# Predicting accumulation and age at onset of amyloid-β from genetic risk and resilience for Alzheimer’s disease

**Authors:** Eleanor K O’Brien, Timothy Cox, Shane Fernandez, Pierrick Bourgeat, Tenielle Porter, Ben Goudey, James D Doecke, Colin L Masters, Jurgen Fripp, Kwangsik Nho, Victor L Villemagne, Carlos Cruchaga, Christopher C Rowe, Andrew J Saykin, Vincent Dore, Simon M Laws

PMC · DOI: 10.21203/rs.3.rs-7911284/v1 · Research Square · 2025-10-22

## TL;DR

This study uses genetic data to predict when amyloid-beta accumulates in the brain, which could help identify Alzheimer's risk early and enable timely interventions.

## Contribution

The study introduces polygenic scores for Alzheimer’s risk and resilience to predict amyloid-beta accumulation and age at onset.

## Key findings

- Higher PGSrisk is linked to increased amyloid-beta accumulation and earlier age at onset.
- PGSresilience is associated with later age at onset of amyloid-beta accumulation.
- Trait-specific PGSs showed inconsistent associations across different genetic folds.

## Abstract

Accumulation of brain amyloid beta (Aβ) is a key pathological hallmark of Alzheimer’s disease (AD) and begins many years before cognitive symptoms. Being able to predict the risk of Aβ accumulation, or the age at which this accumulation exceeds a critical threshold, may enable early intervention and treatment to slow or prevent the onset of AD. We utilised published genome-wide association studies (GWAS) to develop polygenic scores (PGS) based on AD risk (PGSrisk) and resilience (PGSresilience). We tested whether these could predict (i) whether an individual was an accumulator of Aβ (‘Accumulator Status’), and (ii) in accumulators, the age at which brain Aβ is estimated to exceed a threshold of 20 centiloids (CL)(‘Estimated Age at onset of Aβ’; AAO-Aβ) among 2175 participants (1158 with AAO Aβ) from the Alzheimer’s Dementia Onset and Progression in International Cohorts (ADOPIC) study. Additionally, we conducted genome-wide association studies (GWAS) of these traits and developed phenotype-specific PGSs using cross-validation (CV). Higher PGSrisk was associated with a greater risk of being an accumulator and a younger AAO-Aβ. When stratified by number of APOE ε4 alleles, PGSrisk predicted Accumulator Status in APOE ε4 heterozygotes, and AAO-Aβ in ε4 non-carriers and heterozygotes, with the same directions of effect as were seen in the whole cohort. PGSresilience was not significantly associated with Accumulator Status, but higher PGSresilience was associated with later AAO-Aβ overall and in ε4 heterozygotes. Trait-specific PGSs, developed using CV, were not significantly associated with either trait overall and the direction of association varied across CV folds. Polygenic scores, alongside other risk factors, may be useful for identifying individuals at risk of accumulating Aβ, and predicting the age at which this exceeds a critical threshold. This could provide a window for administering disease-modifying treatment or lifestyle interventions to prevent or delay the onset of AD.

## Linked entities

- **Proteins:** APOE (apolipoprotein E)
- **Diseases:** Alzheimer’s disease (MONDO:0004975)

## Full-text entities

- **Genes:** APP (amyloid beta precursor protein) [NCBI Gene 351] {aka AAA, ABETA, ABPP, AD1, APPI, CTFgamma}, APOE (apolipoprotein E) [NCBI Gene 348] {aka AD2, APO-E, ApoE4, LDLCQ5, LPG}
- **Diseases:** AD (MESH:D000544)

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12633517/full.md

## References

71 references — full list in the complete paper: https://tomesphere.com/paper/PMC12633517/full.md

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Source: https://tomesphere.com/paper/PMC12633517