Linking a Person’s Genetic Sequence to Risk of Disease is an Inexact Science
Whoooooosh! That rushing sound you hear could be the plummeting cost of genome scans, the surge in studies linking common genetic markers to widespread human diseases and traits, or the murmurs of people discussing what those genetic markers portend for their personal health risks.
But it is still early days, say the Harvard researchers who helped bring about this convergence of science, technology and popular interest in personal genomics. These researchers are scrambling to bridge the knowledge gap between the reality and the expectations for predicting diseases using high-tech genomics technologies.
In the meantime, scientists caution doctors, patients and consumers to be skeptical about estimates of genetic risk based on the latest findings, especially given interventions that might have even riskier side effects. A person’s actual DNA sequence may stand the test of time, but genetic risk profiles are likely to evolve as science zips ahead.
“We are still too early in the cycle of discovery for most tests that are based on newly discovered associations to provide stable estimates of genetic risk for many diseases,” sum up biostatistician Peter Kraft and genetic epidemiologist David Hunter in a perspective published online April 15 in The New England Journal of Medicine. Kraft is associate professor of epidemiology in the Harvard School of Public Health departments of Epidemiology and Biostatistics. Hunter is the Vincent L. Gregory professor in cancer prevention in the HSPH departments of Epidemiology and Nutrition.
Clinical Utility to Come
Despite the growing list of validated associations, most of the genes contributing to common diseases are still a mystery. In another NEJM essay last June, Hunter and his co-authors refer to the markers discovered so far as “canaries in the coal mine, signaling the relationship to a disease of a biologically important gene or gene regulatory mechanism in humans whose ultimate importance cannot be estimated until the full set of mutations is found, the biologic pathways understood, and clinical utility demonstrated.”
In the last two years, genomewide association (GWA) studies have come of age scientifically, thanks in large part to conceptual and methodological insights by researchers at Harvard Medical School and the Broad Institute of Harvard and MIT (see Focus, Nov. 11, 2005), as well as large datasets of patients and extensive collaborations among researchers worldwide.
Statistically compelling studies reveal new widely shared genetic markers underlying a variety of diseases and traits—macular degeneration, multiple sclerosis, coronary heart disease, type 1 and type 2 diabetes, prostate cancer, Crohn’s disease and rheumatoid arthritis. Kraft, Hunter, and their co-authors added two new breast cancer variants to the list in the May Nature Genetics.
“The real story is about the biology,” said David Altshuler, an HMS professor of genetics at Massachusetts General Hospital and the Broad, who directed the HapMap project that enabled these genomewide mapping studies.
“The primary value of genetic mapping is not risk prediction, but providing novel insights about mechanisms of disease,” Altshuler and his coauthors wrote in a recent Science review. “Knowledge of disease pathways (not limited to the causal genes and mutations) can suggest strategies for prevention, diagnosis and therapy.”
Take just one example of the disparity between biological insight and predictive value: the gene that encodes the enzyme targeted by statins (see related brief, page 2). Variations in the gene only explain a five percent effect on LDL cholesterol levels between individuals, but drugs targeting the enzyme lower LDL levels by about 30 percent.
“For risk prediction, we need to know more variants to explain a higher proportion of inherited risk,” Hunter said. For now, the implicated genetic regions can be “a happy hunting ground for basic scientists.”
For individuals, family history still trumps the known genetic details of heritability. In a large Swedish study of type 2 diabetes, for instance, 11 validated genetic markers heightened disease predication accuracy in 15 percent of people when added to the usual risk factors, such as family history of type 2 diabetes, obesity and cholesterol levels, but that incremental value pales next to the threefold increased risk conferred by family history alone. (Altshuler was a co-author of the study, in the Nov. 20, 2008, NEJM.)
Nine of those same diabetes markers are evaluated by 23andMe, a company that markets personal genome scans directly to consumers for less than $400. The company’s analyses are dominated by recently discovered common genetic markers, but also include other rarer mutations with stronger effects, such as the primary cystic fibrosis mutation and three of the BRCA1 and BRCA2 mutations for breast cancer, said computational biologist Serge Saxonov, a founding scientist of the company (and Harvard College grad, ’99).
Genetic Risks Change
Whatever is now known about the association between genetic variations and disease is likely to change, then change again. “Information about genotypes and their relationships to phenotypes is a moving target,” said Marcy MacDonald, HMS professor of neurology at MGH. “As new phenotypes are accrued, we may come up with different genotype–phenotype correlations than [we had] six months ago, or six years ago, or 60 years ago, and they may be different in the future,” she said at the April 3 HMS nanocourse on personal genetics.
Despite the changing risk scenarios, personal genomes are likely to become more popular as prices drop, and genetic risk profiles for markers of many complex diseases will likely stabilize. Some combination of genetic markers may soon become as conventional as measures of cholesterol and body fat.
More powerful indicators of disease and inheritance await discovery in the fuller details of those personal genomes. The HMS lab of genetics professor George Church has launched the public Personal Genome Project (PGP) to probe the complete sequences, not just the markers, to extract more details about genes (www.personalgenomes.org).
“There is nothing like perusing your genetic data to drive home its limitations as a source of insight into yourself,” wrote Harvard psychology professor Steven Pinker in The New York Times Magazine in a January feature article about his experience as a PGP participant.
To help close the gap between what people may hope their genomes will tell them versus what doctors and scientists know is possible, the HMS genetics lab of Ting Wu is developing the Personal Genetics Education Project (http://genepath.med.harvard.edu/WuLab/pgEd/index.html), under the leadership of Dana Waring, to expand consideration of the ethical, legal and social issues of personal genetics.
Conflict Disclosure: The authors report no conflicts of interest.
Funding Sources: The National Institutes of Health (Hunter); the content of the work is the responsibility solely of the authors.