Mannose-Binding Lectin Gene Variants as Disease Susceptibility Biomarkers in Rheumatoid Arthritis

Abstract

Background:

Rheumatoid arthritis (RA) is a chronic, inflammatory autoimmune disease characterized by progressive destruction of peripheral joints. About 1% of the human population worldwide is suffering from this disease. The pathophysiology of RA is largely being influenced by immune dysregulation. Mannose-binding lectin (MBL), an acute-phase protein, has been reported to play an important role in pathogenesis of RA by the activation of complement pathway. Various studies documented the established the role of MBL in pathogenesis of various autoimmune diseases, including RA. MBL protein is encoded by gene MBL2, mapped on chromosome 10q11.2-q21.

Objective:

Both MBL serum levels and activity are mainly determined genetically by its variants. So considering the putative clinical role of MBL2, this case-control association study was designed to assess its six functional variants in a northwestern Indian cohort.

Methods:

Genetic typing of six MBL2 variants was done by amplification refractory mutation system-polymerase chain reaction. Data were analyzed using suitable statistical tools.

Results:

Significant difference has been observed in genotypic and allelic distribution between cases and controls for rs11003125. Comparison of allelic distribution for rs1800450 showed significantly high prevalence of A allele in cases than controls.

Conclusion:

These results indicate that MBL2 variants may act as plausible marker for susceptibility toward RA. Keeping this in view, it is pertinent to screen these variants in other population groups of India.

Introduction

Rheumatoid arthritis (RA) is an autoimmune, chronic, inflammatory, systemic disease characterized by progressive destruction of peripheral, synovial joints in a symmetric manner (Feldmann et al., 1996). Various comorbidities, including extra-articular manifestations along with cardiovascular diseases, have been associated with RA (Goodson et al., 2005; Turesson et al., 2006). About 1% of the human population worldwide is suffering from this disease (Silman & Pearson, 2002; Cieza et al., 2021). The exact etiology of RA is unknown; various factors, including environmental factors and genetic factors, have been suggested to be involved (Feldmann et al., 1996). The pathogenesis of RA involves increased inflammation, which led to alteration in glycosylation profile of immunoglobulin G (IgG) antibodies (Magorivska et al., 2014). Mannose-binding lectin (MBL), an acute-phase protein, has been reported to play an important role in the pathogenesis of RA. Interaction of MBL complexes with the Fc region of agalactosyl IgG molecules leads to the activation of a complement pathway, one of the suggestive mechanisms involved in the pathogenesis of RA (Troelsen et al., 2012).

MBL protein is encoded by gene MBL2, mapped on chromosome 10q11.2-q21, and consists of five exons (Garred et al., 2009). It plays an important role in the first line of defense, by binding to specific sugar moieties present on the surface of microorganisms, and results in their phagocytosis, along with modulation of inflammation (Kalia et al., 2021; Dong et al., 2022). A perusal of literature documented the well-established dual role of MBL in various autoimmune diseases, including RA (Schafranski et al., 2004; Luz et al., 2010; Glesse et al., 2011; Im et al., 2012; Raj et al., 2022). Several studies demonstrated that disease severity and exacerbation of RA may largely be influenced by MBL levels (Ip et al., 2000; Epp Boschmann et al., 2016). Elevated MBL levels were reported to exert a proinflammatory role in the pathogenesis of RA (Saevarsdottir et al., 2007). This finding is supported by the fact that recognition of immune complexes by MBL leads to unwarranted activation of a complement pathway, resulting in inflammation and exacerbation of disease. A growing body of evidences also reported the correlation of elevated MBL levels with comorbidity/increased risk for myocardial infarction in patients with RA (Troelsen et al., 2007; Raj et al., 2022). On the contrary, lower functional MBL levels lead to defective efferocytosis as a result of inappropriate uptake of cellulose debris by macrophages (Jacobsen et al., 2001). Various studies demonstrated the association of low serum MBL levels with high prevalence of infections and reactive amyloidosis, a clinical manifestation, and major complication of RA (Graudal et al., 2000; Maury et al., 2007).

Both MBL serum levels and activity are mainly determined by the genetic variants (Madsen et al., 1995; Boldt et al., 2006). As per the conventions used extensively in literature, the point mutations in exon 1 elicit decreased serum MBL levels; these mutations are commonly notated in literature as B, C, and D variants, corresponding to rs1800450/codon54 (G > A), rs1800451/codon57 (G > A), and rs5030737/codon 52 (G > A), respectively (Bernig et al., 2004; Garred et al., 2006). Wild-type allele is designated as “A.” Three promoter region polymorphisms are also reported to influence serum MBL levels. These variants are commonly notated as P/Q, X/Y, and L/H for rs7095891, rs7096206, and rs11003125, respectively. Here rs11003125 (L/H), rs7096026 (Y/X), and rs7095891(P/Q) correspond to C > G, G > C, and C > T change, respectively. Despite being extensively studied, the role of MBL in pathogenesis of RA is still being argued. Furthermore, reported functional haplotypes of MBL2 may certainly be affected by different geographical regions and races. So, keeping in view the putative clinical role of MBL2, this study was designed to assess its six functional variants in a northwestern Indian cohort.

Materials and Methods

Study population

This case-control association study was conducted at Department of Human Genetics, Guru Nanak Dev University, Amritsar (Punjab, India). For this study, a total of 170 female patients with RA were recruited from a local rheumatology clinic. All the patients were diagnosed according to 2010 American College of Rheumatology and European League Against Rheumatism criteria (Kay and Upchurch, 2012). One hundred seventy age- and gender-matched (p > 0.05) healthy controls were also recruited from adjoining areas. The study protocol was approved by Institutional Ethics Committee in accordance with the Declaration of Helsinki. A voluntary informed written consent was obtained from each subject or from the accompanied person, in case the patient was unable to give it.

Inclusion criteria

Only age- and gender-matched participants from northwest region of India were included in the study. All individuals were genetically unrelated.

Exclusion criteria

The exclusion criteria for study participants included pregnant women, nursing mothers, smokers, alcoholics, and individuals having known chronic disease conditions. To exclude cases of juvenile RA, patients <18 years of age were excluded in this study.

Genotyping of MBL2 variants

Two milliliters of blood was withdrawn from each participant and immediately transferred to ethylenediaminetetraacetic acid-coated vials. These blood samples were carried to the research laboratory on ice packs and stored at −20°C, pending further use. Genomic DNA was isolated by the inorganic method and stored at −80°C till further use (Miller et al., 1988). The different nucleotide sequences harboring the studied single nucleotide polymorphisms (SNPs) rs11003125, rs7096206, rs7095891, rs5030737, rs1800450, and rs1800451 were amplified by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) in a thermocycler (Eppendorf, Germany). The various primers used for all the SNPs for ARMS-PCR are given in Supplementary Table S1. ARMS-PCR for all SNPs was performed in a final volume of 20 µL using standardized protocol containing 50 ng DNA, 1X Taq buffer A with 15 mM magnesium chloride, 62.5 µM deoxynucleotide triphosphates, 0.2 µM primer mix (forward and reverse primer each), and 0.9 U Taq polymerase. The PCR conditions used for specific SNP along with details of primers, amplicon length, obtained are given in Supplementary Table S1. The ARMS-PCR products were analyzed on 3% agarose gel containing 1 µg/mL ethidium bromide and visualized on gel documentation system (Protein Sample, AlphaImager MINI). Genotyping was cross-confirmed by subjecting 10% of the samples to Sanger sequencing.

Statistical analyses

Sample size for genetic association was calculated by CaTS Power calculator (http://www.sph.umich.edu) to achieve a power of 80%, taking assumptions of 1% worldwide prevalence and an odds ratio of 1.5 (α = 0.05). All the continuous variables were expressed as mean ± standard deviation. Categorical variables were expressed as number or count and were compared between cases and controls using odds ratio (Medcalc software). Analysis was performed assuming dominant, codominant, and recessive genetic models using Web-Assotest program (http://www.ekstroem.com). The haplotype combinations for the SNPs were estimated in cases and controls by PHASE software version 2.1 (https://stephenslab.uchicago.edu/phase/download.html). In line with the available literature, the secretor haplotypes were constructed through the combination of rs11003125, rs7096206, rs7095891, rs5030737, rs1800450, and rs1800451 (Garred et al., 2006). For exon 1 SNPs (rs5030737, rs1800450, and rs1800451), the haplotype A denotes the combination of wild-type allele for all the SNPs, and O denotes the presence of variants for the same. D and C denote the presence of variant allele for rs5030737 and rs1800451, respectively, and the presence of wild-type allele for the other two SNPs in the combination. SNP analyzer software was used for calculating linkage disequilibrium (LD) scores among different studied SNPs. p-Value ≤0.05 was defined as the significant value.

Results

This case-control study included 170 patients with RA having a mean age of 45.65 ± 12.97 years. All patients were rheumatoid factor (RF)-positive females. Genetic analysis revealed no significant difference (p < 0.05) in genotypic and allelic distribution for three structural polymorphisms, rs5030737, rs1800451, and rs1800450, of MBL2 gene (Table 1). For rs5030737, high frequency of DD genotype has been observed in controls (15.3%) than patients with RA (6.5%). There was suggestive evidence of an association of this SNP in the recessive model (DD vs. AA/AD; odds ratio [OR]: 0.38, 95% confidence interval [CI] = 0.18-0.80, p = 0.008). This study found no significant association (p > 0.05) of rs1800451 polymorphism with any genetic model. Almost similar genotypic and allelic distribution with high prevalence of heterozygosity has been observed in both cases and controls for this SNP. For rs1800450, AA genotype was found to be more prevalent in cases (41.2%) than controls (26.4%). Significant suggestive association of this SNP has been observed in dominant model (AB/BB vs. AA; OR: 0.51, 95% CI = 0.33-0.81, p = 0.004). Significant difference has been observed in genotypic and allelic distribution between cases and controls for structural variant rs11003125 (H/L). The frequency of LL genotype was found to be significantly higher in cases (22%) than controls (12.5%). Allelic distribution also showed significantly high prevalence of L allele in cases (22.4%) than controls (14.7%). Genetic analysis revealed strong association in codominant model, as well as in recessive model for this SNP (HH vs. LH = LH vs. LL; OR: 0.39, 95% CI = 0.25-0.62, p = 0.001 and HH vs. LL/LH; OR: 0.06, 95% CI = 0.01-0.25, p = 0.001, respectively). However, almost similar allelic and genotypic distribution had been observed for rs7096206 polymorphism in cases and controls (p > 0.05), and no significant association with any of the genetic model was observed with this SNP.

Table 1.

Genotypic and Allelic Distribution of Various SNPs in Cases and Controls

Genotypes	Cases N (%) n = 170	Controls N (%) n = 170	OR (95% CI)	p-Value
rs11003125 (L/H promoter)
LL (CC)	38 (22.4)	25 (14.7)	1.000
LH (CG)	130 (76.5)	116 (68.2)	0.045 (0.09-0.21)	0.0001
HH (GG)	2 (1.1)	29 (17.1)	0.74 (0.42-1.30)	0.2890
L (C)	206 (60.6)	166 (48.8)	1.000
H (G)	134 (39.4)	174 (51.2)	0.62 (0.46-0.84)	0.0021
Dominant model			0.60 (0.34-1.05)	0.069
Codominant model			0.39 (0.25-0.62)	0.000
Recessive model			0.06 (0.01-0.25)	0.000
rs7096206 (Y/X promoter)
YY (GG)	10 (5.9)	7 (4.1)	1.000
YX (GC)	157 (92.4)	155 (91.2)	0.71 (0.26-1.91)	0.49
XX (CC)	3 (1.7)	8 (4.7)	0.26 (0.05-1.35)	0.11
Y (G)	177 (52.1)	169 (49.7)	1.000
X (C)	163 (47.9)	171 (50.3)	0.91 (0.67-1.23)	0.54
Dominant model			0.69 (0.26-1.85)	0.454
Codominant model			0.55 (0.26-1.20)	0.127
Recessive model			0.36 (0.09-1.40)	0.119
rs7095891 (P/Q promoter)
PP (CC)	1 (0.6)	1 (0.6)
PQ (CT)	169 (99.4)	169 (99.4)
QQ (TT)	0 (0)	0 (0)
P (C)	171 (50.3)	171 (50.3)
Q (T)	169 (49.7)	169 (49.7)
rs5030737 (52 codon)
AA (GG)	10 (5.9)	16 (9.4)	1.000
AD (GA)	149 (87.6)	128 (75.3)	1.85 (0.82-4.25)	0.1394
DD (AA)	11 (6.5)	26 (15.3)	0.68 (0.23-1.91)	0.47
A (G)	169 (49.7)	160 (47.1)	1.000
D (A)	171 (50.3)	180 (52.9)	0.89 (0.66-1.21)	0.48
Dominant model			1.66 (0.73-3.78)	0.22
Codominant model			0.75 (0.45-1.24)	0.26
Recessive model			0.38 (0.18-0.80)	0.008
rs1800450 (54 codon)
AA (GG)	70 (41.2)	45 (26.5)	1.000
AB (GA)	86 (50.6)	110 (64.7)	0.50 (0.31-0.80)	0.0040
BB (AA)	14 (8.2)	15 (8.8)	0.60 (0.26-1.36)	0.2215
A (G)	226 (66.5)	200 (58.8)	1.00
B (A)	114 (33.5)	140 (41.2)	0.72 (0.52-0.98)	0.039
Dominant model			0.51 (0.33-0.81)	0.0040
Codominant model			0.65 (0.45-0.93)	0.018
Recessive model			0.93 (0.43-1.99)	0.846
rs1800451 (57 codon)
AA (GG)	5 (2.9)	6 (3.5)	1.000
AC (GA)	161 (94.7)	159 (93.6)	1.21 (0.36-4.06)	0.75
CC (AA)	4 (2.4)	5 (2.9)	0.96 (0.16-5.64)	0.96
A (G)	171 (50.3)	171 (50.3)	1.000
C (A)	169 (49.7)	169 (49.7)	1.000 (0.7403-1.3507)	1.000
Dominant model			1.21 (0.36-4.03)	0.759
Codominant model			1.000 (0.42-2.40)	1.000
Recessive model			0.80 (0.21-3.01)	0.735

Values in bold signify statistical significance.

CI, confidence interval; OR, odds ratio; SNP, single nucleotide polymorphism.

LD analysis showed strong LD of rs7096206 with rs5030737, rs7095891, and rs1800451 (D′ = 0.75, 0.93, and 0.87 respectively). Furthermore, rs5030737 and rs1800451 SNPs were found to be in LD with rs7095891 (D′ = 0.86 and 0.93 respectively). Table 2 summarizes the complete LD analysis of six studied SNPs in MBL2. This study revealed 10 haplotypes with frequency >0.01 in both cases and controls (Table 3). Significant differences in haplotypic frequencies were observed between cases and controls. The frequency of haplotype HXQD was highest in both cases and controls, so it was taken as reference for the comparison of different haplotypes. Overall haplotypic distribution showed no significant difference (p > 0.05) between cases and controls, except one haplotype. Independent analysis of each haplotype distribution indicated significant differences (p < 0.05) in frequencies of LYPC haplotype between cases and controls. The frequencies of LYPC were found to be higher in cases (19%) than controls (9%). Also, the high frequency of LXQD had been observed in cases (8%) than controls (4%), although the differences were not significant (p > 0.05). A similar distribution has been observed for the remaining haplotypes between cases and controls.

Table 2.

Linkage Disequilibrium Analysis of Studied SNPs in MBL2 Gene

D′ value	rs11003125 (H/L)	rs7096206 (X/Y)	rs7095891 (P/Q)	rs5030737(52 codon)	rs1800450(54 codon)	rs1800451(57 codon)
rs11003125 (H/L)	1	0.11	0.14	0.09	0.06	0.27
rs7096206 (X/Y)	1.00	1.00	0.93	0.75	0.24	0.87
rs7095891 (P/Q)	1.00	1.00	1.00	0.86	0.28	0.93
rs5030737 (52 codon)	1.00	1.00	1.00	1.00	0.05	0.76
rs1800450 (54 codon)	1.00	1.00	1.00	1.00	1.00	0.26

Table 3.

Haplotypic Distribution of Six MBL SNPs in Cases and Controls

Haplotypes		Count in cases	Count in controls	OR	95% CI	p-Value
HXQD	GCTAGG	46	50	1.000	—	—
LYPO	CGCAAA	38	38	0.9200	0.503-1.679	0.786
LYPC	CGCGGA	33	16	0.4461	0.217-0.915	0.027
LXQD	CCTAGG	15	8	0.4907	0.190-1.264	0.141
HXQO	GCTAAA	7	9	1.1829	0.407-3.434	0.758
LYPO	CGCAAA	5	8	1.4720	0.449-4.823	0.523
LXQO	CCTAAA	3	3	0.9200	0.176-4.788	0.921
HYQD	GGTAGG	4	2	0.4600	0.080-2.631	0.383
HXQA	GCTGGG	3	4	1.2267	0.266-5.777	0.796
HYPC	GGCGGA	3	6	1.8400	0.434-7.786	0.407

Values in bold signify statistical significance.

Discussion

MBL, a pattern recognition molecule, plays an important role in activation of lectin pathway of complement system. A growing body of evidences documented the role of MBL in pathogenesis of various autoimmune diseases (Behairy et al., 2022; Schafranski et al., 2004; Vignesh et al., 2017). MBL2 polymorphisms with susceptibility toward RA have been studied in different populations (Martiny et al., 2012; Goeldner et al., 2014a; Kristiansen et al., 2014; Epp Boschmann et al., 2016; Xu et al., 2021). However, well-evident reports of variations among different individuals, moreover even in genetically identical individuals, have been documented in literature, and these variations can lead to altered protein levels (Dommett et al., 2006). So the objective of this study was to evaluate the structural as well as promoter gene polymorphisms in RA population of Indian origin.

In this study, three promoter polymorphisms L/H (rs11003125), Y/X (rs7096206), and P/Q (rs7095891) were studied. These variations are important in way that a line of evidences showed the association of these variations with altered serum MBL levels among different individuals (Madsen et al., 1995, 1998). This study revealed a statistically significant association of only L/H promoter gene polymorphism with RA. Results indicated significant differences in genotypic and allelic distribution between cases and controls for rs11003125. HH genotype emerged out as a significant protective genotype against RA, as indicated by its lower prevalence in cases. This finding is in consonance with various independent studies along with a meta-analysis study (Kristiansen et al., 2014; Song et al., 2014; Xu et al., 2021). However, various others showed contrasting results (Horiuchi et al., 2000; Gupta et al., 2005; Garred et al., 2006). On the contrary, for Y/X promoter and P/Q promoter gene polymorphisms, genetic analysis showed no significant association with disease. Literature documented various studies in support of this finding, whereas other ethnic populations reported conflicting results (van de Geijn et al., 2008; Goeldner et al., 2014a; Kristiansen et al., 2014; Song et al., 2014; Epp Boschmann et al., 2016). Divergent results shown by various populations clearly indicated the influence of ethnicity, lifestyle, and varied regions on these genetic determinants.

Besides promoter polymorphisms, three structural variants of exon 1 at codons 52 (rs5030737), 54 (rs1800450), and 57 (rs1800451) have been genetically determined. These structural variants are functionally relevant, in sense that these can affect the MBL protein stability, which, in turn, can affect its ability to bind its ligands and hence altered activation of complement by lectin-mediated pathway. The results of this study indicated no significant association of genotypic distribution between cases and controls for any of the three variants. However, significantly low prevalence of B allele in case rs1800450 confers risk toward susceptibility of the disease. Divergent reports, including in support and against this finding, have been documented (Stanworth et al., 1998; Ip et al., 2000; Tsutsumi et al., 2001; Gupta et al., 2005; Jacobsen et al., 2009; Martiny et al., 2012; Goeldner et al., 2014b; Zhang et al., 2015). However, heterozygosity for all three structural variants was found to be more predominant in both case and control groups. In line with this finding, various studies in different populations reported similar results. Moreover, heterozygosity at 54 position can be explained by the fact that specific variation in this position results in amino acid substitution from Asp to Gly. This substitution results in the formation of lower order MBL oligomers as a result of disruption of oligomerization. These functionally inactive MBL oligomers are not able to activate lectin-mediated complement pathway and hence antagonize the inflammatory effect.

These evidences in corroboration with the findings may hypothesize toward selective advantage of heterozygotes over homozygotes toward environmental pressure. This hypothesis was well evidenced by study of Søborg et al. (2003), which showed the protected effect of heterozygosity in exon1 variants in tuberculosis infection. Therefore, maintenance of the high heterozygosity in different populations is indicative of a balanced polymorphism system in the MBL2 (Bernig et al., 2004). Haplotypic analysis showed significantly high prevalence of LYPC haplotype in cases compared to controls.

Conclusion

This study reported significant differences in genotypic and allelic distribution of MBL2 variants between cases and controls. The findings emphasize to replicate this study in a larger data set, also including more variants of MBL2. Moreover, considering India as a land of high genetic diversity, suggesting high genetic heterogeneity, these variants are required to be screened in different ethnic cohorts. The outcomes of such studies may assist in genetic discovery of blood-based as well as molecular biomarkers and the development of personalized medicine in polygenic disease conditions. Furthermore, functional studies of MBL along with genetic association studies could give a better insight to validate the role of MBL in pathophysiology of RA.

Footnotes

Acknowledgments

The authors express their sincere gratitude to the study participants for providing their blood samples. They express gratitude to the staff of Arthritis Clinic, Amritsar.

Compliance with Ethical Standards

The study was commenced after getting approval from Institutional Ethics Committee of Guru Nanak Dev University, Amritsar (Punjab), according to Indian Council of Medical Research guidelines (2006), adapted from Declaration of Helsinki (2004) (Behera et al., 2019).

Authors’ Contributions

T.K. reviewed the literature and was involved in designing, as well as performing experiments, analysis, and interpretation of data obtained. T.K. and S.S.K. drafted the article. S.A. was instrumental in sample collection. M.K. and J.S. contributed to the experimental design, data analysis, article editing, and supervision. All authors read and approved the final article.

Author Disclosure Statement

The authors declare no conflicts of interest.

Funding Information

This work was supported by the institutional financial assistance.

Supplementary Material

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