SYSTEMATIC REVIEW article

Front. Genet., 07 January 2022

Sec. Applied Genetic Epidemiology

Volume 12 - 2021 | https://doi.org/10.3389/fgene.2021.791368

Evaluation of Association Studies and an Updated Meta-Analysis of VDR Polymorphisms in Osteoporotic Fracture Risk

  • 1. Second Affiliated Hospital of Soochow University, Suzhou, China

  • 2. Department of Radiotherapy, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China

  • 3. Department of Orthopaedics, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, China

  • 4. Southern Medical University, Guangzhou, China

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Abstract

Background: Several studies have examined the association between vitamin D receptor (VDR) polymorphisms and osteoporotic fracture risk; however, the results are not uniform. Furthermore, many new articles have been published, and therefore, an updated meta-analysis was performed to further explore these issues.

Objectives: The aim of the study was to investigate the association between VDR, BsmI, ApaI, TaqI, FokI, and Cdx2 polymorphisms and osteoporotic fracture risk.

Methods: The odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association between VDR BsmI, ApaI, TaqI, FokI, and Cdx2 polymorphisms and the risk of osteoporotic fracture. We also used the false-positive reporting probability (FPRP) test and the Venice criteria to evaluate the credibility of the statistically significant associations.

Results: Overall, this study found that the VDR ApaI and BsmI polymorphisms significantly increased the risk of osteoporotic fracture in European countries and America, respectively. However, when sensitivity analysis was performed after excluding low-quality and Hardy–Weinberg disequilibrium (HWD) studies, it was found that only individuals with the double-mutated genotype have an increased risk of osteoporotic fracture in European countries. In addition, when the credibility of the positive results was assessed, it was found that the positive results were not credible.

Conclusion: This meta-analysis indicates that there may be no significant association among the polymorphisms of VDR BsmI, ApaI, TaqI, FokI, and Cdx2 and the risk of osteoporotic fracture. The increased risk of osteoporotic fracture is most likely due to false-positive results.

Introduction

Osteoporosis is characterized by reduced bone density and increased bone fragility, leading to an increased risk of fracture (Recker, 2005). Its clinical significance lies in the triggering of osteoporotic fractures (e.g., fractures of the forearm, vertebrae, and hip) (Cummings and Melton, 2002). The World Health Organization estimates that 200 million people worldwide suffer from osteoporosis (Uzzan et al., 2007), placing a huge burden on families and society, and that osteoporosis has become a major public health problem. Therefore, it is important to explore the underlying pathogenic factors.

The main factors in the development of osteoporosis encompass both environmental and genetic factors. The environmental factors include smoking, exercise, and alcohol consumption (Ng et al., 2006; Kaufman et al., 2008; Binici and Gunes, 2010). Many studies have found that genetic factors play an important role in the pathogenesis of osteoporosis (Jin and Ralston, 2001; Recker and Deng, 2002). It has been estimated that the heritability of osteoporosis-related traits (e.g., bone mineral density) can be as high as 60–80% (Uitterlinden et al., 2004). To date, dozens of risk genes for osteoporosis have been identified, of which ESR1, LRP4, ITGA1, LRP5, SOST, SPP1, TNFRSF11A, TNFRSF11B, and TNFSF11 are thought to be involved in bone mineral density (BMD) homeostasis, bone remodeling, and bone matrix composition, and thus influence BMD and osteoporotic fractures. In addition, a number of candidate genes have been investigated (COL1A1, TGFB1, TGFB3, and VDR), but no clear genome-wide significant association with osteoporosis has been demonstrated (Saccone et al., 2015).

The vitamin D receptor (VDR) gene is located on chromosome 12q13 (Seuter et al., 2016) and exerts various biological effects by mediating the downstream signaling 1,25-dihydroxycholecalciferol (1,25(OH)2D3) (Fang et al., 2003). In human monocytes, 1,25(OH)2D3 regulates chromatin susceptibility at 8979 loci (Ling et al., 2016), and as such, VDR single-nucleotide polymorphisms (SNPs) have been associated with various diseases, including reduced bone mineral density and osteoporosis (Gómez et al., 1999; Garnero et al., 2005). In recent years, numerous studies have reported the association of VDR polymorphisms (e.g., BsmI, ApaI, TaqI, FokI, and Cdx2) with osteoporotic fractures. However, these results were inconsistent and even conflicting. For example, Garnero et al. found that the VDR BsmI B allele was associated with lower BMD and an increased risk of fracture (Alvarez-Hernández et al., 2003). In contrast, other studies found no association between the B allele and the risk of osteoporotic fractures (Uitterlinden et al., 2001; Horst-Sikorska et al., 2005; Iván et al., 2008; Karpiński et al., 2017). Similarly, there were conflicting associations between the ApaI, TaqI, FokI, and Cdx2 polymorphisms and osteoporotic fractures in different studies (Gennari et al., 1999; Gómez et al., 1999; Garnero et al., 2005; Nguyen et al., 2005; Fang et al., 2006; Ji et al., 2010; Horst-Sikorska et al., 2013; Jawiarczyk-Przybyłowska et al., 2019; Iveta et al., 2020). These different results may be owing to differences in sample size, ethnicity, and sampling methods used. Although correlations between the VDR BsmI, ApaI, TaqI, and FokI polymorphisms and the risk of osteoporotic fracture development have been reported in several meta-analyses (Aerssens et al., 2000; Moher et al., 2009; Shen et al., 2014; Gao et al., 2015), there are some limitations in these studies. First, their findings are inconsistent; in the study of Ji et al., the bb genotype in the BsmI gene significantly reduced the risk of fracture (odds ratio (OR) 0.87, 95% confidence interval (CI): 0.76–0.98); in the grouped study, they found that the frequency of the bb genotype was significantly decreased in patients with hip fracture, and the frequency of the Tt genotype was also decreased in patients with hip fracture (Gao et al., 2015), while the frequency of the tt genotype was increased in patients with hip fracture. In addition, they observed an increase in the frequency of the Aa genotype in patients with vertebral fractures. Similarly, in a subgroup analysis, Gao et al. found that the BsmI gene was associated with osteoporotic fractures when the control group was population-derived (OR BB vs. bb 1.22, 95% CI 1.01–1.48; OR B vs. b 1.10, 95% CI 1.00–1.20) (Aerssens et al., 2000). No significant association was found between the BmsI and TaqI by Fang et al. and the BmsI by Shen et al. (BsmI OR 0.98, 95% CI 0.86–1.12; BsmI [b vs. B] OR 1.07, 95% CI 0.90–1.29; TaqI [T vs. t] OR 0.89, 95% CI 0.68–1.15; ApaI [A vs. a] OR 0.91, 95% CI 0.76–1.08; FokI [F vs. f] OR 1.20, 95% CI 0.76–1.90) (Moher et al., 2009; Shen et al., 2014). Second, a literature quality assessment was not performed in some of the meta-analyses (Shen et al., 2014; Gao et al., 2015). Finally, the Hardy–Weinberg equilibrium (HWE) test was not performed in the three studies (Moher et al., 2009; Shen et al., 2014; Gao et al., 2015), and not all studies on the VDR polymorphisms with osteoporosis fracture risk adjusted the P-value (Aerssens et al., 2000; Moher et al., 2009; Shen et al., 2014; Gao et al., 2015). Therefore, an updated meta-analysis was conducted to provide results that were more reliable regarding these issues.

Materials and Methods

Search Strategy

The present meta-analysis was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. The databases searched included PubMed, EMBASE, China Knowledge Network, and China Wanfang Data Knowledge Service Platform to analyze the relationship between VDR polymorphisms and osteoporotic fracture risk. The search strategy was (“vitamin D receptor” or “VDR”) and (“polymorphism” or “variant” or “variation” or “mutation” or “SNP” or “genome-wide association study” or “genetic association study” or “genotype” or “allele”) and (“Fractures, Bone” or “Broken Bones” or “Fractures” or “Fracture” or “Broken Bone” or “Bone Fractures” or “Bone Fracture”). The search deadline was March 2021.

Selection Criteria

The inclusion criteria were as follows: 1) case–control or cohort studies; 2) investigation of the association between VDR BsmI, ApaI, TaqI, FokI, and Cdx2 polymorphisms and osteoporosis risk; and 3) detailed control and case group genotype data or their OR with 95% CI. The exclusion criteria were as follows: 1) overlapping studies; 2) articles without detailed genotype data; and 3) abstracts, case reports, editorials, reviews, letters, and meta-analyses.

A total of 221 articles were retrieved from all databases. In all, 194 articles were subsequently excluded because they were abstracts, case reports, editorials, reviews, letters, or meta-analyses. When the remaining 27 articles were read, two articles were excluded because patients with both osteoporosis and osteoporotic fractures were considered in the same group. In addition, two articles were found to be repetitive, and one article had missing genotype data, and attempts to contact the corresponding author have not been answered. In the end, 23 relevant studies were included. In the process of article screening, the retrieval work and the screening process were performed by Yi-yang Mu and Biao-Liu independently and then summarized, and the author Bin-Chen made the final decision when there was any disagreement.

Data Extraction

We predesigned the data extraction form. The data from the selected articles were extracted and cross-checked according to the defined inclusion and exclusion criteria. When different results were obtained, and no consensus could be reached after the discussion, a third author was invited to repeat the data extraction and check for confirmation. If the data were unclear or questionable in the article, the author was contacted to obtain the original data. The following information was extracted: first author of the article, year of publication, country of study, corresponding continent, origin of cases and controls, type of osteoporotic fracture, sex of study subjects, number of cases and controls, number of genotypes distributed among cases and controls, diagnostic criteria for osteoporotic fractures, and conclusion of the investigators.

Quality Assessment

The quality of all articles was independently assessed by two authors. We adopted and refined the quality assessment criteria from two previous meta-analyses (Aerssens et al., 2000; Moher et al., 2009). Supplementary Table S1 lists the quality assessment scales for studies on the factors associated with osteoporotic fracture risk. A total of 20 points were awarded, with articles scoring above 12 rated as excellent, those lying between 9 and 12 labeled as moderate, and studies scoring below 9 rated as poor.

Statistical Analysis

The strength of association was evaluated using ORs with their 95% CIs and was considered statistically significant when the P-value was <0.05. Comparisons were performed using the following five genetic models: 1) allelic model, 2) additive model, 3) dominant model, 4) recessive model, and 5) over-dominant model. The chi-square–based Q test and I2 values were used to assess heterogeneity. P > 0.10 and/or I2 < 50% indicated no significant heterogeneity among the included studies, and a fixed-effects model was used. Otherwise, a random-effects model was applied. Publication bias was detected using Begg’s funnel plot and Egger’s test. Sensitivity analyses were assessed using three methods: 1) exclusion of one included study; ,2) exclusion of included HWD studies and low-quality studies, and 3) only including high-quality studies, the Hardy–Weinberg equilibrium (HWE), and matched studies. A chi-square goodness-of-fit test was applied to assess the HWE, and controls were identified as the HWE when p > 0.05. In addition, the false-positive reporting probability (FPRP) test and Venice criteria were used to assess the credibility of statistically significant associations. The abovementioned statistical analyses were made possible using Stata 12.0 software.

Results

Description of Included Studies

A total of 221 relevant studies were retrieved, and 23 articles met our criteria (5,844 osteoporotic fracture cases and 19,339 controls), of which 18 articles examined VDR BsmI (involving 2,429 osteoporotic fracture cases and 5,187 controls), eight studies discussed VDR ApaI (involving 875 osteoporotic fracture cases and 2,120 controls), nine studies reported VDR TaqI (involving 860 osteoporotic fracture cases and 2,538 controls), seven studies documented VDR FokI (involving 579 osteoporotic fracture cases and 1635 controls), and three studies investigated VDR Cdx2 (involving 1101 osteoporotic fracture cases and 7859 controls), and how each of these polymorphisms correlates with osteoporotic fracture risk. In addition, 18, 5, and 1 case–control studies have been conducted in European, American, and Asian populations, respectively. Among them, four studies discussed these associations in men, and 22 studies analyzed these relationships in women. Finally, there were six high-quality studies and 12 medium-quality studies discussing VDR BsmI; two high-quality studies and seven medium-quality studies discussing VDR ApaI; two high-quality studies and six medium-quality studies on VDR TaqI; one high-quality, five medium-quality, and one low-quality studies on VDR FokI; and one medium-quality and two low-quality studies on VDR Cdx2. Table 1 shows the detailed characteristics and scores of each study. The literature selection and inclusion processes are illustrated in Figure 1. Tables 26 show the genotype frequencies of the VDR BsmI, ApaI, TaqI, FokI, and Cdx2 polymorphisms, and the impact of each on the risk of osteoporotic fracture.

TABLE 1

First author / YearCountryEthnicityGenderCasesControlsscore
NAgeaOF siteDiagnosisMatchingNAgeaHWEHealthyBMD site
Houston et al. (1996)UKEFemale4466.0 ± 0.85VerterbralWHOAge and Sex4465.3 ± 0.95HWEYesVerterbral11
Feskanich et al. (1998)USAAmFemale5462.3±5.7HipWHOAge and Sex10862.2±5.7HWEYesHip13
Feskanich et al. (1998)USAAmFemale16358.3±6.8ForearmWHOAge and Sex16358.1±6.7HWEYesForearm13
Ramalho et al. (1998)BrazilAmFemale5678.52 ± 7.2HipNeAge and Sex3678.52 ± 7.2HWEYesHip11
Gómez et al. (1999)SpainEFemale37NeVerterbralWHOSex122NeHWEYesVerterbral13
Gómez et al. (1999)SpainEMen39NeVerterbralWHOSex114NeHWEYesVerterbral13
Aerssens et al. (2000)BelgiumEFemale13578±9HipWHOAge and Sex23976±4HWEYesHip11
Langdahl et al. (2000)DenmarkEFemale8064.8 ± 8.3VerterbralWHOSex8047.2 ±13.6HWEYesVerterbral12
Langdahl et al. (2000)DenmarkEMen3055.7 ± 11.0VerterbralWHOAge and Sex7351.1 ± 15.7HWEYesVerterbral13
Välimäki et al. (2001)FinlandEFemale64NeVerterbralWHOSex108NeHWEYesVerterbral11
Uitterlinden et al. (2001)NetherlandsEFemale9766.4 ± 7.0NeWHOAge and Sex90766.4 ± 7.0HWEYesNe15
Alvarez-Hernández et al. (2003)SpainEMen2064 ±9VerterbralNeAge and Sex13464±9HWEYesVerterbral13
Garnero et al. (2005)FranceEFemale86NeNoverterbralWHOSex589NeHWEYesN/A15
Garnero et al. (2005)FranceEFemale34NeVerterbralWHOSex589NeHWEYesVerterbral15
Horst-Sikorska et al. (2005)PolandEFemale48NeNeWHOSex93NeHWEYesNe11
Efesoy et al. (2003)TurkeyAFemale1865.75±9.8VerterbralT-Score < 2.0Age and Sex7462.4±8.7HWEYesVerterbral10
Wengreen et al. (2006)USAAmFemale81976.7±9.1HipWHOAge and Sex85476±9.4HWDYesHip11
Horst-Sikorska et al. (2007)PolandEFemale8564.4 ± 10.9Vertebral and femurWHOAge and Sex19165.5 ± 9.9HWEYesVertebral and femur12
Quevedo et al. (2008)ChileAmFemale6777 ± 4HipT-Score < 2.0Age and Sex5978 ± 9HWDYesHip10
Horst-Sikorska et al. (2013)PolandEFemale16768.5 ± 8.2VerterbralWHOAge and Sex21663.5 ± 9.1HWEYesVerterbral13
Horst-Sikorska et al. (2013)PolandEFemale11768.5 ± 8.2NoverterbralWHOAge and Sex21663.5 ± 9.1HWEYesN/A13
Karpinski et al. (2017)BrazilENe10011.5±2.5NeWHOAge and Sex12713.5±2.5HWEYesNe10
Aleksandra et al. (2019)PolandENe6960.3 ± 11.2HipWHOAge and Sex5156.7 ± 11.2HWEYesHip9
Langdahl et al. (2000)DenmarkEFemale7864.8 ± 8.3VerterbralWHOSex7447.2 ± 13.6HWEYesVerterbral12
Langdahl et al. (2000)DenmarkEMen2955.7 ± 11.0VerterbralWHOAge and Sex7351.1 ± 15.7HWEYesVerterbral13
Uitterlinden et al. (2001)NetherlandsEFemale9766.4 ± 7.0NeWHOAge and Sex90766.4 ± 7.0HWEYesNe15
Alvarez-Hernández et al. (2003)SpainEMen1765 ±9VerterbralNeAge and Sex11765 ±9HWEYesVerterbral13
Horst-Sikorska et al. (2005)PolandEFemale48NeVerterbralWHOSex93NeHWEYesVerterbral11
Horst-Sikorska et al. (2007)PolandEFemale8564.4 ± 10.9HipWHOAge and Sex19165.5 ± 9.9HWEYesHip12
Quevedo et al. (2008)ChileAmFemale6777 ± 4HipT-Score < 2.0Age and Sex5978 ± 9HWEYesHip10
Horst-Sikorska et al. (2013)PolandEFemale16868.5 ± 8.2VerterbralWHOAge and Sex21663.5 ± 9.1HWEYesVerterbral13
Horst-Sikorska et al. (2013)PolandEFemale11768.5 ± 8.2NoverterbralWHOAge and Sex21663.5 ± 9.1HWEYesN/A13
Karpinski et al. (2017)BrazilENe10011.5±2.5NeWHOAge and Sex12313.5±2.5HWEYesNe10
Aleksandra et al. (2019)PolandENe6960.3 ± 11.2HipWHOAge and Sex5156.7 ± 11.2HWEYesHip9
Langdahl et al. (2000)DenmarkEFemale7864.8± 8.3VerterbralWHOSex7547.2± 13.6HWEYesVerterbral12
Langdahl et al. (2000)DenmarkEMen2955.7±11.0VerterbralWHOAge and Sex7351.1 ± 15.7HWEYesVerterbral13
Uitterlinden et al. (2001)NetherlandsEFemale9766.4 ± 7.0NeWHOAge and Sex90766.4±7.0HWEYesNe15
Alvarez-Hernández et al. (2003)SpainEMen2164 ±9VerterbralWHOAge and Sex11764 ±9HWEYesVerterbral13
Horst-Sikorska et al. (2005)PolandEFemale48NeVerterbralWHOSex93NeHWEYesVerterbral11
Nguyen et al. (2005)AustraliaEFemale69NeHipWHOSex608NeHWEYesHip12
Quevedo et al. (2008)ChileAmFemale6777 ± 4HipT-Score < 2.0Age and Sex5978 ± 9HWEYesHip10
Horst-Sikorska et al. (2013)PolandEFemale16868.5 ± 8.2VerterbralWHOAge and Sex21663.5 ± 9.1HWDYesVerterbral13
Horst-Sikorska et al. (2013)PolandEFemale11768.5 ± 8.2NoverterbralWHOAge and Sex21663.5 ± 9.1HWDYesN/A13
Karpinski et al. (2017)BrazilENe9711.5±2.5NeWHOAge and Sex12313.5±2.5HWDYesNe10
Aleksandra et al. (2019)PolandENe6960.3 ± 11.2HipWHOAge and Sex5156.7 ± 11.2HWEYesHip9
Gennari et al. (1999)BelgiumEFemale68NeVerterbralWHOSex332NeHWEYesVerterbral11
Langdahl et al. (2000)DenmarkEFemale7964.8 ± 8.3VerterbralWHOSex8047.2 ± 13.6HWEYesVerterbral12
Langdahl et al. (2000)DenmarkEMen3055.7±11.0VerterbralWHOAge and Sex7351.1±15.7HWEYesVerterbral13
Horst-Sikorska et al. (2007)PolandEFemale8564.4 ± 10.9HipWHOAge and Sex19165.5 ± 9.9HWEYesHip12
Quevedo et al. (2008)ChileAmFemale6777 ± 4HipT-Score < 2.0Age and Sex5978 ± 9HWEYesHip10
Karpinski et al. (2017)BrazilENe10011.5±2.5NeWHOAge and Sex12413.5±2.5HWDYesNe10
Aleksandra et al. (2019)PolandENe6960.3 ± 11.2HipWHOAge and Sex5156.7 ± 11.2HWEYesHip9
Iveta et al. (2020)SlovakEFemale1367.16 ± 9.22VerterbralNeAge and Sex39065.01 ± 9.28HWEYesVerterbral8
Iveta et al. (2020)SlovakEFemale6867.16 ± 9.22NoverterbralNeAge and Sex33565.01 ± 9.28HWEYesN/A8
Fang et al. (2003)DutchENe381NeNeWHOSex1534NeHWEYesNe12
Fang et al. (2003)DutchENe217NeVerterbralWHOSex1698NeHWEYesVerterbral12
Fang et al. (2003)DutchENe248NeNoverterbralWHOSex2600NeHWDYesN/A12
Ling et al. (2016)ChinaAFemale67NeNoverterbralWHOSex361NeHWEYesN/A11
Ling et al. (2016)ChinaAMen15NeNoverterbralWHOSex295NeHWEYesN/A11
Ling et al. (2016)ChinaAFemale76NeNeWHOSex352NeHWEYesNe11
Ling et al. (2016)ChinaAMen16NeNeWHOSex294NeHWEYesNe11
Iveta et al. (2020)SlovakEFemale1367.16 ± 9.22VerterbralNeAge and Sex39065.01 ± 9.28HWEYesVerterbral8
Iveta et al. (2020)SlovakEFemale6867.16 ± 9.22NoverterbralNeAge and Sex33565.01 ± 9.28HWEYesN/A8

Main characteristics and Quality score of studies included.

Ne = not available : N/A=Non-vertebral fractures; OF = Osteoporotic fracture;

a

1= (Mean±SD) yrs;HWE: Hardy-Weinberg equilibrium;HWD :Hardy Weinberg Disequilibrium

FIGURE 1

FIGURE 1

Flow diagram of the literature search.

TABLE 2

First author/yearCountryEthnicitySource of controlsFracture typeSexHWENumber of samplesGenotypes of casesAlleles of casesMinor allele frequencyGenotypes of controlsControls' allelesMinor allele frequency
chi2PCasesControlsTotalB/BB/bb/bBbB/BB/bb/bBb
Houston et al. (1996)United KingdomEHospitalVertebralF0.5710.44984444888191735531.5142857149191637511.378378378
Feskanich et al. (1998)United StatesAmPopulationHipF0.0850.77025410816216211753551.037735849165339851311.541176471
Feskanich et al. (1998)United StatesAmPopulationForearmF2.0550.15171631633262583551331931.451127822689481411851.312056738
Ramalho et al. (1998)BrazilAmHospitalHipF3.8250.050556369213232049631.2857142867111825471.88
Gómez et al. (1999)SpainEPopulationVertebralF1.3770.2407371221597201034401.176470588205151911531.681318681
Gómez et al. (1999)SpainEPopulationVertebralM0.2830.5945391141536181530481.6185838941341.425531915
Aerssens et al. (2000)BelgiumEHospitalHipF0.5470.45941352393742660491121581.41071428652125622292491.087336245
Langdahl BL et al. (2000)DenmarkECommunityVertebralF1.7490.1860808016023381984760.90476190525342184760.904761905
Langdahl BL et al. (2000)DenmarkECommunityVertebralM2.8930.08903073103816632280.87515283058881.517241379
Välimäki et al. (2001)FinlandEHospitalVertebralF1.3070.2529641081729352053751.41509434105444741421.918918919
Uitterlinden et al. (2001)NetherlandsEPopulationAnyF3.0450.081097907100474149551392.52727272717241631976010541.386842105
Alvarez-Hernández et al. (2003)SpainEPopulationVerterbralM0.2480.61832013415439815251.6666666672268441121561.392857143
Garnero et al. (2005)FranceEPopulationNon-vertebralF0.1400.70828658967420462086861902862134667121.527896996
Garnero et al. (2005)FranceEPopulationVertebralF0.1400.7082345896235161326421.615384615902862134667121.527896996
Horst-Sikorska et al. (2005)PolandEPopulationAnyF1.5390.214748931413192625712.84183936751111.48
Efesoy et al. (2003)TurkeyAHospitalVertebralF2.2060.1375187492010810262.612431967811.208955224
Wengreen et al. (2006)United StatesAmHospitalHipF4.1150.042581985416731543932727019371.33666191214037633865610521.603658537
Horst-Sikorska et al. (2007)PolandEHospitalVertebral and femurF0.9130.339485191276103540551152.0909090913385731512311.529801325
Quevedo et al. (2008)ChileAmHospitalHipF3.9890.0458675912611461068660.9705882359371355631.145454545
Horst-Sikorska et al. (2013)PolandEHospitalVertebralF2.2400.13451672163832780601342001.4925373134294801782541.426966292
Horst-Sikorska et al. (2013)PolandEHospitalNon-vertebralF2.2400.1345117216333135153771572.0389610394294801782541.426966292
Karpiński et al. (2017)BrazilEHospitalAnyM/F0.2990.584610012722784943651352.0769230771964441021521.490196078
Aleksandra et al. (2019)PolandEHospitalHIpM/F1.0510.3053695112032261190480.53333333320211061410.672131148

Genotype frequencies of VDR BsmI polymorphism in studies included in this meta-analysis.

TABLE 3

First author/yearCountryEthnicitySource of controlsFracture typeSexHWENumber of samplesGenotypes of casesAlleles of casesMinor allele frequencyGenotypes of controlsControls’ allelesMinor allele frequency
chi2prCasesControlsTotalA/AA/aa/aAaA/AA/aa/aAa
Langdahl et al. (2000)DenmarkECommunityVertebralF1.1550.2826787415222441288680.77272727325321782660.804878049
Langdahl et al. (2000)DenmarkECommunityVertebralM1.7790.18232973102817433250.75757575818421378680.871794872
Uitterlinden et al. (2001)NetherlandsEPopulationAnyF2.7090.0998979071004154834781161.4871794872584282219448700.921610169
Alvarez-Hernández et al. (2003)SpainEPopulationVertebralM0.1180.731317117134412120140.73360241231080.87804878
Horst-Sikorska et al. (2005)PolandEPopulationVertebralF1.4450.229348931418211937591.594594595245217100860.86
Horst-Sikorska W et al. (2007)PolandEPopulationHipF0.4500.50248519127620362976740.97368421149100421981840.929292929
Quevedo et al. (2008)ChileAmHospitalHipF0.3830.5363675912625311181530.65432098818271463550.873015873
Horst-Sikorska et al. (2013)PolandEHospitalVertebralF1.5080.21951682163844183441651711.03636363648117512132191.028169014
Horst-Sikorska et al. (2013)PolandEHospitalNon-vertebralF1.5080.2195117216333185940951391.46315789548117512132191.028169014
Karpinski et al. (2017)BrazilEHospitalAnyM/F0.2040.6516100123223234334891111.2471910112964301221241.016393443
Aleksandra et al. (2019)PolandEHospitalHipM/F0.1570.691669511201735176969115241254480.888888889

Genotype frequencies of VDR ApaI polymorphism in studies included in this meta-analysis.

TABLE 4

First author/yearCountryEthnicitySource of controlsFracture typeSexHWENumber of samplesGenotypes of casesAlleles of casesMinor allele frequencyGenotypes of controlsControls' allelesMinor allele frequency
chi2PrCasesControlsTotalT/TT/tt/tTtT/TT/tt/tTt
Langdahl et al. (2000)DenmarkECommunityVertebralF0.2310.6304787515323411487690.79310344828341390600.666666667
Langdahl et al. (2000)DenmarkECommunityVertebralM00.99452973102819235230.65714285729341092540.586956522
Uitterlinden et al. (2001)NetherlandsEPopulationAnyF3.0450.08197907100449417139550.39568345331941617210547600.721062619
Alvarez-Hernández et al. (2003)SpainEPopulationVertebralM0.5230.46952111713877721211406017140940.671428571
Horst-Sikorska et al. (2005)PolandEPopulationVertebralF2.5540.1148931412619371250.352112676383718113730.646017699
Nguyen et al. (2005)AustraliaEPopulationHipF1.0230.31196960867724271875630.84218302887384780.647696477
Quevedo et al. (2008)ChileAmHospitalHipF1.9120.1668675912626311083510.6144578311734868500.735294118
Horst-Sikorska et al. (2013)PolandEHospitalVertebralF4.2370.03961682163846279272031330.6551724148290442541780.700787402
Horst-Sikorska et al. (2013)PolandEHospitalNon-vertebralF4.2370.0396117216333554913159750.4716981138290442541780.700787402
Karpinski et al. (2017)BrazilEHospitalAnyM/F21.41709712322043522138560.40579710144772165810.490909091
Aleksandra et al. (2019)PolandEHospitalHipM/F0.4620.4968695112032261190480.5333333332022962400.64516129

Genotype frequencies of VDR TaqI polymorphism in studies included in this meta-analysis.

TABLE 5

First author/yearCountryEthnicitySource of controlsFracture typeSexHWENumber of samplesGenotypes of casesAlleles of casesMinor allele frequencyGenotypes of controlsControls' allelesMinor allele frequency
chi2prCasesControlsTotalF/FF/ff/fFfF/FF/ff/fFf
Gennari et al. (1999)BelgiumEHospitalVertebralF0.3730.54136833240021301772640.888888889138156384322320.537037037
Langdahl et al. (2000)DenmarkECommunityVertebralF2.5540.11798015928411097610.62886597934311599610.616161616
Langdahl et al. (2000)DenmarkECommunityVertebralM0.0180.894330731031213537230.6216216223034994520.553191489
Horst-Sikorska W et al. (2007)PolandEPopulationHipF1.7430.186885191276403510115550.478260877682332341480.632478632
Quevedo et al. (2008)ChileAmHospitalHipF0.1070.744675912629271185490.5764705882725779390.493670886
Karpinski et al. (2017)BrazilEHospitalAnyM/F7.5380.006100124224264925101990.980198023276161401080.771428571
Aleksandra et al. (2019)PolandEHospitalHipM/F0.0420.8383695112027321086520.6046511631824960420.7
Iveta et al. (2020)SlovakEHospitalVertebralF0.2050.65051339040319311151.363636364861991053714091.102425876
Iveta et al. (2020)SlovakEHospitalNon-vertebralF0.5070.4766683354035342944922.09090909182174793383320.982248521

Genotype frequencies of VDR FokI polymorphism in studies included in this meta-analysis.

TABLE 6

First author/yearCountryEthnicitySource of controlsFracture typeSexHWENumber of samplesGenotypes of casesAlleles of casesMinor allele frequencyGenotypes of controlsControls' allelesMinor allele frequency
chi2prCasesControlsTotalG/GA/GA/AGAG/GA/GA/AGA
Fang et al. (2003)NetherlandsEHospitalAnyF/M2.2930.1338115341915268103106391230.19248826310024646824686000.243111831
Fang et al. (2003)NetherlandsEHospitalVertebralF/M2.1590.141721716981915156565368660.17934782611145117327396570.239868565
Fang et al. (2003)NetherlandsEHospitalNon-vertebralF/M4.5470.03324826002848173705416800.192307692172176811142109900.235154394
Ling et al. (2016)ChinaAHospitalNon-vertebralF1.4270.23236736142815351765691.061538462130164674242980.702830189
Ling et al. (2016)ChinaAHospitalNon-vertebralM0.5950.4405152953108612280.36363636493151513372530.75074184
Ling et al. (2016)ChinaAHospitalAnyF1.1400.28577635242819381976761126161654132910.704600484
Ling et al. (2016)ChinaAHospitalAnyM0.5100.475162943108712390.39130434893150513362520.75
Iveta et al. (2020)SlovakEHospitalVertebralF0.0010.9708133904037602060.3260117136371430.224489796
Iveta et al. (2020)SlovakEHospitalNon-vertebralF1.2590.2619683354032138980560.7246854577930.16117851

Genotype frequencies of VDR Cdx2 polymorphism in studies included in this meta-analysis.

Meta-Analysis Results

We did not observe a significant association between the VDR BsmI polymorphism and the risk of osteoporotic fractures (p > 0.05) in all genetic models. However, subgroup analysis by race showed that the VDR BsmI B allele increased the risk of osteoporotic fracture (OR 1.17, 95% CI 1.03–1.34), and the BB genotype (additive model: OR 0.74, 95% CI 0.58–0.94; recessive model: OR 0.81, 95% CI 0.66–0.99) reduced the risk of osteoporotic fractures in Americans. We believe that articles with HWD control data should be excluded because the inclusion of HWD articles may interfere with the real results. When HWD-related article data were excluded, the positive results of the subgroup analysis corresponding to race changed. Table 7 summarizes the evaluation of the association between VDR BsmI polymorphism and the risk of osteoporotic fractures. Overall, the VDR BsmI polymorphism did not significantly increase the risk of osteoporotic fractures, as shown in Figure 2.

TABLE 7

Genetic modelVariableTest of associationTests for heterogeneityEgger’s test
OR (95% CI)PPhI2 (%)PE
B vs bOverall0.94 (0.81–1.09)0.413<0.00160.700.450
Europe0.92 (0.78–1.09)0.322<0.00161.50
America1.18 (0.82–1.70)0.3630.13949.4
Female0.92 (0.77–1.10)0.369<0.00165.60
Male1.09 (0.69–1.71)0.7090.18341.1
bb vs BBOverall1.13 (0.83–1.53)0.437<0.00155.500.953
Europe1.20 (0.86–1.67)0.2890.00256.20
America0.73 (0.38–1.40)0.3470.18640.5
Female1.16 (0.81–1.65)0.417<0.00161.10
Male0.83 (0.38–1.82)0.6420.29518.00
Bb + bb vs BBOverall1.11 (0.88–1.39)0.3810.04437.500.399
Europe1.18 (0.93–1.49)0.1710.10032.10
America0.72 (0.40–1.31)0.2840.18241.3
Female1.13 (0.86–1.48)0.3770.02047.0
Male0.91 (0.49–1.69)0.7560.8230.00
bb vs BB + BbOverall1.08 (0.89–1.31)0.4570.00748.400.098
Europe1.08 (0.87–1.35)0.4710.00752.00
America0.91 (0.59–1.42)0.6900.24528.90
Female1.09 (0.87–1.36)0.4490.00653.50
Male0.88 (0.40–1.95)0.7560.09857.00
BB + bb vs BbOverall1.01 (0.89–1.15)0.8190.9000.000.372
Europe0.99 (0.87–1.14)0.9350.8930.00
America1.13 (0.39–3.13)0.5450.29917.10
Female1.01 (0.88–1.16)0.8570.8290.00
Male0.95 (0.56–1.60)0.8460.30515.80

Pooled estimates of association of VDR BsmI polymorphism and the risk of osteoporotic fracture.

VDR BsmI: allele model: B vs. b, additive model: bb vs. BB, dominant model: Bb + bb vs. BB, recessive model: bb vs. BB+ Bb, over-dominant model: BB+ bb vs. Bb.

FIGURE 2

FIGURE 2

Forest plots of all selected studies on the association between VDR Bsml polymorphism and the risk of osteoporotic fracture in different races [(A) allele model, (B) additive model, (C) dominant model, and (D) recessive model].

In the overall analysis, it was not found whether VDR ApaI polymorphism could significantly increase the risk of osteoporotic fracture (p > 0.05 in all genetic models). When stratified by race, the results showed that in the European population, the aa genotype increased the risk of osteoporotic fracture compared with the AA genotype (allelic model: OR 0.83, 95% CI 0.71–0.97; additive model: OR 1.50, 95% CI 1.09–2.07; dominant model: OR 1.26, 95% CI 1.02–1.56; recessive model: OR 1.40, 95% CI 1.07–1.83). All data are shown in Table 8 and Figure 3.

TABLE 8

Genetic modelVariableTest of associationTests for heterogeneityEgger’s test
OR (95% CI)PPhI2 (%)PE
A vs aOverall0.86 (0.74–1.01)0.0720.09438.300.220
Europe0.83 (0.71–0.97)0.0190.17030.00
Female0.84 (0.67–1.04)0.1040.03156.90
Male1.19 (0.75–1.91)0.4620.8590
aa vs AAOverall1.38 (0.99–1.93)0.0570.08739.300.186
Europe1.50 (1.09–2.07)0.0120.16830.20
Female1.50 (0.97–2.32)0.0680.03455.90
Male0.57 (0.17–1.87)0.3530.6040
Aa + aa vs AAOverall1.21 (0.99–1.49)0.0630.48200.947
Europe1.26 (1.02–1.56)0.0320.5510
Female1.27 (0.95–1.69)0.1030.19230.90
Male1.01 (0.47–2.14)0.9860.6130
aa vs AA + AaOverall1.31 (1.00–1.73)0.0540.06043.600.061
Europe1.40 (1.07–1.83)0.0150.10538.00
Female1.39 (0.99–1.94)0.056<0.04054.60
Male0.56 (0.19–1.58)0.2710.3530
AA + aa vs AaOverall1.08 (0.90–1.30)0.4200.31913.100.215
Europe1.08 (0.88–1.33)0.4430.24821.10
Female1.10 (0.88–1.36)0.3980.28918.50
Male0.70 (0.33–1.48)0.3490.27715.20

Pooled estimates of association of VDR ApaI polymorphism and the risk of osteoporotic fracture.

VDR ApaI: allele model: A vs. a, additive model: aa vs. AA, dominant model: Aa + aa vs. AA, recessive model: aa vs. AA + Aa, over-dominant model: AA+ aa vs. Aa.

Bold values represent with statistical significance.

FIGURE 3

FIGURE 3

Forest plots of all selected studies on the association between VDR Apal polymorphism and the risk of osteoporotic fracture in different races [(A) allele model, (B) additive model, (C) dominant model, and (D) recessive model].

As shown in Tables 911 and Figures 46, there were no significant associations between the VDR TaqI, FokI, and Cdx2 polymorphisms and the risk of osteoporotic fractures.

TABLE 9

Genetic modelVariableTest of associationTests for heterogeneityEgger’s test
OR (95% CI)PPhI2 (%)PE
T vs tOverall1,10 (0.83–1.47)0.5100.00565.800.497
Europe1.09 (0.78–1.51)0.6230.00270.70
Female1.20 (0.81–1.78)0.3560.00276.50
Male0.78 (0.50–1.23)0.2840.5380
tt vs TTOverall0.82 (0.44–1.54)0.5440.00466.400.549
Europe0.82 (0.40–1.68)0.5900.00271.20
Female0.70 (0.29–1.68)0.4220.00177.80
Male1.54 (0.51–4.67)0.4450.26718.8
Tt + tt vs TTOverall0.84 (0.62–1.14)0.2540.11939.000.183
Europe0.87 (0.62–1.23)0.4390.08546.00
Female0.77 (0.53–1.13)0.1870.08251.70
Male1.36 (0.69–2.68)0.3790.4630
tt vs TT + TtOverall0.91 (0.49–1.66)0.7490.00170.200.276
Europe0.87 (0.43–1.75)0.6990.00174.50
Female0.79 (0.355–1.78)0.5680.00178.20
Male1.29 (0.21–8.00)0.7840.05373.30
TT + tt vs TtOverall1.15 (0.87–1.50)0.3230.21926.200.705
Europe1.10 (0.82–1.47)0.5370.19430.70
Female1.18 (0.92–1.52)0.1860.4270.00
Male0.97 (0.22–4.32)0.9680.02480.30

Pooled estimates of association of VDR TaqI polymorphism and the risk of osteoporotic fracture.

VDR TaqI: allele model: T vs. t, additive model: tt vs. TT, dominant model: Tt + tt vs. TT, recessive model: tt vs. TT + Tt, over-dominant model: TT + tt vs. Tt.

TABLE 10

Genetic modelVariableTest of associationTests for heterogeneityEgger’s test
OR (95% CI)PPhI2 (%)PE
F vs fOverall0.84 (0.63–1.11)0.2100.00962.800.609
Europe0.84 (0.61–1.15)0.2690.00568.00
Female0.79 (0.56–1.11)0.1780.00570.20
ff vs FFOverall1.48 (0.80–2.75)0.2120.00664.300.949
Europe1.49 (0.73–3.03)0.2740.00369.40
Female1.68 (0.77–3.67)0.1880.00371.90
Ff + ff vs FFOverall1.27 (0.88–1.82)0.1960.07146.300.199
Europe1.31 (0.86–2.00)0.2060.04353.80
Female1.43 (0.90–2.27)0.1340.03658.00
ff vs FF + FfOverall1.23 (0.77–1.97)0.3770.01958.200.122
Europe1.20 (0.71–2.03)0.5030.01064.20
Female1.28 (0.72–2.27)0.4000.00967.40
FF + ff vs FfOverall0.97 (0.78–1.22)0.8210.68400.237
Europe0.96 (0.76–1.22)0.7500.5840.00
Female0.96 (0.75–1.22)0.7190.4630.00

Pooled estimates of association of VDR FokI polymorphism and the risk of osteoporotic fracture.

VDR FokI: allele model: F vs. f, additive model: ff vs. FF, dominant model: Ff + ff vs. FF, recessive model: ff vs. FF + Ff, over-dominant model: FF + ff vs. Ff.

TABLE 11

Genetic modelVariableTest of associationTests for heterogeneityEgger’s test
OR (95% CI)PPhI2 (%)PE
G vs AOverall0.89 (0.56–1.41)0.628<0.00190.400.697
AA vs GGOverall1.22 (0.48–3.13)0.679<0.00183.100.918
AG + AA vs GGOverall1.23 (0.71–2.12)0.463<0.00188.300.434
AA vs GG + AGOverall1.11 (0.55–2.24)0.764<0.00173.500.830
GG + AA vs AGOverall0.84 (0.57–1.23)0.377<0.00176.600.385

Pooled estimates of association of VDR Cdx2 polymorphism and the risk of osteoporotic fracture.

VDR Cdx2: allele model: G vs. A, additive model: AA vs. GG, dominant model: AG + AA vs. GG, recessive model: AA vs. GG + AG, over-dominant model: GG + AA vs. AG.

FIGURE 4

FIGURE 4

Forest plots of all selected studies on the association between VDR Taql polymorphism and the risk of osteoporotic fracture in different races [(A) allele model, (B) additive model, (C) dominant model, and (D) recessive model].

FIGURE 5

FIGURE 5

Forest plots of all selected studies on the association between VDR Fokl polymorphism and the risk of osteoporotic fracture in different races [(A) allele model, (B) additive model, (C) dominant model, and (D) recessive model].

FIGURE 6

FIGURE 6

Forest plots of all selected studies on the association between VDR Cdx-2 polymorphism and the risk of osteoporotic fracture in different races [(A) allele model, (B) additive model, (C) dominant model, and (D) recessive model].

Table 12 shows the results of articles that did not exclude HWD.

TABLE 12

Genetic modelVariableTest of associationTests for heterogeneityEgger’s test
OR (95% CI)PPhI2 (%)PE
Pooled estimates of association of VDR BsmI polymorphism and the risk of osteoporotic fracture
 B vs bOverall0.96 (0.84–1.11)0.60<0.00164.200.353
Europe0.92 (0.78–1.09)0.322<0.00161.50
America1.17 (1.03–1.34)0.0180.376.4
Female0.95 (0.81–1.12)0.564<0.00168.60
Male1.09 (0.69–1.71)0.7090.18341.1
 bb vs BBOverall1.07 (0.81–1.41)0.635<0.00157.800.229
Europe1.20 (0.86–1.67)0.2890.00256.20
America0.74 (0.58–0.94)0.0120.4800
Female1.08 (0.79–1.47)0.629<0.00162.80
Male0.83 (0.38–1.82)0.6420.29518.00
 Bb + bb vs BBOverall1.06 (0.87–1.30)0.5350.04236.500.133
Europe1.18 (0.93–1.49)0.1710.10032.10
America0.83 (0.67–1.02)0.0790.4550.00
Female1.08 (0.86–1.36)0.5240.02045.30
Male0.91 (0.49–1.69)0.7560.8230.00
 bb vs BB + BbOverall1.03 (0.85–1.24)0.774<0.00156.200.617
Europe1.08 (0.87–1.35)0.4710.00752.00
America0.81 (0.66–0.99)0.0400.0166.80
Female1.03 (0.84–1.27)0.781<0.00160.90
Male0.88 (0.40–1.95)0.7560.09857.00
 BB + bb vs BbOverall0.96 (0.86–1.06)0.4290.8630.000.496
Europe0.99 (0.87–1.14)0.9350.8930.00
America0.93 (0.75–1.16)0.5270.31515.60
Female0.95 (0.85–1.96)0.3720.7870.00
Male0.95 (0.56–1.60)0.8460.30515.80
Pooled estimates of association of VDR ApaI polymorphism and the risk of osteoporotic fracture
 A vs aOverall0.86 (0.74–1.01)0.0720.09438.300.220
Europe0.83 (0.71–0.97)0.0190.17030.00
Female0.84 (0.67–1.04)0.1040.03156.90
Male1.19 (0.75–1.91)0.4620.8590
 aa vs AAOverall1.38 (0.99–1.93)0.0570.08739.300.186
Europe1.50 (1.09–2.07)0.0120.16830.20
Female1.50 (0.97–2.32)0.0680.03455.90
Male0.57 (0.17–1.87)0.3530.6040
 Aa + aa vs AAOverall1.21 (0.99–1.49)0.0630.48200.947
Europe1.26 (1.02–1.56)0.0320.5510
Female1.27 (0.95–1.69)0.1030.19230.90
Male1.01 (0.47–2.14)0.9860.6130
 aa vs AA + AaOverall1.31 (1.00–1.73)0.0540.06043.600.061
Europe1.40 (1.07–1.83)0.0150.10538.00
Female1.39 (0.99–1.94)0.056<0.04054.60
Male0.56 (0.19–1.58)0.2710.3530
 AA + aa vs AaOverall1.08 (0.90–1.30)0.4200.31913.100.215
Europe1.08 (0.88–1.33)0.4430.24821.10
Female1.10 (0.88–1.36)0.3980.28918.50
Male0.70 (0.33–1.48)0.3490.27715.20
Pooled estimates of association of VDR TaqI polymorphism and the risk of osteoporotic fracture
 T vs tOverall1,15 (0.95–1.40)0.1590.01156.400.466
Europe1.15 (0.93–1.42)0.2120.00660.70
Female1.22 (0.94–1.58)0.1380.00468.70
Male0.78 (0.50–1.23)0.2840.5380
 tt vs TTOverall0.77 (0.49–1.21)0.2640.00857.900.895
Europe0.77 (0.47–1.26)0.2970.00562.20
Female0.68 (0.38–1.20)0.1810.00370.30
Male1.54 (0.51–4.67)0.4450.26718.8
 Tt + tt vs TTOverall0.82 (0.66–1.01)0.0610.18727.000.336
Europe0.83 (0.67–1.05)0.1160.14932.30
Female0.80 (0.61–1.05)0.1010.10343.20
Male1.36 (0.69–2.68)0.3790.4630
 tt vs TT + TtOverall0.84 (0.54–1.32)0.4530.00263.800.775
Europe0.82 (0.50–1.33)0.4210.00167.10
Female0.74 (0.43–1.26)0.2700.00271.80
Male1.29 (0.21–8.00)0.7840.05373.30
 TT + tt vs TtOverall1.09 (0.89–1.34)0.3870.21723.800.743
Europe1.06 (0.86–1.31)0.5600.21524.80
Female1.05 (0.86–1.29)0.6150.3756.90
Male0.97 (0.22–4.32)0.9680.02480.30
Pooled estimates of association of VDR FokI polymorphism and the risk of osteoporotic fracture
 F vs fOverall0.83 (0.65–1.05)0.1210.01657.500.573
Europe0.83 (0.63–1.08)0.1610.00962.80
Female0.79 (0.56–1.11)0.1780.00570.20
 ff vs FFOverall1.53 (0.90–2.61)0.1160.01159.900.996
Europe1.54 (0.85–2.81)0.1570.00664.90
Female1.68 (0.77–3.67)0.1880.00371.90
 Ff + ff vs FFOverall122 (0.89–1.66)0.2200.10040.100.153
Europe1.24 (0.87–1.78)0.2310.06447.60
Female1.43 (0.90–2.27)0.1340.03658.00
 ff vs FF + FfOverall1.34 (0.88–2.04)0.1670.02056.100.086
Europe1.32 (0.83–2.10)0.2400.01161.60
Female1.28 (0.72–2.27)0.4000.00967.40
Male1.42 (0.43–4.66)0.561
 FF + ff vs FfOverall1.06 (0.86–1.30)0.6100.43700.173
Europe1.05 (0.83–1.32)0.7110.33712.00
Female0.96 (0.75–1.22)0.7190.4630.00
Pooled estimates of association of VDR Cdx2 polymorphism and the risk of osteoporotic fracture
 G vs AOverall0.92 (0.63–1.11)0.691<0.00189.500.599
 AA vs GGOverall1.08 (0.46–2.53)0.866<0.00182.600.903
 AG + AA vs GGOverall1.17 (0.76–1.82)0.477<0.00187.000.362
 AA vs GG + AGOverall0.99 (0.52–1.89)0.980<0.00173.300.762
 GG + AA vs AGOverall0.88 (0.64–1.20)0.403<0.00173.600.325

Data related to the HWD article were not excluded.

VDR BsmI: allele model: B vs. b, additive model: bb vs. BB, dominant model: Bb + bb vs. BB, recessive model: bb vs. BB+ Bb, over-dominant model: BB+ bb vs. Bb. VDR ApaI: allele model: A vs. a, additive model: aa vs. AA, dominant model: Aa + aa vs. AA, recessive model: aa vs. AA + Aa, over-dominant model: AA+ aa vs. Aa. VDR TaqI: allele model: T vs. t, additive model: tt vs. TT, dominant model: Tt + tt vs. TT, recessive model: tt vs. TT + Tt, over-dominant model: TT + tt vs. Tt. VDR FokI: allele model: F vs. f, additive model: ff vs. FF, dominant model: Ff + ff vs. FF, recessive model: ff vs. FF + Ff, over-dominant model: FF + ff vs. Ff. VDR Cdx2: allele model: G vs. A, additive model: AA vs. GG, dominant model: AG + AA vs. GG, recessive model: AA vs. GG + AG, over-dominant model: GG + AA vs. AG.

Heterogeneity and Sensitivity Analyses

We observed heterogeneity in the overall and several subgroup analyses. Heterogeneity may be attributed to factors such as race, sex, and HWE. To explore the source of heterogeneity, a regression meta-analysis was used. However, no obvious source of heterogeneity was found by the results of regression meta-analyses. However, if it was taken into consideration that the previous exclusion of HWD-related articles leads to significant results in subgroup analysis, then it can be said that the source of heterogeneity might be HWD-related. Sensitivity analysis was estimated using three methods. First, a study was deleted every time to evaluate its robustness, and no change was observed in the research results. However, a significant change was observed in the obtained results once when low-quality and HWD studies were excluded. In previous studies, the VDR BsmI B allele increased the risk of osteoporotic fracture (OR 1.17, 95% CI 1.03–1.34), and the bb genotype reduced the risk of osteoporotic fracture in the United States (additive model: OR 0.74, 95% CI 0.88–0.94; allelic model: OR 0.81, 95% CI 0.66–0.99), but after excluding low-quality and HWD studies, the results showed no significant association between VDR BsmI gene polymorphism and fracture risk in the American population (allelic model: OR 1.18, 95% CI 0.82–1.70; additive model: OR 0.73, 95% CI 0.38–1.40; recessive model: OR 0.91, 95% CI 0.59–1.42). In addition, an increased risk of osteoporosis fracture was found in individuals with the AA genotype only in the European population (allele model: OR 0.83, 95% CI 0.70–0.98; additive model: OR 1.52, 95% CI 1.07–2.16; dominant model: OR 1.26, 95% CI 1.01–1.57; recessive model: OR 1.42, 95% CI 1.06–1.90), which was also different from previous studies (allelic model: OR 0.83, 95% CI 0.71–0.97; additive model: OR 1.50, 95% CI 1.09–2.07; dominant model: OR 1.26, 95% CI 1.02–1.56; recessive model: OR 1.40, 95% CI 1.07–1.83). In addition, when the studies were limited to only high quality, HWE, and matching, the corresponding total OR value was not significantly changed. The sensitivity analysis results are presented in Table 13.

TABLE 13

Genetic modelTest of associationTests for heterogeneity
OR (95% CI)PPhI2 (%)
VDR BsmI
 B vs b0.93 (0.79–1.08)0.3390.00061.60
 bb VS BB1.15 (0.84–1.58)0.3700.00156.70
 Bb + bb VS BB1.13 (0.90–1.43)0.2980.04238.50
 bb VS BB + Bb1.09 (0.89–1.32)0.4150.00650.20
 BB + bb VS Bb1.01 (0.79–1.15)0.8680.8720
VDR ApaI
 A vs a0.86 (0.73–1.03)0.1000.06344.3
 aa VS AA1.39 (0.96–1.99)0.0790.05945.1
 Aa + aa VS AA1.21 (0.97–1.50)0.0860.3915.5
 aa VS AA + Aa1.33 (0.99–1.78)0.0630.04448.1
 AA + aa VS Aa1.09 (0.90–1.33)0.3830.26918.9
VDR TaqI
 T vs t1.09 (0.78–1.51)0.6240.00270.7
 tt VS TT0.83 (0.40–1.71)0.6110.00271.2
 Tt + tt VS TT0.86 (0.61–1.22)0.3900.07647.6
 tt VS TT + Tt0.90 (0.45–1.82)0.7700.00174.4
 TT + tt VS Tt1.13 (0.83–1.54)0.4410.15036.4
VDR FokI
 F vs f0.90 (0.67–1.21)0.4950.07652.8
 ff VS FF1.23 (0.64–2.38)0.5320.04558.9
 Ff + ff VS FF1.12 (0.83–1.49)0.4640.3686.8
 ff VS FF + Ff1.17 (0.63–2.19)0.6210.03361.8
 FF + ff VS Ff0.98 (0.74–1.29)0.8680.5350

Pooled estimates of association of VDR BsmI, ApaI, TaqI, and FokI polymorphisms and the risk of osteoporotic fracture, excluding low-quality and HWD studies.

Publication Bias

Publication bias was evaluated using Begg’s funnel plot and Egger’s test. The shape of the funnel plot shows that there was no obvious funnel asymmetry in the entire population (Figure 7). Egger’s test also showed no evidence of significant publication bias (p > 0.05 in all genetic models), as displayed in Tables 711.

FIGURE 7

FIGURE 7

Begg’s funnel plot to access publication bias.

Credibility of the Identified Genetic Associations

We determined that significant associations meeting the following statistical criteria were classified as “positive results” (Montazeri et al., 2019): 1) the P value of the Z-test <0.05 in at least two gene models; 2) at the P value level of 0.05, the FPRP was <0.2; 3) statistical power >0.8; and 4) I2 < 50%. Results were considered as “less credible results” with a lower threshold when the following conditions were met: 1) p < 0.05 in at least one of the genetic models; 2) the statistical power was between 50 and 79%, FPRP >0.2, or I2 > 50%. After confidence evaluation, it was determined that the statistically significant associations in this meta-analysis were “unreliable.” The detailed confidence evaluation results are presented in Table 14.

TABLE 14

VariablesOR (95% CI)I2 (%)Statistical powerPrior probability of 0.001
0R = 1.2OR = 1.50R = 1.2OR = 1.5
Europe
 A vs a0.83 (0.71–0.97)30.000.4800.9970.9760.950
 aa vs AA1.50 (1.09–2.07)30.200.0870.5000.9940.965
 Aa + aa vs AA1.26 (1.02–1.56)00.3270.9450.9900.973
 aa vs AA + Aa1.40 (1.07–1.83)38.000.1300.6930.9910.952

False-positive report probability values for the statistically significant associations in the current meta-analysis.

Discussion

Osteoporosis is characterized by decreased bone density and increased bone fragility, which leads to increased fracture risk (Recker, 2005). Genes play an important role in the development of osteoporotic fractures, and the VDR gene has been extensively studied as a candidate gene that plays a key role in regulating bone resorption and metabolism (Jin and Ralston, 2001; Recker and Deng, 2002), and influencing bone mass (Kim et al., 2007). Therefore, it is important to study the relationship between VDR polymorphisms and osteoporotic fracture risk. Many previous studies have attempted to clarify the relationship between the polymorphisms of VDR and the risk of osteoporotic fracture. Unfortunately, there is no reliable evidence to show whether there is a relationship between them, which may be due to different reasons, including small sample size, race, and regional differences. Therefore, a meta-analysis is a valid alternative.

This meta-analysis included 23 studies, among which 18 explored the relationship between the VDR polymorphism BsmI and osteoporosis fracture risk, eight studies reported VDR ApaI polymorphism, nine studies reported VDR TaqI polymorphism, seven studies reported VDR FokI polymorphism, and three studies were related to VDR Cdx2 polymorphism. In addition, five genetic models were compared. Overall, the VDR BsmI polymorphism had no significant effect on the risk of osteoporotic fractures. However, in subgroup analysis, there was a significant correlation between the two. Moreover, the VDR ApaI polymorphism also did not significantly affect the risk of osteoporotic fracture. According to racial stratification, it was found that the genotype aa increased the risk of osteoporotic fracture in European countries compared with the AA genotype. However, no meaningful results were found regarding the relationship between the VDR polymorphisms (TaqI, VDR FokI, and Cdx2) and osteoporotic fracture. Moreover, when the low-quality and HWD research were excluded, and when the combined analysis involved only high-quality, HWE, and matching research, no significant correlation was observed. Furthermore, the current meta-analysis was carried out by applying multiple subgroups and different genetic models at the expense of multiple comparisons; in this case, the aggregated P value must be adjusted (Attia et al., 2003). The Venice standard, statistical ability, and I2 value are important standards (Langdahl et al., 2000). Therefore, the FPRP and Venice standards were used to evaluate positive results. After the credibility evaluation, it was determined that “positive results are not credible,” which are statistically significant in the current meta-analysis. After the regression meta-analysis, no source of obvious heterogeneity was identified. In addition, no obvious asymmetry was found in the study of VDR BsmI, ApaI, TaqI, and FokI polymorphisms using Begg’s funnel plot and Egger’s test. However, owing to the limited number of studies, Begg’s funnel plot was not used to explore publication deviation in VDR Cdx2 research. Finally, Egger’s test showed that there was no clear statistical evidence to show publication bias.

Four meta-analyses analyzed the association between VDR polymorphisms and risk of osteoporotic fracture. Fang et al. (Shen et al., 2014), Shen et al. (Moher et al., 2009), and Gao et al. (Aerssens et al., 2000) discussed the association between the VDR BsmI polymorphism and the risk of osteoporotic fracture, and their results showed that there was no significant association between VDR BsmI polymorphism and the risk of osteoporotic fracture. However, Ji et al. (Gao et al., 2015) examined 17 studies on the relationship of VDR BsmI polymorphism with osteoporotic fracture risk, including 2,112 osteoporotic fracture cases and 4,521 controls, and indicated that there was a statistically significant association between the VDR BsmI polymorphism and osteoporotic fracture risk. In addition, Fang et al. (Shen et al., 2014) and Shen et al. (Moher et al., 2009) examined four and five VDR TaqI studies, respectively, all of which considered that the VDR TaqI polymorphism was not significantly associated with osteoporotic fracture risk. Four studies on VDR ApaI and four studies on VDR FokI analyzed by Shen et al. (Moher et al., 2009) did not find that the VDR ApaI and FokI polymorphisms increased the risk of osteoporotic fracture. In addition, some shortcomings were found when published meta-analyses were carefully checked. First, there was no quality evaluation for the included studies in the two meta-analyses (Shen et al., 2014; Gao et al., 2015), and low-quality studies might have been included, which led to a deviation in the results. Second, the genotype distribution in the control group was not detected by the HWE (Moher et al., 2009; Shen et al., 2014; Gao et al., 2015). The HWE is necessary for a sound genetic association study. If the control group does not meet the requirements of the HWE, there may be selection bias or genotype errors, thus making the results unreliable. Third, the statistical power was not calculated in some previous meta-analyses (Moher et al., 2009; Shen et al., 2014; Gao et al., 2015). At the same time, the statistically significant false-positive report probability was not evaluated in all previously published meta-analyses. Therefore, the meta-analysis results may not be credible. Finally, none of the abovementioned studies discussed the relationship between the VDR Cdx2 polymorphism and osteoporotic fracture.

This meta-analysis had the following advantages: 1) evaluating the quality of the included research; 2) the control group underwent the HWE test; 3) applying the FPRP and Venice criteria to evaluate the correlations that were found to be significant in the current meta-analysis; 4) compared with the previous meta-analysis, the sample size has been significantly expanded; and 5) exploring the sources of heterogeneity based on regression meta-regression analysis. However, there are still some limitations to this study. First, the confounding factors closely related to the outcome were not controlled, such as smoking, drinking, and variable research designs. Second, there are relatively few studies on Americans and Asians in several subgroup analyses, and not enough statistical power to explore the real connection. Moreover, owing to the limited number of studies, a subgroup analysis was not carried out in the summary analysis of the VDR Cdx2 polymorphism and osteoporotic fracture risk. Finally, it was found that the research quality of VDR Cdx2 is low, and hence, the results may not be credible. Future research with large sample sizes and large enough subgroups will help verify our findings.

This meta-analysis strongly indicates that there is no significant association between the polymorphisms of VDR BsmI, ApaI, TaqI, FokI, and Cdx2 and the risk of osteoporotic fracture. The increased risk of osteoporotic fracture elucidated in previous studies is most likely due to false-positive results.

Statements

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding authors.

Author contributions

Y-yM designed research, performed research, collected data, analyzed data, and wrote the article. BL collected data. BC and W-fZ checked the data. X-HY contributed to methodology. H-zL and X-fH designed research and revised the article.

Acknowledgments

We would like to thank the authors of all the original studies included in the meta-analysis. At the same time, we would like to thank X-fH and H-zL for their guidance. In addition, we would like to thank Yu-hui Pan for his help in revising the grammar of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2021.791368/full#supplementary-material

Abbreviations

BMD, bone mineral density; 95% CI, 95% confidence interval; Fn, femoral neck; FPRP, false-positive report probabilities; HWD, Hardy–Weinberg disequilibrium; HWE, Hardy–Weinberg equilibrium (ideally, the frequency of alleles is constant in heredity; that is, gene balance is maintained); LS, lumbar spine; OR, odds ratio; VDR, vitamin D receptor; PRISMA, preferred reporting items for systematic review and meta-analyses; SNP, single-nucleotide polymorphism.

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Summary

Keywords

VDR, polymorphism, osteoporosis, risk of fracture, meta-analysis

Citation

Mu Y-y, Liu B, Chen B, Zhu W-f, Ye X-H, Li H-z and He X-f (2022) Evaluation of Association Studies and an Updated Meta-Analysis of VDR Polymorphisms in Osteoporotic Fracture Risk. Front. Genet. 12:791368. doi: 10.3389/fgene.2021.791368

Received

08 October 2021

Accepted

03 December 2021

Published

07 January 2022

Volume

12 - 2021

Edited by

Melanie Haffner-Luntzer, University of Ulm, Germany

Reviewed by

Fatma Savran Oguz, Istanbul University, Turkey

Atiyeh Abdallah, Birmingham Women’s NHS Foundation Trust, United Kingdom

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Copyright

*Correspondence: Hong-zhuo Li, ; Xiao-feng He,

This article was submitted to Applied Genetic Epidemiology, a section of the journal Frontiers in Genetics

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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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