ResultsGut dysbiosis is pronounced in patients with high disease activity

To study the gut microbial communities in sequential samples from disease-affected individuals, we examined 2–6 faecal samples from 16 individual patients, with 44 samples obtained over 24–291 weeks (online supplemental tables S1 and S2). For comparisons, we also evaluated 72 sequential samples from 22 healthy adult female control (CTL) volunteers. To assess the diversity within these bacterial communities, faecal DNA was used to generate 16S rRNA gene-amplicon libraries.

In these analyses, patients who fulfilled ACR criteria for renal involvement at any time8 were designated as LN (online supplemental tables S1A and S2A). Renal disease activity was designated inactive or active, based on urinary protein creatinine ratio (PCR)<0.5 or >0.5, respectively, as per the SLEDAI domain. The other patients were referred to as non-renal (online supplemental tables S1B and S2B). In continuity with our earlier microbiome studies,7 those with an overall SLEDAI score of >8 were designated as high disease activity, with others as low disease activity. All patients with multiple samples were included. Pilot studies demonstrated results for 16S rRNA libraries were highly reproducible based on principal coordinated analyses (online supplemental figure S1).

Reiterating our earlier results,7 high SLEDAI scores and active LN were both associated with decreased richness/diversity of communities compared with CTL subjects, reflected in several measures of α-diversity (online supplemental figures S2–S5). Medications did not correlate with differences in microbiome diversity (online supplemental table S4A and S4B).

Greater lupus disease activity is associated with greater community β-diversity

Based on principal coordinates analysis, communities from patients displayed significant differences overtime in β-diversity compared with CTL using Jensen-Shannon divergence dissimilarity metric (multivariant distance Welch’s Wd×test, p=0.001)9 (figure 1A). Furthermore, the communities associated with higher disease activity (eg, active LN in figure 1C, purple) was farther from the communities representing CTL individuals (figure 1C, red) than the distance between CTL and lupus with no LN (green) or inactive (blue). There were significantly greater differences for communities associated with high disease activity (p=0.001) (figure 1B), and patients with active LN (p=0.001) (figure 1C).

Figure 1

Dysbiosis and longitudinal instability in SLE microbiota communities compared with healthy individuals. (A) Principal coordinates analysis (PCoA) was used to estimate β-diversity between groups using the Jensen-Shannon divergence (JSD) dissimilarity metric. Commensal communities from SLE patients were heterogeneous, with most exhibiting significant distance variance from CTL (by multivariate distance Welch Wd×test, p=0.001). (B) Compared with CTL, variance in diversity was greatest within the SLEDAI high subgroup, and (C) the subset with active renal disease. (D) To compare the overall dynamics of shifts in faecal communities sampled overtime in different subjects, subject variances were computed based on JSD using the average multivariate dissimilarity estimation method reported in.9 Variances between these three groups were significantly different (Kruskal-Wallis ANOVA, p=0.03). Lupus patients with a history of nephritis were assigned to the lupus nephritis (LN) group based on ACR criteria, whereas the patients in the non-renal group were without a documented history or laboratory findings of LN. Lupus patients have more unstable gut microbiota than healthy individuals. Variance of gut microbiota was significantly different in the renal lupus group, compared with healthy subjects (two-sided Mann-Whitney U test, p=0.02). The non-renal lupus group was significantly different than the healthy subjects (p=0.03). Notably, the overall variance in the renal group was not different from the non-renal group (p=0.379, NS). ACR, American College of Rheumatology; ANOVA, analysis of variance; CTL, control subjects; SLE, systemic lupus erythematosus; SLEDAI, SLE Disease Activity Index.

Instability over time is a common feature of lupus gut microbiota communities

We next assessed the stability of gut microbiota over time by comparisons of community-wide multivariate analyses in the multiple libraries from each of the 16 lupus-affected individuals and of 9 healthy subjects with multiple samples, without assumptions based on time-intervals. Using a proven approach for estimating averages within group dissimilarity,9 for each of the CTL subjects we found limited differences in overall composition among the sampled communities. In contrast, there was significantly raised level of variance between communities at different time points within an individual patient (Kruskal-Wallis analysis of variance, p=0.03) (figure 1D), which was found in both non-renal (two tailed, p=0.03), and renal (LN) groups (p=0.02) (figure 1D). However, we found no overall correlations between community variance; with disease duration, the periods between sample collection, the maximal disease activity, the range of disease activity in different visits (online supplemental tables S1 and S2), or the medications taken by individual subjects (online supplemental table S4). Notably, the variance within the renal and non-renal groups were not significantly different (p=0.379, NS), indicating that impaired community composition resilience is common in SLE. There was no relationship between variance, a marker of microbiota instability, and the intervals between sampling (online supplemental figure S6). Taken together, these findings suggest the gut communities in lupus patients are inherently unstable overtime. We, therefore, next sought to investigate whether within these unstable community milieus there were specific bacterial species that underwent major dynamic shifts.

Dynamic blooms of individual bacterial species are common within lupus microbiota communities

In-depth analyses of the sequential microbiota libraries revealed that in several individual patients there were transient often pronounced blooms of amplicon sequence variants (ASV)-defined taxa within both Veillonella and Fusobacterium genera, which were not detected in any healthy subjects (online supplemental figures S7 and S8). Whereas a Veillonella genus bacterium can represent local gut outgrowths due to translocations from the oral cavity into the intestine, or even overt infections,10 the Fusobacterium genus are generally considered oral pathogens.11 Notably, there were neither temporal associations with Veillonella nor the Fusobacterium expansions with specific clinical features or organ involvement, nor with overall flares of lupus disease activity (online supplemental figures S7 and S8, online supplemental tables S1 and S2).

Figure 2

Dynamic changes in RG abundance documented at sequential time points in healthy and lupus-affected individuals. In 5/16 (31%) of the SLE patients evaluated overtime blooms were documented, and the abundance of RG fluctuated greatly overtime. In these cases, RG abundance at much higher levels were present in faecal samples obtained proximal to visits in which disease flares were documented. All but one of these RG bloom-associated patients had documented LN flares concurrent with a RG bloom. All together, RG relative abundance was evaluated for 16 SLE in 44 samples obtained at different time points, and for CTL subjects in 49 samples obtained at different time points, which ranged from 2 to 12 samples per donor. Clinical and demographic data are shown in online supplemental table S1). Dotted line depicts an arbitrary 1% threshold of 16S rRNA amplicons representing RG abundance that is highly above the mean 0.15% level in these healthy controls. Abundance levels above 1% were considered a bloom. Note that for patient S78 the greater range of RG abundance necessitated a different scale. SLEDAI >8 was here considered high disease activity. See online supplemental figure S6 for depiction of all healthy control subjects and the other 11 SLE patient that displayed a stable low abundance in RG representation. CTL, control; LN, lupus nephritis; RG, Ruminococcus (blautia) gnavus; SLE, systemic lupus erythematosus; SLEDAI, SLE Disease Activity Index.

Ruminococcus gnavus blooms are concordant with lupus disease flare episodes

To follow-up our earlier findings,7 we investigated the abundance of Ruminooccus (blautia) gnavus (RG). A study of 16 samples showed RG abundance as determined by 16S rRNA amplimer analysis and by shotgun cloning were highly correlated (online supplemental figure S9). Consistent with an earlier estimate from a large population-based survey,12 we found a mean 0.15% RG abundance in the CTL libraries (online supplemental table S3). There was an overall trend for an increase in abundance of RG in SLE libraries that did not attain significance (Wilcoxon, p=0.076) (online supplemental figure S5A), while in many SLE samples, RG was undetectable or low abundance (online supplemental table S1A and S1A). However, there were marked increases in RG abundance in patients with high SLEDAI scores of 8 or greater (Wilcoxon, p=0.01) (online supplemental figure S5B), and RG abundance was increased in those with active renal disease (Wilcoxon, p=0.02)(online supplemental figures S5C and S8). Furthermore, when examined in a continuous distribution, there was a weak direct correlation between disease activity and RG abundance (Spearman, r=0.320, p=0.034). Overall, these findings reaffirmed associations between RG expansions within lupus microbiota communities in those experiencing active renal disease, although repeated studies of a limited patient set can evoke concerns about statistical analyses.

To investigate for temporal changes in RG abundance in these patients, we closely examined the sequential libraries of individual donors. These surveys included nine LN patients and the other seven SLE patients who never had renal manifestations but did have inflammatory arthritis, cutaneous disease and/or other disease features (online supplemental table S1A and SB). For RG, we found a remarkable stability within the healthy female CTLs over time (online supplemental figure S8A). Among the 16 patients, 11 patients exhibited low or undetectable RG levels with limited variation over time (online supplemental figure S10B). Of these 11 patients, for patient S134 that had quiescent disease during our study (online supplemental table S1A), also had low or undetectable RG in all four time points sampled. Notably, while four LN patients had RG blooms during disease flares (figure 2) another five LN patients also displayed stable low RG abundance pattern despite episodes of active renal disease documented at one or more of the sampling time points suggesting not all LN flares are associated with RG blooms (online supplemental figure S8B), which could mean other, undetected, disease drivers are involved.

Strikingly, in four LN patients (S107, S47, S120 and S78) (~44% of the LN patients followed over time) dramatic changes in RG abundance were detected, with RG bloom reaching a mean of 9-fold higher abundance compared with other time point sample(s) from the same donor. Such an RG bloom, with temporal concordance with clinical disease flare, was also identified in patient (S61) who was without renal involvement but had inflammatory polyarthritis (figure 2A). When only the samplings from these five patients with an episode of RG bloom were examined, the level of disease activity significantly correlated with RG abundance (r=0.320, p=0.03). Of the seven SLE patients without renal involvement, S61 had a baseline RG abundance of 0.6% with a bloom to 4.6% at the subsequent evaluation, while all other non-renal SLE patients had RG abundance of at undetectable levels to at most 0.4% at different time point. These findings may rationalise that RG blooms can contribute to the clinical pattern of relapsing-remitting disease activity that occurs in many lupus patients despite close clinical monitoring and treatment.

Isolation and characterisation of RG strains from LN patients at disease flare

To more closely investigate the nature of the RG blooms documented in patients, we sought to characterise individual RG isolates from the LN patients. From samples of two active LN patients, S47 and S107, obtained at time of LN clinical flares with concurrent RG blooms, colonies were initially selected based on RG-specific 16S rRNA PCR-based assay. Analysis of the whole genome sequences from these 27 isolates from the LN patients documented that these represented independent non-identical RG strains. By multidimensional analyses these distributed into four groups (online supplemental figure S11), and the representative strains (S47-18, S107-48, S107-61 and S107-86) were selected for further analysis (figure 3, online supplemental figures S11 and S12).

Figure 3

Whole genome sequencing of Ruminococcus (blautia) gnavus (RG) isolates from two lupus patients in clinical flare. Type strain RG2 as well as isolates from patients, S47 and S107, were sequenced and de-novo assembled, while an assembly for RG1, designated *) was obtained from NCBI RefSeq. (A) Long-read assemblies of six RG isolates. From inside to outside, circular tracks show average GC content across 1 kbp windows (black line); assembled contigs (grey ring sections); locations of 1 kbp windows with BLAST hits to type strain assemblies, RG1 (ATCC 29491) and RG2 (CC55_001C); and gene start sites as predicted by Prokka, coloured by strand (+: red, −: blue). (B) Complete-linkage hierarchical clustering of the gene content (orthogroup presence/absence) of newly sequenced RG isolates and publicly available assemblies. Newly sequenced isolates and the type strains RG1 and RG2 are shown in blue. LG producing strains are not in a single cluster. NCBI, National Center for Biotechnology Information.

RG strain genomes from LN patients include genes implicated in inflammatory bowel disease pathogenesis

Comparisons were performed between genomes of all currently known RG isolates, which included nine strains (RJX1120-RJX28) isolated from Crohn’s Disease patients, a form of inflammatory bowel disease (IBD), and two from antibiotic-treated infants (RJX1118, RJX1119) previously reported to together represent a separate clade.13 Yet by our analysis these IBD-associated strain genomes distributed throughout the branches of a dendrogram of all currently available RG genomes (figure 3B and online supplemental figure S10). Whereas the strains from donors, S107-86 and S107-48 were also not related to each other, the genomes of the S47-18 and S107-48 strains, although from different lupus donors, displayed a high level of relatedness (figure 3B, online supplemental figures S11 and S12).

Homology comparisons were performed with 199 genes previously reported to be uniquely associated with RG strains isolated from IBD patients but not healthy individuals.13 Based on a 70% overall sequence homology cut-off, we found 34 of these genes were represented in the genomes of one or more of these four LN RG strains. Indeed, all of the four LN RG strains included 21 of these genes (figure 4 and online supplemental table S5), and many were also assignable to a KEGG orthologue and a putative protein function (online supplemental table S5). All of these LN RG strains contain an anti-oxidant peroxiredoxin gene (PanPhlAn identifier xg001425), postulated to provide a competitive advantage in a host affected by oxidative stress from increased generation of reactive oxygen species (ROS) and reactive nitrogen species (RNS), which affects both host cells and gut commensals.14 15 Highly relevant, a recent metabolomics report found that increased serum ROS and RNS levels distinguish LN patients from non-renal SLE and healthy CTL.16 Further, both the S107-48 and S47-18 RG strains from LN donors contain orthologues of a putative RG PTS sugar transporter and for alpha-L-fucosidase (xg000037 and xg000038), which have been implicated in catabolism of host mucin that is a component of the intestinal barrier, although alone these factors are not currently considered sufficient to cause intestinal injury.17 18 Yet we found that the type strains, RG1 and RG2 also share 24 of the 34 above-mentioned IBD-associated genes (figure 4 and online supplemental table S5). Taken together, the LN strains have genes postulated to facilitate better adaptation to an inflamed host, including LN patients, which could contribute to a competitive advantage with other intestinal bacteria. However, these IBD-associated genes were also found in RG strains from IBD, and in healthy donors. While these analyses may rationalise a driver for RG expansions, our results suggesting these particular genes are more commonly distributed in different strains (figure 4 and online supplemental table S5) than previously reported.13

Figure 4

Genes first identified in RG strains isolated from inflammatory bowel disease (IBD) patients are shared by RG strains from lupus nephritis patients, but only LN strains express the cell-membrane lipoglycan (LG). Within select RG strains, we searched for 199 IBD-associated RG genes previously identified by metagenomic analysis.13 Based on a 70% homology cut-off, 34 of these genes were present in one or more of the LN strains. Comparisons included the genomes from the nine strains from Crohn’s disease patients (IBD), and two from infants in the source report,13 with comparison to strains from a healthy donor (MSK 22.24), two RG type strains (RG1 and RG2), and four strains from LN patients with disease flares and concurrent RG blooms. LN strains, which commonly expressed a number of genes associated with IBD strains, could not be discriminated based on expression of these genes. Expression of the RG LG (shown at far left) was detected in three of four of these LN strains, but was not in any of the strains from IBD, the antibiotic-treated infants nor the RG1 type strain from a healthy donor. Presence or absence of designated individual genes, based on gene sequence homology (see the Methods section), is indicated (see online supplemental table S5). The presence or absence in a strain of the RG lipoglycan that is based on immune reactivity with murine monoclonal IgG or lupus serum IgG antibodies (see figure 6). All strains have substantial numbers of particular genes previously associated with IBD isolates.

Conserved structural features of lipoglycans from three independent RG strains

We, therefore, turned our attention to determine which RG strains produced anon-protein antigen, which had been identified based on recognition by serum IgG-antibodies in a large proportion of patients with active renal disease.7 In immunoblotting studies, we documented serum antibody reactivity with diagnostic oligobands in extracts of three of the four RG isolated from LN patients, while these antigenic oligobands were not detected in any of the strains from IBD, infants or a healthy adult (figure 5).13 19

Figure 5

Conserved structural features of lipoglycans purified from RG strains isolated from three different donors. Mass spectrometric analyses of isolated LG preparations from (A) the type strain RG2, (B) the LN strain S107-86 and (C) the LN strain S47-18 were performed as previously described7 and charge-deconvoluted spectra are shown. Relative abundances for the depicted spectral regions were normalised to the most intense signal of the tri-acyl LG 47:0 found in all strains. Mono-acyl LGs are labelled in blue, di-acyl LGs in green, and tri-acyl LGs in red. Details of all detected molecular LG species for strain RG2 are summarised in online supplemental table 6. (D) Heatmap of the 100 most abundant signals of LGs from the 3 strains (corresponding mass spectra are shown in A–C). Isotope clusters originating from the same molecular species are grouped together and the LG structural composition is assigned if applicable. (E) Spectral similarity score calculated from these 100 most abundant peaks, indicating a high similarity between the LG populations of these three strains (p<2×10−12). (F) A structural model of the major abundant LG species consisting of tri-acyl LGs, di-acyl LGs and mono-acyl LGs. The glycoconjugate consists of a diacylglycerol-hexuronic acid linker and the next two connected sugars are hexoses. The lipid anchor can potentially include one or both of these hexoses, but this structural detail is not yet resolved. The third fatty acid can be either bound to the hexuronic acid, the two adjacent hexoses or to a sugar moiety of the core glycan. The core glycan composition of the purified LG of these RG strains showed a remarkable conservation. Image generated with Biorender.com. LGs, lipoglycans; RG, Ruminococcus (blautia) gnavus.

In surveys of the structural features of these LN-associated glycans, mass spectrometry (MS) detected very similar overall spectra of the glycan species purified from three independent RG strains (RG2, S107-86 and S47-18) (figure 5A–C). From each of these glycans, an acyl-glycerol lipid anchors was identified, and hence these were then referred to as lipoglycans (LGs). The 100 most abundant mass signals, in the range of 2500–5000 Da, were identified, and depicted as a heatmap (figure 5D) of the ion clusters. A calculated similarity score (figure 5E), indicated very high structural similarity between the LG of these three RG strains (p<2×10−12).20

The most abundant molecular species had an average mono-isotopic mass of 3632.645 Da (figure 5A–C), which was interpreted as an LG comprised of three fatty acids with acyl chain composition of 47:0, one glycerol, eight hexoses, five N-acetyl-hexosamines and three hexuronic acids. The difference between the major di-acylated LG with a mass of 3394.415 Da (in RG2; calc. mono-isotopic mass: 3394.407 Da; di-acyl LG 31:0) (figure 5A) can be explained by acyl compositions of 31:0, which differed by one less palmitic acid (16:0). The major mono-acylate species in an LG had a 16:0 acyl composition (with 3170.204 Da; mono-isotopic mass: 3170.193 Da; mono-acyl LG 16:0). The strains RG2 and S107-86 also contain a mono-acyl LG carrying a margaric acid (17:0) that was observed at 3184.217 Da in RG2; mono-isotopic mass: 3184.208 Da; mono-acyl LG 17:0) (figure 5A,B). In addition, independent of the acylation status, we also detected LG variants with up to six additional hexoses detected, which were most prominent within the tri-acyl LGs of the RG2 strain (figure 5A, online supplemental table S6).

To gain further insights into the composition of the glycolipid anchor structure, we used the earlier described de-O-acyl glycan (there named de-O-acyl LG3)7 for MS2-experiments. Analysis of the doubly charged ion of the core de-O-acyl LG (calc. mono-isotopic mass: 2931.963 Da) was interpreted as indicating the presence of a glycerol–hexuronic acid unit that can also include two or more additional hexoses (online supplemental figure S13).

These MS analyses enabled the formulation of a structural model of the LG species (figure 5F), which covers all abundant MS signals of these RG strains. The assembled LG has a central core structure consisting of 18 carbohydrate moieties, and 1 glycerol with 1–3 fatty acids, which are affixed to the cell wall via these lipids that directly attach to the cell membrane. Additional hexose sugars are attached to the core glycan, which result in further microheterogeneity. Taken together, these studies document the great conservation of structural features of the LGs from these different RG strains, including from unrelated LN donors, with only minor structural variation (figure 5).

LN serum and murine monoclonal antibodies recognise conserved non-protein antigens in RG strains

We, therefore, sought to determine whether the LG of RG strains expressed cross-reactive antigenic determinants. Immunoblots were performed with the serum of a representative active LN patient, S47, obtained during clinical flare (figure 6A–E) and we documented whether IgG-reactivity was either present or absent in protease-treated extracts of a large panel of RG strains (figure 6A). In the RG strains, S107-48, S107-86 and S47-18, from the two LN patients, there were IgG-reactive oligobands of the same 20–30 kDa distribution. In contrast, there was neither reactivity with the RG1 type strain from a healthy donor, nor with the nine RG strains from IBD patients, and nor the two RG strains from antibiotic-treated infants13 (figure 6A–C).

Figure 6

Conservation of immunodominant lipoglycan-associated non-protein antigen in RG strains from SLE patients. Molecular components of different RG strains were separated by polyacrylamide gel electrophoresis, transferred to membranes. (A) Immunoblot with serum IgG from LN patient S47, obtained during a disease flare, of strains isolated from LN patient S107 (S107-48, S107-61 and S107-86), and from LN patient S47 (S47-18), while RJX1118 was from an antibiotic-treated infant and RJX1125 strain was from a patient with IBD,13 RG1 and MSK22.24 strains were from healthy donors. (B) Aliquots of these same bacterial extracts were treated with proteinase K, which reveals the immune recognition by lupus serum IgG of oligo bands which are non-protein antigens that migrate akin to 20–30 kDa protein bands. (C) Nine different RG strains from IBD patients and two RG strains from antibiotic-treated infants do not contain the immunoreactive oligo bands of the lipoglycan that are found in RG2 extract and purified RG2 lipoglycan. These non-lupus strains and their genomes were described in.13 Non-reactive RG1 is also from a healthy adult. (D) Immunoblot reactivity of S47 patient serum IgG-antibodies were reactive with extracts of five RG strains, and the lipoglycan purified from lupus S47-18 strain. (E) A replicate immunoblot was performed after preincubation of the S47 sera with 4 μg of purified S47-18 LG, which resulted in complete inhibition of lupus serum IgG reactivity with oligo bands of comparable MW in S107-48, S107-86 and S47-18 extracts and the purified S47-18 LG. The lower MW band in RG1 from a healthy donor, which was previously shown to be protease-sensitive, was unaffected. Lipoglycan oligo bands migrate to an area delineated by the red boxes. IBD, inflammatory bowel disease; LN, lupus nephritis; RG, Ruminococcus (blautia) gnavus; SLE, systemic lupus erythematosus.

To further evaluate the relatedness of LG antigens, immunoblotting was also performed with the LG purified by hydrophobic interaction column fractionation from the lupus S47-18 strain, which had oligobands with the same apparent MW as those detected in the extracts of the lupus strains, S107-48, S107-86 and S47-18 (figure 6A,B, online supplemental figure S14). Strikingly, preincubation with LG purified from RG2 strain of this same lupus sera resulted in complete inhibition of reactivity with oligobands in the RG extracts, and in the LG purified from the lupus RG strains, while the reactivity of a protease-sensitive (ie, unrelated protein) band in the RG1 strain was unaffected (figure 6D,E). Cumulatively, antigenically related non-protein antigens, attributed to a novel LG were common in LN RG strains but not in the RG strains from IBD patients.21 22

To independently investigate the antigenic diversity of different RG strains, murine monoclonal antibodies (mAbs) were generated by bacterial immunisation with purified RG LG (see the Methods section). The clonally distinct mAbs, termed 33.2.2 and 34.2.2 (online supplemental figure S14), were reactive with purified RG LGs, recognised the same MW non-protein oligoband antigen in extracts of S107-48, S107-86, S47-18 and RG2 strain as LN sera, but were non-reactive with a large panel of unrelated purified bacterial glycans (online supplemental table S7).

High-titre serological responses to RG LGs in SLE with high RG intestinal abundance and disease activity

To investigate the host immune response to the expansion of RG strains overtime, we studied available longitudinal sera from three lupus patients (S47, figure 7A–D; S61, figure 7E–H; and S78, figure 7I–L), including at the time of clinical LN flare (see figure 2C). By bead assay, serum IgG-reactivities were assessed for binding interactions with RG2 strain extract (figure 7A, E, I),7 with comparisons with purified RG2 strain LG7 (figure 7B, F and J). The near identical reactivity patterns of whole bacterial extracts and the purified LG, confirmed the high immunogenicity of the LG component within the RG2 bacterial extract. Comparable reactivity patterns were documented with the structurally related LG from the S47-18 strain (S47-18 LG) obtained from the S47 LN donor (figures 5A,B and figure 6D,E), although for this LG there were uniformly stronger binding interactions (as IgG-binding curves for S47-18 LG were shifted due to greater reactivity (figure 7C, G and K). By contrast, there was little or no detectable reactivity with the LPS glycan from a Pseudomonas species (figure 7D, H and L). Cumulatively, these data reveal high-titre lupus host LG-specific serum antibody reactivities, with highest detected levels in lupus patients, S47 and S61, at the time of disease flare, which was also concordant with an RG bloom in abundance. For patient S78, limited variations in antibody titres were detected overtime, and there was substantial clinical disease activity at all but one visit (figure 7I, J and K).