Abnormal amygdala resting-state functional connectivity in adults and adolescents with major depressive disorder: A comparative meta-analysis

Shi Tang, Lu Lu, Lianqing Zhang, Xinyu Hu, Xuan Bu, Hailong Li, Xiaoxiao Hu, Yingxue Gao, Zirui Zeng, Qiyong Gong, Xiaoqi Huang, Shi Tang, Lu Lu, Lianqing Zhang, Xinyu Hu, Xuan Bu, Hailong Li, Xiaoxiao Hu, Yingxue Gao, Zirui Zeng, Qiyong Gong, Xiaoqi Huang

Abstract

Background: Although dysfunction of amygdala-related circuits is centrally implicated in major depressive disorder (MDD), little is known about how this dysfunction differs between adult and adolescent MDD patients.

Methods: Voxel-wise meta-analyses of abnormal amygdala resting-state functional connectivity (rsFC) were conducted in adult and adolescent groups separately, followed by a quantitative meta-analytic comparison of the two groups.

Findings: Nineteen studies that included 665 MDD patients (392 adults and 273 adolescents) and 546 controls (341 adults and 205 adolescents) were identified in the current study. Adult-specific abnormal amygdala rsFC in MDD patients compared to that in controls was located mainly within the affective network, including increased connectivity with the right hippocampus/parahippocampus and bilateral ventromedial orbitofrontal cortex and decreased connectivity with the bilateral insula and the left caudate. Adolescent MDD patients specifically demonstrated decreased amygdala rsFC within the cognitive control network encompassing the left dorsolateral prefrontal cortex and imbalanced amygdala rsFC within the default mode network, which was manifested as hyperconnectivity in the right precuneus and hypoconnectivity in the right inferior temporal gyrus. Additionally, direct comparison between the two groups showed that adult patients had strengthened amygdala rsFC with the right hippocampus/parahippocampus as well as the right inferior temporal gyrus and weakened amygdala rsFC with the bilateral insula compared to that in adolescent patients.

Interpretation: Distinct impairments of amygdala-centered rsFC in adult and adolescent patients were related to different network dysfunctions in MDD. Adult-specific amygdala rsFC dysfunction within the affective network presumably reflects emotional dysregulation in MDD, whereas adolescent-specific amygdala rsFC abnormalities in networks involved in cognitive control might reflect the neural basis of affective cognition deficiency that is characteristic of adolescent MDD. FUND: This study was supported by a grant from the National Natural Science Foundation of China (81671669) and by a Sichuan Provincial Youth Grant (2017JQ0001).

Keywords: Adolescents; Adults; Amygdala; Functional connectivity; Major depressive disorder; Meta-analysis.

Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Figures

Fig. 1
Fig. 1
Flowchart of the identification of articles. Abbreviations: ReHo, regional homogeneity; ALFF, amplitude of low-frequency fluctuation; ICA, independent components analysis; fALFF, fractional ALFF; PD, Parkinson's disease.
Fig. 2
Fig. 2
Results of amygdala rsFC meta-analysis for, from top to bottom, adult patients with major depressive disorder (MDD) relative to healthy controls (HC); adolescent patients with MDD relative to HC (red, MDD patients>HC; blue, MDD patientsadolescent patients; green, adult

Fig. 3

Meta-regression results showing that the…

Fig. 3

Meta-regression results showing that the age of adult MDD patients is negatively correlated…

Fig. 3
Meta-regression results showing that the age of adult MDD patients is negatively correlated with the rsFC in the right insula (peak voxel coordinate: 50, 14, −2, r = 0.604, p < 0.0001). In the graphs, the effect sizes needed to create this plot have been extracted from the peak of the maximum slope significance, and each dataset is represented as a dot, whose size reflects the sample size. Large dots indicate samples with 20–40 patients, and small dots represent samples with <20 patients. The regression line (meta-regression signed differential mapping slope) is shown.
Fig. 3
Fig. 3
Meta-regression results showing that the age of adult MDD patients is negatively correlated with the rsFC in the right insula (peak voxel coordinate: 50, 14, −2, r = 0.604, p < 0.0001). In the graphs, the effect sizes needed to create this plot have been extracted from the peak of the maximum slope significance, and each dataset is represented as a dot, whose size reflects the sample size. Large dots indicate samples with 20–40 patients, and small dots represent samples with <20 patients. The regression line (meta-regression signed differential mapping slope) is shown.

References

    1. Smith K. Mental health: a world of depression. Nature. 2014;515(7526):181.
    1. Anthes E. Depression: a change of mind. Nature. 2014;515(7526):185–187.
    1. Morris J.S., Ohman A., Dolan R.J. Conscious and unconscious emotional learning in the human amygdala. Nature. 1998;393(6684):467–470.
    1. Sergerie K., Chochol C., Armony J.L. The role of the amygdala in emotional processing: a quantitative meta-analysis of functional neuroimaging studies. Neurosci Biobehav Rev. 2008;32(4):811–830.
    1. Biswal B., Yetkin F.Z., Haughton V.M., Hyde J.S. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med. 1995;34(4):537–541.
    1. Fox M.D., Snyder A.Z., Vincent J.L., Corbetta M., Van Essen D.C., Raichle M.E. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A. 2005;102(27):9673–9678.
    1. Zhang X., Zhu X., Wang X. First-episode medication-naive major depressive disorder is associated with altered resting brain function in the affective network. PLoS One. 2014;9(1)
    1. Tang Y., Kong L., Wu F. Decreased functional connectivity between the amygdala and the left ventral prefrontal cortex in treatment-naive patients with major depressive disorder: a resting-state functional magnetic resonance imaging study. Psychol Med. 2013;43(9):1921–1927.
    1. Pannekoek J.N., van der Werff S.J.A., Meens P.H.F. Aberrant resting-state functional connectivity in limbic and salience networks in treatment-naïve clinically depressed adolescents. J Child Psychol Psychiatry. 2014;55(12):1317–1327.
    1. Cullen K.R., Westlund M.K., Klimes-Dougan B. Abnormal amygdala resting-state functional connectivity in adolescent depression. JAMA Psychiat. 2014;71(10):1138.
    1. Kim S.M., Park S.Y., Kim Y.I. Affective network and default mode network in depressive adolescents with disruptive behaviors. Neuropsychiatr Dis Treat. 2015:49.
    1. Kerestes R., Davey C.G., Stephanou K., Whittle S., Harrison B.J. Functional brain imaging studies of youth depression: a systematic review. Neuroimage Clin. 2014;4:209–231.
    1. Schmaal L., Hibar D.P., Samann P.G. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA major depressive disorder working group. Mol Psychiatry. 2017;22(6):900–909.
    1. Connolly M.E., Gollan J.K., Cobia D., Wang X. Reduced striatal activation in females with major depression during the processing of affective stimuli. J Psychiatr Res. 2015;68:384–391.
    1. Nixon N.L., Liddle P.F., Worwood G., Liotti M., Nixon E. Prefrontal cortex function in remitted major depressive disorder. Psychol Med. 2013;43(6):1219–1230.
    1. Miller C.H., Hamilton J.P., Sacchet M.D., Gotlib I.H. Meta-analysis of functional neuroimaging of major depressive disorder in youth. JAMA Psychiat. 2015;72(10):1045–1053.
    1. Ramasubbu R., Konduru N., Cortese F., Bray S., Gaxiola-Valdez I., Goodyear B. Reduced intrinsic connectivity of amygdala in adults with major depressive disorder. Front Psych. 2014;5:17.
    1. Ye J., Shen Z., Xu X. Abnormal functional connectivity of the amygdala in first-episode and untreated adult major depressive disorder patients with different ages of onset. Neuroreport. 2017;28(4):214–221.
    1. Fox P.T., Lancaster J.L., Laird A.R., Eickhoff S.B. Meta-analysis in human neuroimaging: computational modeling of large-scale databases. Annu Rev Neurosci. 2014;37:409–434.
    1. Müller V.I., Cieslik E.C., Laird A.R. Ten simple rules for neuroimaging meta-analysis. Neurosci Biobehav Rev. 2018;84:151–161.
    1. Radua J., Mataix-Cols D. Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. Br J Psychiatry. 2009;195(5):393–402.
    1. Radua J., Romeo M., Mataix-Cols D., Fusar-Poli P. A general approach for combining voxel-based meta-analyses conducted in different neuroimaging modalities. Curr Med Chem. 2013;20(3):462–466.
    1. Knobloch K., Yoon U., Vogt P.M. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement and publication bias. J Craniomaxillofac Surg. 2011;39(2):91–92.
    1. Cipriani A., Zhou X., Del Giovane C. Comparative efficacy and tolerability of antidepressants for major depressive disorder in children and adolescents: a network meta-analysis. Lancet. 2016;388:881–890.
    1. Radua J., Mataix-Cols D., Phillips M.L. A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps. Eur Psychiatry. 2012;27(8):605–611.
    1. Radua J., Rubia K., Canales E., Pomarol-Clotet E., Fusar-Poli P., Mataix-Cols D. Anisotropic kernels for coordinate-based meta-analyses of neuroimaging studies. Front Psych. 2014;5(13)
    1. Radua J., van den Heuvel O.A., Surguladze S., Mataix-Cols D. Meta-analytical comparison of voxel-based morphometry studies in obsessive-compulsive disorder vs other anxiety disorders. Arch Gen Psychiatry. 2010;67(7):701–711.
    1. Sterne Jonathan A.C., Egger Matthias. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol. 2001;54(10):1046–1055.
    1. Kaiser R.H., Andrews-Hanna J.R., Wager T.D., Pizzagalli D.A. Large-scale network dysfunction in major depressive disorder: a meta-analysis of resting-state functional connectivity. JAMA Psychiat. 2015;72(6):603–611.
    1. Anand A., Li Y., Wang Y. Activity and connectivity of brain mood regulating circuit in depression: a functional magnetic resonance study. Biol Psychiatry. 2005;57(10):1079–1088.
    1. Mayberg H.S. Limbic-cortical dysregulation: a proposed model of depression. J Neuropsychiatry Clin Neurosci. 1997;9(3):471–481.
    1. Tye K.M., Mirzabekov J.J., Warden M.R. Dopamine neurons modulate neural encoding and expression of depression-related behaviour. Nature. 2013;493(7433):537–541.
    1. Wager T.D., Davidson M.L., Hughes B.L., Lindquist M.A., Ochsner K.N. Prefrontal-subcortical pathways mediating successful emotion regulation. Neuron. 2008;59(6):1037–1050.
    1. Tye K.M., Stuber G.D., de Ridder B., Bonci A., Janak P.H. Rapid strengthening of thalamo-amygdala synapses mediates cue-reward learning. Nature. 2008;453(7199):1253–1257.
    1. Siegle G.J., Steinhauer S.R., Thase M.E., Stenger V.A., Carter C.S. Can't shake that feeling: event-related fMRI assessment of sustained amygdala activity in response to emotional information in depressed individuals. Biol Psychol. 2002;51(9):693–707.
    1. Johnstone T., van Reekum C.M., Urry H.L., Kalin N.H., Davidson R.J. Failure to regulate: counterproductive recruitment of top-down prefrontal-subcortical circuitry in major depression. J Neurosci. 2007;27(33):8877–8884.
    1. Janak P.H., Tye K.M. From circuits to behaviour in the amygdala. Nature. 2015;517(7534):284–292.
    1. Tahmasian M., Knight D.C., Manoliu A. Aberrant intrinsic connectivity of hippocampus and amygdala overlap in the fronto-insular and dorsomedial-prefrontal cortex in major depressive disorder. Front Hum Neurosci. 2013;7:639.
    1. Labar K.S., Cabeza R. Cognitive neuroscience of emotional memory. Nat Rev Neurosci. 2006;7(1):54–64.
    1. Hamilton J.P., Gotlib I.H. Neural substrates of increased memory sensitivity for negative stimuli in major depression. Biol Psychol. 2008;63(12):1155–1162.
    1. Veer I.M., Beckmann C.F., van Tol M.J. Whole brain resting-state analysis reveals decreased functional connectivity in major depression. Front Syst Neurosci. 2010;4
    1. Seeley W.W., Menon V., Schatzberg A.F. Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007;27(9):2349–2356.
    1. Kjaer T.W., Nowak M., Lou H.C. Reflective self-awareness and conscious states: PET evidence for a common midline parietofrontal core. Neuroimage. 2002;17(2):1080–1086.
    1. Ochsner K.N., Ray R.R., Hughes B. Bottom-up and top-down processes in emotion generation: common and distinct neural mechanisms. Psychol Sci. 2009;20(11):1322–1331.
    1. Ochsner K.N., Gross J.J. The cognitive control of emotion. Trends Cogn Sci. 2005;9(5):242–249.
    1. Mathews A., MacLeod C. Cognitive vulnerability to emotional disorders. Annu Rev Clin Psychol. 2005;1:167–195.
    1. Quevedo K., Ng R., Scott H. The neurobiology of self-face recognition in depressed adolescents with low or high suicidality. J Abnorm Psychol. 2016;125(8):1185–1200.
    1. Ho T.C., Zhang S., Sacchet M.D. Fusiform gyrus dysfunction is associated with perceptual processing efficiency to emotional faces in adolescent depression: a model-based approach. Front Psych. 2016;7:40.
    1. Cooney R.E., Joormann J., Eugène F., Dennis E.L., Gotlib I.H. Neural correlates of rumination in depression. Cogn Affect Behav Neurosci. 2010;10(4):470–478.
    1. Goulden N., McKie S., Thomas E.J. Reversed frontotemporal connectivity during emotional face processing in remitted depression. Biol Psychol. 2012;72(7):604–611.
    1. Ramezani M., Johnsrude I., Rasoulian A. Temporal-lobe morphology differs between healthy adolescents and those with early-onset of depression. NeuroImage. 2014;6:145–155.
    1. Gogtay N., Giedd J.N., Lusk L. Dynamic mapping of human cortical development during childhood through early adulthood. Proc Natl Acad Sci U S A. 2004;101(21):8174.
    1. Allott K., Fisher C.A., Amminger G.P., Goodall J., Hetrick S. Characterizing neurocognitive impairment in young people with major depression: state, trait, or scar? Brain Behav. 2016;6(10)
    1. Glass R.M. Fluoxetine, cognitive-behavioral therapy, and their combination for adolescents with depression: Treatment for Adolescents with Depression Study (TADS) randomized controlled trial. J Pediatr. 2005;146(1):145.
    1. NICE Depression in children and young people. Clin Guidel. 2015;28:1–271.
    1. Gabard-Durnam L.J., Flannery J., Goff B. The development of human amygdala functional connectivity at rest from 4 to 23 years: a cross-sectional study. Neuroimage. 2014;95:193–207.
    1. Lopez J.F., Chalmers D.T., Little K.Y., Watson S.J., A.E. Bennett Research Award Regulation of serotonin1A, glucocorticoid, and mineralocorticoid receptor in rat and human hippocampus: implications for the neurobiology of depression. Biol Psychol. 1998;43:547–573.
    1. March J., Silva S., Petrycki S., Curry J., Wells K., Fairbank J. Fluoxetine, cognitive-behavioral therapy, and their combination for adolescents with depression: Treatment for Adolescents with Depression Study (TADS) randomized controlled trial. JAMA. 2004;292:807–820.
    1. Baas D., Aleman A., Kahn R.S. Lateralization of amygdala activation: a systematic review of functional neuroimaging studies. Brain Res Brain Res Rev. 2004;45(2):96–103.
    1. Wager T.D., Phan K.L., Liberzon I., Taylor S.F. Valence, gender, and lateralization of functional brain anatomy in emotion: a meta-analysis of findings from neuroimaging. Neuroimage. 2003;19(3):513–531.
    1. Vasa R.A., Pine D.S., Thorn J.M. Enhanced right amygdala activity in adolescents during encoding of positively valenced pictures. Dev Cogn Neurosci. 2011;1(1):88–99.
    1. Ma Y. Neuropsychological mechanism underlying antidepressant effect: a systematic meta-analysis. Mol Psychiatry. 2015;20(3):311–319.
    1. Peters A.T., Burkhouse K., Feldhaus C.C., Langenecker S.A., Jacobs R.H. Aberrant resting-state functional connectivity in limbic and cognitive control networks relates to depressive rumination and mindfulness: a pilot study among adolescents with a history of depression. J Affect Disord. 2016;200:178–181.
    1. Chattopadhyay S., Tait R., Simas T. Cognitive behavioral therapy lowers elevated functional connectivity in depressed adolescents. EBioMedicine. 2017;17:216–222.
    1. Connolly C.G., Ho T.C., Blom E.H. Resting-state functional connectivity of the amygdala and longitudinal changes in depression severity in adolescent depression. J Affect Disord. 2017;207:86–94.
    1. Cullen K.R., Gee D.G., Klimes-Dougan B. A preliminary study of functional connectivity in comorbid adolescent depression. Neurosci Lett. 2009;460(3):227–231.
    1. Straub J., Metzger C.D., Plener P.L., Koelch M.G., Groen G., Abler B. Successful group psychotherapy of depression in adolescents alters fronto-limbic resting-state connectivity. J Affect Disord. 2017;209:135–139.
    1. Jacobs R.H., Barba A., Gowins J.R. Decoupling of the amygdala to other salience network regions in adolescent-onset recurrent major depressive disorder. Psychol Med. 2016;46(5):1055–1067.
    1. Altinay M., Karne H., Beall E., Anand A. Quetiapine extended release open-label treatment associated changes in amygdala activation and connectivity in anxious depression an fMRI study. J Clin Psychopharmacol. 2016;36(6):562–571.
    1. Deligiannidis K.M., Sikoglu E.M., Shaffer S.A. GABAergic neuroactive steroids and resting-state functional connectivity in postpartum depression: a preliminary study. J Psychiatr Res. 2013;47(6):816–828.
    1. Lui S., Wu Q., Qiu L. Resting-state functional connectivity in treatment-resistant depression. Am J Psychiatry. 2011;168(6):642–648.
    1. Wang Y.L., Yang S.Z., Sun W.L., Shi Y.Z., Duan H.F. Altered functional interaction hub between affective network and cognitive control network in patients with major depressive disorder. Behav Brain Res. 2016;298(Pt B):301–309.
    1. Yang J., Yin Y., Svob C. Amygdala Atrophy and Its Functional Disconnection with the Cortico-Striatal-Pallidal-Thalamic Circuit in Major Depressive Disorder in Females. PloS one. 2017;12(1):e0168239.

Source: PubMed

Sponsoren und Mitarbeiter

Krankheiten

Drogeninterventionen

3
Abonnieren