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[Preprint]. 2023 Nov 30:2023.11.28.23298693.
doi: 10.1101/2023.11.28.23298693.

Cerebrovascular disease drives Alzheimer plasma biomarker concentrations in adults with Down syndrome

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Cerebrovascular disease drives Alzheimer plasma biomarker concentrations in adults with Down syndrome

Natalie C Edwards et al. medRxiv. .

Update in

  • Cerebrovascular disease is associated with Alzheimer's plasma biomarker concentrations in adults with Down syndrome.
    Edwards NC, Lao PJ, Alshikho MJ, Ericsson OM, Rizvi B, Petersen ME, O'Bryant S, Aguilar LF, Simoes S, Mapstone M, Tudorascu DL, Janelidze S, Hansson O, Handen BL, Christian BT, Lee JH, Lai F, Rosas HD, Zaman S, Lott IT, Yassa MA; Alzheimer’s Biomarkers Consortium–Down Syndrome (ABC-DS) Investigators; Gutierrez J, Wilcock DM, Head E, Brickman AM. Edwards NC, et al. Brain Commun. 2024 Sep 25;6(5):fcae331. doi: 10.1093/braincomms/fcae331. eCollection 2024. Brain Commun. 2024. PMID: 39403075 Free PMC article.

Abstract

Importance: By age 40 years over 90% of adults with Down syndrome (DS) have Alzheimer's disease (AD) pathology and most progress to dementia. Despite having few systemic vascular risk factors, individuals with DS have elevated cerebrovascular disease (CVD) markers that track with the clinical progression of AD, suggesting a role for CVD that is hypothesized to be mediated by inflammatory factors.

Objective: To examine the pathways through which small vessel CVD contributes to AD-related pathophysiology and neurodegeneration in adults with DS.

Design: Cross sectional analysis of neuroimaging, plasma, and clinical data.

Setting: Participants were enrolled in Alzheimer's Biomarker Consortium - Down Syndrome (ABC-DS), a multisite study of AD in adults with DS.

Participants: One hundred eighty-five participants (mean [SD] age=45.2 [9.3] years) with available MRI and plasma biomarker data were included. White matter hyperintensity (WMH) volumes were derived from T2-weighted FLAIR MRI scans and plasma biomarker concentrations of amyloid beta (Aβ42/Aβ40), phosphorylated tau (p-tau217), astrocytosis (glial fibrillary acidic protein, GFAP), and neurodegeneration (neurofilament light chain, NfL) were measured with ultrasensitive immunoassays.

Main outcomes and measures: We examined the bivariate relationships of WMH, Aβ42/Aβ40, p-tau217, and GFAP with age-residualized NfL across AD diagnostic groups. A series of mediation and path analyses examined causal pathways linking WMH and AD pathophysiology to promote neurodegeneration in the total sample and groups stratified by clinical diagnosis.

Results: There was a direct and indirect bidirectional effect through GFAP of WMH on p-tau217 concentration, which was associated with NfL concentration in the entire sample. Among cognitively stable participants, WMH was directly and indirectly, through GFAP, associated with p-tau217 concentration, and in those with MCI, there was a direct effect of WMH on p-tau217 and NfL concentrations. There were no associations of WMH with biomarker concentrations among those diagnosed with dementia.

Conclusions and relevance: The findings suggest that among individuals with DS, CVD promotes neurodegeneration by increasing astrocytosis and tau pathophysiology in the presymptomatic phases of AD. This work joins an emerging literature that implicates CVD and its interface with neuroinflammation as a core pathological feature of AD in adults with DS.

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Figures

Figure 1.
Figure 1.. Frequency map of white matter hyperintensities in adults with Down syndrome.
A voxel-wise frequency map of WMH was created by summing voxels labeled across all 185 individual 3D and dividing by 185. Each voxel’s value represents the proportion of times it was labeled as a WMH across the 185 masks from low frequency (red) to high frequency (yellow).
Figure 2.
Figure 2.. Conditional relationship between WMH and GFAP on p-tau217 concentration
Relationship between GFAP and p-tau217 concentration conditioned by WMH volume (A) and relationship between WMH and p-tau217 concentration conditioned by GFAP (B). The plots show the relationship between GFAP or WMH and p-tau217 for different ranges of WMH and GFAP, respectively. The panels are read from bottom left to top right along each row with the bottom row representing the lowest range of WMH volume and the top row representing the highest range of WMH volume. Rows demonstrating the relationship in individuals with higher distributions are indicated by (ii) while relationships in participants with lower distributions are indicated by rows labeled (i). For example, in Figure 2A., the top right plot shows the relationship between GFAP and p-tau217 in individuals with the largest WMH volume (i) while the bottom left panel shows the relationship between GFAP and p-tau217 in individuals with the smallest WMH volume (ii). WMH: white matter hyperintensities, GFAP: glial fibrillary acidic protein, p-tau217: phosphorylated tau 217
Figure 3.
Figure 3.. Path models for biomarker progression across diagnostic groups.
Statistical modeling calculates relative causal relationships among different pathophysiological contributors. Larger numbers (regression coefficients) signify stronger direct effects. Aβ: β-amyloid, WMH: white matter hyperintensities, p-tau217: phosphorylated tau 217, GFAP: glial fibrillary acidic protein, NfL: neurofilament light chain, MCI: mild cognitive impairment.

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