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

Amanda Annettesdotter1, Nicola Spotorno2, Anika Wuestefeld2

  • 1Department of Clinical Sciences Lund, Lund University, Lund, Sweden.

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

Cognitive decline in amyloid-negative mild cognitive impairment (aMCI) is predicted by baseline cognition and brain atrophy. These findings aid in understanding conditions like LATE and PART, distinct from Alzheimer's disease.

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Area of Science:

  • Neuroscience
  • Neurology
  • Biomarkers

Background:

  • A significant portion of amnestic mild cognitive impairment (aMCI) patients lack amyloid-beta (Aβ) biomarkers, suggesting alternative pathologies beyond Alzheimer's disease (AD).
  • Potential causes for cognitive decline in Aβ-negative (Aβ-) aMCI include limbic-predominant age-related TDP-43 encephalopathy (LATE), cerebrovascular diseases, and primary age-related tauopathy (PART).
  • The prognostic uncertainty for Aβ- aMCI necessitates identifying predictors of cognitive decline and dementia progression.

Purpose of the Study:

  • To identify demographic, cognitive, fluid, and imaging biomarker predictors of cognitive decline in Aβ- aMCI patients.
  • To develop predictive models for cognitive decline and dementia progression in this specific patient group.
  • To differentiate prognostic factors in Aβ- aMCI, potentially linked to LATE and PART pathologies.

Main Methods:

  • Longitudinal data from 140 Aβ- aMCI patients (BioFINDER-1/2) were analyzed, assessing cognitive decline using Mini-Mental State Examination (MMSE) and Clinical Dementia Rating Sum of Boxes (CDR-SB).
  • Predictors included baseline cognition, cerebrospinal fluid (CSF) Aβ42/40, p-tau181, regional brain atrophy (amygdala, frontal gyrus, entorhinal cortex), whole-brain cortical thickness, and white matter hyperintensities.
  • Linear mixed-effects models and model selection (AIC) were used to identify the most parsimonious predictive models for cognitive decline and dementia progression.

Main Results:

  • For MMSE decline, the best model included baseline MMSE and whole-brain cortical thickness.
  • For CDR-SB decline, predictors were baseline CDR-SB, amygdala volume, and middle frontal gyrus cortical thickness.
  • Progression to dementia was best predicted by MMSE, lateral ventricle volume, entorhinal and whole-brain cortical thickness, sex, and CSF Aβ42/40.

Conclusions:

  • Baseline cognitive status and global/regional brain atrophy are significant predictors of cognitive decline in Aβ- aMCI.
  • Regional brain measures offer insights into specific underlying pathologies, relevant for new LATE clinical criteria.
  • Findings require validation in larger cohorts, such as the Alzheimer's Disease Neuroimaging Initiative (ADNI).