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Potential biomarker detection is a crucial area of study for the prediction, diagnosis, and monitoring of Alzheimer's disease (AD). The voxelwise genome-wide association study (vGWAS) is widely used in imaging genomics studies that is usually applied to the detection of AD biomarkers in both imaging and genetic data. However, performing vGWAS remains a challenge because of the computational complexity of the technique and our ignorance of the spatial correlations within the imaging data. In this paper, we propose a novel method based on the exploitation of spatial correlations that may help to detect potential AD biomarkers using a fast vGWAS. To incorporate spatial correlations, we applied a nonlocal method that supposed that a given voxel could be represented by weighting the sum of the other voxels. Three commonly used weighting methods were adopted to calculate the weights among different voxels in this study. Then, a fast vGWAS approach was used to assess the association between the image and the genetic data. The proposed method was estimated using both simulated and real data. In the simulation studies, we designed a set of experiments to evaluate the effectiveness of the nonlocal method for incorporating spatial correlations in vGWAS. The experiments showed that incorporating spatial correlations by the nonlocal method could improve the detecting accuracy of AD biomarkers. For real data, we successfully identified three genes, namely, ANK3, MEIS2, and TLR4, which have significant associations with mental retardation, learning disabilities and age according to previous research. These genes have profound impacts on AD or other neurodegenerative diseases. Our results indicated that our method might be an effective and valuable tool for detecting potential biomarkers of AD.
Pubmed ID: 30584014
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Software package that performs high-dimensional warping of brain images. Standard voxel-based analysis can be applied to these tissue density maps, in order to examine regional volumetrics, effects of disease, or correlations with clinical measurements. In order to make HAMMER as robust as possible to different acquisition protocols and conditions, they provide a distribution that assumes that images have been skull-stripped and segmented into gray matter, white matter, and ventricular CSF. We have other software tools that can perform these steps, including skull stripping, reorientation and reslicing, and segmentation tools. Importantly, they use 250 for WM, 150 for GM, 50 for Ventricles and 10 for CSF in the tissue-segmented brain images. Current modules used for group analysis: Labeling subject brain using a manually-labeled brain Model; Generating RAVENS map for each tissue (WM, GM, VN); Normalizing subject brain images
View all literature mentionsA 4D adult brain extraction and analysis toolbox with graphical user interfaces to consistently analyze 4D adult brain MR images. Single-time-point images can also be analyzed. Main functions of the software include image preprocessing, 4D brain extraction, 4D tissue segmentation, 4D brain labeling, ROI analysis. Linux operating system (64 bit) is required. A computer with 8G memory (or more) is recommended for processing many images simultaneously. The graphical user interfaces and overall framework of the software are implemented in MATLAB. The image processing functions are implemented with the combination of C/C++, MATLAB, Perl and Shell languages. Parallelization technologies are used in the software to speed up image processing.
View all literature mentionsDatabase of the results of the ADNI study. ADNI is an initiative to develop biomarker-based methods to detect and track the progression of Alzheimer's disease (AD) that provides access to qualified scientists to their database of imaging, clinical, genomic, and biomarker data.
View all literature mentionsA public charity whose mission is to support the NIH in its mission to improve health, by forming and facilitating public-private partnerships for biomedical research and training. Its vision is Building Partnerships for Discovery and Innovation to Improve Health. The FNIH draws together the world''s foremost researchers and resources, pressing the frontier to advance critical discoveries. They are recognized as the number-one medical research charity in the countryleveraging support, and convening high level partnerships, for the greatest impact on the most urgent medical challenges we face today. Grants are awarded as part of a public-private partnership with the National Heart, Lung, and Blood Institute (NHLBI) on behalf of The Heart Truth in support of women''s heart health education and research. Funding for the Community Action Program is provided by the FNIH through donations from individuals and corporations including The Heart Truth partners Belk Department Stores, Diet Coke, and Swarovski. Successful biomedical research relies upon the knowledge, training and dedication of those who conduct it. Bringing multiple disciplines to bear on health challenges requires innovation and collaboration on the part of scientists. Foundation for NIH partnerships operate in a variety of ways and formats to recruit, train, empower and retain their next generation of researchers. From lectures and multi-week courses, to scholarships and awards through fellowships and residential training programs, their programs respond to the needs of scientists at every level and stage in their careers.
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