Particular Emphasis on Psycho-Pathological Symptoms-A Review

(1) Background: Identification of typical behavioral manifestations in patients with DEAD-Box Helicase 3 X-linked gene (DDX3X) variants plays a crucial role in accurately diagnosing and managing the syndrome. The objective of this paper was to carry out a review of medical and public databases and assess the behavioral features of the DDX3X syndrome (DDX3X), with a particular focus on psycho-pathological symptoms. (2) Methods: An extensive computerized search was conducted in various databases, including PubMed, Medline Complete, Science Direct, Scopus, and Web of Science. Specific keywords and Medical Subject Headings were used to ensure the inclusion of relevant studies. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied to assess the methodological quality of the manuscripts. (3) Results: Only nine papers out of the 272 assessed met the inclusion criteria. These articles revealed various psycho-pathological manifestations in patients with the DDX3X syndrome. Intellectual disability (ID) or developmental disability (DD), speech delay, autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), generalized anxiety disorder (GAD), self-injurious behaviors (SIBs), sensory symptoms and sleep disturbance were demonstrated to be the most common psycho-pathological behavior manifestations. (4) Conclusions: Patients with the DDX3X syndrome manifest a wide spectrum of psycho-pathological symptoms. A comprehensive investigation of these symptoms in patients is essential for early diagnosis and effective therapy.

Genomic newborn screening for rare diseases

Rare diseases are a leading cause of infant mortality and lifelong disability. To improve outcomes, timely diagnosis and effective treatments are needed. Genomic sequencing has transformed the traditional diagnostic process, providing rapid, accurate and cost-effective genetic diagnoses to many. Incorporating genomic sequencing into newborn screening programmes at the population scale holds the promise of substantially expanding the early detection of treatable rare diseases, with stored genomic data potentially benefitting health over a lifetime and supporting further research. As several large-scale newborn genomic screening projects launch internationally, we review the challenges and opportunities presented, particularly the need to generate evidence of benefit and to address the ethical, legal and psychosocial issues that genomic newborn screening raises.

BBLN triggers CAMK2D pathology in mice under cardiac pressure overload and potentially in unrepaired hearts with tetralogy of Fallot

Tetralogy of Fallot (TOF) is one of the most prevalent congenital heart defects, with adverse cardiac remodeling and long-term cardiac complications. Here, searching for pathomechanisms, we find upregulated bublin coiled-coil protein (BBLN) in heart specimens of TOF patients with cyanosis, which positively correlates with cardiac remodeling pathways. Human BBLN, a protein with largely unknown function, promoted heart failure features, with increased mortality when overexpressed in mice, in a protein dosage-dependent manner. BBLN enhanced cardiac inflammation, fibrosis and necroptosis by calcium/calmodulin-dependent protein kinase II delta (CAMK2D) activation, whereas a BBLN mutant with impaired CAMK2D binding was inert. Downregulation of CAMK2D by an interfering RNA retarded BBLN-induced symptoms of heart failure. Endogenous BBLN was induced by hypoxia as a major TOF feature in human patients and by chronic pressure overload in mice, and its downregulation decreased CAMK2D hyperactivity, necroptosis and cardiovascular dysfunction. Thus, BBLN promotes CAMK2D-induced pathways to pathological cardiac remodeling, which are triggered by hypoxia in TOF.

Surfacing undiagnosed disease: consideration, counting and coding

The diagnostic odyssey for people living with rare diseases (PLWRD) is often prolonged for myriad reasons including an initial failure to consider rare disease and challenges to systemically and systematically identifying and tracking undiagnosed diseases across the diagnostic journey. This often results in isolation, uncertainty, a delay to targeted treatments and increase in risk of complications with significant consequences for patient and family wellbeing. This article aims to highlight key time points to consider a rare disease diagnosis along with elements to consider in the potential operational classification for undiagnosed rare diseases during the diagnostic odyssey. We discuss the need to create a coding framework that traverses all stages of the diagnostic odyssey for PLWRD along with the potential benefits this will have to PLWRD and the wider community.

The Tuscany Regional Network for rare diseases: from European Reference Networks' experience to registry based organisation and management model for rare diseases

BACKGROUND

In the European Union, a disease is defined as rare when it affects fewer than 1 in 2000 people. Currently, there are up to 8000 described rare diseases (RDs), collectively affecting 30 million people in the European Union. In 2004 Tuscany region (Italy) established a Regional Network of hospital units to ensure highly specialised medical care in the field of RDs. Shortly after the Rare Diseases Registry of Tuscany (Registro Toscano Malattie Rare-RTMR) was implemented. Here we describe the analysis performed on RTMR data which has recently allowed to remap the Network based on European Reference Networks' model.

RESULTS

Data analysis was performed on 60,367 cases registered in RTMR, regarding 628 RDs. Two-hundred and fifteen active presidia have been evaluated. The assignment of each RD to the suitable European Reference Network has been made considering not only the number of registered cases, certifications and treatment plans for each Regional Presidium but also the competence in multidisciplinary management of the patient, from diagnosis to treatment. This evaluation has led to the establishment of twenty-one Regional Coordination Centres. They aggregate and coordinate Hospital Units which diagnose and treat one or a group of related RDs. In case of wide groups of RDs, Clinical Subnets are instituted. Updated statistics regarding RDs in Tuscany, list of RDs and Coordination Centres, as well as information about single Presidia are published and freely available on a designated webpage. Regional Decrees are regularly updated according to the network evolution.

CONCLUSIONS

The Rare Diseases Regional Network in Tuscany, based on the ERN model, has played a pivotal role in enhancing RD management and research. The remapping has led to a dynamic system, following not only scientific research but also the development of Presidia's expertise. By pooling resources and expertise, the network has improved the availability and accessibility of specialized care for patients with RDs. Collaborative efforts, data sharing, and standardized registries are crucial for advancing RD research, improving diagnosis and treatment, and ultimately enhancing the quality of life for individuals living with RDs.

Pharmacovigilance for rare diseases: a bibliometrics and knowledge-map analysis based on web of science

OBJECTIVES

The aims of this paper is to search and explore publications in the field of pharmacovigilance for rare diseases and to visualize general information, research hotspots, frontiers and future trends in the field using the bibliometric tool CiteSpace to provide evidence-based evidence for scholars.

METHODS

We searched the Web of Science Core Collection (WoSCC) for studies related to pharmacovigilance for rare diseases, spanning January 1, 1997-October 25, 2022. CiteSpace software was utilized to discuss countries/regions, institutions, authors, journals, and keywords.

RESULTS

After screening, a total of 599 valid publications were included in this study, with a significant upward trend in the number of publications. These studies were from 68 countries/regions with the United States and the United Kingdom making the largest contributions to the field. 4,806 research scholars from 493 institutions conducted studies on pharmacovigilance for rare diseases. Harvard University and University of California were the top two productive institutions in the research field. He Dian of the Affiliated Hospital of Guizhou Medical University and Peter G.M. Mol of the University of Groningen, The Netherlands, were the two most prolific researchers. The Cochrane Database of Systematic Reviews and the New England Journal of Medicine were the journals with the highest number of articles and co-citation frequency respectively. Clinical trial, therapy and adverse event were the top three most cited keywords.

CONCLUSIONS

Based on keywords co-occurrence analysis, four research topics were identified: orphan drug clinical trials, postmarketing ADR surveillance for orphan drugs, rare diseases and orphan drug management, and diagnosis and treatment of rare diseases. Immune-related adverse reactions and benefit-risk assessment of enzyme replacement therapy were at the forefront of research in this field. Treatment outcomes, early diagnosis and natural history studies of rare diseases may become hotspots for future research.

Splicing defects in rare diseases: transcriptomics and machine learning strategies towards genetic diagnosis

Genomic variants affecting pre-messenger RNA splicing and its regulation are known to underlie many rare genetic diseases. However, common workflows for genetic diagnosis and clinical variant interpretation frequently overlook splice-altering variants. To better serve patient populations and advance biomedical knowledge, it has become increasingly important to develop and refine approaches for detecting and interpreting pathogenic splicing variants. In this review, we will summarize a few recent developments and challenges in using RNA sequencing technologies for rare disease investigation. Moreover, we will discuss how recent computational splicing prediction tools have emerged as complementary approaches for revealing disease-causing variants underlying splicing defects. We speculate that continuous improvements to sequencing technologies and predictive modeling will not only expand our understanding of splicing regulation but also bring us closer to filling the diagnostic gap for rare disease patients.

A disease-specific iPS cell resource for studying rare and intractable diseases

BACKGROUND

Disease-specific induced pluripotent stem cells (iPSCs) are useful tools for pathological analysis and diagnosis of rare diseases. Given the limited available resources, banking such disease-derived iPSCs and promoting their widespread use would be a promising approach for untangling the mysteries of rare diseases. Herein, we comprehensively established iPSCs from patients with designated intractable diseases in Japan and evaluated their properties to enrich rare disease iPSC resources.

METHODS

Patients with designated intractable diseases were recruited for the study and blood samples were collected after written informed consent was obtained from the patients or their guardians. From the obtained samples, iPSCs were established using the episomal method. The established iPSCs were deposited in a cell bank.

RESULTS

We established 1,532 iPSC clones from 259 patients with 139 designated intractable diseases. The efficiency of iPSC establishment did not vary based on age and sex. Most iPSC clones originated from non-T and non-B hematopoietic cells. All iPSC clones expressed key transcription factors, OCT3/4 (range 0.27-1.51; mean 0.79) and NANOG (range 0.15-3.03; mean 1.00), relative to the reference 201B7 iPSC clone.

CONCLUSIONS

These newly established iPSCs are readily available to the researchers and can prove to be a useful resource for research on rare intractable diseases.

Application of facial analysis Technology in Clinical Genetics: Considerations for diverse populations

Facial analysis technology in rare diseases has the potential to shorten the diagnostic odyssey by providing physicians with a valuable diagnostic tool. Given that most clinical genetic resources focus on populations of European descent, we compare craniofacial features in genetic syndromes across different populations and review how machine learning algorithms perform on diagnosing genetic syndromes in geographically and ethnically diverse populations. We also discuss the value of populations from ancestrally diverse backgrounds in the training set of machine learning algorithms. Finally, this review demonstrates that across diverse population groups, machine learning models have outstanding accuracy as supported by the area under the curve values greater than 0.9. Artificial intelligence is only in its infancy in the diagnosis of rare disease in diverse populations and will become more accurate as larger and more diverse training sets, including a wider spectrum of ages, particularly infants, are studied.

RDKG-115: Assisting drug repurposing and discovery for rare diseases by trimodal knowledge graph embedding

Rare diseases (RDs) may affect individuals in small numbers, but they have a significant impact on a global scale. Accurate diagnosis of RDs is challenging, and there is a severe lack of drugs available for treatment. Pharmaceutical companies have shown a preference for drug repurposing from existing drugs developed for other diseases due to the high investment, high risk, and long cycle involved in RD drug development. Compared to traditional approaches, knowledge graph embedding (KGE) based methods are more efficient and convenient, as they treat drug repurposing as a link prediction task. KGE models allow for the enrichment of existing knowledge by incorporating multimodal information from various sources. In this study, we constructed RDKG-115, a rare disease knowledge graph involving 115 RDs, composed of 35,643 entities, 25 relations, and 5,539,839 refined triplets, based on 372,384 high-quality literature and 4 biomedical datasets: DRKG, Pathway Commons, PharmKG, and PMapp. Subsequently, we developed a trimodal KGE model containing structure, category, and description embeddings using reverse-hyperplane projection. We utilized this model to infer 4199 reliable new inferred triplets from RDKG-115. Finally, we calculated potential drugs and small molecules for each of the 115 RDs, taking multiple sclerosis as a case study. This study provides a paradigm for large-scale screening of drug repurposing and discovery for RDs, which will speed up the drug development process and ultimately benefit patients with RDs. The source code and data are available at https://github.com/ZhuChaoY/RDKG-115.

Congenital disorders of glycosylation: narration of a story through its patents

Congenital disorders of glycosylation are a group of more than 160 rare genetic defects in protein and lipid glycosylation. Since the first clinical report in 1980 of PMM2-CDG, the most common CDG worldwide, research made great strides, but nearly all of them are still missing a cure. CDG diagnosis has been at a rapid pace since the introduction of whole-exome/whole-genome sequencing as a diagnostic tool. Here, we retrace the history of CDG by analyzing all the patents associated with the topic. To this end, we explored the Espacenet database, extracted a list of patents, and then divided them into three major groups: (1) Drugs/therapeutic approaches for CDG, (2) Drug delivery tools for CDG, (3) Diagnostic tools for CDG. Despite the enormous scientific progress experienced in the last 30 years, diagnostic tools, drugs, and biomarkers are still urgently needed.

Physicians' use and perceptions of genetic testing for rare diseases in China: a nationwide cross-sectional study

BACKGROUND

Genetic testing can facilitate the diagnosis and subsequent therapeutic management of rare diseases. However, there is a lack of data on the use of genetic testing for rare diseases. This study aims to describe the utilization rate and troubles encountered by clinicians in treating rare diseases with genetic testing.

METHODS

A cross-sectional electronic questionnaire survey was conducted between June and October 2022 among the medical staff from the hospitals covering all provinces, municipalities, and autonomous regions of China. The survey on genetic testing focused on whether genetic testing was used in the diagnosis and treatment of rare diseases, the specific methods of genetic testing, and the problems encountered when using genetic testing.

RESULTS

A total of 20,132 physicians who had treated rare diseases were included, of whom 35.5% were from the central region, 36.7% were from the eastern region, and 27.8% were from the western region. The total utilization rate of genetic testing for rare diseases was 76.0% (95%CI: 75.4-76.6). The use of genetic testing was highest in the Eastern region (79.2% [95% CI: 78.3-80.1]), followed by the Central (75.9% [95% CI: 74.9-76.9]) and Western regions (71.9% [95% CI: 70.7-73.1]). More than 90% (94.1% [95%CI: 93.4-94.8]) of pediatricians had used genetic testing to treat rare diseases, with surgeons having the lowest use of genetic testing (58.3% [95% CI: 56.6-60.0]). Physicians' departments and education levels affect the use of genetic testing. Most physicians have used a variety of genetic tests in the management of rare diseases, the most popular methods were "Whole-exome sequencing (Proband)" and "Whole-exome sequencing (families of three or more)". Doctors have encountered many problems with the use of genetic testing in the diagnosis and treatment of rare diseases, among which the high price was the main concern of medical workers.

CONCLUSION

Three-quarters of physicians used genetic testing in rare disease practice, and there were regional differences in the use of genetic testing. Recognition of the utilization of genetic testing can help identify patterns of resource utilization in different regions and provide a more comprehensive picture of the epidemiology of rare diseases in jurisdictions.

Introducing the South African Rare Diseases Access Initiative

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How to START? Four pillars to optimally begin your orphan drug development

Drug development is a complex, resource intensive and long process in any disease area, and developing medicines to treat rare diseases presents even more challenges due to the small patient populations, often limited disease knowledge, heterogeneous clinical manifestations, and disease progression. However, common to all drug development programs is the need to gather as much information as possible on both the disease and the patients' needs ahead of the development path definition. Here, we propose a checklist named START, a tool that provides an overview of the key pillars to be considered when starting an orphan drug development: STakeholder mapping, Available information on the disease, Resources, and Target patient value profile. This tool helps to build solid foundations of a successful patient-centered medicines development program and guides different types of developers through a set of questions to ask for guidance through the starting phase of a rare disease therapeutic pathway.

Clinical applications of gene therapy for rare diseases: A review

Rare diseases collectively exact a high toll on society due to their sheer number and overall prevalence. Their heterogeneity, diversity, and nature pose daunting clinical challenges for both management and treatment. In this review, we discuss recent advances in clinical applications of gene therapy for rare diseases, focusing on a variety of viral and non-viral strategies. The use of adeno-associated virus (AAV) vectors is discussed in the context of Luxturna, licenced for the treatment of RPE65 deficiency in the retinal epithelium. Imlygic, a herpes virus vector licenced for the treatment of refractory metastatic melanoma, will be an example of oncolytic vectors developed against rare cancers. Yescarta and Kymriah will showcase the use of retrovirus and lentivirus vectors in the autologous ex vivo production of chimeric antigen receptor T cells (CAR-T), licenced for the treatment of refractory leukaemias and lymphomas. Similar retroviral and lentiviral technology can be applied to autologous haematopoietic stem cells, exemplified by Strimvelis and Zynteglo, licenced treatments for adenosine deaminase-severe combined immunodeficiency (ADA-SCID) and β-thalassaemia respectively. Antisense oligonucleotide technologies will be highlighted through Onpattro and Tegsedi, RNA interference drugs licenced for familial transthyretin (TTR) amyloidosis, and Spinraza, a splice-switching treatment for spinal muscular atrophy (SMA). An initial comparison of the effectiveness of AAV and oligonucleotide therapies in SMA is possible with Zolgensma, an AAV serotype 9 vector, and Spinraza. Through these examples of marketed gene therapies and gene cell therapies, we will discuss the expanding applications of such novel technologies to previously intractable rare diseases.

Requirements analysis for an AI-based clinical decision support system for general practitioners: a user-centered design process

BACKGROUND

As the first point of contact for patients with health issues, general practitioners (GPs) are frequently confronted with patients presenting with non-specific symptoms of unclear origin. This can result in delayed, prolonged or false diagnoses. To accelerate and improve the diagnosis of diseases, clinical decision support systems would appear to be an appropriate tool. The objective of the project 'Smart physician portal for patients with unclear disease' (SATURN) is to employ a user-centered design process based on the requirements analysis presented in this paper to develop an artificial Intelligence (AI)-based diagnosis support system that specifically addresses the needs of German GPs.

METHODS

Requirements analysis for a GP-specific diagnosis support system was conducted in an iterative process with five GPs. First, interviews were conducted to analyze current workflows and the use of digital applications in cases of diagnostic uncertainty (as-is situation). Second, we focused on collecting and prioritizing tasks to be performed by an ideal smart physician portal (to-be situation) in a workshop. We then developed a task model with corresponding user requirements.

RESULTS

Numerous GP-specific user requirements were identified concerning the tasks and subtasks: performing data entry (open system, enter patient data), reviewing results (receiving and evaluating results), discussing results (with patients and colleagues), scheduling further diagnostic procedures, referring to specialists (select, contact, make appointments), and case closure. Suggested features particularly concerned the process of screening and assessing results: e.g., the system should focus more on atypical patterns of common diseases than on rare diseases only, display probabilities of differential diagnoses, ensure sources and results are transparent, and mark diagnoses that have already been ruled out. Moreover, establishing a means of using the platform to communicate with colleagues and transferring patient data directly from electronic patient records to the system was strongly recommended.

CONCLUSIONS

Essential user requirements to be considered in the development and design of a diagnosis system for primary care could be derived from the analysis. They form the basis for mockup-development and system engineering.

Analysis of Incentive Policies and Initiatives on Orphan Drug Development in China: Challenges, Reforms and Implications

OBJECTIVES

Rare diseases are a global public health issue with a more pressing situation in China. Unfortunately, the relevant research and development in this country are still in its infancy, leading to limited drug accessibility. In view of this, the Chinese government has taken a series of countermeasures to promote orphan drug R&D in recent years, which has presented encouraging results. This paper aims to review incentive policies and funding initiatives formulated by the Chinese government and examine their implications on orphan drug R&D.

METHODS

Policies targeting orphan drug R&D during 2012-2022 were retrieved from the relevant official websites, categorized into different themes and analyzed for the contents. Data on government funding, drug approval, clinical trial approval and orphan drug designation were collected through internet search to analyze the implications of those incentive policies and initiatives on orphan drug R&D in China.

RESULTS

A total of 20 relevant policy documents were identified and five major themes were revealed through content analysis, including national strategy, expedited approval, safety and efficacy requirements, data protection and technical support. The government input in orphan drug R&D has witnessed a steady annual increase. Driven by those incentives, the numbers of orphan drugs approved for marketing and drug candidates entering clinical studies are increasing year by year, and more domestic pharmaceutical companies are actively involved in the R&D of orphan drugs.

CONCLUSIONS

Orphan drug development in China is growing rapidly under the stimulation of incentive regulatory policies and more investment in researches. China is working toward a more standardized and comprehensive rare disease ecosystem. However, there are still some challenges, such as the lack of sufficient financial support and the call for systematic legislation on rare diseases, to be addressed for future success.