“Wow such genetics. So data. Very forever?” – An overview of the blockchain genomics trend

In 2014, Harvard professor and geneticist George Church said: “‘Preserving your genetic material indefinitely’ is an interesting claim. The record for storage of non-living DNA is now 700,000 years (as DNA bits, not electronic bits). So, ironically, the best way to preserve your electronic bitcoins/blockchains might be to convert them into DNA”. In early February 2018, Nebula Genomics, a blockchain-enabled genomic data sharing and analysis platform, co-founded by George Church, was launched. And they are not alone on the market. The common factor between all of them is that they want to give the power back to the user. By leveraging the fact that most companies that currently offer direct-to-consumer genetic testing sell data collected from their customers to pharmaceutical and biotech companies for research purposes, they want to be the next Uber or Airbnb, with some even claiming to create the Alibaba for life data using the next-generation artificial intelligence and blockchain technologies.

Nebula Genomics

Its launch is motivated by the need of increasing genomic data sharing for research purposes, as well as reducing the costs of sequencing on the client side. The Nebula model aims to eliminate personal genomics companies as the middle-man between the customer and the pharmaceutical companies. This way, data owners can acquire their personal genomic data from Nebula sequencing facilities or other sources, join the Nebula network and connect directly with the buyers.
Their main claims from their whitepaper can be summarized as follows:

  • Lower the sequencing costs for customers by joining the network to profiting from directly by connecting with data buyers if they had their genomes sequenced already, or by participating in paid surveys, which can incentivize data buyers to subsidize their sequencing costs
  • Enhanced data protection: shared data is encrypted and securely analyzed using Intel Software Guard Extensions (SGX) and partially homomorphic encryption (such as the Paillier scheme)
  • Efficient data acquisition, enabling data buyers to efficiently acquire large genomic datasets
  • Being big data ready, by allowing data owners to privately store their data, and introducing space efficient data encoding formats that enable rapid transfers of genomic data summaries over the network

Zenome

This project aims to ensure that genomic data from as many people as possible will be openly available to stimulate new research and development in the genomics industry. The founders of the project believe that if we do not provide open access to genomic data and information exchange, we are at risk of ending up with thousands of isolated, privately stored collections of genomic data (from pharmaceutical companies, genomic corporations, and scientific centers), but each of these separate databases will not contain sufficient data to enable breakthrough discoveries. Their claims are not as ambitious as Nebula, focusing more on the customer profiting from selling their own DNA data rather than other sequencing companies. Their whitepaper even highlights that no valid solutions currently exist for the public use of genomic information while maintain individual privacy and that encryption is used when necessary. When buying ZNA tokens (the cryptocurrency associated with Zenome), one has to follow a Know-Your-Customer procedure and upload their ID/Passport.

Gene Blockchain

The Gene blockchain business model states it will use blockchain smart contracts to:

  • Create an immutable ledger for all industry related data via GeneChain
  • Offer payment for industry related services and supplies through GeneBTC
  • Establish advanced labs for human genome data analysis via GeneLab
  • Organize and unite global platform for health, entertainment, social network and etc. through GeneNetwork

Continue reading “Wow such genetics. So data. Very forever?” – An overview of the blockchain genomics trend

A Critical Analysis of Genome Privacy Research

The relationship between genomics and privacy-enhancing technologies (PETs) has been an intense one for the better part of the last decade. Ever since Wang et al.’s paper, “Learning your identity and disease from research papers: Information leaks in genome wide association study”, received the PET Award in 2011, more and more research papers have appeared in leading conferences and journals. In fact, a new research community has steadily grown over the past few years, also thanks to several events, such as Dagstuhl Seminars, the iDash competition series, or the annual GenoPri workshop. As of December 2017, the community website genomeprivacy.org lists more than 200 scientific publications, and dozens of research groups and companies working on this topic.

dagstuhl
Participants of the 2015 Dagstuhl Seminar on Genome Privacy

Progress vs Privacy

The rise of genome privacy research does not come as a surprise to many. On the one hand, genomics has made tremendous progress over the past few years. Sequencing costs have dropped from millions of dollars to less than a thousand, which means that it will soon be possible to easily digitize the full genetic makeup of an individual and run complex genetic tests via computer algorithms. Also, researchers have been able to link more and more genetic features to predisposition of diseases (e.g., Alzheimer’s or diabetes), or to cure patients with rare genetic disorders. Overall, this progress is bringing us closer to a new era of “Precision Medicine”, where diagnosis and treatment can be tailored to individuals based on their genome and thus become cheaper and more effective. Ambitious initiatives, including in UK and in US, are already taking place with the goal of sequencing the genomes of millions of individuals in order to create bio-repositories and make them available for research purposes. At the same time, a private sector for direct-to-consumer genetic testing services is booming, with companies like 23andMe and AncestryDNA already having millions of customers.

23andme
Example of 23andme “Health Overview” test results. (Image from: https://www.singularityweblog.com/)

On the other hand, however, the very same progress also prompts serious ethical and privacy concerns. Genomic data contains highly sensitive information, such as predisposition to mental and physical diseases, as well as ethnic heritage. And it does not only contain information about the individual, but also about their relatives. Since many biological features are hereditary, access to genomic data of an individual essentially means access to that of close relatives as well. Moreover, genomic data is hard to anonymize: for instance, well-known results have demonstrated the feasibility of identifying people (down to their last name) who have participated in genetic research studies just by cross-referencing their genomic information with publicly available data.

Overall, there are a couple of privacy issues that are specific to genomic data, for instance its almost perpetual sensitivity. If someone gets ahold of your genome 30 years from now, that might be still as sensitive as today, e.g., for your children. Even if there may be no immediate risks from genomic data disclosure, things might change. New correlations between genetic features and phenotypical traits might be discovered, with potential effects on perceived suitability to certain jobs or on health insurance premiums. Or, in a nightmare scenario, racist and discriminatory ideologies might become more prominent and target certain groups of people based on their genetic ancestry.

Alt-right trolls are arguing over genetic tests they think “prove” their whiteness. (Image taken from Vice News)

Making Sense of PETs for Genome Privacy

Motivated by the need to reconcile privacy protection with progress in genomics, the research community has begun to experiment with the use of PETs for securely testing and studying the human genome. In our recent paper, Systematizing Genomic Privacy Research – A Critical Analysis, we take a step back. We set to evaluate research results using PETs in the context of genomics, introducing and executing a methodology to systematize work in the field, ultimately aiming to elicit the challenges and the obstacles that might hinder their real-life deployment.

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Caveat emptor: Privacy could turn UK’s genomic dream into a nightmare

Raise your hand if, over the past couple of years, you have not heard of whole genome sequencing (usually abbreviated as WGS), or at least read a sensational headline or two about how fast its costs are dropping. In a nutshell, WGS is used to determine an organism’s complete DNA sequence. But it is actually not the only way to analyze our DNA — in fact, genetic testing has been used in clinical settings for decades, e.g., to diagnose patients with known genetic conditions. Seven-time Wimbledon champion Pete Sampras is a beta-thalassemia carrier – a condition that affects the formation of beta-globin chains, ultimately leading to red blood cells not being formed correctly. Testing for thalassemia, usually triggered by family history or a blood test showing low mean corpuscular volume, is done with a number of simple in-vitro techniques.

The availability of affordable whole genome sequencing not only prompts new hopes toward the discovery and diagnosis of rare/unknown genetic conditions, but also enables researchers to better understand the relationship between the genome and predisposition to diseases, response to treatment, etc. Overall, progress makes it increasingly feasible to envision a not-so-distant future where individuals will undergo sequencing once, making their digitized genome easily available for doctors, clinicians, and third-parties. This would also allow us to use computational algorithms to analyze the genome as a whole, as opposed to expensive, slower, targeted in-vitro tests.

Along these lines is last week’s announcement by Prof. Dame Sally Davies, UK’s Chief Medical Officer, calling the NHS to deliver her “genomic dream” within five years, with whole genome sequencing becoming “as standard as blood tests and biopsies.” As detailed in her annual report, a large number of patients in the UK already undergo genetic testing at least once in their life, and for a wide range of reasons, including the aforementioned thalassemia diagnosis, screening for cancer predisposition triggered by high family incidence, or determining the best course of action in cancer treatment. So wouldn’t it make sense to sequence the genome once and keep the data available for life? My answer is yes, but with a number of bold and double underlined caveats.

The first one is with respect to the security concerns prompted by the need to store data of extreme sensitivity like genomic data. The genome obviously contains information about ethnic heritage and predisposition to diseases/conditions, possibly including mental disorders. Data breaches of sensitive information, including health and medical data, sadly happen on a daily basis. But certain security threats are actually specific to genomic data and much more worrisome. For instance, due to its hereditary nature, access to a genome essentially implies access to that of close relatives as well, including offspring, so one’s decision to publish/donate their genome is also being made for their siblings, kids/grandkids, etc. So sensitivity does not degrade over time, but persists long after a patient’s death. In fact, it might even increase, as new aspects of the genome are studied and discovered. As a consequence, Prof. Dame Davies’ dream could easily turn into a nightmare without adequate investments toward sound security measures, that involve both technical tools (such as upgrading of obsolete hardware) as well as education, awareness, and practices that do not simply shift burden onto clinicians and practitioners, but incorporate security in their design and not as an after-the-fact.

Another concern is with allowing researchers to use the genomic data collected by the NHS, along with medical history, for research purposes – e.g., to discover genetic mutations that are responsible for certain traits or diseases. This requires building a meaningful trust relationship between the NHS/Government and patients, which cannot happen without healing the wounds from recent incidents like the care.data debacle or Google DeepMind’s use of personal NHS records. Instead, the annual report seems to include security/anonymity promises we cannot realistically maintain, while, worse yet, promoting a rhetoric of greater good trumping privacy concerns, as well as seemingly pushing a choice between donating data and access to the best care. It is misleading to use terms like “de-identification” of genomic data as an effective protection tool, while proper anonymization is inherently impossible due to its peculiar combination of unique and hereditary features, as demonstrated by a wide array of scientific results. Rather, we should make it clear that data can never be fully anonymized, or protected with 100% guarantees.

Overall, I believe that patients should not be automatically enrolled in sequencing programs. Even if they are given an option to later withdraw, once the data is out there it is impossible to delete all copies of it. Rather, patients should voluntarily decide to join through an effective informed consent mechanism. This proves to be challenging against a background in which information that can be extracted/inferred from genomes may rapidly change: what if in the future a new mutation responsible for early on-set Alzheimer’s is discovered? What if the NHS is privatized? Encouraging results with respect to education and informed consent, however, do exist. For instance, the Personal Genome Project is a good example of effective strategies to help volunteers understand the risks and could be used to inform future NHS-run sequencing programs.

 

An edited version of this article was originally published on the BMJ.

New EU Innovative Training Network project “Privacy & Us”

Last week, “Privacy & Us” — an Innovative Training Network (ITN) project funded by the EU’s Marie Skłodowska-Curie actions — held its kick-off meeting in Munich. Hosted in the nice and modern Wisschenschafts Zentrum campus by Uniscon, one of the project partners, principal investigators from seven different countries set out the plan for the next 48 months.

Privacy & Us really stands for “Privacy and Usability” and aims to conduct privacy research and, over the next 3 years, train thirteen Early Stage Researchers (ESRs) — i.e., PhD students — to be able to reason, design, and develop innovative solutions to privacy research challenges, not only from a technical point of view but also from the “human side”.

The project involves nine “beneficiaries”: Karlstads Universitet (Sweden), Goethe Universitaet Frankfurt (Germany), Tel Aviv University (Israel), Unabhängiges Landeszentrum für Datenschutz (Germany), Uniscon (Germany), University College London (UK), USECON (Austria), VASCO Innovation Center (UK), and Wirtschaft Universitat Wien (Austria), as well as seven partner organizations: the Austrian Data Protection Authority (Austria), Preslmayr Rechtsanwälte OG (Austria), Friedrich-Alexander University Erlangen (Germany), University of Bonn (Germany), the Bavarian Data Protection Authority (Germany), EveryWare Technologies (Italy), and Sentor MSS AB (Sweden).

The people behind Privacy & Us project at the kick-off meeting in Munich, December 2015
The people behind Privacy & Us project at the kick-off meeting in Munich, December 2015

The Innovative Training Networks are interdisciplinary and multidisciplinary in nature and promote, by design, a collaborative approach to research training. Funding is extremely competitive, with acceptance rate as low as 6%, and quite generous for the ESRs who often enjoy higher than usual salaries (exact numbers depend on the hosting country), plus 600 EUR/month mobility allowance and 500 EUR/month family allowance.

The students will start in August 2016 and will be trained to face both current and future challenges in the area of privacy and usability, spending a minimum of six months in secondment to another partner organization, and participating in several training and development activities.

Three studentships will be hosted at UCL,  under the supervision of Dr Emiliano De Cristofaro, Prof. Angela Sasse, Prof. Ann Blandford, and Dr Steven Murdoch. Specifically, one project will investigate how to securely and efficiently store genomic data, design and implementing privacy-preserving genomic testing, as well as support user-centered design of secure personal genomic applications. The second project will aim to better understand and support individuals’ decision-making around healthcare data disclosure, weighing up personal and societal costs and benefits of disclosure, and the third (with the VASCO Innovation Centre) will explore techniques for privacy-preserving authentication, namely, extending these to develop and evaluate innovative solutions for secure and usable authentication that respects user privacy.

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Sequencing your genome is becoming an affordable reality – but at what personal cost?

Genomics is increasingly hailed by many as the turning point in modern medicine. Advances in technology now mean we’re able to make out the full DNA sequence of an organism and decipher its entire hereditary information, bringing us closer to discovering the causes of particular diseases and disorders and drugs that can be targeted to the individual.

Buzzwords like “whole genome sequencing” and “personalised medicine” are everywhere – but how are they enabling a powerful medical and societal revolution?

It all started in the 1990’s with the Human Genome Project – a very ambitious venture involving 20 international partners and an investment of US$3 billion. In 2003, 13 years after it began, the project yielded the first complete human genome. Today, the cost of sequencing whole genomes is plummeting fast and it is now possible to do the job for less than US$1,000, meaning a whole host of applications both in research and in treatments.

Variants and mutations

Genetic mutations are often linked to disorders, predisposition to diseases and response to treatment. For instance, inherited genetic variants can cause blood disorders such as thalassaemia or others such as cystic fibrosis or sickle cell anaemia.

Genome sequencing is being used today in diagnostic and clinical settings to find rare variants in a patient’s genome, or to sequence cancers’ genomes (to point out genomic differences between solid tumours and develop a more effective therapeutic strategy). It is also possible to test for known simple mutations via a process called genotyping, which can find genetic differences through a set of biomarkers. In the case of thalassemia, for example, there are mutations in the HBB gene on chromosome 11.

A number of drugs, including blood-thinners like warfarin, have already been commercialised with genetic markers (such as a known location on a chromosome) linked to effectiveness and correct dosage.

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