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Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment

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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 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.

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Acknowledgements

Data collection and dissemination for this project were funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI): the National Institutes of Health (grant number U01 AG024904), and the Department of Defense (award numberW81XWH-12-2-0012). ADNI is funded by the National Institute of Aging and the National Institute of Biomedical Imaging and Bioengineering as well as through generous contributions from the following organizations: AbbVie, Alzheimer’s Association, Alzheimer’s Drug Discovery Foundation, Araclon Biotech, BioClinica Inc., Biogen, Bristol-Myers Squibb Company, CereSpir Inc., Eisai Inc., Elan Pharmaceuticals Inc., Eli Lilly and Company, EuroImmun, F. Hoffmann-La Roche Ltd. and its affiliated company Genentech Inc., Fujirebio, GE Healthcare, IXICO Ltd., Janssen Alzheimer Immunotherapy Research & Development LLC., Johnson & Johnson Pharmaceutical Research &Development LLC., Lumosity, Lundbeck, Merck & Co. Inc., Meso Scale Diagnostics LLC., NeuroRx Research, Neurotrack Technologies, Novartis Pharmaceuticals Corporation, Pfizer Inc., Piramal Imaging, Servier, Takeda Pharmaceutical Company, and Transition Therapeutics. The Canadian Institutes of Health Research are 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, CA, USA. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California, CA, USA.

Michael W. Weiner7, Paul Aisen8, Ronald Petersen9, Clifford R. Jack9, William Jagust10, John Q. Trojanowski11, Arthur W. Toga12, Laurel Beckett13, Robert C. Green14, Andrew J. Saykin15, John Morris16, Leslie M. Shaw11, Zaven Khachaturian13,17, Greg Sorensen18, Lew Kuller19, Marcus Raichle16, Steven Paul20, Peter Davies21, Howard Fillit22, Franz Hefti23, David Holtzman16, Marek M. Mesulam24, William Potter25, Peter Snyder26, Adam Schwartz27, Tom Montine28, Ronald G. Thomas28, Michael Donohue28, Sarah Walter28, Devon Gessert28, Tamie Sather28, Gus Jiminez28, Danielle Harvey13, Matthew Bernstein9, Paul Thompson29, Norbert Schuff7,13, Bret Borowski9, Jeff Gunter9, Matt Senjem9, Prashanthi Vemuri9, David Jones9, Kejal Kantarci9, Chad Ward9, Robert A. Koeppe30, Norm Foster31, Eric M. Reiman32, Kewei Chen32, Chet Mathis19, Susan Landau10, Nigel J. Cairns16, Erin Householder16, Lisa Taylor-Reinwald16, Virginia Lee11, Magdalena Korecka11, Michal Figurski11, Karen Crawford12, Scott Neu12, Tatiana M. Foroud15, Steven G. Potkin33, Li Shen15, Kelley Faber15, Sungeun Kim15, Kwangsik Nho15, Leon Thal8, Neil Buckholtz34, Marylyn Albert35, Richard Frank36, John Hsiao34, Jeffrey Kaye37, Joseph Quinn37, Betty Lind37, Raina Carter37, Sara Dolen37, Lon S. Schneider12, Sonia Pawluczyk12, Mauricio Beccera12, Liberty Teodoro12, Bryan M. Spann12, James Brewer8, Helen Vanderswag8, Adam Fleisher8,32, Judith L. Heidebrink30, Joanne L. Lord30, Sara S. Mason9, Colleen S. Albers9, David Knopman9, Kris Johnson9, Rachelle S. Doody38, Javier Villanueva-Meyer38, Munir Chowdhury38, Susan Rountree38, Mimi Dang38, Yaakov Stern38, Lawrence S. Honig38, Karen L. Bell38, Beau Ances16, Maria Carroll16, Sue Leon16, Mark A. Mintun16, Stacy Schneider16, Angela Oliver16, Daniel Marson39, Randall Griffith39, David Clark39, David Geldmacher39, John Brockington39, Erik Roberson39, Hillel Grossman40, Effie Mitsis40, Leyla de Toledo-Morrell41, Raj C. Shah41, Ranjan Duara42, Daniel Varon42, Maria T. Greig42, Peggy Roberts42, Chiadi Onyike35, Daniel D’Agostino35, Stephanie Kielb35, James E. Galvin43, Brittany Cerbone43, Christina A. Michel43, Henry Rusinek43, Mony J. de Leon43, Lidia Glodzik43, Susan De Santi43, P Murali Doraiswamy44, Jeffrey R. Petrella44, Terence Z. Wong44, Steven E. Arnold11, Jason H. Karlawish11, David Wolk11, Charles D. Smith45, Greg Jicha45, Peter Hardy45, Partha Sinha45, Elizabeth Oates45, Gary Conrad45, Oscar L. Lopez19, MaryAnn Oakley19, Donna M. Simpson35, Anton P. Porsteinsson46, Bonnie S. Goldstein46, Kim Martin46, Kelly M. Makino46, M Saleem Ismail46, Connie Brand46, Ruth A. 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MacAvoy51, Howard Chertkow52, Howard Bergman52, Chris Hosein52, Ging-Yuek Robin Hsiung53, Howard Feldman53, Benita Mudge53, Michele Assaly53, Charles Bernick54, Donna Munic54, Andrew Kertesz55, John Rogers55, Dick Trost55, Diana Kerwin24, Kristine Lipowski24, Chuang-Kuo Wu24, Nancy Johnson24, Carl Sadowsky56, Walter Martinez56, Teresa Villena56, Raymond Scott Turner57, Kathleen Johnson57, Brigid Reynolds57, Reisa A. Sperling14, Keith A. Johnson14, Gad Marshall14, Meghan Frey14, Barton Lane14, Allyson Rosen14, Jared Tinklenberg14, Marwan N. Sabbagh58, Christine M. Belden58, Sandra A. Jacobson58, Sherye A. Sirrel58, Neil Kowall58, Ronald Killiany59, Andrew E. Budson59, Alexander Norbash59, Patricia Lynn Johnson59, Joanne Allard59, Alan Lerner61, Paula Ogrocki61, Leon Hudson61, Evan Fletcher13, Owen Carmichae23, John Olichney13, Charles DeCarli13, Smita Kittur62, Michael Borrie63, T-Y. Lee63, Rob Bartha63, Sterling Johnson64, Sanjay Asthana64, Cynthia M. Carlsson64, Adrian Preda29, Dana Nguyen29, Pierre Tariot31, Stephanie Reeder31, Vernice Bates65, Horacio Capote65, Michelle Rainka65, Douglas W. Scharre66, Maria Kataki66, Anahita Adeli66, Earl A. Zimmerman67, Dzintra Celmins67, Alice D. Brown67, Godfrey D. Pearlson68, Karen Blank68, Karen Anderson68, Robert B. Santulli69, Tamar J. Kitzmiller69, Eben S. Schwartz69, Kaycee M. Sink70, Jeff D. Williamson70, Pradeep Garg70, Franklin Watkins70, Brian R. Ott71, Henry Querfurth71, Geoffrey Tremont71, Stephen Salloway72, Paul Malloy72, Stephen Correia72, Howard J. Rosen7, Bruce L. Miller7, Jacobo Mintzer73, Kenneth Spicer73, David Bachman73, Stephen Pasternak55, Irina Rachinsky55, Dick Drost55, Nunzio Pomara74, Raymundo Hernando74, Antero Sarrael74, Susan K. Schultz75, Laura L. 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Funding

This study was supported by grants received from the National Natural Science Foundation of China (grant numbers 61633018, 82020108013, 61603236, 81830059, and 81801052); the National Key Research and Development Program of China (grant numbers 2016YFC1306300, 2018YFC1312000, and 2018YFC1707704); the 111 Project (grant number D20031); the Shanghai Municipal Science and Technology Major Project (grant number 2017SHZDZX01); and the Beijing Municipal Commission of Health and Family Planning (grant number PXM2020_026283_000002).

Author information

Author notes

  1. Jiehui Jiang, Can Sheng, and Guanqun Chen contributed equally to this work.

Authors and Affiliations

  1. Institute of Biomedical Engineering, School of Information and Communication Engineering, Shanghai University, Shanghai, 200444, China

    Jiehui Jiang, Chunhua Liu, Shichen Jin & Lanlan Li

  2. Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China

    Can Sheng, Guanqun Chen & Ying Han

  3. School of Biomedical Engineering, Hainan University, Haikou, 570228, China

    Xueyan Jiang & Ying Han

  4. German Centre for Neurodegenerative Disease, Clinical Research Group, Venusberg Campus 1, 53121, Bonn, Germany

    Xueyan Jiang

  5. Centre of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China

    Ying Han

  6. National Clinical Research Centre for Geriatric Disorders, Beijing, 100053, China

    Ying Han

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  1. Jiehui Jiang
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  2. Can Sheng
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  3. Guanqun Chen
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  4. Chunhua Liu
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  5. Shichen Jin
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  6. Lanlan Li
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  7. Xueyan Jiang
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  8. Ying Han
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Contributions

JJ and YH conceived of the study. CL and XJ performed the statistical analysis. CS, GC, SJ drafted the initial manuscript. XJ and LL drew the pictures. All authors contributed to revision and editing of the manuscript.

Corresponding authors

Correspondence to Jiehui Jiang or Ying Han.

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Jiang, J., Sheng, C., Chen, G. et al. Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment. GeroScience 44, 2319–2336 (2022). https://doi.org/10.1007/s11357-022-00588-2

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