T2DiACoD
Type-2 diabetes Mellitus, a metabolic disease is on the rise affecting increasing number of people worldwide. The rapid growth of data arising from intense investigation in this area necessitates systematic collection and organization of information for further studies. It has been documented that more than 371 million people have diabetes with China being the leading country affected with diabetes (92.3M) followed by India (63M) and USA (24.1M). The risk factors for Type 1 diabetes are still being investigated but there are several risk factors for Type 2 diabetes Mellitus - hereditary, obesity, physical inactivity, age, impaired glucose tolerance. Also, the complications of diabetes like atherosclerosis, diabetic retinopathy, and diabetic nephropathy have also increased over time due to the increased exposure of glucose to the tissues.
To this end we have first embarked upon collecting the genes and their variants with evidential role for pre-disposition for diabetes. Because the number of the genes varies in two dimensions of risk factors and population types we have designed our data collection by considering both these factors. To the best of our knowledge, our effort appears maiden when compared to some efforts carried out about 5 years ago elsewhere in the world. Two such resources in this regard are T2D-Db and T2DGADB. In addition, our collection examines for evidential role of genes and their variants to cause other complex disorders in diabetic patients
Our comprehensive collection named Type 2 Diabetes Mellitus and Associated Complex Disorder (T2-DiACoD), contains updated genes classified on the basis of various risk factors (obesity, inflammation, stress, diet) that progress to diabetes and its associated complex disorders (atherosclerosis, diabetic nephropathy, diabetic retinopathy, diabetic neuropathy). It also includes classification of genes studied in different population. The microRNAs leading with potential causation role in diabetes are also considered and compiled. This would help users to identify genes playing role in the pathogenesis of diabetes under various risk factors and associated complications. The database includes complete gene information with manually curated supporting evidence (PubMed references) for the genes included in the database.