TY - JOUR
T1 - Glucose metabolism patterns
T2 - A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment
AU - for the Alzheimer's Disease Neuroimaging Initiative
AU - Jiang, Jiehui
AU - Sheng, Can
AU - Chen, Guanqun
AU - Liu, Chunhua
AU - Jin, Shichen
AU - Li, Lanlan
AU - Jiang, Xueyan
AU - Han, Ying
AU - Weiner, Michael W.
AU - Aisen, Paul
AU - Petersen, Ronald
AU - Jack, Clifford R.
AU - Jagust, William
AU - Trojanowski, John Q.
AU - Toga, Arthur W.
AU - Beckett, Laurel
AU - Green, Robert C.
AU - Saykin, Andrew J.
AU - Morris, John
AU - Shaw, Leslie M.
AU - Khachaturian, Zaven
AU - Sorensen, Greg
AU - Kuller, Lew
AU - Raichle, Marcus
AU - Paul, Steven
AU - Davies, Peter
AU - Fillit, Howard
AU - Hefti, Franz
AU - Holtzman, David
AU - Mesulam, Marek M.
AU - Potter, William
AU - Snyder, Peter
AU - Schwartz, Adam
AU - Montine, Tom
AU - Thomas, Ronald G.
AU - Donohue, Michael
AU - Walter, Sarah
AU - Gessert, Devon
AU - Sather, Tamie
AU - Jiminez, Gus
AU - Harvey, Danielle
AU - Bernstein, Matthew
AU - Thompson, Paul
AU - Schuff, Norbert
AU - Borowski, Bret
AU - Gunter, Jeff
AU - Senjem, Matt
AU - Vemuri, Prashanthi
AU - Jones, David
AU - Kantarci, Kejal
AU - Ward, Chad
AU - Koeppe, Robert A.
AU - Foster, Norm
AU - Reiman, Eric M.
AU - Chen, Kewei
AU - Mathis, Chet
AU - Landau, Susan
AU - Cairns, Nigel J.
AU - Householder, Erin
AU - Taylor-Reinwald, Lisa
AU - Lee, Virginia
AU - Korecka, Magdalena
AU - Figurski, Michal
AU - Crawford, Karen
AU - Neu, Scott
AU - Foroud, Tatiana M.
AU - Potkin, Steven G.
AU - Shen, Li
AU - Faber, Kelley
AU - Kim, Sungeun
AU - Nho, Kwangsik
AU - Thal, Leon
AU - Buckholtz, Neil
AU - Albert, Marylyn
AU - Frank, Richard
AU - Hsiao, John
AU - Kaye, Jeffrey
AU - Quinn, Joseph
AU - Lind, Betty
AU - Carter, Raina
AU - Dolen, Sara
AU - Schneider, Lon S.
AU - Pawluczyk, Sonia
AU - Beccera, Mauricio
AU - Teodoro, Liberty
AU - Spann, Bryan M.
AU - Brewer, James
AU - Vanderswag, Helen
AU - Fleisher, Adam
AU - Heidebrink, Judith L.
AU - Lord, Joanne L.
AU - Mason, Sara S.
AU - Albers, Colleen S.
AU - Knopman, David
AU - Johnson, Kris
AU - Doody, Rachelle S.
AU - Villanueva-Meyer, Javier
AU - Chowdhury, Munir
AU - Rountree, Susan
AU - Dang, Mimi
AU - Stern, Yaakov
AU - Honig, Lawrence S.
AU - Bell, Karen L.
AU - Ances, Beau
AU - Carroll, Maria
AU - Leon, Sue
AU - Mintun, Mark A.
AU - Schneider, Stacy
AU - Oliver, Angela
AU - Marson, Daniel
AU - Griffith, Randall
AU - Clark, David
AU - Geldmacher, David
AU - Brockington, John
AU - Roberson, Erik
AU - Grossman, Hillel
AU - Mitsis, Effie
AU - de Toledo-Morrell, Leyla
AU - Shah, Raj C.
AU - Duara, Ranjan
AU - Varon, Daniel
AU - Greig, Maria T.
AU - Roberts, Peggy
AU - Onyike, Chiadi
AU - D’Agostino, Daniel
AU - Kielb, Stephanie
AU - Galvin, James E.
AU - Cerbone, Brittany
AU - Michel, Christina A.
AU - Rusinek, Henry
AU - de Leon, Mony J.
AU - Glodzik, Lidia
AU - De Santi, Susan
AU - Murali Doraiswamy, P.
AU - Petrella, Jeffrey R.
AU - Wong, Terence Z.
AU - Arnold, Steven E.
AU - Karlawish, Jason H.
AU - Wolk, David
AU - Smith, Charles D.
AU - Jicha, Greg
AU - Hardy, Peter
AU - Sinha, Partha
AU - Oates, Elizabeth
AU - Conrad, Gary
AU - Lopez, Oscar L.
AU - Oakley, Mary Ann
AU - Simpson, Donna M.
AU - Porsteinsson, Anton P.
AU - Goldstein, Bonnie S.
AU - Martin, Kim
AU - Makino, Kelly M.
AU - Saleem Ismail, M.
AU - Brand, Connie
AU - Mulnard, Ruth A.
AU - Thai, Gaby
AU - McAdams-Ortiz, Catherine
AU - Womack, Kyle
AU - Womack, Kyle
AU - Quiceno, Mary
AU - Diaz-Arrastia, Ramon
AU - King, Richard
AU - Weiner, Myron
AU - Martin-Cook, Kristen
AU - DeVous, Michael
AU - I Levey, Allan
AU - Lah, James J.
AU - Cellar, Janet S.
AU - Burns, Jeffrey M.
AU - Anderson, Heather S.
AU - Swerdlow, Russell H.
AU - Apostolova, Liana
AU - Tingus, Kathleen
AU - Woo, Ellen
AU - Silverman, Daniel H.S.
AU - Lu, Po H.
AU - Bartzokis, George
AU - Graff-Radford, Neill R.
AU - Parfitt, Francine
AU - Kendall, Tracy
AU - Johnson, Heather
AU - Farlow, Martin R.
AU - Hake, Ann Marie
AU - Matthews, Brandy R.
AU - Herring, Scott
AU - Hunt, Cynthia
AU - van Dyck, Christopher H.
AU - Carson, Richard E.
AU - MacAvoy, Martha G.
AU - Chertkow, Howard
AU - Bergman, Howard
AU - Hosein, Chris
AU - Robin Hsiung, Ging Yuek
AU - Feldman, Howard
AU - Mudge, Benita
AU - Assaly, Michele
AU - Bernick, Charles
AU - Munic, Donna
AU - Kertesz, Andrew
AU - Rogers, John
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to American Aging Association.
PY - 2022/8
Y1 - 2022/8
N2 - Exploring individual hallmarks of brain ageing is important. Here, we propose the age-related glucose metabolism pattern (ARGMP) as a potential index to characterize brain ageing in cognitively normal (CN) elderly people. We collected 18F-fluorodeoxyglucose (18F-FDG) PET brain images from two independent cohorts: the Alzheimer’s Disease Neuroimaging Initiative (ADNI, N = 127) and the Xuanwu Hospital of Capital Medical University, Beijing, China (N = 84). During follow-up (mean 80.60 months), 23 participants in the ADNI cohort converted to cognitive impairment. ARGMPs were identified using the scaled subprofile model/principal component analysis method, and cross-validations were conducted in both independent cohorts. A survival analysis was further conducted to calculate the predictive effect of conversion risk by using ARGMPs. The results showed that ARGMPs were characterized by hypometabolism with increasing age primarily in the bilateral medial superior frontal gyrus, anterior cingulate and paracingulate gyri, caudate nucleus, and left supplementary motor area and hypermetabolism in part of the left inferior cerebellum. The expression network scores of ARGMPs were significantly associated with chronological age (R = 0.808, p < 0.001), which was validated in both the ADNI and Xuanwu cohorts. Individuals with higher network scores exhibited a better predictive effect (HR: 0.30, 95% CI: 0.1340 ~ 0.6904, p = 0.0068). These findings indicate that ARGMPs derived from CN participants may represent a novel index for characterizing brain ageing and predicting high conversion risk into cognitive impairment.
AB - Exploring individual hallmarks of brain ageing is important. Here, we propose the age-related glucose metabolism pattern (ARGMP) as a potential index to characterize brain ageing in cognitively normal (CN) elderly people. We collected 18F-fluorodeoxyglucose (18F-FDG) PET brain images from two independent cohorts: the Alzheimer’s Disease Neuroimaging Initiative (ADNI, N = 127) and the Xuanwu Hospital of Capital Medical University, Beijing, China (N = 84). During follow-up (mean 80.60 months), 23 participants in the ADNI cohort converted to cognitive impairment. ARGMPs were identified using the scaled subprofile model/principal component analysis method, and cross-validations were conducted in both independent cohorts. A survival analysis was further conducted to calculate the predictive effect of conversion risk by using ARGMPs. The results showed that ARGMPs were characterized by hypometabolism with increasing age primarily in the bilateral medial superior frontal gyrus, anterior cingulate and paracingulate gyri, caudate nucleus, and left supplementary motor area and hypermetabolism in part of the left inferior cerebellum. The expression network scores of ARGMPs were significantly associated with chronological age (R = 0.808, p < 0.001), which was validated in both the ADNI and Xuanwu cohorts. Individuals with higher network scores exhibited a better predictive effect (HR: 0.30, 95% CI: 0.1340 ~ 0.6904, p = 0.0068). These findings indicate that ARGMPs derived from CN participants may represent a novel index for characterizing brain ageing and predicting high conversion risk into cognitive impairment.
KW - Brain ageing
KW - Glucose metabolism
KW - Pattern
KW - Positron emission tomography
UR - http://www.scopus.com/inward/record.url?scp=85130220126&partnerID=8YFLogxK
U2 - 10.1007/s11357-022-00588-2
DO - 10.1007/s11357-022-00588-2
M3 - Article
C2 - 35581512
AN - SCOPUS:85130220126
SN - 2509-2715
VL - 44
SP - 2319
EP - 2336
JO - GeroScience
JF - GeroScience
IS - 4
ER -