articoletto interessante sulle strategie di ricerca e politica della
ricerca nel campo della genetica.
Nature Genetics - 38, 1221 (2006)
doi:10.1038/ng1106-1221
Human genetics in the Crescent City
Genome-wide association studies are now being carried out for a variety
of human traits. Announcements at the annual meeting of the American
Society of Human Genetics, held recently in New Orleans, offer a glimpse
into the changing landscape surrounding issues such as study design,
reporting, analysis and data accessibility.
The American Society of Human Genetics (ASHG) should be congratulated
for having just held its annual meeting in New Orleans, honorably
fulfilling a commitment to a city still struggling to recover from
Hurricane Katrina. A glance at the abstracts confirmed that genome-wide
association (GWA) studies are now being carried out for a variety of
human traits. Improved genotyping technologies, the HapMap and large
consortia of investigators have enabled such studies, which are the
obvious next step for human geneticists. Announcements both before and
at the meeting provided an opportunity to survey the changing landscape.
In addition to the GWA studies currently underway, the NIH earlier this
year announced the Genetic Association Information Network (GAIN). GAIN
involves Pfizer, Perlegen and Affymetrix in a collaborative effort with
the NIH to carry out GWA studies for several common diseases. In New
Orleans, Francis Collins of the National Human Genome Research Institute
(NHGRI) and Patrice Milos of Pfizer announced the selection of six
peer-reviewed, investigator-initiated proposals for funding. They
include GWA studies of psoriasis, attention-deficit hyperactivity
disorder, schizophrenia, bipolar disorder, depression and nephropathy in
type 1 diabetes. It seems noteworthy that three of the six involve
common and devastating psychiatric disorders, where genetic insights
that might shed light on the underlying pathophysiology are urgently
needed. Genotyping will begin by the end of this year, and data will be
made available to other researchers during the first quarter of 2007.
Several aspects of GAIN should make it a standard-setting effort. First,
a statistical analysis workshop open to the entire community, to be held
at the end of November, will aim to reach a consensus on the most
powerful and appropriate methods of data analysis. Having witnessed a
lack of consensus in the formal review of genetic association studies
submitted to this journal over the last 2–3 years, we urge the widest
possible participation, as well as a wide dissemination of guidelines
for study design, data reporting and analysis.
These are not the only thorny issues to be resolved. In response to a
question about the delay in announcing the recipients of grants under
the medical sequencing program of the NHGRI, Collins noted that the
proposals had been reviewed but that concerns about data accessibility
and privacy issues were still being aired. GAIN clearly faces the same
issues, which is why the NIH issued a request for information in August
asking for advice and laying out proposals for data submission and
access, privacy protection, publication and intellectual property.
In our view, the broad principles laid out in the proposal are
reasonable and deserve support in that they promote accessibility of the
data to a wide range of researchers while taking sensible precautions to
guard against the small chance that such openness could be abused. In
regard to data submission, investigators receiving NIH funds will be
asked to submit the protocol, questionnaires, variables measured and any
other relevant documentation. These data will be available to everyone.
Submission of more detailed coded (de-identified) data covering
phenotype, exposure, genotype and pedigree data will be submitted under
stricter control. Local institutional review boards would be charged
with certifying that the submission to the central repository takes
account of informed consent and contains adequate safeguards to protect
the identities of the participants. Third-party researchers wanting to
use this 'second tier' of data would be granted access by an NIH Data
Access Committee, which will ensure that the data are used only for
approved uses. If this structure is adopted, we would encourage authors
at the time of submission to document the source of the data and to
state that they are in full compliance with the provisions of the Data
Access Committee. The NIH also proposes a 9-month period following data
submission during which the generators of the data would have exclusive
rights to publish an analysis. This policy has the virtue of specifying
an unambiguous period of time for exclusive publication, after which
ethical publication would be available to any researcher. The issue of
intellectual property may actually be the least contentious. At a
workshop earlier this year to discuss similar policies for The Cancer
Genome Atlas, industry representatives were clear that genotype data
should be considered pre-competitive, a position echoed by Pfizer's
Milos at the ASHG meeting.
What can we expect when the results start pouring in? Notably absent
from the above programs is any mention of copy number or other
structural variation. Participants at the ASHG meeting noted the
importance of simultaneous assessments of SNPs and copy number variants,
in aid of the fullest possible picture of common genomic variation.
Epigenetic variation—a dark horse in the search for risk factors—will
also have to be accounted for, although the integration of such data
with genetic variation may be a difficult task.
Preliminary results reported at the meeting suggest that some dramatic
recent findings—CFH in age-related macular degeneration, and TCF7L2 in
type 2 diabetes—may not be representative of the majority of common risk
variants. In a comment on the recent paper by Jonathan Flint and
colleagues describing characteristics of mouse quantitative trait loci
(Nat. Genet. 38, 879–887; 2006), Thomas Mitchell-Olds noted the
"fundamental tragedy of biomedical genetics: that quantitative genetics
is true"—meaning that the vast majority of risk variants will have a
very small influence on disease susceptibility. Although 'tragedy' is
used here with tongue in cheek, it is clear that the separation of true
variants of modest effect from false ones remains a substantial, if not
insurmountable, challenge.
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