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. 2019 Nov;71(11):1858-1868.
doi: 10.1002/art.40935. Epub 2019 Sep 27.

A Link Between Plasma Microbial Translocation, Microbiome, and Autoantibody Development in First-Degree Relatives of Systemic Lupus Erythematosus Patients

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A Link Between Plasma Microbial Translocation, Microbiome, and Autoantibody Development in First-Degree Relatives of Systemic Lupus Erythematosus Patients

Elizabeth Ogunrinde et al. Arthritis Rheumatol. 2019 Nov.

Abstract

Objective: Systemic lupus erythematosus (SLE) is characterized by the production of antibodies against self antigens. However, the events underlying autoantibody formation in SLE remain unclear. This study was undertaken to investigate the role of plasma autoantibody levels, microbial translocation, and the microbiome in SLE.

Methods: Plasma samples from 2 cohorts, one with 18 unrelated healthy controls and 18 first-degree relatives and the other with 19 healthy controls and 21 SLE patients, were assessed for autoantibody levels by autoantigen microarray analysis, measurement of lipopolysaccharide (LPS) levels by Limulus amebocyte assay, and determination of microbiome composition by microbial 16S ribosomal DNA sequencing.

Results: First-degree relatives and SLE patients exhibited increased plasma autoantibody levels compared to their control groups. Parents and children of lupus patients exhibited elevated plasma LPS levels compared to controls (P = 0.02). Plasma LPS levels positively correlated with plasma anti-double-stranded DNA IgG levels in first-degree relatives (r = 0.51, P = 0.03), but not in SLE patients. Circulating microbiome analysis revealed that first-degree relatives had significantly reduced microbiome diversity compared to their controls (observed species, P = 0.004; Chao1 index, P = 0.005), but this reduction was not observed in SLE patients. The majority of bacteria that were differentially abundant between unrelated healthy controls and first-degree relatives were in the Firmicutes phylum, while differences in bacteria from several phyla were identified between healthy controls and SLE patients. Bacteria in the Paenibacillus genus were the only overlapping differentially abundant bacteria in both cohorts, and were reduced in first-degree relatives (adjusted P [Padj ] = 2.13 × 10-12 ) and SLE patients (Padj = 0.008) but elevated in controls.

Conclusions: These results indicate a possible role of plasma microbial translocation and microbiome composition in influencing autoantibody development in SLE.

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Conflict of interest statement

Conflicts of interest: The authors have no conflicts of interest to disclose.

Figures

Figure 1
Figure 1. Plasma levels of autoantibodies in UHCs and FDRs and HCs and SLE patients.
(A, B) Plasma samples from UHCs and FDRs and HCs and SLE patients were tested for reactivities to a variety of autoantigens in an autoantigen array. A heat map with clustering of IgG autoantibodies was generated from the autoantigen array. Intensities higher than the mean were colored red (A) or yellow (B), those below the mean were colored green (A) or blue (B), and cells with signals close to the mean were colored black (A, B). Gray was used to denote missing data. (C-J) The median mean fluorescence intensities (MFIs) of antibodies against dsDNA (C, G), nucleosome antigen (D, H), ssDNA (E, I), and chromatin antigen (F, J) were shown in the two groups. The non-parametric Mann-Whitney U-test was used for comparison and horizontal lines represent medians.
Figure 2
Figure 2. Plasma LPS level is associated with anti-dsDNA autoantibody production.
(A, B) Plasma LPS was tested by the limulus amebocyte assay in a study including 18 UHCs, 11 sibling FDRs, and 7 parent or child FDRs (A), and another study including 19 HCs and 21 SLE patients (B). (C, D) Plasma LPS level correlation with plasma level of anti-dsDNA autoantibody in UHCs and FDRs (C) and in HCs and SLE patients (D). Non-parametric Mann-Whitney U tests and Spearman’s correlation tests were used for comparison and correlation respectively and horizontal lines represent medians.
Figure 3
Figure 3. Circulating microbiome relative abundance in UHCs and FDRs.
(A-E) The top five bacteria at the taxonomic levels of phylum (A), class (B), order (C), family (D) and genus (E) based on relative abundance in both UHCs and FDRs. Non-parametric Mann-Whitney U test was used in QIIME 1 to compare abundances and p-values were adjusted for multiple comparisons by the false discovery rate (p.fdr).
Figure 4
Figure 4. Circulating microbiome relative abundance in HCs and SLE patients.
(A-E) The top five bacteria at the taxonomic levels of phylum (A), class (B), order (C), family (D) and genus (E) based on relative abundance in both HCs and SLE patients. Non-parametric Mann-Whitney U test was used in QIIME 1 to compare abundances and p-values were adjusted for multiple comparisons by the false discovery rate (p.fdr).
Figure 5
Figure 5. Alpha and beta diversity analyses of the circulating microbiome in FDRs and SLE patients compared to their controls.
(A, B) Observed OTUs and the Chao1 species-richness metric were evaluated using the phyloseq package in R to assess alpha diversity. Statistical significance was determined using the Wilcoxon rank sum test in R. (C, D) Principal coordinate analysis (PCoA) was conducted based on the unweighted UniFrac distance to determine beta diversity using the phyloseq and ade4 packages in R. Statistical significance testing of beta diversity was done through permutational MANOVA (‘adonis’ function, vegan package, R).

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