Poster No:
680
Submission Type:
Abstract Submission
Authors:
Zuriel Ceja1, Luis García-Marín1, Sarah Medland1, Miguel Rentería1
Institutions:
1QIMR Berghofer, Brisbane, Queensland
First Author:
Co-Author(s):
Introduction:
Suicide accounts for one in every 100 deaths in the world, and it is the fourth leading death cause for individuals aged between 15 and 29. Suicidal thoughts and behaviours (STBs), such as planning, ideation, and attempts, are highly complex and heterogeneous phenomena with underlying neurobiological mechanisms that remain poorly understood. This study investigates the genetic associations between cortical and subcortical regional brain volumes (RBVs) and distinct subtypes of STB phenotypes, aiming to elucidate the specificity of brain morphology with particular behaviours.
Methods:
Polygenic scores (PGS) were calculated for cortical and subcortical RBVs using summary statistics from recent large-scale meta-analyses (subcortical RBVs: Garcia-Marin et al., 2024, N = 74,898; cortical RBVs: Grasby et al., 2020, N = 51,665) and SBayesR implemented in GCTA. PGS was then applied to two independent Australian cohorts, the Australian Genetics of Depression Study (AGDS, N = 20,689) and the Australian Genetics of Bipolar Disorder study (GBD, N = 6,682), to predict phenotypes of STB using generalised linear mixed models. Models were adjusted for sex, age, and the first ten principal components of ancestry.
Results:
Key findings highlighted robust associations between specific RBVs and STB phenotypes. In subcortical RBVs, the thalamus showed the strongest link to suicide attempt (β = −0.068, p = 0.0002), while the ventral diencephalon was significantly associated with suicide ideation (β = 0.0154, p = 0.0003) and tormenting thoughts (β = −0.0996, p = 0.004). Among cortical RBVs, the superior frontal gyrus exhibited a strong association with suicide planning (β = −0.0177, p = 0.0002), and the medial orbitofrontal cortex was linked to suicide ideation (β = 0.0078, p = 0.004). Notably, subcortical RBVs were more prominently associated with suicide attempts, while cortical regions were linked to ideation and planning.
Conclusions:
These findings enhance our understanding of the neurogenetic underpinnings of suicidal behaviour, underscoring the distinct contributions of cortical and subcortical RBVs to specific STB subtypes. The results highlight the importance of considering STBs as a spectrum, where the variability in behaviours reflects a complex interplay of genetic influences and brain morphology. The observation that different brain structures are associated with distinct STB phenotypes suggests multiple brain processes co-occurring and contributing to varied patterns or subtypes of suicidal behaviours. Furthermore, these findings underscore the need to integrate environmental and comorbid factors in future studies to understand better how genetic, morphological, and phenotypic interactions shape the complexity of STBs.
Genetics:
Genetic Association Studies 1
Genetics Other 2
Keywords:
Computational Neuroscience
Cortex
Meta- Analysis
Psychiatric Disorders
Sub-Cortical
1|2Indicates the priority used for review
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Was this research conducted in the United States?
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Please indicate which methods were used in your research:
Structural MRI
Computational modeling
Provide references using APA citation style.
Byrne, E. M., Kirk, K. M., Medland, S. E., McGrath, J. J., Colodro-Conde, L., Parker, R., Cross, S., Sullivan, L., Statham, D. J., Levinson, D. F., Licinio, J., Wray, N. R., Hickie, I. B., & Martin, N. G. (2020). Cohort profile: the Australian genetics of depression study. BMJ Open, 10(5), e032580.
Ceja, Z., Van Velzen, L. S., Campos, A. I., Jahanshad, N., Medland, S. E., Edwards, A. C., Schmaal, L., & Rentería, M. E. (2024). Recent breakthroughs in genetic and brain structural correlates of suicidal behaviours: A short review. Biological Psychiatry. https://doi.org/10.1016/j.biopsych.2024.09.010
García-Marín, L. M., Campos, A. I., Diaz-Torres, S., Rabinowitz, J. A., Ceja, Z., Mitchell, B. L., Grasby, K. L., Thorp, J. G., Agartz, I., Alhusaini, S., Ames, D., Amouyel, P., Andreassen, O. A., Arfanakis, K., Arias-Vasquez, A., Armstrong, N. J., Athanasiu, L., Bastin, M. E., Beiser, A. S., … Rentería, M. E. (2024). Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries. Nature Genetics, 56(11), 2333–2344.
Lind, P. A., Siskind, D. J., Hickie, I. B., Colodro-Conde, L., Cross, S., Parker, R., Martin, N. G., & Medland, S. E. (2023). Preliminary results from the Australian Genetics of Bipolar Disorder Study: A nation-wide cohort. The Australian and New Zealand Journal of Psychiatry, 57(11), 1428–1442.
Lloyd-Jones, L. R., Zeng, J., Sidorenko, J., Yengo, L., Moser, G., Kemper, K. E., Wang, H., Zheng, Z., Magi, R., Esko, T., Metspalu, A., Wray, N. R., Goddard, M. E., Yang, J., & Visscher, P. M. (2019). Improved polygenic prediction by Bayesian multiple regression on summary statistics. Nature Communications, 10(1), 5086.
Strike, L. T., Hansell, N. K., Couvy-Duchesne, B., Thompson, P. M., de Zubicaray, G. I., McMahon, K. L., & Wright, M. J. (2019). Genetic Complexity of Cortical Structure: Differences in Genetic and Environmental Factors Influencing Cortical Surface Area and Thickness. Cerebral Cortex , 29(3), 952–962.
No