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Approved research

Structural genetic contributions brain function and behavior

Principal Investigator: Professor Avram Holmes
Approved Research ID: 25163
Approval date: February 5th 2017

Lay summary

The goal of this proposal is to identify neurogenetic signatures, or ?fingerprints?, that track behavioral variability in the general population and associate with vulnerability for the onset of psychiatric illness. To date, research on the biological origins of psychopathology has largely focused on discrete illness categories. Although patient groups within this system are treated as distinct entities, there are often murky boundaries between health and disease, and across the disorders themselves. To work to establish the etiology of these complex syndromes we will compute the extent genetic factors influence patterns of brain function and associated physical, clinical, and cognitive characteristics. Emerging evidence indicates that individual differences in behavior are reflected in variability across the collective set of functional brain connections (functional connectome). Genetic factors can predispose disruption within brain networks. These data suggest that the spectra of symptom profiles observed in psychiatric illness may arise through heritable patterns of brain network function. Consistent with the UK Biobank?s central goal to ?to improve the prevention, diagnosis and treatment of illness and the promotion of health throughout society,? the proposed project will provide brain network and genetic biomarkers that will enable future advances in our understanding of pathogenesis of psychiatric illness. We will use a multivariate analytic strategy to examine the relations linking genome-wide marker (single nucleotide polymorphism, or SNP) data with variability in individual participant functional connectomes and associated behavioral phenotypes. These analyses can provide information on the overlapping genetic mechanisms that influence both brain function and wide range of behavioral traits. Pre-processing steps for brain/non-brain data that can bias down-stream analyses. Accordingly, we are requesting bulk data for several non-brain phenotypes (accelerometer). This will allow us to implement independent quality control procedures and derive relevant/novel phenotypes as the scientific literature evolves. Phenotypes and genomic data for the full UK Biobank will be requested (participants with/without brain data).