Hypovitaminosis D and "Metabolic" Inflammatory Status in Patients With Obesity

Introduction Obesity is a major health problem related to a cluster of chronic metabolic disorders and is associated with increased overall morbidity and mortality. Several studies proved that obesity is linked to a low grade of systemic chronic inflammatory status, considering the adipose tissue the largest metabolically active organ with endocrine, inflammatory, and immunological functions.

The "metabolic" inflammatory process leads to the release of inflammatory cytokines with subsequent systemic effects on insulin-sensitive organs, such as the liver which markedly suffers from the systemic proinflammatory environment. Vitamin D (25(OH)D) plays a key role in the regulation of mineral homeostasis by binding the vitamin D receptors, leading to an adequate calcium level to promote skeletal health. Furthermore, vitamin D has anti-inflammatory and immunoregulatory functions. It is an indispensable nutritive component that regulates the inflammatory microenvironment through several mechanisms such as the up-regulation of Mitogen-activated protein kinases (MAPKs) and inhibition of Nuclear Factor-Kappa B (NF-Kb) signaling pathways.

A low level of vitamin D in the visceral adipose tissue (VAT) induces more lipogenesis and less lipolysis promoting fat storage and obesity. The prevalence of vitamin D deficiency is 24% and 35% higher in overweight and obese people, respectively, compared to the general population. Many hypotheses have been proposed to explain the inverse correlation between Vitamin D and obesity:1) the storage of this fatsoluble nutrient in the exceeded VAT; 2) the higher plasma dilution of the Vitamin D in the obese patient compared to the normal-weight population; 3) the reduced sun exposure due to the stigma of obesity; 4) the presence of metabolic syndrome or type 2 diabetes that often co-exist with obesity; 5) molecular interactions between Vitamin D and pro-inflammatory cytokines.

Thus, hypovitaminosis D, inflammation, and obesity are three pathological conditions closely linked. In the literature, data explaining this relationship are still inconsistent, but crosstalk based on molecular signals exists.

On this basis, patients with obesity could be a high-achieving biological model helping to clarify the noncalcemic effects of vitamin D in regulating inflammation.

The first aim of the study is to assess the incidence of hypovitaminosis D in a cohort of obese patients; secondly, our purpose is to evaluate the correlation between hypovitaminosis D and inflammation's indices: inflammation-based prognostic scores, ferritin, C-reactive protein (CRP), inflammation grade on liver biopsy, and bioimpedance measures.

Materials and Methods This monocentric retrospective cohort study is based on a prospective database of consecutive obese patients referred to the General Surgery Department at Cattinara University Hospital in Trieste, Italy, between January 2018 and June 2021.

Patients were divided into three groups according to 25(OH) D levels: deficiency was defined as 25(OH) D levels ≤ 20 ng/mL, insufficiency between 21 and 29 ng/mL, and normal ≥ 30 ng/mL. The cohort was divided into three classes of obesity, according to BMI: grade I obesity 30.0-34.9 kg/m2; grade II obesity, 35.0-39.9 kg/m2; grade III obesity ≥40.0 kg/m2.

Measurements of body composition were conducted with Bioelectrical Impedance Analysis (BIA) technique, asking the participants to stand on the device barefoot to complete the analysis. Among all parameters, BMI, phase angle (PhA), total body water (TBW), extracellular (ECW) and intracellular water (ICW), body fat index, and fat and muscular mass were recorded. The PhA cutoff was not clearly defined in the literature, a value between 7.0 and 6.0 are found to be optimal in adulthood. Before surgery, the systemic inflammatory indices recorded were ferritin plasma level, CRP, and the following inflammation-based prognostic scores were considered for analysis: Glasgow Prognostic Score/modified Glasgow Prognostic Score (GPS/mGPS), Prognostic Nutritional Index (PNI), Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte ratio (PLR), Lymphocyte-to-monocyte ratio (LMR), Systemic immune inflammation index (SII). CRP values≥ 5 mg/dL were considered pathological.

During the bariatric surgery, a liver biopsy was performed and analyzed by a single experienced pathologist blinded to all clinical and laboratory parameters. Patients with other forms of chronic liver disease, including suspected/confirmed hepatocellular carcinoma, alcoholic liver disease (>25 g/day alcohol consumption), or known hepatitis B virus, hepatitis C virus, and human immunodeficiency virus positivity were excluded. The histological diagnosis of nonalcoholic steatohepatitis (NASH) and fibrosis according to Kleiner-Brunt classification was detected. NASH was defined as a total no alcoholic fatty liver disease (NAFLD) activity score ≥ 5.

The study was conducted according to the STROBE Guidelines.

Statistical Analysis Continuous normal variables were expressed as mean ± standard deviation (SD); continuous non-normal variables as median and range (25 percentile-75 percentile). The Shapiro-Wilk test was performed to assess normality. Kruskal-Wallis non-parametric test was performed to identify differences in continuous variables of interest among the three groups. Post-hoc tests, and pair-wise comparisons using Mann-Whitney test, were conducted and corrected using the Holm method Categorical variables were expressed as absolute frequency and percentages and compared with Chi-Squared or Fisher-Exact Test when appropriate. The linear relationship between 25(OH) D levels and study continuous variables was assessed through the Spearman correlation coefficient. The most significant individual variables have been incorporated into a stepwise multiple linear regression (stepwise selection based on Akaike information criterion) to determine significant predictors of 25(OH) D levels. Two multiple linear regression analysis models were performed: 1) to estimate the predictive values of the bioelectrical impedance analysis and 2) to estimate the predictive values of inflammatory parameters. Beta and the standard error of Beta were reported as linear model results. P-Values ≤ 0.05 were considered statistically significant.

Data were analyzed using the R Statistical Software.