Theo G.M. van Erp

Genetic influences on brain structure

Here we report on detailed three-dimensional maps revealing how brain structure is influenced by individual genetic differences. A genetic continuum was detected in which brain structure was increasingly similar in subjects with increasing genetic affinity. Genetic factors significantly influenced cortical structure in Brocas and Wernickes language areas, as well as frontal brain regions (r2MZ > 0.8, p < 0.05). Preliminary correlations were performed suggesting that frontal gray matter differences may be linked to Spearmans g, which measures successful test performance across multiple cognitive domains (p < 0.05). These genetic brain maps reveal how genes determine individual differences, and may shed light on the heritability of cognitive and linguistic skills, as well as genetic liability for diseases that affect the human cortex.

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimers disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood- and adult-onset schizophrenia, bipolar disorder, attention-deficit/hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages.

Diffusion Tensor Imaging of the Superior Longitudinal Fasciculus and Working Memory in Recent-Onset Schizophrenia

BACKGROUND Structural and functional abnormalities in frontal-parietal circuitry are thought to be associated with working memory (WM) deficits in patients with schizophrenia. This study examines whether recent-onset schizophrenia is associated with anatomical changes in the superior longitudinal fasciculus (SLF), the main frontal-parietal white matter connection, and whether the integrity of the SLF is related to WM performance. METHODS We applied a novel registration approach (Tract-Based Spatial Statistics [TBSS]) to diffusion tensor imaging data to examine fractional anisotropy (FA) in the left and right SLF in 12 young adult patients with recent-onset schizophrenia and 17 matched control subjects. RESULTS Schizophrenia patients showed lower FA values than control subjects across the entire SLF, with particular deficits on the left SLF. Fractional anisotropy values were correlated with performance on a verbal WM task in both patient and control groups in the left but not right SLF. CONCLUSIONS Recent-onset schizophrenia patients show deficits in frontal-parietal connections, key components of WM circuitry. Moreover, the integrity of this physiological connection predicted performance on a verbal WM task, indicating that this structural change may have important functional implications. These findings support the view that schizophrenia is a disorder of brain connectivity and implicate white matter changes detectable in the early phases of the illness as one source of this dysfunction.

Progressive Reduction in Cortical Thickness as Psychosis Develops: A Multisite Longitudinal Neuroimaging Study of Youth at Elevated Clinical Risk

BACKGROUND Individuals at clinical high risk (CHR) who progress to fully psychotic symptoms have been observed to show a steeper rate of cortical gray matter reduction compared with individuals without symptomatic progression and with healthy control subjects. Whether such changes reflect processes associated with the pathophysiology of schizophrenia or exposure to antipsychotic drugs is unknown. METHODS In this multisite study, 274 CHR cases, including 35 individuals who converted to psychosis, and 135 healthy comparison subjects were scanned with magnetic resonance imaging at baseline, 12-month follow-up, or the point of conversion for the subjects who developed fully psychotic symptoms. RESULTS In a traveling subjects substudy, excellent reliability was observed for measures of cortical thickness and subcortical volumes. Controlling for multiple comparisons throughout the brain, CHR subjects who converted to psychosis showed a steeper rate of gray matter loss in the right superior frontal, middle frontal, and medial orbitofrontal cortical regions as well as a greater rate of expansion of the third ventricle compared with CHR subjects who did not convert to psychosis and healthy control subjects. Differential tissue loss was present in subjects who had not received antipsychotic medications during the interscan interval and was predicted by baseline levels of an aggregate measure of proinflammatory cytokines in plasma. CONCLUSIONS These findings demonstrate that the brain changes are not explained by exposure to antipsychotic drugs but likely play a role in psychosis pathophysiology. Given that the cortical changes were more pronounced in subjects with briefer durations of prodromal symptoms, contributing factors may predominantly play a role in acute-onset forms of psychosis.

Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: a cross-sectional mega-analysis

BACKGROUND Neuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis. METHODS In this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0·0156. FINDINGS Our sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4-63 years). The volumes of the accumbens (Cohens d=-0·15), amygdala (d=-0·19), caudate (d=-0·11), hippocampus (d=-0·11), putamen (d=-0·14), and intracranial volume (d=-0·10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0·95) and thalamus (p=0·39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (<15 years) versus adults (>21 years): in the accumbens (Cohens d=-0·19 vs -0·10), amygdala (d=-0·18 vs -0·14), caudate (d=-0·13 vs -0·07), hippocampus (d=-0·12 vs -0·06), putamen (d=-0·18 vs -0·08), and intracranial volume (d=-0·14 vs 0·01). There was no difference between children and adults for the pallidum (p=0·79) or thalamus (p=0·89). Case-control differences in adults were non-significant (all p>0·03). Psychostimulant medication use (all p>0·15) or symptom scores (all p>0·02) did not influence results, nor did the presence of comorbid psychiatric disorders (all p>0·5). INTERPRETATION With the largest dataset to date, we add new knowledge about bilateral amygdala, accumbens, and hippocampus reductions in ADHD. We extend the brain maturation delay theory for ADHD to include subcortical structures and refute medication effects on brain volume suggested by earlier meta-analyses. Lifespan analyses suggest that, in the absence of well powered longitudinal studies, the ENIGMA cross-sectional sample across six decades of ages provides a means to generate hypotheses about lifespan trajectories in brain phenotypes. FUNDING National Institutes of Health.

Elucidating a magnetic resonance imaging-based neuroanatomic biomarker for psychosis: classification analysis using probabilistic brain atlas and machine learning algorithms.

BACKGROUND No objective diagnostic biomarkers or laboratory tests have yet been developed for psychotic illness. Magnetic resonance imaging (MRI) studies consistently find significant abnormalities in multiple brain structures in psychotic patients relative to healthy control subjects, but these abnormalities show substantial overlap with anatomic variation that is in the normal range and therefore nondiagnostic. Recently, efforts have been made to discriminate psychotic patients from healthy individuals using machine-learning-based pattern classification methods on MRI data. METHODS Three-dimensional cortical gray matter density (GMD) maps were generated for 36 patients with recent-onset psychosis and 36 sex- and age-matched control subjects using a cortical pattern matching method. Between-group differences in GMD were evaluated. Second, the sparse multinomial logistic regression classifier included in the Multivariate Pattern Analysis in Python machine-learning package was applied to the cortical GMD maps to discriminate psychotic patients from control subjects. RESULTS Patients showed significantly lower GMD, particularly in prefrontal, cingulate, and lateral temporal brain regions. Pattern classification analysis achieved 86.1% accuracy in discriminating patients from controls using leave-one-out cross-validation. CONCLUSIONS These results suggest that even at the early stage of illness, psychotic patients present distinct patterns of regional cortical gray matter changes that can be discriminated from the normal pattern. These findings indicate that we can detect complex patterns of brain abnormality in early stages of psychotic illness, which has critical implications for early identification and intervention in individuals at ultra-high risk for developing psychosis/schizophrenia.

Developmental disruptions in neural connectivity in the pathophysiology of schizophrenia.

Schizophrenia has been thought of as a disorder of reduced functional and structural connectivity. Recent advances in neuroimaging techniques such as functional magnetic resonance imaging, structural magnetic resonance imaging, diffusion tensor imaging, and small animal imaging have advanced our ability to investigate this hypothesis. Moreover, the power of longitudinal designs possible with these noninvasive techniques enable the study of not just how connectivity is disrupted in schizophrenia, but when this disruption emerges during development. This article reviews genetic and neurodevelopmental influences on structural and functional connectivity in human populations with or at risk for schizophrenia and in animal models of the disorder. We conclude that the weight of evidence across these diverse lines of inquiry points to a developmental disruption of neural connectivity in schizophrenia and that this disrupted connectivity likely involves susceptibility genes that affect processes involved in establishing intra- and interregional connectivity.

The relationship between performance and fMRI signal during working memory in patients with schizophrenia, unaffected co-twins, and control subjects

While behavioral research shows working memory impairments in schizophrenics and their relatives, functional neuroimaging studies of patients and healthy controls show conflicting findings of hypo- and hyperactivation, possibly indicating different relationships between physiological activity and performance. In a between-subjects regression analysis of fMRI activation and performance, low performance was associated with relatively lower activation in patients than controls, while higher performance was associated with higher activation in patients than controls in DLPFC and parietal cortex, but not occipital cortex, with unaffected twins of schizophrenics being intermediate between the groups. Accordingly, this supports the idea that both hyper and hypoactivation may be possible along a continuum of behavioral performance in a way consistent with a neural inefficiency model. Further, this study offers preliminary evidence that the relationship between behavior and physiology in schizophrenia may be heritable.

Function biomedical informatics research network recommendations for prospective multicenter functional MRI studies.

This report provides practical recommendations for the design and execution of multicenter functional MRI (MC‐fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The study was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC‐fMRI studies. The introduction briefly discusses the advantages and complexities of MC‐fMRI studies. Prerequisites for MC‐fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC‐fMRI study. Practical multisite aspects include: (i) establishing and verifying scan parameters including scanner types and magnetic fields, (ii) establishing and monitoring of a scanner quality program, (iii) developing task paradigms and scan session documentation, (iv) establishing clinical and scanner training to ensure consistency over time, (v) developing means for uploading, storing, and monitoring of imaging and other data, (vi) the use of a traveling fMRI expert, and (vii) collectively analyzing imaging data and disseminating results. We conclude that when MC‐fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery. J. Magn. Reson. Imaging 2012;36:39–54.

A twin study of genetic contributions to hippocampal morphology in schizophrenia.

Our goal was to establish whether altered hippocampal morphology represents a trait marker for genetic vulnerability in schizophrenia. We outlined the hippocampi on high-resolution MR images obtained from matched samples of control and discordant monozygotic and dizygotic co-twins (N = 40 pairs). Hippocampal measures were used in statistical tests specifically designed to identify disease-associated genetic and nongenetic influences on morphology. 3D surface average maps of the hippocampus were additionally compared in biological risk groups. Smaller hippocampal volumes were confirmed in schizophrenia. Dizygotic affected co-twins showed smaller left hippocampi compared to their healthy siblings. Disease-associated effects were not present between monozygotic discordant co-twins. Monozygotic, but not dizygotic, unaffected co-twins exhibited smaller left hippocampi compared to control twins, supporting genetic influences. Surface areas and posterior volumes similarly revealed schizophrenia and genetic liability effects. Results suggest that hippocampal volume reduction may be a trait marker for identifying individuals possessing a genetic predisposition for schizophrenia.