Addressing heterogeneity (and homogeneity) in treatment mechanisms in depression and the potential to develop diagnostic and predictive biomarkers

Article

Fu, C., Fan, Y. and Davatzikos, C. 2019. Addressing heterogeneity (and homogeneity) in treatment mechanisms in depression and the potential to develop diagnostic and predictive biomarkers. NeuroImage: Clinical. 24 (Art.101997). https://doi.org/10.1016/j.nicl.2019.101997
AuthorsFu, C., Fan, Y. and Davatzikos, C.
Abstract

It has been 10 years since machine learning was first applied to neuroimaging data in psychiatric disorders to identify diagnostic and prognostic markers at the level of the individual. Proof of concept findings in major depression have since been extended in international samples and are beginning to include hundreds of samples from multisite data. Neuroimaging provides the unique capability to detect an acute depressive state in major depression, while we would not expect perfect classification with current diagnostic criteria which are based solely on clinical features. We review developments and the potential impact of heterogeneity, as well as homogeneity, on classification for diagnosis and prediction of clinical outcome. It is likely that there are distinct biotypes which comprise the disorder and which predict clinical outcome. Neuroimaging-based biotypes could aid in identifying the illness in individuals who are unable to recognise their illness and perhaps to identify the treatment resistant form early in the course of the illness. We propose that heterogeneous symptom profiles can arise from a limited number of neural biotypes and that apparently heterogeneous clinical outcomes include a common baseline predictor and common mechanism of treatment. Baseline predictors of clinical outcome reflect factors which indicate the general likelihood of response as well as those which are selective for a particular form of treatment. Irrespective of the mechanism, the capacity for response will moderate the outcome, which includes inherent models of interpersonal relationships that could be associated with genetic risk load and represented by patterns of functional and structural neural correlates as a predictive biomarker. We propose that methods which directly address heterogeneity are essential and that a synergistic combination could bring together data-driven inductive and symptom-based deductive approaches. Through this iterative process, major depression can develop from being syndrome characterized by a collection of symptoms to a disease with an identifiable pathophysiology.

JournalNeuroImage: Clinical
Journal citation24 (Art.101997)
ISSN2213-1582
Year2019
PublisherElsevier
Accepted author manuscript
License
File Access Level
Repository staff only
Publisher's version
License
File Access Level
Anyone
Digital Object Identifier (DOI)https://doi.org/10.1016/j.nicl.2019.101997
Web address (URL)https://doi.org/10.1016/j.nicl.2019.101997
Publication dates
Online28 Aug 2019
Publication process dates
Accepted27 Aug 2019
Deposited05 Sep 2019
FunderNational Institutes of Health
Medical Research Council
Copyright holder© 2019 The Authors
Permalink -

https://repository.uel.ac.uk/item/86zy6

Log in to edit

Download files

Publisher's version
1-s2.0-S221315821930347X-main.pdf
License: CC BY-NC-ND 4.0
File access level: Anyone

  • 232
    total views
  • 128
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Home-based transcranial direct current stimulation treatment for major depressive disorder: a fully remote phase 2 randomized sham-controlled trial
Woodham, R., Selvaraj, S., Lajmi, N., Hobday, H., Sheehan, G., Ghazi-Noori, A., Lagerberg, P., Rizvi, M., Kwon, S. S., Orhii, P., Maislin, D., Hernandez, L., Machado-Vieira, R., Soares, J. C., Young, A. H. and Fu, C. 2024. Home-based transcranial direct current stimulation treatment for major depressive disorder: a fully remote phase 2 randomized sham-controlled trial. Nature Medicine. p. In Press.
Enhanced network synchronization connectivity following transcranial direct current stimulation (tDCS) in bipolar depression: Effects on EEG oscillations and deep learning-based predictors of clinical remission
Xiao, W., Moncy, J. C., Ghazi-Noori, A., Woodham, R., Rezaei, H., Bramon, E., Ritter, P., Bauer, M., Young, A. H. and Fu, C. 2024. Enhanced network synchronization connectivity following transcranial direct current stimulation (tDCS) in bipolar depression: Effects on EEG oscillations and deep learning-based predictors of clinical remission. Journal of Affective Disorders. p. In Press. https://doi.org/10.1016/j.jad.2024.09.054
Home-based transcranial direct current stimulation in bipolar depression: an open-label treatment study of clinical outcomes, acceptability and adverse events
Ghazi-Noori, A., Woodham, R., Rezaei, H., Sharif, S., Bramon, E., Ritter, P., Bauer, M., Young, A. H. and Fu, C. H. Y. 2024. Home-based transcranial direct current stimulation in bipolar depression: an open-label treatment study of clinical outcomes, acceptability and adverse events. International Journal of Bipolar Disorders. 12 (Art. 30). https://doi.org/10.1186/s40345-024-00352-9
Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures
Belov, V., Erwin-Grabner, T., Aghajani, M., Aleman, A., Amod, A. R., Basgoze, Z., Benedetti, F., Besteher, B., Bülow, R., Ching, C. R. K., Connolly, C. G., Cullen, K., Davey, C. G., Dima, D., Dols, A., Evans, J. W., Fu, C. H. Y., Saffet Gonul, A., Gotlib, I. H., Grabe, H. J., Groenewold, N., Paul Hamilton, J. Harrison, B. J., Ho. T. C., Mwangi, B., Jaworska, N., Jahanshad, N., Klimes-Dougan, B., Koopowitz, S-M., Lancaster, T., Li, M., Linden, D. E. J., MacMaster, F. P., Mehler, D. M. A., Melloni, E., Mueller, B. A., Ojha, A., Oudega, M. L., Penninx, B. W. J. H., Poletti, S., Pomarol-Clotet, E., Portella, M. J., Pozzi, E., Reneman, L. Sacchet, M. D., Sämann, P. G., Schrantee, A., Sim, K., Soares, J. C., Stein, D. J., Thomopoulos, S. I., Uyar-Demir, A., van der Wee, N. J. A., van der Werff, S. J. A., Völzke, H., Whittle, S., Wittfield, K., Wright, M. J., Wu, M-J., Yang, T. T., Zarate, C., Veltman, D. J., Schmaal, L., Thompson, P. M., Goya-Maldonado, R. and the ENIGMA Major Depressive Disorder working group 2024. Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures. Scientific Reports. 14 (Art. 1084). https://doi.org/10.1038/s41598-023-47934-8
The Human Affectome
Schiller, D., Yu, A. N. C., Nelly, A-K., Becker, S., Cromwell, H. C., Dolcos, F., Eslinger, P. J., Frewen, P., Kemp, A. H., Pace-Schott, E. F., Raber, J., Silton, R. L., Stefanova, E., Williams, J. H. G., Abe, N., Aghajani, M., Albrecht, F., Alexander, R., Anders, S., Aragón, O. R., Arias, J. A., Arzy, S., Aue, T., Baez, S., Balconi, M., Ballarini, T., Bannister, S., Banta, M. C., Caplovitz Barrett, K., Belzung, C., Bensafi, M., Booij, L., Bookwala, J., Boulanger-Bertolus, J., Weber Boutros, S., Bräscher, A-K., Bruno, A., Busatta, G., Bylsma, L. M., Caldwell-Harris, C., Chan, R. C. K., Cherbuin, N., Chiarella, J., Cipresso, P., Critchley, H., Croote, D. E., Demaree, H. A., Denson, T. A., Depue, B., Derntl, B., Dickson, J. M., Dolcos, S., Drach-Zahavy, A., Dubljević, O., Eerola, T., Ellingsen, D-M., Fairfield, B., Ferdenzi, C., Friedman, B. H., Fu, C. H. Y., Gatt. J. M., deGalder, B., Gendolla, G. H. E., Gilman, G., Goldblatt, H., Kotynski Gooding, A. E., Gosseries, O., Hamm, A. O., Hanson, J. L., Hendler, T., Herbert, C., Hofmann, S. G., Ibanez, A., Joffily, M., Jovanovic, T., Kahrilas, I. J., Kangas, M., Katsumi, Y., Kensinger, E., Kirby, L. A. J., Koncz, R., Koster, E. H. W., Kozlowska, K., Krach, S., Kret, M. E., Krippl, M., Kusi-Mensah, K., Ladouceur, C. D., Laureys, S., Lawrence, A., Li, C-S. R., Liddell, B. J., Lidhar, N. K., Lowry, C. A., Magee, K., Marin, M-F., Mariotti, V., Martin, L. J., Marusak, H. A., Mayer, A. V., Merner, A. R., Minnier, J., Moll, J., Morrison, R. G., Moore, M., Mouly, A-M., Mueller, S. C., Mühlberger, A., Murphy, N. A., Muscatello, M. R. A., Musser, E. D., Newton, T. L., Noll-Hussong, M., Norrholm, S. D., Northoff, G., Nusslock, R., Okon-Singer, H., Olino, T. M., Ortner, C., Owolabi, M., Padulo, C., Palermo, R., Palumbo, R., Palumbo, S., Papadelis, C., Pegna, A. J., Pellegrini, S., Peltonen, K., Penninx, B. W. J. H., Pietrini, P., Pinna, G., Pintos Lobo, R., Polnaszek, K. L., Polyakova, M., Rabinak, C., HeleneRichter, S., Richter, T., Riva, G., Rizzo, A., Robinson, J. L., Rosa, P., Sachdev, P. S., Sato, W., Schroeter, M. L., Schweizer, S., Shiban, Y., Siddharthan, A., Siedlecka, E., Smith, R. C., Soreq, H., Spangler, D. P., Stern, E. R., Styliadis, C., Sullivan, G. B., Swain, J. E., Urben, S., Van den Stock, J., vander Kooij, M. A., van Overveld, M., Van Rheenen, T. E., VanElzakker, M. B., Ventura-Bort, C., Verona, E., Volk, T., Wang, Y., Weingast, L. T., Weymar, M., Williams, C., Willis, M. L., Yamashita, P., Zahn, R., Zupan, B., Lowe, L., Gan, G., Huggins, C. F. and Loeffler, L. 2024. The Human Affectome. Neuroscience & Biobehavioral Reviews. 158 (Art. 105450). https://doi.org/10.1016/j.neubiorev.2023.105450
Acceptability of home-based transcranial direct current stimulation (tDCS) in major depression: a qualitative analysis of individual experiences
Rimmer, R. M., Woodham, R. D., Cahill, S. and Fu, C. 2024. Acceptability of home-based transcranial direct current stimulation (tDCS) in major depression: a qualitative analysis of individual experiences. Mental Health Review Journal. 29 (1), pp. 79-91. https://doi.org/10.1108/MHRJ-07-2022-0050
Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo
Fu, C. H. Y., Antoniades, M., Erus, G., Garcia, J. A., Fan, Y., Arnone, D., Arnott, S. R., Chen, T., Choi, K. S., Chin Fatt, C., Frey, N. B., Frokjaer, V. G., Ganz, M., Godlewska, B. R., Hassel, S., Ho, K., McIntosh, A. M., Qin, K., Rotzinger, S., Sacchet, M. D., Savitz, J., Shou, H., Singh, A., Stolicyn, A., Strigo, I., Strother, S. C., Tosun, D., Victor, T. A., Wei, D., Wise, T., Zahn, R., Anderson, I. M., Craighead, W. E., Deakin, J. F. W., Dunlop, B. W., Elliott, R., Gon, Q., Gotlib, I. H., Harmer, C. J., Kennedy, S. H., Knudsen, G. M., Mayberg, H. S., Paulus, M. P., Qiu, J., Trivedi, M. H., Whalley, H. C., Yan, G-C., Young, A. H. and Davatzikos, C. 2023. Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo. Nature Mental Health. 2, pp. 164-176. https://doi.org/10.1038/s44220-023-00187-w
Employing Machine Learning Algorithms to Detect Stress with a Specific Emphasis on Commuting Methods
Sharif, S., Theeng Tamang, M., Fu, C. and Elmedany, W. 2023. Employing Machine Learning Algorithms to Detect Stress with a Specific Emphasis on Commuting Methods. FiCloud 2023: The 10th International Conference on Future Internet of Things and Cloud. Marrkech, Morocco 14 - 16 Aug 2023 IEEE. https://doi.org/10.1109/FiCloud58648.2023.00067
Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics Among Patients With Late-Life Depression
Wen, J., Fu, C. H. Y., Tosun, D., Veturi, Y., Yang, Z., Abdulkadir, A., Mamourian, E., Srinivasan, D., Skampardoni, I., Singh, A., Nawani, H., Bao, J., Erus, G., Shou, H., Habes, M., Doshi, J., Varol, E., Mackin, R. S., Sotiras, A., Fan, Y., Saykin, A. J., Sheline, Y. I., Shen, L., Ritchie, M. D., Wolk, D. A., Albert, M., Resnick, S. M. and Davatzikos, C. 2022. Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics Among Patients With Late-Life Depression. JAMA Psychiatry. 79 (5), pp. 464-474. https://doi.org/10.1001/jamapsychiatry.2022.0020
Evaluating the Stressful Commutes Using Physiological Signals and Machine Learning Techniques
Sharif, S., Theeng Tamang, M. and Fu, C. 2022. Evaluating the Stressful Commutes Using Physiological Signals and Machine Learning Techniques. 3ICT 2022: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. University of Bahrain, Bahrain 20 - 21 Nov 2022 IEEE. https://doi.org/10.1109/3ICT56508.2022.9990849
Transcranial direct current stimulation effects in late life depression: a meta-analysis of individual participant data
Rimmer, R., Costafreda, S. G., Mutz, J., Joseph, K., Brunoni, A. R., Loo, C. K., Padberg, F., Palm, U. and Fu, C. 2022. Transcranial direct current stimulation effects in late life depression: a meta-analysis of individual participant data. Journal of Affective Disorders Reports. (Art. 100407). https://doi.org/10.1016/j.jadr.2022.100407
Adjunctive home-based transcranial direct current stimulation treatment for major depression with real-time remote supervision: An open-label, single-arm feasibility study with long term outcomes
Woodham, R., Rimmer, R., Young, A. H. and Fu, C. 2022. Adjunctive home-based transcranial direct current stimulation treatment for major depression with real-time remote supervision: An open-label, single-arm feasibility study with long term outcomes. Journal of Psychiatric Research. 153, pp. 197-205. https://doi.org/10.1016/j.jpsychires.2022.07.026
Situational factors shape moral judgments in the trolley dilemma in Eastern, Southern, and Western countries in a culturally diverse sample
Bago, B., Kovacs, M., Protzko, J., Nagy, T., Kekecs, Z., Palfi, B., Adamkovic, M., Adamus, S., Albalooshi, S., Albayrak-Aydemir, N., Alper, S., Alvarez-Solas, S., Alves, S. G., Amaya, S., Andresen, P. K., Anjum, G., Ansari, D., Arriaga, P., Aruta, J. J. B. R., Arvanitis, A., Babincak, P., Barzykowski, K., Bashour, B., Baskin, E., Batalha, L., Batres, C., Bavolar, J., Bayrak, F., Becker, M., Becker, B., Belaus, A., Białek, M., Bilancini, E., Boller, D., Boncinelli, L., Boudesseul, J., Brown, B. T., Buchanan, E. M., Butt, M. M., Calvillo, D. P., Carnes, N. C., Castille, C. M., Celniker, J. B., Chartier, C. R., Chopik, W. J., Chotikavan, P., Chuan-Peng, H., Clancy, R. F., Çoker, O., Correia, R. C., Adoric, V. C., Cubillas, C. P., Czoschke, S., Daryani, Y., de Grefte, J. A. M., de Vries, W. C., Demirag Burak, E. G., Dias, C., Dixson, B. J. W., Du, X., Dumančić, F., Dumbravă, A., Dutra, N. B., Enachescu, J., Esteban-Serna, C., Eudave, L., Evans, T. R., Feldman, G., Felisberti, F. M., Fiedler, S., Findor, A., Fleischmann, A., Foroni, F., Francová, R., Frank, D-A., Fu, C., Gao, S., Ghasemi, O., Ghazi-Noori, A., Ghossainy, M. E., Giammusso, I., Gill, T., Gjoneska, B., Gollwitzer, M., Graton, A., Grinberg, M., Groyecka-Bernard, A., Harris, E. A., Hartanto, A., Hassan, W. A. N. M., Hatami, J., Heimark, K. R., Hidding, J. J. J., Hristova, E., Hruška, M., Hudson, C. A., Huskey, R., Ikeda, A., Inbar, Y., Ingram, G. P. D., Isler, O., Isloi, C., Iyer, A., Jaeger, B., Janssen, S. M. J., Jiménez-Leal, W., Jokić, B., Kačmár, P., Kadreva, V., Kaminski, G., Karimi-Malekabadi, F., Kasper, A. T A., Kendrick, K. M., Kennedy, B. J., Kocalar, H. E., Kodapanakkal, R. I., Kowal, M., Kruse, E., Kučerová, L., Kühberger, A., Kuzminska, A. O., Lalot, F., Lamm, C., Lammers, J., Lange, E. B., Lantian, A., Lau, I. Y.-M., Lazarevic, L. B., Leliveld, M. C., Lenz, J. N., Levitan, C. A., Lewis, S. C., Li, M., Li, Y., Li, H., Lima, T. J. S., Lins, S., Liuzza, M. T., Lopes, P., Lu, J. G., Lynds, T., Máčel, M., Mackinnon, S. P., Maganti, M., Magraw-Mickelson, Z., Magson, L. F., Manley, H., Marcu, G. M., Maslić Seršić, D., Matibag, C-J., Mattiassi, A. D. A., Mazidi, M., McFall, J. P., McLatchie, N., Mensink, M. C., Miketta, L., Milfont, T. L., Mirisola, A., Misiak, M., Mitkidis, P., Moeini-Jazani, M., Monajem, A., Moreau, D., Musser, E. D., Narhetali, E., Nuralfian, I., Ochoa, D. P., Olsen, J., Owsley, N. C., Özdoğru, A. A., Panning, M., Papadatou-Pastou, M., Parashar, N., Pärnamets, P., Paruzel-Czachura, M., Parzuchowski, M., Paterlini, J. V., Pavlacic, J. M., Peker, M., Peters, K., Piatnitckaia, L., Pinto, I., Policarpio, M. R., Pop-Jordanova, N., Pratama, A. J., Primbs, M. A., Pronizius, E., Purić, D., Puvia, E., Qamari, V., Qian, K., Quiamzade, A., Ráczová, B., Reinero, D. A., Reips, U-D., Reyna, C., Reynolds, K., Ribeiro, M. F. F., Röer, J. P., Ross, R. M., Roussos, P., Ruiz-Dodobara, F., Ruiz-Fernandez, S., Rutjens, B. T., Rybus, K., Samekin, A., Santos, A. C., Say, N., Schild, C., Schmidt, K., Ścigała, K. A., Sharifian, M. H., Qureshi, J., Shi, Y., Sievers, E., Sirota, M., Slipenkyj, M., Solak, C., Sorokowska, A., Sorokowski, P., Söylemez, S., Steffens, N. K., Stephen, I. D., Sternisko, A., Stevens-Wilson, L., Stewart, S. L. K., Stieger, S., Storage, D., Strube, J., Susa, K. J., Szekely-Copîndean, R. D., Szostak, N. M., Takwin, B., Tatachari, S., Thomas, A. G., Tiede, K. E., Tiong, L. E., Tonković, M., Trémolière, B., Tunstead, L. V., Türkan, B. N., Twardawski, M., Vadillo, M. A., Vally, Z., Vaughn, L. A., Verschuere, B., Vlašiček, D., Voracek, M., Vranka, M. A., Wang, S., West, S-L., Whyte, S., Wilton, L. S., Wlodarczyk, A., Wu, X., Xin, F., Yadanar, S., Yama, H., Yamada, Y., Yilmaz, O., Yoon, S., Young, D. M., Zakharov, I., Zein, R. A., Zettler, I., Žeželj, I. L., Zhang, D. C., Zhang, J., Zheng, X., Hoekstra, R. and Aczel, B. 2022. Situational factors shape moral judgments in the trolley dilemma in Eastern, Southern, and Western countries in a culturally diverse sample. Nature Human Behaviour. 6, pp. 880-895. https://doi.org/10.1038/s41562-022-01319-5
Predicting the Health Impacts of Commuting Using EEG Signal Based on Intelligent Approach
Sharif, S., Theeng Tamang, M. and Fu, C. 2021. Predicting the Health Impacts of Commuting Using EEG Signal Based on Intelligent Approach. 3ICT 2021: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. Bahrain, University of Bahrain 29 - 30 Sep 2021 IEEE. https://doi.org/10.1109/3ICT53449.2021.9582119
Observing infants together: long-term experiences of observers and families
Papoutsi, V and Fu, C. 2021. Observing infants together: long-term experiences of observers and families. Infant Observation. 24 (1), pp. 4-22. https://doi.org/10.1080/13698036.2021.1952094
Motor adaptation and internal model formation in a robot-mediated forcefield
Taga, M., Curci, A., Pizzamiglio, S., Lacal, I., Turner, D. and Fu, C. 2021. Motor adaptation and internal model formation in a robot-mediated forcefield. Psychoradiology. 1 (2), p. 73–87. https://doi.org/10.1093/psyrad/kkab007
Is tDCS a potential first line treatment for major depression?
Woodham, R., Rimmer, R., Mutz, J. and Fu, C. 2021. Is tDCS a potential first line treatment for major depression? International Review of Psychiatry. 33 (3), pp. 250-265. https://doi.org/10.1080/09540261.2021.1879030
Dehydration in older people: a systematic review of the effects of dehydration on health outcomes, healthcare costs and cognitive performance
Edmonds, C., Foglia, E., Booth, P., Fu, C. and Gardner, M. 2021. Dehydration in older people: a systematic review of the effects of dehydration on health outcomes, healthcare costs and cognitive performance. Archives of Gerontology and Geriatrics. 95 (Art. 104380). https://doi.org/10.1016/j.archger.2021.104380
Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders
Writing Committee for the Attention-Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, Bipolar Disorder, Major Depressive Disorder, Obsessive-Compulsive Disorder, and Schizophrenia ENIGMA Working Groups 2020. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders. JAMA Psychiatry. 78 (1), p. 47–63. https://doi.org/10.1001/jamapsychiatry.2020.2694
ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing
Schmaal, L., Pozzi, E., Ho, T. C., van Velzen, L. S., Veer, I. M., Opel, N., Van Someren, E. J. W., Han, L. K. M., Aftanas, L., Aleman, A., Baune, B. T., Berger, K., Blanken, T. F., Capitão, L., Couvy-Duchesne, B., Cullen, K. R., Dannlowski, U., Davey, C., Erwin-Grabner, T., Evans, J., Frodl, T., Fu, C., Godlewska, B., Gotlib, I. H., Goya-Maldonado, R., Grabe, H. J., Groenewold, N. A., Grotegerd, D., Gruber, O., Gutman, B. A., Hall, G. B., Harrison, B. J., Hatton, S. N., Hermesdorf, M., Hickie, I. B., Hilland, E., Irungu, B., Jonassen, R., Kelly, S., Kircher, T., Klimes-Dougan, B., Krug, A., Landrø, N. I., Lagopoulos, J., Leerssen, J., Li, M., Linden, D. E. J., MacMaster, F. P., McIntosh, A. M., Mehler, D. M. A., Nenadić, I., Penninx, B. W. J. H., Portella, M. J., Reneman, L., Rentería, M. E., Sacchet, M. D., Sämann, P. G., Schrantee, A., Sim, K., Soares, J. C., Stein, D. J., Tozzi, L., van Der Wee, N. J. A., van Tol, M., Vermeiren, R., Vives-Gilabert, Y., Walter, H., Walter, M., Whalley, H. C., Wittfeld, K., Whittle, S., Wright, M. J., Yang, T. T., Zarate Jr, C., Thomopoulos, S. I., Jahanshad, N., Thompson, P. M. and Veltman, D. J. 2020. ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing. Translational Psychiatry . 10 (Art. 172). https://doi.org/10.1038/s41398-020-0842-6
Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
Han, L. K. M., Dinga, R., Hahn, T., Ching, C. R. K., Eyler, L. T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B. T., Berger, K., Brak, I., Filho, G. B., Carballedo, A., Connolly, C. G., Couvy-Duchesne, B., Cullen, K. R., Dannlowski, U., Davey, C. G., Dima, D., Duran, F. L. S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C., Godlewska, B. R., Gotlib, I. H., Grabe, H. J., Groenewold, N. A., Grotegerd, D., Gruber, O., Hall, G. B., Harrison, B. J., Hatton, S. N., Hermesdorf, M., Hickie, I. B., Ho, T. C., Hosten, N., Jansen, A., Kähler, B., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F. P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K. L., Medland, S. E., Mueller, B. A., Mwangi, B., Osipov, E., Portella, M. J., Pozzi, E., Reneman, L., Repple, J., Rosa, P. G. P., Sacchet, M. D., Sämann, P. G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J. C., Sommer, J., Stein, D. J., Steinsträter, O., Strike, L. T., Thomopoulos, S. I., van Tol, M., Veer, I. M., Vermeiren, R. R. J. M., Walter, H., van der Wee, N. J. A., van der Werff, S. J. A., Whalley, H., Winter, N. R., Wittfeld, K., Wright, M. J., Wu, M., Völzke, H., Yang, T. T., Zannias, V., de Zubicaray, G. I., Zunta-Soares, G. B., Abé, C., Alda, M., Andreassen, O. A., Bøen, E., Bonnin, C. M., Canales-Rodriguez, E. J., Cannon, D., Caseras, X., Chaim-Avancini, T. M., Elvsåshagen, T., Favre, P., Foley, S. F., Fullerton, J. M., Goikolea, J. M., Haarman, B. C. M., Hajek, T., Henry, C., Houenou, J., Howells, F. M., Ingvar, M., Kuplicki, R., Lafer, B., Landén, M., Machado-Vieira, R., Malt, U. F., McDonald, C., Mitchell, P. B., Nabulsi, L., Concepcion Garcia Otaduy, M., Overs, B. J., Polosan, M., Pomarol-Clotet, E., Radua, J., Rive, M. M., Roberts, G., Ruhe, H. G., Salvador, R., Sarró, S., Satterthwaite, T. D., Savitz, J., Schene, A. H., Schofield, P. R., Serpa, M. H., Sim, K., Gerhardt Soeiro-de-Souza, M., Sutherland, A. N., Temmingh, H. S., Timmons, G. M., Uhlmann, A., Vieta, E., Wolf, D. H., Zanetti, M. V., Jahanshad, N., Thompson, P. M., Veltman, D. J., Penninx, B. W. J. H., Marquand, A. F., Cole J. H. and Schmaal, L. 2020. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group. Molecular Psychiatry. 26, pp. 5124-5139. https://doi.org/10.1038/s41380-020-0754-0
Brain-derived neurotrophic factor association with amygdala response in major depressive disorder
Lorenzetti, V., Costafreda, S. G., Rimmer, R., Rasenick, M. M., Marangell, L. B. and Fu, C. 2020. Brain-derived neurotrophic factor association with amygdala response in major depressive disorder. Journal of Affective Disorders. 267, pp. 103-106. https://doi.org/10.1016/j.jad.2020.01.159
The Neuroscience of Sadness: A Multidisciplinary Synthesis and Collaborative Review for the Human Affectome Project
Arias, J. A., Williams, C., Raghvani, R., Aghajani, M., Baez, S., Belzung, C., Booij, L., Busatto, G., Chiarella, J., Fu, C., Ibanez, A., Liddell, B. J., Lowe, L., Penninx, B. W. J. H., Rosa, P. and Kemp, A. H. 2020. The Neuroscience of Sadness: A Multidisciplinary Synthesis and Collaborative Review for the Human Affectome Project. Neuroscience & Biobehavioral Reviews. 111, pp. 199-228. https://doi.org/10.1016/j.neubiorev.2020.01.006
Comparative efficacy and acceptability of non-surgical brain stimulation for the acute treatment of major depressive episodes in adults: systematic review and network meta-analysis
Mutz, Julian, Vipulananthan, Vijeinika, Carter, Ben, Hurlemann, René, Fu, C. and Young, Allan H. 2019. Comparative efficacy and acceptability of non-surgical brain stimulation for the acute treatment of major depressive episodes in adults: systematic review and network meta-analysis. BMJ. 364, p. Art. l1079. https://doi.org/10.1136/bmj.l1079
A systematic review and meta-analysis of the neural correlates of psychological therapies in major depression
Sankar, Anjali, Melin, Alice, Lorenzetti, Valentina, Horton, Paul, Costafreda, Sergi G. and Fu, C. 2018. A systematic review and meta-analysis of the neural correlates of psychological therapies in major depression. Psychiatry Research: Neuroimaging. 279, pp. 31-39. https://doi.org/10.1016/j.pscychresns.2018.07.002
Efficacy and acceptability of non-invasive brain stimulation for the treatment of adult unipolar and bipolar depression: A systematic review and meta-analysis of randomised sham-controlled trials
Mutz, Julian, Edgcumbe, Daniel R., Brunoni, Andre R. and Fu, C. 2018. Efficacy and acceptability of non-invasive brain stimulation for the treatment of adult unipolar and bipolar depression: A systematic review and meta-analysis of randomised sham-controlled trials. Neuroscience & Biobehavioral Reviews. 92, pp. 291-303. https://doi.org/10.1016/j.neubiorev.2018.05.015
Predictors of amygdala activation during the processing of emotional stimuli: A meta-analysis of 385 PET and fMRI studies
Costafreda, Sergi G., Brammer, Michael J., David, Anthony S. and Fu, C. 2007. Predictors of amygdala activation during the processing of emotional stimuli: A meta-analysis of 385 PET and fMRI studies. Brain Research Reviews. 58 (1), pp. 57-70. https://doi.org/10.1016/j.brainresrev.2007.10.012
Neural basis of the emotional Stroop interference effect in major depression
Mitterschiffthaler, M. T., Williams, S. C. R., Walsh, N. D., Cleare, A. J., Donaldson, C., Scott, J. and Fu, C. 2008. Neural basis of the emotional Stroop interference effect in major depression. Psychological Medicine. 38 (02), pp. 247-256. https://doi.org/10.1017/S0033291707001523
Pattern Classification of Sad Facial Processing: Toward the Development of Neurobiological Markers in Depression
Fu, C., Mourao-Miranda, Janaina, Costafreda, Sergi G., Khanna, Akash, Marquand, Andre F., Williams, Steve C.R. and Brammer, Michael J. 2008. Pattern Classification of Sad Facial Processing: Toward the Development of Neurobiological Markers in Depression. Biological Psychiatry. 63 (7), pp. 656-662. https://doi.org/10.1016/j.biopsych.2007.08.020
Neural Responses to Sad Facial Expressions in Major Depression Following Cognitive Behavioral Therapy
Fu, C., Williams, Steven C.R., Cleare, Anthony J., Scott, Jan, Mitterschiffthaler, Martina T., Walsh, Nicholas D., Donaldson, Catherine, Suckling, John, Andrew, Chris, Steiner, Herbert and Murray, Robin M. 2008. Neural Responses to Sad Facial Expressions in Major Depression Following Cognitive Behavioral Therapy. Biological Psychiatry. 64 (6), pp. 505-512. https://doi.org/10.1016/j.biopsych.2008.04.033
Neuroanatomy of verbal working memory as a diagnostic biomarker for depression
Marquand, Andre F., Mourão-Miranda, Janaina, Brammer, Michael J., Cleare, Anthony J. and Fu, C. 2008. Neuroanatomy of verbal working memory as a diagnostic biomarker for depression. NeuroReport. 19 (15), pp. 1507-1511. https://doi.org/10.1097/WNR.0b013e328310425e
Neural correlates of sad faces predict clinical remission to cognitive behavioural therapy in depression
Costafreda, Sergi G., Khanna, Akash, Mourao-Miranda, Janaina and Fu, C. 2009. Neural correlates of sad faces predict clinical remission to cognitive behavioural therapy in depression. NeuroReport. 20 (7), pp. 637-641. https://doi.org/10.1097/WNR.0b013e3283294159
Amygdala activation to masked happy facial expressions
Juruena, Mario F., Giampietro, Vincent P., Smith, Stephen D., Surguladze, Simon A., Dalton, Jeffrey A., Benson, Philip J., Cleare, Anthony J. and Fu, C. 2010. Amygdala activation to masked happy facial expressions. Journal of the International Neuropsychological Society. 16 (02), pp. 383-387. https://doi.org/10.1017/S1355617709991172
Subregional hippocampal deformations in major depressive disorder
Cole, James, Toga, Arthur W., Hojatkashani, Cornelius, Thompson, Paul, Costafreda, Sergi G., Cleare, Anthony J., Williams, Steven C.R., Bullmore, Edward T., Scott, Jan L., Mitterschiffthaler, Martina T., Walsh, Nicholas D., Donaldson, Catherine, Mirza, Mubeena, Marquand, Andre, Nosarti, Chiara, McGuffin, Peter and Fu, C. 2010. Subregional hippocampal deformations in major depressive disorder. Journal of Affective Disorders. 126 (1-2), pp. 272-277. https://doi.org/10.1016/j.jad.2010.03.004
Ketamine-Induced Disruption of Verbal Self-Monitoring Linked to Superior Temporal Activation
Stone, J. M., Abel, K. M., Allen, M.P.G., van Haren, N., Matsumoto, K., McGuire, P. K. and Fu, C. 2010. Ketamine-Induced Disruption of Verbal Self-Monitoring Linked to Superior Temporal Activation. Pharmacopsychiatry. 44 (1), pp. 33-48. https://doi.org/10.1055/s-0030-1267942
Machine learning classification with confidence: Application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression
Nouretdinov, Ilia, Costafreda, Sergi G., Gammerman, Alexander, Chervonenkis, Alexey, Vovk, Vladimir, Vapnik, Vladimir and Fu, C. 2011. Machine learning classification with confidence: Application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression. NeuroImage. 56 (2), pp. 809-813. https://doi.org/10.1016/j.neuroimage.2010.05.023
Cortisol responses to serial MRI scans in healthy adults and in depression
Peters, Sabine, Cleare, Anthony J., Papadopoulos, Andrew and Fu, C. 2011. Cortisol responses to serial MRI scans in healthy adults and in depression. Psychoneuroendocrinology. 36 (5), pp. 737-741. https://doi.org/10.1016/j.psyneuen.2010.10.009
No effect of 5HTTLPR or BDNF Val66Met polymorphism on hippocampal morphology in major depression
Cole, J., Weinberger, D. R., Mattay, V. S., Cheng, X., Toga, A. W., Thompson, P. M., Powell-Smith, G., Cohen-Woods, S., Simmons, A., McGuffin, P. and Fu, C. 2011. No effect of 5HTTLPR or BDNF Val66Met polymorphism on hippocampal morphology in major depression. Genes, Brain and Behavior. 10 (7), pp. 756-764. https://doi.org/10.1111/j.1601-183X.2011.00714.x
Hippocampal atrophy in first episode depression: A meta-analysis of magnetic resonance imaging studies
Cole, James, Costafreda, Sergi G., McGuffin, Peter and Fu, C. 2011. Hippocampal atrophy in first episode depression: A meta-analysis of magnetic resonance imaging studies. Journal of Affective Disorders. 134 (1-3), pp. 483-487. https://doi.org/10.1016/j.jad.2011.05.057
Interaction between effects of genes coding for dopamine and glutamate transmission on striatal and parahippocampal function
Pauli, Andreina, Prata, Diana P., Mechelli, Andrea, Picchioni, Marco, Fu, C., Chaddock, Christopher A., Kane, Fergus, Kalidindi, Sridevi, McDonald, Colm, Kravariti, Eugenia, Toulopoulou, Timothea, Bramon, Elvira, Walshe, Muriel, Ehlert, Natascha, Georgiades, Anna, Murray, Robin, Collier, David A. and McGuire, Philip 2012. Interaction between effects of genes coding for dopamine and glutamate transmission on striatal and parahippocampal function. Human Brain Mapping. 34 (9), pp. 2244-2258. https://doi.org/10.1002/hbm.22061
White matter abnormalities and illness severity in major depressive disorder
Cole, James, Chaddock, Christopher A., Farmer, Anne E., Aitchison, Katherine J., Simmons, Andrew, McGuffin, Peter and Fu, C. 2012. White matter abnormalities and illness severity in major depressive disorder. British Journal of Psychiatry. 201 (01), pp. 33-39. https://doi.org/10.1192/bjp.bp.111.100594
Predictive neural biomarkers of clinical response in depression: A meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies
Fu, C., Steiner, Herbert and Costafreda, Sergi G. 2013. Predictive neural biomarkers of clinical response in depression: A meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies. Neurobiology of Disease. 52, pp. 75-83. https://doi.org/10.1016/j.nbd.2012.05.008
Modulation of amygdala response and connectivity in depression by serotonin transporter polymorphism and diagnosis
Costafreda, Sergi G., McCann, Peter, Saker, Pascal, Cole, James H., Cohen-Woods, Sarah, Farmer, Anne E., Aitchison, Katherine J., McGuffin, Peter and Fu, C. 2013. Modulation of amygdala response and connectivity in depression by serotonin transporter polymorphism and diagnosis. Journal of Affective Disorders. 150 (1), pp. 96-103. https://doi.org/10.1016/j.jad.2013.02.028
Modafinil Augmentation Therapy in Unipolar and Bipolar Depression
Goss, Alexander J., Kaser, Muzaffer, Costafreda, Sergi G., Sahakian, Barbara J. and Fu, C. 2013. Modafinil Augmentation Therapy in Unipolar and Bipolar Depression. The Journal of Clinical Psychiatry. 74 (11), pp. 1101-1107. https://doi.org/10.4088/JCP.13r08560
Other race effect on amygdala response during affective facial processing in major depression
Sankar, Anjali, Costafreda, Sergi G., Marangell, Lauren B. and Fu, C. 2018. Other race effect on amygdala response during affective facial processing in major depression. Neuroscience Letters. 662, pp. 381-384. https://doi.org/10.1016/j.neulet.2017.10.043
The effect of psychosis associated CACNA1C, and its epistasis with ZNF804A, on brain function
Tecelão, Diogo, Mendes, Ana, Martins, Daniel, Fu, C., Chaddock, Christopher A, Picchioni, Marco M, McDonald, Colm, Kalidindi, Sridevi, Murray, Robin and Prata, Diana P 2018. The effect of psychosis associated CACNA1C, and its epistasis with ZNF804A, on brain function. Genes, Brain and Behavior. 18 (4), p. e12510. https://doi.org/10.1111/gbb.12510
Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder
Inkster, Becky, Simmons, Andy, Cole, James, Schoof, Erwin, Linding, Rune, Nichols, Tom, Muglia, Pierandrea, Holsboer, Florian, Saemann, Philipp, McGuffin, Peter, Fu, C., Miskowiak, Kamilla, Matthews, Paul M., Zai, Gwyneth and Nicodemus, Kristin 2018. Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder. Psychiatric Genetics. 28 (5), pp. 77-84. https://doi.org/10.1097/YPG.0000000000000203
Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition
Ranlund, Siri, Rosa, Maria Joao, de Jong, Simone, Cole, James H., Kyriakopoulos, Marinos, Fu, C., Mehta, Mitul A. and Dima, Danai 2018. Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition. NeuroImage: Clinical. 20, pp. 1026-1036. https://doi.org/10.1016/j.nicl.2018.10.008
Anodal transcranial direct current stimulation over the right dorsolateral prefrontal cortex enhances reflective judgment & decision-making
Edgcumbe, Daniel R., Thoma, V., Rivolta, Davide, Nitsche, Michael A. and Fu, C. 2018. Anodal transcranial direct current stimulation over the right dorsolateral prefrontal cortex enhances reflective judgment & decision-making. Brain Stimulation. 12 (3), pp. 652-658. https://doi.org/10.1016/j.brs.2018.12.003
Effects of antidepressant therapy on neural components of verbal working memory in depression
Sankar, Anjali, Adams, Tracey M, Costafreda, Sergi G. and Fu, C. 2017. Effects of antidepressant therapy on neural components of verbal working memory in depression. Journal of Psychopharmacology. 31 (9), pp. 1176-1183. https://doi.org/10.1177/0269881117724594
Body mass index, but not FTO genotype or major depressive disorder, influences brain structure
Cole, J.H., Boyle, C.P., Simmons, A., Cohen-Woods, S., Rivera, M., McGuffin, P., Thompson, P.M. and Fu, C. 2013. Body mass index, but not FTO genotype or major depressive disorder, influences brain structure. Neuroscience. 252 (Nov.), pp. 109-117. https://doi.org/10.1016/j.neuroscience.2013.07.015
Classification of Major Depressive Disorder via Multi-Site Weighted LASSO Model
Zhu, Dajiang, Riedel, Brandalyn C., Jahanshad, Neda, Groenewold, Nynke A., Stein, Dan J., Gotlib, Ian H., Dima, Danai, Cole, James H., Fu, C., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Schmaal, Lianne, Veltman, Dick J. and Thompson, Paul M. 2017. Classification of Major Depressive Disorder via Multi-Site Weighted LASSO Model. in: Descoteaux, Maxime, Maier-Hein, Lena, Franz, Alfred, Jannin, Pierre, Collins, D. Louis and Duchesne, Simon (ed.) Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017 Springer, Cham.
Recent Advances in Neuroimaging of Mood Disorders: Structural and Functional Neural Correlates of Depression, Changes with Therapy, and Potential for Clinical Biomarkers
Atkinson, Lauren, Sankar, Anjali, Adams, Tracey M. and Fu, C. 2014. Recent Advances in Neuroimaging of Mood Disorders: Structural and Functional Neural Correlates of Depression, Changes with Therapy, and Potential for Clinical Biomarkers. Current Treatment Options in Psychiatry. 1 (3), pp. 278-293. https://doi.org/10.1007/s40501-014-0022-5
Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis
Wise, T., Radua, J., Via, E., Cardoner, N., Abe, O., Adams, T. M., Amico, F., Cheng, Y., Cole, J. H., de Azevedo Marques Périco, C., Dickstein, D. P., Farrow, T. F. D., Frodl, T., Wagner, G., Gotlib, I. H., Gruber, O., Ham, B. J., Job, D. E., Kempton, M. J., Kim, M. J., Koolschijn, P. C. M. P., Malhi, G. S., Mataix-Cols, D., McIntosh, A. M., Nugent, A. C., O'Brien, J. T.., Pezzoli, S, Phillips, M. L., Sachdev, P. S., Salvadore, G., Selvaraj, S., Stanfield, A. C., Thomas, A. J., van Tol, M. J., van der Wee, N. J. A., Veltman, D. J., Young, A. H., Fu, C., Cleare, A. J. and Arnone, D. 2016. Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis. Molecular Psychiatry. https://doi.org/10.1038/mp.2016.72
Diagnostic potential of structural neuroimaging for depression from a multi-ethnic community sample
Sankar, Anjali, Zhang, Tianhao, Gaonkar, Bilwaj, Doshi, Jimit, Erus, Guray, Costafreda, Sergi G., Marangell, Lauren, Davatzikos, Christos and Fu, C. 2016. Diagnostic potential of structural neuroimaging for depression from a multi-ethnic community sample. BJPsych Open. 2 (4), pp. 247-254. https://doi.org/10.1192/bjpo.bp.115.002493
Meta-analyses of structural regional cerebral effects in type 1 and type 2 diabetes
Moulton, Calum D., Costafreda, Sergi G., Horton, Paul, Ismail, Khalida and Fu, C. 2015. Meta-analyses of structural regional cerebral effects in type 1 and type 2 diabetes. Brain Imaging and Behavior. 9 (4), pp. 651-662.
A systematic review of the neurophysiology of mindfulness on EEG oscillations
Lomas, T., Ivtzan, I. and Fu, C. 2015. A systematic review of the neurophysiology of mindfulness on EEG oscillations. Neuroscience & Biobehavioral Reviews. 57, pp. 401-410.
Multimodal functional and structural neuroimaging investigation of major depressive disorder following treatment with duloxetine
Fu, C., Costafreda, Sergi G, Sankar, Anjali, Adams, Tracey M, Rasenick, Mark M, Liu, Peng, Donati, Robert, Maglanoc, Luigi A, Horton, Paul and Marangell, Lauren B 2015. Multimodal functional and structural neuroimaging investigation of major depressive disorder following treatment with duloxetine. BMC Psychiatry. 15 (1).
Neural effects of cognitive–behavioural therapy on dysfunctional attitudes in depression
Sankar, A., Scott, J., Paszkiewicz, A., Giampietro, V. P., Steiner, H. and Fu, C. 2014. Neural effects of cognitive–behavioural therapy on dysfunctional attitudes in depression. Psychological Medicine. 45 (7), pp. 1425-1433.
Modulatory effects of brain-derived neurotrophic factor Val66Met polymorphism on prefrontal regions in major depressive disorder
Legge, R. M., Sendi, S., Cole, J. H., Cohen-Woods, S., Costafreda, S. G., Simmons, A., Farmer, A. E., Aitchison, K. J., McGuffin, P. and Fu, C. 2015. Modulatory effects of brain-derived neurotrophic factor Val66Met polymorphism on prefrontal regions in major depressive disorder. The British Journal of Psychiatry. 206 (5), pp. 379-384.
Prognostic and Diagnostic Potential of the Structural Neuroanatomy of Depression
Domschke, Katharina, Costafreda, Sergi G., Chu, Carlton, Ashburner, John and Fu, C. 2009. Prognostic and Diagnostic Potential of the Structural Neuroanatomy of Depression. PLoS ONE. 4 (7), p. e6353.
Pattern of neural responses to verbal fluency shows diagnostic specificity for schizophrenia and bipolar disorder
Costafreda, Sergi G, Fu, C., Picchioni, Marco, Toulopoulou, Timothea, McDonald, Colm, Kravariti, Eugenia, Walshe, Muriel, Prata, Diana, Murray, Robin M and McGuire, Philip K 2011. Pattern of neural responses to verbal fluency shows diagnostic specificity for schizophrenia and bipolar disorder. BMC Psychiatry. 11 (1), p. 18.
Neuroimaging-Based Biomarkers in Psychiatry: Clinical Opportunities of a Paradigm Shift
Fu, C. and Costafreda, Sergi G. 2013. Neuroimaging-Based Biomarkers in Psychiatry: Clinical Opportunities of a Paradigm Shift. Canadian Journal of Psychiatry. 58 (9), pp. 499-508.