The Genetics of Personalized Functional MRI Networks

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ABSTRACT Variability in the spatial layout of human brain functional networks on the anatomic cortex is a novel phenotype that can be extracted from functional magnetic resonance imaging (fMRI) with transformative potential for combined imaging-genetics studies of human brain function. Early results show that the individual-specific topography of Personalized Functional Networks (PFNs) is strongly associated with domains of psychopathology and cognition, including executive functioning (EF) which is impacted in multiple mental health conditions and undergoes profound changes during the period of adolescence. PFNs capture individualized aspects of brain function that have unique associations with clinical and developmental outcomes, compared to standard fMRI approaches, which can measure activity in these same functional networks but fail to incorporate the variation in functional network topography that exists among individuals. The over-arching hypothesis of this proposal is that targeting PFNs will rapidly accelerate the discovery of genetic contributions to the organization of brain function, leading to mechanistic insights into genetic risks for behavioral health conditions related to brain function. To this end, we will probe PFNs in genetically informative open fMRI datasets including the Adolescent Brain and Cognitive Development Study (ABCD, n=11,572, n=850 twin pairs, 5 longitudinal time points during study period) and the UK Biobank (UKBB, n>40,000), as well as locally acquired fMRI data on the 22q11.2 deletion syndrome (22qDS, n=100; controls n=500). Analyses will yield a cohesive investigation of inherited polygenic effects and rare, typically de novo copy number variants (CNVs), each of which are hypothesized to influence individualized functional network topography. First, we will use longitudinal twin models in ABCD to investigate the twin heritability of PFNs and their genetic correlation with behavioral domains such as EF, for example, testing the hypothesis that the genetic correlation between EF and association cortex PFNs will increase during adolescence (Aim 1). Second, we will perform genome- and transcriptome-wide association studies (GWAS and TWAS) of PFN topography in ABCD and UKBB to prioritize specific, functionally active genetic loci (Aim 2). Third, we will investigate the influence of rare CNVs on PFNs, using analysis of case-control Penn/CHOP 22q11.2DS data, in ABCD, CNV Risk Scores that we recently showed to correlate with deviations from the typical development of brain anatomy in a community cohort (Aim 3). Allanalyses will be conducted with fully reproducible, transparent imaging processing and genetic pipelines, capitalizing on the PI and assembled team's joint expertise in advanced fMRI methods, genomics, and informatics. Cumulatively, the completion of these aims will result in a major advance in our understanding of the genetic contributions to brain function and its relationship to psychiatric risk, leading to future experimental and clinical trials of targeted neuromodulation guided by individualized neurogenetics.