Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

Background: Early-life factors before age 18 years significantly influence depression risk, but their differential contributions and biological mechanisms remain understudied.

Methods: In this prospective UK Biobank study (N = 104,035), an early-life factor score (ELFS) was constructed using elastic net Cox models incorporating 15 early-life factors, including perinatal conditions, childhood adversities, physical development, and social-environmental exposures. Cox models were used to assess associations of both individual factors and the ELFS with depression. We conducted a genome-wide association study (GWAS) to identify genetic variants, Mendelian randomization to assess causality, and linear regression to examine associations with brain structures and blood markers. Structural equation modeling (SEM) was used to explore biological pathways linking early-life factors to depression.

Results: During the follow-up period (median = 14.6 years), 4168 participants developed depression. Each 1-point increase in the ELFS was associated with a 49% higher depression risk. Individuals with a high ELFS showed a 2.8-fold higher risk than individuals with a low ELFS. GWAS identified 46 significant single nucleotide polymorphisms associated with the ELFS, mapped to 17 genes including FOXP2, with enrichment in metabolic pathways. Mendelian randomization analysis supported the causal relationship between the ELFS and depression. A higher ELFS was associated with smaller volumes particularly in brain regions linked to emotion regulation and with altered inflammation and lipid metabolism. SEM integrating multilevel evidence revealed biological pathways linking early-life factors, brain structure, immunometabolic markers, and depression.

Conclusions: Early-life factors collectively influenced depression risk through an integrated score capturing differential factor contributions. Multiple biological pathways involving brain structure and immunometabolic markers were identified, providing insights into potential mechanisms linking early-life factors to depression.

Background: As neurobiological markers gain prominence in guiding personalized treatments, sulcal depth (SD) remains an underexplored yet pivotal factor in neural processing and therapeutic efficacy. While genetic influences shape cortical architecture, their role in modulating the relationship between SD and treatment outcomes remains unclear. In this study, we investigated whether pretreatment SD predicts symptom alleviation in adults with attention-deficit/hyperactivity disorder (ADHD) and explored moderating effects of genetic susceptibility for ADHD and cross-disorder influences.

Methods: Using structural neuroimaging data from COMPAS (Comparison of Methylphenidate and Psychotherapy in Adult ADHD Study), we examined associations between SD and treatment response following a 12-week intervention involving either group psychotherapy or clinical management with methylphenidate or placebo. Pretreatment SD was derived from 119 T1-weighted anatomical scans and analyzed using linear regression models to assess its predictive value for posttreatment symptom severity. Subsequently, we explored the moderating role of polygenic scores for ADHD and cross-disorder susceptibility. Structural analyses were performed using the threshold-free cluster enhancement approach in CAT, with moderation analyses conducted in SPSS.

Results: Results revealed that SD in parietal, temporal, and occipital regions significantly predicted symptom alleviation, linking deeper sulci with greater treatment efficacy. Moreover, genetic predisposition to ADHD and cross-disorder traits influenced these relationships, highlighting an interaction between cortical structure and genetic susceptibility in determining treatment outcomes.

Conclusions: These findings highlight SD as a promising neurobiological marker of ADHD treatment response and emphasize the importance of integrating neurobiological and genetic factors into predictive models of therapeutic efficacy in psychiatry.

Background: The neural bases of adverse neurodevelopmental outcomes in antenatal opioid exposure are poorly understood. Very limited in vivo human newborn imaging studies have reported disrupted functional connectivity (FC) in limbic and reward-related brain regions, but these studies used small samples and lacked matched controls. Our objective was to compare brain FC in antenatal opioid-exposed and unexposed newborns to study the impact of opioid exposure on early brain development.

Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected using 3T MRI at 4 centers as part of the prospective, observational OBOE (Outcomes of Babies with Opioid Exposure) study. We used seed-based correlation analysis to estimate the FC of 93 brain regions. Voxelwise linear regression with covariate adjustment and correction for multiple comparisons was used to determine significant between-group differences. FC differences based on opioid type were also investigated.

Results: We evaluated 248 rs-fMRI scans (158 opioid-exposed/90 unexposed). Canonical sensorimotor and higher-order resting-state network maps in exposed newborns (mean ± SD postmenstrual age at MRI = 42.80 ± 2.2 weeks, 53 male) were comparable to control newborns (42.82 ± 1.9 weeks, 88 male; Dice indices > 0.9 across 7 networks). Exposed newborns showed decreased FC from seeds in bilateral pre- and left postcentral gyri, bilateral orbitofrontal regions, and cerebellum and increased FC from seeds in peri-opercular, subcortical (e.g., amygdala, hippocampus, and putamen), and mid-to-superior occipital regions (familywise error rate, α < 0.05). Connectivity from 23 of 93 (24.7%) seeds differed between groups. Methadone- and buprenorphine-exposed newborns showed disrupted regional FC compared with control newborns, but there were no FC differences between them.

Conclusions: In a large sample of antenatally opioid-exposed newborns, we found altered organization of brain functional networks, particularly in integrative sensorimotor-affective circuits.

Background: Childhood adversity is associated with susceptibility to posttraumatic stress disorder (PTSD) in adulthood. PTSD and childhood adversity are linked to white matter microstructure, yet the role of white matter as a potential neural mechanism connecting childhood adversity to PTSD remains unclear. In the current study, we investigated the potential moderating role of previous childhood adversity on longitudinal changes in white matter microstructure and posttraumatic stress symptoms following a recent traumatic event in adulthood.

Methods: As part of the AURORA (Advancing Understanding of RecOvery afteR traumA) study, 114 recent trauma survivors completed diffusion-weighted imaging at 2 weeks and 6 months after exposure. Participants reported on prior childhood adversity and PTSD symptoms at 2 weeks, 6 months, and 12 months posttrauma. We performed region of interest (ROI) analysis using fractional anisotropy (FA) and whole-brain correlational tractography using quantitative anisotropy (QA) to index associations between white matter microstructure changes and prior adversity.

Results: ROI-based analyses did not identify significant associations between childhood adversity and changes in FA. Whole-brain correlational tractography revealed that greater childhood adversity moderated the QA changes within threat and visual processing tracts including the cingulum bundle and inferior fronto-occipital fasciculus (IFOF). QA changes within the cingulum bundle and IFOF were associated with changes in PTSD symptoms between 2 weeks and 6 months.

Conclusions: Our findings suggest that temporal variability in threat and visual white matter tracts may be a potential neural pathway through which childhood adversity confers risk for PTSD symptoms after adulthood trauma. Future studies should take the temporal properties of white matter into consideration to better understand the neurobiology of childhood adversity and PTSD.

Background: Cannabis use among young adults has reached the highest levels ever recorded. Evidence indicates that acute Δ⁹-tetrahydrocannabinol (THC) disrupts brain connectivity. Few studies have examined this on a whole-brain level. We examined the effects of a single moderate dose of THC on resting-state functional brain networks among young adult cannabis users.

Methods: In a within-subject, double-blind, randomized study, 33 healthy occasional cannabis users received THC (7.5 mg, oral) and placebo before completing resting-state functional magnetic resonance imaging (rs-fMRI) during peak intoxication. Group-information-guided independent component analysis was performed on resting-state brain data to identify whole-brain networks associated with each scan. Within-samples t tests assessed for differences in intrinsic network functional connectivity and between-network functional connectivity after THC versus placebo. Additional linear models examined relationships between brain connectivity, subjective drug effects, and past-month cannabis use.

Results: THC reduced within-network intrinsic connectivity in corticostriatal circuits and other networks associated with sensory systems, interoceptive experiences, and spatial reasoning. THC reduced connectivity between 2 networks characterized by the anterior cingulate cortex and dorsal insula regions as well as the ventral insula and lingual gyrus, respectively. Network connectivity during THC (vs. placebo) was not related to subjective measures of drug effect or recent cannabis use.

Conclusions: Our findings add to a growing literature showing that THC decreases rs-fMRI throughout the brain, impacting networks linked to the many behavioral and perceptual changes associated with THC. Future work is needed to extend these findings to clinical samples and to assess the extent to which these networks are associated with negative outcomes of chronic THC use.

Background: Advances in neuroimaging of bipolar disorder (BD) have highlighted key structural and functional abnormalities in prefrontal-limbic circuits. Youth with a family history of BD often experience early onset of mood symptoms that may increase their risk for developing BD. However, the etiologic mechanisms underlying this risk remain poorly understood. We aimed to identify white matter connectivity abnormalities by comparing regional microstructure in high-risk youth and healthy control (HC) participants.

Methods: Youths with depression and/or anxiety (n = 108, mean age [SD] = 14.9 [1.6] years) with a family history of BD but no prior antidepressant exposure and matched HC youths (n = 45, age = 14.8 [1.6] years) were recruited at 2 sites. Automated fiber quantification using diffusion tensor imaging was used to calculate the diffusion properties of fiber tracks and identify microstructural abnormalities. Correlations between clinical ratings and diffusion properties that differed between groups were examined in high-risk youths.

Results: The high-risk group showed higher fractional anisotropy in anterior thalamic radiation and corticospinal, higher axial diffusivity in anterior thalamic radiation, lower mean diffusivity in corticospinal, and lower radial diffusivity in corticospinal and callosum forceps minor compared with the HC group (familywise error-corrected p < .05). Significant positive correlations between regional microstructural metrics and both the Pediatric Anxiety Rating Scale and the Children's Global Assessment Scale were observed in high-risk youths (false discovery rate-corrected p < .05).

Conclusions: Compared with the HC group, youths at risk for BD had altered integrity in the white matter of the callosum forceps minor, anterior thalamic radiation, and corticospinal tracts. Damage to these tracts may be a structural basis for impaired emotional regulation in high-risk youth and a potential target for early intervention.

Background: The glymphatic system (GS) plays a central role in eliminating metabolic waste from the human brain. Diffusion tensor image analysis along the perivascular space (ALPS) has emerged as a noninvasive biomarker for evaluating GS function. While decreased ALPS is consistently linked to impaired GS in various central nervous system pathologies, the genetic architectures and neural mechanisms underlying ALPS and its role in maintaining brain health remain unknown.

Methods: A genome-wide association study (GWAS) of ALPS was conducted in 31,579 participants from the UK Biobank. Genetic associations were identified using positional, expression quantitative trait loci, and chromatin mapping strategies. Gene-set enrichment analysis and Mendelian randomization (MR) were performed to characterize biological pathways and causal relationships between ALPS, brain phenotypes, and neurological disorders.

Results: The GWAS identified 6 unique loci and 175 genes associated with ALPS. Gene enrichment analyses identified significant associations with brain morphogenesis, along with implications for GS function and neurodegenerative pathways. Genetic and individual-level correlations linked ALPS to brain volume, cerebrospinal fluid-related imaging phenotypes, and cognitive metrics. MR demonstrated that genetically predicted lower ALPS increased the risk of multiple sclerosis and Alzheimer's disease.

Conclusions: This study elucidates the genetic architecture of ALPS, a biomarker that reflects GS function, and its association with brain health. The findings highlight decreased ALPS as a potential risk factor for neuroinflammatory and neurodegenerative disorders, emphasizing the importance of GS integrity in maintaining neurological health.

Background: American Indians (AIs) experience chronic stressors that may be associated with disproportionate prevalence rates of major depressive disorder (MDD). Stress affects mental health through increased inflammatory processes and has been associated with increased risk of MDD and disruptions to reward processing. In this study, we investigated the role of inflammation in reward-processing disruptions among AI individuals with lifetime MDD, a population at heightened risk due to chronic stressors.

Methods: Participants (N = 73) completed a monetary incentive delay task during simultaneous electroencephalography and functional magnetic resonance imaging. Blood samples were analyzed for proinflammatory (tumor necrosis factor [TNF], interleukin 6 [IL-6], C-reactive protein [CRP]) and anti-inflammatory (IL-10) biomarkers. Depression severity was assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) Depression scale. Covariates were included and assessed using self-report measures.

Results: Regression analyses revealed that elevated TNF concentrations and sex were associated with reduced activation across subregions of the basal ganglia during gain anticipation. Similarly, TNF and CRP concentrations, as well as medication, were associated with reduced activation within basal ganglia subregions across loss anticipation. IL-10, IL-6, and P300 showed limited predictive value for neural responses.

Conclusions: These findings suggest that inflammation may contribute to reward-processing disruptions by impairing striatal function in a sample with lifetime MDD. The observed associations underscore the importance of inflammation's potential role in and association with the pathophysiology of MDD, particularly in contexts of chronic stress. This study highlights the need to address the disproportionate mental health burden in AI communities through a biopsychosocial approach.

Background: Recent epidemiological evidence links early-life obesity and metabolic dysregulation to adult psychosis vulnerability, though a causal relationship remains unclear. Establishing causality in highly heritable psychotic disorders requires 1) demonstrating that early-life metabolic factors mediate between genetic vulnerability and psychosis trajectory, 2) dissecting mechanisms leading to early-life obesity in genetically vulnerable individuals, and 3) clarifying downstream neurodevelopmental pathways linking early-life obesity to psychosis symptoms.

Methods: Here we investigated bidirectional pathways linking behavioral, body mass index (BMI), and neurodevelopmental trajectories in a unique longitudinal cohort of 184 individuals at high genetic risk for psychosis, due to 22q11.2 deletion syndrome (22q11DS), and 182 neurotypical control individuals, followed-up since childhood. We combined repeated BMI measurements with clinical/neurocognitive phenotyping and neuroimaging. We investigated the relationship between BMI trajectories with risk of psychosis and tested whether altered cortical or cerebellar development could underlie this association.

Results: Childhood behavioral impulsivity predicted early and progressive deviations in BMI trajectories, mediating the effects of 22q11DS vulnerability to early-life obesity. Chronic BMI increases manifesting during childhood predicted the subsequent emergence of psychosis during late adolescence/early adulthood, mediating the effects of behavioral impulsivity. A dose-effect relationship linked duration of increased BMI status to worsening of motor and cognitive disorganization, a key schizophrenia symptom domain, which was mediated by progressive gray matter volume reductions in posterior-inferior cerebellum.

Conclusions: These findings suggest that metabolic dysregulation associated with obesity may link childhood behavioral impulsivity to psychosis vulnerability in 22q11DS by influencing cerebellar maturation. These findings might support preventive interventions targeting early-life metabolic trajectories in individuals at risk of psychosis.

Background: Internet gaming disorder (IGD) is a clinically heterogeneous condition, yet the underlying neurobiological subtypes remain to be elucidated. Investigating subpatterns of spontaneous neural activity and state switching from individual to group patterns may provide deeper insights into the etiology of IGD.

Methods: Resting-state functional magnetic resonance imaging data were collected from 519 participants (257 with IGD, 262 recreational game users [RGUs]). The fractional amplitude of low-frequency fluctuations was computed to assess spontaneous neural activity. Nonnegative matrix factorization was used to extract features that were predictive of addiction severity. Network control theory (NCT) was utilized to quantify the energy required for brain state transitions.

Results: Compared with RGUs, participants with IGD exhibited heightened activity in brain patterns (involving the basal ganglia and thalamic regions) associated with reward processing. The individual weight of this pattern was positively associated with addiction severity, and the spatial intensity was negatively correlated with the density of serotonin 1A (5-HT_1A) receptors. Furthermore, NCT analysis demonstrated that transitioning to a high-craving state required less control energy than transitioning to other states.

Conclusions: Although neural activity varies among individuals with IGD, the homogeneity can be embedded in reward processing-related brain areas. Reduction in 5-HT_1A receptor density may be a substrate for this pattern. Individuals with IGD transition more readily to high-craving states than to other states. These results elucidate neural mechanisms underlying IGD and highlight the importance of individualized approaches to treating the disorder.