Program Highlights

The ENIGMA Consortium Maps the Brain’s Gray Matter in People with Bipolar Disorder

Bipolar Brain ImagingBipolar disorder, which affects 1-3% of the adult population, is a disorder of the brain that results in extreme shifts in mood from periods being extremely “up” (manic episodes) to extremely “down” (depressive episodes). Despite bipolar disorder being a common disease, not much is known about the biological mechanisms that lead to it.

In the largest ever imaging study of bipolar disorder, the ENIGMA consortium, a BD2K Center of Excellence, found that the gray matter in particular sections of the brain in people with bipolar disorder is thinner than in healthy individuals. Gray matter covers the surface of the brain and is where the bodies of the brain’s nerve cells are located. This study, which was a collaboration between 79 institutions worldwide, analyzed the MRI scans of 6503 individuals in order to control for variables such as age, sex, prescribed medications, and duration and type of disease. The researchers found that the thinning effect was greater the longer people had the disease and some of the medications used to treat bipolar disorder seemed to protect against thinning. The results of this study could be used to evaluate the effectiveness of treatments and aid in early detection and intervention.

Reference:

Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group. Hibar DP, Westlye LT, Doan NT, et al. Mol Psychiatry. 2017 May 2; doi: 10.1038/mp.2017.73.

 

Making Data FAIR: Findable, Accessible, Interoperable, and Reusable

Members of the data science community recently published a comment article in Scientific Data describing guiding principles for scientific data management and stewardship. Read the article  to learn more about this important effort and how the NIH Big Data to Knowledge (BD2K) initiative is contributing to it.

 

Sustaining the Big-Data Ecosystem

More efficient models are needed for storing, organizing, and accessing biomedical big-data. Read this Nature Outlook perspective (note that full text may require institutional journal access) by the NIH Associate Director for Data Science, Dr. Philip E. Bourne, and the Directors of two NIH Institutes Drs. Lorsch and Green, to learn how the NIH is approaching this issue.

 

Philip Bourne Stanford Big Data 2014Dr. Philip Bourne on Biomedical Big Data

Click on the image to watch a brief video of NIH Associate Data Director Dr. Philip Bourne explaining NIH efforts to coordinate strategies related to computation and informatics in biomedicine across its 27 institutes and centers​.

 

Learn More about the BD2K Initiative and Meet each of its Centers of Excellence:

"NIH Launches a United Ecosystem for Big Data" from Biomedical Computation Review.

 

NIH Invests Almost $32 Million to Increase Utility of Biomedical Research Data:

NIH invests almost $32 million to increase utility of biomedical research dataOn October 9, 2014, the NIH announced the first grants to be issued through the Big Data to Knowledge initiative. Click on the image at the right to read the Press Release.

The NIH Common Fund is contributing support to BD2K efforts involved with:

  • Open Educational Resouces for Biomedical Big Data
  • Courses for Skills Development in Biomedical Big Data Science
  • Mentored Career Development Award in Biomedical Big Data Science for
    Clinicians and Doctorally Prepared Students
  • BD2K-LINCS-Perturbation Data Coordination and Integration Center (DCIC)
  • Development of an NIH Data Discovery Index Coordination Consortium

View the Common Fund-supported BD2K research here. View all the BD2K grants awarded in Fiscal Year 2014 here.

 

Perspective Paper by BD2K Members Describes the Initiative's Purpose and Goals:

"The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data​"

This article by members of the NIH BD2K initiative explains how the NIH is planning to better understand and mine biomedical 'big data' to advance knowledge and promote discovery.

This page last reviewed on May 24, 2017