Brain change trajectories in healthy adults correlate with Alzheimer’s related genetic variation and memory decline across life

Alzheimer’s Disease Neuroimaging Initiative; the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing

doi:10.1038/s41467-024-53548-z

Brain change trajectories in healthy adults correlate with Alzheimer’s related genetic variation and memory decline across life

Alzheimer’s Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing

Lübecker Interdisziplinäre Plattform für Genomanalytik

12 Zitate (Scopus)

Abstract

Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer’s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer’s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.

Originalsprache	Englisch
Aufsatznummer	10651
Zeitschrift	Nature Communications
Jahrgang	15
Ausgabenummer	1
ISSN	1751-8628
DOIs	https://doi.org/10.1038/s41467-024-53548-z
Publikationsstatus	Veröffentlicht - 12.2024

Fördermittel

Scripts were run on the Colossus processing cluster at the University of Oslo, and on resources provided by UNINETT Sigma2 (project NN9769K). LCBC funding: grant 302854 (FRIPRO; to Y.W.), European Research Council under grants 283634, 725025 (to A.M.F.), and 313440 (to K.B.W.); Norwegian Research Council (to A.M.F. and K.B.W.) under grants 249931 (TOPPFORSK) and, The National Association for Public Health’s dementia research program, Norway (to A.M.F). The Lifebrain project is funded by the EU Horizon 2020 Grant: “Healthy minds 0–100 years: Optimising the use of European brain imaging cohorts (Lifebrain).” Grant agreement number: 732592. The Betula project was supported by a Scholar grant from Knut and Alice Wallenberg’s (KAW) foundation to L.N. The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (ZonMw, grant number 10-000‐1002) and financial contributions by participating universities and mental health care organizations (VU University Medical Center, GGZ inGeest, Leiden University Medical Center, Leiden University, GGZ Rivierduinen, University Medical Center Groningen, University of Groningen, Lentis, GGZ Friesland, GGZ Drenthe, Rob Giel Onderzoekscentrum). Some of the data used in the preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; 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 is 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 Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. ADNI investigators contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. Some of the data used in the preparation of this article were obtained from the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing (AIBL) funded by the Commonwealth Scientific and Industrial Research Organisation (CSIRO), which was made available at the ADNI database (www.loni.usc.edu/ADNI). AIBL investigators contributed to the design and implementation of AIBL and/or provided data but did not participate in analysis or writing of this report. Scripts were run on the Colossus processing cluster at the University of Oslo, and on resources provided by UNINETT Sigma2 (project NN9769K). LCBC funding: grant 302854 (FRIPRO; to Y.W.), European Research Council under grants 283634, 725025 (to A.M.F.), and 313440 (to K.B.W.); Norwegian Research Council (to A.M.F. and K.B.W.) under grants 249931 (TOPPFORSK) and, The National Association for Public Health’s dementia research program, Norway (to A.M.F). The Lifebrain project is funded by the EU Horizon 2020 Grant: “Healthy minds 0–100 years: Optimising the use of European brain imaging cohorts (Lifebrain).” Grant agreement number: 732592. The Betula project was supported by a Scholar grant from Knut and Alice Wallenberg’s (KAW) foundation to L.N. The infrastructure for the NESDA study ( www.nesda.nl ) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (ZonMw, grant number 10-000‐1002) and financial contributions by participating universities and mental health care organizations (VU University Medical Center, GGZ inGeest, Leiden University Medical Center, Leiden University, GGZ Rivierduinen, University Medical Center Groningen, University of Groningen, Lentis, GGZ Friesland, GGZ Drenthe, Rob Giel Onderzoekscentrum). Some of the data used in the preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; 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 is 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 Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. ADNI investigators contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf . Some of the data used in the preparation of this article were obtained from the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing (AIBL) funded by the Commonwealth Scientific and Industrial Research Organisation (CSIRO), which was made available at the ADNI database ( www.loni.usc.edu/ADNI ). AIBL investigators contributed to the design and implementation of AIBL and/or provided data but did not participate in analysis or writing of this report.

Träger	Trägernummer
Northern California Institute for Research and Education
Knut och Alice Wallenbergs Stiftelse
National Institute of Biomedical Imaging and Bioengineering
Rijksuniversiteit Groningen
Commonwealth Scientific and Industrial Research Organisation
Alzheimer's Disease Neuroimaging Initiative
National Institute on Aging
National Institutes of Health	U01 AG024904
Norges Forskningsråd	249931
European Research Council	283634, 725025, 313440
Horizon 2020	732592
ZonMw	10-000‐1002
UNINETT Sigma2	302854
U.S. Department of Defense	W81XWH-12-2-0012

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 3 – Gesundheit und Wohlergehen

Strategische Forschungsbereiche und Zentren

Forschungsschwerpunkt: Gehirn, Hormone, Verhalten - Center for Brain, Behavior and Metabolism (CBBM)
Querschnittsbereich: Medizinische Genetik

DFG-Fachsystematik

2.23-06 Molekulare und zelluläre Neurologie und Neuropathologie

Dokumente

10.1038/s41467-024-53548-z

Weitere Links

Link to publication in Scopus

Lifebrain
Bertram, L. (Projektleiter*in (PI))
01.01.16 → 31.12.21
Projekt: Internationale Projekte › EU Konsortialforschung

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title = "Brain change trajectories in healthy adults correlate with Alzheimer{\textquoteright}s related genetic variation and memory decline across life",

abstract = "Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer{\textquoteright}s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer{\textquoteright}s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age \textasciitilde{}50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.",

author = "\{Alzheimer{\textquoteright}s Disease Neuroimaging Initiative\} and \{the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing\} and Roe, \{James M.\} and Didac Vidal-Pi{\~n}eiro and {\O}ystein S{\o}rensen and H{\aa}kon Grydeland and Leonardsen, \{Esten H.\} and Olena Iakunchykova and Mengyu Pan and Athanasia Mowinckel and Marie Str{\o}mstad and Laura Nawijn and Yuri Milaneschi and Micael Andersson and Sara Pudas and Br{\aa}then, \{Anne Cecilie Sj{\o}li\} and Jonas Kransberg and Falch, \{Emilie Sogn\} and Knut {\O}verbye and Kievit, \{Rogier A.\} and Ebmeier, \{Klaus P.\} and Ulman Lindenberger and Paolo Ghisletta and Naiara Demnitz and Boraxbekk, \{Carl Johan\} and Drevon, \{Christian A.\} and Ronald Petersen and Paul Aisen and Michael Weiner and Rowe, \{Christopher C.\} and Masters, \{Colin L.\} and Brenda Penninx and Lars Bertram and Lars Nyberg and Walhovd, \{Kristine B.\} and Fjell, \{Anders M.\} and Yunpeng Wang",

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doi = "10.1038/s41467-024-53548-z",

language = "English",

volume = "15",

journal = "Nature Communications",

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Brain change trajectories in healthy adults correlate with Alzheimer’s related genetic variation and memory decline across life. / Alzheimer’s Disease Neuroimaging Initiative; the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing.
in: Nature Communications, Jahrgang 15, Nr. 1, 10651, 12.2024.

Publikation: Beiträge in Fachzeitschriften › Zeitschriftenaufsätze › Forschung › Begutachtung

TY - JOUR

T1 - Brain change trajectories in healthy adults correlate with Alzheimer’s related genetic variation and memory decline across life

AU - Alzheimer’s Disease Neuroimaging Initiative

AU - the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing

AU - Roe, James M.

AU - Vidal-Piñeiro, Didac

AU - Sørensen, Øystein

AU - Grydeland, Håkon

AU - Leonardsen, Esten H.

AU - Iakunchykova, Olena

AU - Pan, Mengyu

AU - Mowinckel, Athanasia

AU - Strømstad, Marie

AU - Nawijn, Laura

AU - Milaneschi, Yuri

AU - Andersson, Micael

AU - Pudas, Sara

AU - Bråthen, Anne Cecilie Sjøli

AU - Kransberg, Jonas

AU - Falch, Emilie Sogn

AU - Øverbye, Knut

AU - Kievit, Rogier A.

AU - Ebmeier, Klaus P.

AU - Lindenberger, Ulman

AU - Ghisletta, Paolo

AU - Demnitz, Naiara

AU - Boraxbekk, Carl Johan

AU - Drevon, Christian A.

AU - Petersen, Ronald

AU - Aisen, Paul

AU - Weiner, Michael

AU - Rowe, Christopher C.

AU - Masters, Colin L.

AU - Penninx, Brenda

AU - Bertram, Lars

AU - Nyberg, Lars

AU - Walhovd, Kristine B.

AU - Fjell, Anders M.

AU - Wang, Yunpeng

PY - 2024/12

Y1 - 2024/12

N2 - Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer’s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer’s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.

AB - Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer’s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer’s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.

UR - https://www.scopus.com/pages/publications/85212711594

U2 - 10.1038/s41467-024-53548-z

DO - 10.1038/s41467-024-53548-z

M3 - Journal articles

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SN - 1751-8628

VL - 15

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 10651

ER -

Brain change trajectories in healthy adults correlate with Alzheimer’s related genetic variation and memory decline across life

Abstract

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