The predicted binding sites for sialic acid in the N-terminal domain (aa19-135) of the monomeric form of CD33 (PDB ID 5IHB) carrying either an arginine or a glycine residue in position 69 are reported in Figure 3. The affinity of each binding site toward the ligand is expressed as the binding energy (kcal/mol), with lower values indicating a greater bond affinity. In the Arg69 variant, the values were −4.8 kcal/mol near Arg119 and −5.3 kcal/mol near Arg91, while the values were slightly increased in the form with Gly69, with values of −5.2 kcal/mol near Arg119 and −5.7 kcal/mol near Arg91 (Figure 3). *2.3. Docking Analysis* The predicted binding sites for sialic acid in the N‐terminal domain (aa19‐135) of the monomeric form of CD33 (PDB ID 5IHB) carrying either an arginine or a glycine residue in position 69 are reported in Figure 3. The affinity of each binding site toward the ligand is expressed as the binding energy (kcal/mol), with lower values indicating a greater bond affinity. In the Arg69 variant, the values were −4.8 kcal/mol near Arg119 and −5.3 kcal/mol near Arg91, while the values were slightly increased in the form with Gly69, with values of −5.2 kcal/mol near Arg119 and −5.7 kcal/mol near Arg91 (Figure 3).

*Int. J. Mol. Sci.* **2022**, *23*, 3629 5 of 13

**Figure 3.** Sialic acid interactions with the two SNPs of CD33 structures. (**A**) Surface representation of functional domain of the CD33 predominant form with Arg in position 69, colored in red (PDB ID 5IHB). (**B**) Surface representation of functional domain of the CD33 variant form with Gly in position 69, colored in red (PDB ID 5IHB). The areas in orange indicate the binding sites of sialic acid, in stick representation, in correspondence with the positively charged arginine residues with which the ligand establishes saline bridges. The values of the binding energy in kcal/mol are reported for each binding site of sialic acid. **Figure 3.** Sialic acid interactions with the two SNPs of CD33 structures. (**A**) Surface representation of functional domain of the CD33 predominant form with Arg in position 69, colored in red (PDB ID 5IHB). (**B**) Surface representation of functional domain of the CD33 variant form with Gly in position 69, colored in red (PDB ID 5IHB). The areas in orange indicate the binding sites of sialic acid, in stick representation, in correspondence with the positively charged arginine residues with which the ligand establishes saline bridges. The values of the binding energy in kcal/mol are reported for each binding site of sialic acid.

We found similar results when we performed docking analyses on the other two

structures: the N‐terminal domain (aa19‐135) (PDB ID 5J06, 5J0B), which carried a glycine residue in position 69; and the repeated structural type C2 Ig domain (aa145‐228). In the PDB‐ID 5J06 structure, the values were −4.7 kcal/mol in Arg119 proximity and −5.2 kcal/mol in Arg91 proximity; while in the PDB‐ID 5J0B structure, the predicted binding affinity values were −4.7 kcal/mol in Arg119 proximity and −5.3 kcal/mol in Arg91 proximity (Supplementary Figure S2). We confirmed these results through the docking analyses carried out on the other three CD33 structures having only the N‐terminal domain (PDB ID 6D48, 6D49, and 6D4A). In fact, we always observed a greater binding affinity in the Arg91 residue part than in the Arg119 part of the functional domain (Supplementary Figure S3), suggesting a better chance of binding at this site. This result was in contrast with the evidence from the binding of a sialic acid mimetic ligand FVP in the proximity of Arg119, as found by others [32]. However, by analyzing the asymmetric unit assembly of each resolved structure in that study, we observed the formation of dimers and tetramers involving interfaces near Arg91, which likely prevented the binding of ligands near this residue. Considering that the most reactive side of the D2:IgV domain is represented by the positively charged patch comprising arginine residues 89 and 91, the oligomerization trend involving this surface could be explained easily. Notwithstanding We found similar results when we performed docking analyses on the other two structures: the N-terminal domain (aa19-135) (PDB ID 5J06, 5J0B), which carried a glycine residue in position 69; and the repeated structural type C2 Ig domain (aa145-228). In the PDB-ID 5J06 structure, the values were−4.7 kcal/mol in Arg119 proximity and −5.2 kcal/mol in Arg91 proximity; while in the PDB-ID 5J0B structure, the predicted binding affinity values were −4.7 kcal/mol in Arg119 proximity and −5.3 kcal/mol in Arg91 proximity (Supplementary Figure S2). We confirmed these results through the docking analyses carried out on the other three CD33 structures having only the N-terminal domain (PDB ID 6D48, 6D49, and 6D4A). In fact, we always observed a greater binding affinity in the Arg91 residue part than in the Arg119 part of the functional domain (Supplementary Figure S3), suggesting a better chance of binding at this site. This result was in contrast with the evidence from the binding of a sialic acid mimetic ligand FVP in the proximity of Arg119, as found by others [32]. However, by analyzing the asymmetric unit assembly of each resolved structure in that study, we observed the formation of dimers and tetramers involving interfaces near Arg91, which likely prevented the binding of ligands near this residue. Considering that the most reactive side of the D2:IgV domain is represented by the positively charged patch comprising arginine residues 89 and 91, the oligomerization trend involving this surface could be explained easily. Notwithstanding the site of binding,

our results suggested a general increase in the binding affinity and specificity of the glycine variant of CD33 toward ligands.

#### *2.4. Virtual Screening Analysis*

Plotting the carbon 1 atomic coordinate of the best sialic acid poses against the affinity values (kcal/mol) predicted by the docking analysis, we obtained a conceptual understanding of the ligand distributions on the protein surface with respect to the arginine or glycine variants in position 69 of the CD33 protein. The results highlighted a noteworthy increase in the affinity of several binding sites for sialic acid in the glycine 69 variant of CD33 (Supplementary Figure S4). Indeed, the analysis of the distributions of the best ligands on the D2:IgV domain of CD33, obtained by plotting the XYZ coordinates of the C1 atom of sialic acid structures (Supplementary Figure S5), showed binding in specific sites of CD33 receptors for both variants with arginine and glycine residues in position 69. When comparing the position of arginine residues in the D2:IgV domain of the PDB-ID 5IHB structure with the best ligand poses by overlaying the YZ coordinates of the Cζ atom of arginine sidechains with the coordinates of C1 atom of sialic acid poses (Supplementary Figure S6), we observed a number of sialic-acid-binding molecules close to arginine residues 91, 98, and 119. However, the C1 atom of sialic acid near the approximate Z coordinate 70,000, included in the range of Y coordinates 85,000–95,000 and 110,000–115,000, were instead close to the arginine 62 and 89 residues in the 3D representation, respectively. It was apparent that ligands basically spread out on the surface of the Arg69 structure of CD33, with most of the sialic acid binding near arginine residues 91, 119, 89, 98, and 62, ordered by the number of bonded ligands (Supplementary Figure S6A). In contrast, an increased affinity and number of sialic acid molecules was predicted near the position of arginine 91 in the Gly69 variant of CD33 (Supplementary Figure S6B).

These data suggested the possibility of the presence of more than one binding site for sialic acid derivatives with a similar specificity. In fact, it was not surprising that the more reactive domain near arginine 91 was involved in the binding at the interfaces between the CD33 structures (single and double domains) in the crystallographic unit cell, preventing the recognition of this other sialic-acid-binding site in the crystallographic structures resolved in presence of ligands [32].

The 3D representations in Figure 4 illustrate the best orientations of sialic acid molecules in the CD33 binding sites obtained by virtual screening analysis. In the CD33 structure presenting an arginine residue in position 69, we observed the prevalent distribution of the ligands in the two already identified binding sites involving arginine 91 and 119 (Figure 4A). However, two additional binding sites were predicted near arginine 62 and 89. The number of ligands in these two secondary sites increased in the representation of the second-best poses (Figure 4B), having a lower affinity with respect to the previous ones. In contrast, the best poses of sialic acid molecules were located exclusively near arginine 91 and 119 in the Gly69 variant of CD33 (Figure 4C), and only a few ligand poses were predicted near arginine 62 and 89 (Figure 4D). In addition, when observing the manner the sialic acid binds to the sites on the CD33 surface, we can point out that the orientation of sialic acid molecules was very often preferentially maintained in the binding sites of the Gly69 variant of CD33 (Figure 4). Thus, in addition to the increase in affinity, it was likely that the Gly69 variant of CD33 bound to the sialic acid with a higher specificity than the Arg69 variant. These results supported the idea that the balance of the binding equilibrium constant for CD33–sialic acid interaction changed slightly in a positive direction in the Gly69 variants. This suggested a more efficient binding of sialic acid at a lower concentration by this CD33 variant.

**Figure 4.** Detail of the binding sites in the D2:IgV domain for sialic acid molecules, as derived from docking analyses. Surface representation, in light gray, of the N‐terminal D2:IgV functional domain of arginine 69 models of CD33, in which the docked poses of sialic acid molecules with the best (**A**) and the second best (**B**) ligand mode rmsd are shown in stick figures. Surface representation, in light gray, of the N‐terminal D2:IgV functional domain of glycine 69 models of CD33, in which the docked poses of sialic acid molecules with the best (**C**) and the second best (**D**) ligand mode rmsd are shown in stick figures. The surfaces of arginine residues 62, 69, 89, 91, and 119 are presented in light blue. **3. Discussion Figure 4.** Detail of the binding sites in the D2:IgV domain for sialic acid molecules, as derived from docking analyses. Surface representation, in light gray, of the N-terminal D2:IgV functional domain of arginine 69 models of CD33, in which the docked poses of sialic acid molecules with the best (**A**) and the second best (**B**) ligand mode rmsd are shown in stick figures. Surface representation, in light gray, of the N-terminal D2:IgV functional domain of glycine 69 models of CD33, in which the docked poses of sialic acid molecules with the best (**C**) and the second best (**D**) ligand mode rmsd are shown in stick figures. The surfaces of arginine residues 62, 69, 89, 91, and 119 are presented in light blue.

#### Although the association of CD33 with Alzheimer's diseases has not been thoroughly **3. Discussion**

elucidated, literature data supports the hypothesis that through the modulation of immune cell functions (such as phagocytosis, cytokine release, apoptosis, etc.), CD33 could be implicated in the suppression of amyloid fragment uptake [12,18,23,25–27]. Here, we demonstrated a correlation between an SNP variant of the *CD33* gene (SNP rs2455069‐ A>G) and Alzheimer's disease risk, and proposed a new hypothesis for its functional role. Using different in silico approaches, we demonstrated that the binding site for sialic acid could involve additional regions of the protein to the previously documented Arg119 residue. This residue was demonstrated to be essential for the binding of the sialic acid mimetic [32]. Indeed, it was assumed that the binding site for sialic acid was located at the D2:IgV domain of the CD33 receptor, and contained the arginine 119 residue, which was positively charged at physiological pH. Because sialic acid molecules are typically terminal residues on glycoconjugates, the positively charged arginine forms salt bridges with the sialic acid portion of sugar residues, enabling stable interactions [18,33–35]. Due to the presence of FVP (a subtype‐selective sialic acid mimetic ligand) in the 6D49 and 6D4A structures (recently also demonstrated in the 7AW6 structure), the putative binding site was located near the Arg69 and Arg119 positions (Supplementary Figure S7). In agreement with those results, we confirmed the binding of sialic acid to Arg119, but also demonstrated the possibility that the ligand may bind to other regions of the protein with higher affinity that include Arg91. The presence of an additional binding site was recently reported for another Siglec family member [36], pointing out the need to further explore the binding properties of CD33 toward sialic‐acid‐containing molecules. A mutation of arginine 119 to alanine did not affect phagocytosis of U937 cells [27], raising a question on the role of this residue in sialic‐acid‐containing glycan binding, and supporting a hypothesis of additional binding sites for sialic acid. Our *in‐silico* analyses indeed supported the possibility of additional binding sites for sialic acid. In addition, our studies Although the association of CD33 with Alzheimer's diseases has not been thoroughly elucidated, literature data supports the hypothesis that through the modulation of immune cell functions (such as phagocytosis, cytokine release, apoptosis, etc.), CD33 could be implicated in the suppression of amyloid fragment uptake [12,18,23,25–27]. Here, we demonstrated a correlation between an SNP variant of the *CD33* gene (SNP rs2455069- A>G) and Alzheimer's disease risk, and proposed a new hypothesis for its functional role. Using different in silico approaches, we demonstrated that the binding site for sialic acid could involve additional regions of the protein to the previously documented Arg119 residue. This residue was demonstrated to be essential for the binding of the sialic acid mimetic [32]. Indeed, it was assumed that the binding site for sialic acid was located at the D2:IgV domain of the CD33 receptor, and contained the arginine 119 residue, which was positively charged at physiological pH. Because sialic acid molecules are typically terminal residues on glycoconjugates, the positively charged arginine forms salt bridges with the sialic acid portion of sugar residues, enabling stable interactions [18,33–35]. Due to the presence of FVP (a subtype-selective sialic acid mimetic ligand) in the 6D49 and 6D4A structures (recently also demonstrated in the 7AW6 structure), the putative binding site was located near the Arg69 and Arg119 positions (Supplementary Figure S7). In agreement with those results, we confirmed the binding of sialic acid to Arg119, but also demonstrated the possibility that the ligand may bind to other regions of the protein with higher affinity that include Arg91. The presence of an additional binding site was recently reported for another Siglec family member [36], pointing out the need to further explore the binding properties of CD33 toward sialic-acid-containing molecules. A mutation of arginine 119 to alanine did not affect phagocytosis of U937 cells [27], raising a question on the role of this residue in sialic-acid-containing glycan binding, and supporting a hypothesis of additional binding sites for sialic acid. Our *in-silico* analyses indeed supported the possibility of additional

also supported a hypothesis that the CD33‐R69G variant may bind sialic acid with greater

binding sites for sialic acid. In addition, our studies also supported a hypothesis that the CD33-R69G variant may bind sialic acid with greater specificity and affinity, and results in a more efficient binding of the variant to sialic acid, at lower concentrations than that of the wild type. Interestingly, the dependence of binding on sialic acid concentrations was consistent with observations that sialic acid content increases in old-age females [37], who have an increased risk of LOAD compared to males of the same age [38]. In the light of these observations, new perspectives have opened up in the study of CD33, with novel and interesting understandings of the interactions leading to late-onset Alzheimer's disease. Several polymorphisms in the CD33 gene could affect the structure of this receptor, and in turn, the binding affinity for sialic-acid-containing gangliosides. We hypothesized that the microglial phagocytosis, and in turn, the efficient removal of neurotoxic protein aggregates, might also depend on a variety of factors, including dietary habits, sex-specific accumulation of sialic acid, and aging, among others, affecting ganglioside expression in the brain. This may establish a complex inter-relationship between genetic risk factors and additional predictors in the progression of LOAD. Overall, our results led us to hypothesize that the rs2455069-A>G SNP is a risk factor for LOAD, and that the mechanism of the long-term cumulative effects of the CD33-R69G variant are mediated through an increased binding of sialic acid, which then acts as a more effective enhancer of the CD33 inhibitory effects on amyloid plaque degradation (Figure 5). specificity and affinity, and results in a more efficient binding of the variant to sialic acid, at lower concentrations than that of the wild type. Interestingly, the dependence of binding on sialic acid concentrations was consistent with observations that sialic acid content increases in old‐age females [37], who have an increased risk of LOAD compared to males of the same age [38]. In the light of these observations, new perspectives have opened up in the study of CD33, with novel and interesting understandings of the inter‐ actions leading to late‐onset Alzheimer's disease. Several polymorphisms in the CD33 gene could affect the structure of this receptor, and in turn, the binding affinity for sialic‐ acid‐containing gangliosides. We hypothesized that the microglial phagocytosis, and in turn, the efficient removal of neurotoxic protein aggregates, might also depend on a vari‐ ety of factors, including dietary habits, sex‐specific accumulation of sialic acid, and aging, among others, affecting ganglioside expression in the brain. This may establish a complex inter‐relationship between genetic risk factors and additional predictors in the progression of LOAD. Overall, our results led us to hypothesize that the rs2455069‐A>G SNP is a risk factor for LOAD, and that the mechanism of the long‐term cumulative effects of the CD33‐ R69G variant are mediated through an increased binding of sialic acid, which then acts as a more effective enhancer of the CD33 inhibitory effects on amyloid plaque degradation (Fig‐ ure 5).

*Int. J. Mol. Sci.* **2022**, *23*, 3629 8 of 13

**Figure 5.** Model describing the plaque accumulation during aging. The increased effect of the CD33‐ R69G variant in inhibiting the microglial phagocytosis results in a lower extent of clearance of am‐ yloid plaques, supporting late‐onset AD. **Figure 5.** Model describing the plaque accumulation during aging. The increased effect of the CD33-R69G variant in inhibiting the microglial phagocytosis results in a lower extent of clearance of amyloid plaques, supporting late-onset AD.

#### **4. Conclusions 4. Conclusions**

We analyzed the functional role of the SNP rs2455069‐A>G, which we found to be associated with Alzheimer's disease (AD) in a cohort of patients from southern Italy. The SNP changed a single amino acid in the sequence of CD33, and resulted in a local change in its protein structure, which we derived by in silico analysis. Our data demonstrated that this small change resulted in a slight increase in the binding affinity and specificity of CD33 toward sialylated molecules, its natural ligands. We propose that this change in binding enhanced the inhibitory effects of CD33 on amyloid plaque degradation, and to‐ gether with other genetic, epigenetic, and environmental factors, could predispose to the We analyzed the functional role of the SNP rs2455069-A>G, which we found to be associated with Alzheimer's disease (AD) in a cohort of patients from southern Italy. The SNP changed a single amino acid in the sequence of CD33, and resulted in a local change in its protein structure, which we derived by in silico analysis. Our data demonstrated that this small change resulted in a slight increase in the binding affinity and specificity of CD33 toward sialylated molecules, its natural ligands. We propose that this change in binding enhanced the inhibitory effects of CD33 on amyloid plaque degradation, and together with other genetic, epigenetic, and environmental factors, could predispose to the accumulation of amyloid plaques and the onset of AD pathology. These observations support a new approach to the investigation of protein polymorphisms involved in AD, and propose a need for structural analyses to complements genetic studies.

#### **5. Materials and Methods**

#### *5.1. Participant Recruitment and Analysis*

The participants in the study (*n* = 330) were recruited at the Centre for Research and Training in Medicine of Aging (CeRMA) at the University of Molise (Italy). The AD patients (*n* = 195) fulfilled the National Institute of Aging and Alzheimer's Association (NIA-AA) diagnostic criteria for "probable AD with documented decline" [39]. They scored <24 on the Mini Mental State Examination (MMSE) and >0.5 on the Clinical Dementia Rating (CDR).  One hundred and thirty-five sex/age-matched cognitively healthy subjects (HS) were recruited as a control group. DNA from all participants was analyzed for the presence of the rs2455069 SNP by high-resolution melting analysis (HRM). Genomic DNA was extracted from whole blood with a QIAamp DNA Blood Mini Kit (QIAGEN). PCR amplifications were performed on a SureCycler 8800 Thermal Cycler (Agilent, Santa Clara, CA, USA). The study was conducted in accordance with ethical principles stated in the Declaration of Helsinki, and with approved national and international guidelines for human research. The Institutional Review Board (IRB) of the University of Molise approved the study (IRB Prot. n. 16/2020). Written informed consent was obtained from each participant or caregiver.

#### *5.2. High-Resolution Melting Analysis (HRM)*

The high-resolution melting analysis (HRM) was performed as previously described [29] on a LightCycler 480 Instrument II (Roche, Basel, Switzerland) and analyzed using LightCycler® 480 Gene Scanning Software 1.5.1. High-resolution melting Mastermix (Roche) was used. Specific primers used for amplification and sequencing by the Sanger method and the electropherograms were analyzed with Chromas 2.22 software and aligned according to reference sequences present in GenBank (http://www.ncbi.nlm.nih.gov/GenBank/index. html; accessed on 1 September 2019). Templates were amplified in 96-well plates and ~30 ng analyzed in a 20 µL final volume reaction as previously specified [29].

#### *5.3. CD33 Structure Editing and Minimization*

Computer simulations were carried out on the 3D crystallographic structures available in the Protein Data Bank [31] with ID numbers 5IHB, 5J06, 5J0B, 6D48, 6D49, 6D4A, and 7AW6. The first four included the N-terminal domain (aa19-135) and the repeated structural domain Ig of type C2 (aa145-228), while the last three structures included only the N-terminal domain. All PDB structures of CD33 (excluding 6D48) incorporated ligands. Characteristics of the seven human CD33 structures (Siglec-3) are summarized in Supplementary Table S1. The PDB files were edited by using Pymol [40]. Any molecules bound in the protein catalytic sites and water molecules bound to the protein during the crystallization process were removed. The CHARMM-GUI web-based platform (http://www.charmm-gui.org; accessed on 15 February 2022) was used to extract a single monomer from each of the CD33 structures contained in the PDB files, and to generate the two single-nucleotide polymorphisms (SNPs) at position 69 for each monomer. All generated structures were optimized offline using the CHARMM program [41] by performing a basic energy minimization with the steepest descent (SD) algorithm of the initial 25–50 steps to remove bad van der Waals contact. A more precise minimization was carried out subsequently with the Newton–Raphson method (ABNR) of 1,000,000 steps to remove potential problems, such as incorrect contacts, collisions, and nonphysical contacts/interactions. When the step-to-step energy change was less than 0.001 kcal/mol, the structure was considered sufficiently minimized.

#### *5.4. Ligand Structure Editing and Minimization*

The sialic acid and similar ligand (30 -sialyllactose, 60 -sialyllactose) 3D structures were generated using Avogadro software (http://avogadro.cc; accessed on 15 February 2022), and the structures were optimized through the MMFF94 force field with the steepest descent algorithm until the ∆E reach a value approaching 0 (<10–10).

#### *5.5. Docking Analysis*

The minimized monomeric structures of CD33 were used for the docking analysis of sialic acid and similar ligand structures. The docking analysis was carried out using Autodock Vina [42]. The ADT software package was used to determine the grid sizes, visualize the ligand poses, and add hydrogen atoms to the templates [43]. We superimposed the different CD33 structures and generated a single grid box that included all the CD33 structures. The coordinates of the grid box were put in a configuration file (config file in Supplementary Materials) used to perform both the docking and the virtual screening analysis. During the docking procedure, both the proteins and ligands were considered as rigid, and the only torsion that was allowed was for the carboxylic and alcoholic groups of the ligand. A bash shell command was used to pass receptors, ligands, and grid box parameters to Autodock Vina, producing an output file containing the predicted models (ligand poses) and a log file for each analysis. The structures were analyzed and the images were produced by using the PyMOL [40] and the UCSF Chimera 1.13.1 (http://www.cgl.ucsf.edu/chimera; accessed on 15 February 2022) [44] molecular graphics software programs.

#### *5.6. Virtual Screening Analysis*

We prepared two datasets of 100 models each of the Arg69 and Gly69 variants of the CD33 structure (PDB ID 5IHB). We performed a basic energy minimization using the CHARMM program [41], as previously described, to make them more relaxed for subsequent analysis. Using an ad hoc script (see Supplementary Materials) to transfer receptors and grid box parameters for automating the docking process, we submitted the two structure datasets (200 structures total) for analysis by Autodock Vina against the sialic acid as ligand, retrieving at least eight poses for each CD33 structure.

#### *5.7. Statistical Analysis*

Data were analyzed using the SPSS (v. 17.0) statistical software package (SPSS Inc., Chicago, IL, USA). The frequencies of genotypes and allelotypes of the CD33 gene polymorphism were calculated and determined for deviation from the Hardy–Weinberg equilibrium (HWE). The Chi-squared test and odds ratio (OR) were used to evaluate the association of AD risk with different genotypes and alleles. A *p*-value of <0.05 was considered statistically significant.

**Supplementary Materials:** The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/ijms23073629/s1.

**Author Contributions:** F.T. and F.F. performed the molecular modeling and simulation; A.R. performed the in vitro experiments; A.A. and A.D.C. performed the collection of data from patients; A.R., A.D. and E.V. performed the analysis and comparison of experimental data; F.F. performed the analysis of in silico simulations; F.F. and E.V. conceived and designed the research; A.D., F.A., A.D.C., F.F. and E.V. interpreted the results; F.T., A.D., F.F. and E.V. wrote the manuscript; all authors edited the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** A.R. was supported by the EMBO Short-Term Fellowship 7532-2018-2019. F.T. was supported by the FESR Campania 2014-2020 (Asse 1—Obiettivo Specifico 1.2—Azione 1.2.2) (ex PON03PE\_00060\_4). A.D.C. and A.A. were supported by the MIUR/PRIN grant N. 2017T9JNLT.

**Institutional Review Board Statement:** The study was conducted in accordance with ethical principles stated in the Declaration of Helsinki, and with approved national and international guidelines for human research. The Institutional Review Board (IRB) of the University of Molise approved the study (IRB Prot. n. 16/2020).

**Informed Consent Statement:** Written informed consent was obtained from each participant or caregiver.

**Data Availability Statement:** All data are available in the main text or the Supplementary Materials.

**Acknowledgments:** Figure 5 contains graphs provided by SMART (Servier Medical Art) (https://smart. servier.com; accessed on 15 February 2022).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Review* **rs7041 and rs4588 Polymorphisms in Vitamin D Binding Protein Gene (VDBP) and the Risk of Diseases**

**Dominika Rozmus 1,\* , Janusz Płomi ´nski 2,3, Klaudia Augustyn <sup>4</sup> and Anna Cie´sli ´nska <sup>1</sup>**

**Abstract:** The purpose of the study was to investigate the role of vitamin D binding protein (VDBP, DBP) and its polymorphism in the vitamin D pathway and human health. This narrative review shows the latest literature on the most popular diseases that have previously been linked to VDBP. Vitamin D plays a crucial role in human metabolism, controlling phosphorus and calcium homeostasis. Vitamin D binding protein bonds vitamin D and its metabolites and transports them to target tissues. The most common polymorphisms in the VDBP gene are rs4588 and rs7041, which are located in exon 11 in domain III of the VDBP gene. rs4588 and rs7041 may be correlated with differences not only in vitamin D status in serum but also with vitamin D metabolites. This review supports the role of single nucleotide polymorphisms (SNPs) in the VDBP gene and presents the latest data showing correlations between VDBP variants with important human diseases such as obesity, diabetes mellitus, tuberculosis, chronic obstructive pulmonary disease, and others. In this review, we aim to systematize the knowledge regarding the occurrence of diseases and their relationship with vitamin D deficiencies, which may be caused by polymorphisms in the VDBP gene. Further research is required on the possible influence of SNPs, modifications in the structure of the binding protein, and their influence on the organism. It is also important to mention that most studies do not have a specific time of year to measure accurate vitamin D metabolite levels, which can be misleading in conclusions due to the seasonal nature of vitamin D.

**Keywords:** VDBP; vitamin D binding protein; rs7041; rs4588; bone density; diabetes; obesity; COPD; pulmonary tuberculosis; SNP; MD; PD

#### **1. Introduction**

Recent data suggest that vitamin D deficiency is widespread across Europe. Analysis of 14 population studies revealed that 13% of the 55,844 European individuals had average yearly serum 25(OH)D concentrations <30 nmol/L, regardless of age group, ethnic mix, and the latitude of study populations [1]. According to the US Endocrine Society definition of vitamin D deficiency (<50 nmol/L), the prevalence was 40.4% and dark-skinned ethnic subgroups were more likely to be vitamin D deficient [2]. Due to the darker skin color, melanin blocks the UVB radiation, which is necessary for vitamin D synthesis. Hypovitaminosis D was highly prevalent among pregnant Bangladeshi women, and parity and gestational age were common risk factors of vitamin D deficiency [3].

1,25(OH)2D is considered to be the most powerful physiological agent. It stimulates the active transport of calcium, phosphorus, and magnesium. Disorders in vitamin D action can lead to a decrease in the net flux of minerals to the extracellular compartment,

**Citation:** Rozmus, D.; Płomi ´nski, J.; Augustyn, K.; Cie´sli ´nska, A. rs7041 and rs4588 Polymorphisms in Vitamin D Binding Protein Gene (VDBP) and the Risk of Diseases. *Int. J. Mol. Sci.* **2022**, *23*, 933. https:// doi.org/10.3390/ijms23020933

Academic Editor: Elixabet Lopez-Lopez

Received: 29 November 2021 Accepted: 13 January 2022 Published: 15 January 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

which can lead to hypocalcemia and secondary hyperparathyroidism [4]. In addition, low concentrations of calcium and phosphorus will lead to defective mineralization of the bone matrix and rickets [5,6]. Vitamin D is also a regulator of the immune system, where the expression of CYP27B1 in macrophages leads to local production of 1,25-dihydroxyvitamin D ((1,25[OH]2D)), which induces the expression of genes encoding antimicrobial peptides [7]. (1,25[OH]2D) induces and stimulates autophagy resulting in enhanced bacterial killing, suppresses production of pro-inflammatory cytokines, and prevents overstimulated immune response [8].

The purpose of the study is to investigate and systematize the current knowledge regarding the impact of VDBP polymorphisms on the risk of incidence of various diseases and human health. The "Vitamin D" (calciferol) term refers to two secosteroids: vitamin D2 (ergocalciferol) and vitamin D3 (cholecalciferol). They are both produced from sterol precursors with light in the UVB spectrum of 280 to 320 nm. In fungi and plants, ergosterol is the vitamins' D2 precursor, while the vitamins' D3 precursor is 7 dehydrocholesterol (7-DHC), and its high concentration was found in the skin [9]. Vitamin D2 and D3 differ in side chains, but both are converted to 25-hydroxyvitamin D 25(OH)D and 1,25-dihydroxyvitamin D [9,10]. 25OHD is considered to be the best reflection of the vitamin D level in serum [10]. Vitamin D3 can be synthesized endogenously under ultraviolet (UV) light [11].

Vitamin D photoproduction starts with 7-dehydrocholesterol (7-DHC), which is synthesized and built into the membranes of the epidermis and dermis [12]. During sunlight exposure, the epidermal 7-DHC is converted into pre-vitamin D3 [12,13]. Pre-D3 is thermoisomerized to the vitamin D3 in the cell membrane. The produced cholecalciferol is removed into extracellular space and reaches the skin's capillary by diffusion [12]. Prolonged exposure to solar ultraviolet radiation while pre-vitamin D3 synthesis reaches a plateau of 10 to 15 percent of the original 7-DHC has an increasing effect only on lumisterol and tachysterol, two biologically inactive photoisomers [13]. Lumisterol can revert back to pre-D3 in the dark, but maximum levels of pre-D3 lead to the accumulation of inactive luminsterol with continued UV exposure. The production of lumisterol and tachysterol has a protective effect against the production of toxic amounts of D3 [9]. During activation and inactivation processes, cytochrome P450 (CYP) enzymes are involved throughout the vitamin D3 pathway [14,15]. The pathway is presented in Figure 1 (based on [12,15–18].

The first step is the conversion of vitamin D to 25OHD in the liver by 25-hydroxylase enzymes. Enzymes with this activity are identified as: CYP3A4, CYP2R1, CYP27A1, CYP2J1, CYP2C11, CYP2D25 [19]. The production of the hormonally active form: 1α,24 dixydroxyvitamin D (1α,25(OH)2D3) is catalyzed by CYP27B1: 25-hydroxyvitamin D-1 α-hydroxylase. An active form acts with the vitamin D receptor (VDR) [19]. There is also an alternative pathway that starts with the action of CYP11A1 on D3 and produces 20(OH)D3, 22(OH)D3, 20,23(OH)2D3, 20,22(OH)2D3, and 17,20,23(OH)3D3. Hydroxylation of some of these metabolites can occur through the activity of CYP27B1 at C1α, by CYP24A1 at C24 and C25, and by CYP27A1 at C25 and C26 [16,20]. Possible pathways are shown in Figure 2 based on SNPedia base [21]. Mitochondrial CYP24A1 catalyzes the first step of 25(OH)D3 and 1,25(OH)2D3 degradation by 24- or 23-hydroxylation [22]. CYP11A1 was also found to be expressed in extrarenal and extragonadal tissues [23] and also in the immune system [17]. CYP11A1 vitamin D metabolites are also detectable in the serum [16].

Vitamin D receptor is a member of the nuclear receptor superfamily and plays a crucial role in the actions of vitamin D [24]. VDR mediates many genomic and nongenomic effects of vitamin D. Many biological pathways and networks are influenced by VDR, for example metabolism [25], including bone metabolism and remodeling [26,27], immunity and immune response [24,28], cell proliferation and differentiation [24], and cell health [29]. VDR regulates the expression of numerous genes and is involved in calcium/phosphate homeostasis [24]. Many genes are up-regulated (CYP24A1, osteocalcin or *RankI*) or down-regulated (parathormone—PTH, CYP27B1) due to VDR activation [24]. Slominski et al. reported the alternatives to VDR nuclear receptors that are involved in

vitamin D metabolite signaling pathways: retinoic acid-related orphan receptors (RORα–γ; NR1F1–3) [30], AhR [31], and LXR [32]. *Int. J. Mol. Sci.* **2022**, *23*, x FOR PEER REVIEW 3 of 19 *Int. J. Mol. Sci.* **2022**, *23*, x FOR PEER REVIEW 3 of 19

**Figure 1.** Vitamin D metabolic pathways based on Bikle (2014), Slominski et al. (2012, 2015, 2020), Rozmus et al. (2020) [12,15–18]. Figure fully created with biorender.com (accessed on 1 November 2021). **Figure 1.** Vitamin D metabolic pathways based on Bikle (2014), Slominski et al. (2012, 2015, 2020), Rozmus et al. (2020) [12,15–18]. Figure fully created with biorender.com

**Figure 2.** VDBP gene and its polymorphisms (based on the SNPedia database [21]).

**Figure 2.** VDBP gene and its polymorphisms (based on the SNPedia database [21]).

**Figure 2.** VDBP gene and its polymorphisms (based on the SNPedia database [21]). Vitamin D binding protein was initially named the 'group-specific component' (Gc) by Hirschfield in 1959 after isolation from the α2-globulin portion of plasma [33]. As a result of the binding and transport of vitamin D analogs, the DBP name was adopted. After discovering macrophage-stimulating activities, VDBP was renamed as the macrophageactivating factor (GcMAF/DBP-MAF) [34]. The name has been changed several times, as

many different biological functions of VDBP have been discovered [34,35]. VDBP binds to fatty acids and actin monomers and also has immune functions independent of vitamin D transport [35], such as binding to leukocyte membrane proteoglycans and the activation of the complement C5 system [18]. VDBP is well known for its single nucleotide polymorphisms (SNP), and the most common are rs7041 and rs4588, located in exon 11 of the VDBP gene [18,36]. SNPs are the most abundant genetic variants in genomes [37]. SNPs may affect protein stability, folding, flexibility, and aggregation; functional sites, reaction kinetics, and dependence on environmental parameters, such as pH, salt concentration, and temperature; protein expression and subcellular localization; and protein–small molecule, protein–protein, protein–DNA, and protein–membrane interactions [38]. Many studies have shown associations between SNPs and the concentration of protein as well as substance protein transport via VDBP in this particular case [18,39,40]. The effects of vitamin D supplementation according to the most common polymorphisms of the vitamin D binding protein was studied by Al-Daghri et al., and it was shown that 25[OH]D concentrations were significantly higher among people with the major homozygous rs7041 genotype. Post supplementation 25[OH]D was higher in participants carrying homozygous major genotypes in rs4588 and rs7041 compared to other genotypes [41].

The vitamin D binding protein has a single binding site for all vitamin D metabolites and has a high affinity for 25OHD and 1,25(OH)2D [42], but has no affinity for lumisterol and minimum affinity to tachysterol [13].

Possible haplotypes are as follows: Gc1f(1f): rs7041(T) + rs4588(C); Gc1s(1s): rs7041(G) + rs4588(C); Gc2(2): rs7041(T) + rs4588(A). According to some publications, in which rs2282679 is used as a proxy for rs4588, rs2282679(A) is typically coinherited with rs4588(C) and vice versa. Since human have two copies of each gene, it leads to six possible VDBP phenotypes [21] presented in Table 1. Table 2 present SNPs of VDBP, and chromosome location. Table 3 present the frequency of rs7041 and rs4588 among populations and geographic regions. Figure 2 show the location of the most common SNPs of the VDBP gene, and their loci in exons and introns are pointed out with arrows.

**Table 1.** Characteristics of vitamin D binding protein polymorphisms in most common variants (based on Rozmus et al. 2020 with modifications [18,21]).

**Table 2.** SNPs alleles and chromosome location (based on SNPedia [21]).

**Table 3.** Frequencies of alleles in rs4588 and rs7041 among different populations and geographic regions based on [43,44].

\* [42]. \*\* [43]. \*\*\* nd means no data.

Our review focuses on the most important correlations between VDBP polymorphisms and selected diseases described in the latest scientific reports garding obesity, polycystic ovary syndrome, metabolic syndrome, diabetes mellitus, asthma, pulmonary tuberculosis, chronic obstructive pulmonary disease, coronary artery disease, multiple sclerosis, and Parkinson's Disease. This study is supplementation of our previous review concerning the role of VDBP on malignant tumors [18].

#### **2. Diseases**

#### *2.1. Bone Density*

Osteoporosis is a skeletal disease that affects women older than 50 years of age. During the past few years, it has been a serious public health problem because of the high socioeconomic burden. Patients suffer from deterioration of bone microarchitecture, low bone mineral density (BMD), and increased risk of fragility fractures [45]. The first studies on the effect of vitamin D supplementation on bone density showed that vitamin D (with calcium) reduced bone loss measured in the femoral neck, spine, and total body during the 3-year study and reduced the incidence of non-vertebral fractures [46]. The study by Martinez-Aguilar et al. supports the correlation of low serum VDBP levels with low BMD (osteopenic and osteoporotic). VDBP could be considered a novel, potential, and non-invasive biomarker for the early detection of osteoporosis [45]. The study by Rivera-Paredez et al. supports the association of VDBP and bone health. The article showed that the rs7041 G allele is associated with a higher level of VDBP and BMD compared to homozygous TT. The A allele of rs4588 was associated with a lower VDBP and BMD

compared to homozygous CC. Among men, no association was found between these polymorphisms and VDBP, but GC variants were associated with VDBP levels. In both the women and men subgroup, no association was observed between free and bioavailable 25(OH)D and BMD [47]. Among women and adolescents, the GC genotype was associated with susceptibility to low 25(OH)D levels. The study included 198 healthy girls aged 10–18 years. The AA genotype of rs4588, TT genotype of rs7041, and CT-AT/AT-AT (GC 1f-2/2-2) genotypes were significantly associated with lower 25(OH)D levels, even after adjustment for age and season at the time of blood collection [48]. Studies of Lauridsen et al. also support the VDBP role in premenopausal bone fracture risk among white women aged 45–58, as Gc2-2 is considered to increase the risk of bone fracture compared to Gc1- 1 [49]. The results of Ezura et al. indicated a complex combined effect of VDBP SNPs that underlie susceptibility to low BMD and osteoporosis. The genotyping of 13 SNPs among 384 participants and the analysis of results showed that not only a single SNP, but also a combination of them could act as a risk factor of osteoporosis. Five SNPs (39C > T, IVS1 + 827C > T, IVS1 + 1916C > T, IVS1 − 1154A > G, and IVS11 + 1097G > C) had a significant correlation with radial BMD, and IVS11 + 1097G > C located in intron 11 was the most correlated [50].

#### *2.2. Obesity*

Obesity contributes to reduced life expectancy, poor quality of life, cardiovascular diseases, type 2 diabetes, osteoarthritis, and cancer [51]. Serum vitamin D was found to be lower in obese people [52]. Obesity increases the risk of vitamin D deficiency among different population groups. Higher body mass index (BMI), waist circumference, and the sum of skinfolds were statistically significantly associated with lower 25[OH]D levels and with higher levels of PTH [53]. According to genetic studies, higher adiposity also causes an increased concentration of 25-hydroxyvitamin D, which is used as a vitamin D status indicator [54]. Another study showed that among the haplotypes rs7041 and rs4588, GC2-2 (rs7041 AA and rs4588 TT) has the lowest 25[OH]D levels compared to other haplotypes that contained at least one copy of the Gc1 allele (*p* < 0.0001) [55]. Interestingly, it was also observed that VDBP gene rs7041 polymorphism might be associated with the risk of obesity. In obese patients, a difference was found in the gene type TG + GG and TT frequency of rs7041 between obesity and control groups (*p* = 0.020). The G allele frequency was higher compared to the control group (*p* = 0.023). The TG and TG + GG of VDBP gene rs7041 polymorphism increased the risk of obesity after including age and gender [39]. The study of Almesri et al. showed that rs7041-G and the rare GG genotype were associated with an increase in BMI (*p* = 0.007 and *p* = 0.012, respectively) and had no influence on 25OHD3 levels. On the other hand, rs2282679 (A) and rs4588 (C) were associated with low 25[OH]D3 plasma levels (*p* = 0.039 and *p* = 0.021, respectively). There was no association between rs2282679 (A), rs4588 (C), and BMI in general, but after categorizing patients into subgroups based on their sex, it was shown that rs7041 GG was associated with high BMI in females (*p* = 0.003), and rs4588 CC was associated with high BMI in females (*p* = 0.034) and low levels of 25OHD3 in males (*p* = 0.009). Furthermore, rs12721377 AA was associated with low 25[OH]D3 levels in females (*p* = 0.039) [56].

#### *2.3. Polycystic Ovarian Syndrome (PCOS) and Metabolic Syndrome (MetS)*

All participants from Santos et al. were genotyped for polymorphisms rs2282679, rs4588, and rs7041, and serum 25(OH)D levels were determined. Women with PCOS were at a younger age and had significantly higher body mass index, blood pressure, and insulin resistance than the control group (*p* < 0.05). The 25(OH)D levels were lower among PCOS women with MetS, but no association was observed between PCOS and polymorphisms of VDBP. Above that, PCOS participants with MetS had a higher frequency of the TT genotype in rs7041 [57]. The study by Haldar et al. did not show significant differences in the frequency of rs7041, rs4588, and rs2060793 genotypes in PCOS and control women. The GT allele of rs7041, as well as the allelic combination of Gc1F/1F (T allele of rs4588 and C

allele of rs7041; *p* value = 0.03), were associated with an increased risk of developing PCOS in vitamin D deficient women [36].

#### *2.4. Postmenopausal Women*

Postmenopausal women can exhibit biochemical signs of vitamin D insufficiency. Vitamin D is related to bone integrity, and 25-hydroxyvitamin D is a reliable clinical indicator of vitamin D status. Low levels of vitamin D have been linked to secondary hyperparathyroidism, increased bone turnover, reduced BMD, and increased risk of osteoporotic fractures [58]. As VDBP plays a crucial role in vitamin D transport, the study of Pop et al. showed that lower estradiol levels are associated with lowering VDBP levels [59]. Studies by Sinotte et al. showed that 25(OH)D concentrations in premenopausal women are strongly associated with higher VDBP polymorphisms. Rs7041 and rs4588 were associated with lower 25[OH]D concentrations. Rare alleles of rs7041 (TT genotype) and rs4588 (AA genotype) were associated with the lowest levels of vitamin D3 in a period of low (November to April) and high (May to October) vitamin D load [60]. The study by Alharazy et al. shows that rs7041 among postmenopausal women in Saudi Arabia was associated with total 25(OH)D, and rs4588 did not show an association with total or free levels of 25(OH)D [40]. The results presented by Santos et al. suggest that rs2282679 and the DBP GC2 isoform are related to lower serum levels of DBP and with susceptibility to 25(OH)D deficiency in adults and postmenopausal women [57]. Lauridsen et al. showed that the DBP-phenotype is linked with premenopausal bone fracture risk in perimenopausal white women (595 subjects, age 45–58). There was a significant difference in bone fracture risk among women with different DBP-phenotypes (relative risk of 0.32 in Gc2-2, compared with Gc1-1) [49].

#### *2.5. Diabetes Mellitus (DB)*

Diabetes mellitus is a group of dysfunctions as a result of hyperglycemia characterized by insulin resistance (IR) and secretion or excessive secretion of glucagon. Of the two types of diabetes, type 2 (T2D) is more common and connects a problem of impaired glucose regulation with a combination of dysfunctional pancreatic beta cells and insulin resistance. However, the main risk is obesity (where abdominal is the highest risk of all types). Type 1 (T1D) is an autoimmune disorder that leads to the destruction of pancreatic beta-cells [61].

#### 2.5.1. Diabetes Type 1 (T1D)

The meta-analysis of the five studies presented showed no association between rs7041 and rs4588 polymorphisms with the risk of T1D [62].

#### 2.5.2. Diabetes Type 2 (T2DM)

The study by Zhao et al. showed that there was a significant multiplicative interaction between rs7041 and body mass index (BMI) associated with elevated blood glucose levels and a higher BMI (>28.47), and the carrying allele G was given a stronger effect than the genotype of TT. In conclusion, the interactions between GC rs7041–CYP2R1 (enzyme in the vitamin D metabolic pathway), rs1993116, and GC rs7041-BMI may explain the mechanisms by which these may increase the risk of developing T2DM [63]. Another study by Fawzy et al. examined the frequency distribution of GC-rs7041 and showed no difference between patients and healthy controls, while GC-rs4588 showed an association with T2DM in all genetic models. The rs4588 AA variant was correlated with higher serum GC globulin, albuminuria, and poor glycemic control. On the other hand, a higher frequency of rs7041\*TT and rs4588\*AA was noticed in the macroalbuminuria vs. normoalbuminuric group. Patients with the GC-2 haplotype were approximately 2.5 times more likely to develop diabetes and had higher levels of albuminuria [64]. Other results were obtained in the experiment by Klahold et al. during a case-control cohort study that was conducted to investigate an association of SNPs in the vitamin D metabolic pathway with T2D. Up to 464 T2D patients and 292 healthy controls were genotyped. Patients with

genotypes CYP27B1 rs10877012 "CC" (pc = 4 <sup>×</sup> <sup>10</sup>−<sup>5</sup> ), VDBP rs7041 "GG" (pc = 0.003), rs4588 "CC" (pc = 3 <sup>×</sup> <sup>10</sup>−<sup>4</sup> ), CYP24A1 rs2585426 "CG" (pc = 0.006), and rs2248137 "CG" (pc = 0.001) showed lower 25(OH)D3 and VDBP rs4588 "CC" lower 1,25(OH)2D3 levels (pc = 0.005). This study supports that vitamin D deficiency is highly prevalent in type 2 diabetes and most patients are also functionally affected by low levels of the active metabolite 1,25(OH)2D3. Furthermore, vitamin D system genes can affect the risk of type 2 diabetes and 25(OH)D3 concentration when compared to the healthy group. Despite this, the underlying mechanism has not been clarified, and trials, as well as functional studies, appear to be necessary to identify mechanisms by which the vitamin D system affects the pathophysiology of T2DM [65].

#### *2.6. Asthma*

Asthma is a chronic disease affecting inflammation in the lungs and airways. Common symptoms of the disease are a cough, chest tightness, and shortness of breath. Inflammation causes an overabundance of eosinophils, mast cells, activated T helper lymphocytes, and aids in identifying inflammatory mediators [66,67]. Vitamin D has been studied in asthma progression. Levels of vitamin D were significantly decreased in asthmatic patients in comparison to control patients. Results of genotyping the rs7041 among Kurdish patients showed that the GG genotype, as well as VDBP levels, was increased among the asthmatic group compared to the healthy controls (*p* = 0.003). Asthma progression was increased among patients carrying the rs7041 GG genotype [68]. A study by Fawzy et al. on s group of Egyptian patients showed that the rs7041 GG genotype is correlated significantly with asthma disease, while rs4588CA and AA genotypes were found as protective [69]. Another study supported the importance of rs7041 with the GC1S haplotype, especially among children diagnosed with asthma. The GC1S haplotype was considered to increase the risk of respiratory syncytial virus bronchiolitis in childhood and subsequent asthma development. The GC1s haplotype is associated with higher VDBP levels, which results in less free available vitamin D [70]. A study by Paraskakis et al. on a group of children with asthma showed a higher frequency of the rs7041 G allele and the A allele in rs4588 as a lower frequency allele in children with controlled asthma [71].

#### *2.7. Pulmonary Tuberculosis (PTB, TB)*

Tuberculosis is most often acquired through mycobacterial inhalation. It starts as an infection focus in the lung parenchyma (primary tuberculosis). It begins with necrotizing bronchopneumonia and progresses rapidly to necrotizing granuloma. Mycobacteria from the lungs spread only through the lymphatic system to the lymph nodes of the hilum drainage, where they cause necrotizing granulomatous inflammation [72]. As innate immunity plays an important role in the pathophysiology of tuberculosis, vitamin D with its transporter protein VDBP and its nuclear receptor vitamin D receptor can play a potential role in altering host defense against Mycobacterium tuberculosis. Decreased serum levels of vitamin D were observed in active TB patients as compared to healthy controls (*p* < 0.001) 209 [73]. The study by Zhang et al. showed [74] two less common VDBP polymorphisms, rs3733359 GA and rs16847024 CT, that were significantly associated with a reduced risk of PTB, as well as alleles rs3733359 A and rs16847024 T that were associated with a decreased susceptibility to PTB. In one of the most common polymorphisms, rs4588, the GT genotype was significantly higher in patients with PTB when compared to controls. The findings of Harishankar et al. [75] support those mentioned above, as the CA genotype rs4588 was associated with susceptibility to TB [OR: 1.47 (0.85–2.55); *p* = 0.049] and associated with 47.4% deficiency of 25(OH)D in patients with PTB, but the AA genotype was significantly associated with protection from TB [OR: 0.14 (0.02–1.29); *p* = 0.042]. No association was found with rs7041 polymorphism. Gene variants with 25(OH)D deficiency did not reveal a significant association due to the limited sample size, but the results showed a tendency towards 25(OH)D deficiency in rs7041 TG and rs4588 CA [75].

#### *2.8. Chronic Obstructive Pulmonary Disease*

Vitamin D deficiency was associated with increased risks of chronic obstructive pulmonary disease (COPD). However, the mechanism remains unknown. The vitamin D metabolite 1,25(OH)2D3 reinforced physical interactions between the vitamin D receptor with NF-κB p65 and c-Jun. The results of Fu et al. show that vitamin D is inversely correlated with inflammatory signaling in patients with COPD, and vitamin D may be a vital mediator of the progress of COPD in patients with low vitamin D levels [76]. The study of Li et al. also shows that COPD patients are at high risk of vitamin D deficiency, and the severity of COPD is inversely correlated with vitamin D levels. Furthermore, the homozygous carrier of the rs7041 T allele influences serum levels of 25OHD and is related to the susceptibility of COPD, which could be a potential candidate gene for screening COPD [77]. Among COPD smokers, high frequencies of rs7041/rs4588 haplotypes were homozygous GC1S/1S (42.5%), and higher levels of VDBP in the sputum were observed in stage I and II of COPD, only in the genotype GC1S/1S compared to non-smokers (*p* = 0.034 and *p* = 0.002, respectively) [78]. The studies of Horita et al. included 1712 patients and 1181 non COPD controls among Asians and Caucasians. The prevalence of each allele among the control group was: GC-1F 14.0%, GC-1S 53.8%, and GC-2 31.9%. Compared to GC-1S, the GC-1F allele and the GC-2 allele were associated with the risk of COPD with pooled odds ratios of 1.44 (95% CI 1.14–1.83, *p* = 0.002) and 0.83 (95% CI 0.69–0.996, *p* = 0.045), respectively. In comparison to the 1S-1S genotype, the 1F-1F genotype was a risk factor of COPD with a pooled odds ratio of 2.64 (95% CI 1.29–5.39, *p* = 0.008). The VDBP GC-1F allele was a risk for COPD in the recessive model [79]. Another study showed that patients carrying C allele at rs4588 exhibited a higher frequency of exacerbations (*p* = 0.0048), and a greater susceptibility to chronic obstructive pulmonary disease (*p* = 0.0003), as well as emphysema (*p* = 0.0029), and a tendency for rapid decline of airflow obstruction (*p* = 0.0927) [80]. The meta-analysis of Khanna et al. proves that VDBP is a major determinant of vitamin-D metabolism and transport, showing that alleles GC1F and GC1F/1F posed a risk of COPD. GC1S-1S was found to be a risk only among European participants in these studies [81].

#### *2.9. Coronary Artery Disease*

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and among CVD coronary artery disease (CAD), they are almost half of all cardiovascular deaths and the most common cause of death [82]. VDBP and its genetic polymorphisms have been linked as susceptible components for CAD [83]. The study by Peri et al. showed evidence of the association of rs4588 and rs7051 with CAD cases among patients after acute myocardial infarction and correlations of these polymorphisms with serum levels of 25-hydroxyvitamin D 25(OH)D. Rs4588 T/T was determined as a susceptibility factor for anteroseptal myocardial infarction, where the same genotype was generally more prevalent in smokers [82]. A study by Tarighi et al. among the Iranian population showed a significant association between the GG genotype (rs7041) and CAD (*p* = 0.02, OR = 0.5737 95% CI = 0.304–0.944) [83]. Daffara et al., in a group of 1080 patients, proved that 57% carried the mutated G allele of rs7041, while 22% carried the A allele of rs4588. In addition, higher C-reactive protein levels were observed in the carriers of the G allele of rs7041 (*p* = 0.02), and 25-hydroxyvitamin D levels were similar between the groups. The rs4588 A allele was associated with a higher prevalence of lesions in the left anterior descending artery and a longer lesion length (*p* = 0.04 and *p* = 0.03, respectively). Rs7041 and rs4588 did not affect the prevalence of CAD [84].

#### *2.10. Multiple Sclerosis (MS)*

Numerous studies suggest that vitamin D levels affect the risk of multiple sclerosis development and modify disease activity [85–89]. Munger et al. found an inverse relationship between serum 25(OH)D level and risk of MS among Caucasians. No similar association was found among those with darker skin or Hispanics [88]. According to the research, these groups have lower 25-hydroxyvitamin D levels with no significant health

consequences [90,91]. There are racial/ethnical differences in the polymorphism of the vitamin D-binding protein-SNPs at rs7041 and rs4588. The dominant allele in rs7041 in Caucasians is the minor allele in those with African heritage. The VDBP isoform most commonly found in individuals with darker skin is the most efficient transporter of 25 hydroxyvitamin D and its metabolites. The MS Sunshine study found that there is a strong association between higher lifetime sun exposure and MS risk across racial/ethnic groups. Low ultraviolet radiation from the sun should lead to low vitamin D status and can explain the geographic distribution of the disease. There is a lack of association between 25-hydroxyvitamin D and MS risk among those with African heritage and Hispanics [92]. Langer-Gould et al. suggested that these differences cannot be explained by racial/ethnic variations in bioavailable vitamin D [92]. Xin Zhang et al. provide evidence that VDBP rs7041 and 4588 polymorphism may not be associated with an increased risk of multiple sclerosis in the meta-analysis [62].

#### *2.11. Parkinson's Disease*

Low vitamin D status is suggested to be associated with Parkinson's Disease [93–95]. Knekt et al. found that individuals with a serum vitamin D concentration of at least 50 nmol/L had a 65% lower risk than those with values below 25 nmol/L, after the adjustment of several potential cofounders, in the follow-up for Parkinson's disease occurrence of the Mini-Finland Health survey [96]. Zheng Lv et al. suggested that patients with 25(OH)D level <50 nmol/L experienced a twofold increased risk of PD in the meta-analysis [97]. In the prospective cohort study of 137 patients with Parkinson's disease, circulating 25 hydroxivitamin D levels were deficient in one-half of the patients [98]. GC polymorphism was associated with 25(OH)D levels-TT carriers for GC1, and AA carriers for GC2 had lower vitamin D status. There was no significant association between GC polymorphism and 1,25(OH)D levels. SNPs of VDBP showed no significant association with the severity of PD. In another study of 382 patients and 242 controls in a Turkish cohort, only rs7041 was associated with PD risk [94]. Significantly higher levels of serum 25-hydroxyvitamin D was observed in the group of homozygous major allele carriers for rs2282679, rs3755967, and rs2298850 with slower progression of the disease. In the proteomic studies, a decreased level of VDBP in the CSF has been suggested to be a biomarker of disease [99].

All the information above in the Section 2 is gathered into summary table—Table 4.

**Table 4.** Summary of mentioned diseases in the Section 2. Most common VDBP polymorphisms with effects.

#### **Table 4.** *Cont.*

**Table 4.** *Cont.*

#### **3. Research Limitations on Vitamin D**

Vitamin D and its metabolites have some measurement limitations. Even if both serum and plasma can be used for vitamin D metabolite measurements, serum is preferred due to the fact that it is free from anticoagulants (heparin, EDTA, citrate). EDTA, heparin, and citrate may interfere with measurements [100]. The second problem in measuring is the stability of vitamin D metabolites because metabolites are only stable due to the binding to VDBP and proper storing: room temperature, 4 ◦C, or frozen. In case of separation from VDBP, storing at −70 ◦C is required [101]. Seasonal variation of vitamin D also needs to be considered as vitamin D biosynthesis is sun-dependent and depends on geographical locations and seasons (highest levels of vitamin D during the summer, lowest during the winter) [102]. This information may provide many significant differences in studies concerning vitamin D and its metabolites and its connection to polymorphisms occurring in the vitamin D pathway. Genetic variants of VDBP [103], DHCR7 [103], CYP2R1 [104], CYP24A1 [104], VDR [104], CYP3A4 [105], CYP2R1 [105], CYP27B [105], and LRP2 [105] were found to be associated with 25(OH)D levels. There are still many polymorphisms that have not yet been included in any studies.

Other important factors are age, sex, BMI, and lifestyle. Age can play a role, mostly in the group of elderly people >75 years old, due to reduced calcium absorption, intestinal resistance of calcium absorption to circulating 1,25(OH)2D, decreased ability of skin in vitamin D producing, deficiency of vitamin D substrate [106], and less sunshine exposure [107]. BMI is also considered to increase with age. Vitamin D deficiency is prevalent in a group of obese people which suggests the correlation of higher levels of adipose tissue and lower levels of vitamin D status [108]. Skin color also plays a role in vitamin D levels, as darker skin tones protect from UVB irradiation and, consequently, increase the risk of vitamin D deficiency. In addition, darker-skinned individuals have slower vitamin D synthesis [100].

The liver and kidneys are the two most important organs in the metabolism of vitamin D. Decreased kidney and liver functions may provide calcitriol deficiency and disruptions in overall vitamin D catabolism [100]. Diseases associated with these organs and their relationship with vitamin D and its metabolic pathway still require more research.

We suggest that all experiments that include vitamin D and its metabolism should contain more specific information concerning the studied group, age, sex, and geographical location. Articles without such information may lead to misleading conclusions.

#### **4. Conclusions**

Vitamin D and vitamin D binding protein have an undeniable impact on human health. Polymorphisms occurring in the VDBP gene can be a significant risk factor or prevalence factor in many diseases associated with obesity, diabetes, PCOS, MD, or PD. Many studies have shown VDBP and vitamin D level as a biomarker in many diseases, and if that is so, knowing the role of SNPs in proteins may contribute to finding new approaches for many syndromes and diseases associated with the vitamin D metabolic pathway.

In bone density, low levels of VDBP were associated with lowering BMD in the rs7041 "G" allele., while rs4588 "A" was linked to lower 25(OH)D levels and increased bone fracture risk. In obesity, the rs4588 "C" allele was linked to lower 25(OH)D levels and higher BMI scores among females. Rs4588 "T" and rs7041 "C" alleles increased risk in developing PCOS among women who had vitamin D deficiency. In COPD, the rs7041 "T" allele was associated with a higher risk of disease.

We believe that VDBP polymorphisms may affect the levels of vitamin D metabolites and thus contribute to the development of certain diseases. However, we are aware that most studies do not have a specific time of the year to measure vitamin D accurate metabolite levels, which can be misleading due to its seasonal nature. Research to date, although linking some diseases with vitamin D deficiency or VDBP polymorphisms, is not sufficient if the underlying mechanism is not elucidated. For this purpose, further research is required regarding the possible influence of SNP polymorphisms, their modifications in the structure of the binding protein, and their influence on the organism.

**Author Contributions:** Conceptualization, A.C. and D.R.; investigation, J.P., D.R. and K.A.; writing D.R., K.A. and J.P.; writing—review and editing, D.R. and A.C.; visualization, D.R.; supervision, A.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** Figure 1 was created thanks to Natalia Kordulewska and biorender.com.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Review* **Genetic Variants of the NF-**κ**B Pathway: Unraveling the Genetic Architecture of Psoriatic Disease**

**Rubén Queiro 1,2,\* , Pablo Coto <sup>3</sup> , Leire González-Lara <sup>4</sup> and Eliecer Coto 2,5**

**Abstract:** Psoriasis is a multifactorial genetic disease for which the genetic factors explain about 70% of disease susceptibility. Up to 30–40% of psoriasis patients develop psoriatic arthritis (PsA). However, PsA can be considered as a "disease within a disease", since in most cases psoriasis is already present when joint complaints begin. This has made studies that attempt to unravel the genetic basis for both components of psoriatic disease enormously difficult. Psoriatic disease is also accompanied by a high burden of comorbid conditions, mainly of the cardiometabolic type. It is currently unclear whether these comorbidities and psoriatic disease have a shared genetic basis or not. The nuclear factor of kappa light chain enhancer of activated B cells (NF-κB) is a transcription factor that regulates a plethora of genes in response to infection, inflammation, and a wide variety of stimuli on several cell types. This mini-review is focused on recent findings that highlight the importance of this pathway both in the susceptibility and in the determinism of some features of psoriatic disease. We also briefly review the importance of genetic variants of this pathway as biomarkers of pharmacological response. All the above may help to better understand the etiopathogenesis of this complex entity.

**Keywords:** psoriasis; psoriatic arthritis; NF-κB; comorbidities; genetic architecture

#### **1. Introduction**

Psoriasis is a chronic immune-mediated inflammatory dermopathy that affects 2–3% of the general population. Its most common companion is psoriatic arthritis (PsA), a chronic arthritis included under the spondyloarthritis concept that affects one-third of psoriasis patients [1]. According to recent estimates, PsA can affect almost 0.6% of the adult population [2]. Both psoriasis and PsA are the main poles of what is now regarded as psoriatic disease, a systemic nature entity, where apart from the skin and musculoskeletal condition, there are a wide variety of comorbidities, the most relevant being those of cardiometabolic type [1,3]. In fact, we know of the tight connections between the inflammatory burden of psoriatic disease and higher cardiovascular risk [1,4].

Psoriatic disease itself, as well as its pleomorphic clinical manifestations, result from complex stochastic interactions between elements of genetic predisposition, immunopathological alterations, and environmental factors [1]. In the case of PsA, it is currently thought that the genetic substrate of the disease favors certain alterations of the gut microbiome of these patients, which gives rise to an IL17-type immune response, which have the potential capacity to migrate to distant sites such as entheses and joints, where the activation of certain lineages of innate cellularity (ILC-3 and γδ T cells), responsible for the beginning

**Citation:** Queiro, R.; Coto, P.; González-Lara, L.; Coto, E. Genetic Variants of the NF-κB Pathway: Unraveling the Genetic Architecture of Psoriatic Disease. *Int. J. Mol. Sci.* **2021**, *22*, 13004. https://doi.org/ 10.3390/ijms222313004

Academic Editor: Elixabet Lopez-Lopez

Received: 14 November 2021 Accepted: 29 November 2021 Published: 30 November 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

of the manifestations of the disease, would prevail (gut–joint axis theory) [1,5]. Adaptive immunity would act, in this case, as positive feedback for the primal responses of innate immunity [1,5].

Psoriasis is a multifactorial genetic disease for which the genetic factors explain about 70% of disease susceptibility [1,6,7]. However, PsA can be considered as a "disease within a disease", since in most cases psoriasis is already present when arthritis begins [1]. This has made studies that attempt to unravel the genetic basis for both components of psoriatic disease enormously difficult. Moreover, this information is essential as it would help predict which psoriasis patients are at increased risk of developing arthritis over time. Genetic factors are evident from the high prevalence of PsA among first-degree relatives of PsA probands, and a recurrence risk ratio of 30–35 [1,6,7]. Also, the psoriatic disease concordance rate for monozygotic twins is higher compared to that of dizygotic twins [1]. Like psoriasis, both dominant and recessive inheritance, as well as an excessive paternal transmission pattern, has been proposed for PsA but neither apply, thus PsA has also been considered a multifactorial polygenetic disease [1].

Genome wide association studies (GWAS) have revealed more than 80 risk loci associated with psoriatic disease that are basically incorporated into three fundamental networks: (i) genes involved in the maintenance of the cutaneous barrier function, (ii) genes that control innate immune responses mediated by NF-κB and interferon signaling, (iii) genes that control adaptive immune responses that involves CD8 lymphocytes and Th17 signaling [1,7]. However, most of them are related to psoriasis risk, while only a few seem specific to PsA. Genes with genome-wide significance for PsA include *HLA-B/C, HLA-B, IL12B, IL23R, TNP1, TRAF3IP3*, and *REL* [1,7]. Although recent GWAS studies have identified numerous risk loci of psoriatic disease, almost 50% of the heritability of the disease remains unknown, and most of the genes identified so far have a small weight in the genetic etiology of the disease. This "lost" heritability can be attributed, among others, to common variants that have a very small weight in risk, copy number variants, epigenetic or epistatic interactions, or lack of power of current detection tools [1,7].

As we have commented so far, the concept of psoriatic disease not only refers to the skin or musculoskeletal domains of the disease, but also to the wide variety of comorbidities that accompany it [1,3]. Therefore, it would be interesting to know if this complex network of manifestations presents common or different genetic restriction elements. This knowledge could be key in the future to lay the foundations of truly personalized medicine for these patients.

This mini-review will focus on the importance of the NF-κB pathway, both in the predisposition to psoriatic disease, as well as in the differentiation of the genetic architecture of its different components, including the determinism of some of its comorbidities.

#### **2. The NF-**κ**B Signaling Pathway**

The nuclear factor of kappa light chain enhancer of activated B cells (NF-κB) is a transcription factor that regulates a plethora of genes in response to infection, inflammation, and a wide variety of stimuli on immune cells [8,9]. This transcription factor represents a family of structurally related proteins (p100 or NFκB2, p105 or NFκB1, p65 or RelA, RelB, or c-Rel), which exist as homo- or heterodimers [8,9]. Effects of NF-κB are mediated through three pathways. In the canonical pathway, (i) phosphorylation of inhibitory IκB proteins (IkBα) leads to release of NF-κB and its nuclear translocation to promote inflammation and cell survival. The p105 pathway (ii) is dependent on phosphorylation of p105 proteins, leading to nuclear translocation of p52 heterodimer complexes to promote inflammation. Different to the above two pathways, the alternate p100 pathway (iii) does not depend on the NF-κB essential modulator (NEMO)-IKKa-IKKb (NEMO-IKK) complex for phosphorylation, but rather on NF-κB inducing kinase (NIK), and IKKa heterodimers phosphorylate p100 and allows nuclear translocation of p52/RelB heterodimers [8,9].

The pathogenetic role of NF-κB has been demonstrated in many diseases including cancer, immune-mediated inflammatory diseases (IMIDs), as well as cardiovascular

diseases [9]. Genome-wide association studies have revealed several psoriatic disease susceptibility genes associated with the NF-κB pathway [10]. In addition, the role of NF-κB in psoriasis is supported by studies that reported its differential expression in normal vs. affected skin, but also by studies that showed that the inhibition of this transcriptional factor by several compounds ameliorated skin inflammation [11,12]. ceptibility genes associated with the NF-κB pathway [10]. In addition, the role of NF-κB in psoriasis is supported by studies that reported its differential expression in normal vs. affected skin, but also by studies that showed that the inhibition of this transcriptional factor by several compounds ameliorated skin inflammation [11,12]. Due to its relevance to this review, we will refer in detail to a specific pathway, which

The pathogenetic role of NF-κB has been demonstrated in many diseases including cancer, immune-mediated inflammatory diseases (IMIDs), as well as cardiovascular diseases [9]. Genome-wide association studies have revealed several psoriatic disease sus-

Due to its relevance to this review, we will refer in detail to a specific pathway, which involves TNF-α and the NF-κB transcription complex (Figure 1) with special focus on genetic variations in *CARD14*, *TNFSRF1B*, *NFKB1*, *NFKBIA*, and *NFKBIZ*. involves TNF-α and the NF-κB transcription complex (Figure 1) with special focus on genetic variations in *CARD14*, *TNFSRF1B*, *NFKB1*, *NFKBIA*, and *NFKBIZ*.

*Int. J. Mol. Sci.* **2021**, *22*, x FOR PEER REVIEW 3 of 11

**Figure 1.** The TNF-α/TNFRSF1A,B/NF-KB signaling pathway. TNF-α is a pro-inflammatory cytokine synthesized by various cell lineages, mainly macrophages, dendritic cells, keratinocytes as well as various T cell types. It exerts its functions through binding to type 1 (TNFR1) and 2 (TNFR2) cell membrane receptors. TNFR2 (TNFRSF1B) shows higher affinity for TNF-α. NF-κB is a dimer made up of Rel family proteins (p50, p52, Rel A/p65, cRel, and Rel B), the p50/p65 heterodimer being the most common. In the absence of TNF-α stimulation, the activity of NF-κB is regulated at cytoplasmic level by an inhibitory complex of proteins called IKB or Kappa Beta inhibitors (IkB alpha, beta, and epsilon) that regulate its function by blocking its translocation to the nucleus. The binding of TNFα to its receptors triggers the activation of the inhibitor kinases of NF-κB or "IKK complex" consisting of IKK-alpha, IKK-beta and IKK-gamma or NEMO. The characteristic event is the phosphorylation of IKB-alpha by the IKKa/b complex, inducing its ubiquitination and degradation by the proteasome; and thus, allowing the release of NF-κB. Once in the nucleus, NF-κB meets another inhibitory protein called IKBZ. Likewise, IKBZ can act as a transcription factor regulated by IL-17A, IL-1beta, and to a lesser extent, by TNF-α. In turn, IKBZ plays an important role in the development and expansion of Th17 lineages. Finally, CARD14 activates NF-κB by partially known mechanisms (see text for more details), although some authors suggest that CARD14 would activate the IKK complex, consequently regulating the activity of NF-κB, leading to an increase in its transcriptional activity. TNF-α: tumor necrosis factor-alpha. TNFR1 (TNFRSF1A): TNF-α type 1 receptor. TNFR2 (TNFRSF1B): TNF-α type 2 receptor. NF-κB: nuclear factor of kappa light chain enhancer of activated B cells. IKB: kappa-beta inhibitors. IKK: inhibitor kinases of NF-κB. IKBZ: z-inhibitor protein of NF-κB. IL: interleukin. Th: T-helper. CARD14: caspase recruitment domain family member 14. Activation of the NF-κB pathway leads to increased transcription of numerous genes including proinflammatory cytokines, chemokines, and growth factors, all of which are **Figure 1.** The TNF-α/TNFRSF1A,B/NF-KB signaling pathway. TNF-α is a pro-inflammatory cytokine synthesized by various cell lineages, mainly macrophages, dendritic cells, keratinocytes as well as various T cell types. It exerts its functions through binding to type 1 (TNFR1) and 2 (TNFR2) cell membrane receptors. TNFR2 (TNFRSF1B) shows higher affinity for TNF-α. NF-κB is a dimer made up of Rel family proteins (p50, p52, Rel A/p65, cRel, and Rel B), the p50/p65 heterodimer being the most common. In the absence of TNF-α stimulation, the activity of NF-κB is regulated at cytoplasmic level by an inhibitory complex of proteins called IKB or Kappa Beta inhibitors (IkB alpha, beta, and epsilon) that regulate its function by blocking its translocation to the nucleus. The binding of TNF-α to its receptors triggers the activation of the inhibitor kinases of NF-κB or "IKK complex" consisting of IKK-alpha, IKK-beta and IKK-gamma or NEMO. The characteristic event is the phosphorylation of IKB-alpha by the IKKa/b complex, inducing its ubiquitination and degradation by the proteasome; and thus, allowing the release of NF-κB. Once in the nucleus, NFκB meets another inhibitory protein called IKBZ. Likewise, IKBZ can act as a transcription factor regulated by IL-17A, IL-1beta, and to a lesser extent, by TNF-α. In turn, IKBZ plays an important role in the development and expansion of Th17 lineages. Finally, CARD14 activates NF-κB by partially known mechanisms (see text for more details), although some authors suggest that CARD14 would activate the IKK complex, consequently regulating the activity of NF-κB, leading to an increase in its transcriptional activity. TNF-α: tumor necrosis factor-alpha. TNFR1 (TNFRSF1A): TNF-α type 1 receptor. TNFR2 (TNFRSF1B): TNF-α type 2 receptor. NF-κB: nuclear factor of kappa light chain enhancer of activated B cells. IKB: kappa-beta inhibitors. IKK: inhibitor kinases of NF-κB. IKBZ: z-inhibitor protein of NF-κB. IL: interleukin. Th: T-helper. CARD14: caspase recruitment domain family member 14.

involved in the onset and perpetuation of the inflammatory response in psoriatic disease [11,12]. Interestingly, the activation of NF-κB induces the production of TNF-α, which in Activation of the NF-κB pathway leads to increased transcription of numerous genes including proinflammatory cytokines, chemokines, and growth factors, all of which are involved in the onset and perpetuation of the inflammatory response in psoriatic disease [11,12]. Interestingly, the activation of NF-κB induces the production of TNF-α, which

in turn can stimulate this pathway, thus resulting in positive proinflammatory feedback, and playing a key role in the chronicity of the skin/joint inflammatory response [11,12]. Moreover, an association between high levels of TNF-α and the activation of NF-κB has been found in the skin of patients with psoriasis; and therefore, a possible mechanism of action of anti-TNFα drugs would be, at least in part, the inhibition of the transcriptional activity of NF-κB [13], as we will see later.

#### **3. Role in the Etiology of Psoriatic Disease**

The caspase recruitment domain family member 14 (CARD14) is an intracellular scaffold protein that is prominently expressed in keratinocytes and mediates NF-κB activation through the formation of a CBM (CARD14-BCL10-MALT1) signaling complex [14]. It has been shown that gain-of-function mutations of *CARD14* enhance CBM complex formation in keratinocytes driving hyperactivation of the NF-κB pathway [15]. This leads to transcription of several chemokines (CCL20, CXCL1, and CXCL2), cytokines (IL-36 and IL-19), and antimicrobial peptides, followed by recruitment and activation of neutrophils, dendritic cells, and T cells [15]. Activated dendritic cells in turn release IL-23, which drives the downstream expression of IL-17 and IL-22, two central cytokines in the pathogenesis of the disease [15]. Variations in the *CARD14* gene have been associated with psoriatic disease. Jordan et al. identified 15 nucleotide variants in the *CARD14* gene significantly associated with the risk of psoriasis [16]. In a meta-analysis, they confirmed the association between rsll652075 (p. Arg820Trp) and psoriasis [17]. This association was later confirmed by two large meta-analysis [18,19]. We also found a statistically significant association between rsll652075 (CC genotype) and the risk of developing psoriasis (OR 1.59), regardless of the Cw6 genotype. However, we did not find genotypic differences related to psoriasis severity, age at disease onset (above or below 40 years), PsA, or family history of psoriasis [20].

The *TNFSRF1B* gene encodes the type 2 membrane receptor for TNF-α. The SNP TN-FRSF1B rs1061622 (p. Met196Arg) has been implicated in the risk of several IMIDs [21,22]. This variant has hardly been studied in psoriatic disease. In our population, we did not find differences in allelic and genotypic frequencies between patients and controls for the SNP rs1061622. Neither were differences found in psoriasis severity, nor between the presence or absence of PsA. However, we did find an increased frequency of the G allele in the Cw6 + patients (OR 1.69), which suggests an increased risk of developing psoriasis conditioned by the HLA-Cw6 allele [23].

The *NFKB1* gene encodes the p50 protein, responsible for binding to the consensus sequence of the promotor region of many genes [8,9]. The most studied and best characterized polymorphism of this gene is a 4 nucleotide indel in the promoter region (rs28362491; -94 of the ATTG). The copies of the gene with the deletion would have less promoter activity and, therefore, translate into lower protein levels, which could explain the genetic associations described for this variant [24]. Other variants located at the chromosomal region where *NFKB1* is found have been investigated and related to the risk of psoriasis, specifically rs1020760 and rs1609798 [25]. A study in a Han Chinese population has recently established the association between the SNP rs1020760, psoriasis, and a positive family history of psoriasis [26]. We studied the SNP rs230526 A/G in the *NFKB1* gene, which is in complete linkage disequilibrium (LD) with rs28362491 (-94 of ATTG). Therefore, the genotypes of rs230526 would allow us to infer those of rs28362491. Despite this, we did not find any difference between allelic or genotypic frequencies in patients and controls. We also did not see a significant effect on its severity, PsA, or the age of onset of psoriasis; nor differences in relation to the presence of HLA-Cw6 [27].

*NFKBIA* gene encodes IκBα, a cytoplasmic inhibitor of the NF-κB transcriptional complex. That is, its binding to the complex keeps it inactive in the cytoplasm by blocking its ability to move to the cell nucleus. In response to certain stimuli, IκBα is phosphorylated, and this releases it from the complex, which can now migrate to the nucleus and act as a multigenic transcription factor [8,9]. Variants in this gene have been associated with the risk of myocardial infarction and several IMIDs [28,29]. In 2010, two GWAS established

the association of two *NFKBIA* SNPs and the risk of psoriasis, while in 2015 a third GWAS confirmed the association of an additional SNP with psoriasis [30–32]. We have studied the rs7152376 SNP, which is in complete LD with rs12883343, a SNP related in the literature with both psoriasis and PsA. We did not find any association between rs7152376 and the risk of psoriasis, psoriasis severity, or the age at disease onset. However, we did find a statistically significant association between the rare G allele and the risk of PsA, with a dominant effect (AG + GG vs. AA). The rare NFKBIA rs7152376 C was significantly more frequent in PsA vs. controls (OR 2.03). The difference was even higher between PsA vs. "pure" psoriasis (OR 3.2) [33]. These findings are in line with the results of a meta-analysis that described the association of rs12883343, in complete LD with rs7152376, and the risk of PsA [34]. In this meta-analysis, the rare allele was also more frequent in PsA than in controls (meta-OR 1.22). Therefore, this variation in *NFKBIA* could be a true risk marker for PsA within the psoriatic complex.

The *NFKBIZ* gene encodes the IKBζ protein. The activity of NF-κB is regulated by nuclear inhibitors, such as IKBζ, which block its binding to DNA [8,9]. On the other hand, these peptides have a dual effect since by themselves they can act as transcription factors activating the expression of genes regulated by IL-17 or TNFα [35]. In 2015, Tsoi et al. described the genetic association between the *NFKBIZ* SNP rs7637230 and psoriasis [36]. This SNP is located outside the gene at the 3 'end, so it could be an indirect marker of some variant in *NFKBIZ* associated with its expression and/or function. The best candidate described so far would be an indel-type polymorphism in intron 10, rs3217713. Given its proximity to the 5 'end, it could influence the processing of total RNA into messenger RNA, an aspect that should be further investigated in vitro. We have investigated this indel SNP in psoriatic disease. When studying rs3217713, we did not find significant differences between patients and controls, and between the different clinical groups of patients, except for Cw6. Interestingly, the risk of developing psoriasis conferred by the combination of Cw6 + and rs3217713 ins/ins was statistically higher (OR 3.61) than the risk conferred by each genotype separately, which suggests some mechanism of genetic interaction or epistasis between both loci [37].

#### **4. NF-**κ**B Pathway Variants and Drug Response**

Due to the various levels of regulation, the NF-κB signaling pathway can be potentially targeted at various levels including kinases, phosphatases, ubiquitination, nuclear translocation, DNA binding, protein acetyl transferases, and methyl transferases [38]. Currently available drugs for the treatment of psoriasis and PsA interact in some way with these targets within the NF-kB signaling pathway. For example, NSAIDs are commonly used in the treatment of PsA and have been shown to inhibit the activity of IKKβ, preventing the degradation of IκB and blocking NF-κB nuclear translocation. Glucocorticoids are highly effective in the topical treatment of active psoriatic lesions but also as systemic agents in PsA and have been shown to inhibit NF-κB through both indirect and direct mechanisms. Indirectly, glucocorticoids induce the transcription and synthesis of IκBα, enhancing the retention of NF-κB in the cytoplasm and effectively inhibiting its activation. However, under certain conditions, glucocorticoids can directly inhibit activated NF-κB via competition between p65 and the glucocorticoid receptor for limited nuclear supplies of coactivator proteins. Both receptors require these coactivators for maximal activity, and by sequestering the available stores, glucocorticoids interfere with p65-dependent gene activation. Stimulation of human synovial cells with TNFα results in NF-κB activation and subsequent cell proliferation, with NF-κB blockade able to activity inhibit this TNFαinduced proliferation. Anti-TNFα biologics effectively remove these upstream activator stimuli, and as such, the inhibition of NF-κB activation can be considered part of their mechanism of action [38]. Secukinumab, an anti–IL-17A antibody, mediates some of its antipsoriatic effects by rapidly inhibiting IκBζ and subsequently IκBζ signature genes, which highly suggests that IL-17A/IκBζ signaling is a key driver of the complex psoriatic phenotype. These data strongly indicate that an important and very early mechanism of

action of anti–IL-17A therapy in patients with psoriasis is a reduction in IκBζ expression and a concomitant reduction in expression of IκBζ signature genes. It is possible that the IL-17A/IκBζ signaling axis also plays a role in the pathogenesis of psoriatic arthritis [39].

The search for genetic markers of good/bad response to drugs is a booming field, but still in its infancy. In this case, we will focus on the associations between NF-κB pathway variants and the response to anti-TNFα drugs. Anti-TNFα blocking agents could negatively modulate the signaling of the NF-κB pathway [13]. Genetic variations in the components of this pathway, particularly those that are related to the risk of psoriatic disease, could serve as pharmacogenetic markers. With respect to *CARD14* gene, we did find a significant association between rsll652075 (CC genotype) and the response to anti-TNFα drugs measured as PASI 75 at 24 weeks (OR 3.71) [40]. In our study cohorts, carriers of the G allele (GT + GG genotypes) of rs1061622 *TNFRSF1B* were associated with a worse response to anti-TNFα drugs (OR 2.34) [23]. However, the literature shows disparate results both in psoriatic disease and in other IMIDs, in this regard [41]. In our experience with anti-TNFα drugs, we did not observe any association between the genetic variants in *NFKB1*, *NFKBIA*, and drug response. However, in the case of *NFKBIZ*, the insertion allele was found more frequently in the group of non-responders, with a recessive effect (II vs. ID + DD *p* = 0.02), and OR for the negative drug response of 3.01 (95%CI: 1.15–7.88) [42]. However, the results of the literature in this regard are also disparate [43]. Anyway, it must be considered that this insertion allele is associated with the risk of psoriasis conditioned by the presence of HLA-Cw6, and the latter has also been linked to drug response in this disease [44].

#### **5. NF-**κ**B Genetic Variants and Cardiometabolic Comorbidity**

Psoriatic disease is accompanied by extracutaneous and extra-articular manifestations, as well as by a wide range of comorbidities. Compared with controls, patients with psoriatic disease have a higher incidence rate of other autoimmune diseases, cardiovascular disease, obesity/overweight, depression, anxiety, smoking, cancer, diabetes, alcohol abuse, osteoporosis, uveitis, and fatty liver disease [45]. One of the common connectors between the disease and its comorbidities is inflammation. For example, chronic inflammation in both psoriatic disease and atherosclerosis promotes increased production of adipokines and pro-inflammatory cytokines (e.g., TNF) with consequent insulin resistance and endothelial dysfunction. Also, data from animal models and human studies highlight the proatherogenic role of IL-17 on vascular inflammation, acting in synergy with TNF and IL-6. IL-17 is involved in endothelial dysfunction, hypertension, plaque progression and destabilization, stroke, and myocardial infarction. IL-17 also links inflammation with insulin resistance and adipocytes dysfunction (two common aspects of the so-called psoriatic metainflammation). In mice models with systemic inflammation and insulin resistance, there is accumulation of IL-6/IL-17 co-expressing T cells in the adipose tissue; these cells enhance leptin production, which eventually acts in synergy with IL-6 and IL-17 to promote Th17 differentiation. This complex network drives local and systemic insulin resistance, and, in fact, IL-17 neutralization improves glucose uptake. Another example of these relationships is seen in osteoporosis (OP), another common comorbidity among psoriatic patients. Cytokines involved in PsA pathogenesis have an effect on bone cell activity with possible inhibitory or stimulatory stimuli on osteoclasts and osteoblasts. TNF, IL-6, and IL-1, for example, exert stimulatory activity toward osteoclasts and inhibitory activity toward osteoblasts. IL-12 and IL-23 are also critical to inflammation-induced bone resorption. Specifically, IL-23 upregulates the receptor activator of nuclear factor kappa- B (RANK) on preosteoclasts and induces Th17 cells to produce IL-17. IL-17, one of PsA signature cytokines, promotes bone resorption via RANK ligand upregulation. Indeed, Th17 cells have been found to be highly increased in blood and tissues of patients with OP [45].

In any case, for the purposes of this review, we will focus on the most important comorbidity in these patients, such as cardiovascular disease. Although psoriatic disease is frequently accompanied by cardiovascular comorbidity, the potential genetic connections

between this comorbidity and psoriatic disease have received little attention. Furthermore, we do not know whether the genetic pathways to both cardiovascular comorbidity and psoriatic disease are common or differ. Although some studies suggest shared genes between psoriasis and cardiometabolic comorbidity, others suggest that the genetic architecture of psoriatic disease and cardiometabolic traits are largely distinct [46,47]. The NF-κB pathway might play a role in the pathogenesis of renal disease and type 2 diabetes mellitus (T2DM). In that sense, we studied 487 individuals, all Caucasian and aged 65–85 years. A total of 104 (21%) had impaired renal function and 30% were diabetics. The NFKB1 variants were significantly associated with T2DM: rs7667496 (OR 1.68) and rs28362491 (OR 1.67). There was a trend toward the association of these variants with impaired renal function. The two NFKB1 variants were in LD, and homozygous for the two non-risk alleles (rs7667496 CC + rs28362491 II), were significantly more common in the non-diabetics [48]. Therefore, *NFKB1* gene variations may be related to T2DM and an impaired renal function, both aspects clearly present in psoriatic patients [1,3].

Several reports show that the transcription factor NF-κB also activates genes involved in various cardiovascular diseases, in the pathogenesis of cardiac remodeling, and heart failure [49]. NF-κB is activated in the heart in many conditions: during acute ischemia and reperfusion, during unstable angina or in response to preconditioning [49]. An association between inflammation and cardiovascular risk has been suggested by the evidence that inflammatory cytokines, including IL-1β, IL-6, IL-18, and TNF-α, are increased in patients with heart failure, and increased inflammatory markers, such as C-reactive protein, predict a worse survival during acute coronary syndromes [49]. The association between psoriatic disease and cardiovascular risk has been clearly established over the last decade [1,3,4]. We determined whether common variants in three NF-κB genes were associated with early-onset coronary artery disease (CAD). Allele and genotype frequencies for the NFKB1 rs28362491 (-94 delATTG) and NFKBIA rs8904 were not significantly different between patients and controls. For the NFKBIZ rs3217713, the deletion allele was significantly more frequent in early-onset CAD patients. Deletion-carriers were more frequent in CAD (OR 1.48). Therefore, NFKBIZ variant was an independent risk factor for developing early-onset CAD [50]. However, in a recent meta-analysis of 13 case-control studies with 17 individual cohorts containing 9378 cases and 10,738 controls, the mutant D allele in NFKB1 rs28362491 locus increased the risk of CAD [51].

Table 1 summarizes the main results of this review.

**Table 1.** Genetic variants within the TNF-α/NF-κB pathway and psoriatic disease features.

**Table 1.** *Cont.*

\* Other variants located at the chromosomal region where *NFKB1* is found have been investigated and related to psoriasis risk, specifically rs1020760 (also associated with a positive family history) and rs1609798 [25,26]. LD: linkage disequilibrium. IMIDs: immune-mediated inflammatory diseases. CARD14: caspase recruitment domain family member 14 gene. TNFSRF1B: Type 2-TNFα receptor gene. NFKB1: NFκB subunit 1 gene. NFKBIA: NFκB alpha-inhibitor gene. NFKBIZ: NFκB zeta-inhibitor gene.

Obesity, the core element of metabolic syndrome (MetS), is common among patients with psoriatic disease [1,3]. The NF-κB pathway is involved in the low-grade chronic inflammation associated with obesity. The noncanonical IkB kinase ε and TBK1 are upregulated by overnutrition and may therefore be suitable potential therapeutic targets for MetS [52]. Also, NF-κB modulates apical components of metabolic processes including metabolic hormones such as insulin and glucagon, and therefore this pathway is also involved in both insulin resistance and sensitivity, another key component of psoriatic disease-associated MetS [3,49]. The importance between metabolic derangements and NFκB-mediated inflammation associated with psoriatic disease is already moving to the practical realm. Thus, it has recently been set that obese, diabetic, and hypertensive patients with PsA tend to present a better response and persistence to secukinumab, an anti-IL17A therapy [53].

#### **6. Conclusions**

The NF-κB is an essential regulator of inflammatory and metabolic processes associated with psoriatic disease. Genetic variants of this pathway are associated not only with the risk of suffering the condition but may also be at the base of the comorbidities that frequently accompany it. These variants can also help improve treatment selection. In recent years, genetic variant analysis of the NF-κB pathway has contributed to a finer dissection of the genetic architecture of psoriatic disease. However, we still need further analysis of these genetic variants, especially with an emphasis on non-canonical regulators of this pathway, which currently have a direct implication in the appearance of important comorbidities of psoriatic disease such as diabetes and obesity. Thus, for example, an IKK/TBK1 inhibitor has been tested in obese individuals with type 2 diabetes showing encouraging results [52]. These findings may have future implications for a disease approach focused on the needs of each psoriatic patient.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.

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