DOI: 10.1002/alz.081795 ISSN: 1552-5260

Brain‐age prediction and its associations with glial and synaptic CSF markers

Irene Cumplido‐Mayoral, Marta Milà‐Alomà, Carles Falcon, Raffaele Cacciaglia, Carolina Minguillon, Karine Fauria, Jose Luis Molinuevo, Gwendlyn Kollmorgen, Ivonne Suridjan, Norbert Wild, Henrik Zetterberg, Kaj Blennow, Marc Suarez‐Calvet, Verónica Vilaplana, Juan Domingo Gispert
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience
  • Geriatrics and Gerontology
  • Neurology (clinical)
  • Developmental Neuroscience
  • Health Policy
  • Epidemiology

Abstract

Background

MRI‐derived brain‐age prediction is a promising biomarker of biological brain aging. Accelerated brain aging has been found in Alzheimer’s disease (AD) and other neurodegenerative diseases. However, no previous studies have investigated the relationship between specific pathophysiological pathways in AD and biological brain aging. Here, we studied whether glial activation and synaptic dysfunction are associated with biological brain aging in the earliest stages of the Alzheimer’s continuum.

Method

We included 418 cognitively unimpaired individuals (CU) from the ALFA+ study with available structural MRI, and CSF biomarkers of amyloid‐ß (Aß42/40) and tau pathology (p‐tau181), synaptic dysfunction (neurogranin, GAP43, SYT1, SNAP25), glial activation (sTREM2, YKL40, GFAP, interleukin‐6 and S100b) and a‐synuclein (Table 1). Aß42/40, neurogranin and the glial activation biomarkers were measured using the Roche NeuroToolKit. We computed brain‐age delta as the difference between chronological and predicted brain‐age. The latter was estimated using a previously pretrained machine learning algorithm on cerebral morphological measurements on individuals from the UKBioBank cohort (N = 22.000). General linear modeling was used to test the associations between CSF biomarkers and brain‐age delta, adjusting by p‐tau, age, APOE status and sex. For the biomarkers whose associations were significant, we evaluated the interaction term “biomarker” × AT status while adjusting by age, APOE status and sex. AT staging was performed using pre‐established cut‐off values. We then used hippocampal volume as a marker of AD‐related neurodegeneration and repeated the same association studies with CSF biomarkers, adjusting by p‐tau, age, APOE status, sex and TIV.

Result

Brain‐age delta was negatively associated with CSF sTREM2 (Padjusted<0.001), meaning that younger‐appearing brains showed higher levels of this biomarker (Table 1). None of the other biomarkers survived multiple comparisons. Hippocampal volume was not significantly associated with any of the CSF biomarkers (Table 2). There was no significant interaction between AT status and CSF sTREM2 for brain‐age delta, nor for hippocampal volume.

Conclusion

These results showed that higher levels of CSF sTREM2 were associated with younger‐appearing brains in CU individuals independently of AT status, which might indicate a protective effect of this microglial phenotype in brain aging. This effect might not be AD‐related.

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