When personalized medicine is the next frontier for scientists, industry, and the general population, it is important to develop computational approaches that can lead to a better understanding of the etiology of disease. Integration of genetic and molecular information is a sensible step in this direction because it provides a structural and functional perspective to the human variation data.
In this study, we analyzed disease-associated and putatively neutral amino acid substitution data and found that about 4.5% of amino acid substitutions (3.9% of unique sites) may affect protein function through disruption of post-translational modifications. On the other hand, about 2% of neutral polymorphisms may be affecting post-translational modifications. These numbers further indicate that post-translational modifications are not the majority cause of human genetic disease. However, we have still found 238 post-translationally modified sites in human proteins whose mutation was causative of disease. In total, 1,289 modification sites were found to be in the close proximity to the inherited disease mutations and represent candidates for further experimental verification.
Given our data, there are several problems that could have lead to the ascertainment bias. For example, our data set of post-translational modifications was heavily skewed towards phosphorylation (79%), where mass spectrometry techniques have lead to a recent explosion in the number of identified sites. On the other hand, it may be argued that the modifications not identified using high-throughput methods may be more likely to be disease-relevant. It is also unclear whether the sets of inherited disease data is representative since it may be expected that genetic-association studies are more successful in identifying markers of monogenic diseases or familiar forms of complex diseases. Finally, the set of neutral polymorphisms is probably contaminated with yet undiscovered disease mutations and has not been controlled for population biases.
We also analyzed the enrichment and depletion of amino acid substitutions for each post-translational modification and found that most follow similar trends when inherited disease is compared to the neutral polymorphisms. These trends held for both experimentally verified modification sites and those transferred by homology. In the case of somatic mutations, we observed some interesting cases as well. For most examples, we have not found matches between post-translational modifications and observed somatic mutations. However, in the cases of methylation, phosphorylation and ubiquitination, there was an increased trend of disruption of post-translational modifications. Previous work has already addressed disruption of confidently predicted phosphorylation sites in cancer [20
]. Thus, the correspondence between actual sites and somatic mutations found in this study further supports this hypothesis.
While direct disruption of post-translational modifications is likely to have functional implications, the partial disruption of modified sites has a potential to lead to subtle phenotypic effects that may be more dependent on the variation present in other genes before causing organism-wide dysregulation. We believe that such changes are particularly fitting to the framework of complex disease and interaction between genetic and environmental factors.