Research and Management of Rare Diseases in the COVID-19 Pandemic Era: Challenges and Countermeasures

The ongoing coronavirus disease 2019 (COVID-19) pandemic has disrupted every aspect of our life. The need to provide high-level care for an enormous number of patients with COVID-19 infection during this pandemic has impacted resourcing for and restricted the routine care of all non-COVID-19 conditions. Since the beginning of the pandemic, the people living with rare disorders, who represent a marginalized group of the population even in a normal world, have not received enough attention that they deserve. Due to the pandemic situation, they have experienced (and experiencing) an extreme inadequacy of regular clinical services, counseling, and therapies they need, which have made their life more vulnerable and feel more marginalized. Besides, the clinicians, researchers, and scientists working on rare genetic diseases face extra challenges due to the pandemic. Many ongoing research projects and clinical trials for rare and genetic diseases were stalled to avoid patients' and research staff's transmission to COVID-19. Still, with all the odds, telehealth and virtual consultations for rare disease patients have shown hope. The clinical, organizational, and economic challenges faced by institutions, patients, their families, and the caregivers during the pandemic indicate the importance of ensuring continuity of care in managing rare diseases, including adequate diagnostics and priority management strategies for emergencies. In this review, we endeavored to shed light on the issues the rare disease community faces during the pandemic and the adaptations that could help the rare disease community to better sustain in the coming days.

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PP154 Funding Of Treatments For Rare Diseases In Singapore

International Journal of Technology Assessment in Health Care ◽

10.1017/s0266462320001312 ◽

2020 ◽

Vol 36 (S1) ◽

pp. 17-18

Author(s):

Fiona Pearce ◽

Liang Lin ◽

Kwong Ng

Keyword(s):

Rare Disease ◽

Rare Diseases ◽

Genetic Diseases ◽

Evaluation Process ◽

Public Healthcare ◽

Clinical Group ◽

Eligibility Criteria ◽

Number Of Patients ◽

Emerging Treatments ◽

Multi Stakeholder

IntroductionA national multi-stakeholder charity fund has been established in Singapore to provide targeted support to patients with rare genetic diseases whose treatment costs remain unaffordable despite government subsidies and insurance. This presentation will provide an overview of the evaluation, price-setting, and stakeholder engagement processes established to inform the first list of drugs eligible for funding under the Rare Disease Fund (RDF).MethodsThe local prevalence of “rare” and “ultra-rare” conditions was defined in line with international rates (≤4 in 10,000 and <2 in 50,000, respectively) to facilitate an analysis of the rare disease landscape in Singapore, and to identify patients most likely to benefit from the RDF. Public healthcare institutions proposed drugs for consideration, which underwent technical evaluation and were then assessed in line with eligibility criteria by an expert clinical group and prioritized by decision makers for funding.ResultsThe number of patients with select rare diseases in Singapore was lower than global estimates contextualized to the local setting. Supporting clinical evidence, funding decisions from overseas health technology assessment agencies, reference pricing considerations, and local budget impact analyses informed the first tranche of drugs (n = 5) recommended. Extensive engagement with pharmaceutical companies was needed to negotiate fair drug prices relative to overseas countries. Additional treatments will be included in the RDF once sufficient funds are raised.ConclusionsAs the evaluation process evolves, wider considerations of disease and treatment experiences from a multi-stakeholder standpoint should be included to inform RDF listings. There is also a need to balance the sustainability of the fund in the longer term with the number of emerging treatments that may require coverage in the future.

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Leveraging the UMLS As a Data Standard for Rare Disease Data Normalization and Harmonization

Methods of Information in Medicine ◽

10.1055/s-0040-1718940 ◽

2020 ◽

Author(s):

Qian Zhu ◽

Dac-Trung Nguyen ◽

Eric Sid ◽

Anne Pariser

Keyword(s):

Rare Disease ◽

Rare Diseases ◽

Mendelian Inheritance ◽

Data Normalization ◽

Community Settings ◽

Unified Medical Language System ◽

Data Standard ◽

Medical Language ◽

Disease Concepts ◽

High Level

Abstract Objective In this study, we aimed to evaluate the capability of the Unified Medical Language System (UMLS) as one data standard to support data normalization and harmonization of datasets that have been developed for rare diseases. Through analysis of data mappings between multiple rare disease resources and the UMLS, we propose suggested extensions of the UMLS that will enable its adoption as a global standard in rare disease. Methods We analyzed data mappings between the UMLS and existing datasets on over 7,000 rare diseases that were retrieved from four publicly accessible resources: Genetic And Rare Diseases Information Center (GARD), Orphanet, Online Mendelian Inheritance in Men (OMIM), and the Monarch Disease Ontology (MONDO). Two types of disease mappings were assessed, (1) curated mappings extracted from those four resources; and (2) established mappings generated by querying the rare disease-based integrative knowledge graph developed in the previous study. Results We found that 100% of OMIM concepts, and over 50% of concepts from GARD, MONDO, and Orphanet were normalized by the UMLS and accurately categorized into the appropriate UMLS semantic groups. We analyzed 58,636 UMLS mappings, which resulted in 3,876 UMLS concepts across these resources. Manual evaluation of a random set of 500 UMLS mappings demonstrated a high level of accuracy (99%) of developing those mappings, which consisted of 414 mappings of synonyms (82.8%), 76 are subtypes (15.2%), and five are siblings (1%). Conclusion The mapping results illustrated in this study that the UMLS was able to accurately represent rare disease concepts, and their associated information, such as genes and phenotypes, and can effectively be used to support data harmonization across existing resources developed on collecting rare disease data. We recommend the adoption of the UMLS as a data standard for rare disease to enable the existing rare disease datasets to support future applications in a clinical and community settings.

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Cooccurrence of Two Different Genetic Diseases: A Case of Valproic Acid Hepatotoxicity in Nicolaides–Baraitser Syndrome (SMARCA2 Mutation)—Due to a POLG1-Related Effect?

Neuropediatrics ◽

10.1055/s-0039-1694976 ◽

2019 ◽

Vol 51 (01) ◽

pp. 049-052

Author(s):

Benedikt Hofmeister ◽

Celina von Stülpnagel ◽

Steffen Berweck ◽

Angela Abicht ◽

Gerhard Kluger ◽

...

Keyword(s):

Valproic Acid ◽

Literature Review ◽

Rare Disease ◽

Clinical Features ◽

Rare Diseases ◽

Rare Complication ◽

Genetic Diseases ◽

Related Effect ◽

Higher Sensitivity ◽

Polg1 Mutation

AbstractNicolaides–Baraitser syndrome (NCBRS) is a rare disease caused by a mutation in the SMARCA2 gene. Clinical features include craniofacial dysmorphia and abnormalities of the limbs, as well as intellectual disorder and often epilepsy. Hepatotoxicity is a rare complication of the therapy with valproic acid (VPA) and a mutation of the polymerase γ (POLG) might lead to a higher sensitivity for liver hepatotoxicity. We present a patient with the coincidence of two rare diseases, the NCBRS and additionally a POLG1 mutation in combination with a liver hepatotoxicity. The co-occurrence in children for two different genetic diseases is discussed with the help of literature review.

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RDmap: A Map for Exploring Rare Diseases

10.21203/rs.3.rs-84117/v2 ◽

2021 ◽

Author(s):

Jian Yang ◽

Cong Dong ◽

Huilong Duan ◽

Qiang Shu ◽

Haomin Li

Keyword(s):

Rare Disease ◽

Rare Diseases ◽

Genetic Diseases ◽

Distance Matrix ◽

Disease Diagnosis ◽

Human Phenotype ◽

Pathogenic Genes ◽

Disease Information ◽

Rare Genetic Diseases ◽

Interactive Map

Abstract Background: The complexity of the phenotypic characteristics and molecular bases of many rare human genetic diseases makes the diagnosis of such diseases a challenge for clinicians. A map for visualizing, locating and navigating rare diseases based on similarity will help clinicians and researchers understand and easily explore these diseases. Methods: A distance matrix of rare diseases included in Orphanet was measured by calculating the quantitative distance among phenotypes and pathogenic genes based on Human Phenotype Ontology (HPO) and Gene Ontology (GO), and each disease was mapped into Euclidean space. A rare disease map, enhanced by clustering classes and disease information, was developed based on ECharts. Results: A rare disease map called RDmap was published at http://rdmap.nbscn.org. Total 3,287 rare diseases are included in the phenotype-based map, and 3,789 rare genetic diseases are included in the gene-based map; 1,718 overlapping diseases are connected between two maps. RDmap works similarly to the widely used Google Map service and supports zooming and panning. The phenotype similarity base disease location function performed better than traditional keyword searches in an in silico evaluation, and 20 published cases of rare diseases also demonstrated that RDmap can assist clinicians in seeking the rare disease diagnosis. Conclusion: RDmap is the first user-interactive map-style rare disease knowledgebase. It will help clinicians and researchers explore the increasingly complicated realm of rare genetic diseases.

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Genomics of rare genetic diseases—experiences from India

Human Genomics ◽

10.1186/s40246-019-0215-5 ◽

2019 ◽

Vol 13 (1) ◽

Cited By ~ 2

Author(s):

Sridhar Sivasubbu ◽

◽

Vinod Scaria

Keyword(s):

Rare Disease ◽

Rare Diseases ◽

Collaborative Research ◽

Disease Burden ◽

Genetic Diseases ◽

Community Services ◽

Health Concern ◽

Healthy Population ◽

Rare Genetic Diseases ◽

Research Initiative

Abstract Home to a culturally heterogeneous population, India is also a melting pot of genetic diversity. The population architecture characterized by multiple endogamous groups with specific marriage patterns, including the widely prevalent practice of consanguinity, not only makes the Indian population distinct from rest of the world but also provides a unique advantage and niche to understand genetic diseases. Centuries of genetic isolation of population groups have amplified the founder effects, contributing to high prevalence of recessive alleles, which translates into genetic diseases, including rare genetic diseases in India. Rare genetic diseases are becoming a public health concern in India because a large population size of close to a billion people would essentially translate to a huge disease burden for even the rarest of the rare diseases. Genomics-based approaches have been demonstrated to accelerate the diagnosis of rare genetic diseases and reduce the socio-economic burden. The Genomics for Understanding Rare Diseases: India Alliance Network (GUaRDIAN) stands for providing genomic solutions for rare diseases in India. The consortium aims to establish a unique collaborative framework in health care planning, implementation, and delivery in the specific area of rare genetic diseases. It is a nation-wide collaborative research initiative catering to rare diseases across multiple cohorts, with over 240 clinician/scientist collaborators across 70 major medical/research centers. Within the GUaRDIAN framework, clinicians refer rare disease patients, generate whole genome or exome datasets followed by computational analysis of the data for identifying the causal pathogenic variations. The outcomes of GUaRDIAN are being translated as community services through a suitable platform providing low-cost diagnostic assays in India. In addition to GUaRDIAN, several genomic investigations for diseased and healthy population are being undertaken in the country to solve the rare disease dilemma. In summary, rare diseases contribute to a significant disease burden in India. Genomics-based solutions can enable accelerated diagnosis and management of rare diseases. We discuss how a collaborative research initiative such as GUaRDIAN can provide a nation-wide framework to cater to the rare disease community of India.

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RDmap: a map for exploring rare diseases

Orphanet Journal of Rare Diseases ◽

10.1186/s13023-021-01741-4 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Jian Yang ◽

Cong Dong ◽

Huilong Duan ◽

Qiang Shu ◽

Haomin Li

Keyword(s):

Rare Disease ◽

Rare Diseases ◽

Genetic Diseases ◽

Distance Matrix ◽

Disease Diagnosis ◽

Human Phenotype ◽

Pathogenic Genes ◽

Disease Information ◽

Rare Genetic Diseases ◽

Interactive Map

Abstract Background The complexity of the phenotypic characteristics and molecular bases of many rare human genetic diseases makes the diagnosis of such diseases a challenge for clinicians. A map for visualizing, locating and navigating rare diseases based on similarity will help clinicians and researchers understand and easily explore these diseases. Methods A distance matrix of rare diseases included in Orphanet was measured by calculating the quantitative distance among phenotypes and pathogenic genes based on Human Phenotype Ontology (HPO) and Gene Ontology (GO), and each disease was mapped into Euclidean space. A rare disease map, enhanced by clustering classes and disease information, was developed based on ECharts. Results A rare disease map called RDmap was published at http://rdmap.nbscn.org. Total 3287 rare diseases are included in the phenotype-based map, and 3789 rare genetic diseases are included in the gene-based map; 1718 overlapping diseases are connected between two maps. RDmap works similarly to the widely used Google Map service and supports zooming and panning. The phenotype similarity base disease location function performed better than traditional keyword searches in an in silico evaluation, and 20 published cases of rare diseases also demonstrated that RDmap can assist clinicians in seeking the rare disease diagnosis. Conclusion RDmap is the first user-interactive map-style rare disease knowledgebase. It will help clinicians and researchers explore the increasingly complicated realm of rare genetic diseases.

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Use of Zebrafish Models to Boost Research in Rare Genetic Diseases

International Journal of Molecular Sciences ◽

10.3390/ijms222413356 ◽

2021 ◽

Vol 22 (24) ◽

pp. 13356

Author(s):

Lucie Crouzier ◽

Elodie M. Richard ◽

Jo Sourbron ◽

Lieven Lagae ◽

Tangui Maurice ◽

...

Keyword(s):

Rare Diseases ◽

Genetic Diseases ◽

Critical Role ◽

High Rate ◽

Research Strategies ◽

Preclinical Research ◽

In Vivo Models ◽

Rare Genetic Diseases ◽

Number Of Patients

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.

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RDmap: A Map for Exploring Rare Diseases

10.21203/rs.3.rs-84117/v1 ◽

2020 ◽

Author(s):

Jian Yang ◽

Cong Dong ◽

Huilong Duan ◽

Qiang Shu ◽

Haomin Li

Keyword(s):

Rare Disease ◽

Rare Diseases ◽

Keyword Search ◽

Genetic Diseases ◽

Distance Matrix ◽

Pathogenic Genes ◽

Disease Information ◽

Rare Genetic Diseases ◽

Interactive Map ◽

Location Function

Abstract Background: The complexity of the phenotypic characteristics and molecular bases of many rare human genetic diseases make the diagnosis of such diseases a challenge for clinicians. A map for visualizing, locating and navigating rare diseases based on similarity will help clinicians and researchers understand and easily explore these diseases. Methods: By defining the quantitative distance among phenotypes and pathogenic genes based on corresponding ontology systems, the distance matrix of rare diseases included in Orphanet was calculated and mapped into Euclidean space. Enhanced by clustering classes and disease information, a rare disease map was developed based on ECharts. Results: The rare disease map called RDmap was published at http://rdmap.nbscn.org. The phenotype-based map comprises 3,287 rare diseases and the gene-based map comprises 3,789 rare genetic diseases and they were bridged by 1,718 overlapping diseases. RDmap works similar to the widely used Google map and supports zooming and panning. The phenotype similarity base disease location function performed better than traditional keyword search in an in-silico evaluation and 20 published cases of rare diseases also demonstrated that RDmap can be used by clinicians to improve diagnosis. Conclusion: RDmap is the first user-interactive map-style rare disease knowledgebase. It will help clinicians and researchers explore the increasing complicated rare genetic diseases.

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An International Comparative Analysis Highlighting that Canada is Not Keeping Pace With Patient Access to Drugs for Rare Diseases

10.21203/rs.3.rs-725738/v1 ◽

2021 ◽

Author(s):

Leanne Marie Ward ◽

Alexandra Chambers ◽

Emine Mechichi ◽

Durhane Wong-Rieger ◽

Craig Campbell

Keyword(s):

Comparative Analysis ◽

Rare Disease ◽

Orphan Drug ◽

Median Duration ◽

Rare Diseases ◽

Orphan Drug Designation ◽

Patient Access ◽

Number Of Patients ◽

Health Canada ◽

The U.S

Abstract Background: The Canadian government has committed to developing a national strategy for high-cost drugs for rare diseases starting in 2022. Considering this announcement, we conducted a comparative analysis to examine patient access to therapies for rare disease in each of Canada’s 10 provinces relative to Europe and the U.S., to understand how Canada measures up relative to other countries. Methods: We analyzed all of the therapies with an orphan drug designation approved by the European Medicine Agency (EMA) from 1 January 2015 to 31 March 2020 as the reference for the comparative analysis. We then contrasted access to these drugs in Canada (Health Canada) and the U.S. (Food and Drug Administration, FDA). Our analysis focused on: 1) the number of therapies for rare diseases entering the Canadian market; 2) the percentage of these therapies that are publicly available to Canadians; and 3) the timeliness for patient access to these therapies in Canada. Results: Our analysis identified 63 approved therapies with an orphan drug designation from the EMA. The FDA has approved 53/63 (84%) of these drugs, while Health Canada has approved 41/63 (65%). In Europe, Germany, Denmark, and the U.K. had the highest percentage of publicly reimbursed orphan drugs (84%, 70%, 68%, respectively). In comparison, Ontario (20/63, 32%), Quebec (16/63, 25%), and Alberta (16/63, 25%) had the highest percentage of drugs reimbursed among the Canadian provinces. The shortest median duration (in months) from EMA approval to jurisdictional decision on reimbursement was in Austria (3.2), followed by Germany (4.1), and Finland (6.0). In Canada, the shortest median duration (in months) from regulatory approval to reimbursement was in British Columbia (17.3), Quebec (19.6) and Manitoba (19.6), while the longest duration was in P.E.I (38.5), followed by Nova Scotia (25.9), and Newfoundland (25.1).Conclusions: Our comparative analysis found that Canadians had less frequent and timely access to therapies for rare disease than their global counterparts, highlighting the need for a strategy for rare disease in Canada that optimizes the number of patients with access to rare disease therapies, as quickly as possible.

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