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August 30, 2026American Heart Journal Plus Cardiology Research and PracticeOpen Access

Polygenic risk score for early identification of coronary artery disease in a real-world clinical setting within the Latvian patient population

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Why the study?

Polygenic risk scores can potentially improve coronary artery disease prediction beyond traditional models, but their utility and predictive performance needed evaluation in the Latvian population.

Does a polygenic risk score improve the prediction of early-onset coronary artery disease when added to conventional risk factors in a Latvian population?

Population

90 early-onset CAD patients and 43 angiographic controls in Latvia

Comparison

PRS and pathway-specific PRS vs conventional risk factors

Design

Case-control study

Key result

Polygenic risk scores were significantly higher in early-onset CAD patients than controls (mean 0.31 vs -0.65; p<0.0001), and combining PRS with clinical factors yielded an AUC of 0.933.

Authors

EKEvija KanašnieceEOElita OzolaLBLīvija Bārdiņa

Discussion

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Overview

PRS may refine early CAD prediction in similar populations; leaves open prospective validation before clinical adoption.

Key Points

  • To evaluate the predictive performance of genome-wide association study-derived overall and pathway-specific polygenic risk scores for early-onset coronary artery disease alone and alongside standard clinical risk factors.
  • Enrolled 90 early-onset CAD patients (mean age 48.7 years) and 43 controls without angiographic evidence of atherosclerotic lesions (mean age 49.8 years) in Latvia, performing next-generation sequencing.
  • Calculated polygenic risk scores (PRS) using 192 single nucleotide variants from the CARDIoGRAMplusC4D meta-analysis and evaluated discriminatory accuracy across clinical factors and biological pathways using ROC curves.
  • CAD patients had significantly higher PRS (mean 0.31) than controls (mean −0.65; p < 0.0001), with PRS alone achieving moderate discrimination (AUC = 0.773).
  • Integrating PRS with all traditional clinical risk factors yielded the highest predictive accuracy (AUC = 0.933) compared to clinical factors alone (AUC = 0.872).
  • Pathway-specific PRS were elevated in CAD for angiogenesis/tissue repair (p = 0.00038), inflammation (p = 0.043), and vascular remodelling (p = 0.0116), though overall PRS maintained superior overall discrimination.

Study Design

Type

Case-Control (n=133)

Structured PICO

Does a polygenic risk score improve the prediction of early-onset coronary artery disease when added to conventional risk factors in a Latvian population?

P
Population
133 participants, comprising 90 early-onset CAD patients and 43 controls with no atherosclerotic lesions on coronary angiography, from the Latvian population.
E
Exposure
Genome-wide association study (GWAS)-derived polygenic risk score (PRS) calculated using 192 single nucleotide variants, and pathway-specific PRS (PS-PRS).
C
Comparator
Conventional clinical risk factors (including LDL cholesterol and total cholesterol).
O
Outcome
Predictive accuracy for early-onset CAD, measured via Receiver Operating Characteristic (ROC) curves (Area Under the Curve, AUC).surrogate

Main Result

Absolute Event Rate: 0.31% vs -0.65%

p-value: p=<0.0001

Integrating a polygenic risk score with traditional clinical risk factors significantly enhances the predictive accuracy for early-onset coronary artery disease.

Cite This Study

Kanašniece et al. (2026) conducted a case-control in Early-onset coronary artery disease (CAD) (n=133). Polygenic risk score (PRS) vs. Controls without atherosclerotic lesions was evaluated on Polygenic risk score difference and predictive accuracy for early-onset CAD (p=<0.0001). Polygenic risk scores were significantly higher in early-onset CAD patients than controls (mean 0.31 vs -0.65; p<0.0001), and combining PRS with clinical factors yielded an AUC of 0.933.

synapsesocial.com/papers/6a93f00a6c1a8fb52e79c08dhttps://doi.org/10.1016/j.ahjo.2026.100875
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