APPLICATIONS
Sun Grid Engine Helps Find Fat Gene
I knew some of our work will be in the newspaper eventually, but I never thought that the media would focus on one particular finding, nor that half of the UK newspapers carried it on the front page�. Thanks to the Sun people and all the contributors for the good work on SGE. There is an important message in the study which is somewhat lost in media - that we found the FTO gene's influence on body mass because the gene is found to be associated with increased risk of type 2 diabetes. Type 2 diabetes contributes to the personal suffering of the patients - advanced patients can suffer from blindness and kidney failure - and to the National Health Service and the general health care infrastructure, government funding and other resources as a whole. It is especially important that one takes good care of his/herself, eat healthily and have regular exercise. A research paper on the main study is in the review process of a prestigious science journal, together with the type 1 diebetes follow-up paper as well. So hopefully we will probably hear more about it soon. The Case-Control Consortium is formed by researchers of about 8 disease groups. About two years ago some UK researchers thought of exploiting the increasing affordable genotyping technology to do whole-genome disease-association studies. To do it cost-effectively, they banded together (to use the same control groups for comparison - the national blood donor samples and the 1958 cohort - a government statistics of a random selection of people born in a particular week that year) to form the consortium, to share some of the logistic and technical expertise for the task. My boss, Professor David Clayton and our department head, Professor John Todd (www-gene.cimr.cam.ac.uk/todd/DIL.shtml) are two of the strongest driving force of the project. My "real" office is in the Diabetes and Inflammation Laboratory in Cambridge, and officially I belong to the WTCCC (statistical) analysis group, and have a special interest in identifying the genetic causes of Type 1 diabetes, among the 8 diseases. The biological phrase (sample collection/preparation) happened mostly before I joined the project. I was trained as a research physicist and had a few interesting years of academic research (in Cambridge), before I went off to as an IT contractor in the commercial telecom industry, and then driver and management software development with optical storage devices/jukeboxes for data archiving purposes (e.g. in banks, medical institutes, law-enforcements, etc). Just over a year ago, the project was recruiting for expertise required for the statistical analysis phrase of the project. I talked myself into the 2-year post I am currently in, despite not having a statistics background, just based on my having a reasonable research-level mathematics background and programming skills not usually found on scientific researchers. It has been an interesting year; I haven't managed to do as much statistics as I should be doing and I get side-tracked by computing issues easily; but on the other hand, I have been able to so some interesting and unusual things, like some low-level C-codes in the snpMatrix package www-gene.cimr.cam.ac.uk/clayton/software/ which we are writing during the last year for analyzing genotype data, and the grid engine improvements. In the open-source world, I am known to hang out with the ghost script folks and the linuxprinting.org folks, but the qmon GUI change is probably more related to CXterm http://sourceforge.net/projects/cxterm/, an orphaned piece of software I "adopted" with two other people, and some commercial Java programming background in the telecom area, and having played with haploview (www.broad.mit.edu/mpg/haploview/) helped too.
Obesity is a major cause of disease, associated with an increased risk of type 2 diabetes, heart disease and cancer. It is typically measured using body mass index (BMI). As a result of reduced physical activity and increased food consumption, the prevalence of obesity is increasing worldwide. According to the 2001 Health Survey for England, over a fifth of males and a similar proportion of females aged 16 and over in England were classified as obese. Half of men and a third of women were classified as overweight. Scientists from the Peninsula Medical School, Exeter, and the University of Oxford first identified a genetic link to obesity through a genome-wide study of 2000 people with type 2 diabetes and 3000 controls. This study was part of the Wellcome Trust Case Control Consortium, one of the biggest projects ever undertaken to identify the genetic variations that may predispose people to or protect them from major diseases. Through this genome-wide study, the researchers identified a strong association between an increase in BMI and a variation, or 'allele', of the gene FTO. Their findings are published online this week in the journal 'Science'. The researchers then tested a further 37 000 samples for this gene from Bristol, Dundee and Exeter as well as a number of other regions in the UK and Finland. The study found that people carrying one copy of the FTO allele have a 30 per cent increased risk of being obese compared to a person with no copies. However, a person carrying two copies of the allele has a 70 per cent increased risk of being obese, being on average 3 kg heavier than a similar person with no copies. Among white Europeans, approximately one in six people carries both copies of the allele. "As a nation, we are eating more but doing less exercise, and so the average weight is increasing, but within the population some people seem to put on more weight than others," explained Professor Andrew Hattersley from the Peninsula Medical School. "Our findings suggest a possible answer to someone who might ask 'I eat the same and do as much exercise as my friend next door, so why am I fatter?' There is clearly a component to obesity that is genetic." The researchers currently do not know why people with copies of the FTO allele have an increased BMI and rates of obesity. "Even though we have yet to fully understand the role played by the FTO gene in obesity, our findings are a source of great excitement," said Professor Mark McCarthy from the University of Oxford. "By identifying this genetic link, it should be possible to improve our understanding of why some people are more obese, with all the associated implications such as increased risk of diabetes and heart disease. New scientific insights will hopefully pave the way for us to explore novel ways of treating this condition." The findings were welcomed by Dr Mark Walport, Director of the Wellcome Trust. "This is an exciting piece of work that illustrates why it was so important to sequence the human genome," said Dr Walport. "Obesity is one of the most challenging problems for public health in the UK. The discovery of a gene that influences the development of obesity in the general population provides a new tool for understanding how some people appear to gain weight more easily than others. This discovery, along with further results expected from the Wellcome Trust Case Control Consortium later this year, will open up a wealth of new avenues to understand and treat common diseases." The FTO gene was first discovered whilst studying the DNA of a cohort of patients with type 2 diabetes. The risk of developing type 2 diabetes increases significantly for obese people. Through its effect on BMI, having one copy of the FTO allele increases the risk of developing type 2 diabetes by 25%, having two by 50%. "We welcome this result, which holds promise for tackling rising levels of obesity and the associated risk of developing type 2 diabetes," said Professor Simon Howell, Chair of Diabetes UK, which funded the original collection of samples from people with diabetes. "The discovery has been possible not only because of exemplary team work of scientists from a large number of institutions but also because of the cooperation of the 5000 diabetes patients and 37 000 people without diabetes who gave blood samples for the study."