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ABSTRACT Severe acute respiratory syndrome coronavirus 2 mRNA vaccination has reduced effectiveness in certain immunocompromised individuals. However, the cellular mechanisms underlying

these defects, as well as the contribution of disease-induced cellular abnormalities, remain largely unexplored. In this study, we conducted a comprehensive serological and cellular analysis

of patients with autoimmune systemic lupus erythematosus (SLE) who received the Wuhan-Hu-1 monovalent mRNA coronavirus disease 2019 vaccine. Our findings revealed that patients with SLE

exhibited reduced avidity of anti-receptor-binding domain antibodies, leading to decreased neutralization potency and breadth. We also observed a sustained anti-spike response in IgD−CD27−

‘double-negative (DN)’ DN2/DN3 B cell populations persisting during memory responses and with greater representation in the SLE cohort. Additionally, patients with SLE displayed compromised

anti-spike T cell immunity. Notably, low vaccine efficacy strongly correlated with higher values of a newly developed extrafollicular B and T cell score, supporting the importance of

distinct B cell endotypes. Finally, we found that anti-BAFF blockade through belimumab treatment was associated with poor vaccine immunogenicity due to inhibition of naive B cell priming and

an unexpected impact on circulating T follicular helper cells. SIMILAR CONTENT BEING VIEWED BY OTHERS DELAYED GENERATION OF FUNCTIONAL VIRUS-SPECIFIC CIRCULATING T FOLLICULAR HELPER CELLS

CORRELATES WITH SEVERE COVID-19 Article Open access 15 April 2023 THE GERMINAL CENTRE B CELL RESPONSE TO SARS-COV-2 Article 06 December 2021 HUMORAL AND CIRCULATING FOLLICULAR HELPER T CELL

RESPONSES IN RECOVERED PATIENTS WITH COVID-19 Article 13 July 2020 MAIN The deadly coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2

(SARS-CoV-2), created an emergency situation in which mRNA vaccines were trialed in large cohorts of healthy donors (HDs), leading to the eventual approval of these vaccines by the Food and

Drug Administration1,2. The delivery of monovalent mRNA vaccines and subsequent boosters according to a three-dose injection schedule resulted in an effective reduction of severe COVID-19

infections and deaths3, with effectual protection against the ancestral virus and its variants of concern. To date, in response to the emergence of highly contagious and immune-evasive

variants, updated reformulations of mRNA vaccines, such as the Wuhan-Hu-1 (WA.1)/Omicron BA.4/5 bivalent or XBB.1.5 monovalent formulations, have been introduced. The efficacy of mRNA

vaccines has been assessed by investigating both humoral and cellular responses in the healthy population, where they induce prolonged germinal center (GC) activity4,5, the generation of

high-affinity neutralizing antibodies (nAbs) and the establishment of immune memory6,7, as well as de novo B cell engagement upon booster vaccination8,9. While GC activity can be detected at

least up to 6 months after vaccination, the rapid waning of circulating antibodies and nAbs10 suggests that the formation of long-lived plasma cells might be limited11. Correlates of

protection against reinfections and/or severe disease have been proposed to include anti-receptor-binding domain (RBD) titers and antiviral nAbs, as well as persisting memory B and T

cells12. Despite the demonstrated safety and efficacy of SARS-CoV-2 mRNA vaccines in immunocompetent individuals1,2,13, a full understanding of their effectiveness in immunocompromised

persons is still lacking. Overall, previous studies have demonstrated that immunomodulatory drugs can result in poor vaccination responses14 and a higher risk and severity of bacterial and

viral infections15. Yet, there is still a paucity of information about the mechanisms controlling mRNA vaccines’ immunogenicity and long-term efficacy in immunocompromised and autoimmune

patients diagnosed with systemic lupus erythematosus (SLE). Previous studies reported reduced immunogenicity of COVID-19 vaccines in a wide spectrum of autoimmune disorders16, including

SLE17. Largely, those studies addressed mRNA vaccine efficacy in patients with lupus by assessing the seroconversion rate of anti-spike immunoglobulin G (IgG) responses in small-sized

cohorts17,18. To date, the cellular basis of these antibody deficiencies and the impact of anti-B cell therapies other than rituximab-induced B cell depletion have not been addressed. In

this study, we investigated the efficacy of SARS-CoV-2 mRNA vaccinations in patients with SLE, a B cell-induced disease19 with an important cross-talk with functionally abnormal T

cells20,21. Several groups including our own have shown that B cell regulation is profoundly disturbed in SLE, with SLE heterogeneity underpinned by the expression of separate B cell

endotypes22,23. Specifically, we have shown that the expansion of activated effector B cells and plasma cells segregates with more severe disease and may reflect a naive-derived

extrafollicular endotype that is distinct from a GC/memory endotype and is predominant in Black patients with SLE. Notably, severe COVID-19 infections share these characteristics and induce

prominent extrafollicular B cell differentiation and expansion of autoreactive antibody-secreting cells (ASCs)24,25. Here, we show that patients with SLE have reduced antibody titers and IgG

neutralizing activity and lack coordinated activity between the memory T and B cell compartments, with poor vaccine immunogenicity associated with increased extrafollicular immune endotypes

and treatment with belimumab26,27, an anti-BAFF monoclonal antibody approved by the Food and Drug Administration for lupus therapy. RESULTS DONOR COHORT CHARACTERISTICS AND STUDY DESIGN To

study the efficacy of mRNA COVID-19 vaccines in SLE, we enrolled donors who received two (Vax1 + Vax2) or three (Vax3) doses of monovalent (WA.1) BioNTech/Pfizer or mRNA-1273

(Moderna/National Institute of Allergy and Infectious Diseases (NIAID)) vaccines. The cohort consisted of patients with SLE (_n_ = 79 patients; _n_ = 10 prepandemic individuals, _n_ = 69

vaccinees) and age- and sex-matched HD controls (_n_ = 64 HDs; _n_ = 8 prepandemic individuals, _n_ = 56 vaccinees) collected between March 2021 and October 2022. The SLE group was enriched

for female patients of Black ancestry, reflecting the race and sex bias of SLE and the demographics of the Atlanta metropolitan area (Supplementary Table 1). Owing to the restrictions

imposed by the pandemic isolation requirements, the HD group had an underrepresentation of Black individuals relative to the SLE cohort. Samples were mainly cross-sectional collections, with

longitudinal follow-ups as indicated in the diagrams (Supplementary Table 1 and Extended Data Fig. 1). Given that our study was designed to evaluate primary responses to mRNA vaccines, in

the absence of any infection at a time when vaccine administration was erratic, longitudinal follow-up was limited to the fraction of patients who fulfilled these criteria. A total of 256 HD

and 212 SLE samples were serologically evaluated for vaccine-induced antibody responses, and a total of 161 HD and 182 SLE paired peripheral blood mononuclear cell (PBMC) samples were

assessed for antigen-specific B and T cell responses using high-dimensional flow cytometry combining antigen reactivity and deep immune profiling (Extended Data Fig. 2). LOWER SEROCONVERSION

UPON PRIMARY MRNA VACCINATION IN PATIENTS WITH SLE To assess the level of seroconversion in our two cohorts and to define the specificity, kinetics and persistence of circulating antibodies

recognizing different portions of the mRNA-coded proteins, we performed an isotype-specific plasma screen28 against the following SARS-CoV-2 targets: S1 and S2 subunit domains of the spike

protein, RBD of the S1 subunit, and the N-terminal domain (NTD) (Extended Data Fig. 3a). Nucleocapsid-specific IgG antibodies were also tested to exclude prior infections (Extended Data Fig.

3b). Overall, IgM responses were minor contributors to the spike reactivity in the HD cohort and were increased in the SLE cohort (Extended Data Fig. 3c). IgA-specific responses were

largely induced against the spike domain and RBD (Extended Data Fig. 3d), with similar responses between the two groups. As previously reported, we observed a predominant IgG-mediated

anti-spike and anti-RBD response (Extended Data Fig. 3e and Fig. 1a–g). Upon the administration of one vaccine dose (Vax1, 3–4 weeks), ~85% of HDs seroconverted, whereas patients with SLE

had a lower seroconversion rate of ~58%, with significantly more negative/low responders (Fig. 1e and Extended Data Fig. 3e). Completion of the primary series of vaccines (Vax2) increased

the seroconversion rate of both the SLE (88%) and HD (100%) groups, although reduced mean titers and overall increased number of negative/low responders remained among the vaccinees with SLE

(Fig. 1f and Extended Data Fig. 3e). A booster dose (Vax3) normalized the mean titers of IgG RBD between the two cohorts (Fig. 1g). While the RBD of the S1 subunit has been described as a

main target of broad nAbs, other non-RBD structural proteins of the spike, namely S2 and NTD, can harbor neutralizing epitopes. The S2 domain, harboring more conserved epitopes and some

level of cross-reactivity with other coronaviruses, was targeted by IgG similarly in HD and SLE samples (Extended Data Fig. 3e), whereas the IgG reactivity toward the NTD was lower in the

SLE cohort, potentially compromising the control of viral escape29 (Extended Data Fig. 3e). Preexisting immunity to the four seasonal common-cold coronaviruses (CCCs)—alpha coronavirus

strains ‘HKU1’ and ‘229E’ and beta coronavirus strains ‘OC43’ and ‘NL63’—was similar at baseline, with the only detectable difference being the higher anti-OC43 IgG titers in SLE (Extended

Data Fig. 3f). Whether this observation could be explained by either more frequent or prolonged seasonal infections in patients with SLE remains to be elucidated. Overall, the evaluation of

serological responses to mRNA vaccination revealed a defective primary response in SLE that requires vaccine boosters for full seroconversion. REDUCED RBD-SPECIFIC ANTIBODY COMPETITIVENESS

AND NEUTRALIZATION IN SLE The functional activity of circulating RBD-specific antibodies was determined by a competitive ELISA to assess their efficiency in blocking the interaction of

recombinant human RBD with its receptor, recombinant human angiotensin-converting enzyme 2 (ACE2) (Fig. 2a,b)30. Interestingly, while the overall anti-RBD titers were only mildly reduced in

patients with SLE (Fig. 1), this group displayed significantly impaired ability to block ACE2 binding across most time points (Fig. 2a,b). Despite medium/high RBD IgG titers, SLE samples

were more frequently enriched for either non- or low-competitive antibodies (Fig. 2c), which are usually low-avidity IgG antibodies30,31. To test the hypothesis that impaired ACE2-blocking

activity could result from defective affinity maturation of B cell responses in SLE, we tested antibody avidity using surface plasmon resonance (SPR)32. Comparisons of off-rate values

confirmed that patients with SLE were enriched for anti-RBD immunoglobulins with medium/low avidity, with the greatest impairment observed after Vax2; this was only partially rescued after

the booster dose (Fig. 2d). Of note, at Vax2, the absence of detectable RBD binding (Fig. 2d, nonbinder) was detected exclusively in a fraction of patients with SLE treated with belimumab.

To corroborate the ELISA results further, we performed pseudoviral neutralization assays33 against the SARS-CoV-2 WA.1 (wild-type), Delta (B.1.617.2) and Omicron (B.1.1.529 BA.1) strains

(Extended Data Fig. 4a,b). Patients with SLE displayed impaired neutralization activity against those viruses, with significantly lower neutralization titers and reduced breadth, relative to

their HD counterparts (Fig. 2e–g and Extended Data Fig. 4b). Interestingly, neutralizing titers decayed significantly faster in HDs relative to patients with SLE, with significant

differences for the WA.1 wild-type (half-life of 38 days for the HD group versus 73 days for the SLE group; _P_ = 0.03) and Delta (half-life of 39 versus 68 days; _P_ = 0.03) strains after

Vax3 (day 42 after vaccination and onwards)34. These data identify qualitatively defective and lower-avidity circulating antibodies resulting in reduced breadth of neutralization in patients

with SLE. DEFECTIVE AND DISTINCT ANTI-SPIKE B CELL RESPONSES IN SLE To evaluate the magnitude of cellular responses and the identity of B cells induced upon mRNA vaccination, we performed

immunophenotypic profiling with a high-dimensional 28-color flow panel that provided tetramer-based detection of WA.1 spike- and RBD-reactive B cells (Extended Data Fig. 2a and Fig. 3a,b).

During the post-Vax1 priming phase, 62% of the HDs mounted an early anti-spike B cell response (Fig. 3c), with ~35% of anti-Spike B cells also binding to the RBD tetramer (Fig. 3d). Overall,

the HD group displayed a higher and persistent anti-spike and anti-RBD recall response to Vax2 and Vax3 (Fig. 3c,d). The SLE group had a significantly lower proportion of responders after

priming and within memory recall responses, with ~10–30% of patients failing to generate a detectable B cell response at any time (Fig. 3c,d). B cell lymphopenia is common in SLE owing to

both disease activity and therapy. To account for this variable, we compared the frequencies of the total CD19+ B cells between the HD and SLE groups (Extended Data Fig. 4c). Both total and

antigen-specific circulating B cells were reduced in patients with SLE, with enrichment of patients with very low B cell frequency (<1%) and low spike-reactive B cells (<0.0022%)

(Extended Data Fig. 4c,d). Normalization of antigen-specific reactivity to B cell numbers confirmed that the SLE cohort carried more negative responders than the HD cohort (Extended Data

Fig. 4e,f). Preexisting immunity to CCCs in the B cell memory compartment did not significantly influence the anti-SARS-CoV-2 B cell response, as measured by the level of cross-reactive

WA.1+/CCC+ spike B cells (Extended Data Fig. 5a–c). Furthermore, this response was not notably different between the two cohorts (Extended Data Fig. 5c). Contrary to the greater durability

of their antibody response, the frequency of spike-reactive B cells declined more rapidly in the SLE group after Vax2 (half-life; 95% confidence interval, calculated decay _P_ = 0.009) but

was similar to that in the HD group after Vax3. Together, these results suggest that B cell defects in SLE are responsible for reduced mRNA vaccine efficacy. ANTI-SPIKE CD27− POPULATIONS

PERSIST DURING THE MEMORY PHASE AND EXPAND IN SLE Despite the increasingly recognized complexity of these compartments, previous studies have largely concentrated on plasmablast and CD27+

memory responses. As different effector and memory pathways and the participation of IgD−CD27− double-negative (DN) B cells may be induced in different SLE types24,35, we sought to

interrogate further the expanded pool of antigen-reactive B cells and define their dynamics. The distribution of DN subsets (DN1–DN4) is an indicator of the origin and function of the

corresponding B cells. Specifically, we have previously associated DN1 B cells with conventional CD27+ memory pathways36 and shown that they represent a large majority of DN cells in healthy

individuals. In contrast, DN1 cells represent a much lower fraction in acute SLE and severe COVID-19 infections, in which DN2 and DN3 B cells are dominant. In these acute situations, DN2

and DN3 cells are considered extrafollicular naive-derived effector cells23,24,25,37,38. However, little is known about the contribution of DN subsets to effector and memory vaccination

responses and specifically to mRNA vaccination. Using unsupervised PaCMAP (pairwise controlled manifold approximation) and FlowSOM tools, we determined the complexity of the global B cell

compartment and defined the participation of multiple B cell clusters in the anti-spike/RBD response (Extended Data Fig. 6a and Fig. 4a). In SLE, the major differences were driven by

populations of B cells typically associated with the disease (for example, activated B naive, DN2, DN3 and 9G4-expressing cells24,35; Extended Data Fig. 6a and Fig. 4a). In particular,

within the DN B cells, RBD−spike+ B cells in the SLE group were significantly enriched for DN2/DN3 clusters (#4, 5, 25) over DN1 (cluster #11) (Extended Data Fig. 6a). Increased DN2 and

spike++ DN2 populations were shared among patients with SLE, with greater frequency in those of Black ancestry (Extended Data Fig. 6b). We also used a supervised two-dimensional flow

cytometry approach to measure the distribution of spike-reactive B cells among previously identified parental populations defined by the expression of IgD and CD27: naive, CD27+ unswitched

memory, CD27+ isotype-switched memory and IgD−CD27− DN cells. DN B cells were further fractioned into four specific subsets (DN1–DN4)23,24,39 determined by the expression of CD21 and CD11c

(full gating strategy; Extended Data Fig. 2a and Fig. 4b). The CD20+spike+ B cell responses to Vax1 included in both cohorts similarly large fractions of naive B cells (~40%) that rapidly

contracted over subsequent vaccinations (Fig. 4c). The IgD+ unswitched memory cells also contributed to a small portion of the total antigen-induced population that rapidly contracted (Fig.

4c). The initial priming responses included significant fractions of early CD27+ switched memory cells and DN cells, the latter representing naive-derived effector responses as we had

previously reported for autoreactive B cells in SLE and severe COVID-19 infections25,35,37. Notably, DN cells dominated the spike response early in SLE and remained dominant in both groups

before booster vaccination, presumably reflecting memory cells induced by Vax1 and effector/activated memory cells induced by Vax2 (ref. 40). In both groups, while conventional CD27+ memory

cells dominated the response following booster vaccination, DN cells represented a large fraction of the memory responses (Fig. 4c,d). In this study, DN1 strongly dominated the

spike-specific responses in HDs across all time points. In contrast, in patients with SLE, DN2 cells dominated the early response to Vax1 and Vax2 and remained significantly higher relative

to the HD cohort in the post-Vax3 period (Fig. 4d,e). Moreover, DN2 cells were enriched in low spike responders (below the limit of sensitivity (LOS)) (Fig. 4f). DN3 cells also contributed

to different phases of the response and were significantly expanded at late time points after Vax2 and Vax3 in the SLE group (Fig. 4d). The expression of C–C chemokine receptor type 6 (CCR6)

and C–X–C motif chemokine receptor 3 (CXCR3) on spike-reactive B cells was also qualitatively different between the two cohorts (Fig. 4g–i). In the HD cohort, we observed a predominance of

CCR6+spike+ B cells that expanded within subsequent vaccinations (Fig. 4g–i). In contrast, in patients with SLE, spike+ B cells were highly enriched for CXCR3+ cells (Fig. 4g–i). We further

analyzed the contribution of several B cell isotypes to the anti-spike responses by examining their immunoglobulin surface expression with flow cytometry (Extended Data Fig. 6c–g). IgG

responses dominated the spike reactivity (Extended Data Fig. 6c,d,g), whereas IgM and IgA memory B cells represented a smaller portion of this response (Extended Data Fig. 6c–f).

Interestingly, IgM+ memory B cells were increased in SLE, particularly in the early post-Vax2 and Vax3 phases, accounting for >20% of all antigen-reactive CD20+ B cells in several

patients (Extended Data Fig. 6e). Additionally, in the SLE cohort, spike reactivity was associated with a smaller and delayed expansion of IgG+ B cells upon recall doses (Extended Data Fig.

6g). Collectively, these data indicate that patients with SLE mount a diverse anti-B cell immunity upon mRNA vaccination, with greater expansion of DN2/DN3 B cells also persisting during the

establishment of memory responses. IMPAIRED ACTIVATION AND PERSISTENCE OF ANTI-SPIKE LUPUS T CELLS We also sought to define the magnitude, kinetics and differentiation of CD8+ and CD4+ T

cells upon mRNA vaccination. To this end, we used an in vitro system suitable for scoring the frequency of antigen-reactive T cells and that relies on the incubation of cells with megapools

of peptides and allows their quantification using the activation-induced marker (AIM) assay6,41 (Fig. 5a and Extended Data Fig. 7a,b). Cells were stimulated with megapools of spike

overlapping peptides spanning the entire protein (WA.1, spike aa 5–1,273) or with peptides from the hemagglutinin (HA) H1N1 (A/California/04/2009) protein, an unrelated control for viral T

cell reactivity. Twenty-four hours after incubation, samples were analyzed to score the magnitude of antigen-reactive AIM+ cells using a combination of two surface markers (CD69 and 41BB for

CD8+ T cells and CD40L and OX40 for CD4+ T cells). T helper CD4+ cells were classified based on their expression of chemokine receptors, and their polarization was further investigated in

both the CXCR5− or CXCR5+ (referred to as ‘AIM+ circulating T follicular helper (cTFH)’) compartments (Fig. 5b and Extended Data Fig. 7b). Lower T cell responses were observed in the SLE

cohort, with impaired priming of AIM+CD8+ T cells (Fig. 5c) and lower levels of both AIM+CD8+ and AIM+CD4+ T cells at the late memory and recall phases (Fig. 5c–e and Extended Data Fig.

7c–e). The overall fold reduction in the SLE group compared to the HD group was 6.71 (AIM+CD8+ T cells) and 3.15 (AIM+CD4+ T cells) at Vax2 and 3.85 (AIM+CD8+ T cells) and 2.92 (AIM+CD4+ T

cells) at Vax3. Unsupervised PaCMAP and FlowSOM cluster analyses were informative of significant differences in terms of T cell polarization, with T cells in the SLE cohort characterized by

a reduction in effector memory T (TEM) cell subsets, also expressing CCR4 and/or CCR6 (CD8+ T cell clusters #8 and 12–14, CD4+ T cell clusters #1–3, 7 and 8) (Fig. 5f and Extended Data Fig.

7f,g). Two-dimensional flow cytometry comparisons confirmed that the SLE anti-spike T cell responses were less represented in the TEM pool over three doses of vaccine (Fig. 5g–i) and were

distinguished in their SLE cTFH compartment, with an initial skewing of primed AIM+ cTFH cells into CCR6+ TFH17 cells (Extended Data Fig. 8a) and a general reduction in the magnitude of the

SLE AIM+ cTFH pool upon memory responses, especially after Vax2 (Fig. 5e). Notably, HA-reactive memory T cells were detected at normal levels in patients with SLE (Extended Data Fig. 8b),

although the AIM+ HA CD8+ pool still failed to generate normal TEM cells (Extended Data Fig. 8c), suggesting that CD8+ T cell defects might be mediated by associated lupus-disease defects42.

These results suggest that anti-spike T cell defects in SLE might be largely a result of inefficient mRNA activity and/or a property of vaccine- versus infection-induced T cell immunity.

POOR VACCINE-MEDIATED RESPONSES ASSOCIATE WITH AN SLE EXTRAFOLLICULAR IMMUNE SIGNATURE To investigate the influence of B cell endotypes on different vaccine responses, we used the total

RBD-reactive IgG levels to classify all vaccinees into three groups of responders: negative/low (VNL), medium (VM) or high (VH) vaccine responders (Fig. 6a). As expected, RBD IgG titers

directly correlated with the potency of WA.1 neutralization (Fig. 6b). Vaccinees with SLE who received one or two vaccine doses were enriched for negative/low responders, and their

neutralizing IgG potency upon Vax2 was still significantly lower than that in HDs. While the booster dose improved the responses in the SLE cohort, only 78% reached high antibody titers

relative to 97% in the HD cohort (Fig. 6a). We then tested the hypothesis that, in our SLE cohort, a predisposition to strong extrafollicular immune responses might be responsible for lower

immunogenicity of the mRNA vaccine. To address this question, we assessed patients for circulating cellular surrogates of extrafollicular activity identified in previous studies of SLE and

acute COVID-19 infections25,35,37. Based on these studies, we created an ‘extrafollicular activity score’ that included markers proposed to represent decreased GC activity (low B DN1

frequency) and low activated cTFH (act cTFH, CXCR5+PD-1+CD38+) frequency, together with markers of extrafollicular activation, including increase in B DN2 and circulating plasmablasts, as

well as expansions of CXCR5− peripheral activated T helper (act TPH, CXCR5−PD-1+CD38+) cells43,44 (Fig. 6c and Extended Data Fig. 9a). We observed that higher extrafollicular scores were

indeed associated with VNL groups, with strong overrepresentation of its components in the SLE cohort, where they negatively correlated with vaccine responsiveness (Fig. 6d). Factors

contributing to vaccine responses, such as age, sex or race, did not appear to drive a strong bias in mRNA immunogenicity and vaccine responsiveness (Extended Data Fig. 9b–e). We next asked

whether the qualitative assessment of serological reactivity was correlated to the magnitude of antigen-specific memory B and T cells. A strong correlation was detected between negative and

low antigen-specific B and T cell responses and the VNL group (Fig. 6e–h and Extended Data Fig. 9f,g). Notably, a great lack of immune memory responses in the B and T cell compartments was

uniquely observed in a group of VNL patients with SLE who received two mRNA vaccine doses (Vax2) (Fig. 6e–h and Extended Data Fig. 9f,g). These results confirm defective humoral and cellular

immunity in poor vaccine responders and their association with extrafollicular endotypes. POOR VACCINE RESPONSES AND HIGH EXTRAFOLLICULAR SCORES LINKED TO BAFF INHIBITION IN SLE We next

investigated cellular variables within the different SLE treatment groups. Integrating our immunophenotyping postvaccination data through principal component analysis (PCA), we segregated

the HD and SLE cohorts based on underlying immunological-associated features (Fig. 7a and Extended Data Fig. 10a). The results indicated that the general immune cell composition remained

distinct between the SLE and HD cohorts throughout the vaccine-mediated responses. Overlaying patient metadata onto the PCA plot revealed that patients receiving anti-BAFF therapy

(belimumab) were the most distant group from both HDs and patients with SLE receiving other classes of SLE therapy (Fig. 7a, Extended Data Fig. 10b and Supplementary Table 2). Comparisons of

vaccinated HDs and patients with SLE subgrouped by treatment class confirmed that unique extrafollicular signatures were globally associated with the SLE diagnosis. Features included a

stronger extrafollicular B cell signature with an expansion of activated naive cells, DN2 cells and ASCs (for example, plasma cells) in the B cell compartment, as well as reduced cTFH cells

(Extended Data Fig. 10c–h). The multivariate analysis suggested that not only disease-associated immunophenotype characteristics but also lupus-specific medications might distinguish

vaccine-mediated immune responses. Therefore, we sought to explore whether there was a meaningful correlation between poor vaccine responses and specific SLE treatments. Humoral and cellular

responses were diverse and changed dynamically in each SLE subgroup. Thus, the subgroup of patients with SLE receiving belimumab was enriched for the category of poor vaccine responders

(VNL), whereas the other subgroups (patients receiving mycophenolate mofetil, azathioprine or methotrexate) were similarly distributed among the three vaccine groups, with the

hydroxychloroquine subgroup being overrepresented among good vaccine responders (Fig. 7b–d). Disease activity score (measured as the SELENA-SLEDAI (Safety of Estrogens in Lupus National

Assessment-SLE Disease Activity Index) score) differed significantly between the SLE subgroups, with the lowest score in the hydroxychloroquine group (Extended Data Fig. 10i); however, it

did not seem to influence vaccine-mediated antibody and B cell responses (data not shown). The total RBD-specific IgG levels also reflected the nAb potency and breadth in the SLE subgroups

(Fig. 7e and Extended Data Fig. 10j). From a cellular standpoint, poor responses correlated with a general reduction in total circulating B cells (Extended Data Fig. 10c). The overall

spike-specific B cell responses were largely unaffected in hydroxychloroquine-treated patients across all vaccine doses (Fig. 7f). In contrast, all other treatment subgroups had

significantly impaired responses at Vax1. Notably, subsequent vaccine doses induced normal responses in the group treated with mycophenolate mofetil. Antimetabolite treatments with

azathioprine or methotrexate as well as belimumab treatment induced the poorest levels of response, which remained greatly diminished even after three doses. The belimumab group had the

lowest frequency of spike-specific B cells, albeit not significantly different from the azathioprine/methotrexate group, and contained the largest fraction of patients with spike-specific B

cells below the limit of detection (LOD) (Fig. 7f). From a qualitative standpoint, antigen-specific B cells shifted in all treatment groups except for the belimumab subgroup, from an early

dominance of naive and DN cells to a predominance of CD27+ memory B cells. Consistent with its preferential impact on naive cells relative to memory cells27, belimumab treatment led to the

largest accumulation of CD27+ memory cells (Extended Data Fig. 10k); this is unlikely to depend on enhanced cross-reactivity with the CCCs, which appeared to be proportionally small and not

dissimilar to that in the other groups (Extended Data Fig. 5c). In contrast, DN cells remained the majority of antigen-specific B cells in the azathioprine/methotrexate subgroup after Vax3.

Within the heterogeneous DN compartment (Fig. 7g), there was a gradual increase in the contribution of DN1 responses, which accounted for approximately 50% of all spike+ DN B cells after

three doses in the HD cohort as well as in the hydroxychloroquine and azathioprine/methotrexate SLE subgroups. However, non-DN1 cells represented >75% of spike+ DN cells in the

mycophenolate mofetil and belimumab groups (Fig. 7h). T cell responses were broadly reduced in patients with SLE, with a more pronounced and general loss of CD8 reactivity against the spike

(Extended Data Fig. 10l) and low CD4+ T cell (Extended Data Fig. 10l) and memory cTFH cell (Fig. 7i) responses in the poor B cell responder groups. Overall, the most profound reduction or

lack of vaccine efficiency, measured as a combined activity of serological and cellular-mediated responses, was observed in patients with SLE receiving anti-BAFF treatment at the time of the

initial vaccination (and remained treated over the course of vaccine sample collections); this group contained the largest proportion of nonresponders (Fig. 7j). Notably, consistent with

the preferential impact of belimumab on naive B cell activation and survival, all belimumab-treated patients failed to respond to the priming dose (Fig. 7f) and were characterized by

significantly reduced potency and breadth of neutralization (Fig. 7e and Extended Data Fig. 10j) upon subsequent dosing. Additionally, these patients showed significantly reduced magnitude

of memory antigen-specific B cell (Fig. 7f) and spike-specific cTFH (Fig. 7i) responses. DISCUSSION Clinical efficacy and immune correlates of mRNA vaccination have been amply tested in the

healthy population and in patients with cancer33,45 or solid organ transplantation46,47,48. In contrast, the humoral and cellular responses to these vaccines are poorly understood in

patients with SLE in whom both components can be compromised by the autoimmune disease itself and by multiple immunosuppressive treatments. Our study provides an in-depth antibody and

cellular analysis of a large cohort of patients with SLE, most of whom were of Black ancestry (_n_ = 79, 68% Black). Globally, patients with SLE showed reduced seroconversion rates and a

generalized reduction in ACE2-blocking activity that was uncoupled from anti-RBD IgG titers, suggesting some caution in assessing vaccine efficacy simply based on anti-spike/RBD titers. In

harmony with lower competitiveness, the neutralizing power and breadth of neutralization of the SLE plasma samples were significantly lower than those in the control group even after full

seroconversion. While the mechanistic basis of these qualitative antibody defects remains to be determined, we propose that these features could be explained by defective affinity

maturation, possibly due to aberrant GC activity and/or dominant extrafollicular activity49,50,51. This conclusion is supported by direct SPR measurements of lower avidity of the SLE

anti-spike antibodies. Notably, a slower decline in nAb titers observed after booster vaccination in patients with SLE, an opposite trend to the shorter durability of anti-spike memory B

cell responses, suggests that the lupus milieu may facilitate the generation of long-lived plasma cells and interfere with memory B cell formation. Overall, our study provides new insights

into the impact of abnormal B cell biology on mRNA vaccine responses. We had previously shown that, in Black patients with severe SLE, despite strong preexisting autoimmune memory, disease

flares are characterized by an influx of newly activated naive cells whose differentiation through an extrafollicular pathway generates a large fraction of the ASCs expanded during active

disease24,35. Those studies identified effector DN2 B cells downstream of activated naive B cells, epigenetically poised in SLE to differentiate into ASCs52. From the analysis of

antigen-specific anti-spike B cells, one notable result is the demonstration of the contribution of DN2 cells to both effector and memory responses. This finding indicates the limitations of

ascribing memory function based on phenotypic markers shared by effector cells, including loss of CD21 expression and positive expression of CD11c. Moreover, it strongly suggests the

ability of human extrafollicular responses to generate a separate memory cell compartment, a phenomenon already established in mice. In keeping with the accentuation of the extrafollicular

pathway in severe SLE and its potential contribution to a memory compartment, both components of extrafollicular responses previously described in SLE and severe COVID-19 infections23,25,

DN2 and DN3 cells, dominated the effector phase of the priming response and remained a large part of spike-specific B cells several months after booster vaccination in the absence of

intervening infection. In contrast, DN1 cells, presumed to represent early GC memory24, dominated normal responses across all vaccination time points. Of great interest, within the SLE

cohort, a high extrafollicular index score strongly correlated with lower antibody responses. Combined, our data are consistent with a model that predicts that extrafollicular B cell SLE

endotypes would promote decreased antibody responses with reduced neutralization activity presumably based on defective affinity maturation. Also indicative of the SLE milieu with high

levels of type II interferon in association with enhanced extrafollicular responses53, antigen-reactive B cells in patients with SLE were significantly enriched for CXCR3-bearing cells53.

Conversely, CCR6+ cells devoid of CXCR3 dominated the HD responses, a pattern that could promote an enhanced GC origin of memory cells in normal responses. In contrast, the SLE profile could

promote relocation of tissue CXCR3+ memory cells to sites of viral reinfection. In addition to disease-related determinants, the response to vaccination in SLE is also modulated by

treatment. Previous studies, restricted to antibody assessment, have predictably shown that B cell- and plasma cell-targeting agents used in the treatment of SLE can dampen antibody-mediated

responses and the global B cell pool33,45,54. Other immunomodulatory drugs, such as mycophenolate mofetil, have been shown to reduce vaccine efficacy in some vulnerable populations such as

patients with autoimmune rheumatic diseases16,17 or solid organ transplant recipients46,47. In our SLE cohort, we also observed reduced seroconversion associated with treatment with

mycophenolate mofetil. Yet, in contrast to findings in kidney transplant recipients, the second and third doses were able to rescue the initially deficient responses in these patients55.

This discrepancy can be due to both disease-specific features, the dose of mycophenolate mofetil administered and cotreatments with other potent immunosuppressive drugs. Notably, within the

SLE cohort, the most profound and persistent deficit in vaccine efficacy was observed in patients treated with belimumab, characterized by a reduction in de novo generation of anti-spike B

cells and spike-reactive cTFH cells. Combined, our data suggest that the role of BAFF in the generation of cTFH cells and in the affinity maturation of GC B cells could explain how belimumab

treatment results in poor antibody ACE2 competitiveness, neutralization and breadth potency56,57. Globally, the knowledge acquired in this study should form the basis for new strategies to

enhance the efficacy and durability of mRNA vaccinations, including modifications of vaccine dosing and timing and modulation of the magnitude and/or timing of the administration of

immunosuppressive agents. Our study has some limitations, as our cohorts were not perfectly sex- and race-matched due to the recruitment limitations imposed by the pandemic isolation

requirements and limited access to a broader population of HDs. Nevertheless, we believe that our results could contribute to the understanding of mRNA vaccine responses in general and in

particular in patients with autoimmune diseases and other immune conditions with underlying B cell defects or immunomodulating treatments. METHODS HUMAN PARTICIPANTS This research was

approved by the Emory University Institutional Review Board (Emory IRB nos. IRB000057983 and IRB000058515) and performed in accordance with all relevant guidelines and regulations. Blood

draws were obtained after acquiring written informed consent from the participants. Participants were compensated for their time and interest in the study. Healthy individuals (_n_ = 64) and

patients diagnosed with SLE (_n_ = 79) were recruited from Emory University Hospital, Emory University Hospital Midtown and Emory/Grady (all in Atlanta in the United States). The

demographics of the HD and SLE cohorts and the medications used by patients with SLE are listed in Supplementary Tables 1 and 2. Study data were collected and managed using the REDCap

electronic data capture tool (a secure web platform for building and managing online databases and surveys) hosted at Emory University. All individuals enrolled in this study were considered

naive to SARS-CoV-2 infections based on the absence of self-reported symptoms and/or negative PCR test results. All tested samples were screened for the absence of SARS-CoV-2

nucleocapsid-reactive IgG, and nucleocapsid-positive samples were excluded from the study (Extended Data Fig. 2a,b). PBMC ISOLATION AND SERUM AND PLASMA COLLECTION Peripheral blood samples

were collected in green-top (Vacutainer) sodium heparin tubes. Red-top tubes (Vacutainer) were centrifuged for 10 min at 800_g_ to collect the serum. Undiluted plasma was collected after

centrifugation of the blood for 10 min at 500_g_. Serum and plasma aliquots were stored at −20 °C. Next, blood samples were diluted (1:2) with PBS, and PBMCs were isolated by Ficoll density

gradient centrifugation at 1,000_g_ for 10 min. PBMCs were washed twice with R10 complete medium and lysed with ACK lysis buffer. Viability was assessed using trypan blue exclusion, and live

cells were counted using an automated hemocytometer. Frozen cells were stored at −80 °C in FBS/10% DMSO. FLOW CYTOMETRY PBMCs in frozen vials were thawed, washed and centrifuged at 800_g_

for 5 min and then resuspended in warm R10 complete medium at a final concentration of 20 × 106 cells per ml. Cell suspensions were divided into three parts to perform (1) AIM assays (~1 × 

106 cells), (2) B cell tetramer staining (~4 × 106–8 × 106 cells) and (3) T cell staining (~2 × 106–4 × 106 cells). A mixture of diluted antibodies was prepared in staining buffer (PBS/2%

FCS, 1 mM EDTA) supplemented with Super Bright Complete Staining Buffer and added to the samples in a 96-well round-bottom plate at a final volume of 50 μl per well. After each step,

antibody staining was blocked with a wash in staining buffer (~100 μl) and centrifugation of the plate at 800_g_ for 5 min. For the B cell immunophenotype, after incubation with the

tetramers for 1 h at 4 °C, cells were washed and stained with a mixture of anti-immunoglobulins (anti-IgD + anti-IgM + anti-IgA + anti-IgG) for ~15 min at room temperature (RT) in the dark.

The cells were then incubated with the cocktails of the remaining antibodies for ~40 min at RT in the dark. After washing and centrifugation, cells were stained with L/D Zombie NIR (diluted

at 1:500 in PBS) for 10 min at RT in the dark. Similarly, for the T cell immunophenotype, samples were stained with the antibody mixture for ~40 min at RT in the dark, and viable cells were

detected with L/D Zombie NIR. Cells were resuspended in ~180 μl staining buffer, kept on ice and immediately analyzed on a 5L Cytek Aurora flow cytometer using Cytek SpectroFlo software. The

extrafollicular score was determined by defining ‘normal’ population frequencies ±1 or ±2 s.d. and based on the average flow cytometry values for B DN1 cells, B DN2 cells,

plasmablasts/plasma cells, act cTFH cells and act TPH cells in the HD group, as shown in Extended Data Fig. 9e. The combined score was calculated giving a value of 1 for positivity of each

of the five variables tested for each donor and creating a sum of those positive values to reach a range of 0 (none of the cellular variables fit the extrafollicular score) to 5 (all

cellular variables fit the extrafollicular score) and intermediate values of 1–4, according to the sum. Flow cytometry data were analyzed using FlowJo v10.8.0. DETECTION OF TETRAMER-BINDING

B CELLS Antigen-specific B cells were detected using tetramer probes. Biotinylated spike and RBD proteins (R&D Systems) were multimerized with fluorescently labeled streptavidin (SA) for

1 h at 4 °C. Full-length spike protein was mixed with SA-BV421 using ~100 ng spike and ~20 ng SA for each sample (~4:1 molar ratio). RBD was mixed with SA-AF647 using ~25 ng RBD and ~12.5 

ng SA (~4:1 molar ratio). SA-PerCP was used as a decoy probe. After 1 h, all tetramers were mixed in free d-biotin (5 μM, Avidity) to minimize cross-reactivity. PBMCs were incubated for 1 h

at 4 °C with the mixture of tetramers, washed and stained with surface markers, and labeled for viability with L/D Zombie NIR (1:500) for ~10 min before being acquired with the 5L Aurora

(Cytek). AIM ASSAY AIM assay was performed as follows. Briefly, PBMCs were counted and adjusted to 20 × 106 cells per ml in complete medium (RPMI 1640/5% human AB serum supplemented with

GlutaMAX, nonessential amino acids, sodium pyruvate and penicillin–streptomycin). Antigen-specific T cell responses were assessed by incubating 1 × 106 cells with megapools of peptides

(15-mers overlapping by 11 aa) encompassing the sequences of human pathogens: SARS-CoV-2 WA.1 full spike (aa 5–1,273, Miltenyi Biotec) or HA (H1N1, strain swl A/California/04/2009, Miltenyi

Biotec). Cells were incubated in a 96-well U-bottom plate in a final volume of 200 μl. To detect extracellular CD40L expression, we preincubated cells with an anti-human CD40 antibody

(Miltenyi Biotec, pure functional grade, cat. no. 130-094-133) used at 0.5 μg ml−1 for 15 min at 37 °C before stimulation. Cells were then stimulated with each megapool of spike or HA (used

at 1 μg ml−1). Polyclonal stimulation of cells was performed with TCR triggering by staphylococcal enterotoxin B (1 μg ml−1) injection, and the stimulated cells were used as a positive

control. Unstimulated cells at the same density were incubated in complete medium and used as background signals for the quantification of AIM+ cells. Cells were stimulated for ~24 h before

washing and staining for flow cytometry. Cells were analyzed on a 5L Aurora flow cytometer (Cytek). Data in the graphs are shown as background-subtracted (control) values, and negative

values are shown as 0.003 in the log10-scale graphs. ELISA DETECTION OF HUMAN CORONAVIRUS (CCC) IGG To detect IgG antibodies to the four seasonal CCCs, we coated 96-well ELISA half-area

plates (Corning) overnight with 2 μg ml−1 recombinant spike protein from four separate human coronavirus strains (OC43, NL63, 229E and HKU1). Plates were blocked with PBS, 1% casein and 0.1%

Tween 20 for 30 min at RT. Serially diluted (at 1:3 fold) heat-inactivated serum or plasma samples were added for 2 h at RT. After four washes with DPBS/0.1% Tween 20 and 1× DPBS, goat

anti-human IgG-HRP was added to each well (1:5,000 dilution), and plates were incubated for 1 h at RT. Finally, signals were developed with ready-to-use tetramethylbenzidine solution and

stopped with stop solution. Plates were read at 450 nm, and raw optical density (OD) data were expressed as ‘endpoint titers’ using a cutoff value of 0.2. CARBODIIMIDE COUPLING OF

MICROSPHERES TO SARS-COV-2 ANTIGENS AND LUMINEX PROTEOMIC ASSAYS FOR MEASUREMENT OF ANTI-ANTIGEN ANTIBODY This analysis was carried out as previously described. Briefly, five SARS-CoV-2

proteins were coupled to MagPlex microspheres of different regions (Luminex). The nucleocapsid (cat. no. Z03480, expressed in _Escherichia coli_) and S1-RBD (cat. no. Z03483, expressed in

HEK293 cells) proteins were purchased from GenScript. The S1 domain (aa 16–685, cat. no. S1N-C52H2, expressed in HEK293 cells), S1-NTD (aa 13–303, cat. no. S1D-C52H6, expressed in HEK293

cells) and S2 domain (cat. no. S2N-C52H2, expressed in HEK293 cells) proteins were purchased from ACROBiosystems. Each protein was expressed with an N-terminal His6-tag to facilitate

purification (>85% purity) and appeared as a predominant single band on SDS–PAGE analysis. Coupling was carried out at 22 °C following standard carbodiimide coupling procedures. The

concentrations of coupled microspheres were confirmed using a Bio-Rad T20 cell counter. Approximately 50 μl of the mixture of coupled microspheres was added to each well of 96-well

clear-bottom black polystyrene microplates (Greiner Bio-One) at a concentration of 1,000 microspheres per region per well. All wash steps and dilutions were accomplished using 1% BSA/1× PBS

assay buffer. Serum samples were assayed at a 1:500 dilution and surveyed for antibodies to the nucleocapsid, S1, S2, NTD and RBD proteins. After incubation for 1 h in the dark on a plate

shaker at 800 rpm, the wells were washed five times with 100 μl assay buffer using a BioTek 405 TS plate washer and then applied with 3 μg ml−1 PE-conjugated goat anti-human IgA, IgG and/or

IgM (Southern Biotech). After 30 min of incubation at 800 rpm in the dark, the wells were washed three times with 100 μl assay buffer, resuspended in 100 μl assay buffer and analyzed using a

Luminex FLEXMAP 3D instrument (Luminex) running xPONENT 4.3 software at an enhanced photomultiplier tube setting. The MFI using combined or individual detection antibodies (anti-IgA,

anti-IgG or anti-IgM) was measured using the Luminex xPONENT software. The background value of the assay buffer was subtracted from each serum sample result to obtain the net MFI (MFI minus

background) value. RBD COMPETITIVE ELISA ELISA plates (96-well half-area, Corning, #3690) were precoated overnight with 2 μg ml−1 recombinant human ACE2 in PBS at 4 °C. The plates were

blocked with 1% casein for 30 min at 37 °C. Serially diluted plasma and serum samples were mixed with RBD mouse Fc-tagged antigen (Sino Biological, final concentration 20 ng ml−1) for 30 min

at 37 °C, and the mixture was then added to the plates for 30 min at 37 °C. The plates were washed with PBS/0.1% Tween 20, and RBD binding was revealed using secondary goat anti-mouse IgG

(Southern Biotech, #1031-05, 1:5,000 in PBS). The plates were incubated for 30 min at 25 °C; after washing, 40 μl tetramethylbenzidine substrate was added, and developed plates were blocked

with 40 μl stop solution and read at 405 nm with an ELISA reader. The percentage of inhibition was calculated as follows: (1 − (OD sample − OD negative control)/(OD positive control − OD

negative control)) × 100. PSEUDOVIRAL IN VITRO NEUTRALIZATION ASSAY Neutralization activities against the SARS-CoV-2 wild-type (WA.1), Delta (B.1.617.2) and Omicron BA.1 strains were

measured in a single round of infection assay with pseudoviruses, as previously described. Briefly, for the production of the SARS-CoV-2 wild-type, Delta and Omicron pseudoviruses, an

expression plasmid bearing codon-optimized SARS-CoV-2 full-length spike plasmid (parental sequence Wuhan-1, GenBank accession no. MN908947.3) was cotransfected into HEK293T cells (ATCC,

#CRL-11268) with plasmids encoding nonsurface proteins for lentivirus production and a lentiviral backbone plasmid expressing a Luciferase-IRES-ZsGreen reporter, HIV-1 Tat and Rev packing

plasmids (BEI Resources, NR-53818) and pseudoviruses harvested 48 h after transfection; then, titration was performed. Pseudoviruses were mixed with serial dilutions (1:50 to 1:328,050) of

plasma, incubated for 1 h for the reaction at 37 °C in a 5% CO2 incubator and then added to monolayers of ACE2-overexpressing 293T cells (BEI Resources, NR-52511) in duplicate. Forty-eight

hours after infection, cells were lysed, luciferase was activated with the Luciferase Assay System (Bright-Glo, Promega), and the amount of light produced (in relative light units) was

measured on a synergy Biotek reader. Statistical analysis was performed using GraphPad Prism 9.0 for the determination of ID50 (median infectious dose) values through a dose–response curve

fit with nonlinear regression. SPR ANALYSIS OF ANTIBODY BINDING KINETICS TO SARS-COV-2 SPIKE PROTEINS The steady-state equilibrium binding of post-SARS-CoV-2-vaccinated human polyclonal

samples was monitored at 25 °C using a ProteOn SPR system (Bio-Rad). The purified recombinant SARS-CoV-2 spike RBD protein was captured to a GLC sensor chip with 300 resonance units (RU) in

the test flow channels. Serial dilutions (10-, 50- and 250-fold) of freshly prepared samples in BSA–PBST buffer (PBS pH 7.4 with Tween 20 and BSA) were injected at a flow rate of 50 µl min−1

(contact duration 240 s) for association, and disassociation was performed over a 1,200-s interval. Responses from the protein surface were corrected for the response from a mock surface

and for responses from a buffer-only injection. All SPR experiments were performed twice. In these optimized SPR conditions, the variation for each sample in duplicate SPR runs was <7%.

Antibody off-rate constants, which describe the stability of the antigen–antibody complex (that is, the fraction of complexes that decays per second in the dissociation phase), were

determined directly from the interaction of human polyclonal samples with recombinant purified SARS-CoV-2 RBD protein using SPR in the dissociation phase only for sensorgrams with maximum RU

in the range of 10–150 RU and calculated using the Bio-Rad ProteOn manager software for the heterogeneous sample model as previously described. Off-rate constants were determined from two

independent SPR runs. UNSUPERVISED FLOW CYTOMETRY DATA ANALYSIS For high-dimensional visualization of B and T cell flow cytometry data, PBMC samples were downsampled to 200,000 spike++ B

cell and 30,000 AIM+ T cell events. PaCMAP was performed on the samples in https://www.omiq.ai. Unsupervised clustering of PaCMAP populations was done using FlowSOM. Following the initial

quality control exclusion, PBMC samples were used to generate the respective PaCMAP plots. Comparisons of the resulting cluster frequencies were done using the EdgeR plug-in function. PCA

plots were generated in R v3.6.2 (released on 12 December 2019) using the ‘ggbiplot’ library. Custom plotting was performed using the ‘ggplot2’ library for base analysis, and plots were

postprocessed in Adobe Illustrator. Bubble plots were generated in R v4.3.3 (released on 29 February 2024) using the ‘ggplot2’ and ‘dplyr’ libraries. HALF-LIFE AND DURABILITY ANALYSIS Immune

responses, starting 42 days after the second and third mRNA vaccinations, were analyzed using linear mixed-effect models with the log immune response as the dependent variable and time as

the independent variable. Models for patients with SLE, HDs and combined donors included population-level fixed effects and individual-level random intercepts. Statistical significance of

fixed-effect coefficients was assessed using the Wald test. Those with a maximum response less than or equal to the 95th percentile of the baseline and prepandemic samples and data

associated with unexpected greater than twofold increases in NTD IgG were excluded. Models were fit using the lmer function from the lme4 package and the R programming language. STATISTICAL

ANALYSIS Statistical analysis was carried out using Prism v.9.5.1, v.10.2.2 and v10.0.3 (GraphPad Software). For each experiment, the type of statistical testing, summary statistics and

levels of significance can be found in the figures and corresponding legends. Levels of significance are indicated as follows: _*P_ < 0.05, **_P_ < 0.01, ***_P_ < 0.001 and ****_P_ 

< 0.0001. REPORTING SUMMARY Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. DATA AVAILABILITY The flow cytometry

dataset is available upon request from the corresponding author. CHANGE HISTORY * _ 02 DECEMBER 2024 A Correction to this paper has been published: https://doi.org/10.1038/s41590-024-02045-y

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references ACKNOWLEDGEMENTS We thank all the donors for their generosity in participating in this research and making this study possible. We thank the nurses, staff and providers in the

Emory Clinics and Hospitals in Atlanta, GA. We also thank the members of the Sanz and Lee laboratories for helpful discussions. We would also like to thank the Sanz/Lee clinical coordination

and sample processing teams for sample identification, scheduling and collection. We thank K.S. Bonham for helpful discussions on biostatistical analyses. Finally, we would like to thank D.

Corti, L. Piccoli and J. Bassi for helping with the delineation of the ELISA blocking protocol. This work was supported by the National Institutes of Health grants U54-762 CA260563-01 Emory

SeroNet (I.S., F.E.-H.L.) and U19-AI110483 Emory Autoimmunity Center of Excellence (I.S.). The SPR-based antibody measurement was supported by the Food and Drug Administration’s Perinatal

Health Center of Excellence (PHCE) project grants #GCBER005 and #GCBER008 to S.K. The content of this publication does not necessarily reflect the views or policies of the Department of

Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the US government. Opinions, interpretations, conclusions and

recommendations are those of the authors and are not necessarily endorsed by the US government. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Medicine, Division of

Rheumatology, Lowance Center for Human Immunology, Emory University, Atlanta, GA, USA Caterina E. Faliti, Trinh T. P. Van, Fabliha A. Anam, Sabeena Y. Usman, Matthew C. Woodruff, Daniel

Sanz, Midushi Ghimire, Weirong Chen, Jennifer Hom, Christopher M. Tipton, Eliver Ghosn, Arezou Khosroshahi & Ignacio Sanz * Emory Autoimmunity Center of Excellence, Emory University,

Atlanta, GA, USA Caterina E. Faliti, Trinh T. P. Van, Fabliha A. Anam, Sabeena Y. Usman, Matthew C. Woodruff, Daniel Sanz, Midushi Ghimire, Weirong Chen, Jennifer Hom, Christopher M. Tipton,

 Arezou Khosroshahi & Ignacio Sanz * Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA Narayanaiah Cheedarla, Suneethamma Cheedarla, 

Andrew S. Neish & John D. Roback * Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, USA M. Elliott Williams & Christopher D. Scharer *

Division of Viral Products, Center for Biologics Evaluation and Research (CBER), Food and Drug Administration, Silver Spring, MD, USA Ashish Kumar Mishra & Surender Khurana * Dotmatics,

Inc., Boston, MA, USA Geoff Kraker * Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University, Atlanta, GA, USA Martin C. Runnstrom, Shuya

Kyu, Andrea Morrison-Porter, Hannah Quehl, Natalie S. Haddad & F. Eun-Hyung Lee * Department of Biology, Emory University, Atlanta, GA, USA Hasan Ahmed & Rustom Antia * MicroB-plex,

Inc., Atlanta, GA, USA Natalie S. Haddad * BioMed X Institute, Heidelberg, Germany John M. Lindner Authors * Caterina E. Faliti View author publications You can also search for this author

inPubMed Google Scholar * Trinh T. P. Van View author publications You can also search for this author inPubMed Google Scholar * Fabliha A. Anam View author publications You can also search

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inPubMed Google Scholar * Ignacio Sanz View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS C.E.F. and I.S. conceived and directed the study.

C.E.F. processed samples and performed most of the experiments and data analyses. T.T.P.V. helped in performing flow cytometry, 10X Genomics single-cell RNA sequencing and sample

organization. T.T.P.V. and M.G. helped in running ELISA. C.E.F. and M.G. generated some figure representations with R. M.C.W. performed PCA. H.A. performed between-cohort comparisons of the

half-life and durability of antibody- and cellular-mediated fold-change responses. M.C.R. and F.E.-H.L. provided data from healthy controls tested for viral antigens. N.C. and S.C. performed

pseudoviral in vitro tests with plasma samples. F.A.A., N.S.H., A.M.-P. and H.Q. performed serum Luminex screening against viral antigens. A.K.M. and K.S. performed SPR experiments. J.M.L.,

C.M.T., J.H., M.E.W. and C.D.S. assisted with B cell analyses. G.K. and E.G. helped with unsupervised analyses. S.Y.U. and A.K. conducted chart review, identified patient samples for study

inclusion and provided donors’ information. D.S., S.K. and F.E.-H.L. coordinated the processing of samples from healthy donors and the biobank repository. W.C., A.S.N., J.D.R. and R.A.

participated in manuscript review. C.E.F. and I.S. wrote the manuscript, with all authors providing input and editorial support. CORRESPONDING AUTHOR Correspondence to Ignacio Sanz. ETHICS

DECLARATIONS COMPETING INTERESTS F.E.-H.L. is the founder of MicroB-plex, Inc., and has research grants with Genentech. I.S. has research grants with Glaxo Smith Kline. The other authors

declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Immunology_ thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer

reports are available. Primary Handling Editor: L.A. Dempsey, in collaboration with the _Nature Immunology_ team. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with

regard to jurisdictional claims in published maps and institutional affiliations. EXTENDED DATA EXTENDED DATA FIG. 1 STUDY COHORTS’ SAMPLES AND TIMELINE OF SAMPLES’ COLLECTION. A, Study

design, vaccine administration scheme, and time points collected after SARS-CoV-2 mRNA vaccination for healthy controls and patients with SLE. B, Diagrams showing the longitudinal collection

of blood draws from HD and SLE enrolled in the study (circles) and pre-pandemic controls (Pre-CoV, squares). The SLE cohort is grouped for the main treatment by colored circles: Untreated

(none, black), Hydroxychloroquine (HCQ, yellow), Azathioprine (AZA, red), Methotrexate (MTX, dark red), Mycophenolate Mofetil (MMF, dark blue), Belimumab (BLM, turquoise). EXTENDED DATA FIG.

2 HIGH-DIMENSIONAL FLOW CYTOMETRY CHARACTERIZATION OF B AND T CELLS. A, Representative gating strategy for the quantification of CD19+ B cells, their subsets, and tetramer-based reactivity

detection for spike and RBD by flow cytometry. B, Representative gating strategy for quantification of CD3+ T cells, and their CD4s and CD8s populations and subsets by flow cytometry.

EXTENDED DATA FIG. 3 DETECTION OF CIRCULATING ANTIGEN-SPECIFIC IGS ANTIBODIES UPON VACCINATION. A, Cartoon showing the Luminex bead-based assay. B, Nucleocapsid IgG threshold used to define

SARS-CoV-2 negative samples. Each dot represents a sample tested. Boxplots represent min to max and show all points. Statistics was calculated with non-parametric Kruskal-Wallis with Dunn’s

multiple comparisons C, IgM and D, IgA reactivity to the SARS-CoV-2 proteins NTD, S2, S1 and RBD and percentage of responders in HD and SLE. Each dot represents a sample tested. Negative

values are based on MFI values of time 0 (T0) from pre-pandemic and vaccine baseline samples, and are indicated below the gray area. Percentage of positive responders above the gray area is

shown as a numberical value above each tested time-point E, Kinetics analyses for IgG binding to S1, RBD, S2, and NTD proteins by Luminex assay. Overlay of geometric mean and pie charts

showing the proportion of negative, low, medium, or high values. Statistics of the geomean between HD and SLE were performed with two-sided U Mann Whitney for comparison of each indicated

time. Pie chart comparison statistics performed with Chi-square with Fisher test analysis. F, ELISA detection of IgG reactive to beta-common cold coronaviruses (beta-CoV) HKU-1 and OC43 and

alpha-common cold coronaviruses (alpha-CoV) NL63 and 229E, tested with sera from pre-vaccinated (baseline) donors enrolled in the study. Boxplots represent median with interquartile range,

and whiskers indicate range. Each dot represents a tested sera sample from n = 8 HD and n = 9 SLE at baseline. Statistical comparison was performed with unpaired t-test. Not significant, ns

p > 0.05; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. EXTENDED DATA FIG. 4 DETECTION OF CIRCULATING NEUTRALIZING IGS UPON VACCINATION AND QUANTITATION OF ANTI-SPIKE B

CELLS. A, Cartoon showing the steps of pseudoviral _in vitro_ neutralization assay. B, NT50 values detected from HD and SLE plasma and comparison of all viral strains for each sample. Fold

changes show the difference between Delta and Omicron compared to the WT values. C, Circulating CD19+ B cells frequency comparison in our cohorts. D, Correlation of CD19+ frequency and spike

reactive B cells in HD and SLE for each vaccine time point. Blue lines show the range observed in the HD. Pearson analysis was performed for each comparison. Quantification of total (E)

spike-specific and (F) RBD-specific B cells shown as the frequency of viable lymphocytes in the HD and SLE cohorts. Each dot represents an individual sample tested at baseline (d0) and after

receiving one (Vax 1), two (Vax 2), or three (Vax 3) vaccine doses. Pie charts comparisons and Chi-square with Fisher’s test are shown. When indicated, LOD=limit of detection set to

logarithmic 0.001 for B cells and 0.003 for T cells. LOS=limit of sensitivity, based on median values of baseline + 2 x SD. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

EXTENDED DATA FIG. 5 IMMUNITY TO THE FOUR SEASONAL CCCS. A, Representative gating strategy to score the frequency of Spike-reactive B cells and their binding to the four CCCs Spikes and

cross-reactivity with WA.1 Spike by flow cytometry. B, Quantitation of CCCs cross-reactive memory B cells with WA.1 reactive Spike B cells from PBMC samples collected during mRNA vaccination

(Vax 1 + 2 + 3). C, Quantitation of CCCs cross-reactive memory B cells with WA.1 reactive Spike CD27+ Bmem cells from PBMC samples collected during mRNA vaccination (Vax 1 + 2 + 3). SLE

patients treated with Belimumab (SLE/BLM) are shown in teal color. Each dot represents an individual sample. Statistical comparison performed with unpaired, two-sided Mann-Whitney U test.

Not significant, ns p > 0.05; *p < 0.05. EXTENDED DATA FIG. 6 UNSUPERVISED PACMAP AND FLOWSOM ANALYSIS OF ANTI-SPIKE B AND QUANTITATION OF SURFACE IGM, IGA AND IGG EXPRESSION. A,

Spike++ B cells, EdgeR comparison and significance of low vs high represented clusters in SLE vs HD. B, Frequency of DN2 (left graph) and Spike++ DN2 B cells (right graph) from all subjects

enrolled in the study, divided by race (AA/Black vs others). Each dot represents an individual sample. For the DN2, horizontal lines are means and statistics was calculated with

Kruskal-Wallis with Dunn’s multiple comparisons. For the Spike++ DN2, horizontal lines are medians and statistics was calculated with Unpaired T test. C, Representative flow detection of Ig

surface expression on B cells. D, Distribution of IgM, IgG and IgA and Chi-square (Fisher) comparison. Frequency of membrane-bound E, IgM, F, IgA and G, IgG in HD and SLE spike+ B cells

showed for each vaccine time point as shown in (D). Each dot represents an individual sample. The overlay of the median signals for HD and SLE is shown for each Ig tested. One-way ANOVA test

is shown within the HD or SLE groups. Not significant, ns p > 0.05; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. EXTENDED DATA FIG. 7 UNSUPERVISED PACMAP AND FLOWSOM

ANALYSIS OF ANTI-SPIKE T CELLS AND AIM ASSAY. A, Cartoon showing the AIM assay. B, Representative flow plots and gating strategies used to define AIM+ T cells and their differentiation. C-E

Overlay graphs showing the geometric mean values of the groups are shown for C, AIM+ CD8, D, AIM+ CD4 and E, AIM+ Tfh. Below each graph, the pie charts represent the proportion of negative

and positive responders at each indicated time-point. Vax time points in the figures (c-e) indicate the following binned Time-Points (T) and as indicated in the Extended Data Fig. 1a: 0 (T0,

baseline), 1 (T1-3), 2 (T4-5), 3 (T6-7), 4 (T8-9), 5 (B1-5) and 6 (B6-9). The Chi-Square test was performed to define significance in c, d and e. F, Spike++ AIM+ CD8 T cells, EdgeR

comparison and significance of low vs high represented clusters in SLE vs HD. G, Spike++ AIM+ CD4 T cells, EdgeR comparison and significance of low vs high represented clusters in SLE vs HD.

EdgeR comparisons and significance (expressed as FDR) was generated with ‘omiq.ai’. All cluster’s names were compiled by using the surface markers’ expression as indicated in the relative

heatmap. Not significant, ns p > 0.05; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. EXTENDED DATA FIG. 8 ANALYSIS OF ANTIGEN-SPECIFIC T CELL RESPONSES TO SPIKE AND HA

PROTEINS. A, Frequency of AIM+ cTfh17 upon Vax1, 2 or 3. Each dot represents an individual sample collected at the indicated time-points. Boxplots represent min to max and show all points.

Sample from HD (Vax1, n = 18; Vax2, n = 49; Vax3, n = 47) and SLE (Vax1, n = 18; Vax2, n = 67;Vax3, n = 34). B, Reactivity towards the HA MP for all tested samples, and comparison of HD and

SLE. C, Differentiation of AIM+ HA T cells based on CD45RA and CCR7 expression. Not significant, ns p > 0.05; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. EXTENDED

DATA FIG. 9 CLINICAL, DEMOGRAPHICS, AND IMMUNOLOGICAL FEATURES CHARACTERIZING OUR TWO COHORTS OF VACCINATED HD AND SLE. A, Frequency of DN1, DN2, PB/PC, act cTfh and act Tph used to create

the EF score and unpaired, Mann-Whitney U test shown for significance between HD and SLE cohorts. B, Age and race showing the distribution in HD and SLE based on vaccine responsiveness

(negative/low VNL, medium VM, or high VH). C, Distribution of females (F) and males (M) in our cohorts, based on vaccine responsiveness (negative/low VNL, medium VM, or high VH). D, Number

of subjects within each group based on age and vaccine responses clustered by age (18-50, >50 years old, yo). Each dot represents an individual sample collected at the indicated

time-points. Numbers of samples tested (n = ) are indicated in the figure. Boxplots represent min to max and show all points. E, Vaccine responsiveness based on sex (M/F) in our two cohorts.

F, AIM+ CD8 and G, AIM+ CD8 frequencies and percentage of non-responders identified for each vaccine group of VNL, VM, and VH. When indicated, LOD = limit of detection set to logarithmic

0.003 for T cells. LOS = limit of sensitivity, based on median values of baseline + 2 x SD. ****p < 0.0001. EXTENDED DATA FIG. 10 IMMUNOPHENOTYPE OF VACCINATED SLE CATEGORIZED BY

TREATMENT. A, Variance plot driving the PCA analyses. B, Simple cartoon showing lupus-associated drugs targeting B cells and table showing the main group of SLE divided by treatment as

analyzed in this study. C-H, Representative high-dimensional flow cytometry characterization of B cell in HD and SLE groups showing the comparison of C, CD19+ D, Naïve B cells, activated

Naïve (aN) B cell, Transitional B cells (Btr) and CD21lo Btr. E, CD27+ conventional memory. F, DN B cells and subsets; ratio of DN2:DN1 expressed as log2 value. G, IgD- ASC and CD20−CD38hi

PC. H, cTfh. SLE sub-group frequency of each population is compared to the HD group for statistical significance. When indicated in the graph, the gray line is a threshold for normal range

below (that is, CD19, DN1, cTfh) or above (that is, DN2, ASC, PC) the HD calculated average ranges. I, SELENA-SLEDAI score, comparison of sub-group of SLE by treatments. Statistical

comparisons performed with unpaired, two-sided Mann-Whitney U test. J, NT50 values for Delta and Omicron neutralization observed in HD and sub-groups of SLE. K, Relative frequency of spike

reactive B cell populations for all subjects from HD and SLE sub-groups based on CD27 and IgD expression. L, Symbol (one per column) with geometric mean values with 95% CI shown for spike

reactive CD8 and CD4 within all the SLE sub-groups and HD enrolled in the study. Boxplots represent mean and whiskers indicate range. Statistical comparison between HD and SLE sub-groups per

each vaccine dose performed with unpaired, Mann-Whitney U test. Not significant, ns p > 0.05; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION Supplementary Tables Supplementary Table 1. Cohort characteristics. Supplementary Table 2. Medications of vaccinated patients with SLE. REPORTING SUMMARY PEER

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Faliti, C.E., Van, T.T.P., Anam, F.A. _et al._ Disease-associated B cells and immune endotypes shape adaptive immune responses to SARS-CoV-2 mRNA vaccination in human SLE. _Nat Immunol_ 26,

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