Reward- and threat-related neural function associated with risk and presence of depression in adolescents: a study using a composite risk score in Brazil.
Depression
adolescence
functional MRI (fMRI)
risk factors
Journal
Journal of child psychology and psychiatry, and allied disciplines
ISSN: 1469-7610
Titre abrégé: J Child Psychol Psychiatry
Pays: England
ID NLM: 0375361
Informations de publication
Date de publication:
05 2022
05 2022
Historique:
accepted:
22
06
2021
pubmed:
8
8
2021
medline:
23
4
2022
entrez:
7
8
2021
Statut:
ppublish
Résumé
Neuroimaging studies on adolescents at risk for depression have relied on a single risk factor and focused on adolescents in high-income countries. Using a composite risk score, this study aims to examine neural activity and connectivity associated with risk and presence of depression in adolescents in Brazil. Depression risk was defined with the Identifying Depression Early in Adolescence Risk Score (IDEA-RS), calculated using a prognostic model that included 11 socio-demographic risk factors. Adolescents recruited from schools in Porto Alegre were classified into a low-risk (i.e., low IDEA-RS and no lifetime depression), high-risk (i.e., high IDEA-RS and no lifetime depression), or clinically depressed group (i.e., high IDEA-RS and depression diagnosis). One hundred fifty adolescents underwent a functional MRI scan while completing a reward-related gambling and a threat-related face-matching task. We compared group differences in activity and connectivity of the ventral striatum (VS) and amygdala during the gambling and face-matching tasks, respectively, and group differences in whole-brain neural activity. Although there was no group difference in reward-related VS or threat-related amygdala activity, the depressed group showed elevated VS activity to punishment relative to high-risk adolescents. The whole-brain analysis found reduced reward-related activity in the lateral prefrontal cortex of patients and high-risk adolescents compared with low-risk adolescents. Compared with low-risk adolescents, high-risk and depressed adolescents showed reduced threat-related left amygdala connectivity with thalamus, superior temporal gyrus, inferior parietal gyrus, precentral gyrus, and supplementary motor area. We identified neural correlates associated with risk and presence of depression in a well-characterized sample of adolescents. These findings enhance knowledge of the neurobiological underpinnings of risk and presence of depression in Brazil. Future longitudinal studies are needed to examine whether the observed neural patterns of high-risk adolescents predict the development of depression.
Sections du résumé
BACKGROUND
Neuroimaging studies on adolescents at risk for depression have relied on a single risk factor and focused on adolescents in high-income countries. Using a composite risk score, this study aims to examine neural activity and connectivity associated with risk and presence of depression in adolescents in Brazil.
METHODS
Depression risk was defined with the Identifying Depression Early in Adolescence Risk Score (IDEA-RS), calculated using a prognostic model that included 11 socio-demographic risk factors. Adolescents recruited from schools in Porto Alegre were classified into a low-risk (i.e., low IDEA-RS and no lifetime depression), high-risk (i.e., high IDEA-RS and no lifetime depression), or clinically depressed group (i.e., high IDEA-RS and depression diagnosis). One hundred fifty adolescents underwent a functional MRI scan while completing a reward-related gambling and a threat-related face-matching task. We compared group differences in activity and connectivity of the ventral striatum (VS) and amygdala during the gambling and face-matching tasks, respectively, and group differences in whole-brain neural activity.
RESULTS
Although there was no group difference in reward-related VS or threat-related amygdala activity, the depressed group showed elevated VS activity to punishment relative to high-risk adolescents. The whole-brain analysis found reduced reward-related activity in the lateral prefrontal cortex of patients and high-risk adolescents compared with low-risk adolescents. Compared with low-risk adolescents, high-risk and depressed adolescents showed reduced threat-related left amygdala connectivity with thalamus, superior temporal gyrus, inferior parietal gyrus, precentral gyrus, and supplementary motor area.
CONCLUSIONS
We identified neural correlates associated with risk and presence of depression in a well-characterized sample of adolescents. These findings enhance knowledge of the neurobiological underpinnings of risk and presence of depression in Brazil. Future longitudinal studies are needed to examine whether the observed neural patterns of high-risk adolescents predict the development of depression.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
579-590Subventions
Organisme : National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London
Organisme : Maudsley NHS Foundation Trust and King's College London
Organisme : UK Medical Research Council
ID : MC_PC_MR/R019460/1
Organisme : MQ
ID : MQBF/1 IDEA
Organisme : Conselho Nacional de Desenvolvimento Científico e Tecnológico
ID : 445828/2014-5
Organisme : Conselho Nacional de Desenvolvimento Científico e Tecnológico
ID : 477129/2012-9
Organisme : Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul
ID : 17/2551-0001009-4
Organisme : Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
ID : 62/2014
Organisme : Academy of Medical Sciences
ID : GCRFNG\100281
Pays : United Kingdom
Informations de copyright
© 2021 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.
Références
Andersen, S.L., & Teicher, M.H. (2008). Stress, sensitive periods and maturational events in adolescent depression. Trends in Neurosciences, 31, 183-191.
Barch, D.M., Burgess, G.C., Harms, M.P., Petersen, S.E., Schlaggar, B.L., Corbetta, M., … & Van Essen, D.C. (2013). Function in the human connectome: Task-fMRI and individual differences in behavior. NeuroImage, 80, 169-189.
Bartra, O., Mcguire, J.T., & Kable, J.W. (2013). The valuation system: A coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value. NeuroImage, 76, 412-427.
Battel, L., Cunegatto, F., Viduani, A., Fisher, H.L., Kohrt, B.A., Mondelli, V., … & Kieling, C. (2021). Mind the brain gap: The worldwide distribution of neuroimaging research on adolescent depression. NeuroImage, 231, 117865.
Caye, A., Kieling, R.R., Rocha, T.B., Graeff-Martins, A.S., Geyer, C., Krieger, F., … & Kieling, C. (2017). Schedule for Affective Disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL), DSM-5 update: Translation into Brazilian Portuguese. Brazilian Journal of Psychiatry, 39, 384-386.
Davidow, J.Y., Insel, C., & Somerville, L.H. (2018). Adolescent development of value-guided goal pursuit. Trends in Cognitive Sciences, 22, 725-736.
Dixon, M.L., & Christoff, K. (2014). The lateral prefrontal cortex and complex value-based learning and decision making. Neuroscience and Biobehavioral Reviews, 45, 9-18.
Erskine, H., Moffitt, T.E., Copeland, W., Costello, E., Ferrari, A., Patton, G., … & Scott, J. (2015). A heavy burden on young minds: the global burden of mental and substance use disorders in children and youth. Psychological Medicine, 45, 1551-1563.
Etkin, A., Egner, T., & Kalisch, R. (2011). Emotional processing in anterior cingulate and medial prefrontal cortex. Trends in Cognitive Sciences, 15, 85-93.
Feczko, E., Miranda-Dominguez, O., Marr, M., Graham, A.M., Nigg, J.T., & Fair, D.A. (2019). The heterogeneity problem: Approaches to identify psychiatric subtypes. Trends in Cognitive Sciences, 23, 584-601.
Fischer, A.S., Camacho, M.C., Ho, T.C., Whitfield-Gabrieli, S., & Gotlib, I.H. (2018). Neural markers of resilience in adolescent females at familial risk for major depressive disorder. JAMA Psychiatry, 75, 493-502.
Haber, S.N., & Knutson, B. (2010). The reward circuit: Linking primate anatomy and human imaging. Neuropsychopharmacology, 35, 4-26.
Hanson, J.L., Knodt, A.R., Brigidi, B.D., & Hariri, A.R. (2018). Heightened connectivity between the ventral striatum and medial prefrontal cortex as a biomarker for stress-related psychopathology: understanding interactive effects of early and more recent stress. Psychological Medicine, 48, 1835-1843.
Hardin, M.G., Schroth, E., Pine, D.S., & Ernst, M. (2007). Incentive-related modulation of cognitive control in healthy, anxious, and depressed adolescents: Development and psychopathology related differences. Journal of Child Psychology and Psychiatry, 48, 446-454.
Hariri, A.R., Brown, S.M., Williamson, D.E., Flory, J.D., De Wit, H., & Manuck, S.B. (2006). Preference for immediate over delayed rewards is associated with magnitude of ventral striatal activity. Journal of Neuroscience, 26, 13213-13217.
IBGE. (2018). Pesquisa Nacional por Amostra de Domicílios. Educação, 2018. Retrieved May 17, 2021, from: https://biblioteca.IBGE.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=2101657.
Janak, P.H., & Tye, K.M. (2015). From circuits to behaviour in the amygdala. Nature, 517(7534), 284-292. https://doi.org/10.1038/nature14188.
Jimura, K., Locke, H.S., & Braver, T.S. (2010). Prefrontal cortex mediation of cognitive enhancement in rewarding motivational contexts. Proceedings of the National Academy of Sciences, 107, 8871-8876.
Kaiser, R.H., Andrews-Hanna, J.R., Wager, T.D., & Pizzagalli, D.A. (2015). Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity. JAMA Psychiatry, 72, 603-611.
Keedwell, P.A., Andrew, C., Williams, S.C., Brammer, M.J., & Phillips, M.L. (2005). The neural correlates of anhedonia in major depressive disorder. Biological Psychiatry, 58(11), 843-853. https://doi.org/10.1016/j.biopsych.2005.05.019.
Kieling, C., Buchweitz, C., Caye, A., Manfro, P., Pereira, R., Viduani, A., … & Mondelli, V. (2021). The Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo): rationale, methods, and baseline characteristics. Frontiers in Psychiatry, 12, Article 697144.
Luking, K.R., Pagliaccio, D., Luby, J.L., & Barch, D.M. (2016). Reward processing and risk for depression across development. Trends in Cognitive Sciences, 20, 456-468.
Manica, A., Prugnolle, F., & Balloux, F. (2005). Geography is a better determinant of human genetic differentiation than ethnicity. Human Genetics, 118, 366-371.
Mclaren, D.G., Ries, M.L., Xu, G., & Johnson, S.C. (2012). A generalized form of context-dependent psychophysiological interactions (gPPI): A comparison to standard approaches. NeuroImage, 61, 1277-1286.
Mel’nikov, M.E., Petrovskii, E.D., Bezmaternykh, D.D., Kozlova, L.I., Shtark, M.B., Savelov, A.A., … & Natarova, K.A. (2018). fMRI response of parietal brain areas to sad facial stimuli in mild depression. Bulletin of Experimental Biology and Medicine, 165(6), 741-745. https://doi.org/10.1007/s10517-018-4255-y.
Morgan, J.K., Shaw, D.S., Olino, T.M., Musselman, S.C., Kurapati, N.T., & Forbes, E.E. (2016). History of depression and frontostriatal connectivity during reward processing in late adolescent boys. Journal of Clinical Child and Adolescent Psychology, 45(1), 59-68. https://doi.org/10.1080/15374416.2015.1030753.
Murray, J., Cerqueira, D.R.C., & Kahn, T. (2013). Crime and violence in Brazil: Systematic review of time trends, prevalence rates and risk factors. Aggression and Violent Behavior, 18(5), 471-483. https://doi.org/10.1016/j.avb.2013.07.003.
Ochsner, K.N., Silvers, J.A., & Buhle, J.T. (2012). Functional imaging studies of emotion regulation: A synthetic review and evolving model of the cognitive control of emotion. Annals of the New York Academy of Sciences, 1251, E1-E24.
Oldham, S., Murawski, C., Fornito, A., Youssef, G., Yücel, M., & Lorenzetti, V. (2018). The anticipation and outcome phases of reward and loss processing: A neuroimaging meta-analysis of the monetary incentive delay task. Human Brain Mapping, 39, 3398-3418.
Olson, E.A., Kaiser, R.H., Pizzagalli, D.A., Rauch, S.L., & Rosso, I.M. (2018). Anhedonia in trauma-exposed individuals: functional connectivity and decision-making correlates. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 3, 959-967.
Penzo, M.A., Robert, V., Tucciarone, J., De Bundel, D., Wang, M., Van Aelst, L., … & Li, B.O. (2015). The paraventricular thalamus controls a central amygdala fear circuit. Nature, 519, 455-459.
Redlich, R., Opel, N., Bürger, C., Dohm, K., Grotegerd, D., Förster, K., … & Dannlowski, U. (2018). The limbic system in youth depression: Brain structural and functional alterations in adolescent in-patients with severe depression. Neuropsychopharmacology, 43, 546-554.
Rizzo, G., Milardi, D., Bertino, S., Basile, G.A., Di Mauro, D., Calamuneri, A., … & Cacciola, A. (2018). The limbic and sensorimotor pathways of the human amygdala: A structural connectivity study. Neuroscience, 385, 166-180.
Rocha, T.-B.-M., Fisher, H.L., Caye, A., Anselmi, L., Arseneault, L., Barros, F.C., … & Kieling, C. (2021). Identifying adolescents at risk for depression: A prediction score performance in cohorts based in three different continents. Journal of the American Academy of Child and Adolescent Psychiatry, 60(2), 262-273. https://doi.org/10.1016/j.jaac.2019.12.004.
Rolls, E.T., Huang, C.-C., Lin, C.-P., Feng, J., & Joliot, M. (2020). Automated anatomical labelling atlas 3. NeuroImage, 206, 116189.
Rosa, M., Metcalf, E., Rocha, T.-B.-M., & Kieling, C. (2018). Translation and cross-cultural adaptation into Brazilian portuguese of the mood and feelings questionnaire (MFQ)-long version. Trends in Psychiatry and Psychotherapy, 40, 72-78.
Swartz, J.R., Williamson, D.E., & Hariri, A.R. (2015). Developmental change in amygdala reactivity during adolescence: effects of family history of depression and stressful life events. American Journal of Psychiatry, 172, 276-283.
Toenders, Y.J., Van Velzen, L.S., Heideman, I.Z., Harrison, B.J., Davey, C.G., & Schmaal, L. (2019). Neuroimaging predictors of onset and course of MDD in childhood and adolescence: a systematic review of longitudinal studies. Developmental Cognitive Neuroscience, 39, 100700.
Toschi, N., Duggento, A., & Passamonti, L. (2017). Functional connectivity in amygdalar-sensory/(pre) motor networks at rest: new evidence from the Human Connectome Project. European Journal of Neuroscience, 45, 1224-1229.
Ubl, B., Kuehner, C., Kirsch, P., Ruttorf, M., Diener, C., & Flor, H. (2015). Altered neural reward and loss processing and prediction error signalling in depression. Social Cognitive and Affective Neuroscience, 10, 1102-1112.
Vijayakumar, N., Allen, N.B., Dennison, M., Byrne, M.L., Simmons, J.G., & Whittle, S. (2017). Cortico-amygdalar maturational coupling is associated with depressive symptom trajectories during adolescence. NeuroImage, 156, 403-411.
Wackerhagen, C., Wüstenberg, T., Mohnke, S., Erk, S., Veer, I.M., Kruschwitz, J.D., … & Romanczuk-Seiferth, N. (2017). Influence of familial risk for depression on cortico-limbic connectivity during implicit emotional processing. Neuropsychopharmacology, 42, 1729-1738.
Wang, L., Labar, K.S., & Mccarthy, G. (2006). Mood alters amygdala activation to sad distractors during an attentional task. Biological Psychiatry, 60, 1139-1146.
Wolf, R.C., & Herringa, R.J. (2016). Prefrontal-amygdala dysregulation to threat in pediatric posttraumatic stress disorder. Neuropsychopharmacology, 41(3), 822-831. https://doi.org/10.1038/npp.2015.209.
Zaki, J., Hennigan, K., Weber, J., & Ochsner, K.N. (2010). Social cognitive conflict resolution: contributions of domain-general and domain-specific neural systems. Journal of Neuroscience, 30, 8481-8488.