Conceptualizing neuroanatomic deviance as a function of disease prevalence
Poster No:
1869
Submission Type:
Abstract Submission
Authors:
Rebecca Cooper1, Chris Ching2, Neda Jahanshad3, Sophia Thomopoulos4, Theo van Erp5, Paul Thompson4, Maria Jalbrzikowski6, David Glahn6
Institutions:
1Boston Children's Hospital, Brookline, MA, 2University of Southern California, California, CA, 3University of Southern California,, Marina del Rey, CA, 4University of Southern California, Los Angeles, CA, 5University of California, Irvine,, Irvine, CA, 6Boston Children's Hospital, BOSTON, MA
First Author:
Co-Author(s):
Introduction:
Evolutionary biology suggests that common genetic variants contribute to common, complex diseases via small cumulative effects, whereas rarer variants exert larger effects on disease phenotypes. In other words, greater phenotypic effects are proportional to allelic frequency. We propose that this relationship may be reflected in neuroanatomic variation; that is, neurological and psychiatric disorders with greater brain structural deviation would exhibit lower population prevalence, whereas smaller neuroanatomic deviation would occur in more common disorders. Here, we tested this hypothesis by examining structural brain variations from ENIGMA disease working groups, examining whether greater neuroanatomic deviation in neurological and psychiatric disorders is associated with rarer disease prevalence.
Methods:
We estimated neuroanatomic deviation using Cohen's d effect sizes from case-control comparisons of T1-weighted MRI data from 18 ENIGMA disease working group publications (N cases=19,020, N controls=32,016). Greater case-control effect sizes reflected greater neuroanatomic deviation. We extracted summary statistics for global measures of cortical thickness, surface area, intracranial volume, and eight subcortical volumes across ENIGMA studies using harmonized processing and quality control protocols. We estimated the global population prevalence of each disease from Global Burden of Disease statistics (Global Burden of Disease Collaborative Network, 2024), World Health Organization Mental Health Surveys (Scott et al., 2018), and recent meta-analyses (Fawcett et al., 2020; Ohayon & Reynolds, 2009; Olsen et al., 2018; Salazar De Pablo et al., 2021; Solmi et al., 2022). We used Pearson correlations to assess the relationship between Cohen's d effect sizes for brain measures from each ENIGMA disease working group with the respective disease's corresponding global population prevalence.
Results:
Mean effect sizes varied from d=0.002-0.56 for intracranial volume, d=0.04-0.91 for cortical thickness, and d=0.01-1.02 for surface area. Greater neuroanatomical deviation in intracranial volume was associated with lower global disease population prevalence at trend level (r=-0.46, p=0.072, Figure 1), but no relationships were observed for cortical thickness (r=-0.44, p=0.15) or surface area (r=-0.32, p=0.34). Greater neuroanatomical deviation in intracranial volume was also associated with smaller sample sizes used in ENIGMA Working group publications (r=-0.59, p=0.011, Figure 2).
·Figure 1. Correlation between disease prevalence (%) and Cohen’s d effect size reflecting case-control neuroanatomic differences for ENIGMA disease working groups.
·Figure 2. Correlation between sample size used in ENIGMA working group publication and Cohen’s d effect size reflecting case-control neuroanatomic differences for ENIGMA disease working groups.
Conclusions:
These findings suggest lower disease prevalence is associated with a trend towards greater neuroanatomic deviation from normative populations, providing empirical support for disease prevalence in influencing brain structure. Future work should seek to expand these findings by examining additional brain structural and functional measures with greater granularity.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s)
Neurodevelopmental/ Early Life (eg. ADHD, autism)
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems 2
Novel Imaging Acquisition Methods:
Anatomical MRI 1
Keywords:
Meta- Analysis
Neurological
Pediatric Disorders
Psychiatric Disorders
STRUCTURAL MRI
1|2Indicates the priority used for review
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