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Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
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Biomarkers.

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Updated: Jan 7, 2026

Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Sokratis Charisis1, Sachintha Ransara Brandigampala2, Di Wang3

  • 1Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center at San Antonio, San Antonio, TX, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 26, 2025
PubMed
Summary
This summary is machine-generated.

Machine learning models can detect Alzheimer's disease (AD) and aging brain patterns. These models show generalizability across diverse populations, but older Hispanic individuals may exhibit different aging-related brain atrophy and cognition associations.

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Area of Science:

  • Neuroimaging
  • Machine Learning
  • Cognitive Neuroscience

Background:

  • Machine learning (ML) models identify Alzheimer's disease (AD) and aging brain atrophy patterns.
  • Existing ML tools are primarily validated in White populations, limiting their use in diverse groups.
  • This study assesses the generalizability of ML indices in a racially and ethnically diverse neuroimaging sample.

Purpose of the Study:

  • To evaluate the generalizability of ML-derived brain atrophy indices (SPARE-AD and SPARE-BA) across diverse racial and ethnic groups.
  • To examine the association of AD-like and aging-related brain atrophy patterns with cognitive function in a multi-ethnic cohort.

Main Methods:

  • Utilized MRI data from 6,700 scans across four studies (FHS, NACC, CHS, NOMAS).
  • Applied robust statistical harmonization to remove scanner effects and derive SPARE-AD and SPARE-BA indices.
  • Examined associations of SPARE-AD with cognitive impairment and SPARE-BA with global cognition using mixed-effects models across racial/ethnic groups.

Main Results:

  • SPARE-AD index indicating >50% probability of AD-like atrophy significantly increased odds of cognitive impairment (OR=10.37), consistent across races.
  • A 1-year increase in SPARE-BA-predicted brain age was associated with decreased global cognition (β=-0.086).
  • The SPARE-BA association with cognition was not significant in Hispanic individuals and was more consistent across groups in those <75 years old.

Conclusions:

  • Harmonization techniques and diverse training data enable ML index expansion to various racial and ethnic groups.
  • Older Hispanic individuals may show distinct relationships between aging brain patterns and cognition.
  • Potential differences in neuropathology or other factors may underlie observed variations in cognitive associations.