Shared genetic etiology between ADHD, task-related behavioral measures and brain activation during response inhibition in a youth ADHD case-control study.

Impaired response inhibition is commonly present in individuals with attention-deficit/hyperactivity disorder (ADHD) and their unaffected relatives, suggesting impaired response inhibition as a candidate endophenotype in ADHD. Therefore, we explored whether behavioral and neural correlates of response inhibition are related to polygenic risk scores for ADHD (PRS-ADHD). We obtained functional magnetic resonance imaging of neural activity and behavioral measures during a stop-signal task in the NeuroIMAGE cohort, where inattention and hyperactivity-impulsivity symptoms were assessed with the Conners Parent Rating Scales. Our sample consisted of 178 ADHD cases, 103 unaffected siblings, and 173 controls (total N = 454; 8-29 years), for whom genome-wide genotyping was available. PRS-ADHD was constructed using the PRSice-2 software. We found PRS-ADHD to be associated with ADHD symptom severity, a slower and more variable response to Go-stimuli, and altered brain activation during response inhibition in several regions of the bilateral fronto-striatal network. Mean reaction time and intra-individual reaction time variability mediated the association of PRS-ADHD with ADHD symptoms (total, inattention, hyperactivity-impulsivity), and activity in the left temporal pole and anterior parahippocampal gyrus during failed inhibition mediated the relationship of PRS-ADHD with hyperactivity-impulsivity. Our findings indicate that PRS-ADHD are related to ADHD severity on a spectrum of clinical, sub-threshold, and normal levels; more importantly, we show a shared genetic etiology of ADHD and behavioral and neural correlates of response inhibition. Given the modest sample size of our study, future studies with higher power are warranted to explore mediation effects, suggesting that genetic liability to ADHD may adversely affect attention regulation on the behavioral level and point to a possible response inhibition-related mechanistic pathway from PRS-ADHD to hyperactivity-impulsivity.

Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium.

Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium's ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

Mapping brain asymmetry in health and disease through the ENIGMA consortium.

Left-right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables such as age and sex. Over the last 4 years, the ENIGMA-Laterality Working Group has published six studies of gray matter morphological asymmetry based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. A population-level mapping of average asymmetry was achieved, including an intriguing fronto-occipital gradient of cortical thickness asymmetry in healthy brains. ENIGMA's multi-dataset approach also supported an empirical illustration of reproducibility of hemispheric differences across datasets. Effect sizes were estimated for gray matter asymmetry based on large, international, samples in relation to age, sex, handedness, and brain volume, as well as for three psychiatric disorders: autism spectrum disorder was associated with subtly reduced asymmetry of cortical thickness at regions spread widely over the cortex; pediatric obsessive-compulsive disorder was associated with altered subcortical asymmetry; major depressive disorder was not significantly associated with changes of asymmetry. Ongoing studies are examining brain asymmetry in other disorders. Moreover, a groundwork has been laid for possibly identifying shared genetic contributions to brain asymmetry and disorders.

An overview of the first 5 years of the ENIGMA obsessive-compulsive disorder working group: The power of worldwide collaboration.

Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive-compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi-site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA-OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA.

Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure.

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.

Low-grade inflammation as mediator between diet and behavioral disinhibition: A UK Biobank study.

BACKGROUND: Dietary patterns have been associated with variations in behavior. However, evidence has been limited and mixed, and the underlying mechanism remains unclear. OBJECTIVE: Extend a previous study reporting significant associations between food patterns and behavioral disinhibition and explore whether low-grade inflammation is linked to behaviors and mediates the association between diet and behavioral disinhibition. DESIGN: Among participants of the UK Biobank (UKB) we extracted a single behavioral disinhibition principal component using the UKB touchscreen questionnaire, Mental Health Questionnaire (MHQ), and registered diagnoses. We identified four dietary patterns (prudent diet, elimination of wheat/dairy/eggs, meat-based diet, full-cream dairy consumption) by using the Food Frequency Questionnaire (FFQ). Immune biomarkers and an aggregated inflammation score (INFLA-score) were used to characterize low-grade inflammation. Associations between dietary patterns and immune biomarkers, between immune biomarkers and disinhibition were assessed, with adjustment for demographics, lifestyle factors, and somatic health conditions. Next, mediation analyses were run to examine whether the association between dietary patterns and disinhibition was partially explained by inflammatory levels. We also conducted subgroup analyses to explore whether associations and the mediation effect differed by sex, age, ethnicity/race, body-mass-index (BMI), and socioeconomic status (SES). RESULTS: The prudent diet was negatively, and the meat-based diet was positively associated with several pro-inflammatory biomarkers. Most immune biomarkers were positively associated with disinhibition (numbers of lymphocytes (ßstandardized = 0.082, p < 0.001), monocytes (ßstandardized = 0.043, p < 0.001), neutrophils (ßstandardized = 0.071, p < 0.001), platelets (ßstandardized = 0.022, p < 0.001), leukocytes (ßstandardized = 0.093, p < 0.001), C-reactive protein (ßstandardized = 0.051, p < 0.001), and for INFLA-score (ßstandardized = 0.074, p < 0.001). In the mediation model, the INFLA-score mediated the association between prudent diet and meat-based diet and disinhibition score, with a significant indirect effect of low-grade inflammation for the prudent diet-disinhibition association (ßstandardized = -0.007, p < 0.001) and for meat-disinhibition association (ßstandardized = 0.001, p < 0.001)). Although all effects were small, covariates and interaction term adjustments did not attenuate the effects, and neither did most subgroup-only analyses. CONCLUSIONS: The prudent diet was associated with a lower disinhibition score and this effect was partially mediated by the lower inflammation. Reversely, the meat-based diet was linked to more inflammation, which was associated with more disinhibition. Our findings suggest mediating effects of immune function in the relationship between diet and behavioral disinhibition. However further alternative designs such as interventional trials are needed to establish causal effects.

Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders.

Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

Effects of substance misuse on inhibitory control in patients with attention-deficit/hyperactivity disorder.

Patients with attention-deficit/hyperactivity disorder (ADHD) are often diagnosed with comorbid substance misuse (SM), which is associated with poor treatment efficacy. Although literature indicates similar inhibitory control deficits in both conditions, it is unclear whether SM in ADHD exaggerates pre-existing deficits, with additive or distinct impairments in patients. Our aim was to examine SM effects on inhibitory control in ADHD. Behavioural and functional magnetic resonance imaging (fMRI) data from a stop-signal task were compared across ADHD patients with and without SM (ADHD + SM and ADHD-only, respectively) and controls (n = 33/group; 79 males, mean age 18.02 ± 2.45). To limit substance use disorder (SUD) trait effects, groups were matched for parental SUD. Overall, we found worse performance for ADHD-only and/or ADHD + SM compared with controls but no difference between the ADHD groups. Moreover, the ADHD groups showed decreased frontostriatal and frontoparietal activity during successful and failed stop trials. There were no differences between the ADHD groups in superior frontal nodes, but there was more decreased activation in temporal/parietal nodes in ADHD-only compared with ADHD + SM. During go-trials, ADHD + SM showed decreased activation in inferior frontal nodes compared with ADHD-only and controls. Findings during response inhibition showed deficits in inhibition and attentional processes for ADHD patients with and without SM. Despite no evidence for SM effects during response inhibition, results during go-trials suggest distinct effects on nodes that are associated with several executive functions. Future studies should investigate whether distinct deficits in ADHD + SM relate to poor treatment results and can direct development of distinct ADHD treatment strategies for these patients.

Effects of family history of substance use disorder on reward processing in adolescents with and without attention-deficit/hyperactivity disorder.

Patients with attention-deficit/hyperactivity disorder (ADHD) often develop early onset substance use disorder (SUD) and show poor treatment outcomes. Both disorders show similar reward-processing alterations, but it is unclear whether these are associated with familial vulnerability to SUD. Our aim was to investigate effects of family history of SUD (FH) on reward processing in individuals with and without ADHD, without substance misuse. Behavioural and functional magnetic resonance imaging (fMRI) data from a modified monetary incentive delay task were compared between participants with and without FH (FH positive [FH+]: n = 76 and FH negative [FH-]: n = 69; 76 with ADHD, aged 16.74 ± 3.14, 82 males), while accounting for continuous ADHD scores. The main analysis showed distinct positive association between ADHD scores and reaction times during neutral versus reward condition. ADHD scores were also positively associated with anticipatory responses of dorsolateral prefrontal cortex, independent of FH. There were no main FH effects on brain activation. Yet, FH+ participants showed distinct neural alterations in ventrolateral prefrontal cortex (VLPFC), dependent on ADHD. This was driven by positive association between ADHD scores and VLPFC activation during reward outcome, only in FH+. Sensitivity analysis with stricter SUD index showed hyperactivation of anterior cingulate cortex for FH+, independent of ADHD, during reward anticipation. There were no FH or ADHD effects on activation of ventral striatum in any analysis. Findings suggest both FH and ADHD effects in circuits of reward and attention/memory during reward processing. Future studies should examine whether these relate to early substance use initiation in ADHD and explore the need for adjusted SUD prevention strategies.

Amygdala reactivity and ventromedial prefrontal cortex coupling in the processing of emotional face stimuli in attention-deficit/hyperactivity disorder.

Impaired emotion recognition is common in individuals with attention-deficit/hyperactivity disorder (ADHD) and may, via deficient emotion self-regulation, relate to the frequently co-occurring affective and social problems. The present study used an emotional face-matching task and functional magnetic resonance imaging (fMRI) to investigate neural responses during the processing of angry and fearful faces and visuo-spatial control stimuli. Additionally, measures for emotion dysregulation, ADHD type, and age were investigated in relation to the behavioral and neural fMRI data. We utilized a sample of 61 adolescents/young adults with ADHD and 51 age-matched healthy controls (age range: 12-28 years). Participants with ADHD had higher emotion dysregulation scores than controls. They also reacted slower and less accurate in response to emotional but not visuo-spatial control stimuli. Neural response differences between emotional and visuo-spatial trials were significantly smaller in cases, particularly in the left amygdala. While coupling between the right amygdala and bilateral ventromedial prefrontal cortex was stronger for emotional than visuo-spatial stimuli in control subjects, levels of positive coupling between the trial types did not significantly differ in participants with ADHD. Neither emotion dysregulation scores, nor ADHD type or age were related to the behavioral and neural processing alterations during the emotional face-matching task. Results indicate that emotion recognition deficits in ADHD are particularly associated with lower amygdala activation to emotional stimuli and alterations in the functional connections of the amygdala to medial prefrontal areas. Emotion recognition deficits and associated neural alterations were unrelated to emotion dysregulation, ADHD type, or age.

Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. Neuroanatomic heterogeneity limits our understanding of ADHD's etiology. This study aimed to parse heterogeneity of ADHD and to determine whether patient subgroups could be discerned based on subcortical brain volumes. METHODS: Using the large ENIGMA-ADHD Working Group dataset, four subsamples of 993 boys with and without ADHD and to subsamples of 653 adult men, 400 girls, and 447 women were included in analyses. We applied exploratory factor analysis (EFA) to seven subcortical volumes in order to constrain the complexity of the input variables and ensure more stable clustering results. Factor scores derived from the EFA were used to build networks. A community detection (CD) algorithm clustered participants into subgroups based on the networks. RESULTS: Exploratory factor analysis revealed three factors (basal ganglia, limbic system, and thalamus) in boys and men with and without ADHD. Factor structures for girls and women differed from those in males. Given sample size considerations, we concentrated subsequent analyses on males. Male participants could be separated into four communities, of which one was absent in healthy men. Significant case-control differences of subcortical volumes were observed within communities in boys, often with stronger effect sizes compared to the entire sample. As in the entire sample, none were observed in men. Affected men in two of the communities presented comorbidities more frequently than those in other communities. There were no significant differences in ADHD symptom severity, IQ, and medication use between communities in either boys or men. CONCLUSIONS: Our results indicate that neuroanatomic heterogeneity in subcortical volumes exists, irrespective of ADHD diagnosis. Effect sizes of case-control differences appear more pronounced at least in some of the subgroups.

Effects of Substance Misuse and Family History of Substance Use Disorder on Delay Discounting in Adolescents and Young Adults with Attention-Deficit/Hyperactivity Disorder.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) and substance use disorder (SUD) often co-occur. Both disorders are characterized by impulsive choice. However, little is known about the effects of substance misuse (SM) and family history of SUD (FH) on impulsive choice in ADHD-SUD comorbidity. Impulsive choice is also linked to callous-unemotional (CU) traits, which are suggested to play a role in ADHD-SUD comorbidity. Our aim was to examine the effects of (1) FH and (2) SM on impulsive choice, while exploring the role of CU traits. METHODS: Impulsive choice was assessed with the delay discounting (DD) task. We compared task performance across (1) ADHD patients and controls with or without FH of SUD (ADHD FH+: n = 86; ADHD FH-: n = 63; control FH+: n = 49; control FH-: n = 72; mean age of the whole sample [n = 270]: 16.39, SD: 3.43) and (2) family history-matched ADHD groups with and without SM and controls (ADHD + SM: n = 62; ADHD-only: n = 62; controls: n = 62; mean age of the whole sample [n = 186]: 18.01, SD: 2.71). Effects of CU traits were explored by adding this as a covariate in all analyses. RESULTS: (1) There was no main effect of FH on DD. (2) We found increased DD in ADHD + SM compared to ADHD-only and no difference between ADHD-only and controls. Finally, increased DD was associated with increased callous traits only in ADHD FH+ and control FH+. CONCLUSIONS: In adolescents and young adults with ADHD, high impulsive choice might only be present in those with comorbid SM and in an FH+ subgroup with high callous traits. This suggests that impulsive choice in ADHD might result from (1) effects of SM and (2) a combined effect of SUD vulnerability and high callousness. Future studies should investigate efficacy of early interventions, targeting CU traits.

Frontostriatal functional connectivity correlates with repetitive behaviour across autism spectrum disorder and obsessive-compulsive disorder.

BACKGROUND: Autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD) are neurodevelopmental disorders with considerable overlap in terms of their defining symptoms of compulsivity/repetitive behaviour. Little is known about the extent to which ASD and OCD have common versus distinct neural correlates of compulsivity. Previous research points to potentially common dysfunction in frontostriatal connectivity, but direct comparisons in one study are lacking. Here, we assessed frontostriatal resting-state functional connectivity in youth with ASD or OCD, and healthy controls. In addition, we applied a cross-disorder approach to examine whether repetitive behaviour across ASD and OCD has common neural substrates. METHODS: A sample of 78 children and adolescents aged 8-16 years was used (ASD n = 24; OCD n = 25; healthy controls n = 29), originating from the multicentre study COMPULS. We tested whether diagnostic group, repetitive behaviour (measured with the Repetitive Behavior Scale-Revised) or their interaction was associated with resting-state functional connectivity of striatal seed regions. RESULTS: No diagnosis-specific differences were detected. The cross-disorder analysis, on the other hand, showed that increased functional connectivity between the left nucleus accumbens (NAcc) and a cluster in the right premotor cortex/middle frontal gyrus was related to more severe symptoms of repetitive behaviour. CONCLUSIONS: We demonstrate the fruitfulness of applying a cross-disorder approach to investigate the neural underpinnings of compulsivity/repetitive behaviour, by revealing a shared alteration in functional connectivity in ASD and OCD. We argue that this alteration might reflect aberrant reward or motivational processing of the NAcc with excessive connectivity to the premotor cortex implementing learned action patterns.

Putamen functional connectivity during inhibitory control in smokers and non-smokers.

The putamen has been shown to play a key role in inhibitory control and addiction, and consists of distinct subregions associated with distinct functions. The anterior putamen is thought to be specialized in goal-directed control or response-monitoring in connection with frontal regions, whereas the posterior part is specialized in habitual or automatic responding in connection with sensorimotor regions. The present study is the first to delineate functional networks of the anterior and posterior putamen in a Go-NoGo response inhibition task, and to examine differences between smokers (n = 25) and non-smokers (n = 23) within these networks. Functional connectivity analyses were conducted on fMRI data from a Go-NoGo study, using the generalized form of psychophysiological interaction with anterior and posterior putamen seed regions. In the context of inhibition, the anterior putamen exhibited connectivity with the anterior cingulate cortex (ACC) and precuneus (pFWE < .05), which was in line with previous literature. Conversely, the posterior putamen showed connectivity with regions implicated in sensorimotor processing. When we compared smokers to non-smokers, we did not observe the expected weaker connectivity between the anterior putamen and ACC during inhibition in smokers. Instead, our study revealed stronger inhibition-related connectivity between the anterior putamen and right insula in smokers. This finding highlights the involvement of putamen - insula interactions in addiction and impulse control.

Effects of dopaminergic genes, prenatal adversities, and their interaction on attention-deficit/hyperactivity disorder and neural correlates of response inhibition.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is often accompanied by impaired response inhibition; both have been associated with aberrant dopamine signalling. Given that prenatal exposure to alcohol or smoking is known to affect dopamine-rich brain regions, we hypothesized that individuals carrying the ADHD risk alleles of the dopamine receptor D4 (DRD4) and dopamine transporter (DAT1) genes may be especially sensitive to their effects. METHODS: Functional MRI data, information on prenatal adversities and genetic data were available for 239 adolescents and young adults participating in the multicentre ADHD cohort study NeuroIMAGE (average age 17.3 yr). We analyzed the effects of DRD4 and DAT1, prenatal exposure to alcohol and smoking and their interactions on ADHD severity, response inhibition and neural activity. RESULTS: We found no significant gene × environment interaction effects. We did find that the DRD4 7-repeat allele was associated with less superior frontal and parietal brain activity and with greater activity in the frontal pole and occipital cortex. Prenatal exposure to smoking was also associated with lower superior frontal activity, but with greater activity in the parietal lobe. Further, those exposed to alcohol had more activity in the lateral orbitofrontal cortex, and the DAT1 risk variant was associated with lower cerebellar activity. LIMITATIONS: Retrospective reports of maternal substance use and the cross-sectional study design restrict causal inference. CONCLUSION: While we found no evidence of gene × environment interactions, the risk factors under investigation influenced activity of brain regions associated with response inhibition, suggesting they may add to problems with inhibiting behaviour.

ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data.

Head motion during functional MRI (fMRI) scanning can induce spurious findings and/or harm detection of true effects. Solutions have been proposed, including deleting ('scrubbing') or regressing out ('spike regression') motion volumes from fMRI time-series. These strategies remove motion-induced signal variations at the cost of destroying the autocorrelation structure of the fMRI time-series and reducing temporal degrees of freedom. ICA-based fMRI denoising strategies overcome these drawbacks but typically require re-training of a classifier, needing manual labeling of derived components (e.g. ICA-FIX; Salimi-Khorshidi et al. (2014)). Here, we propose an ICA-based strategy for Automatic Removal of Motion Artifacts (ICA-AROMA) that uses a small (n=4), but robust set of theoretically motivated temporal and spatial features. Our strategy does not require classifier re-training, retains the data's autocorrelation structure and largely preserves temporal degrees of freedom. We describe ICA-AROMA, its implementation, and initial validation. ICA-AROMA identified motion components with high accuracy and robustness as illustrated by leave-N-out cross-validation. We additionally validated ICA-AROMA in resting-state (100 participants) and task-based fMRI data (118 participants). Our approach removed (motion-related) spurious noise from both rfMRI and task-based fMRI data to larger extent than regression using 24 motion parameters or spike regression. Furthermore, ICA-AROMA increased sensitivity to group-level activation. Our results show that ICA-AROMA effectively reduces motion-induced signal variations in fMRI data, is applicable across datasets without requiring classifier re-training, and preserves the temporal characteristics of the fMRI data.

Gray matter covariations in autism: out-of-sample replication using the ENIGMA autism cohort.

BACKGROUND: Autism spectrum disorder (henceforth autism) is a complex neurodevelopmental condition associated with differences in gray matter (GM) volume covariations, as reported in our previous study of the Longitudinal European Autism Project (LEAP) data. To make progress on the identification of potential neural markers and to validate the robustness of our previous findings, we aimed to replicate our results using data from the Enhancing Neuroimaging Genetics Through Meta-Analysis (ENIGMA) autism working group. METHODS: We studied 781 autistic and 927 non-autistic individuals (6-30 years, IQ ≥ 50), across 37 sites. Voxel-based morphometry was used to quantify GM volume as before. Subsequently, we used spatial maps of the two autism-related independent components (ICs) previously identified in the LEAP sample as templates for regression analyses to separately estimate the ENIGMA-participant loadings to each of these two ICs. Between-group differences in participants' loadings on each component were examined, and we additionally investigated the relation between participant loadings and autistic behaviors within the autism group. RESULTS: The two components of interest, previously identified in the LEAP dataset, showed significant between-group differences upon regressions into the ENIGMA cohort. The associated brain patterns were consistent with those found in the initial identification study. The first IC was primarily associated with increased volumes of bilateral insula, inferior frontal gyrus, orbitofrontal cortex, and caudate in the autism group relative to the control group (ß = 0.129, p = 0.013). The second IC was related to increased volumes of the bilateral amygdala, hippocampus, and parahippocampal gyrus in the autism group relative to non-autistic individuals (ß = 0.116, p = 0.024). However, when accounting for the site-by-group interaction effect, no significant main effect of the group can be identified (p > 0.590). We did not find significant univariate association between the brain measures and behavior in autism (p > 0.085). LIMITATIONS: The distributions of age, IQ, and sex between LEAP and ENIGMA are statistically different from each other. Owing to limited access to the behavioral data of the autism group, we were unable to further our understanding of the neural basis of behavioral dimensions of the sample. CONCLUSIONS: The current study is unable to fully replicate the autism-related brain patterns from LEAP in the ENIGMA cohort. The diverse group effects across ENIGMA sites demonstrate the challenges of generalizing the average findings of the GM covariation patterns to a large-scale cohort integrated retrospectively from multiple studies. Further analyses need to be conducted to gain additional insights into the generalizability of these two GM covariation patterns.

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.

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.

Structural brain morphometry as classifier and predictor of ADHD and reward-related comorbidities.

Attention deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, and around two-thirds of affected children report persisting problems in adulthood. This negative trajectory is associated with high comorbidity with disorders like obesity, depression, or substance use disorder (SUD). Decreases in cortical volume and thickness have also been reported in depression, SUD, and obesity, but it is unclear whether structural brain alterations represent unique disorder-specific profiles. A transdiagnostic exploration of ADHD and typical comorbid disorders could help to understand whether specific morphometric brain changes are due to ADHD or, alternatively, to the comorbid disorders. In the current study, we studied the brain morphometry of 136 subjects with ADHD with and without comorbid depression, SUD, and obesity to test whether there are unique or common brain alterations. We employed a machine-learning-algorithm trained to classify subjects with ADHD in the large ENIGMA-ADHD dataset and used it to predict the diagnostic status of subjects with ADHD and/or comorbidities. The parcellation analysis demonstrated decreased cortical thickness in medial prefrontal areas that was associated with presence of any comorbidity. However, these results did not survive correction for multiple comparisons. Similarly, the machine learning analysis indicated that the predictive algorithm grouped most of our ADHD participants as belonging to the ADHD-group, but no systematic differences between comorbidity status came up. In sum, neither a classical comparison of segmented structural brain metrics nor an ML model based on the ADHD ENIGMA data differentiate between ADHD with and without comorbidities. As the ML model is based in part on adolescent brains, this might indicate that comorbid disorders and their brain changes are not captured by the ML model because it represents a different developmental brain trajectory.