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Driven by technological advances, an ever-increasing number of genes and mutations are implicated in neuromuscular diseases. This has led to revised classifications of neuromuscular diseases and expanding phenotypic spectra related to single genes. As a result, gene-targeted therapies are emerging. Combined with the reduction in costs of genome sequencing, genetic testing plays an increasingly important role in the diagnostic process of neuromuscular diseases. Nevertheless, caution is warranted since results of genome sequencing can be challenging regarding the interpretation of the results. Here we discuss general principles that aid the efficient use of genetic testing that may improve the interpretation of results (see Table 7.1).
As the federal government continues to expand upon and improve its data sharing policies over the past 20 years, complex challenges remain. Our interviews with U.S. academic genetic researchers (n=23) found that the burden, translation, industry limitations, and consent structure of data sharing remain major governance challenges.
This Position Statement provides guidelines for health professionals who work with individuals and families seeking predictive genetic testing and laboratory staff conducting the tests. It presents the major practical, psychosocial and ethical considerations associated with presymptomatic and predictive genetic testing in adults who have the capacity to make a decision, children and young people who lack capacity, and adults living with reduced or fluctuating cognitive capacity.
Predictive Testing Recommendations: (1) Predictive testing in adults, young people and children should only be offered with pretest genetic counseling, and the option of post-test genetic counseling. (2) An individual considering whether to have a predictive test should be supported to make an autonomous and informed decision. Regarding Children and Young People: (1) Predictive testing should only be offered to children and young people for conditions where there is likely to be a direct medical benefit to them through surveillance, use of prevention strategies, or other medical interventions in the immediate future. (2) Where symptoms are likely to develop in childhood, in the absence of direct medical benefit from this knowledge, genetic health professionals and parents/guardians should discuss whether undertaking predictive testing is the best course of action for the child and the family as a whole. (3) Where symptoms are likely to develop in adulthood, the default position should be to postpone predictive testing until the young person achieves the capacity to make an autonomous and informed decision. This is applicable regardless of whether there is some action that can be taken in adulthood.
Male factor infertility contributes to roughly 50% of the causes of infertility among couples. Advancements in the diagnostic field of reproduction allowed for the recognition of various etiologies for male factor infertility. Various pretesticular, testicular, and posttesticular etiologies have been identified and are believed to arise from genetic causes in 15–30% of cases. While a number of laboratory tests are available, the indication of genetic testing relies primarily on the findings in the history, physical examination, and semen analysis. Men with suspicion of nonobstructive azoospermia and those with idiopathic severe oligozoospermia are investigated with karyotype and Y-chromosome microdeletion assays. Analysis of the cystic fibrosis transmembrane conductance regulator (CFTR) gene is reserved for patients with obstructive azoospermia secondary to a unilateral or bilateral complete absence of the vas deference. In addition to the more commonly adopted tests, the genetic evaluation may have a role in patients with congenital hypogonadotropic hypogonadism and androgen insensitivity syndrome. Genetic testing of male infertility is a rapidly evolving field in andrology. Epigenetics, next-generation DNA sequencing, and microarray-based technologies represent some of the promising development in the area and may further expand the clinical utilization of genetic evaluation.
In the years following FDA approval of direct-to-consumer, genetic-health-risk/DTCGHR testing, millions of people in the US have sent their DNA to companies to receive personal genome health risk information without physician or other learned medical professional involvement. In Personal Genome Medicine, Michael J. Malinowski examines the ethical, legal, and social implications of this development. Drawing from the past and present of medicine in the US, Malinowski applies law, policy, public and private sector practices, and governing norms to analyze the commercial personal genome sequencing and testing sectors and to assess their impact on the future of US medicine. Written in relatable and accessible language, the book also proposes regulatory reforms for government and medical professionals that will enable technological advancements while maintaining personal and public health standards.
This Position Statement provides guidelines to assist all health professionals who receive requests for carrier testing and laboratory staff conducting the tests.
In this Statement, the term ‘carrier testing’ refers to genetic testing in an individual to determine whether they have inherited a pathogenic variant associated with an autosomal or X-linked recessive condition previously identified in a blood relative. Carrier testing recommendations: (1) Carrier testing should only be performed with the individual’s knowledge and consent; (2) An individual considering (for themselves, or on behalf of another) whether to have a carrier test should be supported to make an informed decision; (3) The mode of inheritance, the individual’s personal experience with the condition, and the healthcare setting in which the test is being performed should be considered when determining whether carrier testing should be offered by a genetic health professional. Regarding children and young people: Unless there is direct medical benefit in the immediate future, the default position should be to postpone carrier testing until the child or young person can be supported to make an informed decision. There may be some specific situations where it is appropriate to facilitate carrier testing in children and young people (see section in this article). In such cases, testing should only be offered with pre- and post-test genetic counseling in which genetic health professionals and parents/guardians should explore the rationale for testing and the interests of the child and the family.
The expansion of genetic and genomic testing in clinical practice and research, and the growing market for direct-to-consumer genomic testing has led to increased awareness about the impact of this form of testing on insurance. Genetic or genomic information can be requested by providers of mutually rated insurance products, who may then use it when setting premiums or determining eligibility for cover under a particular product. Australian insurers are subject to relevant legislation and an industry led standard that was updated in 2019 to introduce a moratorium on the use of genetic test results in life insurance underwriting for policies <AU$500K. The Human Genetics Society of Australasia has updated its position statement on genetic testing and life insurance to account for these changes and to increase the scope of the statement to include a wider range of personally-rated insurance products, such as life, critical care, and income protection products. Recommendations include that: providers of professional education involving genetics should include ethical, legal, and social aspects of insurance discrimination in their curricula; the Australian Government take a more active role in regulating use of genetic information in personal insurance; that information obtained in the course of a research project be excluded; insurers seek expert advice when making underwriting decisions regarding genetic testing; and engagement between the insurance industry, regulators, and the genetics profession be improved.
Genetic testing for breast and ovarian cancer can help target prevention programs, and possibly reduce morbidity and mortality. A positive result of BRCA1/2 is a substantial risk factor for breast and ovarian cancer, and its detection often leads to risk reduction interventions such as increased screening, prophylactic mastectomy and oophorectomy. We examined predictors of the decision to undergo cancer related genetic testing: perceived risk, family risk of breast or ovarian cancer, and numeracy as predictors of the decision to test among women at high risk of breast cancer. Stepwise regression analysis of survey responses from 459 women registered in the Cancer Genetics Network revealed greater likelihood to test for women with more family history, higher perceived risk of mutation, or Ashkenazi descent. Neither subjective nor objective numeracy was associated with the decision to test, although we replicated an earlier finding that subjective numeracy predicted willingness to pay for testing. Findings underscore the need for genetic counselling that disentangles risk perception from objective information to promote better decision-making in the context of genetic testing. Highlighting these factors is crucial for public health campaigns, as well as to clinic-based testing and direct-to-consumer testing.
A positive test result for BRCA1/2 gene mutation is a substantial risk factor for breast and ovarian cancer. However, testing is not always covered by insurance, even for high risk women. Variables affecting willingness to pay (WTP) have implications for clinic-based and direct-to-consumer testing. The relative impact of objective and subjective numeracy on WTP, in the context of worry, perceived risk (of having the mutation and developing breast cancer) and family history, was examined in 299 high-risk women, not previously tested for BRCA1/2. Objective and subjective numeracy correlated positively with one another, yet only subjective numeracy correlated (positively) with WTP. This could not be explained by educational level or worry. In line with the numeracy result, other objective factors including family history, age, and Ashkenazi descent were not correlated with WTP. Perceived risk of having a mutation was also correlated with WTP, though perceived risk of developing breast cancer was not, perhaps because it lacks direct connection with testing. Thus, subjective confidence in the ability to interpret test results and perceived risk of a positive test result are more important drivers in paying for BRCA1/2 testing than factors more objective and/or further removed from the testing itself (e.g., perceived risk of developing cancer, family history). Findings underscore the need for genetic counselling that makes probabilistic information accessible and intelligible, so as to build confidence and promote accurate perception of mutation risk and ultimately better decision-making.
We highlight non-health-related impacts associated with genetic testing (GT) and knowing one’s genetic status so that health technology assessment (HTA) analysts and HTA audiences may more appropriately consider the pros and cons of GT. Whereas health-related impacts of GT (e.g., increased healthy behaviors and avoidance of harms of unnecessary treatment) are frequently assessed in HTA, some non-health-related impacts are less often considered and are more difficult to measure. This presents a challenge for accurately assessing whether a genetic test should be funded. In health systems where HTA understandably places emphasis on measurable clinical outcomes, there is a risk of creating a GT culture that is pro-testing without sufficient recognition of the burdens of GT. There is also a risk of not funding a genetic test that provides little clinical benefit but nonetheless may be seen by some as autonomy enhancing. The recent development of expanded HTA frameworks that include ethics analyses helps to address this gap in the evidence and bring awareness to non-health-related impacts of GT. The HTA analyst should be aware of these impacts, choose appropriate frameworks for assessing genetic tests, and use methods for evaluating impacts. A new reporting tool presented here may assist in such evaluations.
There is limited data on the utility, yield, and cost efficiency of genetic testing in adults with epilepsy. We aimed to describe the yield and utility of genetic panels in our adult epilepsy clinic.
Methods:
We performed a retrospective, cross-sectional study of all patients followed by an epileptologist at a Canadian tertiary care centre’s epilepsy clinic between January 2016 and August 2021 for whom a genetic panel was ordered. A panel was generally ordered when the etiology was unknown or in the presence of a malformation of cortical development. We determined the yield of panel positivity and of confirmed genetic diagnoses. We also estimated the proportion of these diagnoses that were clinically actionable.
Results:
In total, 164 panels were ordered in 164 patients. Most had refractory epilepsy (80%), and few had comorbid intellectual disability (10%) or a positive family history of epilepsy (11%). The yield of panel positivity was 11%. Panel results were uncertain 49% of the time and negative 40% of the time. Genetic diagnoses were confirmed in 7 (4.3%) patients. These genetic conditions involved the following genes: SCARB2, DEPDC5, PCDH19, LGI1, SCN1A, MT-TL1, and CHRNA7. Of the seven genetic diagnoses, 5 (71%) were evaluated to be clinically actionable.
Conclusion:
We report a lower diagnostic yield for genetic panels in adults with epilepsy than what has so far been reported. Although the field of the genetics of epilepsy is a fast-moving one and more data is required, our findings suggest that guidelines for genetic testing in adults are warranted.
DNA ancestry companies generate revenues in the region of $1bn a year, and the company 23andMe is said to have sold 10 million DNA ancestry kits to date. Although evidently popular, the science behind how DNA ancestry tests work is mystifying and difficult for the general public to interpret and understand. In this accessible and engaging book, Sheldon Krimsky, a leading researcher, investigates the methods that different companies use for DNA ancestry testing. He also discusses what the tests are used for, from their application in criminal investigations to discovering missing relatives. With a lack of transparency from companies in sharing their data, absent validation of methods by independent scientists, and currently no agreed-upon standards of accuracy, this book also examines the ethical issues behind genetic genealogy testing, including concerns surrounding data privacy and security. It demystifies the art and science of DNA ancestry testing for the general reader.
When individuals sign on to a DNA ancestry test, they understand that the company will undertake an analysis of certain segments of their genome, called ancestry information markers (AIMs). These segments can, under proper analysis, reveal their genetic descent from certain regions of the world.
Over a period of 20 years, family genetic genealogy, through the purchase of consumer ancestry testing kits, has been one of the fastest growing family activities of this generation. Citing data from the International Society of Genetic Genealogy, the Washington Post reported in 2017 that eight million people worldwide were involved with recreational genomics. It is estimated that by 2019 about 25 million people had signed up for a DNA ancestry test offered by one of the dozens of companies that have entered this marketplace. The kits are sent to a person’s home with return packaging that includes a reservoir for depositing saliva or swabs for sampling cheek cells. The MITTechnology Review predicted that by 2021 there would be 100 million consumers of ancestry DNA services.
Most human genetic diversity is found within populations rather than between populations. Scientists have reported that any two individuals within a particular population are as different genetically as any two people selected from any two populations in the world. Given this finding, how can science use a small percentage of genetic diversity between populations as markers of ancestral origins?
Much of recreational DNA ancestry offers consumers a long reach into the history of their descent by discovering which biogeographical population most closely matches their DNA profiles. The science and DNA analytics provide probability estimates that their DNA markers (ancestry informative markers, or AIMs) are most likely from a particular continent or even a specific country. But DNA ancestry tests have applications that go well beyond recreational genealogy. Even prior to the growth of this sector of direct-to-consumer testing, DNA was used to determine paternity and to establish identity in criminal investigations. An important and largely unintended application of ancestry DNA testing has been the uncovering of family secrets: “Why does my father look so different from his parents?” or “Why are my mother’s skin tones so much darker than those of her parents?”
As we noted previously, the science behind DNA ancestry requires that one compares the unique genetic markers on the consumer’s DNA sample with the frequency of those markers in reference panels representing different regions of the world. When the field of DNA ancestry began, it was a scientific project that involved the search for biogeographical DNA. Scientists could use changes in the human genome to determine how ancient populations moved around the globe. The further populations moved across the globe and the more time elapsed (many thousands of years), the greater the number of mutations or genetic variants. Genetic ancestry began with a half-dozen distinct continental regions and with markers called hypervariable microsatellites, or short tandem repeats (STRs) of DNA, 2–6 base pairs in length. These microsatellites were considered ideal at the time because they had a high heterozygosity, which means two different alleles at a site. A site that has an AA is homozygous, whereas one that has AG is heterozygous. The more diverse the alleles, the greater the chance of distinguishing allele frequencies among populations. Initially, scientists used changes in the maternally inherited mitochondrial DNA (mtDNA) and the paternally inherited Y chromosome. That changed when autosomal markers were chosen for ancestry analysis.
In order to locate people’s ancestry to a region of the world through their DNA, the markers on their DNA sample have to be compared to population reference panels for the regions that form part of the comparison group. These ancestry inference methods have served medical research, forensic science, and commercial popular genealogical interests. According to Santo et al., the reliability of any ancestry inference depends on the existence of reliable population reference databases. Many researchers and ancestry DNA companies utilize different sources for population data on different countries. For example, ALFRED is an allele frequency database supported by the Yale Center for Medical Informatics, which has genomic data from population samples across the globe. You can enter the name of a country or population group, such as Siberian Yupik (the sample was collected from unrelated Siberian Yupiks from northeastern Siberia, Russia) and it will provide information on the number of people (29) and/or chromosomes sampled (58).
The criminal justice system began using DNA to solve crimes in the 1980s, after a geneticist from the University of Leicester in the UK developed a method for sequencing certain segments of chromosomal DNA. Those segments, called short tandem repeats (STRs), were expressed differently in different people, in contrast to the 99.9 percent of our DNA that is the same, and thus could be used to establish an indicator of personal identity (see Chapter 1).