The goal of the proposed study is to identify and functionally characterize genetic variation that physiologically influences basic cognitive phenotypes. The phenotypes of interest measure basic cognitive performance indexes, reflecting the function of well characterized neuronal circuits. They are often impaired in neuropsychiatric disorders like schizophrenia, bipolar disorder, autism, attention deficit disorder, Huntington's disease and others. We propose to use a pre-existing sample of over 2,000 young healthy males with cognitive performance data and the publicly available sample from the Consortium on the Genetics of Endophenotypes in Schizophrenia (COGS) for an efficient three stage genome wide association study (GWAS), maximizing our power while minimizing the possibility of false positive results. Our main analysis will focus in two domains, executive function and occulomotor function, including a total of 6 phenotypes: Performance accuracy, performance speed, voluntary saccade movement speed, inhibition function, eye pursuit system function and reaction time variability. Secondary exploratory analyses will examine associations with underlying latent factors reflecting common elements across tasks and two more phenotypes, the frequency of saccades in an eye fixation task, likely to reflect inhibition function similar to what is measured in the antisaccade task and the open loop pursuit function. Variants identified in our main analysis will be further explored through sequencing, in silico analyses, in vitro analyses and gene transcript analyses on post mortem brain samples in order to point to specific functional DNA variants and explore the biological mechanism through which they influence cognitive performance. Linking genes to cognitive phenotypes will have a significant impact on multiple aspects of biomedical research leading to important public health benefits. Identifying genes that influence aspects of cognition already linked to specific neuronal circuitry will be a considerable benefit to our knowledge and understanding of brain function, tying together neuroscience and genetics. The observed defects of these phenotypes in multiple psychiatric disorders suggests these results will also contribute to untangle the genetics of many psychiatric diseases. Another significant contribution of this study will be through data sharing. Regarding the cognitive phenotypes this data will not only uncover the first genes but also be available for future projects to incorporate into powerful study designs. Regarding the study of psychiatric disorders it will allow the examination of disease - associated DNA variants for effects on cognitive variables, promoting a better understanding of each disorder and the related brain dysfunctions. To maximize these benefits we have paid special attention to provide data informative across genotyping platforms that will be share together with our phenotype data through the NIMH repository.

Public Health Relevance

This study aims to find genes involved in specific aspects of cognitive performance in humans. We have used standardized tasks to measure in about 2,000 individuals aspects of cognitive performance like speed and accuracy and eye movement control and we propose to analyze DNA variation across the genome, follow an efficient staged approach to locate genetic variants that influence these cognitive variables and explore the function of those genetic variants. An immediate benefit of this project will be to our understanding of the relationships between genes, neuronal circuitry and cognition. An additional and perhaps more important benefit will be to the study of the numerous psychiatric and other diseases that often perturb these same cognitive functions, including schizophrenia, autism, attention deficit disorder and many others.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Genetics of Health and Disease Study Section (GHD)
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Senthil, Geetha
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Johns Hopkins University
Schools of Medicine
United States
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Wang, R; Halper-Stromberg, E; Szymanski-Pierce, M et al. (2014) Genetic determinants of neuroglobin transcription. Neurogenetics 15:65-75
Hatzimanolis, A; McGrath, J A; Wang, R et al. (2013) Multiple variants aggregate in the neuregulin signaling pathway in a subset of schizophrenia patients. Transl Psychiatry 3:e264