APOE‐dependent and ‐independent polygenic pathways determining early Alzheimer’s Disease pathological changes in CSF and MRI
Luigi Lorenzini, Lyduine E. Collij, Niccoló Tesi, Silvia Ingala, Carole H Sudre, Robin Wolz, Sven Haller, Kaj Blennow, Giovanni B Frisoni, Pierre Payoux, Pablo Martinez‐Lage, Michael Ewers, Gael Chetelat, Craig W Ritchie, Juan Domingo Gispert, Henk‐Jan Mutsaerts, Andre Altmann, Betty M. Tijms, Alle Meije Wink, Pieter Jelle Visser, Frederik Barkhof- Psychiatry and Mental health
- Cellular and Molecular Neuroscience
- Geriatrics and Gerontology
- Neurology (clinical)
- Developmental Neuroscience
- Health Policy
- Epidemiology
Abstract
Background
Little is known about the genetic factors and downstream molecular pathways determining individual variability in fluid and imaging biomarkers associated with Alzheimer’s disease(AD). We studied polygenic risk scores (PRS) and pathway‐specific PRS in relationship with AD fluid and imaging biomarkers, in non‐demented individuals from the European Prevention of Alzheimer’s Dementia (EPAD) cohort.
Method
EPAD inclusion criteria were age>50 and Clinical Dementia Rating = 0.5 (n = 1886, Table 1). AD‐PRS was based on 85 previously identified loci, including and excluding APOE (PRSAPOE, PRSnoAPOE)[1]. Using gene‐variant and variant‐pathway mapping[2], six pathway‐specific PRSnoAPOE were identified:1) immune‐activation, 2) signal‐transduction, 3) inflammatory‐response, 4) migration, 5) amyloid‐production, and 6) clearance. Linear models were used to assess the relationship of all PRS with fluid AD biomarkers, including Aß1‐42, p‐Tau181, and t‐tau; and several imaging biomarkers, including hippocampal volume, global and lobar white matter hyperintensities (WMH) volumes, fractional anisotropy (FA) in 14 regions of interest from diffusion tensor imaging, and 10 resting‐state network connectivity from functional MRI. Models were adjusted for age, sex, site, and multiple comparisons.
Result
Models’ coefficients are reported in Table 2. PRSAPOE was significantly associated with decreased Aß1‐42, and increased p‐Tau181 and t‐Tau. PRSnoAPOE showed a weaker, but still significant, negative association with Aß1‐42 levels, and a significant positive association with p‐Tau181 and t‐Tau. Aß1‐42 was only significantly associated with the migration, amyloid, and clearance pathways, while all pathways were significantly positively associated with p‐Tau181 and t‐Tau. Hippocampal volume was only significantly associated with PRSAPOE. Regarding WMH load, PRSAPOE showed a positive association with global, frontal periventricular, and parietal deep lobes. Furthermore, the clearance pathway was related to WMH load in all regions, most strongly in periventricular areas. Only the migration pathway was related to increases in FA in the splenium, body, and genu of the corpus callosum. Only the PRSAPOE was related to reduced functional connectivity (FC) in the default mode, control, and visual networks.
Conclusion
We show that genetic risk beyond APOE facilitates the manifestation of AD related pathologies. Moreover, clearance and migration pathways were associated with neuroimaging measures of white matter integrity, while FC and hippocampal volume were associated with overall AD genetic risk.