Relating individual brain similarity to disease patterns with dimensions of mental health
Poster No:
536
Submission Type:
Abstract Submission
Authors:
Huantao Wen1, Bin Wan1, Sofie Valk1
Institutions:
1Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Saxony
First Author:
Co-Author(s):
Introduction:
Neuropsychiatric disorders exhibit both common and unique patterns of structural brain alterations at the group level (Hettwer MD, 2022). However, the extent to which individual variability in cortical thickness aligns with these group-level differences and its relevance for continuous mental health dimensions remains unclear. In this study, we leveraged group-level maps of cortical thickness alterations from the ENIGMA consortium and individual-level cortical thickness data to investigate whether the similarity of an individual's brain to disease-related patterns is reflective of underlying mental health dimensions.
Methods:
We utilized ENIGMA-derived group-level cortical thickness maps for autism spectrum disorder, bipolar disorder, attention deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia (Larivière, 2022). Individual cortical thickness was measured using the Desikan-Killiany atlas in the HCP S1200 sample, age 22-35 (Van Essen, 2012), and z-scores to obtain a relative measure of thickness variability per region. Two similarity markers were computed: based on cosine similarity and using Spearman correlations, both focussing on different aspects of similarity. Finally, we applied partial least squares (PLS) regression models to explore the linkage of these similarity markers with behavioral measures, specifically the ASR and DSM-based questionnaires (Heine SJ, 2009; McCrae, Robert R, 2004).
Results:
Overall, we found that all similarity measures varied across individuals. The similarity showed subtle variations across disorders ranging from -0.90 to 0.93 for cosine similarity and from -0.69 to 0.71 for spearman correlations (Fig 1B). The regression between similarity markers and behavioral measures shows there are significant correlations between them, indicating individuals who have higher similarity to one psychiatric disorder map will also be strongly related to related behavioral life functions. Whereas cosine similarity related to rule-breaking and thought problems versus anxious/avoidant, differentiating versus autism, spearman association rather differentiated autism versus bipolar for avoidance versus aggression/anxiety (Fig 2B).
·Similarity measures between cortical thickness and psychiatric disorder across individuals
·Relation of similarity biomarkers and behavioral functions
Conclusions:
In this study, we investigated the link between individual brain similarity to group-level disorder profiles derived from averaged maps of clinically diagnosed individuals. We found that overall mental health scores showed correspondence with brain-wise similarity maps across individuals, possibly differentiating between more cognitive and affective and externalizing and internalizing dimensions. These findings suggest that individual variability in mental health may partially align with structural MRI markers of clinical phenotypes. Future work could further elucidate the relationship between mental health dimensions and brain-based markers of neuropsychiatric disorders.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems 2
Keywords:
Data analysis
Psychiatric
Psychiatric Disorders
Structures
1|2Indicates the priority used for review
Abstract Information
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Provide references using APA citation style.
Hettwer, M. D. (2022). Coordinated cortical thickness alterations across six neurodevelopmental and psychiatric disorders. Nature communications, 13(1), 6851.
Larivière, S. (2021). The ENIGMA Toolbox: multiscale neural contextualization of multisite neuroimaging datasets. Nature Methods, 18(7), 698-700.
McCrae, R. R. (2004). A contemplated revision of the NEO Five-Factor Inventory. Personality and individual differences, 36(3), 587-596.
Van Essen, D. C. (2012). The Human Connectome Project: a data acquisition perspective. Neuroimage, 62(4), 2222-2231.