| Title: | Biobank-Scale Plasma Proteomics Identifies Novel Biomarkers in Hypertrophic Cardiomyopathy. |
| Journal: | Circulation Genomic and Precision Medicine |
| Published: | 22 Apr 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42017215/ |
| DOI: | https://doi.org/10.1161/circgen.125.005325 |
Publication 17882
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Abstract
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is characterized by substantial heterogeneity in both clinical phenotype and risk of adverse outcomes, including heart failure and sudden cardiac death. This highlights the need for robust biomarkers for risk stratification, and while previous studies have identified the role of select plasma proteins, comprehensive large-scale proteomic analyses have been limited in HCM.</p>
METHODS: We performed a case-control analysis of 2922 plasma proteins in 49 588 UK Biobank participants (100 HCM cases) to identify proteins associated with HCM. External replication analyses were performed in the deCODE Genetics Icelandic study (51 cases/38 904 controls) and All of Us (546 cases/41 049 controls) data sets. Associations with adverse clinical outcomes and cardiac endophenotypes of disease severity were further identified, and causal relationships were evaluated using Mendelian randomization. Relative biomarker importance was also assessed by joint modeling via machine learning.</p>
RESULTS: We identified novel associations of ANGPT2 (angiopoietin-2) and LTBP2 (latent transforming growth factor-beta binding protein 2) with HCM, with both also showing prognostic utility for heart failure-related outcomes in HCM cases. We also confirmed the associations of established biomarkers (eg, NT-proBNP [N-terminal pro-B-type natriuretic peptide], troponins I and T) with HCM cases, cardiac imaging markers of disease severity, and adverse outcomes. Mendelian randomization analyses supported a causal effect of HCM on increasing NT-proBNP and troponin T levels.</p>
CONCLUSIONS: This biobank-scale plasma proteomic study in HCM identified ANGPT2 and LTBP2 as novel HCM biomarkers with potential diagnostic and prognostic utility. These findings highlight the potential for plasma proteomics to improve risk prediction and provide insight into HCM pathobiology.</p>
77 Authors
- Jonathan H. Chan
- Christopher Grace
- Mohsen Mazidi
- Robert Clarke
- Carolyn Y. Ho
- Stefan Neubauer
- Christopher M. Kramer
- Hugh Watkins
- Anuj Goel
- William Weintraub
- Raymond Kwong
- Milind Desai
- John DiMarc
- Paul Kolm
- Patrice Desvigne-Nickens
- Nancy Geller
- Dong-Yun Kim
- John DiMarco
- Mark Link
- Gary Francis
- Barry Greenberg
- Milind Desai
- Masliza Mahmod
- Betty Raman
- Daniel Jacoby
- Lauren Baldassarre
- Jeanette Schulz-Menger
- James White
- Amedeo Chiribiri
- Adam Helms
- Lubna Choudhury
- Michelle Michels
- William Bradlow
- Michael Salerno
- Michael Salerno
- Steven Heitner
- Ahmad Masri
- Sanjay Prasad
- Saidi Mohiddin
- Sven Plein
- Martin Maron
- Christopher Madias
- Heiko Mahrholdt
- Chiara Bucciarelli-Ducci
- Angus Nightingale
- Jonathan Weinsaft
- Han Kim
- Gerry P. McCann
- Albert van Rossum
- Tjeerd Germans
- Eric Williamson
- Jeff Geske
- Andrew Flett
- Dana Dawson
- F. Pierre Mongeon
- Iacopo Olivotto
- Andrew Crean
- Anna Woo
- Anjali Owens
- Lisa Anderson
- Sanjay Sharma
- Elena Biagini
- David Newby
- Florian Andre
- Colin Berry
- Bette Kim
- Eric Larose
- Theodore Abraham
- Allison Hays
- Mark Sherrid
- Evan Appelbaum
- Eli Gelfand
- Sherif Nagueh
- Ornella Rimoldi
- Eleanor Elstein
- Matthias Friedrich
- Camillo Autore
1 Application
| Application ID | Title |
|---|---|
| 11223 | Population prevalence of putative cardiomyopathy-causing genetic variants. |
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