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Prediction of cognitive decline in healthy aging based on neuropsychiatric symptoms and PET-biomarkers of Alzheimer's disease

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Abstract

Neuropsychiatric symptoms (NPS) have been associated with a risk of accelerated cognitive decline or conversion to dementia of the Alzheimer’s Disease (AD) type. Moreover, the NPS were also associated with higher AD biomarkers (brain tau and amyloid burden) even in non-demented patients. But the effect of the relationship between NPS and biomarkers on cognitive decline has not yet been studied. This work aims to assess the relationship between longitudinal cognitive changes and NPS, specifically depression and anxiety, in association with AD biomarkers in healthy middle-aged to older participants. The cohort consisted of 101 healthy participants aged 50–70 years, 66 of whom had neuropsychological assessments of memory, executive functions, and global cognition at a 2-year follow-up. At baseline, NPS were assessed using the Beck Depression and Anxiety Inventories while brain tau and amyloid loads were measured using positron emission topography. For tau burden, THK5351 uptake is used as a proxy of tau and neuroinflammation. Participants, declining or remaining stable at follow-up, were categorized into groups for each cognitive domain. Group classification was investigated using binary logistic regressions based on combined AD biomarkers and the two NPS. The results showed that an association between anxiety and prefrontal amyloid burden significantly classified episodic memory decline, while the classification of global cognitive decline involved temporal and occipital amyloid burden but not NPS. Moreover, depression together with prefrontal and hippocampal tau burden were associated with a decline in memory. The classification of participants based on executive decline was related to depression and mainly prefrontal tau burden. These findings suggest that the combination of NPS and brain biomarkers of AD predicts the occurrence of cognitive decline in aging.

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Data availability

The data that support the findings of this study are not publicly available due to privacy or ethical restrictions but are available upon reasonable request.

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Funding

For this project, Lucas Ronat received a grant from the MITACS Globalink program. This work was supported by the Fonds National de la Recherche Scientifique (CS is a research associate, CB and GV are senior research associates, and FC and CP are research directors at the FRS-FNRS) and by the Wallonia-Brussels Federation (Concerted Research Actions – grant 17/21-09 SLEEPDEM).

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Authors and Affiliations

  1. Faculty of Medicine, Department of Medicine, University of Montreal, Montreal, QC, Canada

    Lucas Ronat

  2. Research Centre, University Institute of Geriatrics of Montreal, CIUSSS du Centre-Sud-de-l’Ile-de-Montréal, Montreal, QC, Canada

    Lucas Ronat & Alexandru Hanganu

  3. GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, 4000, Liège, Belgium

    Lucas Ronat, Daphné Chylinski, Maxime Van Egroo, Justinas Narbutas, Gabriel Besson, Vincenzo Muto, Christina Schmidt, Mohamed Ali Bahri, Christophe Phillips, Eric Salmon, Pierre Maquet, Gilles Vandewalle, Fabienne Collette & Christine Bastin

  4. Faculty of Arts and Sciences, Department of Psychology, University of Montreal, Montreal, QC, Canada

    Alexandru Hanganu

  5. Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liege, 4000, Liege, Belgium

    Justinas Narbutas, Christina Schmidt, Eric Salmon, Fabienne Collette & Christine Bastin

  6. Department of Neurology, CHU Liege, 4000, Liege, Belgium

    Eric Salmon & Pierre Maquet

  7. F.R.S.-Fonds National de la Recherche Scientifique, Brussels, Belgium

    Gilles Vandewalle, Fabienne Collette & Christine Bastin

  8. Bât. B30 GIGA CRC In Vivo Imaging - Aging and Memory, Quartier Agora, Allée du 6 Août 8, 4000, Liege, Belgium

    Christine Bastin

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  1. Lucas Ronat
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  2. Alexandru Hanganu
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  3. Daphné Chylinski
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  4. Maxime Van Egroo
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  5. Justinas Narbutas
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  6. Gabriel Besson
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  7. Vincenzo Muto
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  8. Christina Schmidt
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  9. Mohamed Ali Bahri
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  10. Christophe Phillips
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  11. Eric Salmon
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  13. Gilles Vandewalle
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  14. Fabienne Collette
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  15. Christine Bastin
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Contributions

Conceptualization: LR, CB, GV, FC, AH; methodology: LR, CB, AH; data acquisition and process: JN, MVE, DC, GB, VM, CS, MAB, CP, ES, PM, GV, FC and CB; formal analysis and investigation: LR; writing—original draft preparation: LR; writing—review and editing: all authors; funding acquisition: LR, CS, CB, GV, FC, CP; supervision: CB, AH.

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Correspondence to Christine Bastin.

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Ronat, L., Hanganu, A., Chylinski, D. et al. Prediction of cognitive decline in healthy aging based on neuropsychiatric symptoms and PET-biomarkers of Alzheimer's disease. J Neurol 271, 2067–2077 (2024). https://doi.org/10.1007/s00415-023-12131-0

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