Results of clinical and genetic diagnosis of rare diseases in the Eastern region of Hungary (2007–2013)

Introduction: 80% of rare diseases have a genetic origin, and 50% manifest themselves as congenital anomalies. Their adequate health care includes early recognition of genetic anomalies and prevention of recurrence. Aim: The aims of the authors were to provide correct diagnoses to patients with multiple congenital anomalies with or without mental retardation attending to the outpatient clinic of the Clinical Genetics Center at the University of Debrecen in the time interval between August 1, 2007 and March 31, 2013, establish the possibility of prenatal diagnosis, assess the distribution of different genetic mechanisms in the background of rare genetic diseases, compare them with international data, and develop an algorithm for the diagnostic approach of rare genetic diseases applicable in Hungary. Method: Clinical data and genetic results of patients were evaluated, and patients were categorized into one of the ten proposed etiological groups, based on which the distribution of genetic causes was defined. Results: Clinical diagnosis was achieved in 64.3% of patients, confirmed genetic diagnosis in 37.8%, while 35.7% of patients remained undiagnosed. Several dysmorphic syndromes and metabolic disorders were first diagnosed in Hungary, two of which unique in the literature. Conclusions: In the centre of the authors the diagnostic effectiveness of chromosome aberrations exceeds the international standards, that of known microdeletions and dysmorphic syndromes meets international data, and the genetic diagnosis of mendelian disorders and submicroscopic copy number changes remain below international figures. Orv. Hetil., 2014, 155(9), 348–357.

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Ethics and equity in rare disease research and healthcare

Personalized Medicine ◽

10.2217/pme-2020-0144 ◽

2021 ◽

Author(s):

Maria Koromina ◽

Vasileios Fanaras ◽

Gareth Baynam ◽

Christina Mitropoulou ◽

George P Patrinos

Keyword(s):

Rare Diseases ◽

Ethical Issues ◽

Genetic Diseases ◽

Ethical Framework ◽

Middle Income ◽

Next Generation Sequencing Technology ◽

Ethical Frameworks ◽

Rare Genetic Diseases ◽

Conducting Research ◽

Key Aspects

Rapid advances in next-generation sequencing technology, particularly whole exome sequencing and whole genome sequencing, have greatly affected our understanding of genetic variation underlying rare genetic diseases. Herein, we describe ethical principles of guiding consent and sharing of genomics research data. We also discuss ethical dilemmas in rare diseases research and patient recruitment policies and address bioethical and societal aspects influencing the ethical framework for genetic testing. Moreover, we focus on addressing ethical issues surrounding research in low- and middle-income countries. Overall, this perspective aims to address key aspects and issues for building proper ethical frameworks, when conducting research involving genomics data with a particular emphasis on rare diseases and genetics testing.

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Reference exome data for a Northern Brazilian population

Scientific Data ◽

10.1038/s41597-020-00703-y ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Alexia L. Weeks ◽

Richard W. Francis ◽

Joao I. C. F. Neri ◽

Nathaly M. C. Costa ◽

Nivea M. R. Arrais ◽

...

Keyword(s):

Rare Diseases ◽

Sequence Data ◽

Genetic Diseases ◽

Specific Reference ◽

Single Nucleotide Variants ◽

Data Set ◽

Single Nucleotide ◽

Rare Genetic Diseases ◽

Genetics And Genomics ◽

Brazilian Cohort

Abstract Exome sequencing is widely used in the diagnosis of rare genetic diseases and provides useful variant data for analysis of complex diseases. There is not always adequate population-specific reference data to assist in assigning a diagnostic variant to a specific clinical condition. Here we provide a catalogue of variants called after sequencing the exomes of 45 babies from Rio Grande do Nord in Brazil. Sequence data were processed using an ‘intersect-then-combine’ (ITC) approach, using GATK and SAMtools to call variants. A total of 612,761 variants were identified in at least one individual in this Brazilian Cohort, including 559,448 single nucleotide variants (SNVs) and 53,313 insertion/deletions. Of these, 58,111 overlapped with nonsynonymous (nsSNVs) or splice site (ssSNVs) SNVs in dbNSFP. As an aid to clinical diagnosis of rare diseases, we used the American College of Medicine Genetics and Genomics (ACMG) guidelines to assign pathogenic/likely pathogenic status to 185 (0.32%) of the 58,111 nsSNVs and ssSNVs. Our data set provides a useful reference point for diagnosis of rare diseases in Brazil. (169 words).

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Rett syndrome in Russia and abroad: a scientific historical review

Rossiyskiy Vestnik Perinatologii i Pediatrii (Russian Bulletin of Perinatology and Pediatrics) ◽

10.21508/1027-4065-2020-65-3-25-31 ◽

2020 ◽

Vol 65 (3) ◽

pp. 25-31

Author(s):

S. G. Vorsanova ◽

Yu. B. Yurov ◽

V. Yu. Voinova ◽

I. Yu. Yurov

Keyword(s):

Rett Syndrome ◽

Rare Diseases ◽

Gene Sequence ◽

Genetic Diseases ◽

Historical Review ◽

Mecp2 Gene ◽

Cellular Mechanisms ◽

Rare Genetic Diseases ◽

Present Information ◽

Genomic Disorders

This review presents the theoretical, practical and geographical aspects of Rett syndrome and other rare diseases, according to the data of the last VIII International Congress in Russia, and the main publications on Rett syndrome. The issues highlighted by the participants remain relevant and determine the direction of modern studies. The presentations made at the symposium helped to form a global concept of the molecular and cellular mechanisms of Rett syndrome and a number of rare genetic/genomic diseases. The article presents a number of domestic findings in the field of Rett syndrome and other rare diseases. The authors also present information on rare diseases associated with the Rett-like-phenotype or with mutations/variations of the MECP2 gene sequence copies. The authors consider the identified chromosomal (genomic) disorders / diseases in the context of rare diseases. This approach to the Rett syndrome studies analysis is quite new in the world research practice. We hope this review to become valuable not only for specialists in the field of rare genetic diseases, but also for the scientists and clinicians studying Rett syndrome and for physicians (pediatricians, geneticists, neurologists, psychiatrists) meeting these patients in their practice.

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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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Whole-genome sequencing as a first-tier diagnostic framework for rare genetic diseases

Experimental Biology and Medicine ◽

10.1177/15353702211040046 ◽

2021 ◽

pp. 153537022110400

Author(s):

Haseeb Nisar ◽

Bilal Wajid ◽

Samiah Shahid ◽

Faria Anwar ◽

Imran Wajid ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Rare Diseases ◽

Genetic Diseases ◽

Correct Diagnosis ◽

Clinical Settings ◽

Whole Genome ◽

Rare Genetic Diseases ◽

Diagnostic Approaches ◽

Diagnostic Framework

Rare diseases affect nearly 300 million people globally with most patients aged five or less. Traditional diagnostic approaches have provided much of the diagnosis; however, there are limitations. For instance, simply inadequate and untimely diagnosis adversely affects both the patient and their families. This review advocates the use of whole genome sequencing in clinical settings for diagnosis of rare genetic diseases by showcasing five case studies. These examples specifically describe the utilization of whole genome sequencing, which helped in providing relief to patients via correct diagnosis followed by use of precision medicine.

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An invincible memory: what surname analysis tells us about history, health and population medical genetics in the Brazilian Northeast

Journal of Biosocial Science ◽

10.1017/s0021932020000127 ◽

2020 ◽

pp. 1-16

Author(s):

Augusto César Cardoso-dos-Santos ◽

Virginia Ramallo ◽

Marcelo Zagonel-Oliveira ◽

Maurício Roberto Veronez ◽

Pablo Navarro ◽

...

Keyword(s):

Congenital Anomalies ◽

Genetic Diseases ◽

Genetic System ◽

Quantitative Information ◽

Medical Genetics ◽

Epidemiological Surveillance ◽

Spatially Correlated ◽

Demographic Heterogeneity ◽

Rare Genetic Diseases ◽

Brazilian Northeast

Abstract Several studies have shown that the Brazilian Northeast is a region with high rates of inbreeding as well as a high incidence of autosomal recessive diseases. The elaboration of public health policies focused on the epidemiological surveillance of congenital anomalies and rare genetic diseases in this region is urgently needed. However, the vast territory, socio-demographic heterogeneity, economic difficulties and low number of professionals with expertise in medical genetics make strategic planning a challenging task. Surnames can be compared to a genetic system with multiple neutral alleles and allow some approximation of population structure. Here, surname analysis of more than 37 million people was combined with health and socio-demographic indicators covering all 1794 municipalities of the nine states of the region. The data distribution showed a heterogeneous spatial pattern (Global Moran Index, GMI = 0.58; p < 0.001), with higher isonymy rates in the east of the region and the highest rates in the Quilombo dos Palmares region – the largest conglomerate of escaped slaves in Latin America. A positive correlation was found between the isonymy index and the frequency of live births with congenital anomalies (r = 0.268; p < 0.001), and the two indicators were spatially correlated (GMI = 0.50; p < 0.001). With this approach, quantitative information on the genetic structure of the Brazilian Northeast population was obtained, which may represent an economical and useful tool for decision-making in the medical field.

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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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