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. 2023 Jan;62(1):59-73.
doi: 10.1016/j.jaac.2022.06.015. Epub 2022 Jul 19.

IQ Modulates Coupling Between Diverse Dimensions of Psychopathology in Children and Adolescents

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IQ Modulates Coupling Between Diverse Dimensions of Psychopathology in Children and Adolescents

Bridget W Mahony et al. J Am Acad Child Adolesc Psychiatry. 2023 Jan.

Abstract

Objective: Correlations between cognitive ability and psychopathology are well recognized, but prior research has been limited by focusing on individuals with intellectual disability, single-diagnosis psychiatric populations, or few measures of psychopathology. Here, we quantify relationships between full-scale IQ and multiple dimensions of psychopathology in a diverse care-seeking population, with a novel focus on differential coupling between psychopathology dimensions as a function of IQ.

Method: A total of 70 dimensional measures of psychopathology, plus IQ and demographic data, were collated for 2,752 children and adolescents from the Healthy Brain Network dataset. We first examined univariate associations between IQ and psychopathology, and then characterized how the correlational architecture of psychopathology differs between groups at extremes of the IQ distribution.

Results: Associations with IQ vary in magnitude between different domains of psychopathology: IQ shows the strongest negative correlations with attentional and social impairments, but is largely unrelated to affective symptoms and psychopathy. Lower IQ is associated with stronger coupling between internalizing problems and aggression, repetitive behaviors, and hyperactivity/inattentiveness.

Conclusion: Our analyses reveal that variation in general cognitive ability is associated not only with significant and selective shifts in severity of psychopathology, but also in the coupling between different dimensions of psychopathology. These findings have relevance for the clinical assessment of mental health in populations with varying IQ, and may also inform ongoing efforts to improve the measurement of psychopathology and to understand how relationships between cognition and behavior are reflected in brain organization.

Diversity & inclusion statement: We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure sex balance in the selection of non-human subjects. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper received support from a program designed to increase minority representation in science. We actively worked to promote sex and gender balance in our author group. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science.

Keywords: Healthy Brain Network (HBN); cognition; comorbidity; development; psychopathology.

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Conflict of interest statement

Disclosure: Dr. Shinohara has received consulting income from Octave Bioscience and compensation for scientific reviewing from the American Medical Association, the National Institutes of Health, the Department of Defense, and the Emerson Collective. Drs. Rau, Liu, Lalonde, Alexander-Bloch, Satterthwaite, Bassett, Milham, Raznahan and Mss. Mahony and Tu have reported no biomedical financial interests or potential conflicts of interest.

Figures

Figure 1:
Figure 1:. Workflow for Coupling-Change Analyses
Note: (A) IQ distribution with lower and upper tertiles highlighted. (B) Pairwise Fisher z-transformed correlation matrices in low IQ group and high IQ groups. (C) Difference matrix calculated as the pairwise Fisher z-score in the high IQ tertile, minus the pairwise Fisher z-score in the low IQ tertile. (D) Difference matrix after weighted stochastic block model (WSBM) clustering, with each edge grouped into a block. (E) Thresholded WSBM difference matrix, showing only those WSBM blocks that were significant after permutation-based testing.
Figure 2:
Figure 2:. Diverse Relationships Between IQ and 70 Subscale Measures of Psychopathology
Note: Bar plot showing Cohen’s d score difference (y-axis) between lower and upper IQ tertiles in the HBN for all subscale measures of psychopathology (x-axis). Positive Cohen’s d indicates greater symptom severity among the upper tertile, while negative d indicates greater symptom severity among the lower tertile. Blue bars denote the 29 subscales that showed statistically significant non-zero Cohen’s d values after 10,000 permutations and Bonferroni correction across subscales. Multi-colored tiles provide information on which instrument the subscale came from. Notable associations in decreasing order of magnitude were: learning problems, social abilities, repetitive behaviors, and attentional impairments. Severity of psychopathy and general anxiety symptoms were notably uncorrelated with IQ. CBCL = Child Behavior Checklist; CSR = Conner’s 3 Self-Report; ICU_PR = Inventory of Callous-Unemotional Traits, Parent-Report; ICU_SR = Inventory of Callous-Unemotional Traits, Self-Report; RBS = Repetitive Behavior Scale; SCARED_PR = Screen for Child Anxiety-Related Disorders, Parent-Report; SCARED_SR = Screen for Child Anxiety-Related Disorders, Self-Report; SDQ = Strengths and Difficulties Questionnaire; SRS = Social Responsiveness Scale; YSR = Youth Self-Report.
Figure 3:
Figure 3:. Characterizing Differences in Coupling Between Measures of Psychopathology as a Function of IQ
Note: (A) Difference matrix (upper IQ tertile minus lower IQ tertile) organized by WSBM blocks. (B) WSBM-organized difference matrix where lower triangle shows color only for those unique blocks with nominally significant changes in coupling after permutation testing (p < 0.05). Blocks with a black outline were also significant after further Bonferroni correction for multiple comparisons across all 45 unique blocks. CBCL = Child Behavior Checklist; CSR = Conner’s 3 Self-Report; ICU_PR = Inventory of Callous-Unemotional Traits, Parent-Report; ICU_SR = Inventory of Callous-Unemotional Traits, Self-Report; PR = parent-report; RBS = Repetitive Behavior Scale; RRBIs = restricted, repetitive behaviors and interests; SCARED_PR = Screen for Child Anxiety-Related Disorders, Parent-Report; SCARED_SR = Screen for Child Anxiety-Related Disorders, Self-Report; SDQ = Strengths and Difficulties Questionnaire; SR = self-report; SRS = Social Responsiveness Scale; YSR = Youth Self-Report.

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