scholarly journals ENIGMA + COINSTAC: Improving Findability, Accessibility, Interoperability, and Re-usability

2021 ◽  
Author(s):  
Jessica A. Turner ◽  
Vince D. Calhoun ◽  
Paul M. Thompson ◽  
Neda Jahanshad ◽  
Christopher R. K. Ching ◽  
...  
Keyword(s):  
Sex Differences ◽  
Negative Symptom ◽  
Symptom Severity ◽  
Meta Analysis ◽  
Sociological Approach ◽  
Technological Approach ◽  
Neuroimaging Data ◽  
Fair Principles ◽  
Data Objects ◽  
Neuroimaging Genetics

AbstractThe FAIR principles, as applied to clinical and neuroimaging data, reflect the goal of making research products Findable, Accessible, Interoperable, and Reusable. The use of the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymized Computation (COINSTAC) platform in the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium combines the technological approach of decentralized analyses with the sociological approach of sharing data. In addition, ENIGMA + COINSTAC provides a platform to facilitate the use of machine-actionable data objects. We first present how ENIGMA and COINSTAC support the FAIR principles, and then showcase their integration with a decentralized meta-analysis of sex differences in negative symptom severity in schizophrenia, and finally present ongoing activities and plans to advance FAIR principles in ENIGMA + COINSTAC. ENIGMA and COINSTAC currently represent efforts toward improved Access, Interoperability, and Reusability. We highlight additional improvements needed in these areas, as well as future connections to other resources for expanded Findability.

scholarly journals EnigmaVis: Online Interactive Visualization of Genome-Wide Association Studies of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium

2012 ◽  
Vol 15 (3) ◽  
pp. 414-418 ◽  
Author(s):  
Nic M. Novak ◽  
Jason L. Stein ◽  
Sarah E. Medland ◽  
Derrek P. Hibar ◽  
Paul M. Thompson ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Intracranial Volume ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Genome Wide ◽  
Neuroimaging Data ◽  
Neuroimaging Genetics

In an attempt to increase power to detect genetic associations with brain phenotypes derived from human neuroimaging data, we recently conducted a large-scale, genome-wide association meta-analysis of hippocampal, brain, and intracranial volume through the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. Here, we present a freely available online interactive tool, EnigmaVis, which makes it easy to visualize the association results generated by the consortium alongside allele frequency, genes, and functional annotations. EnigmaVis runs natively within the web browser, and generates plots that show the level of association between brain phenotypes at user-specified genomic positions. Uniquely, EnigmaVis is dynamic; users can interact with elements on the plot in real time. This software will be useful when exploring the effect on brain structure of particular genetic variants influencing neuropsychiatric illness and cognitive function. Future projects of the consortium and updates to EnigmaVis will also be displayed on the site. EnigmaVis is freely available online at http://enigma.loni.ucla.edu/enigma-vis/

scholarly journals Modeling and Explaining Sex Differences in the Prevalence of Autism Spectrum Disorder:

2020 ◽  
Author(s):  
Meng-Ting Chen ◽  
Marisa E. Marraccini ◽  
Rune J. Simeonsson ◽  
Xiaopeng Lu ◽  
Yen-Ping Chang
Keyword(s):  
Autism Spectrum Disorder ◽  
Sex Differences ◽  
Symptom Severity ◽  
Statistical Models ◽  
Meta Analysis ◽  
Strong Support ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Assessment Scores

Why is autism spectrum disorder (ASD) less prevalent among females than among males? Synthesizing existing theories, we constructed two statistical models, one for each of both classes of theories on the issue, and derived testable competing predictions for the expression hypothesis—females express less severe ASD traits so are diagnosed less—against the perception hypothesis—females’ expressions are perceived as less severe so are diagnosed less—in their associations with expected symptom severity of ASD-diagnosed individuals. Examining the predictions with the highest precision, a meta-analysis on 103,958 historical assessment scores across ages, IQ, diagnoses, and assessments indicated that diagnosed females and males show almost equally severe and non-conditioned symptoms. Given the models are direct representations of the literature, the evidence therefore lends strong support for both, but not neither of the hypotheses, showing that the diagnosis of ASD is simultaneously an expression and a perception issue of the disorder.

scholarly journals Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium

2017 ◽  
Vol 48 (1) ◽  
pp. 82-94 ◽  
Author(s):  
E. Walton ◽  
D. P. Hibar ◽  
T. G. M. van Erp ◽  
S. G. Potkin ◽  
R. Roiz-Santiañez ◽  
...  
Keyword(s):  
Cortical Thickness ◽  
Negative Symptom ◽  
Symptom Severity ◽  
Negative Symptoms ◽  
Age Of Onset ◽  
Meta Analysis ◽  
Secondary Analysis ◽  
Prefrontal Cortical ◽  
Scale Scores ◽  
Structural Brain

BackgroundOur understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.MethodsThis study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).ResultsMeta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (βstd = −0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.ConclusionsUsing an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

What did you do yesterday? A meta-analysis of sex differences in episodic memory.

2019 ◽  
Vol 145 (8) ◽  
pp. 785-821 ◽  
Author(s):  
Martin Asperholm ◽  
Nadja Högman ◽  
Jonas Rafi ◽  
Agneta Herlitz
Keyword(s):  
Sex Differences ◽  
Episodic Memory ◽  
Meta Analysis

Sex differences in burnout: A meta-analysis

2007 ◽  
Author(s):  
John P. Muros ◽  
Radostina Purvanova
Keyword(s):  
Sex Differences ◽  
Meta Analysis

The ENIGMA Brain Injury Working Group: Approach, Challenges, and Potential Benefits

2019 ◽  
Author(s):  
Elisabeth A. Wilde ◽  
Emily L. Dennis ◽  
David F Tate
Keyword(s):  
Brain Injury ◽  
Working Group ◽  
Meta Analysis ◽  
Special Issue ◽  
Group Approach ◽  
Challenges And Opportunities ◽  
Brain Structure And Function ◽  
Potential Benefits ◽  
And Function ◽  
Neuroimaging Genetics

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium brings together researchers from around the world to try to identify the genetic underpinnings of brain structure and function, along with robust, generalizable effects of neurological and psychiatric disorders. The recently-formed ENIGMA Brain Injury working group includes 8 subgroups, based largely on injury mechanism and patient population. This introduction to the special issue summarizes the history, organization, and objectives of ENIGMA Brain Injury, and includes a discussion of strategies, challenges, opportunities and goals common across 6 of the subgroups under the umbrella of ENIGMA Brain Injury. The following articles in this special issue, including 6 articles from different subgroups, will detail the challenges and opportunities specific to each subgroup.

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