What is the clinical evidence from this study?

Study design: Observational. Population: Cardiac aging. Intervention: Age. Primary outcome: Identification of cardiac age-associated genes and predictive modeling performance.

What does this research mean for the field?

Human cardiac aging is characterized by a distinct cardioselective transcriptomic signature—featuring upregulated senescence and fibrotic pathways and downregulated metabolic and conduction pathways—that can be used to predict cardiac age. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This research aims to uncover the molecular mechanisms of cardiac aging by identifying age-associated genes.

July 26, 2026Biogerontology

Transcriptomic landscape of human cardiac aging: identification of cardioselective age-associated genes and predictive modeling

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Key result

An elastic net model trained on age-associated genes predicts cardiac aging with ~0.90 concordance.

Authors

SCSheena Yi-Hsin ChengUniversity of Southern California YHYi‐Chiung HsuNational Central University

Discussion

Member takes

Implication

Hypothesis-generating for cardiac aging biomarkers; leaves open therapeutic translation pending prospective validation.

Key Points

This research aims to uncover the molecular mechanisms of cardiac aging by identifying age-associated genes.
Analyzed bulk RNA sequencing data from the GTEx project to identify cardiac age-associated genes.
Defined 131 positive and 262 negative age-correlated genes while performing functional enrichment analyses.
Developed an ordinal elastic net regression model to evaluate predictive capabilities.
Identified pathways enriched with age include p53 pathway and cardiac epithelial-mesenchymal transition.
Neutrophil fractions increased with age, while monocyte abundance decreased.
Achieved quadratic weighted kappa of 0.797 and concordance index of 0.901; R2 values of 0.20 and 0.38 in external validation.

Study Design

Type

Observational

PICO

Population

Cardiac aging

Exposure / Comparator

Age

Primary Outcome

Identification of cardiac age-associated genes and predictive modeling performance

Cite This Study

Cheng et al. (2026) conducted an observational in Cardiac aging. Age was evaluated on Identification of cardiac age-associated genes and predictive modeling performance. An ordinal elastic net regression model trained on cardiac age-associated genes predicted cardiac aging with a quadratic weighted kappa of 0.797 and an ordinal concordance index of 0.901.

synapsesocial.com/papers/6a65aae4d3aea3239cd794ca https://doi.org/10.1007/s10522-026-10479-0

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