**1. Introduction**

The vitamin D receptor (VDR), a member of the nuclear receptor superfamily of transcriptional regulators, plays a crucial role in calcitriol or 1-alfa,25-dihidroxicolecalciferol (1<sup>α</sup>,25(OH)2D) signalling. VDR is activated by binding with 1<sup>α</sup>,25(OH)2D, which forms a heterodimer with the retinoid X receptor (RXR). The 1<sup>α</sup>,25(OH)2D-VDR-RXR complex migrates to the nucleus to regulate the transcription of genes involved in vitamin D effects including phosphorous and calcium metabolism, cell proliferation and the control of innate and adaptive immunity [1–3].

The *VDR* gene is located on chromosome 12 (12q13.11) and more than 900 allelic variants in the *VDR* locus have been reported. The best studied *VDR* gene polymorphisms are Apal (rs7975232), BsmI (rs1544410), Taql (rs731236) and Fokl (rs10735810). ApaI, TaqI

**Citation:** Usategui-Martín, R.; De Luis-Román, D.-A.; Fernández-Gómez, J.M.; Ruiz-Mambrilla, M.; Pérez-Castrillón, J.-L. Vitamin D Receptor (*VDR*) Gene Polymorphisms Modify the Response to Vitamin D Supplementation: A Systematic Review and Meta-Analysis. *Nutrients* **2022**, *14*, 360. https://doi.org/10.3390/ nu14020360

Academic Editor: Andrea Fabbri

Received: 16 December 2021 Accepted: 13 January 2022 Published: 15 January 2022

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and BsmI are silent genetic variants that increase mRNA stability. The FokI polymorphism is located on exon 2 and results in a protein shortened by three amino acids [4–6]. These genetic variants have been associated with a predisposition to chronic diseases such as type 2 diabetes, cancer, autoimmune diseases, cardiovascular alterations, rheumatic arthritis and metabolic bone diseases [7–10].

VDR regulation is determined by genetic and environmental factors [11]. The principal environmental factors associated with VDR regulation are diet, exposure to sunlight, infections and pollution [12–15]. It has been postulated that these environmental factors could modify vitamin D levels which regulate the receptor. The mechanism is not clearly understood but it is hypothesised that it may be through epigenetic mechanisms [16]. Other factors involved in VDR regulation are the intake of the vitamin D precursor and the production and activity of the ligand. Genetic factors could modulate the influence of environmental factors on VDR regulation [11]. In this scenario, it has been reported that the response to vitamin D supplementation differs widely between individuals and one hypothesis is that genetic variants in the *VDR* gene are important in the response to vitamin D supplementation. The polymorphisms in the *VDR* gene could modify the VDR activity and therefore could be the explanation for the different response to vitamin D supplementation [4–6,17]. Various authors have examined how genetic variants in the *VDR* gene are associated with the response to vitamin D supplementation, and the many genetic association studies show contradictory results [18–21]. Therefore, our objective was to conduct a systematic review and meta-analysis to evaluate the response to vitamin D supplementation according to the BsmI, TaqI, ApaI and FokI polymorphisms in the *VDR* gene.

### **2. Material and Methods**

### *2.1. Inclusion Criteria and Search Strategy*

To analyse the influence of *VDR* genetic variants on the response to vitamin D supplementation, studies including serum vitamin D levels before and after supplementation according to the genetic distribution of the BsmI, TaqI, ApaI and FokI *VDR* polymorphisms were considered eligible for inclusion.

This systematic review and meta-analysis were performed in accordance with the PRISMA guidelines [22] (Supplementary Material Table S1). We included studies evaluating the response to vitamin D supplementation according to genetic variants in the *VDR* gene. To identify eligible studies, we conducted a computer-based search in the PubMed, Web of Science, Scopus and Embase electronic databases up to November 2021. Potentially relevant articles were searched for using the following terms in combination with Medical Subject Headings (MeSH) terms and text words: "Vitamin D receptor", "VDR", "BsmI", "TaqI", "ApaI", "FokI", "polymorphism", "mutations", "variants", "cholecalciferol", "vitamin D", "supplementation" and "vitamin D supplementation". No language restrictions were applied. The references of selected articles were scanned to identify additional relevant articles. The MedLine option "related articles" and review articles on the topic were also used to supplement the search.

### *2.2. Data Extraction*

Bibliographic research and data extraction were conducted independently by three investigators (RUM, DDLR and JMFG). Differences were resolved by consensus with the senior author (JLPC). We extracted the authors names, the publication year, demographic information (age and sex), the follow-up time after vitamin D supplementation and serum vitamin D levels before and after supplementation according to the *VDR* gene polymorphisms.

### *2.3. Statistical Analysis*

Independent meta-analyses were carried out to compare baseline and post-supplementation serum vitamin D levels according to the genetic distribution of the *VDR* polymorphisms

included. Sub-analyses by age and sex were also carried out. Meta-analysis was only carried out when ≥3 studies were available. We analysed all polymorphisms under a dominant model for the minor alleles.

As previously described [23–25], meta-analyses were carried out using RevMan 5.0 software [26]. The difference between baseline and post-supplementation status and their 95% confidence interval (CI) were estimated for each study. Random-effects model was used to calculate the *p*-values (DerSimonian and Laird method). A *p*-value < 0.05 was considered statistically significant. To analyse the heterogeneity of the studies we applied Cochran's Q-statistic (*p* < 0.10 indicated heterogeneity across studies). Inconsistency in the meta-analysis was estimated using the I2 statistic and this represented the percentage of the observed between-study variability due to heterogeneity. The following cut-off points were applied: (I2 = 0–25%, no heterogeneity; I2 = 25–50%, moderate heterogeneity; I2 = 50–75%, large heterogeneity; I2 = 75–100%, extreme heterogeneity). To assess publication bias, Begger's funnel plot was examined based on visual inspection. Asymmetry suggested publication bias. Finally, sensitivity analyses to examine the effect of excluding individual studies were carried out.
