NIDDK huge information applications assist to boost, share new analysis in diabetes

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March 21, 2021

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Rodgers G. Diabetes Research in the Age of Big Data: The NIDDK Perspective. Presented at: Endocrine Society Annual Meeting; March 20-23, 2021 (virtual meeting).

Disclosure:
Rodgers does not report any relevant financial information.

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According to a speaker at ENDO’s annual meeting, new digital tools and technology are being used to analyze big data and empower researchers to study diabetes in unprecedented ways.

Griffin P. Rodgers, MD, MACPThe director of the National Institute for Diabetes and Digestive and Kidney Diseases said big data – large, complex sets of data – are being used in several of the NIDDK’s programs to advance diabetes research in ways that were not possible in the past.

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“The NIDDK integrates big data tools and analytics to streamline and accelerate research in diabetes and other mission areas,” Rodgers told Healio. “With these technologies, we can harness large amounts of clinical, laboratory and diagnostic data in a way that is available to researchers and scientists across the country and around the world, so that they can better understand and develop treatments for diabetes and other diseases.”

Using Big Data to Improve Diabetes Research

During his talk, Rodgers discussed four NIDDK programs that use big data to analyze genes, beta cells, and more. In the TEDDY (The Environmental Determinants of Diabetes in the Young) study, researchers investigate how genes interact with environmental factors to determine environmental triggers for type 1 diabetes. More than 6,000 children who are genetically at high risk of developing type 1 diabetes are monitored in TEDDY from birth to 15 years of age. The study resulted in the collection of more than 3.2 million samples, and using advanced technology, thousands of genome, proteome and metabolome samples are analyzed.

Griffin P. Rodgers

“This approach will allow us to identify even the most subtle environmental and biological factors that distinguish children who later develop type 1 diabetes from those who don’t, so that one day we may prevent many cases of the disease can, “Rodgers said.

Another program is to test new preventive measures identified by TEDDY. The Type 1 Diabetes TrialNet is an international consortium for clinical trials aimed at delaying or preventing the progression of type 1 diabetes. More than 200,000 relatives of people with type 1 diabetes have been examined in studies for their suitability via TrialNet. TrialNet continues to screen more than 15,000 people each year.

The NIDDK has used big data to drive research on its Human Islet Research Network. As part of the human pancreas analysis program, researchers identify, collect, and characterize primary pancreatic tissue, beta cells, antibodies, and rare forms of islet dysfunction in type 1 diabetes. The imaging analysis of the samples allows researchers to see how cells interact with each other as type 1 diabetes progresses and could lead to new therapies for prevention or treatment.

NIDDK is also working to make big data more accessible. As part of the Accelerating Medicine Partnership’s type 2 diabetes program, a type 2 diabetes knowledge portal with DNA sequences and functional genomic, epigenomic and clinical data from type 2 diabetes studies with cardiac and kidney complications of hundreds of thousands was created Created by people all over the world.

“It was designed to turn data on genetic variations that contribute to diabetes into deeper insight into potential therapeutic targets and disease precursors,” said Rodgers.

Big data in the future

In order to continue working with Big Data in the future, the NIDDK offers various training programs to support future researchers. The organization supports awards and grants for research in bioinformatics. It also runs its Diabetes Medical Student Research Program, a summer program that has helped more than 900 students from more than 120 medical schools provide avenues to keep students in bioinformatics.

Rodgers believes that big data will continue to transform diabetes research in the future. The NIH recently launched the Precision Medicine Initiative to identify personalized, maximally effective treatments for individuals based on gene, environment and lifestyle. Additionally, according to Rodgers, the NIH All of Us program collects data from at least one million volunteers to reflect the diversity of the United States.

“In the future, these approaches could even eliminate the term ‘type 2 diabetes’ by letting us identify new subsets or forms of the disease that progress and / or respond in different and predictable ways to different therapeutic approaches,” Rodgers said. “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.”

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