Predicting Short-term MCI-to-AD Progression Using Imaging, CSF, Genetic Factors, Cognitive Resilience, and Demographics

著者: Yogatheesan Varatharajah, Vijay K. Ramanan, Ravishankar K. Iyer, Prashanthi Vemuri, For the Alzheimer’s Disease Neuroimaging Initiative, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, Andrew J. Saykin, William J. Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, John C. Morris, Leslie M. Shaw, Zaven S. Khachaturian, Greg Sorensen, Marı́a C. Carrillo, Lew Kuller, Marc Raichle, Steven M. Paul, Peter J. Davies, Howard Fillit, Franz Hefti, David M. Holtzman, M. Marcel Mesulam, William C. Potter, Peter J. Snyder, Adam J. Schwartz, Tom Montine, Ronald G. Thomas, Michael Donohue, Sarah Walter, Devon Gessert, Tamie Sather, Gus Jiminez, Archana B. Balasubramanian, Jennifer Mason, Iris Sim, Danielle Harvey, Matt A. Bernstein, Nick C. Fox, Paul M. Thompson, Norbert Schuff, Charles DeCArli, Bret Borowski, Jeff Gunter, Matthew L. Senjem, David Jones, Kejal Kantarci, Chad Ward, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, Susan Landau, Nigel J. Cairns, Erin Franklin, Lisa Taylor‐Reinwald, Virginia Lee, Magdalena Korecka, Michal Figurski, Karen Crawford, Scott Neu, Tatiana Foroud, Steven Potkin, Kelley Faber, Sungeun Kim, Kwangsik Nho, Leon J. Thal, Neil Buckholtz, Marilyn Albert, Richard Frank, John Hsiao, Jeffrey Kaye, Joseph F. Quinn, Lisa C. Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Beccera, Liberty Teodoro, Bryan M. Spann, James B. Brewer, Helen Vanderswag, Adam Fleisher, Judith L. Heidebrink, Joanne Lord, Sara S. Mason, Colleen S. Albers, David S. Knopman, Kris Johnson, Rachelle S. Doody, Javier Villanueva‐Meyer, Valory Pavlik, Victoria Shibley, Munir Chowdhury, Susan Rountree, Mimi Dang, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, Beau M. Ances, Maria Carroll, Mary L. Creech, Erin Franklin, Mark A. Mintun, Stacy Schneider, Angela Oliver, Daniel Marson, David Geldmacher, Marissa Natelson Love, Randall Griffith, David G. Clark, John Brockington, Erik D. Roberson, Hillel Grossman, Effie Mitsis, Raj C. Shah, Leyla deToledo‐Morrell, Ranjan Duara, Maria T. Greig‐Custo, Warren Barker, Chiadi Onyike, Daniel D’Agostino, Stephanie Kielb, Martin Sadowski, Mohammed O. Sheikh, Anaztasia Ulysse, Mrunalini Gaikwad, P. Murali Doraiswamy, Jeffrey R. Petrella, Salvador Borges‐Neto, Terence Z. Wong, Edward Coleman, Steven E. Arnold, Jason H. Karlawish, David A. Wolk, Christopher M. Clark, Charles D. Smith, Gregory A. Jicha, Peter Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad, Oscar L. Lopez, Mary Ann Oakley, Donna M. Simpson, Anton P. Porsteinsson, Bonnie S. Goldstein, Kim Martin, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Adrian Preda, Dana Nguyen, Kyle Womack, Dana Mathews, Mary Quiceno, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Russell H. Swerdlow, William M. Brooks, Liana Apostolova, Kathleen Tingus, Ellen Woo, Daniel Silverman, Po H. Lu, George Bartzokis, Neill R. Graff‐Radford, Francine Parfitt, Kim Poki-Walker, Martin R. Farlow, Ann Marie Hake, Brandy R. Matthews, Jared R. Brosch, Scott Herring, Christopher H. van Dyck, Richard E. Carson, Martha G. MacAvoy, Pradeep Varma, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Curtis Caldwell, Ging‐Yuek Robin Hsiung, Benita Mudge, Vesna Sossi, Howard Feldman, Michele Assaly, Elizabeth Finger, Stephen Pasternack, Irina Rachisky, John Rogers, Dick Trost, Andrew Kertesz, Charles Bernick, Donna Munic, Emily Rogalskı, Kristine Lipowski, Sandra Weıntraub, Borna Bonakdarpour, Diana Kerwin, Chuang‐Kuo Wu, Nancy Johnson, Carl Sadowsky, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad A. Marshall, Jerome A. Yesavage, Joy L. Taylor, Barton Lane, Allyson Rosen, Jared Tinklenberg, Marwan N. Sabbagh, Christine M. Belden, Sandra A. Jacobson, Sherye A. Sirrel, Neil W. Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Saba Wolday, Joanne Allard, Alan J. Lerner, Paula Ogrocki, Curtis Tatsuoka, Parianne Fatica, Evan Fletcher, Pauline Maillard, John Olichney, Charles DeCarli, Owen Carmichael, Smita Kittur, Michael Borrie, T.-Y. Lee, Robert Bartha, Sterling C. Johnson, Sanjay Asthana, Cynthia M. Carlsson, Pierre N. Tariot, Anna Burke, Ann Marie Milliken, Nadira Trncic, Adam Fleisher, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Douglas W. Scharre, Maria Kataki, B E Kelly, Earl A. Zimmerman, Dzintra Celmins, Alice D. Brown, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Laura A. Flashman, Marc Seltzer, Mary L. Hynes, Robert B. Santulli, Kaycee M. Sink, Leslie Gordineer, Jeff D. Williamson, Pradeep Garg, Franklin Watkins, Brian R. Ott, Geoffrey Tremont, Lori A. Daiello, Stephen Salloway, Paul Malloy, Stephen Correia, Howard J. Rosen, Bruce L. Miller, David C. Perry, Jacobo Mintzer, Kenneth Spicer, David Bachman, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Susan K. Schultz, Karen Ekstam Smith, Hristina Koleva, Ki Won Nam, Hyungsub Shim, Norman Relkin, Gloria Chaing, Michael Lin, Lisa Ravdin, Amanda Smith, Balebail Ashok Raj, Kristin Fargher - Scientific Reports 2019 被引用: 94

In the Alzheimer's disease (AD) continuum, the prodromal state of mild cognitive impairment (MCI) precedes AD dementia and identifying MCI individuals at risk of progression is important for clinical management. Our goal was to develop generalizable multivariate models that integrate high-dimensional data (multimodal neuroimaging and cerebrospinal fluid biomarkers, genetic factors, and measures of cognitive resilience) for identification of MCI individuals who progress to AD within 3 years. Our main findings were i) we were able to build generalizable models with clinically relevant accuracy (~93%) for identifying MCI individuals who progress to AD within 3 years; ii) markers of AD pathophysiology (amyloid, tau, neuronal injury) accounted for large shares of the variance in predicting progression; iii) our methodology allowed us to discover that expression of CR1 (complement receptor 1), an AD susceptibility gene involved in immune pathways, uniquely added independent predictive value. This work highlights the value of optimized machine learning approaches for analyzing multimodal patient information for making predictive assessments.