Behavioural and functional evidence revealing the role of RBFOX1 variation in multiple psychiatric disorders and traits.

Common variation in the gene encoding the neuron-specific RNA splicing factor RNA Binding Fox-1 Homolog 1 (RBFOX1) has been identified as a risk factor for several psychiatric conditions, and rare genetic variants have been found causal for autism spectrum disorder (ASD). Here, we explored the genetic landscape of RBFOX1 more deeply, integrating evidence from existing and new human studies as well as studies in Rbfox1 knockout mice. Mining existing data from large-scale studies of human common genetic variants, we confirmed gene-based and genome-wide association of RBFOX1 with risk tolerance, major depressive disorder and schizophrenia. Data on six mental disorders revealed copy number losses and gains to be more frequent in ASD cases than in controls. Consistently, RBFOX1 expression appeared decreased in post-mortem frontal and temporal cortices of individuals with ASD and prefrontal cortex of individuals with schizophrenia. Brain-functional MRI studies demonstrated that carriers of a common RBFOX1 variant, rs6500744, displayed increased neural reactivity to emotional stimuli, reduced prefrontal processing during cognitive control, and enhanced fear expression after fear conditioning, going along with increased avoidance behaviour. Investigating Rbfox1 neuron-specific knockout mice allowed us to further specify the role of this gene in behaviour. The model was characterised by pronounced hyperactivity, stereotyped behaviour, impairments in fear acquisition and extinction, reduced social interest, and lack of aggression; it provides excellent construct and face validity as an animal model of ASD. In conclusion, convergent translational evidence shows that common variants in RBFOX1 are associated with a broad spectrum of psychiatric traits and disorders, while rare genetic variation seems to expose to early-onset neurodevelopmental psychiatric disorders with and without developmental delay like ASD, in particular. Studying the pleiotropic nature of RBFOX1 can profoundly enhance our understanding of mental disorder vulnerability.

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 network dynamics during working memory are modulated by dopamine and diminished in schizophrenia.

Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory performance entails brain-wide switching between activity states using a combination of functional magnetic resonance imaging in healthy controls and individuals with schizophrenia, pharmacological fMRI, genetic analyses and network control theory. The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expression and pharmacological modulation. Individuals with schizophrenia show altered network control properties, including a more diverse energy landscape and decreased stability of working memory representations. Our results demonstrate the relevance of dopamine signaling for the steering of whole-brain network dynamics during working memory and link these processes to schizophrenia pathophysiology.

Structural alterations in brainstem, basal ganglia and thalamus associated with parkinsonism in schizophrenia spectrum disorders.

The relative roles of brainstem, thalamus and striatum in parkinsonism in schizophrenia spectrum disorder (SSD) patients are largely unknown. To determine whether topographical alterations of the brainstem, thalamus and striatum contribute to parkinsonism in SSD patients, we conducted structural magnetic resonance imaging (MRI) of SSD patients with (SSD-P, n = 35) and without (SSD-nonP, n = 64) parkinsonism, as defined by a Simpson and Angus Scale (SAS) total score of ≥ 4 and < 4, respectively, in comparison with healthy controls (n = 20). FreeSurfer v6.0 was used for segmentation of four brainstem regions (medulla oblongata, pons, superior cerebellar peduncle and midbrain), caudate nucleus, putamen and thalamus. Patients with parkinsonism had significantly smaller medulla oblongata (p = 0.01, false discovery rate (FDR)-corrected) and putamen (p = 0.02, FDR-corrected) volumes when compared to patients without parkinsonism. Across the entire patient sample (n = 99), significant negative correlations were identified between (a) medulla oblongata volumes and both SAS total (p = 0.034) and glabella-salivation (p = 0.007) scores, and (b) thalamic volumes and both SAS total (p = 0.033) and glabella-salivation (p = 0.007) scores. These results indicate that brainstem and thalamic structures as well as basal ganglia-based motor circuits play a crucial role in the pathogenesis of parkinsonism in SSD.

White matter microstructure alterations in cortico-striatal networks are associated with parkinsonism in schizophrenia spectrum disorders.

The specific role of white matter (WM) microstructure in parkinsonism among patients with schizophrenia spectrum disorders (SSD) is largely unknown. To determine whether topographical alterations of WM microstructure contribute to parkinsonism in SSD patients, we examined healthy controls (HC, n=16) and SSD patients with and without parkinsonism, as defined by Simpson-Angus Scale total score of ≥4 (SSD-P, n=33) or <4 (SSD-nonP, n=62). We used whole brain tract-based spatial statistics (TBSS), tractometry (along tract statistics using TractSeg) and graph analytics (clustering coefficient (CCO), local betweenness centrality (BC)) to provide a framework of specific WM microstructural changes underlying parkinsonism in SSD. Using these methods, post hoc analyses showed (a) decreased fractional anisotrophy (FA), as measured via tractometry, in the corpus callosum, corticospinal tract and striato-fronto-orbital tract, and (b) increased CCO, as derived by graph analytics, in the left orbitofrontal cortex (OFC) and left superior frontal gyrus (SFG), in SSD-P patients when compared to SSD-nonP patients. Increased CCO in the left OFC and SFG was associated with SAS scores. These findings indicate the prominence of OFC alterations and aberrant connectivity with fronto-parietal regions and striatum in the pathogenesis of parkinsonism in SSD. This study further supports the notion of altered "bottom-up modulation" between basal ganglia and fronto-parietal regions in the pathobiology of parkinsonism, which may reflect an interaction between movement disorder intrinsic to SSD and antipsychotic drug-induced sensorimotor dysfunction.

Generative network models of altered structural brain connectivity in schizophrenia.

Alterations in the structural connectome of schizophrenia patients have been widely characterized, but the mechanisms remain largely unknown. Generative network models have recently been introduced as a tool to test the biological underpinnings of altered brain network formation. We evaluated different generative network models in healthy controls (n=152), schizophrenia patients (n=66), and their unaffected first-degree relatives (n=32), and we identified spatial and topological factors contributing to network formation. We further investigated how these factors relate to cognition and to polygenic risk for schizophrenia. Our data show that among the four tested classes of generative network models, structural brain networks were optimally accounted for by a two-factor model combining spatial constraints and topological neighborhood structure. The same wiring model explained brain network formation across study groups. However, relatives and schizophrenia patients exhibited significantly lower spatial constraints and lower topological facilitation compared to healthy controls. Further exploratory analyses point to potential associations of the model parameter reflecting spatial constraints with the polygenic risk for schizophrenia and cognitive performance. Our results identify spatial constraints and local topological structure as two interrelated mechanisms contributing to regular brain network formation as well as altered connectomes in schizophrenia and healthy individuals at familial risk for schizophrenia. On an exploratory level, our data further point to the potential relevance of spatial constraints for the genetic risk for schizophrenia and general cognitive functioning, thereby encouraging future studies in following up on these observations to gain further insights into the biological basis and behavioral relevance of model parameters.

Multiparametric mapping of white matter microstructure in catatonia.

Catatonia is characterized by motor, affective and behavioral abnormalities. To date, the specific role of white matter (WM) abnormalities in schizophrenia spectrum disorders (SSD) patients with catatonia is largely unknown. In this study, diffusion magnetic resonance imaging (dMRI) data were collected from 111 right-handed SSD patients and 28 healthy controls. Catatonic symptoms were examined on the Northoff Catatonia Rating Scale (NCRS). We used whole-brain tract-based spatial statistics (TBSS), tractometry (along tract statistics using TractSeg) and graph analytics (clustering coefficient-CCO, local betweenness centrality-BC) to provide a framework of specific WM microstructural abnormalities underlying catatonia in SSD. Following a categorical approach, post hoc analyses showed differences in fractional anisotrophy (FA) measured via tractometry in the corpus callosum, corticospinal tract and thalamo-premotor tract as well as increased CCO as derived by graph analytics of the right superior parietal cortex (SPC) and left caudate nucleus in catatonic patients (NCRS total score ≥ 3; n = 30) when compared to non-catatonic patients (NCRS total score = 0; n = 29). In catatonic patients according to DSM-IV-TR (n = 43), catatonic symptoms were associated with FA variations (tractometry) of the left corticospinal tract and CCO of the left orbitofrontal cortex, primary motor cortex, supplementary motor area and putamen. This study supports the notion that structural reorganization of WM bundles connecting orbitofrontal/parietal, thalamic and striatal regions contribute to catatonia in SSD patients.

Association of a Reproducible Epigenetic Risk Profile for Schizophrenia With Brain Methylation and Function.

Importance: Schizophrenia is a severe mental disorder in which epigenetic mechanisms may contribute to illness risk. Epigenetic profiles can be derived from blood cells, but to our knowledge, it is unknown whether these predict established brain alterations associated with schizophrenia. Objective: To identify an epigenetic signature (quantified as polymethylation score [PMS]) of schizophrenia using machine learning applied to genome-wide blood DNA-methylation data; evaluate whether differences in blood-derived PMS are mirrored in data from postmortem brain samples; test whether the PMS is associated with alterations of dorsolateral prefrontal cortex hippocampal (DLPFC-HC) connectivity during working memory in healthy controls (HC); explore the association between interactions between polygenic and epigenetic risk with DLPFC-HC connectivity; and test the specificity of the signature compared with other serious psychiatric disorders. Design, Setting, and Participants: In this case-control study conducted from 2008 to 2018 in sites in Germany, the United Kingdom, the United States, and Australia, blood DNA-methylation data from 2230 whole-blood samples from 6 independent cohorts comprising HC (1238 [55.5%]) and participants with schizophrenia (803 [36.0%]), bipolar disorder (39 [1.7%]), major depressive disorder 35 [1.6%]), and autism (27 [1.2%]), and first-degree relatives of all patient groups (88 [3.9%]) were analyzed. DNA-methylation data were further explored from 244 postmortem DLPFC samples from 136 HC and 108 patients with schizophrenia. Neuroimaging and genome-wide association data were available for 393 HC. The latter data was used to calculate a polygenic risk score (PRS) for schizophrenia. The data were analyzed in 2019. Main Outcomes and Measures: The accuracy of schizophrenia control classification based on machine learning using epigenetic data; association of schizophrenia PMS scores with DLPFC-HC connectivity; and association of the interaction between PRS and PMS with DLPFC-HC connectivity. Results: This study included 7488 participants (4395 men [58.7%]), of whom 3158 (2230 men [70.6%]) received a diagnosis of schizophrenia. The PMS signature was associated with schizophrenia across 3 independent data sets (area under the curve [AUC] from 0.69 to 0.78; P value from 0.049 to 1.24 × 10-7) and data from postmortem DLPFC samples (AUC = 0.63; P = 1.42 × 10-4), but not with major depressive disorder (AUC = 0.51; P = .16), autism (AUC = 0.53; P = .66), or bipolar disorder (AUC = 0.58; P = .21). Pathways contributing most to the classification included synaptic processes. Healthy controls with schizophrenia-like PMS showed significantly altered DLPFC-HC connectivity (validation methylation/magnetic resonance imaging, t < -3.81; P for familywise error, <.04; validation magnetic resonance imaging, t < -3.54; P for familywise error, <.02), mirroring the lack of functional decoupling in schizophrenia. There was no significant association of the interaction between PMS and PRS with DLPFC-HC connectivity (P > .19). Conclusions and Relevance: We identified a reproducible blood DNA-methylation signature specific for schizophrenia that was correlated with altered functional DLPFC-HC coupling during working memory and mapped to methylation differences found in DLPFC postmortem samples. This indicates a possible epigenetic contribution to a schizophrenia intermediate phenotype and suggests that PMS could be of interest to be studied in the context of multimodal biomarkers for disease stratification and treatment personalization.

Neural responses to social evaluative threat in the absence of negative investigator feedback and provoked performance failures.

Functional neuroimaging of social stress induction has considerably furthered our understanding of the neural risk architecture of stress-related mental disorders. However, broad application of existing neuroimaging stress paradigms is challenging, among others due to the relatively high intensity of the employed stressors, which limits applications in patients and longitudinal study designs. Here, we introduce a less intense neuroimaging stress paradigm in which subjects anticipate, prepare, and give speeches under simulated social evaluation without harsh investigator feedback or provoked performance failures (IMaging Paradigm for Evaluative Social Stress, IMPRESS). We show that IMPRESS significantly increases perceived arousal as well as adrenergic (heart rate, pupil diameter, and blood pressure) and hormonal (cortisol) responses. Amygdala and perigenual anterior cingulate cortex (pACC), two key regions of the emotion and stress regulatory circuitry, are significantly engaged by IMPRESS. We further report associations of amygdala and pACC responses with measures of adrenergic arousal (heart rate, pupil diameter) and social environmental risk factors (adverse childhood experiences, urban living). Our data indicate that IMPRESS induces benchmark psychological and endocrinological responses to social evaluative stress, taps into core neural circuits related to stress processing and mental health risk, and is promising for application in mental illness and in longitudinal study designs.

MAOA-VNTR genotype affects structural and functional connectivity in distributed brain networks.

Previous studies have linked the low expression variant of a variable number of tandem repeat polymorphism in the monoamine oxidase A gene (MAOA-L) to the risk for impulsivity and aggression, brain developmental abnormalities, altered cortico-limbic circuit function, and an exaggerated neural serotonergic tone. However, the neurobiological effects of this variant on human brain network architecture are incompletely understood. We studied healthy individuals and used multimodal neuroimaging (sample size range: 219-284 across modalities) and network-based statistics (NBS) to probe the specificity of MAOA-L-related connectomic alterations to cortical-limbic circuits and the emotion processing domain. We assessed the spatial distribution of affected links across several neuroimaging tasks and data modalities to identify potential alterations in network architecture. Our results revealed a distributed network of node links with a significantly increased connectivity in MAOA-L carriers compared to the carriers of the high expression (H) variant. The hyperconnectivity phenotype primarily consisted of between-lobe ("anisocoupled") network links and showed a pronounced involvement of frontal-temporal connections. Hyperconnectivity was observed across functional magnetic resonance imaging (fMRI) of implicit emotion processing (pFWE = .037), resting-state fMRI (pFWE = .022), and diffusion tensor imaging (pFWE = .044) data, while no effects were seen in fMRI data of another cognitive domain, that is, spatial working memory (pFWE = .540). These observations are in line with prior research on the MAOA-L variant and complement these existing data by novel insights into the specificity and spatial distribution of the neurogenetic effects. Our work highlights the value of multimodal network connectomic approaches for imaging genetics.

The 5-HTTLPR Polymorphism Affects Network-Based Functional Connectivity in the Visual-Limbic System in Healthy Adults.

The serotonin transporter-linked polymorphic region 5-HTTLPR is a key genetic regulator of 5-HTT expression in the human brain where the short allele S has been implicated in emotion dysregulation. However, the neural mechanism underlying the association between this variant and emotion processing is still unclear. Earlier studies suggested an effect of 5-HTTLPR on amygdala activation during emotional face processing. However, this association has been questioned in recent studies employing larger sample sizes and meta-analyses. Here, we examined a sample of 223 healthy subjects with a well-established fMRI emotional face processing task to (1) re-evaluate the association between 5-HTTLPR and amygdala activation, (2) explore potential network-based functional connectivity phenotypes for associations with 5-HTTLPR, and (3) probe the reliability, behavioral significance and potential structural confounds of the identified network phenotype. Our results revealed no significant effect of 5-HTTLPR on amygdala activation (P>0.79). However, the number of S alleles was significantly correlated with functional connectivity of a visual-limbic subnetwork (PFWE=0.03). The subnetwork cluster included brain regions that are pivotal to emotion regulation such as the hippocampus, orbitofrontal cortex, anterior cingulate gyrus, fusiform gyrus, and subcortex. Notably, individuals with lower subnetwork connectivity had significantly higher emotion suppression scores (P=0.01). Further, the connectivity metrics were test-retest reliable and independent from subnetwork gray matter volume and white matter anisotropy. Our data provide evidence for a functional network-based phenotype linking genetic variation in 5-HTTLPR to emotion regulation, and suggest that further critical evaluations of the association between 5-HTTLPR and amygdala activation are warranted.

Neuroimaging Intermediate Phenotypes of Executive Control Dysfunction in Schizophrenia.

Genetic risk for schizophrenia is associated with impairments in the initiation and performance of executive control of cognition and action. The nature of these impairments and of the neural dysfunction that underlies them has been extensively investigated using experimental psychology and neuroimaging methods. In this article, we review schizophrenia-associated functional connectivity and activation abnormalities found in subjects performing experimental tasks that engage different aspects of executive function, such as working memory, cognitive control, and response inhibition. We focus on heritable traits associated with schizophrenia risk (intermediate phenotypes or endophenotypes) that have been revealed using imaging genetics approaches. These data suggest that genetic risk for schizophrenia is associated with dysfunction in systems supporting the initiation and application of executive control in neural circuits involving the anterior cingulate and dorsolateral prefrontal cortex. This article discusses current findings and limitations and their potential relevance to symptoms and disease pathogenesis.

Cognitive heterogeneity in adult attention deficit/hyperactivity disorder: A systematic analysis of neuropsychological measurements.

Attention Deficit/Hyperactivity Disorder (ADHD) in childhood is associated with impaired functioning in multiple cognitive domains: executive functioning (EF), reward and timing. Similar impairments have been described for adults with persistent ADHD, but an extensive investigation of neuropsychological functioning in a large sample of adult patients is currently lacking. We systematically examined neuropsychological performance on tasks measuring EF, delay discounting, time estimation and response variability using univariate ANCOVA's comparing patients with persistent ADHD (N=133, 42% male, mean age 36) and healthy adults (N=132, 40% male, mean age 36). In addition, we tested which combination of variables provided the highest accuracy in predicting ADHD diagnosis. We also estimated for each individual the severity of neuropsychological dysfunctioning. Lastly, we investigated potential effects of stimulant medication and a history of comorbid major depressive disorder (MDD) on performance. Compared to healthy adults, patients with ADHD showed impaired EF, were more impulsive, and more variable in responding. However, effect sizes were small to moderate (range: 0.05-0.70) and 11% of patients did not show neuropsychological dysfunctioning. The best fitting model predicting ADHD included measures from distinct cognitive domains (82.1% specificity, 64.9% sensitivity). Furthermore, patients receiving stimulant medication or with a history of MDD were not distinctively impaired. To conclude, while adults with ADHD as a group are impaired on several cognitive domains, the results confirm that adult ADHD is neuropsychologically heterogeneous. This provides a starting point to investigate individual differences in terms of impaired cognitive pathways.