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Chronic insomnia disorder (CID) is a multidimensional disease that may influence various levels of brain organization, spanning the macroscopic structural connectome to microscopic gene expression. However, the connection between genomic variations and morphological alterations in CID remains unclear. Here, we investigated brain structural changes in CID patients at the whole‐brain level and whether these link to transcriptional characteristics. Brain structural data from 104 CID patients and 102 matched healthy controls (HC) were acquired to examine cortical structural alterations using morphometric similarity (MS) analysis. Partial least squares (PLS) regression and transcriptome data from the Allen Human Brain Atlas were used to extract genomes related to MS changes. Gene‐category enrichment analysis (GCEA) was used to identify potential molecular mechanisms behind the observed structural changes. We found that CID patients exhibited MS reductions in the parietal and limbic regions, along with enhancements in the temporal and frontal regions compared to HCs (pFDR <.05). Subsequently, PLS and GCEA revealed that these MS alterations were spatially correlated with a set of genes, especially those significantly correlated with excitatory and inhibitory neurons and chronic neuroinflammation. This neuroimaging‐transcriptomic study bridges the gap between cortical structural changes and the molecular mechanisms in CID patients, providing novel insight into the pathophysiology of insomnia and targeted treatments. The association between genomics and brain structural changes in chronic insomnia disorder is not well understood. Imaging transcriptional analysis bridges the gap between cortical structural changes and molecular mechanisms. Integrating neuroimaging and gene expression data, our work indicates that structural changes in chronic insomnia may be related to chronic neuroinflammation and imbalances between excitatory and inhibitory neuronal activities. [ABSTRACT FROM AUTHOR]

The high and increasing proportion of single-parent families is considered a risk factor associated with various childhood trauma experiences. Consequently, concerns have been raised regarding the potential long-term effects of the childhood single-parent family structure. In this study, we employed advanced magnetic resonance imaging technology, including morphometric similarity mapping, functional connectivity density, and network-based analysis, to investigate brain connectivity and behavioral differences among young adults who were raised in single-parent families. Our study also aimed to explore the relationship between these differences and childhood trauma experiences. The results showed that individuals who grew up in single-parent families exhibited higher levels of anxiety, depression, and harm-avoidant personality. The multimodal MRI analysis further showed differences in regional and network-based connectivity properties in the single-parent family group, including increased functional connectivity density in the left inferior parietal lobule, enhanced cortical structural connectivity between the left isthmus cingulate cortex and peri-calcarine cortex, and an increase in temporal functional connectivity. Moreover, elevated levels of anxiety and depression, along with heightened functional connectivity density in the left inferior parietal lobule and increased temporal functional connectivity, were found to be correlated with a greater number of childhood trauma experiences. Through analyzing multiple data patterns, our study provides objective neuropsychobiological evidence for the enduring impact of childhood single-parent family structure on psychiatric vulnerability in adulthood. [ABSTRACT FROM AUTHOR]

Background: Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear. Objective: This study aimed to characterize the morphometric changes of brain regions in early drug‐naive PD patients and uncover the brain‐wide gene expression correlates. Methods: The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug‐naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD‐related genes were enriched and the cellular characterization of these genes. Results: Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug‐naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron‐specific biological processes related to trans‐synaptic signaling and nervous system development. Conclusions: These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug‐naive PD patients and provide potential targets for future therapeutic trials. [ABSTRACT FROM AUTHOR]

Intro: Paediatric traumatic brain injury (pTBI) is likely to result in cognitive impairment, specifically executive dysfunction. Evidence of the neuroanatomical correlates of this executive function (EF) impairment is derived from studies that treat morphometry of brain regions as distinct, independent features, rather than as a complex network of interrelationships. Morphometric similarity captures the meso-scale organisation of the cortex as the interrelatedness of multiple macro-architectural features and presents a novel tool with which to investigate the brain post pTBI. Methods: In a retrospective sample (83 pTBI patients, 33 controls), we estimate morphometric similarity from structural MRI by correlating morphometric features between cortical regions. We compared the meso-scale organisation of the cortex between groups then, using partial least squares regression, assessed the predictive validity of morphometric similarity in understanding later executive functioning, two years post-injury. Results: We found that patients and controls did not differ in terms of the overall magnitude of morphometric similarity. However, a pattern of ROI-level morphometric similarity was predictive of day-to-day EF difficulties reported by parents two years post-injury. This prediction was validated using a leave-one-out, and 20-fold cross-validation approach. Prediction was driven by regions of the prefrontal cortex, typically important for healthy maturation of EF skills in childhood. The meso-scale organisation of the cortex also produced more accurate predictions than any one morphometric feature (i.e. cortical thickness or folding index) alone. Conclusion: We conclude that these methodologies show utility in predicting later executive functioning in this population.

Intro: Paediatric traumatic brain injury (pTBI) is likely to result in cognitive impairment, specifically executive dysfunction. Evidence of the neuroanatomical correlates of this executive function (EF) impairment is derived from studies that treat morphometry of brain regions as distinct, independent features, rather than as a complex network of interrelationships. Morphometric similarity captures the meso-scale organisation of the cortex as the interrelatedness of multiple macro-architectural features and presents a novel tool with which to investigate the brain post pTBI., Methods: In a retrospective sample (83 pTBI patients, 33 controls), we estimate morphometric similarity from structural MRI by correlating morphometric features between cortical regions. We compared the meso-scale organisation of the cortex between groups then, using partial least squares regression, assessed the predictive validity of morphometric similarity in understanding later executive functioning, two years post-injury., Results: We found that patients and controls did not differ in terms of the overall magnitude of morphometric similarity. However, a pattern of ROI-level morphometric similarity was predictive of day-to-day EF difficulties reported by parents two years post-injury. This prediction was validated using a leave-one-out, and 20-fold cross-validation approach. Prediction was driven by regions of the prefrontal cortex, typically important for healthy maturation of EF skills in childhood. The meso-scale organisation of the cortex also produced more accurate predictions than any one morphometric feature (i.e. cortical thickness or folding index) alone., Conclusion: We conclude that these methodologies show utility in predicting later executive functioning in this population., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Abstract: Chronic pain is a highly debilitating and difficult to treat condition, which affects the structure of the brain. Although the development of chronic pain is moderately heritable, how disease-related alterations at the microscopic genetic architecture drive macroscopic brain abnormalities is currently largely unknown. Here, we examined alterations in morphometric similarity (MS) and applied an integrative imaging transcriptomics approach to identify transcriptional and cellular correlates of these MS changes, in 3 independent small cohorts of patients with distinct chronic pain syndromes (knee osteoarthritis, low back pain, and fibromyalgia) and age-matched and sex-matched pain-free controls. We uncover a novel pattern of cortical MS remodelling involving mostly small-to-medium MS increases in the insula and limbic cortex (none of these changes survived stringent false discovery rate correction for the number of regions tested). This pattern of changes is different from that observed in patients with major depression and cuts across the boundaries of specific pain syndromes. By leveraging transcriptomic data from Allen Human Brain Atlas, we show that cortical MS remodelling in chronic pain spatially correlates with the brain-wide expression of genes related to pain and broadly involved in the glial immune response and neuronal plasticity. Our findings bridge levels to connect genes, cell classes, and biological pathways to in vivo imaging correlates of chronic pain. Although correlational, our data suggest that cortical remodelling in chronic pain might be shaped by multiple elements of the cellular architecture of the brain and identifies several pathways that could be prioritized in future genetic association or drug development studies. [ABSTRACT FROM AUTHOR]

Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluate the impact of several processing steps on the processing time and quality of registration of manually labelled T1‐weighted MRI scans. Subsequently, we apply the selected rapid processing pipeline both to rapidly acquired multicontrast EPImix scans of 95 participants (which include T1‐FLAIR, T2, T2*, T2‐FLAIR, DWI and ADC contrasts, acquired in ~1 min), as well as to slower, more standard single‐contrast T1‐weighted scans of a subset of 66 participants. We quantify the correspondence between EPImix T1‐FLAIR and single‐contrast T1‐weighted scans, using correlations between voxels and regions of interest across participants, measures of within‐ and between‐participant identifiability as well as regional structural covariance networks. Furthermore, we explore the use of EPImix for the rapid construction of morphometric similarity networks. Finally, we quantify the reliability of EPImix‐derived data using test–retest scans of 10 participants. Our results demonstrate that quantitative information can be derived from a neuroimaging scan acquired and processed within minutes, which could further be used to implement adaptive multimodal imaging and tailor neuroimaging examinations to individual patients. [ABSTRACT FROM AUTHOR]

Disruptions in brain connectivity have been widely reported in Alzheimer’s disease (AD). Morphometric similarity (MS) mapping provides a new way of estimating structural connectivity by interregional correlation of T1WI- and DTI-derived parameters within individual brains. Here, we aimed to identify AD-related MS changing patterns and genes related to the changes and further explored the molecular and cellular mechanism underlying MS changes in AD. Both 3D-T1WI and DTI data of 106 AD patients and 106 well-matched healthy elderly individuals from the ADNI database were included in our study. Cortical regions with significantly decreased MS were found in the temporal and parietal cortex, increased MS was found in the frontal cortex and variant changes were found in the occipital cortex in AD patients. Mean MS in regions with significantly changed MS was positively or negatively associated with memory function. Negative MS-related genes were significantly downregulated in AD, specifically enriched in neurons, and participated in biological processes, with the most significant term being synaptic transmission. This study revealed AD-related cortical MS changes associated with memory function. Linking gene expression to cortical MS changes may provide a possible molecular and cellular substrate for MS abnormality and cognitive decline in AD.

Summary: The topological organization of the cerebral cortex provides hierarchical axes, namely gradients, which reveal systematic variations of brain structure and function. However, the hierarchical organization of macroscopic brain morphology and how it constrains cortical function along the organizing axes remains unclear. We map the gradient of cortical morphometric similarity (MS) connectome, combining multiple features conceptualized as a “fingerprint” of an individual’s brain. The principal MS gradient is anchored by motor and sensory cortices at two extreme ends, which are reliable and reproducible. Notably, divergences between motor and sensory hierarchies are consistent with the laminar histological thickness gradient but contrary to the canonical functional connectivity (FC) gradient. Moreover, the MS dissociates with FC gradients in the higher-order association cortices. The MS gradient recapitulates fundamental properties of cortical organization, from gene expression and cyto- and myeloarchitecture to evolutionary expansion. Collectively, our findings provide a heuristic hierarchical organization of cortical morphological neuromarkers.

Disruptions in brain connectivity have been widely reported in Alzheimer's disease (AD). Morphometric similarity (MS) mapping provides a new way of estimating structural connectivity by interregional correlation of T1WI- and DTI-derived parameters within individual brains. Here, we aimed to identify AD-related MS changing patterns and genes related to the changes and further explored the molecular and cellular mechanism underlying MS changes in AD. Both 3D-T1WI and DTI data of 106 AD patients and 106 well-matched healthy elderly individuals from the ADNI database were included in our study. Cortical regions with significantly decreased MS were found in the temporal and parietal cortex, increased MS was found in the frontal cortex and variant changes were found in the occipital cortex in AD patients. Mean MS in regions with significantly changed MS was positively or negatively associated with memory function. Negative MS-related genes were significantly downregulated in AD, specifically enriched in neurons, and participated in biological processes, with the most significant term being synaptic transmission. This study revealed AD-related cortical MS changes associated with memory function. Linking gene expression to cortical MS changes may provide a possible molecular and cellular substrate for MS abnormality and cognitive decline in AD. [ABSTRACT FROM AUTHOR]

A common task in brain image analysis includes diagnosis of a certain medical condition wherein groups of healthy controls and diseased subjects are analyzed and compared. On the other hand, for two groups of healthy participants with different proficiency in a certain skill, a distinctive analysis of the brain function remains a challenging problem. In this study, we develop new computational tools to explore the functional and anatomical differences that could exist between the brain of healthy individuals identified on the basis of different levels of task experience/proficiency. Toward this end, we look at a dataset of amateur and professional chess players, where we utilize resting-state functional magnetic resonance images to generate functional connectivity (FC) information. In addition, we utilize T1-weighted magnetic resonance imaging to estimate morphometric connectivity (MC) information. We combine functional and anatomical features into a new connectivity matrix, which we term as the functional morphometric similarity connectome (FMSC). Since, both the FC and MC information is susceptible to redundancy, the size of this information is reduced using statistical feature selection. We employ off-the-shelf machine learning classifier, support vector machine, for both single- and multi-modality classifications. From our experiments, we establish that the saliency and ventral attention network of the brain is functionally and anatomically different between two groups of healthy subjects (chess players). We argue that, since chess involves many aspects of higher order cognition such as systematic thinking and spatial reasoning and the identified network is task-positive to cognition tasks requiring a response, our results are valid and supporting the feasibility of the proposed computational pipeline. Moreover, we quantitatively validate an existing neuroscience hypothesis that learning a certain skill could cause a change in the brain (functional connectivity and anatomy) and this can be tested via our novel FMSC algorithm.

A common task in brain image analysis includes diagnosis of a certain medical condition wherein groups of healthy controls and diseased subjects are analyzed and compared. On the other hand, for two groups of healthy participants with different proficiency in a certain skill, a distinctive analysis of the brain function remains a challenging problem. In this study, we develop new computational tools to explore the functional and anatomical differences that could exist between the brain of healthy individuals identified on the basis of different levels of task experience/proficiency. Toward this end, we look at a dataset of amateur and professional chess players, where we utilize resting-state functional magnetic resonance images to generate functional connectivity (FC) information. In addition, we utilize T1-weighted magnetic resonance imaging to estimate morphometric connectivity (MC) information. We combine functional and anatomical features into a new connectivity matrix, which we term as the functional morphometric similarity connectome (FMSC). Since, both the FC and MC information is susceptible to redundancy, the size of this information is reduced using statistical feature selection. We employ off-the-shelf machine learning classifier, support vector machine, for both single- and multi-modality classifications. From our experiments, we establish that the saliency and ventral attention network of the brain is functionally and anatomically different between two groups of healthy subjects (chess players). We argue that, since chess involves many aspects of higher order cognition such as systematic thinking and spatial reasoning and the identified network is task-positive to cognition tasks requiring a response, our results are valid and supporting the feasibility of the proposed computational pipeline. Moreover, we quantitatively validate an existing neuroscience hypothesis that learning a certain skill could cause a change in the brain (functional connectivity and anatomy) and this can be tested via our novel FMSC algorithm. [ABSTRACT FROM AUTHOR]

The morphometry of the hydrographic basins of the Pacific slope in the Ecuadorian territory is analyzed with digitized topographic information in an Elevation Model obtaining surface characteristics, relief, and water network that determine the hydrological behavior. The analysis is carried out in 13 Hydrographic Systems that represent an area of 92775.87 km2; the results are obtained through a statistical analysis of the relationships that form the morphometric characteristics obtaining a hydrological characterization of an area of the great influence of the Pacific Pending. The parameters used are Horton factor, compactness coefficient, drainage density, the roughness of the basin, bifurcation ratio, and elongation ratio. From each parameter, position and dispersion statistics were obtained, statistical tests and cluster analysis were performed, evaluating the relationships that exist between each of the systems, obtaining morphometric similarities and forming groups that share similar characteristics. [ABSTRACT FROM AUTHOR]

Human brain structure shows heterogeneous patterns of change across adults aging and is associated with cognition. However, the relationship between cortical structural changes during aging and gene transcription signatures remains unclear. Here, using structural magnetic resonance imaging data of two separate cohorts of healthy participants from the Cambridge Centre for Aging and Neuroscience (n = 454, 18-87 years) and Dallas Lifespan Brain Study (n = 304, 20-89 years) and a transcriptome dataset, we investigated the link between cortical morphometric similarity network and brain-wide gene transcription. In two cohorts, we found reproducible morphometric similarity network change patterns of decreased morphological similarity with age in cognitive related areas (mainly located in superior frontal and temporal cortices), and increased morphological similarity in sensorimotor related areas (postcentral and lateral occipital cortices). Changes in morphometric similarity network showed significant spatial correlation with the expression of age-related genes that enriched to synaptic-related biological processes, synaptic abnormalities likely accounting for cognitive decline. Transcription changes in astrocytes, microglia, and neuronal cells interpreted most of the age-related morphometric similarity network changes, which suggest potential intervention and therapeutic targets for cognitive decline. Taken together, by linking gene transcription signatures to cortical morphometric similarity network, our findings might provide molecular and cellular substrates for cortical structural changes related to cognitive decline across adults aging., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Schizophrenia has been conceived as a disorder of brain connectivity, but it is unclear how this network phenotype is related to the underlying genetics. We used morphometric similarity analysis of MRI data as a marker of interareal cortical connectivity in three prior case-control studies of psychosis: in total, n = 185 cases and n = 227 controls. Psychosis was associated with globally reduced morphometric similarity in all three studies. There was also a replicable pattern of case-control differences in regional morphometric similarity, which was significantly reduced in patients in frontal and temporal cortical areas but increased in parietal cortex. Using prior brain-wide gene expression data, we found that the cortical map of case-control differences in morphometric similarity was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms and pathways. In addition, genes that were normally overexpressed in cortical areas with reduced morphometric similarity were significantly up-regulated in three prior post mortem studies of schizophrenia. We propose that this combined analysis of neuroimaging and transcriptional data provides insight into how previously implicated genes and proteins as well as a number of unreported genes in their topological vicinity on the protein interaction network may drive structural brain network changes mediating the genetic risk of schizophrenia. [ABSTRACT FROM AUTHOR]

Background: Pediatric bipolar disorder (PBD) has been proven to be related to abnormal brain structural connectivity, but how the abnormalities in PBD correlate with gene expression is debated., Objective: This study aims at identification of cell-type-specific gene modules based on cortical structural differences in PBD., Methods: Morphometric similarity networks (MSN) were computed as a marker of interareal cortical connectivity based on MRI data from 102 participants (59 patients and 43 controls). Partial least squares (PLS) regression was used to calculate MSN differences related to transcriptomic data in AHBA. The biological processes and cortical cell types associated with this gene expression profile were determined by gene enrichment tools., Results: MSN analysis results demonstrated differences of cortical structure between individuals diagnosed with PBD and healthy control participants. MSN differences were spatially correlated with the PBD-related weighted genes. The weighted genes were enriched for "trans-synaptic signaling" and "regulation of ion transport", and showed significant specific expression in excitatory and inhibitory neurons., Conclusions: This study identified the genes that contributed to structural network aberrations in PBD. It was found that transcriptional changes of excitatory and inhibitory neurons might be associated with abnormal brain structural connectivity in PBD., Competing Interests: W.L., Q.X., Y.D., Y.Z., G.L., Y.X., C.W., W.G., and L.S. report no biomedical financial interests or potential conflicts of interest., (© The Author(s) 2022. Published by Oxford University Press on behalf of West China School of Medicine/West China Hospital (WCSM/WCH) of Sichuan University.)

Chronic drug use negatively impacts ageing, resulting in diminished health and quality of life. However, little is known about biomarkers of abnormal ageing in stimulant drug users. Using morphometric similarity network mapping, a novel approach to structural connectomics, we first mapped cross-sectional morphometric similarity trajectories of ageing in the publicly available Rockland Sample (20-80 years of age, n  = 665). We then compared morphometric similarity and neuropsychological function between non-treatment-seeking, actively using patients with stimulant use disorder ( n  = 183, mean age: 35.6 years) and healthy control participants ( n  = 148, mean age: 36.0 years). The significantly altered mean regional morphometric similarity was found in 43 cortical regions including the inferior and orbital frontal gyri, pre/postcentral gyri and anterior temporal, superior parietal and occipital areas. Deviations from normative morphometric similarity trajectories in patients with stimulant use disorder suggested abnormal brain ageing. Furthermore, deficits in paired associates learning were consistent with neuropathology associated with both ageing and stimulant use disorder. Morphometric similarity mapping provides a promising biomarker for ageing in health and disease and may complement existing neuropsychological markers of age-related cognitive decline. Neuropathological ageing mechanisms in stimulant use disorder warrant further investigation to develop more age-appropriate treatments for older people addicted to stimulant drugs., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

The topological organization of the cerebral cortex provides hierarchical axes, namely gradients, which reveal systematic variations of brain structure and function. However, the hierarchical organization of macroscopic brain morphology and how it constrains cortical function along the organizing axes remains unclear. We map the gradient of cortical morphometric similarity (MS) connectome, combining multiple features conceptualized as a "fingerprint" of an individual's brain. The principal MS gradient is anchored by motor and sensory cortices at two extreme ends, which are reliable and reproducible. Notably, divergences between motor and sensory hierarchies are consistent with the laminar histological thickness gradient but contrary to the canonical functional connectivity (FC) gradient. Moreover, the MS dissociates with FC gradients in the higher-order association cortices. The MS gradient recapitulates fundamental properties of cortical organization, from gene expression and cyto- and myeloarchitecture to evolutionary expansion. Collectively, our findings provide a heuristic hierarchical organization of cortical morphological neuromarkers. [Display omitted] • Primary motor and sensory areas occupy two extreme ends in the MS gradient • The MS gradient closely correlates with mesoscale histological layering thickness • The MS gradient dissociates with the FC gradient in high-level association cortices • The MS gradient pattern is closely associated with cortical fundamental properties Yang et al. investigate the patterning of the cortical morphometric similarity (MS) gradient, which is anchored by sensory and motor cortices and diverges from the functional gradient. The MS gradient also shows similarities to other properties of cortical organization, such as gene expression, cyto-, and myeloarchitecture as well as evolutionary cortical expansion. [ABSTRACT FROM AUTHOR]

• MBDNF × CTQ interactions on morphological and functional connectivity of regions regulate emotion processing. • The Val/Val genotype with higher BDNF availability is more susceptible to experience-induced brain plasticity. • Childhood adversity contributes to functional plasticity of the self-reference network, increasing the risk of anxiety. Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism may modulate the link between childhood trauma experience and psychopathology by altering trophic signaling on neuroplasticity. However, few multimodal magnetic resonance imaging (MRI) researches have investigated this gene-environment interaction on both structural and functional plasticity, thereby advancing knowledge about the etiology, prevention, and customized therapeutic directions of mental disease in individuals with childhood trauma experience. We recruited a large non-clinical sample of young adults that completed Childhood Trauma Questionnaire (CTQ), behavioral scores, multimodal MRI scans, and genotyping. Morphometric similarity network (MSN) and independent component analysis were adopted to quantify brain structural and functional changes. Gene-environment-brain-behavior relationships were identified by multiple regression and mediation effect analysis. CTQ score was positively associated with depression and anxiety scores. We found interactions on MSN in sensorimotor, temporal, and orbitofrontal cortex. For intra-network connectivity, significant interaction was noted in clusters within sensorimotor network. For inter-network connectivity, connectivity between dorsal attention network and salience network showed an interactive effect. For mean connectivity strength of each network, we found a main effect of CTQ score on self-reference network that was an outstanding mediator supporting the relationship between CTQ score and anxiety. Our findings demonstrate that childhood trauma and the BDNF Val66Met polymorphism are associated with brain plasticity involving emotion regulation, structurally and functionally, which may contribute to understanding psychotic mechanisms and predicting differential susceptibility. Imaging genetics may be useful as biomarkers to provide early assessment and guide cognitive interventions to avoid or decrease the risk of developing psychopathology. [ABSTRACT FROM AUTHOR]