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1. The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

Author

Weiner, MW, Aisen, P, Petersen, R, Jack, CR, Jagust, W, Trojanowki, JQ, Toga, AW, Beckett, L, Green, RC, Saykin, AJ, Morris, JC, Perrin, RJ, Shaw, LM, Khachaturian, Z, Carrillo, M, Potter, W, Barnes, L, Bernard, M, González, H, Ho, C, Hsiao, JK, Jackson, J, Masliah, E, Masterman, D, Okonkwo, O, Perrin, R, Ryan, L, Silverberg, N, Fleisher, A, Sacrey, DT, Fockler, J, Conti, C, Veitch, D, Neuhaus, J, Jin, C, Nosheny, R, Ashford, M, Flenniken, D, Kormos, A, Monine, T, Rafii, M, Raman, R, Jimenez, G, Donohue, M, Gessert, D, Salazar, J, Zimmerman, C, Cabrera, Y, Walter, S, Miller, G, Coker, G, Clanton, T, Hergesheimer, L, Smith, S, Adegoke, O, Mahboubi, P, Moore, S, Pizzola, J, Shaffer, E, Sloan, B, Harvey, D, Forghanian-Arani, A, Borowski, B, Ward, C, Schwarz, C, Jones, D, Gunter, J, Kantarci, K, Senjem, M, Vemuri, P, Reid, R, Fox, NC, Malone, I, Thompson, P, Thomopoulos, SI, Nir, TM, Jahanshad, N, DeCarli, C, Knaack, A, Fletcher, E, Tosun-Turgut, D, Chen, SR, Choe, M, Crawford, K, Yushkevich, PA, Das, S, Koeppe, RA, Reiman, EM, Chen, K, Mathis, C, Landau, S, Cairns, NJ, Householder, E, Franklin, E, Bernhardt, H, Taylor-Reinwald, L, Tojanowki, JQ, Korecka, M, and Figurski, M

Subjects
Biological Sciences, Genetics, Prevention, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Knowledge Bases, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Risk Factors, Alzheimer’s Disease Neuroimaging Initiative, Biological sciences, Biomedical and clinical sciences
Abstract

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.

Published
2022

2. Survival following dementia onset: Vascular dementia versus Alzheimer’s disease

Author

Fitzpatrick, AL, Kuller, LH, Lopez, OL, Kawas, CH, and Jagust, W

Subjects
Clinical Sciences, Neurosciences, Psychology
Abstract

Although there is general agreement that the diagnosis of dementia reduces life expectancy, the estimated number of years for survival following the onset of dementia has been reported to vary from 3 to over 9 years. We examined mortality in 3602 participants of the Cardiovascular Health Cognition Study in four U.S. communities evaluated for dementia incidence between 1992 and 1999 and followed an average of 6.5 years. Alzheimer’s disease (AD) was determined using NINCDS–ADRDA criteria and vascular dementia (VaD) used ADDTC criteria. Average age of the cohort was 75.1 years. By June 2000, 33 of 62 (53.2%) participants with VaD had died compared to 79 of 245(32.2%) with AD, 66 of 151 (43.7%) with both AD and VaD, and 429 of 2318 (18.5%) with normal cognition. Using Cox proportional hazards regression with a time-dependent covariate for dementia status adjusted for age, gender and race, individuals with VaD were more than four times as likely to die during follow-up than those with normal cognitive status (HR: 4.4, 95% CI: 3.1–6.3). The hazard ratios were 2.1 (95% CI: 1.6–2.7) for AD and 2.5 (95% CI: 1.9–3.3) for both types. Individuals with VaD were more likely to die of cerebrovascular disease (42.4%) than those with AD (9.2%), both types (9.2%) or with normal cognition (7.5%). Accelerated life models estimated median survival from dementia onset to death as 3.8 years for those with VaD only, 6.8 years for those with AD only, and 5.2 years for those with both types of dementia.

Published
2005

3. Comparison of methods for measuring longitudinal brain change in cognitive impairment and dementia

Author

Cardenas, V A, Du, A T, Hardin, D, Ezekiel, F, Weber, P, Jagust, W J, Chui, H C, Schuff, N, and Weiner, M W

Subjects
cognitive disorders/dementia, neuroradiology, image processing, longitudinal
Abstract

Purpose: The goal of this project was to compare MRI measures of hippocampal, entorhinal cortex (ERC), and whole brain longitudinal change in cognitively normal elderly controls (C), non-demented subjects with cognitive impairment (CI), and demented (D) subjects. Methods: 16 C, 6 CI, and 7 D subjects of comparable age were studied with MRI twice, at least 1 year apart. Longitudinal change in total brain size was measured by several methods, including computerized segmentation, non-linear warping, and change in the fluid/tissue boundaries between cerebrospinal fluid (CSF) and brain. Change in hippocampal volume was measured by semi-automated methods, and ERC volumes were manually measured. Results: The annual rate of atrophy was greater in D versus C and D versus CI for cortical gray matter (cGM) (P = 0.009 and 0.002), hippocampus (P = 0.0001 and 0.002), and for the change in the fluid/tissue boundary (P = 0.03 and 0.03). The annual rate of atrophy of ERC was greater in both CI and D versus C (P = 0.01 and 0.0002). No significant differences between groups were found using non-linear warping. Conclusions: In CI, the greatest annual rates of atrophy were in ERC, while in D the greatest annual rates of atrophy were in hippocampus and cortex. Progressive ERC atrophy was observed with a greater degree of cognitive impairment, while hippocampal and cortical atrophy were only observed in demented subjects. (C) 2002 Elsevier Science Inc. All rights reserved.

Published
2003

4. Survival following dementia onset: Vascular dementia versus Alzheimer’s disease

Author

Fitzpatrick, AL, Kuller, LH, Lopez, OL, Kawas, CH, and Jagust, W

Abstract

Survival following the onset of dementia has been reported to vary from 3 to over 9 years. We examined mortality in 3602 participants of the Cardiovascular Health Cognition Study in four U.S. communities evaluated for dementia incidence between 1992-1999 and followed for 6.5 years. By June 2000, 33 of 62 (53.2%) participants who had developed VaD had died compared to 79 of 245 (32.2%) with AD, 66 of 151 (43.7%) with both AD and VaD, and 429 of 2318 (18.5%) with normal cognition. Using Cox proportional hazards regression with a time-dependent covariate for dementia status adjusted for age, gender and race, individuals with VaD were more than four times as likely to die during follow-up than those with normal cognition (HR: 4.4, 95% CI: 3.1-6.3). The hazard ratios were 2.1. (95% CI: 1.6-2.7) for AD and 2.5 (95% CI: 1.9-3.3) for both types. Adjusted accelerated life models estimated median survival from dementia onset to death as 3.9 years for those with VaD, 7.1 years for AD, and 5.4 years for those with both types of dementia.

Published
2003

7. The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores.

Author

Page, Madeline L., Vance, Elizabeth L., Cloward, Matthew E., Ringger, Ed, Dayton, Louisa, Ebbert, Mark T. W., The Alzheimer's Disease Neuroimaging Initiative, Principal Investigator, Weiner, M. W., ATRI PI and Director of Coordinating Center Clinical Core, Aisen, P., Petersen, R., Executive Committee, Jack Jr, C. R., Jagust, W., Trojanowki, J. Q., Toga, A. W., Beckett, L., Green, R. C., and Saykin, A. J.

Subjects
DISEASE risk factors, MONOGENIC & polygenic inheritance (Genetics), GENOME-wide association studies, ALZHEIMER'S disease, GENETIC variation
Abstract

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research. The Polygenic Risk Score Knowledge Base (PRSKB) is a web-based interface that stores data from >2,300 distinct genome-wide association studies, and can estimate polygenic risk scores for general use. [ABSTRACT FROM AUTHOR]

Published
2022
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8. The Worldwide Alzheimer's Disease Neuroimaging Initiative: ADNI-3 updates and global perspectives

Author

Weber, CJ, Carrillo, MC, Jagust, W, Jack, CR, Shaw, LM, Trojanowski, JQ, Saykin, AJ, Beckett, LA, Sur, C, Rao, NP, Mendez, PC, Black, SE, Li, K, Iwatsubo, T, Chang, C-C, Sosa, AL, Rowe, CC, Perrin, RJ, Morris, JC, Healan, AMB, Hall, SE, Weiner, MW, Weber, CJ, Carrillo, MC, Jagust, W, Jack, CR, Shaw, LM, Trojanowski, JQ, Saykin, AJ, Beckett, LA, Sur, C, Rao, NP, Mendez, PC, Black, SE, Li, K, Iwatsubo, T, Chang, C-C, Sosa, AL, Rowe, CC, Perrin, RJ, Morris, JC, Healan, AMB, Hall, SE, and Weiner, MW

Abstract

The Worldwide Alzheimer's Disease Neuroimaging Initiative (WW-ADNI) is a collaborative effort to investigate imaging and biofluid markers that can inform Alzheimer's disease treatment trials. It is a public-private partnership that spans North America, Argentina, Australia, Canada, China, Japan, Korea, Mexico, and Taiwan. In 2004, ADNI researchers began a naturalistic, longitudinal study that continues today around the globe. Through several successive phases (ADNI-1, ADNI-GO, ADNI-2, and ADNI-3), the study has fueled amyloid and tau phenotyping and refined neuroimaging methodologies. WW-ADNI researchers have successfully standardized analyses and openly share data without embargo, providing a rich data set for other investigators. On August 26, 2020, the Alzheimer's Association convened WW-ADNI researchers who shared updates from ADNI-3 and their vision for ADNI-4.

Published
2021

9. How Will Aducanumab Approval Impact AD Research?

Author

Weiner, M.W., primary, Aisen, P.S., additional, Beckett, L.A., additional, Green, R.C., additional, Jagust, W., additional, Morris, J.C., additional, Okonkwo, O., additional, Perrin, R.J., additional, Petersen, R.C., additional, Rivera Mindt, M., additional, Saykin, A.J., additional, Shaw, L.M., additional, Toga, A.W., additional, and Trojanowski, J.Q., additional

Published
2021
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11. 18F-flortaucipir (AV-1451) tau PET in frontotemporal dementia syndromes 11 Medical and Health Sciences 1109 Neurosciences

Author

Tsai, RM, Bejanin, A, Lesman-Segev, O, Lajoie, R, Visani, A, Bourakova, V, O'Neil, JP, Janabi, M, Baker, S, Lee, SE, Perry, DC, Bajorek, L, Karydas, A, Spina, S, Grinberg, LT, Seeley, WW, Ramos, EM, Coppola, G, Gornoini, ML, Miller, BL, Rosen, HJ, Jagust, W, Boxer, AL, and Rabinovici, GD

Subjects
Tau imaging, Medical And Health Sciences, mental disorders, Tau, Biomarkers, Frontotemporal dementia, Neuropathology
Abstract

© 2019 The Author(s). Background: The tau positron emission tomography (PET) ligand 18F-flortaucipir binds to paired helical filaments of tau in aging and Alzheimer's disease (AD), but its utility in detecting tau aggregates in frontotemporal dementia (FTD) is uncertain. Methods: We performed 18F-flortaucipir imaging in patients with the FTD syndromes (n = 45): nonfluent variant primary progressive aphasia (nfvPPA) (n = 11), corticobasal syndrome (CBS) (n = 10), behavioral variant frontotemporal dementia (bvFTD) (n = 10), semantic variant primary progressive aphasia (svPPA) (n = 2) and FTD associated pathogenic genetic mutations microtubule-associated protein tau (MAPT) (n = 6), chromosome 9 open reading frame 72 (C9ORF72) (n = 5), and progranulin (GRN) (n = 1). All patients underwent MRI and β-amyloid biomarker testing via 11C-PiB or cerebrospinal fluid. 18F-flortaucipir uptake in patients was compared to 53 β-amyloid negative normal controls using voxelwise and pre-specified region of interest approaches. Results: On qualitative assessment, patients with nfvPPA showed elevated 18F-flortacupir binding in the left greater than right inferior frontal gyrus. Patients with CBS showed elevated binding in frontal white matter, with higher cortical gray matter uptake in a subset of β-amyloid-positive patients. Five of ten patients with sporadic bvFTD demonstrated increased frontotemporal binding. MAPT mutation carriers had elevated 18F-flortaucipir retention primarily, but not exclusively, in mutations with Alzheimer's-like neurofibrillary tangles. However, tracer retention was also seen in patients with svPPA, and the mutations C9ORF72, GRN predicted to have TDP-43 pathology. Quantitative region-of-interest differences between patients and controls were seen only in inferior frontal gyrus in nfvPPA and left insula and bilateral temporal poles in MAPT carriers. No significant regional differences were found in CBS or sporadic bvFTD. Two patients underwent postmortem neuropathological examination. A patient with C9ORF72, TDP-43-type B pathology, and incidental co-pathology of scattered neurofibrillary tangles in the middle frontal, inferior temporal gyrus showed corresponding mild 18F-flortaucipir retention without additional uptake matching the widespread TDP-43 type B pathology. A patient with sporadic bvFTD demonstrated punctate inferior temporal and hippocampus tracer retention, corresponding to the area of severe argyrophilic grain disease pathology. Conclusions: 18F-flortaucipir in patients with FTD and predicted tauopathy or TDP-43 pathology demonstrated limited sensitivity and specificity. Further postmortem pathological confirmation and development of FTD tau-specific ligands are needed.

Published
2019

12. A blood-based signature of cerebrospinal fluid A beta(1-42) status

Author

Goudey, B., Fung, B.J., Schieber, C., Faux, N.G., Weiner, M.W., Aisen, P., Petersen, R., Jack, C.R., Jagust, W., Trojanowki, J.Q., Toga, A.W., Beckett, L., Green, R.C., Saykin, A.J., Morris, J., Shaw, L.M., Kaye, J., Quinn, J., Silbert, L., Lind, B., Carter, R., Dolen, S., Schneider, L.S., Pawluczyk, S., Beccera, M., Teodoro, L., Spann, B.M., Brewer, J., Vanderswag, H., Fleisher, A., Heidebrink, J.L., Lord, J.L., Mason, S.S., Albers, C.S., Knopman, D., Johnson, K., Doody, R.S., Villanueva-Meyer, J., Chowdhury, M., Rountree, S., Dang, M., Stern, Y., Honig, L.S., Bell, K.L., Ances, B., Morris, J.C., Carroll, M., Creech, M.L., Franklin, E., Mintun, M.A., Schneider, S., Oliver, A., Marson, D., Griffth, R., Clark, D., Geldmacher, D., Brockington, J., Roberson, E., Natelson Love, M., Grossman, H., Mitsis, E., Shah, R.C., deToledo-Morrell, L., Duara, R., Varon, D., Greig, M.T., Roberts, P., Albert, M., Onyike, C., D'Agostino, D., Kielb, S., Galvin, J.E., Cerbone, B., Michel, C.A., Pogorelec, D.M., Rusinek, H., Leon, M.J. de, Glodzik, L., De Santi, S., Doraiswamy, P.M., Petrella, J.R., Borges-Neto, S., Wong, T.Z., Coleman, E., Smith, C.D., Jicha, G., Hardy, P., Sinha, P., Oates, E., Conrad, G., Porsteinsson, A.P., Goldstein, B.S., Martin, K., Makino, K.M., Ismail, M.S., Brand, C., Mulnard, R.A., Thai, G., McAdams-Ortiz, C., Womack, K., Mathews, D., Quiceno, M., Levey, A.I., Lah, J.J., Cellar, J.S., Burns, J.M., Swerdlow, R.H., Brooks, W.M., Apostolova, L., Tingus, K., Woo, E., Silverman, D.H.S., Lu, P.H., Bartzokis, G., Graff-Radford, N.R., Parftt, F., Kendall, T., Johnson, H., Farlow, M.R., Hake, A.M., Matthews, B.R., Brosch, J.R., Herring, S., Hunt, C., Dyck, .H. van, Carson, R.E., MacAvoy, M.G., Varma, P., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Hsiung, Ging-Yuek Robin, Feldman, H., Mudge, B., Assaly, M., Finger, E., Pasternack, S., Rachisky, I., Trost, D., Kertesz, A., Bernick, C., Munic, D., Mesulam, M.-M., Lipowski, K., Weintraub, S., Bonakdarpour, B., Kerwin, D., Wu, C.-K., Johnson, N., Sadowsky, C., Villena, T., Turner, R.S., Reynolds, B., Sperling, R.A., Johnson, K.A., Marshall, G., Yesavage, J., Taylor, J.L., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M.N., Belden, C.M., Jacobson, S.A., Sirrel, S.A., Kowall, N., Killiany, R., Budson, A.E., Norbash, A., Johnson, P.L., Obisesan, T.O., Wolday, S., Allard, J., Lerner, A., Ogrocki, P., Tatsuoka, C., Fatica, P., Fletcher, E., Maillard, P., Olichney, J., DeCarli, C., Carmichael, O., Kittur, S., Borrie, M., Lee, T.-Y., Bartha, R., Johnson, S., Asthana, S., Carlsson, C.M., Potkin, S.G., Preda, A., Nguyen, D., Tariot, P., Burke, A., Trncic, N., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, D.W., Kataki, M., Adeli, A., Zimmerman, E.A., Celmins, D., Brown, A.D., Pearlson, G.D., Blank, K., Anderson, K., Flashman, L.A., Seltzer, M., Hynes, M.L., Santulli, R.B., Sink, K.M., Gordineer, L., Williamson, J.D., Garg, P., Watkins, F., Ott, B.R., Querfurth, H., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, H.J., Miller, B.L., Perry, D., Mintzer, J., Spicer, K., Bachman, D., Pomara, N., Hernando, R., Sarrael, A., Relkin, N., Chaing, G., Lin, M., Ravdin, L., Smith, A., Raj, B.A., Fargher, K., Saykin, A., Nho, K., Kling, M., Toledo, J., Shaw, L., Trojanowski, J., Farrer, L., Kastsenmueller, G., Arnold, M., Wishart, D., Wurtz, P., Bhattcharyya, S., Duijin, C. van, Mangravite, L., Han, X., Hankemeier, T., Fiehn, O., Barupal, D., Thiele, I., Heinken, A., Meikle, P., Price, N., Funk, C., Jia, W., Kueider-Paisley, A., Tenebaum, J., Black, C., Moseley, A., Thompson, W., Mahmoudiandehkorki, S., Baillie, R., Welsh-Bohmer, K., Plassman, B., and Epidemiology

Subjects
Male, 0301 basic medicine, Apolipoprotein E, Oncology, medicine.medical_specialty, Amyloid, Amyloid beta, lcsh:Medicine, Article, 03 medical and health sciences, Apolipoproteins E, 0302 clinical medicine, Cerebrospinal fluid, Alzheimer Disease, Predictive Value of Tests, Internal medicine, medicine, Humans, Dementia, Cognitive decline, lcsh:Science, Aged, Aged, 80 and over, Amyloid beta-Peptides, Multidisciplinary, biology, Chemokine CCL26, business.industry, lcsh:R, Alzheimer’s Disease Metabolomics Consortium, Alzheimer’s Disease Neuroimaging Initiative, medicine.disease, Peptide Fragments, 3. Good health, 030104 developmental biology, biology.protein, Chromogranin A, Female, lcsh:Q, Alzheimer's disease, business, Biomarkers, 030217 neurology & neurosurgery, Alzheimer's Disease Neuroimaging Initiative
Abstract

It is increasingly recognized that Alzheimer’s disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1−42 (Aβ1−42) may be an earlier indicator of Alzheimer’s disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual’s CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1−42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1−42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1−42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1−42 levels and that the resulting model also validates reasonably across PET Aβ1−42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1−42 status, the earliest risk indicator for AD, with high accuracy.

Published
2019

16. Contributors

Author

Adam, M., primary, Alpert, Nathaniel M., additional, Anderson, J.R., additional, Andreasen, Nancy C., additional, Antonini, A., additional, Ardekani, Babak A., additional, Arndt, Stephan, additional, Ashburner, John, additional, Ashworth, Sharon, additional, Bailey, Dale L., additional, Baker, E., additional, Barnes, D.G., additional, Bench, C., additional, Bendriem, B., additional, Berdichevsky, D., additional, Biegon, A., additional, Blair, R.C., additional, Blomqvist, G., additional, Bloomfield, Peter M., additional, Ponto, Laura L. Boles, additional, Brakeman, Paul, additional, Braun, Michael, additional, Brooks, David J., additional, Brown, C.K., additional, Brown, W.D., additional, Bruckbauer, T., additional, Buckley, K.R., additional, Calonder, C., additional, Campbell, Gregory, additional, Carson, Richard E., additional, Chaly, Thomas, additional, Chan, G. L-Y., additional, Chen, Chin-Tu, additional, Cizadlo, Ted, additional, Cliffe, I.A., additional, Collins, D.L., additional, Cooper, Malcolm, additional, Crivello, F., additional, Crossnoe, M., additional, Cumming, Paul, additional, Cunningham, Vincent J., additional, Czernin, J., additional, Dahlbom, M., additional, Damasio, H., additional, DaSilva, J., additional, Witherspoon, Margaret E. Daube-, additional, DeJesus, O.T., additional, Delforge, J., additional, Dhawan, Vijay, additional, Dickhoven, S., additional, Diksic, Mirko, additional, Eberl, Stefan, additional, Egan, G.F., additional, Eidelberg, David, additional, Eriksson, Lars, additional, Evans, Alan C., additional, Fink, G.R., additional, Fischman, Alan J., additional, Fisher, Ronald E., additional, Fletcher, A., additional, Fontaine, A., additional, Ford, I., additional, Forse, G., additional, Frackowiak, R.S.J., additional, Frank, R.J., additional, Friston, K.J., additional, Frost, J. James, additional, Frouin, V., additional, Fujita, Hideaki, additional, Fujiwara, Takehiko, additional, Fukuda, H., additional, Fulham, Michael J., additional, Gee, Anthony D., additional, Gillings, N., additional, Gjedde, Albert, additional, Glaser, Robert, additional, Grabowski, T.J., additional, Graf, R., additional, Grafton, S.T., additional, Graham, Michael M., additional, Grasby, P., additional, Gunn, R.N., additional, Günther, I., additional, Hagisawa, S., additional, Haida, A., additional, Halber, M., additional, Hallett, Mark, additional, Hansen, Lars K., additional, Harris, Greg, additional, Haslam, Jane, additional, Hasselbalch, Steen, additional, Hatazawa, Jun, additional, Heiss, W.-D., additional, Herholz, K., additional, Herscovitch, Peter, additional, Herzog, H., additional, Hichwa, Richard D., additional, Hoh, C., additional, Holden, J.E., additional, Holm, Søren, additional, Holmes, A.P., additional, Holmes, C.J., additional, Hooper, Patrick K., additional, Houle, S., additional, Houser, D., additional, Huang, Sung-Cheng, additional, Hume, S.P., additional, Hurtig, Richard R., additional, Hussey, D., additional, Hutton, Brian F., additional, Iacoboni, M., additional, Ido, T., additional, Iida, Hidehiro, additional, Inoue, O., additional, Ishii, Kazunari, additional, Ishikawa, Tatsuya, additional, Itoh, H., additional, Itoh, Masatoshi, additional, Iwata, R., additional, Jadali, F., additional, Jagust, W., additional, Jivan, S., additional, Joliot, M., additional, Jones, A.K.P., additional, Jones, C., additional, Jones, Terry, additional, Kanno, Iwao, additional, Kao, Chien-Min, additional, Kapur, S., additional, Karbe, H., additional, Kessler, J., additional, Kilbourn, Michael R., additional, Kimura, Yuichi, additional, Kinahan, P.E., additional, Knorr, U., additional, Kobayashi, K., additional, Kops, E. Rota, additional, Kosugi, Yukio, additional, Kruger, Mark, additional, Kuwabara, Hiroto, additional, Lammertsma, Adriaan A., additional, Laurier, L., additional, Law, Ian, additional, Leenders, K.L., additional, Legg, B., additional, Levin, Z., additional, Lin, Kang-Ping, additional, Links, Jonathan M., additional, Lipinski, B., additional, Lopresti, B.J., additional, Löttgen, J., additional, Luthra, S.K., additional, Ma, Yilong, additional, Maguire, R.P., additional, Mahmood, K., additional, Malizia, Andrea L., additional, Mankoff, David A., additional, Marenco, Stefano, additional, Marrett, S., additional, Mathis, C.A., additional, Matsumura, Y., additional, Mazoyer, B., additional, Mazziotta, John C., additional, McCarron, J.A., additional, Meguro, K., additional, Meikle, Steven R., additional, Mejia, Marco A., additional, Mellet, E., additional, Meltzer, Carolyn Cidis, additional, Meyer, Ernst, additional, Millet, P., additional, Minoshima, S., additional, Mintun, M.A., additional, Missimer, J., additional, Miura, Shuichi, additional, Miyake, M., additional, Momose, Toshimitsu, additional, Mørch, Niels, additional, Morris, Evan D., additional, Morrish, Paul K., additional, Morrison, S., additional, Müller-Gärtner, H.W., additional, Murase, Kenya, additional, Muzi, Mark, additional, Myers, R., additional, Nakamura, Takashi, additional, Nariai, Tadashi, additional, Neelin, P., additional, Nickles, R.J., additional, Nishikawa, Junichi, additional, Nishizawa, Sadahiko, additional, Nutt, D.J., additional, O'Keefe, G.J., additional, O'Leary, Daniel S., additional, O'Sullivan, B.T., additional, O'Sullivan, Finbarr, additional, Oberschelp, W., additional, Ogawa, Toshihide, additional, Ono, S., additional, Osman, S., additional, Patlak, Clifford, additional, Paulson, Olaf B., additional, Pawlik, Gunter, additional, Petit, L., additional, Pietrzyk, U., additional, Pike, V.W., additional, Poline, J.-B., additional, Poole, K., additional, Price, J.C., additional, Psylla, M., additional, Pyzalski, Robert, additional, Rajeswaran, S., additional, Rakshi, James S., additional, Ranicar, Alex, additional, Rauch, Scott L., additional, Remy, P., additional, Reutens, David C., additional, Roberts, Andy, additional, Rosenqvist, G., additional, Rottenberg, D.A., additional, Rousset, Olivier G., additional, Ruth, T.J., additional, Sadato, Norihiro, additional, Samson, Y., additional, Sasaki, H., additional, Sase, Mikiya, additional, Sashin, D., additional, Schaper, K., additional, Schlaug, G., additional, Schnorr, L., additional, Seitz, R.J., additional, Senda, Michio, additional, Shelton, S.E., additional, Shields, Anthony F., additional, Shimosegawa, Eku, additional, Shiraishi, Masahiro, additional, Shrager, Richard, additional, Sidtis, J.J., additional, Simpson, N.R., additional, Smith, D., additional, Smith, Donald F., additional, Snow, B.J., additional, Snyder, Abraham Z., additional, Sossi, V., additional, Spelle, L., additional, Spence, Alexander, additional, Strother, S.C., additional, Stumpf, Martin J., additional, Suganami, Yusuke, additional, Svarer, Claus, additional, Swerdloff, S.J., additional, Syrota, A., additional, Taguchi, A., additional, Talarico, E., additional, Taylor, Chris, additional, Tellman, L., additional, Thiel, A., additional, Danguy, H. J. Tochon-, additional, Toga, Arthur W., additional, Toussaint, P.-J., additional, Townsend, D.W., additional, Toyama, Hinako, additional, Trébossen, R., additional, Tzourio, N., additional, Uchiyama, A., additional, Uemura, Kazuo, additional, Uno, H., additional, Vafaee, M., additional, Vingerhoets, F.J.G., additional, Vontobel, P., additional, Wagner, R., additional, Watabe, Hiroshi, additional, Watkins, G. Leonard, additional, Watson, J.D.G., additional, Wernick, Miles, additional, Wienhard, K., additional, Wilson, A.A., additional, Wilson, S., additional, Wollenweber, Scott D., additional, Wong, Dean F., additional, Woods, Roger P., additional, Worsley, K.J., additional, Yan, Yuchen, additional, Yanai, K., additional, Yang, J., additional, Yap, Jeffrey T., additional, Yu, D.C., additional, Zeien, Gene, additional, Zhou, Y., additional, and Zubieta, Jon Kar, additional

Published
1996
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17. Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

Author

Young, A. L., Marinescu, R. V., Oxtoby, N. P., Bocchetta, M., Yong, K., Firth, N. C., Cash, D. M., Thomas, D. L., Dick, K. M., Cardoso, J., van Swieten, J., Borroni, B., Galimberti, D., Masellis, M., Tartaglia, M. C., Rowe, J. B., Graff, C., Tagliavini, F., Frisoni, G. B., Laforce, R., Finger, E., de Mendonca, A., Sorbi, S., Warren, J. D., Crutch, S., Fox, N. C., Ourselin, S., Schott, J. M., Rohrer, J. D., Alexander, D. C., Andersson, C., Archetti, S., Arighi, A., Benussi, L., Binetti, G., Black, S., Cosseddu, M., Fallstrom, M., Ferreira, C., Fenoglio, C., Freedman, M., Fumagalli, G. G., Gazzina, S., Ghidoni, R., Grisoli, M., Jelic, V., Jiskoot, L., Keren, R., Lombardi, G., Maruta, C., Meeter, L., Mead, S., van Minkelen, R., Nacmias, B., Oijerstedt, L., Padovani, A., Panman, J., Pievani, M., Polito, C., Premi, E., Prioni, S., Rademakers, R., Redaelli, V., Rogaeva, E., Rossi, G., Rossor, M., Scarpini, E., Tang-Wai, D., Thonberg, H., Tiraboschi, P., Verdelho, A., Weiner, M. W., Aisen, P., Petersen, R., Jack, C. R., Jagust, W., Trojanowki, J. Q., Toga, A. W., Beckett, L., Green, R. C., Saykin, A. J., Morris, J., Shaw, L. M., Khachaturian, Z., Sorensen, G., Kuller, L., Raichle, M., Paul, S., Davies, P., Fillit, H., Hefti, F., Holtzman, D., Mesulam, M. M., Potter, W., Snyder, P., Schwartz, A., Montine, T., Thomas, R. G., Donohue, M., Walter, S., Gessert, D., Sather, T., Jiminez, G., Harvey, D., Bernstein, M., Thompson, P., Schuff, N., Borowski, B., Gunter, J., Senjem, M., Vemuri, P., Jones, D., Kantarci, K., Ward, C., Koeppe, R. A., Foster, N., Reiman, E. M., Chen, K., Mathis, C., Landau, S., Cairns, N. J., Householder, E., Taylor-Reinwald, L., Lee, V., Korecka, M., Figurski, M., Crawford, K., Neu, S., Foroud, T. M., Potkin, S., Shen, L., Faber, K., Kim, S., Nho, K., Thal, L., Buckholtz, N., Albert, M., Frank, R., Hsiao, J., Kaye, J., Quinn, J., Lind, B., Carter, R., Dolen, S., Schneider, L. S., Pawluczyk, S., Beccera, M., Teodoro, L., Spann, B. M., Brewer, J., Vanderswag, H., Fleisher, A., Heidebrink, J. L., Lord, J. L., Mason, S. S., Albers, C. S., Knopman, D., Johnson, K., Doody, R. S., Villanueva-Meyer, J., Chowdhury, M., Rountree, S., Dang, M., Stern, Y., Honig, L. S., Bell, K. L., Ances, B., Carroll, M., Leon, S., Mintun, M. A., Schneider, S., Oliver, A., Marson, D., Griffith, R., Clark, D., Geldmacher, D., Brockington, J., Roberson, E., Grossman, H., Mitsis, E., de Toledo-Morrell, L., Shah, R. C., Duara, R., Varon, D., Greig, M. T., Roberts, P., Onyike, C., D'Agostino, D., Kielb, S., Galvin, J. E., Cerbone, B., Michel, C. A., Rusinek, H., de Leon, M. J., Glodzik, L., De Santi, S., Doraiswamy, P. M., Petrella, J. R., Wong, T. Z., Arnold, S. E., Karlawish, J. H., Wolk, D., Smith, C. D., Jicha, G., Hardy, P., Sinha, P., Oates, E., Conrad, G., Lopez, O. L., Oakley, M. A., Simpson, D. M., Porsteinsson, A. P., Goldstein, B. S., Martin, K., Makino, K. M., Ismail, M. S., Brand, C., Mulnard, R. A., Thai, G., Mc-Adams-Ortiz, C., Womack, K., Mathews, D., Quiceno, M., Diaz-Arrastia, R., King, R., Weiner, M., Martin-Cook, K., Devous, M., Levey, A. I., Lah, J. J., Cellar, J. S., Burns, J. M., Anderson, H. S., Swerdlow, R. H., Apostolova, L., Tingus, K., Woo, E., Silverman, D. H., P. H., Lu, Bartzokis, G., Graff-Radford, N. R., Parfitt, F., Kendall, T., Johnson, H., Farlow, M. R., Hake, A. M., Matthews, B. R., Herring, S., Hunt, C., van Dyck, C. H., Carson, R. E., Macavoy, M. G., Chertkow, H., Bergman, H., Hosein, C., Stefanovic, B., Caldwell, C., Hsiung, G. -Y. R., Feldman, H., Mudge, B., Assaly, M., Kertesz, A., Rogers, J., Bernick, C., Munic, D., Kerwin, D., Mesulam, M. -M., Lipowski, K., C. -K., Wu, Johnson, N., Sadowsky, C., Martinez, W., Villena, T., Turner, R. S., Reynolds, B., Sperling, R. A., Johnson, K. A., Marshall, G., Frey, M., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M. N., Belden, C. M., Jacobson, S. A., Sirrel, S. A., Kowall, N., Killiany, R., Budson, A. E., Norbash, A., Johnson, P. L., Allard, J., Lerner, A., Ogrocki, P., Hudson, L., Fletcher, E., Carmichael, O., Olichney, J., Decarli, C., Kittur, S., Borrie, M., Lee, T. -Y., Bartha, R., Johnson, S., Asthana, S., Carlsson, C. M., Potkin, S. G., Preda, A., Nguyen, D., Tariot, P., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, D. W., Kataki, M., Adeli, A., Zimmerman, E. A., Celmins, D., Brown, A. D., Pearlson, G. D., Blank, K., Anderson, K., Santulli, R. B., Kitzmiller, T. J., Schwartz, E. S., Sink, K. M., Williamson, J. D., Garg, P., Watkins, F., Ott, B. R., Querfurth, H., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, H. J., Miller, B. L., Mintzer, J., Spicer, K., Bachman, D., Pasternak, S., Rachinsky, I., Drost, D., Pomara, N., Hernando, R., Sarrael, A., Schultz, S. K., Ponto, L. L. B., Shim, H., Smith, K. E., Relkin, N., Chaing, G., Raudin, L., Smith, A., Fargher, K., Raj, B. A., Neylan, T., Grafman, J., Davis, M., Morrison, R., Hayes, J., Finley, S., Friedl, K., Fleischman, D., Arfanakis, K., James, O., Massoglia, D., Fruehling, J. J., Harding, S., Peskind, E. R., Petrie, E. C., Li, G., Yesavage, J. A., Taylor, J. L., and Furst, A. J.

Published
2018

20. F-18-AV-1451 in frontotemporal dementia spectrum disorders

Author

Tsai, R., Bejanin, A., Schonhaut, D., Ossenkoppele, R., O'Neil, J., Janabi, M., Baker, S., Lazaris, A., Ayakta, N., Tammewar, G., Gorno-Tempini, M., Miller, B., Boxer, A., Jagust, W., Rabinovici, G., Neurology, and Amsterdam Neuroscience - Neurodegeneration

Published
2016

22. Sex-dependent association of common variants of microcephaly genes with brain structure

Author

Rimol, L. M., Agartz, I., Djurovic, S., Brown, A. A., Roddey, J. C., Kahler, A. K., Mattingsdal, M., Athanasiu, L., Joyner, A. H., Schork, N. J., Halgren, E., Sundet, K., Melle, I., Dale, A. M., Andreassen, O. A., Weiner, M., Thal, L., Petersen, R., Jack, C. R., Jagust, W., Trojanowki, J., Toga, A. W., Beckett, L., Green, R. C., Gamst, A., Potter, W. Z., Montine, T., Anders, D., Bernstein, M., Felmlee, J., Fox, N., Thompson, P., Schuff, N., Alexander, G., Bandy, D., Koeppe, R. A., Foster, N., Reiman, E. M., Chen, K., Shaw, L., Lee, V. M.- Y., Korecka, M., Crawford, K., Neu, S., Harvey, D., Kornak, J., Kachaturian, Z., Frank, R., Snyder, P. J., Molchan, S., Kaye, J., Vorobik, R., Quinn, J., Schneider, L., Pawluczyk, S., Spann, B., Fleisher, A. S., Vanderswag, H., Heidebrink, J. L., Lord, J. L., Johnson, K., Doody, R. S., Villanueva-Meyer, J., Chowdhury, M., Stern, Yaakov, Honig, L. S., Bell, K. L., Morris, J. C., Mintun, M. A., Schneider, S., Marson, D., Griffith, R., Badger, B., Grossman, H., Tang, C., Stern, J., deToledo-Morrell, L., Shah, R. C., Bach, J., Duara, R., Isaacson, R., Strauman, S., Albert, M. S., Pedroso, J., Toroney, J., Rusinek, H., de Leon, M. J., De Santi, S. M., Doraiswamy, P. M., Petrella, J. R., Aiello, M., Clark, C. M., Pham, C., Nunez, J., Smith, C. D., Given II, C. A., Hardy, P., DeKosky, S. T., Oakley, M., Simpson, D. M., Ismail, M. S., Porsteinsson, A., McCallum, C., Cramer, S. C., Mulnard, R. A., McAdams-Ortiz, C., Diaz-Arrastia, R., Martin-Cook, K., DeVous, M., Levey, A. I., Lah, J. J., Cellar, J. S., Burns, J. M., Anderson, H. S., Laubinger, M. M., Bartzokis, G., Silverman, D. H. S., Lu, P. H., Fletcher, R., Parfitt, F., Johnson, H., Farlow, M., Herring, S., Hake, A. M., van Dyck, C. H., MacAvoy, M. G., Bifano, L. A., Chertkow, H., Bergman, H., Hosein, C., Black, S., Graham, S., Caldwell, C., Feldman, H., Assaly, M., Hsiung, G.-Y. R., Kertesz, A., Rogers, J., Trost, D., Bernick, C., Gitelman, D., Johnson, N., Mesulam, M., Sadowsky, C., Villena, T., Mesner, S., Aisen, P. S., Johnson, K. B., Behan, K. E., Sperling, R. A., Rentz, D. M., Johnson, K. A., Rosen, A., Tinklenberg, J., Ashford, W., Sabbagh, M., Connor, D., Obradov, S., Killiany, R., Norbash, A., Obisesan, T. O., Jayam-Trouth, A., Wang, P., Auchus, A. P., Huang, J., Friedland, R. P., DeCarli, C., Fletcher, E., Carmichael, O., Kittur, S., Mirje, S., Johnson, S. C., Borrie, M., Lee, T.-Y., Asthana, S., Carlsson, C. M., Potkin, S. G., Highum, D., Preda, A., Nguyen, D., Tariot, P. N., Hendin, B. A., Scharre, D. W., Kataki, M., Beversdorf, D. Q., Zimmerman, E. A., Celmins, D., Brown, A. D., Gandy, S., Marenberg, M. E., Rovner, B. W., Pearlson, G., Blank, K., Anderson, K., Saykin, A. J., Santulli, R. B., Pare, N., Williamson, J. D., Sink, K. M., Potter, H., Ashok Raj, B., Giordano, A., Ott, B. R., Wu, C.-K., Cohen, R., Wilks, K. L., and Alzheimer's Disease Neuroimaging Initiative

Subjects
Adult, Male, Microcephaly, Molecular Sequence Data, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Brain mapping, ASPM, Sex Factors, medicine, Animals, Humans, SNP, Genetic Predisposition to Disease, Genetics, Brain Mapping, Multidisciplinary, CDK5RAP2, Brain morphometry, Brain, Middle Aged, Biological Sciences, medicine.disease, Magnetic Resonance Imaging, Phenotype, Brain size, Female
Abstract

Loss-of-function mutations in the genes associated with primary microcephaly (MCPH) reduce human brain size by about two-thirds, without producing gross abnormalities in brain organization or physiology and leaving other organs largely unaffected [Woods CG, et al. (2005) Am J Hum Genet 76:717–728]. There is also evidence suggesting that MCPH genes have evolved rapidly in primates and humans and have been subjected to selection in recent human evolution [Vallender EJ, et al. (2008) Trends Neurosci 31:637–644]. Here, we show that common variants of MCPH genes account for some of the common variation in brain structure in humans, independently of disease status. We investigated the correlations of SNPs from four MCPH genes with brain morphometry phenotypes obtained with MRI. We found significant, sex-specific associations between common, nonexonic, SNPs of the genes CDK5RAP2 , MCPH1 , and ASPM , with brain volume or cortical surface area in an ethnically homogenous Norwegian discovery sample ( n = 287), including patients with mental illness. The most strongly associated SNP findings were replicated in an independent North American sample ( n = 656), which included patients with dementia. These results are consistent with the view that common variation in brain structure is associated with genetic variants located in nonexonic, presumably regulatory, regions.

Published
2009

23. Large-scale genomics unveil polygenic architecture of human cortical surface area

Author

Chen, CH, Peng, Q, Schork, AJ, Lo, MT, Fan, CC, Wang, Y, Desikan, RS, Bettella, F, Hagler, DJ, Westlye, LT, Kremen, WS, Jernigan, TL, Le Hellard, S, Steen, VM, Espeseth, T, Huentelman, M, Håberg, AK, Agartz, I, Djurovic, S, Andreassen, OA, Schork, N, Dale, AM, McCabe, C, Chang, L, Akshoomoff, N, Newman, E, Ernst, T, Van Zijl, P, Kuperman, J, Murray, S, Bloss, C, Appelbaum, M, Gamst, A, Thompson, W, Bartsch, H, Weiner, M, Aisen, P, Petersen, R, Jack, CR, Jagust, W, Trojanowki, JQ, Toga, AW, Beckett, L, Green, RC, Saykin, AJ, Morris, J, Shaw, LM, Khachaturian, Z, Sorensen, G, Carrillo, M, Kuller, L, Raichle, M, Paul, S, Davies, P, Fillit, H, Hefti, F, Holtzman, D, Mesulman, MM, Potter, W, Snyder, PJ, Schwartz, A, Montine, T, Thomas, RG, Donohue, M, Walter, S, Gessert, D, Sather, T, Jiminez, G, Harvey, D, Bernstein, M, Fox, N, Thompson, P, Schuff, N, DeCarli, C, Borowski, B, Gunter, J, Senjem, M, Vemuri, P, Jones, D, Kantarci, K, Ward, C, Koeppe, RA, Foster, N, and Reiman, EM

Abstract

© 2015 Macmillan Publishers Limited. All rights reserved. Little is known about how genetic variation contributes to neuroanatomical variability, and whether particular genomic regions comprising genes or evolutionarily conserved elements are enriched for effects that influence brain morphology. Here, we examine brain imaging and single-nucleotide polymorphisms (SNPs) data from ∼ 2,700 individuals. We show that a substantial proportion of variation in cortical surface area is explained by additive effects of SNPs dispersed throughout the genome, with a larger heritable effect for visual and auditory sensory and insular cortices (h2 ∼ 0.45). Genome-wide SNPs collectively account for, on average, about half of twin heritability across cortical regions (N = 466 twins). We find enriched genetic effects in or near genes. We also observe that SNPs in evolutionarily more conserved regions contributed significantly to the heritability of cortical surface area, particularly, for medial and temporal cortical regions. SNPs in less conserved regions contributed more to occipital and dorsolateral prefrontal cortices.

Published
2015

24. Ferritin levels in the cerebrospinal fluid predict Alzheimer's disease outcomes and are regulated by APOE

Author

Ayton, S, Faux, NG, Bush, AI, Weiner, MW, Aisen, P, Petersen, R, Jack, CR, Jagust, W, Trojanowki, JQ, Toga, AW, Beckett, L, Green, RC, Saykin, AJ, Morris, J, Shaw, LM, Khachaturian, Z, Sorensen, G, Kuller, L, Raichle, M, Paul, S, Davies, P, Fillit, H, Hefti, F, Holtzman, D, Mesulam, MM, Potter, W, Snyder, P, Schwartz, A, Montine, T, Thomas, RG, Donohue, M, Walter, S, Gessert, D, Sather, T, Jiminez, G, Harvey, D, Bernstein, M, Fox, N, Thompson, P, Schuff, N, Borowski, B, Gunter, J, Senjem, M, Vemuri, P, Jones, D, Kantarci, K, Ward, C, Koeppe, RA, Foster, N, Reiman, EM, Chen, K, Mathis, C, Landau, S, Cairns, NJ, Householder, E, Taylor-Reinwald, L, Lee, V, Korecka, M, Figurski, M, Crawford, K, Neu, S, Foroud, TM, Potkin, S, Shen, L, Faber, K, Kim, S, Nho, K, Thal, L, Buckholtz, N, Albert, M, Frank, R, Hsiao, J, Kaye, J, Quinn, J, Lind, B, Carter, R, Dolen, S, Schneider, LS, Pawluczyk, S, Beccera, M, Teodoro, L, Spann, BM, Brewer, J, Vanderswag, H, Fleisher, A, Heidebrink, JL, Lord, JL, Mason, SS, Albers, CS, Knopman, D, Johnson, K, Doody, RS, Villanueva-Meyer, J, Chowdhury, M, and Rountree, S

Abstract

© 2015 Macmillan Publishers Limited. All rights reserved. Brain iron elevation is implicated in Alzheimer's disease (AD) pathogenesis, but the impact of iron on disease outcomes has not been previously explored in a longitudinal study. Ferritin is the major iron storage protein of the body; by using cerebrospinal fluid (CSF) levels of ferritin as an index, we explored whether brain iron status impacts longitudinal outcomes in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We show that baseline CSF ferritin levels were negatively associated with cognitive performance over 7 years in 91 cognitively normal, 144 mild cognitive impairment (MCI) and 67 AD subjects, and predicted MCI conversion to AD. Ferritin was strongly associated with CSF apolipoprotein E levels and was elevated by the Alzheimer's risk allele, APOE-ε4. These findings reveal that elevated brain iron adversely impacts on AD progression, and introduce brain iron elevation as a possible mechanism for APOE-ε4 being the major genetic risk factor for AD.

Published
2015

25. Predicting reduction of cerebrospinal fluid β-Amyloid 42 in Cognitively healthy controls

Author

Mattsson, N, Insel, PS, Donohue, M, Jagust, W, Sperling, R, Aisen, P, and Weiner, MW

Abstract

© 2015 American Medical Association. All rights reserved. IMPORTANCE Alzheimer disease has a long preclinical stage characterized by β-amyloid (Aβ) accumulation without symptoms. Several trials focus on this stage and use biomarkers to include Aβ-positive participants, but an even earlier prevention of Aβ accumulation may be an effective treatment strategy. OBJECTIVE To determine whether people who appear to be Aβ negative but are at high risk for Aβ positivity within the near future can be identified. DESIGN, SETTING, AND PARTICIPANTS Longitudinal biomarker cohort study involving 35 cognitively healthy individuals who underwent cerebrospinal fluid (CSF) sampling for up to 3 years during the study (October 24, 2005, to September 1, 2014). All participants had normal CSF Aβ42 levels at baseline. MAIN OUTCOMES AND MEASURES Predictors of future Aβ positivity (levels of CSF Aβ42 declining below a previously validated cutoff level of 192 ng/L) tested by random forest models. Tested predictors included levels of protein in the CSF, hippocampal volume, genetics, demographics, and cognitive scores. RESULTS The CSF Aβ42 levels declined in 11 participants, and the CSF became Aβ positive. The baseline CSF Aβ42 level was a strong predictor of future positivity (accuracy, 79% [95% CI, 70%-87%]). Ten of 11 decliners had baseline CSF Aβ42 levels in the lower tertile of the reference range (

Published
2015

27. Brain structure and cognition in a community sample of elderly Latinos

Author

Wu, C. C., Mungas, D., Petkov, C. I., Eberling, J. L., Patricia Zrelak, Buonocore, M. H., Brunberg, J. A., Haan, M. N., and Jagust, W. J.

Subjects
Aged, 80 and over, Male, Aging, Analysis of Variance, Chi-Square Distribution, Data Collection, Brain, Middle Aged, Hippocampus, Magnetic Resonance Imaging, Cohort Studies, Logistic Models, Mexican Americans, Confidence Intervals, Odds Ratio, Humans, Female, Neurology (clinical), Atrophy, Cognition Disorders, Aged
Abstract

Previous studies have found that hippocampal atrophy and white matter hyperintensities (WMH) on MRI are linked to cognitive impairment and dementia. The authors measured these variables in a population-based cohort of older Mexican Americans with a wide spectrum of cognitive ability, ranging from normal cognition to dementia.To investigate whether these structural brain changes were seen in individuals prior to the development of dementia and how these changes were related to the presence of dementia.A sample of 122 subjects was selected from the Sacramento Area Latino Study on Aging, and subjects were categorized into four groups of increasing levels of cognitive impairment: normal, memory impaired (MI), cognitively impaired but not demented (CIND), and demented. Hippocampal volume was quantified using a region of interest approach. WMH was rated on a semiquantitative scale as the percent of total volume of white matter.Hippocampal volume was significantly reduced in CIND and demented individuals, and WMH were significantly increased in demented subjects. MI subjects did not have any significant changes in hippocampal volume or WMH. The risk for developing dementia was significantly and comparably increased in subjects with either hippocampal atrophy or high WMH. However, the risk for dementia increased dramatically in subjects with both hippocampal atrophy and a high degree of WMH.Reductions in hippocampal volume may be present before dementia but not until cognitive impairment is relatively severe. Because there is a synergistic effect between high WMH and hippocampal atrophy, interactions between vascular and degenerative processes may be important determinants of dementia.

Published
2002

29. Prefrontal atrophy, disrupted NREM slow waves and impaired hippocampal-dependent memory in aging

Author

Mander, BA, Rao, V, Lu, B, Saletin, JM, Lindquist, JR, Ancoli-Israel, S, Jagust, W, and Walker, MP

Abstract

Aging has independently been associated with regional brain atrophy, reduced slow wave activity (SWA) during non-rapid eye movement (NREM) sleep and impaired long-term retention of episodic memories. However, whether the interaction of these factors represents a neuropatholgical pathway associated with cognitive decline in later life remains unknown. We found that age-related medial prefrontal cortex (mPFC) gray-matter atrophy was associated with reduced NREM SWA in older adults, the extent to which statistically mediated the impairment of overnight sleep-dependent memory retention. Moreover, this memory impairment was further associated with persistent hippocampal activation and reduced task-related hippocampal-prefrontal cortex functional connectivity, potentially representing impoverished hippocampal-neocortical memory transformation. Together, these data support a model in which age-related mPFC atrophy diminishes SWA, the functional consequence of which is impaired long-term memory. Such findings suggest that sleep disruption in the elderly, mediated by structural brain changes, represents a contributing factor to age-related cognitive decline in later life. © 2013 Nature America, Inc.

Published
2013

30. Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity

Author

Jahanshad, N., Rajagopalan, P., Hua, X., Hibar, D. P., Nir, T. M., Toga, A. W., Jack, C. R., Saykin, A. J., Green, R. C., Weiner, M. W., Medland, S. E., Montgomery, G. W., Hansell, N. K., McMahon, K. L., de Zubicaray, G. I., Martin, N. G., Wright, M. J., Thompson, P. M., the Alzheimer's Disease Neuroimaging Initiative, Weiner, M., Aisen, P., Petersen, R., Jagust, W., Trojanowski, J. Q., Beckett, L., Morris, J., Liu, E., Montine, T., Gamst, A., Thomas, R. G., Donohue, M., Walter, S., Gessert, D., Sather, T., Harvey, D., Kornak, J., Dale, A., Bernstein, M., Felmlee, J., Fox, N., Thompson, P., Schuff, N., Alexander, G., DeCarli, C., Bandy, D., Koeppe, R. A., Foster, N., Reiman, E. M., Chen, K., Mathis, C., Cairns, N. J., Taylor-Reinwald, L., Trojanowki, J. Q., Shaw, L., Lee, V. M. Y., Korecka, M., Crawford, K., Neu, S., Foroud, T. M., Potkin, S., Shen, L., Khachaturian, Z., Frank, R., Snyder, P. J., Molchan, S., Kaye, J., Quinn, J., Lind, B., Dolen, S., Schneider, L. S., Pawluczyk, S., Spann, B. M., Brewer, J., Vanderswag, H., Heidebrink, J. L., Lord, J. L., Johnson, K., Doody, R. S., Villanueva-Meyer, J., Chowdhury, M., Stern, Yaakov, Honig, L. S., Bell, K. L., Morris, J. C., Ances, B., Carroll, M., Leon, S., Mintun, M. A., Schneider, S., Marson, D., Griffith, R., Clark, D., Grossman, H., Mitsis, E., Romirowsky, A., deToledo-Morrell, L., Shah, R. C., Duara, R., Varon, D., Roberts, P., Albert, M., Onyike, C., Kielb, S., Rusinek, H., de Leon, M. J., Glodzik, L., De Santi, S., Doraiswamy, P. M., Petrella, J. R., Coleman, R. E., Arnold, S. E., Karlawish, J. H., Wolk, D., Smith, C. D., Jicha, G., Hardy, P., Lopez, O. L., Oakley, M., Simpson, D. M., Porsteinsson, A. P., Goldstein, B. S., Martin, K., Makino, K. M., Ismail, M. S., Brand, C., Mulnard, R. A., Thai, G., Mc-Adams-Ortiz, C., Womack, K., Mathews, D., Quiceno, M., Diaz-Arrastia, R., King, R., Martin-Cook, K., DeVous, M., Levey, A. I., Lah, J. J., Cellar, J. S., Burns, J. M., Anderson, H. S., Swerdlow, R. H., Apostolova, L., Lu, P. H., Bartzokis, G., Silverman, D. H. S., Graff-Radford, N. R., Parfitt, F., Johnson, H., Farlow, M. R., Hake, A. M., Matthews, B. R., Herring, S., van Dyck, C. H., Carson, R. E., MacAvoy, M. G., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Hsiung, G.-Y. R., Feldman, H., Mudge, B., Assaly, M., Kertesz, A., Rogers, J., Trost, D., Bernick, C., Munic, D., Kerwin, D., Mesulam, M.-M., Lipowski, K., Wu, C.-K., Johnson, N., Sadowsky, C., Martinez, W., Villena, T., Turner, R. S., Reynolds, B., Sperling, R. A., Johnson, K. A., Marshall, G., Frey, M., Yesavage, J., Taylor, J. L., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M., Belden, C., Jacobson, S., Kowall, N., Killiany, R., Budson, A. E., Norbash, A., Johnson, P. L., Obisesan, T. O., Wolday, S., Bwayo, S. K., Lerner, A., Hudson, L., Ogrocki, P., Fletcher, E., Carmichael, O., Olichney, J., Kittur, S., Borrie, M., Lee, T.- Y., Bartha, R., Johnson, S., Asthana, S., Carlsson, C. M., Potkin, S. G., Preda, A., Nguyen, D., Tariot, P., Fleisher, A., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, D. W., Kataki, M., Zimmerman, E. A., Celmins, D., Brown, A. D., Pearlson, G. D., Blank, K., Anderson, K., Santulli, R. B., Schwartz, E. S., Sink, K. M., Williamson, J. D., Garg, P., Watkins, F., Ott, B. R., Querfurth, H., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, H. J., Miller, B. L., Mintzer, J., Longmire, C. F., Spicer, K., Finger, E., Rachinsky, I., and Drost, D.

Published
2013
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31. Association of common genetic variants in GPCPD1 with scaling of visual cortical surface area in humans

Author

Bakken, TE, Roddey, JC, Djurovic, S, Akshoomoff, N, Amaral, DG, Bloss, CS, Casey, BJ, Chang, L, Ernst, TM, Gruen, JR, Jernigan, TL, Kaufmann, WE, Kenet, T, Kennedy, DN, Kuperman, JM, Murray, SS, Sowell, ER, Rimol, LM, Mattingsdal, M, Melle, I, Agartz, I, Andreassen, OA, Schork, NJ, Dale, AM, Alzheimer’s Disease Neuroimaging Initiative, Pediatric Imaging, Neurocognition, Genetics Study, Weiner, M, Aisen, P, Petersen, R, Jack, CR, Jr, Jagust, W, Trojanowki, JQ, Toga, AW, Beckett, L, Green, RC, Saykin, AJ, Morris, J, Liu, E, Montine, T, Gamst, A, Thomas, RG, Donohue, M, Walter, S, Gessert, D, Sather, T, Harvey, D, Kornak, J, Dale, A, Bernstein, M, Felmlee, J, Fox, N, Thompson, P, Schuff, N, Alexander, G, DeCarli, C, Bandy, D, Koeppe, RA, Foster, N, Reiman, EM, Chen, K, Mathis, C, Cairns, NJ, Taylor-Reinwald, L, Shaw, L, Lee, VM, Korecka, M, Crawford, K, Neu, S, Foroud, TM, Potkin, S, Shen, L, Kachaturian, Z, Frank, R, Snyder, PJ, Molchan, S, Kaye, J, Quinn, J, Lind, B, Dolen, S, Schneider, LS, Pawluczyk, S, Spann, BM, Brewer, J, Vanderswag, H, Heidebrink, JL, Lord, JL, Johnson, K, Doody, RS, Villanueva-Meyer, J, Chowdhury, M, Stern, Yaakov, Honig, LS, Bell, KL, Morris, JC, Ances, B, Carroll, M, Leon, S, Mintun, MA, Schneider, S, Marson, D, Griffith, R, Clark, D, Grossman, H, Mitsis, E, Romirowsky, A, deToledo-Morrell, L, Shah, RC, Duara, R, Varon, D, Roberts, P, Albert, M, Onyike, C, Kielb, S, Rusinek, H, de, Leon, MJ, Glodzik, L, De, Santi, S, Doraiswamy, PM, Petrella, JR, Coleman, RE, Arnold, SE, Karlawish, JH, Wolk, D, Smith, CD, Jicha, G, Hardy, P, Lopez, OL, Oakley, M, Simpson, DM, Porsteinsson, AP, Goldstein, BS, Martin, K, Makino, KM, Ismail, MS, Brand, C, Mulnard, RA, Thai, G, Mc-Adams-Ortiz, C, Womack, K, Mathews, D, Quiceno, M, Diaz-Arrastia, R, King, R, Martin-Cook, K, DeVous, M, Levey, AI, Lah, JJ, Cellar, JS, Burns, JM, Anderson, HS, Swerdlow, RH, Apostolova, L, Lu, PH, Bartzokis, G, Silverman, DH, Graff-Radford, NR, Parfitt, F, Johnson, H, Farlow, MR, Hake, AM, Matthews, BR, Herring, S, van, Dyck, CH, Carson, RE, MacAvoy, MG, Chertkow, H, Bergman, H, Hosein, C, Black, S, Stefanovic, B, Caldwell, C, Ging-Yuek, Hsiung, R, Feldman, H, Mudge, B, Assaly, M, Kertesz, A, Rogers, J, Trost, D, Bernick, C, Munic, D, Kerwin, D, Mesulam, MM, Lipowski, K, Wu, CK, Johnson, N, Sadowsky, C, Martinez, W, Villena, T, Turner, RS, Reynolds, B, Sperling, RA, Johnson, KA, Marshall, G, Frey, M, Yesavage, J, Taylor, JL, Lane, B, Rosen, A, Tinklenberg, J, Sabbagh, M, Belden, C, Jacobson, S, Kowall, N, Killiany, R, Budson, AE, Norbash, A, Johnson, PL, Obisesan, TO, Wolday, S, Bwayo, SK, Lerner, A, Hudson, L, Ogrocki, P, Fletcher, E, Carmichael, O, Olichney, J, Kittur, S, Borrie, M, Lee, TY, Bartha, R, Johnson, S, Asthana, S, Carlsson, CM, Potkin, SG, Preda, A, Nguyen, D, Tariot, P, Fleisher, A, Reeder, S, Bates, V, Capote, H, Rainka, M, Scharre, DW, Kataki, M, Zimmerman, EA, Celmins, D, Brown, AD, Pearlson, GD, Blank, K, Anderson, K, Santulli, RB, Schwartz, ES, Sink, KM, Williamson, JD, Garg, P, Watkins, F, Ott, BR, Querfurth, H, Tremont, G, Salloway, S, Malloy, P, Correia, S, Rosen, HJ, Miller, BL, Mintzer, J, Longmire, CF, Spicer, K, Finger, E, Rachinsky, I, Drost, D, Jernigan, T, McCabe, C, Grant, E, Ernst, T, Kuperman, J, Chung, Y, Murray, S, Bloss, C, Darst, B, Pritchett, L, Saito, A, Amaral, D, DiNino, M, Eyngorina, B, Sowell, E, Houston, S, Soderberg, L, Kaufmann, W, van, Zijl, P, Rizzo-Busack, H, Javid, M, Mehta, N, Ruberry, E, Powers, A, Rosen, B, Gebhard, N, Manigan, H, Frazier, J, Kennedy, D, Yakutis, L, Hill, M, Gruen, J, Bosson-Heenan, J, and Carlson, H

Subjects
anatomy & histology, pathology [Visual Cortex], Adult, Diagnostic Imaging, Male, Linkage disequilibrium, Visual perception, genetic structures, Adolescent, Genotype, Imaging genetics, methods [Diagnostic Imaging], Single-nucleotide polymorphism, Genome-wide association study, Saccharomyces cerevisiae, Biology, Polymorphism, Single Nucleotide, Cohort Studies, methods [Brain Mapping], pathology [Brain], Cortex (anatomy), Genetic variation, Medicine and Health Sciences, medicine, Humans, genetics [Phosphoric Diester Hydrolases], Aged, Visual Cortex, Genetics, Brain Mapping, Multidisciplinary, Models, Genetic, Phosphoric Diester Hydrolases, metabolism [Saccharomyces cerevisiae], Brain, Genetic Variation, Genomics, Middle Aged, Biological Sciences, Visual cortex, medicine.anatomical_structure, Female, Genome-Wide Association Study
Abstract

Visual cortical surface area varies two- to threefold between human individuals, is highly heritable, and has been correlated with visual acuity and visual perception. However, it is still largely unknown what specific genetic and environmental factors contribute to normal variation in the area of visual cortex. To identify SNPs associated with the proportional surface area of visual cortex, we performed a genome-wide association study followed by replication in two independent cohorts. We identified one SNP (rs6116869) that replicated in both cohorts and had genome-wide significant association ( P combined = 3.2 × 10 −8 ). Furthermore, a metaanalysis of imputed SNPs in this genomic region identified a more significantly associated SNP (rs238295; P = 6.5 × 10 −9 ) that was in strong linkage disequilibrium with rs6116869. These SNPs are located within 4 kb of the 5′ UTR of GPCPD1 , glycerophosphocholine phosphodiesterase GDE1 homolog ( Saccharomyces cerevisiae ), which in humans, is more highly expressed in occipital cortex compared with the remainder of cortex than 99.9% of genes genome-wide. Based on these findings, we conclude that this common genetic variation contributes to the proportional area of human visual cortex. We suggest that identifying genes that contribute to normal cortical architecture provides a first step to understanding genetic mechanisms that underlie visual perception.

Published
2012

33. Apolipoprotein E (APOE) genotype has dissociable effects on memory and attentional-executive network function in Alzheimer's disease

Author

Wolk, D. A., Dickerson, B. C., the Alzheimer's Disease Neuroimaging Initiative, Weiner, M., Aiello, M., Aisen, P., Albert, M. S., Alexander, G., Anderson, H. S., Anderson, K., Apostolova, L., Arnold, S., Ashford, W., Assaly, M., Asthana, S., Bandy, D., Bartha, R., Bates, V., Beckett, L., Bell, K. L., Benincasa, A. L., Bergman, H., Bernick, C., Bernstein, M., Black, S., Blank, K., Borrie, M., Brand, C., Brewer, J., Brown, A. D., Burns, J. M., Cairns, N. J., Caldwell, C., Capote, H., Carlsson, C. M., Carmichael, O., Cellar, J. S., Celmins, D., Chen, K., Chertkow, H., Chowdhury, M., Clark, D., Connor, D., Correia, S., Crawford, K., Dale, A., de Leon, M. J., De Santi, S. M., DeCarli, C., deToledo-Morrell, L., DeVous, M., Diaz-Arrastia, R., Dolen, S., Donohue, M., Doody, R. S., Doraiswamy, P. M., Duara, R., Englert, J., Farlow, M., Feldman, H., Felmlee, J., Fleisher, A., Fletcher, E., Foroud, T. M., Foster, N., Fox, N., Frank, R., Gamst, A., Given, C. A., Graff-Radford, N. R., Green, R. C., Griffith, R., Grossman, H., Hake, A. M., Hardy, P., Harvey, D., Heidebrink, J. L., Hendin, B. A., Herring, S., Honig, L. S., Hosein, C., Robin Hsiung, G.-Y., Hudson, L., Ismail, M. S., Jack, C. R., Jacobson, S., Jagust, W., Jayam-Trouth, A., Johnson, K., Johnson, H., Johnson, N., Johnson, K. A., Johnson, S., Kachaturian, Z., Karlawish, J. H., Kataki, M., Kaye, J., Kertesz, A., Killiany, R., Kittur, S., Koeppe, R. A., Korecka, M., Kornak, J., Kozauer, N., Lah, J. J., Laubinger, M. M., Lee, V. M.- Y., Lee, T.- Y., Lerner, A., Levey, A. I., Longmire, C. F., Lopez, O. L., Lord, J. L., Lu, P. H., MacAvoy, M. G., Malloy, P., Marson, D., Martin-Cook, K., Martinez, W., Marzloff, G., Mathis, C., Mc-Adams-Ortiz, C., Mesulam, M., Miller, B. L., Mintun, M. A., Mintzer, J., Molchan, S., Montine, T., Morris, J., Mulnard, R. A., Munic, D., Nair, A., Neu, S., Nguyen, D., Norbash, A., Oakley, M., Obisesan, T. O., Ogrocki, P., Ott, B. R., Parfitt, F., Pawluczyk, S., Pearlson, G., Petersen, R., Petrella, J. R., Potkin, S., Potter, W. Z., Preda, A., Quinn, J., Rainka, M., Reeder, S., Reiman, E. M., Rentz, D. M., Reynolds, B., Richard, J., Roberts, P., Rogers, J., Rosen, A., Rosen, H. J., Rusinek, H., Sabbagh, M., Sadowsky, C., Salloway, S., Santulli, R. B., Saykin, A. J., Scharre, D. W., Schneider, L., Schneider, S., Schuff, N., Shah, R. C., Shaw, L., Shen, L., Silverman, D. H. S., Simpson, D. M., Sink, K. M., Smith, C. D., Snyder, P. J., Spann, B. M., Sperling, R. A., Spicer, K., Stefanovic, B., Stern, Yaakov, Stopa, E., Tang, C., Tariot, P., Taylor-Reinwald, L., Thai, G., Thomas, R. G., Thompson, P., Tinklenberg, J., Toga, A. W., Tremont, G., Trojanowki, J. Q., Trost, D., Turner, R. S., van Dyck, C. H., Vanderswag, H., Varon, D., Villanueva-Meyer, J., Villena, T., Walter, S., Wang, P., Watkins, F., Williamson, J. D., Wolk, D., Wu, C.-K., Zerrate, M., and Zimmerman., E. A.

Published
2010
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34. A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly

Author

Ho, A. J., Stein, J. L., Hua, X., Lee, S., Hibar, D. P., Leow, A. D., Dinov, I. D., Toga, A. W., Saykin, A. J., Shen, L., Foroud, T., Pankratz, N., Huentelman, M. J., Craig, D. W., Gerber, J. D., Allen, A. N., Corneveaux, J. J., Stephan, D. A., DeCarli, C. S., DeChairo, B. M., Potkin, S. G., Jack, C. R., Weiner, M. W., Raji, C. A., Lopez, O. L., Becker, J. T., Carmichael, O. T., Thompson, P. M., the Alzheimer's Disease Neuroimaging Initiative, Weiner, M., Thal, L., Petersen, R., Jagust, W., Trojanowki, J., Beckett, L., Green, R. C., Gamst, A., Potter, W. Z., Montine, T., Anders, D., Bernstein, M., Felmlee, J., Fox, N., Thompson, P., Schuff, N., Alexander, G., Bandy, D., Koeppe, R. A., Foster, N., Reiman, E. M., Chen, K., Shaw, L., Lee, V. M.- Y., Korecka, M., Crawford, K., Neu, S., Harvey, D., Kornak, J., Kachaturian, Z., Frank, R., Snyder, P. J., Molchan, S., Kaye, J., Vorobik, R., Quinn, J., Schneider, L., Pawluczyk, S., Spann, B., Fleisher, A. S., Vanderswag, H., Heidebrink, J. L., Lord, J. L., Johnson, K., Doody, R. S., Villanueva-Meyer, J., Chowdhury, M., Stern, Yaakov, Honig, L. S., Bell, K. L., Morris, J. C., Mintun, M. A., Schneider, S., Marson, D., Griffith, R., Badger, B., Grossman, H., Tang, C., Stern, J., deToledo-Morrell, L., Shah, R. C., Bach, J., Duara, R., Isaacson, R., Strauman, S., Albert, M. S., Pedroso, J., Toroney, J., Rusinek, H., de Leon, M. J., De Santi, S. M., Doraiswamy, P. M., Petrella, J. R., Aiello, M., Clark, C. M., Pham, C., Nunez, J., Smith, C. D., Given II, C. A., Hardy, P., DeKosky, S. T., Oakley, M., Simpson, D. M., Ismail, M. S., Porsteinsson, A., McCallum, C., Cramer, S. C., Mulnard, R. A., McAdams-Ortiz, C., Diaz-Arrastia, R., Martin-Cook, K., DeVous, M., Levey, A. I., Lah, J. J., Cellar, J. S., Burns, J. M., Anderson, H. S., Laubinger, M. M., Bartzokis, G., Silverman, D. H. S., Lu, P. H., Fletcher, R., Parfitt, F., Johnson, H., Farlow, M., Herring, S., Hake, A. M., van Dyck, C. H., MacAvoy, M. G., Bifano, L. A., Chertkow, H., Bergman, H., Hosein, C., Black, S., Graham, S., Caldwell, C., Feldman, H., Assaly, M., Hsiung, G.-Y. R., Kertesz, A., Rogers, J., Trost, D., Bernick, C., Gitelman, D., Johnson, N., Mesulam, M., Sadowsky, C., Villena, T., Mesner, S., Aisen, P. S., Johnson, K. B., Behan, K. E., Sperling, R. A., Rentz, D. M., Johnson, K. A., Rosen, A., Tinklenberg, J., Ashford, W., Sabbagh, M., Connor, D., Obradov, S., Killiany, R., Norbash, A., Obisesan, T. O., Jayam-Trouth, A., Wang, P., Auchus, A. P., Huang, J., Friedland, R. P., DeCarli, C., Fletcher, E., Carmichael, O., Kittur, S., Mirje, S., Johnson, S. C., Borrie, M., Lee, T.-Y., Asthana, S., Carlsson, C. M., Highum, D., Preda, A., Nguyen, D., Tariot, P. N., Hendin, B. A., Scharre, D. W., Kataki, M., Beversdorf, D. Q., Zimmerman, E. A., Celmins, D., Brown, A. D., Gandy, S., Marenberg, M. E., Rovner, B. W., Pearlson, G., Blank, K., Anderson, K., Santulli, R. B., Pare, N., Williamson, J. D., Sink, K. M., Potter, H., Ashok Raj, B., Giordano, A., Ott, B. R., Wu, C.-K., Cohen, R., and Wilks, K. L.

Published
2010
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40. Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease.

Author

Alzheimer's Disease Neuroimaging Initiative, Weiner, M., Aisen, P., Petersen, R., Jack CR.<Suffix>Jr</Suffix>, Jagust, W., Trojanowki, JQ., Toga, AW., Beckett, L., Green, RC., Saykin, AJ., Morris, J., Liu, E., Montine, T., Gamst, A., Thomas, RG., Donohue, M., Walter, S., Gessert, D., Sather, T., Harvey, D., Kornak, J., Dale, A., Bernstein, M., Felmlee, J., Fox, N., Thompson, P., Schuff, N., DeCarli, C., Bandy, D., Koeppe, RA., Foster, N., Reiman, EM., Chen, K., Mathis, C., Cairns, NJ., Taylor-Reinwald, L., Shaw, L., Lee, VM., Korecka, M., Crawford, K., Neu, S., Foroud, TM., Potkin, S., Shen, L., Kachaturian, Z., Frank, R., Snyder, PJ., Molchan, S., Kaye, J., Quinn, J., Lind, B., Dolen, S., Schneider, LS., Pawluczyk, S., Spann, BM., Brewer, J., Vanderswag, H., Heidebrink, JL., Lord, JL., Johnson, K., Doody, RS., Villanueva-Meyer, J., Chowdhury, M., Stern, Y., Honig, LS., Bell, KL., Morris, JC., Ances, B., Carroll, M., Leon, S., Mintun, MA., Schneider, S., Marson, D., Griffith, R., Clark, D., Grossman, H., Mitsis, E., Romirowsky, A., deToledo-Morrell, L., Shah, RC., Duara, R., Varon, D., Roberts, P., Albert, M., Onyike, C., Kielb, S., Rusinek, H., de Leon MJ., Glodzik, L., De Santi, S., Doraiswamy, P., Petrella, JR., Coleman, R., Arnold, SE., Karlawish, JH., Wolk, D., Smith, CD., Jicha, G., Hardy, P., Lopez, OL., Oakley, M., Simpson, DM., Porsteinsson, AP., Goldstein, BS., Martin, K., Makino, KM., Ismail, M., Brand, C., Mulnard, RA., Thai, G., Mc-Adams-Ortiz, C., Womack, K., Mathews, D., Quiceno, M., Diaz-Arrastia, R., King, R., Martin-Cook, K., DeVous, M., Levey, AI., Lah, JJ., Cellar, JS., Burns, JM., Anderson, HS., Swerdlow, RH., Apostolova, L., Lu, PH., Bartzokis, G., Silverman, DH., Graff-Radford, NR., Parfitt, F., Johnson, H., Farlow, MR., Hake, AM., Matthews, BR., Herring, S., van Dyck CH., Carson, RE., MacAvoy, MG., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Hsiung, GY., Feldman, H., Mudge, B., Assaly, M., Kertesz, A., Rogers, J., Trost, D., Bernick, C., Munic, D., Kerwin, D., Mesulam, MM., Lipowski, K., Wu, CK., Johnson, N., Sadowsky, C., Martinez, W., Villena, T., Turner, RS., Reynolds, B., Sperling, RA., Johnson, KA., Marshall, G., Frey, M., Yesavage, J., Taylor, JL., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M., Belden, C., Jacobson, S., Kowall, N., Killiany, R., Budson, AE., Norbash, A., Johnson, PL., Obisesan, TO., Wolday, S., Bwayo, SK., Lerner, A., Hudson, L., Ogrocki, P., Fletcher, E., Carmichael, O., Olichney, J., Kittur, S., Borrie, M., Lee, TY., Bartha, R., Johnson, S., Asthana, S., Carlsson, CM., Potkin, SG., Preda, A., Nguyen, D., Tariot, P., Fleisher, A., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, DW., Kataki, M., Zimmerman, EA., Celmins, D., Brown, AD., Pearlson, GD., Blank, K., Anderson, K., Santulli, RB., Schwartz, ES., Sink, KM., Williamson, JD., Garg, P., Watkins, F., Ott, BR., Querfurth, H., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, HJ., Miller, 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Abstract

The failure of current strategies to provide an explanation for controversial findings on the pattern of pathophysiological changes in Alzheimer's Disease (AD) motivates the necessity to develop new integrative approaches based on multi-modal neuroimaging data that captures various aspects of disease pathology. Previous studies using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (sMRI) report controversial results about time-line, spatial extent and magnitude of glucose hypometabolism and atrophy in AD that depend on clinical and demographic characteristics of the studied populations. Here, we provide and validate at a group level a generative anatomical model of glucose hypo-metabolism and atrophy progression in AD based on FDG-PET and sMRI data of 80 patients and 79 healthy controls to describe expected age and symptom severity related changes in AD relative to a baseline provided by healthy aging. We demonstrate a high level of anatomical accuracy for both modalities yielding strongly age- and symptom-severity- dependant glucose hypometabolism in temporal, parietal and precuneal regions and a more extensive network of atrophy in hippocampal, temporal, parietal, occipital and posterior caudate regions. The model suggests greater and more consistent changes in FDG-PET compared to sMRI at earlier and the inversion of this pattern at more advanced AD stages. Our model describes, integrates and predicts characteristic patterns of AD related pathology, uncontaminated by normal age effects, derived from multi-modal data. It further provides an integrative explanation for findings suggesting a dissociation between early- and late-onset AD. The generative model offers a basis for further development of individualized biomarkers allowing accurate early diagnosis and treatment evaluation.

Published
2013

41. Practical utility of amyloid and FDG-PET in an academic dementia center

Author

Sanchez-Juan, P., primary, Ghosh, P. M., additional, Hagen, J., additional, Gesierich, B., additional, Henry, M., additional, Grinberg, L. T., additional, O'Neil, J. P., additional, Janabi, M., additional, Huang, E. J., additional, Trojanowski, J. Q., additional, Vinters, H. V., additional, Gorno-Tempini, M., additional, Seeley, W. W., additional, Boxer, A. L., additional, Rosen, H. J., additional, Kramer, J. H., additional, Miller, B. L., additional, Jagust, W. J., additional, and Rabinovici, G. D., additional

Published
2013
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43. Memory Failure Has Different Mechanisms in Subcortical Stroke and Alzheimer’s Disease

Author

Reed, B. R., Eberling, J. L., Mungas, D., Weiner, M. W., and Jagust, W. J.

Subjects
Aged, 80 and over, Male, Stroke, Memory Disorders, Alzheimer Disease, Memory, Task Performance and Analysis, Brain, Humans, Female, Radionuclide Imaging, Article, Aged
Abstract

Patients with extensive subcortical cerebrovascular disease may have impaired memory, often despite the absence of medial temporal or diencephalic strokes. In this group, episodic memory failure may arise from frontal lobe dysfunction based on disruption of frontosubcortical loops caused by lacunae. We tested this idea by studying cognitively impaired subcortical stroke (CIS) patients and Alzheimer's disease (AD) patients with [18F]-fluorodeoxyglucose positron emission tomography using a continuous verbal memory task during the period of tracer uptake. Patients were matched on severity of cognitive impairment and overall memory task performance. As hypothesized, we found a double dissociation in the relations between metabolism and memory in these groups, such that memory in CIS (but not in AD) correlates with prefrontal lobe metabolism, whereas in AD (but not in CIS), memory correlates with left hippocampal and temporal lobe metabolism. Analysis of memory subscores showed that CIS patients made more errors on short-delay trials, which is consistent with working memory failure. It seems that different pathogenic mechanisms underlie episodic memory failure in subcortical cerebrovascular disease and AD.

Published
2000

44. The 1998 Workshop on Neuroimaging Research in Alzheimer's Disease:Observation and issues

Author

De Leon, M. J., Scheltens, P., Jagust, W., Small, G., Decarli, C., and Wahlund, L. O.

Abstract

In July of 1998, at the Amsterdam meeting of the International Alzheimer's Disease Congress, the first workshop was convened on the Neuroimaging of Alzheimer's Disease. Twenty-two of 24 presenters contributed to this document. Each contributor was asked to summarize a single salient observation on one of four topics: 1) Structural and functional brain imaging and dementia diagnosis; 2) assessment of Alzheimer's disease progression; 3) clinical and post-mortem validation studies; and 4) new and innovative imaging techniques. The summaries show that structural hippocampal formation (hippocampus and entorhinal cortex) changes are the most consistently observed early features of AD. SPECT perfusion studies and PET glucose metabolism studies, with arguably greater disease sensitivity, show the additional involvement of the temporal neocortical metabolism in the early stages of AD. It is offered that imaged changes could serve as biological indicators of disease progression. Progress continues to be made with the differential diagnosis of AD. Further, post mortem studies have been used increasingly to confirm diagnoses and provide anatomical validation for in vivo imaging of the hippocampus and entorhinal cortex. MRI spectroscopy, SPECT and PET studies promise the non-invasive longitudinal examination of brain chemistry and an expansion in the exploration for mechanisms of disease. We anticipate that the next few years will see the standardization of imaging protocols with the adoption of diagnostic imaging criteria for AD and with intervention studies using image derived outcome measures.

Published
2000

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