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Publications

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1800 Total Publications

Voxelwise genome-wide association study (vGWAS)
Stein, J. L., Hua, X., Lee, S., Ho, A. J., Leow, A. D., Toga, A. W., … Thompson, P. M.
PMID: 20171287 ; PMCID:2900429 ; 2010; Journal Neuroimage; vol. 53; no. 3; pp. 1160-1174; AWTYmIlBwAl_G9zjEveH doi:10.1016/j.neuroimage.2010.02.032

Genome-Wide Analysis Reveals Novel Genes Influencing Temporal Lobe Structure with Relevance to Neurodegeneration in Alzheimer’s Disease
Stein, J. L., Hua, X., Morra, J. H., Lee, S., Hibar, D. P., Ho, A. J., … Thompson, P. M.
PMID: 20197096 ; PMCID:2856746 ; 2010; Journal Neuroimage; vol. 51; no. 2; pp. 542-54; AWTYmIlBwAl_G9zjEveI doi:10.1016/j.neuroimage.2010.02.068

One year brain atrophy evident in healthy aging
Anders M. Fjell, Kristine B. Walhovd, Christine Fennema-Notestine, Linda K. McEvoy, Donald J. Hagler, Dominic Holland, James B. Brewer, Anders M. Dale
PMID: 19955375 ; PMCID:2827793 ; 2010; Journal J Neurosci; vol. 29; no. 48; pp. 15223-31; AWTYjl7cwAl_G9zjEvcz doi:10.1523/JNEUROSCI.3252-09.2009

Meta-Analysis confirms CR1, CLU, and PICALM as Alzheimer’s disease risk loci and reveals interactions with APOE genotypes
un, G., Naj, A. C., Beecham, G. W., Wang, L.-S., Buros, J., Gallins, P. J., … Schellenberg, G. D.
PMID: 20697030 ; PMCID:3048805 ; 2010; Journal JAMA Neurology; vol. 67; no. 12; pp. 1473-84; AWTYJYqowAl_G9zjEvZz doi:10.1001/archneurol.2010.201

Comparing 3 T and 1.5 T MRI for Tracking Alzheimer’s Disease Progression with Tensor-Based Morphometry
Ho, A. J., Hua, X., Lee, S., Leow, A. D., Yanovsky, I., Gutman, B., … Thompson, P. M.
PMID: 19780044 ; PMCID:2875376 ; 2010; Journal Human Brain Mapping; vol. 31; no. 4; pp. 499-514; AWTYIUWHMOwVf_qbJr4- doi:10.1002/hbm.20882

Neuroimaging to assess safety and efficacy of AD therapies
Hill D1
PMID: 19947893 ; 2010; Journal Expert Opin Investig Drugs; vol. 19; no. 1; pp. 23-6.; AWTYH9GudzjauPDbjhmn doi: 10.1517/13543780903381320

Discovering genetic associations with high-dimensional neuroimaging phenotypes: 2 A sparse reduced-rank regression approach
Vounou, M., Nichols, T. E., & Montana, G.
PMID: 20624472 ; PMCID:5253177 ; 2010; Journal Neuroimage; vol. 53; no. 3; pp. 1147-1159; AWTYm_u8wAl_G9zjEvel doi:10.1016/j.neuroimage.2010.07.002

Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation
Huang, S., Li, J., Sun, L., Ye, J., Fleisher, A., Wu, T., … Reiman, E.
PMID: 20079441 ; PMCID:3068623 ; 2010; Journal Neuroimage; vol. 50; no. 3; pp. 935-949; AWTYIuKfwAl_G9zjEvZQ doi:10.1016/j.neuroimage.2009.12.120

Impact of scanner hardware and imaging protocol on image quality and compartment volume precision in the ADNI cohort
Kruggel, F., Turner, J., & Muftuler, L. T.
PMID: 19913626 ; PMCID:2951115 ; 2010; Journal Neuroimage; vol. 49; no. 3; pp. 2123-33; AWTYKMCDMOwVf_qbJr53 doi:10.1016/j.neuroimage.2009.11.006

Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer’s disease
Jack, C. R., Wiste, H. J., Vemuri, P., Weigand, S. D., Senjem, M. L., Zeng, G., … Knopman, D. S.
PMID: 20935035 ; PMCID:2965425 ; 2010; Journal Brain; vol. 133; no. 11; pp. 3336-3348; AWTYJYqowAl_G9zjEvZb doi:10.1093/brain/awq277