Sex and age variations in the impact of puberty on cortical thickness and associations with internalizing symptoms and suicidal ideation in early adolescence

Characterizing the effects of age, puberty, and sex on variability in resting-state functional connectivity in late childhood and early adolescence

Understanding the relative influences of age, pubertal development, and sex assigned at birth on brain development is a key priority of developmental neuroscience given the complex interplay of these factors in the onset of psychopathology. Previous research has investigated how these factors relate to static (time-averaged) functional connectivity (FC), but little is known about their relationship with dynamic (time-varying) FC. The present study aimed to investigate the unique and overlapping roles of these factors on dynamic FC in children aged approximately 9 to 14 in the ABCD Study using a sample of 5122 low-motion resting-state scans (from 4136 unique participants). Time-varying correlations in the frontolimbic, default mode, and dorsal and ventral corticostriatal networks, estimated using the Dynamic Conditional Correlations (DCC) method, were used to calculate variability of within- and between-network connectivity and of graph theoretical measures of segregation and integration. We found decreased variability in global efficiency across the age range, and increased variability within the frontolimbic network driven primarily by those assigned female at birth (AFAB). AFAB youth specifically also showed increased variability in several other networks. Controlling for age, both advanced pubertal development and being AFAB were associated with decreased variability in all within- and between-network correlations and increased variability in measures of network segregation. These results potentially suggest advanced brain maturation in AFAB youth, particularly in key networks related to psychopathology, and lay the foundation for future investigations of dynamic FC.

Cerebral cortical alterations in adolescent early-onset psychosis: a surface-based morphometry mega-analysis

Cortical brain morphology in early-onset psychosis (EOP; age of onset < 19 years) is poorly understood, partly due to recruitment constraints linked to its low incidence. We pooled T1-weighted magnetic resonance imaging (MRI) data from 387 adolescents with EOP (mean age=16.1±1.5; 49.6% female) and 338 healthy controls (CTR; mean age=15.8±1.9, 54.4% female) from nine research sites worldwide. Using harmonized processing protocols with FreeSurfer, we extracted cortical brain metrics from 34 bilateral regions. Univariate regression analysis revealed widespread lower bilateral cortical thickness (left/right hemisphere: d =-0.36/-0.31), surface area (left/right: d =-0.42/-0.41), cortical volume (left/right: d =-0.58/-0.56), and Local Gyrification Index (LGI; left/right: d =-0.39/-0.52) in EOP relative to CTR. Subgroup analyses showed broader and more pronounced case-control differences in early-onset schizophrenia for area, volume, and LGI. We found no associations with antipsychotic medication use, illness duration, age of onset, or positive symptoms. Negative symptoms were related to smaller left lingual volumes (partial r =-0.21; p FDR =0.014) and antidepressant users had smaller area ( d =-0.43; p FDR =0.034) and volume ( d =-0.50; p FDR =0.003) of the right rostral anterior cingulate compared to non-users. Cortical alterations in EOP showed a similar pattern to those observed in prior studies on adults with schizophrenia (SCZ; r =0.62) and bipolar disorders (BD; r =0.61). However, surface area alterations were overall 1.5 times greater for EOP than adult SCZ and 4.6 times greater than adult BD. In the largest study of its kind, we observed an extensive pattern of cortical alterations in adolescents with psychotic disorders, highlighting the potential impact of aberrant neurodevelopment on cortical morphology in this clinical group.

Personality perspective on depression and anxiety symptoms among Chinese adolescents and young adults: a two-sample network analysis

BACKGROUND

The mental health burden among adolescents has been increasing, impacting individuals even before formal diagnosis of common mental disorders. Although personality traits, as key indicators of mental health conditions, play a crucial role in the development of mental disorders, there is a gap regarding the trait-to-symptom pathways and similarities and differences between adolescents and young adults.

METHODS

A total of 860 adolescents and 1751 young adults participated in this study. The Chinese Big Five Personality Inventory assessed the Big Five traits, while depression and anxiety symptoms were measured using the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7, respectively. Network analysis computed the bridging centrality of Big Five traits and elucidated trait-to-symptom pathways. Furthermore, network comparison was applied to compare network structure between adolescents and young adults.

RESULTS

In both age groups, neuroticism exhibited a transdiagnostic activating effect on depression and anxiety. Conscientiousness demonstrated the strongest protective effect against depression, whereas agreeableness was most protective against anxiety. In both samples, neuroticism primarily influenced symptoms associated with negative emotions and thoughts. Comparatively, extraversion exhibited a significant increasing protective effect against depression throughout adolescence, while neuroticism increasingly activated anxiety symptoms.

CONCLUSIONS

This study highlights the potential to utilize personality traits for early detection and precise intervention in adolescent populations, providing actionable insights. By identifying the level of neuroticism, we can effectively detect high-risk adolescent individuals prior to formal diagnosis. By delineating the neuroticism-to-symptom pathways, we can implement targeted intervention on their pathological interactions.

Longitudinal Sex-at-Birth and Age Analyses of Cortical Structure in the ABCD Study

While the brain continues to develop during adolescence, such development may depend on sex-at-birth. However, the elucidation of such differences may be hindered by analytical decisions (e.g., covariate selection to address brain-size differences) and the typical reporting of cross-sectional data. To further evaluate adolescent cortical development, we analyzed data from the Adolescent Brain Cognitive Development Study, whose cohort of 11,000+ youth participants with biannual neuroimaging data collection can facilitate understanding neuroanatomical change during a critical developmental window. Doubly considering individual differences within the context of group-level effects, we analyzed regional changes in cortical thickness, sulcal depth, surface area, and volume between two timepoints (∼2 years apart) in 9- to 12-year-olds assigned male or female sex-at-birth. First, we conducted linear mixed-effect models to gauge how controlling for intracranial volume, whole-brain volume (WBV), or a summary metric (e.g., mean cortical thickness) influenced interpretations of age-dependent cortical change. Next, we evaluated the relative changes in thickness and surface area as a function of sex-at-birth and age. Here, we showed that WBV (thickness, sulcal depth, volume) and total cortical surface area were more optimal covariates; controlling for different covariates would have substantially altered our interpretations of overall and sex-at-birth-specific neuroanatomical development. Furthermore, we provided evidence to suggest that aggregate change in how cortical thickness is changing relative to surface area is generally comparable across those assigned male or female sex-at-birth, with corresponding change happening at slightly older ages in those assigned male sex-at-birth. Overall, these results help elucidate neuroanatomical developmental trajectories in early adolescence.

Seeing adolescents grow from many angles using a multilevel approach: A tribute to the contributions of Dante Cicchetti to the field of developmental psychopathology

Dante Cicchetti propelled forward the field of developmental psychopathology by advancing this framework and championing new methods, including emphasizing the central role that multilevel analysis holds for explicating pathways of risk and resilience. His work continues to change the face of existing science. It has also paved the way for the formation of new projects, like the Research Domain Criteria initiative. This paper uses our laboratory's work on multilevel approaches to studying adolescent depression, non-suicidal self-injury, and suicidal thoughts and behaviors to shine a spotlight on Dr Cicchetti's contributions. In addition, we review recent developments, ongoing challenges, and promising future directions within developmental psychopathology as we endeavor to carry on the tradition of growth in the field.

Psychiatric neuroimaging at a crossroads: Insights from psychiatric genetics

Thanks to methodological advances, large-scale data collections, and longitudinal designs, psychiatric neuroimaging is better equipped than ever to identify the neurobiological underpinnings of youth mental health problems. However, the complexity of such endeavors has become increasingly evident, as the field has been confronted by limited clinical relevance, inconsistent results, and small effect sizes. Some of these challenges parallel those historically encountered by psychiatric genetics. In past genetic research, robust findings were historically undermined by oversimplified biological hypotheses, mistaken assumptions about expectable effect sizes, replication problems, confounding by population structure, and shared biological patterns across disorders. Overcoming these challenges has contributed to current successes in the field. Drawing parallels across psychiatric genetics and neuroimaging, we identify key shared challenges as well as pinpoint relevant insights that could be gained in psychiatric neuroimaging from the transition that occurred from the candidate gene to (post) genome-wide "eras" of psychiatric genetics. Finally, we discuss the prominent developmental component of psychiatric neuroimaging and how that might be informed by epidemiological and omics approaches. The evolution of psychiatric genetic research offers valuable insights that may expedite the resolution of key challenges in psychiatric neuroimaging, thus potentially moving our understanding of psychiatric pathophysiology forward.

The Dynamic Interplay Between Puberty and Structural Brain Development as a Predictor of Mental Health Difficulties in Adolescence: A Systematic Review

Puberty is a time of intense reorganization of brain structure and a high-risk period for the onset of mental health problems, with variations in pubertal timing and tempo intensifying this risk. We conducted 2 systematic reviews of articles published up to February 1, 2024, focusing on 1) the role of brain structure in the relationship between puberty and mental health, and 2) precision psychiatry research evaluating the utility of puberty in making individualized predictions of mental health outcomes in young people. The first review provides inconsistent evidence about whether and how pubertal and psychopathological processes may interact in relation to brain development. While most studies found an association between early puberty and mental health difficulties in adolescents, evidence on whether brain structure mediates this relationship is mixed. The pituitary gland was found to be associated with mental health status during this time, possibly through its central role in regulating puberty and its function in the hypothalamic-pituitary-gonadal and hypothalamic-pituitary-adrenal axes. In the second review, the design of studies that have explored puberty in predictive models did not allow for a quantification of its predictive power. However, when puberty was evaluated through physically observable characteristics rather than hormonal measures, it was more commonly identified as a predictor of depression, anxiety, and suicidality in adolescence. Social processes may be more relevant than biological ones to the link between puberty and mental health problems and represent an important target for educational strategies.

Sex, gender diversity, and brain structure in early adolescence

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Abnormal brain structure in atopic dermatitis: Evidence from Mendelian randomization study

BACKGROUND

Structural abnormalities in the brain of patients with atopic dermatitis (AD) have been reported; however, the cause has not been determined yet. Herein, we used Mendelian randomization (MR) to reveal the causal effect of AD on brain structure.

METHODS

This study utilized summary statistics from genome-wide association studies (GWASs) to investigate a collection of cerebral structural measures, encompassing cortical thickness (CT), cortical surface area (CA), and subcortical volumes in T1 images. A comprehensive GWAS meta-analysis identified a total of 20 independent single nucleotide polymorphisms linked to AD, surpassing the genome-wide significance threshold (p < 5 × 10⁻⁸). MR estimates were aggregated through the application of the inverse variance weighted method. Additional complementary analyses (i.e., MR-Egger and weighted median approaches) were conducted to further assess the robustness of the obtained results. Sensitivity analysis and multivariate MR (MVMR) while adjusting for brain structural changes risk factors (i.e., depression and anxiety) were performed to assess the reliability and stability of observed causality.

RESULTS

Genetically determined AD exhibited a causal link with reduced caudate volumes (IVW-MR: β = -0.186, p = 0.001, p-corrected = 0.009). Furthermore, we identified potential causal associations between AD and reduced CT in the cingulate region (posterior cingulate, IVW-MR: β = -0.065, p = 0.018, p-corrected = 0.551; isthmus cingulate, IVW-MR: β = -0.086, p = 0.003, p-corrected = 0.188), as well as abnormal cortical surface area (CA) in the supramarginal (IVW-MR: β = -0.047, p = 0.044, p-corrected = 0.714) and isthmus cingulate (IVW-MR: β = 0.053, p = 0.018, p-corrected = 0.714). Additional supplementary analyses yielded consistent outcomes. There was no evidence of horizontal pleiotropy. MVMR analysis showed that the causal effects of AD on abnormal brain structure remained significant while adjusting for depression and anxiety.

CONCLUSION

This MR study provided suggestive evidence that decreased caudate nucleus, posterior cingulate cortex, isthmus cingulate cortex and supramarginal gyrus are suggestively associated with higher AD risk. Future investigation into the brain regions is recommended, which helps to clarify the underlying mechanisms and point to new therapies against AD.

Sex, gender diversity, and brain structure in children ages 9 to 11 years old

There remains little consensus about the relationship between sex and brain structure, particularly in childhood. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest - many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years-old (N=7693). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. The model with sex, but not gender diversity, was the best-fitting model in 75% of gray matter regions and 79% of white matter regions examined. The addition of gender to the sex model explained significantly more variance than sex alone with regard to bilateral cerebellum volume, left precentral cortical thickness, as well as gyrification in the right superior frontal gyrus, right parahippocampal gyrus, and several regions in the left parietal lobe. For mean diffusivity in the left uncinate fasciculus, the model with sex, gender, and their interaction captured the most variance. Nonetheless, the magnitude of variance accounted for by sex was small in all cases and felt-gender score was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years-old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.