Category Archives: Genetic Medicine

Public release date: 24-May-2012 [ | E-mail | Share ]

Contact: Marge Dwyer mhdwyer@hsph.harvard.edu 617-432-8416 Harvard School of Public Health

Boston, MA Harvard School of Public Health (HSPH) researchers have found that detailed knowledge about your genetic makeupthe interplay between genetic variants and other genetic variants, or between genetic variants and environmental risk factorsmay only change your estimated disease prediction risk for three common diseases by a few percentage points, which is typically not enough to make a difference in prevention or treatment plans. It is the first study to revisit claims in previous research that including such information in risk models would eventually help doctors either prevent or treat diseases.

"While identifying a synergistic effect between even a single genetic variant and another risk factor is known to be extremely challenging and requires studies with a very large number of individuals, the benefit of such discovery for risk prediction purpose might be very limited," said lead author Hugues Aschard, research fellow in the Department of Epidemiology.

The study appears online May 24, 2012 and will appear in the June 8, 2012 print issue of The American Journal of Human Genetics.

Scientists have long hoped that using genetic information gleaned from the Human Genome Project and other genetic research could improve disease risk prediction enough to help aid in prevention and treatment. Others have been skeptical that such "personalized medicine" will be of clinical benefit. Still others have argued that there will be benefits in the future, but that current risk prediction algorithms underperform because they don't allow for potential synergistic effectsthe interplay of multiple genetic risk markers and environmental factorsinstead focusing only on individual genetic markers.

Aschard and his co-authors, including senior author Peter Kraft, HSPH associate professor of epidemiology, examined whether disease risk prediction would improve for breast cancer, type 2 diabetes, and rheumatoid arthritis if they included the effect of synergy in their statistical models. But they found no significant effect by doing so. "Statistical models of synergy among genetic markers are not 'game changers' in terms of risk prediction in the general population," said Aschard.

The researchers conducted a simulation study by generating a broad range of possible statistical interactions among common environmental exposures and common genetic risk markers related to each of the three diseases. Then they estimated whether such interactions would significantly boost disease prediction risk when compared with models that didn't include these interactions since, to date, using individual genetic markers in such predictions has provided only modest improvements.

For breast cancer, the researchers considered 15 common genetic variations associated with disease risk and environmental factors such as age of first menstruation, age at first birth, and number of close relatives who developed breast cancer. For type 2 diabetes, they looked at 31 genetic variations along with factors such as obesity, smoking status, physical activity, and family history of the disease. For rheumatoid arthritis, they also included 31 genetic variations, as well as two environmental factors: smoking and breastfeeding.

But, for each of these disease models, researchers calculated that the increase in risk prediction sensitivitywhen considering the potential interplay between various genetic and environmental factorswould only be between 1% and 3% at best.

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Knowing genetic makeup may not significantly improve disease risk prediction

Washington, May 25 : Detailed knowledge about your genetic makeup'the interplay between genetic variants and other genetic variants, or between genetic variants and environmental risk factors'may only change your estimated disease prediction risk for three common diseases by a few percentage points, which is typically not enough to make a difference in prevention or treatment plans, say researchers.

The study by Harvard School of Public Health (HSPH) researchers is the first to revisit claims in previous research that including such information in risk models would eventually help doctors either prevent or treat diseases.

'While identifying a synergistic effect between even a single genetic variant and another risk factor is known to be extremely challenging and requires studies with a very large number of individuals, the benefit of such discovery for risk prediction purpose might be very limited,' said lead author Hugues Aschard, research fellow in the Department of Epidemiology.

Scientists have long hoped that using genetic information gleaned from the Human Genome Project and other genetic research could improve disease risk prediction enough to help aid in prevention and treatment. Others have been skeptical that such 'personalized medicine' will be of clinical benefit.

Still others have argued that there will be benefits in the future, but that current risk prediction algorithms underperform because they don't allow for potential synergistic effects'the interplay of multiple genetic risk markers and environmental factors'instead focusing only on individual genetic markers.

Aschard and his co-authors, including senior author Peter Kraft, HSPH associate professor of epidemiology, examined whether disease risk prediction would improve for breast cancer, type 2 diabetes, and rheumatoid arthritis if they included the effect of synergy in their statistical models. But they found no significant effect by doing so.

'Statistical models of synergy among genetic markers are not 'game changers' in terms of risk prediction in the general population,' said Aschard.

The researchers conducted a simulation study by generating a broad range of possible statistical interactions among common environmental exposures and common genetic risk markers related to each of the three diseases. Then they estimated whether such interactions would significantly boost disease prediction risk when compared with models that didn't include these interactions since, to date, using individual genetic markers in such predictions has provided only modest improvements.

For breast cancer, the researchers considered 15 common genetic variations associated with disease risk and environmental factors such as age of first menstruation, age at first birth, and number of close relatives who developed breast cancer.

For type 2 diabetes, they looked at 31 genetic variations along with factors such as obesity, smoking status, physical activity, and family history of the disease. For rheumatoid arthritis, they also included 31 genetic variations, as well as two environmental factors: smoking and breastfeeding.

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Genetic information may not significantly improve disease risk prediction

ScienceDaily (May 23, 2012) A team of scientists from the German Primate Center (DPZ), led by Dr Christian Roos, have completed genetic studies on all five snub-nosed monkey species, providing crucial information for the conservation of these rare primates.

The Myanmar snub-nosed monkey, discovered by a team from Fauna & Flora International (FFI), Biodiversity and Nature Conservation Association (BANCA) and People Resources and Conservation Foundation (PRCF) in 2010, has been of particular interest, given recent efforts in developing a conservation plan and protected areas within Myanmar, to ensure the survival of the species.

Previous scientific descriptions were based on information from Dr Thomas Geissmann's taxonomic description, but the Myanmar snub-nosed monkey, or Rhinopithecus strykeri, is now confirmed as its own species.

Dr Christian Roos, with colleagues from Switzerland, USA, China, Myanmar and Vietnam analysed the DNA of all five snub-nosed monkey species currently known to science. The genetic material was isolated from faecal samples and skin fragments, cut out from museum exhibits. "We can indeed confirm that the Myanmar Snub-Nosed Monkey is a new species," says Christian Roos.

"Even more exciting, however, is the information we gained about the evolutionary history of the species as it allows us insights into primate evolution and speciation," Christian Roos says.

Biogeographic processes, like the raising of the Himalayas altered the landscape profoundly and created new physical and climatic barriers that certain species could not cross anymore. Therefore, gene flow was hampered and new species developed. However, the barriers were not constant over geological times and species started mixing again, resulting in hybridisation, that is the production of offspring between separate species. "Hybridisation is much more frequent than generally thought, making it necessary to adjust our species concept profoundly," said Roos.

Next steps for ensuring the survival of the Myanmar snub-nosed monkey have now been put in place. The current political situation in Myanmar provides a unique opportunity for science and nature conservation but poses all the threats that come with accelerated economic and population growth. "This historic chance for democracy and development may also be a crossroad for nature conservation," says Frank Momberg, FFI's Myanmar Programme Director. With economic growth leading to an increase in roads being built and more forests being cleared, "there is also the one-time chance of implementing protected areas, which the government has now agreed to, and to conduct research that was hampered for years. Myanmar is only now opening to the world." Momberg continues.

Yet to be classified on the IUCN Red List, it is expected the Myanmar snub-nosed monkey will be listed as Critically Endangered, with only an estimated 260 to 330 of the species in existence and all closely related monkeys classified as Endangered or Critically Endangered.

Hunting for food and traditional medicine as well as accelerated deforestation are the main threats for these enigmatic animals. In reaction to the discovery and population estimates, the Ministry of Environmental Conservation and Forestry and FFI organised an international workshop for the conservation of the Myanmar snub-nosed monkey in February this year.

The outcomes of the workshop were very positive, with the Myanmar government now planning to protect the species under Myanmar law and to protect its habitat by creating a new national park in the Imawbum mountain range. In addition, FFI has started a community-based conservation programme on the ground, which provides alternative livelihoods to local indigenous hunters and operates a community ranger programme to protect the species.

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Genetic study sheds light on evolution and may help prevent extinction of the Myanmar snub-nosed monkey

May 23, 2012

Isabel Teotonio

In a landmark study examining the smoking behaviour of more than 32,300 African Americans, researchers have identified a genetic marker linked to how much a person smokes.

The findings of the study, which were published Tuesday in Translational Psychiatry, may prove useful in helping develop treatments to help smokers butt out.

This kind of research has been done in the past on white populations, but studying those who are non-European is important given their greater genetic diversity.

If we want to think about a future where we can use biological markers and psychosocial history to really tailor treatments, we need to understand the genetic architecture of smoking in multiple populations, said clinical associate professor of medicine at Stanford University Sean David, the studys lead author.

We havent found the cure to smoking with this study, said David, referring to the Study of Tobacco in Minority Populations Genetics Consortium, called STOMP. But we have found an informative genetic marker of smoking quantity that we think could inform future research to help move the field forward.

Researchers combined the findings of 13 previous studies, which provided a sample size of 32,389 men and women of African ancestry. This enabled them to better see links that may have been too subtle to spot in smaller studies. Genome-wide association studies are used to identify common genetic factors that influence health and disease.

The STOMP study, which included 78 researchers from 50 academic institutions across the United States, is the first meta-analysis of genome-wide association studies for smoking behaviours in African Americans. (Meta-analysis is a statistical technique for combining the results of independent studies.)

Investigators gathered a variety of data, including when people smoked their first cigarette, when they began smoking regularly and if they were heavy, or light, smokers.

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Genetic marker predicts smoking behaviour in African Americans

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.

"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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New genetic method pinpoints geographic origin

Public release date: 22-May-2012 [ | E-mail | Share ]

Contact: Dina Basin dina.basin@sri.com 650-862-1657 SRI International

In a step toward understanding possible genetic differences in smoking behaviors, a team of researchers co-led by SRI International has identified a genetic marker associated with smoking quantity in people of African ancestry. The study's findings may help guide future public health decisions related to smoking, because the more people smoke, the higher their risk of lung cancer.

The genetic variant, called rs2036527, appears to function as a marker of smoking quantity in African Americans, predicting the number of cigarettes smoked per day. It is on the same nicotine receptor gene, located on Chromosome 15, as another marker previously identified in people of European descent. Earlier studies have also shown that this gene plays a role in limiting nicotine intake by affecting how pleasurable nicotine is, which in turn affects how much nicotine is consumed.

Findings from the Study of Tobacco Use in Minority Populations (STOMP) Genetics Consortium study are published in the May 22, 2012 issue of Translational Psychiatry (part of Nature Publishing Group).

To find the genetic variants for smoking behavior, researchers combined 13 genome-wide association studies. The result included data for genetics and smoking behavior for more than 32,000 African Americans.

Although African Americans are less likely to smoke than European Americans, if they do start smoking, they tend to start smoking later in life, are less likely to quit smoking, and die more often from smoking-related lung cancer. Smoking is the leading cause of premature death among African Americans. STOMP investigators did not assess lung cancer risk, but other researchers have found that the genetic marker (rs2036527) is associated with risk of lung cancer in African Americans.

"This study may have implications for personalized medicine and the need to identify targets for drug discovery." said Sean P. David, M.D., D.Phil., research physician and director of the Translational Medicine program in the Center for Health Sciences in SRI's Policy Division and also a family medicine physician and Clinical Associate Professor of Medicine at Stanford University School of Medicine. "However, we need to be careful not to draw conclusions about the degree to which a genetic variant associated with smoking quantity affects smoker's ability to quit. Future studies of smoking behavior, including smoking cessation clinical trials, should be performed in non-European ancestry groups, so that other informative biomarkers aren't missed."

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The STOMP study, done in collaboration with 78 researchers from dozens of academic institutions and the National Institutes of Health, is the first meta-analysis of genome-wide association studies of smoking behaviors among African Americans. Meta-analysis is a powerful technique that combines a number of similar research questions and studies. Using statistical techniques, researchers were able to find genetic linkages to smoking behaviors too subtle to see in small studies.

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Genetic marker may predict smoking quantity in African Americans