This study aimed to investigate the correlation between vitamin D-binding protein (DBP) gene polymorphisms at rs4588 and rs7041 loci and the prevalence and mortality rates of the coronavirus disease 2019 (COVID-19) up to 2022. In addition, the study sought to conduct a current situation analysis regarding vaccination among the populations of 10 countries, including Türkiye. The study examined the relationships between the COVID-19 prevalence and mortality rates and the frequencies of different genotypes according to rs7041 and rs4588 loci, which were collected from the literature. Total number of the COVID-19 cases and mortality rate because of SARS-CoV-2 infection before and after vaccination, and the vaccine data, including all types of vaccines, were collected from the World Health Organization coronavirus dashboard in 2022. The data from China, Japan, Nigeria, Kenya, Mexico, Italy, Türkiye, Finland, Germany, and Czechia was included. The mortality rates in China, Nigeria, Mexico, and Italy decreased significantly after the vaccination (P < 0.05), while the prevalence of COVID-19 after the vaccination was not affected in all the countries included (P > 0.05). It was observed that the higher the frequency of GG and GT genotypes of rs7041, the higher the prevalence of COVID-19 (P = 0.02 and P = 0.01, respectively), but only frequency of GT genotype was directly associated with increasing mortality rates in all countries during pre-vaccination period (P < 0.01). There was a significant inverse relationship between the frequency of TT genotype of rs7041 and the prevalence of COVID-19 (P = 0.02), but the relationship with mortality rate was not significant in all countries (P > 0.05). No significant correlation was found between the frequencies of AA, AC and CC genotypes of rs4588, and the COVID-19 prevalence and mortality rates in all countries (P > 0.05). Our findings suggest that the vaccination did not change the prevalence of COVID-19 but decreased mortality rates in four of the 10 countries studied. Significant correlations were observed in the frequencies of rs7041 single nucleotide polymorphism (SNP) with the COVID-19 prevalence and mortality rates, while no correlation was observed in those of rs4588 SNP.
Key words: COVID-2019, polymorphism, rs4588, rs7041, vitamin D binding protein (DBP)
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The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, resulting in approximately 7 million deaths globally as reported by the World Health Organization (WHO), resulted in the associated illness of Coronavirus Disease 2019 (COVID-19). SARS-CoV-2, a member of the coronavirus family, induced severe respiratory failure (Lu et al., 2020). Vitamin D was implicated in playing a crucial role in acute respiratory tract infections, with its deficiency hypothesised to be associated with disease severity and progression among the COVID-19 patients (Aleebrahim-Dehkordi et al., 2021; Ilie et al., 2020; Jayawardena et al., 2021; Karcioğlu Batur et al., 2022; Zacharioudaki et al., 2021). Furthermore, it was suggested that vitamin D could confer protection against acute respiratory infections and be linked with the prevalence and mortality of COVID-19 because of coronavirus infections (Bikle & Schwartz, 2019).
Vitamin D-binding protein (DBP), also known as Gc-globulin, is a serum protein (Bikle & Schwartz, 2019). DBP binds to over 99% of the circulating vitamin D metabolites and facilitates their transport along with albumin (Haynes et al., 2020). The most prevalent polymorphisms in the DBP gene are rs4588 and rs7041, which are located in exon 11 in domain III of the DBP gene. These polymorphisms may not only be associated to variations in serum vitamin D levels but also in vitamin D metabolites (Rozmus et al., 2022). Previous studies have demonstrated that DBP polymorphisms play a crucial role in modulating vitamin D functioning by influencing the availability of free vitamin D (Karcıoğlu Batur & Hekim, 2021; Karcıoğlu Batur et al., 2021; Wiersinga et al., 2020).
Vaccination has been a cornerstone approach for protecting against virus-related diseases. While vaccines are pivotal in preventing severe illnesses, it is equally crucial to assess their efficacy in limiting virus transmission and decreasing the incidence of infections (Lu et al., 2021). Different vaccines developed against COVID-19 demonstrated varying levels of effectiveness (Polack et al., 2020). Epidemiological evidence identified several factors that could indirectly impact ability of the COVID-19 vaccines to mitigate transmission of virus (Al-Kassmy et al., 2020; Haynes et al., 2020), underscoring the importance of continued research in this area. Therefore, this study aimed to investigate the potential correlation between DBP gene polymorphisms in both rs4588 and rs7041 gene loci and the prevalence and mortality rates of COVID-19 up to 2022. In addition, we conducted a comprehensive analysis of the current situation among the populations of included 10 countries, including Türkiye. We also assessed whether the relationship between the COVID-19 prevalence and mortality rates and factors, such as vaccination, can evolve over time, even in the presence of precautions and effective vaccines. This assessment was conducted under the assumption that the genetic structure remains constant, regardless of differences in the vaccines administered to populations and other implemented measures.
The deficiency of vitamin D is highly prevalent in mid-latitude countries, such as Italy, Japan, Türkiye, and Czechia, and in subtropical regions, such as China, compared to tropical areas, such as Mexico, Nigeria, and Kenya, and high-latitude countries, such as Iceland, Norway, Sweden, and Finland. Accordingly, this cross-sectional epidemiological study encompassed data from 10 countries, which included Türkiye, Japan, Nigeria, Finland, Germany, Italy, China, Kenya, Mexico, and Czechia. Information regarding the COVID-19 prevalence and mortality rate, spanning from the onset of first diagnosed COVID-19 case to 2022, along with details of all administered vaccines and number of vaccinations, was retrieved from the WHO coronavirus (COVID-19) dashboard (World Health Organization, 2022). Comparative analyses were conducted for both pre- and post-vaccination. This study adopted the ecological correlation methodology that was previously established and validated in our earlier peer-reviewed publications, in which population-level gene polymorphism frequencies were correlated with the COVID-19 prevalence and mortality data obtained from global databases (Karcıoğlu Batur & Hekim, 2021; Karcıoğlu Batur et al., 2022a, 2022b).
Genetic polymorphism of the DBP gene at rs7041 and rs4588 sites that were discovered in the populations of above-mentioned 10 countries were collected from previously published articles. The distribution of genotypes was found based on the six studies involving cohorts and two systematic reviews and meta-analyses (Jones et al., 2020; Khanna et al., 2019; Pleva et al., 2020; Rivera-Paredez et al., 2020; Terock et al., 2020; Zhou et al., 2012).
Primary objective: The main objective of the research was to examine the relationship between the genetic polymorphism of the DBP gene at rs4588 and rs7041 sites and the incidence and fatality rates of COVID-19 up to 2022. In other words, the effect of genetic polymorphism on the COVID-19 infection was studied.
Secondary objectives: Performing a situational analysis on the vaccination status of the populations in 10 studied countries, including Türkiye, and evaluating their immunisation proportions, types of vaccines used, and effectiveness in controlling the spread of COVID-19 and decreasing fatalities.
Data analysis was performed by using of the Statistical Package for Social Sciences (SPSS) software version 22. Data normality was tested using the Shapiro–Wilk test, considering assumptions of normal distribution, kurtosis, skewness values, and data size. Comparison of two independent samples was made through the Mann–Whitney U test. Spearman’s correlation coefficient test was applied to identify any relationships between numerical variables. For calculated values, P < 0.05 was considered statistically significant.
The correlation measure ranged between the values of -1 and 1 showing the direction and strength of the relationship. Negative value of correlation measure shows inverse relationship between variables, whereas positive value of correlation shows a direct relationship between them. The closer the correlation measure to ±1, the stronger the relationship; whereas the closer the correlation measure to zero, the weaker the relationship (Durmuş et al, 2013). Correlation is categorised as a strong relationship (±1 ≤ r ≤ ±0.7), a medium relationship (±0.7 ≤ r ≤ ±0.3), and a weak relationship (±0.3 ≤ r ≤ ± 0), where r is the Spearman’s correlation coefficient.
We followed stringent ethical protocols while managing the data. The data collected from the literature was exclusively utilised for research objectives. As our study relied on an openly accessible dataset intended for retrospective analysis, we did not seek ethical board’s approval. No human participants, patient-identifiable data, or animal subjects were involved. Nevertheless, our research methodology was crafted to align with global norms for research ethics, especially in the settings involving conflict and susceptible groups.
The COVID-19 mortality rates demonstrated a significant difference before and after the administration of vaccines in the studied 10 countries (Mann–Whitney U test [z] = -3.11; P < 0.05). There existed a wide effect level of difference that was established as significant (r: -0.69). Regarding the mean rank values, low proportions of the COVID-19 mortality were observed after the administration of vaccines (X Rank: 7), compared to pre-vaccination condition (X Row: 14). In China, Nigeria, Mexico, and Italy, there were significant reduction in the mortality rates after vaccination (P < 0.05), but the incidence of the disease remained unchanged in nearly all countries (P > 0.05) (Table 1).
Table 1. Comparison of COVID-19 prevalence and mortality rates before and after vaccination.
| Country | COVID-19 prevalence per million | COVID-19 mortality rate per million | Total Vaccination | ||
|---|---|---|---|---|---|
| Pre-vaccine | Post-vaccine | Pre-vaccine | Post-vaccine | ||
| China | 62.74 | 11.74 | 3.23 | 0.0 | 3,465,113,661 |
| Japan | 3 303.12 | 36 765.67 | 55.47 | 133.0 | 349,234,331 |
| Nigeria | 761.45 | 474.51 | 9.42 | 6.0 | 102,292,641 |
| Kenya | 1 986.20 | 4 015.79 | 34.69 | 70.0 | 23,063,539 |
| Mexico | 15 911.70 | 16 082.64 | 1 560.64 | 801.0 | 225,063,079 |
| Italy | 32 311.00 | 47 804.88 | 1 137.88 | 1.0 | 149,340,886 |
| Türkiye | 27 698.60 | 71 979.05 | 272.40 | 598.0 | 139,652,529 |
| Finland | 6 050.80 | 24 774.35 | 100.15 | 143.0 | 12,898,474 |
| Germany | 18 153.10 | 42 705.57 | 492.27 | 743.0 | 192,337,174 |
| Czechia | 58 892.50 | 102 220.76 | 999.33 | 1 860.0 | 18,562,139 |
| Average rank | 9.00 | 12.00 | 14.00 | 7.00 | |
| z | –1.13 | –3.11 | |||
| P value | 0.26 | 0.00* | |||
Notes. z: Mann–Whitney U test. *P < 0.01.
Table 2 presents the population diversity of rs7041 and rs4588 polymorphism loci in the DBP gene through relevant literature. Table 3 presents the results obtained from the correlation analysis of genotype frequency of rs7041 and rs4588 polymorphisms with the prevalence and mortality rates of COVID-19. Frequency of GG genotype of rs7041 showed a significant direct correlation with the prevalence of COVID-19 both before and after vaccination (r: 0.733 and 0.721, respectively; P < 0.05). GT genotype of rs7041 showed a significant direct correlation with the prevalence and mortality rate of COVID-19 during the pre-vaccination period (r: 0.770 and 0.889, respectively; P < 0.05). Only GT genotype frequency had a significant direct association with the increasing mortality rate in all countries during the pre-vaccination period (P < 0.01), while it showed no significance with the prevalence and mortality rate of COVID-19 after vaccination (P > 0.05). However, there was a significant inverse correlation between the frequency of TT genotype of rs7041 and the prevalence of COVID-19 both before and after vaccination (r: –0.721, P = 0.02; and r: -0.648, P = 0.04, respectively), while its correlation with mortality rate remained insignificant in all countries (P > 0.05).
Table 2. Population diversities of rs7041 and rs4588 polymorphisms presented in the following literature.
| SNP | rs7041 | rs4588 | Reference | ||||
|---|---|---|---|---|---|---|---|
| Country | GG | GT | TT | AA | AC | CC | |
| China | 7.30 | 42.3 | 50.4 | 8.8 | 44.9 | 46.3 | Zhou et al., 2012 |
| Japan | 8.80 | 31.9 | 59.3 | 2.7 | 43.8 | 53.6 | Khanna et al.,2019 |
| Nigeria | 0.70 | 15.6 | 83.7 | 0.0 | 8.20 | 91.8 | Khanna et al.,2019 |
| Kenya | 0.90 | 12.7 | 86.4 | 0.9 | 11.0 | 88.1 | Jones et al., 2020 |
| Mexico | 24.1 | 50.0 | 25.9 | 1.8 | 46.4 | 51.8 | Rivera-Paredez et al., 2020 |
| Italy | 25.5 | 56.9 | 17.6 | 5.9 | 39.2 | 54.9 | Jones et al., 2020 |
| Türkiye | 31.0 | 49.0 | 20.0 | 2.0 | 53.0 | 45.0 | Karcıoğlu Batur and Hekim, 2021 |
| Finland | 63.6 | 32.5 | 3.9 | 10.8 | 48.7 | 40.5 | Enlund-Cerullo et al., 2019 |
| Germany | 31.9 | 48.2 | 19.9 | 8.7 | 42.0 | 49.3 | Terock et al., 2020 |
| Czechia | 38.8 | 49.4 | 11.9 | 6.2 | 42.5 | 51.2 | Pleva et al., 2020 |
Note. SNP: single nucleotide polymorphism.
Table 3. Correlation analysis of the relationship between DBP gene polymorphisms and COVID-19 prevalence and mortality rates.
| Pre-vaccination | Post-vaccination | |||||
|---|---|---|---|---|---|---|
| SNP | Genotype | COVID-19 prevalence |
COVID-19 mortality rate |
COVID-19 prevalence |
COVID-19 mortality rate | |
| rs7041 | GG | r | 0.733* | 0.57 | 0.721* | 0.61 |
| P | 0.02 | 0.08 | 0.02 | 0.06 | ||
| GT | r | 0.770** | 0.899** | 0.59 | 0.33 | |
| P | 0.01 | 0.00 | 0.07 | 0.35 | ||
| TT | r | –0.721* | –0.60 | –0.648* | –0.41 | |
| P | 0.02 | 0.06 | 0.04 | 0.24 | ||
| rs4588 | AA | r | 0.18 | 0.11 | 0.20 | 0.18 |
| P | 0.63 | 0.76 | 0.58 | 0.63 | ||
| AC | r | 0.18 | 0.25 | 0.21 | 0.48 | |
| P | 0.63 | 0.49 | 0.56 | 0.16 | ||
| CC | r | –0.21 | –0.13 | –0.26 | –0.47 | |
| P | 0.56 | 0.72 | 0.47 | 0.17 | ||
Notes. r: Spearman’s correlation coefficient; *P < 0.05, **P < 0.01.
SNP: single nucleotide polymorphism.
There was no statistical association between genotype frequencies of AA, AC, and CC at the rs4588 locus and the prevalence and mortality rates of COVID-19 in all countries before and after vaccination (P > 0.05) (Table 2).
Vitamin D has an important role in different immune system processes, such as maintenance of cell connection, prevention of cytokine storm, improvement of cellular immunity, and regulation of adaptive immunity by inducing T cells (Al-Kassmy et al., 2020). The importance of all these roles dwells in reducing the risk of developing the COVID-19 infection. The most frequent polymorphisms in the DBP gene are rs4588 and rs7041. Previous research indicates that there is an association between these polymorphisms and both serum vitamin D levels and vitamin D metabolites. Our earlier research proposed that variations in the incidence and mortality rates of COVID-19 in different countries could be linked with vitamin D metabolism because of DBP polymorphisms at rs7041 and rs4588 loci (Karcıoğlu Batur et al., 2024). The current study determined the relationship between DBP gene polymorphisms at rs7041 and rs4588 sites and the incidence and mortality rates of COVID-19 before 2022. The study also analysed the current situation in terms of vaccine usage in 10 different countries, including Türkiye.
The global vaccination efforts against COVID-19 commenced in December 2020. Nonetheless, questions came up during clinical trials whether vaccinated individuals would experience the COVID-19 infection at a comparable frequency and likelihood as unvaccinated individuals, or whether they would still fall ill (Cantorna et al., 2015). In this study, all available vaccination data was included, regardless of vaccine type, based on the information published by the WHO (2022). The findings revealed that vaccination, regardless of its type, did not significantly alter the COVID-19 prevalence but did influence mortality rates because of SARS-CoV-2 infection. Following vaccination, a noticeable decline in the COVID-19-related mortality was observed, compared to the pre-vaccination period. This outcome was expected, as the primary aim of pathogens was not to cause immediate death. Immunisation not only played a vital role in preventing the disease but also served as a protective measure in reducing burden of the disease (Vitello et al., 2021; Voysey et al., 2021).
Differences in vitamin D metabolism because of DBP gene polymorphisms at both rs4588 and rs7041 loci may explain disparities in the COVID-19 prevalence and mortality in different countries, as reported by Karcıoğlu Batur et al. (2021).
Previous studies confirmed the relationship between mean vitamin D levels and the COVID-19 mortality in some European countries (Boucher et al., 2020; Karcıoğlu Batur & Hekim, 2021; Karcıoğlu Batur et al., 2021; Lurie et al., 2020).
The present study focused on the effects of different genotype frequencies at both rs7041 and rs4588 loci on the prevalence and mortality of COVID-19 in 10 countries, including Türkiye before and after vaccination. It was observed that the frequency of GG genotype at rs7041 locus had a positive effect on prevalence of the disease during both periods. Mortality rate because of COVID-19 showed no significant correlation with the GG genotype frequency, whereas prevalence of COVID-19 showed a significant association. In addition, a significant correlation was observed between the high frequency of GT genotype at rs7041 locus and the COVID-19 prevalence and mortality before vaccination. Furthermore, an inverse relationship was observed between frequency of TT genotype at rs7041 locus and the COVID-19 prevalence, while no relationship was observed regarding mortality rates. On the other hand, no correlation was found between the COVID-19 prevalence or mortality rates and the frequencies of AA, AC, and CC genotypes at rs4588 locus. In summary, significant relationship was observed between rs7041 variants, whereas no association was observed for rs4588 variants.
The first limitation of this study was that data regarding the COVID-19 prevalence, mortality rate, and vaccination was obtained from various online sources, including the WHO coronavirus dashboard. While these databases provided valuable insights, they could contain bias and inconsistencies because of the differences in healthcare infrastructure across countries; this could have affected the validity and reliability of our findings. Another limitation was the focus on only two DBP gene polymorphisms (rs4588 and rs7041), which did not account for other genetic or environmental factors that could influence the COVID-19 outcomes. Furthermore, the publicly available data sources used in this study – the WHO coronavirus dashboard and previously published population-based genetic studies – did not provide individual-level clinical and demographic stratification, such as gender, age, ethnicity, and comorbidities. Because mortality and morbidity outcomes could vary substantially across different demographic subgroups, this heterogeneity could act as a confounding factor in the epidemiological interpretation of results. Future studies incorporating individual-level clinical and demographic data would be valuable in validating and refining these population-level findings. In addition, the cross-sectional design of the current study did not allow for causal inferences; hence, longitudinal studies are needed to confirm these findings.
Considering results of the current study, it can be stated that global vaccination against COVID-19, authorised with rapid WHO approval, did not significantly influence prevalence of the disease. However, vaccination appears to have reduced mortality rates in four out of 10 countries. These effectscould have been influenced by the DBP gene polymorphism, as certain genotypes showed correlations with the COVID-19 prevalence and mortality. Therefore, this study could serve as a useful basis for future research focusing on genetic risk factors associated with the disease. Future studies should also evaluate the effects of other genetic variants (such as CYP2R1 and CYP27B1) and DBP polymorphism on the COVID-19 infection, prevalence, and mortality. Furthermore, future studies should consider employing Bayesian modelling approaches, which would allow the incorporation of literature-derived genetic frequencies as probability distributions rather than fixed values, provide more informative posterior distributions beyond P value-based inferences, and enable adjustment for potential confounding factors, such as healthcare infrastructure and age distribution, through random effects. In addition, vaccine efficacy and potential adverse effects should be further investigated.
The authors reported no financial disclosures or funding sources associated with this study.
The authors declared that there was no conflict of interest regarding the publication of this manuscript.
The data supporting the findings of this study was obtained from publicly accessible sources, including the WHO coronavirus (COVID-19) dashboard and previously published literature. The compiled dataset used in the current study is available from the corresponding author upon reasonable request.
Not applicable. Ethics approval was not required for this study.
Study conception and design: A.P., I.T., B.A., N.A., and L.K.B.; data collection: A.P., I.T., B.A., N.A., and L.K.B.; analysis and interpretation of results: A.P., I.T., B.A., N.A., and L.K.B.; and manuscript draft preparation: A.P., I.T., B.A., N.A., and L.K.B. All authors reviewed the results and approved the final version of the manuscript.
No artificial intelligence based tools or applications were used in the preparation of this study. The entire content of the study was produced by the author(s) in accordance with scientific research methods and academic ethical principles.
Ahsen Pektas | 0009-0004-1239-653X | ahsennzerin@gmail.com
Ilknur Tunc | 0000-0002-0372-7948 | tuncilknur006@gmail.com
Buse Aslan | 0009-0009-9911-1694 | busseaaslan@gmail.com
Nermin Akcali | 0000-0001-6816-9687 | nakcali@biruni.edu.tr
Lutfiye Karcioglu Batur | 0000-0002-4803-9137 | lbatur@biruni.edu.tr
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