Browsing by Subject "Brain imaging"

Now showing 1 - 6 of 6
  • Thumbnail Image
    Item
    Association of structural brain imaging markers with alcoholism incorporating structural connectivity information: a regularized statistical approach
    (Office of the Vice Chancellor for Research, 2016-04-08) Karas, Marta; Dzemidzic, Mario; Goñi, Joaquin; Kareken, David A.; Harezlak, Jaroslaw
    Abstract: Brain imaging studies collect multiple imaging data types, but most analyses are done for each modality separately. Statistical methods that simultaneously utilize and combine multiple data types can instead provide a more holistic view of brain function. Here we model associations between alcohol abuse phenotypes and imaging data while incorporating prior scientific knowledge. Specifically, we utilize cortical thickness and integrated rectified mean curvature measures obtained by FreeSurfer software [1] to predict the alcoholism-related phenotypes while incorporating prior information from the structural connectivity between cortical regions. The sample consisted of 148 young (21-35 years) social-to-heavy drinking male subjects from several alcoholism risk studies [2,3,4]. Structural connectivity model [5] was used to estimate the density of connections between 66 cortical regions based on Desikan-Killiany atlas [6]. We employed a functional linear model with a penalty operator to quantify the relative contributions of imaging markers obtained from high resolution structural MRI (cortical thickness and curvature) as predictors of drinking frequency and risk-relevant personality traits, while co-varying for age. Model parameters were estimated by a unified approach directly incorporating structural connectivity information into the estimation by exploiting the joint eigenproperties of the predictors and the penalty operator [7]. We found that the best predictive imaging markers of the Alcohol Use Disorders Identification Test (AUDIT) score were the average thickness of left frontal pole (-), right transverse temporal gyrus (+), left inferior parietal lobule (+), right supramarginal gyrus (-), right rostral middle frontal gyrus (+), right precentral gyrus (+), left superior parietal lobule (-), left lateral orbitofrontal cortex (+), left rostral middle frontal gyrus (+), left postcentral gyrus (+) and left supramarginal gyrus (-), where (+) denotes positive and (-) negative association. In summary, the use of structural connectivity information allowed the incorporation of different modalities in associating cortical measures and alcoholism risk.
  • Thumbnail Image
    Item
    Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept
    (SpringerNature, 2016-03) Franke, Barbara; Stein, Jason L.; Ripke, Stephan; Anttila, Verneri; Hibar, Derrek P.; van Hulzen, Kimm J.; Arias-Vasquez, Alejandro; Smoller, Jordan W.; Nichols, Thomas E.; Neale, Michael C.; McIntosh, Andrew M.; Lee, Phil; McMahon, Francis J.; Meyer-Lindenberg, Andreas; Mattheisen, Manuel; Andreassen, Ole A.; Gruber, Oliver; Sachdev, Perminder S.; Roiz-Santiañez, Roberto; Saykin, Andrew J.; Ehrlich, Stefan; Mather, Karen A.; Turner, Jessica A.; Schwarz, Emanuel; Thalamuthu, Anbupalam; Shugart, Yin Yao; Ho, Yvonne Y.W.; Martin, Nicholas G.; Wright, Margaret J.; O'Donovan, Michael C.; Thompson, Paul M.; Neale, Benjamin M.; Medland, Sarah E.; Sullivan, Patrick F.; Department of Medical and Molecular Genetics, IU School of Medicine
    Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.
  • Thumbnail Image
    Item
    Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease
    (BMC, 2020-12-29) Meng, Xianglian; Li, Jin; Zhang, Qiushi; Chen, Feng; Bian, Chenyuan; Yao, Xiaohui; Xu, Zhe; Risacher, Shannon L.; Saykin, Andrew J.; Liang, Hong; Shen, Li; Radiology and Imaging Sciences, School of Medicine
    Background: Genome-wide association studies (GWAS) have identified many individual genes associated with brain imaging quantitative traits (QTs) in Alzheimer's disease (AD). However single marker level association discovery may not be able to address the underlying biological interactions with disease mechanism. Results: In this paper, we used the MGAS (Multivariate Gene-based Association test by extended Simes procedure) tool to perform multivariate GWAS on eight AD-relevant subcortical imaging measures. We conducted multiple iPINBPA (integrative Protein-Interaction-Network-Based Pathway Analysis) network analyses on MGAS findings using protein-protein interaction (PPI) data, and identified five Consensus Modules (CMs) from the PPI network. Functional annotation and network analysis were performed on the identified CMs. The MGAS yielded significant hits within APOE, TOMM40 and APOC1 genes, which were known AD risk factors, as well as a few new genes such as LAMA1, XYLB, HSD17B7P2, and NPEPL1. The identified five CMs were enriched by biological processes related to disorders such as Alzheimer's disease, Legionellosis, Pertussis, and Serotonergic synapse. Conclusions: The statistical power of coupling MGAS with iPINBPA was higher than traditional GWAS method, and yielded new findings that were missed by GWAS. This study provides novel insights into the molecular mechanism of Alzheimer's Disease and will be of value to novel gene discovery and functional genomic studies.
  • Thumbnail Image
    Item
    The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services
    (Springer Nature, 2019-05-23) Avesani, Paolo; McPherson, Brent; Hayashi, Soichi; Caiafa, Cesar F.; Henschel, Robert; Garyfallidis, Eleftherios; Kitchell, Lindsey; Bullock, Daniel; Patterson, Andrew; Olivetti, Emanuele; Sporns, Olaf; Saykin, Andrew J.; Wang, Lei; Dinov, Ivo; Hancock, David; Caron, Bradley; Qian, Yiming; Pestilli, Franco; Radiology and Imaging Sciences, School of Medicine
    We describe the Open Diffusion Data Derivatives (O3D) repository: an integrated collection of preserved brain data derivatives and processing pipelines, published together using a single digital-object-identifier. The data derivatives were generated using modern diffusion-weighted magnetic resonance imaging data (dMRI) with diverse properties of resolution and signal-to-noise ratio. In addition to the data, we publish all processing pipelines (also referred to as open cloud services). The pipelines utilize modern methods for neuroimaging data processing (diffusion-signal modelling, fiber tracking, tractography evaluation, white matter segmentation, and structural connectome construction). The O3D open services can allow cognitive and clinical neuroscientists to run the connectome mapping algorithms on new, user-uploaded, data. Open source code implementing all O3D services is also provided to allow computational and computer scientists to reuse and extend the processing methods. Publishing both data-derivatives and integrated processing pipeline promotes practices for scientific reproducibility and data upcycling by providing open access to the research assets for utilization by multiple scientific communities.
  • Thumbnail Image
    Item
    Reduced top‐down attentional control in adolescents with generalized anxiety disorder
    (Wiley, 2021) Bashford-Largo, Johannah; Aloi, Joseph; Lukoff, Jennie; Johnson, Kimberly; White, Stuart F.; Dobbertin, Matthew; Blair, Robert James; Blair, Karina S.; Psychiatry, School of Medicine
    Background: Generalized anxiety disorder (GAD) can significantly impair quality of life and is associated with a relatively poor long-term prognosis. Anxiety disorders are often associated with hyper-responsiveness to threat, perhaps coupled with impaired executive functioning. However, GAD, particularly adolescent GAD, has been the focus of little functional neuroimaging work compared to other anxiety disorders. Here, we examine the neural association of adolescent GAD with responsiveness to threat and response control. Methods: The study involved 35 adolescents with GAD and 34 healthy comparison individuals (N = 69) matched on age, gender, and IQ. Participants were scanned during an affective number Stroop task. Results: We found significant Group-by-Task Condition interactions in regions involved in response control/motor responding (bilateral precentral gyri and cerebellum) and/or cognitive control/attention (dorsomedial and lateral frontal cortex, posterior cingulate cortex, cuneus, and precuneus). In line with predictions, the youth with GAD showed significantly less recruitment during task trials than the healthy comparison individuals. However, no indications of specific heightened responses to threat were seen. Conclusions: GAD involves reduced capacity for engaging regions involved in response control/motor responding and/or cognitive control/attention. This might reflect either a secondary consequence of the patient's worry or an early risk factor for the development of worry.
  • Thumbnail Image
    Item
    Short-Term Practice Effects on Cognitive Tests Across the Late Life Cognitive Spectrum and How They Compare to Biomarkers of Alzheimer’s Disease
    (Sage, 2024) Duff, Kevin; Hammers, Dustin B.; Koppelmans, Vincent; King, Jace B.; Hoffman, John M.; Neurology, School of Medicine
    Background: Practice effects on cognitive testing in mild cognitive impairment (MCI) and Alzheimer's disease (AD) remain understudied, especially with how they compare to biomarkers of AD. Objective: The current study sought to add to this growing literature. Methods: Cognitively intact older adults (n = 68), those with amnestic MCI (n = 52), and those with mild AD (n = 45) completed a brief battery of cognitive tests at baseline and again after one week, and they also completed a baseline amyloid PET scan, a baseline MRI, and a baseline blood draw to obtain APOE ɛ4 status. Results: The intact participants showed significantly larger baseline cognitive scores and practice effects than the other two groups on overall composite measures. Those with MCI showed significantly larger baseline scores and practice effects than AD participants on the composite. For amyloid deposition, the intact participants had significantly less tracer uptake, whereas MCI and AD participants were comparable. For total hippocampal volumes, all three groups were significantly different in the expected direction (intact > MCI > AD). For APOE ɛ4, the intact had significantly fewer copies of ɛ4 than MCI and AD. The effect sizes of the baseline cognitive scores and practice effects were comparable, and they were significantly larger than effect sizes of biomarkers in 7 of the 9 comparisons. Conclusion: Baseline cognition and short-term practice effects appear to be sensitive markers in late life cognitive disorders, as they separated groups better than commonly-used biomarkers in AD. Further development of baseline cognition and short-term practice effects as tools for clinical diagnosis, prognostic indication, and enrichment of clinical trials seems warranted.