5 research outputs found
Functional and structural imaging phenotypes of the amygdala and the cingulate cortex : an investigation in remitted depressed patients
Die Major Depression (MD) ist eine der vier Hauptursachen von MorbiditĂ€t und LetalitĂ€t und stellt ein in hohem Grad variables klinisches Krankheitsbild dar. Folglich ist die Identifikation biologischer PhĂ€notypen, vor allem durch bildgebende Verfahren gefundene PhĂ€notypen, die mit MD assoziiert sind, Ă€uĂerst wichtig, um die zugrundeliegenden pathophysiologischen Prozesse der MD aufzudecken. Da die meisten Neuroimaging Studien akute depressive Episoden erforschen, reflektieren Unterschiede zwischen akut depressiven Patienten und gesunden Probanden eher die klinischen Symptome als die neurobiologischen VerĂ€nderungen, die zu VulnerabilitĂ€t fĂŒr Depression fĂŒhren. Deshalb war das Ziel der vorliegenden Studie, remittierte MD Patienten, die frei von akuten Symptomen sind, und gesunde Kontrollen zu untersuchen. Dieser Ansatz hat den potentiellen Vorteil, von der klinischen Symptomatik unabhĂ€ngige Imaging PhĂ€notypen als VulnerabilitĂ€tsbiomarker zugĂ€nglich zu machen.
Es wurde strukturelle und funktionelle Magnetresonanztomographie (MRT) verwendet, um lokale strukturelle und funktionelle Unterschiede bwz.
funktionelle KonnektivitĂ€tsunterschiede zu entdecken. Der Schwerpunkt war auf Regionen gerichtet, die wĂ€hrend akuter Depression hĂ€ufig dysfunktional sind. Es wurde vor allem eine verringerte funktionelle KonnektivitĂ€t zwischen der Amygdala und Subregionen des CingulĂ€ren Cortex (CC) in akut depressiven Patienten gefunden, was als Ursache fĂŒr erhöhte Amygdalaaktivierung in akuter MD angesehen wurde.
Die Hauptergebnisse der gegenwÀrtigen Studie zeigen eine verminderte AmygdalaaktivitÀt in remittierten MD Patienten im Vergleich zu gesunden Kontrollen. Auf Gehirnsystemebene zeigen Patienten erhöhte KonnektivitÀt zwischen der Amygdala und verschiedenen Subregionen des CC im Vergleich zur Kontrollgruppe.
Die vorliegenden Ergebnisse verminderter AmygdalaaktivitÀt und erhöhter funktioneller KonnektivitÀt weisen darauf hin, dass remittierte MD Patienten adaptive Mechanismen zur Regulation von AmygdalahyperaktivitÀt entwickelt haben, die somit zur Aufrechterhaltung des remittierten Zustandes beitragen könnten.Major Depressive Disorder (MDD) is among the four leading causes of disease burden and mortality and exhibits a highly variable clinical picture. Therefore, the detection of biological phenotypes, in particular those assessed by imaging methods, which are associated with MDD might be crucial to reveal the pathophysiology of this disease.
Since most neuroimaging studies are investigating acute depression, differences between acute MDD patients and healthy controls might rather reflect the current psychopathological state than neurobiological alterations conferring vulnerability to depression. Therefore, this study aimed to investigate remitted MDD patients who are free of acute symptoms, and healthy controls in order to identify potential biological (imaging) phenotypes which are independent of the current clinical status thereby indicating depression vulnerability. We used structural and functional magnetic resonance imaging (MRI) to assess local structural/functional and functional connectivity differences of regions frequently found to be dysfunctional in acute MDD. More specifically, acutely depressed patients have been shown to display decreased functional connectivity between the amygdala and subregions of the cingulate cortex (CC) which has been suggested to result in amygdala hyperactivity in acute MDD.
The main findings of the current study showed decreased amygdala activity in remitted MDD patients compared to controls. At a brain system level, patients had increased connectivity between the amygdala and different subregions of the CC compared to controls. The current findings of decreased amygdala activity and increased functional connectivity suggest that remitted MDD patients might have developed adaptive mechanisms which regulate amygdala hyperactivity and by this contribute to maintain the remitted state.submitted by Beate HartingerAbweichender Titel laut Ăbersetzung der Verfasserin/des VerfassersAbstract, ZsfassungWien, Med. Univ., Diss., 2010OeBB(VLID)171393
Platelet Serotonin Transporter Function Predicts Default-Mode Network Activity
<div><p>Background</p><p>The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene <i>SLC6A4</i> and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence.</p><p>Methods</p><p>A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (V<sub>max</sub>) was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA) to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD) activity and platelet V<sub>max</sub>.</p><p>Results</p><p>The present study demonstrates that increases in platelet V<sub>max</sub> significantly predict default-mode network (DMN) suppression in healthy subjects independent of genetic variation within <i>SLC6A4</i>. Furthermore, functional connectivity analyses indicate that platelet V<sub>max</sub> is related to global DMN activation and not intrinsic DMN connectivity.</p><p>Conclusion</p><p>This study provides evidence that platelet V<sub>max</sub> predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal V<sub>max</sub> coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation.</p></div
Functional brain correlates of platelet 5-HT uptake velocity.
<p>(<b>AâB</b>) Figures display right-hemispheric surface mappings of a whole-brain correlation analysis between platelet V<sub>max</sub> and BOLD activity (nâ=â48). Significant brain areas showed positive and negative correlations. Negatively correlated clusters comprised areas of the DMN such as regions within the mPFC/ACC as well as the PCC, MTG, and ITG. Positive correlations were found in the fronto-parietal control system encompassing the CEN and SN with a significant cluster located in the right MOC and PMC. The corresponding left-hemispheric mapping is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092543#pone.0092543.s002" target="_blank">Figure S2</a>. Colorbar represents t-values. (<b>C</b>) Scatter plot shows the negative relationship between platelet V<sub>max</sub> and BOLD activity averaged across the mPFC cluster (peak at [â7.7, 44.1, 27.5]). (<b>D</b>) Scatter plot shows the positive relationship between platelet V<sub>max</sub> and BOLD activity averaged across the MOC cluster (peak at [20.8, â21.6, 69.1]). All analyses are controlled for age, gender and 5-HTTLPR. Serotonin, 5-HT; maximal 5-HT uptake velocity, V<sub>max</sub>; default mode network, DMN; medial prefrontal cortex, mPFC; anterior cingulate cortex, ACC; posterior cingulate cortex, PCC; middle temporal gyrus, MTG; inferior temporal gyrus, ITG; central executive network, CEN; salience network, SN; motor cortex, MOC; premotor cortex, PMC; blood-oxygen-level dependent, BOLD; a.u., arbitrary units.</p
Correlation analysis between maximal platelet 5-HT uptake velocity (V<sub>max</sub>) and neuronal activation (nâ=â48).
<p>Medial prefrontal cortex, mPFC; anterior cingulate cortex, ACC; motor cortex, MOC; premotor cortex, PMC; posterior cingulate cortex, PCC; precuneus, PRE; middle temporal gyrus, MTG; inferior temporal gyrus, ITG; p, uncorrected p value; significance level after correction for multiple comparisons based on recent recommendations <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092543#pone.0092543-Johnson1" target="_blank">[63]</a>: ***p<0.001; **p<0.005; *p<0.05; x, y, z are coordinates in Talairach space; L, left hemisphere; R, right hemisphere; cluster size expressed as number of voxels.</p