Abstract Electroconvulsive Therapy (ECT) is arguably the most effective intervention for treatment-resistant depression. While large interindividual variability exists, a theory capable of explaining individual response to ECT remains elusive. To address this, we posit a quantitative, mechanistic framework of ECT response based on Network Control Theory (NCT). Then, we empirically test our approach and employ it to predict ECT treatment response. To this end, we derive a formal association between Postictal Suppression Index (PSI)—an ECT seizure quality index—and whole-brain modal and average controllability, NCT metrics based on white-matter brain network architecture, respectively. Exploiting the known association of ECT response and PSI, we then hypothesized an association between our controllability metrics and ECT response mediated by PSI. We formally tested this conjecture in N = 50 depressive patients undergoing ECT. We show that whole-brain controllability metrics based on pre-ECT structural connectome data predict ECT response in accordance with our hypotheses. In addition, we show the expected mediation effects via PSI. Importantly, our theoretically motivated metrics are at least on par with extensive machine learning models based on pre-ECT connectome data. In summary, we derived and tested a control-theoretic framework capable of predicting ECT response based on individual brain network architecture. It makes testable, quantitative predictions regarding individual therapeutic response, which are corroborated by strong empirical evidence. Our work might constitute a starting point for a comprehensive, quantitative theory of personalized ECT interventions rooted in control theory.
To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files ; Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation-intolerant genes and suggest a mechanism by which common risk variants persist in the population. ; European Union's Seventh Framework Programme Medical Research Council (MRC) Centre European Community's Seventh Framework Programme German Research Foundation (DFG) Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Munster National Health and Medical Research Council (NHMRC) Agencia Estatal de Investigacion (AEI) Xunta de Galicia Fondo Europeo de Desarrollo Regional (FEDER) Lundbeck Foundation Stanley Medical Research Institute, an advanced grant from the European Research Council Danish Strategic Research Council Aarhus University Wellcome Trust Juvenile Diabetes Research Foundation (JDRF) European Union National Institute for Health Research (NIHR) programme Chief Scientist Office of the Scottish government Health Directorates Scottish Funding Council National Institute of ...
The PGC was funded by National Institute of Mental Health (NIMH) Grant Nos. MH085520 (to PFS) and MH080403. Statistical analyses were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org) hosted by SURFsara and financially supported by the Netherlands Scientific Organization Grant No. NWO 480-05-003 (to D. Posthuma) and the department of Psychology, Vrije Universiteit Amsterdam along with a supplement from the Dutch Brain Foundation. The Bonn/Mannheim GWAS was supported by the German Federal Ministry of Education and Research (BMBF) through the Integrated Genome Research Network Systematic Investigation of the Molecular Causes of Major Mood Disorders and Schizophrenia Grant Nos. 01GS08144 and 01GS08147, under the auspices of the National Genome Research Network plus, and through the Integrated Network Integrated Understanding of Causes and Mechanisms in Mental Disorders, under the auspices of the e:Med Programme Grant Nos. 01ZX1314A and 01ZX1314G. The Bonn/Mannheim GWAS was also supported by the German Research Foundation (DFG) Grant Nos. FOR2107, RI908/11-1, and NO246/10-1. The GenRED GWAS project was supported by NIMH R01 Grant Nos. MH061686 (to DFL), MH059542 (to W.H. Coryell), MH075131 (W.B. Lawson), MH059552 (JBP), MH059541 (W.A. Scheftner), and MH060912 (MMW). Max Planck Institute of Psychiatry MARS study was supported by the BMBF Program Molecular Diagnostics: Validation of Biomarkers for Diagnosis and Outcome in Major Depression by Grant No. 01ES0811. Genotyping was supported by the Bavarian Ministry of Commerce, and the BMBF in the framework of the National Genome Research Network by Grant Nos. NGFN2 and NGFN-Plus, FKZ 01GS0481 and 01GS08145. The Netherlands Study of Depression and Anxiety and the Netherlands Twin Register contributed to Genetic Association Information Network (GAIN)-MDD and to MDD2000. Funding for NTR/NESDA was from the following: the Netherlands Organization for Scientific Research (MagW/ZonMW Grant Nos. 904-61-090, 985-10- 002, 904-61-193, 480-04-004, 400-05-717, 912-100-20; Spinozapremie Grant No. 56-464-14192; Geestkracht program Grant No. 10-000-1002); the Center for Medical Systems Biology (NWO Genomics), Biobanking and Biomolecular Resources Research Infrastructure, Vrije Universiteit's Institutes for Health and Care Research and Neuroscience Campus Amsterdam, BIC/BioAssist/RK (Grant No. 2008.024); the European Science Foundation (Grant No. EU/QLRT-2001-01254); the European Community's Seventh Framework Program (Grant No. FP7/2007-2013); ENGAGE (Grant No. HEALTH-F4-2007-201413); and the European Science Council (Grant No. ERC 230374). Genotyping was funded in part by the GAIN of the Foundation for the US National Institutes of Health, and analysis was supported by grants from GAIN and the NIMH (Grant No. MH081802). Funding for the QIMR samples was provided by the Australian National Health and Medical Research Council (Grant Nos. 241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496675, 496739, 552485, 552498, 613602, 613608, 613674, 619667), the Australian Research Council (Grant Nos. FT0991360, FT0991022), the FP-5 GenomEUtwin Project (Grant No. QLG2-CT-2002-01254), and the US National Institutes of Health (Grant Nos. AA07535, AA10248, AA13320, AA13321, AA13326, AA14041, MH66206, DA12854, DA019951), and the Center for Inherited Disease Research (Baltimore, MD). RADIANT was funded by the following: a joint grant from the UK Medical Research Council and GlaxoSmithKline (Grant No. G0701420); the National Institute for Health Research Specialist Biomedical Research Centre for Mental Health at the South London and Maudsley National Health Service Foundation Trust and the Institute of Psychiatry, King's College London; the UK Medical Research Council (Grant No. G0000647), and the Marie Curie Industry-Academia Partnership and Pathways (Grant No. 286213). The GENDEP study was funded by a European Commission Framework 6 grant (EC Contract Ref.: LSHB-CT-2003-503428). Genotyping of STAR*D was supported by NIMH Grant No. MH072802 (to SPH). STAR*D was funded by NIMH Grant No. N01MH90003 to the University of Texas Southwestern Medical Center at Dallas (to A.J. Rush). The CoLaus/PsyCoLaus study was supported by research grants from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (Grant Nos. 3200B0–105993, 3200B0-118308, 33CSCO-122661, 33CS30-139468, 33CS30-148401) and two grants from GlaxoSmithKline Clinical Genetics. SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (Grant Nos. 01ZZ9603, 01ZZ0103, 01ZZ0403), the Ministry of Cultural Affairs, and the Social Ministry of the Federal State of Mecklenburg–West Pomerania. Genome-wide data have been supported by the Federal Ministry of Education and Research (Grant No. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. SHIP-LEGEND is funded by the DFG (Grant No. GR 1912/5-1). The TwinGene study was supported by the Swedish Ministry for Higher Education, the Swedish Research Council (Grant No. M-2005-1112), GenomEUtwin (Grant Nos. EU/QLRT-2001-01254, QLG2-CT-2002-01254), the Swedish Foundation for Strategic Research and the US National Institutes of Health (Grant No. U01 DK066134). The collection of PRISME control subjects and genotyping of the 883 Danish control subjects was supported by grants from The Danish Strategic Research Council, The Stanley Research Foundation, and H. Lundbeck A/S. The Muenster Depression cohorts were supported by the European Union (Grant No. N Health-F2-2008-222963) and by grants from the DFG (Grant Nos. FOR 2107 and DA1151/5-1 [to UD]), Innovative Medizinische Forschung of the Medical Faculty of Mu¨nster (Grant Nos. DA120903, DA111107, and DA211012 [all to UD]). Generation Scotland is supported by a Wellcome Trust Strategic Award "Stratifying Resilience and Depression Longitudinally" (Reference No.: 104036/Z/14/Z) and core support from the Chief Scientist Office of the Scottish Government Health Directorates (Grant No. CZD/16/6) and the Scottish Funding Council (Grant No. HR03006). Supplementary material cited in this article is available online at http:// dx.doi.org/10.1016/j.biopsych.2016.05.010. ; Peer reviewed ; Publisher PDF
A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research. ; ENIGMA MDD work is supported by NIH grants U54 EB020403 (Thompson), R01 MH116147 (Thompson), and R01 MH117601 (Jahanshad & Schmaal). LS was supported by an NHMRC Career Development Fellowship (1140764). AFFDIS cohort: this study was funded by the University Medical Center Goettingen (UMG Startfoerderung) and the research team is supported by German Federal Ministry of Education and Research (Bundesministerium fuer Bildung und Forschung, BMBF: 01 ZX 1507, "PreNeSt - e:Med"). Barcelona cohort: MJP is funded by the Ministerio de Ciencia e Innovación of the Spanish Government and by the Instituto de Salud Carlos III through a 'Miguel Servet' research contract (CP16–0020); National Research Plan (Plan Estatal de I + D + I 2016–2019); and co-financed by the European Regional Development Fund (ERDF). BRC DeCC cohort: CHYF is supported by NIHR BRC. Calgary cohort: supported by Canadian Institutes for Health Research, Branch Out Neurological Foundation. Cardiff cohort: supported by the Medical Research Council (grant G 1100629) and the National Center for Mental Health (NCMH), funded by Health Research Wales (HS/14/20). CLING cohort: this study was partially supported by the Deutsche Forschungsgemeinschaft (DFG) via grants to OG (GR1950/5–1 and GR1950/10–1). CODE cohort: Henrik Walter is supported by a grant of the Deutsche Forschungsgemeinschaft (WA 1539/4–1). The CODE cohort was collected from studies funded by Lundbeck and the German Research Foundation (WA 1539/4–1, SCHN 1205/3–1, SCHR443/11–1). DIP-Groningen cohort: this study was supported by the Gratama Foundation, the Netherlands (2012/35 to NG). Edinburgh cohort: The research leading to these results was supported by IMAGEMEND, which received funding from the European Community's Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 602450. This paper reflects only the author's views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award 104036/Z/14/Z. FOR2107-Marburg cohort: funded by the German Research Foundation (DFG, grant FOR2107 KR 3822/7–2 to AK; FOR2107 KI 588/14–2 to TK and FOR2107 JA 1890/7–2 to AJ). Houston cohorts: supported in part by NIMH grant R01 085667 and the Dunn Research Foundation. JCS is supported by the Pat Rutherford, Jr. Endowed Chair in Psychiatry. IMH Study cohort: supported by funding from NHG (SIG/15012) and NMRC CISSP (2018). Melbourne cohort: funded by National Health and Medical Research Council of Australia (NHMRC) Project Grants 1064643 (Principal Investigator BJH) and 1024570 (Principal Investigator CGD). Minnesota cohort: the study was funded by the National Institute of Mental Health (K23MH090421; Dr. Cullen) and Biotechnology Research Center (P41 RR008079; Center for Magnetic Resonance Research), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, and the Minnesota Medical Foundation. This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute. Münster cohort: funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5–1 and DA1151/5–2 to UD; SFB-TRR58, Projects C09 and Z02 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). NESDA cohort: The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10–000–1002) and is supported by participating universities (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen) and mental health care organizations, see www.nesda.nl. Pharmo cohort: supported by ERA-NET PRIOMEDCHILD FP 6 (EU) grant 11.32050.26. PSYABM-NORMENT: supported by the Research Council of Norway (project number 229135). The South East Norway Health Authority Research Funding (project number 2015052). The Department of Psychology, University of Oslo, Norway. San Francisco cohort: supported by NIH/NCCIH 1R61AT009864–01A1. NIMH R01MH085734. SHIP and SHIP-trend cohorts: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. Stanford cohorts: this work was supported by NIH grant R37 MH101495. The BiDirect Study was supported by grants from the German Federal Ministry of Education and Research (BMBF; grants FKZ-01ER0816 and FKZ-01ER1506). MDS is partially supported by an award funded by the Phyllis and Jerome Lyle Rappaport Foundation. TCH is supported by NIMH grant 5K01MH117442. EJWVS, JL, and TFB are supported by European Research Council grant no. ERC-ADG-2014–671084 INSOMNIA. TFB is supported by a VU University Amsterdam University Research Fellowship 2016–2017. JL is supported by a VU University Amsterdam University Research Fellowship 2017–2018. ; publishedVersion
The 10Kin1day workshop was generously sponsored by the Neuroscience and Cognition program Utrecht (NCU) of the Utrecht University (https://www.uu.nl/en/research/neuroscience-and-cognition-utrecht), the ENIGMA consortium (http://enigma.ini.usc.edu), and personal grants: MvdH: NWO-VIDI (452-16-015), MQ Fellowship; SB-C: the Wellcome Trust; Medical Research Council UK; NIHR CLAHRC for Cambridgeshire and Peterborough Foundation National Health Services Trust; Autism Research Trust; LB: New Investigator Award, Canadian Institutes of Health Research; Dara Cannon: Health Research Board (HRB), Ireland (grant code HRA-POR-2013-324); SC: Research Grant Council (Hong Kong)-GRF 14101714; Eveline Crone: ERC-2010-StG-263234; UD: DFG, grant FOR2107 DA1151/5-1, DA1151/5-2, SFB-TRR58, Project C09, IZKF, grant Dan3/012/17; SD: MRC-RFA-UFSP-01-2013 (Shared Roots MRC Flagship grant); TF: Marie Curie Programme, International Training Programme, r'Birth; DG: National Science Centre (UMO-2011/02/A/NZ5/00329); BG: National Science Centre (UMO-2011/02/A/NZ5/00329); JH: Western Sydney University Postgraduate Research Award; LH: Science Foundation Ireland, ERC; HH: Research Grant Council (Hong Kong)-GRF 14101714; LJ: Velux Stiftung, grant 369 & UZH University Research Priority Program Dynamics of Healthy Aging; AJ: DFG, grant FOR2107 JA 1890/7-1; KJ: National Science Centre (UMO-2013/09/N/HS6/02634); VK: The Russian Foundation for Basic Research (grant code 15-06-05758 A); TK: DFG, grant FOR2107 KI 588/14-1, DFG, grant FOR2107 KI 588/15-1; AK: DFG, grant FOR2107 KO 4291/4-1, DFG, grant FOR2107 KO 4291/3-1; IL: The Russian Foundation for Basic Research (grant code 15-06-05758 A); EL: Health and Medical Research Fund - 11121271; SiL: NHMRC-ARC Dementia Fellowship 1110414, NHMRC Dementia Research Team Grant 1095127, NHMRC Project Grant 1062319; CL-J: 537-2011, 2014-849; AM: Wellcome Trust Strategic Award (104036/Z/14/Z), MRC Grant MC_PC_17209; CM: Heisenberg-Grant, German Research Foundation, DFG MO 2363/3-2; PM: Foundation for Science and Technology, Portugal - PDE/BDE/113601/2015; KN: National Science Centre (UMO-2011/02/A/NZ5/00329); PN: National Science Centre (UMO-2013/09/N/HS6/02634); JiP: NWO-Veni 451-10-007; PaR: PER and US would like to thank the Schizophrenia Research Institute and the Chief-Investigators of the Australian Schizophrenia Research Bank V. Carr, U. Schall, R. Scott, A. Jablensky, B. Mowry, P. Michie, S. Catts, F. Henskens, and C. Pantelis; AS: National Science Centre (UMO-2011/02/A/NZ5/00329); SS: European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 707730; CS-M: Carlos III Health Institute (PI13/01958), Carlos III Health Institute (PI16/00889), Carlos III Health Institute (CPII16/00048); ES: National Science Centre (UMO-2011/02/A/NZ5/00329); AT: The Russian Foundation for Basic Research (grant code 15-06-05758 A); DT-G: PI14/00918, PI14/00639; Leonardo Tozzi: Marie Curie Programme, International Training Programme, r'Birth; SV: IMPRS Neurocom stipend; TvE: National Center for Research Resources at the National Institutes of Health (grant numbers: NIH 1 U24 RR021992 (Function Biomedical Informatics Research Network), NIH 1 U24 RR025736-01 (Biomedical Informatics Research Network Coordinating Center; http://www.birncommunity.org) and the NIH Big Data to Knowledge (BD2K) award (U54 EB020403 to Paul Thompson). NvH: NWO-VIDI (452-11-014); MW: National Science Centre (UMO-2011/02/A/NZ5/00329); Veronica O'Keane: Meath Foundation; AV and AW: CRC Obesity Mechanism (SFB 1052) Project A1 funded by DFG. The funding sources had no role in the study design, data collection, analysis, and interpretation of the data ; We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain. Ongoing grand-scale projects like the European Human Brain Project (1), the US Brain Initiative (2), the Human Connectome Project (3), the Chinese Brainnetome (4) and exciting world-wide neuroimaging collaborations such as ENIGMA (5) herald the new era of big neuroscience. In conjunction with these major undertakings, there is an emerging trend for bottom-up initiatives, starting with small-scale projects built upon existing collaborations and infrastructures. As described by Mainen et al. (6), these initiatives are centralized around self-organized groups of researchers working on the same challenges and sharing interests and specialized expertise. These projects could scale and open up to a larger audience and other disciplines over time, eventually lining up and merging their findings with other programs to make the bigger picture.