We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the
NIH Research Portfolio Online Reporting Tools and the
NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
You can help! If you notice any innacuracies, please
sign in and mark grants as correct or incorrect matches.
Sign in to see low-probability grants and correct any errors in linkage between grants and researchers.
High-probability grants
According to our matching algorithm, Nikolaos P. Daskalakis is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2020 |
Daskalakis, Nikolaos |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Integrating Neuroimaging and Brain Gene Expression For Functional Characterization of Psychiatric Gwas
PROJECT SUMMARY/ABSTRACT Mental disorders are complex, debilitating health conditions, yet the neurobiological causes and pathophysiological mechanisms underlying these disorders are not well understood. The emergence of large- scale genome-wide association studies (GWAS) has enabled identification of significant, reliable genetic associations to mental disorders. However, it has been difficult to translate GWAS loci into specific causal driver variants/genes to extract mechanistic insights for identifying actionable targets for therapeutic interventions. Neurobiological intermediate phenotypes (NBIPs) are invaluable in understanding the brain?s structural and functional correlates of elevated risk of psychopathology, although the underlying processes and molecular mechanisms for observed NBIPs are elusive. Recent advances in genetic-based imputation now allow one to infer genetically-regulated portions of intermediate phenotypes from genome-wide genotype data. Our research team has successfully employed brain-specific transcriptomic imputation approaches across mental disorders to identify novel genes and pathways of risk. In this proposal, we seek to increase the biological resolution of the link between neuroimaging genetics and psychiatric genetics by creating novel polygenic models of multimodal neuroimaging based on brain-specific gene expression that can be applied to psychiatric GWAS. In Aim 1, we will generate brain transcriptomic predictive models of multimodal neuroimaging and replicate them in independent datasets. In Aim 2, we will conduct Imaging Transcriptome-wide Association Studies (ITWAS) to identify neuroimaging associations with mental disorders at a brain-specific gene-level and distinguish the causal ones. Our integrative analyses will enhance our understanding of NBIPs and mental disorder risk; thus, they will provide mechanistic insights that may drive identification of novel diagnostic, trans-diagnostic and treatment approaches.
|
0.915 |