Multimodal Associations of FKBP5 Methylation With Emotion-Regulatory Brain Circuits.

BACKGROUND: Understanding the biological processes that underlie individual differences in emotion regulation and stress responsivity is a key challenge for translational neuroscience. The gene FKBP5 is a core regulator in molecular stress signaling that is implicated in the development of psychiatric disorders. However, it remains unclear how FKBP5 DNA methylation in peripheral blood is related to individual differences in measures of neural structure and function and their relevance to daily-life stress responsivity. METHODS: Here, we characterized multimodal correlates of FKBP5 DNA methylation by combining epigenetic data with neuroimaging and ambulatory assessment in a sample of 395 healthy individuals. RESULTS: First, we showed that FKBP5 demethylation as a psychiatric risk factor was related to an anxiety-associated reduction of gray matter volume in the ventromedial prefrontal cortex, a brain area that is involved in emotion regulation and mental health risk and resilience. This effect of epigenetic upregulation of FKBP5 on neuronal structure is more pronounced where FKBP5 is epigenetically downregulated at baseline. Leveraging 208 functional magnetic resonance imaging scans during a well-established emotion-processing task, we found that FKBP5 DNA methylation in peripheral blood was associated with functional differences in prefrontal-limbic circuits that modulate affective responsivity to daily stressors, which we measured using ecological momentary assessment in daily life. CONCLUSIONS: Overall, we demonstrated how FKBP5 contributes to interindividual differences in neural and real-life affect regulation via structural and functional changes in prefrontal-limbic brain circuits.

Linking functional and structural brain organisation with behaviour in autism: a multimodal EU-AIMS Longitudinal European Autism Project (LEAP) study.

Neuroimaging analyses of brain structure and function in autism have typically been conducted in isolation, missing the sensitivity gains of linking data across modalities. Here we focus on the integration of structural and functional organisational properties of brain regions. We aim to identify novel brain-organisation phenotypes of autism. We utilised multimodal MRI (T1-, diffusion-weighted and resting state functional), behavioural and clinical data from the EU AIMS Longitudinal European Autism Project (LEAP) from autistic (n = 206) and non-autistic (n = 196) participants. Of these, 97 had data from 2 timepoints resulting in a total scan number of 466. Grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps were extracted from respective MRI modalities and were then integrated with Linked Independent Component Analysis. Linear mixed-effects models were used to evaluate the relationship between components and group while accounting for covariates and non-independence of participants with longitudinal data. Additional models were run to investigate associations with dimensional measures of behaviour. We identified one component that differed significantly between groups (coefficient = 0.33, padj = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal (uncorrected p < 0.05) associations with behavioural measures, none were significant following multiple comparison correction. Our analysis considered the relative contributions of both structural and functional brain phenotypes simultaneously, finding that functional phenotypes drive associations with autism. These findings expanded on previous unimodal studies by revealing the topographic organisation of functional connectivity patterns specific to autism and warrant further investigation.

Fine-grained topographic organization within somatosensory cortex during resting-state and emotional face-matching task and its association with ASD traits.

Sensory atypicalities are particularly common in autism spectrum disorders (ASD). Nevertheless, our knowledge about the divergent functioning of the underlying somatosensory region and its association with ASD phenotype features is limited. We applied a data-driven approach to map the fine-grained variations in functional connectivity of the primary somatosensory cortex (S1) to the rest of the brain in 240 autistic and 164 neurotypical individuals from the EU-AIMS LEAP dataset, aged between 7 and 30. We estimated the S1 connection topography ('connectopy') at rest and during the emotional face-matching (Hariri) task, an established measure of emotion reactivity, and accessed its association with a set of clinical and behavioral variables. We first demonstrated that the S1 connectopy is organized along a dorsoventral axis, mapping onto the S1 somatotopic organization. We then found that its spatial characteristics were linked to the individuals' adaptive functioning skills, as measured by the Vineland Adaptive Behavior Scales, across the whole sample. Higher functional differentiation characterized the S1 connectopies of individuals with higher daily life adaptive skills. Notably, we detected significant differences between rest and the Hariri task in the S1 connectopies, as well as their projection maps onto the rest of the brain suggesting a task-modulating effect on S1 due to emotion processing. All in all, variation of adaptive skills appears to be reflected in the brain's mesoscale neural circuitry, as shown by the S1 connectivity profile, which is also differentially modulated during rest and emotional processing.

Dose-dependent changes in real-life affective well-being in healthy community-based individuals with mild to moderate childhood trauma exposure.

BACKGROUND: Childhood trauma exposures (CTEs) are frequent, well-established risk factor for the development of psychopathology. However, knowledge of the effects of CTEs in healthy individuals in a real life context, which is crucial for early detection and prevention of mental disorders, is incomplete. Here, we use ecological momentary assessment (EMA) to investigate CTE load-dependent changes in daily-life affective well-being and psychosocial risk profile in n = 351 healthy, clinically asymptomatic, adults from the community with mild to moderate CTE. FINDINGS: EMA revealed significant CTE dose-dependent decreases in real-life affective valence (p = 0.007), energetic arousal (p = 0.032) and calmness (p = 0.044). Psychosocial questionnaires revealed a broad CTE-related psychosocial risk profile with dose-dependent increases in mental health risk-associated features (e.g., trait anxiety, maladaptive coping, loneliness, daily hassles; p values < 0.003) and a corresponding decrease in factors protective for mental health (e.g., life satisfaction, adaptive coping, optimism, social support; p values < 0.021). These results were not influenced by age, sex, socioeconomic status or education. CONCLUSIONS: Healthy community-based adults with mild to moderate CTE exhibit dose-dependent changes in well-being manifesting in decreases in affective valence, calmness and energy in real life settings, as well as a range of established psychosocial risk features associated with mental health risk. This indicates an approach to early detection, early intervention, and prevention of CTE-associated psychiatric disorders in this at-risk population, using ecological momentary interventions (EMI) in real life, which enhance established protective factors for mental health, such as green space exposure, or social support.

Connectome-wide Mega-analysis Reveals Robust Patterns of Atypical Functional Connectivity in Autism.

BACKGROUND: Neuroimaging studies of functional connectivity (FC) in autism have been hampered by small sample sizes and inconsistent findings with regard to whether connectivity is increased or decreased in individuals with autism, whether these alterations affect focal systems or reflect a brain-wide pattern, and whether these are age and/or sex dependent. METHODS: The study included resting-state functional magnetic resonance imaging and clinical data from the EU-AIMS LEAP (European Autism Interventions Longitudinal European Autism Project) and the ABIDE (Autism Brain Imaging Data Exchange) 1 and 2 initiatives of 1824 (796 with autism) participants with an age range of 5-58 years. Between-group differences in FC were assessed, and associations between FC and clinical symptom ratings were investigated through canonical correlation analysis. RESULTS: Autism was associated with a brainwide pattern of hypo- and hyperconnectivity. Hypoconnectivity predominantly affected sensory and higher-order attentional networks and correlated with social impairments, restrictive and repetitive behavior, and sensory processing. Hyperconnectivity was observed primarily between the default mode network and the rest of the brain and between cortical and subcortical systems. This pattern was strongly associated with social impairments and sensory processing. Interactions between diagnosis and age or sex were not statistically significant. CONCLUSIONS: The FC alterations observed, which primarily involve hypoconnectivity of primary sensory and attention networks and hyperconnectivity of the default mode network and subcortex with the rest of the brain, do not appear to be age or sex dependent and correlate with clinical dimensions of social difficulties, restrictive and repetitive behaviors, and alterations in sensory processing. These findings suggest that the observed connectivity alterations are stable, trait-like features of autism that are related to the main symptom domains of the condition.

Investigating the neural correlates of affective mentalizing and their association with general intelligence in patients with schizophrenia.

BACKGROUND AND HYPOTHESIS: Mentalizing impairment in schizophrenia has been linked to altered neural responses. This study aimed to replicate previous findings of altered activation of the mentalizing network in schizophrenia and investigate its possible association with impaired domain-general cognition. STUDY DESIGN: We analyzed imaging data from two large multi-centric German studies including 64 patients, 64 matched controls and a separate cohort of 300 healthy subjects, as well as an independent Australian study including 46 patients and 61 controls. All subjects underwent functional magnetic resonance imaging while performing the same affective mentalizing task and completed a cognitive assessment battery. Group differences in activation of the mentalizing network were assessed by classical as well as Bayesian two-sample t-tests. Multiple regression analysis was performed to investigate effects of neurocognitive measures on activation of the mentalizing network. STUDY RESULTS: We found no significant group differences in activation of the mentalizing network. Bayes factors indicate that these results provide genuine evidence for the null hypothesis. We found a positive association between verbal intelligence and activation of the medial prefrontal cortex, a key region of the mentalizing network, in three independent samples. Finally, individuals with low verbal intelligence showed altered activation in areas previously implicated in mentalizing dysfunction in schizophrenia. CONCLUSIONS: Mentalizing activation in patients with schizophrenia might not differ compared to large well-matched groups of healthy controls. Verbal intelligence is an important confounding variable in group comparisons, which should be considered in future studies of the neural correlates of mentalizing dysfunction in schizophrenia.

Excitatory/inhibitory imbalance in autism: the role of glutamate and GABA gene-sets in symptoms and cortical brain structure.

The excitatory/inhibitory (E/I) imbalance hypothesis posits that imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism. However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood. We used innovative analysis methods-combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT) to investigate relationships between genetic variance, brain structure and autism symptomatology of participants from the AIMS-2-TRIALS LEAP cohort (autism = 359, male/female = 258/101; neurotypical control participants = 279, male/female = 178/101) aged 6-30 years. Using competitive gene-set analyses, we investigated whether aggregated genetic variation in glutamate and GABA gene-sets could be associated with behavioral measures of autism symptoms and brain structural variation. Further, using the same gene-sets, we corelated expression profiles throughout the cortex with differences in CT between autistic and neurotypical control participants, as well as in separate sensory subgroups. The glutamate gene-set was associated with all autism symptom severity scores on the Autism Diagnostic Observation Schedule-2 (ADOS-2) and the Autism Diagnostic Interview-Revised (ADI-R) within the autistic group. In adolescents and adults, brain regions with greater gene-expression of glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants although in opposing directions. Additionally, the gene expression profiles were associated with CT profiles in separate sensory subgroups. Our results suggest complex relationships between E/I related genetics and autism symptom profiles as well as brain structure alterations, where there may be differential roles for glutamate and GABA.

Processing of social and monetary rewards in autism spectrum disorders.

BACKGROUND: Reward processing has been proposed to underpin the atypical social feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social reward processing in ASD. AIMS: Utilising a large sample, we aimed to assess reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD. METHOD: Functional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6-30.6 years of age) and 181 typically developing participants (7.6-30.8 years of age). RESULTS: Across social and monetary reward anticipation, whole-brain analyses showed hypoactivation of the right ventral striatum in participants with ASD compared with typically developing participants. Further, region of interest analysis across both reward types yielded ASD-related hypoactivation in both the left and right ventral striatum. Across delivery of social and monetary reward, hyperactivation of the ventral striatum in individuals with ASD did not survive correction for multiple comparisons. Dimensional analyses of autism and attention-deficit hyperactivity disorder (ADHD) scores were not significant. In categorical analyses, post hoc comparisons showed that ASD effects were most pronounced in participants with ASD without co-occurring ADHD. CONCLUSIONS: Our results do not support current theories linking atypical social interaction in ASD to specific alterations in social reward processing. Instead, they point towards a generalised hypoactivity of ventral striatum in ASD during anticipation of both social and monetary rewards. We suggest this indicates attenuated reward seeking in ASD independent of social content and that elevated ADHD symptoms may attenuate altered reward seeking in ASD.

The Link Between Autism and Sex-Related Neuroanatomy, and Associated Cognition and Gene Expression.

OBJECTIVE: The male preponderance in prevalence of autism is among the most pronounced sex ratios across neurodevelopmental conditions. The authors sought to elucidate the relationship between autism and typical sex-differential neuroanatomy, cognition, and related gene expression. METHODS: Using a novel deep learning framework trained to predict biological sex based on T1-weighted structural brain images, the authors compared sex prediction model performance across neurotypical and autistic males and females. Multiple large-scale data sets comprising T1-weighted MRI data were employed at four stages of the analysis pipeline: 1) pretraining, with the UK Biobank sample (>10,000 individuals); 2) transfer learning and validation, with the ABIDE data sets (1,412 individuals, 5-56 years of age); 3) test and discovery, with the EU-AIMS/AIMS-2-TRIALS LEAP data set (681 individuals, 6-30 years of age); and 4) specificity, with the NeuroIMAGE and ADHD200 data sets (887 individuals, 7-26 years of age). RESULTS: Across both ABIDE and LEAP, features positively predictive of neurotypical males were on average significantly more predictive of autistic males (ABIDE: Cohen's d=0.48; LEAP: Cohen's d=1.34). Features positively predictive of neurotypical females were on average significantly less predictive of autistic females (ABIDE: Cohen's d=1.25; LEAP: Cohen's d=1.29). These differences in sex prediction accuracy in autism were not observed in individuals with ADHD. In autistic females, the male-shifted neurophenotype was further associated with poorer social sensitivity and emotional face processing while also associated with gene expression patterns of midgestational cell types. CONCLUSIONS: The results demonstrate an increased resemblance in both autistic male and female individuals' neuroanatomy with male-characteristic patterns associated with typically sex-differential social cognitive features and related gene expression patterns. The findings hold promise for future research aimed at refining the quest for biological mechanisms underpinning the etiology of autism.

Lack of amygdala habituation to negative emotional faces in alcohol use disorder and the relation to adverse childhood experiences.

Aberrant limbic circuit reactivity to negative stimuli might be related to alterations in emotion processing and regulation in alcohol use disorder (AUD). The current study tested for the first time in AUD the hypothesis of aberrant amygdala habituation to repeated aversive stimuli-a robust and reliable neuroimaging marker for emotion processing. We explored the link between deficits in habituation to adverse childhood experience (ACE), a common risk factor for impaired emotion regulation and AUD. AUD individuals (N = 36) and healthy controls (HC; N = 26) participated in an observational case-control functional magnetic resonance imaging (fMRI) study. An established habituation index was used to investigate processing of aversive emotional faces of the amygdala. AUD individuals showed an overall deficit in amygdala habituation (right: t = 4.26, pFWE = 0.004; left: t = 4.79, pFWE ≤ 0.001). Amygdala habituation was significantly related to increased exposure to ACE in HC (t = 3.88, pFWE = 0.012), whereas this association was not observed in AUD individuals (T = 1.80, pFWE = 0.662). Further, a significant association between higher alcohol consumption and reduced amygdala habituation (right: R2  = -0.356, F = 8.736, p = 0.004; left: R2  = -0.309, F = 6.332, p = 0.015) was observed. We found novel evidence for neural alterations in emotion processing in AUD individuals, indexed by deficient amygdala habituation to negative emotional content. We replicated a prior report on a link between ACE and amygdala habituation, a well-established environmental risk factor for mental disorders and emotion dysregulation, in our control sample. Additionally, deficient amygdala habituation related to the amount of alcohol consumption in the overall sample might indicate a short-term substance effect.

Autism Is Associated With Interindividual Variations of Gray and White Matter Morphology.

BACKGROUND: Although many studies have explored atypicalities in gray matter (GM) and white matter (WM) morphology of autism, most of them relied on unimodal analyses that did not benefit from the likelihood that different imaging modalities may reflect common neurobiology. We aimed to establish brain patterns of modalities that differentiate between individuals with and without autism and explore associations between these brain patterns and clinical measures in the autism group. METHODS: We studied 183 individuals with autism and 157 nonautistic individuals (age range, 6-30 years) in a large, deeply phenotyped autism dataset (EU-AIMS LEAP [European Autism Interventions-A Multicentre Study for Developing New Medications Longitudinal European Autism Project]). Linked independent component analysis was used to link all participants' GM volume and WM diffusion tensor images, and group comparisons of modality shared variances were examined. Subsequently, we performed univariate and multivariate brain-behavior correlation analyses to separately explore the relationships between brain patterns and clinical profiles. RESULTS: One multimodal pattern was significantly related to autism. This pattern was primarily associated with GM volume in bilateral insula and frontal, precentral and postcentral, cingulate, and caudate areas and co-occurred with altered WM features in the superior longitudinal fasciculus. The brain-behavior correlation analyses showed a significant multivariate association primarily between brain patterns that involved variation of WM and symptoms of restricted and repetitive behavior in the autism group. CONCLUSIONS: Our findings demonstrate the assets of integrated analyses of GM and WM alterations to study the brain mechanisms that underpin autism and show that the complex clinical autism phenotype can be interpreted by brain covariation patterns that are spread across the brain involving both cortical and subcortical areas.

Reduced Real-life Affective Well-being and Amygdala Habituation in Unmedicated Community Individuals at Risk for Depression and Anxiety.

BACKGROUND: Early identification of risk for depression and anxiety disorders is important for prevention, but real-life affective well-being and its biological underpinnings in the population remain understudied. Here, we combined methods from epidemiology, psychology, ecological momentary assessment, and functional magnetic resonance imaging to study real-life and neural affective functions in individuals with subclinical anxiety and depression from a population-based cohort of young adults. METHODS: We examined psychological measures, real-life affective valence, functional magnetic resonance imaging amygdala habituation to negative affective stimuli, and the relevance of neural readouts for daily-life affective function in 132 non-help-seeking community individuals. We compared psychological and ecological momentary assessment measures of 61 unmedicated individuals at clinical risk for depression and anxiety (operationalized as subthreshold depression and anxiety symptoms or a former mood or anxiety disorder) with those of 48 nonrisk individuals and 23 persons with a mood or anxiety disorder. We studied risk-associated functional magnetic resonance imaging signals in subsamples with balanced sociodemographic and image quality parameters (26 nonrisk, 26 at-risk persons). RESULTS: Compared with nonrisk persons, at-risk individuals showed significantly decreased real-life affective valence (p = .038), reduced amygdala habituation (familywise error-corrected p = .024, region of interest corrected), and an intermediate psychological risk profile. Amygdala habituation predicted real-life affective valence in control subjects but not in participants at risk (familywise error-corrected p = .005, region of interest corrected). CONCLUSIONS: Our data suggest real-life and neural markers for affective alterations in unmedicated community individuals at risk for depression and anxiety and highlight the significance of amygdala habituation measures for the momentary affective experience in real-world environments.

Facial expression recognition is linked to clinical and neurofunctional differences in autism.

BACKGROUND: Difficulties in social communication are a defining clinical feature of autism. However, the underlying neurobiological heterogeneity has impeded targeted therapies and requires new approaches to identifying clinically relevant bio-behavioural subgroups. In the largest autism cohort to date, we comprehensively examined difficulties in facial expression recognition, a key process in social communication, as a bio-behavioural stratification biomarker, and validated them against clinical features and neurofunctional responses. METHODS: Between 255 and 488 participants aged 6-30 years with autism, typical development and/or mild intellectual disability completed the Karolinska Directed Emotional Faces task, the Reading the Mind in the Eyes Task and/or the Films Expression Task. We first examined mean-group differences on each test. Then, we used a novel intersection approach that compares two centroid and connectivity-based clustering methods to derive subgroups based on the combined performance across the three tasks. Measures and subgroups were then related to clinical features and neurofunctional differences measured using fMRI during a fearful face-matching task. RESULTS: We found significant mean-group differences on each expression recognition test. However, cluster analyses showed that these were driven by a low-performing autistic subgroup (~ 30% of autistic individuals who performed below 2SDs of the neurotypical mean on at least one test), while a larger subgroup (~ 70%) performed within 1SD on at least 2 tests. The low-performing subgroup also had on average significantly more social communication difficulties and lower activation in the amygdala and fusiform gyrus than the high-performing subgroup. LIMITATIONS: Findings of autism expression recognition subgroups and their characteristics require independent replication. This is currently not possible, as there is no other existing dataset that includes all relevant measures. However, we demonstrated high internal robustness (91.6%) of findings between two clustering methods with fundamentally different assumptions, which is a critical pre-condition for independent replication. CONCLUSIONS: We identified a subgroup of autistic individuals with expression recognition difficulties and showed that this related to clinical and neurobiological characteristics. If replicated, expression recognition may serve as bio-behavioural stratification biomarker and aid in the development of targeted interventions for a subgroup of autistic individuals.

Cerebellar Atypicalities in Autism?

BACKGROUND: The cerebellum contains more than 50% of the brain's neurons and is involved in social cognition. Cerebellar anatomical atypicalities have repeatedly been reported in individuals with autism. However, studies have yielded inconsistent findings, likely because of a lack of statistical power, and did not capture the clinical and neuroanatomical diversity of autism. Our aim was to better understand cerebellar anatomy and its diversity in autism. METHODS: We studied cerebellar gray matter morphology in 274 individuals with autism and 219 control subjects of a multicenter European cohort, EU-AIMS LEAP (European Autism Interventions-A Multicentre Study for Developing New Medications; Longitudinal European Autism Project). To ensure the robustness of our results, we conducted lobular parcellation of the cerebellum with 2 different pipelines in addition to voxel-based morphometry. We performed statistical analyses with linear, multivariate (including normative modeling), and meta-analytic approaches to capture the diversity of cerebellar anatomy in individuals with autism and control subjects. Finally, we performed a dimensional analysis of cerebellar anatomy in an independent cohort of 352 individuals with autism-related symptoms. RESULTS: We did not find any significant difference in the cerebellum when comparing individuals with autism and control subjects using linear models. In addition, there were no significant deviations in our normative models in the cerebellum in individuals with autism. Finally, we found no evidence of cerebellar atypicalities related to age, IQ, sex, or social functioning in individuals with autism. CONCLUSIONS: Despite positive results published in the last decade from relatively small samples, our results suggest that there is no striking difference in cerebellar anatomy of individuals with autism.

Stratifying the autistic phenotype using electrophysiological indices of social perception.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties in social communication, but also great heterogeneity. To offer individualized medicine approaches, we need to better target interventions by stratifying autistic people into subgroups with different biological profiles and/or prognoses. We sought to validate neural responses to faces as a potential stratification factor in ASD by measuring neural (electroencephalography) responses to faces (critical in social interaction) in N = 436 children and adults with and without ASD. The speed of early-stage face processing (N170 latency) was on average slower in ASD than in age-matched controls. In addition, N170 latency was associated with responses to faces in the fusiform gyrus, measured with functional magnetic resonance imaging, and polygenic scores for ASD. Within the ASD group, N170 latency predicted change in adaptive socialization skills over an 18-month follow-up period; data-driven clustering identified a subgroup with slower brain responses and poor social prognosis. Use of a distributional data-driven cutoff was associated with predicted improvements of power in simulated clinical trials targeting social functioning. Together, the data provide converging evidence for the utility of the N170 as a stratification factor to identify biologically and prognostically defined subgroups in ASD.

In-depth characterization of neuroradiological findings in a large sample of individuals with autism spectrum disorder and controls.

BACKGROUND: Autism spectrum disorder (ASD) is a group of neurodevelopmental conditions associated with quantitative differences in cortical and subcortical brain morphometry. Qualitative assessment of brain morphology provides complementary information on the possible underlying neurobiology. Studies of neuroradiological findings in ASD have rendered mixed results, and await robust replication in a sizable and independent sample. METHODS: We systematically and comprehensively assessed neuroradiological findings in a large cohort of participants with ASD and age-matched controls (total N = 620, 348 ASD and 272 controls), including 70 participants with intellectual disability (47 ASD, 23 controls). We developed a comprehensive scoring system, augmented by standardized biometric measures. RESULTS: There was a higher incidence of neuroradiological findings in individuals with ASD (89.4 %) compared to controls (83.8 %, p = .042). Certain findings were also more common in ASD, in particular opercular abnormalities (OR 1.9, 95 % CI 1.3-3.6) and mega cisterna magna (OR 2.4, 95 % CI 1.4-4.0) reached significance when using FDR, whereas increases in macrocephaly (OR 2.0, 95 % CI 1.2-3.2), cranial deformities (OR 2.4, 95 % CI: 1.0-5.8), calvarian / dural thickening (OR 1.5, 95 % CI 1.0-2.3), ventriculomegaly (OR 3.4, 95 % CI 1.3-9.2), and hypoplasia of the corpus callosum (OR 2.7, 95 % CI 1.1-6.3) did not survive this correction. Furthermore, neuroradiological findings were more likely to occur in isolation in controls, whereas they clustered more frequently in ASD. The incidence of neuroradiological findings was higher in individuals with mild intellectual disability (95.7 %), irrespective of ASD diagnosis. CONCLUSION: There was a subtly higher prevalence of neuroradiological findings in ASD, which did not appear to be specific to the condition. Individual findings or clusters of findings may point towards the neurodevelopmental mechanisms involved in individual cases. As such, clinical MRI assessments may be useful to guide further etiopathological (genetic) investigations, and are potentially valuable to fundamental ASD research.

Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis.

BACKGROUND: Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed. METHODS: We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2-32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants' MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%-30% split). RESULTS: In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52-0.62, specificity 0.59-0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset. LIMITATIONS: The statistical power to detect weak effects-of the magnitude of those found in the training dataset-in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset's effects. CONCLUSIONS: This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.

Interindividual Differences in Cortical Thickness and Their Genomic Underpinnings in Autism Spectrum Disorder.

OBJECTIVE: Autism spectrum disorder (ASD) is accompanied by highly individualized neuroanatomical deviations that potentially map onto distinct genotypes and clinical phenotypes. This study aimed to link differences in brain anatomy to specific biological pathways to pave the way toward targeted therapeutic interventions. METHODS: The authors examined neurodevelopmental differences in cortical thickness and their genomic underpinnings in a large and clinically diverse sample of 360 individuals with ASD and 279 typically developing control subjects (ages 6-30 years) within the EU-AIMS Longitudinal European Autism Project (LEAP). The authors also examined neurodevelopmental differences and their potential pathophysiological mechanisms between clinical ASD subgroups that differed in the severity and pattern of sensory features. RESULTS: In addition to significant between-group differences in "core" ASD brain regions (i.e., fronto-temporal and cingulate regions), individuals with ASD manifested as neuroanatomical outliers within the neurotypical cortical thickness range in a wider neural system, which was enriched for genes known to be implicated in ASD on the genetic and/or transcriptomic level. Within these regions, the individuals' total (i.e., accumulated) degree of neuroanatomical atypicality was significantly correlated with higher polygenic scores for ASD and other psychiatric conditions, and it scaled with measures of symptom severity. Differences in cortical thickness deviations were also associated with distinct sensory subgroups, especially in brain regions expressing genes involved in excitatory rather than inhibitory neurotransmission. CONCLUSIONS: The study findings corroborate the link between macroscopic differences in brain anatomy and the molecular mechanisms underpinning heterogeneity in ASD, and provide future targets for stratification and subtyping.

Ventral Striatal-Hippocampus Coupling During Reward Processing as a Stratification Biomarker for Psychotic Disorders.

BACKGROUND: Altered ventral striatal (vST) activation to reward expectancy is a well-established intermediate phenotype for psychiatric disorders, specifically schizophrenia (SZ). Preclinical research suggests that striatal alterations are related to a reduced inhibition by the hippocampal formation, but its role in human transdiagnostic reward-network dysfunctions is not well understood. METHODS: We performed functional magnetic resonance imaging during reward processing in 728 individuals including healthy control subjects (n = 396), patients (SZ: n = 46; bipolar disorder: n = 45; major depressive disorder: n = 60), and unaffected first-degree relatives (SZ: n = 46; bipolar disorder: n = 50; major depressive disorder: n = 85). We assessed disorder-specific differences in functional vST-hippocampus coupling and transdiagnostic associations with dimensional measures of positive, negative, and cognitive symptoms. We also probed the genetic underpinning using polygenic risk scores for SZ in a subset of healthy participants (n = 295). RESULTS: Functional vST-hippocampus coupling was 1) reduced in patients with SZ and bipolar disorder (pFWE < .05, small-volume corrected [SVC]); 2) associated transdiagnostically to dimensional measures of positive (pFWE = .01, SVC) and cognitive (pFWE = .02, SVC), but not negative, (pFWE > .05, SVC) symptoms; and 3) reduced in first-degree relatives of patients with SZ (pFWE = .017, SVC) and linked to the genetic risk for SZ in healthy participants (p = .035). CONCLUSIONS: We provide evidence that reduced vST-hippocampus coupling during reward processing is an endophenotype for SZ linked to positive and cognitive symptoms, supporting current preclinical models of the emergence of psychosis. Moreover, our data indicate that vST-hippocampus coupling is familial and linked to polygenic scores for SZ, supporting the use of this measure as an intermediate phenotype for psychotic disorders.

Brain structural correlates of upward social mobility in ethnic minority individuals.

PURPOSE: Perigenual anterior cingulate cortex (pACC) is a neural convergence site for social stress-related risk factors for mental health, including ethnic minority status. Current social status, a strong predictor of mental and somatic health, has been related to gray matter volume in this region, but the effects of social mobility over the lifespan are unknown and may differ in minorities. Recent studies suggest a diminished health return of upward social mobility for ethnic minority individuals, potentially due to sustained stress-associated experiences and subsequent activation of the neural stress response system. METHODS: To address this issue, we studied an ethnic minority sample with strong upward social mobility. In a cross-sectional design, we examined 64 young adult native German and 76 ethnic minority individuals with comparable sociodemographic attributes using whole-brain structural magnetic resonance imaging. RESULTS: Results showed a significant group-dependent interaction between perceived upward social mobility and pACC gray matter volume, with a significant negative association in the ethnic minority individuals. Post-hoc analysis showed a significant mediation of the relationship between perceived upward social mobility and pACC volume by perceived chronic stress, a variable that was significantly correlated with perceived discrimination in our ethnic minority group. CONCLUSION: Our findings extend prior work by pointing to a biological signature of the "allostatic costs" of socioeconomic attainment in socially disadvantaged upwardly mobile individuals in a key neural node implicated in the regulation of stress and negative affect.