Personal Genomes and Ethical Issues
Declining Cost of Genome Sequencing
•
The genome sequencing is expected to happen rouAnely in
The era of big data
: the genome data are already being collected in a
large scale and being mined for scienAfic discovery to drive more
accurate descripAve and predicAve models that inform decision
making for the best diagnosis and treatment choice for a given paAent.
Genomes and Privacy
•
DNA sequence data contain informaAon that can be used to
uniquely idenAfy an individual (i.e., genome sequences are
like fingerprints)
Genomes and Privacy
•
Privacy concerns
– Genome sequence data and other related types of data (gene
expressions, clinical records, epigeneAc data, etc.) are collected for a large number of paAents for medical research
– Most types of data are freely available through internet except for
genotype data
• NCBI GEO database for gene expression data
• The cancer genome atlas data portals
– Genotype data are available to scienAsts through restricted access
The
Cancer
Genome
Atlas
(TCGA)
Data
hWps://tcga-‐data.nci.nih.gov/tcga/tcgaHome2.jspThe Cancer Genome Atlas (TCGA) Data
hWps://tcga-‐data.nci.nih.gov/tcga/tcgaCancerDetails.jsp?
Access Control for TCGA Data
•
Open access data Aer
– De-‐idenAfied clinical and demographic data
– Gene expression data
– Copy-‐number alteraAons in regions of the genome
– EpigeneAc data
– Summaries of data, such as genotype frequencies, compiled across individuals
•
Controlled-‐access data Aer
– Individual germline variant data
– DNA sequence data
– One should apply for an access to the data through NIH (database of genotypes and phenotypes)
Informed Consent for Scientific Research
•
Standard pracAce for enrolling human subjects in a research
study
– fully informing potenAal parAcipants on all aspects of a study including
the aims of the study, risks, benefits, costs, and protecAon of personal privacy
– The origins of modern day informed consent for medical research can
be traced to the Nuremberg Code in 1947 in an effort to protect parAcipants in research studies (Homan, 1991).
Nuremberg Code
•
Research ethics principles for human experimentaAon
•
Established ader the Nuremberg Trials at the end of the
Second World War
Nuremberg Code
• On August 19, 1947, the judges of the American military tribunal in the case of the
USA vs. Karl Brandt et. al. delivered their verdict. Before announcing the guilt or
innocence of each defendant, they confronted the difficult quesAon of medical
experimentaAon on human beings. Several German doctors had argued in their
own defense that their experiments differed liWle from previous American or German ones. Furthermore they showed that no internaAonal law or informal
statement differenAated between legal and illegal human experimentaAon. This
argument worried Drs. Andrew Ivy and Leo Alexander, American doctors who had worked with the prosecuAon during the trial. On April 17, 1947, Dr. Alexander submiWed a memorandum to the United States Counsel for War Crimes which
outlined six points defining legiAmate research. The verdict of August 19 reiterated almost all of these points in a secAon enAtled "Permissible Medical Experiments" and revised the original six points into ten. Subsequently, the ten points became known as the "Nuremberg Code." Although the code addressed the defense
arguments in general, remarkably none of the specific findings against Brandt and his codefendants menAoned the code. Thus the legal force of the document was not well established. The uncertain use of the code conAnued in the half century following the trial when it informed numerous internaAonal ethics statements but failed to find a place in either the American or German naAonal law codes.
Nevertheless, it remains a landmark document on medical ethics and one of the most lasAng products of the "Doctors Trial."
hWp://www.ushmm.org/informaAon/exhibiAons/online-‐features/special-‐focus/doctors-‐trial/ nuremberg-‐code
Institutional Review Board (IRB)
•
A commiWee that has been formally designated to approve,
monitor, and review biomedical and behavioral research
involving humans
•
Title 45 Code of Federal RegulaAons Part 46
Current Generation Informed Consents
• Single study focused
• Top-‐down unidirecAonal researcher-‐parAcipant (research subject)
relaAonship.
• ProtecAng the parAcipant is considered among the chief aims
• Data generaAon on study parAcipants usually an integral part of the
consent
• Data ownership and terms of use driven by the invesAgator and/or hosAng
insAtuAon
• Study parAcipants are counseled to ensure they understand all aspects of
the study, although no evidence of understanding is sought or required
• In most cases, anonymity, privacy, and confidenAality are guaranteed as a
key condiAon for a parAcipant’s consent
• Big data, more open data sharing mentality demand a new genera<on of informed consents
Genomes and Privacy
•
How much should we be concerned about the privacy issues
regarding personal genome data?
•
Non-‐geneAc data can be used to predict the genotypes of
individuals
(Bayesian method to predict individual SNP genotypes from gene expression data, Schadt et al. Nature GeneAcs, 2012)– Uses gene expressions as non-‐geneAc data and predicts the genotypes
Predicting Genotypes with Non-Genetic
Data
(Schadt et al., 2012)•
Study design
– Learn a predicAve model for predicAng genotypes given gene expression data from training set
– Use the learned predicAve model to test whether genotype can be predicted correctly given gene expression from test set
•
Two datasets from non-‐overlapping groups of individuals
– the human liver cohort (HLC): liver gene expression and genotype data for 378 European-‐ American individuals
– Roux-‐en-‐Y gastric bypass cohort (RYGB): genotype data and expression data for liver and adipose Assue from 580 European-‐American subjects undergoing Roux-‐en-‐Y gastric bypass (RYGB)
•
Learn model from HLC data (training set) and predict RYGB
genotypes given RYGB expressions (test set)
Predicting Genotypes from Gene
Expressions
• Led semicircle: observed genotypes
• Right semicircle: predicted genotype
• Blue line: correctly matched individuals
• White line: incorrectly matched individuals
•
Overall, we can
resolve 99% of the
idenAAes of
Personal Genome Project
(www.personalgenomes.org)
•
Volunteers from the general public
working together with researchers to
advance personal genomics
•
Aims to sequence genomes of 100,000
individuals from the general public
•
Volunteers should be willing to make their
geneAc and trait informaAon publicly
available
The Evolving Informed Consent for
Scientific Research I
•
Open consents for public resources -‐ the Personal Genome
Project (PGP) Consent (Church, 2005; Lunshof et al, 2008)
•
Differs from classic informed consent in the following ways
– Data ownership and terms of use of data no longer driven by study
invesAgator
– Data are published to the web and made available without restricAon
– Single-‐study focused, but has broad and open-‐ended scope (data
sharing as an aim)
– ParAcipants agree to reciprocal interacAon with researchers
– ParAcipants must pass an exam to ensure they possess basic geneAc
literacy, are informed about the public nature of the study, understand the possibility of re-‐idenAficaAon, and that some risks are unknown and unpredictable.
The Evolving Informed Consent for
Scientific Research II
•
Interoperable and Open Consents -‐ The Portable Legal Consent
(PLC) (
hWp://weconsent.us/
)
•
Based upon the PGP consent, but altered in the following important
ways
– The PLC can be used across any number of studies
– If variaAons of the same PLC form guarantee the same freedoms and creates no more than the same obligaAons, then it can be cerAfied as interoperable across the PLC network
– Fully digital, requires no input from a physician or other health/ research professional
– Requires users sign terms of a contract to ensure compliance with data use terms
– Intended for data already generated to enable open access of data across many studies
Other Issues in Scientific Research
•
Open personal data environment
•
A greater parAcipaAon of informed paAents
•
ProtecAng individuals from discriminaAon
– GeneAc InformaAon NondiscriminaAon Act (2008)
• Law protecAng individuals from discriminaAon based on their
Other Social/Ethical Issues in Personal
Genomes
•
Consumer genomics services
– 23andme, deCODE geneAcs, Navigenics
– Personal genomic services are offered in the private sectors more
widely than by clinicians
– Commercial genomic services may displace clinicians as the primary
provider of health-‐related geneAc informaAon
– Individuals may assume more responsibility for health-‐promoAng
Other Social/Ethical Issues in Personal
Genomes
•
P4 medicine (
hWp://p4mi.org
)
– PredicAve, prevenAve, personalized, and parAcipatory medicine
– Apply systems biology to personalized disease prevenAon and
Summary
•
Ethical/Social/Legal issues in personal genomes
– ProtecAng privacy in terms of geneAc informaAon while enabling
scienAfic research
– ProtecAng individuals from discriminaAon based on geneAc
informaAon
– Empowering individuals by keeping them informed of the various
