Mapping molecular pathways underlying the relationship between plasma ptau and Alzheimer's disease pathology: an imaging‐transcriptomic study

TL;DR

This study identifies molecular pathways linking plasma ptau levels to Alzheimer's disease pathology using imaging and transcriptomic data.

Contribution

The novel contribution is the identification of mitochondrial metabolism and synaptic function as key AD-biodomains linked to plasma ptau.

Findings

Mitochondrial metabolism is associated with ptau181-PET relationships.

Synaptic function and cytokine interactions are linked to ptau217-PET associations.

MAPT, SNCA, and intracellular signaling are highlighted as key molecular pathways.

Abstract

Collective evidence suggests that plasma ptau181 and 217 reflect Alzheimer's disease (AD) from the amyloid‐beta (Aβ) to tau pathologies. However, possible molecular pathways underlying the biological mechanisms that relate AD pathology with plasma ptau have not yet been elucidated.

We studied 549 participants from two cohorts: ADNI (Aβ‐: 83 CN; Aβ+: 171 CN, 97MCI, 39 AD; Aβ‐PET: [18F]AV45; tau‐PET: [18F]AV1451) and TRIAD (Aβ‐: 26 Young, 62 CN; Aβ+: 29 CN, 30 MCI, 24 AD; Aβ‐PET: [18F]AZD4694; tau‐PET: [18F]MK6240). Both cohorts included plasma ptau181 and 217, which were quantified using the SIMOA/Janssen. All images were processed using Freesurfer or PETsurfer into the DKT atlas. Linear regression models investigated the associations between plasma ptau and Aβ‐PET or tau‐PET, adjusted for age, sex, education, and APOEε4. Partial least squares (PLS) analysis identified a set of transcriptomic profiles from the Allen Human Brain Atlas (AHBA) associated with the ptau181‐PET (Aβ and tau‐PET) or ptau217‐PET relationships. Then, gene set enrichment analyses based on GO and KEGG databases and STRINGdb protein‐protein interactions were conducted to highlight which molecular/biological processes and cellular components are associated with the identified transcriptomic profiles.

The ptau181‐PET and ptau217‐PET relationships were significantly associated with the spatial distribution of the AHBA, explaining >90% and >82% in variance in the 1st PLS component from both cohorts, respectively (Figure 1). Subsequent gene enrichment analyses showed mitochondrial metabolism for ptau181‐PET and synaptic function for ptau217‐PET as converging GO AD‐Biodomains (Figure 2). The KEGG enrichment analyses identified pathways of neurodegeneration for ptau181‐PET and cytokine‐cytokine receptor interaction for ptau217‐PET as converging annotations (Figure 2). Notably, TRIAD also showed Alzheimer's disease KEGG annotation from both ptau models (Figure 2). The STRINGdb analyses confirmed significant protein‐protein interactions and revealed MAPT, PINK1, and SNCA proteins with the largest betweenness metric within significant networks of KEGG terms from TRIAD, while BCL2L1, PINK1, and GSK3β proteins were identified in ADNI (Figure 3).

Imaging‐transcriptomic analyses showed unique sets of transcriptomic profiles, highlighting mitochondrial metabolism and synaptic as key AD‐biodomains underlying the plasma ptau‐AD pathology relationship. Our study underscores the MAPT and SNCA proteins and intracellular signalling as salient molecular pathways in neurodegeneration and AD dementia.

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