Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

Background: Atypical balance of excitation (E) and inhibition (I) in the brain is thought to contribute to the emergence and symptomatology of autism spectrum disorders (ASD). E/I ratio can be estimated from resting state functional magnetic resonance imaging (fMRI) using the Hurst Exponent (H). A recent study reported decreased ventromedial prefrontal cortex (vmPFC) H in male adults with ASD. Part of the default mode network (DMN), vmPFC plays an important role in emotion regulation, decision making, and social cognition. It frequently shows altered function and connectivity in autistic individuals.

Methods: The current study presents the first fMRI evidence of altered early development of vmPFC H and its link to DMN functional connectivity (FC) and emotional control in toddlers and preschoolers with ASD. 83 children (n=45 ASD), ages 1½ - 5 years, underwent natural sleep fMRI as part of a longitudinal study.

Results: In a cross-sectional analysis, vmPFC H decreased with age in children with ASD, reflecting increasing E/I ratio, but not in typically developing children. This effect remained significant when controlling for gestational age at birth, socioeconomic status, or ethnicity. The same pattern was also observed in a subset of children with longitudinal fMRI data acquired two years apart on average. Lower vmPFC H was further associated with reduced FC within the DMN as well as with higher emotional control deficits (though only significant transdiagnostically).

Conclusions: These results suggest an early onset of E/I imbalances in vmPFC in ASD with likely consequences for the maturation of the DMN.

Objective: Understanding the intricate relationship between symptom dimensions, clusters, and cognitive impairments is crucial for early detection and intervention in individuals at clinical high-risk(CHR) for psychosis. This study delves into this complex interplay within a CHR sample and aims to predict the conversion to psychosis.

Methods: A comprehensive cognitive assessment was performed among 744 CHR individuals. The study included a three-year follow-up period to assess conversion to psychosis. Symptom profiles were determined using the Structured Interview for Prodromal Syndromes. By applying factor analysis, symptom dimensions were categorized as dominant negative symptoms(NS), positive symptoms-stressful(PS-S), and positive symptoms-odd(PS-O). The factor scores were used to define three dominant symptom groups. Latent class analysis(LCA) and factor mixture model(FMM) were employed to identify discrete clusters based on symptom patterns. The three-class solution was chosen for the LCA and FMM analysis.

Results: Individuals in the dominant NS group exhibited significantly higher conversion rates to psychosis than those in the other groups. Specific cognitive variables, including performance in the Brief Visuospatial Memory Test-Revised(Odd ratio, OR=0.702, p=0.001) and Neuropsychological Assessment Battery mazes(OR=0.776, p=0.024), significantly predicted conversion to psychosis. Notably, cognitive impairments associated with NS and PS-S affected different cognitive domains. LCA- and FMM-Cluster 1, characterized by severe NS and PS-O, exhibited more impairments in cognitive domains than other clusters. No significant difference in the conversion rate was observed among LCA and FMM clusters.

Conclusions: These findings highlight the importance of NS in the development of psychosis and suggest specific cognitive domains that are affected by symptom dimensions.

Background: There is increasing evidence of shared genetic factors between psychiatric disorders and brain magnetic resonance imaging (MRI) phenotypes. However, deciphering the joint genetic architecture of these outcomes has proven challenging, and new approaches are needed to infer potential genetic structure underlying those phenotypes. Multivariate analyses is arising as a meaningful approach to reveal links between MRI phenotypes and psychiatric disorders missed by univariate approaches.

Methods: We first conducted univariate and multivariate genome-wide association studies (GWAS) for nine MRI-derived brain volume phenotypes in 20K UK Biobank participants. We next performed various complementary enrichment analyses to assess whether and how univariate and multitrait approaches can distinguish disorder-associated and non-disorder-associated variants from six psychiatric disorders: bipolarity, attention-deficit/hyperactivity disorder (ADHD), autism, schizophrenia, obsessive-compulsive disorder, and major depressive disorder. Finally, we conducted a clustering analysis of top associated variants based on their MRI multitrait association using an optimized k-medoids approach.

Results: Univariate MRI GWAS displayed only negligible genetic correlation with psychiatric disorders, while multitrait GWAS identified multiple new associations and showed significant enrichment for variants related to both ADHD and schizophrenia. Clustering analyses further detected two clusters displaying not only enrichment for association with ADHD and schizophrenia, but also consistent direction of effects. Functional annotation analyses of those clusters pointed to multiple potential mechanisms, suggesting in particular a role of neurotrophins pathways on both MRI and schizophrenia.

Conclusions: Our results show that multitrait association signature can be used to infer genetically-driven latent MRI variables associated with psychiatric disorders, opening paths for future biomarker development.

Background: Schizophrenia Spectrum Disorders (SSDs), which are characterized by social cognitive deficits, have been associated with dysconnectivity in "unimodal" (e.g., visual, auditory) and "multimodal" (e.g., default-mode and frontoparietal) cortical networks. However, little is known regarding how such dysconnectivity relates to social and non-social cognition, and how such brain-behavioral relationships associate with clinical outcomes of SSDs.

Methods: We analyzed cognitive (non-social and social) measures and resting-state functional magnetic resonance imaging data from the 'Social Processes Initiative in Neurobiology of the Schizophrenia(s) (SPINS)' study (247 stable participants with SSDs and 172 healthy controls, ages 18-55). We extracted gradients from parcellated connectomes and examined the association between the first 3 gradients and the cognitive measures using partial least squares correlation (PLSC). We then correlated the PLSC dimensions with functioning and symptoms in the SSDs group.

Results: The SSDs group showed significantly lower differentiation on all three gradients. The first PLSC dimension explained 68.53% (p<.001) of the covariance and showed a significant difference between SSDs and Controls (bootstrap p<.05). PLSC showed that all cognitive measures were associated with gradient scores of unimodal and multimodal networks (Gradient 1), auditory, sensorimotor, and visual networks (Gradient 2), and perceptual networks and striatum (Gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSDs group.

Conclusions: These results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.

Background: Although the Clinical High-Risk for Psychosis (CHR-P) criteria are widely used to ascertain individuals at heightened risk for imminent onset of psychosis, it remains controversial whether CHR-P status define a diagnostic construct in its own right. In a prior study, CHR-P non-converters were observed to follow three distinct trajectories in symptoms and functioning: remission, partial remission, and maintenance of symptoms and functional impairments at subthreshold levels of intensity.

Methods: Here, we utilized the North American Prodrome Longitudinal Study Phase 3 (NAPLS3) sample (N = 806) to determine whether: 1) the same trajectory groups can be detected when assessing symptoms at 2-month intervals over an 8-month period and 2) the resulting trajectory groups differ from each other and from healthy controls and converting CHR-P cases in terms of risk factors, comorbidities, and functional outcomes.

Results: Three distinctive subgroups within the CHR non-converters were identified, largely paralleling those previously observed. Importantly, these extracted groups, along with non-CHR controls and CHR converters, differ from each other significantly with respect to putative etiological risk factors (e.g., predicted risk scores, physiological and self-report measures of stress), affective comorbidities, as well as functional outcomes, providing converging evidence supporting the validity of the identified trajectory groups.

Conclusions: This pattern, along with the fact that even the subgroup of CHR-P nonconverters showing a remission trajectory deviated from healthy controls, supports treating the CHR-P syndrome not just as a status that denotes risk for onset of full psychosis, but also as a marker of ongoing distress for a population in need of interventions.

Background: Pain empathy represents a fundamental building block of several social functions, which have been demonstrated to be impaired across various mental disorders by accumulating evidence from case-control functional magnetic resonance imaging (fMRI) studies. However, it remains unclear whether the dysregulations are underpinned by robust neural alterations across mental disorders.

Methods: This study utilized coordinate-based meta-analyses to quantitatively determine robust markers of altered pain empathy across mental disorders. To support the interpretation of the findings exploratory network-level and behavioral meta-analyses were conducted.

Results: Quantitative analysis of eleven case-control fMRI studies with data from 296 patients and 229 controls revealed patients with mental disorders exhibited increased pain empathic reactivity in the left anterior cingulate gyrus, adjacent medial prefrontal cortex, and right middle temporal gyrus, yet decreased activity in the left cerebellum IV/V and left middle occipital gyrus compared to controls. The hyperactive regions showed network-level interactions with the core default mode network (DMN) and were associated with affective and social cognitive domains.

Conclusions: The findings suggest that pain-empathic alterations across mental disorders are underpinned by excessive empathic reactivity in brain systems involved in empathic distress and social processes, highlighting a shared therapeutic target to normalize basal social dysfunctions in mental disorders.

Background: Reduced social attention - looking at faces - is one of the most common manifestations of social difficulty in autism central to social development. Although reduced social attention is well-characterized in autism, qualitative differences in how social attention unfolds across time remains unknown.

Methods: We used a computational modeling (i.e., hidden Markov modeling) approach to assess and compare the spatiotemporal dynamics of social attention in a large, well-characterized sample of autistic (n = 280) and neurotypical (n = 120) children (ages 6-11) that completed three social eye-tracking assays across three longitudinal time points (Baseline, 6 weeks, 24 weeks).

Results: Our analysis supported the existence of two common eye movement patterns that emerged across three ET assays. A focused pattern was characterized by small face regions of interest, which had high probability of capturing fixations early in visual processing. In contrast, an exploratory pattern was characterized by larger face regions of interest, with lower initial probability of fixation, and more non-social regions of interest. In the context of social perception, autistic children showed significantly more exploratory eye movement patterns than neurotypical children across all social perception assays and all three longitudinal time points. Eye movement patterns were associated with clinical features of autism, including adaptive function, face recognition, and autism symptom severity.

Conclusions: Decreased likelihood of precisely looking to faces early in social visual processing may be an important feature of autism that was associated with autism-related symptomology and may reflect less visual sensitivity to face information.

Background: Quantitative susceptibility mapping (QSM) is a neuroimaging technique that detects local changes in magnetic susceptibility induced by brain iron. Brain iron and the dopaminergic system are linked since iron is an important cofactor for dopamine synthesis. ADHD is associated with dysregulation of dopaminergic transmission. Therefore, we applied QSM on subcortical structures, to study potential alterations in brain iron and its impact on cognition and mental health in children with ADHD.

Methods: 3 Tesla QSM-data of 111 participants (n_ADHD= 58, mean age: 13.2 (0.63); n_Controls=53, mean age: 13.2 (0.51)) were analyzed. Subcortical regional brain iron values were extracted. ANOVAs examined group differences for each region of interest. For dimensional approaches, Pearson correlation analysis was performed across the cohort examining the association with symptoms, mental health, and cognition.

Results: No significant differences were found in iron susceptibility between ADHD and control, between persistent and remitted ADHD, or between medication use. An unexpected finding was that children with internalising disorder had significantly higher iron susceptibility, but the result did not survive multiple comparison corrections. Higher brain iron was associated with sustained attention, but not on inhibition, IQ, and working memory.

Conclusion: This is the first study addressing brain iron susceptibility and its association with comorbidities and cognition in ADHD. Alterations in brain iron may not account for the full diagnosis of ADHD but may be an indicator of internalising problems in children. Alterations in brain iron content in children were linked to detrimental sustained attention and may represent developmental variation in cognition.

Background: Current clinical studies have indicated that major depressive disorder (MDD) with adverse childhood experiences (ACEs) is associated with greater anhedonia. However, little is known about whether the change in reward sensitivity among young MDD individuals with ACEs are related to anhedonia.

Methods: We evaluated anhedonia and ACEs of each patient. Then, we performed Iowa gambling task during EEG to measure the reward positivity (RewP) and its difference (ΔRewP) in 86 MDD patients (31 with no or one ACE and 55 with two or more ACEs) and 44 healthy controls (HCs). Furthermore, we constructed a mediation model to assessed whether aberrant ΔRewP could mediate the relationship between ACEs and anhedonia.

Results: Compared with healthy controls and MDD patients with no or one ACE, MDD patients with two or more ACEs had the most severe symptoms of anhedonia and impaired decision-making, and showed significantly reduced reward sensitivity (most blunted ΔRewP). More importantly, ΔRewP mediated relationship between ACEs and anhedonia in MDD.

Conclusions: We found that the ΔRewP partially mediates the association between ACEs and anhedonia in MDD patients, which provides evidence for the neurobiological basis of abnormal changes in the reward system in MDD individuals with early adverse experiences.

Background: Treatment-resistant depression (TRD) affects about 30% of individuals with major depressive disorder. Deep brain stimulation (DBS) is an investigational intervention for TRD with varied results. We undertook this meta-analysis to synthesize outcome data across trial designs, anatomical targets, and institutions to better establish efficacy and side effect profiles.

Methods: We conducted a systematic PubMed review following PRISMA guidelines. Seven randomized-controlled trials (n=198) and eight open-label trials (n=77) were included, spanning 2009-2020. Outcome measures included Hamilton Depression Rating Scale or Montgomery-Åsberg Depression Rating Scale scores, as well as response and remission rates over time. Outcomes were tracked at last follow-up and quantified as a time course using model-based network meta-analysis. Linear mixed models were fit to individual patient data to identify covariates.

Results: DBS achieved 47% improvement in long-term depression scale scores, with an estimated time to reach 50% improvement around 23 months. There were no significant subgroup effects of stimulation target, time of last follow-up, sex, age of disease onset, or duration of disease, but open-label trials showed significantly greater treatment effects compared to randomized controlled trials. Long-term (12-60 month) response and remission rates were 48% and 35%, respectively. The time course of improvement with active stimulation could not be adequately distinguished from that with sham stimulation, when available.

Conclusions: DBS produces significant chronic improvement in symptoms of TRD. The limited sham-controlled data, however, does not demonstrate significant improvement over placebo. Future advancements in stimulation optimization and careful blinding and placebo schemes are important next steps for this therapy.