ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

The ENIGMA sports injury working group - an international collaboration to further our understanding of sport-related brain injury

Sport-related brain injury is very common, and the potential long-term effects include a wide range of neurological and psychiatric symptoms, and potentially neurodegeneration. Around the globe, researchers are conducting neuroimaging studies on primarily homogenous samples of athletes. However, neuroimaging studies are expensive and time consuming, and thus current findings from studies of sport-related brain injury are often limited by small sample sizes. Further, current studies apply a variety of neuroimaging techniques and analysis tools which limit comparability among studies. The ENIGMA Sports Injury working group aims to provide a platform for data sharing and collaborative data analysis thereby leveraging existing data and expertise. By harmonizing data from a large number of studies from around the globe, we will work towards reproducibility of previously published findings and towards addressing important research questions with regard to diagnosis, prognosis, and efficacy of treatment for sport-related brain injury. Moreover, the ENIGMA Sports Injury working group is committed to providing recommendations for future prospective data acquisition to enhance data quality and scientific rigor

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15–90. The effects of dementia, mild cognitive impairment, Parkinson’s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p \u3c 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p \u3e 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson's disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Altered lateralization of the cingulum in deployment-related traumatic brain injury: An ENIGMA military-relevant brain injury study

Traumatic brain injury (TBI) in military populations can cause disruptions in brain structure and function, along with cognitive and psychological dysfunction. Diffusion magnetic resonance imaging (dMRI) can detect alterations in white matter (WM) microstructure, but few studies have examined brain asymmetry. Examining asymmetry in large samples may increase sensitivity to detect heterogeneous areas of WM alteration in mild TBI. Through the Enhancing Neuroimaging Genetics Through Meta-Analysis Military-Relevant Brain Injury working group, we conducted a mega-analysis of neuroimaging and clinical data from 16 cohorts of Active Duty Service Members and Veterans (n = 2598). dMRI data were processed together along with harmonized demographic, injury, psychiatric, and cognitive measures. Fractional anisotropy in the cingulum showed greater asymmetry in individuals with deployment-related TBI, driven by greater left lateralization in TBI. Results remained significant after accounting for potentially confounding variables including posttraumatic stress disorder, depression, and handedness, and were driven primarily by individuals whose worst TBI occurred before age 40. Alterations in the cingulum were also associated with slower processing speed and poorer set shifting. The results indicate an enhancement of the natural left laterality of the cingulum, possibly due to vulnerability of the nondominant hemisphere or compensatory mechanisms in the dominant hemisphere. The cingulum is one of the last WM tracts to mature, reaching peak FA around 42 years old. This effect was primarily detected in individuals whose worst injury occurred before age 40, suggesting that the protracted development of the cingulum may lead to increased vulnerability to insults, such as TBI

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis

Data Availability Statement: The raw data supporting the conclusions of this article and code used for analysis will be made available by the authors on reasonable request pending appropriate study approvals and data transfer agreements between participating institutions.Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/brainsci14070669/s1, Table S1: Inclusion/exclusion criteria for each data source; Table S2: Deficit in words recalled for each clinical condition relative to matched controls. Refs. [61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100] are cited in the Supplementary Materials.Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15–90. The effects of dementia, mild cognitive impairment, Parkinson’s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.This research was funded by the Psychological Health/Traumatic Brain Injury Research Program Long-Term Impact of Military Relevant Brain Injury Consortium (LIMBIC), Grant/Award Numbers: W81XWH18PH, TBIRPLIMBIC under Awards Numbers: W81XWH1920067 and W81XWH1320095; US Department of Defense, Grant/Award Number: AZ150145; US Department of Veterans Affairs, Grant/Award Numbers: I01 CX002097, I01 CX002096, I01 HX003155, I01 RX003444, I01 RX003443, I01 RX003442, I01 CX001135, I01 CX001246, I01 RX001774, I01 RX001135, I01 RX002076, I01 RX001880, I01 RX002172, I01 RX002173, I01 RX002171, I01 RX002174, I01 RX002170, 1I01 RX003444; National Institutes of Health (NIH), Grant/Award Number(s): RF1NS115268, RF1NS128961, U01NS086625, U01MH124639, P50MH115846, R01MH113827, R25MH080663, K08MH068540, R01NS100973, R01EB006841, P20GM103472, RO1MH083553, T32MH019535, R01 HD061504, RO1MH083553, R01AG050595, R01AG076838, R01AG060470, R01AG064955, P01AG055367, K23MH095661, R01MH094524, R01MH121246, T32MH019535, R01NS124585, R01NS122827, R61NS120249, R01NS122184, U54EB020403, R01MH116147, R56AG058854, P41EB015922, R01MH111671, P41RR14075, M01RR01066, R01EB006841, R01EB005846, R01 EB000840, RC1MH089257, U24 RR021992, and NCRR 5 month-RR001066 (MGH General Clinical Research Center); National Institute of Mental Health (NIMH), Grant/Award Number: 1P20RR021938; Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III, Grant/Award Numbers: PI15-00852, PI18-00945, JR19-00024, PI17-00481, PI20-00721; Sara Borrell contract, Grant/Award Number: CD19-00149; German Research Foundation DFG grant FOR2107, Grant/Award Numbers: JA 1890/7-1, JA 1890/7-2, NE2254/1-2, NE2254/2-1, NE2254/3-1, NE2254/4-1, KI588/14-1, KI588/14-2, DA1151/5-1, DA1151/5-2, SFB-TRR58, Projects C09 and Z02; European Union, NextGenerationEU, Grant/Award Numbers: PMP21/00051, PI19/01024; Structural Funds; Seventh Framework Program; H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking: Project PRISM-2, Grant/Award Number: 101034377; Project AIMS-2-TRIALS, Grant/Award Number: 777394; Horizon Europe; NSF, Grant/Award Number: 2112455; Madrid Regional Government, Grant/Award Number: B2017/BMD-3740 AGES-CM-2; Dalhousie Medical Research Foundation; Research Nova Scotia, Grant/Award Number: RNS-NHIG-2021-1931; NJ Commission on TBI Research Grants, Grant/Award Numbers: CBIR11PJT020, CBIR13IRG026; Department of Psychology, University of Oslo; Sunnaas Rehabilitation Hospital, Grant/Award Number: HF F32NS119285; Canadian Institutes of Health Research, Grant/Award Number: 166098; Neurological Foundation of New Zealand, Grant/Award Number: 2232 PRG; Canterbury Medical Research Foundation, University of Otago; Biogen US Investigator-initiated grant; Italian Ministry of Health, Grant/Award Number: RF-2019-12370182 and Ricerca Corrente RC 23; National Institute on Aging; National Health and Medical Research Council, Investigator Grant/Award Number: APP1176426; PA Health Research, Grant/Award Number: 4100077082; La Caixa Foundation, Grant/Award Number: 100010434, fellowship code: LCF/BQ/PR22/11920017; Research Council of Norway, Grant/Award Number: 248238; Health Research Council of New Zealand Sir Charles Hercus Early Career Development, Grant/Award Numbers: 17/039 and 14-440; Health Research Council of New Zealand, Grant/Award Numbers: 20/538 and 14/440; Research and Education Trust Pacific Radiology, Grant/Award Number: MRIJDA; South-Eastern Norway Regional Health Authority, Grant/Award Number: 2018076; Norwegian ExtraFoundation for Health and Rehabilitation, Grant/Award Numbers: 2015/FO5146; South-Eastern Norway Regional Health Authority, Grant/Award Number: 2015044; Stiftelsen K.G. Jebsen, Grant/Award Number: SKGJ MED-02; The Liaison Committee between Central Norway Regional Health Authority (RHA) and the Norwegian University of Science and Technology (NTNU), Grant/Award Number: 2020/39645; National Health and Medical Research Council, Grant/Award Number: APP1020526; Brain Foundation; Wicking Trust; Collie Trust; Sidney and Fiona Myer Family Foundation; U.S. Army Medical Research and Materiel Command (USAMRMC), Grant/Award Number: 13129004; Department of Energy, Grant/Award Number: DE-FG02-99ER62764; Mind Research Network; National Association for Research in Schizophrenia and Affective Disorders, Young Investigator Award; Blowitz Ridgeway and Essel Foundations; Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster; NOW ZonMw TOP, Grant/Award Number: 91211021; UCLA Easton Clinic for Brain Health; UCLA Brain Injury Research Center; Stan and Patty Silver; Clinical and Translational Research Center, Grant/Award Numbers: UL1RR033176, UL1TR000124; Mount Sinai Institute for NeuroAIDS Disparities; VA Rehab SPIRE; CDMRP PRAP; VA RR&D, Grant/Award Number: IK2RX002922; Veski Fellowship; Femino Foundation grant; Fundación Familia Alonso; Fundación Alicia Koplowitz; CIBERSAM, Madrid Regional Government, Grant/Award Numbers: B2017/BMD-3740 AGES-CM-2, 2019R1C1C1002457, 21-BR-03-01, 2020M3E5D9079910, 21-BR-03-01; Deutsche Forschungsgemeinschaft (DFG), Grant/Award Numbers: NE2254/1-2, NE2254/2-1, NE2254/3-1, NE2254/4-1