10.2 Rare disease genomics and variant interpretation
6 min read•july 30, 2024
Rare disease genomics tackles the challenges of diagnosing and understanding disorders affecting few people. It uses advanced sequencing tech and data sharing to unravel the genetic basis of these conditions, aiming to improve diagnosis and develop targeted treatments.
Variant interpretation is crucial in rare disease genomics. It involves assessing genetic changes to determine their role in causing disease. This process uses guidelines, databases, and prediction tools to classify variants, guiding clinical decisions and research directions.
Genetic basis of rare diseases
Definition and prevalence of rare diseases
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- Rare diseases are disorders affecting a small number of people compared to the general population
- Often defined as affecting fewer than 200,000 individuals in the United States
- Defined as affecting fewer than 1 in 2,000 individuals in Europe
Genetic basis of rare diseases
- The majority of rare diseases have a genetic basis
- Monogenic disorders caused by single gene defects
- Complex disorders involving multiple genetic and environmental factors
Challenges in diagnosing rare diseases
- Limited number of affected individuals
- Phenotypic heterogeneity
- Variability in clinical presentation and severity among individuals with the same genetic defect
- Incomplete penetrance or variable expressivity of causal variants
- Not all individuals with a variant may develop the disease (incomplete penetrance)
- Individuals with the same pathogenic variant may have varying degrees of severity (variable expressivity)
- The "diagnostic odyssey"
- Prolonged and challenging process of obtaining an accurate diagnosis for a rare disease
- Can involve multiple specialist consultations, extensive testing, and significant emotional and financial burden for patients and families
Strategies to improve rare disease diagnosis
- Comprehensive phenotyping
- Detailed characterization of clinical features and symptoms
- Aids in identifying potential genetic causes and guiding targeted testing
- Utilization of genomic sequencing technologies
- and
- Enable the identification of novel or rare genetic variants
- Data sharing through rare disease databases and registries
- Facilitates the aggregation and comparison of clinical and genetic data from multiple patients
- Helps identify patterns and potential causative variants
- International collaboration among researchers and clinicians
- Pooling of expertise and resources to accelerate rare disease research and diagnosis
- Initiatives such as the Undiagnosed Diseases Network (UDN) and RD-Connect
Variant interpretation and pathogenicity
Guidelines for variant interpretation
- and the guidelines
- Standardized framework for the interpretation and reporting of sequence variants
- Classify variants into five categories: pathogenic, likely pathogenic, uncertain significance, likely , and benign
- Criteria for pathogenicity assessment
- Population frequency, functional evidence, computational predictions, segregation analysis, etc.
Variant interpretation tools and databases
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- Public archive of reports on the relationships among human variations and phenotypes
- Aggregates and curates information on the clinical significance of genetic variants
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- Comprehensive collection of germline mutations in nuclear genes associated with human inherited disease
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- Flexible, open-source database system for the curation and sharing of genetic variants
- These databases facilitate the sharing of knowledge and evidence-based classification of variants
In silico prediction tools
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- Predicts the impact of amino acid substitutions on protein function based on sequence homology and physical properties
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- Predicts the possible impact of amino acid substitutions on the structure and function of human proteins using physical and comparative considerations
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- Integrates multiple annotations into a single metric to predict the deleteriousness of variants
- These tools utilize algorithms to predict the potential impact of genetic variants on protein function and pathogenicity
Evidence for pathogenicity assessment
- Segregation analysis
- Evaluates the co-occurrence of a variant with the phenotype within affected families
- Provides evidence for or against pathogenicity based on the mode of inheritance and penetrance of the disorder
- Allele frequency in population databases
- Databases such as provide population-specific allele frequencies
- Pathogenic variants are expected to be rare or absent in the general population
- Functional evidence
- In vitro or in vivo studies demonstrating the impact of a variant on protein function, cellular processes, or model organisms
- Supports the pathogenicity of a variant by establishing a causal link to the disease mechanism
Functional studies for validation
In vitro functional assays
- Protein expression and activity assays
- Assess the impact of genetic variants on protein stability, folding, and function
- Examples: enzymatic assays, binding assays, reporter gene assays
- Cell-based assays
- Patient-derived induced pluripotent stem cells (iPSCs)
- Enable the study of cellular and molecular phenotypes in a disease-relevant context
- Allow for the investigation of disease mechanisms and drug screening
- Engineered cell lines expressing specific variants
- Provide a controlled system to study the effects of genetic variants on cellular processes
- Examples: edited cell lines, overexpression or knockdown models
- Patient-derived induced pluripotent stem cells (iPSCs)
Animal models
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- Mice, zebrafish, Drosophila, etc.
- Allow for the study of the in vivo effects of genetic variants on development, physiology, and behavior
- Provide insights into disease pathogenesis and potential therapeutic targets
- Genotype-phenotype correlation studies
- Establish the causal relationship between genetic variants and disease phenotypes in animal models
- Support the pathogenicity of the variants and inform human disease mechanisms
Preclinical therapeutic studies
- Testing of potential therapeutic interventions in animal models or cell-based systems
- Small molecules, gene therapy, antisense oligonucleotides, etc.
- Assess the efficacy and safety of therapies in a preclinical setting
- Guide the development of targeted treatments for rare diseases
Importance of functional validation
- Strengthens the evidence for variant pathogenicity
- Complements computational predictions and population frequency data
- Provides a mechanistic understanding of disease pathogenesis
- Informs the development of targeted therapies
- Identifies potential therapeutic targets and pathways
- Enables the preclinical testing of personalized treatment approaches
Ethical implications of rare diseases
Psychosocial impact of the diagnostic odyssey
- Emotional and psychological challenges for patients and families
- Uncertainty, isolation, and frustration during the prolonged diagnostic process
- Need for psychosocial support and counseling services
- Impact on family relationships and dynamics
- Strain on caregivers and siblings
- Potential for guilt, blame, or overprotectiveness within the family
Genetic testing and informed consent
- Implications for family members
- Genetic testing results may have consequences for biological relatives
- Issues of confidentiality and the right to know or not know one's genetic status
- Reproductive decision-making
- Prenatal diagnosis, preimplantation genetic testing, or the decision to forgo having biological children
- Ethical considerations surrounding the use of assisted reproductive technologies
- process
- Ensuring adequate understanding of the risks, benefits, and limitations of genetic testing
- Addressing the potential for incidental findings or variants of uncertain significance
Access to treatments and resources
- Limited availability and high cost of treatments
- Enzyme replacement therapy, gene therapy, or other targeted therapies may be expensive or not widely accessible
- Raises issues of equity and resource allocation in healthcare systems
- Advocacy for rare disease community
- Efforts to increase awareness, funding, and research for rare diseases
- Collaborations among patient organizations, researchers, and policymakers to improve access to care and support
Participation in rare disease research
- Informed consent and data sharing
- Ensuring participant understanding of the risks and benefits of research participation
- Addressing concerns about privacy, confidentiality, and the use of genetic and clinical data
- Balancing individual benefits and societal value
- Considerations of personal autonomy and the potential for research to advance knowledge and treatments for the broader rare disease community
- Engaging patients and families as partners in the research process
Psychosocial support and quality of life
- Impact of living with a rare disease
- Challenges in social relationships, education, and employment
- Potential for stigma, discrimination, or misunderstanding
- Importance of comprehensive support services
- Access to specialized medical care, rehabilitation, and assistive technologies
- Peer support groups, patient advocacy organizations, and educational resources
- Addressing the unique needs and experiences of individuals and families affected by rare diseases
Key Terms to Review (28)
American College of Medical Genetics and Genomics (ACMG): The American College of Medical Genetics and Genomics (ACMG) is a professional organization that focuses on the practice of medical genetics and genomics, providing education, advocacy, and setting standards for genetic healthcare. It plays a crucial role in rare disease genomics and variant interpretation by guiding clinicians and researchers in the analysis and understanding of genetic variants associated with rare conditions.
Association for Molecular Pathology (AMP): The Association for Molecular Pathology (AMP) is a professional organization that focuses on advancing the practice of molecular pathology and precision medicine. AMP plays a vital role in fostering education, setting standards for testing, and guiding the interpretation of genetic variants, especially in the context of rare diseases where accurate diagnosis is crucial for patient management and treatment.
Benign: In the context of rare disease genomics, 'benign' refers to genetic variants that are unlikely to cause disease or have a harmful effect on an individual's health. These variants do not contribute to the risk of developing specific conditions and are generally considered harmless. Understanding benign variants is crucial for accurate interpretation of genetic data, especially when distinguishing them from pathogenic or likely pathogenic variants.
Cadd (combined annotation dependent depletion): CADD, or Combined Annotation Dependent Depletion, is a computational tool used to assess the deleteriousness of genetic variants by integrating multiple annotations and predicting their impact on gene function. It provides a score that reflects the likelihood of a variant being harmful, which is especially useful in rare disease genomics for variant interpretation and prioritization. This scoring system helps researchers and clinicians distinguish between benign and pathogenic variants in the context of genetic disorders.
Carrier screening: Carrier screening is a genetic testing method used to identify individuals who carry one copy of a gene mutation associated with a genetic disorder, even if they do not exhibit any symptoms. This process is crucial in understanding the risk of passing on genetic conditions to future offspring and plays a significant role in the context of rare disease genomics and variant interpretation.
Clinical Laboratory Improvement Amendments (CLIA): Clinical Laboratory Improvement Amendments (CLIA) refers to a set of U.S. federal regulations that establish quality standards for laboratory testing to ensure accurate and reliable results. These amendments play a crucial role in the context of rare disease genomics and variant interpretation by setting guidelines for laboratory operations, including test accuracy and personnel qualifications, ultimately impacting patient diagnosis and treatment.
ClinVar: ClinVar is a publicly accessible database that aggregates and shares information about the relationships between genetic variants and human health. It serves as a vital resource for clinicians, researchers, and genetic counselors by providing a comprehensive platform for understanding the clinical significance of genetic variations, especially in the context of rare diseases and variant interpretation.
Copy Number Variations (CNVs): Copy Number Variations (CNVs) are a type of structural variation in the genome where sections of DNA are repeated, resulting in a variable number of copies of that particular region. CNVs can influence gene dosage, affect gene expression, and contribute to phenotypic diversity, making them particularly significant in the study of rare diseases and genetic disorders.
CRISPR-Cas9: CRISPR-Cas9 is a revolutionary genome-editing technology that allows scientists to make precise modifications to DNA within living organisms. It harnesses a natural defense mechanism used by bacteria to target and cut specific DNA sequences, making it a powerful tool for applications in genetic research, therapy, agriculture, and synthetic biology.
Cystic fibrosis: Cystic fibrosis is a genetic disorder caused by mutations in the CFTR gene, leading to the production of thick and sticky mucus that can clog various organs, particularly the lungs and pancreas. This condition significantly impacts respiratory function and digestion, making it a critical example of how rare genetic diseases can be understood and managed through genomic insights and clinical practices.
DbSNP: dbSNP (Database of Single Nucleotide Polymorphisms) is a comprehensive public database that catalogs genetic variation in the form of single nucleotide polymorphisms (SNPs) and other minor genetic variants. It serves as an essential resource for researchers in genomics, allowing them to access information on SNP locations, allele frequencies, and associations with diseases. This database plays a critical role in various areas of genetic research, including understanding population genetics, conducting genome-wide association studies, and interpreting genetic variants in rare diseases.
Food and Drug Administration (FDA) Guidelines: FDA guidelines refer to the regulations and recommendations set forth by the Food and Drug Administration, an agency of the U.S. Department of Health and Human Services. These guidelines ensure that food, drugs, and medical devices are safe, effective, and manufactured according to established standards. In the realm of genomics, particularly concerning rare diseases, these guidelines play a critical role in determining how genetic tests are validated, how variant interpretations are made, and how treatments are developed and approved.
Genetic privacy: Genetic privacy refers to the right of individuals to control access to and the use of their genetic information. This concept is crucial as genetic data can reveal sensitive information about a person's health, ancestry, and potential future medical conditions, making it essential to protect individuals from discrimination, breaches of confidentiality, and unauthorized use of their genetic data.
GnomAD (Genome Aggregation Database): gnomAD is a comprehensive resource that aggregates and harmonizes genomic data from diverse populations to provide insights into human genetic variation. It plays a crucial role in rare disease genomics and variant interpretation by offering a large dataset that researchers can utilize to assess the frequency of genetic variants across different populations, helping to distinguish between benign and pathogenic variants.
Human Gene Mutation Database (HGMD): The Human Gene Mutation Database (HGMD) is a comprehensive resource that catalogs mutations in human genes that are associated with inherited diseases. This database is essential for understanding rare genetic disorders and facilitates variant interpretation by providing a centralized collection of mutation data, which helps researchers and clinicians assess the pathogenicity of specific genetic variants in the context of rare diseases.
Informed consent: Informed consent is the process through which individuals are provided with information about a medical or research procedure, allowing them to make knowledgeable decisions regarding their participation. This process is crucial in ensuring that participants understand the risks, benefits, and alternatives involved, fostering trust and transparency in healthcare and research settings.
Leiden Open Variation Database (LOVD): The Leiden Open Variation Database (LOVD) is a centralized online platform designed to facilitate the collection, curation, and sharing of genetic variation data, specifically for genes associated with rare diseases. It enables researchers and clinicians to access a wealth of variant information, including clinical interpretations, which aids in understanding the relationship between genetic variants and specific phenotypes in rare diseases.
Pathogenic: Pathogenic refers to the ability of an organism, often a microorganism, to cause disease in a host. This term is crucial in understanding how certain genetic variants can disrupt normal biological functions, leading to rare diseases and influencing clinical outcomes through genomic variation.
Polyphen (polymorphism phenotyping): PolyPhen, short for polymorphism phenotyping, is a computational tool used to predict the potential impact of amino acid substitutions on the function of human proteins. By analyzing genetic variants, PolyPhen assesses whether a change is likely to be benign, possibly damaging, or probably damaging, which is crucial for understanding the relationship between genetic mutations and rare diseases.
Pre-symptomatic testing: Pre-symptomatic testing refers to genetic testing conducted to identify individuals who may carry genetic mutations associated with a disease, even before symptoms appear. This type of testing is particularly important in the context of rare diseases, as it allows for early diagnosis and potential interventions, while also providing critical information for family planning and management.
Rna sequencing: RNA sequencing is a powerful technique used to determine the quantity and sequences of RNA in a sample, providing insights into gene expression and regulation. By capturing the transcriptome, it allows researchers to identify differentially expressed genes and variants associated with rare diseases, facilitating a better understanding of the genetic basis of these conditions.
Sickle cell disease: Sickle cell disease is a genetic blood disorder caused by a mutation in the HBB gene, leading to the production of abnormal hemoglobin known as hemoglobin S. This disease affects red blood cells, causing them to become rigid and shaped like a sickle, which can block blood flow and lead to severe pain and various health complications. Understanding its genetic basis is crucial in rare disease genomics and variant interpretation, as it highlights the importance of identifying mutations and their impacts on health.
Sift (sorting intolerant from tolerant): Sift, in the context of genomics, refers to a computational method used to categorize genetic variants based on their potential impact on protein function, specifically distinguishing between harmful (intolerant) and benign (tolerant) variants. This process is crucial for interpreting genetic data, especially when analyzing rare diseases, as it helps prioritize variants for further investigation and clinical decision-making.
Single Nucleotide Variants (SNVs): Single nucleotide variants (SNVs) are the most common type of genetic variation among individuals, involving a change in a single nucleotide in the DNA sequence. These variations can contribute to individual differences in traits, susceptibility to diseases, and responses to medications, playing a crucial role in rare disease genomics and variant interpretation.
Transgenic or knockout animal models: Transgenic or knockout animal models are genetically engineered organisms that have had their genomes altered to either express a foreign gene (transgenic) or to disable a specific gene (knockout). These models are essential for studying the roles of genes in biological processes and for understanding the genetic basis of rare diseases, enabling researchers to simulate human conditions and test potential treatments.
Variant of uncertain significance (VUS): A variant of uncertain significance (VUS) refers to a genetic alteration that has been identified but whose impact on an individual's health or disease risk is not clear. VUS can arise in the context of genomic testing, particularly in rare disease genomics, where the interpretation of genetic variants becomes challenging due to limited knowledge of the genes involved and their functions.
Whole exome sequencing (WES): Whole exome sequencing (WES) is a genomic technique that sequences all the protein-coding regions of genes in a genome, known as the exome. This method is particularly useful in identifying genetic variants associated with rare diseases, as it captures approximately 1% of the entire genome but accounts for about 85% of known disease-related variants, making it a powerful tool for variant interpretation in clinical settings.
Whole genome sequencing (WGS): Whole genome sequencing (WGS) is a comprehensive method for analyzing the complete DNA sequence of an organism's genome. This technique enables the identification of genetic variations, including those associated with rare diseases, by providing a full picture of an individual's genetic makeup. It has become a crucial tool in genomic medicine, especially in the understanding and interpretation of variants that contribute to rare genetic disorders.