Large Scale Genomics Data Network

Diabetes Clinical Knowledgebase

Diabetes is a chronic disorder of glucose metabolism and is a major cause of heart disease and end-stage renal disease in world populations. It is also the single biggest cause of preventable blindness, the leading cause of non-traumatic lower extremity amputation and major cause of premature mortality. 415 million people have diabetes globally and is expected to reach 642 million by 2040. Unhealthy lifestyle, genetic predisposition to diabetes and excessive weight are all risk factors for the onset of Type 2 diabetes. At MedGenome we have launched the Diabetome a knowledgebase of diabetes patients phenotypic and drug response data to enable cohort specific analyses for effective drug discovery.

With data from over 300,000 patients, researchers have access to demographics, clinical characteristics, biochemical results, family history, treatment history, drug responses, genotypes as well as secondary complications of diabetes. Diabetome facilitates the study of a large number of familial cases over multiple generations, and provides information on trio and first degree relatives affected families, as well as consanguineous families, and comprehensive phenotype, genotype and family pedigree information via pedigree charts with age of onset.

Diabetome utilizes an IDRS based scoring system for risk assessment. Researchers benefit from longitudinal views of individual laboratory profiles and descriptive statistical tools to summarize the data. The association of these individual criteria is more readily accessible, providing an efficient and responsive scientific discovery platform for researchers.

To know more about Diabetome click here for the whitepaper  

Key features include

  • Access to patients phenotype, biochemical and familial data
  • Data on risk factors and complications associated with diabetes
  • Data available to build predictive models on likelihood of developing diabetes
  • Data on drug responses and ability to stratify patients into responders and non-responders and query for underlying mechanisms of difference in response
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