Announcements


GAAIN at AD/PD 2025 in Vienna, Austria


Meet GAAIN representatives and learn more about our data sharing efforts in the exhibit hall at AD/PD 2025 from April 1-5, 2025.

Register for the conference here.

 

GAAIN Article in Keck School News


Learn more about how GAAIN is changing the way researchers approach Alzheimer's disease research, featured by the Keck School of Medicine of USC.

Read more here.

 

New GAAIN Secondary Analysis Manuscript


GAAIN allows for discovery of existing data sets to use in secondary analyses, which resulted in the manuscript "Comparison of genetic and health risk factors for mild cognitive impairment and Alzheimer's disease between Hispanic and non-Hispanic white participants" published in Alzheimer's & Dementia.

Read more here.

 

World Dementia Council (WDC) Essay Collection


Read about GAAIN in WDC's essay collection, "Global dialogue on data sharing for dementia research: Reflections" and how we are contributing to the worldwide effort of data sharing and dissemination.

 

Interrogator Update Released


We are pleased to announce the latest release of the Interrogator with several exciting new features! Users can save and reload their work. We’ve used this new functionality to construct a set of highlighted analyses visible to all users. Each of these is linked to a Data Partner publication and reproduces part of the analysis reported in the paper, allowing users to explore these results in the GAAIN environment. These analyses highlight our Data Partner research, and give users several examples of how to use the Interrogator to work with variables, create cohorts, and run preliminary analyses.

Visit the new improved Interrogator at www.gaaindata.org

 

GAAIN System Tools Tutorial Series and Training


Need assistance with our tools?

Tutorials are available for the GAAIN system tools on the GAAIN YouTube channel to help users navigate the Data Landing Page, Scoreboard, Cohort Scout, and New Interrogator.

Request a training session by emailing info@gaain.org with a few dates and times (note, we are in the Pacific time zone) and we will arrange a web-ex training session.

 

Media Coverage of New GAAIN Study


A study published in JAMA Neurology used GAAIN data to reexamine the link between age, sex, and Alzheimer's disease risk. Click here to see the buzz this paper is generating and read more in the following publications:

 


“We can use GAAIN to understand the entire landscape of Alzheimer’s disease research and identify places where additional investigation needs to be undertaken. That will be instrumental in advancing our knowledge faster. This is the wave of the future,” Dr. Arthur Toga (GAAIN’s Principal Investigator) said. Read the article here.

 

PAST EVENTS

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NEWSLETTER

Click here to view Jan 2022 newsletter

GAAIN Brochure


GAAIN Publications


Toga, A.W., Phatak, M., Pappas, I., Thompson, S., McHugh, C.P., Clement, M.H.S., Bauermeister, S., Maruyama T., Gallacher, J. The pursuit of approaches to federate data to accelerate Alzheimer's disease and related dementia research: GAAIN, DPUK, and ADDI. Front Neuroinform. 2023; 17:1175689.
https://doi.org/10.3389/fninf.2023.1175689


Xiao, C., Pappas, I., Aksman, L.M., O'Bryant, S.E., Toga, A.W., Health and Aging Brain Study (HABS-HD) Study Team, Alzheimer's Disease Neuroimaging Initiative. Comparison of genetic and health risk factors for mild cognitive impairment and Alzheimer's disease between Hispanic and non-Hispanic white participants. Alzheimers Dement. 2023; 19:5086-5094.
https://doi.org/10.1002/alz.13110


Xiao, C., Neu, S.C., Toga, A.W. Sharing of Alzheimer’s Disease Research Data in the Global Alzheimer’s Association Interactive Network. In J. Cummings, J. Kinney, H. Fillit (Eds.), Alzheimer's Disease Drug Development: Research and Development Ecosystem. Cambridge: Cambridge University Press; 2022, p. 395-403.
http://doi.org/10.1017/9781108975759.035


Neu, S.C., Pa, J., Kukull, W., Beekly, D., Kuzma, A., Gangadharan, P., Wang, L., Romero, K., Arneric, S.P., Redolfi, A., Orlandi, D., Frisoni, G.B., Au, R., Devine, S., Auerbach, S., Espinosa, A., Boada, M., Ruiz, A., Johnson, S.C., Koscik, R., Wang, J., Hsu, W., Chen, Y., Toga, A.W. Apolipoprotein E Genotype and Sex Risk Factors for Alzheimer Disease. JAMA Neurol. 2017; 74:1178-1189.
http://doi.org/10.1001/jamaneurol.2017.2188


Neu S.C., Crawford, K.L., Toga, A.W. Sharing data in the Global Alzheimer’s Association Interactive Network. NeuroImage. 2016; 124:1168-1174.
http://doi.org/10.1016/j.neuroimage.2015.05.082


Toga, A.W., Neu, S.C., Bhatt, P., Crawford, K.L., Ashish, N. The Global Alzheimer’s Association Interactive Network. Alzheimers Dement. 2016; 12:49-54.
http://doi.org/10.1016/j.jalz.2015.06.1896


Ashish, N., Bhatt, P., Toga, A.W. Global data sharing in Alzheimer’s disease research. Alzheimer Dis Assoc Disord. 2016; 30:160-168.
http://doi.org/10.1097/WAD.0000000000000121


Ashish, N., Dewan, P., Toga, A.W. The GAAIN Entity Mapper: An Active-Learning System for Medical Data Mapping. Front Neuroinform. 2016; 9:30.
http://doi.org/10.3389/fninf.2015.00030


Ashish, N., Dewan, P., Ambite, J.L., Toga, A.W. GEM: The GAAIN Entity Mapper. In: Ashish, N., Ambite, J.L. (eds) Data Integration in the Life Sciences. DILS 2015. Lecture Notes in Computer Science, vol 9162. Springer, Cham; 2015, p. 13-27.
http://doi.org/10.1007/978-3-319-21843-4_2


Ashish, N., Toga, A.W. Medical data transformation using rewriting. Front Neuroinform. 2015; 9:1.
http://doi.org/10.3389/fninf.2015.00001

GAAIN COLLABORATIONS


Leuzy, A., Raket, L.L., Villemagne, V.L., Klein, G., Tonietto, M., Olafson, E., Baker, S., Saad, Z.S., Bullich, S., Lopresti, B., Bohorquez, S.S., Boada, M., Betthauser, T.J., Charil, A., Collins, E.C., Collins, J.A., Cullen, N., Gunn, R.N., Higuchi, M., Hostetler, E., Hutchison, R.M., Iaccarino, L., Insel, P.S., Irizarry, M.C., Jack Jr., C.R., Jagust, W.J., Johnson, K.A., Johnson, S.C., Karten, Y., Marquié, M., Mathotaarachchi, S., Mintun, M.A., Ossenkoppele, R., Pappas, I., Petersen, R.C., Rabinovici, G.D., Rosa-Neto, P., Schwarz, C.G., Smith, R., Stephens, A.W., Whittington, A., Carrillo, M.C., Pontecorvo, M.J., Haeberlein, S.B., Dunn, B., Kolb, H.C., Sivakumaran, S., Rowe, C.C., Hansson, O., Doré, V. Harmonizing tau positron emission tomography in Alzheimer's disease: The CenTauR scale and the joint propagation model. Alzheimers Dement. 2024; 20:5833-5848.
https://doi.org/10.1002/alz.13908


Chen, K., Ghisays, V., Luo, J., Chen, Y., Lee, W., Wu, T., Reiman, E.M., Su, Y. Harmonizing florbetapir and PiB PET measurements of cortical Aβ plaque burden using multiple regions-of-interest and machine learning techniques: An alternative to the Centiloid approach. Alzheimers Dement. 2024; 20:2165-2172.
https://doi.org/10.1002/alz.13677


Bourgeat, P., Doré, V., Rowe, C.C., Benzinger, T., Tosun, D., Goyal, M.S., LaMontagne, P., Jin, L., Weiner, M.W., Masters, C.L., Fripp, J., Villemagne, V.L., Alzheimer's Disease Neuroimaging Initiative, OASIS3, the AIBL research group. A universal neocortical mask for Centiloid quantification. Alzheimers Dement. 2023; 15:e12457.
https://doi.org/10.1002/dad2.12457


Villemagne, V.L., Leuzy, A., Bohorquez, S.S., Bullich, S., Shimada, H., Rowe, C.C., Bourgeat, P., Lopresti, B., Huang, K., Krishnadas, N., Fripp, J., Takado, Y., Gogola, A., Minhas, D., Weimer, R., Higuchi, M., Stephens, A., Hansson, O., Doré, V., Alzheimer's Disease Neuroimaging Initiative, the AIBL research group. CenTauR: Toward a universal scale and masks for standardizing tau imaging studies. Alzheimers Dement. 2023; 15:e12454.
https://doi.org/10.1002/dad2.12454


Matsuda, H., Soma, T., Okita, K., Shigemoto, Y., Sato, N. Development of software for measuring brain amyloid accumulation using 18F-florbetapir PET and calculating global Centiloid scale and regional Z-score values. Brain Behav. 2023; 13:e3092.
https://doi.org/10.1002/brb3.3092


Redolfi, A., Archetti, D., De Francesco, S., Crema, C., Tagliavini, F., Lodi, R., Ghidoni, R., Gandini Wheeler-Kingshott, C.A.M., Alexander, D.C., D'Angelo, E. Italian, European, and international neuroinformatics efforts: An overview. Eur J Neurosci. 2023; 57:2017-2039.
https://doi.org/10.1111/ejn.15854


Imabayashi, E., Tamamura, N., Yamaguchi, Y., Kamitaka, Y., Sakata, M., Ishii, K. Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer's disease. Ann Nucl Med. 2022; 36:865-875.
https://doi.org/10.1007/s12149-022-01769-x


Rane Levendovszky, S. Cross-Sectional and Longitudinal Hippocampal Atrophy, Not Cortical Thinning, Occurs in Amyloid-Negative, p-Tau-Positive, Older Adults with Non-Amyloid Pathology and Mild Cognitive Impairment. Front Neuroimaging. 2022; 1:828767.
https://doi.org/10.3389/fnimg.2022.828767


Matsuda, H., Yamao, T. Software development for quantitative analysis of brain amyloid PET. Brain Behav. 2022; 12:e2499.
https://doi.org/10.1002/brb3.2499


Royse, S.K., Minhas, D.S., Lopresti, B.J., Murphy, A., Ward, T., Koeppe, R.A., Bullich, S., DeSanti, S., Jagust, W.J., Landau, S.M., Alzheimer’s Disease Neuroimaging Initiative. Validation of amyloid PET positivity thresholds in Centiloids: A multisite PET study approach. Alzheimers Res Ther. 2021; 13:99.
https://doi.org/10.1186/s13195-021-00836-1


Hanseeuw, B.J., Malotaux, V., Dricot, L., Quenon, L., Sznajer, Y., Cerman, J., Woodard, J.L., Buckley, C., Farrar, G., Ivanoiu, A., Lhommel, R. Defining a Centiloid scale threshold predicting long-term progression to dementia in patients attending the memory clinic: An [18F] flutemetamol amyloid PET study. Eur J Nucl Med Mol Imaging. 2021; 48:302-310.
https://doi.org/10.1007/s00259-020-04942-4


Rowe, C.C., Doré, V., Jones, G., Baxendale, D., Mulligan, R.S., Bullich, S., Stephens, A.W., De Santi, S., Masters, C.L., Dinkelborg, L., Villemagne, V.L. 18F-Florbetaben PET beta-amyloid binding expressed in Centiloids. Eur J Nucl Med Mol Imaging. 2017; 44:2053-2059.
https://doi.org/10.1007/s00259-017-3749-6