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Vitamin D Receptor (VDR) Polymorphisms and Cardiometabolic Profiles in Orthopedic Patients: A Cluster-Based Analysis
Dariusz Larysz1, Remigiusz Recław2,3, Aleksandra Suchanecka2
1Department of Trauma and Orthopaedic Surgery, 109th Military Hospital with Polyclinic, Ministry of National Defense, ul. Ksiedza Piotra Skargi 9/11, 71-422 Szczecin, Poland.
International Journal of Molecular Sciences
|February 27, 2026
Summary
Genetic variations influence cardiometabolic risk and quality of life. This study used clustering to identify patient subgroups, revealing distinct cardiometabolic profiles linked to specific gene polymorphisms in orthopedic patients.
Area of Science:
- Genetics and Precision Medicine
- Cardiovascular and Metabolic Health
- Orthopedic Surgery Outcomes
Background:
- Individual variability in cardiometabolic risk and quality of life is influenced by genetic polymorphisms.
- Clinical relevance of these genetic factors is often obscured by population heterogeneity and single-variant analyses.
- Orthopedic patients frequently experience cardiometabolic comorbidities, highlighting the need for integrated genetic and phenotypic insights.
Purpose of the Study:
- To characterize complex disease profiles in orthopedic patients by integrating genetic and phenotypic data.
- To identify homogeneous patient subgroups using unsupervised clustering based on clinical, anthropometric, hematological, biochemical, and quality-of-life data.
- To investigate the association of specific gene polymorphisms (VDR, COMT, OPRM1) with identified patient clusters.
Main Methods:
- Genotyping of polymorphisms in vitamin D receptor (VDR), catechol-O-methyltransferase (COMT rs4680), and opioid receptor mu 1 (OPRM1 rs510769) genes.
- Collection of comprehensive clinical, anthropometric, hematological, biochemical, and SF-36 quality-of-life data from 289 orthopedic surgery patients.
- Application of unsupervised k-means clustering to identify patient subgroups, followed by ANOVA and chi-squared tests to assess inter-cluster differences.
Main Results:
- Three distinct patient clusters were identified, each characterized by unique combinations of cardiometabolic, inflammatory, and quality-of-life features.
- VDR polymorphisms showed differential distribution across clusters, correlating with variations in body mass index, hypertension prevalence, and inflammatory status.
- COMT and OPRM1 variants were associated with differences in physical and mental quality-of-life dimensions, underscoring multidimensional clinical heterogeneity.
Conclusions:
- A cluster-based approach effectively reveals complex patient heterogeneity in cardiometabolic profiles, surpassing conventional univariate analyses.
- Integrating genetic polymorphisms with clinical and quality-of-life data aids in identifying and interpreting distinct cardiometabolic profiles within orthopedic populations.
- This stratification framework supports precision-oriented research for orthopedic and cardiometabolic patient management.
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