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Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

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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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Cardiac biomarkers are critical in diagnosing, prognosing, and managing cardiovascular diseases. Routine measurement of specific biomarkers such as B-type natriuretic peptide (BNP), C-reactive protein (CRP), and homocysteine (Hcy) is common practice in clinical settings to evaluate heart function and predict cardiovascular events.
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Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Xiaolin Zhou1

  • 1University of Toronto, Toronto, ON, Canada.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

Genetic factors influence brain cell type proportions, offering insights into neuronal vulnerability in neuropsychiatric disorders like Alzheimer's disease. This study validates methods for inferring these proportions from bulk brain tissue RNA sequencing data.

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Area of Science:

  • Neuroscience
  • Genetics
  • Computational Biology

Background:

  • Neuropsychiatric disorders are associated with altered brain composition, including neuronal loss in Alzheimer's disease (AD).
  • GABAergic cell types are implicated in neural dysregulation and neurodegeneration.
  • Studying cell type proportion changes in human brain tissue is challenging due to accessibility issues.

Purpose of the Study:

  • To identify genetic factors influencing cell-type vulnerabilities in the brain.
  • To investigate the link between genetic risk factors and neuropsychiatric traits.
  • To hypothesize that neuronal subtype vulnerability is tied to specific genetic risk factors.

Main Methods:

  • Benchmarking and validating cell-type deconvolution algorithms for bulk RNA sequencing (RNAseq) data using single-nucleus RNA sequencing (snRNA-seq) data.
  • Conducting a genome-wide association study (GWAS) to identify genetic variants associated with cell type proportions (CTPs).
  • Utilizing data from the Religious Orders Study/Memory and Aging Project (ROSMAP) cohort (n=912).

Main Results:

  • No single deconvolution method is universally optimal for all cell types and datasets.
  • The MarkerGeneProfile (MGP) method showed high accuracy in predicting cell type proportions.
  • Accounting for technical covariates in RNAseq data enhanced GWAS power, revealing genetic variants linked to CTPs.

Conclusions:

  • Brain cell type proportions can be reliably inferred from bulk brain tissue RNAseq data.
  • These proportions are significantly influenced by genetic factors.
  • This research advances the understanding of neuronal vulnerability in neuropsychiatric disorders.