Identification of pleiotropic genetic effects on obesity and brain anatomy.

Background/aims: Obesity is a major contributor to the global burden of chronic disease and disability, though current knowledge of causal biologic underpinnings is lacking. Through the regulation of energy homeostasis and interactions with adiposity and gut signals, the brain is thought to play a significant role in the development of this disorder. While neuroanatomical variation has been associated with obesity, it is unclear if this relationship is influenced by common genetic mechanisms.

Sulcal depth-position profile is a genetically mediated neuroscientific trait: description and characterization in the central sulcus.

Genetic and environmental influences on brain morphology were assessed in an extended-pedigree design by extracting depth-position profiles (DPP) of the central sulcus (CS). T1-weighted magnetic resonance images were used to measure CS length and depth in 467 human subjects from 35 extended families. Three primary forms of DPPs were observed.

Impulsivity and risk taking in bipolar disorder and schizophrenia.

Impulsive risk taking contributes to deleterious outcomes among clinical populations. Indeed, pathological impulsivity and risk taking are common in patients with serious mental illness, and have severe clinical repercussions including novelty seeking, response disinhibition, aggression, and substance abuse. Thus, the current study seeks to examine self-reported impulsivity (Barratt Impulsivity Scale) and performance-based behavioral risk taking (Balloon Analogue Risk Task) in bipolar disorder and schizophrenia.

Multi-region hemispheric specialization differentiates human from nonhuman primate brain function.

The human behavioral repertoire greatly exceeds that of nonhuman primates. Anatomical specializations of the human brain include an enlarged neocortex and prefrontal cortex (Semendeferi et al. in Am J Phys Anthropol 114:224-241, 2001), but regional enlargements alone cannot account for these vast functional differences.

Neuroinformatics Database (NiDB)--a modular, portable database for the storage, analysis, and sharing of neuroimaging data.

We present a modular, high performance, open-source database system that incorporates popular neuroimaging database features with novel peer-to-peer sharing, and a simple installation. An increasing number of imaging centers have created a massive amount of neuroimaging data since fMRI became popular more than 20 years ago, with much of that data unshared. The Neuroinformatics Database (NiDB) provides a stable platform to store and manipulate neuroimaging data and addresses several of the impediments to data sharing presented by the INCF Task Force on Neuroimaging Datasharing, including 1) motivation to share data, 2) technical issues, and 3) standards development.

Characterizing thalamo-cortical disturbances in schizophrenia and bipolar illness.

Schizophrenia is a devastating neuropsychiatric syndrome associated with distributed brain dysconnectivity that may involve large-scale thalamo-cortical systems. Incomplete characterization of thalamic connectivity in schizophrenia limits our understanding of its relationship to symptoms and to diagnoses with shared clinical presentation, such as bipolar illness, which may exist on a spectrum. Using resting-state functional magnetic resonance imaging, we characterized thalamic connectivity in 90 schizophrenia patients versus 90 matched controls via: (1) Subject-specific anatomically defined thalamic seeds; (2) anatomical and data-driven clustering to assay within-thalamus dysconnectivity; and (3) machine learning to classify diagnostic membership via thalamic connectivity for schizophrenia and for 47 bipolar patients and 47 matched controls.

Is aberrant functional connectivity a psychosis endophenotype? A resting state functional magnetic resonance imaging study.

Background: Schizophrenia and bipolar disorder share overlapping symptoms and risk genes. Shared aberrant functional connectivity is hypothesized in both disorders and in relatives.

Methods: We investigated resting state functional magnetic resonance imaging in 70 schizophrenia and 64 psychotic bipolar probands, their respective first-degree relatives (n = 70 and 52), and 118 healthy subjects.

Genetics of the connectome.

Connectome genetics attempts to discover how genetic factors affect brain connectivity. Here we review a variety of genetic analysis methods--such as genome-wide association studies (GWAS), linkage and candidate gene studies--that have been fruitfully adapted to imaging data to implicate specific variants in the genome for brain-related traits. Studies that emphasized the genetic influences on brain connectivity.

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group.

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure.

Polygenic risk and white matter integrity in individuals at high risk of mood disorder.

Background: Bipolar disorder (BD) and major depressive disorder (MDD) are highly heritable and genetically overlapping conditions characterized by episodic elevation and/or depression of mood. Both demonstrate abnormalities in white matter integrity, measured with diffusion tensor magnetic resonance imaging, that are also heritable. However, it is unclear how these abnormalities relate to the underlying genetic architecture of each disorder.

Social and nonsocial cognition in bipolar disorder and schizophrenia: relative levels of impairment.

Objective: This study aimed to determine the relative extent of impairment in social and nonsocial cognitive domains in patients with bipolar disorder compared with schizophrenia patients and healthy comparison subjects.

Methods: Sixty-eight clinically stable outpatients with bipolar disorder, 38 clinically stable outpatients with schizophrenia, and 36 healthy comparison subjects completed a range of social (facial affect perception, emotional regulation, empathic accuracy, mental state attribution, and self-referential memory) and nonsocial (speed of processing, attention/vigilance, working memory, verbal memory, visual memory, and reasoning/problem solving) cognitive tasks.

Results: For each social cognitive task, patients with bipolar disorder did not differ significantly from comparison subjects, and both groups performed better than schizophrenia patients.

Can risk-taking be an endophenotype for bipolar disorder? A study on patients with bipolar disorder type I and their first-degree relatives.

Risk-taking behavior and impulsivity are core features of bipolar disorder. Whether they are part of the inherited aspect of the illness is not clear. We aimed to evaluate risk-taking behavior as a potential endophenotype for bipolar disorders, and its relationship with impulsivity and illness features.

Testing the hypothesis of accelerated cerebral white matter aging in schizophrenia and major depression.

Background: Elevated rate of aging-related biological and functional decline, termed "accelerated aging," is reported in patients with schizophrenia (SCZ) and major depressive disorder (MDD). We used diffusion tensor imaging derived fractional anisotropy (FA) as a biomarker of aging-related decline in white matter (WM) integrity to test the hypotheses of accelerated aging in SCZ and MDD.

Methods: The SCZ cohort comprised 58 SCZ patients and 60 controls (aged 20-60 years).

Dedifferentiation and substitute strategy: deconstructing the processing-speed impairment in schizophrenia.

Background: Recent research has identified impairment in processing speed, measured by the digit-symbol substitution task, as central to the cognitive deficit in schizophrenia. However, the underlying cognitive correlates of this impairment remain unknown.

Methods: A sample of cases (N=125) meeting DSM-IV criteria for schizophrenia and a sample of community controls (N=272) from the same geographical area completed a set of putative measures of processing-speed ability to which we implemented confirmatory factor and structural regression modelling in order to elucidate the latent structure of processing speed.

Meta-analytic connectivity modeling reveals differential functional connectivity of the medial and lateral orbitofrontal cortex.

The orbitofrontal cortex (OFC) is implicated in a broad range of behaviors and neuropsychiatric disorders. Anatomical tracing studies in nonhuman primates reveal differences in connectivity across subregions of the OFC, but data on the connectivity of the human OFC remain limited. We applied meta-analytic connectivity modeling in order to examine which brain regions are most frequently coactivated with the medial and lateral portions of the OFC in published functional neuroimaging studies.

Global prefrontal and fronto-amygdala dysconnectivity in bipolar I disorder with psychosis history.

Background: Pathophysiological models of bipolar disorder postulate that mood dysregulation arises from fronto-limbic dysfunction, marked by reduced prefrontal cortex (PFC) inhibitory control. This might occur due to both disruptions within PFC networks and abnormal inhibition over subcortical structures involved in emotional processing. However, no study has examined global PFC dysconnectivity in bipolar disorder and tested whether regions with within-PFC dysconnectivity also exhibit fronto-limbic connectivity deficits.

Genetic contributions to the midsagittal area of the corpus callosum.

The degree to which genes and environment determine variations in brain structure and function is fundamentally important to understanding normal and disease-related patterns of neural organization and activity. We studied genetic contributions to the midsagittal area of the corpus callosum (CC) in pedigreed baboons (68 males, 112 females) to replicate findings of high genetic contribution to that area of the CC reported in humans, and to determine if the heritability of the CC midsagittal area in adults was modulated by fetal development rate. Measurements of callosal area were obtained from high-resolution MRI scans.

Trait impulsivity as an endophenotype for bipolar I disorder.

Objective: Impulsivity, conceptualized as impairment in planning and poor attentional and inhibitory control, is a key feature of bipolar disorder. Familial risk for bipolar disorder is known to affect inhibitory control but its impact on the attentional and planning dimensions of impulsivity is still unclear.

Methods: We administered the Barratt Impulsiveness Scale, version 11 (BIS-11) to 54 euthymic individuals with DSM-IV bipolar I disorder, 57 of their clinically unaffected siblings, and 49 healthy comparison subjects.

Cross-diagnostic comparison of duration mismatch negativity and P3a in bipolar disorder and schizophrenia.

Objectives: Bipolar disorder and schizophrenia share common pathophysiological processes and may have similar perceptual abnormalities. Mismatch negativity (MMN) and P3a - event-related potentials associated with auditory preattentional processing - have been extensively studied in schizophrenia, but rarely in bipolar disorder. Furthermore, MMN and P3a have not been examined between diagnostic subgroups of patients with bipolar disorder.

Identification of common variants associated with human hippocampal and intracranial volumes.

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies.

Measuring and comparing brain cortical surface area and other areal quantities.

Structural analysis of MRI data on the cortical surface usually focuses on cortical thickness. Cortical surface area, when considered, has been measured only over gross regions or approached indirectly via comparisons with a standard brain. Here we demonstrate that direct measurement and comparison of the surface area of the cerebral cortex at a fine scale is possible using mass conservative interpolation methods.

Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives.

Background: Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders.

Methods: We compared 70 schizophrenia and 64 psychotic bipolar probands, their respective unaffected first-degree relatives (n = 70, and n = 52), and 118 healthy subjects, all group age-, gender-, and ethnicity-matched.

Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions.

Classic cognitive theory conceptualizes executive functions as involving multiple specific domains, including initiation, inhibition, working memory, flexibility, planning, and vigilance. Lesion and neuroimaging experiments over the past two decades have suggested that both common and unique processes contribute to executive functions during higher cognition. It has been suggested that a superordinate fronto-cingulo-parietal network supporting cognitive control may also underlie a range of distinct executive functions.

A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort.

The underlying genetic etiology of late onset Alzheimer's disease (LOAD) remains largely unknown, likely due to its polygenic architecture and a lack of sophisticated analytic methods to evaluate complex genotype-phenotype models. The aim of the current study was to overcome these limitations in a bi-multivariate fashion by linking intermediate magnetic resonance imaging (MRI) phenotypes with a genome-wide sample of common single nucleotide polymorphism (SNP) variants. We compared associations between 94 different brain regions of interest derived from structural MRI scans and 533,872 genome-wide SNPs using a novel multivariate statistical procedure, parallel-independent component analysis, in a large, national multi-center subject cohort.

The functional connectivity of the human caudate: an application of meta-analytic connectivity modeling with behavioral filtering.

Meta-analysis based techniques are emerging as powerful, robust tools for developing models of connectivity in functional neuroimaging. Here, we apply meta-analytic connectivity modeling to the human caudate to 1) develop a model of functional connectivity, 2) determine if meta-analytic methods are sufficiently sensitive to detect behavioral domain specificity within region-specific functional connectivity networks, and 3) compare meta-analytic driven segmentation to structural connectivity parcellation using diffusion tensor imaging. Results demonstrate strong coherence between meta-analytic and data-driven methods.