Abstract
BackgroundThe study of relationships between human diseases provides new possibilities for biomedical research. Recent achievements on human genetic diseases have stimulated interest to derive methods to identify disease associations in order to gain further insight into the network of human diseases and to predict disease genes.ResultsUsing about 10000 manually collected causal disease/gene associations, we developed a statistical approach to infer meaningful associations between human morbidities. The derived method clustered cardiometabolic and endocrine disorders, immune system-related diseases, solid tissue neoplasms and neurodegenerative pathologies into prominent disease groups. Analysis of biological functions confirmed characteristic features of corresponding disease clusters. Inference of disease associations was further employed as a starting point for prediction of disease genes. Efforts were made to underpin the validity of results by relevant literature evidence. Interestingly, many inferred disease relationships correspond to known clinical associations and comorbidities, and several predicted disease genes were subjects of therapeutic target research.ConclusionsCausal molecular mechanisms present a unifying principle to derive methods for disease classification, analysis of clinical disorder associations, and prediction of disease genes. According to the definition of causal disease genes applied in this study, these results are not restricted to genetic disease/gene relationships. This may be particularly useful for the study of long-term or chronic illnesses, where pathological derangement due to environmental or as part of sequel conditions is of importance and may not be fully explained by genetic background.
Highlights
The study of relationships between human diseases provides new possibilities for biomedical research
In Additional file 2 we report the top 30 biological processes associated with each disease cluster according to enrichment P-values calculated by the DAVID tool
Causal molecular mechanisms present a unifying principle for disease classification and definition, analysis of clinical disorder associations, as well as prediction of disease genes, therapeutic targets and diagnostic markers
Summary
The study of relationships between human diseases provides new possibilities for biomedical research. Recent achievements on human genetic diseases have stimulated interest to derive methods to identify disease associations in order to gain further insight into the network of human diseases and to predict disease genes. A major goal of medical research is to identify the molecular components which play a role in causing a pathological condition. Phenotype/genotype associations provide evidence for a role of affected gene products in respective causal mechanisms and extensive resources document medically relevant gene variants [2,3]. Recent studies on hereditary phenotypes have shown that similarities among disorders imply involvement of functionally related gene. It is clear that analysis of disease relationships unfolds new opportunities for both medical and biological research. Rzhetsky et al [9] analyzed associations among 161 diseases based on their co-occurrence in patient records
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