Received: 2 March 2020 Revised: 9 May 2020 Accepted: 8 June 2020 DOI: 10.1002/hbm.25100 REVIEW ARTICLE ENIGMA-anxiety working group: Rationale for and organization of large-scale neuroimaging studies of anxiety disorders Janna Marie Bas-Hoogendam1,2,3 | Nynke A. Groenewold4 | Moji Aghajani5,6 | 7 7 8 9 Gabrielle F. Freitag | Anita Harrewijn | Kevin Hilbert | Neda Jahanshad | Sophia I. Thomopoulos9 | Paul M. Thompson9 | Dick J. Veltman5 | Anderson M. Winkler7 Ulrike Lueken8 | Daniel S. Pine7 | | Nic J. A. van der Wee2,3 | Dan J. Stein4,10,11 | ENIGMA-Anxiety Working Group 1 Department of Developmental and Educational Psychology, Leiden University, Institute of Psychology, Leiden, The Netherlands 2 Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands 3 Leiden Institute for Brain and Cognition, Leiden, The Netherlands 4 Department of Psychiatry & Mental Health, University of Cape Town, Cape Town, South Africa 5 Department of Psychiatry, Amsterdam UMC / VUMC, Amsterdam, The Netherlands 6 Department of Research & Innovation, GGZ inGeest, Amsterdam, The Netherlands 7 National Institute of Mental Health, Emotion and Development Branch, Bethesda, Maryland, USA 8 Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany 9 University of Southern California Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA 10 University of Cape Town, South African MRC Unit on Risk & Resilience in Mental Disorders, Cape Town, South Africa 11 University of Cape Town, Neuroscience Institute, Cape Town, South Africa Correspondence Janna Marie Bas-Hoogendam, Developmental Abstract and Educational Psychology, Institute of Anxiety disorders are highly prevalent and disabling but seem particularly tractable to Psychology, Leiden University, investigation with translational neuroscience methodologies. Neuroimaging has Nic J. A. van der Wee and Dan J. Stein should be considered joint last author Janna Marie Bas-Hoogendam and Nynke A. Groenewold should be considered joint first author Collaborators ENIGMA-Anxiety Working Group: Federica Agosta; Fredrik Åhs; Iseul An; Bianca A. V. Alberton; Carmen Andreescu; Takeshi Asami; Michal Assaf; Suzanne N. Avery; Nicholas L. Balderston; Jacques P. Barber; Marco Battaglia; Ali Bayram; Katja Beesdo-Baum; Francesco Benedetti; Rachel Berta; Johannes Björkstrand; Jennifer Urbano Blackford; James R. Blair; Karina S. Blair; Stephanie Boehme; Paolo Brambilla; Katie Burkhouse; Marta Cano; Elisa Canu; Elise M. Cardinale; Narcis Cardoner; Jacqueline A. Clauss; Camilla Cividini; Hugo D. Critchley; Udo Dannlowski; Jurgen Deckert; Tamer Demiralp; Gretchen J. Diefenbach; Katharina Domschke; Alex Doruyter; Thomas Dresler; Angelika Erhardt; Andreas J. Fallgatter; Lourdes Fañanás; Brandee Feola; Courtney A. Filippi; Massimo Filippi; Gregory A. Fonzo; Erika E. Forbes; Nathan A. Fox; Mats Fredrikson; Tomas Furmark; Tian Ge; Andrew J. Gerber; Savannah N. Gosnell; Hans J. Grabe; Dominik Grotegerd; Raquel E. Gur; Ruben C. Gur; Catherine J. Harmer; Jennifer Harper; Alexandre Heeren; John Hettema; David Hofmann; Stefan G. Hofmann; Andrea P. Jackowski; Andreas Jansen; Antonia N. Kaczkurkin; Ellen Kingsley; Tilo Kircher; Milutin Kostic; Benjamin Kreifelts; Axel Krug; Bart Larsen; Sang-Hyuk Lee; Elisabeth J. Leehr; Ellen Leibenluft; Christine Lochner; Eleonora Maggioni; Elena Makovac; Matteo Mancini; Gisele G. Manfro; Kristoffer N. T. Månsson; Frances Meeten; Jarosław Michałowski; Barbara L. Milrod; Andreas Mühlberger; Lilianne R. Mujica-Parodi; Ana Munjiza; Benson Mwangi; Michael Myers; Igor Nenadic; Susanne Neufang; Jared A. Nielsen; Hyuntaek Oh; Cristina Ottaviani; Pedro M. Pan; Spiro P. Pantazatos; Martin P. Paulus; Koraly Perez-Edgar; Wenceslao Peñate; Michael T. Perino; Jutta Peterburs; Bettina Pfleiderer; K. Luan Phan; Sara Poletti; Daniel Porta-Casteràs; Rebecca B. Price; Jesus Pujol; Andrea Reinecke; Francisco Rivero; Karin Roelofs; Isabelle Rosso; Philipp Saemann; Ramiro Salas; Giovanni A. Salum; Theodore D. Satterthwaite; Franklin Schneier; Koen R. J. Schruers; Stefan M. Schulz; Hanna Schwarzmeier; Fabian R. Seeger; Jordan W. Smoller; Jair C. Soares; Rudolf Stark; Murray B. Stein; Benjamin Straube; Thomas Straube; Jeffrey R. Strawn; Benjamin Suarez-Jimenez; Boris Suchan; Chad M. Sylvester; Ardesheer Talati; Erica Tamburo; Raşit Tükel; Odile A. van den Heuvel; Sandra Van der Auwera; Helena van Nieuwenhuizen; Marie-José van Tol; Laura S. van Velzen; Carlos Ventura Bort; Robert R. J. M. Vermeiren; Renee M. Visser; Inge Volman; Andre Wannemüller; Julia Wendt; Kathryn E. Werwath; P. Michiel Westenberg; Julian Wiemer; Katharina Wittfeld; Mon-Ju Wu; Yunbo Yang; Anna Zilverstand; Andre Zugman; Hannah L. Zwiebel. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. © 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. Hum Brain Mapp. 2022;43:83–112. wileyonlinelibrary.com/journal/hbm 83 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 84 BAS-HOOGENDAM ET AL. Wassenaarseweg 52, 2333 AK Leiden, The Netherlands. informed our understanding of the neurobiology of anxiety disorders, but research Email: j.m.hoogendam@fsw.leidenuniv.nl has been limited by small sample sizes and low statistical power, as well as heteroge- Funding information nous imaging methodology. The ENIGMA-Anxiety Working Group has brought Anxiety Disorders Research Network together researchers from around the world, in a harmonized and coordinated effort European College of Neuropsychopharmacology; Claude Leon to address these challenges and generate more robust and reproducible findings. This Postdoctoral Fellowship; Deutsche paper elaborates on the concepts and methods informing the work of the working Forschungsgemeinschaft (DFG, German Research Foundation), Grant/Award Number: group to date, and describes the initial approach of the four subgroups studying gen- 44541416 - TRR 58; EU7th Frame Work Marie eralized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. Curie Actions International Staff Exchange Scheme grant ‘European and South African At present, the ENIGMA-Anxiety database contains information about more than Research Network in Anxiety Disorders’ 100 unique samples, from 16 countries and 59 institutes. Future directions include (EUSARNAD); Geestkracht programme of the Netherlands Organization for Health Research examining additional imaging modalities, integrating imaging and genetic data, and and Development (ZonMw), Grant/Award collaborating with other ENIGMA working groups. The ENIGMA consortium creates Number: 10-000-1002; Intramural Research Training Award (IRTA) program within the synergy at the intersection of global mental health and clinical neuroscience, and the National Institute of Mental Health under the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroim- Intramural Research Program (NIMH-IRP), Grant/Award Number: MH002781; National aging research on anxiety disorders. Institute of Mental Health under the Intramural Research Program (NIMH-IRP), Grant/Award KEYWORDS Number: ZIA-MH-002782; SA Medical Research Council; U.S. National Institutes of amygdala, anxiety disorders, genetics, limbic system, magnetic resonance imaging, Health grants, Grant/Award Numbers: P01 neuroimaging, prefrontal cortex AG026572, P01 AG055367, P41 EB015922, R01 AG060610, R56 AG058854, RF1 AG051710, U54 EB020403 1 | I N T RO DU CT I O N approximately 11% globally (Kessler et al., 2009), with even higher estimates in high-income countries (Wittchen et al., 2011). Anxiety Although anxiety symptoms have long been described in literature on disorders typically have an early age of onset and are accompanied by psychopathology, only more recent research emphasizes the construct significant subsequent comorbidity of both physical and mental disor- of anxiety disorder diagnoses, including conditions such as generalized ders, as well as by considerable burden for patients, relatives and soci- anxiety disorder (GAD), panic disorder (PD), social anxiety disorder ety (Fineberg et al., 2013; Stein et al., 2017). The Global Burden of (SAD), and specific phobia (SP). The third edition of the Diagnostic Disease Study found that, in high-income as well as low- and middle- and Statistical Manual (DSM-III [1980]) and the 10th edition of the income regions, anxiety disorders are the sixth leading cause of dis- International Classification of Diseases (ICD-10 [1990]) stimulated ability, in terms of years lived with disability (Baxter, Vos, Scott, research on these diagnostic categories by providing operational diag- Ferrari, & Whiteford, 2014). nostic guidelines and criteria for specific anxiety disorders. Based on Several factors support the need for more research on the neuro- subsequent research, nosological constructs were refined and the biology of anxiety disorders. First, the early onset of anxiety disorders, overarching conceptualization of anxiety disorders was altered in and their association with subsequent comorbidity (Beesdo DSM-5 (2013) and ICD-11 (2019). For example, both classification et al., 2007; Beesdo-Baum & Knappe, 2012; Bulley, Miloyan, Brilot, systems, unlike earlier schemes, now distinguish obsessive– Gullo, & Suddendorf, 2016; Kessler et al., 2005; Plana-Ripoll compulsive disorder (OCD) and post-traumatic stress disorder (PTSD) et al., 2019) raise the question of whether a better understanding of from anxiety disorders (Kogan et al., 2016). the relevant underlying mechanisms might ultimately be useful for Important insights on the DSM and ICD constructs defining anxi- preventive interventions. Second, although there is now a growing ety disorders came from community surveys. Serious mental illnesses evidence-base of efficacious and cost-effective interventions for anxi- are relatively common in clinical settings, but there is a relative under- ety disorders, many individuals do not respond to first-line treatments, recognition of the symptomatology and need for treatment of anxiety do respond but do not remit, or have relapse and recurrence of their disorders by clinicians (Aydin et al., 2020; Calleo et al., 2009; illness (Fernandez, Salem, Swift, & Ramtahal, 2015; Loerinc Chapdelaine, Carrier, Fournier, Duhoux, & Roberge, 2018; Edwards, et al., 2015; Taylor, Abramowitz, & McKay, 2012). Improvements in Thind, Stranges, Chiu, & Anderson, 2019; Furmark, 2002; Ormel, health-care delivery could lead to earlier diagnosis and scaling up of Koeter, van den Brink, & van de Willige, 1991). However, research in currently available, efficacious treatments that can close the treat- community settings finds that anxiety disorders are the most preva- ment gap (Alonso et al., 2018). However, better delineation of specific lent group of mental disorders, with lifetime prevalence averaging underlying mechanisms might also lead to more personalized and 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License BAS-HOOGENDAM ET AL. 85 more effective interventions (Beauchaine, Neuhaus, Brenner, & disorders. Early neuroimaging studies suggested that these conditions Gatzke-Kopp, 2008). were characterized by structural and functional alterations, thereby Anxiety disorders may be particularly tractable to translational stimulating the formulation of neurobiological models for anxiety dis- neuroscience. First, similar forms of brain-behavior associations mani- orders that focused on the frontolimbic system (Etkin & fest in a range of mammalian species during encounters with threats Wager, 2007). Subsequent MRI studies have led to more detailed neu- (stimuli capable of harming the organisms), as demonstrated through rocircuitry models of GAD, PD, SP, and SAD (Bandelow et al., 2016; research on fear conditioning and extinction (Kalin, 2017; Milad & Bas-Hoogendam, Roelofs, Westenberg, & van der Wee, 2020; Brühl, Quirk, 2011). Second, vulnerability for anxiety disorders can be quan- Delsignore, Komossa, & Weidt, 2014; Cremers & Roelofs, 2016; tified using intermediate phenotypes such as corticolimbic reactivity, Duval, Javanbakht, & Liberzon, 2015; Goddard, 2017; Hilbert, behavioral inhibition, anxious temperament, and increased startle Lueken, & Beesdo-Baum, 2014; Kolesar, Bilevicius, Wilson, & response (Gottschalk & Domschke, 2016); the neural circuitry and Kornelsen, 2019; Mochcovitch, da Rocha Freire, Garcia, & molecular mechanisms of these intermediate phenotypes can be pro- Nardi, 2014), and of anxiety in general (Grupe & Nitschke, 2013; ductively investigated in rodent, nonhuman primates, and human Shin & Liberzon, 2010; Taylor & Whalen, 2015; VanElzakker, Kathryn models (Fox and Kalin, 2014). Third, genetic studies of anxiety disor- Dahlgren, Caroline Davis, Dubois, & Shin, 2014), including its neu- ders show considerable heritability, with heritability estimates ranging rodevelopmental origins (Blackford & Pine, 2012; Caouette & between 30 and 67% (Bandelow et al., 2016; Levey et al., 2020; Guyer, 2014) (we refer to Figure 1 for an overview of neurocircuitry Meier & Deckert, 2019; Shimada-Sugimoto, Otowa, & involved in anxiety disorders). Finally, neuroimaging studies have iden- Hettema, 2015), and recent genome-wide association studies (GWAS) tified putative neurobiological predictors for treatment response in, reported on various single-nucleotide polymorphisms associated with and also across, anxiety disorders (Klumpp & Fitzgerald, 2018; Lueken anxiety (Levey et al., 2020; Meier et al., 2019; Purves et al., 2019). et al., 2016). Thus, extending such genetic work through brain imaging could reveal Despite several promising findings, neuroimaging research on molecular pathways associated with psychopathology through influ- anxiety disorders has had important limitations. Small sample sizes ences on brain structure and function. have entailed low statistical power and, together with differences in Neuroimaging studies using magnetic resonance imaging (MRI) acquisition and analytic approaches, have likely contributed to incon- have begun to advance research into the neurobiology of anxiety sistent findings and limited reproducibility (Blackford, 2017). In SAD, Neurocircuitry implicated in anxiety disorders (a) Subcortical (b) Cortical Medial view Lateral view ParaC CMF Cau SF PoC SP SF PCun PreC Pu SP Pcc Pa CAcc RMF SuM IP Ist Hip NAcc OPER Cun RAcc TRI Amy INS TT Peri MOF ORB ST LOC Ling ParaH LOF MT FF Ent ST IT F I G U R E 1 Overview of neurocircuitry involved in anxiety disorders. This schematic overview illustrates the subcortical (Figure 1a) and cortical (Figure 1b) regions that are part of the FreeSurfer pipeline (RRID:SCR_001847; http://surfer.nmr.mgh.harvard.edu). Regions involved in anxiety are colored based on the work on the neurocircuitry of anxiety disorders (Duval et al., 2015), implicating brain areas involved in sensory processing (occipital cortex, fusiform gyrus, thalamus; green), emotion generating and processing (striatum, amygdala, insula, dorsal anterior cingulate cortex; red) and emotion modulation regions (medial prefrontal cortex, hippocampus, dorsolateral prefrontal cortex, subgenual/rostral anterior cingulate cortex; blue). Note that other models of brain circuitry in anxiety, for example those described by (Brühl et al., 2014; Kolesar et al., 2019), are more extended and also involve other regions—most notably regions of the parietal cortex. Figure 1a (subcortical) Amy, Amygdala; Cau, Nucleus Caudatus; Hip, Hippocampus; NAcc, Nucleus Accumbens; Pa, Pallidum; Pu, Putamen; Tha, Thalamus. Figure 1b (cortical) CAcc, Caudal Anterior Cingulate Cortex; CMF, Caudal Middle Frontal; Cun, Cuneus; Ent, Entorhinal; FF, Fusiform; INS, Insula; IP, Inferior Parietal; Ist, Isthmus; IT, Inferior Temporal; Ling, Lingual; LOC, Lateral Occipital; LOF, Lateral Orbitofrontal; MOF, Medial Orbitofrontal; MT, Middle Temporal; OPER, Pars Opercularis; ORB, Pars Orbitalis; ParaC, Paracentral; ParaH, Parahippocampal; Pcc, Posterior Cingulate Cortex; PCun, precuneus; Peri, Pericalcarine; PoC; Postcentral; PreC, Precentral; RAcc, Rostral Anterior Cingulate Cortex; RMF, Rostral Middle Frontal; SF, Superior Frontal; SP, Superior Parietal; ST, Superior Temporal; SuM, Supramarginal; TRI, Pars Triangularis; TT, Transverse Temporal TABLE 1 Anx_GAD (generalized anxiety disorder) General sample information Clinical information Questionnaires MRI and genetic information Field Material Sample Key- Age- Diagnostic Anx Other Age Psych STAI- strength T1-w for # Country Institute Sample references # GAD # HC range (y) Sex interview comorb comorb onset med trait ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SCARED (T) Scanner MRI DTI fMRI genetics GAD_01 BR INPD Brazilian (Salum et al., 101 668 5–15 M&F OTH 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1.5 GE 1 1 1 1 HRC study 2015) GAD_02 BR Universidade PROTAIA (Salum et al., 26 18 13–22 M&F KSADS 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 1 1 3 ? 1 ? 0 1 Federal do 2011; Toazza Rio Grande et al., 2016) do Sul GAD_03 DE Technische Dresden GAD (Hilbert et al., 47 47 18–51 M&F CIDI 1 1 0 1 1 0 0 1 0 0 0 0 1 0 1 0 0 0 3 SIE 1 0 1 1 Universität 2015) Dresden GAD_04 DE University Muenster GAD (Buff et al., 25 29 19–56 M&F ? 0 0 0 1 1 1 0 0 0 0 0 0 1 0 0 0 0 0 3 SIE 1 0 1 0 of muenster 2016) GAD_05 DE University SHIP (Völzke et al., 12 24 41–70 M&F CIDI 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1.5 SIE 1 0 0 1 Medicine 2011) Greifswald GAD_06 ES Universitat Barcelona (Porta et al., 31 60 18–40 M&F MINI 1 1 0 1 1 1 1 1 0 0 0 1 1 0 1 0 0 0 1.5 GE 1 0 1 0 Autonoma 2017) de Barcelona GAD_07 IT University Milan (Molent et al., 34 64 21–73 M&F SCID 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 3 PHI 1 1 1 1 of Milan 2018) GAD_08 IT University San Raffaele (Canu et al., 21 71 22–63 M&F SCID 1 1 1 1 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1.5 PHI 1 1 1 1 Vita-Salute 2015) San Raffaele GAD_09 UK Sussex university/ Sussex (Makovac et al., 19 21 18–55 M&F SCID 1 Excl. 1 1 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1.5 SIE 1 0 1 0 Sapienza 2016; Makovac university et al., 2016) of Rome GAD_10 US National Institute ABCD study (Casey et al., 114 1,495 8–11 M&F OTH 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 ? 1 ? ? ? on Drug Abuse 2018; Volkow et al., 2018) GAD_11 US Baylor College Baylor (Curtis et al., 98 149 12–79 M&F SCID 1 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 3 SIE 1 1 1 1 of Medicine 2019; Gosnell et al., 2020) GAD_12 US Boys Town Boystown (Blair et al., 2019; 50 45 13–18 M&F OTH 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 3 SIE 1 0 1 1 National Blair et al., 2019) Research Hospital 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 1 (Continued) General sample information Clinical information Questionnaires MRI and genetic information Field Material Sample Key- Age- Diagnostic Anx Other Age Psych STAI- strength T1-w for # Country Institute Sample references # GAD # HC range (y) Sex interview comorb comorb onset med trait ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SCARED (T) Scanner MRI DTI fMRI genetics GAD_13 US University Chicago-Phan (Gorka et al., 2019; 104 43 18–60 M&F ? 1 1 0 1 1 0 1 1 0 0 1 1 1 0 1 1 0 0 ? ? 1 ? ? ? of Illinois Klumpp at Chicago et al., 2018) GAD_14 US University of Chicago-Milad 27 16 18–59 M&F ? 1 1 0 0 1 1 1 0 0 0 0 0 0 0 1 0 0 0 ? ? 1 ? ? ? Illinois at Chicago GAD_15 US University Cincinnati (Strawn et al., 2012) 10 11 12–18 M&F KSADS 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 OTH 1 0 1 1 of Cincinnati GAD_16 US Child Mind CMI (Alexander 121 170 5–21 M&F KSADS 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 3 SIE 1 1 1 1 Institute et al., 2017) GAD_17 US Duke Duke (Carpenter 26 19 6–10 M&F OTH 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 GE 1 1 1 0 University et al., 2015) GAD_18 US Harvard Harvard 203 57 18–40 M&F SCID 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 3 SIE 1 1 1 1 Medical School GAD_19 US UT Health Houston_GAD 9 264 8–68 M&F SCID 1 1 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 1 1.5 PHI 1 0 0 0 GAD_20 US University PittsburghAndreescu (Karim et al., 2016) 38 741 19–90 M&F SCID 1 1 1 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 3 SIE 1 1 1 0 of Pittsburgh GAD_21 US University PittsburghPrice [Price et al., in 69 0 18–54 M&F MINI 1 1 0 1 1 0 1 1 0 0 0 0 1 0 1 0 0 0 3 SIE 1 0 1 0 of Pittsburgh press; Price et al., 2018] GAD_22 US National Institute SDAN (Gold et al., 2020; 243 166 8–51 M&F SCID & KSADS 1 1 0 0 1 1 1 1 0 0 0 1 1 0 1 0 1 1 3 GE 1 1 1 1 of Mental Gold et al., 2017) Health GAD_23 US National Institute SNFA (Balderston 23 40 19–50 M&F SCID 1 1 0 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 3 GE 1 0 0 0 of Mental et al., 2017) Health GAD_24 US Stony Brook Stony Brook (Cha et al., 2016) 41 20 18–49 Only F ? 0 1 0 1 1 1 0 0 0 0 0 0 1 0 1 0 0 0 ? ? 1 ? ? ? University GAD_25 US University UCSD (Ball, Ramsawh, 46 50 17–53 M&F MINI & SCID 1 1 0 1 1 1 0 0 0 0 0 0 1 0 1 0 0 0 3 GE 1 0 1 ? of California - Campbell-Sills, San Diego Paulus, & Stein, 2013; Fonzo et al., 2014) GAD_26 US University PNC (Calkins et al., 2015; 27 428 8–23 M&F OTH 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 SIE 1 1 1 1 of Pennsylvania Satterthwaite et al., 2014) (Continues) 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Material DTI fMRI genetics for 0 0 1 1 for example, a review of samples included in a recent volumetric MRI and genetic information 0 0 meta-analysis (Bas-Hoogendam, 2019; Wang, Cheng, Luo, Qiu, & T1-w Scanner MRI 1 1 Wang, 2018) and a recent paper on anatomical endophenotypes of SAD (Table 1 of (Bas-Hoogendam et al., 2018)), show that the num- SIE SIE bers of patients included in individual studies are seldom higher than strength Field 30. In addition, common artifacts (for example, related to head ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SCARED (T) 3 3 motion, breathing effects), and important confounders (such as educa- tional attainment and psychiatric comorbidity) may vary systematically 1 0 1 0 between patient and control groups, leading some authors to con- clude that study findings largely represent artifacts or false-positive 0 1 results, so potentially misinforming practitioners and patients 0 0 (Weinberger & Radulescu, 2015). Hence, there is a need for rigorous examination of the replicability of neuroimaging findings within and 0 0 across anxiety disorders, and for closer investigation of clinical and 0 1 methodological variables that contribute to heterogeneity in findings. 0 1 0 0 2 | EA R L Y M U L T I - S I T E CO L L A B O RA T I O N 0 0 0 0 Researchers on anxiety disorders have forged many collaborations in recent decades. Regular conferences (such as that of the Anxiety Dis- 0 1 Questionnaires orders Association of America) as well as specially convened meetings 0 0 0 0 (such as those convened by the Dutch Royal Academy of Sciences) Psych STAI- trait have provided opportunities for interaction, and funding mechanisms 0 0 comorb comorb onset med for network science have been useful in initiating and promoting col- 1 1 laborative research. The “European South-African Research Network Age 1 0 in Anxiety Disorders” (EUSARNAD), for example, was funded by the Other EU (Baldwin & Stein, 2012); one aim was to conduct a multi-center 1 1 voxel-based morphological mega-analysis of SAD. In this early initia- Anx Clinical information 1 1 tive, research centers from five different countries participated, and T1-weighted 3 Tesla brain MRI scans of 174 SAD patients and Diagnostic interview KSADS 213 healthy controls were included in the analysis (Bas-Hoogendam MINI et al., 2017b). A hypothesis-driven region of interest (ROI) approach M&F M&F # GAD # HC range (y) Sex was used and found that patients with SAD had, on average, larger gray matter volume in the dorsal striatum than healthy controls, after 21–71 8–12 Age- Note: Leaders of the Anx_GAD subgroup: Anderson M. Winkler and Daniel S. Pine. adjusting for gender, age, scan center, and total gray matter volume. 31 21 Notably, this increase correlated positively with the severity of self- reported social anxiety symptoms (Bas-Hoogendam et al., 2017b). 32 32 This mega-analysis, however, did not replicate gray matter changes in amygdala, hippocampus, precuneus, prefrontal cortex and parietal et al., 2016) Diefenbach (Assaf et al., references regions, which had previously been reported in small-sample case– 2018; Key- control studies. Taken together, the findings of this study emphasize the importance of standardized meta-analytic and mega-analytic approaches for SAD in particular, and the anxiety disorders in general Washing-ton (Bas-Hoogendam et al., 2017a). Sample During the data collection for the EURSANAD project and the IOL subsequent steps for the mega-analysis, the Enhancing Neuroimaging Living/Hartford Genetics through Meta-Analysis (ENIGMA) initiative, launched in University Washington Hospital Institute of 2009, gained momentum. As described extensively elsewhere, Institute (Continued) ENIGMA has developed a well-supported and robust platform to per- General sample information form novel meta-analyses on data derived from harmonized and Country locally applied data-processing pipelines (Bearden & Thompson, 2017; US US Thompson et al., 2014; Thompson et al., 2020), publicly available at TABLE 1 GAD_27 GAD_28 Sample # 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License BAS-HOOGENDAM ET AL. 89 http://enigma.ini.usc.edu/protocols/imaging-protocols/. Considering continues to welcome new contributors. Interested researchers are the advantages of this approach, the quality of support provided by encouraged to contact the Working Group leaders and coordinators the ENIGMA core, the expanding reach and resources of the ENIGMA to discuss their participation (http://enigma.ini.usc.edu/ongoing/ consortium, and the clear need to facilitate large-scale analyses of enigma-anxiety/). Importantly, the availability of genotyping data is anxiety disorders and across disorders, the EUSARNAD-SAD consor- not a prerequisite for joining. However, samples do need to be phe- tium decided to join the ENIGMA initiative and to launch the notyped with regard to anxiety disorders or symptoms, and structural ENIGMA-Anxiety Working Group. MRI data need to be available (T1-weighted scans; diffusion tensor imaging [DTI] and functional MRI data are optional). To facilitate future cross-disorder comparisons between anxiety 3 | THE ST A RT AND STRUC TU RE OF T HE disorders as well as across ENIGMA working groups, and building on ENIGMA-ANXIETY WORKING GROUP the experience of already existing working groups, we aimed for a detailed characterization of samples when constructing the ENIGMA- When the ENIGMA-Anxiety Working Group was initiated in 2016, we Anxiety database. Thus, in addition to details about the MRI data, we immediately noted that most ENIGMA working groups devoted to inquired for each sample whether the researchers collected informa- psychiatric disorders focused on just one condition, such as schizo- tion on the presence of psychiatric diagnoses (derived from clinical phrenia (van Erp et al., 2016), major depressive disorder (MDD) interviews), severity of anxiety and depressive symptoms (derived (Schmaal et al., 2016; Schmaal et al., 2017), or OCD (Boedhoe from self-report questionnaires), imaging parameters, and demo- et al., 2017). The anxiety disorders comprise a number of disparate graphic characteristics of the samples; we strove to collect this infor- conditions with disorder-specific clinical presentations (American Psy- mation in a standardized way across the four subgroups. This collation chiatric Association, 2013). Nevertheless, the class of anxiety disor- of information subsequently aided us with study design; it was partic- ders involves very high rates of comorbidity between the disorders, ularly important for deciding which variables to include in plans for and few studies link individual anxiety disorders to unique neurobio- analysis and to assess the feasibility of secondary proposals (for a logical alterations, suggesting that there (partly) are shared neurobio- recent paper illustrating the effect of accounting for psychiatric logical characteristics (Fonzo et al., 2015; Kim & Yoon, 2018; comorbidity while investigating biomarkers in psychiatry, we refer to Pannekoek et al., 2015; Rabany et al., 2017). We therefore set up (Gosnell et al., 2020)). Data availability is summarized in Table 1 three subgroups under the umbrella of ENIGMA-Anxiety (focused on (Anx_GAD), Table 2 (Anx_PD), Table 3 (Anx_SAD) and Table 4 SAD, PD with and without agoraphobia, and GAD) and later also (Anx_SP). added a fourth group (focused on SP). Our initial focus was on case– In addition to the samples that could be allocated to the four sub- control comparisons per subgroup, as this was expected to be sensi- groups, the ENIGMA-Anxiety database contains information on sam- tive to relatively small effect sizes, would allow for comparisons with ples with anxiety disorder diagnoses that are not an immediate focus findings from other ENIGMA working groups, and help to gain a criti- of investigation; these samples concern, for example, children with cal mass (as illustrated by the addition of the SP subgroup). We envis- separation anxiety (Calkins et al., 2015; Salum et al., 2011; Salum aged that this sort of collaboration would facilitate progress in each et al., 2015; Satterthwaite et al., 2014), children at risk for developing disorder, and also provide a foundation for subsequent cross-disorder an anxiety disorder (Battaglia et al., 2012; Fu, Taber-Thomas, & Pérez- collaborations. Edgar, 2017; Taber-Thomas, Morales, Hillary, & Pérez-Edgar, 2016), The leaders of each subgroup reached out to research sites across participants with anxiety-related traits and at risk phenotypes the world, explaining the aim and methods of the ENIGMA approach, (Campbell-Sills et al., 2011; Dannlowski et al., 2015; Dannlowski and asking principal investigators whether they were willing to con- et al., 2016; Mujica-Parodi et al., 2009; Thompson et al., 2019; tribute data to the initiative. Potential sites were identified via per- Tolkunov, Rubin, & Mujica-Parodi, 2010), participants with behavioral sonal contacts of the coordinators and literature searches, as well as inhibition (Blackford, Allen, Cowan, & Avery, 2013; Blackford, Avery, by carefully screening abstracts submitted for scientific meetings (for Cowan, Shelton, & Zald, 2011), as well as participants with hypochon- example, the annual OHBM meeting (2016) and the annual meeting driasis (van den Heuvel et al., 2011) and twin-pairs with and without a of the Society of Biological Psychiatry (2017)). In addition, when the diagnosis of an anxiety disorder (Córdova-Palomera et al., 2015). As initiative became more known, several sites contacted the ENIGMA- discussed in the section on future research directions, analyses of Anxiety Working Group themselves and expressed their interest to these data may in due time shed light on the developmental timeline contribute data. For each contributing site, the principal investigator(s) of anxiety-related alterations in the brain, across the full spectrum of signed the Memorandum of Understanding (MOU), describing the pol- subclinical and clinical anxiety phenotypes. icies of the working group with respect to authorship, publications, Within each subgroup, data availability was highest for secondary proposals, and an opt-in approach to project participation. T1-weighted anatomical MRI scans. Therefore, and following the Next, members provided information on data availability for their usual ENIGMA procedures, the first projects within each subgroup samples; this material was used to construct the ENIGMA-Anxiety were devoted to investigation of subcortical volumes (initiated in database and, subsequently, to allocate research samples to the 2017) and cortical morphology (initiated in 2019). Secondary projects appropriate subgroup. We want to stress that the Working Group that have been recently proposed will examine anxiety-related TABLE 2 Anx_PD (panic disorder) General sample information Clinical information Questionnaires MRI and genetic information Age-range Diagnostic Anx Other Age Psych STAI- Field T1-w Material for Sample # Country Institute Sample Key-references # PD # HC (y) Sex interview comorb comorb onset med trait ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SC2ARED strength (T) Scanner MRI DTI fMRI genetics PD_01 DE Max Planck Institute of MARS anxiety (Erhardt et al., 2012) 20 212 19–79 M&F SCID 1 1 1 1 1 0 0 0 1 0 0 1 0 0 1 1 0 0 1.5 GE 1 0 1 1 Psychiatry (RUD controls) PD_02 DE Philipps-University Panic-net (Kircher et al., 2013; 159 182 19–67 M&F SCID 1 1 0 Excl 0 1 0 0 1 1 0 1 0 0 1 0 0 0 3 SIE 1 0 1 1 Marburg Yang et al., 2019) PD_03 DE University Medicine SHIP (Pané-Farré 27 699 31–90 M&F CIDI 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1.5 SIE 1 0 0 1 Greifswald et al., 2014; Völzke et al., 2011) PD_04 DE University of FOR2107 MR (Kircher et al., 2019; 35 471 18–65 M&F SCID 1 1 0 1 1 0 0 0 0 0 0 1 0 0 1 1 0 0 3 SIE 1 1 1 1 Marburg Vogelbacher et al., 2018) PD_05 DE University of DOM-PANTHER (Gottschalk 33 45 21–55 M&F SCID 1 1 1 1 1 1 1 0 0 1 0 1 1 0 1 0 0 0 3 SIE 1 1 1 1 Wuerzburg et al., 2019; Neufang et al., 2019) PD_06 DE University of Muenster IMPS (Feldker et al., 2016) 40 41 18–46 M&F SCID 1 1 0 1 1 1 0 0 1 1 0 0 0 0 0 0 0 0 3 SIE 1 0 1 0 PD_07 DE University of Muenster Münster (Ohrmann 71 735 15–65 M&F SCID 1 1 0 1 1 0 0 0 0 0 0 1 0 0 1 1 0 0 3 PHI 1 1 1 1 neuroimaging et al., 2010; Opel cohort and panic et al., 2019) emotion processing PD_08 DE University of Muenster FOR2107 MS (Repple et al., 2020) 29 233 18–65 M&F SCID 1 1 0 1 1 0 0 0 0 0 0 1 0 0 1 1 0 0 3 SIE 1 1 1 1 PD_09 DE University Hospital Wuerzburg (Dresler et al., 2011; 18 27 21–59 M&F OTH 1 1 0 1 1 1 0 0 1 1 0 0 0 0 1 0 0 0 1.5 SIE 1 0 0 ? Wuerzburg Dresler et al., 2012) PD_10 DE University Hospital Hamburg (Dresler et al., 2012) 20 23 19–49 M&F SCID 1 1 0 1 1 1 0 0 1 1 0 0 0 0 1 0 0 0 3 SIE 1 0 0 ? Wuerzburg, Department of systems neuroscience Hamburg PD_11 IT University Vita-Salute Milan_OSR (Poletti et al., 2015) 21 196 18–65 M&F OTH Excl 1 1 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 3 PHI 1 0 1 0 San Raffaele PD_12 IT University of Milan Milan_1.5 T (Maggioni 11 21 18–66 M&F SCID 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1.5 SIE 1 1 1 1 et al., 2019) PD_13 IT University of Milan Milan_3T (Molent et al., 2018) 12 64 19–65 M&F SCID 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 3 PHI 1 1 1 1 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 2 (Continued) General sample information Clinical information Questionnaires MRI and genetic information Age-range Diagnostic Anx Other Age Psych STAI- Field T1-w Material for Sample # Country Institute Sample Key-references # PD # HC (y) Sex interview comorb comorb onset med trait ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SC2ARED strength (T) Scanner MRI DTI fMRI genetics PD_14 JP Yokohama City YCU (Asami et al., 2018) 38 68 19–58 M&F SCID 1 Excl 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1.5 SIE 1 0 0 0 University PD_15 KR CHA Bundang Cortical (Kang, Lee, & 43 2 17–62 M&F SCID 1 1 1 1 1 1 1 0 0 0 1 1 0 1 1 1 0 0 3 GE 1 1 1 1 Medical Center morphology Lee, 2017; Kim et al., 2014) PD_16 NL Amsterdam, Groningen, NESDA (Penninx et al., 2008; 44 65 18–65 M&F CIDI 1 1 1 1 1 0 1 0 0 0 0 1 0 0 1 1 0 0 3 PHI 1 0 1 1 Leiden University van Tol Medical Centers et al., 2010) PD_17 NL Amsterdam UMC, Vrije Vumc (van den Heuvel 15 23 18–58 M&F SCID 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.5 SIE 1 0 1 0 Universiteit et al., 2005) Amsterdam PD_18 UK Oxford university (Reinecke 68 20 18–65 M&F SCID 1 1 1 1 1 0 0 0 0 1 1 1 0 0 0 1 0 0 3 SIE 1 0 1 1 et al., 2015; Reinecke, Thilo, Croft, & Harmer, 2018) PD_19 US Boys Town National Boystown (Blair, Aloi, 50 56 1–18 M&F OTH 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 3 SIE 1 0 1 1 Research Hospital et al., 2019) PD_20 US University of PNC (Calkins et al., 2015; 14 428 8–23 M&F OTH 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 SIE 1 1 1 0 Pennsylvania Satterthwaite et al., 2014) PD_21 US Harvard Medical School RDoC 24 57 18–40 M&F CIDI 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 3 SIE 1 ? ? ? PD_22 US UT Health Houston_PD (Wu et al., 2015) 15 34 08–62 M&F SCID 1 1 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1.5 PHI 1 0 0 0 PD_23 US Columbia University & (Talati, Pantazatos, 17 19 18–65 M&F OTH 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1.5 PHI 1 0 0 1 New York State Schneier, psychiatric institute Weissman, & Hirsch, 2013) PD_24 US University of California INSULA, DV, SDSU (Ball et al., 2013; 45 45 20–49 M&F OTH 1 1 0 1 1 1 0 0 0 0 0 0 1 0 1 0 0 0 3 GE 1 0 1 1 - San Diego Fonzo et al., 2015) PD_25 US Weill Cornell Medical (Milrod et al., 2016) 24 0 18–70 M&F OTH 1 1 1 1 0 1 0 0 0 0 1 1 0 0 0 1 0 0 3 GE 1 0 1 0 College and University of Pennsylvania Note: Leaders of the Anx_PD subgroup: Moji Aghajani and Dick J. Veltman. 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 3 Anx_SAD (social anxiety disorder) General sample information Clinical information Questionnaires MRI and genetic information Age- Anx Material for range Diagnostic comorb Other Age Psych STAI- Field T1-w Sample # Country Institute Sample Key-references # SAD # HC (y) Sex interview rb comorb onset med trait ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SCARED strength (T) Scanner MRI DTI fMRI genetics SAD_01 BE Université Louvain (Heeren et al., 2017) 23 23 18–38 Only F MINI Excl Excl 0 Excl 1 0 0 1 0 0 0 0 0 0 1 0 0 0 3 PHI 1 0 0 0 Catholique de Louvain SAD_02 BR INPD Brazilian (Salum et al., 2015) 8 668 5–15 M&F OTH 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1.5 GE 1 1 1 1 HRC study SAD_03 CN West China HMRRC (Qiu et al., 2015) 19 20 18–32 M&F SCID Excl Excl 1 Excl 0 0 0 1 0 0 0 1 0 0 0 1 0 0 3 GE 1 1 1 0 Hospital of Sichuan University SAD_04 DE Technische Dresden SAD 20 21 18–40 M&F CIDI 1 1 1 Excl 1 0 0 1 0 0 0 0 1 0 1 0 0 0 3 SIE 1 0 1 1 Universität Dresden SAD_05 DE University FOR2107 MR (Kircher et al., 2019; 29 370 18–65 M&F SCID 1 1 0 1 1 0 0 0 0 0 0 1 0 0 1 1 0 0 3 SIE 1 1 1 1 of Marburg Vogelbacher et al., 2018) SAD_06 DE University FOR2107 MS (Repple et al., 2020) 27 238 18–65 M&F SCID 1 1 0 1 1 0 0 0 0 0 0 1 0 0 1 1 0 0 3 SIE 1 1 1 1 of Muenster SAD_07 DE University Fortuene (Kreifelts et al., 2017) 12 14 19–30 M&F SCID 1 1 0 Excl 1 0 0 1 0 0 0 0 0 0 1 0 0 0 3 SIE 1 1 1 0 of Tübingen SAD_08 DE University Muenster PACK (Heitmann et al., 2016) 45 46 19–57 M&F SCID 1 1 0 1 1 1 0 1 0 0 0 0 0 0 1 1 0 0 3 SIE 1 1 1 1 of Muenster SAD_09 DE University SHIP (Völzke et al., 2011) 32 699 31–90 M&F CIDI 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1.5 SIE 1 0 0 1 Medicine Greifswald SAD_10 DE University SP_Münster (Laeger et al., 2014; 67 490 17–59 M&F SCID 1 1 1 1 1 0 0 1 0 0 0 0 0 0 1 1 0 0 3 PHI 1 1 1 1 of Muenster Laeger et al., 2014) SAD_11 DE University TIP 27 38 18–53 M&F SCID Excl 1 1 1 1 1 0 1 0 0 0 0 0 0 1 0 0 0 3 SIE 1 1 1 1 of Muenster SAD_12 DE University Muenster SAD (Boehme et al., 2014; 19 22 19–56 M&F SCID 1 1 0 Excl 0 0 0 1 0 0 0 0 0 0 1 0 0 0 3 SIE 1 0 0 0 of Muenster Boehme, Mohr, Becker, Miltner, & Straube, 2014) SAD_13 ES Hospital del DelMar 63 99 18–61 M&F OTH Excl Excl 0 Excl 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1.5 GE 1 0 1 0 Mar Barcelona SAD_14 NL DCCN 23 24 19–57 M&F MINI 1 1 0 Excl 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1.5 SIE 1 0 1 0 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 3 (Continued) General sample information Clinical information Questionnaires MRI and genetic information Age- Anx Material for range Diagnostic comorb Other Age Psych STAI- Field T1-w Sample # Country Institute Sample Key-references # SAD # HC (y) Sex interview rb comorb onset med trait ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SCARED strength (T) Scanner MRI DTI fMRI genetics Donders Institute Nijmegen SAD_15 NL Leiden University LFLSAD (Bas-Hoogendam 11 11 18–61 M&F MINI 1 1 1 1 1 0 0 1 0 0 0 0 0 0 1 0 0 0 3 PHI 1 1 1 1 Medical Center, et al., 2018; Leiden University Bas-Hoogendam, van Steenbergen, et al., 2018) SAD_16 NL Leiden University LUMC (Cremers et al., 2014; 20 20 20–45 M&F MINI 1 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 3 PHI 1 0 1 0 Medical Center Cremers, Veer, Spinhoven, Rombouts, & Roelofs, 2015) SAD_17 NL Amsterdam, Groningen, NESDA (Penninx et al., 2008; 102 64 19–56 M&F CIDI 1 1 1 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 3 PHI 1 0 1 1 Leiden University van Tol et al., 2010) Medical Centers SAD_18 SA SU/UCT MRC Unit SU_MRC (Doruyter et al., 2016) 11 11 21–46 M&F SCID Excl Excl 1 Excl 1 0 0 1 0 0 0 0 0 0 1 0 0 0 1.5 SIE 1 0 0 1 on Anxiety & Stress Disorders SAD_19 SA SU/UCT MRC Unit UCT_MRC (Howells et al., 2015; 11 11 18–45 M&F SCID 1 1 1 Excl 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 SIE 1 0 1 1 on Anxiety & Syal et al., 2012) Stress Disorders SAD_20 SE Umea University Umea_Vox (Månsson et al., 2019) 46 42 18–52 M&F MINI & SCID 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 3 GE 1 0 1 1 SAD_21 SE Umea University Umea_Sofie (Månsson et al., 2013; 26 23 18–57 M&F SCID 1 1 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 3 GE 1 0 1 1 Månsson et al., 2015) SAD_22 TR Istanbul University Istanbul (Tükel et al., 2015) 34 22 23–45 M&F SCID 1 1 0 Excl 0 0 0 1 0 0 0 1 0 0 0 1 0 0 1.5 PHI 1 1 1 0 SAD_23 US Baylor College of Baylor (Curtis et al., 2019; 72 149 12–79 M&F SCID 1 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 3 SIE 1 1 1 1 Medicine Gosnell et al., 2020) SAD_24 US Boys Town National Boystown (Blair, Aloi, et al., 2019; 50 44 11–18 M&F OTH 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 3 SIE 1 0 1 1 Research Hospital Blair, White, et al., 2019) SAD_25 US Columbia University Columbia_SAD (Talati et al., 2013; 16 16 19–53 M&F OTH 1 1 0 Excl 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1.5 GE 1 0 1 0 & New York State Talati, Pantazatos, Psych. Institute Hirsch, & Schneier, 2015) (Continues) 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 3 (Continued) General sample information Clinical information Questionnaires MRI and genetic information Age- Anx Material for range Diagnostic comorb Other Age Psych STAI- Field T1-w Sample # Country Institute Sample Key-references # SAD # HC (y) Sex interview rb comorb onset med trait ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SCARED strength (T) Scanner MRI DTI fMRI genetics SAD_26 US Columbia University & Columbia_SPP (Pantazatos, Talati, 16 19 21–53 M&F SCID 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1.5 GE 1 0 1 0 New York State Schneier, & Hirsch, Psychiatric Institute 2014; Talati et al., 2013) SAD_27 US UT Health Houston_SAD 34 34 8–61 M&F SCID 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1.5 PHI 1 0 0 0 SAD_28 US University PNC (Calkins et al., 2015; 328 428 8–23 M&F OTH 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 SIE 1 1 1 0 of Pennsylvania Satterthwaite et al., 2014) SAD_29 US National Institute SDAN (Gold et al., 2020; Gold 80 95 8–22 M&F SCID & KSADS 1 1 0 Excl 1 0 0 1 0 0 0 0 0 0 1 0 1 1 3 GE 1 1 1 1 of Mental Health et al., 2017) SAD_30 US University of UCSD_Ball_SDSU (Campbell-Sills et al., 2011) 17 19 17–33 M&F SCID 1 1 0 Excl 1 1 0 1 0 0 0 0 1 0 1 0 0 0 3 GE 1 0 1 0 California-San Diego SAD_31 US University of California - UCSD_Sapient_INSULA (Fonzo et al., 2015) 44 26 18–53 M&F MINI 1 1 0 Excl 1 1 0 0 0 0 0 0 1 0 1 0 0 0 3 GE 1 0 1 1 San Diego SAD_32 US Vanderbilt University Vanderbilt (Clauss et al., 2014; Clauss 10 15 19–26 M&F SCID 1 1 0 Excl 1 1 0 0 0 0 0 0 0 0 1 0 0 0 3 PHI 1 1 1 1 et al., 2014) SAD_33 US Washington University Washington 19 30 8–12 M&F KSADS 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 3 SIE 1 0 1 0 SAD_34 US University of Illinois at UIC (Phan et al., 2013) 12 11 22–50 M&F SCID 1 1 1 Excl 1 0 0 1 0 0 0 0 0 0 1 0 0 0 3 GE 1 1 0 1 Chicago SAD_35 US Institute of Living/Hartford IOL (Rabany et al., 2017) 11 21 21–71 M&F MINI 1 1 0 1 0 0 0 1 0 0 0 1 1 0 0 1 0 0 3 SIE 1 0 1 0 hospital Note: Leaders of the Anx_SAD subgroup: Janna Marie Bas-Hoogendam, Nynke A. Groenewold, Dan J. Stein, Nic J. A. van der Wee. 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 4 Anx_SP (specific phobia) General sample information Clinical information Questionnaires MRI and genetic information Specific Field Material Age-range Diagnostic Anx Other Age Psych STAI- phobia strength T1-w for Sample # Country Institute Sample Key-references # SP # HC (y) Sex interview comorb comorb onset med trait ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SCARED questionnaires (T) Scanner MRI DTI fMRI genetics SP_01 AT University of Graz Graz dental phobia (Wabnegger, Scharmüller, 36 36 20–56 M&F OTH 1 1 1 Excl 0 0 0 0 0 0 0 0 0 0 0 0 0 0 DAS, FDP 3 SIE 1 0 0 0 & Schienle, 2014) SP_02 AT University of Graz Graz dental phobia II (Schienle, Scharmüller, 45 41 19–62 M&F SCID 1 1 1 Excl 0 0 0 0 0 0 0 0 0 0 0 0 0 0 DAS 1.5 SIE 1 0 0 0 Leutgeb, Schäfer, & Stark, 2013) SP_03 BR INPD Brazilian HRC study (Salum et al., 2015) 89 516 5–15 M&F OTH 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 DAWBA 1.5 GE 1 1 1 1 SP_04 DE Ruhr-Universität Bochum dental 18 0 27–60 M&F OTH 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 DAS 1.5 SIE 1 0 1 1 Bochum phobia SP_05 DE Technische Dresden specific (Hilbert, Evens, Isabel 59 37 18–46 M&F CIDI 1 1 0 Excl 0 1 0 0 0 0 0 0 0 0 1 0 0 0 SNAQ, DFS 3 SIE 1 0 1 0 Universität phobia subtypes Maslowski, Wittchen, Dresden & Lueken, 2015) SP_06 DE Technische CRC940C5 None 100 82 18–49 M&F CIDI 1 1 1 Excl 1 0 0 0 0 0 0 0 0 0 1 0 0 0 FSQ 3 SIE 1 0 1 0 Universität Dresden SP_07 DE University of Gießen BION_SP (Schweckendiek 15 14 18–31 M&F OTH Excl Excl 0 Excl 1 0 0 0 0 0 0 0 0 0 0 0 0 0 SPQ 1.5 SIE 1 0 0 0 et al., 2011) SP_08 DE University of Greifswald spider/ (Wendt, Schmidt, Lotze, & 20 25 18–29 Only F OTH 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SPQ, SNAQ 1.5 SIE 1 0 1 0 Greifswald Snake phobia Hamm, 2012) SP_09 DE University Medicine SHIP (Völzke et al., 2011) 148 699 31–90 M&F CIDI 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1.5 SIE 1 0 0 1 Greifswald SP_10 DE Friedrich-Schiller- Jena spider phobia (Lipka, Miltner, & 14 15 19–49 Only F SCID Excl Excl 0 Excl 1 0 0 0 0 0 0 0 0 0 0 0 0 0 SPQ 3 SIE 1 0 1 0 Universität Jena Straube, 2011) SP_11 DE University of FOR2107 MR (Kircher et al., 2019; 16 516 18–65 M&F SCID 1 1 0 1 1 0 0 0 0 0 0 1 0 0 1 1 0 0 0 3 SIE 1 1 1 1 Marburg Vogelbacher et al., 2018) SP_12 DE University of FOR2107 MS (Repple et al., 2020) 28 247 18–65 M&F SCID 1 1 0 1 1 0 0 0 0 0 0 1 0 0 1 1 0 0 0 3 SIE 1 1 1 1 Muenster SP_13 DE University of Muenster dental (Feldker et al., 2017) 19 19 18–60 M&F SCID Excl Excl 0 Excl 1 1 0 0 0 0 0 0 0 0 1 0 0 0 DAS 3 SIE 1 0 1 0 muenster phobia SP_14 DE University of Muenster spider (Münsterkötter 29 478 18–59 M&F SCID 1 1 0 Excl 0 0 0 0 0 0 0 0 0 0 1 0 0 0 SPQ, FSQ 3 PHI 1 1 1 1 Muenster phobia et al., 2015) SP_15 DE University of SFBTRR-58 project (Schwarzmeier et al., 2019) 87 0 18–56 M&F SCID 1 1 1 1 1 1 1 1 0 1 0 0 1 0 1 0 0 0 SPQ 3 SIE 1 0 1 1 Muenster C09 (SpiderVR) SP_16 DE University of Wuerzburg spider (Wiemer et al., 2014) 18 18 18–37 Only F SCID Excl Excl 0 Excl 1 0 0 0 0 0 0 0 0 0 1 0 0 0 SPQ, FSQ 1.5 SIE 1 0 0 0 Wuerzburg phobia (Continues) 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 4 (Continued) General sample information Clinical information Questionnaires MRI and genetic information Specific Field Material Age-range Diagnostic Anx Other Age Psych STAI- phobia strength T1-w for Sample # Country Institute Sample Key-references # SP # HC (y) Sex interview comorb comorb onset med trait ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SCARED questionnaires (T) Scanner MRI DTI fMRI genetics SP_17 DE University of Wuerzburg spider 13 12 19–42 M&F SCID 0 0 0 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 FSQ, FEAS 1.5 SIE 1 0 1 0 Wuerzburg phobia II SP_18 DE University of Wuerzburg spider 10 6 18+ ? SCID 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.5 SIE 1 0 1 0 Wuerzburg phobia III SP_19 DE University Hospital SFBTRR-58 project (Schwarzmeier et al., 2019) 87 0 18–65 M&F SCID 1 1 1 1 1 1 1 1 0 1 0 0 1 0 1 0 0 0 SPQ 3 SIE 1 0 1 1 of Wuerzburg C09 (SpiderVR) SP_20 DE Multicenter study PROTECT-AD: (Heinig et al., 2017) 57 0 18–67 M&F CIDI 1 1 1 Excl 0 1 0 1 1 1 0 1 0 1 1 0 0 0 DSM-5-SP 3 SIE 1 0 1 1 (University of Specific phobia Marburg) sample SP_21 ES Universidad de La Teneriffa animals (Rivero, Herrero, Viña, 37 41 18–60 M&F OTH Excl Excl 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 S-R IA 3 GE 1 0 1 0 Laguna phobia  Alvarez-Pérez, & Peñate, 2017) SP_22 NL University of RepSpi (Visser, Haver, Zwitser, 18 20 18–43 M&F OTH 0 0 0 Excl 1 1 0 0 0 0 0 0 0 0 0 0 0 0 SPQ 3 PHI 1 0 1 0 Amsterdam Scholte, & Kindt, 2016) SP_23 NL Maastricht University SPIN (Zilverstand, Sorger, 7 7 18–29 ? MINI Excl Excl 1 Excl ? ? ? ? ? ? ? ? ? ? ? ? ? ? SPQ, FSQ 3 SIE 1 0 1 0 Kaemingk, & Goebel, 2017) SP_24 NL Maastricht University SPIN NF (Zilverstand et al., 2017) 18 0 19–26 ? MINI Excl Excl 1 Excl ? ? ? ? ? ? ? ? ? ? ? ? ? ? SPQ, FSQ 3 SIE 1 0 1 0 SP_25 NL Maastricht University SMARTSCAN (Lange et al., 2019) 46 47 16–25 ? MINI 1 1 0 Excl 1 0 0 0 0 0 0 0 0 0 0 0 0 0 FSQ 3 SIE 1 1 1 1 PHOBIA SP_26 NL Maastricht PHOBIA exposure (Lange et al., 2016) 20 0 19–29 Only F MINI 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SPQ 3 PHI 1 1 0 0 University, Katholieke Universiteit Leuven SP_27 PL SWPS University of Czuwaj (Michałowski et al., 2017) 25 11 19–36 M&F OTH 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 FSS 3 SIE 1 1 1 0 Social Sciences and Humanities SP_28 SE Uppsala University Uppsala spider (Björkstrand et al., 2016) 47 0 20–55 M&F OTH 0 0 1 Excl 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SPQ 3 PHI 1 1 1 0 phobia SP_29 UK COMIC Research/ Spider phobia (Wright et al., 2013; 12 0 17–42 M&F OTH 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 FSQ 3 GE 1 0 0 0 LYPFT Wright et al., 2015) SP_30 US National Institute of SDAN (Gold et al., 2020; Gold 125 225 10–51 M&F SCID & KSADS 1 1 0 Excl 0 0 0 1 0 0 0 0 0 0 1 0 0 0 None 3 GE 1 0 ? 0 Mental Health et al., 2017) 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Material Scanner MRI DTI fMRI genetics 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License for 0 1 1 1 MRI and genetic information alterations in the microstructure of white matter tracts based on DTI 1 0 T1-w data (Kochunov et al., 2015), in the connectivity of brain functional 1 1 networks utilizing resting-state functional (f)MRI (Adhikari PHI SIE strength et al., 2018), and in the responsivity of brain regions to anxiety-related cues utilizing task-related functional (f)MRI paradigms (under develop- Field ASI BAI LSAS PAS ACQ PDSS HAM_A PSWQ GAD_7 BDI-II HAM_D CDI SCARED questionnaires (T) 3 3 ment). Then, ENIGMA approaches that assess more subtle variations in brain morphology including investigation of regional subfields Specific phobia None (e.g., of hippocampus and amygdala (Salminen et al., 2019; Saygin 0 et al., 2017)), subcortical shape (Ching et al., 2020; Gutman et al., 2015; Gutman, Wang, Rajagopalan, Toga, & Thompson, 2012; 0 0 Ho et al., 2019), and brain asymmetry (Kong et al., 2018), can be key 0 0 next steps. 0 0 0 1 4 | DATA AVAILABILITY WITHIN THE 0 0 E N I G M A - A N X I E T Y W O R K I N G GR O U P 0 0 At present, more than 180 researchers from 80 research groups based 0 0 within 59 institutes around the world (16 countries—see Figure 2) are 0 0 members of the ENIGMA-Anxiety Working Group. In Tables 1–4, 0 0 details on the MRI samples and data-collection within the participat- 0 0 ing cohorts within the four ENIGMA-Anxiety subgroups are summa- 0 0 rized. It should be noted that the numbers of subjects in these tables Questionnaires 0 0 represent initial sample sizes, before exclusion of data due to, for 0 1 Psych STAI- example, comorbidity with other severe psychopathology (e.g., bipolar trait 1 1 disorder), and that data from individual subjects can be included in comorb comorb onset med Excl 1 several subgroups due to comorbidity; in addition, healthy control par- Age ticipants from samples included in multiple subgroups are nonunique. 0 0 Other Here, we wish to highlight several interesting and valuable features of 1 1 the available neuroimaging data that may well be unique to the Anx Clinical information ENIGMA-Anxiety Working Group. 1 1 First, to our best knowledge, the ENIGMA-Anxiety Working Diagnostic interview Group is the largest neuroimaging (MRI) collaboration (with respect to SCID OTH sample size and number of collaborators) to date focusing on anxiety M&F M&F disorders, encompassing a broad range of studies varying in geo- Sex Age-range graphic location, clinical setting, and disease stage. The individual sub- 10–25 8–23 groups each include over 800 (Anx_PD) or even over 1,000 # SP # HC (y) (Anx_GAD, Anx_SAD, Anx_SP) anxiety patients and as such the total 426 428 Note: Leaders of the Anx_SP subgroup: Kevin Hilbert and Ulrike Lueken. 9 sample size is substantial, even when considering anticipated data loss (Clauss, Avery, et al., 2014; 9 due to, for example, insufficient scan quality and segmentation failures. (Calkins et al., 2015; Satterthwaite Clauss, Seay, Key-references Second, there is considerable overlap in recorded clinical charac- et al., 2014) et al., 2014) teristics such as age of onset and symptom severity measures within and across subgroups, and data are available for a range of possible confounders (for example, medication-use at the time of scan). At the Vanderbilt phobia same time, there are several limitations regarding the availability of sample more detailed clinical characteristics (for example, treatment use dur- Sample PNC ing the lifetime, adverse life-events, level of depressive symptoms). Importantly, the majority of samples within ENIGMA-Anxiety col- (Continued) Pennsylvania lected information about comorbidity with other anxiety disorders, as University University of Vanderbilt Sample # Country Institute well as with nonanxiety disorders. As to be expected, this comorbidity General sample information is considerable, and most prominent in the Anx_GAD subgroup. In a first exploration of data in 910 GAD patients, 299 met criteria for US US TABLE 4 SP_31 SP_32 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 98 BAS-HOOGENDAM ET AL. FIGURE 2 Institutes participating in ENIGMA-Anxiety—world map concurrent SAD, 164 met criteria for concurrent MDD, and 132 met samples. The analyses revealed subtle alterations in the left thalamus criteria for concurrent SP. Comorbidity rates vary considerably across (patients < controls), and the right amygdala and right hippocampus, samples as a function of recruitment setting and inclusion strategy, with smaller volumes for patients with higher severity of SAD symp- introducing heterogeneity. Importantly, comorbidity is inherent to the toms (Groenewold et al., 2018). Results from these preliminary ana- clinical anxiety phenotype. Therefore, the inclusion of patients with lyses were not significant after correction for multiple comparisons. comorbidity improves the generalizability of findings while allowing Since then, data availability has more than doubled, as IPD has been exploration of moderating effects of comorbid diagnoses. submitted for 16 additional cohorts. Presently, one site is continuing to work to provide IPD data, which will allow for mega-analysis with- out bias related to attrition. Final analyses for the Anx_SAD subcorti- 5 | WORK IN PROGRESS cal and cortical projects are scheduled for later in 2020. For the Anx_PD and Anx_SP subgroups, it was not yet possible to Projects examining subcortical volumes and cortical thickness and conduct preliminary analyses, but analyses for these subgroups are cortical surface area are currently being performed within all four scheduled for 2020. The first set of analyses within Anx_PD will subgroups of ENIGMA-Anxiety. These studies are based on individual- simultaneously probe cortical and subcortical morphology in PD with participant data (IPD), meaning that anonymized summary statistics at and without agoraphobia, using a mega-analytical approach. The the level of individual output are shared (Anx_PD, Anx_SAD, Anx_SP), ANX_SP project will investigate differences between patients and or on raw imaging data (Anx_GAD) (cf. discussion provided in healthy controls, but will also include analyses examining potential dif- (Thompson et al., 2020)). For the Anx_PD, Anx_SAD, and Anx_SP ferences between specific phobia subtypes. Prior research indicated a subgroups, detailed protocols enabling harmonized data processing distinct psychophysiological response pattern for blood–injection– have been distributed to individual sites, and these local analyses are injury phobia compared to more prototypical animal phobias currently being performed or have been completed. (McTeague, Lang, Wangelin, Laplante, & Bradley, 2012; Thyer & With respect to the Anx_SAD subgroup, preliminary results on Curtis, 1985). Similarly, there were at least partly different neural cor- SAD-related differences in subcortical volumes have been presented relates between these subtypes, but sample sizes were small (Hilbert, at the SOBP and OHBM 2018 meetings (Groenewold et al., 2018). Evens, et al., 2015; Lueken et al., 2011). The ENIGMA-Anxiety SP pro- The analyses, which involved only a subset of the present data set ject presents a rare opportunity to examine the replicability of these (SOBP 2018 meeting: n = 404 patients with SAD and 775 healthy findings with considerably increased statistical power. controls, from 14 adult cohorts; OHBM 2018 meeting: additional An innovative approach of the Anx_GAD subgroup involved pre- n = 98 patients with SAD and 106 healthy controls, from two pediatric registration of the data-analytic plan (publicly available at osf.io/yxajs); cohorts) used a meta-analytic approach to pool effect sizes across furthermore, the group adopted a comprehensive approach to address 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License BAS-HOOGENDAM ET AL. 99 potential sources of heterogeneity in effects. This plan included OCD, ADHD, and ASD (Boedhoe et al., 2019), and a cross-disorder or 12 statistical contrasts involving 16 subcortical regions, as well as transdiagnostic approach is particularly relevant to anxiety disorders vertex-wise cortical thickness and surface area as dependent vari- given their high comorbidity rates (Janiri et al., 2019; Kunas ables, a random intercept per scanner, and random slopes per site for et al., 2019). Notably, an early meta-analysis found that patients with two sets of variables. The first set of analyses included GAD, sex, age, anxiety disorders (including OCD and PTSD) showed decreased bilat- age-squared (age2) and their interactions, IQ, years of education, med- eral gray matter volumes in dorsomedial frontal/anterior cingulate ication use at time of the scan, comorbidity, and scanner. The second gyri, but that individuals with OCD had increased bilateral gray matter set also included total surface area, mean thickness and total intracra- volumes in the lenticular/caudate nuclei (Radua, van den Heuvel, Sur- nial volume as covariates. Permutation tests controlled for multiple guladze, & Mataix-Cols, 2010). It would be timely to return to such testing across all factors (Winkler, Ridgway, Webster, Smith, & work; we are particularly interested in comparisons of anxiety disor- Nichols, 2014). Similarly to Anx_SAD, preliminary analyses of the ders with OCD and PTSD, as well as with MDD (cf. (Gong Anx_GAD subgroup using subcortical regions, as well as thickness and et al., 2019)). surface area in 68 cortical regions as dependent variables, have so far Second, we are enthusiastic about extending our analyses to revealed no significant associations between GAD and brain structure include genetic data (also see (Mufford et al., 2017)), a key goal of the when correcting for multiple comparisons (Harrewijn et al., 2020), ENIGMA Consortium. In proof of principle work, we have explored despite the presence of effect sizes of comparable magnitude seen in the overlap between genes contributing to anxiety disorders and ENIGMA research on other mental disorders, including MDD and genes contributing to brain structure (van der Merwe et al., 2019). OCD. Importantly, these findings are based on a mega-analytic We obtained summary statistics of GWAS of anxiety disorders, PTSD, approach. The Anx_GAD subgroup chose this approach to address the and of subcortical brain volumes, and conducted SNP effect concor- high comorbidity between GAD and other disorders (Beesdo, dance analysis (SECA) and linkage disequilibrium (LD) analyses. Signifi- Knappe, & Pine, 2009), as comorbidity hinders attempts to differenti- cant concordance was observed between variants associated with ate associations that brain structure shows with GAD as opposed to increased anxiety risk and variants associated with smaller amygdala associated disorders (Pine, Cohen, Gurley, Brook, & Ma, 1998). volume, consistent with a range of translational neuroscience research Random-effects models can assess cross-site heterogeneity both in focused on the role of this structure in anxiety disorders. However, GAD-related findings and in effects of comorbidity, as well as other these findings need to be interpreted with caution, given heterogene- site-specific differences. These models were immediately feasible: ity and limited power in the input GWAS (for recent work, see: 25 sites provided raw data, and in addition structural MRI data from (Satizabal et al., 2019); PGC-Anxiety GWAS underway). These genetic three publicly available imaging repositories were downloaded overlap analyses could be extended to involve cortical structure, for (Adolescent Brain Cognitive Development Study (Casey et al., 2018; example with summary statistics derived from ENIGMA's recent Volkow et al., 2018), Child Mind Institute Healthy Brain Network large-scale GWAS of cortical structure (Grasby et al., 2020). Any (Alexander et al., 2017), and Duke Preschool Anxiety Study regions of genetic overlap can be queried for alterations in gene (Carpenter et al., 2015)). The analytic approach of the Anx_GAD group expression, and the aberrant genes can be categorized by cell type or is outlined elsewhere in more detail (Zugman et al., 2020, this issue). function (an approach called virtual histology; (Patel et al., 2020)). In Analyses on subcortical and cortical characteristics are currently being addition, we will plan analyses of polygenic risk scores for anxiety, finalized. building on GWAS summary statistics and odds ratios for the disor- We welcome sharing data with researchers, requiring only that ders, to compute individual measures of risk based on a person's they submit an analysis plan for a secondary project to the leading genome. In the case of Alzheimer's disease, we know that the major team of the Working Group (http://enigma.ini.usc.edu/ongoing/ risk haplotypes (such as APOE4) and measures of overall polygenic enigma-anxiety/). Once this analysis plan is approved, access to the risk are robustly associated with net shifts in volumes of key brain relevant data will be provided contingent on data availability and local structures implicated in the disease, and the timing of these shifts PI approval. Where applicable, distribution of analysis protocols to across the lifespan can be identified with great power using genetic sites will be facilitated. analysis of neuroimaging data (Brouwer et al., 2020). As the PGC- Anxiety GWAS increases in power and discovers more genome-wide significant loci, we will be able to see which phenotypes are shifted in 6 | SOME RECOMMENDATIONS FOR THE people at high polygenic risk, and when these shifts occur. F I E L D A N D P E R S P E C T I V E S F O R TH E F U T U R E Third, in alignment with the focus on translational neuroscience OF ENIGMA-ANXIETY exemplified by the Research Domain Criteria (RDoC; (Insel, 2014)), it would be useful to move beyond work that is framed using traditional Once these ongoing projects are completed, we foresee several future diagnostic boundaries, and toward research that addresses trans- research directions. First, the ENIGMA-Anxiety Working Group is well species and trans-diagnostic behavioral dimensions underpinned by placed to conduct rigorous comparisons of data both across anxiety specific neuronal circuitry and molecular mechanisms (Grillon, Robin- disorders, and with other neuropsychiatric conditions (cf. information son, Cornwell, & Ernst, 2019). In line with this, neurobiological candi- in Tables 1–4). ENIGMA has already initiated such work in comparing date endophenotypes of anxiety disorders, to be assessed by family- 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 100 BAS-HOOGENDAM ET AL. genetic studies, may inform about the stability of observed alterations potential value of discovery research on the neurobiology of mental and could potentially serve as risk signatures (Bas-Hoogendam disorders) (Stein et al., 2015; Stein & Wegener, 2017). et al., 2016; Bas-Hoogendam et al., 2019; Bas-Hoogendam, Harrewijn, Despite these promising future research directions, several limita- et al., 2018; Bas-Hoogendam, van Steenbergen, et al., 2018; Bas- tions of the large-scale approach taken by ENIGMA need to be Hoogendam, van Steenbergen, Tissier, van der Wee, & emphasized. Although it can be considered good practice to re-utilize Westenberg, 2019; Bas-Hoogendam, van Steenbergen, van der Wee, & valuable imaging data from vulnerable patient groups, analyses of Westenberg, 2020; Bearden & Freimer, 2006; Beauchaine & aggregated data sets are limited by variations in data acquisition and Constantino, 2017; Glahn et al., 2012; Glahn, Thompson, & phenotyping of the samples. The resulting noise may decrease sensi- Blangero, 2007; Hasler, Drevets, Gould, Gottesman, & Manji, 2006; tivity to detect effects. To improve the comparability of samples, the Lenzenweger, 2013; Miller & Rockstroh, 2013). Furthermore, behav- ENIGMA-Anxiety Working Group plans (sub-)analyses using DSM ioral innate trait characteristics, such as behavioral inhibition, may help diagnoses established with validated clinical interviews, which can be to predict the development of anxiety disorders, and may involve supplemented with sensitivity analyses to account for variations in mechanisms that can be investigated in nonhuman experimental data availability across sites. Furthermore, the use of harmonized models, in healthy individuals, and in a range of mental disorders processing protocols executed locally by participating sites offers (Auday & Pérez-Edgar, 2019; Blackford, Clauss, & Benningfield, 2018; some protection against the selection bias that can arise from data Clauss & Blackford, 2012; Henderson, Pine, & Fox, 2015; Muris, van sharing restrictions. Nonetheless, local processing makes it more chal- Brakel, Arntz, & Schouten, 2011). lenging to perform fine-grained analyses and limits model complexity, Fourth, ENIGMA has a growing interest in using multivariate pat- especially in the context of interaction effects and restricted ranges tern recognition and machine learning to explore neuroimaging data in within sites. This limitation can be addressed by planning mega- search of individual-level inferences (cf. (Poldrack, Huckins, & analyses on individual participant (imaging) data in addition to meta- Varoquaux, 2019)). ENIGMA-OCD has, for example, performed multi- analyses. Moreover, an improved spatial resolution can be achieved variate analysis of structural neuroimaging data on 46 data sets using with vertex-wise structural analyses (cf. ongoing work by the GAD machine learning methods for group classification. Classification per- subgroup) or seed-based functional connectivity analyses. Finally, formance for OCD versus controls was poor, but good classification although large-scale analyses come with an increase in power to performance was achieved within subgroups of patients, split according detect small effect sizes, it is important to bear in mind that any statis- to their medication status (Bruin, Denys, & van Wingen, 2019). How- tically significant findings are not necessarily clinically significant and ever, with sufficiently large and detailed data sets, future work may ulti- may not apply to individual patients. Hence, we intend to interpret mately open new avenues for generating predictive markers that can our results with appropriate caution. be applied to individual patients, to inform clinical decision-making regarding diagnosis and treatment (Durstewitz, Koppe, & Meyer- Lindenberg, 2019; Lueken & Hahn, 2016; Woo, Chang, Lindquist, & 7 | CONC LU SION Wager, 2017). Fifth, it would be ideal if prospective neuroimaging data on anxi- Research on anxiety disorders has greatly advanced in recent decades: ety disorders could be collected at a range of sites, using similar proto- we have a much better appreciation of their early onset, high preva- cols, and in alignment with clinical interventions over time. Until that, lence, and significant morbidity and comorbidity; we have developed research within the ENIGMA-Anxiety Working Group will suffer from models of their underlying neurocircuitry and obtained insights into several limitations of current neurobiological and neuroimaging their significant heritability and polygenic architecture; and we have research, including relatively sparse clinical data on participating indi- introduced a range of evidence-based interventions encompassing viduals (Etkin, 2019). Prospectively planned research would ensure both pharmacotherapy and psychotherapy. At the same time, much that clinical data as well as confounding variables are carefully col- remains to be accomplished: there is a large treatment gap for anxiety lated, and longitudinal designs would allow more detailed investiga- disorders and our models require much greater depth. Importantly, tion of the mechanisms underlying anxiety disorders as well as of the our findings require much more replicability if they are to form the impact of interventions (Gloster et al., 2009; Heinig et al., 2017; Mån- basis of a personalized medicine approach to intervention. Such an sson et al., 2016; Phan et al., 2013; Schwarzmeier et al., 2019; Steiger approach seems crucial, as many individuals with anxiety disorders do et al., 2017; Talati et al., 2015; Yang et al., 2019); cf. the accomplish- not respond or remit to first-line intervention. ments by the Alzheimer's Disease Neuroimaging Initiative (ADNI), an Against this context, the ENIGMA Consortium in general, and the ongoing, longitudinal, multicenter study aimed at developing clinical, ENIGMA-Anxiety Working Group in particular, are exciting collabora- imaging, genetic, and biochemical biomarkers for the early detection tions with much potential. First, they exemplify how cross-national and tracking of Alzheimer's disease using standardized methods collaboration can be useful in obtaining data sets with sufficient sta- (Mueller et al., 2005; Weiner et al., 2013). There is a need to integrate tistical power to obtain robust and replicable results even when effect the concerns of global mental health (which have focused on the sizes are small. Second, they illustrate how access to big data (brain importance of implementing treatments in real-world contexts) with imaging, genetics) together with sophisticated analytic approaches those of translational neuroscience (which have focused on the can yield novel and significant findings. Although based firmly within 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License BAS-HOOGENDAM ET AL. 101 the conceptual framework of translational neuroscience, many of the SCID Structured Clinical Interview for DSM-IV disorders (First, concerns and methods of ENIGMA (e.g., ensuring diverse samples, Spitzer, Gibbon, Williams, & Benjamin, 1998) scaling up methods) are redolent of the best features of global mental Anx comorb Comorbidity with other anxiety disorders. health. Taken together, ENIGMA-Anxiety exemplifies the synergy Other comorb Comorbidity with psychopathology other than found at the intersection of global mental health and clinical neurosci- anxiety (major depressive disorder, obsessive–compulsive disorder, ence, and promises to further contribute to advancing the field of anx- post-traumatic stress disorder, substance use dependence, other DSM iety disorders in particular. diagnoses). Psych med Psychotropic medication. Tables Information box belonging to the tables Questionnaires Tables 1–4 summarize samples that have been submitted to the ENIGMA-Anxiety Working Group (either individual patient data (IPD) or General anxiety raw scans), or that are in the process of submission. The tables list for STAI-trait State Trait Anxiety Inventory (Spielberger & Vagg, 1984). each sample whether certain information was collected in the original ASI Anxiety Sensitivity Index (Reiss, Peterson, Gursky, & study. Importantly, the numbers of subjects in these tables represent ini- McNally, 1986) tial sample sizes, before exclusion of data due to, for example, comorbid- BAI Beck Anxiety Inventory (Steer & Beck, 1997). ity with other severe psychopathology (e.g., bipolar disorder); furthermore, data from individual subjects can be included in several sub- Social anxiety groups due to anxiety disorder comorbidity, and healthy control partici- LSAS Liebowitz Social Anxiety Scale (Heimberg et al., 1999) pants from samples included in multiple subgroups can be nonunique. Panic disorder and agoraphobia PAS Panic and Agoraphobia Scale (Bandelow, 1995). List of abbreviations used in tables ACQ Agoraphobic Cognitions Questionnaire (Chambless, Caputo, Bright, & Gallagher, 1984) General PDSS Panic Disorder Severity Scale (Shear et al., 1997) 0 No, not investigated/information not collected. Generalized anxiety 1 Yes, information was collected. HAM_A Hamilton Anxiety Rating Scale (Hamilton, 1959). ? No information available yet. PSWQ Penn State Worry Questionnaire (Molina & Borkovec, 1994). GAD_7 Generalized Anxiety Disorder 7 item scale (Spitzer, General sample information Kroenke, Williams, & Löwe, 2006) GAD Patients with a diagnosis of generalized anxiety disorder. Depression PD Patients with a diagnosis of panic disorder. BDI-II Beck Depression Inventory (second edition) (Beck, Steer, & SAD Patients with a diagnosis of social anxiety disorder. Carbin, 1988) SP Patients with a diagnosis of specific phobia. HAM_D Hamilton Depression Rating Scale (Hamilton, 1960). HC Healthy control participants. CDI Child Depression Inventory (Kovacs, 1985). M&F Males and females were included in the study. Only F Only females were included in the study. Pediatric anxiety SCARED Screen for Child Anxiety Related Emotional Disorders (Muris et al., 1998) Clinical information Excl This was an exclusion criterion for this sample. Specific phobia questionnaires CIDI Composite Interview Diagnostic Instrument version (Kessler & Ustün, 2004). Only in Table 4 KSADS Schedule for Affective Disorders and Schizophrenia for DAS Dental Anxiety Scale (Corah, 1969). School-Age Children (Ambrosini, 2000). DAWBA Development and Well-Being Assessment (Goodman, MINI Mini-International Neuropsychiatric Interview (Sheehan Ford, Richards, Gatward, & Meltzer, 2000) et al., 1997) DFS Dental Fear Survey (Kleinknecht, Klepac, & OTH Other diagnostic interview. Alexander, 1973; Tönnies, Mehrstedt, & Eisentraut, 2002) 10970193, 2022, 1, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hbm.25100 by Readcube (Labtiva Inc.), Wiley Online Library on [06/06/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 102 BAS-HOOGENDAM ET AL. DSM-5-SP Dimensional Specific Phobia Scale for DSM-5 International Staff Exchange Scheme grant 'European and South African (Lebeau et al., 2012) Research Network in Anxiety Disorders' (EUSARNAD). FDP Fear of Dental Pain Questionnaire (Van Wijk & Hoogstraten, 2003). CONFLIC T OF INT ER E ST FEAS Fragebogen zu Ekel und Angst vor Spinnen [Anxiety and N. J. received a research grant from Biogen, Inc., for work unrelated to disgust towards Spiders Questionnaire] (Schaller, Gerdes, & this manuscript. P. M. T received a research grant from Biogen, Inc., for Alpers, 2006) work unrelated to this manuscript. N. J. A. W. has received consultancy FSS Fear Survey Schedule. honoraria from Wyeth, Pfizer, Eli Lilly and Servier, for work unrelated to SNAQ Snake Phobia Questionnaire (Klorman, Weerts, Hastings, this manuscript. D. J. S. has received research grants and/or consultancy Melamed, & Lang, 1974) honoraria from Lundbeck, ORION Pharma and Sun, for work unrelated to SPQ Spider Phobia Questionnaire (Klorman et al., 1974) this manuscript. All other authors declare no potential conflict of interest. S-RIA S-R Inventory of Anxiousness (Endler, Hunt, & Rosenstein, 1962) DATA AVAILABILITY STAT EMEN T Data sharing is not applicable to this article as no new data were cre- ated or analyzed in this study. MRI and genetic information OR CID T Tesla. Janna Marie Bas-Hoogendam https://orcid.org/0000-0001-8982- T1-w-MRI T1-weighted structural MRI scan. 1670 DTI Diffusion tensor imaging scan. Sophia I. Thomopoulos https://orcid.org/0000-0002-0046-4070 fMRI functional MRI scan (during rest or related to a task). Anderson M. Winkler https://orcid.org/0000-0002-4169-9781 GE General Electric scanner. PHI Philips scanner. RE FE RE NCE S OTH Other scanner. Adhikari, B. M., Jahanshad, N., Shukla, D., Turner, J., Grotegerd, D., SIE Siemens scanner. Dannlowski, U., … Kochunov, P. (2018). A resting state fMRI analysis Material for genetics Blood or saliva collected for genetic ana- pipeline for pooling inference across diverse cohorts: An ENIGMA rs- lyses, or GWAS data available. fMRI protocol. Brain Imaging and Behavior, 13, 1453–1467. https:// doi.org/10.1007/s11682-018-9941-x Alexander, L. M., Escalera, J., Ai, L., Andreotti, C., Febre, K., Mangone, A., … ACKNOWLEDGMENTS Milham, M. P. (2017). An open resource for transdiagnostic research in J. M. B. H. none. N. A. G was supported by a Claude Leon Postdoc- pediatric mental health and learning disorders. Science Data, 4, toral Fellowship. M. A. none. G. F. F. is supported by the Intramural 170181. https://doi.org/10.1038/sdata.2017.181 Research Training Award (IRTA) program within the National Institute Alonso, J., Liu, Z., Evans-Lacko, S., Sadikova, E., Sampson, N., Chatterji, S., … Thornicroft, G. 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