Friday, February 17, 2012
Inactive genes surprisingly common in humans
(Medical Xpress) -- Every person carries on average 100 variants that disable genes - yet very few suffer ill effects, an international team of researchers led by Yale University and Wellcome Trust Sanger Institute report in the Feb. 17 issue of the journal Science.Scientists were surprised to find so many of these variants in healthy individuals because loss of gene functions leads to diseases such as cystic fibrosis and muscular dystrophy. The findings will allow researchers to better pinpoint new disease-causing mutations by helping them differentiate between frequently occurring but harmless genetic variants and rare dangerous ones, the authors say.
The study is the latest coming from the 1000 Genomes Project, a massive international personal genomics effort aiming to provide a comprehensive resource of human genetic variation that will help speed the development of personalized therapies based on the genetic makeup of patients.
The team analyzed the genomes of 185 individuals from Europe, Asia, and Africa looking for so-called loss-of-function variants, mutations that disable a gene’s ability to make protein.
“Even though previous studies have shown that loss-of-function variants exist in the general population, their extent has been underappreciated. This is the first time we have a definite sense of variation in the numbers of functional genes between individuals,” said Suganthi Balasubramanian, the lead Yale author in the paper.
The study shows no individual has a full complement of functional genes. On average, each individual has 20 genes where both copies of the gene are disabled.
“In total, this study identified 253 such genes. This means at least one percent of human genes can be shut down without causing serious disease,” explains Mark Gerstein, Albert L. Williams Professor of Biomedical Informatics, co-senior author from Yale University.
The catalog of loss-of-function variants in healthy genomes will be invaluable to clinicians as they begin to use personalized genomic analysis to help diagnose and treat disease, the authors say.
“Our research will be beneficial for current DNA sequencing studies underway in disease patients,” says Dr Chris Tyler-Smith, co-senior author from the Wellcome Trust Sanger Institute. “The common loss-of-function variants were typically in genes that can be shut down without causing serious effects.”
Scientists also found a large number of extremely rare variants and “we believe these will be the most interesting cases in terms of a potential role in human disease,” says Dr Daniel MacArthur from the Wellcome Trust Sanger Institute, lead author on the study.
The study also showed that as many as a quarter of the loss-of-function variants involve large stretches of DNA (so-called structural variants), rather than mutations of single base pairs, which were believed to be the primary source of genetic variation. Structural variants are not yet well characterized in the human population and represent a major Yale contribution to 1000 Genomes Project. The Yale team is also looking at variants outside of regions of DNA that code for genes, an area that constitutes the vast majority of the genome.
More information: "A Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes," by D.G. MacArthur, Science, 2012.
Provided by Yale University
"Inactive genes surprisingly common in humans." February 16th, 2012. http://medicalxpress.com/news/2012-02-inactive-genes-surprisingly-common-humans.html
Posted by
Robert Karl Stonjek
Robert Karl Stonjek
Aging studies suggest older people are happier
Lab manager Julia Harris (right) places glasses with a mobile tracking device on Derek Isaacowitz, associate professor of psychology, in the Lifespan Emotional Development Lab (LEDlab). Credit: Mary Knox Merrill.(Medical Xpress) -- We get wrinkles. Our hair turns gray, or we lose it altogether. Our job prospects diminish and our chances of incurring disease increase. Researchers across the globe focus their efforts on increasing our life span because so many of us believe getting old stinks.
But that may not be so, according to Derek Isaacowitz a newly appointed associate professor of psychology in the College of Science. Contrary to popular opinion, he says, older people are happier than their younger counterparts.
“Self-report studies of happiness typically find that older people are happier,” Isaacowitz explains. But for the psychologist, who joined the Northeastern faculty after spending a decade at Brandeis, self-reporting is not enough. He wants to know why older people are happier.
To tackle this question, he employs a state-of-the-art testing method not typically used in aging research: eye tracking.
Eye tracking, he says, follows a participant’s eye movements by taking 60 snapshots of his or her pupils each second. Isaacowitz couples self-reports of mood with eye tracking data to pinpoint exactly what a person is looking at while rating his or her mood.
“We can analyze data in a moment to say, ‘how does what you’re looking at relate to what you feel?’” Isaacowitz says.
Results revealed that older and younger participants might regulate their emotions in vastly different ways. As Isaacowitz puts it, “One way of regulating emotion is to change your thinking about something, to see something upsetting and say ‘no’.” This seems to be the strategy of most younger test subjects.
On the other hand, older people tend to look at negative images less often, possibly indicating that they regulate emotion by distracting themselves from negative stimuli.
Isaacowitz says this makes sense, since the elderly tend to have fewer resources than the young: “If I made you really tired or gave you something else to do, it would be easier to distract instead of reappraise.”
While Isaacowitz’ research has already confirmed a cognitive difference between older and younger people, many questions remain about how this difference may relate to the role of age in regulating day-to-day emotion.
Isaacowitz was eager to join the Affective Science Institute at Northeastern and help advance the university’s strength in aging research. He says his lab on campus will conduct a number of new studies, including an analysis of subjects in a more natural environment. “We’ll be nicely set up to do that in the lab here,” he says.
Provided by Northeastern University
"Aging studies suggest older people are happier." February 16th, 2012. http://medicalxpress.com/news/2012-02-aging-older-people-happier.html
Posted by
Robert Karl Stonjek
Robert Karl Stonjek
Computer programs may be able to identify individuals most at risk of anxiety, mood disorders
An MRI scan of the sagittal section of the brain. Credit: Wellcome Images.
(Medical Xpress) -- Computer programs can be taught to differentiate between the brain scans of healthy adolescents and those most at risk of developing psychiatric disorders, such as anxiety and depression, according to research published yesterday in the open access journal PLoS ONE. The research suggests that it may be possible to design programs that can accurately predict which at-risk adolescents will subsequently develop these disorders.
There are no known biomarkers - biological measures - that can accurately predict future psychiatric disorders in individual adolescents. Even genetic risk cannot accurately predict individual risk for future psychiatric illness: for example, a family history of bipolar disorder confers a 10 per cent risk of future bipolar disorder, as well as a 10 to 25 per cent risk of disorders such as attention deficit hyperactivity disorder, major depression and anxiety disorders, but it is impossible to accurately determine whether an individual will develop these disorders.
The early identification of individuals at high risk of future psychiatric illness is critical. Most psychiatric disorders typically have an onset in adolescence or early adulthood, and early detection and treatment could potentially delay, or even prevent, the onset of these illnesses in high-risk adolescents.
Now, a team of researchers led by Dr Janaina Mourao-Miranda, a Wellcome Trust Research Career Development Fellow at UCL (University College London), has shown that computer programs can distinguish between brain scans of healthy but genetically at-risk adolescents and healthy low-risk controls.
Sixteen healthy adolescents who each had a parent with bipolar disorder took part in the study, along with 16 healthy adolescents whose parents had no history of psychiatric illness. The adolescents performed an emotional face gender-labelling task in a functional magnetic resonance imaging (fMRI) scanner, which measures activity in the brain.
In the first experiment, the faces presented had happy or neutral expressions; in the second experiment, the faces had fearful or neutral expressions. The researchers then used a computer program capable of machine learning to predict the probability that an individual belonged to the low-risk or the at-risk group.
They found that the program was accurate in three out of four cases. The predictive probabilities were significantly higher for at-risk adolescents who subsequently developed a psychiatric disorder, such as anxiety and depression, than for those who remained healthy at follow-up. This suggests that it may be possible, in time, to develop a computer program able to identify those individuals at greatest risk of developing psychiatric disorders.
Interestingly, the researchers found that the best discrimination between at-risk and low-risk adolescents occurred when neutral faces were presented in the happy face experiment. This supports previous studies that suggest that individuals diagnosed with anxiety or mood disorders are more likely to perceive neutral faces as ambiguous or potentially threatening.
"Combining machine learning and neuroimaging, we have a technique which shows enormous potential to help us identify which adolescents are at true risk of developing anxiety and mood disorders, especially where there is limited clinical or genetic information," says Dr Mourao-Miranda.
Coauthor Professor Mary Phillips, from the Clinical and Translational Affective Neuroscience Program at University of Pittsburgh, adds: "Anxiety and mood disorders can have a devastating effect on the individuals concerned and on their families and friends. If we are able to identify those individuals at greatest risk early on, we can offer early and appropriate interventions to delay, or even prevent, onset of these terrible conditions."
The study was funded by the National Institute of Mental Health, the Wellcome Trust and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazil).
More information: Mourao-Miranda J et al. Pattern recognition and functional neuroimaging help to discriminate healthy adolescents at risk for mood disorders from low risk adolescents. PLoS One 2012 (epub ahead of print).
Provided by Wellcome Trust
"Computer programs may be able to identify individuals most at risk of anxiety, mood disorders." February 16th, 2012.http://medicalxpress.com/news/2012-02-individuals-anxiety-mood-disorders.html
Posted by
Robert Karl Stonjek
Robert Karl Stonjek
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