Friday, July 18, 2014

Connectomes Related to Human Disease (U01)

NEI is participating in this Funding Opportunity Announcement. They are  interested in research in populations where the visual pathways may be compromised due to congenital or acquired disease, or injury (e.g. blindness, strabismus, amblyopia, and low vision). Cohorts of patients with visual disorders should be compared with normal age-matched controls. Studies of plasticity in the visual pathways associated with the loss or restoration of vision are of particular interest.  NIMH, NIA, NIAAA, NIDA and NINDS are also participating. See below for more details



Agency: NIH
Funding Opportunity Number: PAR-14-281
Title: Connectomes Related to Human Disease (U01)
Deadline: November 14, 2014; July 14, 2015; July 14, 2016

Summary:

Background:
There has long been an interest in understanding the connectional organization of the human brain, though interest in connectivity has recently increased, as the tools to obtain such data have emerged and as other lines of inquiry have made clear the importance of such data.  Prior to the Human Connectome Project (HCP), little neural connectivity data from humans was available.

Continuing to fill this knowledge gap is paramount because connectivity is a major organizing principle of the nervous system and is fundamental to understanding brain function and dysfunction.  Attempts to understand neural connectivity in model organisms are helping to develop an integrated understanding of the interplay of genes, molecules, cells, neural systems, and behavior.  Such understanding, in turn, provides the basis for detailed models from which hypotheses about brain function in health and illness can be generated.  Without connectivity data, this kind of understanding is not possible for human brain function and dysfunction.  Knowledge of human brain connectivity will transform human neuroscience by providing not only a qualitatively novel class of data, but also by providing the basic framework necessary to synthesize diverse data and, ultimately, elucidate how our brains work in health, illness, youth, and old age.

It is important to link connectivity data to architectonic features rather than merely to coordinates, or locations of sulci and gyri.  The surface geometry of the human brain is extremely variable and idiosyncratic, and the relationship of surface features to functional subdivisions and their differential connectivity is imprecise.  Classical neuroanatomy shows strong correlations between connectivity patterns and features such as cytoarchitecture and the differential distribution of molecular tags (including enzymes, neurotransmitters, transmitter receptors, expressed genes, etc.).  For this reason, connectional studies in model organisms routinely relate connectional data to such architectonic data.  While architectonic features have been mapped extensively in the human brain, the relationship of projections and connections to these features has heretofore not been demonstrated, because human connectivity data were absent.  Linking such architectural features to the distribution of specific connections is providing a critical “anchor” that will permit connectional data to be related to a variety of other types of data, broadening and enhancing their utility.

Connectivity, in the context of brain architecture, has long figured in understanding, diagnosing, and treating certain neurological disorders.  Increasingly, disrupted or aberrant connectivity is being implicated or suspected in the etiology of disorders not previously considered from this perspective.  For example, it is very likely that quantifiable changes in connectivity accompany the variations in cortical thickness (as demonstrated with structural magnetic resonance imaging) that are seen in diseased brains (e.g., Alzheimer) relative to healthy brains, and that are seen in brains through the course of early development, through adolescence and senescence.  Similarly, it is likely that qualitative or quantitative changes in connectivity contribute to morphometric differences observed in brains of those with particular disorders, such as schizophrenia.

The overall purpose of the HCP has been to develop and share knowledge about the structural and functional connectivity of the human brain.  This purpose has been achieved through awards to two different multi-institutional research teams centered at Washington University (http://www.humanconnectome.org/) and Massachusetts General Hospital (http://www.humanconnectomeproject.org/).  These teams have developed and optimized non-invasive imaging technologies to acquire structural and functional in vivo data about axonal projections and neural connections from brains of hundreds of healthy adults.  Demographic data and data regarding sensory, motor, cognitive, emotional, and social function have also been collected for each subject.  Subjects have also donated DNA samples for genotyping and that data will be available before the awards end in September 2015.  The data and experimental protocols have been made available to the research community, and both are now being widely used.  Both research groups are now undertaking pilot studies to explore the issues with extending the HCP to children and to older adults to represent the lifespan.  Those data will also be made available at http://www.humanconnectome.org/.

While the HCP project has provided an excellent start at providing connectivity data for a community sample of normal subjects, the purpose of this announcement is to expand the HCP data to disease/disorder cohorts of interest to the Institutes and Centers that are participating in this FOA.  Applicants should review recent Notices related to Study Design (NOT-MH-14-004 and NOT-NS-11-023).


Research Studies and Objectives
The bulk of the data collection in the HCP has been by the group at Washington University.  By September 2015, they will have collected data on 1200 healthy young adults (ages 22-35), with release of the final subjects shortly thereafter.  Most of these adults are monozygotic or dizygotic twins or their family members.  The data collected includes non-invasive imaging, behavioral assessments, and genotyping assays.  It is expected that data collected under this FOA will be compatible with the existing HCP dataset.

The Institutes and Centers that are participating in this FOA have different priority/disease areas of interest.

For NIMH, research cohorts should come from either a broad category such as those with psychiatric based psychosis, mood and anxiety disorders, or depression. Subject groups can also be based on RDoC categories or based on a specific genetic profile.  Applicants must avoid cohorts from a narrowly defined DSM diagnostic group.

The NEI is interested in research in populations where the visual pathways may be compromised due to congenital or acquired disease, or injury (e.g. blindness, strabismus, amblyopia, and low vision). Cohorts of patients with visual disorders should be compared with normal age-matched controls. Studies of plasticity in the visual pathways associated with the loss or restoration of vision are of particular interest.

For NIA, research cohorts should be comprised of individuals with neurodegenerative diseases associated with aging such as Alzheimer’s disease (preclinical, early- and late-onset), other dementias of aging, and/or age-related cognitive disorders such as Mild Cognitive Impairment (early, mild and late MCI).  Also of interest are cohorts with age-related hearing loss, sleep disorders, or delirium.  Normal, healthy cohorts will be critical as age-appropriate controls for connectome studies.  Disease/disorder and control cohorts should be well defined and characterized by clinical, biomarker, genetic, and/or behavioral data.

For NIAAA, the research cohorts to be studied must be explicitly defined by the applicant in terms of alcohol use patterns currently and in the past, presence of comorbid conditions, and other factors such as a specific genetic profile.  The information to be acquired must clearly relate to the mission of NIAAA to understand the effects of alcohol use and abuse on brain and behavior.

For NIDA, research cohorts should be comprised of users or abusers of licit or illicit psychotropic drugs, either currently or in the past.  Cohorts can also be composed of subjects who have known risk factors for future substance use or relapse.  These subjects should be carefully characterized for quantification of historical and current patterns of use of alcohol and multiple substances (including toxicological evidence when possible), and, when appropriate, by DSM diagnoses of substance abuse or dependence as evidence for clinically-significant use.  Because circuit-level abnormalities in abusing populations may co-occur with mental disorders, proposals featuring additional population (s) of other mental illness diagnosis or RDoC categories without substance use as comparison or control groups will be considered.

The NINDS is interested in a broad range of disorders affecting the brain and nervous system (http://www.ninds.nih.gov/about_ninds/ninds_overview.htm), and has a strong interest in the development of imaging connectomes as biomarkers.  For the NINDS, applications will be expected to 1) use HCP image acquisition protocols; 2) focus on connectomes that have been shown to be reliable and reproducible; and 3) select well-defined patient populations with clearly delineated phenotypes (e.g., defined by genetics, characteristic structural deficits, or unique pathophysiology).  Applicants may focus on neurological populations that are at-risk, prodromal, or affected.  Interested investigators are encouraged to contact program staff listed below to ensure that their application is consistent with the NINDS mission and appropropriate for  this FOA.

The full announcement can be found at the NIH Guide.