Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

Background: It is unknown whether brain-based predictive models derived from sleep features are useful for the clinical diagnosis of major depressive disorder (MDD).

Methods: Using resting-state functional magnetic resonance imaging data from the curated ABCD (Adolescent Brain Cognitive Development) Study Data Release 3.0, we trained a connectome-based predictive model (CPM) on 35,778 pairwise connections (Pearson's r) from 2349 (237 participants with at least 1 psychiatric disorder and 2112 control participants) participants ages 11 to 12 to predict sleep duration (measured from a Fitbit tracker). Linear regression models were used to compare the predicted values from these CPMs with self-reported sleep duration and diagnostic group status in an independent cohort of 78 participants (57 participants with MDD and 21 control participants) ages 14 to 18.

Results: The ABCD-based CPM predicted self-reported sleep duration in the independent cohort of participants with MDD (partial r = 0.332, p = .009). Even though self-reported sleep duration did not significantly differ between diagnostic groups (t₇₅ = 0.13, p = .90), the ABCD-based CPM successfully distinguished between diagnostic groups (partial r = 0.334, p < .001), and CPM-predicted sleep durations correlated with depression symptom severity (partial r = 0.294, p < .001). These diagnostic group differences were driven primarily by patterns of hypoconnectivity between various resting-state networks (including the default mode, frontoparietal, motor, subcortical, and visual associative networks).

Conclusions: CPMs trained to predict objective sleep duration are robust and generalizable. Intrinsic functional connectivity differences between clinically depressed and psychiatrically healthy adolescents are detectable by CPMs optimized for sleep prediction, underscoring the shared neural bases between sleep health and depression. Future work will test whether sleep-based CPMs are predictive of clinical course and if they generalize to other disorders beyond depression.

Background: Electroencephalography (EEG) alpha-band neural activity has previously been reported to be altered in autism spectrum disorder (ASD), but no studies have addressed different parameters of alpha-band activity and their relationship to clinical phenotype and copy number variants (CNVs) in ASD.

Methods: The study included 310 youths with and without ASD and consisted of resting-state EEG, behavioral phenotyping, and genome-wide CNV analysis.

Results: First, the results revealed that alpha peak power was reduced in ASD, and younger-age autistic males had a higher number of peaks compared with younger-age autistic females. Second, a higher number of alpha peaks was related to lower language skills and a higher presence of autistic traits. Finally, a higher number of alpha peaks was related to a higher number of CNVs.

Conclusions: In this study, we explored a novel measure (number of peaks) associated with both clinical phenotype and genetic burden and provide evidence that supports alterations in alpha-band activity in ASD.

Background: Attention-deficit/hyperactivity disorder (ADHD) is increasingly being recognized as a disorder linked to atypical white matter development across large-scale brain networks. However, current research predominantly focuses on cortical networks, leaving the developmental trajectories of many subcortical networks, including the limbic system, largely unexplored. The limbic system is crucial for emotion and cognition, making it a key area of interest in ADHD research.

Methods: In this study, we used multishell high-angular resolution diffusion magnetic resonance imaging in a sample of 169 participants (72 with ADHD and 97 control participants) across 3 time points between ages 9 and 14 years to map the development of limbic system white matter. Diffusion kurtosis imaging and graph theory metrics were used to characterize limbic system white matter, alongside assessments of emotional regulation and ADHD symptom severity.

Results: Compared with control participants, individuals with ADHD exhibited significantly lower microstructural organization, particularly in kurtosis anisotropy, within the bilateral cingulum bundle from childhood to adolescence. There were no significant group-by-time interactions in limbic system white matter metrics, suggesting no significant differences in developmental trajectories between the ADHD and control groups. Furthermore, brain-behavior analyses revealed that higher ADHD symptom severity was associated with fewer limbic system white matter connections, notably decreased routing efficiency and network density.

Conclusions: These findings offer novel insights into the role of disrupted limbic system white matter, particularly the cingulum bundle, in ADHD pathophysiology, thereby broadening our understanding of the disorder's neural mechanisms and opening promising avenues for future exploration of subcortical brain networks.

Background: Preclinical research indicates that chronic stress can induce synaptic loss in corticolimbic brain regions regulating mood and cognition. Presynaptic density can now be measured in vivo using radioligands targeting synaptic vesicle protein 2A (SV2A) and positron emission tomography (PET). We conducted the first in vivo PET study to investigate chronic stress-induced synaptic density changes in rats and examined correlates with behavior and protein expression.

Methods: Male and female Long Evans rats were exposed to chronic unpredictable stress (CUS) (n = 24/sex) and compared with controls (n = 12/sex). Sucrose preference and novel object recognition (NOR) were used to assess stress-related behavioral phenotypes. PET with [¹⁸F]SynVesT-1 was used to measure synaptic density in a subset of rats (n = 8-9/group/sex). Prefrontal cortex (PFC) and hippocampal proteins were quantified via liquid chromatography-tandem mass spectrometry (n = 5/group/sex), followed by pathway analysis and linear regression to examine molecular profiles associated with CUS and correlated with synaptic density as measured by PET.

Results: Synaptic density was lower in the PFC of CUS rats relative to controls (d = 0.94, p = .012) and correlated with sucrose preference (r = 0.35, p = .042). Synaptic density was also lower in the hippocampus (d = 0.55, p = .017), which correlated with NOR (r = 0.35 p = .045). Differentially expressed proteins were enriched for transcriptional regulation and metabolic pathways. Proteins implicated in synaptogenesis and neurodegeneration were positively and negatively correlated, respectively, with synaptic density.

Conclusions: We demonstrated that [¹⁸F]SynVesT-1 PET can be used for in vivo quantification of synaptic density in a rodent model of chronic stress. Therefore, this method can facilitate translational research investigating synaptic mechanisms in stress-related pathology and treatment response.

Background: Abnormalities in the functional connectivity of large-scale brain networks, including the default mode network (DMN), salience network, frontoparietal network (FPN), and limbic network, have been implicated in repetitive negative thinking (RNT), a construct characterized by persistent and intrusive thoughts. However, the potential of these large-scale network abnormalities for predicting RNT in daily life remains underexplored.

Methods: We leveraged brain-based graph-theoretical predictive modeling (GPM) to predict daily-life RNT in 54 individuals. Functional magnetic resonance imaging data were acquired during 1) resting state and 2) an RNT-induced state. RNT severity and its momentary fluctuations were assessed using ecological momentary assessments (EMAs).

Results: GPM identified key functional organizational properties of the DMN, FPN, and limbic networks that differentially predicted the severity and fluctuations of RNT and its specific clinical features (intrusiveness, repetitiveness, RNT-related anxiety). Specifically, the centrality of the medial prefrontal cortex (DMN) predicted EMA fluctuations of intrusiveness and severity of anxiety. Conversely, the strength and centrality of the orbitofrontal cortex (part of the limbic network) predicted EMA fluctuations of repetitiveness, and the segregation of the temporal pole (limbic network) predicted overall severity of RNT. Last, fluctuations in total RNT were predicted from the strength of the orbitofrontal cortex (limbic network) and segregation of the posterior mid-cingulate cortex (FPN). Notably, RNT was better predicted from daily-life prospective assessments than from laboratory-assessed clinical questionnaires.

Conclusions: These findings highlight the utility of GPM for predicting the emergence of daily-life RNT and suggest specific network-level attributes (e.g., centrality, segregation) underlying RNT and its clinical features.

Background: In this study, we aimed to evaluate glymphatic system function in children with Tourette syndrome (TS) using diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) and explored its potential role in TS pathophysiology.

Methods: Seventy-six children with TS and 82 age- and sex-matched typically developing (TD) control participants underwent DTI scans. Glymphatic function was quantified using the ALPS index, derived from atlas-based regions of interest in the superior corona radiata and superior longitudinal fasciculus. We examined associations between the left ALPS (ALPS_L) index and clinical measures, including tic severity (Yale Global Tic Severity Scale [YGTSS]) and quality of life (Gilles de la Tourette Syndrome-Quality of Life Scale [GTS-QOL]). Mediation analysis assessed whether tic severity mediated the relationship between ALPS_L index and GTS-QOL subscales.

Results: The ALPS_L index was significantly reduced in the TS group compared with the TD group (p < .05). The ALPS_L index showed significant negative correlations with YGTSS motor tic (r = -0.850, p < .001), total tic (r = -0.702, p < .001), and global tic (r = -0.629, p < .001) severity. It was also negatively correlated with the physical/activities of daily living (ADL) (r = -0.265, p = .020) and obsessive-compulsive (r = -0.380, p < .001) subscales of the GTS-QOL. Motor tic severity partially mediated the relationship between the ALPS_L index and physical/ADL scores (β = -0.037; 95% CI, -0.060 to -0.015).

Conclusions: Children with TS exhibit altered glymphatic function, associated with tic severity and impaired QOL. These findings suggest that glymphatic dysfunction may underlie TS-related neurobiological abnormalities.

Background: Low endogenous estradiol (E2) levels can occur naturally during menstruation or through oral contraceptive (OC) use. Such low levels have been suggested as vulnerability factors for impaired fear extinction memory recall. Although hormonal contraceptives have been linked to enduring psychological outcomes, their possible long-term relevance for extinction memory remains underexplored.

Methods: In this study, we aimed to replicate findings linking OC use with altered extinction recall and to examine potential long-term associations and neural correlates. To do so, a validated fear protocol (day 1: fear conditioning, extinction learning; day 2: extinction recall, fear renewal) was administered to 147 healthy adults. Psychophysiological (skin conductance responses [SCRs]) and neural between-group differences were examined across the protocol using 2 types of groupings: 1) E2-based groups (men, current OC users, women in the early follicular phase, women in the preovulatory phase) and 2) OC history-based groups (men, current OC users, never OC users, past OC users).

Results: During extinction recall, higher SCRs were found in current OC users relative to preovulatory women (grouping 1) and never users (grouping 2). Among current OC users, SCRs during extinction recall correlated with hippocampus, dorsal-rostral anterior cingulate cortex (ACC), and ventromedial prefrontal cortex (vmPFC) activations. Exploratory analyses revealed that past OC users who were in the early follicular phase exhibited SCRs as high as current users.

Conclusions: These findings highlight impaired extinction recall in current OC users, with vmPFC, ACC, and hippocampal involvement. Past OC use may carry lasting associations with fear dysregulation, particularly under low-E2 states.

Background: Individuals from marginalized ethnoracial groups face higher risk for posttraumatic stress disorder (PTSD) symptoms, exacerbated by experiencing racial/ethnic discrimination. Previous work separately explored the endocannabinoid (eCB) system and functional connectivity response to stress/trauma and suggested that experiences of chronic minority stress, such as racial discrimination, contribute to eCB tone and resting-state functional connectivity. We explored how circulating eCB tone, in conjunction with resting-state connectivity, contributes to increased risk for PTSD symptoms following trauma among individuals experiencing discrimination.

Methods: Black/African Americans (n = 74; mean age = 33.81 years) were recruited from a level 1 trauma center. Correlational and linear models explored whether experiences of racial/ethnic discrimination (Perceived Ethnic Racial Discrimination Questionnaire), eCB (AEA [N-arachidonoylethanolamine], 2-AG [2-arachidonoylglycerol]) concentrations, default mode network (DMN) functional connectivity, or salience network (SN) functional connectivity were associated with PTSD symptoms (PTSD Checklist for DSM-5). Then, we explored moderated mediation models in which discrimination predicted PTSD symptoms with eCB concentration as a mediator and functional connectivity as a moderator.

Results: Discrimination was correlated with PTSD symptoms (r = 0.50), serum AEA concentration (r = 0.43), and DMN connectivity (r = 0.23). When including urine Δ⁹-tetrahydrocannabinol, lifetime trauma, age, and sex as covariates, AEA concentration was associated with PTSD symptoms (r = 0.30) and DMN connectivity (r = 0.24). AEA mediated the relationship between discrimination and PTSD symptoms, and SN connectivity moderated this mediation (B = 52.46).

Conclusions: Our findings highlight how racial/ethnic discrimination impacts neurobiological systems that may lead to increased vulnerability for PTSD symptoms following an injury. Future work should continue to explore biological factors associated with the socioecological model of health as mechanisms of risk for adverse outcomes following trauma.

Background: Adolescence is a critical period of neurodevelopment marked by ongoing maturation of structural and functional brain connectivity. Simultaneously, this period is associated with an increase in mental health problems, spanning from subclinical symptoms to diagnosable disorders.

Methods: This study investigated longitudinal associations between psychopathology dimensions and voxelwise brain measures related to connectivity across 3 time points (ages 14, 19, and 23) in more than 1500 participants using the IMAGEN dataset. White matter (WM) microstructure was indexed using diffusion metrics quantified along the WM skeleton (N = 1736), while functional connectivity was captured as voxelwise degree centrality (DC) derived from resting-state functional imaging (N = 1510).

Results: Development of WM microstructure was selectively linked to externalizing (but not internalizing) symptoms. Here, higher externalizing symptoms were associated with widespread reductions in fractional anisotropy (FA) across the WM skeleton as well as accelerated decreases in FA in the corticospinal tract over time. In contrast, functional DC was developmentally associated with general, rather than specific, psychopathology in frontal and temporal regions. An increase in total difficulties over time was associated with developmental decrease in DC in bilateral superior frontal gyri. In addition, a positive association between total difficulties and DC in left inferior temporal gyrus was observed in younger, but not older, adolescents or young adults.

Conclusions: These findings highlight the dynamic interplay between brain connectivity development and psychopathology in adolescence, with potential implications for identifying neural markers of risk and resilience during sensitive windows of development.

Background: Large comorbidity and heterogeneity within psychiatric populations have prompted the use of transdiagnostic methods to account for this variability in brain-phenotype associations. Normative modeling offers a way to map individual deviations in brain functioning with respect to a large reference population. This study aims to explore brain-phenotype associations, using normative modeling to compute individual deviation scores of brain functioning, and relating them to different levels of psychopathology in a naturalistic patient sample.

Methods: We applied normative modeling to estimate individual deviations in brain functional connectivity in a naturalistic sample (N = 309) comprising both patients and healthy control participants. We examined the association between the resulting neural deviation scores and levels of psychopathology, including traditional diagnostic categories, transdiagnostic symptom profiles, and cognition measures using sparse canonical correlation analysis.

Results: We successfully estimated normative models using data from the MIND-Set (Measuring Integrated Novel Dimensions in Neurodevelopmental and Stress-Related Mental Disorders) study and found significantly more extreme deviation scores in the patient as compared with the control population. We found a significant association (R_c = 0.16, R² = 2.56%, p = .021) between neural deviation scores and transdiagnostic symptom profiles, aligning with 4 Research Domain Criteria (RDoC) domains: negative valence, cognition, arousal/inhibition, and social systems.

Conclusions: With the use of normative modeling, we were able to detect differences in functional brain connectivity in patients compared with control participants, even in a highly heterogeneous and comorbid patient sample. Additionally, transdiagnostic approaches, such as those embodied in the RDoC framework, are more accurate in uncovering shared neurobiological mechanisms compared with traditional diagnostic categories or cognitive measures.