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REVIEW article

Front. Immunol., 06 July 2021
Sec. Inflammation

Effects of Lipopolysaccharide-Binding Protein (LBP) Single Nucleotide Polymorphism (SNP) in Infections, Inflammatory Diseases, Metabolic Disorders and Cancers

  • 1Department of Pathophysiology, School of Basic Medical Sciences, Anhui Medical University, Hefei, China
  • 2Experimental Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
  • 3Experimental Transplantation Surgery, Department of General, Visceral and Vascular Surgery, Friedrich-Schiller-University Jena, Jena, Germany

Inflammation, which is induced by the immune response, is recognized as the driving factor in many diseases, including infections and inflammatory diseases, metabolic disorders and cancers. Genetic variations in pivotal genes associated with the immune response, particularly single nucleotide polymorphisms (SNPs), may account for predisposition and clinical outcome of diseases. Lipopolysaccharide (LPS)-binding protein (LBP) functions as an enhancer of the host response to LPS, the main component of the outer membrane of gram-native bacteria. Given the crucial role of LBP in inflammation, we will review the impact of SNPs in the LBP gene on infections and inflammatory diseases, metabolic disorders and cancers.

Highlights

● Inflammation, which is induced by the immune response, is recognized as the driving factor in many diseases, including infections and inflammatory diseases, metabolic disorders and cancers.

● Genetic variations in pivotal genes associated with the immune response, particularly single nucleotide polymorphisms (SNPs), account for predisposition and clinical outcome of inflammation-related diseases.

● Lipopolysaccharide (LPS)-binding protein (LBP) plays a crucial role in the innate immune response for the development of inflammatory and infectious-related diseases.

● This review aims to summarize the investigation and association of SNPs in the LBP gene with infections and inflammatory diseases, metabolic disorders and cancers.

Introduction

In many diseases, including infections, metabolic disorders and cancers, inflammation is recognized as the driving factor (13). Functionally, inflammation is widely defined as a protective response against invading pathogens and endogenous stress signals (4), regulated by various pathways (such as TLR4/NF-kB pathway and IL-6/JAK/STAT3) and a multitude of genes (57). Interactions of cells from the innate and the adaptive immune system, together with the corresponding inflammatory mediators, contribute to various aspects of inflammation underlying many organ diseases (3, 8). Although the spectrum of inflammatory diseases is rather wide (ranging from systemic diseases such as sepsis, Type 1 diabetes and organ disease such as hepatitis) the cellular and molecular pathways involved in the inflammatory response remain similar (5).

Lipopolysaccharide, also called endotoxin, is a major component of the outer membrane of gram-negative (GN) bacteria (9). LPS causes endotoxemia when released into blood (10). Release of high levels of LPS into the systemic circulation (or release of lower levels in case of LPS-sensitization), induces a systemic inflammatory response syndrome, also called SIRS. The development of SIRS aggravates any other concomitant inflammatory condition, e.g. contributes to the development of septic shock in cases of sepsis (10).

The inflammatory response to LPS is mediated via LPS binding protein LBP. Lipopolysaccharide (LPS)-binding protein (LBP) is mainly produced in hepatocytes, functions as a secretory class I acute-phase protein (1113) and plays a pivotal role in the innate immune response. Initially, LPS binds to LBP forming the LPS-LBP complex, which subsequently binds to CD14 and to the MD-4/MD-2 complex (14), ultimately results in the activation of signal transduction pathways and the production of cytokines and other pro-inflammatory mediators (15). Circulating LBP has a concentration-dependent immunologic function. Subnormal levels of LBP protein enhance phagocytosis and clearance of LPS from blood (16). In contrast, at high concentrations, LBP protein attenuates the release of pro-inflammatory cytokines (17). Additionally, LBP transfers LPS to very-low-density lipoproteins, low-density lipoproteins, high-density lipoproteins or chylomicrons, contributing to immune reaction against the infection (1822). LBP also contributes to the immune response to gram-positive bacteria and fungal infection (2325).

The physiological concentration of LBP in the serum of healthy human individuals is 5 to 10μg/mL (26). In contrast, during sepsis, up to seven-fold higher levels were observed within 24h (27). Increased LBP levels were also induced by a diet rich in fat and carbohydrates (28). Therefore, individuals suffering from obesity, diabetes, and related metabolic disorders also present with highly elevated LBP-levels (2931), which was probably attributed to chronic low-grade inflammation induced by alterations of the intestinal flora together with an increased gut permeability to LPS (32, 33).

LBP is encoded by the LBP gene (34). The human LBP gene locates on chromosome 20 and shares an intron-exon pattern with other lipid-binding and transferring proteins on the same chromosome (34, 35). Genetic variations in LBP may contribute to susceptibility and clinical course of infectious diseases (36). On the basis of the crucial function of LPS in the innate immune response, many studies were performed to the genetic variation in the LBP gene in respect to the development of inflammatory diseases.

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation. The term refers to sequence alternatives (alleles) of a single DNA base with a frequency of more than 1% (37). SNPs influence the risk for the development and the outcome of a disease via various mechanisms but they are not considered to cause diseases (38). In coding regions, nonsynonymous SNPs could generate an amino-acid exchange and in turn affect the structure and biological function of the encoded protein, whereas synonymous SNPs do not lead to amino-acid exchange (39). Gu et al. reported that both synonymous and nonsynonymous SNP led to abnormal gene expression via altering the structure of local messenger RNA (38). In addition, mutations in the promoter region usually result in reduced mRNA levels (37). John C has demonstrated in his previous study that SNPs occurred in less conserved regions more frequently and the lowest occurrence rate was at the splice sites (40).

Evidence accumulated that genetic variations in pivotal genes associated with the immune response, particularly SNPs, may account for predisposition and clinical outcome of many diseases and potentially allow to predict prognosis and therapeutic effects (36, 41, 42).

In this review, we aim to present the current knowledge regarding the occurrence of SNP in the LBP gene and the impact of SNP in the LBP gene on the development and the course of selected infections, inflammatory diseases, metabolic disorders and cancers.

Correlation Between SNP in LBP Gene and Infections, Inflammatory Diseases, Metabolic Disorders and Cancers

LBP-SNPs in Infections

Evidence is accumulating that specific SNPs in the LBP gene are associated with a different course of many infections, including sepsis, infectious complications, and some organs infectious diseases (see in Table 1).

TABLE 1
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Table 1 Impact of SNPs in LBP gene on infectious diseases, sepsis and septic complications.

Hubacek et al. reported that a gender-related polymorphism, a nonsynonymous SNP at the 292nd nucleotide of the LBP gene, was associated with an increased predisposition to sepsis in males (p<0.02) but not in female patients (43). Compared with controls, a significantly higher proportion of male individuals in the cohort of patients with sepsis carried at least one Gly98 allele (43). Interestingly, Barber and colleague determined this SNP (T292G) was not exist by pyrosequencing, which occurred due to adjacent nucleotide substitution (T→C) at 291 position. Therefore, the association was thought to be false-positive (52). In addition, Barber et al. reported T291C lacked association with septic complications and survival after trauma (52).

Rs2232582 (T291C) is a synonymous variant located in the coding region, which conferred a nucleotide substitution from T to C. Both variants encoded the amino acid at residue 97 (52). Chien and colleagues used a SNP haplotype tagging approach tagSNP in a retrospectively case-control population with 97 patients and 204 controls (21). They reported the C allele of rs2232582 (tagSNP 6878) was associated with GN bacteremia after hematopoietic cell transplantation (HCT) in multivariate analysis (p=0.001) (21). And in whites, the C allele was identified to be associated with a 2-fold higher risk for GN bacteremia (p=0.002) (21). Additionally, Vollmer et al. studied five LBP-SNPs in 78 infective endocarditis (IE) patients and 156 healthy blood donors, among which T allele of rs2232582 (291C>T) had a weak association with an increased susceptibility to infective endocarditis (p=0.019) (44). However, the significance didn’t remain after Bonferroni correction (291C>T pc=0.095) (44).

Rs2232596 is a synonymous variant and confers A→G nucleotide substitution at the 613rd position. Chien et al. reported rs2232596 (SNP 17002) was associated with GN bacteria in multivariate analysis in HCT (p=0.027) (21). Vollmer et al. determined the Gallele of rs2232596 (613A>G) was associated with an increased susceptibility to infective endocarditis(p=0.018) (44). Similar with rs2232582 in this research,no significance remained after Bonferroni correction (Pc=0.090) (44).

Rs2232571, which confers a C→T nucleotide substitution at -778 position in a CAAT box, locates in the promotor region of LBP gene (21) and regulates promoter efficiency (11). Chien et al. described that the SNP is in strong linkage disequilibrium with rs2232582 aforementioned (21). In a prospective cohort of 234 cases, patients of HCT carrying rs2232571 (SNP1683) C allele significantly displayed a 3-fold increase in the risk of death prior to discharge (p=0.001) (21). In the development of GN bacteremia, mortality risk of patients significantly increased five-fold when they carried C allele of rs2232571 (p=0.013) (21). Moreover, rs2232571 C allele carriers exhibited higher median basal serum LBP levels (CC, 17.39μg/mL; TC 10.4μg/mL; TT 8.07μg/mL, p=0.004) (21). In addition, Guinan et al. confirmed previous linkage between rs2232571and plasm LBP levels in HCT (46). Flores and colleagues explored nine polymorphisms of LBP gene in the 5’-flanking region which is the transcription start site from position -1978 to -763. They observed no association between these SNPs along with the incidence of severe sepsis (45). Notably, a common 4-SNP haplotype consisting of allelic combination rs1780616-C/rs5741812-A/rs2232571-T/rs1780617-A was significantly associated with the predisposition to severe sepsis (p=0.016) (45). In comparison with non-carriers, homozygous carriers showed an increased risk of sepsis (p=0.016) and higher mean serum LBP concentrations at inclusion (130.1μg/mL for homozygous carriers and 101.6μg/mL for non-carriers, respectively) and at the seventh day (98.9μg/mL for homozygous carriers and 58.7μg/mL for non-carriers, respectively. p=0.046) (45).

Rs2232613 is a nonsynonymous mutation, which leads to proline changed to leucine at residue 333 (47). Eckert and colleagues described the structure of murine LBP and revealed the presence of rs2232613 affected a “phenylalanine core” in the C-terminal of the LBP and resulted in a dysfunction protein (47). The mutant protein reduced bacterial ligands binding capacity and cytokines-induction function in vitro (47). It was consistent with the results in vivo experiments that the variant T allele carriers displayed lower cytokine levels during experimental LPS stimulation. For example, at 1hr after injection of LPS, the production of TNF-α of heterozygous mutation carriers is significantly lower (p=0.013) (47). Carriers produced lower cytokine concentrations when suffering from ventilator-associated pneumonia (6.2 ± 1.76pg/mL for carriers and 18.4 ± 4.9 pg/mL for WT individuals, respectively. P=0.014) (47). A retrospective clinical analysis of 424 ICU surgical patients indicated that T allele carriers exhibited higher risk for mortality (CT/TT vs. CC, 11.5% vs. 5.8%, p=0.1) (47). Statistically significant difference was also seen in mortality in patients with infectious complications (CT/TT vs. CC, 21.2% vs. 8.9%, p=0.02 for hospital-acquired pneumonia; 33.3% vs. 8.2%,p=0.03 for hospital-acquired pneumonia caused by Gram-negative bacteria) (47). Studies demonstrated that LBP deficiency protected mice from LPS stimulation but exhibited higher lethality in bacterial stimulation, which might account for that carriers of rs2232613 exhibited higher risk of severe clinical infection (47). Guinan et al. also confirmed T allele carriers of rs2232613 displayed lower plasm LBP concentrations but higher efficiency in endotoxin extraction and transfer to MD-2 in HCT patients (46).

Rs2232618, is a functional variant conferring an amino acid substitution from phenylalanine to leucine at residue 436 caused by a T→C nucleotide substitution in the C-terminal domain of the LBP protein (48). According to the research conducted by Hubacek and colleagues, no positive association between rs2232618 with the occurrence of sepsis was described (43). However, Zeng et al. assessed the entire LBP gene in major trauma cohorts in Chinese population via using haplotype tagging SNPs (htSNPs) and detected that among the nine htSNPs studied in LBP, only rs2232618 associated with traumatic sepsis (48). According to 557 trauma patients in Chongqing cohort, C allele carriers showed a higher of sepsis and MODS (TT vs. TC+CC, p<0.0001 for sepsis morbidity rate and p=0.011 for MOD scores, respectively), when compared with T allele carriers (48). TNFα production by peripheral leukocytes of C allele carriers in vitro revealed a significantly increased response to LPS (TT vs. TC, p=0.01). The clinical relevance of genotypic distribution of rs2232618 was further confirmed in Zhejiang cohort with 230 patients (TT vs. TC, p=0.012 for sepsis morbidity rate and p=0.046 for MOD scores, respectively) (48). In vitro experiments, the binding capacity with LPS (p<0.001) and TNFα production (p<0.001) were significantly enhanced with the presence of the variant Leu436 LBP protein. Furthermore, Leu436 LBP protein has stronger binding interactions with CD14 (p=0.043) (48). Lu and their groups confirmed the correlation between genotypic distributions and traumatic sepsis in an enlarged co-located population sample size with 1296 patients in Chongqing (TT vs. TC+CC, p=0.002 for sepsis morbidity rate and p=1.8E-6 for MOD scores, respectively) and 445 patients in Zhejiang (TT vs. TC+CC, p=0.002 for sepsis morbidity rate and p=0.005 for MOD scores, respectively) (50). Combined analysis of two cohorts also showed relevance between rs2232618 and traumatic sepsis (TT vs. TC+CC, p=4.5×10-4 for sepsis morbidity rate and p=1.4E-9 for MOD scores, respectively) (50). In addition, Jabandziev et al. reported rs2232618 in combination with additional four SNPs (BPI rs574350, TLR rs4986790, HSP70 rs2227956, IL-6 rs1800795) could be regarded as a predictor of clinical outcome of sepsis in children (49). The authors defined wild-type homozygotes as A, heterozygotes and mutant homozygotes as B. Among analyses of BPI, TLR and LBP, LBP A + BPI A + TLR A was associated with a high risk of sepsis (p=0.005), LBP B + BPI A + TLR A was a high-risk combination for sepsis with severe condition (p=0.034) (49). On the contrary, LBP A + BPI B + TLR A was a low-risk combination for both sepsis and severe condition (p<0.001 and p=0.003, respectively) (49). In terms of combinations of LBP, IL-6 and TLR, LBP A + IL-6 B +TLR A is a low-risk combination of severe sepsis (p=0.027) (49). Combinations of LBP A + IL-6 A +TLR B and LBP B + IL-6 A +TLR A were regarded to be a high risk for sepsis (p<0.006 and p=0.012, respectively), but the proportion of patients was low (4.2% and 4.8%, respectively) (49). Analysis of five genes showed a combination of wild-type homozygotes was associated with high risk of sepsis. Moreover, BPI A + LBP A + TLR A +HSP70 A +IL-6 B was also a high-risk combination for sepsis (p=0.016) (49). On the contrary, BPI B + LBP A + TLR A +HSP70 A +IL-6 B and BPI B + LBP A + TLR B +HSP70 A +IL-6 B were low-risk combinations for both sepsis (p=0.006 and p=0.041, respectively) and sepsis with severe condition (p=0.001 and p=0.026) (49). In addition, Verstraelen et al. observed rs2232618 was marginally significantly associated with carriage of Atopobium vaginae in bacterial vaginosis during early pregnancy (p=0.056) (51).

LBP-SNPs in Atopy and Asthma

Atopy is viewed as a predisposition to the immune response to diverse antigens/allergens, inducing CD4+ Th2 differentiation and overproduction of immunoglobulin E (IgE) (53). Asthma is a manifestation of atopy, which is a chronic inflammatory airway disease caused by combined influence of genetic and environmental factors (54). Asymptomatic atopic individuals, healthy individuals or atopic individuals without current manifestation of disease exhibited increased serum LBP levels after inhaling LPS. These findings suggest that atopy and asthma related phenotype might be associated with LBP genetic variants (55). Two studies related to asthma reported six SNPs of LBP. In the coding region, rs2232596 is a synonymous mutation and rs2232580 is a missense mutation that confers an amino acid substitution from proline to leucine at residue 9. Moreover, rs6025083 and rs12624843 are located in the intron, rs5741812 is located in the 5’-UTR and rs745144 is located in the 3’-UTR. Reijmerink and colleagues and colleagues demonstrated gene-environment interactions of atopy in children (56). Rs2232596, day-care and one sibling were selected as the best three-factor model (p=0.007) (56). Day-care protected children from developing high total IgE at 1-2 years old who were heterozygotes for rs2232596, but not in children with more than one sibling (56). rs745144, in combination with sibling and CD14 (rs2915863) were selected as the there-factor predictors for total IgE at 6-8 years old (56). Besides, rs6025083, along with TLR1 (rs5743594) and TLR5 (rs851186) were selected as three-factor predictors of gene-gene interaction of specific IgE to indoor allergens 6–8 years old (56). Daley et al. reported rs2232580 and rs5741812 associated with atopy in children with a family history of allergies (p=0.0141 and p=0.423, respectively) (57). In the healthy study cohort, rs12624843 were associated with airway hyperresponsiveness (AHR) (p=0.0443) (57). Additionally, SNP-virus interaction analyses showed rs5741812 was significantly associated with AHR and picornavirus (p=0.048) (57) (see in Table 2).

TABLE 2
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Table 2 Effect of SNP in LBP-gene atopy, metabolic diseases and cancer.

LBP-SNPs in Metabolic Disorders

Increasing evidence suggested gut microbiota and low-grade inflammation are associated with chronic diseases, such as metabolic disorders (66), cardiovascular disease (67) and hypertension (68). Given the involvement of LBP in inflammation (67), some SNPs have been investigated in related diseases (see in Table 2).

Rs1739654 is a synonymous mutation located in the coding region, rs2232578 is located in the 5’-UTR, rs1780627 and rs2232592 are located in intron region. Takeuchi et al. identified this four SNPs of LBP gene on chromosome 20q significantly correlated with susceptibility to type 2 diabetes p=0.001 for rs1739654, p=0.003 for rs1780627, p=0.011 for rs2232592 and p=0.0004 for rs2232578, respectively (58). Further stratified analysis for rs2232592 indicated diabetic patients with the history of obesity and/or earlier age of onset have prominent genetic risk (58).

As previously mentioned, rs2232582 is a synonymous variant and confers T→C nucleotide substitution. Vilade's et al. reported rs2232582 was associated with HIV-1/HAART-associated lipodystrophy syndrome (HALS). Carriage of T allele was significantly associated the higher incidence of HALS whereas carriage of C allele seemed to protect individuals against HALS (p=0.01) (59). Besides, Zhan et al. reported 291T>C (rs2232582) was associated the Carotid intima-media thickness (CIMT) (p<0.05), but not cerebral infarction in Chinese population (61). CIMT is considered to be a risk of cardiovascular and cerebrovascular disease and a surrogate marker to assess AS (69), patients carrying TC genotype exhibited higher mean CIMT compared with TT genotype (61).

As the leading cause of myocardial infarction and stroke (70), atherosclerosis (AS) is a complex disease and involves a series of pathophysiological processes such as inflammation and lipid metabolism (71). Hubacek et al. demonstrated that the frequency of LBP 1306T>C (rs2232618) C allele (Leu436) homozygotes is about threefold in patients with myocardial infarction than in controls (60). But the frequency of this genotype in controls is very low and did not reach statistical significance (2.3% in patients and 0.7% in controls, respectively) (60). In addition, Zhan et al. reported 1306T>C (rs2232618), similar to rs2232582 in the study, was associated with CIMT (p<0.05) (61). Individuals with TC genotype exhibited higher mean CIMT compared with TT genotype (61).

LBP-SNPs in Cancer

Inflammation is closely related to the pathogenesis of cancer (72, 73) and genetic variations of inflammatory regulators were demonstrated to associate with the increased risk or adverse consequence of several tumors (7479).

Intestinal microbiota dysbiosis leads to more release of LPS and thereby to a higher stimulation of LBP and subsequent production of inflammatory cytokines (75). Chronic low-grade inflammation contributes to carcinogenesis and the development of colorectal carcinoma (CRC) (80). Chen et al. demonstrated that mutant G allele of rs2232596 was significantly associated with the CRC risk in patients compared with healthy controls (GA vs. AA, p=0.003; GG vs. AA, p=0.016; GA+GG vs. AA, p=0.001, respectively). When combined with CD14 rs4914, the risk of CRC increased 3.4 times (p=0.000) (62). Additionally, both smokers carrying GA genotype and drinkers carrying GA or GG genotype had an increased risk for CRC (p=0.005 for smokers and p=0.001 for drinkers, respectively), which revealed the interaction between genes with tobacco and alcohol (62). According to another study conducted by Chang et al, rs1780617 G allele was significantly associated with the risk of CRC and adenoma, a precursor to CRC (p=0.046) (63).

Helicobacter pylori (HP) infection accounts for the progression of gastric cancer (GC) (76). Castaño-Rodríguez et al. demonstrated that rs2232578, which is located in 5’-UTR, induced an increased risk for GC in combination with HP infection in Chinese population (p=0.0292 for AA and p=0.017 for G carriers) (64).

LEE et al. conducted a Genome-wide pathway analysis and identified six SNPs, five genes and nine pathways in glioma. Rs2232580 contributed to the risk of glioma via affecting the interaction of LBP to LPS and immune responses (0.002≤p ≤ 0.013) (65).

The overview of analysis of LBP SNPs which exhibit association in inflammation-related diseases is shown in Table 3 classified with SNP ID. In addition, SNPs that were investigated but did not show correlation are summarized in Table 4.

TABLE 3
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Table 3 Summary of Lipopolysaccharide Binding Protein (LBP) SNPs correlated with corresponding disease.

TABLE 4
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Table 4 Summary of Lipopolysaccharide Binding Protein (LBP) SNPs not associated with corresponding disease.

Results of Meta-analysis

Results of smeta -analysis of susceptibility associated with rs2232618, synonymous 292 and rs2232592 in diseases are performed in Figures 13, respectively.

FIGURE 1
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Figure 1 Forest plot in rs2232618. (A) Dominant model (TT+TC vs CC). (B) heterozygote model (TC vs CC). (C) homozygotes models (TT vs CC). (D) recessive models (TT vs TC + CC).

FIGURE 2
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Figure 2 Forest plot in synonymous 292. (A) Dominant model (TT+TG vs GG). (B) heterozygote model (TG vs GG). (C) homozygotes models (TT vs GG). (D) recessive models (TT vs TG +GG).

FIGURE 3
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Figure 3 Forest plot in rs2232582. (A) Dominant model (TT+TC vs CC). (B) heterozygote model (TC vs CC). (C) homozygotes models (TT vs CC). (D) recessive models (TT vs TC + CC).

Conclusion

Characterization of genetic predisposition underlying diseases is the prerequisite for identifying patients at risk and for developing specific therapeutic strategies. In this review we give evidence for the relationship between SNPs in the LBP gene and certain inflammatory diseases.

Our finding might help to identify individuals at risk for inflammatory complications by genotyping and thereby contribute to developing more widely applicable diagnostic strategies. Furthermore, our finding might represent one step towards designing therapeutic strategies based on genetic heterogeneity using e.g. KO technologies.

However, more clinical studies including much higher patient numbers are needed to reach statistical significance confirming the reported trends as well as for confirming the postulated relationships in independent patient cohorts.

In addition, identifying high-risk individuals based on genotype and adjusting therapeutic strategies timely in the clinic could improve the prognosis of patients.

However, our findings are limited in three aspects: reproducibility of results and size of patient cohorts. So far, only two of the reported association between LBP-polymorphism and disease association were replicated by an independent study. Thus, additional studies are needed to verify the association between a certain SNP and susceptibility for a given disease.

Some of the reported positive but also negative associations were obtained in small patient cohorts (see in Table 3 and Table 4), which calls for confirmatory studies investigating larger groups of patients. Doing so will lead to sound results which can be used for developing novel therapeutic approaches, e.g., using pharmacological KO strategies.

Author Contributions

Data collection: LM, ZS and HF. Manuscript preparation: LM, AL and HF. Critical revision: LM, UD, XY and HF. All authors contributed to the article and approved the submitted version.

Funding

This work was supported by National Science Foundation of China (No. 81971875) and the University Natural Science Foundation of Anhui Province (No. KJ2019A0220)

Conflict of Interest

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

Abbreviations

LBP, lipopolysaccharide binding protein; LPS, lipopolysaccharide; SNP, Single nucleotide polymorphism; GN, Gram-negative; HCT, hematopoietic cell transplantation; htSNPs, haplotype tagging SNPs; AHR, airway hyperresponsiveness; HALS, HIV-1/HAART-associated lipodystrophy syndrome; AS, atherosclerosis; CIMT, Carotid intima-media thickness; CRC, colorectal carcinoma; HP, Helicobacter pylori; GC, gastric cancer.

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Keywords: inflammation, single nucleotide polymorphisms, lipopolysaccharide-binding protein, infections, inflammatory diseases, metabolic disorders, cancers

Citation: Meng L, Song Z, Liu A, Dahmen U, Yang X and Fang H (2021) Effects of Lipopolysaccharide-Binding Protein (LBP) Single Nucleotide Polymorphism (SNP) in Infections, Inflammatory Diseases, Metabolic Disorders and Cancers. Front. Immunol. 12:681810. doi: 10.3389/fimmu.2021.681810

Received: 18 March 2021; Accepted: 08 June 2021;
Published: 06 July 2021.

Edited by:

Anna Di Nardo, University of California, San Diego, United States

Reviewed by:

Maurizio Zanetti, University of California, San Diego, United States
Changjiang Dong, University of East Anglia, United Kingdom

Copyright © 2021 Meng, Song, Liu, Dahmen, Yang and Fang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xiao Yang, yx19920716@yeah.net; Haoshu Fang, fanghaoshu@ahmu.edu.cn

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