Josselin Houenou

Increased white matter connectivity in euthymic bipolar patients: diffusion tensor tractography between the subgenual cingulate and the amygdalo-hippocampal complex

Bipolar disorder has been associated with anatomical as well as functional abnormalities in a brain network that mediates normal and impaired emotion regulation. Previous brain imaging studies have highlighted the subgenual cingulate (SC) and the amygdalo-hippocampal (AH) complex as core regions of this network. Thus we investigated white matter (WM) fiber tracts between the SC and the AH region, the uncinate fasciculus, as well as between two control regions (pons and cerebellum), using diffusion tensor imaging tractography in 16 euthymic bipolar patients (BP) and 16 sex-, age- and handedness-matched controls. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) of the reconstructed fiber bundle and the number of virtual reconstructed fibers were compared between groups. The tractography results revealed a significantly increased number of reconstructed fibers between the left SC and left AH in BP as compared to healthy controls. FA and ADC of the reconstructed fiber tract did not differ significantly between the groups. Furthermore, no significant group differences were observed neither for reconstructed fiber tracts between the right SC and right AH nor between the control regions. The present results suggest an altered WM pathway between the left SC and AH region and thus extend previous findings of anatomical and functional modifications in these structures in BP.

Subcortical volumetric abnormalities in bipolar disorder.

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case–control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen’s d=−0.232; P=3.50 × 10−7) and thalamus (d=−0.148; P=4.27 × 10−3) and enlarged lateral ventricles (d=−0.260; P=3.93 × 10−5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.

Microstructural white matter changes in euthymic bipolar patients: a whole-brain diffusion tensor imaging study.

OBJECTIVESnBrain structures of a distributed ventral-limbic and dorsal brain network have been associated with altered mood states and emotion regulation in affective disorders. So far, diffusion tensor imaging studies in bipolar patients have focused on frontal/prefrontal brain regions and found alterations in white matter integrity in manic, depressed, and euthymic bipolar patients, observed as changes in fractional anisotropy and mean diffusivity. To extend previous findings, we investigated whole-brain modifications in white matter integrity in euthymic bipolar patients with minimal manic and depressive symptoms.nnnMETHODSnTwenty-two patients with a DSM-IV-TR diagnosis of bipolar I and II disorder in remission, with no lifetime or present comorbidities of substance abuse, and 21 sex- and age-matched healthy controls underwent diffusion tensor imaging with diffusion gradients applied along 41 directions. Fractional anisotropy and mean diffusivity group differences were explored using two voxel-based, whole-brain analyses that differ in their normalization approaches.nnnRESULTSnFractional anisotropy was significantly increased in bipolar patients relative to healthy controls in medial frontal, precentral, inferior parietal, and occipital white matter. No group differences in mean diffusivity were found.nnnCONCLUSIONSnThe result of increased fractional anisotropy in euthymic bipolar patients in the present study suggests increased directional coherence of white matter fibers in bipolar patients during remission.

The arcuate fasciculus in auditory-verbal hallucinations: A meta-analysis of diffusion-tensor-imaging studies

Auditory-verbal hallucinations (AVHs) are associated with an impaired connectivity of large-scale networks. To examine the relationship between white-matter integrity and AVHs, we conducted a meta-analysis of diffusion-tensor-imaging studies that compared patients with schizophrenia and AVHs with matched healthy controls (HCs). Five studies were retained gathering 256 DTI data points, divided into AVHs (n=106) and HCs (n=150). The meta-analysis demonstrated a reduced fractional anisotropy in the left Arcuate Fasciculus (AF) of hallucinators (hg= -0.42; CI[-0.69,-0.16]; p<10(-3)). The current meta-analysis confirmed disruptions of white matter integrity in the left AF bundle of schizophrenia patients with AVHs.

Gene x environment interactions in schizophrenia and bipolar disorder: evidence from neuroimaging.

Introduction: Schizophrenia (SZ) and Bipolar disorder (BD) are considered as severe multifactorial diseases, stemming from genetic and environmental influences. Growing evidence supports gene x environment (GxE) interactions in these disorders and neuroimaging studies can help us to understand how those factors mechanistically interact. No reviews synthesized the existing data of neuroimaging studies in these issues. Methods: We conduct a systematic review on the neuroimaging studies exploring GxE interactions relative to SZ or BD in PubMed. Results: First results of the influence of genetic and environmental risks on brain structures came from monozygotic twin pairs concordant and discordant for SZ or BD. Few structural magnetic resonance imaging (sMRI) studies have explored the GxE interactions. No other imaging methods were found. Two main GxE interactions on brain volumes have arisen. First, an interaction between genetic liability to SZ and obstetric complications on gray matter, cerebrospinal fluid, and hippocampal volumes. Second, cannabis use and genetic liability interaction effects on cortical thickness and white matter volumes. Conclusion: Combining GxE interactions and neuroimaging domains is a promising approach. Genetic risk and environmental exposures such as cannabis or obstetrical complications seem to interact leading to specific neuroimaging cerebral alterations in SZ. They are suggestive of GxE interactions that confer phenotypic abnormalities in SZ and possibly BD. We need further, larger neuroimaging studies of GxE interactions for which we may propose a framework focusing on GxE interactions data already known to have a clinical effect such as infections, early stress, urbanicity, and substance abuse.

Cytomegalovirus seropositivity and serointensity are associated with hippocampal volume and verbal memory in schizophrenia and bipolar disorder.

INTRODUCTIONnCytomegalovirus (CMV) is a member of the herpesviridae family that has a limbic and temporal gray matter tropism. It is usually latent in humans but has been associated with schizophrenia, bipolar disorder and cognitive deficits in some populations. Hippocampal decreased volume and dysfunction play a critical role in these cognitive deficits. We hypothesized that CMV seropositivity and serointensity would be associated with hippocampal volume and cognitive functioning in patients with schizophrenia or bipolar disorder.nnnMETHODSn102 healthy controls, 118 patients with bipolar disorder and 69 patients with schizophrenia performed the California Verbal Learning Test (CVLT) and had blood samples drawn to assess CMV IgG levels. A subgroup of 52 healthy controls, 31 patients with bipolar disorder and 27 patients with schizophrenia underwent T1 MRI for hippocampal volumetry. We analyzed the association between CMV serointensity and seropositivity with hippocampal volume. We also explored the correlation between CMV serointensity and seropositivity and CVLT scores.nnnRESULTSnIn both patient groups but not in controls, higher CMV serointensity was significantly associated with smaller right hippocampal volume. Further, in the group of patients with schizophrenia but not bipolar disorder, CMV serointensity was negatively correlated with CVLT scores.nnnCONCLUSIONnCMV IgG titers are associated with decreased hippocampal volume and poorer episodic verbal memory in patients with schizophrenia or bipolar disorder. The mechanism of this association warrants further exploration.

T145. ALTERATIONS IN SUPERFICIAL WHITE MATTER IN THE FRONTAL CORTEX IN SCHIZOPHRENIA: A DWI STUDY USING A NOVEL ATLAS

Abstract Background Alterations in brain connectivity are strongly implicated in the pathophysiology of schizophrenia (SZ). Very recently, evidence is mounting to suggest that changes in superficial white matter (SWM) U-shaped short range fibers are integral components of disease neuropathology, a theory that is supported by findings from postmortem studies and less often in vivo in patients with SZ. This diffusion weighted imaging (DWI) study aimed to investigate SWM microstructure in the frontal cortex in people with SZ. Methods Whole brain tractography was performed in 31 people with SZ and 54 healthy controls using BrainVISA and Connectomist 2.0 software. Segmentation and labelling of superficial white matter tracts were performed using a novel atlas characterizing 100 bundles. Principal Components Analysis (PCA) using a varimax orthogonal rotation was performed on mean generalised fractional anisotropy (gFA) of bundles located in the frontal cortex. Composites scores were computed for each subject, reflecting a linear combination of mean gFA values. Results PCA revealed three components explaining 19.7 %, 5.8 %, and 5.4 % of the total variance. The mean score of the second component was significantly lower in the people with SZ compared with controls (p = 0.01) and included 13 bundles connecting regions in the pars orbitalis, insula, pars triangularis, pars opercularis, orbitofrontal cortex, anterior cingulate, superior frontal cortex and middle frontal cortex. Discussion Our results support findings of reduced white matter integrity in the frontal cortex in people with SZ. Moreover, PCA may be helpful in identifying specific networks as the deficits do not appear to be widespread. Identifying patterns of superficial white matter dysconnectivity may be helpful in understanding the prominent symptoms and cognitive deficits and observed in SZ.

Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CIu2009=u200963.47–67.00, ROC-AUCu2009=u200971.49%, 95% CIu2009=u200969.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CIu2009=u200956.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappau2009=u20090.83, 95% CIu2009=u20090.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracyxa0threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.