Is Medicine ready for Genome Sequencing?
Genetics news has been popular for many years, complete with premature
promises of revolutionary new medical treatments. These inflated expectations
are certain to disappoint the uninitiated. The unfolding science reveals more
complexity and uncertainty with each discovery. New methods emerge quickly that
empower scientists to discover more, faster and at lower cost, but there is no
assurance that new discoveries will take us closer to practical applications,
rather than farther away from affordable medical miracles.
The mastermind behind the whole festival of life is DNA, a self-seeking
molecular code. DNA expresses genes that direct the assembly of amino acids into
proteins. Some of the proteins are enzymes that assemble molecules that are used
to construct living cells. The human genome is a living text that continually
edits and rewrites itself. Over half of the human genome is occupied by
repeating sequences and a historical record of evolution. Some gene
sequences suggest two lines of evolution. One is a set of genes from aerobic
bacteria. The second set comes from the single-celled organisms that
incorporated bacteria as mitochondria. Animal cells depend on mitochondria to
combine oxygen with fatty acids and amino acids to produce energy.
Human DNA is contained in chromosomes is 3 about billion letters long. When
a cell divides, DNA splits down the center of the rungs leaving two long strands
with only one nucleotide per rung. An enzyme, DNA polymerase, copies each
strand. The nucleotides always form complementary pairs; adenosine pairs with
thymine and cytosine with guanine. As the new strand is made, each nucleotide
pairs with its partner. Copying errors are common. Slippages occur if the new
strand gets out of sync with the parent strand. They have to be aligned so that
the copies are linked in the same order as the original. A shift of just one
base pair in the sequence alters the meaning of the code. Copying errors are a
form of genetic mutation. Human populations accumulate mutations that contribute
to the diversity of human abilities, diseases and destinies.
In their description of the National Human Genome Research Institute’s
Encyclopedia of DNA Elements (ENCODE) project, Guigó and Reese stated:
“Finding human genes is a complex task because of the peculiar anatomy of the eukaryotic genome. Eukaryotic genes lie within long stretches of intergenic DNA,
and within the genes only a few short fragments—the exons—are spliced together,
often in alternative configurations, to form the mRNAs. Sequence signals in the
genome are degenerate, and computational programs using them are able to
identify the exons and link them into genes with relative success. But only
through the sequencing of the corresponding mRNA molecule can a gene be
unequivocally identified. It is unclear, however, what fraction of genes can be
ascertained through mRNA sequencing. In addition, genes are only one type of
functional elements. It is likely that most of the functionality of the human
genome sequence remains largely unexplored.”The modest aim of the first phase
of ENCODE was to identify all functional elements in about 1% of the genome
sequence through the collaborative effort of computational and laboratory-based
scientists.
In time, the complete genomes of many species and many individuals within a species
will be determined. Sophisticated comparative analyses of genomes will reveal
more about the evolution of species. Computers with increasingly sophisticated
software are essential to using genomic information in meaningful ways. DNA sequencing, brilliant programming and digital computing are perfect matches.
Personal Genome
The idea that each person will have their entire genome sequenced and that
someone, somehow can read the genome and predict the future is both intriguing
and misleading. Sequencing technology is advancing rapidly toward cheaper,
faster, somewhat reliable genome analysis. However the brutal truth is that
having access to a complete genome of 3 million base pairs in a sequence is having a surplus of
mostly useless information. The intriguing aspect of having abundant genome
information is that the doors open to a century of new research, new methods of
computing large data sets and work for armies of researchers who can run
studies of populations of humans to find out what the genomic information really
means. In other words, genomes are just a beginning of a journey of discovery,
not an endpoint.
A nature editorial reviewing the 10 years since the fist
human genome was reported stated:" The first post-genome decade saw spectacular
advances in science. The success of the original genome project inspired many
other 'big biology' efforts — notably the International HapMap Project, which
charted the points at which human genomes commonly differ, and the Encyclopedia
of DNA Elements (ENCODE), which aims to identify every functional element in the
human genome. Dramatic leaps in sequencing technology and a precipitous drop in
costs have helped generate torrents of genetic data, including more than two
dozen published human genomes and close to 200 unpublished ones. Along the way,
geneticists have discovered that such basic concepts as 'gene' and 'gene
regulation' are far more complex than they ever imagined. But for all the
intellectual ferment of the past decade, has human health truly benefited from
the sequencing of the human genome? Francis Collins and Craig Venter both
say 'not much'. Granted, there has been some progress, in the form of drugs
targeted against specific genetic defects identified in a few types of cancer,
for example, and in some rare inherited disorders. But the complexity of
post-genome biology has dashed early hopes that this trickle of therapies would
rapidly become a flood. Witness the multitude of association studies that aimed
to find connections between common genetic variants and common diseases, with
only limited success, or the discovery that most cancers have their own unique
genetic characteristics, making widely applicable therapies hard to find.
(Editorial. The human genome. Nature 464, 649-650 (1 April 2010) |
doi:10.1038/464649a; Published online 31 March 2010)
George Church, a professor of genetics at Harvard Medical School, founded the Personal Genome Project with the intention of sequencing selected
individuals who were willing to share their genomes and medical histories in a
public database. Personal Genomes.org held a conference in Boston April, 2010,
inviting prominent individuals who have already been sequenced to share their
experiences. Personal Genomics stated that there are fewer than 25 individuals
to-date with public genome sequences, we expect that in this decade, there may
be 1 million or more individuals with complete genome sequences worldwide.
Rehm et al reviewed the history of gene-disease
correlations: "During the past 25 years, major advances in deciphering the
genetic bases of human disease have been achieved, and more than 5000 disorders
are now recognized at the genetic level. Although
this is an extraordinarily important achievement in our understanding of the
biologic features of human disease, the integration of these findings into
clinical care is severely challenged by a lack of publicly available and
accurate interpretations of the vast amount of human genetic variation known to
exist. More than 80 million genetic variants have been uncovered in the human
genome and for the majority, we have no clear understanding of their role in
human health and disease. Thus, we are very far from a world in which we can
sequence patients’ genomes and easily interpret their risk of disease, even if
patients carry a variant in a gene that is associated with a highly penetrant
genetic disorder. The rarity of most variants that are identified in genes has
made it difficult to decipher the effect of such variants on gene function; most
rare variants are labeled a “variant of uncertain significance.” A final factor
contributing to our lack of consistent, clear, and clinically relevant
annotation of human genetic variation is the so-called silo effect, in which
various commercial and academic entities maintain isolated, sometimes
proprietary, databases of variant interpretations, thus preventing the sharing
of critical knowledge that could benefit patients, families, health care
providers, diagnostic laboratories, and payers." (Heidi L. Rehm et al.ClinGen — The Clinical Genome Resource. N Engl J Med June 4, 2015.)
In 2017 the U.S. Food and Drug Administration today allowed marketing of
23andMe Personal Genome Service Genetic Health Risk (GHR) tests for 10 diseases
or conditions. These are the first direct-to-consumer (DTC) tests authorized by
the FDA that provide information on an individual’s genetic predisposition to
certain medical diseases or conditions, which may help to make decisions about
lifestyle choices or to inform discussions with a health care professional. The
tests are based on identifying SNPs associated with 10 diseases. Seven of these
diseases are rare. The FDA cautioned: "Risks associated with use of the 23andMe
GHR tests include false positive findings, which can occur when a person
receives a result indicating incorrectly that he or she has a certain genetic
variant, and false negative findings that can occur when a user receives a
result indicating incorrectly that he or she does not have a certain genetic
variant. Results obtained from the tests should not be used for diagnosis or to
inform treatment decisions. Users should consult a health care professional with
questions or concerns about results. (USA FDA. FDA allows marketing of first
direct-to-consumer tests that provide genetic risk information for certain
conditions. News Release April 6 2017).
Medical Genetics Old Fashioned
In medical papers, old ideas of genes often prevail. Phrases such as
genetic tendency, genetic component, and genes play a role in are
typical of obsolete generalities that confuse rather than inform. The new
appreciation that genes are not solid, real entities is difficult for physicians
to understand. Part of the problem is that medical education pretends that
humans are static entities and that diseases are discrete phenomena.
A dynamic, interactive systems model better accounts for what actually
happens. Rather than solid, reliable genes, you can imagine segments of DNA as
codes that are read differently depending on circumstances. Much of the coding
deals with getting food, digesting it, distributing and using nutrients, and
excreting waste products. Food intake to the body is a major player in
determining gene expression.
Beyond the genome lies epigenetics - the study of how the expression of the
DNA code is altered as dynamic processes that can change in minutes. The
expression of DNA is balanced between stability mechanisms that preserve the
long-term species memory in the genome and adaptive mechanisms that change the
expression, depending on circumstances. It is the adaptive mechanisms and
changing DNA expressions that make individual predictions based on genome
analysis alone an act of faith rather than a reliable expression of science.
Epigenetics began with the discovery that DNA nucleotides can be silenced by
adding methyl groups. Somehow, somebody in cells or cell to cell communications
adds or subtracts methyl code to change the expression of DNA. Methylation was
just the beginning of discoveries that revealed more and more mechanism
that alter the expression of the genome. The DNA code is translated into many
different kinds of RNA. The emphasis has been on messenger RNA that is
transferred to ribosomes where it acts as a template for protein
synthesis. The meaning of gene has be limited to protein encoding sequences of
DNA, but already this understanding is seen as a partial truth at best. Short
RNA pieces, for example, can interfere with messenger RNA encoding.
Single-nucleotide polymorphisms (SNPs)
A screening technology that identifiers single-nucleotide
polymorphisms (SNPs) has developed rapidly and is less expensive and more
accessible than complete genome sequencing. As a tool of basic science SNP
scanning is interesting and promising. Databases have developed that associated
SNPs with diseases in thousands of cases and provide a preliminary view of complex traits and diseases caused by many genetic and environmental factors
working together. SNP screens have been offered commercially as tests for
disease risk. Their value is doubtful. In a 2010 review of SNP research Monolo
stated:" What is becoming clear from these early attempts at genetically based
risk assessment is that currently known variants explain too little about the
risk of disease occurrence to be of clinically useful predictive value. One can
anticipate that as sample sizes increase and more risk variants are identified,
the predictive value of cumulative genotypic scores will increase. It has also
been argued that the use of dense genotyping information, from tens of thousands
of SNPs with only nominal associations with disease, may improve the accuracy of
phenotypic prediction. Care is needed in evaluating genetic predictive models,
since they are often specific to the population in which they were developed,
and their value can vary with genotypic frequencies, effect sizes, and disease
incidence. Possible clinical uses of predictive scores — for example, in
deciding which patients should be screened more intensively for breast cancer
with the use of mammography or for statin-induced myopathy with the use of
muscle enzyme assays — will require rigorous, preferably prospective, evaluation
before being accepted into clinical practice. Genome wide scans permit screening
for many conditions at once. If probabilities were applied to 40 independent
diseases, for example, roughly 90% of the population would be placed in the top
5% of those at genetic risk for at least one of the diseases, 33% would be in
the top 1%, and 4% would be in the top 0.1%. Expanding such screening to 120
diseases would nearly triple the proportion in the top 0.001% at risk and
identify 1.2% at the top 0.01%, levels that could justify population-based
screening if appropriate interventions were available. The ability to assess
risk for 120 conditions at the same time also raises the concern that predictive
models will yield conflicting recommendations; if implemented, they could reduce
a person's risk for development of one condition and exacerbate the risk for
development of another. Such considerations are timely and important, since
several commercial ventures are marketing genome wide association–based
screening directly to consumers. Patients inquiring about genome wide
association testing should be advised that at present the results of such
testing have no value in predicting risk and are not clinically directive.
Clinicians would do well to use the discussion as an opportunity to point out
other identifiable, modifiable risk factors that motivated patients can control.
Whether to heed such advice or instead undergo testing and present the physician
with the test results as a fait accompli is the choice of the individual
patient. A decision to undergo genome wide association testing may result in the
diversion of scarce time and resources to counseling or follow-up investigation
of findings." Teri A. Manolio. Genomewide Association Studies and Assessment of
the Risk of Disease. NEJM Volume 363:166-176 July 8, 2010 Number 2
While there is great interest in developing rapid,
inexpensive genome sequencing, we lack even the most basic understanding of how
to read the genomic data. The predication of disease risk is the least likely
result of genomic data. Since the code is interactive, the expression of any
sequence associated with a disease may be altered by changing food intake or
other variables in the environment.
Author: Stephen Gislason MD
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