Neuroimaging predictors of onset and course of depression in childhood and adolescence: A systematic review of longitudinal studies

Ventral striatal-cingulate resting-state functional connectivity in healthy adolescents relates to later depression symptoms in adulthood

BACKGROUND

Depression is a significant public health concern. Identifying biopsychosocial risk factors for depression is important for developing targeted prevention. Studies have demonstrated that blunted striatal activation during reward processing is a risk factor for depression; however, few have prospectively examined whether adolescent reward-related resting-state functional connectivity (rsFC) predicts depression symptoms in adulthood and how this relates to known risk factors (e.g., childhood trauma).

METHODS

At baseline, 66 adolescents (mean age = 14.7, SD = 1.4, 68 % female) underwent rsFC magnetic resonance imaging and completed the Children's Depression Inventory (CDI). At follow-up (mean time between adolescent scan and adult follow-up = 10.1 years, SD = 1.6, mean adult age = 24.8 years, SD = 1.7), participants completed the Childhood Trauma Questionnaire (CTQ) and Beck Depression Inventory- Second Edition (BDI-2). Average rsFC was calculated between nodes in mesocorticolimbic reward circuitry: ventral striatum (VS), rostral anterior cingulate cortex (rACC), medial orbitofrontal cortex, and ventral tegmental area. Linear regressions assessed associations between rsFC, BDI-2, and CTQ, controlling for adolescent CDI, sex assigned at birth, and scan age (Bonferroni corrected).

RESULTS

Greater childhood trauma was associated with higher adulthood depression symptoms. Stronger VS-rACC rsFC during adolescence was associated with greater depression symptoms in adulthood and greater childhood trauma.

LIMITATIONS

The small sample size, limited depression severity, and seed-based approach are limitations.

CONCLUSIONS

The associations between adolescent striatal-cingulate rsFC and childhood trauma and adult depression symptoms suggest this connectivity may be an early neurobiological risk factor for depression and that early life experience plays an important role. Increased VS-rACC connectivity may represent an over-regulatory response on the striatum, commonly reported in depression, and warrants further investigation.

Neural activation signatures in individuals with subclinical depression: A task-fMRI meta-analysis

BACKGROUND

Previous task-related functional magnetic resonance imaging (task-fMRI) investigations have documented abnormal brain activation associated with subclinical depression (SD), defined as a clinically relevant level of depressive symptoms that does not meet the diagnostic criteria for major depressive disorder. However, these task-fMRI studies have not reported consistent conclusions. Performing a voxel-based meta-analysis of task-fMRI studies may yield reliable findings.

METHODS

We extracted the peak coordinates and t values of included studies and analyzed brain activation between individuals with SD and healthy controls (HCs) using anisotropic effect-size signed differential mapping (AES-SDM).

RESULTS

A systematic literature search identified eight studies, including 266 individuals with SD and 281 HCs (aged 14 to 25). The meta-analysis showed that individuals with SD exhibited significantly greater activation in the right lenticular nucleus and putamen according to task-fMRI. The meta-regression analysis revealed a negative correlation between the proportion of females in a group and activation in the right striatum.

LIMITATIONS

The recruitment criteria for individuals with SD, type of tasks and MRI acquisition parameters of included studies were heterogeneous. The results should be interpreted cautiously due to insufficient included studies.

CONCLUSION

Our findings suggest that individuals with SD exhibit increased activation in the right lenticular nucleus, putamen and striatum, which may indicate a compensatory increase in response to an impairment of insular and striatal function caused by depression. These results provide valuable insights into the potential pathophysiology of brain dysfunction in SD.

The importance of timing of socioeconomic disadvantage throughout development for depressive symptoms and brain structure

Prior studies have reported associations between socioeconomic disadvantage, brain structure and mental health outcomes, but the timing of these relations is not well understood. Using prospective longitudinal data from the Avon Longitudinal Study of Parents and Children (ALSPAC), this preregistered study examined whether socioeconomic disadvantage related differentially to depressive symptoms (n=3012-3530) and cortical and subcortical structures (n=460-733) in emerging adults, depending on the timing of exposure to socioeconomic disadvantage. Family income in early childhood and own income measured concurrently were both significantly related to depressive symptoms in emerging adulthood. Similar results were observed for perceived financial strain. In contrast, only family income in early childhood was associated with brain structure in emerging adulthood, with positive associations with intracranial volume and total and regional cortical surface area. The findings suggest that both objective and subjective aspects of one's financial standing throughout development relate to depressive symptoms in adulthood, but that specifically early life family income is related to brain structural features in emerging adulthood. This suggests that associations between socioeconomic disadvantage and brain structure originate early in neurodevelopment, highlighting the role of timing of socioeconomic disadvantage.

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.

Leveraging distributed brain signal at rest to predict internalizing symptoms in youth

BACKGROUND

The prevalence of internalizing psychopathology rises precipitously from early to mid-adolescence, yet the underlying neural phenotypes that give rise to depression and anxiety during this developmental period remain unclear.

METHODS

Youth from the Adolescent Brain and Cognitive DevelopmentSM Study (ages 9-10 years at baseline) with a resting-state fMRI scan and mental health data were eligible for inclusion. Internalizing subscale scores from the Brief Problem Monitor - Youth Form were combined across two years of follow-up to generate a cumulative measure of internalizing symptoms. The total sample (n = 6521) was split into a large discovery dataset and a smaller validation dataset. Brain-behavior associations of resting-state functional connectivity (RSFC) with internalizing symptoms were estimated in the discovery dataset. The weighted contributions of each functional connection were aggregated using multivariate statistics to generate a polyneuro risk score (PNRS). The predictive power of the PNRS was evaluated in the validation dataset.

RESULTS

The PNRS explained 10.73% of the observed variance in internalizing symptom scores in the validation dataset. Model performance peaked when the top 2% functional connections identified in the discovery dataset (ranked by absolute β-weight) were retained. The RSFC networks that were implicated most prominently were the default mode, dorsal attention, and cingulo-parietal networks. These findings were significant (p < 1*10-6) as accounted for by permutation testing (n = 7000).

CONCLUSIONS

These results suggest that the neural phenotype associated with internalizing symptoms during adolescence is functionally distributed. The PNRS approach is a novel method for capturing relationships between RSFC and behavior.

Familial risk for depression moderates neural circuitry in healthy preadolescents to predict adolescent depression symptoms in the Adolescent Brain Cognitive Development (ABCD) Study

BACKGROUND

There is an imminent need to identify neural markers during preadolescence that are linked to developing depression during adolescence, especially among youth at elevated familial risk. However, longitudinal studies remain scarce and exhibit mixed findings. Here we aimed to elucidate functional connectivity (FC) patterns among preadolescents that interact with familial depression risk to predict depression two years later.

METHODS

9-10 year-olds in the Adolescent Brain Cognitive Development (ABCD) Study were classified as healthy (i.e., no lifetime psychiatric diagnoses) at high familial risk for depression (HR; n=559) or at low familial risk for psychopathology (LR; n=1203). Whole-brain seed-to-voxel resting-state FC patterns with the amygdala, putamen, nucleus accumbens, and caudate were calculated. Multi-level, mixed-effects regression analyses were conducted to test whether FC at ages 9-10 interacted with familial risk to predict depression symptoms at ages 11-12.

RESULTS

HR youth demonstrated stronger associations between preadolescent FC and adolescent depression symptoms (ps<0.001) as compared to LR youth (ps>0.001), primarily among amygdala/striatal FC with visual and sensory/somatomotor networks.

CONCLUSIONS

Preadolescent amygdala and striatal FC may be useful biomarkers of adolescent-onset depression, particularly for youth with family histories of depression. This research may point to neurobiologically-informed approaches to prevention and intervention for depression in adolescents.

Macrostructural Brain Morphology as Moderator of the Relationship Between Pandemic-Related Stress and Internalizing Symptomology During COVID-19 in High-Risk Adolescents

BACKGROUND

According to person-by-environment models, individual differences in traits may moderate the association between stressors and the development of psychopathology; however, findings in the literature have been inconsistent and little literature has examined adolescent brain structure as a moderator of the effects of stress on adolescent internalizing symptoms. The COVID-19 pandemic presented a unique opportunity to examine the associations between stress, brain structure, and psychopathology. Given links of cortical morphology with adolescent depression and anxiety, the current study investigated whether cortical morphology moderated the relationship between stress from the COVID-19 pandemic and the development of internalizing symptoms in familial high-risk adolescents.

METHODS

Prior to the COVID-19 pandemic, 72 adolescents (27 male) completed a measure of depressive and anxiety symptoms and underwent magnetic resonance imaging. T1-weighted images were acquired to assess cortical thickness and surface area. Approximately 6 to 8 months after COVID-19 was declared a global pandemic, adolescents reported their depressive and anxiety symptoms and pandemic-related stress.

RESULTS

Adjusting for pre-pandemic depressive and anxiety symptoms and stress, increased pandemic-related stress was associated with increased depressive but not anxiety symptoms. This relationship was moderated by cortical thickness and surface area in the anterior cingulate and cortical thickness in the medial orbitofrontal cortex such that increased stress was only associated with increased depressive and anxiety symptoms among adolescents with lower cortical surface area and higher cortical thickness in these regions.

CONCLUSIONS

Results further our understanding of neural vulnerabilities to the associations between stress and internalizing symptoms in general and during the COVID-19 pandemic in particular.

Individual differences in internalizing symptoms in late childhood: A variance decomposition into cortical thickness, genetic and environmental differences

The brain undergoes extensive development during late childhood and early adolescence. Cortical thinning is a prominent feature of this development, and some researchers have suggested that differences in cortical thickness may be related to internalizing symptoms, which typically increase during the same period. However, research has yielded inconclusive results. We utilized a new method that estimates the combined effect of individual differences in vertex-wise cortical thickness on internalizing symptoms. This approach allows for many small effects to be distributed across the cortex and avoids the necessity of correcting for multiple tests. Using a sample of 8763 children aged 8.9 to 11.1 from the ABCD study, we decomposed the total variation in caregiver-reported internalizing symptoms into differences in cortical thickness, additive genetics, and shared family environmental factors and unique environmental factors. Our results indicated that individual differences in cortical thickness accounted for less than 0.5% of the variation in internalizing symptoms. In contrast, the analysis revealed a substantial effect of additive genetics and family environmental factors on the different components of internalizing symptoms, ranging from 06% to 48% and from 0% to 34%, respectively. Overall, while this study found a minimal association between cortical thickness and internalizing symptoms, additive genetics, and familial environmental factors appear to be of importance for describing differences in internalizing symptoms in late childhood. RESEARCH HIGHLIGHTS: We utilized a new method for modelling the total contribution of vertex-wise individual differences in cortical thickness to internalizing symptoms in late childhood. The total contribution of individual differences in cortical thickness accounted for <0.5% of the variance in internalizing symptoms. Additive genetics and shared family environmental variation accounted for 17% and 34% of the variance in internalizing symptoms, respectively. Our results suggest that cortical thickness is not an important indicator for internalizing symptoms in childhood, whereas genetic and environmental differences have a substantial impact.

An empirical analysis of structural neuroimaging profiles in a staging model of depression

We examine structural brain characteristics across three diagnostic categories: at risk for serious mental illness; first-presenting episode and recurrent major depressive disorder (MDD). We investigate whether the three diagnostic groups display a stepwise pattern of brain changes in the cortico-limbic regions. Integrated clinical and neuroimaging data from three large Canadian studies were pooled (total n = 622 participants, aged 12-66 years). Four clinical profiles were used in the classification of a clinical staging model: healthy comparison individuals with no history of depression (HC, n = 240), individuals at high risk for serious mental illness due to the presence of subclinical symptoms (SC, n = 80), first-episode depression (FD, n = 82), and participants with recurrent MDD in a current major depressive episode (RD, n = 220). Whole-brain volumetric measurements were extracted with FreeSurfer 7.1 and examined using three different types of analyses. Hippocampal volume decrease and cortico-limbic thinning were the most informative features for the RD vs HC comparisons. FD vs HC revealed that FD participants were characterized by a focal decrease in cortical thickness and global enlargement in amygdala volumes. Greater total amygdala volumes were significantly associated with earlier onset of illness in the FD but not the RD group. We did not confirm the construct validity of a tested clinical staging model, as a differential pattern of brain alterations was identified across the three diagnostic groups that did not parallel a stepwise clinical staging approach. The pathological processes during early stages of the illness may fundamentally differ from those that occur at later stages with clinical progression.

Predicting depression risk in early adolescence via multimodal brain imaging

Depression is an incapacitating psychiatric disorder with increased risk through adolescence. Among other factors, children with family history of depression have significantly higher risk of developing depression. Early identification of pre-adolescent children who are at risk of depression is crucial for early intervention and prevention. In this study, we used a large longitudinal sample from the Adolescent Brain Cognitive Development (ABCD) Study (2658 participants after imaging quality control, between 9-10 years at baseline), we applied advanced machine learning methods to predict depression risk at the two-year follow-up from the baseline assessment, using a set of comprehensive multimodal neuroimaging features derived from structural MRI, diffusion tensor imaging, and task and rest functional MRI. Prediction performance underwent a rigorous cross-validation method of leave-one-site-out. Our results demonstrate that all brain features had prediction scores significantly better than expected by chance, with brain features from rest-fMRI showing the best classification performance in the high-risk group of participants with parental history of depression (N = 625). Specifically, rest-fMRI features, which came from functional connectomes, showed significantly better classification performance than other brain features. This finding highlights the key role of the interacting elements of the connectome in capturing more individual variability in psychopathology compared to measures of single brain regions. Our study contributes to the effort of identifying biological risks of depression in early adolescence in population-based samples.

Identifying two distinct neuroanatomical subtypes of first-episode depression using heterogeneity through discriminative analysis

BACKGROUND

Neurobiological heterogeneity in depression remains largely unknown, leading to inconsistent neuroimaging findings.

METHODS

Here, we adopted a novel proposed machine learning method ground on gray matter volumes (GMVs) to investigate neuroanatomical subtypes of first-episode treatment-naïve depression. GMVs were obtained from high-resolution T1-weighted images of 195 patients with first-episode, treatment-naïve depression and 78 matched healthy controls (HCs). Then we explored distinct subtypes of depression by employing heterogeneity through discriminative analysis (HYDRA) with regional GMVs as features.

RESULTS

Two prominently divergent subtypes of first-episode depression were identified, exhibiting opposite structural alterations compared with HCs but no different demographic features. Subtype 1 presented widespread increased GMVs mainly located in frontal, parietal, temporal cortex and partially located in limbic system. Subtype 2 presented widespread decreased GMVs mainly located in thalamus, cerebellum, limbic system and partially located in frontal, parietal, temporal cortex. Subtype 2 had smaller TIV and longer illness duration than Subtype 1. And TIV in Subtype 1 was positively correlated with age of onset while not in Subtype 2, probably implying the different potential neuropathological mechanisms.

LIMITATIONS

Despite results obtained in this study were validated by employing another brain atlas, the conclusions were acquired from a single dataset.

CONCLUSIONS

This study revealed two distinguishing neuroanatomical subtypes of first-episode depression, which provides new insights into underlying biological mechanisms of the heterogeneity in depression and might be helpful for accurate clinical diagnosis and future treatment.

Intracortical Myelin in Youths at Risk for Depression

Background

Major depressive disorder (MDD) is a leading cause of disability. To understand why depression develops, it is important to distinguish between early neural markers of vulnerability that precede the onset of MDD and features that develop during depression. Recent neuroimaging findings suggest that reduced global and regional intracortical myelination (ICM), especially in the lateral prefrontal cortex, may be associated with depression, but it is unknown whether it is a precursor or a consequence of MDD. The study of offspring of affected parents offers the opportunity to distinguish between precursors and consequences by examining individuals who carry high risk at a time when they have not experienced depression.

Methods

We acquired 129 T1-weighted and T2-weighted scans from 56 (25 female) unaffected offspring of parents with depression and 114 scans from 63 (34 female) unaffected offspring of parents without a history of depression (ages 9 to 16 years). To assess scan quality, we calculated test-retest reliability. We used the scan ratios to calculate myelin maps for 68 cortical regions. We analyzed data using mixed-effects modeling.

Results

ICM did not differ between high and low familial risk youths in global (B = 0.06, SE = 0.03, p = .06) or regional (B = 0.05, SE = 0.03, p = .08) analyses. Our pediatric sample had high ICM reliability (intraclass correlation coefficient = 0.79; 95% CI, 0.55-0.88).

Conclusions

Based on our results, reduced ICM does not appear to be a precursor of MDD. Future studies should examine ICM in familial high-risk youths across a broad developmental period.

Genetics, epigenetics, and neurobiology of childhood-onset depression: an umbrella review

Depression is a serious and persistent psychiatric disorder that commonly first manifests during childhood. Depression that starts in childhood is increasing in frequency, likely due both to evolutionary trends and to increased recognition of the disorder. In this umbrella review, we systematically searched the extant literature for genetic, epigenetic, and neurobiological factors that contribute to a childhood onset of depression. We searched PubMed, EMBASE, OVID/PsychInfo, and Google Scholar with the following inclusion criteria: (1) systematic review or meta-analysis from a peer-reviewed journal; (2) inclusion of a measure assessing early age of onset of depression; and (3) assessment of neurobiological, genetic, environmental, and epigenetic predictors of early onset depression. Findings from 89 systematic reviews of moderate to high quality suggest that childhood-onset depressive disorders have neurobiological, genetic, environmental, and epigenetic roots consistent with a diathesis-stress theory of depression. This review identified key putative markers that may be targeted for personalized clinical decision-making and provide important insights concerning candidate mechanisms that might underpin the early onset of depression.

deepPGSegNet: MRI-based pituitary gland segmentation using deep learning

Introduction

In clinical research on pituitary disorders, pituitary gland (PG) segmentation plays a pivotal role, which impacts the diagnosis and treatment of conditions such as endocrine dysfunctions and visual impairments. Manual segmentation, which is the traditional method, is tedious and susceptible to inter-observer differences. Thus, this study introduces an automated solution, utilizing deep learning, for PG segmentation from magnetic resonance imaging (MRI).

Methods

A total of 153 university students were enrolled, and their MRI images were used to build a training dataset and ground truth data through manual segmentation of the PGs. A model was trained employing data augmentation and a three-dimensional U-Net architecture with a five-fold cross-validation. A predefined field of view was applied to highlight the PG region to optimize memory usage. The model's performance was tested on an independent dataset. The model's performance was tested on an independent dataset for evaluating accuracy, precision, recall, and an F1 score.

Results and discussion

The model achieved a training accuracy, precision, recall, and an F1 score of 92.7%, 0.87, 0.91, and 0.89, respectively. Moreover, the study explored the relationship between PG morphology and age using the model. The results indicated a significant association between PG volume and midsagittal area with age. These findings suggest that a precise volumetric PG analysis through an automated segmentation can greatly enhance diagnostic accuracy and surveillance of pituitary disorders.

Challenges in Identifying Individualized Brain Biomarkers of Late Life Depression

Research into neuroimaging biomarkers for Late Life Depression (LLD) has identified neural correlates of LLD including increased white matter hyperintensities and reduced hippocampal volume. However, studies into neuroimaging biomarkers for LLD largely fail to converge. This lack of replicability is potentially due to challenges linked to construct variability, etiological heterogeneity, and experimental rigor. We discuss suggestions to help address these challenges, including improved construct standardization, increased sample sizes, multimodal approaches to parse heterogeneity, and the use of individualized analytical models.

The potential role of gray matter volume differences in the association between smoking and depression: A narrative review

Tobacco use and major depression are both leading contributors to the global burden of disease and are also highly comorbid. Previous research indicates bi-directional causality between tobacco use and depression, but the mechanisms that underlie this causality are unclear, especially for the causality from tobacco use to depression. Here we narratively review the available evidence for a potential causal role of gray matter volume in the association. We summarize the findings of large existing neuroimaging meta-analyses, studies in UK Biobank, and the Enhancing NeuroImaging Genetics through MetaAnalysis (ENIGMA) consortium and assess the overlap in implicated brain areas. In addition, we review two types of methods that allow us more insight into the causal nature of associations between brain volume and depression/smoking: longitudinal studies and Mendelian Randomization studies. While the available evidence suggests overlap in the alterations in brain volumes implicated in tobacco use and depression, there is a lack of research examining the underlying pathophysiology. We conclude with recommendations on (genetically-informed) causal inference methods useful for studying these associations.

Functional dysconnectivity in youth depression: Systematic review, meta-analysis, and network-based integration

Youth depression has been associated with heterogenous patterns of aberrant brain connectivity. To make sense of these divergent findings, we conducted a systematic review encompassing 19 resting-state fMRI seed-to-whole-brain studies (1400 participants, comprising 795 youths with major depression and 605 matched healthy controls). We incorporated separate meta-analyses of connectivity abnormalities across the levels of the most commonly seeded brain networks (default-mode and limbic networks) and, based on recent additions to the literature, an updated meta-analysis of amygdala dysconnectivity in youth depression. Our findings indicated broad and distributed findings at an anatomical level, which could not be captured by conventional meta-analyses in terms of spatial convergence. However, we were able to parse the complexity of region-to-region dysconnectivity by considering constituent regions as components of distributed canonical brain networks. This integration revealed dysconnectivity centred on central executive, default mode, salience, and limbic networks, converging with findings from the adult depression literature and suggesting similar neurobiological underpinnings of youth and adult depression.

Stress to inflammation and anhedonia: Mechanistic insights from preclinical and clinical models

Anhedonia, as evidenced by impaired pleasurable response to reward, reduced reward motivation, and/or deficits in reward-related learning, is a common feature of depression. Such deficits in reward processing are also an important clinical target as a risk factor for depression onset. Unfortunately, reward-related deficits remain difficult to treat. To address this gap and inform the development of effective prevention and treatment strategies, it is critical to understand the mechanisms that drive impairments in reward function. Stress-induced inflammation is a plausible mechanism of reward deficits. The purpose of this paper is to review evidence for two components of this psychobiological pathway: 1) the effects of stress on reward function; and 2) the effects of inflammation on reward function. Within these two areas, we draw upon preclinical and clinical models, distinguish between acute and chronic effects of stress and inflammation, and address specific domains of reward dysregulation. By addressing these contextual factors, the review reveals a nuanced literature which might be targeted for additional scientific inquiry to inform the development of precise interventions.

The longitudinal role of family conflict and neural reward sensitivity in youth's internalizing symptoms

Adolescence is often associated with an increase in psychopathology. Although previous studies have examined how family environments and neural reward sensitivity separately play a role in youth's emotional development, it remains unknown how they interact with each other in predicting youth's internalizing symptoms. Therefore, the current research took a biopsychosocial approach to examine this question using two-wave longitudinal data of 9353 preadolescents (mean age = 9.93 years at T1; 51% boys) from the Adolescent Brain Cognitive Development study. Using mixed-effects models, results showed that higher family conflict predicted youth's increased internalizing symptoms 1 year later, whereas greater ventral striatum (VS) activity during reward receipt predicted reduced internalizing symptoms over time. Importantly, there was an interaction effect between family conflict and VS activity. For youth who showed greater VS activation during reward receipt, high family conflict was more likely to predict increased internalizing symptoms. In contrast, youth with low VS activation during reward receipt showed high levels of internalizing symptoms regardless of family conflict. The findings suggest that youth's neural reward sensitivity is a marker of susceptibility to adverse family environments and highlight the importance of cultivating supportive family environments where youth experience less general conflict within the family.

Amygdala and nucleus accumbens activation during reward anticipation moderates the association between life stressor frequency and depressive symptoms

BACKGROUND

Life stressors confer risk for depressive symptoms, but individuals vary in the extent of their sensitivity to life stressors. One protective factor may be an individual's level of reward sensitivity, e.g., a stronger neurobiological response to environmental rewards may mitigate emotional responses to stressors. However, the nature of neurobiological reward sensitivity that corresponds with stress resilience is unknown. Further, this model is untested in adolescence, when life stressor frequency and depression increase.

METHODS

We tested the hypothesis that stronger reward-related activation in the left and right nucleus accumbens (NAc), amygdala, and medial prefrontal cortex (mPFC) attenuates the strength of the stress-depression relation. We measured BOLD activation throughout Win and Lose blocks of a monetary reward task, as well as during anticipation and outcome phases of the task. Participants (N = 151, ages 13-19) were recruited to be stratified on risk for mood disorders to enhance variance in depressive symptoms.

RESULTS

Activation during anticipation of rewards in the bilateral amygdala and NAc, but not mPFC, buffered the association between life stressors and depressive symptoms. This buffering effect was not found for reward outcome activation or activation across Win blocks.

CONCLUSIONS

Results highlight the importance of reward anticipation activation of subcortical structures in attenuating the stress-depression link, suggesting that reward motivation may be a cognitive mechanism through which this stress buffering occurs.

PREDICTING DEPRESSION RISK IN EARLY ADOLESCENCE VIA MULTIMODAL BRAIN IMAGING

Depression is an incapacitating psychiatric disorder with high prevalence in adolescent populations that is influenced by many risk factors, including family history of depression. The ability to predict who may develop depression before adolescence, when rates of depression increase markedly, is important for early intervention and prevention. Using a large longitudinal sample from the Adolescent Brain Cognitive Development (ABCD) Study (2658 participants after imaging quality control, between 9-10 years at baseline), we applied machine learning methods on a set of comprehensive multimodal neuroimaging features to predict depression risk at the two-year follow-up from the baseline visit. Features include derivatives from structural MRI, diffusion tensor imaging, and task and rest functional MRI. A rigorous cross-validation method of leave-one-site-out was used. Additionally, we tested the prediction models in a high-risk group of participants with parental history of depression (N=625). The results showed all brain features had prediction scores significantly better than expected by chance. When predicting depression onset in the high-risk group, brain features from resting-state functional connectomes showed the best classification performance, outperforming other brain features based on structural MRI and task-based fMRI. Results demonstrate that the functional connectivity of the brain can predict the risk of depression in early adolescence better than other univariate neuroimaging derivatives, highlighting the key role of the interacting elements of the connectome capturing more individual variability in psychopathology compared to measures of single brain regions.

Annual Research Review: Emotion processing in offspring of mothers with depression diagnoses - a systematic review of neural and physiological research

BACKGROUND

Theories of the intergenerational transmission of depression emphasize alterations in emotion processing among offspring of depressed mothers as a key risk mechanism, raising questions about biological processes contributing to these alterations. The objective of this systematic annual research review was to examine and integrate studies of the associations between maternal depression diagnoses and offspring's emotion processing from birth through adolescence across biological measures including autonomic psychophysiology, electroencephalography (EEG), magnetoencephalography (MEG), event-related potentials (ERP), and structural and functional magnetic resonance imaging (MRI).

METHODS

The review was conducted in accordance with the PRISMA 2020 standards. A systematic search was conducted in PsycInfo and PubMed in 2022 for studies that included, 1) mothers with and without DSM-defined depressive disorders assessed via a clinical or diagnostic interview, and 2) measures of offspring emotion processing assessed at the psychophysiological or neural level between birth and 18 years of age.

RESULTS

Findings from 64 studies indicated that young offspring of mothers with depression histories exhibit heightened corticolimbic activation to negative emotional stimuli, reduced left frontal brain activation, and reduced ERP and mesocorticolimbic responses to reward cues compared to offspring of never-depressed mothers. Further, activation of resting-state networks involved in affective processing differentiate offspring of depressed relative to nondepressed mothers. Some of these alterations were only apparent among youth of depressed mothers exposed to negative environmental contexts or exhibiting current emotional problems. Further, some of these patterns were observable in infancy, reflecting very early emerging vulnerabilities.

CONCLUSIONS

This systematic review provides evidence that maternal depression is associated with alterations in emotion processing across several biological units of analysis in offspring. We present a preliminary conceptual model of the role of deficient emotion processing in pathways from maternal depression to offspring psychopathology and discuss future research avenues addressing limitations of the existing research and clinical implications.

Frontolimbic Network Topology Associated With Risk and Presence of Depression in Adolescents: A Study Using a Composite Risk Score in Brazil

BACKGROUND

There have been significant challenges in understanding functional brain connectivity associated with adolescent depression, including the need for a more comprehensive approach to defining risk, the lack of representation of participants from low- and middle-income countries, and the need for network-based approaches to model connectivity. The current study aimed to address these challenges by examining resting-state functional connectivity of frontolimbic circuitry associated with the risk and presence of depression in adolescents in Brazil.

METHODS

Adolescents in Brazil ages 14 to 16 years were classified into low-risk, high-risk, and depressed groups using a clinical assessment and composite risk score that integrates 11 sociodemographic risk variables. After excluding participants with excessive head movement, resting-state functional magnetic resonance imaging data of 126 adolescents were analyzed. We compared group differences in frontolimbic network connectivity using region of interest-to-region of interest, graph theory, and seed-based connectivity analyses. Associations between self-reported depressive symptoms and brain connectivity were also explored.

RESULTS

Adolescents with depression showed greater dorsal anterior cingulate cortex (ACC) connectivity with the orbitofrontal cortex compared with the 2 risk groups and greater dorsal ACC global efficiency than the low-risk group. Adolescents with depression also showed reduced local efficiency and a lower clustering coefficient of the subgenual ACC compared with the 2 risk groups. The high-risk group also showed a lower subgenual ACC clustering coefficient relative to the low-risk group.

CONCLUSIONS

These findings highlight altered connectivity and topology of the ACC within frontolimbic circuitry as potential neural correlates and risk factors of developing depression in adolescents in Brazil. This study broadens our understanding of the neural connectivity associated with adolescent depression in a global context.

IABC: A Toolbox for Intelligent Analysis of Brain Connectivity

Brain functional networks and connectivity have played an important role in exploring brain function for understanding the brain and disclosing the mechanisms of brain disorders. Independent component analysis (ICA) is one of the most widely applied data-driven methods to extract brain functional networks/connectivity. However, it is hard to guarantee the reliability of networks/connectivity due to the randomness of component order and the difficulty in selecting an optimal component number in ICA. To facilitate the analysis of brain functional networks and connectivity using ICA, we developed a MATLAB toolbox called Intelligent Analysis of Brain Connectivity (IABC). IABC incorporates our previously proposed group information guided independent component analysis (GIG-ICA), NeuroMark, and splitting-merging assisted reliable ICA (SMART ICA) methods, which can estimate reliable individual-subject neuroimaging measures for further analysis. After user inputs functional magnetic resonance imaging (fMRI) data of multiple subjects that are regularly organized (e.g., in Brain Imaging Data Structure (BIDS)) and clicks a few buttons to set parameters, IABC automatically outputs brain functional networks, their related time courses, and functional network connectivity of each subject. All these neuroimaging measures are promising for providing clues in understanding brain function and differentiating brain disorders.

Social environment and brain structure in adolescent mental health: A cross-sectional structural equation modelling study using IMAGEN data

Adolescent mental health is impacted by a myriad of factors, including the developing brain, socioeconomic conditions and changing social relationships. Studies to date have neglected investigating those factors simultaneously, despite evidence of their interacting effects and distinct profiles for males and females. The current study addressed that gap by applying structural equation modelling to IMAGEN data from adolescents aged 14 years (n = 1950). A multi-group model split by sex was tested with the variables of socioeconomic stress, family support, peer problems, and brain structure as predictors, and emotional symptoms as the main outcome. Findings indicated that, for both sexes, peer problems were positively associated with emotional symptoms, and socioeconomic stress was negatively associated with family support. Additionally, there were sex-specific findings within the full models: ventromedial prefrontal cortex grey matter volume was negatively associated with emotional symptoms for males when corrected for whole brain volume, and socioeconomic stress was negatively associated with whole brain volume for females. This study underscores the importance of the peer environment for early adolescent emotional symptoms in both boys and girls, but goes further to suggest distinct gender associations with socioeconomic factors and brain structure which provides a multi-level view of risk and resilience. Future research could exploit existing IMAGEN longitudinal data to strengthen causal claims and to determine the potential longstanding impact of social environment and brain development on adolescent mental health.

Resting state functional connectivity as a marker of internalizing disorder onset in high-risk youth

While research has linked alterations in functional connectivity of the default mode (DMN), cognitive control (CCN), and salience networks (SN) to depression and anxiety, little research has examined whether these alterations may be premorbid vulnerabilities. This study examined resting state functional connectivity (RSFC) of the CCN, DMN, and SN as markers of risk for developing an onset of a depressive or anxiety disorder in adolescents at high familial risk for these disorders. At baseline, 135 participants aged 11-17 completed resting-state functional magnetic resonance imaging, measures of internalizing symptoms, and diagnostic interviews to assess history of depressive and anxiety disorders. Diagnostic assessments were completed again at 9- or 18-month follow-up for 112 participants. At baseline, increased CCN connectivity to areas of the visual network, and decreased connectivity between the left SN and the precentral gyrus, predicted an increased likelihood of a new onset at follow-up. Increased connectivity between the right SN and postcentral gyrus at baseline predicted first episode onsets at follow-up. Altered connectivity between these regions may represent a risk factor for developing a clinically significant onset of an internalizing disorder. Results may have implications for understanding the neural bases of internalizing disorders for early identification and prevention efforts.

Neural function underlying reward expectancy and attainment in adolescents with diverse psychiatric symptoms

Reward dysfunction has been hypothesized to play a key role in the development of psychiatric conditions during adolescence. To help capture the complexity of reward function in youth, we used the Reward Flanker fMRI Task, which enabled us to examine neural activity during expectancy and attainment of both certain and uncertain rewards. Participants were 84 psychotropic-medication-free adolescents, including 67 with diverse psychiatric conditions and 17 healthy controls. Functional MRI used high-resolution acquisition and high-fidelity processing techniques modeled after the Human Connectome Project. Analyses examined neural activation during reward expectancy and attainment, and their associations with clinical measures of depression, anxiety, and anhedonia severity, with results controlled for family-wise errors using non-parametric permutation tests. As anticipated, reward expectancy activated regions within the fronto-striatal reward network, thalamus, occipital lobe, superior parietal lobule, temporoparietal junction, and cerebellum. Unexpectedly, however, reward attainment was marked by widespread deactivation in many of these same regions, which we further explored using cosine similarity analysis. Across all subjects, striatum and thalamus activation during reward expectancy negatively correlated with anxiety severity, while activation in numerous cortical and subcortical regions during reward attainment positively correlated with both anxiety and depression severity. These findings highlight the complexity and dynamic nature of neural reward processing in youth.

Neural markers of familial risk for depression - A systematic review

Structural and functional brain alterations are found in adults with depression. It is not known whether these changes are a result of illness or exist prior to disorder onset. Asymptomatic offspring of parents with depression offer a unique opportunity to research neural markers of familial risk to depression and clarify the temporal sequence between brain changes and disorder onset. We conducted a systematic review to investigate whether asymptomatic offspring at high familial risk have structural and functional brain changes like those reported in adults with depression. Our literature search resulted in 44 studies on 18,645 offspring ranging from 4 weeks to 25 years old. Reduced cortical thickness and white matter integrity, and altered striatal reward processing were the most consistent findings in high-risk offspring across ages. These alterations are also present in adults with depression, suggesting the existence of neural markers of familial risk for depression. Additional studies reproducing current results, streamlining fMRI data analyses, and investigating underexplored topics (i.e intracortical myelin, gyrification, subcortical shape) may be among the next steps required to improve our understanding of neural markers indexing the vulnerability to depression.

Exploring the course of adolescent anxiety and depression: associations with white matter tract microstructure

Cross-sectional Diffusion Tensor Imaging (DTI) studies have reported alterations in white matter (WM) microstructure in adolescents with internalizing psychopathology. Yet, longitudinal studies investigating the course of WM microstructure are lacking. This study explored WM alterations and its relation to clinical symptoms over time in adolescents with internalizing disorders. DTI scans were acquired at baseline and after three months in 22 adolescents with clinical depression and comorbid anxiety (INT), and 21 healthy peers (HC) (age: 12-18). Tract-based spatial statistics was used for three voxelwise analyses: i) changes in WM microstructure between and within the INT and HC group; ii) associations between changes in symptom severity and changes in WM microstructure within youths with INT; and iii) associations between baseline WM parameters with changes in symptom severity within youths with INT. Data did not reveal changes in WM microstructure between or within groups over three months' time nor associations between changes in WM microstructure and changes in self-reported symptoms (analyses corrected for age, gender and puberty stage). Lower baseline levels of fractional anisotropy (FA) in the right posterior corona radiata (PCR) and right cingulum were associated with a higher decrease of depressive symptoms within the INT group. Post hoc analysis of additional WM parameters in the significant FA clusters showed that higher levels of baseline mean diffusivity and radial diffusivity in the PCR were associated with a lower decrease in depressive symptoms. Baseline WM microstructure characteristics were associated with a higher decrease in depressive symptoms over time. These findings increase our understanding of neurobiological mechanisms underlying the course of internalizing disorders in adolescents.

Adolescent depression and resting-state fMRI brain networks: a scoping review of longitudinal studies

The neurobiological factors associated with the emergence of major depressive disorder (MDD) in adolescence are still unclear. Previous cross-sectional studies have documented aberrant connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) networks. However, whether these findings precede MDD onset has not been established. This scoping review mapped key methodological aspects and main findings of longitudinal rs-fMRI studies of MDD in adolescence. Three sets of neuroimaging methods to analyze rs-fMRI data were identified: seed-based analysis, independent component analysis, and network-based approaches. Main findings involved aberrant connectivity within and between the default mode network (DMN), the cognitive control network (CCN), and the salience network (SN). Accordingly, we utilized Menon's (2011) triple-network model for neuropsychiatric disorders to summarize key results. Adolescent MDD was associated with hyperconnectivity within the SN and between DMN and SN, as well as hypoconectivity within the CCN. These findings suggested that dysfunctional connectivity among the three main large-scale brain networks preceded MDD onset. However, there was high heterogeneity in neuroimaging methods and sampling procedures, which may limit comparisons between studies. Future studies should consider some level of harmonization for clinical instruments and neuroimaging methods.

Brain morphometry and connectivity differs between adolescent- and adult-onset major depressive disorder

BACKGROUND

Early-onset (EO) major depressive disorder (MDD) patients experience more depressive episodes and an increased risk of relapse. Thus, on a neurobiological level, adult EO patients might display brain structure and function different from adult-onset (AO) patients.

METHODS

A total of 103 patients (66 females) underwent magnetic resonance imaging. Structural measures of gray matter volume (GMV) and functional connectivity networks during resting state were compared between EO (≤19 years) and AO groups. Four residual major depression symptoms, mood, anxiety, insomnia, and somatic symptoms, were correlated with GMV between groups.

RESULTS

We found comparatively increased GMV in the EO group, namely the medial prefrontal and insular cortex, as well as the anterior hippocampus. Functional networks in EO patients showed a comparatively weaker synchronization of the left hippocampus with the adjacent amygdala, and a stronger integration with nodes in the contralateral prefrontal cortex and supramarginal gyrus. Volumetric analysis of depression symptoms associated the caudate nuclei with symptoms of insomnia, and persisting mood symptoms with the right amygdala, while finding no significant clusters for somatic and anxiety symptoms.

CONCLUSIONS

The study highlights the important role of the hippocampus and the prefrontal cortex in EO patients as part of emotion-regulation networks. Results in EO patients demonstrated subcortical volume changes irrespective of sleep and mood symptom recovery, which substantiates adolescence as a pivotal developmental phase for MDD. Longitudinal studies are needed to differentiate neural recovery trajectories while accounting for age of onset.

Reward- and threat-related neural function associated with risk and presence of depression in adolescents: a study using a composite risk score in Brazil

BACKGROUND

Neuroimaging studies on adolescents at risk for depression have relied on a single risk factor and focused on adolescents in high-income countries. Using a composite risk score, this study aims to examine neural activity and connectivity associated with risk and presence of depression in adolescents in Brazil.

METHODS

Depression risk was defined with the Identifying Depression Early in Adolescence Risk Score (IDEA-RS), calculated using a prognostic model that included 11 socio-demographic risk factors. Adolescents recruited from schools in Porto Alegre were classified into a low-risk (i.e., low IDEA-RS and no lifetime depression), high-risk (i.e., high IDEA-RS and no lifetime depression), or clinically depressed group (i.e., high IDEA-RS and depression diagnosis). One hundred fifty adolescents underwent a functional MRI scan while completing a reward-related gambling and a threat-related face-matching task. We compared group differences in activity and connectivity of the ventral striatum (VS) and amygdala during the gambling and face-matching tasks, respectively, and group differences in whole-brain neural activity.

RESULTS

Although there was no group difference in reward-related VS or threat-related amygdala activity, the depressed group showed elevated VS activity to punishment relative to high-risk adolescents. The whole-brain analysis found reduced reward-related activity in the lateral prefrontal cortex of patients and high-risk adolescents compared with low-risk adolescents. Compared with low-risk adolescents, high-risk and depressed adolescents showed reduced threat-related left amygdala connectivity with thalamus, superior temporal gyrus, inferior parietal gyrus, precentral gyrus, and supplementary motor area.

CONCLUSIONS

We identified neural correlates associated with risk and presence of depression in a well-characterized sample of adolescents. These findings enhance knowledge of the neurobiological underpinnings of risk and presence of depression in Brazil. Future longitudinal studies are needed to examine whether the observed neural patterns of high-risk adolescents predict the development of depression.

Predicting Depression Onset in Young People Based on Clinical, Cognitive, Environmental, and Neurobiological Data

BACKGROUND

Adolescent onset of depression is associated with long-lasting negative consequences. Identifying adolescents at risk for developing depression would enable the monitoring of risk factors and the development of early intervention strategies. Using machine learning to combine several risk factors from multiple modalities might allow prediction of depression onset at the individual level.

METHODS

A subsample of a multisite longitudinal study in adolescents, the IMAGEN study, was used to predict future (subthreshold) major depressive disorder onset in healthy adolescents. Based on 2-year and 5-year follow-up data, participants were grouped into the following: 1) those developing a diagnosis of major depressive disorder or subthreshold major depressive disorder and 2) healthy control subjects. Baseline measurements of 145 variables from different modalities (clinical, cognitive, environmental, and structural magnetic resonance imaging) at age 14 years were used as input to penalized logistic regression (with different levels of penalization) to predict depression onset in a training dataset (n = 407). The features contributing the highest to the prediction were validated in an independent hold-out sample (three independent IMAGEN sites; n = 137).

RESULTS

The area under the receiver operating characteristic curve for predicting depression onset ranged between 0.70 and 0.72 in the training dataset. Baseline severity of depressive symptoms, female sex, neuroticism, stressful life events, and surface area of the supramarginal gyrus contributed most to the predictive model and predicted onset of depression, with an area under the receiver operating characteristic curve between 0.68 and 0.72 in the independent validation sample.

CONCLUSIONS

This study showed that depression onset in adolescents can be predicted based on a combination multimodal data of clinical characteristics, life events, personality traits, and brain structure variables.

Associations Between Parental Mood and Anxiety Psychopathology and Offspring Brain Structure: A Scoping Review

A family history of mood and anxiety disorders is one of the most well-established risk factors for these disorders in offspring. A family history of these disorders has also been linked to alterations in brain regions involved in cognitive-affective processes broadly, and mood and anxiety disorders specifically. Results from studies of brain structure of children of parents with a history of mood or anxiety disorders (high-risk offspring) have been inconsistent. We followed the PRISMA protocol to conduct a scoping review of the literature linking parental mood and anxiety disorders to offspring brain structure to examine which structures in offspring brains are linked to parental major depressive disorder (MDD), anxiety, or bipolar disorder (BD). Studies included were published in peer-reviewed journals between January 2000 and July 2021. Thirty-nine studies were included. Significant associations between parental BD and offspring caudate volume, inferior frontal gyrus thickness, and anterior cingulate cortex thickness were found. Associations were also identified between parental MDD and offspring amygdala and hippocampal volumes, fusiform thickness, and thickness in temporoparietal regions. Few studies have examined associations between parental anxiety and high-risk offspring brain structure; however, one study found associations between parental anxiety symptoms and offspring amygdala structure, and another found similar associations with the hippocampus. The direction of grey matter change across studies was inconsistent, potentially due to the large age ranges for each study and the non-linear development of the brain. Children of parents with MDD and bipolar disorders, or elevated anxiety symptoms, show alterations in a range of brain regions. Results may further efforts to identify children at high risk for affective disorders and may elucidate whether alterations in specific brain regions represent premorbid markers of risk for mood and anxiety disorders.

A Functional Near-Infrared Spectroscopy Examination of the Neural Correlates of Mental Rotation for Individuals With Different Depressive Tendencies

The present study aimed to examine the neural mechanisms underlying the ability to process the mental rotation with mirrored stimuli for different depressive tendencies with psychomotor retardation. Using functional near-infrared spectroscopy (fNIRS), we measured brain cortex activation of participants with higher and lower depressive tendencies while performing a left-right paradigm of object mental rotation or a same-different paradigm of subject mental rotation. Behavioral data revealed no differences in reaction time and rotation speed. The fNIRS data revealed a higher deactivation of oxyhemoglobin (HbO) change for the higher depression group in the perceptual stage of object mental rotation with mirrored stimuli in the superior external frontal cortex (BA46), inferior frontal gyrus (BA45), premotor cortex (BA6), and primary motor cortex (BA4) (study 1). In addition, there existed a significant difference between the two groups in premotor cortex (BA6) in subject mental rotation with mirrored stimuli (study 2). These results suggest that the neural mechanism of higher depression individuals connected with psychomotor retardation exists in the frontal and motor areas when processing object mental rotation with mirrored stimuli, and the motor cortex when processing subject mental rotation.

Correlations between facial emotion processing and biochemical abnormalities in untreated adolescent patients with major depressive disorder: A proton magnetic resonance spectroscopy study

BACKGROUND

Studies show that disturbances of the fronto-striato-thalamic-cerebellar circuit could be correlated to facial emotion processing (FEP) biases in major depressive disorder (MDD). Nevertheless, the underlying mechanism of natural metabolism-emotion relationships in adolescent MDD remains unclear.

METHODS

Thirty-seven adolescent patients with MDD and 30 healthy controls completed FEP tasks using the Chinese Facial Affective Picture System (CAFPS). Proton magnetic resonance spectroscopy (¹H-MRS) was also used to obtain ratios of N-acetylaspartate (NAA) /creatine (Cr) and choline (Cho) /Cr ratios in the prefrontal cortex (PFC), anterior cingulate cortex (ACC), putamen, thalamus and cerebellum. Correlations between abnormal neurometabolic ratios and FEP were also computed.

RESULTS

Compared with the control group, the MDD group had significantly lower accuracy and perception intensity of happiness, and significantly higher accuracy of disgust and perception intensity of sad and fearful faces in FEP tasks. Compared to healthy controls, adolescent patients with MDD showed significantly lower NAA/Cr ratios in the left PFC, higher NAA/Cr ratios in the right thalamus, and higher Cho/Cr ratios in the right putamen, although there were no significant differences in metabolites in the ACC and cerebellum between two groups. In the MDD group, NAA/Cr ratios of the right thalamus were negatively correlated with happy reaction time and positively correlated with sad, anger, and fear intensity; Cho/Cr ratios in the right putamen were positively correlated with fear reaction time.

CONCLUSIONS

Our findings suggest that FEP bias may exist in adolescents with MDD, while the impairment of FEP may be associated with abnormal metabolites in the fronto-striato-thalamic circuit.

Preventive strategies for adolescent depression: What are we missing? A focus on biomarkers

Adolescent depression is an important global issue with several unmet needs that still must be addressed and, to date, there are only few effective preventive strategies to reduce the burden of this disorder worldwide. In this mini-review, the evidence and potential ways to improve an early detection will be discussed as well as prompt interventions by focusing on a better understanding of the risks underlying the developing of adolescent depression from both a sociodemographic and a biological perspective.

Dose-dependent opposite effects of nortriptyline on affective-like behavior in adolescent rats: Comparison with adult rats

Antidepressant drugs elicit different behavioral and neurochemical responses with age. In fact, the use of antidepressants during adolescence is associated with an increased risk of suicidal thinking, being the best pharmacological treatment during this critical period a matter of constant debate in terms of its risk-benefit outcome. In this regard, the present study compared the effects of nortriptyline (3-10 mg/kg, 7 days) on regulating different aspects of affective-like behavior by screening adolescent and adult Sprague-Dawley rats through several consecutive tests (forced-swim, open field, sucrose preference). Brains were later collected to evaluate hippocampal neurogenesis and mBDNF protein content as potential molecular correlates of the observed behavioral responses. The main results in adolescent rats showed that nortriptyline induced dose-dependent opposite effects: while 3 mg/kg decreased immobility and increased mBDNF (indicative of an antidepressant-like response), 10 mg/kg decreased exploratory time in the open field and mBDNF (suggestive of an anxiogenic-like response). These effects were not associated with changes in neurogenesis regulation. In adult rats, nortriptyline failed to modulate affective-like behavior or the neuroplasticity markers evaluated at the doses tested. In conclusion, clear behavioral and neurochemical differences were observed between adolescent and adult rats in response to nortriptyline treatment. Interestingly, while nortriptyline displayed an antidepressant-like potential at the lowest dose examined in adolescence, a higher dose shifted these results towards a negative outcome, thus reinforcing the need to extreme caution when considering this treatment for our younger population.

Medial prefrontal brain activity correlates with emerging symptoms of anxiety and depression in late adolescence: A fNIRS study

The brain undergoes dramatic changes over the course of the adolescent years, and these developmental changes are implicated in the emergence of disorders that involve negative emotionality. Late adolescence might be the window within which brain networks manifest vulnerabilities to depressive and anxiety symptomology; particularly within the prefrontal cortex (PFC), which houses emotional control (dorsolateral) and emotional processing (medial) nodes. Given the comorbidity of depressive and anxious symptomology, it may be that the neural signature is similar for both within the developing PFC. In a sample of 67 adolescents (M = 15.97 years, SD = 1.36), we used functional near-infrared spectroscopy (fNIRS) to examine the neural signature of emergent anxiety and depressive symptoms among younger and older adolescents. We further examined the extent to which neural signatures of anxiety and depressive symptoms within the PFC were similar or different. Findings revealed that self-reported anxiety and depressive symptoms were highly correlated, and that the neural signatures of both within the PFC were similar, corresponding with the medial subregions of the PFC (i.e., those involved in evaluative processing). These findings were evident only in later adolescence, suggesting the possibility of a common vulnerability for anxiety and depressive disorders emerging around this developmental window.

Multimodal Investigations of Reward Circuitry and Anhedonia in Adolescent Depression

Depression is a highly prevalent condition with devastating personal and public health consequences that often first manifests during adolescence. Though extensively studied, the pathogenesis of depression remains poorly understood, and efforts to stratify risks and identify optimal interventions have proceeded slowly. A major impediment has been the reliance on an all-or-nothing categorical diagnostic scheme based solely on whether a patient endorses an arbitrary number of common symptoms for a sufficiently long period. This approach masks the well-documented heterogeneity of depression, a disorder that is highly variable in presentation, severity, and course between individuals and is frequently comorbid with other psychiatric conditions. In this targeted review, we outline the limitations of traditional diagnosis-based research and instead advocate an alternative approach centered around symptoms as unique dimensions of clinical dysfunction that span across disorders and more closely reflect underlying neurobiological abnormalities. In particular, we highlight anhedonia-the reduced ability to anticipate and experience pleasure-as a specific, quantifiable index of reward dysfunction and an ideal candidate for dimensional investigation. Anhedonia is a core symptom of depression but also a salient feature of numerous other conditions, and its severity varies widely within clinical and even healthy populations. Similarly, reward dysfunction is a hallmark of depression but is evident across many psychiatric conditions. Reward function is especially relevant in adolescence, a period characterized by exaggerated reward-seeking behaviors and rapid maturation of neural reward circuitry. We detail extensive work by our research group and others to investigate the neural and systemic factors contributing to reward dysfunction in youth, including our cumulative findings using multiple neuroimaging and immunological measures to study depressed adolescents but also trans-diagnostic cohorts with diverse psychiatric symptoms. We describe convergent evidence that reward dysfunction: (a) predicts worse clinical outcomes, (b) is associated with functional and chemical abnormalities within and beyond the neural reward circuitry, (c) is linked to elevated peripheral levels of inflammatory biomarkers, and (d) manifests early in the course of illness. Emphasis is placed on high-resolution neuroimaging techniques, comprehensive immunological assays, and data-driven analyses to fully capture and characterize the complex, interconnected nature of these systems and their contributions to adolescent reward dysfunction.

Multiple domains of risk factors for first onset of depression in adolescent girls

BACKGROUND

First onsets of depression are especially common in adolescent females and often develop into chronic/recurrent illness. Surprisingly few studies have comprehensively evaluated multiple domains of etiologically-informative risk factors for first onset in adolescents from the community. We investigated whether clinical, cognitive, personality, interpersonal, and biological risk factors prospectively predict a first onset of depressive disorder (DD), and of DD with a chronic/recurrent course, in a community sample of adolescent girls.

METHODS

479 girls (13.5-15.5 years) with no history of DD completed baseline assessments of risk factors and five diagnostic assessments over 3 years. Baseline measures were analyzed separately and jointly to prospectively predict first-onset DD and first-onset chronic/recurrent DD.

RESULTS

Most risk factors predicted first-onset DD (n = 93), including depressive symptoms, anxiety disorders, rumination, personality traits, blunted neural response (late positive potential [LPP]) to unpleasant pictures, peer victimization, parental criticism, and parental mood disorder. Depressive symptoms, rumination, parental mood disorder, and parental criticism were independently associated with first onsets. Nearly all measures, including a blunted neural response to rewards (reward positivity [RewP]), also predicted first-onset chronic/recurrent DD (n = 52), with depressive symptoms, low extraversion, poor peer relationships, and blunted RewP emerging as independent risk factors.

LIMITATIONS

This study focused on adolescent females and therefore does not provide information on males.

CONCLUSIONS

Multiple domains of risk factors in early adolescence are prospectively associated with first-onset DD and chronic/recurrent DD. A smaller subset of risk factors uniquely contributing to first onsets may represent core vulnerabilities for adolescent-onset depression and promising prevention targets.

Reward Versus Nonreward Sensitivity of the Medial Versus Lateral Orbitofrontal Cortex Relates to the Severity of Depressive Symptoms

BACKGROUND

The orbitofrontal cortex (OFC) is implicated in depression. The hypothesis investigated was whether the OFC sensitivity to reward and nonreward is related to the severity of depressive symptoms.

METHODS

Activations in the monetary incentive delay task were measured in the IMAGEN cohort at ages 14 years (n = 1877) and 19 years (n = 1140) with a longitudinal design. Clinically relevant subgroups were compared at ages 19 (high-severity group: n = 116; low-severity group: n = 206) and 14.

RESULTS

The medial OFC exhibited graded activation increases to reward, and the lateral OFC had graded activation increases to nonreward. In this general population, the medial and lateral OFC activations were associated with concurrent depressive symptoms at both ages 14 and 19 years. In a stratified high-severity depressive symptom group versus control group comparison, the lateral OFC showed greater sensitivity for the magnitudes of activations related to nonreward in the high-severity group at age 19 (p = .027), and the medial OFC showed decreased sensitivity to the reward magnitudes in the high-severity group at both ages 14 (p = .002) and 19 (p = .002). In a longitudinal design, there was greater sensitivity to nonreward of the lateral OFC at age 14 for those who exhibited high depressive symptom severity later at age 19 (p = .003).

CONCLUSIONS

Activations in the lateral OFC relate to sensitivity to not winning, were associated with high depressive symptom scores, and at age 14 predicted the depressive symptoms at ages 16 and 19. Activations in the medial OFC were related to sensitivity to winning, and reduced reward sensitivity was associated with concurrent high depressive symptom scores.

Predictive modeling of depression and anxiety using electronic health records and a novel machine learning approach with artificial intelligence

Generalized anxiety disorder (GAD) and major depressive disorder (MDD) are highly prevalent and impairing problems, but frequently go undetected, leading to substantial treatment delays. Electronic health records (EHRs) collect a great deal of biometric markers and patient characteristics that could foster the detection of GAD and MDD in primary care settings. We approached the problem of predicting MDD and GAD using a novel machine learning pipeline to re-analyze data from an observational study. The pipeline constitutes an ensemble of algorithmically distinct machine learning methods, including deep learning. A sample of 4,184 undergraduate students completed the study, undergoing a general health screening and completing a psychiatric assessment for MDD and GAD. After explicitly excluding all psychiatric information, 59 biomedical and demographic features from the general health survey in addition to a set of engineered features were used for model training. We assessed the model's performance on a held-out test set and found an AUC of 0.73 (sensitivity: 0.66, specificity: 0.7) and 0.67 (sensitivity: 0.55, specificity: 0.7) for GAD, and MDD, respectively. Additionally, we used advanced techniques (SHAP values) to illuminate which features had the greatest impact on prediction for each disease. The top predictive features for MDD were being satisfied with living conditions and having public health insurance. The top predictive features for GAD were vaccinations being up to date and marijuana use. Our results indicate moderate predictive performance for the application of machine learning methods in detection of GAD and MDD based on EHR data. By identifying important predictors of GAD and MDD, these results may be used in future research to aid in the early detection of MDD and GAD.

Dissecting diagnostic heterogeneity in depression by integrating neuroimaging and genetics

Depression is a heterogeneous and etiologically complex psychiatric syndrome, not a unitary disease entity, encompassing a broad spectrum of psychopathology arising from distinct pathophysiological mechanisms. Motivated by a need to advance our understanding of these mechanisms and develop new treatment strategies, there is a renewed interest in investigating the neurobiological basis of heterogeneity in depression and rethinking our approach to diagnosis for research purposes. Large-scale genome-wide association studies have now identified multiple genetic risk variants implicating excitatory neurotransmission and synapse function and underscoring a highly polygenic inheritance pattern that may be another important contributor to heterogeneity in depression. Here, we review various sources of phenotypic heterogeneity and approaches to defining and studying depression subtypes, including symptom-based subtypes and biology-based approaches to decomposing the depression syndrome. We review "dimensional," "categorical," and "hybrid" approaches to parsing phenotypic heterogeneity in depression and defining subtypes using functional neuroimaging. Next, we review recent progress in neuroimaging genetics (correlating neuroimaging patterns of brain function with genetic data) and its potential utility for generating testable hypotheses concerning molecular and circuit-level mechanisms. We discuss how genetic variants and transcriptomic profiles may confer risk for depression by modulating brain structure and function. We conclude by highlighting several promising areas for future research into the neurobiological underpinnings of heterogeneity, including efforts to understand sexually dimorphic mechanisms, the longitudinal dynamics of depressive episodes, and strategies for developing personalized treatments and facilitating clinical decision-making.

Relationship between depression and dorsolateral prefronto-thalamic tract injury in patients with mild traumatic brain injury

The prefrontal lobe has been considered to be closely related to depression. This study examined the relationship between depression and three prefronto-thalamic tract (PF-TT) regions (the dorsolateral prefronto-thalamic tract [DLPF-TT], ventrolateral prefronto-thalamic tract [VLPF-TT], and the orbitofronto-thalamic tract [OF-TT]) in patients with mild traumatic brain injury (TBI), using diffusion tensor tractography (DTT). Thirty-seven patients with depression following mild TBI were recruited based on Beck Depression Inventory-II (BDI-II) scores. Thirty-one normal control subjects were also recruited. The three regions of the PF-TTs were reconstructed using probabilistic tractography and DTT parameters for each of the three PF-TT regions were determined. The tract volume of the DLPF-TT and OF-TT in the patient group showed a significant decrease compared to that of the control group (p < 0.05). The BDI-II score of the patient group showed a moderate negative correlation with the tract volume value of the right (r =  − 0.33) and left (r =  − 0.41) DLPF-TT (p < 0.05). On the other hand, no significant correlations were detected between the BDI-II score of the patient group and the values of the other DTT parameters values for the three PF-TT regions (p > 0.05). Using DTT, depression was found to be closely related to a DLPF-TT injury in patients with mild TBI. We believe that evaluation of the DLPF-TT using DTT would be helpful when assessing patients with depression following mild TBI. These results can provide useful information regarding the proper application of neuromodulation in the management of depression.

Critical appraisal of clinical practice guidelines for depression in children and adolescents: A protocol for systematic review

BACKGROUND

Depression as a clinically significant and growing public health issue is the third leading cause of disability. Adolescent-onset depression has been associated with psychiatric, anxiety disorders, suicidality, medical comorbidities, and an elevated risk of major depressive disorder episodes later in life. How to effectively identify, prevent, and treat depression has become one of the key points of discussion among medical institutions/departments. With the importance of depression being emphasized, countries/organizations around the world have developed guidelines for clinical practice related to depression for different groups of people to guide medical staff to implement scientific, effective, and standardized depression management. However, the quality of such guidelines is not yet clear, which is not conducive to the selection of medical staff and affects clinical application to a certain extent. This study aims to evaluate the rigor of the development of clinical practice guidelines (CPGs) for depression in children and adolescents and will identify, in these documents, the recommendations for depression in children and adolescents.

METHODS

Electronic databases and specific databases of CPGs will be searched. Study selection and data extraction will be performed independently by 2 reviewers. The AGREE II Instrument and RIGHT checklist will be used to assess the methodological quality and reporting quality of included CPGs about depression in children and adolescents. We will also analyze consistency and inconsistency of the recommendations in CPGs, including assessment, diagnosis, screening, treatment, and management. Bubble charts will be used to show the differences in methodological and reporting quality. Subgroup analysis will be conducted according to the result of evaluation. Excel and Endnote X9 will be used.

RESULTS

Using the search drafts of electronic databases, we included 6 CPGs. The results of our study will be published in a peer-reviewed journal.

CONCLUSIONS

Our study will provide systematic evidence for existing CPGs for depression in children and adolescents and provide a guidance for CPGs users.

PROTOCOL REGISTRATION

INPLASY202080002.

Decreased sensitivity in adolescent versus adult rats to the antidepressant-like effects of cannabidiol

RATIONALE

Cannabidiol is a non-psychoactive phytocannabinoid with great therapeutic potential in diverse psychiatric disorders; however, its antidepressant potential has been mainly ascertained in adult rats.

OBJECTIVES

To compare the antidepressant-like response induced by cannabidiol in adolescent and adult rats and the possible parallel modulation of hippocampal neurogenesis.

METHODS

Male Sprague-Dawley rats were repeatedly treated with cannabidiol (3, 10, and 30 mg/kg) or vehicle (1 mL/kg) during adolescence (postnatal days, PND 27-33) or adulthood (PND 141-147) and exposed to 3 consecutive tests (forced swim, open field, two-bottle choice) that quantified behavioral despair, anxiety, and sucrose intake respectively.

RESULTS

Cannabidiol induced differential effects depending on the age and dose administered, with a decreased sensitivity observed in adolescent rats: (1) cannabidiol (30 mg/kg) decreased body weight only in adult rats; (2) cannabidiol ameliorated behavioral despair in adolescent and adult rats, but with a different dose sensitivity (10 vs. 30 mg/kg), and with a different extent (2 vs. 21 days post-treatment); (3) cannabidiol did not modulate anxiety-like behavior at any dose tested in adolescent or adult rats; and (4) cannabidiol increased sucrose intake in adult rats.

CONCLUSIONS

Our findings support the notion that cannabidiol exerts antidepressant- and anorexigenic-like effects in adult rats and demonstrate a decreased potential when administered in adolescent rats. Moreover, since cannabidiol did not modulate hippocampal neurogenesis (cell proliferation and early neuronal survival) in adolescent or adult rats, the results revealed potential antidepressant-like effects induced by cannabidiol without the need of regulating hippocampal neurogenesis.