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February 9, 20261 citations

Analyses of plasma multi-omic data across ancestries identify novel pathways implicated in Alzheimer's disease.

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CYChengran YangWashington University in St. LouisJTJigyasha TimsinaWashington University in St. LouisMLMenghan LiuWashington University in St. Louis

Key Points

  • The aim is to identify novel pathways linked to Alzheimer's disease by analyzing multi-omic data across different ancestries.
  • Analyzed multi-omic plasma data focusing on proteomics and metabolomics across European and African ancestries.
  • Compared findings to previous literature to determine novelty of results.
  • Stratified analyses were performed based on ancestry to identify convergent and divergent pathways.
  • 61% of proteomics findings for European ancestry and 72% for African ancestry were novel.
  • 83% of metabolomics findings for European ancestry and 50% for African ancestry were novel.
  • Both convergent and divergent pathways were highlighted in stratified analyses for proteomics and metabolomics.

Abstract

For proteomics, 61% of findings for European (EUR) ancestry and 72% for African (AFR) ancestry were not previously reported. For metabolomics, 83% of findings for EUR ancestry and 50% AFR ancestry were not previously reported. Both convergent and divergent pathways were identified in EUR- and AFR-ancestry stratified analyses in either proteomics or metabolomics findings.

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Cite This Study

Yang et al. (2026) studied this question.

synapsesocial.com/papers/698979f5f0ec2af6756e8064https://doi.org/10.1002/alz.71164
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