White and gray matter brain development in children and young adults with phenylketonuria.

Phenylketonuria (PKU) is a recessive disorder characterized by disruption in the metabolism of the amino acid phenylalanine (Phe). Prior research indicates that individuals with PKU have substantial white matter (WM) compromise. Much less is known about gray matter (GM) in PKU, but a small body of research suggests volumetric differences compared to controls. To date, developmental trajectories of GM structure in individuals with PKU have not been examined, nor have trajectories of WM and GM been examined within a single study. To address this gap in the literature, we compared longitudinal brain development over a three-year period in individuals with PKU (n = 35; 18 male) and typically-developing controls (n = 71; 35 male) aged 7-21 years. Using diffusion tensor imaging (DTI) and structural magnetic resonance imaging (MRI), we observed whole-brain and regional WM differences between individuals with PKU and controls, which were often exacerbated with increasing age. In marked contrast with trajectories of WM development, trajectories of GM development did not differ between individuals with PKU and controls, indicating that neuropathology in PKU is more prominent in WM than GM. Within individuals with PKU, mediation analyses revealed that whole-brain mean diffusivity (MD) and regional MD in the corpus callosum and centrum semiovale mediated the relationship between dietary treatment compliance (i.e., Phe control) and executive abilities, suggesting a plausible neurobiological mechanism by which Phe control may influence cognitive outcomes. Our findings clarify the specificity, timing, and cognitive consequences of whole-brain and regional WM pathology, with implications for treatment and research in PKU.

Transdiagnostic Multimodal Neuroimaging in Psychosis: Structural, Resting-State, and Task Magnetic Resonance Imaging Correlates of Cognitive Control.

BACKGROUND: Disorders with psychotic features, including schizophrenia and some bipolar disorders, are associated with impairments in regulation of goal-directed behavior, termed cognitive control. Cognitive control-related neural alterations have been studied in psychosis. However, studies are typically unimodal, and relationships across modalities of brain function and structure remain unclear. Thus, we performed transdiagnostic multimodal analyses to examine cognitive control-related neural variation in psychosis. METHODS: Structural, resting, and working memory task imaging for 31 control participants, 27 participants with bipolar disorder, and 23 participants with schizophrenia were collected and processed identically to the Human Connectome Project, enabling identification of relationships with prior multimodal work. Two cognitive control-related independent components (ICs) derived from the Human Connectome Project using multiset canonical correlation analysis with joint IC analysis were used to predict performance in psychosis. De novo multiset canonical correlation analysis with joint IC analysis was performed, and the results were correlated with cognitive control. RESULTS: A priori working memory and cortical thickness maps significantly predicted cognitive control in psychosis. De novo multiset canonical correlation analysis with joint IC analysis identified an IC correlated with cognitive control that also discriminated groups. Structural contributions included insular and cingulate regions; task contributions included precentral, posterior parietal, cingulate, and visual regions; and resting-state contributions highlighted canonical network organization. Follow-up analyses suggested that correlations with cognitive control were primarily influenced by participants with schizophrenia. CONCLUSIONS: A priori and de novo imaging replicably identified a set of interrelated patterns across modalities and the healthy-to-psychosis spectrum, suggesting robustness of these features. Relationships between imaging and cognitive control performance suggest that shared symptomatology may be key to identifying transdiagnostic relationships in psychosis.

Multimodal neural correlates of cognitive control in the Human Connectome Project.

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions hypothesized to be modulated by cognitive control signaling, such as visual cortex. Taken together, these results illustrate the potential utility of multi-modal analyses in identifying the neural correlates of cognitive control across different indicators of brain structure and function.

Transdiagnostic Associations Between Functional Brain Network Integrity and Cognition.

Importance: Cognitive impairment occurs across the psychosis spectrum and is associated with functional outcome. However, it is unknown whether these shared manifestations of cognitive dysfunction across diagnostic categories also reflect shared neurobiological mechanisms or whether the source of impairment differs. Objective: To examine whether the general cognitive deficit observed across psychotic disorders is similarly associated with functional integrity of 2 brain networks widely implicated in supporting many cognitive domains. Design, Setting, and Participants: A total of 201 healthy control participants and 375 patients with psychotic disorders from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were studied from September 29, 2007, to May 31, 2011. The B-SNIP recruited healthy controls and stable outpatients from 6 sites: Baltimore, Maryland; Boston, Massachusetts; Chicago, Illinois; Dallas, Texas; Detroit, Michigan; and Hartford, Connecticut. All participants underwent cognitive testing and resting-state functional magnetic resonance imaging. Data analysis was performed from April 28, 2015, to February 21, 2017. Main Outcomes and Measures: The Brief Assessment of Cognition in Schizophrenia was used to measure cognitive ability. A principal axis factor analysis on the Brief Assessment of Cognition in Schizophrenia battery yielded a single factor (54% variance explained) that served as the measure of general cognitive ability. Functional network integrity measures included global and local efficiency of the whole brain, cingulo-opercular network (CON), frontoparietal network, and auditory network and exploratory analyses of all networks from the Power atlas. Group differences in network measures, associations between cognition and network measures, and mediation models were tested. Results: The final sample for the current study included 201 healthy controls, 143 patients with schizophrenia, 103 patients with schizoaffective disorder, and 129 patients with psychotic bipolar disorder (mean [SD] age, 35.1 [12.0] years; 281 male [48.8%] and 295 female [51.2%]; 181 white [31.4%], 348 black [60.4%], and 47 other [8.2%]). Patients with schizophrenia (Cohen d = 0.36, P < .001) and psychotic bipolar disorder (Cohen d = 0.33, P = .002) had significantly reduced CON global efficiency compared with healthy controls. All patients with psychotic disorders had significantly reduced CON local efficiency, but the clinical groups did not differ from one another. The CON global efficiency was significantly associated with general cognitive ability across all groups (ß = 0.099, P = .009) and significantly mediated the association between psychotic disorder status and general cognition (ß = -0.037; 95% CI, -0.076 to -0.014). Subcortical network global efficiency was also significantly reduced in psychotic disorders (F3,587 = 4.01, P = .008) and positively predicted cognitive ability (ß = 0.094, P = .009). Conclusions and Relevance: These findings provide evidence that reduced CON and subcortical network efficiency play a role in the general cognitive deficit observed across the psychosis spectrum. They provide new support for the dimensional hypothesis that a shared neurobiological mechanism underlies cognitive impairment in psychotic disorders.

Network community structure alterations in adult schizophrenia: identification and localization of alterations.

A growing body of literature suggests functional connectivity alterations in schizophrenia. While findings have been mixed, evidence points towards a complex pattern of hyper-connectivity and hypo-connectivity. This altered connectivity can be represented and analyzed using the mathematical frameworks provided by graph and information theory to represent functional connectivity data as graphs comprised of nodes and edges linking the nodes. One analytic technique in this framework is the determination and analysis of network community structure, which is the grouping of nodes into linked communities or modules. This data-driven technique finds a best-fit structure such that nodes in a given community have greater connectivity with nodes in their community than with nodes in other communities. These community structure representations have been found to recapitulate known neural-systems in healthy individuals, have been used to identify novel functional systems, and have identified and localized community structure alterations in a childhood onset schizophrenia cohort. In the present study, we sought to determine whether community structure alterations were present in an adult onset schizophrenia cohort while stringently controlling for sources of imaging artifacts. Group level average graphs in healthy controls and individuals with schizophrenia exhibited visually similar network community structures and high amounts of normalized mutual information (NMI). However, testing of individual subject community structures identified small but significant alterations in community structure with alterations being driven by changes in node community membership in the somatosensory, auditory, default mode, salience, and subcortical networks.

Macrophage migration inhibitory factor acts as a neurotrophin in the developing inner ear.

This study is the first to demonstrate that macrophage migration inhibitory factor (MIF), an immune system 'inflammatory' cytokine that is released by the developing otocyst, plays a role in regulating early innervation of the mouse and chick inner ear. We demonstrate that MIF is a major bioactive component of the previously uncharacterized otocyst-derived factor, which directs initial neurite outgrowth from the statoacoustic ganglion (SAG) to the developing inner ear. Recombinant MIF acts as a neurotrophin in promoting both SAG directional neurite outgrowth and neuronal survival and is expressed in both the developing and mature inner ear of chick and mouse. A MIF receptor, CD74, is found on both embryonic SAG neurons and adult mouse spiral ganglion neurons. Mif knockout mice are hearing impaired and demonstrate altered innervation to the organ of Corti, as well as fewer sensory hair cells. Furthermore, mouse embryonic stem cells become neuron-like when exposed to picomolar levels of MIF, suggesting the general importance of this cytokine in neural development.