Abstract
Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-The-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
Original language | English |
---|---|
Pages (from-to) | 645-653 |
Number of pages | 9 |
Journal | Alzheimer's and Dementia |
Volume | 12 |
Issue number | 6 |
DOIs | |
State | Published - Jun 1 2016 |
Keywords
- Azheimer's disease
- Big data
- Bioinformatics
- Biomarkers
- Cognitive decline
- Crowdsource
- Genetics
- Imaging
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Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease. / Allen, Genevera I.; Amoroso, Nicola; Anghel, Catalina; Balagurusamy, Venkat; Bare, Christopher J.; Beaton, Derek; Bellotti, Roberto; Bennett, David A.; Boehme, Kevin L.; Boutros, Paul C.; Caberlotto, Laura; Caloian, Cristian; Campbell, Frederick; Chaibub Neto, Elias; Chang, Yu Chuan; Chen, Beibei; Chen, Chien Yu; Chien, Ting Ying; Clark, Tim; Das, Sudeshna; Davatzikos, Christos; Deng, Jieyao; Dillenberger, Donna; Dobson, Richard J.B.; Dong, Qilin; Doshi, Jimit; Duma, Denise; Errico, Rosangela; Erus, Guray; Everett, Evan; Fardo, David W.; Friend, Stephen H.; Fröhlich, Holger; Gan, Jessica; St George-Hyslop, Peter; Ghosh, Satrajit S.; Glaab, Enrico; Green, Robert C.; Guan, Yuanfang; Hong, Ming Yi; Huang, Chao; Hwang, Jinseub; Ibrahim, Joseph; Inglese, Paolo; Iyappan, Anandhi; Jiang, Qijia; Katsumata, Yuriko; Kauwe, John S.K.; Klein, Arno; Kong, Dehan; Krause, Roland; Lalonde, Emilie; Lauria, Mario; Lee, Eunjee; Lin, Xihui; Liu, Zhandong; Livingstone, Julie; Logsdon, Benjamin A.; Lovestone, Simon; Ma, Tsung Wei; Malhotra, Ashutosh; Mangravite, Lara M.; Maxwell, Taylor J.; Merrill, Emily; Nagorski, John; Namasivayam, Aishwarya; Narayan, Manjari; Naz, Mufassra; Newhouse, Stephen J.; Norman, Thea C.; Nurtdinov, Ramil N.; Oyang, Yen Jen; Pawitan, Yudi; Peng, Shengwen; Peters, Mette A.; Piccolo, Stephen R.; Praveen, Paurush; Priami, Corrado; Sabelnykova, Veronica Y.; Senger, Philipp; Shen, Xia; Simmons, Andrew; Sotiras, Aristeidis; Stolovitzky, Gustavo; Tangaro, Sabina; Tateo, Andrea; Tung, Yi An; Tustison, Nicholas J.; Varol, Erdem; Vradenburg, George; Weiner, Michael W.; Xiao, Guanghua; Xie, Lei; Xie, Yang; Xu, Jia; Yang, Hojin; Zhan, Xiaowei; Zhou, Yunyun; Zhu, Fan; Zhu, Hongtu; Zhu, Shanfeng.
In: Alzheimer's and Dementia, Vol. 12, No. 6, 01.06.2016, p. 645-653.Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease
AU - Allen, Genevera I.
AU - Amoroso, Nicola
AU - Anghel, Catalina
AU - Balagurusamy, Venkat
AU - Bare, Christopher J.
AU - Beaton, Derek
AU - Bellotti, Roberto
AU - Bennett, David A.
AU - Boehme, Kevin L.
AU - Boutros, Paul C.
AU - Caberlotto, Laura
AU - Caloian, Cristian
AU - Campbell, Frederick
AU - Chaibub Neto, Elias
AU - Chang, Yu Chuan
AU - Chen, Beibei
AU - Chen, Chien Yu
AU - Chien, Ting Ying
AU - Clark, Tim
AU - Das, Sudeshna
AU - Davatzikos, Christos
AU - Deng, Jieyao
AU - Dillenberger, Donna
AU - Dobson, Richard J.B.
AU - Dong, Qilin
AU - Doshi, Jimit
AU - Duma, Denise
AU - Errico, Rosangela
AU - Erus, Guray
AU - Everett, Evan
AU - Fardo, David W.
AU - Friend, Stephen H.
AU - Fröhlich, Holger
AU - Gan, Jessica
AU - St George-Hyslop, Peter
AU - Ghosh, Satrajit S.
AU - Glaab, Enrico
AU - Green, Robert C.
AU - Guan, Yuanfang
AU - Hong, Ming Yi
AU - Huang, Chao
AU - Hwang, Jinseub
AU - Ibrahim, Joseph
AU - Inglese, Paolo
AU - Iyappan, Anandhi
AU - Jiang, Qijia
AU - Katsumata, Yuriko
AU - Kauwe, John S.K.
AU - Klein, Arno
AU - Kong, Dehan
AU - Krause, Roland
AU - Lalonde, Emilie
AU - Lauria, Mario
AU - Lee, Eunjee
AU - Lin, Xihui
AU - Liu, Zhandong
AU - Livingstone, Julie
AU - Logsdon, Benjamin A.
AU - Lovestone, Simon
AU - Ma, Tsung Wei
AU - Malhotra, Ashutosh
AU - Mangravite, Lara M.
AU - Maxwell, Taylor J.
AU - Merrill, Emily
AU - Nagorski, John
AU - Namasivayam, Aishwarya
AU - Narayan, Manjari
AU - Naz, Mufassra
AU - Newhouse, Stephen J.
AU - Norman, Thea C.
AU - Nurtdinov, Ramil N.
AU - Oyang, Yen Jen
AU - Pawitan, Yudi
AU - Peng, Shengwen
AU - Peters, Mette A.
AU - Piccolo, Stephen R.
AU - Praveen, Paurush
AU - Priami, Corrado
AU - Sabelnykova, Veronica Y.
AU - Senger, Philipp
AU - Shen, Xia
AU - Simmons, Andrew
AU - Sotiras, Aristeidis
AU - Stolovitzky, Gustavo
AU - Tangaro, Sabina
AU - Tateo, Andrea
AU - Tung, Yi An
AU - Tustison, Nicholas J.
AU - Varol, Erdem
AU - Vradenburg, George
AU - Weiner, Michael W.
AU - Xiao, Guanghua
AU - Xie, Lei
AU - Xie, Yang
AU - Xu, Jia
AU - Yang, Hojin
AU - Zhan, Xiaowei
AU - Zhou, Yunyun
AU - Zhu, Fan
AU - Zhu, Hongtu
AU - Zhu, Shanfeng
N1 - Funding Information: Study data were provided by the following groups: (1) The Alzheimer's Disease Neuroimaging Initiative (ADNI)—ADNI is funded by the National Institutes of Health (U01 AG024904), the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering and through generous contributions from the following: Alzheimer's Association; Alzheimer's Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This research was also supported by NIH grants P30 AG010129 and K01 AG030514 . (2) The Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago—Data collection was supported through funding by NIA grants P30AG10161 , R01AG15819 , R01AG17917 , R01AG30146 , R01AG36836 , U01AG32984 , and U01AG46152 , the Illinois Department of Public Health, and the Translational Genomics Research Institute. (3) European AddNeuroMed study—The AddNeuroMed data are from a public-private partnership supported by EFPIA companies, SMEs and the EU under the FP6 programme. Clinical leads responsible for data collection are Iwona Kłoszewska (Lodz), Simon Lovestone (London), Patrizia Mecocci (Perugia), Hilkka Soininen (Kuopio), Magda Tsolaki (Thessaloniki), and Bruno Vellas (Toulouse). Funding Information: This study was supported by the following individuals and organizations: Alan Evans (McGill University), Gaurav Pandey (MSSM), Gil Rabinovici (UCSF), Kaj Blennow (Göteborg University), Kristine Yaffe (UCSF), Maria Isaac (EMA), Nolan Nichols (University of Washington), Paul Thompson (UCLA), Reisa Sperling (Harvard), Scott Small (Columbia), Guy Eakin (BrightFocus Foundation), Maria Carillo (Alzheimer's Association), Neil Buckholz (NIA), Alzheimer's Research UK, European Medicines Agency, Global CEO Initiative on Alzheimer's Disease, Pfizer, Inc, Ray and Dagmar Dolby Family Fund, Rosenberg Alzheimer's Project, Sanofi S.A, and Takeda Pharmaceutical Company Ltd, USAgainstAlzheimer's. Publisher Copyright: © 2016 The Authors.
PY - 2016/6/1
Y1 - 2016/6/1
N2 - Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-The-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
AB - Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-The-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
KW - Azheimer's disease
KW - Big data
KW - Bioinformatics
KW - Biomarkers
KW - Cognitive decline
KW - Crowdsource
KW - Genetics
KW - Imaging
UR - http://www.scopus.com/inward/record.url?scp=84966539175&partnerID=8YFLogxK
U2 - 10.1016/j.jalz.2016.02.006
DO - 10.1016/j.jalz.2016.02.006
M3 - Article
C2 - 27079753
AN - SCOPUS:84966539175
VL - 12
SP - 645
EP - 653
JO - Alzheimer's and Dementia
JF - Alzheimer's and Dementia
SN - 1552-5260
IS - 6
ER -