Longitudinal associations between exercise and biomarkers in autosomal dominant Alzheimer's disease

Kelsey R Sewell¹, James D Doecke², Chengjie Xiong³, Tammie Benzinger³, Colin L Masters⁴, Christoph Laske^{5

6}, Mathias Jucker^{5

6}, Francisco Lopera⁷, Brian A Gordon³, Jorge Llibre-Guerra³, Johannes Levin^{8

9

10}, Edward D Huey¹¹, Jason Hassenstab^{12

13}, Peter R Schofield^{14

15}, Gregory S Day¹⁶, Nick C Fox¹⁷, Jasmeer Chhatwal¹⁸, Laura Ibanez³, Jee Hoon Roh^{19

20}, Richard Perrin³, Jae-Hong Lee²¹, Ricardo F Allegri²², Charlene Supnet-Bell³, Sarah B Berman²³, Alisha Daniels¹³, James Noble²⁴, Ralph N Martins^{1

25

26

27}, Stephanie Rainey-Smith^{1

25

26}, Jeremiah Peiffer¹, Samantha L Gardener^{25

26}, Randall J Bateman³, John C Morris³, Eric McDade³, Kirk I Erickson²⁸, Hamid R Sohrabi^{1

25

26

27}, Belinda M Brown^{1

25

26

29}; Dominantly Inherited Alzheimer's Network

Affiliations

¹ Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, Western Australia, Australia.
² Australian E-Health Research Centre, CSIRO, Herston, Queensland, Australia.
³ Washington University in St. Louis, St. Louis, Missouri, USA.
⁴ The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.
⁵ German Center for Neurodegenerative Diseases, Tubingen, Germany.
⁶ Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
⁷ Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia.
⁸ Department of Neurology, LMU University Hospital, LMU, Munich, Germany.
⁹ German Center for Neurodegenerative Diseases, Site Munich, Munich, Germany.
¹⁰ Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
¹¹ Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
¹² Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, Missouri, USA.
¹³ Department of Neurology, Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA.
¹⁴ Neuroscience Research Australia, Sydney, New South Wales, Australia.
¹⁵ School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia.
¹⁶ Department of Neurology, Mayo Clinic Florida, Jacksonville, Florida, USA.
¹⁷ Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
¹⁸ Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
¹⁹ Department of Neurology, Korea University Anam Hospital, Seoul, South Korea.
²⁰ Department of Physiology, Korea University College of Medicine, Seoul, South Korea.
²¹ Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
²² Cognitive Neurology Service of the FLENI Foundation, Foundation for Childhood Neurological Disorders, Cognitive Neurology, Neuropsychology and Neuropsychiatry Section (CONICET-FLENI), Buenos Aires, Argentina.
²³ Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
²⁴ Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA.
²⁵ Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.
²⁶ Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, Western Australia, Australia.
²⁷ Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales, Australia.
²⁸ AdventHealth Research Institute, Neuroscience, Orlando, Florida, USA.
²⁹ Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia.

PMID: 39324510
PMCID: PMC11567864
DOI: 10.1002/alz.14270

Longitudinal associations between exercise and biomarkers in autosomal dominant Alzheimer's disease

Kelsey R Sewell et al. Alzheimers Dement. 2024 Nov.

. 2024 Nov;20(11):7923-7939.

doi: 10.1002/alz.14270. Epub 2024 Sep 26.

Authors

Affiliations

¹ Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, Western Australia, Australia.
² Australian E-Health Research Centre, CSIRO, Herston, Queensland, Australia.
³ Washington University in St. Louis, St. Louis, Missouri, USA.
⁴ The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.
⁵ German Center for Neurodegenerative Diseases, Tubingen, Germany.
⁶ Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
⁷ Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia.
⁸ Department of Neurology, LMU University Hospital, LMU, Munich, Germany.
⁹ German Center for Neurodegenerative Diseases, Site Munich, Munich, Germany.
¹⁰ Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
¹¹ Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
¹² Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, Missouri, USA.
¹³ Department of Neurology, Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA.
¹⁴ Neuroscience Research Australia, Sydney, New South Wales, Australia.
¹⁵ School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia.
¹⁶ Department of Neurology, Mayo Clinic Florida, Jacksonville, Florida, USA.
¹⁷ Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
¹⁸ Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
¹⁹ Department of Neurology, Korea University Anam Hospital, Seoul, South Korea.
²⁰ Department of Physiology, Korea University College of Medicine, Seoul, South Korea.
²¹ Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
²² Cognitive Neurology Service of the FLENI Foundation, Foundation for Childhood Neurological Disorders, Cognitive Neurology, Neuropsychology and Neuropsychiatry Section (CONICET-FLENI), Buenos Aires, Argentina.
²³ Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
²⁴ Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA.
²⁵ Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.
²⁶ Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, Western Australia, Australia.
²⁷ Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales, Australia.
²⁸ AdventHealth Research Institute, Neuroscience, Orlando, Florida, USA.
²⁹ Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia.

PMID: 39324510
PMCID: PMC11567864
DOI: 10.1002/alz.14270

Abstract

Introduction: We investigated longitudinal associations between self-reported exercise and Alzheimer's disease (AD)-related biomarkers in individuals with autosomal dominant AD (ADAD) mutations.

Methods: Participants were 308 ADAD mutation carriers aged 39.7 ± 10.8 years from the Dominantly Inherited Alzheimer's Network. Weekly exercise volume was measured via questionnaire and associations with brain volume (magnetic resonance imaging), cerebrospinal fluid biomarkers, and brain amyloid beta (Aβ) measured by positron emission tomography were investigated.

Results: Greater volume of weekly exercise at baseline was associated with slower accumulation of brain Aβ at preclinical disease stages β = -0.16 [-0.23 to -0.08], and a slower decline in multiple brain regions including hippocampal volume β = 0.06 [0.03 to 0.08].

Discussion: Exercise is associated with more favorable profiles of AD-related biomarkers in individuals with ADAD mutations. Exercise may have therapeutic potential for delaying the onset of AD; however, randomized controlled trials are vital to determine a causal relationship before a clinical recommendation of exercise is implemented.

Highlights: Greater self-reported weekly exercise predicts slower declines in brain volume in autosomal dominant Alzheimer's disease (ADAD). Greater self-reported weekly exercise predicts slower accumulation of brain amyloid beta in ADAD. Associations varied depending on closeness to estimated symptom onset.

Keywords: Alzheimer's disease; exercise; magnetic resonance imaging; physical activity; positron emission tomography.

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Conflict of interest statement

R.J.B. reports grants from Eli Lilly, Roche, Pharma Consortium (AbbVie, AstraZeneca, Biogen, Eisai, Eli Lilly and Company, Hoffmann La‐Roche Inc, Janssen, Pfizer, Sanofi‐Aventis), and Tau SILK/PET Consortium (Biogen/AbbVie/Lilly); non‐financial support from Avid Radiopharmaceuticals; personal fees and other from Washington University, outside the submitted work. J.C.M. is currently participating in clinical trials of antidementia drugs from Eli Lilly and Company, Biogen, and Janssen. J.C.M. serves as a consultant for Lilly USA and receives research support from Eli Lilly/Avid Radiopharmaceuticals. T.B. receives grant funding from Avid Radiopharmaceuticals/Eli Lilly and participates in clinical trials sponsored by Eli Lilly, Avid Radiopharmaceuticals, Roche, and Pfizer. F.L. holds grants from NIH, NIA, Alzheimer Association, DIAN, Tau‐Consortium, Large PD, Biogen, and Roche. J.L. reports speaker fees from Bayer Vital, Biogen, EISAI, TEVA, Zambon, Merck, and Roche; consulting fees from Axon Neuroscience, EISAI, and Biogen; author fees from Thieme medical publishers and W. Kohlhammer GmbH medical publishers; and is an inventor in a patent “Oral Phenylbutyrate for Treatment of Human 4‐Repeat Tauopathies” (EP 23 156 122.6) filed by LMU Munich. In addition, J.L. reports compensation for serving as chief medical officer for MODAG GmbH, is beneficiary of the phantom share program of MODAG GmbH, and is an inventor in a patent “Pharmaceutical Composition and Methods of Use” (EP 22 159 408.8) filed by MODAG GmbH, all activities outside the submitted work. R.J.P.’s laboratory receives cost recovery funding from Biogen for tissue procurement and processing services related to ALS clinical trials, outside the submitted work. All other authors have declared no conflicts of interest. Author disclosures are available in the supporting information.

Figures

**FIGURE 1**
Flow diagram indicating number of participants with data available for inclusion for each analysis. Timepoints refer to number of visits at which both exercise and biomarker data were collected. *APP*, amyloid precursor protein; CDR, Clinical Dementia Rating; CSF, cerebrospinal fluid; DIAN, Dominantly Inherited Alzheimer Network; EYO, estimated years from expected symptom onset; MRI, magnetic resonance imaging; PiB PET, Pittsburgh compound B positron emission tomography; SD, standard deviation

**FIGURE 2**
Baseline exercise x time interaction on structural brain outcomes at baseline EYO. Baseline EYO was treated as a continuous variable in all models and is only separated here for visual aid (i.e., EYO groups were not created); a negative EYO represents years before estimated symptom onset, positive EYO represents years post estimated symptom onset. The data presented here are fitted values from analyses modeling associations between exercise and brain outcomes given a particular EYO. Scatterplots of raw data are presented in Figure S4 in supporting information. The left‐hand panel shows the fitted values for change in brain volume over time if EYO is −15, the middle demonstrates the association if EYO is 0, and the right shows this association if EYO is 5. Gray bands show 95% confidence intervals. A, Right hippocampal volume. B, Total gray matter volume. EYO, estimated years from expected symptom onset; SD, standard deviation

**FIGURE 3**
Association between change in exercise and change in right hippocampal volume over time. Exercise categories were created based on a 365 minutes/week cut off and classified as: 1 = “decreasers,” 2 = “stable low,” 3 = “stable high,” 4 = “increasers,” based on follow‐up data. Differences exist between “decreasers” versus “stable high category,” β = 0.13, SE = 0.05, P = .006 and “stable low”’ versus “stable high” category, β = 0.11, SE = 0.04, P = = 0.006. Gray bands represent 95% confidence intervals. EYO, estimated years from expected symptom onset; SE, standard error

**FIGURE 4**
Change in exercise on structural brain outcomes over time and across EYO. Exercise categories were created based on a 365 minute/week cut off and classified as: 1 = “decreasers,” 2 = “stable low,” 3 = “stable high,” 4 = “increasers,” based on follow‐up data. EYO was treated as a continuous variable in all models and is only separated here for visual aid. Gray bands represent 95% confidence intervals. Total cortical volume, differences exist between decreasers versus stable high category, β = 0.08, SE = 0.04, P = .028; and decreasers versus increasers, β = 0.08, SE = 0.04, P = .041. Total gray matter volume, a trend exists for differences between decreasers versus stable high: β = 0.06, SE = 0.03, P = .065, and decreasers versus increasers: β = 0.07, SE = 0.04, P = .060. EYO, estimated years to symptom onset; SE, standard error

**FIGURE 5**
Baseline exercise x time on brain Aβ (log) in subsets of EYO stages (i.e., EYO groups were created). Data were subset based on EYO because of a non‐linear association between EYO and brain Aβ (Figure S2 in supporting information). The left panel demonstrates the change in Aβ over time separated by exercise level within the pre‐onset group (n = 80), the middle panel demonstrates change over time in those nearing EYO (n = 109), the right panel demonstrates those post EYO (n = 94). Gray bands represent 95% confidence intervals. Aβ, amyloid beta; EYO, estimated years from expected symptom onset; SD, standard deviation

See this image and copyright information in PMC

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Longitudinal associations between exercise and biomarkers in autosomal dominant Alzheimer's disease

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Longitudinal associations between exercise and biomarkers in autosomal dominant Alzheimer's disease

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Conflict of interest statement

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