ORCID Profile
0000-0001-7112-4009
Current Organisations
Syracuse University
,
University of Utah
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Publisher: Wiley
Date: 05-2009
Publisher: Research Square Platform LLC
Date: 06-10-2022
DOI: 10.21203/RS.3.RS-2085479/V1
Abstract: A number of studies of posttraumatic stress disorder (PTSD) report thinner cerebral cortical gyri using gyrus-based analysis or thinner foci within the gyri using vertex-based analysis. However, the locations of these findings are inconsistent across studies, and the spatial transformations required during vertex-based analysis may affect the focal findings. A mega-analysis using a large number of subjects from multiple PTSD studies could potentially identify more reproducible cortical thickness abnormalities. Investigating both the vertex and gyral thicknesses simultaneously may verify the vertex-based focal findings using gyral data without imposing any spatial transformation. Here we aggregated data from 24 international laboratories using ENIGMA standardized procedures for 949 adult PTSD patients and 1493 controls without PTSD (age 18 to 65 years). We examined whether gyral and vertex cortical thickness are (a) different between subjects with PTSD and controls and (b) associated with PTSD symptom severity in trauma-exposed subjects. Regions with overlapping thinner cortical gyri and thinner vertex clusters were located in frontal, temporal, parietal, and occipital cortices. Thinner right lateral orbitofrontal and right lingual gyri and concomitantly thinner vertex clusters in the anterior portions of both gyri were associated with PTSD symptom severity. Convergent findings in these locations suggest focally thinner cortex in these gyri, which may be involved in altered processing and regulation of emotion and sensory inputs underlying posttraumatic stress symptoms.
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 11-2022
Publisher: Elsevier BV
Date: 12-2023
Publisher: Cold Spring Harbor Laboratory
Date: 13-12-2022
DOI: 10.1101/2022.12.12.519838
Abstract: Current clinical assessments of Posttraumatic stress disorder (PTSD) rely solely on subjective symptoms and experiences reported by the patient, rather than objective biomarkers of the illness. Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. Here we aimed to classify in iduals with PTSD versus controls using heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. We analyzed brain MRI data from 3,527 structural-MRI 2,502 resting state-fMRI and 1,953 diffusion-MRI. First, we identified the brain features that best distinguish in iduals with PTSD from controls (TEHC and HC) 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. 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 across all three modalities (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. Our findings highlight the promise offered by machine learning methods for the diagnosis of patients with PTSD. The utility of brain biomarkers across three MRI modalities and the contribution of DVAE models for improving generalizability offers new insights into neural mechanisms involved in PTSD. ⍰ Classifying PTSD from trauma-unexposed healthy controls (HC) using three imaging modalities performed well (∼75% AUC), but performance suffered markedly when classifying PTSD from trauma-exposed healthy controls (TEHC) using three imaging modalities (∼60% AUC). ⍰ Using deep learning for feature reduction (denoising variational auto-encoder DVAE) dramatically reduced the number of features with no concomitant performance degradation. ⍰ Utilizing denoising variational autoencoder (DVAE) models improves generalizability across heterogeneous multi-site data compared with the traditional machine learning frameworks
Publisher: Cold Spring Harbor Laboratory
Date: 17-10-2023
Publisher: Center for Open Science
Date: 03-10-2019
Abstract: The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant and the heterogeneity of TBI patients and the relatively small s le sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with nonimaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for largescale neuroimaging data analysis. In this consensus statement we outline the working group’s short-term, intermediate, and long-term goals.
Publisher: Cold Spring Harbor Laboratory
Date: 27-12-2022
DOI: 10.1101/2022.12.24.22283926
Abstract: While traditionally ignored as a region purely responsible for motor function, the cerebellum is increasingly being appreciated for its contributions to higher order functions through various cerebro-cerebellar networks. Traumatic brain injury (TBI) research generally focuses on the cerebrum, in part because acute pathology is not found in the cerebellum as often. Acute pathology is an important predictor of outcome, but neural disruption also evolves over time in ways that have implications for daily-life functioning. Here we examine these changes in a multi-modal, multi-cohort study. Combining 12 datasets from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Pediatric msTBI (moderate-severe TBI) working group, we measured volume of the total cerebellum and 17 subregions using a state-of-the-art, deep learning-based approach for automated parcellation in 598 children and adolescents with or without TBI (msTBI n = 314 | non-TBI n = 284 age M = 14.0 ± 3.1 years). Further, we investigated brain-behavior relations between cerebellar volumes and a measure of executive functioning (i.e., Behavioral Rating Inventory of Executive Function [BRIEF]). In a subs le with longitudinal data, we then assessed whether late changes in cerebellar volume were associated with early white matter microstructural organization using diffusion tensor imaging (DTI). Significantly smaller total cerebellar volume was observed in the msTBI group (Cohen’s d = −0.37). In addition, lower regional cerebellar volume was found in posterior lobe regions including crus II, lobule VIIB, lobule VIIIB, vermis VII, and IX (Cohen’s d range = −0.22 to −0.43). Smaller cerebellum volumes were associated with more parent-reported executive function problems. These alterations were primarily driven by participants in the chronic phase of injury ( 6 months). In a subset of participants with longitudinal data (n = 80), we found evidence of altered growth in total cerebellum volume, with younger msTBI participants showing secondary degeneration in the form of volume reductions, and older participants showing disrupted development reflected in slower growth rates. Changes in total cerebellum volume over time were also associated with white matter microstructural organization in the first weeks and months post-injury, such that poorer white matter organization in the first months post-injury was associated with decreases in volume longitudinally. Pediatric msTBI was characterized by smaller cerebellar volumes, primarily in the posterior lobe and vermis. The course of these alterations, along with group differences in longitudinal volume changes as well as injury-specific associations between DTI measures and volume changes, is suggestive of secondary cerebellar atrophy, possibly related to supra-tentorial lesions, and/or disruption in cerebellar structural and functional circuits. Moreover, evidence for robust brain-behavior relationships underscore the potential cognitive and behavioral consequences of cerebellar disruption during a critical period of brain development.
Publisher: Springer Science and Business Media LLC
Date: 30-07-2020
Publisher: Center for Open Science
Date: 04-07-2019
Abstract: This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1,400 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 ersified 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 erse s les and associated genetic, environmental, demographic, cognitive and psychosocial factors.
Publisher: Cold Spring Harbor Laboratory
Date: 17-10-2022
DOI: 10.1101/2022.10.13.512111
Abstract: The cerebellum critically contributes to higher-order cognitive and emotional functions such fear learning and memory. Prior research on cerebellar volume in PTSD is scant and has neglected neuroanatomical sub isions of the cerebellum that differentially map on to motor, cognitive, and affective functions. We quantified cerebellar lobule volumes using structural magnetic resonance imaging in 4,215 adults (PTSD n= 1640 Control n=2575) across 40 sites from the from the ENIGMA-PGC PTSD working group. Using a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation, we obtained volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum total and subregional volume in PTSD compared to healthy controls. The Benjamini-Hochberg procedure was used to control the false discovery rate ( p -FDR .05). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume. In addition, people with PTSD showed reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), but also the vermis (VI, VIII), flocculonodular lobe (lobule X), and cerebellar white matter (all p -FDR 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in high-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.
Publisher: Springer Science and Business Media LLC
Date: 19-03-2013
Publisher: Springer Science and Business Media LLC
Date: 25-07-2017
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 20-07-2021
DOI: 10.1212/WNL.0000000000012222
Abstract: Our study addressed aims (1) to test the hypothesis that moderate-severe traumatic brain injury (TBI) in pediatric patients is associated with widespread white matter (WM) disruption, (2) to test the hypothesis that age and sex affect WM organization after injury, and (3) to examine associations between WM organization and neurobehavioral outcomes. Data from 10 previously enrolled, existing cohorts recruited from local hospitals and clinics were shared with the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Pediatric Moderate/Severe TBI (msTBI) working group. We conducted a coordinated analysis of diffusion MRI (dMRI) data using the ENIGMA dMRI processing pipeline. Five hundred seven children and adolescents (244 with complicated msTBI and 263 controls) were included. Patients were clustered into 3 postinjury intervals: acute/subacute, months postacute, 2 to 6 months and chronic, ≥6 months. Outcomes were dMRI metrics and postinjury behavioral problems as indexed by the Child Behavior Checklist. Our analyses revealed altered WM diffusion metrics across multiple tracts and all postinjury intervals (effect sizes range d = −0.5 to −1.3). Injury severity is a significant contributor to the extent of WM alterations but explained less variance in dMRI measures with increasing time after injury. We observed a sex-by-group interaction: female patients with TBI had significantly lower fractional anisotropy in the uncinate fasciculus than controls (β = 0.043), which coincided with more parent-reported behavioral problems (β = −0.0027). WM disruption after msTBI is widespread, persistent, and influenced by demographic and clinical variables. Future work will test techniques for harmonizing neurocognitive data, enabling more advanced analyses to identify symptom clusters and clinically meaningful patient subtypes.
Publisher: Springer Science and Business Media LLC
Date: 19-12-2019
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 11-2014
Location: United States of America
No related grants have been discovered for Emily Dennis.