Subcortical surface morphometry in substance dependence: An ENIGMA addiction working group study

Chye, Yann; Mackey, Scott; Gutman, Boris A.; Ching, Christopher R. K.; Batalla, Albert; Blaine, Sara K.; Brooks, Samantha J.; Caparelli, Elisabeth C.; Cousijn, Janna; Foxe, John J.; Goudriaan, Anna E.; Hester, Robert; Hutchison, Kent E.; Jahanshad, Neda; Kaag, Anne Marije; Korucuoglu, Ozlem; Li, Chiang‐Shan R.; London, Edythe D.; Lorenzetti, Valentina; Luijten, Maartje; Martín‐Santos, Rocío; Meda, Shashwath A.; Momenan, Reza; Morales, Angelica M.; Orr, Catherine; Paulus, Martin P.; Pearlson, Godfrey D.; Reneman, Liesbeth; Schmaal, Lianne; Sinha, Rajita; Solowij, Nadia; Stein, Dan J.; Stein, Elliot A.; Tang, Deborah; Uhlmann, Anne; Holst, Ruth J. van; Veltman, Dick J.; Verdejo-García, Antonio; Wiers, Reínout W.; Yücel, Murat; Thompson, Paul M.; Conrod, Patricia J.; Garavan, Hugh

doi:10.1111/adb.12830

Cited by 44 publications

(39 citation statements)

References 61 publications

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“…The ENIGMA-Addiction Working Group is currently expanding this work to investigate sex-specific neuroimaging signatures of alcohol (Grace et al, in press), tobacco, cocaine (Rabin et al, in press), and methamphetamine using a global framework. This type of big data analysis is ideal for parsing the complexity of SUDs in the brain, as has been shown by our earlier work [Chye et al, 2019;Mackey et al, 2019].…”

Section: Substance Use Disordersmentioning

confidence: 90%

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Salminen¹,

Tubi²,

Bright³

et al. 2020

Preprint

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Sex differences are found in the incidence and expression of psychiatric and neurodegenerative conditions, and many studies suggest these differences are influenced by innate biological differences between males and females and risk factors that interact with these differences. However, few studies have used neuroimaging to examine brain signatures of disease separately by sex, and many studies of sex differences have been based on small samples and their findings have not been replicated in larger cohorts. Large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses (ENIGMA) consortium, the UK Biobank, Human Connectome Project, and others offer an unprecedented source of power to address important questions about the role of sex as a risk or protective factor for suboptimal brain health, as well as sex-specific neuroimaging phenotypes in brain-related illnesses. Here we review the existing neuroimaging literature on sex differences in the human brain in healthy adults and those with the most common and debilitating psychiatric and age-related neurodegenerative conditions. Finally, we discuss key gaps in this literature and opportunities of large-scale collaborative efforts to identify, characterize, and explain how biological sex influences the humanbrain in health and disease.

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Section: Substance Use Disordersmentioning

confidence: 90%

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Salminen¹,

Tubi²,

Bright³

et al. 2020

Preprint

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“…Other methodological WGs have focused on anatomical shape analyses that enable a more precise characterization of regional brain alterations thus resolving subregional effects in the basal ganglia, amygdala, and hippocampus 55,85,[137][138][139][140][141][142] . Other approaches currently used in ENIGMA include brain structural covariance analysis graph theory approach for intra-individual brain structural covariance networks in OCD 77,143 , sulcal morphometry 144 , hippocampal subfield analysis [80][81][82]145 and disease effects on lateralization (in OCD, MDD, and ASD) 71,90,97 .…”

Section: Enigma-methods Focused Working Groupsmentioning

confidence: 99%

“…The ENIGMA-Addictions/SUDs WG has 33 participating sites, contributing MRI data from 12,347 individuals of whom 2277 are adult patients with SUD relating to one of five substances (alcohol, nicotine, cocaine, methamphetamine, or cannabis) 5,84,85 . In these data, Mackey 5 observed lower cortical thickness/subcortical volume in cases relative to controls in regions that play key roles in evaluating reward (MOFC, amygdala), task monitoring (superior frontal cortex), attention (superior parietal cortex, posterior cingulate) and perception/regulation of internal body states (insula).…”

Section: Enigma-addictions/sudmentioning

confidence: 99%

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

Thompson¹,

Jahanshad²,

Ching³

et al. 2020

Transl Psychiatry

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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, attentiondeficit/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.

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“…Researchers need to consider whether imaging analyses should use measures obtained at every point of an image (e.g., voxelwise or vertexwise data) or aggregate measures computed over regions of interest or parcellations, broadly termed as "ROIs". Although vertexwise analyses have been performed in recent ENIGMA research (Chye et al, 2019;Ho et al, 2019), most previous ENIGMA studies used meta-analyses. In these cases, an ROI-based approach is more robust to small deviations from a common image registration scheme.…”

Section: Choice Of Resolutionmentioning

confidence: 99%

Mega-Analysis Methods in ENIGMA: The Experience of the Generalized Anxiety Disorder Working Group

Zugman¹,

Harrewijn²,

Cardinale³

et al. 2020

Preprint

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The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

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Subcortical surface morphometry in substance dependence: An ENIGMA addiction working group study

Cited by 44 publications

References 61 publications

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

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

Mega-Analysis Methods in ENIGMA: The Experience of the Generalized Anxiety Disorder Working Group

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