Nine steps to proteomic wisdom: A practical guide to using protein-protein interaction networks and molecular...

A major aim of proteomic profiling of disease is to uncover the mechanistic basis of a given pathology. High-throughput experimental techniques continue to advance rapidly, but are still plagued by high rates of false negatives, false positives, and other spurious findings. By reducing a disease profile to a subset of differentially expressed proteins and determining functional over-representation, one can often make a reasonable first-pass assessment as to what might be happening in disease. Integrating mRNA expression patterns together with prior knowledge of protein-protein interaction networks and biological pathway information goes a step further, providing clues into the core processes that are aberrant in the disease state, and indicating which cellular functions are activated or repressed as a maladaptive pathophysiological response. This multi-step framework allows one to hypothesize as to possible cause and effect of pathology, and highlights potentially instructive pathways or sub-networks for subsequent experimental validation. Indeed, efficiently exploiting data regarding the myriad of physical and genetic interactions among expressed gene products, in parallel with the systematic sampling of genetic variation among diverse human populations, promises to revolutionize our current understanding of disease action at a deeper molecular level.