Extensive computational analysis by a team of researchers has revealed that different genetic variants linked to a particular disease affect similar biological mechanisms - providing a model for predicting how individual genetic make up increases, or decreases disease risk
Large scale genomic studies in recent years have identified scores of genetic polymorphisms linked to an assortment of diseases including Alzheimer's, rheumatoid arthritis and and cancer. While this is a big step up, we still need to identify exactly how these each interact and disease risk.
Now 3 research teams from University of Arizona Health Sciences, University of Pennsylvania and Vanderbilt University, have developed a novel method for exploring the biological impact of these specific variants.
Sorting through the data
When mutations happen inside genes, it's much easier to study their effect. When they happen outside of coding sequences, their effects are harder to ascertain. When the researchers analysed these variants in combination, they discovered many of them affected shared crossover biological mechanisms like influencing the same cellular machinery, or promoting the same line of genes. When they applied this analysis to age-related disease like Alzheimer's and rheumatoid arthritis they found that independent variants often caused similar effects and that these could be worked out by computational analysis. This means we could work out how different combinations of specific polymorphisms co-ordinate together to affect disease risk.
"The discovery of these shared properties offer the opportunity to broaden our understanding of the biological basis of disease and identify new therapeutic targets"
Read more at EurekaAlert