Genome Studies Identify Lifestyle Risks for Diseases
News Feb 17, 2016
The technique is employed to identify biological pathways - the series of actions and changes that have occurred in cells and genetic material - that can be linked to the causation of a disease.
A team of researchers from the University of Bristol and Oxford University have suggested that a GWAS for a disease should also identify genetic variants that predict behaviours that increase the risk of the disease as well. If this is the case, GWAS may be useful places to look for potentially modifiable risk factors for disease, which could then be targeted by medics for interventions.
Professor Marcus Munafo, the study's lead author, said: "Genome-wide association studies of lung cancer have identified genetic variants that strongly predict smoking. It is possible these genetic variants have independent effects on both smoking and lung cancer, but it seems far more likely that this variant was seen because smoking causes lung cancer.
"Genetic predictors for lifestyle are still being identified. We already know about variants that predict smoking, alcohol or caffeine use, and research is ongoing to predict things like cannabis use. As larger GWASs of disease are carried out, more of these variants which indicate the causal modifiable risk factors for disease will be identified. This will help the development of more effective and better-targeted interventions.
"These discoveries really underline how valuable the investment in genetic studies is - more so than is often thought. Genetic studies can not only identify the biological risk factors for disease, but the behavioural risk factors as well"
Mechanism Controlling Multiple Sclerosis Risk IdentifiedNews
Researchers at Karolinska Institutet have now discovered a new mechanism of a major risk gene for multiple sclerosis (MS) that triggers disease through so-called epigenetic regulation. They also found a protective genetic variant that reduces the risk for MS through the same mechanism.
Synthetic DNA Shuffling Enzyme Outpaces Natural CounterpartNews
A new synthetic enzyme, crafted from DNA rather than protein, flips lipid molecules within the cell membrane, triggering a signal pathway that could be harnessed to induce cell death in cancer cells. Researchers say their lipid-scrambling DNA enzyme is the first in its class to outperform naturally occurring enzymes – and does so by three orders of magnitudeREAD MORE
Antarctic Worm and Machine Learning Help Identify Cerebral Palsy EarlierNews
A research team has released a study in the peer-reviewed journal BMC Bioinformatics showing that DNA methylation patterns in circulating blood cells can be used to help identify spastic cerebral palsy (CP) patients. The technique which makes use of machine learning, data science and even analysis of Antarctic worms, raises hopes for earlier targeted CP therapies.