“The brain is more than an assemblage of autonomous modules, each crucial for a specific mental function. Every one of these functionally specialized areas must interact with dozens or hundreds of others, their total integration creating something like a vastly complicated orchestra with thousands of instruments, an orchestra that conducts itself, with an ever-changing score and repertoire.“
- Oliver Sacks: The Mind’s Eye
The CommonMind Consortium has as a goal to generate and analyze large scale data from human subjects with neuropsychiatric disorders and to make this data and the analytical results broadly available to the public as a free resource. We welcome participation in our data generation efforts through funding, or “in kind” data or samples. A modular design will be used to expand scope according to funding and data will be released one year after generation. Contact us at info@CommonMind.org.
As many as 450 million people worldwide are believed to be living with a mental or behavioral disorder: schizophrenia and bipolar disorder are two of the top six leading causes of years lived with disability according to the World Health Organization. The burden on the individual as well as on society is significant with estimates for the health care costs for these individuals as high as four percent GNP. This highlights a grave need for new therapies to alleviate suffering.
Technology has reached a level of maturity where generation of large scale molecular data is feasible, enabling a better understanding of the molecular underpinnings of these disorders. CommonMind consists of a multi-faceted team with expertise in the generation, management, and analysis of this data.
A central tenant of this project is that biological insights stemming from integrative genomic analysis are most compelling when they leverage the expertise across multiple disciplines and provide a transparent, reproducible description of analytical process. As such, the consortium has committed to making all data, analytical results, and methodological source code available to the public. The goal of this is to provide the opportunity for researchers to assess the quality of the data and results in order to (1) estimate the likelihood of our biological conclusions and (2) determine the most meaningful way of incorporating these findings into their own research.
Public release of data will take place through the Sage Bionetworks Synapse system and dbGAP. A description of current data generation efforts can be found under the Data Generation tab, where links to public releases will be posted.