Genetic mutations can cause diseases. That’s been known for many decades. However, there are tens of thousands of known mutations that can happen to the human genome. Not all of them cause diseases. Also, it’s known that mutations that have an impact on biological processes usually rearrange the amino acids that build proteins. However, the actual chain of chemical events that lead from mutation to dysfunctional protein is generally not known at the molecular level. So, wouldn’t it be great if there was a database that catalogued most of the major known mutations, identified the amino acids most likely affected by them, and used computer modeling to make inferences about the kind of protein chemistry that would result? Yes, it would be great, and it has just been done. A massive team of researchers have put together a major reference tool for mutation research.
The research study focused on the ‘out of order’ amino acids, called amino acid substitutes (AAS), comparing the amino acids produced by mutated genes and those from normal genes. They looked for statistical differences between the percentage of mutations that shared a DNA site with both non-disease and disease-associated amino acid substitutes. Then they looked for changes in protein activity (enrichment or depletion) based on the type of AAS. This information was used to generate hypothetical molecular models for the mechanism of genetic disease. Over 40,000 amino acid substitutes were analyzed, the most comprehensive study of mutations to-date.
In today’s scientific world, big projects usually require big teams, often assembled from many institutions. This is clearly the case for the mutations database and statistical modeling – lists like the following are not exciting reading, but this one is instructive:
The project involved collaborations with several organizations. Scientists from Cardiff University in the UK supplied the Human Gene Mutation Database (http://www.hgmd.org). Researchers at the Indiana University School of Informatics and Computing helped develop the statistical methods for measuring enrichment and depletion of the mutations. Scientists at the National Center for Biomedical Ontology at Stanford University mapped the disease names and provided a standard vocabulary for the work. Researchers at the Department of Biological Sciences at the University of Maryland collected the genetic data from the National Library of Medicine and formatted them for this study. All the analysis was done by scientists at the Buck Institute and Cardiff University.
The information provided by this study, including the on-line reference tool (Mutation Database) are intended to assist further research into the details of molecular changes in disease causing mutations. It will hopefully stimulate ideas and research that no one in the study had even thought about.