Studies on complex genetic disorders are generally driven by statistical and computational methods, and not by considerations about the deficits in the underlying biological processes that contribute to these disorders. Moreover, the few studies that have tried to find functional connections between the top genes for these disorders have only cited the results from analyses through currently (commercially) available bioinformatics-based, pathway-building programs. These types of analyses are very ‘superficial’ and usually not really informative, as the programs that produce them still have important limitations, e.g. due to the current incompleteness of the functional annotation of the human genome.
Our ‘molecular landscape building approach’ is hypothesis free, and we take advantage of and handle the available GWAS and other genetic data in a different way than others do. We do use gene-enrichment and protein-protein interaction analyses, but it is only through subsequent and systematic manual literature analyses as well as the integration/addition of corroborating evidence that the actual landscapes are built. It has taken several years of research experience and fine-tuning to get our ‘molecular landscape building approach’ to its current form and usability.
Our approach is applicable to any complex genetic disorder and enables for the first time the identification of truly evidence-based and novel biomarkers and druggable targets that can lead to the development of new medications that – much more than is currently the case – specifically modulate the (disturbed) biological processes.
Despite the fact that a large amount of genetic data for most complex genetic disorders has now been available for several years, an effective approach of integrating evidence for these disorders has not yet been developed. Given the currently available data and knowledge, we thus strongly think that our ‘molecular landscape building approach’ is the best solution to find true and disorder-specific biomarkers and druggable targets. Furthermore, extensive background knowledge and ‘landscape building experience’ is required to implement the approach appropriately and successfully. The uniqueness of our approach is reflected by the quality of the international scientific journals in which our landscapes have been published thus far (journal impact factors 12-14).