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TM9SF1 expression correlates with autoimmune disease activity and regulates antibody production through mTOR-dependent autophagy

BMC Medicine volume 22, Article number: 502 (2024) Cite this article

Abstract

Background

Transmembrane 9 superfamily member 1 (TM9SF1) is involved in inflammation. Since both inflammatory and autoimmune diseases are linked to immune cells regulation, this study investigated the association between TM9SF1 expression and autoimmune disease activity. As B cell differentiation and autoantibody production exacerbate autoimmune disease, the signaling pathways involved in these processes were explored.

Methods

Tm9sf1−/− mouse rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) models were used to verify the relationship between gene expression and disease severity. Peripheral blood mononuclear cells (PBMCs) from 156 RA and 145 SLE patients were used to explore the relationship between TM9SF1 expression and disease activity. The effectiveness of TM9SF1 as a predictor of disease activity was assessed using multiple logistic regression and receiver operating characteristic (ROC) curves. The signaling pathways regulated by TM9SF1 in B cell maturation and antibody production were conducted by plasma cell induction experiment in vitro.

Results

The Tm9sf1−/− RA and SLE model mice produced fewer autoantibodies and showed reduced disease severity relative to wild-type (WT) mice. TM9SF1 levels in PBMCs of patients were higher than those in healthy controls, and were reduced in patients with low disease activity relative to those with active RA and SLE. Furthermore, TM9SF1 levels were positively linked with autoantibody titers and pro-inflammatory cytokine levels in both diseases. ROC analyses indicated TM9SF1 outperformed several important clinical indicators in predicting disease activity (area under the curve (AUC) were 0.858 and 0.876 for RA and SLE, respectively). In vitro experiments demonstrated that Tm9sf1 knockout blocked differentiation of B cells into antibody-producing plasma cells by activating mTOR and inhibiting autophagy, and mTOR inhibitors such as rapamycin could reverse this effect.

Conclusions

The primary finding was the identification of the molecular mechanism underlying autophagy regulation in B cells, in which Tm9sf1 knockout was found to modulate mTOR-dependent autophagy to block B cell differentiation into antibody-secreting plasma cells. It was also found that TM9SF1 expression level in PBMCs was an accurate indicator of disease activity in patients with RA and SLE, suggesting its clinical potential for monitoring disease activity in these patients.

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Background

Autoimmune disease involves cells of both the innate and adaptive immune systems, including T and B lymphocytes, macrophages, natural killer cells, and neutrophils [1, 2]. B cell hyperactivity and autoantibody generation are prominent features of several autoimmune diseases, including rheumatoid arthritis (RA) [3] and systemic lupus erythematosus (SLE) [4]. These antibodies bind to tissue-associated antigens, generating immune complexes (ICs) which are subsequently deposited in the joints, kidneys, and other tissues [5, 6]. The ICs are responsible for complement activation and membrane attack complex (MAC) formation, both of which can drive organ and tissue inflammation and injury [7]. The clinical course of SLE and RA includes a persistent period of low disease activity and intermittent acute exacerbation periods [8, 9]. Genes related to the differentiation of B cells into plasma cells may be important in distinguishing the different disease stages, considering the essential roles played by autoantibodies in the pathophysiology of RA and SLE.

Transmembrane 9 superfamily member 1 (TM9SF1) was first cloned in 1997 [10]. TM9SF1 is associated with the autophagy-related proteins LC3 and LC3-II, and silencing of TM9SF1 was found to reduce autophagy [11]. It has been proposed that TM9SF1 is an autophagy-related biomarker which is upregulated in tumors [12,13,14], but the exact molecular mechanisms by which TM9SF1 regulates autophagy are currently unclear. Marked upregulation of TM9SF1 has also been observed in a range of vascular tissues, possibly related to immune function and inflammatory activity. Using a proteomic approach, Wang et al. showed that TM9SF1 levels were increased 8.6-fold in pooled intracranial aneurysm samples from 14 patients as compared to matched tissue samples from the superficial temporal artery [15]. Through RNA-Seq and qPCR approaches, Zhang et al. further showed the presence of significant TM9SF1 upregulation in varicose vein samples from three patients with varicocele infertility compared with proximal healthy veins [16]. Studies of the TM9SF family in Dictyostelium, Drosophila, and zebrafish have suggested that TM9SF1 functions as a regulator of immune functionality [17], and we demonstrated that TM9SF1 serves as a major regulator of immunomodulatory and inflammatory processes [18]. Specifically, increases in Tm9sf1 mRNA levels were evident in mouse lungs 24 h after lipopolysaccharide (LPS)-induced pulmonary inflammation, while lung inflammation was reduced by Tm9sf1 knockout(18).

Since both inflammatory reactions and autoimmune diseases involve regulating the activity of various immune cells [19], we further investigated whether TM9SF1 expression is increased in autoimmune disease, together with changes in expression patterns between the phases of active and low disease activity in patients. Tm9sf1−/− mouse models of both RA and SLE were first established to assess the impact of Tm9sf1 deficiency on autoantibody production and disease activity. Patients with RA and SLE were recruited to determine TM9SF1 expression levels in peripheral blood mononuclear cells (PBMCs) (including T and B lymphocytes, monocytes and natural killer cells). The expression of the gene was compared between active and low disease activity stages, and its association with autoantibody levels was assessed. While these findings suggested that TM9SF1 is involved in immune-related processes, the mechanisms responsible for immunomodulation are complex and it is possible that TM9SF1 may play distinct roles associated with different pathways in various immune cells. Data from databases showed that TM9SF1 expression was markedly higher in plasma cells relative to B cells and B cells were thus selected for in vitro evaluation of the role and potential mechanisms associated with TM9SF1 in the differentiation of B cells into plasma cells.

Methods

Reagents and antibodies

Purified azide-free goat anti-mouse IgM (μ chain) was obtained from BioLegend (157,102). Leinco (C2825) provided the purified in vivo GOLD™ Functional Grade anti-mouse CD40 (Clone FGK45). Mouse interleukin (IL)-21 recombinant was from Novoprotein (CK10), while LPS (L8880) was from Biolegend Solarbio (China), the Foxp3/Transcription Factor Staining Buffer Set (00–5523-00) was from eBioscience and Fixable Viability Dye eFluor™ 506 (65–0866-14) was obtained from Invitrogen.

Antibodies from BioLegend included mouse antibodies against PE-Blimp-1 (150,005), FITC-CD21/CD35 (CR2/CR1) (123,407), PE-CD23 (101,607), APC IgM (406,509), PE/Cyanine7 CD19 (152,418), FITC-CD3 (100,203), Brilliant Violet 605-CD138 (142,515), PerCP-IgD (405,735), PerCP-CD4 (100,432), APC/Cyanine7-CD8 (140,422), and APC-F4/80 (123,115), as well as Brilliant Violet 421-anti-mouse/human CD11b (101,251), FITC- CD25 (101,907), PerCP-CD69 (104,520), APC-CD86 (105,011), FITC-anti-mouse/human CD45R/B220 (103,205), and PE-CD138 (142,503).

Study participants

A total of 156 patients defined with RA based on the 2010 American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) classification criteria, and 145 cases defined with SLE as per the 2019 ACR/EULAR classification criteria were enrolled [20, 21]. Patients were recruited between August 2022 and July 2023 when they were treated at Xiangyang Central Hospital, and showed active-stage disease. Samples and data were also obtained from 41 RA and 37 SLE patients during the low disease activity stage. The clinical activity of RA was defined using the Disease Activity Score 28-joint count erythrocyte sedimentation rate (DAS28-ESR), with a cut-off of 5.1 [22]. Clinically active SLE was defined by an SLE Disease Activity Index (SLEDAI)-2 K score greater than 6, whereas low disease activity was defined as an SLEDAI-2 K score of 4 or lower, following the lupus low level disease activity state (LLDAS) criteria [23, 24].

Participants were excluded if they (1) had been defined with other autoimmune disease types (including systemic sclerosis, connective tissue diseases, Sjogren's syndrome, and dermatomyositis), (2) acquired glucocorticoid or immunosuppressive therapies within one month prior to this admission, or (3) had insufficient information regarding their age, sex, or key clinical test results.

Furthermore, 39 healthy control (HC) individuals, matched in age and sex with the RA and SLE groups, were recruited from the hospital's Physical Examination Center. The Hubei University of Arts and Science Ethics Committee approved all experiments, ensuring that the Declaration of Helsinki's principles were strictly followed during the analysis. All participants provided written informed consent.

Clinical analyses

Levels of white blood cells (WBCs), IgA, IgM, IgG, ESR, anti-cyclic citrullinated peptide (anti-CCP), rheumatoid factor (RF), C-reactive protein (CRP), anti-double-stranded DNA (anti-dsDNA), and anti-Smith (anti-Sm) were measured in the clinical laboratory and were used in the basic clinical data for the RA and SLE cases analyzed. The levels of IgA, IgG, IgM, and RF were measured on an IMMAGE800 instrument (Beckman Coulter, CA, USA). Anti-CCP levels were measured using indirect immunofluorescence with a Sprinter XL system (Euroimmun, Lubeck, Germany), CRP levels were evaluated with i-CHROMA (Chuncheon, BodiTech Med, Korea), WBC with a Sysmex XE-2100 (TOA Medical Electronics, Kobe, Japan), and ESR was measured with a Vacuette ESR System (Greiner Bio-One GmbH, Frickenhausen, Germany). The RA DAS28 values were estimated to approximate disease severity, while SLEDAI scores were used to assess SLE severity as described previously [22,23,24].

Follow-up

Without interfering with the enrolled patients’ medical decisions, patient data were tracked and documented from admission to discharge. In this investigation, hospitalized patients classified as having SLE and RA were monitored. Information on medication included treatment with glucocorticoids, such as prednisone acetate, together with immunosuppressive treatment for RA (leflunomide, tofacitinib, and methotrexate) and SLE patients (cyclosporin, cyclophosphamide, mycophenolate mofetil, tacrolimus, azathioprine, methotrexate, and leflunomide). After discharge, patients were followed up until the end of the study (January 31, 2024) or until they were lost to follow-up. Patients with low disease activity during follow-up were followed up every 3 months, while those showing increased disease activity were assessed once per month. Data regarding the disease, such as disease activity, drug side effects (including bone marrow suppresion and liver damage), and therapy adjustments, were collected.

qPCR

Following standard blood count tests, the remaining blood was analyzed further. PBMCs were isolated from 2 mL of blood using a lymphocyte separation medium (P8610)(Beijing Solarbio Science & Technology, China). The separated cells were then frozen at -80 °C before extraction of RNA with 1 mL of TRIzol reagent (269,212, Ambion, USA). The extracted RNA was reverse-transcribed to cDNA using an iScript cDNA Synthesis Kit (Bio-Rad, 1,708,891), according to the provided instructions. The RNA extraction process, as well as the subsequent qPCR procedures, were undertaken based on the established protocols from prior studies [18, 25]. The cDNA was amplified using iTaq Universal SYBR Green Supermix (Bio-Rad, 1,725,122) on an ABI7500 PCR system. The reaction volume (20 μL) contained diluted cDNA (3.0 μL), forward and reverse primers (10 μM each, 1.0 μL each), SYBR Green Supermix (10 μL), and DEPC water (5 μL). The amplification conditions were 95 ℃ for 5 min; 95 ℃ for 40 cycles of 10 s, and 60 ℃ for 20 s. Ct values for each gene were read through the ABI7500 system. GAPDH was used as a reference when calculating the gene mRNA expression level using the 2−ΔΔCt method [26] (Additional File 1: Table S1).

Analysis of TM9SF1 expression patterns

Information on TM9SF1 expression was obtained from the Human Protein Atlas (https://www.proteinatlas.org/). Proteinatlas.org/ENSG00000100926-TM9SF1/single + cell + type provided information on TM9SF1 expression patterns in human-derived cells, bone marrow, and spleen tissues.

Animals, cell culture, and IgM detection

The study used matched wild-type (WT) mice and six-week-old female Tm9sf1 knockout (Tm9sf1−/−) C57BL/6 mice produced using a CRISPR/Cas9 technique. The genotyping of the animals was performed as previously described [18]. The Animal Ethics Committee of Hubei University of Arts and Science authorized all protocols and procedures used in the experiments.

mRNA and protein expression of Tm9sf1 in B cells treated with 10 µg/mL LPS for predetermined durations was assessed by qPCR and Western blotting, respectively. After four days of stimulation with 10 µg/mL LPS + 5 nM rapamycin (IR0010, Solarbio, China), the expression of autophagy-related proteins was evaluated by Western blotting. An ELISA kit (Nanjing Kamiluo, China) was utilized for measuring IgM levels in cell culture supernatants. All measurements were performed in triplicate.

Cell sorting and flow cytometry (FCM) analyses

Splenocytes were obtained from six-week-old female Tm9sf1−/− and WT mice. The cells stained with an anti-CD19 antibody and sorted using a FACS machine (BD Biosciences, USA) by gating on the CD19+ population. CD19+B cells and CD3+T cells were sorted and Tm9sf1 expression was measured by qPCR. Before analysis, the cells were twice rinsed with 1 × FACS buffer after treatment with antibodies for 30 min at 4 °C in 1 × FACS buffer (1% FBS in phosphate-buffered saline (PBS)) for cell surface marker staining. Surface marker-stained cells were fixed (10 min, room temperature) with Fixation/Permeabilization buffer (eBioscience, 00–5523-00), rinsed with 1 × permeabilization buffer, and incubated with the appropriate antibodies at 4 °C. The stained cells were evaluated using a FACS Calibur flow cytometer together with CellQuest software (BD Biosciences, USA).

The indicated markers were applied to the surface of splenocytes to quantify the proportion of immature, mature, and plasma cells. Immature B: CD19+CD21−CD23−IgMhighIgD−; Follicular B (FOB): CD19+CD21lowCD23+; Marginal zone B (MZB): CD19+CD21highCD23−; Plasma cells: CD19−CD138+.

Splenocytes were surface-stained with the following markers to determine immune cell proportions: B cells: CD19+; T cells: CD4+ or CD8+; Macrophages: CD19−CD4−CD8−F4/80+; Other myeloid cells: CD19−CD4−CD8−F4/80−CD11b+.

Cells were surface-labelled with anti-CD138 and stained intracellularly with anti-Blimp1 to identify induced plasma cells. Cells were surface-stained with the designated markers CD25, CD69, and CD86 to quantify B cell activation.

Bone marrow cells were obtained from the femur and stained with anti-CD45R/B220 together with anti-CD138 to identify bone marrow plasma cells in the collagen-induced arthritis (CIA) and lupus animal models.

Fixable Viability Dye eFluor™ 506 was used to label cells for the cell viability test.

In vitro stimulation of B cells and plasma cell differentiation

Positively sorted splenic CD19+ B cells were plated at 1 × 106 cells/well in 24-well plates, and grown in RPMI 1640 with 10% FBS after stimulation with either LPS (10 µg/mL) or anti-m IgM (5 µg/mL) + anti-m CD40 (2 µg/mL) + IL-21 (100 ng/mL). FCM was used to analyse the cell activation markers CD25, CD69, and CD86 following a 24-h stimulation period. Following four days of stimulation, FCM was used to assess cell viability and CD138+Blimp1+ plasma cells.

Western blotting

Western blotting was performed as previously described [27]. After denaturation and separation on 10–12% SDS-PAGE gels, the proteins were transferred to nitrocellulose membranes. The blots were probed with primary antibodies for three hours at 37 °C, followed by incubation with secondary antibodies conjugated to either IRDye 800CW or IRDye 680CW. The fluorescence intensities were assessed using the Odyssey FC (LI-COR, USA) imaging system and ImageJ software. Antibodies against LC3 (Cell Signaling, #12,741, USA), p62 (ABclonal, A7758, China), GAPDH (GoodHere, AB-P-R 001, China), phospho-mTOR (Ser2448; #5536, Cell Signaling), mTOR (#2983, Cell Signaling), TM9SF1 (PA5-84,406, Invitrogen, USA), and IgM µ heavy chain (B1240, Bersee, China) were among the primary antibodies utilized in this study.

CIA model in WT and Tm9sf1 −/− mice and the measurement of serum anti-col II antibody

8 male (8-weeks-old) WT C57/B6 mice and 8 male (8-week-old) Tm9sf1−/− mice were used to establish the CIA model according to a previously described protocol [28, 29]. Bovine type II collagen (2 mg/mL in acetic acid; Sigma-Aldrich) was homogenized on ice for 30 min with an equal volume of complete Freund's adjuvant (Sigma-Aldrich). One-hundred microliters of the emulsion was injected subcutaneoulsy into the tails of the mice on days 0 and 7. The mice were euthanized 60 days later. The joints were graded as follows: 0 for no erythema or swelling; 1 for mild swelling or erythema; 2 for mild swelling and erythema that extended from the ankle to the tarsus; 3 for moderate swelling and erythema that extended from the ankle joint to the metatarsal joint; and 4 for severe swelling that included the ankles, paws, and stiffness in the toes or limbs. An overall arthritis severity score was calculated by summation of the clinical scores of the two forelimbs and two hindlimbs. Higher scores indicated greater arthritis severity. The arthritis clinical scores were calculated by taking the average of the values provided by two investigators for analysis. The ankle joints were collected for histological analysis. Sera were collected after centrifugation of blood obtained from the hearts and anti-col II antibody levels were measured by ELISA (Shzkswkj, ZK-5186, China), as previously described [30]. Absorbances at 450 nm were read on a Microplate Absorbance Reader (SpectraMax i3X, Molecular Devices, USA).

Mouse models of SLE and the measurement of serum anti-dsDNA, total IgG, and ANA

Eight-week-old female WT C57/B6 and Tm9sf1−/− mice were randomly allocated to two groups with 8 mice per group. For lupus development, 0.5 mL of pristane (Sigma-Aldrich) was injected intraperitoneally into one group [31], while the other group received equal volumes of PBS. All mice were euthanized at week 23. Serum was extracted from the collected heart blood after centrifugation. Antinuclear antibodies (ANA), anti-dsDNA, and total IgG were measured in the sera using ELISA kits, as previously reported (CUSABIO, Wuhan, China) [32], with all measurements done in duplicate.

One kidney was removed for immunofluorescent staining, and the other was removed for histological investigation. The kidneys were fixed with 10% formalin for 24 h and were subsequently paraffin-embedded and sectioned (4 μm). Hematoxylin–Eosin (H&E, Solarbio, G1120, China) and Periodic Acid-Schiff (PAS, Solarbio, G1280, China) stains were used to assess the extent of glomerular lesions [33, 34]. The presence of immunological complexes (total IgG) was assessed using immunofluorescence, and mean fluorescence intensities (MFIs) were determined using ImageJ.

Histological analysis

The ankle joints or kidney tissues were harvested, fixed, embedded, sectioned, and stained as described above. Sections were evaluated under optical microscopy (DMIL LED, Leica, Germany). For immunofluorescence analysis, the sections were incubated with an anti-IgG (Abcam, ab166996, UK) primary antibody for three hours at 37℃, and then with an Alexa Fluor 488-conjugated secondary antibody (Thermo Fisher, A21206, USA) for one hour at 37℃. The sections were sealed with Mowiol containing 1 µg/mL DAPI, and examined under a fluorescence microscope (AxioScopeA1, Carl Zeiss, Germany).

The ankle joint sections were assessed and scored qualitatively. The scale (from 0 to 4) was according to the extent of inflammation, cartilage damage, pannus formation, and bone erosion linked to arthritis. Specifically, scores of 0 indicated no lesions, with scores of 1 representing a minimal amount of inflammation, 2 indicating mild inflammation with hyperplasia of the synovia, 3 indicating pannus formation with damage to the cartilage, and 4 representing severe inflammation, presence of debris within the joint, chondrocyte damage, loss of the collagenous matrix with substitution by new bone, and bone destruction [35].

Statistical analyses

Categorical data are presented as numbers (%) and continuous data are shown as mean ± SD (standard deviation). T-tests or rank sum tests (continuous variables) and Chi-square tests (categorical variables) were used for comparisons between two groups. Correlation analyses were used to assess relationships between the expression levels of TM9SF1 and the values of biochemical indices. Receiver operating characteristic (ROC) curves were used to evaluate the predictive power of TM9SF1 and clinical markers for RA or SLE activity. The study utilized both univariate and multivariate logistic regression analyses with odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) to determine the association between TM9SF1 levels and the disease activity of RA or SLE. Covariates such as age, sex, smoking status, alcohol consumption, and disease history of heart disease, hypertension, and diabetes, were taken into account when adjusting for these analyses. To determine statistical significance, two-sided P < 0.05 was used as the significance level. Data were analyzed using SAS (v.9.4) software (SAS Institute, NC, USA) and GraphPad Prism 5 was used to generate the graphical representations.

Results

In CIA and lupus animal models, Tm9sf1 −/− mice had less severe RA and SLE and fewer autoantibodies

To investigate the role of TM9SF1 in the development of autoimmune disease, Tm9sf1−/− and matched WT mice were used to create CIA and lupus animal models to analyze the roles of TM9SF1 in RA and SLE. The procedures used for establishment of the two mouse models are well-documented and the models are widely used [28, 31, 36, 37]. The basal immune cell proportions (specifically B cells [CD19+], T cells [CD4+ or CD8+], macrophages [CD19−CD4−CD8−F4/80+], and Other myeloid cells [CD19−CD4−CD8−F4/80−CD11b+]) were found to be similar between Tm9sf1−/− and WT mice, as shown in Fig. S1A (Additional file 2). There was no Tm9sf1 expression in Tm9sf1−/− animals relative to WT mice (Additional file 2: Fig. S1B).

In mice with col-II-CFA-induced arthritis, the severity of paw swelling was less in the Tm9sf1−/− mice relative to the WT diseased mice (Fig. 1A). Clinical scoring of the CIA mice was markedly lower in Tm9sf1−/− mice than the WT mice (Fig. 1B). The joint histology of the Tm9sf1−/− mice showed milder symptoms, such as cartilage destruction, compared to the WT mice (Fig. 1C). There was less autoantibody production in the Tm9sf1−/− mice relative to WT control animals (Fig. 1D).

Fig. 1
figure 1

Tm9sf1−/− mice exhibit reduced RA and SLE severity and decreased levels of autoantibodies compared to WT mice. A Photographs of the hind paws of WT and Tm9sf1−/− mice at 60 days after immunization with col II-CFA. B The clinical severity of CIA at various time points following immunization with col II-CFA. Results are presented as the mean ± SD of the clinical score for each mouse. Scoring criteria: 0, no swelling or erythema; 1, low level of swelling or erythema; 2, mild swelling and erythema extending from the ankle to the tarsus; 3, moderate swelling and erythema extending from the ankle to the metatarsal joint; 4, severe swelling, including ankles and paws, with stiffness in the digits or limbs. The total scores shown in the figure are the sum of the forelimb and hindlimb scores. C The joints of WT and Tm9sf1−/− mice underwent histological analysis 60 days after immunization with col II-CFA. Quantitative criteria: 0, no lesion; 1, minimal inflammation; 2, low levels of inflammatory infiltration and synovial hyperplasia; 3, pannus formation accompanied by cartilage breakdown; 4, severe infiltration, accompanied by joint debris, damaged chondrocytes, and loss of the cartilagenous matrix with substitution of new bone, and bone destruction. D Mouse models of CIA with anti-col II antibody levels. E–F Representative H&E and PAS-stained images of the kidneys of WT and Tm9sf1−/− mice with lupus caused by pristane. Percentage of abnormal glomeruli (right). G IgG deposition in kidney tissues evaluated by immunofluorescence (left). The mean fluorescence intensity (MFI) was determined with ImageJ (right). H-J Antibody levels in lupus model mice. K B220lowCD138+ bone marrow plasma cells from WT and Tm9sf1−/− mice in both models. Results are shown as mean ± SD. (B)-(K) were analyzed by independent-samples t-tests. *P < 0.05, **P < 0.01

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In the pristane-induced nephritis mouse model, H&E and PAS staining showed more severe active renal lesions (such as glomerular proliferation, hyaline deposits, fibrinoid necrosis, and hyaline deposits) in WT animals, which was milder in the Tm9sf1−/− model animals (Fig. 1E-F). Furthermore, IgG deposition in the kidneys caused by pristane was reduced in the Tm9sf1−/− mice (Fig. 1G). Similarly, Tm9sf1−/− mice exhibited significantly lower levels of anti-ANA, anti-dsDNA, and total IgG following lupus modeling as compared to WT lupus model controls (Fig. 1H-J).

We further examined bone marrow plasma cells in the CIA and lupus animal model, as shown in Fig. 1K, Tm9sf1−/− mice exhibited decreased frequency of B220lowCD138+ bone marrow plasma cells in both models.

These findings indicated that the loss of Tm9sf1 expression improves symptoms and reduces levels of autoantibodies in model mice. We speculate that Tm9sf1 may be involved in immune regulation.

Patient characteristics

The study enrolled 156 patients with active RA, 145 patients with active SLE, and 39 HCs. Samples were also taken from 41 and 37 RA and SLE patients, respectively, who were in low disease activity (Table 1). T-tests or rank sum tests for continuous variables and Chi-square tests for categorical variables were used to compare active and low disease activity stages in the RA and SLE patients. There were no marked differences in age and sex between the groups. The average time period between admission and discharge of RA patients was 7.48 ± 2.25, 5–12 days, and 9.07 ± 3.64, 8–16 days of SLE patients. The PLT counts were significantly higher in patients with active RA than in those with low disease activity (236.19 ± 29.34 vs. 127.49 ± 24.58, P < 0.001), while the opposite was observed in SLE (139.42 ± 27.69 in active vs. 214.62 ± 18.86 in low disease activity, P < 0.001). The active disease group had markedly increased levels of CRP (30.76 ± 8.80 vs. 18.29 ± 5.18, P < 0.001 in RA cases, 22.65 ± 6.12 vs. 13.15 ± 2.86, P < 0.001 in SLE cases) and ESR (48.36 ± 9.62 vs. 27.35 ± 4.68, P < 0.001 in RA cases, 31.02 ± 11.15 vs. 20.07 ± 3.28, P < 0.001 in SLE cases) relative to the low disease activity group. The same was observed when comparing the levels of RF and the DAS28 between these groups in RA patients, and the SLEDAI score in SLE patients. Following their discharge from the hospital, the average time between discharge and end of the follow-up was 8.32 ± 2.13, 5–16 months for RA patients, and 9.61 ± 2.07, 6–16 months for SLE patients.

Table 1 Demographic and clinical characteristics of the participants
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Elevated TM9SF1 expression levels in PBMCs were associated with active disease in RA and SLE patients

TM9SF1 expression levels were next assessed in the patients using qPCR (Fig. 2). RA patients had significantly higher TM9SF1 expression levels than HCs (0.68 ± 0.27 vs. 0.16 ± 0.10, P < 0.001), and cases with low disease activity exhibited lower levels of TM9SF1 compared to those with active disease status, as shown in paired t-test analyses (1.02 ± 0.44 vs. 0.56 ± 0.16, P = 0.001) (Fig. 2A and B). Comparable results were found in SLE patients, as displayed in Fig. 2C and D. Increased TM9SF1 levels were seen in SLE patients compared to HCs (0.72 ± 0.29 vs. 0.15 ± 0.08, P < 0.001). In addition, TM9SF1 levels were higher in patients with active SLE than in those with low disease activity (1.45 ± 0.51 vs. 0.32 ± 0.11, P < 0.001).

Fig. 2
figure 2

Patients with RA and SLE exhibit TM9SF1 upregulation. A RA patients (n = 156) and HCs (n = 39). B Paired RA patient samples during periods of active disease and low disease activity (n = 41). C SLE patients (n = 145) and HCs (n = 39). D Paired SLE patient samples during periods of active disease and low disease activity (n = 37). RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; HC, healthy control. A and C were analyzed by independent-samples t-tests; B and (D) were analyzed by paired t-tests. **P < 0.01, ***P < 0.001

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Following this, univariate and multivariate logistic regression analyses examined TM9SF1 expression levels and disease activity of RA and SLE patients. After adjustment for age, sex, smoking status, alcohol consumption, and history of heart disease, hypertension, and diabetes, the risk of active RA and SLE rose with increased TM9SF1 expression levels (OR = 1.84, 95%CI = 1.46–2.07, P = 0.013 in RA patients, OR = 2.51, 95%CI = 1.75–3.10, P = 0.007 in SLE patients) (Table 2). Cases with RA and SLE were assigned to low and high groups based on median TM9SF1 levels (0.29 for RA cases and 0.40 for SLE cases). Relative to low-level cases, high-level patients had a 3.04-fold higher risk of active RA (OR = 3.04, 95%CI = 2.49–4.72, P = 0.009), and 4.17-fold higher risk of active SLE (OR = 4.17, 95%CI = 2.91–5.68, P = 0.008).

Table 2 Association between TM9SF1 expression levels and disease activity in RA and SLE patients
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TM9SF1 expression levels were positively correlated with antibody-related markers and proinflammatory cytokines in RA and SLE patients

To further elucidate the association between the expression levels of TM9SF1 and antibody-related markers, differences in TM9SF1 expression levels were compared between groups of RA and SLE patients stratified according to specific antibody-related parameters (Fig. 3). Based on the median IgG level (14.50 g/L), RA individuals were assigned to low and high IgG groups. The high IgG group showed substantially higher TM9SF1 expression levels than the low IgG group (0.76 ± 0.20 vs. 0.22 ± 0.09, P < 0.001). The IgA (median value = 3.40 g/L) and anti-CCP (median value = 59.60 RU/mL) levels showed similar trends (0.70 ± 0.17 vs. 0.27 ± 0.12, P < 0.001; 0.82 ± 0.16 vs. 0.17 ± 0.08, P < 0.001; respectively). When SLE patients were stratified by IgM levels (median value = 1.07 g/L) and anti-dsDNA titers (median value = 34.50 IU/mL), TM9SF1 expression levels also showed significant differences (0.85 ± 0.21 vs. 0.10 ± 0.06, P < 0.001; 0.80 ± 0.23 vs. 0.14 ± 0.09, P < 0.001).

Fig. 3
figure 3

Differences in TM9SF1 expression levels between RA and SLE patients stratified based on low or high levels of antibody-associated markers. RA patients: A IgG, (B) IgA, (C) IgM, (D) anti-CCP. SLE patients: E IgG, (F) IgA, (G) IgM, (H) anti-dsDNA, (I) anti-Sm. Median values, A: 14.50 g/L; B: 3.40 g/L; C: 1.50 g/L; D: 59.60 RU/mL; E: 12.6 g/L; F: 3.71 g/L; G: 1.07 g/L; H: 34.50 IU/mL; I: 47.40 RU/mL. RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; anti-CCP, anti-cyclic citrullinated peptide; anti-dsDNA, anti-double-stranded DNA; anti-Sm, anti-Smith. (A)-(I) were analyzed by independent-samples t tests. ***P < 0.001

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Analyses of correlations between TM9SF1 and IgG, IgA, IgM, anti-CCP, anti-Sm, and anti-dsDNA levels (Fig. 4) indicated that TM9SF1 expression level was significantly positively associated with IgG (r = 0.734, P < 0.001), IgA (r = 0.660, P = 0.001), IgM (r = 0.718, P = 0.013), and anti-CCP (r = 0.742, P = 0.004) levels in RA patients. In SLE patients, TM9SF1 levels were significantly correlated with IgM (r = 0.791, P < 0.001), anti-Sm (r = 0.815, P = 0.008), and anti-dsDNA (r = 0.817, P = 0.005).

Fig. 4
figure 4

Associations between TM9SF1 expression levels and indicators associated with antibodies in RA and SLE patients. RA patients: A IgG, (B) IgA, (C) IgM, (D) anti-CCP. SLE patients: E IgG, (F) IgA, (G) IgM, (H) anti-dsDNA; I anti-Sm. RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; CI, confidence interval; anti-CCP, anti-cyclic citrullinated peptide; anti-dsDNA, anti-double-stranded DNA; anti-Sm, anti-Smith. (A)-(I) were analyzed by Spearman correlation analyses

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Proinflammatory cytokines, such as tumor necrosis factor (TNF)-α, interferon (IFN)-γ, IL-17A and IL-6, participate in the damage observed in individuals with RA [38] and SLE [39]. The associations between TM9SF1 expression and the levels of the transcription factor Forkhead box P3 (FOXP3), IFN-γ, TNF-α, IL-6 and IL-17A in PBMCs from patients with RA and SLE were further evaluated. Cytokine levels were compared between the two groups of RA and SLE patients divided according to the median TM9SF1 expression level (0.29 for RA cases and 0.40 for SLE cases) (Fig. 5). The high-TM9SF1 group showed significantly higher levels of FOXP3 expression than the low-TM9SF1 group (0.53 ± 0.22 vs. 0.13 ± 0.10, P < 0.001 in RA cases, 0.46 ± 0.27 vs. 0.07 ± 0.05, P < 0.001 in SLE cases). The expression levels of IFN-γ, TNF-α, IL-6 and IL-17A also showed the same trend in both in RA and SLE patients.

Fig. 5
figure 5

Differences in cytokine expression levels in RA and SLE patients stratified according to low or high levels of TM9SF1 expression. RA patients: A FOXP3; B IFN-γ; C TNF-α; D IL-6; E IL-17A. SLE patients: F FOXP3; G IFN-γ; H TNF-α; I IL-6; J IL-17A. Median TM9SF1 expression levels, for RA patients: 0.29; for SLE patients: 0.40. RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; FOXP3, forkhead box P3; IFN-γ, interferon-γ; TNF-α, tumor necrosis factor-α; IL-6, interleukin-6; IL-17A, interleukin-17A. (A)-(J) were analyzed by independent-samples t tests. ***P < 0.001

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Correlation analyses were also conducted to evaluate the association between TM9SF1 expression levels and cytokine production (Fig. 6). The results showed a positive correlation between TM9SF1 levels and FOXP3 (r = 0.765, P = 0.001 in RA patients, r = 0.704, P = 0.014 in SLE patients), IFN-γ (r = 0.724, P = 0.009 in RA patients, r = 0.699, P = 0.005 in SLE patients), IL-17A (r = 0.737, P = 0.018 in RA patients, r = 0.691, P = 0.007 in SLE patients), IL-6 (r = 0.774, P = 0.002 in RA patients, r = 0.812, P = 0.001 in SLE patients), and TNF-α (r = 0.817, P < 0.001 in RA patients, r = 0.802, P < 0.001 in SLE patients). The TM9SF1 expression levels remained significantly positively correlated with IL-17A (r = 0.783, P = 0.021 in RA patients, r = 0.720, P = 0.005 in SLE patients), TNF-α (r = 0.740, P = 0.004 in RA patients, r = 0.713, P < 0.001 in SLE patients), and IFN-γ (r = 0.821, P < 0.001 in RA patients, r = 0.796, P = 0.002 in SLE patients) levels in RA and SLE patients with active disease. These results further confirmed the association between TM9SF1 expression and disease activity.

Fig. 6
figure 6

Correlations between TM9SF1 expression and cytokine levels in PBMCs from RA and SLE patients. RA patients: A FOXP3; B IFN-γ; C TNF-α; D IL-6; E IL-17A. SLE patients: F FOXP3; G IFN-γ; H TNF-α; I IL-6; J IL-17A. RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; CI, confidence interval; FOXP3, forkhead box P3; IFN-γ, interferon-γ; TNF-α, tumor necrosis factor-α; IL-6, interleukin-6; IL-17A, interleukin-17A. (A)-(J) were analyzed by Spearman correlation analyses

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TM9SF1 outperforms clinical indicators in predicting disease activity in RA and SLE

The effectiveness of TM9SF1 and clinical markers as disease activity predictors of RA and SLE was evaluated using ROC curve analysis (Fig. 7). The TM9SF1 expression level showed superior performance compared to RF and anti-CCP in predicting disease activity for RA. The area under the curve (AUC) was 0.858 (95%CI: 0.795–0.920) with a sensitivity of 86.5% and a specificity of 83.6%. For RF and anti-CCP, the corresponding AUCs were 0.769 (95%CI: 0.681–0.857) and 0.792 (95%CI: 0.718–0.866), respectively. In addition, TM9SF1 also showed better predictive ability than anti-dsDNA and anti-Sm in predicting SLE disease activity (AUC [95%CI]: 0.876 [0.821–0.930] for TM9SF1, AUC [95%CI]: 0.737 [0.643–0.831] for anti-dsDNA and 0.814 [0.746–0.883] for anti-Sm). TM9SF1 is thus more effective than other clinical indicators in predicting disease activity of RA and SLE, suggesting its potential as a new biomarker.

Fig. 7
figure 7

Evaluation of TM9SF1 and clinical indicators as predictors of disease activity in patients with RA and SLE. RA patients: A TM9SF1; B RF; C anti-CCP. SLE patients: D TM9SF1; E anti-dsDNA; F anti-Sm. RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; AUC, area under the curve; CI, confidence interval; RF, rheumatoid factor; anti-CCP, anti-cyclic citrullinated peptide; anti-dsDNA, anti-double-stranded DNA; anti-Sm, anti-Smith

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Tm9sf1 deficiency inhibits B cell maturation into antibody-secreting plasma cells by modulating mTOR-dependent autophagy

TM9SF1 expression levels were analyzed in human cells, as well as in bone marrow and spleen samples, using data from the website https://www.proteinatlas.org/ENSG00000100926-TM9SF1/single+cell+type (Fig. 8A). Compared to B cells, human plasma cells showed significantly higher TM9SF1 expression (Fig. 8A). This led to further investigation of the role of TM9SF1 in B cell differentiation, as autoantibody secretion is crucial in the pathogenesis of autoimmune diseases. It was not known whether these expression profiles correspond to mouse immune cells as these data were from human sources and thus Tm9sf1 expression in mouse B and plasma cells was investigated. LPS-induced polyclonal stimulation of B cells lead to the development of murine plasma cells [40]. It was found that treatment of mouse CD19+B cells, confirmed by FCM, with 10 µg/mL LPS resulted in a significant increase in Tm9sf1 mRNA and protein levels, as predicted (Fig. 8B).

Fig. 8
figure 8

Knockout of Tm9sf1 inhibited plasma cell maturation and autoantibody production through regulation of autophagy. A Levels of human B and plasma cell TM9SF1 expression (database research https://www.proteinatlas.org/ENSG00000100926-TM9SF1/single+cell+type). The "c" in “c-0, 1, 2, 3, 4, 5, 6, 7, 8, 9” is short for "Cluster Cell type", which stands for the different subpopulations used in single-cell sequencing. B Levels of Tm9sf1 mRNA and protein expression in LPS-stimulated (10 µg/mL) murine B cells. C-D B cell activation markers CD25, CD69, and CD86, as well as CD138+Blimp1+ plasma cells, from WT and Tm9sf1−/− mice treated with either LPS (10 µg/mL) or anti-mouse IgM (purified [azide-free] F(ab')2 goat anti-mouse IgM (μ chain), 5 µg/mL) + anti-mouse CD40 (2 µg/mL) + IL-21 (100 ng/mL), were analyzed and quantified using FCM. E Expression of proteins linked to autophagy in plasma cells with LPS (10 µg/mL) together with or without rapamycin (5 nM). F-G CD138+Blimp1+ plasma cells and IgM secretion in supernatants of plasma cells treated with LPS (10 µg/mL) together with or without rapamycin (5 nM) (n = 3). (B)-(G) were analyzed by independent-samples t-tests. The following are the hierarchical symbols that represent increasing thresholds in the evaluation of observed outcomes: *P < 0.05 represents a moderate level of significance, **P < 0.01 indicates a higher degree of significance, and ***P < 0.001 indicates the highest level of statistical significance

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Since LPS stimulation promotes marginal zone B cells over follicular B cells [41], the elevated Tm9sf1 expression level may have been unrelated to the differentiation as even marginal zone B cells do not differentiate into plasma cells within a day. Therefore, we used anti-mouse IgM to stimulate the B cell receptor (BCR) in addition to LPS stimulation. We also used anti-mouse CD40 and IL-21 to promote the maturation of B cells into plasma cells.

Tm9sf1−/− and matched WT mice had essentially similar proportions of immature and mature B cells, including immature (CD19+CD21−CD23−IgMhighIgD−), follicular (FOB: CD19+CD21lowCD23+), and marginal zone (MZB: CD19+CD21highCD23−) B cells, as well as plasma cells (CD19−CD138+) (Additional file 3: Fig. S2). Following stimulation with either LPS or anti-mouse IgM + anti-mouse CD40 + IL-21, CD19+B cell positivity determined by FCM with 99% purity (Additional file 4: Fig. S3) from Tm9sf1−/− and WT mice was analyzed independently for B cell activation at 24 h and differentiation at 4 days.

The expression of B cell activation markers, such as CD25, CD69, and CD86, stimulated by either LPS or anti-mouse IgM + anti-mouse CD40 + IL-21, was examined after 24 h of stimulation. The expression of these activation markers was observed to the same in both WT and Tm9sf1−/− B cells, suggesting that Tm9sf1 expression was unrelated to B cell activation (Fig. 8C). We measured the proportions of CD138+Blimp1+ plasma cells and cell viability after four days of stimulation, finding similar viability in both WT and Tm9sf1−/− mice. In comparison to WT mice, Tm9sf1−/− mice showed a marked reduction in the development of CD138+Blimp1+ plasma cells from B cells treated with LPS or anti-mouse IgM + anti-mouse CD40 + IL-21. Specifically, after treatment with anti-mouse CD40, anti-mouse IgM, and IL-21, the number of Tm9sf1−/− plasma cells was reduced by approximately 45% relative to the WT cell numbers. The results indicate that Tm9sf1 knockout resulted in reduced proportions of plasma cells (Fig. 8D).

Intact autophagic flux is necessary for plasma cell differentiation, viability, and antibody secretion [40, 42]. TM9SF1 has been identified as a gene that is directly involved in the process of autophagy, according to all available published evidence. Mammalian target of rapamycin (mTOR) inhibits autophagy. Typically, inhibition of mTOR activates autophagy [43]. As autophagosomes mature, cytoplasmic LC3 associates with phosphatidylethanolamine (PE) on the phagophore surface. This results in an increase in the ratio of PE-LC3 (LC3-II) to cytoplasmic LC3 (LC3-I) [44]. When autophagy is activated, p62, an adapter and regulator of autophagy, is also broken down. This makes p62 a frequently utilized indicator of cellular autophagy activity(44). These autophagy-related proteins were thus investigated in B cells.

Figure 8E showed that there was a marked reduction in the LC3-II/LC3-I ratio and an increase in the p-mTOR/mTOR ratio and p62 level in Tm9sf1−/− B cells compared to WT B cells. However, the effects were reversed when treated with rapamycin to inhibit mTOR (5 nM). This suggests that the deficiency of Tm9sf1 inhibits mTOR-dependent autophagy. Fig. S4 indicates the viability of B cells after treatment with varying concentrations of rapamycin, ranging from 0 to 80 nM (Additional file 5: Fig. S4). The results indicated that there was no difference in cell survival rates between 0 and 5 nM rapamycin-treated B cells. The inhibitory effect of Tm9sf1 depletion on the development of plasma cells and the production of IgM was also counteracted by rapamycin (Fig. 8F-G). These findings indicate that a lack of Tm9sf1 reduces the differentiation of B cells to antibody-secreting plasma cells by controlling autophagy, which is dependent on mTOR.

Discussion

TM9SF1 is widely expressed in a variety of human tissue types, and is known to be involved in regulating autophagy [11]. Previous studies have focused mainly on its expression patterns [13, 15, 17, 45]. We recently reported that Tm9sf1 was upregulated in LPS-induced lung inflammation with Tm9sf1 knockout alleviating this inflammation [18]. Therefore, we extended our research to investigate whether TM9SF1 expression is also elevated during the onset and active phase of autoimmune disease. In the present study, Tm9sf1−/− mice were found to show markedly reduced production of autoantibodies in both RA and SLE models. Clinical data demonstrated that PBMCs from patients with low disease activity exhibited lower TM9SF1 levels than those with active disease. TM9SF1 levels were closely associated with the levels of several antibody-associated indicators and inflammatory cytokines and were effective in predicting disease activity. Collectively, these results supported the application of TM9SF1 as a novel biomarker for the prediction of disease activity in RA and SLE.

Patients may experience extended periods (lasting from months to years) of chronic systemic inflammatory activity resulting from the persistent infiltration of affected organs by activated immune cells [8]. This follows the expansion of lymphocyte populations for specific autoantigens causing clinical manifestations [9]. Novel biomarkers that reflect disease activity may be used in conjunction with symptoms and signs to assess treatment efficacy. Marked differences have been observed in the expression profiles of IFN-related genes in PBMCs from RA and SLE patients relative to HCs [46, 47]. The gene signatures of peripheral blood indicators associated with autoreactive B cell activation and maturation bear similarities to the expression profiles of inflammatory synovial fibroblasts in RA patients [48]. In addition, the expression levels of certain genes in PBMCs can reflect autoimmune organ damage. Lewis et al. performed an RNA-Seq analysis of genes associated with early RA and found that the expression of these genes in PBMCs provided insight into the magnitude of inflammatory activity and injury within affected tissues and organs throughout the progression of autoimmune rheumatic disease [49]. Since PBMCs are commonly used for transcriptomic analysis in autoimmune diseases, we measured the relative expression levels of TM9SF1 in PBMCs from 156 RA and 145 SLE patients. This showed that TM9SF1 levels in PBMCs were significantly correlated with different stages of disease activity in both RA and SLE. Additionally, TM9SF1 was found to be more effective than several clinical indicators in predicting disease activity in RA and SLE.

Furthermore, TM9SF1 levels were positively correlated with the levels of TNF-α, IL-6, IFN-γ, and IL-17A in patients. In SLE and RA, IFN-γ has inflammatory effects [50, 51] and is markedly increased even before the extensive production of autoantibodies characteristic of SLE [50]. During the development of RA, IFN-γ contributes to periarticular bone loss and synovial inflammation [51]. IL-6 stimulates the migration of neutrophils and the maturation of osteoclasts, resulting in synovitis, joint destruction, and pannus development in RA [52]. IL-17A is mostly produced by Th17 cells and may upregulate the levels of local pro-inflammatory cytokines generated by synoviocytes and chondrocytes, worsening joint injury [52]. TNF-α activates osteoclasts in damaged joint cartilage, leading to synovial hyperplasia and erosion in synovial fibroblasts [52]. TNF-α, IL-6, and IL-17A levels are also associated with SLE disease activity [53]. Exploring the mechanisms and signaling pathways modulated by TM9SF1 in promoting the secretion of inflammatory cytokines requires further investigation, and the potential influence of TM9SF1 on the cells responsible for secreting these cytokines is also worth exploring to elucidate the complex interaction networks in autoimmune diseases.

After analyzing the above results, we then explored the mechanisms by which TM9SF1 regulates autoimmune diseases. In RA and SLE Tm9sf1−/− mice, Tm9sf1 expression was absent in multiple immune cells associated with lesion formation. The alleviation observed in the disease models was probably associated with reduced cytokine production by T and myeloid cells, inhibition of B cell maturation, and downregulation of antibody production. The gene expression levels in patient PBMCs may also be due to changes in expression levels in all constituent cells. We observed that TM9SF1 expression levels were significantly upregulated in plasma cells compared to B cells, using database research. It was speculated that TM9SF1 may be involved in B cell maturation. A series of experiments were conducted to confirm the mechanism by which Tm9sf1 deficiency inhibited B cell differentiation. In vitro plasma cell induction experiments showed that Tm9sf1 knockout in B cells markedly reduced both their maturation into plasma cells and antibody secretion, indicating the importance of Tm9sf1 in plasma cell differentiation. Tm9sf1−/− mice showed markedly reduced autoantibody production in RA and SLE models. However, the factors affecting the titers of autoantibodies may not necessarily be dependent on the inhibition of plasma cell differentiation in Tm9sf1−/− mice. TM9SF1 expression levels were found to be positively correlated with levels of TNF-α, IL-6, IFN-γ, and IL-17A secreted by other immune cells, and the effects of TM9SF1 on other immune cells could have influenced antibody generation indirectly. In future research, the extent to which the effect of TM9SF1 on plasma cell differentiation contributes to the autoimmune disease requires further investigation by establishing Tm9sf1 knockout models in B cells. Researchers may also establish Tm9sf1 knockout models in other immune cell types to discover or rule out their effects.

The mechanism by which Tm9sf1 deficiency inhibited plasma cell differentiation was an innovative finding of this study. Autophagy is characterized by the recycling of aged or damaged organelles and misfolded proteins, and is important for the differentiation of plasma cells [54], antibody production [42], and the persistence of memory B cells [55]. Defective plasma cell differentiation resulting from IκBNS deficiency has been attributed to mTOR activation and reduced autophagy [40]. Autophagy levels have been positively correlated with the activity of autoimmune rheumatic diseases [54, 56]. Deletion of the autophagy-related gene Atg5 in B cells can reduce the viability of long-lived plasma cells, as well as the secretion of antinuclear antibodies and IgG IC deposits in the kidneys of lupus mouse models [57]. However, inhibition of autophagy was not able to clear autoantigens released from dying cells, thus leading to the accumulation of autoantigens and autoimmunity [56]. In addition, the promotion of autophagy induces type II programmed cell death which can release large amounts of autoantigens [58]. Nevertheless, increased levels of autophagy are necessary for antibody-secreting plasma cells which require significant amounts of energy for the production of thousands of antibody molecules per second [42, 57, 59,60,61]. The majority of published data support TM9SF1 as a promoter of autophagy [11, 13, 15, 45, 62]; an exception is a recent study of ours that suggests that TM9SF1 may inhibit autophagy in A549 lung cancer cells [18]. It is thus possible that the function of TM9SF1 may vary in different cell types, especially between normal and tumor cells, and the differences may also depend on its expression level. According to the present study, TM9SF1 depletion in B cells inhibited plasma cell differentiation and antibody production by activating mTOR and inhibiting autophagy in vitro. Therefore, we speculated that elevated TM9SF1 expression may promote autophagy to meet the growing energy requirements for plasma cell maturation and antibody production.

However, the study has several limitations. First, the mechanisms underlying the modulation of autoimmune disease severity by Tm9sf1 require elucidation in individual immune cells involved in autoantibody production by knocking out Tm9sf1 in specific immune cells in mouse models. Second, the expression profile of TM9SF1 in population-based research reflects the overall trend in both innate and adaptive immune cells, and thus single-cell RNA sequencing of plasma cells is recommanded for transcriptomic analysis to reveal the expression patterns of TM9SF1 in different autoimmune disease stages. Furthermore, the predictive ability of TM9SF1 in other inflammation-related diseases, such as those caused by infection, requires further verification, together with disease specificity. Changes in TM9SF1 expression levels between the time of hospital discharge and the end of the follow-up period should be evaluated in larger samples and longer follow-ups.

Conclusions

Clinical data from subjects indicated that TM9SF1 may function as a novel biomarker that can predict disease activity in RA and SLE patients. The findings of reduced autoantibody production and lower disease activity in RA and SLE Tm9sf1−/− mice, it is reasonable to assume that TM9SF1 may possess immunomodulatory functions. Plasma cell induction experiments demonstrated that TM9SF1 deficiency inhibits antibody-secreting plasma cell maturation through activation of mTOR and inhibition of autophagy.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request (KW: wangk201912@hbuas.edu.cn; AZ: xf_zab@sina.com; HC: chenhb@hbuas.edu.cn).

Abbreviations

ACR:

American College of Rheumatology

ANA:

antinuclear antibodies

anti-CCP:

anti-cyclic citrullinated peptide

anti-dsDNA:

anti-double-stranded DNA

anti-Sm:

anti-Smith

AUC:

area under the curve

BCR:

B cell Receptor

CI:

confidence interval

CIA:

collagen-induced arthritis

CRP:

C-reactive protein

DAS28:

Disease Activity Score 28-joint count

ESR:

erythrocyte sedimentation rate

EULAR:

European League Against Rheumatism

FOXP3:

Forkhead box P3

HC:

healthy control

H&E:

Hematoxylin-Eosin

IC:

immune complex

IFN:

interferon

IL:

interleukin

KO:

knockout

LLDAS:

lupus low level disease activity state

LPS:

lipopolysaccharide

MAC:

membrane attack complex

MFIs:

mean fluorescence intensities

mTOR:

mammalian target of rapamycin

OR:

odds ratio

PAS:

Periodic Acid-Schiff

PBMC:

peripheral blood mononuclear cell

PBS:

phosphate-buffered saline

RA:

rheumatoid arthritis

RF:

rheumatoid factor

ROC:

receiver operating characteristic

SD:

standard deviation

SLE:

systemic lupus erythematosus

SLEDAI:

SLE Disease Activity Index

TM9SF1:

Transmembrane 9 superfamily member 1

TNF:

tumor necrosis factor

WBC:

white blood cell

WT:

wild-type

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Acknowledgements

The authors would like to thank all the reviewers who participated in the review and MJEditor (www.mjeditor.com) for its linguistic assistance during the preparation of this manuscript.

Funding

This work was supported by the Key R&D Program of Hubei province (2022BCE014), the Hubei Provincial Natural Science Foundation of China (2024AFB165 and 2022CFC032), Xiangyang Medical-health Areas Science and Technology Program (2021YL047), and the Research Foundation for Teacher Cultivation of Hubei University of Arts and Science (2022pygpzk10).

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Authors and Affiliations

  1. Institute of Neuroscience and Brain Diseases, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, 441021, China

    Juan Xiao, Zhenwang Zhao, Fengqiao Zhou, Lei Xiang, Mingming Liu, Fengsheng Cao, Hong Xiao, Huabo Chen, Anbing Zhang & Ke Wang

  2. Department of Rheumatology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, 441021, China

    Juan Xiao, Zhenwang Zhao, Fengqiao Zhou, Lei Xiang, Mingming Liu, Fengsheng Cao, Hong Xiao, Huabo Chen, Anbing Zhang & Ke Wang

  3. Gucheng People’s Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, 441700, China

    Jinsong Xiong, Zean Yang & Baoxian Gong

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  1. Juan Xiao
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Contributions

JX1 (Juan Xiao), KW, AZ and HC had full access to all of the data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. JX1, KW and HC designed research; ZZ, FZ, JX2 (Jinsong Xiong), ZY, BG, LX, ML, FC and HX conducted research; KW and HC analyzed data; and JX1 and KW wrote the paper. JX1, KW, AZ and HC had primary responsibility for the final content. All authors read and approved the final manuscript.

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@chenhb610(Huabo Chen).

Corresponding authors

Correspondence to Huabo Chen, Anbing Zhang or Ke Wang.

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Ethics approval and consent to participate

The study was conducted following the Declaration of Helsinki (as revised in 2013). The study protocol was approved by the Ethics Committee of Hubei University of Arts and Science (2022-030). Informed written consent was obtained from all subject participants in the study. Animal experiment protocols were approved by the Ethics Committee of Hubei University of Arts and Science (2022-029). All animal experiments followed the guidelines of the IACUC.

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Supplementary Information

Additional file 1: Table S1. The primer sequences used for quantitative polymerase chain reaction (qPCR).

12916_2024_3729_MOESM2_ESM.tif

Additional file 2: Fig. S1. (A) There was no difference in the fundamental proportions of immune cells, such as B cells (CD19+), T cells (CD4+ or CD8+), Macrophages (CD19−CD4−CD8−F4/80+), and other myeloid cells (CD19−CD4−CD8−F4/80−CD11b+), between Tm9sf1−/− and WT mice. (B) There were no differences in Tm9sf1 expression among immune cells. However, Tm9sf1 expression was absent in these immune cells in Tm9sf1−/− mice compared to WT mice.

12916_2024_3729_MOESM3_ESM.tif

Additional file 3: Fig. S2. In Tm9sf1−/− and matching WT mice, the basal makeup of immature, mature, and plasma cells was the same. This included immature B cells (CD19+CD21−CD23−IgMhighIgD−), mature B cells (Follicular B (FOB): CD19+CD21lowCD23+; Marginal zone B (MZB): CD19+CD21highCD23−), and plasma cells (CD19−CD138+).

Additional file 4: Fig. S3. The purity of CD19+ B lymphocytes isolated by FCM was 99%.

12916_2024_3729_MOESM5_ESM.tif

Additional file 5: Fig. S4. The viability of B cells was assessed after treatment with varying doses of rapamycin, ranging from 0 to 80 nM.

Additional file 6: Fig. S5. The complete, unedited photos of blots for this investigation.

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Xiao, J., Zhao, Z., Zhou, F. et al. TM9SF1 expression correlates with autoimmune disease activity and regulates antibody production through mTOR-dependent autophagy. BMC Med 22, 502 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12916-024-03729-w

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BMC Medicine

ISSN: 1741-7015

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