Integrative prediction of Alzheimer's disease and related dementias using multi‐omics aging clocks and genetic data

Abstract INTRODUCTION We tested whether combining Alzheimer's disease and related dementias (ADRD) polygenic risk scores (PRS) with biological aging markers improves ADRD risk prediction.

Methods

In 16,215 UK Biobank (UKB) participants free of ADRD at baseline (median follow‐up: 10.08 years), 397 incident diagnoses were identified. Biological aging measures included clinical, telomere, proteomic, and metabolomic aging markers. External validation/replication was performed in TwinGene (N = 3772; 331 cases).

Results

The fully integrated model achieved area under the curve (AUC) = 0.90 and area under the precision‐recall curve (AUPRC) = 0.24 in the UKB held‐out test set. PRS was the strongest predictor (subdistribution hazard ratio [sHR] = 2.24, 95% CI: 2.02–2.48), followed by ProtAge (sHR = 2.01, 95% CI: 1.13–3.58). The top predicted‐risk quartile showed higher ADRD incidence (sHR = 16.73, 95% CI: 6.49–43.11). TwinGene showed moderate transportability (AUC = 0.757; AUPRC = 0.223) and preserved risk stratification (sHR = 4.02, 95% CI: 3.25–5.02).

Discussion

Integrating PRS and biological aging measures improved ADRD risk stratification.