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  • 1. Adams, Hieab H. H.
    et al.
    Hibar, Derrek P.
    Chouraki, Vincent
    Stein, Jason L.
    Nyquist, Paul A.
    Renteria, Miguel E.
    Trompet, Stella
    Arias-Vasquez, Alejandro
    Seshadri, Sudha
    Desrivieres, Sylvane
    Beecham, Ashley H.
    Jahanshad, Neda
    Wittfeld, Katharine
    Van der Lee, Sven J.
    Abramovic, Lucija
    Alhusaini, Saud
    Amin, Najaf
    Andersson, Micael
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Arfanakis, Konstantinos
    Aribisala, Benjamin S.
    Armstrong, Nicola J.
    Athanasiu, Lavinia
    Axelsson, Tomas
    Beiser, Alexa
    Bernard, Manon
    Bis, Joshua C.
    Blanken, Laura M. E.
    Blanton, Susan H.
    Bohlken, Marc M.
    Boks, Marco P.
    Bralten, Janita
    Brickman, Adam M.
    Carmichael, Owen
    Chakravarty, M. Mallar
    Chauhan, Ganesh
    Chen, Qiang
    Ching, Christopher R. K.
    Cuellar-Partida, Gabriel
    Den Braber, Anouk
    Doan, Nhat Trung
    Ehrlich, Stefan
    Filippi, Irina
    Ge, Tian
    Giddaluru, Sudheer
    Goldman, Aaron L.
    Gottesman, Rebecca F.
    Greven, Corina U.
    Grimm, Oliver
    Griswold, Michael E.
    Guadalupe, Tulio
    Hass, Johanna
    Haukvik, Unn K.
    Hilal, Saima
    Hofer, Edith
    Hoehn, David
    Holmes, Avram J.
    Hoogman, Martine
    Janowitz, Deborah
    Jia, Tianye
    Kasperaviciute, Dalia
    Kim, Sungeun
    Klein, Marieke
    Kraemer, Bernd
    Lee, Phil H.
    Liao, Jiemin
    Liewald, David C. M.
    Lopez, Lorna M.
    Luciano, Michelle
    Macare, Christine
    Marquand, Andre
    Matarin, Mar
    Mather, Karen A.
    Mattheisen, Manuel
    Mazoyer, Bernard
    Mckay, David R.
    McWhirter, Rebekah
    Milaneschi, Yuri
    Mirza-Schreiber, Nazanin
    Muetzel, Ryan L.
    Maniega, Susana Munoz
    Nho, Kwangsik
    Nugent, Allison C.
    Loohuis, Loes M. Olde
    Oosterlaan, Jaap
    Papmeyer, Martina
    Pappa, Irene
    Pirpamer, Lukas
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Puetz, Benno
    Rajan, Kumar B.
    Ramasamy, Adaikalavan
    Richards, Jennifer S.
    Risacher, Shannon L.
    Roiz-Santianez, Roberto
    Rommelse, Nanda
    Rose, Emma J.
    Royle, Natalie A.
    Rundek, Tatjana
    Saemann, Philipp G.
    Satizabal, Claudia L.
    Schmaal, Lianne
    Schork, Andrew J.
    Shen, Li
    Shin, Jean
    Shumskaya, Elena
    Smith, Albert V.
    Sprooten, Emma
    Strike, Lachlan T.
    Teumer, Alexander
    Thomson, Russell
    Tordesillas-Gutierrez, Diana
    Toro, Roberto
    Trabzuni, Daniah
    Vaidya, Dhananjay
    Van der Grond, Jeroen
    Van der Meer, Dennis
    Van Donkelaar, Marjolein M. J.
    Van Eijk, Kristel R.
    Van Erp, Theo G. M.
    Van Rooij, Daan
    Walton, Esther
    Westlye, Lars T.
    Whelan, Christopher D.
    Windham, Beverly G.
    Winkler, Anderson M.
    Woldehawariat, Girma
    Wolf, Christiane
    Wolfers, Thomas
    Xu, Bing
    Yanek, Lisa R.
    Yang, Jingyun
    Zijdenbos, Alex
    Zwiers, Marcel P.
    Agartz, Ingrid
    Aggarwal, Neelum T.
    Almasy, Laura
    Ames, David
    Amouyel, Philippe
    Andreassen, Ole A.
    Arepalli, Sampath
    Assareh, Amelia A.
    Barral, Sandra
    Bastin, Mark E.
    Becker, Diane M.
    Becker, James T.
    Bennett, David A.
    Blangero, John
    van Bokhoven, Hans
    Boomsma, Dorret I.
    Brodaty, Henry
    Brouwer, Rachel M.
    Brunner, Han G.
    Buckner, Randy L.
    Buitelaar, Jan K.
    Bulayeva, Kazima B.
    Cahn, Wiepke
    Calhoun, Vince D.
    Cannon, Dara M.
    Cavalleri, Gianpiero L.
    Chen, Christopher
    Cheng, Ching -Yu
    Cichon, Sven
    Cookson, Mark R.
    Corvin, Aiden
    Crespo-Facorro, Benedicto
    Curran, Joanne E.
    Czisch, Michael
    Dale, Anders M.
    Davies, Gareth E.
    De Geus, Eco J. C.
    De Jager, Philip L.
    de Zubicaray, Greig I.
    Delanty, Norman
    Depondt, Chantal
    DeStefano, Anita L.
    Dillman, Allissa
    Djurovic, Srdjan
    Donohoe, Gary
    Drevets, Wayne C.
    Duggirala, Ravi
    Dyer, Thomas D.
    Erk, Susanne
    Espeseth, Thomas
    Evans, Denis A.
    Fedko, Iryna
    Fernandez, Guillen
    Ferrucci, Luigi
    Fisher, Simon E.
    Fleischman, Debra A.
    Ford, Ian
    Foroud, Tatiana M.
    Fox, Peter T.
    Francks, Clyde
    Fukunaga, Masaki
    Gibbs, J. Raphael
    Glahn, David C.
    Gollub, Randy L.
    Goring, Harald H. H.
    Grabe, Hans J.
    Green, Robert C.
    Gruber, Oliver
    Gudnason, Vilmundur
    Guelfi, Sebastian
    Hansell, Narelle K.
    Hardy, John
    Hartman, Catharina A.
    Hashimoto, Ryota
    Hegenscheid, Katrin
    Heinz, Andreas
    Le Hellard, Stephanie
    Hernandez, Dena G.
    Heslenfeld, Dirk J.
    Ho, Beng-Choon
    Hoekstra, Pieter J.
    Hoffmann, Wolfgang
    Hofman, Albert
    Holsboer, Florian
    Homuth, Georg
    Hosten, Norbert
    Hottenga, Jouke-Jan
    Pol, Hilleke E. Hulshoff
    Ikeda, Masashi
    Ikram, M. Kamran
    Jack, Clifford R., Jr.
    Jenldnson, Mark
    Johnson, Robert
    Jonsson, Erik G.
    Jukema, J. Wouter
    Kahn, Rene S.
    Kanai, Ryota
    Kloszewska, Iwona
    Knopman, David S.
    Kochunov, Peter
    Kwok, John B.
    Lawrie, Stephen M.
    Lemaitre, Herve
    Liu, Xinmin
    Longo, Dan L.
    Longstreth, W. T., Jr.
    Lopez, Oscar L.
    Lovestone, Simon
    Martinez, Oliver
    Martinot, Jean-Luc
    Mattay, Venkata S.
    McDonald, Colm
    McIntosh, Andrew M.
    McMahon, Katie L.
    McMahon, Francis J.
    Mecocci, Patrizia
    Melle, Ingrid
    Meyer-Lindenberg, Andreas
    Mohnke, Sebastian
    Montgomery, Grant W.
    Morris, Derek W.
    Mosley, Thomas H.
    Muhleisen, Thomas W.
    Mueller-Myhsok, Bertram
    Nalls, Michael A.
    Nauck, Matthias
    Nichols, Thomas E.
    Niessen, Wiro J.
    Noethen, Markus M.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Ohi, Kazutaka
    Olvera, Rene L.
    Ophoff, Roel A.
    Pandolfo, Massimo
    Paus, Tomas
    Pausova, Zdenka
    Penninx, Brenda W. J. H.
    Pike, G. Bruce
    Potkin, Steven G.
    Psaty, Bruce M.
    Reppermund, Simone
    Rietschel, Marcella
    Roffman, Joshua L.
    Romanczuk-Seiferth, Nina
    Rotter, Jerome I.
    Ryten, Mina
    Sacco, Ralph L.
    Sachdev, Perminder S.
    Saykin, Andrew J.
    Schmidt, Reinhold
    Schofield, Peter R.
    Sigurdsson, Sigurdur
    Simmons, Andy
    Singleton, Andrew
    Sisodiya, Sanjay M.
    Smith, Colin
    Smoller, Jordan W.
    Soininen, Hindu.
    Srikanth, Velandai
    Steen, Vidar M.
    Stott, David J.
    Sussmann, Jessika E.
    Thalamuthu, Anbupalam
    Tiemeier, Henning
    Toga, Arthur W.
    Traynor, Bryan J.
    Troncoso, Juan
    Turner, Jessica A.
    Tzourio, Christophe
    Uitterlinden, Andre G.
    Hernandez, Maria C. Valdes
    Van der Brug, Marcel
    Van der Lugt, Aad
    Van der Wee, Nic J. A.
    Van Duijn, Cornelia M.
    Van Haren, Neeltje E. M.
    Van't Ent, Dennis
    Van Tol, Marie Jose
    Vardarajan, Badri N.
    Veltman, Dick J.
    Vernooij, Meike W.
    Voelzke, Henry
    Walter, Henrik
    Wardlaw, Joanna M.
    Wassink, Thomas H.
    Weale, Michael E.
    Weinberger, Daniel R.
    Weiner, Michael W.
    Wen, Wei
    Westman, Eric
    White, Tonya
    Wong, Tien Y.
    Wright, Clinton B.
    Zielke, H. Ronald
    Zonderman, Alan B.
    Deary, Ian J.
    DeCarli, Charles
    Schmidt, Helena
    Martin, Nicholas G.
    De Craen, Anton J. M.
    Wright, Margaret J.
    Launer, Lenore J.
    Schumann, Gunter
    Fornage, Myriam
    Franke, Barbara
    Debette, Stephanie
    Medland, Sarah E.
    Ikram, M. Arfan
    Thompson, Paul M.
    Novel genetic loci underlying human intracranial volume identified through genome-wide association2016In: Nature Neuroscience, ISSN 1097-6256, E-ISSN 1546-1726, Vol. 19, no 12, p. 1569-1582Article in journal (Refereed)
    Abstract [en]

    Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (rho(genetic) = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (N-combined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

  • 2.
    Anjomshoae, Sule
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Umeå University.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Explaining graph convolutional network predictions for clinicians: an explainable AI approach to Alzheimer’s disease classification2024In: Frontiers in Artificial Intelligence, E-ISSN 2624-8212, Vol. 6, article id 1334613Article in journal (Refereed)
    Abstract [en]

    Introduction: Graph-based representations are becoming more common in the medical domain, where each node defines a patient, and the edges signify associations between patients, relating individuals with disease and symptoms in a node classification task. In this study, a Graph Convolutional Networks (GCN) model was utilized to capture differences in neurocognitive, genetic, and brain atrophy patterns that can predict cognitive status, ranging from Normal Cognition (NC) to Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD), on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Elucidating model predictions is vital in medical applications to promote clinical adoption and establish physician trust. Therefore, we introduce a decomposition-based explanation method for individual patient classification.

    Methods: Our method involves analyzing the output variations resulting from decomposing input values, which allows us to determine the degree of impact on the prediction. Through this process, we gain insight into how each feature from various modalities, both at the individual and group levels, contributes to the diagnostic result. Given that graph data contains critical information in edges, we studied relational data by silencing all the edges of a particular class, thereby obtaining explanations at the neighborhood level.

    Results: Our functional evaluation showed that the explanations remain stable with minor changes in input values, specifically for edge weights exceeding 0.80. Additionally, our comparative analysis against SHAP values yielded comparable results with significantly reduced computational time. To further validate the model's explanations, we conducted a survey study with 11 domain experts. The majority (71%) of the responses confirmed the correctness of the explanations, with a rating of above six on a 10-point scale for the understandability of the explanations.

    Discussion: Strategies to overcome perceived limitations, such as the GCN's overreliance on demographic information, were discussed to facilitate future adoption into clinical practice and gain clinicians' trust as a diagnostic decision support system.

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  • 3.
    Degerman, Sofie
    et al.
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Josefsson, Maria
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Nordin Adolfsson, Annelie
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Wennstedt, Sigrid
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Landfors, Mattias
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Haider, Zahra
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Hultdin, Magnus
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Adolfsson, Rolf
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Maintained memory in aging is associated with young epigenetic age2017In: Neurobiology of Aging, ISSN 0197-4580, E-ISSN 1558-1497, Vol. 55, p. 167-171Article in journal (Refereed)
    Abstract [en]

    Epigenetic alterations during aging have been proposed to contribute to decline in physical and cognitive functions, and accelerated epigenetic aging has been associated with disease and all-cause mortality later in life. In this study, we estimated epigenetic age dynamics in groups with different memory trajectories (maintained high performance, average decline, and accelerated decline) over a 15-year period. Epigenetic (DNA-methylation [DNAm]) age was assessed, and delta age (DNAm age - chronological age) was calculated in blood samples at baseline (age: 55-65 years) and 15 years later in 52 age- and gender-matched individuals from the Betula study in Sweden. A lower delta DNAm age was observed for those with maintained memory functions compared with those with average (p = 0.035) or accelerated decline (p = 0.037). Moreover, separate analyses revealed that DNAm age at follow-up, but not chronologic age, was a significant predictor of dementia (p = 0.019). Our findings suggest that young epigenetic age contributes to maintained memory in aging.

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  • 4. Fjell, Anders M.
    et al.
    Sørensen, Øystein
    Amlien, Inge K.
    Bartrés-Faz, David
    Brandmaier, Andreas M.
    Buchmann, Nikolaus
    Demuth, Ilja
    Drevon, Christian A.
    Düzel, Sandra
    Ebmeier, Klaus P.
    Ghisletta, Paolo
    Idland, Ane-Victoria
    Kietzmann, Tim C.
    Kievit, Rogier A.
    Kühn, Simone
    Lindenberger, Ulman
    Magnussen, Fredrik
    Macià, Didac
    Mowinckel, Athanasia M.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Sexton, Claire E.
    Solé-Padullés, Cristina
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Roe, James M.
    Sederevicius, Donatas
    Suri, Sana
    Vidal-Piñeiro, Didac
    Wagner, Gerd
    Watne, Leiv Otto
    Westerhausen, René
    Zsoldos, Enikő
    Walhovd, Kristine B.
    Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline-Results From the Lifebrain Consortium2021In: Cerebral Cortex, ISSN 1047-3211, E-ISSN 1460-2199, Vol. 31, no 4, p. 1953-1969Article in journal (Refereed)
    Abstract [en]

    We examined whether sleep quality and quantity are associated with cortical and memory changes in cognitively healthy participants across the adult lifespan. Associations between self-reported sleep parameters (Pittsburgh Sleep Quality Index, PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n = 2205, 4363 MRIs, 18-92 years). In additional analyses, we tested coherence with cell-specific gene expression maps from the Allen Human Brain Atlas, and relations to changes in memory performance. "PSQI # 1 Subjective sleep quality" and "PSQI #5 Sleep disturbances" were related to thinning of the right lateral temporal cortex, with lower quality and more disturbances being associated with faster thinning. The association with "PSQI #5 Sleep disturbances" emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. None of the sleep scales were related to a longitudinal change in episodic memory function, suggesting that sleep-related cortical changes were independent of cognitive decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.

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  • 5. Fjell, Anders M.
    et al.
    Sørensen, Øystein
    Amlien, Inge K.
    Bartrés-Faz, David
    Bros, Didac Maciá
    Buchmann, Nikolaus
    Demuth, Ilja
    Drevon, Christian A
    Düzel, Sandra
    Ebmeier, Klaus P
    Idland, Ane-Victoria
    Kietzmann, Tim C
    Kievit, Rogier
    Kühn, Simone
    Lindenberger, Ulman
    Mowinckel, Athanasia M
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Price, Darren
    Sexton, Claire E
    Solé-Padullés, Cristina
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Sederevicius, Donatas
    Suri, Sana
    Wagner, Gerd
    Watne, Leiv Otto
    Westerhausen, René
    Zsoldos, Enikő
    Walhovd, Kristine B
    Self-reported sleep relates to hippocampal atrophy across the adult lifespan: results from the Lifebrain consortium2020In: Sleep, ISSN 0161-8105, E-ISSN 1550-9109, Vol. 43, no 5, article id zsz280Article in journal (Refereed)
    Abstract [en]

    Objectives: Poor sleep is associated with multiple age-related neurodegenerative and neuropsychiatric conditions. The hippocampus plays a special role in sleep and sleep-dependent cognition, and accelerated hippocampal atrophy is typically seen with higher age. Hence, it is critical to establish how the relationship between sleep and hippocampal volume loss unfolds across the adult lifespan.

    Methods: Self-reported sleep measures and MRI-derived hippocampal volumes were obtained from 3105 cognitively normal participants (18–90 years) from major European brain studies in the Lifebrain consortium. Hippocampal volume change was estimated from 5116 MRIs from 1299 participants for whom longitudinal MRIs were available, followed up to 11 years with a mean interval of 3.3 years. Cross-sectional analyses were repeated in a sample of 21,390 participants from the UK Biobank.

    Results: No cross-sectional sleep—hippocampal volume relationships were found. However, worse sleep quality, efficiency, problems, and daytime tiredness were related to greater hippocampal volume loss over time, with high scorers showing 0.22% greater annual loss than low scorers. The relationship between sleep and hippocampal atrophy did not vary across age. Simulations showed that the observed longitudinal effects were too small to be detected as age-interactions in the cross-sectional analyses.

    Conclusions: Worse self-reported sleep is associated with higher rates of hippocampal volume decline across the adult lifespan. This suggests that sleep is relevant to understand individual differences in hippocampal atrophy, but limited effect sizes call for cautious interpretation.

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  • 6.
    Gorbach, Tetiana
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Bartrés-Faz, David
    Brandmaier, Andreas M.
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
    Düzel, Sandra
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
    Henson, Richard N.
    MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
    Idland, Ane-Victoria
    Oslo Delirium Research Group, Department of Geriatric Medicine, University of Oslo,Oslo, Norway.
    Lindenberger, Ulman
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
    Macià Bros, Dídac
    Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain.
    Mowinckel, Athanasia M.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo,Oslo, Norway.
    Solé-Padullés, Cristina
    Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain.
    Sørensen, Øystein
    Center for Lifespan Changes in Brain and Cognition, University of Oslo,Oslo, Norway.
    Walhovd, Kristine B.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
    Watne, Leiv Otto
    MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
    Westerhausen, René
    Center for Lifespan Changes in Brain and Cognition, University of Oslo,Oslo, Norway.
    Fjell, Anders M.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Longitudinal association between hippocampus atrophy and episodic-memory decline in non-demented APOE ε4 carriers2020In: Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, E-ISSN 2352-8729, Vol. 12, no 1, article id e12110Article in journal (Refereed)
    Abstract [en]

    Introduction: The apolipoprotein E (APOE) ε4 allele is the main genetic risk factor for Alzheimer's disease (AD), accelerated cognitive aging, and hippocampal atrophy, but its influence on the association between hippocampus atrophy and episodic-memory decline in non-demented individuals remains unclear.

    Methods: We analyzed longitudinal (two to six observations) magnetic resonance imaging (MRI)–derived hippocampal volumes and episodic memory from 748 individuals (55 to 90 years at baseline, 50% female) from the European Lifebrain consortium.

    Results: The change-change association for hippocampal volume and memory was significant only in ε4 carriers (N = 173, r = 0.21, P = .007; non-carriers: N = 467, r = 0.073,P = .117). The linear relationship was significantly steeper for the carriers [t(629) =2.4, P = .013]. A similar trend toward a stronger change-change relation for carriers was seen in a subsample with more than two assessments.

    Discussion: These findings provide evidence for a difference in hippocampus-memory association between ε4 carriers and non-carriers, thus highlighting how genetic factors modulate the translation of the AD-related pathophysiological cascade into cognitive deficits.

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  • 7.
    Gorbach, Tetiana
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Lundquist, Anders
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Orädd, Greger
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Josefsson, Maria
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Salami, Alireza
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Longitudinal association between hippocampus atrophy and episodic-memory decline2017In: Neurobiology of Aging, ISSN 0197-4580, E-ISSN 1558-1497, Vol. 51, p. 167-176Article in journal (Refereed)
    Abstract [en]

    There is marked variability in both onset and rate of episodic-memory decline in aging. Structural magnetic resonance imaging studies have revealed that the extent of age-related brain changes varies markedly across individuals. Past studies of whether regional atrophy accounts for episodic-memory decline in aging have yielded inconclusive findings. Here we related 15-year changes in episodic memory to 4-year changes in cortical and subcortical gray matter volume and in white-matter connectivity and lesions. In addition, changes in word fluency, fluid IQ (Block Design), and processing speed were estimated and related to structural brain changes. Significant negative change over time was observed for all cognitive and brain measures. A robust brain-cognition change-change association was observed for episodic-memory decline and atrophy in the hippocampus. This association was significant for older (65-80 years) but not middle-aged (55-60 years) participants and not sensitive to the assumption of ignorable attrition. Thus, these longitudinal findings highlight medial-temporal lobe system integrity as particularly crucial for maintaining episodic-memory functioning in older age. 

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  • 8. Grydeland, Håkon
    et al.
    Sederevicius, Donatas
    Wang, Yunpeng
    Bartres-Faz, David
    Bertram, Lars
    Dobricic, Valerija
    Duzel, Sandra
    Ebmeier, Klaus P.
    Lindenberger, Ulman
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Sexton, Claire E.
    Sole-Padulles, Cristina
    Sørensen, Øystein
    Walhovd, Kristine B.
    Fjell, Anders M.
    Self-reported sleep relates to microstructural hippocampal decline in beta-amyloid positive Adults beyond genetic risk2021In: Sleep, ISSN 0161-8105, E-ISSN 1550-9109, Vol. 44, no 11, article id zsab110Article in journal (Refereed)
    Abstract [en]

    Study Objectives: A critical role linking sleep with memory decay and beta-amyloid (A beta) accumulation, two markers of Alzheimer's disease (AD) pathology, may be played by hippocampal integrity. We tested the hypotheses that worse self-reported sleep relates to decline in memory and intra-hippocampal microstructure, including in the presence of A beta.

    Methods: Two-hundred and forty-three cognitively healthy participants, aged 19-81 years, completed the Pittsburgh Sleep Quality Index once, and two diffusion tensor imaging sessions, on average 3 years apart, allowing measures of decline in intra-hippocampal microstructure as indexed by increased mean diffusivity. We measured memory decay at each imaging session using verbal delayed recall. One session of positron emission tomography, in 108 participants above 44 years of age, yielded 23 A beta positive. Genotyping enabled control for APOE epsilon 4 status, and polygenic scores for sleep and AD, respectively.

    Results: Worse global sleep quality and sleep efficiency related to more rapid reduction of hippocampal microstructure over time. Focusing on efficiency (the percentage of time in bed at night spent asleep), the relation was stronger in presence of A beta accumulation, and hippocampal integrity decline mediated the relation with memory decay. The results were not explained by genetic risk for sleep efficiency or AD.

    Conclusions: Worse sleep efficiency related to decline in hippocampal microstructure, especially in the presence of A beta accumulation, and A beta might link poor sleep and memory decay. As genetic risk did not account for the associations, poor sleep efficiency might constitute a risk marker for AD, although the driving causal mechanisms remain unknown.

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  • 9.
    Josefsson, Maria
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Daniels, Michael J.
    Department of Statistics, University of Florida, USA.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    A Bayesian semiparametric approach for inference on the population partly conditional mean from longitudinal data with dropout2023In: Biostatistics, ISSN 1465-4644, E-ISSN 1468-4357, Vol. 24, no 2, p. 372-387Article in journal (Refereed)
    Abstract [en]

    Studies of memory trajectories using longitudinal data often result in highly non-representative samples due to selective study enrollment and attrition. An additional bias comes from practice effects that result in improved or maintained performance due to familiarity with test content or context. These challenges may bias study findings and severely distort the ability to generalize to the target population. In this study we propose an approach for estimating the finite population mean of a longitudinal outcome conditioning on being alive at a specific time point. We develop a flexible Bayesian semi-parametric predictive estimator for population inference when longitudinal auxiliary information is known for the target population. We evaluate sensitivity of the results to untestable assumptions and further compare our approach to other methods used for population inference in a simulation study. The proposed approach is motivated by 15-year longitudinal data from the Betula longitudinal cohort study. We apply our approach to estimate lifespan trajectories in episodic memory, with the aim to generalize findings to a target population.

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  • 10.
    Josefsson, Maria
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nilsson, Lars-Göran
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Centre for Population Studies (CPS). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Genetic and lifestyle predictors of 15-Year longitudinal change in episodic memory2012In: Journal of The American Geriatrics Society, ISSN 0002-8614, E-ISSN 1532-5415, Vol. 60, no 12, p. 2308-2312Article in journal (Refereed)
    Abstract [en]

    OBJECTIVES: To reveal distinct longitudinal trajectories in episodic memory over 15 years and to identify demographic, lifestyle, health-related, and genetic predictors of stability or decline. DESIGN: Prospective cohort study. SETTING: The Betula Project, Umeå, Sweden. PARTICIPANTS: One thousand nine hundred fifty-four healthy participants aged 35 to 85 at baseline. MEASUREMENTS: Memory was assessed according to validated episodic memory tasks in participants from a large population-based sample. Data were analyzed using a random-effects pattern-mixture model that considered the effect of attrition over two to four longitudinal sessions. Logistic regression was used to determine significant predictors of stability or decline relative to average change in episodic memory. RESULTS: Of 1,558 participants with two or more test sessions, 18% were classified as maintainers and 13% as decliners, and 68% showed age-typical average change. More educated and more physically active participants, women, and those living with someone were more likely to be classified as maintainers, as were carriers of the met allele of the catechol-O-methyltransferase gene. Less educated participants, those not active in the labor force, and men were more likely to be classified as decliners, and the apolipoprotein E ɛ4 allele was more frequent in decliners. CONCLUSION: Quantitative, attrition-corrected assessment of longitudinal changes in memory can reveal substantial heterogeneity in aging trajectories, and genetic and lifestyle factors predict such heterogeneity.

  • 11.
    Josefsson, Maria
    et al.
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR). Demographic Data Base.
    Sundström, Anna
    Umeå University, Faculty of Social Sciences, Department of Psychology. Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nordin Adolfsson, Annelie
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Adolfsson, Rolf
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Memory profiles predict dementia over 23–28 years in normal but not successful aging2023In: International psychogeriatrics, ISSN 1041-6102, E-ISSN 1741-203X, Vol. 35, no 7, p. 351-359Article in journal (Refereed)
    Abstract [en]

    Objectives: Prospective studies suggest that memory deficits are detectable decades before clinical symptoms of dementia emerge. However, individual differences in long-term memory trajectories prior to diagnosis need to be further elucidated. The aim of the current study was to investigate long-term dementia and mortality risk for individuals with different memory trajectory profiles in a well-characterized population-based sample.

    Methods: 1062 adults (aged 45–80 years) who were non-demented at baseline were followed over 23–28 years. Dementia and mortality risk were studied for three previously classified episodic memory trajectory groups: maintained high performance (Maintainers; 26%), average decline (Averages; 64%), and accelerated decline (Decliners; 12%), using multistate modeling to characterize individuals’ transitions from an initial non-demented state, possibly to a state of dementia and/or death.

    Results: The memory groups showed considerable intergroup variability in memory profiles, starting 10–15 years prior to dementia diagnosis, and prior to death. A strong relationship between memory trajectory group and dementia risk was found. Specifically, Decliners had more than a fourfold risk of developing dementia compared to Averages. In contrast, Maintainers had a 2.6 times decreased dementia risk compared to Averages, and in addition showed no detectable memory decline prior to dementia diagnosis. A similar pattern of association was found for the memory groups and mortality risk, although only among non-demented.

    Conclusion: There was a strong relationship between accelerated memory decline and dementia, further supporting the prognostic value of memory decline. The intergroup differences, however, suggest that mechanisms involved in successful memory aging may delay symptom onset.

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  • 12.
    Kauppi, Karolina
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Department of Medical Epidemiology and Biostatistics, Karolinska Institutet,Stockholm, Sweden.
    Rönnlund, Michael
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Nordin Adolfsson, Annelie
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Adolfsson, Rolf
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Effects of polygenic risk for Alzheimer's disease on rate of cognitive decline in normal aging2020In: Translational Psychiatry, E-ISSN 2158-3188, Vol. 10, no 1, article id 250Article in journal (Refereed)
    Abstract [en]

    Most people's cognitive abilities decline with age, with significant and partly genetically driven, individual differences in rate of change. Although APOE 4 and genetic scores for late-onset Alzheimer's disease (LOAD) have been related to cognitive decline during preclinical stages of dementia, there is limited knowledge concerning genetic factors implied in normal cognitive aging. In the present study, we examined three potential genetic predictors of age-related cognitive decline as follows: (1) the APOE 4 allele, (2) a polygenic score for general cognitive ability (PGS-cog), and (3) a polygenic risk score for late-onset AD (PRS-LOAD). We examined up to six time points of cognitive measurements in the longitudinal population-based Betula study, covering a 25-year follow-up period. Only participants that remained alive and non-demented until the most recent dementia screening (1-3 years after the last test occasion) were included (n=1087). Individual differences in rate of cognitive change (composite score) were predicted by the PRS-LOAD and APOE 4, but not by PGS-cog. To control for the possibility that the results reflected a preclinical state of Alzheimer's disease in some participants, we re-ran the analyses excluding cognitive data from the last test occasion to model cognitive change up-until a minimum of 6 years before potential onset of clinical Alzheimers. Strikingly, the association of PRS-LOAD, but not APOE 4, with cognitive change remained. The results indicate that PRS-LOAD predicts individual difference in rate of cognitive decline in normal aging, but it remains to be determined to what extent this reflects preclinical Alzheimer's disease brain pathophysiology and subsequent risk to develop the disease.

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  • 13.
    Koch, Elise
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Lundquist, Anders
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Adolfsson, Rolf
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Kauppi, Karolina
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Solna, Sweden.
    Sex-specific effects of polygenic risk for schizophrenia on lifespan cognitive functioning in healthy individuals2021In: Translational Psychiatry, E-ISSN 2158-3188, Vol. 11, no 1, article id 520Article in journal (Refereed)
    Abstract [en]

    Polygenic risk for schizophrenia has been associated with lower cognitive ability and age-related cognitive change in healthy individuals. Despite well-established neuropsychological sex differences in schizophrenia patients, genetic studies on sex differences in schizophrenia in relation to cognitive phenotypes are scarce. Here, we investigated whether the effect of a polygenic risk score (PRS) for schizophrenia on childhood, midlife, and late-life cognitive function in healthy individuals is modified by sex, and if PRS is linked to accelerated cognitive decline. Using a longitudinal data set from healthy individuals aged 25–100 years (N = 1459) spanning a 25-year period, we found that PRS was associated with lower cognitive ability (episodic memory, semantic memory, visuospatial ability), but not with accelerated cognitive decline. A significant interaction effect between sex and PRS was seen on cognitive task performance, and sex-stratified analyses showed that the effect of PRS was male-specific. In a sub-sample, we observed a male-specific effect of the PRS on school performance at age 12 (N = 496). Our findings of sex-specific effects of schizophrenia genetics on cognitive functioning across the lifespan indicate that the effects of underlying disease genetics on cognitive functioning is dependent on biological processes that differ between the sexes.

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  • 14.
    Nyberg, Lars
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Andersson, Micael
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Kauppi, Karolina
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Lundquist, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Persson, Jonas
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Stockholm Brain Institute, Karolinska Institute, Stockholm, Sweden.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Karolinska Institute, Stockholm, Sweden.
    Nilsson, Lars-Göran
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Stockholm University, Stockholm Brain Institute.
    Age-related and genetic modulation of frontal cortex efficiency2014In: Journal of cognitive neuroscience, ISSN 0898-929X, E-ISSN 1530-8898, Vol. 26, no 4, p. 746-754Article in journal (Refereed)
    Abstract [en]

    The dorsolateral pFC (DLPFC) is a key region for working memory. It has been proposed that the DLPFC is dynamically recruited depending on task demands. By this view, high DLPFC recruitment for low-demanding tasks along with weak DLPFC upregulation at higher task demands reflects low efficiency. Here, the fMRI BOLD signal during working memory maintenance and manipulation was examined in relation to aging and catechol-O-methyltransferase (COMT) Val(158)Met status in a large representative sample (n = 287). The efficiency hypothesis predicts a weaker DLPFC response during manipulation, along with a stronger response during maintenance for older adults and COMT Val carriers compared with younger adults and COMT Met carriers. Consistent with the hypothesis, younger adults and met carriers showed maximal DLPFC BOLD response during manipulation, whereas older adults and val carriers displayed elevated DLPFC responses during the less demanding maintenance condition. The observed inverted relations support a link between dopamine and DLPFC efficiency.

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  • 15.
    Nyberg, Lars
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, Oslo, Norway.
    Andersson, Micael
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Lundquist, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Baaré, William F.C.
    Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
    Bartrés-Faz, David
    Department of Medicine, Faculty of Medicine and Health Sciences, Institut de Neurociències, Universitat de Barcelona, and Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain.
    Bertram, Lars
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, Oslo, Norway; Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany.
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark; Faculty of Medical and Health Sciences, Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; Department of Neurology, Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.
    Brandmaier, Andreas M.
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; MSB Medical School Berlin, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK.
    Demnitz, Naiara
    Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
    Drevon, Christian A.
    Vitas AS, Science Park, Oslo, Norway; Department of Nutrition, Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
    Duezel, Sandra
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.
    Ebmeier, Klaus P.
    Department of Psychiatry, University of Oxford, Oxford, UK.
    Ghisletta, Paolo
    Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland; UniDistance Suisse, Brig, Switzerland; Swiss National Centre of Competence in Research LIVES, University of Geneva, Geneva, Switzerland.
    Henson, Richard
    Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge, England.
    Jensen, Daria E.A.
    5Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Oxford, UK.
    Kievit, Rogier A.
    Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands.
    Knights, Ethan
    Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge, England.
    Kühn, Simone
    Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK.
    Lindenberger, Ulman
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK.
    Plachti, Anna
    Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Roe, James M.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, Oslo, Norway,.
    Madsen, Kathrine Skak
    Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK.
    Solé-Padullés, Cristina
    Department of Medicine, Faculty of Medicine and Health Sciences, Institut de Neurociències, Universitat de Barcelona, and Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain.
    Sommerer, Yasmine
    Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany.
    Suri, Sana
    Department of Psychiatry, University of Oxford, Oxford, UK; 1Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands.
    Zsoldos, Enikő
    Department of Psychiatry, University of Oxford, Oxford, UK; 1Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands.
    Fjell, Anders M.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, Oslo, Norway; Center for Computational Radiology and Artificial Intelligence, Oslo University Hospital, Oslo, Norway.
    Walhovd, Kristine B.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, Oslo, Norway; Center for Computational Radiology and Artificial Intelligence, Oslo University Hospital, Oslo, Norway.
    Individual differences in brain aging: heterogeneity in cortico-hippocampal but not caudate atrophy rates2023In: Cerebral Cortex, ISSN 1047-3211, E-ISSN 1460-2199, Vol. 33, no 9, p. 5075-5081Article in journal (Refereed)
    Abstract [en]

    It is well documented that some brain regions, such as association cortices, caudate, and hippocampus, are particularly prone to age-related atrophy, but it has been hypothesized that there are individual differences in atrophy profiles. Here, we document heterogeneity in regional-atrophy patterns using latent-profile analysis of 1,482 longitudinal magnetic resonance imaging observations. The results supported a 2-group solution reflecting differences in atrophy rates in cortical regions and hippocampus along with comparable caudate atrophy. The higher-atrophy group had the most marked atrophy in hippocampus and also lower episodic memory, and their normal caudate atrophy rate was accompanied by larger baseline volumes. Our findings support and refine models of heterogeneity in brain aging and suggest distinct mechanisms of atrophy in striatal versus hippocampal-cortical systems.

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  • 16.
    Nyberg, Lars
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark; Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark .
    Eriksson Sörman, Daniel
    Hansson, Patrik
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Herlitz, Agneta
    Kauppi, Karolina
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden .
    Ljungberg, Jessica K.
    Lövheim, Hugo
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine. Umeå University, Faculty of Medicine, Wallenberg Centre for Molecular Medicine at Umeå University (WCMM).
    Lundquist, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Nordin Adolfsson, Annelie
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Oudin, Anna
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health. Environment Society and Health, Occupational and Environmental Medicine, Lund University.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Rönnlund, Michael
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Stiernstedt, Mikael
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Sundström, Anna
    Umeå University, Faculty of Social Sciences, Department of Psychology. Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Adolfsson, Rolf
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Biological and environmental predictors of heterogeneity in neurocognitive ageing: Evidence from Betula and other longitudinal studies2020In: Ageing Research Reviews, ISSN 1568-1637, E-ISSN 1872-9649, Vol. 64, article id 101184Article in journal (Refereed)
    Abstract [en]

    Individual differences in cognitive performance increase with advancing age, reflecting marked cognitive changes in some individuals along with little or no change in others. Genetic and lifestyle factors are assumed to influence cognitive performance in ageing by affecting the magnitude and extent of age-related brain changes (i.e., brain maintenance or atrophy), as well as the ability to recruit compensatory processes. The purpose of this review is to present findings from the Betula study and other longitudinal studies, with a focus on clarifying the role of key biological and environmental factors assumed to underlie individual differences in brain and cognitive ageing. We discuss the vital importance of sampling, analytic methods, consideration of non-ignorable dropout, and related issues for valid conclusions on factors that influence healthy neurocognitive ageing.

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  • 17.
    Nyberg, Lars
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
    Magnussen, Fredrik
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
    Lundquist, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Baaré, William
    Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, Amager and Hvidovre, Hvidovre, Denmark.
    Bartrés-Faz, David
    Department of Medicine, Faculty of Medicine and Health Sciences and Neurosciences Institute, University of Barcelona, Barcelona, Spain.
    Bertram, Lars
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway; Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany.
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, Amager and Hvidovre, Hvidovre, Denmark; Institute of Sports Medicine Copenhagen, Copenhagen University Hospital, Bispebjerg, Copenhagen, Denmark.
    Brandmaier, Andreas M.
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
    Drevon, Christian A.
    Vitas AS, Research Park, Oslo, Norway; Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, Medicine/University of Oslo, Oslo, Norway.
    Ebmeier, Klaus
    Warneford Hospital, University of Oxford, Oxford, United Kingdom.
    Ghisletta, Paolo
    Faculté de Psychologie et des Sciences de l'Education, Université de Genève, Geneva, Switzerland.
    Henson, Richard N.
    Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.
    Junqué, Carme
    Department of Medicine, Faculty of Medicine and Health Sciences and Neurosciences Institute, University of Barcelona, Barcelona, Spain.
    Kievit, Rogier
    Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, Netherlands.
    Kleemeyer, Maike
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.
    Knights, Ethan
    Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.
    Kühn, Simone
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Department of Psychiatry and Psychotherapy, University Clinic Hamburg-Eppendorf, Hamburg, Germany.
    Lindenberger, Ulman
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
    Penninx, Brenda W.J.H.
    Department of Psychiatry, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, Netherlands.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Sørensen, Øystein
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
    Vaqué-Alcázar, Lídia
    Department of Medicine, Faculty of Medicine and Health Sciences and Neurosciences Institute, University of Barcelona, Barcelona, Spain.
    Walhovd, Kristine B.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
    Fjell, Anders M.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
    Educational attainment does not influence brain aging2021In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 118, no 18, article id 2101644118Article in journal (Refereed)
    Abstract [en]

    Education has been related to various advantageous lifetime outcomes. Here, using longitudinal structural MRI data (4,422 observations), we tested the influential hypothesis that higher education translates into slower rates of brain aging. Cross-sectionally, education was modestly associated with regional cortical volume. However, despite marked mean atrophy in the cortex and hippocampus, education did not influence rates of change. The results were replicated across two independent samples. Our findings challenge the view that higher education slows brain aging.

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  • 18.
    Nyberg, Lars
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Successful Memory Aging2019In: Annual Review of Psychology, ISSN 0066-4308, E-ISSN 1545-2085, Vol. 70, p. 219-243Article, review/survey (Refereed)
    Abstract [en]

    For more than 50 years, psychologists, gerontologists, and, more recently, neuroscientists have considered the possibility of successful aging. How to define successful aging remains debated, but well-preserved age-sensitive cognitive functions, like episodic memory, is an often-suggested criterion. Evidence for successful memory aging comes from cross-sectional and longitudinal studies showing that some older individuals display high and stable levels of performance. Successful memory aging may be accomplished via multiple paths. One path is through brain maintenance, or relative lack of age-related brain pathology. Through another path, successful memory aging can be accomplished despite brain pathology by means of efficient compensatory and strategic processes. Genetic, epigenetic, and lifestyle factors influence memory aging via both paths. Some of these factors can be promoted throughout the life course, which, at the individual as well as the societal level, can positively impact successful memory aging.

  • 19.
    Nyberg, Lars
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Lundquist, Anders
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Structural and functional imaging of aging: longitudinal sudies2017In: Cognitive neuroscience of aging: linking cognitive and cerebral aging / [ed] Roberto Cabeza, Lars Nyberg, and Denise C. Park, New York: Oxford University Press, 2017, 2, p. 155-182Chapter in book (Refereed)
    Abstract [en]

    This chapter on longitudinal structural and functional brain imaging examines points of convergence and divergence in findings from neuroimaging studies using cross-sectional versus longitudinal designs. Representative longitudinal age gradients are identified. It presents key methodological issues in longitudinal imaging, including test-retest effects, the influence of attrition, and different kinds of missing data. Various ways of handling data missingness in statistical analyses are also discussed.

  • 20.
    Nyberg, Lars
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Salami, Alireza
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Andersson, Mikael
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Kalpouzos, Grégoria
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Kauppi, Karolina
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Lind, Johanna
    Center for Study of Human Cognition, Department of Psychology, University of Oslo, Norway.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Persson, Jonas
    Department of Psychology and Stockholm Brain Institute, Stockholm University, 106 91 Stockholm, Sweden .
    Nilsson, Lars-Göran
    Department of Psychology and Stockholm Brain Institute, Stockholm University, 106 91 Stockholm, Sweden .
    Longitudinal evidence for diminished frontal cortex function in aging2010In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 107, no 52, p. 22682-22686Article in journal (Refereed)
    Abstract [en]

    Cross-sectional estimates of age-related changes in brain structure and function were compared with 6-y longitudinal estimates. The results indicated increased sensitivity of the longitudinal approach as well as qualitative differences. Critically, the cross-sectional analyses were suggestive of age-related frontal overrecruitment, whereas the longitudinal analyses revealed frontal underrecruitment with advancing age. The cross-sectional observation of overrecruitment reflected a select elderly sample. However, when followed over time, this sample showed reduced frontal recruitment. These findings dispute inferences of true age changes on the basis of age differences, hence challenging some contemporary models of neurocognitive aging, and demonstrate age-related decline in frontal brain volume as well as functional response.

  • 21.
    Persson, Jonas
    et al.
    Stockholm Univ, Dept Psychol, S-10691 Stockholm, Sweden .
    Pudas, Sara
    Stockholm Univ, Dept Psychol, S-10691 Stockholm, Sweden .
    Lind, Johanna
    Stockholm Univ, Dept Psychol, S-10691 Stockholm, Sweden .
    Kauppi, Karolina
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Nilsson, Lars-Göran
    Stockholm Univ, Dept Psychol, S-10691 Stockholm, Sweden .
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Longitudinal structure-function correlates in elderly reveal MTL dysfunction with cognitive decline2012In: Cerebral Cortex, ISSN 1047-3211, E-ISSN 1460-2199, Vol. 22, no 10, p. 2297-2304Article in journal (Refereed)
    Abstract [en]

    By integrating behavioral measures and imaging data, previous investigations have explored the relationship between biological markers of aging and cognitive functions. Evidence from functional and structural neuroimaging has revealed that hippocampal volume and activation patterns in the medial temporal lobe (MTL) may predict cognitive performance in old age. Most past demonstrations of age-related differences in brain structure-function were based on cross-sectional comparisons. Here, the relationship between 6-year intraindividual change in functional magnetic resonance imaging (fMRI) signal and change in memory performance over 2 decades was examined. Correlations between intraindividual change in fMRI signal during episodic encoding and change in memory performance measured outside of scanning were used as an estimate for relating brain-behavior changes. The results revealed a positive relationship between activation change in the hippocampus (HC) and change in memory performance, reflecting reduced hippocampal activation in participants with declining performance. Using a similar analytic approach as for the functional data, we found that individuals with declining performance had reduced HC volume compared with individuals with intact performance. These observations provide a strong link between cognitive change in older adults and MTL structure and function and thus provide insights into brain correlates of individual variability in aging trajectories.

  • 22.
    Persson, Jonas
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Department of Psychology, Aging Research Center (ARC) at Karolinska Institute and Stockholm University, Stockholm, Sweden and Department of Psychology, Stockholm University, Stockholm, Sweden.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Department of Psychology, Stockholm University, Stockholm, Sweden.
    Nilsson, Lars-Göran
    Karolinska Inst, Aging Res Ctr ARC, S-11330 Stockholm, Sweden and Stockholm Univ, Dept Psychol, S-11330 Stockholm, Sweden.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Longitudinal assessment of default-mode brain function in aging2014In: Neurobiology of Aging, ISSN 0197-4580, E-ISSN 1558-1497, Vol. 35, no 9, p. 2107-2117Article in journal (Refereed)
    Abstract [en]

    Age-related changes in the default-mode network (DMN) have been identified in prior cross-sectional functional magnetic resonance imaging studies. Here, we investigated longitudinal change in DMN activity and connectivity. Cognitively intact participants (aged 49-79 years at baseline) were scanned twice, with a 6-year interval, while performing an episodic memory task interleaved with a passive control condition. Longitudinal analyses showed that the DMN (control condition > memory task) could be reliably identified at both baseline and follow-up. Differences in the magnitude of task-induced deactivation in posterior DMN regions were observed between baseline and follow-up indicating reduced deactivation in these regions with increasing age. Although no overall longitudinal changes in within-network connectivity were found across the whole sample, individual differences in memory change correlated with change in connectivity. Thus, our results show stability of whole-brain DMN topology and functional connectivity over time in healthy older adults, whereas within-region DMN analyses show reduced deactivation between baseline and follow-up. The current findings provide novel insights into DMN functioning that may assist in identifying brain changes in patient populations, as well as characterizing factors that distinguish between normal and pathologic aging.

  • 23.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Aging of memory and brain functions: usual and successful2016In: From Neuroscience to Neurospyschology: the study of the human brain. Volume II / [ed] Alexandra Isabel Dias Reis & Luis Faísca, Bogotá, Colombia: Ediciones Corporación Universitaria Reformada , 2016, 1, p. 163-192Chapter in book (Refereed)
  • 24.
    Pudas, Sara
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Josefsson, Maria
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Nordin Adolfsson, Annelie
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Landfors, Mattias
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Kauppi, Karolina
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
    Veng-Taasti, Line Marie
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Hultdin, Magnus
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Adolfsson, Rolf
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Degerman, Sofie
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology. Umeå University, Faculty of Medicine, Department of Clinical Microbiology.
    Short leukocyte telomeres, but not telomere attrition rates, predict memory decline in the 20-year longitudinal Betula study2021In: The journals of gerontology. Series A, Biological sciences and medical sciences, ISSN 1079-5006, E-ISSN 1758-535X, Vol. 76, no 6, p. 955-963Article in journal (Refereed)
    Abstract [en]

    Leukocyte telomere length (LTL) is a proposed biomarker for aging-related disorders, including cognitive decline and dementia. Long-term longitudinal studies measuring intra-individual changes in both LTL and cognitive outcomes are scarce, precluding strong conclusions about a potential aging-related relationship between LTL shortening and cognitive decline. This study investigated associations between baseline levels and longitudinal changes in LTL and memory performance across an up to 20-year follow-up in 880 dementia-free participants from a population-based study (mean baseline age: 56.8 years, range: 40–80; 52% female). Shorter baseline LTL significantly predicted subsequent memory decline (r = .34, 95% confidence interval: 0.06, 0.82), controlling for age, sex, and other relevant covariates. No significant associations were however observed between intra-individual changes in LTL and memory, neither concurrently nor with a 5-year time-lag between LTL shortening and memory decline. These results support the notion of short LTL as a predictive factor for aging-related memory decline, but suggest that LTL dynamics in adulthood and older age may be less informative of cognitive outcomes in aging. Furthermore, the results highlight the importance of long-term longitudinal evaluation of outcomes in biomarker research.

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  • 25.
    Pudas, Sara
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Josefsson, Maria
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Rieckmann, Anna
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Longitudinal evidence for increased functional response in frontal cortex for older adults with hippocampal atrophy and memory decline2018In: Cerebral Cortex, ISSN 1047-3211, E-ISSN 1460-2199, Vol. 28, no 3, p. 936-948Article in journal (Refereed)
    Abstract [en]

    The functional organization of the frontal cortex is dynamic. Age-related increases in frontal functional responses have been shown during various cognitive tasks, but the cross-sectional nature of most past studies makes it unclear whether these increases reflect reorganization or stable individual differences. Here, we followed 130 older individuals' cognitive trajectories over 20-25 years with repeated neuropsychological assessments every 5th year, and identified individuals with stable or declining episodic memory. Both groups displayed significant gray matter atrophy over 2 successive magnetic resonance imaging sessions 4 years apart, but the decline group also had a smaller volume of the right hippocampus. Only individuals with declining memory demonstrated increased prefrontal functional responses during memory encoding and retrieval over the 4-year interval. Regions with increased functional recruitment were located outside, or on the borders of core task-related networks, indicating an expansion of these over time. These longitudinal findings offer novel insight into the mechanisms behind age-associated memory loss, and are consistent with a theoretical model in which hippocampus atrophy, past a critical threshold, induces episodic-memory decline and altered prefrontal functional organization.

  • 26.
    Pudas, Sara
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Persson, Jonas
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Josefsson, Maria
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Nilsson, Lars-Göran
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Brain Characteristics of Individuals Resisting Age-Related Cognitive Decline over Two Decades2013In: Journal of Neuroscience, ISSN 0270-6474, E-ISSN 1529-2401, Vol. 33, no 20, p. 8668-8677Article in journal (Refereed)
    Abstract [en]

    Some elderly appear to resist age-related decline in cognitive functions, but the neural correlates of successful cognitive aging are not well known. Here, older human participants from a longitudinal study were classified as successful or average relative to the mean attrition-corrected cognitive development across 15-20 years in a population-based sample (n = 1561). Fifty-one successful elderly and 51 age-matched average elderly (mean age: 68.8 years) underwent functional magnetic resonance imaging while performing an episodic memory face-name paired-associates task. Successful older participants had higher BOLD signal during encoding than average participants, notably in the bilateral PFC and the left hippocampus (HC). The HC activation of the average, but not the successful, older group was lower than that of a young reference group (n = 45, mean age: 35.3 years). HC activation was correlated with task performance, thus likely contributing to the superior memory performance of successful older participants. The frontal BOLD response pattern might reflect individual differences present from young age. Additional analyses confirmed that both the initial cognitive level and the slope of cognitive change across the longitudinal measurement period contributed to the observed group differences in BOLD signal. Further, the differences between the older groups could not be accounted for by differences in brain structure. The current results suggest that one mechanism behind successful cognitive aging might be preservation of HC function combined with a high frontal responsivity. These findings highlight sources for heterogeneity in cognitive aging and may hold useful information for cognitive intervention studies.

  • 27.
    Pudas, Sara
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Persson, Jonas
    Nilsson, Lars-Göran
    Nyberg, Lars
    Maintenance and Manipulation in Working Memory: Differential Ventral and Dorsal Frontal Cortex fMRI Activity2009In: Acta Psychologica Sinica, Vol. 41, no 11, p. 1054-1062Article in journal (Other academic)
  • 28.
    Pudas, Sara
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Department of Psychology, Stockholm University, Stockholm.
    Persson, Jonas
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Department of Psychology, Stockholm University, Aging Research Center, Karolinska Institute and Stockholm University, Stockholm.
    Nilsson, Lars-Göran
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Aging Research Center, Karolinska Institute and Stockholm University, Stockholm.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Midlife memory ability accounts for brain activity differences in healthy aging2014In: Neurobiology of Aging, ISSN 0197-4580, E-ISSN 1558-1497, Vol. 35, no 11, p. 2495-2503Article in journal (Refereed)
    Abstract [en]

    Cross-sectional neuroimaging studies suggest that hippocampal and prefrontal cortex functions underlie individual differences in memory ability in older individuals, but it is unclear how individual differences in cognitive ability in youth contribute to cognitive and neuroimaging measures in older age. Here, we investigated the relative influences of midlife memory ability and age-related memory change on memory-related BOLD-signal variability at one time point, using a sample from a longitudinal population-based aging study (N = 203, aged 55-80 years). Hierarchical regression analyses showed that midlife memory ability, assessed 15-20 years earlier, explained at least as much variance as memory change in clusters in the left inferior prefrontal cortex and the bilateral hippocampus, during memory encoding. Furthermore, memory change estimates demonstrated higher sensitivity than current memory levels in identifying distinct frontal regions where activity was selectively related to age-related memory change, as opposed to midlife memory. These findings highlight challenges in interpreting individual differences in neurocognitive measures as age-related changes in the absence of longitudinal data and also demonstrate the improved sensitivity of longitudinal measures.

  • 29.
    Pudas, Sara
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Rönnlund, Michael
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    School Performance and Educational Attainment as Early-Life Predictors of Age-Related Memory Decline: Protective Influences in Later-Born Cohorts2019In: The journals of gerontolog