Journal of Psychiatry & Neuroscience最新文献

Background: Psychosocial interventions have emerged as an important component of a comprehensive therapeutic approach in early-onset schizophrenia, typically representing a more severe form of the disorder. Despite the feasibility and efficacy of Theory of Mind (ToM) psychotherapy for schizophrenia, relatively little is known regarding the neural mechanism underlying its effect on early-onset schizophrenia.

Methods: We performed a randomized, active controlled trial in patients with early-onset schizophrenia, who were randomly allocated into either an intervention (ToM psychotherapy) or an active control (health education) group. Diffusion tensor imaging data were collected to construct brain structural networks, with both global and regional topological properties measured using graph theory.

Results: We enrolled 28 patients with early-onset schizophrenia in our study. After 5 weeks of treatment, both the intervention and active control groups showed significant improvement in psychotic symptoms, yet the improvement was greater in the intervention group. Importantly, in contrast with no brain structural network change after treatment in the active control group, the intervention group showed increased nodal centrality of the left insula that was associated with psychotic symptom improvement.

Limitations: We did not collect important information concerning the participants' cognitive abilities, particularly ToM performance.

Conclusion: These findings suggest a potential neural mechanism by which ToM psychotherapy exerts a beneficial effect on early-onset schizophrenia via strengthening the coordination capacity of the insula in brain structural networks, which may provide a clinically translatable biomarker for monitoring or predicting responses to ToM psychotherapy.Clinical trial registration: NCT05577338; ClinicalTrials.gov.

Background: There have been conflicting reports on whether conventional verbal fluency measures can predict the prognosis of individuals at clinical high risk (CHR) for psychosis. We aimed to investigate whether verbal fluency task measures that represent semantic processing more directly than conventional measures could be more reliable predictors of later remission in CHR individuals.

Methods: We recruited CHR individuals and healthy controls to participate in a baseline verbal fluency assessment. We identified semantic clusters within the verbal fluency task responses based on cosine similarity between consecutive words, calculated from the word embedding model. Binomial logistic regression was performed to test whether average semantic cluster size and number of words produced could be predictors of remission in CHR individuals.

Results: Our study sample included 96 CHR individuals and 178 healthy controls. According to clinical assessment at the last follow-up, 23 CHR individuals were classified as remitters and 73 as nonremitters, including 29 individuals who converted to psychosis. The CHR remitters showed larger average and maximum semantic cluster sizes than CHR nonremitters and healthy controls. Average semantic cluster size, but not the number of words, was a significant predictor of later remission in CHR individuals.

Limitations: Our sample included only native Korean speakers.

Conclusion: A verbal fluency task measure that more specifically represents semantic processing may be a better neurocognitive predictive marker for remission in CHR individuals than conventional verbal fluency measures. Our results provide an explanation for heterogeneous reports on whether verbal fluency can predict prognosis in CHR individuals and suggest that semantic processing is a putative cognitive predictor of their prognosis.

Background: Apathy is associated with reduced antidepressant response and dementia in late-life depression (LLD). However, the functional cerebral basis of apathy is understudied in LLD. We investigated the functional connectivity of 5 resting-state networks (RSN) hypothesized to underlie apathy in LLD.

Methods: Resting-state functional MRI data were collected from individuals with LLD who did not have dementia as well as healthy older adults between October 2019 and April 2022. Apathy was evaluated using the diagnostic criteria for apathy (DCA), the Apathy Evaluation Scale (AES) and the Apathy Motivation Index (AMI). Subnetworks whose connectivity was significantly associated with each apathy measure were identified via the threshold-free network-based statistics. Regions that were consistently associated with apathy across the measures were reported as robust findings.

Results: Our sample included 39 individuals with LLD who did not have dementia and 26 healthy older adults. Compared with healthy controls, individuals with LLD had an altered intra-RSN and inter-RNS connectivity in the default mode, the cingulo-opercular and the frontoparietal networks. All 3 apathy measurements showed associations with modified intra-RSN connectivity in these networks, except for the DCA in the cingulo-opercular network. The AMI scores showed stronger associations with the cingulo-opercular and frontoparietal networks, whereas the AES had stronger associations with the default mode network and the goal-oriented behaviour network.

Limitations: The study was limited by the small number of participants without apathy according to the DCA, which may have reduced the statistical power of between-group comparisons. Additionally, the reliance on specific apathy measures may have influenced the observed overlap in brain regions.

Conclusion: Our findings indicate that apathy in LLD is consistently associated with changes in both intra-RSN and inter-RSN connectivity of brain regions implicated in goal-oriented behaviours. These results corroborate previous findings of altered functional RSN connectivity in severe LLD.

Background: Human navigation of social interactions relies on the processing of emotion on faces. This meta-analysis aimed to produce an updated brain atlas of emotional face processing from whole-brain studies based on a single emotional face-viewing paradigm (PROSPERO CRD42022251548).

Methods: We conducted a systematic literature search of Embase, MEDLINE and PsycINFO from May 2008 to October 2021. We used seed-based d mapping with permutation of subject images to conduct a quantitative meta-analysis of functional neuroimaging contrasts between emotional (e.g., angry, happy) and neutral faces. We conducted agglomerative hierarchical clustering of meta-analytic map contrasts of emotional faces relative to neutral faces. We investigated lateralization of emotional face processing.

Results: From 5549 studies identified, 55 data sets (1489 healthy participants) met our inclusion criteria. Relative to neutral faces, we found extensive activation clusters by fearful faces in the right inferior temporal gyrus, right fusiform area, left putamen and amygdala, right parahippocampalgyrus and cerebellum; we found smaller activation clusters by angry faces in the right cerebellum and right middle temporal gyrus (MTG) and by disgusted faces in the left MTG. Happy and sad faces did not reach statistical significance. Clustering analyses showed similar activation patterns of fearful and angry faces; activation patterns of happy and sad faces showed the least correlation with other emotional faces. Emotional face processing was predominantly left-lateralized in the amygdala and anterior insula, and right-lateralized in the ventromedial prefrontal cortex.

Limitations: Reliance on discretized effect sizes based on peak coordinate location instead of statistical brain maps, and the varying level of statistical threshold reporting from original studies, could lead to underdetection of smaller clusters of activation.

Conclusion: Processing of emotional faces appeared to be oriented toward identifying threats on faces, from highest (i.e., angry or fearful faces) to lowest level (i.e., happy or sad faces), with a more complex lateralization pattern than previously theorized. Emotional faces may be processed in latent grouping but organized by threat content rather than emotional valence.

Background: Attention deficit/hyperactivity disorder (ADHD) is a highly prevalent childhood disorder. Maternal smoking during pregnancy is a replicated environmental risk factor for this disorder. It is also a robust modifier of gene methylation during the prenatal developmental period. In this study, we sought to identify loci differentially methylated by maternal smoking during pregnancy and relate their methylation levels to various behavioural and physical outcomes relevant to ADHD.

Methods: We extracted DNA from blood samples from children diagnosed with ADHD and deeply phenotyped. Genome-wide DNA methylation was assessed using Infinium MethylationEPIC BeadChip. Maternal smoking during pregnancy was self-declared and assessed retrospectively.

Results: Our sample included 231 children with ADHD. Statistically significant differences in DNA methylation between children exposed or not to maternal smoking during pregnancy were detected in 3457 CpGs. We kept 30 CpGs with at least 5% of methylation difference between the 2 groups for further analysis. Six genes were associated with varied phenotypes of clinical relevance to ADHD. The levels of DNA methylation in RUNX1 were positively correlated with the CBCL scores, and DNA methylation in MYO1G correlated positively with the score at the Conners rating scale. Methylation level in a CpG located in GFI1 correlated with birthweight, a risk factor for ADHD. Differentially methylated regions were also identified and confirmed the association of RUNX1 methylation levels with the CBCL score.

Limitations: The study has several limitations, including the retrospective recall with self-report of maternal smoking during pregnancy as well as the grouping of individuals of varying age and developmental stage and of both males and females. In addition, the correlation design prevents the building of causation models.

Conclusion: This study provides evidence for the association between the level of methylation at specific loci and quantitative dimensions highly relevant for ADHD as well as birth weight, a measure that has already been associated with increased risk for ADHD. Our results provide further support to public health educational initiatives to stop maternal smoking during pregnancy.

Background: Among healthy participants, the interindividual variability of brain response to facial emotions is associated with genetic variation, including common risk variants for schizophrenia, a heritable brain disorder characterized by anomalies in emotion processing. We aimed to identify genetic variants associated with heritable brain activity during processing of facial emotions among healthy participants and to explore the impact of these identified variants among patients with schizophrenia.

Methods: We conducted a data-driven stepwise study including samples of healthy twins, unrelated healthy participants and patients with schizophrenia. Participants approached or avoided pictures of faces with negative emotional valence during functional magnetic resonance imaging (fMRI).

Results: We investigated 3 samples of healthy participants - including 28 healthy twin pairs, 289 unrelated healthy participants (genome-wide association study [GWAS] discovery sample) and 90 unrelated healthy participants (replication sample) - and 1 sample of 48 patients with schizophrenia. Among healthy twins, we identified the amygdala as the brain region with the highest heritability during processing of angry faces (heritability estimate 0.54, p < 0.001). Subsequent GWAS in both discovery and replication samples of healthy non-twins indicated that amygdala activity was associated with a polymorphism in the miR-137 locus (rs1198575), a micro-RNA strongly involved in risk for schizophrenia. A significant effect in the same direction was found among patients with schizophrenia (p = 0.03).

Limitations: The limited sample size available for GWAS analyses may require further replication of results.

Conclusion: Our data-driven approach shows preliminary evidence that amygdala activity, as evaluated with our task, is heritable. Our genetic associations preliminarily suggest a role for miR-137 in brain activity during explicit processing of facial emotions among healthy participants and patients with schizophrenia, pointing to the amygdala as a brain region whose activity is related to miR-137.

Background: Among its pleiotropic properties, gender-affirming hormone therapy (GHT) affects regional brain volumes. The hypothalamus, which regulates neuroendocrine function and associated emotional and cognitive processes, is an intuitive target for probing GHT effects. We sought to assess changes to hypothalamus and hypothalamic subunit volumes after GHT, thereby honouring the region's anatomical and functional heterogeneity.

Methods: Individuals with gender dysphoria and cisgender controls underwent 2 MRI measurements, with a median interval of 145 days (interquartile range [IQR] 128.25-169.75 d, mean 164.94 d) between the first and second MRI. Transgender women (TW) and transgender men (TM) underwent the first MRI before GHT and the second MRI after approximately 4.5 months of GHT, which comprised estrogen and anti-androgen therapy in TW or testosterone therapy in TM. Hypothalamic volumes were segmented using FreeSurfer, and effects of GHT were tested using repeated-measures analysis of covariance.

Results: The final sample included 106 participants: 38 TM, 15 TW, 32 cisgender women (CW) and 21 cisgender men (CM). Our analyses revealed group × time interaction effects for total, left and right hypothalamus volume, and for several subunits (left and right inferior tubular, left superior tubular, right anterior inferior, right anterior superior, all p _corr < 0.01). In TW, volumes decreased between the first and second MRI in these regions (all p _corr ≤ 0.01), and the change from the first to second MRI in TW differed significantly from that in CM and CW in several subunits (p _corr < 0.05).

Limitations: We did not address the influence of transition-related psychological and behavioural changes.

Conclusion: Our results suggest a subunit-specific effect of GHT on hypothalamus volumes in TW. This finding is in accordance with previous reports of positive and negative effects of androgens and estrogens, respectively, on cerebral volumes.

Background: Over recent decades, autism spectrum disorder (ASD) has been of increasing epidemiological importance, given the substantial increase in its prevalence; at present, clinical diagnosis is possible only after 2 years of age. In this study, we sought to develop a potential predictive model for ASD screening.

Methods: We conducted a longitudinal follow-up study of newborns over 3 years. We measured transcript levels of 4 genes (superoxide dismutase-2 [SOD2], retinoic acid-related orphan receptor-α [RORA], G protein-coupled estrogen receptor-1 [GPER], progesterone receptor [PGR]), 2 oxidative stress markers and epigenetic marks at the RORA promoter in case-control umbilical cord blood mononuclear cell (UCBMC) samples.

Results: We followed 2623 newborns; we identified 41 children with ASD, 63 with delayed development and 2519 typically developing children. We matched the 41 children with ASD to 41 typically developing children for UCBMC measurements. Our results showed that children with ASD had significantly higher levels of H3K9me3 histone modifications at the RORA promoter and oxidative stress in UCBMC than typically developing children; children with delayed development showed no significant differences. Children with ASD had significantly lower expression of SOD2, RORA and GPER, but higher PGR expression than typically developing children. We established a model based on these 4 candidate genes, and achieved an area under the curve of 87.0% (standard deviation 3.9%) with a sensitivity of 1.000 and specificity of 0.854 to predict ASD in UCBMC.

Limitations: Although the gene combinations produced a good pass/fail cut-off value for ASD evaluation, relatively few children in our study sample had ASD.

Conclusion: The altered gene expression in UCBMC can predict later autism development, possibly providing a predictive model for ASD screening immediately after birth.