{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Jiang J"],"funding":["Shanghai Municipal Science and Technology Major Project","the 111 Project","NIA NIH HHS","National Natural Science Foundation of China","NCI NIH HHS","National Key Research and Development Program of China","Beijing Municipal Commission of Health and Family Planning"],"pagination":["2319-2336"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9616982"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["44(4)"],"pubmed_abstract":["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 <sup>18</sup>F-fluorodeoxyglucose (<sup>18</sup>F-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 calcul"],"journal":["GeroScience"],"pubmed_title":["Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment."],"pmcid":["PMC9616982"],"funding_grant_id":["61633018","61603236","2018YFC1312000","D20031","81801052","R01 AG071514","P01 CA095616","2017SHZDZX01","82020108013","U01 AG024904","2018YFC1707704","2016YFC1306300","R01 CA094143","81830059","PXM2020_026283_000002"],"pubmed_authors":["Massoglia D","Crawford K","Belden CM","Taylor JL","Grossman H","Elizabeth Smith K","Brewer J","Rosen HJ","James O","Lane B","Chertkow H","DeCarli C","Gunter J","Leon S","Figurski M","Lord JL","Kendall T","Montine T","Villanueva-Meyer J","Wolk D","Taylor-Reinwald L","Petrella JR","Mathis C","Rachinsky I","Woo E","Frank R","Roberson E","Geldmacher D","Duara R","Watkins F","Reeder S","Grafman J","de Leon MJ","Oates E","Celmins D","Wu CK","Morrison R","Pawluczyk S","Jiminez G","Fletcher E","Lah JJ","DeVous M","Raichle M","Munic D","Salloway S","Peskind ER","Karlawish JH","Mintun MA","Turner RS","Capote H","Neu S","Feldman H","Khachaturian Z","Jones D","Dang M","Johnson KA","Lee TY","Bernick C","Preda A","Saleem Ismail M","Asthana S","Aisen P","Hosein C","Ott BR","Burns JM","Holtzman D","Brockington J","MacAvoy MG","Quinn J","Chaing G","Smith CD","Mintzer J","Snyder P","Hsiao J","Roberts P","Trojanowski JQ","Swerdlow RH","Tremont G","Paul S","Borowski B","Landau S","Fargher K","Davis M","Koeppe RA","Varon D","McAdams-Ortiz C","Sorensen G","Hunt C","Jicha G","Raudin L","Carter R","Reynolds B","Kowall N","Green RC","Reiman EM","Finley S","Li G","Chen K","Brand C","Petrie EC","Bell KL","Kitzmiller TJ","Teodoro L","Chen G","Sirrel SA","Jacobson SA","Carlsson CM","Li L","Zimmerman EA","Pomara N","Fleisher A","Sadowsky C","Friedl K","Anderson HS","Nho K","Porsteinsson AP","Tingus K","Jiang J","Miller BL","Johnson K","Johnson N","Hayes J","Schuff N","Johnson S","Diaz-Arrastia R","Rusinek H","Robin Hsiung GY","Martinez W","Kertesz A","Honig LS","Shah RC","Jiang X","Lerner A","Morris J","Fillit H","Kerwin D","Schultz SK","Lind B","Villena T","Johnson H","Bachman D","Jagust W","Saykin AJ","Mason SS","Heidebrink JL","Gessert D","Rosen A","Scharre DW","Albert M","Anderson K","Potkin SG","Faber K","Apostolova L","Thompson P","Albers CS","Liu C","Kittur S","Schwartz ES","Vemuri P","Petersen R","Shen L","Oliver A","Budson AE","Clark D","Tinklenberg J","Senjem M","Onyike C","Vanderswag H","Thal L","Martin K","Furst AJ","Sather T","Fleischman D","Silverman DHS","Frey M","Spann BM","Stern Y","Greig MT","Bartzokis G","Jin S","Kaye J","Hefti F","Bartha R","Mitsis E","Norbash A","Jay Fruehling J","Trost D","Davies P","Conrad G","Walter S","Kielb S","Knopman D","Adeli A","Bernstein M","Killiany R","Yesavage JA","Neylan T","Kataki M","Cairns NJ","Quiceno M","Drost D","Oakley M","Arfanakis K","Han Y","Buckholtz N","Murali Doraiswamy P","Toga AW","Galvin JE","D'Agostino D","Santulli RB","Sabbagh MN","Hake AM","Foroud TM","Schneider S","Beccera M","Weiner M","Sarrael A","Blank K","Kim S","I Levey A","Relkin N","Arnold SE","Sperling RA","Carson RE","Householder E","Lee V","Hudson L","Rainka M","Pearlson GD","Farlow MR","Mudge B","Beckett L","Carroll M","Jack CR","Herring S","Lopez OL","Mesulam MM","Lipowski K","Graff-Radford NR","Dolen S","Foster N","Ogrocki P","van Dyck CH","Querfurth H","Ponto LLB","Hernando R","Mulnard RA","Malloy P","Griffith R","Bates V","Lu PH","Garg P","Marson D","Wong TZ","Sinha P","Glodzik L","Weiner MW","Potter W","Simpson DM","de Toledo-Morrell L","Williamson JD","Korecka M","Kuller L","Harvey D","Ward C","De Santi S","Correia S","Womack K","Hardy P","Martin-Cook K","Michel CA","Mathews D","Carmichae O","Cerbone B","Matthews BR","Ances B","Sheng C","Shim H","Doody RS","Chowdhury M","Alzheimer’s Disease Neuroimaging Initiative","Brown AD","Borrie M","Bergman H","Olichney J","Rogers J","Thai G","Harding S","Schwartz A","Makino KM","King R","Cellar JS","Schneider LS","Spicer K","Pasternak S","Smith A","Marshall G","Parfitt F","Donohue M","Johnson PL","Raj BA","Rountree S","Nguyen D","Allard J","Assaly M","Tariot P","Goldstein BS","Shaw LM","Sink KM","Thomas RG","Kantarci K"],"additional_accession":[]},"is_claimable":false,"name":"Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment.","description":"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 <sup>18</sup>F-fluorodeoxyglucose (<sup>18</sup>F-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 calcul","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Aug","modification":"2026-05-28T03:35:32.613Z","creation":"2024-10-17T18:37:14.459Z"},"accession":"S-EPMC9616982","cross_references":{"pubmed":["35581512"],"doi":["10.1007/s11357-022-00588-2"]}}