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Basic Science and Pathogenesis.

Xuewen Xiao1, Xinxin Liao1, Yiliang Liu1

  • 1Xiangya Hospital, Central South University, Changsha, Hunan, China.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 23, 2025
PubMed
Summary
This summary is machine-generated.

Polygenic risk scores and rare variants in ABCA7, ECSIT, and ADPRHL1 are linked to Alzheimer's disease (AD) risk and biomarkers. This research offers new insights into AD pathophysiology and potential diagnostic targets.

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Area of Science:

  • Genetics
  • Neuroscience
  • Biomarker Discovery

Background:

  • Genetics significantly influences Alzheimer's disease (AD) biomarker traits, but the specific genetic factors are not well understood.
  • Investigating genetic contributions is crucial for understanding AD pathophysiology and developing effective interventions.

Purpose of the Study:

  • To explore the genetic underpinnings of Alzheimer's disease (AD) biomarker traits.
  • To identify novel genetic variants and polygenic risk scores associated with AD risk and key biomarkers.

Main Methods:

  • Whole genome sequencing was performed on 3,707 individuals (1,697 AD patients, 2,010 controls).
  • Association analyses were conducted for common and rare genetic variants with AD biomarker traits, including cerebrospinal fluid (CSF) and plasma biomarkers.
  • A polygenic risk score (PRS) was developed and evaluated for its association with AD risk and biomarker levels.

Main Results:

  • The PRS demonstrated significant associations with increased AD risk, lower Mini-Mental State Examination (MMSE) scores, and elevated plasma p-tau217 and GFAP levels.
  • Gene-based rare variant analyses identified three novel genes (ABCA7, ECSIT, ADPRHL1) associated with genome-wide significance for specific AD biomarker traits.
  • Rare damaging variants in ABCA7 were linked to MMSE scores, ECSIT to CSF Aβ42, and ADPRHL1 to plasma GFAP.

Conclusions:

  • Both polygenic risk scores and rare variants in ABCA7, ECSIT, and ADPRHL1 contribute significantly to Alzheimer's disease biomarker traits.
  • These findings enhance our understanding of AD pathophysiology.
  • The identified genetic factors may represent novel targets for AD diagnosis and therapeutic strategies.