Abstract
BACKGROUND: Obesity is a medical condition that is known for increased body mass index (BMI). It is also associated with chronic low level inflammation. Obesity disrupts the immune-metabolic homeostasis by changing the secretion of adipocytes. This affects the end-organs, and gives rise to several diseases including type 2 diabetes, asthma, non-alcoholic fatty liver diseases and cancers. These diseases are known as co-morbid diseases. Several studies have explored the underlying molecular mechanisms of developing obesity associated comorbid diseases. To understand the development and progression of diseases associated with obesity, we need a detailed scenario of gene interactions and the distribution of the responsible genes in human system. RESULTS: Obesity and Co-morbid Disease Database (OCDD) is designed for relating obesity and its co-morbid diseases using literature mining, and computational and systems biology approaches. OCDD is aimed to investigate the genes associated with comorbidity. Several existing databases have been used to extract molecular interactions and functional annotations of each gene. The degree of co-morbid associations has been measured and made available to the users. The database is available at http://www.isical.ac.in/~systemsbiology/OCDD/home.php. CONCLUSIONS: The main objective of the database is to derive the relations among the genes that are involved in both obesity and its co-morbid diseases. Functional annotation of common genes, gene interaction networks and key driver analyses have made the database a valuable and comprehensive resource for investigating the causal links between obesity and co-morbid diseases.