2 results
Disrupted structural brain networks across psychiatric disorders determined using multivariate graph analyses
- R. K. Paunova, D. Stoyanov, C. Ramponi, A. Latypova, F. Kherif
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- Journal:
- European Psychiatry / Volume 66 / Issue S1 / March 2023
- Published online by Cambridge University Press:
- 19 July 2023, pp. S295-S296
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Introduction
Identifying the specific brain pattern characterizing psychiatric disorders could lead us to precise diagnostic process, better treatment plan and outcome prediction. Structural covariance is a graph-analysis method with which disruptions in large scale brain network organization can be observed. More studies, employing this method in psychiatry, are still needed.
ObjectivesThe current study aims to investigate how the main psychiatric disorders – schizophrenia, major depressive disorder, bipolar disorder, affect brain circuitry by means of multivariate graph theory, more specifically – structural covariance. We hypothesized that specific abnormalities in the brain circuits would be found in separate diagnostic entities.
Methods164 subjects were included with schizophrenia-SCH (n=17), bipolar disorder-BD(n=25), major depressive disorder–MDD(n=68) and a healthy control group-HC(n=54). Each participant provided a written informed consent and the study protocol was approved by the University’s Ethics Committee. High resolution structural MRI was acquired, and preprocessing was performed using SPM 12 toolbox. The structural covariance method was applied consisting of calculation of the correlation across subjects between the different pairs of regions by using the gray matter average volume. We used the threshold statistic to binarize the covariance matrix and transform it into an adjacency matrix. This allows us to compare psychiatric disorders at a network level by calculating measures such as authorities, hubs and outdegree.
Results61 statistically significant regions were found for the whole sample. The matrices of the four groups were compared according to their ‘authorities’ ,‘hubs’ and ‘outdegree’ as first, second and third ranking variables, respectively. In the group comparison between HC and BD patients the top five significant regions were Planum temporale (PT), Putamen, Precuneus (PreCu), Calcarine cortex (Calc_cor) and Postcentral gyrus medial segment (PostCGms). The MDD group demonstrated the following regions with most significant difference including Precentral gyrus (PreCG), Entorhinal area (EntA), Amygdala (Amy), Anterior cingulate gyrus (ACC), Anterior insula (AI). While SCH grop was charachterized by ACC, PreCG – medial segment, PostCGms, anterior orbital gyrus, and frontal pole.
ConclusionsThe results of our study demonstrated that schizophrenia and mood disorders have specific disturbances in brain network structural organization, affecting hubs of default mode network, salience network, motor, sensory and visual cortex, as well as limbic system. These alterations might elucidate the pathophysiological mechanisms of common symptoms of the disorders under investigation including perceptual, affective and cognitive disturbances.
Disclosure of InterestNone Declared
CYP2C19 expression modulates affective functioning and brain anatomy – a large single-center community-dwelling cohort study
- C. Grosu, O. Trofimova, M. Gholam, M.-P. Strippoli, F. Kherif, A. Lutti, M. Preisig, B. Draganski, C. Eap
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- Journal:
- European Psychiatry / Volume 65 / Issue S1 / June 2022
- Published online by Cambridge University Press:
- 01 September 2022, p. S120
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Introduction
The association between CYP2C19 poor metabolizer status, depressive symptom severity and hippocampal volume in humans is controversial. Progress in understanding not only the pathophysiology of depression but also potential protective mechanisms is important both for daily clinical practice and for the development of new antidepressant therapies.
ObjectivesTo test and validate previous findings regarding the impact of CYP2C19 status on depressive symptoms and to examine whether it could influence hippocampus subregions and brain tissue microstructure.
MethodsA total of 4152 individuals from the Longitudinal cohort in the community-dwelling adult population - Colaus|PsyCoLaus in Lausanne, Switzerland were included. They have participated in at least one psychiatric evaluation. Brain anatomy patterns using a comprehensive set of psychometry, water diffusion- and relaxometry-based magnetic resonance imaging data were analysed in a subset of the cohort (BrainLaus, n=1187).
ResultsIn this population-based cohort study, better lifetime global assessment of functioning scores were observed in poor metabolizers when compared to other metabolizers, this result was mainly driven by female participants (ß=3.9, P=0.01). Examination of brain imaging data revealed that higher right hippocampal subiculum volume was related to poor metabolizer status (ß=0.03, P=0.006). In addition, associations were observed between metabolizer status and white matter microstructure in the left uncinate fasciculus (ß=-0.01, P=0.01) and the left cingulum bundle (ß=-0.01, P=0.01).
ConclusionsCYP2C19 status is associated with modifications in lifetime global functioning, and brain anatomy. Such differences in brain structures can contribute to explain the protective effect of CYP2C19 poor metabolizer status.
DisclosureNo significant relationships.