A semi-mechanism approach based on MRI and proteomics for prediction of conversion from mild cognitive impairment to Alzheimer’s disease

DSpace/Manakin Repository

A semi-mechanism approach based on MRI and proteomics for prediction of conversion from mild cognitive impairment to Alzheimer’s disease

Citable link to this page

 

 
Title: A semi-mechanism approach based on MRI and proteomics for prediction of conversion from mild cognitive impairment to Alzheimer’s disease
Author: Liu, Haochen; Zhou, Xiaoting; Jiang, Hao; He, Hua; Liu, Xiaoquan; Weiner, Michael W.; Aisen, Paul; Petersen, Ronald; Jack, Clifford R.; Jagust, William; Trojanowki, John Q.; Toga, Arthur W.; Beckett, Laurel; Green, Robert C.; Saykin, Andrew J.; Morris, John; Shaw, Leslie M.; Khachaturian, Zaven; Sorensen, Greg; Carrillo, Maria; Kuller, Lew; Raichle, Marc; Paul, Steven; Davies, Peter; Fillit, Howard; Hefti, Franz; Holtzman, Davie; Mesulam, M. Marcel; Potter, William; Snyder, Peter; Montine, Tom; Thomas, Ronald G.; Donohue, Michael; Walter, Sarah; Sather, Tamie; Jiminez, Gus; Balasubramanian, Archana B.; Mason, Jennifer; Sim, Iris; Harvey, Danielle; Bernstein, Matthew; Fox, Nick; Thompson, Paul; Schuff, Norbert; DeCArli, Charles; Borowski, Bret; Gunter, Jeff; Senjem, Matt; Vemuri, Prashanthi; Jones, David; Kantarci, Kejal; Ward, Chad; Koeppe, Robert A.; Foster, Norm; Reiman, Eric M.; Chen, Kewei; Mathis, Chet; Landau, Susan; Cairns, Nigel J.; Householder, Erin; Taylor-Reinwald, Lisa; Lee, Virginia; Korecka, Magdalena; Figurski, Michal; Crawford, Karen; Neu, Scott; Foroud, Tatiana M.; Potkin, Steven; Shen, Li; Faber, Kelley; Kim, Sungeun; Nho, Kwangsik; Thal, Lean; Frank, Richard; Hsiao, John; Kaye, Jeffrey; Quinn, Joseph; Silbert, Lisa; Lind, Betty; Carter, Raina; Dolen, Sara; Ances, Beau; Carroll, Maria; Creech, Mary L.; Franklin, Erin; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Brewer, James; Vanderswag, Helen; Fleisher, Adam; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Love, Marissa Natelson; Heidebrink, Judith L.; Lord, Joanne L.; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Grossman, Hillel; Mitsis, Effie; Shah, Raj C.; deToledo-Morrell, Leyla; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Albert, Marilyn; Onyike, Chiadi; D’Agostino II, Daniel; Kielb, Stephanie; Galvin, James E.; Cerbone, Brittany; Michel, Christina A.; Pogorelec, Dana M.; Rusinek, Henry; de Leon, Mony J.; Glodzik, Lidia; De Santi, Susan; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Borges-Neto, Salvador; Wong, Terence Z.; Coleman, Edward; Levey, Allan I.; Lah, James J.; Cella, Janet S.; Burns, Jeffrey M.; Swerdlow, Russell H.; Brooks, William M.; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Clark, Christopher M.; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H.S.; Lu, Po H.; Bartzokis, George; Smith, Charles D.; Jicha, Greg; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Graff-Radford, Neill R; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Lopez, Oscar L.; Oakley, MaryAnn; Simpson, Donna M.; Farlow, Martin R.; Hake, Ann Marie; Matthews, Brandy R.; Brosch, Jared R.; Herring, Scott; Hunt, Cynthia; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Mulnard, Ruth A.; Thai, Gaby; Mc-Adams-Ortiz, Catherine; van Dyck, Christopher H.; Carson, Richard E.; MacAvoy, Martha G.; Varma, Pradeep; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Robin Hsiung, Ging-Yuek; Feldman, Howard; Mudge, Benita; Assaly, Michele; Finger, Elizabeth; Pasternack, Stephen; Rachisky, Irina; Trost, Dick; Kertesz, Andrew; Bernick, Charles; Munic, Donna; Lipowski, Kristine; Weintraub, MASandra; Bonakdarpour, Borna; Kerwin, Diana; Wu, Chuang-Kuo; Johnson, Nancy; Sadowsky, Carl; Villena, Teresa; Turner, Raymond Scott; Johnson, Kathleen; Reynolds, Brigid; Sperling, Reisa A.; Johnson, Keith A.; Marshall, Gad; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Sabbagh, Marwan N.; Belden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Johnson, Patricia Lynn; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Tatsuoka, Curtis; Fatica, Parianne; Fletcher, Evan; Maillard, Pauline; Olichney, John; Carmichael, Owen; Kittur, Smita; Borrie, Michael; Lee, T-Y; Bartha, Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Burke, Anna; Trncic, Nadira; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Scharre, Douglas W.; Kataki, Maria; Adeli, Anahita; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Flashman, Laura A.; Seltzer, Marc; Hynes, Mary L.; Santulli, Robert B.; Sink, Kaycee M.; Gordineer, Leslie; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J.; Miller, Bruce L.; Perry, David; Mintzer, Jacobo; Spicer, Kenneth; Bachman, David; Finger, Elizabether; Pasternak, Stephen; Rachinsky, Irina; Rogers, John; Drost, Dick; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Schultz, Susan K.; Boles Ponto, Laura L.; Shim, Hyungsub; Smith, Karen Ekstam; Relkin, Norman; Chaing, Gloria; Lin, Michael; Ravdin, Lisa; Smith, Amanda; Raj, Balebail Ashok; Fargher, Kristin

Note: Order does not necessarily reflect citation order of authors.

Citation: Liu, H., X. Zhou, H. Jiang, H. He, X. Liu, M. W. Weiner, P. Aisen, et al. 2016. “A semi-mechanism approach based on MRI and proteomics for prediction of conversion from mild cognitive impairment to Alzheimer’s disease.” Scientific Reports 6 (1): 26712. doi:10.1038/srep26712. http://dx.doi.org/10.1038/srep26712.
Full Text & Related Files:
Abstract: Mild cognitive impairment (MCI) is a precursor phase of Alzheimer’s disease (AD). As current treatments may be effective only at the early stages of AD, it is important to track MCI patients who will convert to AD. The aim of this study is to develop a high performance semi-mechanism based approach to predict the conversion from MCI to AD and improve our understanding of MCI-to-AD conversion mechanism. First, analysis of variance (ANOVA) test and lasso regression are employed to identify the markers related to the conversion. Then the Bayesian network based on selected markers is established to predict MCI-to-AD conversion. The structure of Bayesian network suggests that the conversion may start with fibrin clot formation, verbal memory impairment, eating pattern changing and hyperinsulinemia. The Bayesian network achieves a high 10-fold cross-validated prediction performance with 96% accuracy, 95% sensitivity, 65% specificity, area under the receiver operating characteristic curve of 0.82 on data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The semi-mechanism based approach provides not only high prediction performance but also clues of mechanism for MCI-to-AD conversion.
Published Version: doi:10.1038/srep26712
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896009/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:27662150
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters