New digital tools and technologies are being used to parse through big data and allow diabetes researchers to study diabetes in unprecedented ways, according to a speaker at the international ENDO annual meeting.

Dr Griffin Rodgers, director of the American National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), said big data, (large, complex datasets), is being used to further diabetes research in ways impossible until now.

Using big data to enhance diabetes research

“The NIDDK is integrating big data tools and analysis to help optimise and accelerate research in diabetes and other mission areas,” Dr Rodgers told Healio, a specialty clinical information website.

“These technologies allow us to harness vast amounts of clinical, laboratory and diagnostic data in a way that’s accessible to researchers and scientists around the country and the world to enable them to better understand and develop treatments for diabetes and other conditions.”

During his presentation, Dr Rodgers discussed programs that are using big data to analyze genes, beta cells and more.

In The Environmental Determinants of Diabetes in the Young study, or TEDDY, researchers are examining how genes interact with environmental factors to determine environmental triggers for type 1 diabetes. More than 6,000 children who are genetically at a high risk for developing type 1 diabetes are being followed from birth to age 15 years in TEDDY.

More than 3.2 million samples

The study has resulted in the collection of more than 3.2 million samples, and sophisticated technology is being used to analyse thousands of genome, proteome and metabolome samples.

“This approach will allow us to identify even fairly subtle environmental and biological factors that distinguish children who go on to develop type 1 diabetes from those who do not, so that one day we may be able to prevent many cases,” Dr Rodgers said.

Trials to delay or prevent t1 onset

Another program is set up to test new preventive efforts. The Type 1 Diabetes TrialNet is an international consortium for clinical trials to delay or prevent type 1 diabetes progression. Through TrialNet, more than 200,000 relatives of people with type 1 diabetes have been screened for eligibility in trials. TrialNet continues to screen more than 15,000 people per year.

Big data used in human islet research

Big data is also being used to advance research in the Human Islet Research Network. In the Human Pancreas Analysis Program, researchers are identifying, collecting and characterising primary pancreatic tissues, beta cells, antibodies, and rare forms of islet dysfunction in type 1 diabetes.

Imaging-based analysis of the samples allows researchers to see how cells interact with each other during type 1 diabetes progression and could lead to new therapies for prevention or treatment.

Diabetes knowledge portal

There is also a push to make big data more accessible.

A type 2 diabetes knowledge portal has been created with DNA sequences and functional genomic, epigenomic and clinical data from studies examining cardiac and renal complications from hundreds of thousands of people across the world.

“It was developed to turn data on genetic variations contributing to diabetes into a deeper insight into potential therapeutic targets and disease precursors,” Dr Rodgers said.

Big data in the future

Many institutions worldwide are developing research programs to identify personalised, effective treatments for individuals based on gene, environment and lifestyle factors.

“This knowledge could greatly improve our ability to treat and prevent diabetes and its complications by using the best available interventions and treatment goals for each individual patient,” he said.