Protecting Genetic Privacy in Biobanking through Data Protection Law
Protecting Genetic Privacy in Biobanking through Data Protection Law
DARA HALLINAN
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Abbreviations
BCR Binding Corporate Rules
BGB Bürgerliches Gesetzbuch (Germany)
CoE Council of Europe
CJEU Court of Justice of the European Union
CNIL Commission Nationale de l’Informatique et des Libertés
DPA Data Protection Authority
DPIA Data Protection Impact Assessment
DPO Data Protection Officer
ECHR European Convention on Human Rights
EctHR European Court of Human Rights
EDPB European Data Protection Board
EDPS European Data Protection Supervisor
FFPE Formalin-Fixed, Paraffin-Embedded
GDPR General Data Protection Regulation
GWAS genome-wide association study
HGP Human Genome Project
MTA Material Transfer Agreement
NHS National Health Service (UK)
OECD Organization for Economic Co-operation and Development
PGP Personal Genomes Project
REC Research Ethics Committee
RFID Radio Frequency Identification
SGB Sozialgesetzbuch (Germany)
SNP single nucleotide polymorphism
SMEs small and medium-sized enterprise
StPO Strafprozessordnung (Germany)
UNESCO United Nations Educational, Scientific and Cultural Organization
WMA World Medical Association
Table of Cases and Legislation
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167–68
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160–61
ECLI:EU:C:2014:238 168
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Lindqvist v. Sweden [2003] ECLI:EU:C:2003:596 151
Maximillian Schrems v Data Protection Commissioner [2015] ECLI:EU:C:2015:650 182–83
Patrick Breyer v Bundesrepublik Deutschland [2016] ECLI:EU:C:2016:779 134
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L.H. v. Latvia, App no 52019/07, 29 April 2014
Leyla Şahin v. Turkey, App no� 44774/98, 10 November 2005
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V.C. v. Slovakia, App no 18968/07, 8 November 2011 197
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United Nations Educational, Scientific and Cultural Organzation Universal Declaration on the Human Genome and Human Rights (11 November 1997) 29 C/Resolutions + CORR 67
Article 5 49, 73, 83
Article 10 53, 76
Article 22 74–75
United Nations Educational, Scientific and Cultural Organization International Declaration on Human Genetic Data (16 October 2003) 32 C/Resolutions�
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United Nations Educational, Scientific and Cultural Organization Universal Declaration on Bioethics and Human Rights (21 October 2005) 33 C/Resolutions + CORR + CORR 2 + CORR 3 + CORR 4 + CORR 5
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World Medical Association, Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Subjects (Policy, 1964 (updated 2013))
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Article 17
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EUROPEAN UNION INSTRUMENTS
Consolidated Version of the Treaty on European Union [2012] OJ C326/13
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Charter of Fundamental Rights of the European Union [2012] OJ C 326/391
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Directive 96/9/EC of the European Parliament and of the European Council on the Protection of Databases [1996] OJ L77/20
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Article 2 94
Directive (EU) 2016/680 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data by competent authorities for the purposes of the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, and on the free movement of such data, and repealing Council Framework Decision 2008/977/JHA [2016] OJ L119/89
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Article 9 105
Article 15
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1 Introduction
Over the past two decades, genomic research has become an increasingly significant approach to medical research. This results from its scientific and practical promise for human health. In the first instance, genomic research provides a methodological approach suited to reveal new information about a great number of diseases and, in particular, about diseases with particularly high instance—and therefore social significance—in modern societies. In turn, the approach supports the stratification of populations and the identification of the biomarkers essential for personalised medicine. As much as genomic research holds promise for human health, however, it is resource-intensive. Genomic research requires the availability, and capacity for distribution, of large stores of biological samples and associated data. The entities which function in this storage and distribution capacity, and which sit at the centre of the genomic research endeavour, are biobanks.
As genomic research has grown in significance as an approach to medical research, biobanks and biobanking have grown in significance as support infrastructure for medical research. With this increased significance, however, biobanks have also come under ever-increasing ethical and legal scrutiny. In particular, the novelty of biobanks as significant entities in medical research, and the novelty of the type of research they support, have given rise to new questions as to the rights engaged by the biobanking process and as to how these rights should be effectively protected. One right which has been the focus of much discussion and uncertainty is the right to privacy. It is not that the right to privacy is novel to medical research. Rather, the specifics of the biobanking process have meant that the meaning and value of privacy has needed to be considered in novel ways.
From a fundamental perspective, the fact that genomic research relies on the processing of large quantities of individuals’ genomic data has raised new questions as to which forms of privacy right are engaged by research, and as to which privacy rights holders are engaged by research: questions of genetic privacy. For example, previously, discussion of privacy in research had focused on questions of bodily privacy and the restriction of third-party access to research subject data. Yet, the deep interrogation of a genome can reveal novel information about research subjects, of which they may not be aware, raising questions as to whether privacy rights may be engaged concerning the return of this information—rights to know and not know. Equally, previously, discussions of privacy rights in research focused predominantly on the research subject. Yet, as genomic data is hereditary, the processing of this data raises questions as to whether genetic relatives and genetic groups may also have privacy rights engaged.
In turn, the novel institutional, and actor, constellations involved in biobanking and genomic research have raised novel questions as to how to effectively and proportionately balance the need to protect genetic privacy rights with the need to promote other legitimate interests engaged by biobanking and genomic research—in particular interests tied up with the conduct and outcome of research. For example, previously, discussions of protecting privacy in research had predominantly focused on questions of clinical research involving live subjects. As biobanking and genomic research engage with biological samples and associated data sets, as opposed to live individuals, questions are raised as to the degree to which approaches to protect privacy in clinical research should also apply to data-based research involving little, if any, interaction with subjects’ bodies.
Ordinarily, one might look to the law to provide some clue, or image, as to which genetic privacy rights are worthy of protection and as to what an effective and proportionate approach to their protection should look like. In this regard, a brief look at the legal landscape relevant to biobanking in Europe reveals a great quantity of legislation apparently relevant for the protection of genetic privacy in biobanking. Relevant instruments appear at international, EU, and at national level. Despite the quantity of relevant legislation, however, criticism has been, and continues to be, voiced as to the suitability of available approaches. Criticism appears concerning the structure of frameworks—for example, concerning their complexity and contradictions in relation to international biobanking activity.1 Criticism also appears concerning the level of substantive protection provided.2
Since 25 May 2018, Regulation 2016/679—the General Data Protection Regulation (hereafter the GDPR or Regulation)—has applied, and now constitutes the keystone of European data protection law.3 The GDPR aims to provide a comprehensive system of protection for individuals’ rights engaged by data processing, applies to the processing of almost all personal data and, as a Regulation is, in principle, directly applicable in all European states in which it applies—including in all EU states. There is no doubt the GDPR applies to biobanking. There is also no doubt that the GDPR now occupies a significant place in the European legal framework relevant for the regulation of biobanking. As a result, over the past few years, there have been several works considering the applicability and consequences of the GDPR for biobanks and
1 See, for example, Mahsa Shabani and Pascal Borry, ‘Rules for Processing Genetic Data for Research Purposes in View of the New EU General Data Protection Regulation’ (2018) European Journal of Human Genetics 26 149, 149–56; Gauthier Chassang, ‘The Impact of the EU General Data Protection Regulation on Scientific Research’ [2017] Ecancermedicalscience 11(709) <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5243137/> accessed 11 December 2019; Edward Dove and Jiahong Chen, ‘Should Consent for Data Processing Be Privileged in Health Research? A Comparative Legal Analysis’ (2019) International Data Privacy Law ipz023 1, 3–5; Michael Morrison, Jessica Bell, Carol George, et al., ‘The European General Data Protection Regulation: Challenges and Considerations for iPSC Researchers and Biobanks’ (2017) Regenerative Medicine 12(6) 693, 693–703.
2 See, for example, Susan Gibbons, ‘Mapping the Regulatory Space’, in Jane Kaye, Susan M. C. Gibbons, Catherine Heeney, Michael Parker, and Andrew Smart (eds.), Governing Biobanks: Understanding the Interplay between Law and Practice (Hart 2012), 51, 53.
3 Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) [2016] OJ, L 119/1.
biobanking.4 Somewhat surprisingly, however, there remains little extensive analysis of the capacity of the GDPR—indeed of European data protection law generally, even prior to the GDPR—as a framework for the protection of genetic privacy in biobanking.
In light of the above, this book takes an in-depth look at the function, problems, and opportunities presented by the GDPR as a framework for the protection of genetic privacy in biobanking in Europe. In doing so, the book presents the following argument: European data protection law, under the GDPR, can and ought to be looked at to play a central role in the protection of genetic privacy in biobanking. The book argues that the substantive framework presented by the GDPR already offers an admirable baseline level of protection for genetic privacy. The book further argues that whilst numerous problems with this standard of protection are indeed identifiable, the GDPR offers the normative flexibility to accommodate solutions to these problems, as well as the procedural mechanisms to facilitate the realisation of solutions.
It might be argued that looking to the GDPR to play a role in the protection of genetic privacy in biobanking is obvious. Close inspection, however, reveals this argument is far from cut and dried. Three types of uncertainty emerge. First, whilst EU data protection law has historically had a close link with the protection of privacy, the precise nature of this link, and accordingly, the capacity of the GDPR as a framework for the protection of privacy, remain ambiguous and the subject of much academic discussion.5 The right to data protection under Article 8 of the Charter of Fundamental Rights is a separate right to the right to respect for private and family life under Article 7 of the Charter and has been argued to have a separate function.6 Equally, the GDPR, as second-order EU data protection law, at no point specifically mentions the protection of privacy in its stated goals—Article 1(2) states the GDPR seeks to protect: ‘fundamental rights and freedoms of natural persons’.
Second, even if the function of the GDPR in relation to privacy generally were clear, uncertainty remains in relation to the degree to which the GDPR can function to protect genetic privacy. At a fundamental level, there remains uncertainty as to which genetic privacy rights, and genetic privacy rights holders, deserve protection under European law and as to the form of protection these rights deserve. Equally, issues of genetic privacy played little role in discussion leading up to the adoption of the GDPR. As a result, at no point in the GDPR is specific provision made for the protection of genetic privacy. There is no express reference, for example, to protection for genetic privacy rights to know and not know novel information produced via genetic analysis. Nor is there express reference to the protection of the genetic privacy rights of genetic
4 See, for example, Marion Albers, ‘Rechtsrahmen und Rechtsprobleme bei Biobanken’ (2013) Medizinrecht 31(8) 483, 486.
5 See, for a discussion: Orla Lynsky, The Foundations of EU Data Protection Law (Oxford University Press 2015) 89–131.
6 Charter of Fundamental Rights of the European Union [2012] OJ C 326/391, Articles 7 and 8.
See, for example, the argumentation by De Hert et al. concerning the difference between privacy and data protection: Paul De Hert and Serge Gutwirth, ‘Privacy, Data Protection and Law Enforcement. Opacity of the Individual and Transparency of Power’, in E. Claes, A. Duff, and S. Gutwirth (eds.), Privacy and the Criminal Law (Intersentia 2006) 61, 61–104.
relatives or genetic groups.7 There is thus little basis on which to assume the law will function optimally in relation to genetic privacy.
Third, uncertainty appears as to the degree to which the GDPR provides a suitable framework for the protection of genetic privacy in biobanking. In the first instance, there are other relevant legal frameworks in operation around Europe—some of which have a much longer pedigree in relation to the regulation of medical research than the GDPR. It remains unclear as to whether, and if so how, European data protection law under GDPR can provide a superior approach to these frameworks. In turn, the GDPR was designed as omnibus legislation—legislation applicable across many contexts in which personal data are processed. There are only a few references to the specifics of the research context in the GDPR, and not one of these refers to biobanking or genomic research. As a result, there remains doubt as to the extent to which the provisions of the GDPR can strike the right balance between protecting genetic privacy rights and promoting other legitimate interests in biobanking.8
In this regard, the book begins, in the next two chapters, by providing background to the subject of study. Chapter 2 provides an overview of the concept of genetic data and how this data may be used to produce socially significant information. The chapter considers, in particular, the range of types of genetic data, the range of socially relevant information which might be produced from these data, the modalities of production of socially relevant information, and the range of parties to whom this information might relate. Chapter 3 then provides an overview of the current European biobanking landscape. The chapter starts with a brief overview of the history and function of genomic research. The chapter then provides a working definition for the concepts of ‘biobank’ and ‘biobanking’ and an overview of the variety of types of activities and organisational structures constituting the modern European biobanking landscape. The chapter finally highlights a set of trends likely to define European biobanking in future.
The book then continues, in Chapter 4, by looking at how the concept of genetic privacy unpacks in the biobanking context. The chapter begins by providing a definition for the concepts of privacy and of genetic privacy. Next, the chapter maps the range of genetic privacy rights held by the research subject in biobanking as well as the range of other parties—specifically genetic relatives and genetic groups—which might also claim to have genetic privacy rights engaged by biobanking. As genetic privacy rights in biobanking do not exist in a vacuum, the chapter then moves to map the range of other legitimate interests engaged by the biobanking process—including interests tied up with the conduct and outcome of research supported by biobanking, and thirdparty non-research interests tied up with access to biobanking substances. Finally, the
7 See, for example, the criticism of the protection provided by data protection law in relation to genetic privacy in: Mark Taylor, Genetic Data and the Law: A Critical Perspective on Privacy Protection (Cambridge University Press 2012) 101–98.
8 See, for example, the criticism of the GDPR in this regard in: David Peloquin, Michael DiMaio, Barbara Bierer, et al., ‘Disruptive and Avoidable: GDPR Challenges to Secondary Research Uses of Data’ [2020] European Journal of Human Genetics 28 697, 697–705.
chapter provides a schematic for the way in which genetic privacy rights and other interests in biobanking relate to one another.
Next, in Chapter 5, the book sketches a baseline level of protection for genetic privacy rights in biobanking, against which legal systems—including the GDPR—might be compared. This baseline level of protection is provided via identifying principles dealing with the protection of all types of genetic privacy rights, and rights holders, in biobanking in the international framework. Two types of international principles are identified: common international principles—principles identified in a majority of all biobank-relevant international instruments; and emerging international principles— principles identifiable in a majority of biobank-specific international instruments. Finally, the chapter engages in a critique of the international framework and the set of identified principles constituting this framework. This critique aims not to undermine the legitimacy of regarding identified international principles as offering a baseline level of protection, but rather to highlight that the protection provided has flaws, and thus should not be regarded as definitive, or perfect.
Chapter 6 then considers a question which must be answered before any detailed consideration of European data protection law under the GDPR can be undertaken: is there any need to consider European data protection law as a framework for the protection of genetic privacy in biobanking at all? The chapter answers this question by engaging in a thought experiment. In this regard, the chapter begins by mapping the protection provided to genetic privacy in biobanking by the EU’s, and three European states’—Estonia, Germany, and the UK—legal systems excluding through data protection law. The chapter then engages in a critical analysis, highlighting the significant inadequacy of the protection provided by these systems excluding data protection law. The chapter then finishes by showing why, generally, European data protection law under the GDPR looks a viable solution to address the problems displayed by other approaches.
On the back of the work in Chapter 6, the book subsequently moves, in the next three chapters, to offer a detailed elaboration of how European data protection law under the GDPR will apply to biobanking. Chapter 7 describes when the GDPR will apply, rationae materiae, to biobanking—considering, in particular, the key questions as to whether biological samples can fall within the scope of the GDPR, and which types of biobanking substances will qualify as identifiable. Chapter 8 describes how the key classification systems in the GDPR—the actor classification system and the personal data classification system—classify the biobanking process. Chapter 9 finally describes how the GDPR’s substantive provisions apply to biobanking. The chapter breaks provisions down into seven groups—oversight, legitimate processing, data subject rights, data controller obligations, international transfers, sanctions, and derogations—and provides a detailed analysis of the applicability of provisions in each group in turn.
Finally, Chapter 10 shows the utility of the GDPR as a framework for the protection of genetic privacy in biobanking. In this regard, the chapter outlines twenty-three problems concerning the standard of protection offered by the GDPR. Problems are outlined in relation to: the structure of the GDPR; the range of types of genetic privacy
rights protected; the range of types of genetic privacy rights holders protected; the standard of substantive protection offered—in relation to the genetic privacy rights and rights holders which are protected; the technical suitability of the GDPR’s substantive provisions in relation to biobanking; the disproportionate impact of substantive provisions on other legitimate interests engaged by biobanking; the practical applicability of the GDPR’s substantive provisions to biobanking; and the degree to which the GDPR harmonises protection across Europe.
The chapter also, however, considers the degree to which each problem casts doubt on the efficacy of the GDPR as a framework for the protection of genetic privacy in biobanking. In this regard, the chapter considers whether there are factors evident which are likely to mitigate the severity of the impact of each problem, as well as whether each problem is subject to resolution—either through the GDPR’s internal interpretation and adaptation mechanisms or through external legislation operating in tandem with the GDPR. The analysis shows that the great majority of problems are not as severe as they initially seem and, as a result, do not call into question the efficacy of the GDPR as a framework for the protection of genetic privacy in biobanking. The analysis also shows that all problems which either require a solution, or would benefit from a solution, can be resolved via the GDPR’s internal mechanisms or via external law operating in parallel with the GDPR, or both.
2 Genetic Data, Genome Understanding, and Socially Relevant Information
A. Introduction
Genetic privacy concerns rights engaged by the collection and processing of genetic data to produce socially relevant information. This chapter thus provides a background to the analysis in the rest of the book by providing an overview of the relationship between genetic data, genetic analysis of genetic data—based on scientific understanding of the structure and function of the genome—and the production of socially relevant information. In particular, the chapter provides an insight into the complexity and variations in the relationships between genetic data, genetic analysis, and socially relevant information.
The chapter begins by providing a basic typology of the range of data which might be subject to genetic analysis: genetic data (section B). The chapter then highlights the types of socially relevant information which might be extracted, via genetic analysis, from these types of data (section C). Next, the chapter discusses two significant modalities of genetic data: that genetic data may be subject to multiple analyses; and that the results of genetic analyses may not always produce accurate information (sections D and E). Finally, the chapter looks at the range of parties about whom socially significant information may be produced (section F).
B. Types of Genetic Data
Scientific understanding of genes and their relationship with human heredity, development, and phenotypes, can be used to subject certain types of data to genetic analysis to produce socially relevant information. We might call these types of data genetic data. There are a variety of different types of genetic data. Four are particularly important:
1. The genomic sequence
2. Phenotype information
3. Inheritance information
4. Ostensibly non-genetic data connected to genome expression.
The genomic sequence: this is the core form of genetic data and may exist in both computerised and biological form. Whilst the gene concept may still lack defined edges in the biological sciences, the genome remains firmly at its core. There is no doubt that the genome plays a central role in organismal heredity, development, and eventual phenotype. Thus, the sequence of the genome can always be subject to genetic analysis to produce socially relevant information.
Phenotype information: this becomes relevant when the relationship between genotypes and phenotypes is understood. The genotype plays a role in the construction of the phenotype. Therefore, data about a certain phenotype may be subject to genetic analysis to reveal information about the genotype. Usually, if the phenotype is already known, there will be no use in knowing the genotype. Certain aspects of genetic architecture, however, may play a role in multiple biological functions. Accordingly, deducing a genotype in relation to one phenotype may allow further genetic deductions which reveal other likely phenotypes or likely future phenotypes. As Visscher et al. observe: ‘Multiple lines of evidence are consistent with widespread pleiotropy for complex traits . . . [for example] studies have reported genetic correlations between traits, implying that a number of the same [genetic] variants affect two or more traits in the same direction.’1
Inheritance information: this becomes relevant when genetically defined inheritance patterns are understood. If the genetic inheritance patterns of a phenotype are known, it is possible to infer information about an individual’s genetic architecture from relevant information related to inheritance. For example, family health records can reveal information about an individual’s propensity to contract a disease if the genetic inheritance patterns for that disease are clear. Indeed, such genetic inheritance inferences are even possible without direct knowledge of the specific genetic architecture of inheritance—if a trait displays genetic inheritance patterns, then, in certain cases, the form of these patterns can be known without knowing the specifics of the genetic architecture involved. For example, the genetic inheritance patterns of the disease alkaptonuria have been researched since 1902. It was only in 1996, however, when the specific genetic architecture was isolated—abnormalities in the gene ‘HGD’.2
Ostensibly non-genetic data connected with genome expression: this becomes relevant when the influence of external factors on gene expression is understood. Gene expression in final phenotypes is highly dependent on external factors—such as environmental factors. Accordingly, such non-genomic information may also be subject to genetic analysis to provide information as to how an individual’s genetic architecture will eventually express. For example, As McPherson et al. observe, susceptibility to breast cancer may be partially determined by genetics, but it may also be influenced by
1 Peter Visscher, Naomi Wray, Quan Zhang, et al., ‘10 Years of GWAS Discovery: Biology, Function, and Translation’ (2017) American Journal of Human Genetics 101(1) 5, 8 (hereafter Visscher, Wray, Zhang, et al., ‘10 Years of GWAS Discovery’).
2 J. M. Fernández-Cañón, B. Granadino, D. Beltrán-Valero de Bernabé, et al., ‘The Molecular Basis of Alkaptonuria’ (1996) Nature Genetics 14(1) 19, 19–24.
environmental factors.3 Thus, an individual’s environmental information could be analysed to shed light on the likelihood with which identified genetic architecture related to breast cancer is likely to express in terms of contracting the disease.
Against this background, it is now possible to move to consider the content of socially significant information which can be extracted via genetic analysis.
C. Types of Socially Significant Information Revealed via Genetic Analysis
The range of socially significant information which can be revealed through genetic analysis is broad. Six types of such socially relevant information are particularly important:
1. Identity information
2. Biological relationship information
3. Ethnicity and ethnic heritage information
4. Physical appearance information
5. Health information
6. Social and behavioural trait information.
Identity information: the unique characteristics of an individual’s genome makes it a near-perfect biometric identifier. Genetic analysis producing identification information might be done in several ways. Two are noteworthy. First, through cross-matching of genomic data. Data extracted from a biological sample—a genetic profile—can be compared with an existing database in which an individual’s genetic profile has already been stored together with identifying information. This is how genetic databases for law enforcement work. They rely on the matching of genetic profiles found at crime scenes, with profiles stored in existing databases.4 Second, a variation of the above process relying on other forms of genetic data is also possible—even if data has supposedly been anonymised and there is no comparator sample. For example, Gymrek et al. have shown it to be possible to use genealogy information as a proxy to identify specific individuals from genomic data sets.5
Biological relationship information: the inherited nature of the genome means it can be used to identify familial genetic relationships. Genetic analysis producing relationship information might happen in three ways. First, the genetic relationship between any original genome, or genetic profile—a reduced section of the genome—and
3 K. McPherson, C. M. Steel, and J. M. Dixon, ‘Breast Cancer: Epidemiology, Risk Factors and Genetics’ (2000) British Medical Journal 321(7261) 624, 624–8.
4 Nuffield Council of Bioethics, The Forensic Use of Bioinformation: Ethical Issues (Report, 2007) 8–11 (hereafter Nuffield Council of Bioethics, ‘The Forensic Use of Bioinformation’).
5 M. Gymrek, A. L. McGuire, D. Golan, et al., ‘Identifying Personal Genomes by Surname Inference’ (2013) Science 339(6117) 321, 321–4.
another genome, or genetic profile, can be determined by comparing the quantity of genetic architecture shared.6 Such matching procedures are used, for example, by law enforcement. If a sample found at a crime scene does not show any clear matches in a police database, a familial search might be performed to find relatives in the database. Second, matching can also happen using other forms of data potentially subject to genetic analysis as a proxy for genome data. Such matching procedures can be used, for example, by individuals trying to track down relatives. In 2005, Kramer used a combination of his own genetic data and genealogy records to track down his anonymous sperm-donor father.7 Finally, genetic analysis of genome data can be used to establish infertility problems and can be used to disprove the existence of a genetic relationship originally presumed to exist.8
Ethnicity and ethnic heritage information: genetic relationships between those who share ancestry can be analysed to reveal ethnicity information. Certain ethnic groups display tendencies towards possession of certain genetic architecture and certain phenotypic traits.9 If an individual has certain architecture or displays certain phenotypes, then their ethnic origin might be inferred via genetic analysis. It should be noted, however, that ethnicity analysis is problematic.10 Three problems present. First, as Collins observes, ethnicity is as much a social and political concept as a genetic concept.11 Producing clearly definable objective genetic categories relating to ethnicity is thus difficult. Second, the Nuffield Council of Bioethics points out that, whilst ethnic inferences may be more or less specific, inferences will never be completely exact—largely due to the fact that global mobility has led to considerable mixing.12 Finally, ethnic genetic inference can be socially problematic. For example, with particular reference to police databases in the UK, the Nuffield Council further observe: ‘In the light of the social factors and policing practices that lead to a disproportionate number of people from black and ethnic minority groups being stopped, searched and arrested by the police, and hence having their DNA profiles recorded . . . there are concerns that inferring ethnic identity from biological samples risks reinforcing racist views of propensity to criminality.’13
Physical appearance information: genetic analysis can reveal information about physical appearance. That aspects of physical appearance are genetically determined has been known for over a century. There is thus much data on genetic determinants of physical appearance. Traits known to have genetic determinants include eye colour,
6 Nuffield Council of Bioethics, ‘The Forensic Use of Bioinformation’ (n. 4) 19–20.
7 Rob Stein, ‘Found on the Web, with DNA: A Boy’s Father’ Washington Post (Washington 13 November 2005) available at <http://www.washingtonpost.com/wp-dyn/content/article/2005/11/12/AR2005111200958.html> accessed 27 November 2019.
8 Nuffield Council of Bioethics, ‘The Forensic Use of Bioinformation’ (n. 4) 20.
9 A. L. Lowe, A. Urquhart, L. A. Foreman, et al., ‘Inferring Ethnic Origin by Means of an STR Profile’ (2001) Forensic Science International 119 17, 17–22.
10 Nuffield Council of Bioethics, ‘The Forensic Use of Bioinformation’ (n. 4) 80–3.
11 Francis Collins, ‘What We Do and Don’t Know about “Race”, “Ethnicity”, Genetics and Health at the Dawn of the Genome Era’ (2004) Nature Genetics 36 513, 513.
12 Nuffield Council of Bioethics, ‘The Forensic Use of Bioinformation’ (n. 4) 20.
13 Nuffield Council of Bioethics, ‘The Forensic Use of Bioinformation’ (n. 4) 20.
hair colour, and skin colour.14 Looking into the future, it has even been suggested that the recreation of an image of an individual’s bodily and facial appearance could be accurately generated from genome analysis. There are reports of the use of such analysis in law enforcement. However, these are limited.15 In practice, the science is not anywhere near ready for broad deployment in any sector.16 Despite such predictions, it should be recalled: not only are the precise genetic determinants of many physical features not yet known, but it is also thought that most physical characteristics result from the interaction of genetic and environmental factors.
Health information: genetic analysis can be used to reveal significant information about an individual’s health. If a health condition is known to be genetically influenced, genetic analysis of genetic data can reveal information about an individual’s status in relation to that condition. For example, whether an individual suffers from Down syndrome can be confirmed either through analysing their genome or through analysing their phenotype—sufferers of Down syndrome usually have one extra chromosome, forty-seven rather than forty-six, and tend to have a distinctive facial phenotype.17 As an individual’s genome plays a role in future development, genetic analysis in relation to health is often used to extrapolate information about the likelihood of future health status. This is particularly the case in relation to the genome and in relation to hereditary information. For example, as Ford et al. observe, genetic analysis of the genome in relation to mutations in the BRCA1 gene can be used to make predictions as to the likelihood of the onset of breast cancer.18
Social and behavioural trait information: the field of behavioural genetics suggests genetic analysis may reveal social or behavioural traits. The field suggests a great many social and behavioural traits may be—at least partially—genetic. For example, it is suggested there are genetic determinants for aggression. Gronek et al., for example, observe aggression may, at least in part, be determined by ‘genes located on chromosome Xp11.3’.19 A sub-field of behavioural genetics is psychiatric genetics, which seeks to locate the genetic basis of psychiatric illnesses. For example, several genes related to neural pathways have been cited as related to alcohol dependence. Morozova et al., for example, cite the significance of CHRM2, CHRNA5, and COMT.20 However, it should
14 See, for example, on eye colour: Jonas Mengel-From, Terence Wong, Niels Morling, et al., ‘Genetic Determinants of Hair and Eye Colours in the Scottish and Danish Populations’ (2009) BMJ Genetics 10 88, 88.
15 Andrew Pollack, ‘Building a Face, and a Case, on DNA’ New York Times (New York, 23 February 2015) <http:// www.nytimes.com/2015/02/24/science/building-face-and-a-case-on-dna.html> accessed 27 November 2019.
16 M. Kayser and P. M. Schneider, ‘DNA-Based Prediction of Human Externally Visible Characteristics in Forensics: Motivations, Scientific Challenges, and Ethical Considerations’ (2009) Forensic Science International Genetics 3(3) 154, 154–61.
17 See: Genetics Home Reference, ‘Down Syndrome’ (Genetics Home Reference) <https://ghr.nlm.nih.gov/ condition/down-syndrome#genes> accessed 27 November 2019 (hereafter Genetics Home Reference, ‘Down Syndrome’).
18 D. Ford, D. F. Easton, M. Stratton, et al., ‘Genetic Heterogeneity and Penetrance Analysis of the BRCA1 and BRCA2 Genes in Breast Cancer Families’ (1998) American Journal of Human Genetics 62(3) 676, 676–89.
19 Piotr Gronek, Dariusz Wieliński, and Joanna Gronek, ‘Genetic and Non-Genetic Determinants of Aggression in Combat Sports’ (2015) Open Life Sciences 10 7, 13.
20 Tatiana Morozova, David Goldman, Trudy Mackay, et al., ‘The Genetic Basis of Alcoholism: Multiple Phenotypes, Many Genes, Complex Networks’ [2012] Genome Biology 13(239) <http://genomebiology.com/content/pdf/gb-2012-13-2-239.pdf> accessed 27 November 2019.
be noted that the difficulties in clearly defining behavioural, social, or psychiatric traits as subjects of genetic analysis, combined with the multiple environmental and genetic influences which need to be taken into account, have limited the number of scientifically irrefutable claims in this field.21 In turn, claims that social, behavioural, or psychiatric characteristics are rooted in genetics can have eminently political implications. Such claims thus require a high degree of scrutiny.22
This section provided an overview of the types of socially significant information which might be revealed through genetic analysis of genetic data. Yet, a mere consideration of the types of information which might be extracted from a genome ignores important modalities of these types of information. Two such modalities are particularly significant.
1. Genetic data may be subject to a range of genetic analyses.
2. Genetic analysis may not produce accurate information.
D. The Range of Genetic Analyses Potentially Applicable to Genetic Data
Taylor observes that information might be regarded as ‘data + interpretation’.23 It is not the case, however, that all data can only be subject to one interpretation. This is true for genetic data and genetic analysis in relation to the production of socially relevant information. The significance of the applicability of multiple interpretations—multiple genetic analyses—is true for many types of genetic data, but is most prominently true for raw genomic data.
Multiple types of genetic analysis can be applied to any large set of genomic data. The full range of possible analyses might be referred to as the absolute analytical potential of the available data set.24 The absolute analytical potential of any set of sequenced genomic data is a function of two factors. First, it is a function of the genomic data at hand. Whilst an individual’s DNA contains their complete genome, it is not always the case that the complete genome will be available for analysis—for example, if the sequencing process aimed at extracting data from the genome was not intended to sequence the whole genome. Naturally, limitations on the genomic data available places limitations on the analyses possible, and thus limitations on the range of socially relevant information which can be extracted. Second, it is a function of the state of the art in scientific knowledge. The socially significant information which can be extracted from
21 Antoinette Rouvroy, Human Genes and Neoliberal Governance: A Foucauldian Critique (Routledge-Cavendish 2008) 105–7 (hereafter Rouvroy, Human Genes and Neoliberal Governance).
22 Rouvroy, Human Genes and Neoliberal Governance (n. 21) 105–7.
23 Mark Taylor, Genetic Data and the Law: A Critical Perspective on Privacy Protection (Cambridge University Press 2012) 42 (hereafter Taylor, Genetic Data and the Law).
24 Taylor, Genetic Data and the Law (n. 23) 43–4. Taylor refers to the concept of interpretative potential. As the idea of genetic analysis has already been introduced in this chapter, the term analytical potential is preferred.
sequenced genomic data naturally depends on what is known—in the abstract—about the significance of the data available.
Absolute analytical potential, however, may be further limited by factors specific to the context of processing. The analytical potential in context might be referred to as the contextual analytical potential. The contextual analytical potential is defined by two further factors, supplemental to those defining absolute analytical potential. The first factor is the type of entity processing the genomic data. This will define the aims of processing and the range of analyses likely to be applied. For example, the analysis of genetic data by an insurance company will likely be focused on the risk of disease contraction, whereas the use of genetic data in criminal forensics will likely aim to extract identity information relating to criminal investigations. The second factor is the capabilities and expertise available to the entity conducting the analysis. For example, analytical potential will differ depending on whether the analysing entity in question relies on trained geneticists or on genetic testing kits.
Analytical potential, however, is not static. It is liable to change as shifts occur in key determinative factors. Such shifts may occur in relation to either absolute or contextual analytical potential. In terms of absolute analytical potential, the scope of possible analyses is likely to continually expand because of advances in genetic science. Every day, more information about the function of the genome and its relationship with extragenomic—both biological and environmental—factors comes to light. It seems highly unlikely that progression in this understanding is likely to slow or stop anytime soon. As analytical potential depends on the state of the art in genetic science, the consequence of this development is that the analytical potential of genetic data will continue to expand over time. For example, not long ago, over 98 per cent of the genome was regarded as junk DNA. Now, it is apparent that this junk DNA has several functions; for example, in genome regulation and expression.25 As Kellis et al. observe: ‘Many human genomic regions previously assumed to be nonfunctional have . . . been found to be teeming with . . . activity.’26
In terms of contextual analytical potential, the context of analysis is liable to change. Change may happen as the context itself undergoes change—for example, if a new business model requiring novel genetic analysis is introduced into a company. Equally, the analytical context itself can shift. Just because genetic data is subject to one sort of genetic analysis in one context today, does not mean it cannot be transferred and analysed in another context tomorrow.
Finally, whilst providing analyses to extract significance from a genome can be complex, this need not necessarily the case. It is true that conducting an extensive analysis of a genome is complicated and expensive. In the first instance, expensive sequencing equipment is required—although this is getting cheaper, as will be discussed in the subsequent chapters. Without this equipment, it will not be possible to turn the raw
25 Elizabeth Pennisi, ‘ENCODE Project Writes Eulogy for Junk DNA’ (2012) Science 337(6099) 1159, 1159–61.
26 Manolis Kellis, Barbara Wold, Michael Snyder, et al., ‘Defining Functional DNA Elements in the Human Genome’ (2014) Proceedings of the National Academy of Sciences of the United States of America 111(17) 6131, 6134.
biological data into the computerised data necessary to conduct the analysis capable of produce socially significant information. In turn, extensive analysis of raw sequenced genomic data requires an expert eye and scientific training. However, identifying the presence of certain sequences in a genome, and thereby identifying the likelihood that the individual from whom the genome comes will possess a certain phenotype, need not be so complicated. Indeed, certain limited forms of analyses can be automated.
E. The Accuracy of Information Produced via Genetic Analysis
There may be a considerable breadth of types of socially significant information which may be revealed about an individual via genetic analysis. It is not, however, always the case that this information will be accurate—in the sense of being true—about that individual.
There are indeed certain types of genetic analysis which will reveal accurate information about an individual. These cases constitute, however, the minority. Analysis of identity from genomic data, for example, tends to be accurate. If an individual’s genome is sequenced, the raw sequence data revealed tends to be accurate—although sequencing errors are possible. As each individual’s genome is unique, the sequenced genomic can then be said to be an accurate biometric identifier. As Faundez-Zanuy suggests: ‘the highest possible accuracy is achieved through DNA identification’.27 Equally, analysis of the genome can accurately reveal certain types of phenotypic information. Certain phenotypes are completely—or at least almost completely—genetically defined. This is the case in relation to hair colour. As Branicki et al., for example, observe: ‘a model based on a subset of 13 single or compound genetic markers from 11 genes’ can predict red hair at over 90 per cent, and black hair at almost 90 per cent, accuracy.28
Accurate claims through genetic analysis are not limited to analysis of the genome, however. For example, observation of certain genetically defined phenotypes, or possession of relevant family history, may also allow accurate claims to be made about underlying architecture. For example, as discussed above, most Down-syndrome sufferers have a distinct physical phenotype from which an accurate assumption as to the presence of an issue in chromosome 21 can be made.29
In most cases, the picture of genome and genome expression is, however, less clear and thus genetic analysis may not reveal accurate socially relevant information. Rather, often, analysis will only reveal limited probabilistic information. There are several
27 Marcos Faundez-Zanuy, ‘Privacy Issues on Biometric Systems’ (2005) IEEE Aerospace and Engineering Systems Magazine February 13, 14. See also: Beau Sperry, Megan Allyse, and Richard Sharp, ‘Genetic Fingerprints and National Security’ [2017] American Journal of Bioethics 17 <https://www.tandfonline.com/doi/full/10.1080/ 15265161.2017.1316627> accessed 27 November 2019. Sperry et al. discuss the increasing significance of DNA as an identifier for national security.
28 Wojciech Branicki, Fan Liu, Kate van Duijn, et al., ‘Model-Based Prediction of Human Hair Color Using DNA Variants’ (2011) Human Genetics 129 453, 453. See also: Jonathan Rees, ‘Genetics of Hair and Skin Color’ (2003) Annual Review Genetics 37 67, 68.
29 Genetics Home Reference, ‘Down Syndrome’ (n. 17).
reasons genetic analysis may reveal information of limited accuracy. In the first instance, certain phenotypic traits may indeed have some genetic basis, whilst the precise genetic architecture, or the modalities of its expression, are not yet fully known or understood. In relation to such traits, science is simply not yet able to provide an analytical framework capable of producing accurate information. In turn, the accuracy of analysis will depend on the comprehensiveness of available information. For example, many traits emerge as the result of an interplay between genes and the environment. In relation to such traits, genetic analyses of the genome would only reveal part of the puzzle.
Finally, even if the role of genetics is generally well understood in relation to a trait, in individual cases, genetic analysis may still lead to inaccurate conclusions. To produce genetic science, many individuals’ genetic codes may be interrogated to extrapolate a general truth about human—or some human group’s—genetics. However, there is in fact no archetype human genome. Each individual genome is unique. Even the huge efforts at producing the complete sequence of the human genome relied on biological samples from limited numbers of individuals. For example, the Celera Genomics human genome sequencing effort—discussed in more detail in the next chapter—used samples from only five volunteers.30 It is thus not the case that general models of human genetics will always apply to specific individuals. For example, a risk factor for a disease may be produced following interrogation of an individual’s architecture. Yet, that individual may have a mutation elsewhere on the genome which renders the problematic architecture irrelevant. The risk factor would thus, in that individual’s case, be wrong. As Visscher et al. observe in relation to complex traits: ‘each individual will carry several [factors] that increase . . and several [factors] that decrease . . trait . . risk’.31
The probabilistic nature of much socially relevant information based on genetic analysis often takes on significance concerning claims that a certain phenotype will manifest in future. Such predictive analysis is most often used to find out an individual’s propensity towards contracting medical conditions. It is true that there are illnesses whose onset can be predicted with a degree of certainty through genetic analysis—for example, Huntington’s Chorea, whose cause is located solely in one known gene.32 However, the vast majority of illnesses are either polygenic—resulting from the interplay of multiple genes—or multifactorial—resulting from both genetic and environmental factors operating together. In relation to most of these diseases, the full genetic picture is still not known. As Craig observes, for example: ‘For the most part, complex diseases are caused by a combination of genetic, environmental, and lifestyle factors, most of which have not yet been identified. The vast majority of diseases fall into this category.’33 In these cases, a genetic risk factor might be produced via genetic analysis.
30 J. C. Venter, M. D. Adams, E. W. Myers, et al., ‘The Sequence of the Human Genome’ (2001) Science 291 1304, 1306.
31 Visscher, Wray, Zhang, et al., ‘10 Years of GWAS Discovery’ (n. 1) 8.
32 Marcy MacDonald, Christine Ambrose, Mabel Duyao, et al., ‘A Novel Gene Containing a Trinucleotide Repeat That Is Expanded and Unstable on Huntington’s Disease Chromosomes’ (1993) Cell 72(6) 971, 971–83.
33 Johanna Craig, ‘Complex Diseases: Research and Applications’ (2008) Nature Education 1(1) 184, 184.
