| Title: | Proteomic signatures for sudden cardiac death and related intermediate phenotypes |
| Journal: | Heart Rhythm |
| Published: | 2 Mar 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41780576/ |
| DOI: | https://doi.org/10.1016/j.hrthm.2026.02.039 |
Publication 17551
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Abstract
BACKGROUND: Novel markers for sudden cardiac death (SCD) are needed.</p>
OBJECTIVE: To explore whether a protein risk score derived from large-scale proteomics data improves risk prediction of SCD in the general population.</p>
METHODS: A total of 52,705 individuals with 1,459 unique plasma protein measurements were included from the UK Biobank Pharma Proteomics Project. Protein risk score was developed with lasso penalized Cox regression on 40,722 participants enrolled at the English centers and validated on 11,983 participants enrolled at remaining centers.</p>
RESULTS: The protein risk score formula developed from the derivation set was composed of 64 unique plasma proteins including LTBP2, PTPRS, and SPON1. In the test set, per SD increase in protein risk score was associated with a hazard ratio of 2.60 (95% CI, 2.12-3.18) for SCD. Adding a protein risk score to SCD clinical risk factors resulted in a C-index increase of 0.063 (95% CI, 0.037-0.105) for SCD. For ventricular arrhythmia mediated SCDs, increase in C-index when a protein risk score was added to SCD clinical risk factors was 0.070 (95% CI, 0.010 to 0.188). Protein risk score added to SCD clinical risk factors resulted in a risk reclassification of 16.9% (95% CI, 9.0-24.7) at 10-year risk threshold of 5%. A protein risk score was significantly associated with intermediate phenotypes of SCD including QTc prolongation, increase in left ventricular (LV) mean myocardial thickness, and decrease in LV global longitudinal strain.</p>
CONCLUSIONS: Protein risk score derived from a single plasma sample significantly improved risk prediction of SCD and related intermediate phenotypes.</p>
11 Authors
- Hanjin Park
- Daehoon Kim
- Eunsun Jang
- Hee Tae Yu
- Tae-Hoon Kim
- Jae-Sun Uhm
- Jung-Hoon Sung
- Hui-Nam Pak
- Moon-Hyoung Lee
- Pil-Sung Yang
- Boyoung Joung
1 Application
| Application ID | Title |
|---|---|
| 77793 | The causal inference study to determine the association of genetically predicted biological, behavioral, ethnic factors with risk of atrial fibrillation and its associated complications. |
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