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.

Why the study?

Age is a major risk factor for cardiovascular disease, but the molecular mechanisms underlying human cardiac aging are not fully understood.

Population

Human atrial appendage, left ventricle, and skeletal muscle tissue from the GTEx project and two validation cohorts

Design

Transcriptomic profiling and predictive modeling study

Authors

SCSheena Yi-Hsin Cheng YHYi‐Chiung Hsu

Discussion

Member takes

Overview

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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July 26, 2026Biogerontology

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

View Full Paper

Ask AI

Bookmark

Key result

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

Why the study?

Age is a major risk factor for cardiovascular disease, but the molecular mechanisms underlying human cardiac aging are not fully understood.

Population

Human atrial appendage, left ventricle, and skeletal muscle tissue from the GTEx project and two validation cohorts

Design

Transcriptomic profiling and predictive modeling study

Authors

SCSheena Yi-Hsin Cheng YHYi‐Chiung Hsu

Discussion

Member takes

Overview

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

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

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

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