Genomic Technologies
Introduction
The risks associated with different genomic technologies are closely related to the risk of detecting rare disease-causing variants. Such variants can predict future risk of developing disease and thus care must be taken when returning this information, as there may be significant health implications for the participant and their relatives.
Common variants may be associated with a risk for developing common diseases e.g., heart disease. However, each individual variant has a low predictive value and therefore the relevance to future health and family members is low.
This section first covers microarray technology which will detect common variants associated with disease and two of the common applications of microarrays (genome wide association studies and polygenic scores). It then addresses sequencing technologies which look at the code of a specific gene (Sanger sequencing), a group of genes (panel testing), the coding region of all genes (whole exome sequencing) or the entire genome (whole genome sequencing). Finally, we touch on RNA sequencing which is used to evaluate the expression of genes in specific tissues or cells.
Microarrays
Microarrays use custom baits to capture common variants (usually present in >5% of the population) at specific locations throughout the genome (often >500,000). As microarrays are used to detect specific variants, it is referred to as a genotyping technology.
Most commonly, microarrays are used in GWAS studies or to create polygenic risk scores (see below). Clinically, a microarray can be used to identify genomic regions which are deleted or duplicated in a person, typically a child with multiple congenital anomalies.
Risk assessment:
The risk of re-identifying a person based on microarray information is very low. In a research context, a microarray is unlikely to identify a variant which causes a disease. Therefore, the risk of psychological distress and/or genetic discrimination is very low.
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A GWAS uses microarrays to compare the frequency of common variants between large groups of individuals who do, and do not, have a specific disease. The strength of each variant’s association with disease is denoted by odds ratios.
Risk assessment:
The risk of re-identifying a person based on GWAS information is very low. There is no risk of discovering a high-risk variant for a rare disease and thus there are no implications for family members. Similarly, the risk of genetic discrimination is very low.
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Polygenic scores (PGS) are calculated by combining all the odds ratios from GWAS significant variants to create a cumulative score. Each person will have different PGS’s for different diseases.
Occasionally, PGS is used to refine risk in individuals who are known to carry a rare variant associated with familial disease e.g., BRCA1/2 in hereditary breast and ovarian cancer.
Risk assessment:
The risk of identifying a person based on their PGS alone is very low. As PGS is the combination of multiple variants, the risk for each family member differs. It is theoretically possible that life insurance companies could utilise PGS for common conditions (e.g., diabetes, heart disease) when negotiating policies.
Sequencing
Sequencing looks at all the letters in the genetic code for a given gene or groups of genes. It is usually utilised to test genes associated with disease and is therefore capable of detecting rare variants associated with high risk.
Sequencing used to be done on a sequential basis by looking at the code of one gene at a time (Sanger sequencing) but the evolution of technology now allows for the interrogation of multiple genes at the same time, which is known as massive parallel sequencing. Examples of massive parallel sequencing include panel testing, exome sequencing and whole genome sequencing.
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Evaluates the code of a gene, or specific exons within a gene.
Risk assessment:
Sanger sequencing is not as commonly used today but was used when a person was suspected to have a genetic condition and clinicians were trying to confirm the diagnosis, identify the underlying gene and/or predict the risk of future disease. If positive, the results could have health and psychological implications for the individual and family members. If Sanger sequencing was performed to confirm a clinical diagnosis, then there would not be any risk of genetic discrimination for the affected individual, but there could be a risk for unaffected, at-risk family members. Conversely, if a healthy person was undergoing predictive testing, the results could affect their ability to obtain life insurance thereafter. There is no risk of incidental, unexpected or incidental findings.
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Sequences multiple genes associated with a particular disease or group of diseases.
Risk assessment:
Panel sequencing involves testing multiple genes associated with a particular disease or group of diseases. If positive, the results could have health and psychological implications for the individual and family members. If panel sequencing was performed to confirm a clinical diagnosis, then there would not be any risk of genetic discrimination for the affected individual, but there could be a risk for unaffected, at-risk family members. As per above, if a healthy person was undergoing predictive testing, the results could affect their ability to obtain life insurance thereafter. There is no risk of incidental or secondary findings, but it is possible that the implicated gene could be associated with other disease risks, which could be unexpected.
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Sequencing the coding regions (exome) or coding and non-coding regions (genome) of all genes.
Risk assessment:
Data is typically analysed using a candidate gene list first (i.e., a virtual panel), but if negative, the data could be reinterrogated to allow for gene discovery. It is very important that the researcher is clear about their analytical approach and how they will mitigate the risk of incidental findings. Researchers may also state whether they are excluding certain genes (e.g., those associated with incurable neurodegenerative disorders). Potential results include primary, incidental, and secondary findings.
If primary findings confirm a clinical diagnosis, then this is unlikely to cause undue stress for the individual or be associated with any risk of insurance discrimination. It will, however, confirm the mode of inheritance, which may have risks for other family members.
If an incidental finding is identified, then consultation with a genetics practitioner and/or ethics consult may be needed
Secondary analysis of data for genes which are potentially actionable will have to be included in the PICF with appropriate genetic counselling.
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Although each of our cells contain the genetic code for every gene, only a subset is expressed in each cell. Some of these are “housekeeping genes” which are essential to cell function, and some are specific to the cell type and stage of development. All the genes which are active in a cell will make RNA. Therefore, by sequencing the RNA you can determine which genes are expressed and, if there is a pathogenic variant one of those genes, what impact that may have on the protein.
Risk assessment:
RNA sequencing is often performed in cancer cells, and it may detect a variant which adversely affects the function of the protein. The researcher will not know whether that variant is germline or somatic without sequencing a control sample from the same participant. Otherwise, RNA sequencing poses very little risk for revealing results of significance to the participant and their family members.
Did you know? the Transcriptome is all the RNA in a cell, including coding and non-coding RNA.
Summarizing the ELSI Risk of Genomic Technologies
Given the above information, the following image is a summary of the ELSI considerations and level of risk associated with each type of genomic technology/analysis methodology.
