Int J Obes (Lond). 2022 Aug 20. doi: 10.1038/s41366-022-01212-1. Online ahead of print.
BACKGROUND/OBJECTIVES: Although vascular endothelial growth factor b (VEGFb) might have an impact on the development of obesity, diabetes and related disorders, the possible relationship between VEGFb serum levels and the incidence of these metabolic complications in humans is still unknown. The aim of our study was to evaluate the association between VEGFb serum levels and the new-onset of metabolic syndrome (MS) and its components in the Spanish adult population after 7.5 years of follow-up.
SUBJECTS/METHODS: A total of 908 subjects from the Di@bet.es cohort study without MS at cross-sectional stage according to International Diabetes Federation (IDF) or Adult Treatment Panel III (ATP-III) criteria were included. Additionally, five sub-populations were grouped according to the absence of each MS component at baseline. Socio-demographic, anthropometric and clinical data were recorded. The Short Form of International Physical Activity Questionnaire (SF-IPAQ) was used to estimate physical activity. A fasting blood extraction and an oral glucose tolerance test were performed. Serum determinations of glucose, lipids, hsCRP and insulin were made. VEGFb levels were determined and categorized according to the 75th percentile of the variable. New cases of MS and its components were defined according to ATPIII and IDF criteria.
RESULTS: A total of 181 or 146 people developed MS defined by IDF or ATP-III criteria respectively. Serum triglyceride levels, hs-CRP and systolic blood pressure at the baseline study were significantly different according to the VEGFb categories. Adjusted logistic regression analysis showed that the likelihood of developing MS and abdominal obesity was statistically reduced in subjects included in the higher VEGFb category.
CONCLUSION: Low serum levels of VEGFb may be considered as early indicators of incident MS and abdominal obesity in the Spanish adult population free of MS, independently of other important predictor variables.