Neurogenetic Factors of Antisocial Behavior: Brain Gene Expression and fMRI Analysis
Poster No:
693
Submission Type:
Abstract Submission
Authors:
Jaroslav Rokicki1, Megan Campbell2, Alina Irene Sartorius3, Dennis Van der Meer3, Natalia Tesli1, Piotr Jahołkowski3, Alexey Shadrin3, Ole Andreassen3, Lars Westlye3, Daniel Quintana3, Unn Kristin Haukvik3
Institutions:
1Oslo University Hospital, Oslo, Oslo, 2University of Cape Town, Cape Town, Western Cape, 3University of Oslo, Oslo, Oslo
First Author:
Co-Author(s):
Introduction:
Antisocial behaviour (ASB) involves covert and overt hostility, irresponsibility, and violations of others' rights and safety, posing significant societal issues. Recent genome-wide meta-analyses have identified loci linked to the FOXP2 gene (Tielbeek et al., 2022), which is associated with complex mental processes such as language and speech (Lai et al., 2003). However, the expression patterns of these genes in the brain, and their roles in ASB remain unclear. In this study, we aim to elucidate the neurogenetic factors associated with ASB by exploring the expression patterns of genes identified through GWAS. We will then perform fMRI meta-analyses on these gene expression patterns to understand their functional implications in ASB.
Methods:
Using the Functional Mapping and Gene Annotation (FUMA) protocol (Watanabe et al., 2017), SNPs with p < 10^-6 were selected and mapped to genes via Open Targets Genetics, integrating positional information and various quantitative trait loci (QTL) data (Ghoussaini et al., 2021). For the gene expression data we used the Allen Human Brain Atlas, covering diverse demographic post-mortem samples to analyze expression patterns of 15,633 protein-coding genes. High-density brain expression maps and atlas-based maps were constructed using the abagen toolbox (Markello et al., 2021), focusing on the left hemisphere. Donor-to-donor reproducibility was assessed using Spearman's correlation coefficients. The robustness of our findings was validated through out-of-sample comparison using RNAseq data from the GTEx-project across 54 tissues (including 13 brain regions). To determine cognitive traits, we calculated associations between gene-expression patterns and fMRI meta-analyses using NiMARE (Salo et al., 2023), encompassing a database of ~400,000 fMRI activations. Spearman's correlation coefficients were used to assess robustness, with specificity metrics highlighting the most relevant cognitive associations.
Results:
Using FUMA, we identified 329 single nucleotide polymorphisms (SNPs) and mapped them to 15 genes. Ten out of the 15 ASB-associated genes showed reproducible expression patterns among individual donors, independent of sex and ethnicity. These patterns were also cross-validated using RNAseq data (mean correlation = 0.66, SD = 0.24). Notably stable genes included FOXP2 and SMAD5, ranking above the 50th percentile of all 15,633 protein-coding genes. The cerebellum consistently displayed significant gene expression deviations among seven of the ten reproducible ASB-linked genes, with additional substantial deviations observed in subcortical regions and the frontal lobe.The fMRI meta-analysis revealed that ASB-related genes exhibited strong correlations with cognitive terms related to distress, motor processing, cognitive functions, and conditioning. Notably, four of the 15 genes ranked within the top 2.5% of the strongest associations to cognitive terms when compared to all 15,633 genes. Furthermore, ASB-related genes were associated with chronic pain, heart rate, and aphasia, revealing broader clinical implications of these genes in the context of ASB.
Conclusions:
This extensive analysis connects genetic expression patterns with brain activity related to ASB, suggesting intricate links between specific gene activity and cognitive functions. The findings present a multi-dimensional framework that could inform targeted interventions and enhance our understanding of the biological basis underlying antisocial behaviours.
Genetics:
Genetics Other 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
Keywords:
Psychiatric Disorders
Other - Gene expression
1|2Indicates the priority used for review
·Cognitive states were decoded using fMRI meta-analysis of mRNA maps. Top fifteen relationships for selected genes (a) Top five cognitive states for each gene (b) Sensitivity analysis (c)
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Lai, C. S. L., Gerrelli, D., Monaco, A. P., Fisher, S. E., & Copp, A. J. (2003). FOXP2 expression during brain development coincides with adult sites of pathology in a severe speech and language disorder. Brain, 126(11), 2455–2462. https://doi.org/10.1093/brain/awg247
Markello, R. D., Arnatkeviciute, A., Poline, J.-B., Fulcher, B. D., Fornito, A., & Misic, B. (2021). Standardizing workflows in imaging transcriptomics with the abagen toolbox. eLife, 10, e72129. https://doi.org/10.7554/eLife.72129
Salo, T., Yarkoni, T., Nichols, T. E., Poline, J.-B., Bilgel, M., Bottenhorn, K. L., Jarecka, D., Kent, J. D., Kimbler, A., Nielson, D. M., Oudyk, K. M., Peraza, J. A., Pérez, A., Reeders, P. C., Yanes, J. A., & Laird, A. R. (2023). NiMARE: Neuroimaging Meta-Analysis Research Environment. Aperture Neuro, 3, 1–32. https://doi.org/10.52294/001c.87681
Tielbeek, J. J., Uffelmann, E., Williams, B. S., Colodro-Conde, L., Gagnon, É., Mallard, T. T., Levitt, B. E., Jansen, P. R., Johansson, A., Sallis, H. M., Pistis, G., Saunders, G. R. B., Allegrini, A. G., Rimfeld, K., Konte, B., Klein, M., Hartmann, A. M., Salvatore, J. E., Nolte, I. M., … Posthuma, D. (2022). Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis. Molecular Psychiatry, 27(11), 4453–4463. https://doi.org/10.1038/s41380-022-01793-3
Watanabe, K., Taskesen, E., van Bochoven, A., & Posthuma, D. (2017). Functional mapping and annotation of genetic associations with FUMA. Nature Communications, 8(1), Article 1. https://doi.org/10.1038/s41467-017-01261-5