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

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

Nichtinvasive Bestimmung des intrakraniellen Drucks MR-basierte Untersuchung bei Kindern mit Hydrozephalus

Der intrakranielle Druck („intracranial pressure“ – ICP) ist ein entscheidender Parameter bei der Diagnostik, Therapie und Verlaufsbeurteilung von Patienten mit Hydrozephalus.Derzeit gibt es keine radiologische Standardmethode, um den intrakraniellen Druck quantitativ zu bestimmen. Methoden zur invasiven und nichtinvasiven Einschätzung des ICP werden diskutiert und die Anwendung eines MR-basierten Verfahrens (MR-ICP) bei Patienten mit Hydrozephalus vorgestellt.Der MR-ICP wird nichtinvasiv aus der intrakraniellen Volumenänderung, die während eines Herzzyklus entsteht, und dem kraniozervikalen Druckgradienten des Liquorflusses berechnet.Fünfzehn Patienten mit Hydrozephalus, davon 6 (2,5–14,61 Jahre alt; Mittelwert 7,4 Jahre) mit Verdacht auf erhöhten ICP, und 9 ohne klinische Zeichen eines erhöhten ICP (2,1–15,9 Jahre alt; Mittelwert 9,8 Jahre) wurden an einem 3-T-MRT mittels Phasenkontrastangiographie untersucht. Der mediane MR-ICP der Patienten mit akuter Symptomatik lag bei 24,5 mmHg (25%-Perzentile 20,4 mmHg; 75%-Perzentile 44,5 mmHg). Der mediane MR-ICP der Patienten ohne akute Symptomatik war 9,8 mmHg (25%-Perzentile 8,6 mmHg; 75%-Perzentile 11,4 mmHg). Der Gruppenunterschied war signifikant (p <0,001; Mann-Whitney-U-Test).Der MR-ICP ist eine vielversprechende, nichtinvasive Methode zur Einschätzung des ICP.Weitere Studien zur Evaluation der Anwendung bei verschiedenen klinischen Fragestellungen sind notwendig.The intracranial pressure (ICP) is a crucially important parameter for diagnostic and therapeutic decision-making in patients with hydrocephalus.So far there is no standard method to non-invasively assess the ICP. Various approaches to obtain the ICP semi-invasively or non-invasively are discussed and the clinical application of a magnetic resonance imaging (MRI)-based method to estimate ICP (MR-ICP) is demonstrated in a group of pediatric patients with hydrocephalus.Arterial inflow, venous drainage and craniospinal cerebrospinal fluid (CSF) flow were quantified using phase-contrast imaging to derive the MR-ICP.A total of 15 patients with hydrocephalus (n=9 treated with shunt placement or ventriculostomy) underwent MRI on a 3 T scanner applying retrospectively-gated cine phase contrast sequences. Of the patients six had clinical symptoms indicating increased ICP (age 2.5–14.61 years, mean 7.4 years) and nine patients had no clinical signs of elevated ICP (age 2.1–15.9 years; mean 9.8 years; all treated with shunt or ventriculostomy). Median MR-ICP in symptomatic patients was 24.5 mmHg (25th percentile 20.4 mmHg; 75th percentile 44.6 mmHg). Median MR-ICP in patients without acute signs of increased ICP was 9.8 mmHg (25th percentile 8.6 mmHg; 75th percentile 11.4 mmHg). Group differences were significant (p < 0.001; Mann-Whitney U-test).The MR-ICP technique is a promising non-invasive tool for estimating ICP.Further studies in larger patient cohorts are warranted to investigate its application in children with hydrocephalus

A Longitudinal Diffusion Tensor Imaging Study Assessing White Matter Fiber Tracts after Sports-Related Concussion

The extent of structural injury in sports-related concussion (SRC) is central to the course of recovery, long-term effects, and the decision to return to play. In the present longitudinal study, we used diffusion tensor imaging (DTI) to assess white matter (WM) fiber tract integrity within 2 days, 2 weeks, and 2 months of concussive injury. Participants were right-handed male varsity contact-sport athletes (20.2±1.0 years of age) with a medically diagnosed SRC (no loss of consciousness). They were compared to right-handed male varsity non-contact-sport athletes serving as controls (19.9±1.7 years). We found significantly increased radial diffusivity (RD) in concussed athletes (n=12; paired t-test, tract-based spatial statistics; p<0.025) at 2 days, when compared to the 2-week postinjury time point. The increase was found in a cluster of right hemisphere voxels, spanning the posterior limb of the internal capsule (IC), the retrolenticular part of the IC, the inferior longitudinal fasciculus, the inferior fronto-occipital fasciculus (sagittal stratum), and the anterior thalamic radiation. Post-hoc, univariate, between-group (controls vs. concussed), mixed-effects analysis of the cluster showed significantly higher RD at 2 days (p=0.002), as compared to the controls, with a trend in the same direction at 2 months (p=0.11). Results for fractional anisotropy (FA) in the same cluster showed a similar, but inverted, pattern; FA was decreased at 2 days and at 2 months postinjury, when compared to healthy controls. At 2 weeks postinjury, no statistical differences between concussed and control athletes were found with regard to either RD or FA. These results support the hypothesis of increased RD and reduced FA within 72 h postinjury, followed by recovery that may extend beyond 2 weeks. RD appears to be a sensitive measure of concussive injury

Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup mega-analysis

Studies of posttraumatic stress disorder (PTSD) report volume abnormalities in multiple regions of the cerebral cortex. However, findings for many regions, particularly regions outside commonly studied emotion-related prefrontal, insular, and limbic regions, are inconsistent and tentative. Also, few studies address the possibility that PTSD abnormalities may be confounded by comorbid depression. A mega-analysis investigating all cortical regions in a large sample of PTSD and control subjects can potentially provide new insight into these issues. Given this perspective, our group aggregated regional volumes data of 68 cortical regions across both hemispheres from 1379 PTSD patients to 2192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA standardized procedures. We examined whether regional cortical volumes were different in PTSD vs. controls, were associated with posttraumatic stress symptom (PTSS) severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients than controls (standardized coefficients = -0.111 to -0.068, FDR corrected P values < 0.039) and were significantly negatively correlated with PTSS severity. After adjusting for depression symptoms, the PTSD findings in left and right LOFG remained significant. These findings indicate that cortical volumes in PTSD patients are smaller in prefrontal regulatory regions, as well as in broader emotion and sensory processing cortical regions.Stress-related psychiatric disorders across the life spa