Category Archives: Genetic Medicine

Your DNA may hold valuable information about your health, but current genetic tests can't improve doctors' ability to predict your risk of major disease.

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Our genome the blueprint for what makes us who we are can provide valuable clues about our health and potentially help us predict our risk for various diseases. But a new study shows that knowledge of our DNA isnt actually as revealing as doctors hoped.

In a report published in the American Journal of Human Genetics, scientists at the Harvard School of Public Health found that incorporating genetic information did not improve doctors ability to predict disease risk above and beyond standard risk factors, including things like family history, lifestyle and behavior. So, having detailed genetic information didnt change doctors prevention or treatment plans.

For most people, your doctors advice before seeing your genetic test for a particular disease will be exactly the same as after seeing your tests, Peter Kraft, a co-author of the paper and an epidemiologist at the Harvard School of Public Health, said in a statement.

The researchers looked at risk factors both genetic and environmental for three common, chronic diseases, breast cancer, Type 2 diabetes and rheumatoid arthritis. All conditions are known to be influenced by some genetic and some lifestyle factors. The researchers wanted to determine whether adding information about the interplay of these factors would improve the sensitivity of disease risk prediction.

(MORE: Genetic Testing for Kids: Is It a Good Idea?)

For breast cancer, the scientists created a simulation that included 15 common genetic variants associated with increased risk of the disease, along with environmental factors, such as a womans age at first period, age when she gave birth to her first child and the number of close relatives affected by breast cancer. For Type 2 diabetes, researchers included 31 genetic variants, as well as lifestyle factors like obesity, physical activity, smoking status and family history of diabetes. Finally, for rheumatoid arthritis, they considered 31 genetic variants and two major lifestyle risk factors smoking and breast-feeding.

The researchers analyzed whether interactions among the genes, or interactions between genes and environmental factors, significantly changed the risk profile for any of these diseases. The disease models generated a variety of statistical combinations of genetic and environmental factors, but none produced any marked improvement in predicting disease risk over the lifestyle factors alone.

So, while genome sequencing has become a popular buzzword in medicine, the researchers conclude that given our current limited ability to interpret the genome or understand the complex interplay between genes and environment, getting genetic tests or whole-genome sequencing may not be as helpful as it could be when it comes to informing our health decisions. Even with the current list of 15 genetic variants associated with breast cancer, for example, scientists cant tell which variants are driving disease or are necessary to cause it, and which are merely along for the ride.

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Why Genetic Tests Don’t Help Doctors Predict Your Risk of Disease

ScienceDaily (May 24, 2012) Understanding the genetic diversity within and between populations has important implications for studies of human disease and evolution. This includes identifying associations between genetic variants and disease, detecting genomic regions that have undergone positive selection and highlighting interesting aspects of human population history.

Now, a team of researchers from the UCLA Henry Samueli School of Engineering and Applied Science, UCLA's Department of Ecology and Evolutionary Biology and Israel's Tel Aviv University has developed an innovative approach to the study of genetic diversity called spatial ancestry analysis (SPA), which allows for the modeling of genetic variation in two- or three-dimensional space.

Their study is published online this week in the journal Nature Genetics.

With SPA, researchers can model the spatial distribution of each genetic variant by assigning a genetic variant's frequency as a continuous function in geographic space. By doing this, they show that the explicit modeling of the genetic variant frequency -- the proportion of individuals who carry a specific variant -- allows individuals to be localized on a world map on the basis of their genetic information alone.

"If we know from where each individual in our study originated, what we observe is that some variation is more common in one part of the world and less common in another part of the world," said Eleazar Eskin, an associate professor of computer science at UCLA Engineering. "How common these variants are in a specific location changes gradually as the location changes.

"In this study, we think of the frequency of variation as being defined by a specific location. This gives us a different way to think about populations, which are usually thought of as being discrete. Instead, we think about the variant frequencies changing in different locations. If you think about a person's ancestry, it is no longer about being from a specific population -- but instead, each person's ancestry is defined by the location they're from. Now ancestry is a continuum."

The team reports the development of a simple probabilistic model for the spatial structure of genetic variation, with which they model how the frequency of each genetic variant changes as a function of the location of the individual in geographic space (where the gene frequency is actually a function of the x and y coordinates of an individual on a map).

"If the location of an individual is unknown, our model can actually infer geographic origins for each individual using only their genetic data with surprising accuracy," said Wen-Yun Yang, a UCLA computer science graduate student.

"The model makes it possible to infer the geographic ancestry of an individual's parents, even if those parents differ in ancestry. Existing approaches falter when it comes to this task," said UCLA's John Novembre, an assistant professor in the department of ecology and evolution.

SPA is also able to model genetic variation on a globe.

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Nnew genetic method developed to pinpoint individuals' geographic origin

BOSTON The great promise of the Human Genome Project is that if we can crack the genetic code in each of our cells, we may be able to predict what diseases we might get and prevent them. But more than a decade into this project, no medical miracles have been produced. Now, a new study by the Harvard School of Public Health has more disappointing news. WBURs All Things Considered host Sacha Pfeiffer spoke with the studys senior author, Peter Kraft, an associate professor of epidemiology at Harvard.

Sacha Pfeiffer: Your study looked at one of the possible key reasons for why simply mapping the human genome as huge a scientific accomplishment as that is might not alone be enough to start curing or preventing diseases. What else have researchers thought might be necessary to do that?

Peter Kraft: Weve actually been fabulously successful, in the last five years especially, in finding genetic variants that are associated with disease risk. But when people looked and asked the question, Do these actually help us predict whos going to be at high risk? the answer was mostly no. And one of reasons that might have been is that people looked at these variants in isolation, one at a time. But if you considered how they work together, and how they work together with the environment, to influence cancer risk or disease risk generally, people thought that might help boost the predictive ability.

So in terms of how genes work with other genes, or how genes react if you smoke, or if youre overweight, or if youve taken hormones that kind of thing?

Right, exactly. So the models up till now have assumed that a gene is a gene and its effect is the same whether you smoke or not. But, of course, that may not be the case and in fact probably isnt the case.

And so in your study you took those factors into account environmental and lifestyle factors. What did you find?

We sort of played a thought experiment and said, What if we knew how actually these things worked together? And given that information we tried to predict who was at high risk and who was at low risk. And we found that even knowing that information, which were a long way from knowing and understanding but even if we knew it, the change in the risk estimates would not be all that great. Its giving us a 1 to 3 percent increase of our ability to detect people who are at high risk.

Is that not a very useful increase?

Well, it depends on the context, but not necessarily. It seems to be in the range where your decision as a patient and your clinicians recommendations wouldnt really change that much. So given what they knew before they drew your blood and looked at your genetics, their recommendation would probably be the same.

So your study tells us that if we get our genes mapped, we might learn a little bit more if were at risk of a disease, but not very much to help our doctors. So where does that leave us in terms of our hopes for the Humane Genome Project and this idea that we could create personalized medicine customized for every individual?

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Study: Knowing Genetic Makeup May Not Help Predict Disease Risk

Public release date: 23-May-2012 [ | E-mail | Share ]

Contact: Wileen Wong Kromhout wwkromhout@support.ucla.edu 310-206-0540 University of California - Los Angeles

Understanding the genetic diversity within and between populations has important implications for studies of human disease and evolution. This includes identifying associations between genetic variants and disease, detecting genomic regions that have undergone positive selection and highlighting interesting aspects of human population history.

Now, a team of researchers from the UCLA Henry Samueli School of Engineering and Applied Science, UCLA's Department of Ecology and Evolutionary Biology and Israel's Tel Aviv University has developed an innovative approach to the study of genetic diversity called spatial ancestry analysis (SPA), which allows for the modeling of genetic variation in two- or three-dimensional space.

Their study is published online this week in the journal Nature Genetics.

With SPA, researchers can model the spatial distribution of each genetic variant by assigning a genetic variant's frequency as a continuous function in geographic space. By doing this, they show that the explicit modeling of the genetic variant frequency the proportion of individuals who carry a specific variant allows individuals to be localized on a world map on the basis of their genetic information alone.

"If we know from where each individual in our study originated, what we observe is that some variation is more common in one part of the world and less common in another part of the world," said Eleazar Eskin, an associate professor of computer science at UCLA Engineering. "How common these variants are in a specific location changes gradually as the location changes.

"In this study, we think of the frequency of variation as being defined by a specific location. This gives us a different way to think about populations, which are usually thought of as being discrete. Instead, we think about the variant frequencies changing in different locations. If you think about a person's ancestry, it is no longer about being from a specific population but instead, each person's ancestry is defined by the location they're from. Now ancestry is a continuum."

The team reports the development of a simple probabilistic model for the spatial structure of genetic variation, with which they model how the frequency of each genetic variant changes as a function of the location of the individual in geographic space (where the gene frequency is actually a function of the x and y coordinates of an individual on a map).

"If the location of an individual is unknown, our model can actually infer geographic origins for each individual using only their genetic data with surprising accuracy," said Wen-Yun Yang, a UCLA computer science graduate student.

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Researchers develop new genetic method to pinpoint individuals' geographic origin

ScienceDaily (May 25, 2012) Chromosomal deletions in DNA often involve just one of two gene copies inherited from either parent. But scientists haven't known how a deletion in one gene from one parent, called a "hemizygous" deletion, can contribute to cancer.

A research team led by Stephen Elledge, a professor in the Department of Genetics at Harvard Medical School, and his post-doctoral fellow Nicole Solimini, has now provided an answer. The most common hemizygous deletions in cancer, their research shows, involve a variety of tumor suppressing genes called STOP genes (suppressors of tumorigenesis and proliferation) that scatter randomly throughout the genome, but that sometimes cluster in the same place on a chromosome. And these clusters, said Elledge, who is also a professor of medicine at Brigham and Women's Hospital, tend to be deleted as a group. "Eliminating the cluster gives a bigger bang for the deletion buck," he said.

This finding is especially interesting in light of the two-hit model of cancer formation, which holds that both copies of a recessive gene need to be inactivated to trigger a biological effect. Thus the loss of a single tumor suppressor copy should have little or no influence on tumor cell proliferation because the remaining copy located on the other chromosome is there to pick up the slack.

Elledge's research points to a different hypothesis, namely that STOP genes in a hemizygous deletion aren't recessive but are instead haploinsufficient, meaning that they depend on two copies to function normally. "If a tumor suppressor is haploinsufficient, then a single gene copy lacks the potency needed to fully restrain tumorigenesis," Elledge explained, who is also a Howard Hughes Medical Institute Investigator. "So by removing clusters of haploinsufficient genes all at once, the cancer cell immediately propels its growth forward without having to wait for the other copies to also be lost."

Angelika Amon, a professor of biology at the Massachusetts of Technology, said she's surprised by the findings. "We've known from a lot of human syndromes that haploinsufficiency is widespread in the development of complex multicellular organisms," she said. "But these data show it's also critical for individual cells and cell proliferation."

The results also offer a different take on the two-hit model in carcinogenesis, Amon said. Being remarkably unstable, cancer cells can delete gene copies at every turn of the corner. If the loss of a single tumor suppressor copy provides no survival advantage for the tumor, then the tumor has no incentive to retain the cell with that deletion. But if the loss of that copy boosts proliferation, then the probability of a second hit later is greatly increased. "So haploinsufficiency is a way for the cancer cell to dramatically accelerate the acquisition of growth beneficial mutations," Amon said.

In other words, all it takes is a 50 percent reduction in gene activity for a cancer cell to grow. "That tells us it's a lot easier to get cancer than we might have hoped," Amon said.

According to Elledge, the number of hemizygotic deletions averages roughly six per tumor, with some tumors -- breast and pancreatic, for instance -- averaging up to ten. Each deletion involves 25 to 40 genes, many of them STOP genes, but also a few GO genes (growth enhancers and oncogenes) that enhance proliferation. That the STOP genes substantially outnumber their GO counterparts is important, Elledge explained, because it means cancer cells can tilt scales toward proliferation without also compromising it at the same time.

"The data reveal a lot of haploinsufficient players that have small effects individually, but large effects in combination," Elledge said. "Unfortunately, it's not easy to see how to take advantage of that chemotherapeutically."

What's important about the results, he emphasized, is that they open up new views on how tumors evolve. Moreso, they underscore the importance of proliferation as a fundamental feature of tumor growth, he added.

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Cancer may require simpler genetic mutations than previously thought

ASTANA, Kazakhstan, May 24, 2012 /PRNewswire/ --Sir Richard Roberts, the eminent British biologist and Nobel Prize laureate, said today European opposition to genetically modified organisms is political rather than scientific in nature.

He also said "personal medicine" based on human genome research holds large-scale promise to improve the health of the world's people on an individualized basis.

Roberts, who won the Nobel in 1993 for his shared discovery of split genes, made his remarks at the Astana Economic Forum, a global conference of scientists, academics, multinational executives and government leaders.

"On a political level, governments must embrace genetically modified organisms (GMOs) and not give way to European prophets of doom, who oppose the use of GMOs for purely political reasons," said Roberts. "It is important to note there is a complete absence of evidence that GMOs can cause any harm. Indeed to any well-informed scientist, traditionally bred plants seem much more likely to be harmful than GMOs."

Roberts predicted growing knowledge of the human genome will yield better medical treatments and diagnostics. "It is just as important that we learn more about the bacteria that colonize our bodies since they are an essential part of what it means to be human," he said.

He also predicated synthetic biology will enable scientists to build novel microorganisms from "scratch."

"Most exciting is the promise of stem cells where the challenge is to understand how they drive their differentiation into all of the other cell types in our bodies," Roberts said. "While I do not advocate prolonging life indefinitely, I am very much in favor of ensuring that as we age, the quality of our life does not diminish."

The annual Astana Economic Forum this year has drawn thousands of participants from more than 80 nations to this rapidly growing Central Asian nation. There has been much focus at the current sessions on the Greek financial crisis and turbulence in the Euro currency, in addition to the broader economic, scientific and international trade issues that are a traditional mainstay at Astana.

Deal making is a big part of both the official and the unofficial agenda at Astana. Multinationals represented include Chevron, Toyota, Nestle, Microsoft, BASF, Total, General Electric.

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Nobelist Speaks Out on Genetic Modification, Synthetic Biology, Stem Cell Research