The time to stop recreational testing has come

 Direct-to-Consumer Genetic Testing: Value and Risk

Piecing together information from a variety of sources, one reporter concluded that by early 2019, more than 26 million people worldwide had been tested by the four leading companies, 23andMe, Ancestry, Gene By Gene, and MyHeritage (1). That volume was fueled by aggressive marketing, including discounts in the lead-up to major holidays to promote gifting of test kits. As of May 2020, the  undiscounted price of the basic test offered by the leading companies was $59–$99.

This is an example of what should not had happened. Recreative genomics doesn't add value and increases uncertainty and anxiety. 

Although many consumers of DTCgenetic testing express an intention to modify their lifestyle to address risk factors, studies typically show no changes at follow-up (15, 30). In the PGen Study, 59% of participants said that test results would influence their management of their health (31). However, an analysis of the 762 participants who had complete cancer-related data found that those who received elevated risk estimates were not significantly more likely to change lifestyle or engage in cancer screening than those who received average or below-average risk estimates (44). It may be relevant that no participants tested positive for pathogenic variants in highly penetrant cancer susceptibility genes. As for population health, the Centers for Disease Control and Prevention identify three conditions—hereditary breast and ovarian cancer syndrome,Lynch syndrome, and familial hypercholesterolemia—that are poorly ascertained despite the potential for early detection and intervention to significantly reduce morbidity and mortality (45). The hope is that DTC genetic testing could improve the situation (15). However,DTC genetic testing as currently carried out is likely to fill gaps in haphazard fashion, given the characteristics of purchasers, the scope of available products, and integration issues.

One message. Right now and until we don't know the implications of recreational genetic testing, direct to consumers testing should stop.

Banksy

 

The long and bumpy road to CRISPR (2)

 Editing Humanity. The CRISPR Revolution and the New Era of Genome Editing

In 2017 I wrote a post about the book by Jennifer Doudna, A Crack in Creation, now Kevin Davies, the editor of the CRISPR journal has published a new book on CRISPR. It is an effort to put all the information and details about CRISPR in one book. Therefore, if you want to now the whole story (or close to) this is the book to read. If you are interested in a general approach, then the Doudna book is better.

It is quite relevant the chapter that explains the role of Francis Mojica in CRISPR (chapter 3), and the chapter 18, on crossing the germline and what happened about the scandal of genome editing by JK.

“When science moves faster than moral understanding,” Harvard philosopher Michael Sandel wrote in 2004, “men and women struggle to articulate their own unease.” The genomic revolution has induced “a kind of moral vertigo.”49 That unease has been triggered numerous times before and after the genetic engineering revolution—the structure of the double helix, the solution of the genetic code, the recombinant DNA revolution, prenatal genetic diagnosis, embryonic stem cells, and the cloning of Dolly. “Test tube baby” was an epithet in many circles but five million IVF babies are an effective riposte to critics of assisted reproductive technology.

With CRISPR, history is repeating itself,

That's it, great book.

 

Cost-effectiveness of genome sequencing (3)

Application of next-generation sequencing to improve cancer management: A review of the clinical effectiveness and cost-effectiveness

Once again, there is no need for cost-effectiveness if there is not a clear message on the analytical validity, clinical validity and utility of a diagnostic test.
A new article want to shed light on cancer and NGS, and says:

Our search for cost‐effectiveness studies on NGS in cancer care yielded 2037 articles. Only 6 articles included cost‐effectiveness studies of the application of NGS (targeted gene panel) in cancer

The 6 selected reports could be separated into 2 types. Three of the articles assessed the cost‐effectiveness of recommending patients receiving targeted therapy matching their genetic mutation identified via NGS; and the remaining 3 articles assessed the cost‐effectiveness of using NGS as part of the screening program to direct patients or high risk family members into prophylactic treatment

Two out of 3 articles in the “targeted therapy” group reported that NGS and targeted therapy was not cost-effective (Table 3A), using an ICER threshold of US$100 000 per Quality Adjusted Life
Year (QALY) gained. An ICER of less than US$100 000/QALYs gained is generally considered favourable for funding in the United States

Two out of the 3 articles in the “screening” group reported that the use of NGS was cost‐effective (Table 3B), that is, under US$100 000 per QALY gained.loser surveillance.

 In our evaluation of the effectiveness of NGS, we found that NGS is effective at identifying mutations in cancer patients, and we reported that 37% of the diagnosed patients proceeded to receive therapy matching their genetic profile. However, with only 6 articles available that assess the cost-effectiveness of NGS in various settings, it remains an area for future research to determine whether the technology is cost-effective in routine cancer management

Summary: the message is that there is no message with such a few observations!


Something is being missed...

Guillem Roma and Marta Roma

Integrating genome and epigenome studies

The Key Role of Epigenetics in Human Disease Prevention and Mitigation

I've said it many times: beware of snake-oil sellers. Nowadays you may find it everywhere, specially on internet. You may get a genetic test for a disease that creates a false illusion of safety, or another that provides an unnecessary and avoidable concern. Only evidence based prescribed tests can be considered appropriate.
Therefore, if you want to confirm that genome is not enough, you have to check the review at NEJM on epigenetics. At the end of the article you'll find the explanation on why we do need integrated genome and epigenome association studies. You'll understand that cancer is fundamentally an epigenetic disease.
The current knowledge is changing quickly some conventional truths and "known unknowns" that we've had for years. This is good news for citizens, and bad news for snake-oil sellers if detected. Governments should help citizens on this screening effort, and protect citizens from fake medical information.

Challenges in Cost-Effectiveness Analysis of genomic tests

From: Cost-effectiveness analyses of genetic and genomic diagnostic tests (Must read)

Type of challenge	Example of challenge	Description of challenge
Methodological	Selecting the appropriate evaluative framework	Is the standard extra-welfarist view and use of CEA appropriate, or should the distinct theoretical approach reflecting the welfarist view and use of CBA be adopted to allow consequences other than health gain, such as the value of diagnostic information from the genomic-targeted diagnostic test, to be valued?
	Relevant study perspective	Is the standard recommendation to focus on the use of health-care services appropriate when the genomic-targeted diagnostic test may provide information that affects the use of other services, such as education or employment?
	Relevant time horizon	Is a lifetime sufficient when the impact of a genomic-targeted diagnostic test may extend to infinite time horizons that are not limited by the lifespan of one individual?
	Defining the relevant study population	Is the standard definition of a patient (the person receiving the technology) appropriate when there could be spillover effects to family members (currently alive or to be born) as a result of information from a genomic-targeted diagnostic test?
	Valuing consequences	Is identifying and measuring the impact on health status alone sufficient to capture the (good and bad) consequences of a genomic-targeted diagnostic test?
Technical	Variation in the individual characteristics of the relevant study population	The use of cohort state transition Markov models, sometimes combined with decision trees, cannot easily capture the impact of individual patient variation within a population with different genotypes and phenotypes
	Number of diagnostic and, if appropriate, subsequent treatment pathways	The use of cohort state transition Markov models, sometimes combined with decision trees, cannot easily account for multiple comparators often needed when evaluating a new genomic-targeted diagnostic test
	Capturing impact of reduced time to diagnosis	The use of cohort state transition Markov models, sometimes combined with decision trees, cannot account for the impact of reduced time to achieve a diagnosis, which is often a proposed benefit of a genomic-targeted diagnostic test
	Capturing impact of capacity constraints	Decision analytic model-based CEA currently assumes limitless capacity within health-care systems, which is often not a reasonable assumption when introducing a genomic-targeted diagnostic test to populations for whom a diagnosis was not previously available
Practical	Availability of data	There is often a lack of data available to populate decision analytic model-based CEA
	National tariff of test cost	No national tariff for genomic-targeted tests exist
Organizational	Complex health-care systems	Decision analytic model-based CEA assumes that money saved and benefits accrued are transferable, but this is often challenging in complex health-care systems that comprise an overarching funding mechanism (public, private, insurance), a service and staffing model for providing care for different sectors (community, general practice, hospital, specialist) and a means of allocating funding to these different sectors
	Generalizability of results	Decision analytic model-based CEA is relevant only to the defined decision problem, and decision-makers who want to use the results must decide whether the focus of the analysis is relevant to their own jurisdiction
	Expensive nature of health technology assessment	Decision analytic model-based CEA conducted within national health technology assessment processes requires considerable funding and expertise that are not available to all, which may contribute to the inequity in access to new genomic-targeted diagnostic tests across the world

1. CBA, cost-benefits analysis; CEA, cost-effectiveness analysis.