Regional gene expression signatures are associated with sex-specific functional connectivity changes in depression

Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder

BACKGROUND

Patients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to those seen in aging. However, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool that quantifies normative neurodevelopmental trajectories.

METHODS

A total of 304 participants with MDD and 236 control participants without depression were recruited and scanned from 3 studies under the Canadian Biomarker Integration Network for Depression. Volumetric data were used to generate brain centile scores, which were examined for 1) differences between participants with MDD and control participants; 2) differences between individuals with versus without severe childhood maltreatment; and 3) correlations with depressive symptom severity, neurocognitive assessment domains, and escitalopram treatment response.

RESULTS

Brain centiles were significantly lower in the MDD group than in the control group. Brain centile was also significantly correlated with working memory in the control group but not the MDD group. No significant associations were observed between depression severity or antidepressant treatment response and brain centiles. Likewise, childhood maltreatment history did not significantly affect brain centiles.

CONCLUSIONS

Consistent with previous work on machine learning models that predict brain age, brain centile scores differed in people diagnosed with MDD, and MDD was associated with differential relationships between centile scores and working memory. The results support the notion of atypical development and aging in MDD, with implications for neurocognitive deficits associated with aging-related cognitive function.

Electroencephalography connectome changes in chronic insomnia disorder are correlated with neurochemical signatures

STUDY OBJECTIVES

This study aimed to investigate the alterations in resting-state electroencephalography (EEG) global brain connectivity (GBC) in patients with chronic insomnia disorder (CID) and to explore the correlation between macroscale connectomic variances and microscale neurotransmitter distributions.

METHODS

We acquired 64-channel EEG from 35 female CID patients and 34 healthy females. EEG signals were source-localized using individual brain anatomy and orthogonalized to mitigate volume conduction. Correlation coefficients between band-limited source-space power envelopes of the DK 68 atlas were computed and averaged across regions to determine specific GBC values. A support vector machine (SVM) classifier utilizing GBC features was employed to differentiate CID patients from controls. We further used Neurosynth and a 3D atlas of neurotransmitter receptors/transporters to assess the cognitive functions and neurotransmitter landscape associated with CID cortical abnormality maps, respectively.

RESULTS

CID patients exhibited elevated GBC within the medial prefrontal cortex and limbic cortex, particularly at the gamma carrier frequency, compared to controls (pFDR < .05). GBC patterns were found to effectively distinguish CID patients from controls with a precision of 90.8% in the SVM model. The cortical abnormality maps were significantly correlated with meta-analytic terms like "cognitive control" and "emotion regulation." Notably, GBC patterns were associated with neurotransmitter profiles (pspin < .05), with neurotransmitter systems such as norepinephrine, dopamine, and serotonin making significant contributions.

CONCLUSIONS

This work characterizes the EEG connectomic profile of CID, facilitating the cost-effective clinical translation of EEG-derived markers. Additionally, the linkage between GBC patterns and neurotransmitter distribution offers promising avenues for developing targeted treatment strategies for CID.

Neurodevelopmental signature of a transcriptome-based polygenic risk score for depression

Disentangling the molecular underpinnings of major depressive disorder (MDD) is necessary for identifying new treatment and prevention targets. The functional impact of depression-related transcriptomic changes on the brain remains relatively unexplored. We recently developed a novel transcriptome-based polygenic risk score (tPRS) composed of genes transcriptionally altered in MDD. Here, we sought to investigate effects of tPRS on brain structure in a developmental cohort (Adolescent Brain Cognitive Development study; n = 5124; 2387 female) at baseline (9-10 years) and 2-year follow-up (11-12 years). We tested associations between tPRS and Freesurfer-derived measures of cortical thickness, cortical surface area, and subcortical volume. Across the whole sample, higher tPRS was significantly associated with thicker left posterior cingulate cortex at both baseline and 2-year follow-up. In females only, tPRS was associated with lower right hippocampal volume at baseline and 2-year follow-up, and lower right pallidal volume at baseline. Furthermore, regional subcortical volume significantly mediated an indirect effect of tPRS on depressive symptoms in females at both timepoints. Conversely, tPRS did not have significant effects on cortical surface area. These findings suggest the existence of a sex-specific neurodevelopmental signature associated with shifts towards a more depression-like brain transcriptome, and highlight novel pathways of developmentally mediated MDD risk.

Sex differences in aberrant functional connectivity of three core networks and subcortical networks in medication-free adolescent-onset major depressive disorder

Major depressive disorder demonstrated sex differences in prevalence and symptoms, which were more pronounced during adolescence. Yet, research on sex-specific brain network characteristics in adolescent-onset major depressive disorder remains limited. This study investigated sex-specific and nonspecific alterations in resting-state functional connectivity of three core networks (frontoparietal network, salience network, and default mode network) and subcortical networks in adolescent-onset major depressive disorder, using seed-based resting-state functional connectivity in 50 medication-free patients with adolescent-onset major depressive disorder and 56 healthy controls. Irrespective of sex, compared with healthy controls, adolescent-onset major depressive disorder patients showed hypoconnectivity between bilateral hippocampus and right superior temporal gyrus (default mode network). More importantly, we further found that females with adolescent-onset major depressive disorder exhibited hypoconnectivity within the default mode network (medial prefrontal cortex), and between the subcortical regions (i.e. amygdala, striatum, and thalamus) with the default mode network (angular gyrus and posterior cingulate cortex) and the frontoparietal network (dorsal prefrontal cortex), while the opposite patterns of resting-state functional connectivity alterations were observed in males with adolescent-onset major depressive disorder, relative to their sex-matched healthy controls. Moreover, several sex-specific resting-state functional connectivity changes were correlated with age of onset, sleep disturbance, and anxiety in adolescent-onset major depressive disorder with different sex. These findings suggested that these sex-specific resting-state functional connectivity alterations may reflect the differences in brain development or processes related to early illness onset, underscoring the necessity for sex-tailored diagnostic and therapeutic approaches in adolescent-onset major depressive disorder.

Sex-specific resting state brain network dynamics in patients with major depressive disorder

Sex-specific neurobiological changes have been implicated in Major Depressive Disorder (MDD). Dysfunctions of the default mode network (DMN), salience network (SN) and frontoparietal network (FPN) are critical neural characteristics of MDD, however, the potential moderating role of sex on resting-state network dynamics in MDD has not been sufficiently evaluated. Thus, resting-state functional magnetic resonance imaging (fMRI) data were collected from 138 unmedicated patients with first-episode MDD (55 males) and 243 healthy controls (HCs; 106 males). Recurring functional network co-activation patterns (CAPs) were extracted, and time spent in each CAP (the total amount of volumes associated to a CAP), persistence (the average number of consecutive volumes linked to a CAP), and transitions across CAPs involving the SN, DMN and FPN were quantified. Relative to HCs, MDD patients exhibited greater persistence in a CAP involving activation of the DMN and deactivation of the FPN (DMN + FPN-). In addition, relative to the sex-matched HCs, the male MDD group spent more time in two CAPs involving the SN and DMN (i.e., DMN + SN- and DMN-SN + ) and transitioned more frequently from the DMN + FPN- CAP to the DMN + SN- CAP relative to the male HC group. Conversely, the female MDD group showed less persistence in the DMN + SN- CAP relative to the female HC group. Our findings highlight that the imbalance between SN and DMN could be a neurobiological marker supporting sex differences in MDD. Moreover, the dominance of the DMN accompanied by the deactivation of the FPN could be a sex-independent neurobiological correlate related to depression.

Brain-based sex differences in schizophrenia: A systematic review of fMRI studies

Schizophrenia is a chronic psychiatric disorder with characteristic symptoms of delusions, hallucinations, lack of motivation, and paucity of thought. Recent evidence suggests that the symptoms of schizophrenia, negative symptoms in particular, vary widely between the sexes and that symptom onset is earlier in males. A better understanding of sex-based differences in functional magnetic resonance imaging (fMRI) studies of schizophrenia may provide a key to understanding sex-based symptom differences. This study aimed to summarize sex-based functional magnetic resonance imaging (fMRI) differences in brain activity of patients with schizophrenia. We searched PubMed and Scopus to find fMRI studies that assessed sex-based differences in the brain activity of patients with schizophrenia. We excluded studies that did not evaluate brain activity using fMRI, did not evaluate sex differences, and were nonhuman or in vitro studies. We found 12 studies that met the inclusion criteria for the current systematic review. Compared to females with schizophrenia, males with schizophrenia showed more blood oxygen level-dependent (BOLD) activation in the cerebellum, the temporal gyrus, and the right precuneus cortex. Male patients also had greater occurrence of low-frequency fluctuations in cerebral blood flow in frontal and parietal lobes and the insular cortex, while female patients had greater occurrence of low-frequency fluctuations in the hippocampus, parahippocampus, and lentiform nucleus. The current study summarizes fMRI studies that evaluated sex-based fMRI brain differences in schizophrenia that may help to shed light on the underlying pathophysiology and further understanding of sex-based differences in the clinical presentation and course of the disorder.

Spatial transcriptomic patterns underlying amyloid-β and tau pathology are associated with cognitive dysfunction in Alzheimer's disease

Amyloid-β (Aβ) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aβ and tau pathologies than others, gene expression may play a role. We study the association between brain-wide gene expression profiles and regional vulnerability to Aβ (gene-to-Aβ associations) and tau (gene-to-tau associations) pathologies by leveraging two large independent AD cohorts. We identify AD susceptibility genes and gene modules in a gene co-expression network with expression profiles specifically related to regional vulnerability to Aβ and tau pathologies in AD. In addition, we identify distinct biochemical pathways associated with the gene-to-Aβ and the gene-to-tau associations. These findings may explain the discordance between regional Aβ and tau pathologies. Finally, we propose an analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations.

Effects of sex and gender on the etiologies and presentation of select internalizing psychopathologies

The internalizing spectrum encompasses a subset of psychopathologies characterized by emotional liability, anhedonia, anxiousness, distress, and fear, and includes, among others, diagnoses of major depressive disorder (MDD), generalized anxiety disorder (GAD), and posttraumatic stress disorder (PTSD). In this review, we describe the vast body of work highlighting a role for sex and gender in the environment, symptom onset, genetic liability, and disorder progression and comorbidities of MDD, GAD, and PTSD. We also point the reader to different language used in diverse fields to describe sexual and gender minorities that may complicate the interpretation of emerging literature from the social sciences, psychiatric and psychological sciences, and genetics. Finally, we identify several gaps in knowledge that we hope serve as launch-points for expanding the scope of psychiatric studies beyond binarized sex-stratification. Despite being under-represented in genomics studies, placing emphasis on inclusion of sexual and gender diverse participants in these works will hopefully improve our understanding of disorder etiology using genetics as one tool to inform how biology (e.g., hormone concentration) and environmental variables (e.g., exposure to traumatic events) contribute to differences in symptom onset, pattern, and long-term trajectory.

Dimensional and Categorical Solutions to Parsing Depression Heterogeneity in a Large Single-Site Sample

BACKGROUND

Recent studies have reported significant advances in modeling the biological basis of heterogeneity in major depressive disorder, but investigators have also identified important technical challenges, including scanner-related artifacts, a propensity for multivariate models to overfit, and a need for larger samples with more extensive clinical phenotyping. The goals of the current study were to evaluate dimensional and categorical solutions to parsing heterogeneity in depression that are stable and generalizable in a large, single-site sample.

METHODS

We used regularized canonical correlation analysis to identify data-driven brain-behavior dimensions that explain individual differences in depression symptom domains in a large, single-site dataset comprising clinical assessments and resting-state functional magnetic resonance imaging data for 328 patients with major depressive disorder and 461 healthy control participants. We examined the stability of clinical loadings and model performance in held-out data. Finally, hierarchical clustering on these dimensions was used to identify categorical depression subtypes.

RESULTS

The optimal regularized canonical correlation analysis model yielded 3 robust and generalizable brain-behavior dimensions that explained individual differences in depressed mood and anxiety, anhedonia, and insomnia. Hierarchical clustering identified 4 depression subtypes, each with distinct clinical symptom profiles, abnormal resting-state functional connectivity patterns, and antidepressant responsiveness to repetitive transcranial magnetic stimulation.

CONCLUSIONS

Our results define dimensional and categorical solutions to parsing neurobiological heterogeneity in major depressive disorder that are stable, generalizable, and capable of predicting treatment outcomes, each with distinct advantages in different contexts. They also provide additional evidence that regularized canonical correlation analysis and hierarchical clustering are effective tools for investigating associations between functional connectivity and clinical symptoms.

Prediction of brain sex from EEG: using large-scale heterogeneous dataset for developing a highly accurate and interpretable ML model

This study presents a comprehensive examination of sex-related differences in resting-state electroencephalogram (EEG) data, leveraging two different types of machine learning models to predict an individual's sex. We utilized data from the Two Decades-Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) EEG study, affirming that gender prediction can be attained with noteworthy accuracy. The best performing model achieved an accuracy of 85% and an ROC AUC of 89%, surpassing all prior benchmarks set using EEG data and rivaling the top-tier results derived from fMRI studies. A comparative analysis of LightGBM and Deep Convolutional Neural Network (DCNN) models revealed DCNN's superior performance, attributed to its ability to learn complex spatial-temporal patterns in the EEG data and handle large volumes of data effectively. Despite this, interpretability remained a challenge for the DCNN model. The LightGBM interpretability analysis revealed that the most important EEG features for accurate sex prediction were related to left fronto-central and parietal EEG connectivity. We also showed the role of both low (delta and theta) and high (beta and gamma) activity in the accurate sex prediction. These results, however, have to be approached with caution, because it was obtained from a dataset comprised largely of participants with various mental health conditions, which limits the generalizability of the results and necessitates further validation in future studies. . Overall, the study illuminates the potential of interpretable machine learning for sex prediction, alongside highlighting the importance of considering individual differences in prediction sex from brain activity.

Sex differences in bipolar disorder: The dorsolateral prefrontal cortex as an etiopathogenic region

Bipolar disorder (BD) is worldwide a prevalent mental illness and a leading risk factor for suicide. Over the past three decades, it has been discovered that sex differences exist throughout the entire panorama of BD, but the etiologic regions and mechanisms that generate such differences remain poorly characterized. Available evidence indicates that the dorsolateral prefrontal cortex (DLPFC), a critical region that controls higher-order cognitive processing and mood, exhibits biological disparities between male and female patients with psychiatric disorders, which are highly correlated with the co-occurrence of psychotic symptoms. This review addresses the sex differences in BD concerning epidemiology, cognitive impairments, clinical manifestations, neuroimaging, and laboratory abnormalities. It also provides strong evidence linking DLPFC to the etiopathogenesis of these sex differences. We emphasize the importance of identifying gene signatures using human brain transcriptomics, which can depict sexually different variations, explain sex-biased symptomatic features, and provide novel targets for sex-specific therapeutics.

Sex matters: acute functional connectivity changes as markers of remission in late-life depression differ by sex

The efficacy of antidepressant treatment in late-life is modest, a problem magnified by an aging population and increased prevalence of depression. Understanding the neurobiological mechanisms of treatment response in late-life depression (LLD) is imperative. Despite established sex differences in depression and neural circuits, sex differences associated with fMRI markers of antidepressant treatment response are underexplored. In this analysis, we assess the role of sex on the relationship of acute functional connectivity changes with treatment response in LLD. Resting state fMRI scans were collected at baseline and day one of SSRI/SNRI treatment for 80 LLD participants. One-day changes in functional connectivity (differential connectivity) were related to remission status after 12 weeks. Sex differences in differential connectivity profiles that distinguished remitters from non-remitters were assessed. A random forest classifier was used to predict the remission status with models containing various combinations of demographic, clinical, symptomatological, and connectivity measures. Model performance was assessed with area under the curve, and variable importance was assessed with permutation importance. The differential connectivity profile associated with remission status differed significantly by sex. We observed evidence for a difference in one-day connectivity changes between remitters and non-remitters in males but not females. Additionally, prediction of remission was significantly improved in male-only and female-only models over pooled models. Predictions of treatment outcome based on early changes in functional connectivity show marked differences between sexes and should be considered in future MR-based treatment decision-making algorithms.

Exploring specific associations of childhood maltreatment with social cognition in drug-naive first-episode major depressive disorder: a sex-centric approach

Childhood maltreatment (CM) has been linked to social cognition deficits in major depressive disorder (MDD), but little is known about sex-specific effects. This study aimed to investigate the sex-specific associations of CM with social cognition in first-episode drug-naive patients with MDD. A total of 117 first-episode drug-naive patients with MDD and 134 healthy controls (HCs) were recruited and assessed for demographic and clinical characteristics. All participants completed the Childhood Trauma Questionnaire (CTQ), Toronto Alexithymia Scale (TAS-20), Interpersonal Reactivity Index-C (IRI), and Facial Emotion Recognition Test. Partial correlation analysis was used to explore the sex-specific association of CM with social cognition. Our findings revealed significant differences in the associations of CM with social cognition between males and females in MDD patients. In comparison to HCs, the associations of CM with social cognition displayed distinct and even contrasting sex-specific patterns in MDD patients. Specifically, male MDD patients exhibited unique imbalanced associations between emotional neglect and alexithymia, while both female and male MDD patients shared imbalanced associations of childhood abuse with empathy. These results emphasize the importance of considering the sex-specific associations of CM with social cognition in MDD and highlight the need for personalized interventions and treatments based on sex for MDD patients with a history of CM.

Brain-based Sex Differences in Depression: A Systematic Review of Neuroimaging Studies

Major depressive disorder (MDD) is a common psychiatric illness with a wide range of symptoms such as mood decline, loss of interest, and feelings of guilt and worthlessness. Women develop depression more often than men, and the diagnostic criteria for depression mainly rely on female patients' symptoms. By contrast, male depression usually manifests as anger attacks, aggression, substance use, and risk-taking behaviors. Various studies have focused on the neuroimaging findings in psychiatric disorders for a better understanding of their underlying mechanisms. With this review, we aimed to summarize the existing literature on the neuroimaging findings in depression, separated by male and female subjects. A search was conducted on PubMed and Scopus for magnetic resonance imaging (MRI), functional MRI (fMRI), and diffusion tensor imaging (DTI) studies of depression. After screening the search results, 15 MRI, 12 fMRI, and 4 DTI studies were included. Sex differences were mainly reflected in the following regions: 1) total brain, hippocampus, amygdala, habenula, anterior cingulate cortex, and corpus callosum volumes, 2) frontal and temporal gyri functions, along with functions of the caudate nucleus and prefrontal cortex, and 3) frontal fasciculi and frontal projections of corpus callosum microstructural alterations. Our review faces limitations such as small sample sizes and heterogeneity in populations and modalities. But in conclusion, it reflects the possible roles of sex-based hormonal and social factors in the depression pathophysiology.

Spatial transcriptomic patterns underlying regional vulnerability to amyloid-β and tau pathologies and their relationships to cognitive dysfunction in Alzheimer's disease

Amyloid-β (Aβ) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aβ and tau pathologies than others, gene expression may play a role. We studied the association between brain-wide gene expression profiles and regional vulnerability to Aβ (gene-to-Aβ associations) and tau (gene-to-tau associations) pathologies leveraging two large independent cohorts (n = 715) of participants along the AD continuum. We identified several AD susceptibility genes and gene modules in a gene co-expression network with expression profiles related to regional vulnerability to Aβ and tau pathologies in AD. In particular, we found that the positive APOE -to-tau association was only seen in the AD cohort, whereas patients with AD and frontotemporal dementia shared similar positive MAPT -to-tau association. Some AD candidate genes showed sex-dependent negative gene-to-Aβ and gene-to-tau associations. In addition, we identified distinct biochemical pathways associated with the gene-to-Aβ and the gene-to-tau associations. Finally, we proposed a novel analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations. Taken together, our study identified distinct gene expression profiles and biochemical pathways that may explain the discordance between regional Aβ and tau pathologies, and filled the gap between gene-to-pathology associations and cognitive dysfunction in individual AD patients that may ultimately help identify novel personalized pathogenetic biomarkers and therapeutic targets.

One Sentence Summary

We identified replicable cognition-related associations between regional gene expression profiles and selectively regional vulnerability to amyloid-β and tau pathologies in AD.

Transcriptomics and magnetic resonance imaging in major psychiatric disorders

Major psychiatric disorders create a significant public health burden, and mental disorders such as major depressive disorder, bipolar disorder, and schizophrenia are major contributors to the national disease burden. The search for biomarkers has been a leading endeavor in the field of biological psychiatry in recent decades. And the application of cross-scale and multi-omics approaches combining genes and imaging in major psychiatric studies has facilitated the elucidation of gene-related pathogenesis and the exploration of potential biomarkers. In this article, we summarize the results of using combined transcriptomics and magnetic resonance imaging to understand structural and functional brain changes associated with major psychiatric disorders in the last decade, demonstrating the neurobiological mechanisms of genetically related structural and functional brain alterations in multiple directions, and providing new avenues for the development of quantifiable objective biomarkers, as well as clinical diagnostic and prognostic indicators.

Not immune to stress: LBP's link to depression

Investigators have long suspected a link between inflammation and depression, but the underlying mechanisms are not well understood. Fang et al. report that lipopolysaccharide-binding protein regulates monoamine biosynthesis and might be a missing link and potential therapeutic target for inflammation-associated depressive behaviors.

Selective effects of acute and chronic stress on slow and alpha-theta cortical functional connectivity and reversal with subanesthetic ketamine

Anxious, depressive, traumatic, and other stress-related disorders are associated with large scale brain network functional connectivity changes, yet the relationship between acute stress effects and the emergence of persistent large scale network reorganization is unclear. Using male Thy 1-jRGECO1a transgenic mice, we repeatedly sampled mesoscale cortical calcium activity across dorsal neocortex. First, mice were imaged in a homecage control condition, followed by an acute foot-shock stress, a chronic variable stress protocol, an acute on chronic foot-shock stress, and finally treatment with the prototype rapid acting antidepressant ketamine or vehicle. We derived functional connectivity metrics and network efficiency in two activity bands, namely slow cortical activity (0.3-4 Hz) and theta-alpha cortical activity (4-15 Hz). Compared to homecage control, an acute foot-shock stress induced widespread increases in cortical functional connectivity and network efficiency in the 4-15 Hz temporal band before normalizing after 24 h. Conversely, chronic stress produced a selective increase in between-module functional connectivity and network efficiency in the 0.3-4 Hz band, which was reversed after treatment with the rapid acting antidepressant ketamine. The functional connectivity changes induced by acute stress in the 4-15 Hz band were strongly related to those in the slow band after chronic stress, as well as the selective effects of subanesthetic ketamine. Together, this data indicates that stress induces functional connectivity changes with spatiotemporal features that link acute stress, persistent network reorganization after chronic stress, and treatment effects.