The case study paper is an invited contribution for the Journal of Genetic Counseling in a special issue on Direct-To-Consumer (DTC) genetic testing. This paper describes the journey I went through with my family when we all embarked into analysing our personal genomes via a DTC genetic testing company. I believe my experiences could be related to many other people in the world as they gain access to this technology. In the commentary Dr Middleton discusses the implications of the difficulties I went through when communicating my relatives their genomic information.

Sharing and comparing one’s genome with other personal genomes is a matter of necessity if one is to shed light on the meaning of one’s personal DNA.

This is why I became a genome blogger myself. Why one should be constrained by the information that genomic test reports provide? No personal genome analysis report can ever be complete, they will always be influenced by the biases of whomever is providing such a report.

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Although no formal document seems to have been produced on what the core values for genome blogging should be yet, core beliefs driving personal genome-sharing should be made explicit. Here I present an initial and inherently imperfect first attempt to put in writing of what I believe genome blogger values could be. I do not expect every fellow blogger to agree with them, but I hope that at least they inspire some debate. These are not a fixed set of rules; on the contrary, I expect this thinking to evolve with the genomics technology itself. I base some of the ideas below on Marcus Wohlsen’s ‘Biopunk’ book, Meredith Patterson’s ‘biopunk manifesto’, Misha Angrist’s ‘Here is a human being’ book and Pekka Himanen’s ‘Hacker’s ethics’ book.

Core Values for Genome Blogging

1. Intelligent exploration, experimentation and trial to push the boundaries of knowledge are a right for ordinary people. The days in which genetic science was only done by university professors or people working in corporate labs are now over. Now everyone should have the power and legitimacy to be able to discover, develop and find new things about their own genome data.
2. Sharing with the world is more useful than keeping the data to oneself. Whether one wants to share genome data or keep it private it should be a matter personal choice. I have my own right to do what I want with my genome, learn from it, share it with the world or keep it private. Sharing personal experiences about personal genomics findings is a way of creative self-expression and a channel for curiosity to find its way to better self-awareness. Freedom to be open about one’s genome information and the ability to have accessibility to one’s own information is of paramount importance to every human being.
3. Whatever attitude a person has towards personal genome privacy, it should be utterly respected. Knowledge of genetics is not as important for informed consent as the personal/psychological attitude of the person. The decision of openness of personal genome data completely resides in the individual and although openness is the better default option, privacy must be utterly respected and not judged.
4. Personal genome data access should be affordable to all irrespective of nationality, gender, social background or any other circumstance. Whole genome sequencing and tools for its interpretation should become accessible to everyone, not just the realm of those who can pay for it. Genome interpretation tools should be accessible and free for all. Not having access to a personal genetic test is in itself a new kind of discrimination.
5. Stating that genetic tests merely provide non-clinical information misses the point of what personal genomics is all about. Genetic risks tests do tell something about one’s health, one’s ability to respond to certain drugs and one’s ethnic ancestry. Trying to downplay the importance of these predictions because we do not have enough statistical discrimination power does not take away the effect such predictions may cause in the recipient regardless of whether they right or wrong.
6. Genes affect one’s present but they do not determine one’s future. One’s genetic data is just one more factor among many others in predispositions, risks and behavioural reactions. Genes are affected by the environment as much as the environment is affected by my genes. Although some dramatic genetic diseases can significantly alter one’s life style, genes can never determine the decisions that make us the way we are.
7. Education in risks and opportunities for personal genetic testing should be the primary aim of policy makers. Restricting access to interested people makes no sense and it is virtually impossible to ensure. The power of Internet allows anyone to order a test with no need to physically be in any particular location.  
8. Corporate interest can never compromise any human right. Laws must fully protect individual human rights of equality for every person, irrespective of whatever risks are predicted from genetic data.
9. Privacy does not have to be incompatible with openness. Knowing one’s bank account movements are probably a better reflection of oneself than a personal genome.

Conclusion

Genome blogging is about sharing the thrill of discovering uncharted territory. Sharing one’s experiences on the Internet may help start answering personal questions without having to wait for others to find out. The challenge of personal genomics does not lie in the sequencing itself but in the interpretation of results. The wide access to the technology to the public is driving some policy makers to exert a “protective” approach to keep users away from unpredictable or undesirable “potential” consequences. However, legal and health systems seem hardly suited to keep up with advancements. It is pointless to restrict access to genetic testing: education in risks and opportunities seem a more reasonable approach. Despite the ease with which it is now possible to access one’s genome data, the personal genomics field is still inaccessible to most people.

In other words, in the US it’s still possible to be discriminated against for genetic reasons. How is this situation likely to change in the near future?

When I look more closely at it in the NIH factsheet for GINA it is stated that

As genomic medicine is poised to revolutionize medicine, patients will be able to utilize advances in genetic testing to create highly personalized care and treatment plans without fear of discrimination.

I have two main objections with that:

1. The current level of protection is not near enough to dissipate the fears for people to ‘utilize advances in genetic testing’. The law itself states that GINA sets a ‘minimum standard’ but still does not cover some crucial scenarios where being discriminated against may be devastating (e.g. life insurance).
2. If Direct-to-consumer (DTC) genetic testing is only going to be available via medical prescription, as many in the FDA are seeking to implement, does this approach help in any way the advancement of personalized health care? According to Misha Angrist [1], the top requestor for genetic tests in 2006 in the US was a Spa company; i.e. rich people with disposable income who wanted to understand their health risks. The impression I gather is that private demand is the main driver for DTC genetic testing and not the institutionalized health care. If the worst fears of DTC providers become a reality it may well be the end of an open, accessible, democratized personal genomics field as we now it. This does not take away the grave obligation DTC providers and relevant governmental agencies have to educate the public to ensure that they understand their results and that rigorous standards are met in reported findings.

Genetic Information Nondiscrimination Act Factsheet

It also strikes me that, in GINA, concepts like ‘privacy’ and the ‘right not to know’ are not even mentioned. My family and I chose to share our genotypes with the world, which should be as respectable as not sharing this data in the strictest sense. Both being open or protective of one’s genetic data should be an informed personal choice and not something imposed. I thus think this should be an important aspect that remains to be addressed at the juridical level.

In the NIH GINA factsheet it also reads that

Insurers cannot use genetic information obtained intentionally or unintentionally in decisions about enrollment or coverage.

To my mind this means that there is no restriction in collecting genetic information even though it cannot be used. I’ve heard say that some insurers may be collecting genetic data in anticipation of changes in laws that would allow them future use of the data.

Ignorance is the worst possible kind of discrimination

The need to educate the public and help them make an informed decision on genetic testing should remain the single most important priority by governments and regulatory agencies alike. Trying to impose on the public tight regulations on access to DTC genetic testing may create the wrong public opinion and backfire in the same way as GM food and crops did in Europe. Now is the time, when opinions are still to be formed, to make people aware of what DTC can or can’t tell them about themselves. The worst form of discrimination I know is ignorance and only ignorance can lead to the wrong interpretation of test results. Perhaps the solution does not lie so much in restricting access to DTC genetics testing as it is in helping consumers choose the right option for themselves.

[1] Here Is a Human Being: At the Dawn of Personal Genomics (2010) HaperCollins Books.

Some numbers presented by Richard gave context to the startling prediction that by 2015 millions of individual genomes will be sequenced. This is in fact the expected number if the current pattern of growth continues. Ten years have now been celebrated after the draft for the first Human Genome was released in 2001. By 2006, with next generation sequencing in full swing and sequencing centers churning out many gigabases per week, tens of genomes had been sequenced. Today the number of individual genomes is in the order of thousands, meaning that every year a 4 fold growth is predicted. Extrapolating this estimation to five years from now makes thus the number of genomes sequenced 1024 times (4⁵) our current number, hence millions of genomes.

Having such an incredible amount of data will clearly create challenges which we are just beginning to find. How are we going to hold all this data when processing capacity in computers “only” grows 2 fold every year? The answer is that as more genomes become available, an individual’s data will not be stored in its totality but only the differences that define his/her particular variations.

Although many genomes may have been sequenced by now, accessing them is not a trivial matter. Stored in many different places, with different restrictions and inconsistent levels of detail, the bulk of this data is likely to remain at least mildly challenging to handle.  Results of investigations will certainly be accessible, but think of the effort it could cost to access every single database containing public individual genome data. I do not believe that a great number of genomes will be optimally researched unless more straightforward and standardized access protocols are put in place, something that currently is lacking. Times for excitement are reasonably justified, yet base pair to bedside medicine may be delayed if current data sharing procedures are not streamlined.

With the results in hand, you identify a candidate mutation most likely to have caused the observed symptoms. You look then at the parents’ genotype to see whether the mutation is inherited and find that the father is not the real biological one, i.e. you are faced with an incidental finding of non-paternity. This is one example of pieces of information contained in the genetic material, not related to the diagnosis, but necessary to carry out the analysis. Incidental findings like these have the potential of dramatically affecting the lives of patients and their families.

How should we deal with incidental findings capable of dramatically affecting families? The answer is not simple. For instance, when non-paternity is identified, the case could be dismissed as non-analyzable to avoid the complex ethical ramifications of such a revelation on the family.

Let’s consider another incidental finding, such as detecting that one of the parents is a carrier of the disease that is causing the mutation in the patient. Such a finding may imply that future children from the couple may also inherit the mutation. Should parents be informed or should they be allowed to choose whether they find out or not?

There are many other incidental findings where strong arguments can be made either for or against informing the family. One example is the discovery of a malignant variant for the APOE gene in the patient, implicated in early onset Alzheimer’s. This is something for which the patient was not tested, but still it has the potential of having a life changing effect on the patients or their parents. Another example is the finding of a malignant mutation for BRCA2, which increases by 70% the chances of developing breast cancer in female carriers. There are many other incidental findings such as these where practitioners are undecided on how to manage that information sensibly.

What it is clear though is that incidental findings will have to be dealt with on an individual basis. Informing the family will depend on the possible effects of the information found as well as personal circumstances. Here I have just limited my exposition to a few common examples of current challenges, but as technology progresses and more patients and families are sequenced, many new conundrums are likely to appear, requiring new ethical debate.

Recently, this topic has been addressed by Loukides et al., in a PNAS paper were they present a method for automatically extracting linkable clinical features, which are then modified in a way that they can no longer be used to link to a small number of patients.

Modifications to clinical features are carried out preserving the associations between genomic sequences and specific sets of clinical features relevant to GWAS-related diseases. The user specifies the sets of diagnosis codes that are linkable to specific disorders and the algorithm modifies the linkable codes so that they cannot be attributed to a small number of individuals. Such code modification is carried out making sure that clinical association validation is retained, where sets of clinical features are replaced with semantically related codes to satisfy the distribution of GWAS-related diseases.

Thus, an attacker who knows a set of clinical features diagnosed for a single visit, would not be able to uniquely identify an individual because each record links to no fewer than say, 5 individuals (k=5).

Some limitations to this approach are also discussed. Data linkage may be performed if additional sources of data are possessed about the individual. Allowing data owners to make the decision of the appropriate level of protection (setting k) may hamper the reproducibility of findings if the attacker’s knowledge is overestimated, as well as compromise the individual’s privacy if underestimated. Their method also does not guarantee that the information loss for the chosen level of protection is minimized.

A resource available for social networking to allow mass comparison of people sharing traits and genomic variants, I believe could have revolutionary effects. Such a network could allow one start making sense of specific personal traits, susceptibility to illnesses and determination of potential treatments proven successful by genetically similar people. Exchange of genetic information made easy should be a reality soon.

The time is ripe for social genome networks. Indeed there are lots of potential ethical and legal challenges ahead. How long are laws and social prejudices going to stop the inevitable?

And the future is now become a present reality. The rise of next generation sequencing technology, together with the adoption of microarray techniques in normal clinical practice is revolutionizing the way patient’s data is handled. Similarly, the amount of data created is surpassing most software tools available. Projects like the 1000 Genomes are generating an enormous pool of variability of genome data and derived sources of information. This makes necessary the exchange of data between research centers to be able to establish what constitutes normal and pathogenic variation in human beings.

Personalized medicine, a widely used term since the near completion of the Human Genome Project, implies the application and use of personal genome data for the determining genomic changes leading to disease, risk factors and patient’s susceptibilities. The problem with this sort of data is that it may yield information that could severely change the life style of the person, affect relatives and, in many cases, with little ability to do anything to mitigate the effects of findings. As our current knowledge is so fragmented and rudimentary, it is expected that collected information with no current value may be relevant in the future, influencing analyses and results.

Some ethical practices currently implemented in Computational Bioethics include the creation of consent forms that allow putting anonymized patient information in genome databases. This information may be accessed by the scientific community and compared with other previously consented patient data for the characterization of new syndromes, the effect of knockout genes in the general population and the understanding of genome variation in normal individuals.