B-cell repertoire sequencing reveals frequent rearrangements of IGHD5-5 in patients with systemic sclerosis
KoFujii1
MotokiHorii1
KentaKudo1
JiroNishio1
NatsumiFushida1
TasukuKitano1
KieMizumaki1
KyosukeOishi1
YasuhitoHamaguchi1
TakashiMatsushita
MD, PhD
1✉Phone81-76-265-2343Emailt-matsushita@med.kanazawa-u.ac.jp1Department of Dermatology, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health SciencesKanazawa University920-8641KanazawaJapan
Ko Fujii,1 Motoki Horii,1 Kenta Kudo,1 Jiro Nishio,1 Natsumi Fushida,1 Tasuku Kitano,1
Kie Mizumaki,1 Kyosuke Oishi,1 Yasuhito Hamaguchi,1 and Takashi Matsushita1
1Department of Dermatology, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan
Running title: B-cell repertoire in systemic sclerosis
Address correspondence and reprint requests to: Takashi Matsushita MD, PhD, Department of Dermatology, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa 920–8641, Japan
Phone: 81-76-265-2343; Fax: 81-76-234-4270
E-mail: t-matsushita@med.kanazawa-u.ac.jp
Abstract
Systemic sclerosis (SSc) is an autoimmune disorder marked by fibrosis of the skin and internal organs, with B cells increasingly recognized as key players in its pathogenesis. However, the characteristics of the B cell receptor (BCR) repertoire in SSc remain insufficiently defined. In this study, we performed high-throughput sequencing of immunoglobulin heavy chain genes in 15 female anti-centromere antibody (ACA)-positive SSc patients and five age-matched healthy female controls to explore disease-specific repertoire biases. A total of 2,597,460 in-frame sequence reads and 384,111 unique reads were obtained. While diversity metrics, including the Shannon, Simpson, and Pielou indices, tended to be higher in the SSc group, the differences were not statistically significant. Notably, the average complementarity-determining region 3 (CDR3) length was significantly shorter in SSc patients compared to controls (16.91 ± 3.727 vs. 17.44 ± 3.836, p < 0.0001). Gene usage analysis revealed no significant differences in IGHJ or IGHC segments; however, several IGHV and IGHD segments displayed statistically significant differences. IGHD5-5 (1.636% vs. 0.547%, p = 0.0001) and IGHD5-18 (1.607% vs. 0.547%, p = 0.0001) were significantly overrepresented in the SSc group, whereas IGHV1/OR15-2 was significantly underrepresented (0.062% vs. 0.130%, p = 0.0080). Further analysis demonstrated that IGHD5-5 clones with a 15-nucleotide CDR3 length were more conserved and exhibited distinctive sequence patterns compared to other lengths or genes. Specific nucleotide lengths, including 15, 23, and 24 for IGHD5-5, and 18 for IGHV1/OR15-2, showed significant frequency differences between groups (p < 0.05). Sequence logo plots confirmed reduced variability in these conserved clones, suggesting antigen-driven clonal selection. These findings identify unique BCR repertoire features in ACA-positive SSc patients and suggest their potential utility as disease biomarkers or therapeutic targets.
Keywords:
Anti-centromere antibodies
B cell repertoire
Systemic sclerosis
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1. Introduction
Systemic sclerosis (SSc) is a complex autoimmune disease characterized by vasculopathy and fibrosis of the skin and various internal organs1, which occurs against a background of autoimmune phenomena, including the production of antinuclear antibodies. Accumulating evidence suggests that B cells play a significant role in the pathogenesis of SSc2. One of the key findings supporting this hypothesis is the increased serum levels of B cell-activating factor (BAFF), a cytokine belonging to the tumor necrosis factor family that promotes B cell activation and survival. Elevated BAFF levels in SSc patients have been reported to correlate with the severity of skin fibrosis3, suggesting a pathogenic link between B cell activation and disease progression.
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Further supporting the involvement of B cells in SSc, clinical trials have demonstrated that B cell depletion therapy using anti-CD20 monoclonal antibodies leads to significant improvements in both skin fibrosis and interstitial lung disease in patients with SSc4, 5. These findings indicate that B cells are not merely bystanders but actively contribute to disease pathogenesis. Despite these insights, the precise characteristics and alterations of the B cell receptor (BCR) repertoire in SSc remain largely unknown.BCR repertoire analysis has been extensively studied in various autoimmune diseases6, including systemic lupus erythematosus (SLE)7, immune thrombocytopenic purpura8, and multiple sclerosis9, revealing disease-specific repertoire biases. Given the established role of B cells in SSc and the potential significance of BCR diversity in autoimmune pathogenesis, a comprehensive investigation into the BCR repertoire of SSc patients is warranted.
In this study, we aimed to elucidate potential disease-specific biases in the BCR repertoire of SSc patients by performing a comprehensive BCR repertoire analysis. This approach may provide novel insights into the immunological mechanisms underlying SSc and contribute to the identification of potential biomarkers or therapeutic targets associated with disease progression.
2. Methods
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2.1 Patients. This study included a total of 15 female patients with systemic sclerosis (SSc) who were positive for anti-centromere antibodies (ACA) and had no history of complications or prior immunosuppressive therapy. In addition, five age-matched healthy individuals were enrolled as controls. All patients fulfilled the criteria for SSc with the 2013 American College of Rheumatology and European League Against Rheumatism classification criteria for systemic sclerosis10. Detailed demographic and clinical characteristics of the patients are provided in the supplementary table.All healthy control donors underwent annual routine medical examinations and had no history of autoimmune or other immune-related disorders. The age range of the participants was between 53 and 64 years, with a median age of 56 years. Importantly, all individuals included in this study were female. This carefully selected study population allowed for a focused investigation of the B cell repertoire characteristics associated with SSc while minimizing potential confounding factors.
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Each sequence reads was analyzed using bioinformatics software developed by Repertoire Genesis Inc.(Ibaraki, Japan). The usage frequencies of IGHV, IGHD, IGHJ, IGHC, and complementarity-determining region 3 (CDR3) sequences were determined based on previously established methodologies. Briefly, the identification of V, D, J, and C regions was performed by selecting the sequence with the highest identity to reference datasets available in the international Immunogenetics information system (IMGT) database (http://www.imgt.org). The software automatically processed, assigned, and aggregated the sequencing data to ensure consistent and accurate identification of immunoglobulin gene segments. A
All procedures were conducted in accordance with the Declaration of Helsinki. A
The study protocol was approved by the Ethics Committee of Kanazawa University. A
Written informed consent was obtained from all participants.A
2.2 Analysis of immune receptor gene repertoire. For the classification of unique sequence reads, sequences that shared identical V, D, J segments and deduced amino acid sequences of CDR3 were considered as a single unique sequence reads. Since somatic hypermutation generates minor sequence variations within the immunoglobulin repertoire, multiple variant sequences that arose due to such mutations were categorized under the same unique sequence reads. Furthermore, sequence reads that shared the same V, D, and J segments and identical CDR3 amino acid sequences were classified as belonging to the same clonal lineage. This approach allowed for a more precise assessment of B-cell repertoire diversity while accounting for potential sequence variations introduced by hypermutation.The Repertoire Genesis software automatically quantified the number of unique sequences reads and ranked them based on their copy numbers. This automated approach enabled an unbiased and efficient assessment of clonal expansion and repertoire diversity within the studied samples.
2.3 Statistical Analysis. For statistical analysis of paired samples, Wilcoxon matched-pairs signed rank test and t-test was used. P-values < 0.05 were considered to be statistically significant. The data were shown as the median (range) unless otherwise indicated.
To evaluate repertoire diversity comprehensively, the Shannon diversity index, Simpson richness index, and Pielou evenness index were calculated using the R statistical program. The Shannon index was normalized by dividing it by the logarithm of the total number of unique sequences reads to ensure comparability across different sample sizes. These diversity indices provided insights into the distribution, richness, and evenness of the B-cell receptor repertoire, allowing for a quantitative assessment of immune repertoire heterogeneity among the studied groups.
3. Results
3.1 Overview and Diversity Index Comparison
A total of 2,597,460 in-frame sequence reads and 384,111 unique reads were obtained from 20 blood samples. The number of reads obtained per sample ranged from 53,725 to 226,536, with an average of 129,873 reads per sample. The detailed clinical characteristics of the patients are presented in the supplementary table. A comparative analysis of diversity between the disease group and the control group was conducted using the Shannon diversity index, the Simpson richness index, and the Pielou evenness index. Across all indices, the disease group exhibited a higher level of diversity compared to the control group. However, these differences did not reach statistical significance. Additionally, the overall CDR3 nucleotide sequence length in the diseased and control groups was intentionally shorter in the diseased group (16.91 ± 3.727 vs 17.44 ± 3.836, p < 0.0001).
3.2 Comparison of Gene Segment Usage Frequencies
Certain IGHV and IGHD gene segments exhibited significant differences in usage between the disease and control groups (Fig. 1A, B), while there are no significant differences in overall usage frequency regarding the IGHC and IGHJ segments between the patient and control groups (Fig. 1C, D). However, Specifically, IGHV3-30-3, IGHV4-28, IGHV4-30-2, IGHV4-30-4, IGHD5-5, and IGHD5-18 were significantly more frequently utilized in the disease group than in the control group, whereas IGHV1/OR15-2, IGHV3-69-1, and IGHV3/OR16-6 showed significantly lower usage frequencies in the disease group compared to the control group (Fig. 1A, B). Among these, the most notable differences (p < 0.01) were observed for IGHD5-5 (1.63614% vs. 0.547188%, p = 0.0001), IGHD5-18 (1.607832% vs. 0.546591%, p = 0.0001), and IGHV1/OR15-2 (0.061765% vs. 0.13043%, p = 0.0080) (Fig. 2).
Fig. 1
Comparison of IGHV, IGHD, IGHC, and IGHJ gene usage frequencies in IgG-BCR
The average usage rates of IGHV (A), IGHD (B), IGHC (C), and IGHJ (D) genes are presented. The bar graphs and error bars display the mean usage rates and standard deviations for 15 ACA-positive patients and 5 control patients. In the disease group, the usage frequencies of IGHV3-30-3, IGHV4-28, IGHV4-30-2, IGHV4-30-4, IGHD5-5, and IGHD5-18 were significantly higher than in controls, while IGHV1/OR15-2, IGHV3-69-1, and IGHV3/OR16-6 were significantly lower. No genes within IGHJ or IGHC showed significant differences between the groups.
Fig. 2
Genes with significant differences in usage frequency
Among the genes with significant differences in usage frequency, those with a significance level of p < 0.01 were IGHD5-5, IGHD5-18, and IGHV1/OR15-2.
3.3 Structural Analysis of the CDR3 Region Containing IGHD5-5 and IGHV1/OR15-2
To further investigate the structure of the CDR3 in IgG-BCR-expressing B cell clones containing IGHD5-5 and IGHV1/OR15-2, we conducted a detailed analysis. The CDR3 region is a highly variable sequence within the variable region of antibodies and T cell receptors that plays a crucial role in antigen recognition. The CDR3 region, particularly in the heavy chain, is formed through the recombination of variable (V), diversity (D), and joining (J) segments, resulting in extensive structural and sequence diversity. Such diversity underlies the immune system’s ability to recognize a vast array of antigens. Since all IGHD5-18 segments were included within the IGHD5-5 category, further structural analysis of IGHD5-18 was omitted.
3.4 Sequence Length Comparison and Sequence Logo Analysis
The nucleotide sequence lengths ranged from 9 to 31 for IGHD5-5 and from 9 to 35 for IGHV1/OR15-2. The distribution of IGHD5-5 sequences lengths approximated a normal distribution, with similar usage frequencies between the ACA-positive and control groups (Fig. 3A). In contrast, IGHV1/OR15-2 exhibited an irregular distribution pattern (Fig. 3B). Further analysis of sequence length distributions revealed statistically significant differences in specific nucleotide sequence lengths between the ACA-positive and control groups. In IGHD5-5, significant differences were observed at sequence lengths of 15 (10.622% vs. 2.089982%, p = 0.0230; Fig. 4A), 23 (1.033462% vs. 0.040689%, p = 0.0292; Fig. 4B), and 24 (2.021335% vs. 0.033879%, p = 0.0238; Fig. 4C). For IGHV1/OR15-2, a significant difference was identified at sequence length 18 (14.3727% vs. 0.31008%, p = 0.0199; Fig. 4D). Given the potential similarity of CDR3 sequences at the 15-nucleotide sequence length across different individuals, we employed sequence logo plot visualization for comparative analysis. Sequence logo plots are widely used in bioinformatics to visualize sequence conservation and patterns across nucleotides or amino acids11. These plots provide a graphical representation of sequence conservation at each position, with letter heights reflecting the degree of conservation. The information content is measured in bits, with higher values indicating greater sequence conservation. Larger letters denote more frequently occurring nucleotides or amino acids at a given position. Due to the limited number of clones available for sequence lengths 23, 24, and 18, comparative analysis was restricted to clones with a sequence length of 15 nucleotides. Although the smaller sample size in the control group led to an overall increase in relative frequency values, visual comparisons revealed that, unlike the ACA-positive group, the control group did not exhibit dominant nucleotide patterns, suggesting greater sequence variability(Fig. 5A,B). To further validate these findings, we compared IGHD3-10 and IGHD5-5 within the disease group(Fig. 5A,C), as these genes exhibited no significant differences in usage frequency between disease and control groups and were supported by relatively large sample sizes. The comparison revealed substantial variability in IGHD3-10 sequences. Next, we compared IGHD5-5 clones with sequence length 15 to those with sequence length 16, as the latter showed no significant differences in frequency between the disease and control groups and were similarly well represented(Fig. 5A,D). While the overall sequence conservation levels remained comparable, the IGHD5-5 sequences of length 15 exhibited a more distinct and conserved nucleotide pattern. These findings suggest that the CDR3 region of IGHD5-5 sequences with a length of 15 nucleotides displays reduced variability and greater sequence similarity compared to other IGHD genes and sequence lengths.
Fig. 3
Comparison of CDR3 lengths of the IGHD5-5 and IGHV1/OR15-2 genes between the ACA-positive and control groups
The nucleotide sequence length ranged from 9 to 31 for IGHD5-5 (A) and from 9 to 35 for IGHV1/OR15-2 (B). The IGHD5-5 gene approximated a normal distribution, with similar usage frequencies observed between the ACA-positive and control groups; however, IGHV1/OR15-2 displayed an irregular distribution.
Fig. 4
Statistically significant nucleotide sequence length
The nucleotide sequence lengths that showed statistically significant differences between the ACA group and the control group were 15 (A), 23 (B), and 24 (C) nucleotides for IGHD5-5, and 18 nucleotides for IGHV1/OR15-2 (D).
Fig. 5
Sequence logo plot
The smaller sample size in the control group led to an overall increase in relative frequency values; however, visual comparisons revealed that, unlike the ACA-positive group(A), the control group(B) did not exhibit dominant nucleotide patterns, suggesting greater sequence variability.To further validate these findings, we compared IGHD3-10(C) and IGHD5-5(A) within the disease group, as these genes exhibited no significant differences in usage frequency between disease and control groups and were supported by relatively large sample sizes. The comparison revealed substantial variability in IGHD3-10 sequences. Next, we compared IGHD5-5 clones with sequence length 15(A) to those with sequence length 16(D), as the latter showed no significant differences in frequency between the disease and control groups and were similarly well represented. While the overall sequence conservation levels remained comparable, the IGHD5-5 sequences of length 15 exhibited a more distinct and conserved nucleotide pattern.
Discussion
The observed biases in IGHD5-5 usage, CDR3 nucleotide sequence length, and sequence composition in this study are likely the result of selection pressure exerted by a specific antigen. However, the precise identity of this antigen remains undetermined.
Similar studies on BCR repertoires in autoimmune diseases have reported characteristic deviations in gene usage and CDR3 length. For instance, in SLE, an increased frequency of IGHV4 family gene usage and significantly longer CDR3 sequences compared to healthy individuals have been documented7. In rheumatoid arthritis, IGHV4-34 has been found to be upregulated in synovial tissue, along with elongation of the CDR3 region12. In multiple sclerosis (MS), a decrease in IGHV1-69 and an increase in IGHV3-23 have been observed9, accompanied by a reduction in BCR repertoire diversity. Additionally, in type 1 diabetes, an increased frequency of IGHJ6 gene usage has been reported13.
With regard to SSc, studies have described a decreased usage of IGHV5-5114, while IGHV3-9 and IGHJ4 have been reported to exhibit significantly higher usage frequencies. Furthermore, the CDR3 length was significantly shorter and repertoire diversity was increased in SSc compared to healthy controls15. In patients with SSc complicated by pulmonary hypertension, IGHV2-5 usage was found to be lower16. Despite these findings on BCR repertoire alterations in autoimmune diseases, including SSc, no studies to date have successfully identified specific antigens responsible for these biased repertoires. Moreover, there is a lack of research explicitly addressing future methodologies for antigen identification.
Interestingly, in Myalgic encephalomyelitis/chronic fatigue syndrome, a higher frequency of IGHV3-30/3-30-3 usage has been reported. These genes have also been implicated in immune responses to various infectious diseases, including malaria, influenza, and COVID-1917, suggesting that biases in specific gene family usage may not be exclusive to autoimmune mechanisms but could also be associated with infectious agents. While the direct link remains speculative, it aligns with previous studies suggesting a potential role for viral and microbial antigens in autoimmune B-cell activation18. Additionally, in T-cell repertoire studies, databases exist that allow the inference of antigen specificity based on CDR3 sequences. If similar databases are developed for BCR repertoires through the accumulation of comprehensive sequencing data, it may become possible to advance antigen identification efforts in B-cell-mediated immune responses.
While this study provides valuable insights into the BCR repertoire inSSc patients positive for ACA, several limitations should be acknowledged. First, the sample size of this study was relatively small, consisting of 15 ACA-positive SSc patients and 5 healthy controls. Although the findings suggest significant differences in gene usage and CDR3 sequence characteristics, larger cohort studies are necessary to validate these observations and confirm their generalizability to the broader SSc patient population. This study exclusively included female participants, which limits the generalizability of the findings to male SSc patients. Sex-based differences in immune responses have been suggested to influence selection pressure on B cells, with estrogen in particular being reported to contribute to the risk of developing autoimmune diseases19. Given these potential immunological differences, future studies should incorporate a more diverse population, including male SSc patients and postmenopausal women, to determine whether the observed BCR repertoire biases are consistent across sexes and to elucidate the impact of sex hormones on BCR repertoire composition and selection dynamics.
Third, the study focused on a specific subset of SSc patients—those with ACA positivity. While this approach minimized potential confounding factors, it also restricts the applicability of the findings to other SSc subtypes, particularly those with anti-topoisomerase I (Scl-70) or anti-RNA polymerase III antibodies, which may exhibit distinct immunological characteristics.
Although the study suggests that selection pressure from an unknown antigen may be driving IGHD5-5 usage biases, the precise antigenic stimuli remain unidentified. Further investigations utilizing antigen-specific B-cell sorting, functional assays, and structural analysis of antibody-antigen interactions are necessary to elucidate the underlying mechanisms. Despite these limitations, the study provides a valuable foundation for future research aimed at unraveling the role of B cells in SSc pathogenesis and identifying potential biomarkers or therapeutic targets.
In conclusion, this study provides novel insights into the BCR repertoire in patients with SSc positive for ACA. Our findings reveal a significant increase in the usage of IGHD5-5 and IGHD5-18 gene segments, accompanied by characteristic biases in CDR3 nucleotide sequence length and composition. These biases suggest that specific antigenic selection may be shaping the BCR repertoire in ACA-positive SSc patients. Although previous studies have demonstrated altered BCR repertoires in autoimmune diseases, including SSc, the antigenic drivers of these biases remain unidentified. The selective expansion of IGHD5-5-containing B-cell clones with a conserved CDR3 sequence highlights a potential avenue for future research into disease-specific antigen recognition. Further investigations, including antigen discovery approaches and functional analyses, are warranted to elucidate the immunological mechanisms underlying these repertoire alterations. Our findings contribute to a deeper understanding of the humoral immune response in SSc and suggest that the BCR repertoire could serve as a biomarker for disease progression or therapeutic response. Additionally, the identification of disease-associated BCR patterns may facilitate the development of targeted immunotherapies aimed at modulating autoreactive B-cell populations.
Age | Sex | Autoantibodies | Disease duration (years) | ILD | PAH | SSc subset | GERD | |
|---|---|---|---|---|---|---|---|---|
01 | 74 | F | ACA | 2 | + | - | limited | + |
02 | 64 | F | ACA | 13 | - | - | limited | - |
03 | 60 | F | ACA | 21 | - | + | limited | + |
04 | 59 | F | ACA | 4 | - | - | limited | - |
05 | 48 | F | ACA | 7 | - | - | limited | + |
06 | 53 | F | ACA | 5 | - | - | limited | - |
07 | 59 | F | ACA | 8 | - | - | limited | + |
08 | 75 | F | ACA | 20 | + | - | limited | - |
09 | 73 | F | ACA | 21 | - | - | limited | + |
10 | 67 | F | ACA | 3 | - | - | limited | + |
11 | 68 | F | ACA | 8 | - | - | limited | + |
12 | 48 | F | ACA | 3 | - | - | limited | + |
13 | 64 | F | ACA | 2 | - | - | limited | - |
14 | 57 | F | ACA | 2 | - | - | limited | + |
15 | 54 | F | ACA | 6 | - | + | limited | + |
| ACA: anti-centromere antibody, ILD: Interstitial lung disease, PAH: pulmonary arterial hypertension, GERD: Gastro Esophageal Reflux Disease | ||||||||
Acknowledgements
This work was supported by JSPS KAKENHI Grant Number 22K08375. We thank Masako Matsubara for their technical assistance.
Conflict of interest statement
None declared.
Electronic Supplementary Material
Below is the link to the electronic supplementary material
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Author Contribution
Ko Fujii (K.F.) conceived and designed the study, performed data processing and formal statistical analyses, curated the dataset, and prepared all figures and tables. K.F. drafted the original manuscript. Motoki Horii (M.H.), Kenta Kudo (K.K.), Jiro Nishio (J.N.), Natsumi Fushida (N.F.), Tasuku Kitano (T.K.), Kie Mizumaki (K.M.), and Kyosuke Oishi (K.O.) recruited participants, collected clinical samples, and contributed to data acquisition. Yasuhito Hamaguchi (Y.H.) and Takashi Matsushita (T.M.) provided clinical oversight, essential resources, and supervision. All authors reviewed the manuscript critically for important intellectual content, approved the final version, and agree to be accountable for all aspects of the work.
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Supporting information
Additional supporting information can be found online in the Supporting Information section at the end of this article.
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Data Availability
The raw sequencing data generated in this study have been deposited in the NCBI Sequence Read Archive (SRA) under accession number PRJNA1333387.Please note that raw data for Patients 1, 2, and 8–15 were unfortunately lost during storage. Nevertheless, these patients were included in the analyses, and their processed repertoire summary data underlying the findings are available as Supplementary Data (Excel file).
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Funding.
This work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI, Grant-in-Aid for Scientific Research (C) [Grant Number 22K08375].