Cluster Profiles of Health Metabolic Markers and Vitamin D
Vitamin D (VD) is an essential nutrient for which deficiency is highly prevalent and worthy of attention. In fact, VD deficiency may increase the risk of developing chronic diseases, including cardiovascular disease, diabetes and metabolic syndrome, and cancer. Recent studies have also reported a li...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-03-01
|
| Series: | Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-3900/91/1/414 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Vitamin D (VD) is an essential nutrient for which deficiency is highly prevalent and worthy of attention. In fact, VD deficiency may increase the risk of developing chronic diseases, including cardiovascular disease, diabetes and metabolic syndrome, and cancer. Recent studies have also reported a link between VD deficiency, comorbid conditions, and infectious diseases such as COVID-19, which is caused by the Sars-CoV-2 virus. The impact of VD deficiency on the metabolomic profiles of some of these diseases is poorly understood. The aim of this study was to analyse the relationship between VD and some metabolomics/biochemical markers. Metabolomics data (249 NMR-derived Nightingale Health markers) and some common biochemical markers related to VD and inflammation (VD, CRP, IGF-1, GGT, and steroid hormones, among others) were taken from the UK BIOBANK database. Two sets of markers were subjected to a hierarchical clustering analysis after data normalization: (i) the metabolomics-derived markers with VD (N = 10,000 randomly selected subjects) and (ii) the metabolomics-derived markers with all other biochemical markers (N = 674 subjects with complete data). Ward’s inter-cluster linkages and Euclidean and Manhattan distances were applied to group the markers and subjects based on their similarity. The silhouette method was considered to choose the optimal number of clusters. The results showed three distinctive clusters of subjects and three clusters of metabolites. The first cluster of HDL-related metabolites defined subjects with high, intermediate, and low levels of these metabolites. The second cluster of metabolites included VD, inflammatory markers (CRP and IGF-1), branched-chain amino acids (Valine, Isoleucine, and Leucine), polyunsaturated fatty acids, markers of the acetate metabolism, and LDL-related markers. VD showed a heterogeneous trend across the clusters of subjects. The third cluster comprised other cholesterol-related markers. Results were consistent in both sets of markers and distance matrixes. In conclusion, this exploratory study suggests that VD aggregates with key metabolic markers of energy metabolism and inflammation, pointing to synergistic mechanisms through which these markers could modulate metabolic disorders. These markers, however, do not seem to define subgroups of subjects with VD deficiency. Analyses are underway to explore the influence of other VD-related variables on these results. |
|---|---|
| ISSN: | 2504-3900 |