| Title: | Effect of genetically predicted sclerostin on cardiovascular biomarkers, risk factors, and disease outcomes |
| Journal: | Nature Communications |
| Published: | 13 Nov 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39537602/ |
| DOI: | https://doi.org/10.1038/s41467-024-53623-5 |
Publication 14188
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Abstract
Sclerostin inhibitors protect against osteoporotic fractures, but their cardiovascular safety remains unclear. We conducted a cis-Mendelian randomisation analysis to estimate the causal effect of sclerostin levels on cardiovascular risk factors. We meta-analysed three GWAS of sclerostin levels including 49,568 Europeans and selected 2 SNPs to be used as instruments. We included heel bone mineral density and hip fracture risk as positive control outcomes. Public GWAS and UK Biobank patient-level data were used for the study outcomes, which include cardiovascular events, risk factors, and biomarkers. Lower sclerostin levels were associated with higher bone mineral density and 85% reduction in hip fracture risk. However, genetically predicted lower sclerostin levels led to 25-85% excess coronary artery disease risk, 40% to 60% increased risk of type 2 diabetes, and worse cardiovascular biomarkers values, including higher triglycerides, and decreased HDL cholesterol levels. Results also suggest a potential (but borderline) association with increased risk of myocardial infarction. Our study provides genetic evidence of a causal relationship between reduced levels of sclerostin and improved bone health and fracture protection, but increased risk of cardiovascular events and risk factors.</p>
18 Keywords
- Adaptor Proteins, Signal Transducing
- Aged
- Biomarkers
- Bone Density
- Cardiovascular Diseases
- Diabetes Mellitus, Type 2
- Female
- Genetic Markers
- Genome-Wide Association Study
- Hip Fractures
- Humans
- Male
- Mendelian Randomization Analysis
- Middle Aged
- Myocardial Infarction
- Osteoporotic Fractures
- Polymorphism, Single Nucleotide
- Risk Factors
9 Authors
- Marta Alcalde-Herraiz
- JunQing Xie
- Danielle Newby
- Clara Prats
- Dipender Gill
- María Gordillo-Marañón
- Daniel Prieto-Alhambra
- Martí Català
- Albert Prats-Uribe
1 Application
| Application ID | Title |
|---|---|
| 98358 | Real-world data linked to genetics and biomarkers to triangulate the evidence on the risk-benefit of medical products |
Enabling scientific discoveries that improve human health