Analysis of the heterogeneity of the BCR H-CDR3 repertoire in peripheral blood B cells of adult women with increasing age in Central China

Analysis of the heterogeneity of the BCR H-CDR3 repertoire in peripheral blood B cells of adult women with increasing age in Central China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of the heterogeneity of the BCR H-CDR3 repertoire in peripheral blood B cells of adult women with increasing age in Central China Lina Ma, Hu Zhang, Wenyi Wang, Lili Chen, Xinrui Lei, Lijuan Fan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7535948/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract With the intensification of population aging, the health issues of the elderly have attracted increasing attention. The structure and function of the immune system decline with age, and changes in the quantity, subsets, and functionality of B cells are closely associated with aging. In this study, high-throughput sequencing (HTS) was employed to analyze the diversity and dynamic changes of the B-cell receptor (BCR) H-CDR3 repertoire in peripheral blood samples from nine healthy adults across different age groups (young, middle-aged, and elderly). The results revealed that the CDR3 amino acid(AA) length in the middle-aged group was significantly longer than that in the young and elderly groups (P < 0.05). Additionally, significant differences in IGHV gene usage were observed among the age groups, suggesting that IGHV gene usage is strongly influenced by age. Furthermore, the number of shared AA sequences in the BCR increased with age, reflecting the cumulative effects of antigen exposure. Although no significant differences in clonal diversity or clonal frequency distribution were detected among the age groups, the elderly group exhibited a more concentrated clonal frequency distribution, indicating that the immune system's antigen-specific response becomes more focused with aging. This study provides new insights into the impact of age on the BCR and lays a foundation for future research on age-related diseases and personalized therapies. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Immunosenescence is a complex process involving multiple changes in recombination, development, and regulation, rather than a simple decline in function. However, the significant reduction of certain immunological indicators in the elderly is often closely related to good functional and health status. The elderly immune system is characterized by decreased sensitivity to vaccines and infections, and increased incidence of autoimmune diseases and cancer [ 1 ]. Studies on age-related changes in the quantity, subsets, and functions of B cells play an important role in aging and vaccine development. When the body ages, the quantity and quality of antibodies produced differ from those in the young stage. With increasing age, the immune effect of vaccines decreases significantly. Under the same intensity of antigen stimulation, the number of B cells produced by elderly animals is less than that by adult animals [ 2 ]. Studies on immunoglobulin gene repertoires suggest dynamic changes with age [ 3 ]. Age-related immune system defects may be due to restrictions on bone marrow B cell production or migration to peripheral lymphoid tissues caused by peripheral homeostasis pressure [ 4 ]. The total number of B cells remains unchanged for most of life [ 5 ]. Therefore, it is generally believed that it is the quality of B cells or antibody repertoires that changes with age, leading to a decline in the effectiveness of antibody responses with increasing age. Although most studies on the impact of aging on hematopoietic stem cell function have used mouse models, recent work has demonstrated similarities in aging effects between mice and humans [ 6 ]. The ability of hematopoietic stem cells to generate lymphoid progenitors is impaired in the elderly, and differences in bone marrow output are observed. In addition, like in mice, the absolute number of human hematopoietic stem cells increases with age, and genes responsible for myeloid differentiation are upregulated. Thus, age-related changes in hematopoietic stem cell potential in mice and humans may share some common characteristics [ 6 ]. Antibodies are a class of globulins produced by plasma cells, which are derived from B cells that recognize antigens, become activated, proliferate, and differentiate. They can specifically bind to corresponding antigens and are important effector molecules in immune responses. Immunoglobulins are globulins with a chemical structure similar to antibodies. They mainly exist in body fluids, called secreted Ig (SIg), and a small part exists on the surface of B cells, called membrane Ig (MIg), i.e., B cell surface antigen receptors (BCR). BCR is a tetramer composed of two homologous heavy chains and two homologous light chains, which is divided into the variable region (V region), constant region (C region), and hinge region (H region). Among them, the AA composition and sequence of 3 subregions in the V region are highly variable, which are called Complementarity Determining Regions, namely CDR1, CDR2, and CDR3. The non-CDR regions in the V region with relatively small changes are called framework regions (FRs); 4 FRs separate the 3 CDRs and serve to maintain the spatial configuration of the CDRs. The key part of BCR for recognizing antigen peptides is the most diverse CDR3 region [ 7 ]. The gene sequence encoding the human BCR heavy chain CDR3 region is composed of the rearrangement of discontinuous IGHV (56 functional gene segments) terminal - IGHD (23 functional gene segments) - IGHJ front-end (6 functional gene segments) gene segments, as well as the nucleotides (N/P base sequences) inserted or deleted during V-D and D-J joining. Moreover, when B cells migrate to the periphery for further development after central rearrangement and selection, class switching and somatic hypermutation occur in the germinal center. These factors endow BCR with extremely high diversity, which enables B cells to respond to almost all antigens [ 8 , 9 ]. B cells recognize specific antigens and produce antibodies through BCR. The diversity of the BCR H-CDR3 repertoire is related to antigen recognition ability. Detection of the BCR H-CDR3 repertoire in B cells can determine the ability of B cells to recognize antigens, thereby reflecting the immune status of the body. When mature B cells are induced by peripheral antigens, high-frequency point mutations occur in the heavy and light chain V genes of germinal center cells, which will greatly increase the diversity of BCR. In mice and humans, this mechanism is called somatic hypermutation (SHM). Currently, HTS has been widely applied to monitor the T/B cell repertoires in normal and diseased individuals, and systematic analysis methods for T/B cell repertoires have been established [ 10 – 12 ]. To better understand the diversity of human BCR repertoires, many studies have performed deep sequencing on BCR sequences, especially the heavy chain CDR3 region sequences, to estimate the diversity of human B cell receptor repertoires and analyze their compositional characteristics. It is currently believed that the initial stage of human V (D) J gene segment rearrangement is not completely random, but has a certain genetic bias in the selection of V-D-J pairing. The diversity of BCR H-CDR3 ranges from 3–9×10 9 , and there are some consistent sequences among different individuals [ 13 ]. At present, monitoring the peripheral blood B cell receptor repertoire of the same individual at different times through HTS can help discover the dynamic changes of human peripheral blood B cell receptor repertoire [ 14 ]. The above studies provide a research basis for exploring the correlation between the formation of BCR repertoires and genetic and environmental factors. Currently, the emergence of HTS enables comprehensive research on changes in the Ig gene repertoire. Studies on identical twins have shown that the selection of immunoglobulin gene segments is strongly influenced by genetic and environmental factors [ 15 ]. Therefore, any observed age- or disease-related changes in gene usage, especially changes in the CDR3 region, may reflect environmental influences or may be caused by individual differences. For this reason, we used HTS to analyze the BCR H-CDR3 repertoire of B cells in healthy adults of different ages, aiming to understand the dynamic changes of the BCR H-CDR3 repertoire of B cells. In this study, we selected peripheral blood from healthy adults of three age groups and used HTS to obtain the sequences of B cell BCR H-CDR3 repertoires, in order to preliminarily explore the homogeneity and heterogeneity of B cells in healthy adults and gain an in-depth understanding of the composition and characteristics of human peripheral blood B cell repertoires. RESULTS CDR3 length distribution An important determinant of B-cell repertoire diversity is the length of the BCR H-CDR3 loop. In this study, the length distribution of the AA sequences in the CDR3 region of all clones from each sample was analyzed. It was found that the length of the BCR H-CDR3 region in all nine volunteers followed a Gaussian distribution centered around 16–18 AA. Statistical analysis revealed that the percentage of 37-amino acid sequences in the middle-aged group was significantly higher than that in the young and elderly groups (P < 0.05, Fig. 1). The average CDR3 length in the young group was 18.38 AA, in the middle-aged group it was 18.81 AA, and in the elderly group it was 18.25 AA. The middle-aged group exhibited longer CDR3 lengths compared to both the young and elderly groups. Gene usage frequency in the BCR H-CDR3 repertoire IGHV gene usage( Fig. 2a ) :(1)In the BCR H-CDR3 repertoire, the IGHV gene families were analyzed across nine samples. The top 20 IGHV genes used were: IGHV1-18 , IGHV1-2 , IGHV1-3 , IGHV1-46 , IGHV1-69 , IGHV1-8 , IGHV2-5 , IGHV3-23 , IGHV3-30 , IGHV3-33 , IGHV3-53 , IGHV3-7 , IGHV3-74 , IGHV3-9 , IGHV4-34 , IGHV4-39 , IGHV4-4 , IGHV4-61 , IGHV5-51 , and IGHV7-81 .༈2༉High-frequency usage: IGHV1-8 usage was significantly higher in the middle-aged group compared to the young and elderly groups. IGHV3-30 and IGHV4-4 usage was notably higher in the elderly group compared to the young and middle-aged groups. IGHV3-7 showed significant differences in usage with increasing age. IGHV5-51 was more frequently used in the young group compared to the middle-aged and elderly groups (P < 0.05).༈3༉Low-frequency usage: With increasing age, IGHV1-67 , IGHV1-68 , IGHV3-16 , IGHV3-20 , IGHV3-49 , and IGHV3-72 exhibited statistically significant differences (P < 0.05). IGHJ gene usage(Fig. 2b) IGHJ4 and IGHJ6 genes are frequently used in all 9 samples. Statistical analysis reveals that there are no significant differences among the six IGHJ gene families. IGHV-IGHJ pairing in the BCR H-CDR3 repertoire(Fig. S1) The recombination of V-J gene segments encodes the CDR3 region, contributing to its extensive diversity. The pairing usage of V-J genes reflects the diversity of the CDR3 repertoire. We compared the V-J gene pairing usage in the BCR H-CDR3 repertoire across different age groups. The results indicate that there are many similarities in the usage of V-J gene combinations among the groups, while certain differences in expression levels were also observed. Clonal diversity and clonal frequency distribution Analysis of clonal expansion in BCR H-CDR3 repertoire The inverse Simpson’s diversity index (1/DS) is widely recognized for evaluating the diversity changes in T/B cell CDR3 repertoires between diseased and healthy individuals [16, 17]. The corrected formula for the inverse Simpson’s index is calculated as 1/DS = 1/∑{ni*(ni-1)}/{n*(n-1)}, where ni represents the total number of the i-th sequence. A higher 1/DS value indicates greater diversity and lower clonal expansion [18]. The frequency of unique CDR3 sequences was sorted from high to low, with the Y-axis displayed on a Log10 scale to represent frequency magnitude. The clonal distribution of the three BCR H-CDR3 repertoires was similar, as shown in Fig. 3a. Statistical analysis of the 1/DS values across the three groups revealed no significant differences ,as shown in Fig. 3b(P > 0.05). The clonal expansion frequencies of each sample were divided into three intervals based on the total distribution range: Highly Expanded Clones (HEC): Frequency > 0.1%. Intermediate Expanded Clones (MEC): Frequency between 0.03% and 0.1%. Low Expanded Clones (LEC): Frequency < 0.03%. The results showed that the majority of sequences in the repertoires of all three groups belonged to LEC with frequencies below 0.03%, as shown in Fig. 3c. Subsequent statistical analysis of the differences between the three groups revealed no significant disparities, indicating high similarity among the groups. Smaller differences suggest greater similarity, and no notable variations were observed. See Fig. 3d for details. Clonal frequency distribution and D50 analysis : The clonal frequency distribution graph provides a visual representation of the frequency distribution of all clonal types within each sample. D50 is a recently introduced metric that reflects the clonal population structure of a sample. A lower D50 value indicates a more concentrated clonal frequency distribution, while a higher value suggests a more dispersed distribution [19]. For detailed data, refer to supplementary Fig. 2. Among the three groups, the young group exhibited the highest D50 values, indicating a more dispersed clonal frequency distribution. The middle-aged group showed slightly lower D50 values, while the elderly group had the lowest D50 values, reflecting the most concentrated clonal frequency distribution. However, statistical analysis revealed no significant differences among the groups. The clonal frequency distributions for all samples are shown in Fig. 4a. Shared Clones The shared clones among samples intuitively reflect the commonalities between two samples, and the evaluation of shared clones can be carried out by comparing the nucleotide sequences (nt) and amino acid sequences (aa). The heatmap of shared clones between two samples, characterized by the percentage of shared aa clone numbers in the total, has both X-axis and Y-axis representing each sample. The color represents the number or percentage of shared clones between two samples (the lighter the color, the more clones, and vice versa). It can be seen from the figure that the proportion of common clones in the group is slightly higher, while that between groups is lower. However, sample B1 has more common clones with the three samples in group A, and sample B1 is more similar to the samples in group A (Fig. 4b). There are various indicators to measure the similarity between samples, including the Pearson correlation coefficient of clone frequency (P), the relative clone overlap between samples (D), the geometric distance of clone overlap between samples (F), and the clonotype-wise geometric distance of clone overlap (F2) [20]. These indicators are used to calculate the distance between samples for hierarchical clustering. In this project, the geometric distance of clone overlap (F) was adopted for evaluation. The same color represents the same group, and samples that are closer to each other have higher similarity.Cluster analysis revealed that the young, middle-aged, and elderly groups all followed the age distribution. The three samples in group A were relatively close to each other. Among the three samples in group B, samples B2 and B3 were closer, while sample B1 was farther away, showing a certain difference in similarity from the other samples in group B, but was closer to and more similar to the samples in group A. The three samples in group C were close to each other and relatively similar (Fig. 4c). The shared clones among samples directly reflect the commonalities between two samples. We can intuitively observe the commonalities of AA sequences among different age groups by using Venn diagrams. In this experiment, an analysis was conducted on the shared AA sequences in the BCR H-CDR3 repertoire of peripheral blood B cells from different age groups. The number of shared AA sequences in the BCR H-CDR3 repertoire of peripheral blood B cells in the young group was 186; that in the middle-aged group was 237; and that in the elderly group was 246. As can be seen from the figures, the number of shared amino acids among samples in each group increases with age (Fig. 4d, 4e, 4f). B cell SHM (Somatic Hypermutation) statistics Nucleotide truncation and insertion: The BCR H-CDR3 receptor repertoire undergoes not only V(D)J rearrangement but also nucleotide truncation and insertion at the V(D)J junctions, mainly mediated by terminal deoxynucleotidyl transferase (TdT). This further enriches the diversity of the CDR3 receptor repertoire on the basis of the diversity from random rearrangement. The diversity of CDR3 arises from "N" nucleotide insertions at the V→D (N1) and D→J (N2) junctions, exonucleolytic truncations (3' V truncation, 5' D truncation, and 5' J truncation), and additions of palindromic "P" nucleotides (P3' V , P5' D , and P5' J ) [21]. Statistics were conducted on single-base mutations in the B cell CDR3 region, and the results are shown in Table 3. Statistical analysis revealed no significant differences (Fig. 5). DISCUSSION We analyzed the distribution of CDR3 lengths in an average of 92.9844 filtered sequencing reads per sample, which provides extensive information on the BCR repertoires across different age groups. For instance, we identified the most frequently observed lengths. Variable rearrangements result in different CDR3 lengths, and the characteristics of BCR clonality can be determined by measuring the lengths of the CDR3 repertoire. Generally, the range of CDR3 lengths is related to the degree of CDR3 diversity. For the same species, the wider the range of CDR3 lengths and the closer it is to a normal distribution, the higher the diversity of the CDR3 repertoire [ 22 , 23 ]. In our study, the percentage of 37-amino-acid length in the middle-aged group was significantly higher than that in the young and elderly groups. It has been reported in the literature that the length of CDR3 in BCR on B cells is longer in adults than in infants [ 21 ]. Another literature reported that the CDR3 length in humans is similar to that in mice, and the CDR3 region in the elderly is longer than that in young people, mainly due to the response to recognized antigens, mutations, and clonal proliferation [ 24 ]. The average AA length in the young group was 18.38, 18.81 in the middle-aged group, and 18.25 in the elderly group, with no significant differences. However, the fact that the average AA length in the young group was shorter than that in the middle-aged group may be because the young group encounters limited antigens during growth, and the number of cell subsets is smaller than that in the middle-aged group, resulting in shorter AA lengths and lower diversity than the middle-aged group. The elderly group had a shorter length than the young and middle-aged groups, with reduced diversity, which may be caused by immune aging; it may also be due to individual differences caused by the small sample size, which requires further research. There was no significant difference in the AA length distribution of the peripheral blood BCR H-CDR3 repertoires among the three age groups, further suggesting that the external environment has no impact on the AA length distribution of the CDR3 receptor repertoire, which is consistent with previous studies [ 22 ]. Rubelt F et al. [ 25 ] found that the length of inserted and deleted nucleotide sequences in the naive BCR H-CDR3 receptor repertoire is not affected by genetic factors, while the formation of nucleotide sequences in the memory BCR H-CDR3 receptor repertoire is mainly related to external antigen stimulation. The usage of IGHV in the BCR H-CDR3 repertoire varies among the 9 samples. IGHV1-67 , IGHV1-68 , IGHV1-8 , IGHV3-16 , IGHV3-20 , IGHV3-30 , IGHV3-49 , IGHV3-7 , IGHV3-72 , IGHV4-4 , and IGHV5-51 show significant statistical differences. Among them, IGHV1-8 , IGHV3-30 , IGHV3-7 , IGHV4-4 , and IGHV5-51 are not only used at high frequencies but also exhibit significant differences. The significant differences in IGHV genes suggest that IGHV usage is affected by age. There is no difference in IGHJ usage with increasing age among the three groups, indicating that IGHJ usage is less affected by age. IGHJ4 and IGHJ6 genes are used at high frequencies in all three groups with no significant differences. Theoretically, the usage frequency of V(D)J gene segments is random in pro-B cells or during pro-B cell recombination (before the selection of self-antigens). However, in vitro experiments conducted in B cell lines have confirmed that the contribution of V(D)J gene segments to the main components is uneven, and the consensus heptamer and nonamer sequences of the recombination signal sequence (RSS) are considered the main factors [ 26 ]. This result suggests that IGHJ4 and IGHJ6 may be related to the regulation of RSS, and the specific mechanism needs further research to confirm. The usage trend of V and J genes in peripheral blood is roughly the same among people of different ages. This is due to the same reasons as the reported similarity in V and J gene usage between neonatal and adult peripheral blood, namely, the same species, similar genetic background, and little difference in living environment [ 22 ]. Glanville J et al. [ 27 ] found that the usage frequency of IGHV differs among unrelated individuals, while the usage frequency of IGHJ shows no significant genetic differences regardless of whether there is a relationship between individuals. Glanville J et al. [ 27 ] further analyzed Ig transcripts from class-switch recombination regions that have experienced antigens and found that IGHV usage during class switching is significantly related to the profile of their respective naive repertoire IGHV usage. Even when variations occur, the usage frequency of most gene segments in class switching and the naive repertoire is similar. The human adaptive immune response controls defense against pathogens by expressing a variety of specific antigen receptors. During early developmental stages, a unique B cell receptor repertoire is ultimately formed through the combination of a randomly selected set of V(D)J gene segments from the initial genes, a process known as V(D)J gene rearrangement [ 28 ]. Although the process of selecting gene segments for rearrangement is largely random, some gene segments are used more frequently than others [ 26 , 29 ]. Studies have shown that the overall bias in gene segment usage is caused by multiple factors, including preferential recombination between V and (D)J segments, selection based on self-tolerance during development, and the distance between V(D)J gene segments [ 30 – 32 ]. Rubelt F et al. [ 25 ] used the "Repertoire Dissimilarity Index (RDI)" as a measure of the distance between receptor repertoires and quantified that genetic factors have a significant impact on the gene recombination process and receptor repertoire formation of naive B cells, CD4 + T cells, and CD8 + T cells. They also showed that genetic differences in the naive cell repertoire can be observed in the memory cell repertoire, which also proves from the perspective of the CDR3 receptor repertoire that individual genetic factors have differential effects on the cell receptor repertoire. Studies have reported that the clonal diversity of peripheral B cell repertoires decreases with age in the human body, and this reduction may already occur in the bone marrow [ 33 – 35 ]. In this experiment, a comparative analysis of the clonal diversity of peripheral blood B cell repertoires among humans of different ages was conducted, revealing that the clonal diversity of peripheral blood B cell repertoires decreases with age. However, statistical analysis of 1/DS among 9 volunteers showed no significant differences, indicating that there is no correlation in the clonal diversity of the CDR3 receptor repertoire regardless of the age relationship between individuals. The changing trends of HEC, MEC, and LEC among the 9 volunteers were similar, with no statistical differences. The main reason is that the diversity of the BCR H-CDR3 receptor repertoire stems from the diversity of V (D) J gene rearrangement and the joining diversity of nucleotide insertions and deletions, and gene rearrangement as well as nucleotide insertions and deletions are completed during the recombination stage. This also explains that environmental factors have minimal impact on the diversity of the BCR H-CDR3 receptor repertoire, which is consistent with previous studies [ 21 ]. Rubelt F et al. [ 25 ] found that genetic factors influence the formation of the naive B cell repertoire, and this influence is transmitted to the memory B cell repertoire, suggesting that the proliferative clonal sequences of the BCR H-CDR3 receptor repertoire are greatly affected by genetic factors. However, since the 9 volunteers belong to the same species with little difference in genetic background, the differences in the peripheral blood repertoires are small. From the perspective of clonal distribution, there are differences in the clonal distribution of the 9 samples with increasing age. The younger the age, the more dispersed the clonal frequency, and the higher the diversity of the immune system; with increasing age, the clonal frequency becomes concentrated, reflecting the specific response of the immune system to antigens. However, statistical analysis showed no significant differences, suggesting that in the same species, age has little impact on clonal frequency, mainly due to the small differences in genetic background and living environment. Each unique CDR3 sequence represents a type of B cell and can specifically recognize antigens. The overlapping sequences between samples are the common sequences among the samples, which respond to the same antigenic epitopes [ 36 ]. The analysis results showed that the number of shared AA sequences in the peripheral blood of people of different ages increases with age. This is mainly because the number of antigens encountered in human life increases with age, and people living in the same environment will encounter similar antigens, thus leading to an increase in overlapping sequences. However, these overlapping sequences account for a small proportion of the total individual sequences. The formation of overlapping sequences is related to three factors: nucleotide insertion, deletion, and TdT. Consistent with previous studies, the number of shared clonal proliferation sequences in the CDR3 receptor repertoire between two individuals is small regardless of whether they are related [ 37 ]. Rubelt F et al. [ 25 ] found that the length of inserted and deleted nucleotide sequences in the naive BCR H-CDR3 receptor repertoire is not affected by genetic factors, while the formation of nucleotide sequences in the memory BCR H-CDR3 receptor repertoire is mainly related to stimulation by external antigens. This indirectly reflects that the number of overlapping AA sequences in the BCR H-CDR3 receptor repertoire between individuals accounts for a small proportion of the total number. From the analysis of shared clones and multi-sample clustering, it can be seen that the clonal overlaps among the three samples in group A are relatively similar, and the clonal overlaps among the three samples in group C are also relatively similar, suggesting that clonal overlap is affected by age. However, sample B1 is quite different from the other two samples in group B, which may be related to stimulation by external antigens or individual differences. The classic "clonal selection theory" holds that during the development of T cells in the thymus and B cells in the bone marrow, various V , D , and J gene segments of germline genes undergo "completely random" rearrangement to generate TCR and BCR CDR3 receptor repertoires [ 38 ]. Nucleotide insertions and deletions are also "random" and occur during the "completely random" rearrangement of V(D)J , mainly accomplished by exonucleases and TdT [ 26 ]. Under the stimulation of peripheral antigens, recombination or mutation may occur in the V-D-J gene segments of BCR, a mechanism known as somatic hypermutation [ 39 ]. The results of this experiment suggest that age factors have little impact on nucleotide insertions and deletions in the peripheral blood BCR H-CDR3 receptor repertoire. V-D-J recombination is a random process that generates the initial diversity of the repertoire. The adaptive immune system relies on the functional sequences generated by this initial diversity and the specificity of the receptor repertoire. Previous studies on human repertoires have shown that compared with adults, the diversity of neonatal repertoires is limited, mainly through recombination or a small number of “N” insertions [ 40 ]. As the body ages, more nucleotide insertions and deletions occur. Our comparison of nucleotide insertions and deletions among people of different ages found that, in terms of the overall trend, the same insertions and deletions show roughly similar trends across different age groups, which is consistent with previously reported information. Through systematic analysis of the BCR immune repertoire in healthy adults of different age groups, we have not only deepened the understanding of the characteristics of the immune repertoire in the normal population in central China but also laid a scientific foundation for exploring age-related diseases and therapeutic monitoring, thereby providing a basis for the optimization of future treatment strategies. Although this study is limited by the sample size, with the decrease in the cost of HTS, future studies are expected to expand the sample size, cover more age groups, populations and health statuses, and further reveal the role of the BCR repertoire in aging, immune response and immune-related diseases. These research results are expected to be transformed into disease markers, contributing to the development of early diagnosis and personalized medicine. CONCLUSION This experiment employed HTS to preliminarily investigate the impact of aging on the characteristics of the BCR H-CDR3 repertoire in human peripheral blood B cells. It revealed that the BCR H-CDR3 repertoire exhibits temporal heterogeneity. With the increase of human age, certain changes occur in the usage of individual gene families within the BCR H-CDR3 repertoire, suggesting that there is a certain genetic bias in the usage of IGHV during the initial V (D) J rearrangement. This bias may affect the composition and characteristics of an individual's peripheral naive B cell receptor repertoire, thereby influencing the individual's immune response to peripheral antigens. Nucleotide insertions and deletions did not show significant changes with increasing age; the diversity of the B cell BCR H-CDR3 repertoire decreased with age, yet without a marked difference; the length of AA sequences gradually increased as human age advanced, also with no significant difference. In summary, as humans age, the B cell repertoire in the aging body undergoes little change, meaning it is less affected by the external environment. METHODS Study subjects In accordance with the principles of obtaining volunteers' informed consent and ethical approval, peripheral blood samples were collected from 9 healthy adults belonging to three different age groups, with 3 cases in each group (young, middle-aged, and elderly). The age selection criteria for the three groups of healthy adults were based on the classification by the World Health Organization of the United Nations. Table 1 . Table 1 Clinical characteristics of the study sample. Sample Age(years) Sex Permanent residence A1 22 M Wuhan, Hubei province A2 22 M Wuhan, Hubei province A3 22 M Wuhan, Hubei province B1 50 M Wuhan, Hubei province B2 46 M Wuhan, Hubei province B3 50 M Wuhan, Hubei province C1 74 M Wuhan, Hubei province C2 81 M Wuhan, Hubei province C3 86 M Wuhan, Hubei province Sample Preparation Preparation of single-cell suspension: 2 ml of venous blood was drawn from each volunteer to prepare a single-cell suspension, after which DNA was extracted from the lymphocyte samples. High-Throughput Sequencing V -region primers and J -region primers containing Illumina sequencing adapter sequences were added to the extracted DNA samples, and a multiplex PCR reaction was performed using the QIAGEN kit. The multiplex PCR products were purified with magnetic beads. The purified DNA was subjected to fragment screening using Agencourt AMPure XP magnetic beads. Then, the recovered DNA products were subjected to a second round of amplification using primers with Illumina Flow Cell sequences. The PCR products were subjected to agarose gel electrophoresis, and after cutting out the fragments of the target size, gel purification and recovery were performed using the QIAquick Gel Extraction Kit, which were then dissolved in Elution Buffer and labeled with library tags, thus completing the library construction. After passing the library quality inspection, sequencing was performed on the Illumina platform. Data Analysis In this project, the BGISEQ-500 platform was used to sequence the immune repertoires of 9 samples. Each sample yielded an average of 4816.75 Mb of data. The raw sequencing data contained reads with low quality, adapter contamination, and excessively high content of unknown base N. After removing these reads, each sample obtained an average of 92.9844 Mb of data. Each sample had high Q20 and Q30 values, reflecting good sequencing quality of the sequencing data (Table 2 ). The filtered reads are shown in supplement Table 1 . After obtaining clean reads, the alignment software MiXCR was used in this project to align the clean reads to the BCR reference gene sequences. For successfully aligned sequences, each clone sequence was obtained after assembly, and sequences with low quality values needed further correction. Finally, sequences with completely identical clone sequences were clustered together to obtain a tab-delimited text file containing all alignment and clone information for each sample. The statistics of alignment results are shown in Table 2 . Table 2 IGH sequence statistics Sample Clean fragments Aligned fragments Align rate(%) Fragments used Clonetype.no With stop codons Out of frame A1 15857049 14765906 93.12 12495261 15894 1459 5838 A2 15970209 15033008 94.13 13050269 28396 3816 12265 A3 16003657 15004715 93.76 13230465 17290 2192 6972 B1 15905789 14860591 93.43 12900699 17385 2495 7111 B2 15976951 14838619 92.88 12815531 21560 2927 8088 B3 16473433 15484859 94.00 13530968 30810 3297 13944 C1 16433944 14732124 89.64 12457615 17202 1995 6911 C2 16318181 15376012 94.23 13195347 32207 3585 14684 C3 16624374 15502088 93.25 13295775 21678 2409 9147 Table 3. Statistical table of SHM in B cells. Samples CDR3 mutation(%) Vmutation(%) Dmutation(%) Jmutation(%) Deletion(%) Insertion(%) Substitution(%) A1 54.85 14.85 25.94 30.95 7.87 7.59 49.06 A2 62.43 19.75 30.03 37.28 8.51 9.06 57.35 A3 68.11 18.47 34.88 40.47 9.49 10.14 63.90 B1 61.68 16.70 32.75 35.21 8.19 6.56 57.12 B2 60.76 19.41 29.54 34.52 8.04 7.97 56.32 B3 61.50 16.75 25.01 38.40 8.69 8.55 56.46 C1 63.77 16.08 31.74 35.62 7.51 8.94 58.38 C2 58.14 18.37 21.83 34.93 8.41 9.30 52.34 C3 64.8 17.26 39.69 41.13 5.43 6.49 60.75 Statistical Analysis SPSS (one-way ANOVA) test was used to compare the expression levels and expression diversity among the three groups. For statistical significance, ∗indicates P < 0.05 . Abbreviations HTS: High-Throughput Sequencing; BCR: B Cell Receptor; H-CDR3: Heavy chain Complementarity Determining Region 3; IGHV : Immunoglobulin Heavy chain Variable gene; IGHJ : Immunoglobulin Heavy chain Jointing gene; SHM: somatic hypermutation; 1/DS: The inverse Simpson’s diversity index; HEC: Highly Expanded Clones ; MEC: Intermediate Expanded Clones ; LEC: Low Expanded Clones ; TdT: deoxynucleotidyl transferase. Declarations Supplementary information Supplemental Information can be found online at immunity. Acknowledgements We are grateful to all for supporting this study,and we thank all the authors, BGI for using their HTS data for analysis. Authors contributions Lina Ma and Ming Li were responsible for designing the research work. Lina Ma analyzed the data and wrote the paper. Hu Zhang, Wenyi Wang，Lili Chen，Xinrui Lei，Lijuan Fan，Yan Tan assisted with the interpretation of the findings and development of the manuscript. all authors reviewed and approved the final manuscript. Funding This project was supported by the Young and Middle-aged Talents Project of the Science and Technology Research Program of Hubei Provincial Department of Education, China (Q20221109). Availability of data and materials The datasets used and/or analyzed during the current study are available from the author on reasonable reqest. Ethics approval and consent to participate This study was approved by the Ethics Committee of the hospital responsible for clinical affairs. All volunteers provided written informed consent, and the research protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki. Consent for publication Formal permission for publication has been obtained from Tianyou Hospital Affiliated to Wuhan University of Science and Technology. Competing interests The authors declare that they have no competing interests. References Duchowny, K.A., Zhang, Y.S., Stebbins, R.C. et al. The aging immune system and all-cause mortality in older Americans: differences across sex and race/ethnicity[J]. Immun Ageing 22, 25 (2025). Elene A Clemens, Martha A Alexander-Miller. Understanding Antibody Responses in Early Life: Baby Steps towards Developing an Effective Influenza Vaccine [J]. Review. 2021 Jul 17;13(7):1392. DK Dunn-walters. The ageing human B cell repertoire: A failure of selection?[J]. Clinical Experimental Immunology, 2016, Jan: 183(1): 50-56. Hilla TK, Lena H, Ginette S, et al. Aging affects B-cell antigen receptor repertoire diversity in primary and secondary lymphoid tissues[J]. Eur.J.Immunol, 2016. 46: 480–492. Tavares SM, Junior Wde L, Lopes E Silva MR. Normal lymphocyte immunophenotype in an elderly population[J]. Rev Bras Hematol Hemoter. 2014 May-Jun; 36(3): 180-3. Kovaltsuk A, Raybould MIJ, Wong WK, et al. Structural diversity of B-cell receptor repertoires along the B-cell differentiation axis in humans and mice[J]. PLoS Comput Biol. 2020 Feb 18;16(2):e1007636. Xu J L, Davis M M. Diversity in the CDR3 region of V(H) is sufficient for most antibody specificities[J]. Immunity, 2000, 13(1): 37-45. Lefranc M P, Giudicelli V, Ginestoux C, et al. IMGT, the international ImMunoGeneTics information system[J]. Nucleic Acids Res, 2009, 37(Database issue): D1006-D1012. Victora G D, Nussenzweig M C. Germinal centers[J]. Annu Rev Immunol, 2022 Apr 26; 40: 413-442 Irac SE, Soon MSF, Borcherding N., et al. Single-cell immune repertoire analysis[J]. Nat Methods. 2024 May; 21(5): 777-792. Lin H, Peng Y, Chen X, Liang Y, Tian G, Yang J. T Cell Receptor Repertoire Sequencing[J]. Methods Mol Biol. 2020; 2204: 3-12. Yuuki H, Itamiya T, Nagafuchi Y, Ota M, Fujio K. B cell receptor repertoire abnormalities in autoimmune disease[J]. Front Immunol. 2024 Jan 31; 15: 1326823. Arnaout R, Lee W, Cahill P, et al. High-resolution description of antibody heavy-chain repertoires in humans[J]. PLoS One, 2011, 6(8): e22365. Horns F, Dekker CL, Quake SR. Memory B Cell Activation, Broad Anti-influenza Antibodies, and Bystander Activation Revealed by Single-Cell Transcriptomics[J]. Cell Rep. 2020 Jan 21; 30(3): 905-913. Tanno H, Gould TM, McDaniel JR, et al. Determinants governing T cell receptor alpha/beta-chain pairing in repertoire formation of identical twins[J]. Proc Natl Acad Sci U S A. 2020 Jan 7; 117(1): 532-540. Tiffeau-Mayer A.. Unbiased estimation of sampling variance for Simpson's diversity index[J]. Phys Rev E. 2024 Jun; 109(6-1): 064411. Kvålseth TO. Ecol Evol. Diversity analysis: Richness versus evenness[J]. 2024 Sep 23; 14(9): e70275. Pothuri VS, Hogg GD, Conant L, et al. Intratumoral T-cell receptor repertoire composition predicts overall survival in patients with pancreatic ductal adenocarcinoma[J]. Oncoimmunology. 2024 Mar 15; 13(1): 2320411. Cailing Song , Wenjing Pan, Brittany Brown, et al. Immune repertoire analysis of normal Chinese donors at different ages[J]. Cell Prolif. 2022 Nov; 55(11): e13311. Bolotin, Dmitriy A., Stanislav Poslavsky, et al. "MiXCR: software for comprehensive adaptive immunity profiling"[J]. Nature methods 12, no. 5 (2015): 380-381. Lina Ma, Xinxin Tao, Xiaoyan He, et al. Analysis of the heterogeneity of the BCR H-CDR3 repertoire in the bone marrow and spleen of 3-, 12-, and 20-month old mice[J]. Immun Ageing. 2021 Apr 12; 18(1): 17. Binbin Hong, Yanling Wu, Wei Li, et al. In Depth analysis of human neonatal and adult IgM antibody repertoires[J]. Frontiers in immunology, 2018, 3, 18(9): 128. Oscar Mejias-Gomez, Andreas V. Madsen, Kerstin Skovgaard, et al. A window into the human immune system: comprehensive characterization of the complexity of antibody complementary-determining regions in functional antibodies[J]. MAbs，2023, VOL. 15, NO. 1, 2268255. Xiaodong Shi , Tihong Shao, Feifei Huo, et al. An analysis of abnormalities in the B cell receptor repertoire in patients with systemic sclerosis using high-throughput sequencing[J]. PeerJ, 2020 Jan 14: 8: e8370. Rubelt F, Bolen C R, Mcguire H M, et al. Individual heritable differences result in unique cell lymphocyte receptor repertoires of naive and antigen-experienced cells[J]. Nat Commun, 2016, 7: 11112. Shi B, Dong X, Ma Q, et al. The Usage of Human IGHJ Genes Follows a Particular Non-random Selection: The Recombination Signal Sequence May Affect the Usage of Human IGHJ Genes[J]. Front Genet. 2020 Dec 8; 11: 524413. Glanville J, Kuo T C, von Budingen H C, et al. Naive antibody gene-segment frequencies are heritable and unaltered by chronic lymphocyte ablation[J]. Proc Natl Acad Sci U S A, 2011, 108(50): 20066-20071. Schatz D G, Ji Y. Recombination centres and the orchestration of V(D)J recombination[J]. Nat Rev Immunol, 2011, 11(4): 251-263. Lanwei Zhu, Qi Peng, Yingjie Wu , et al. scBCR-seq revealed a special and novel IG H&L V(D)J allelic inclusion rearrangement and the high proportion dual BCR expressing B cells[J]. Cell Mol Life Sci. 2023 Oct 7; 80(11): 319. Marie J Kidd, Katherine J L Jackson , Scott D Boyd, et al. DJ pairing during VDJ recombination shows positional biases that vary between individuals with differing IGHD locus Immunogenotypes[J]. J Immunol. 2016 Feb1; 196(3): 1158-64. Hayato Yuuki , Takahiro Itamiya , Yasuo Nagafuchi, et al. B cell receptor repertoire abnormalities in autoimmune disease[J]. Front Immunol. 2024 Jan 31: 15: 1326823. Qian Wang , Delong Feng , Sujie Jia, et al. B-Cell Receptor Repertoire: Recent Advances in Autoimmune Diseases[J]. Clin Rev Allergy Immunol. 2024 Feb; 66(1): 76-98. Chen Wang, Yi Liu, Lan T. Xu, et al. Effects of aging, CMV infection, and EBV infection on human B cell repertoires[J]. J Immunol. 2014 Jan 15; 192(2): 603-611. Jean L Scholz, Alain Diaz, Richard L Riley, et al. A comparative review of aging and B cell function in mice and humans[J]. Current Opinion in Immunology 2013, 25, 504-510 Meng Wang , Ruoyi Jiang , Subhasis Mohanty, et al. High throughput single cell profiling of B cell responses following inactivated influenza vaccination in young and older adults[J]. Aging (Albany NY). 2023 Jun 26; 15(18): 9250-9274. Johannes Dirks, Dorothee Viemann, Niklas Beyersdorf, et al. Insights into B-cell ontogeny inferred from human immunology[J]. Eur J Immunol 2023 Jun;53(6): e2250116. Cinque Soto, Robin G Bombardi, Andre Branchizio, et al. High frequency of shared clonotypes in human B cell receptor Repertoires[J]. Nature. 2019 Feb; 566(7744): 398-402. S. Kilpatrick，E. Goldstein，J. Krebs. Lewin Genes X [M]. Higher Education Press, Published 27 November 2009 Biology. Nima Nouri, Steven H Kleinstein. Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing date[J]. PLoS Comput Biol. 2020 Jun 23; 16(6): e1007977. Marie J Kidd, Katherine J L Jackson, Scott D Boyd. DJ pairing during VDJ recombination shows positional biases that vary between individuals with differing IGHD locus immunogenotypes[J]. J Immunol. 2016 Feb 1; 196(3): 1158-64. Additional Declarations No competing interests reported. Supplementary Files Supplementaryinformation.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7535948","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510232714,"identity":"e2294ad8-ea99-4f9b-a3d7-78c0db350ba1","order_by":0,"name":"Lina Ma","email":"","orcid":"","institution":"Tianyou Hospital Affiliated to Wuhan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Lina","middleName":"","lastName":"Ma","suffix":""},{"id":510232715,"identity":"94de5156-b9d9-4018-8735-80723c7b13fb","order_by":1,"name":"Hu Zhang","email":"","orcid":"","institution":"Tianyou Hospital Affiliated to Wuhan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Hu","middleName":"","lastName":"Zhang","suffix":""},{"id":510232716,"identity":"488f9911-636f-45fe-ae20-2b138d999bae","order_by":2,"name":"Wenyi Wang","email":"","orcid":"","institution":"Tianyou Hospital Affiliated to Wuhan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Wenyi","middleName":"","lastName":"Wang","suffix":""},{"id":510232717,"identity":"637ec94b-134d-45b0-a1fb-0c05736e79d7","order_by":3,"name":"Lili Chen","email":"","orcid":"","institution":"Tianyou Hospital Affiliated to Wuhan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"Chen","suffix":""},{"id":510232718,"identity":"5a99ed45-df75-4ccb-bce0-010816db5a36","order_by":4,"name":"Xinrui Lei","email":"","orcid":"","institution":"Tianyou Hospital Affiliated to Wuhan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Xinrui","middleName":"","lastName":"Lei","suffix":""},{"id":510232719,"identity":"865216ff-447f-4add-b906-f476142ec53d","order_by":5,"name":"Lijuan Fan","email":"","orcid":"","institution":"Tianyou Hospital Affiliated to Wuhan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Lijuan","middleName":"","lastName":"Fan","suffix":""},{"id":510232720,"identity":"d22732e6-081f-48c3-b62d-0c0d1ba4e084","order_by":6,"name":"Yan Tan","email":"","orcid":"","institution":"Tianyou Hospital Affiliated to Wuhan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Tan","suffix":""},{"id":510232721,"identity":"294ea3bf-8672-4aa8-8a4b-310ff412a75d","order_by":7,"name":"Ming Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIie3PsUvDQBTH8TufvCxn51eE9C8QUg5CoN38R+6W6yIuLh1ErxTapeA/IO1/4XwQcKp0Dbg0CpkcdMvQodHN5ZJR8L7bg99neIyFQn80ONTjGKOHr72aUjzoZM5WRvaEk8l+m8mh7UIE5npNKu2Xi6lmrmV9sXypiETOF0wZ+obcQvlWeEi6naSUZBNA5vJMP9F1xFDKKx9xBkmJESKfzYqG3HAr8NxLdhWSQxAIwEg/kraujRQG+xYvCRFPmn0nUsGIr0yCQkCinkkO522/7Ax/ZfX4frP54GV9excPonn57iNNp/T7Bv/8Z/LZvgmFQqF/3REAvkdxG5m4ngAAAABJRU5ErkJggg==","orcid":"","institution":"Tianyou Hospital Affiliated to Wuhan University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Ming","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-09-04 12:08:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7535948/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7535948/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90653048,"identity":"bafbb60e-684d-4edb-bf04-4e2a7b785355","added_by":"auto","created_at":"2025-09-05 09:11:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":83813,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of BCR H-CDR3 lengths across different age groups. *p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7535948/v1/ca2ebc0e9cf52cedd86580f2.png"},{"id":90653257,"identity":"70e97986-21da-4567-b350-7b6e126e0755","added_by":"auto","created_at":"2025-09-05 09:19:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":192504,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency distribution of gene family usage in the BCR H-CDR3 repertoire across different age groups. \u003cstrong\u003ea \u003c/strong\u003eThe gene frequency of the IGHV gene in the different age groups. \u003cstrong\u003eb\u003c/strong\u003e The gene frequency of the IGHJ gene in the different age groups. *p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7535948/v1/0893dee35e2273c5ef0ef161.png"},{"id":90653056,"identity":"09ca9e46-21e9-4c4c-b375-25cd4652e434","added_by":"auto","created_at":"2025-09-05 09:11:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":168243,"visible":true,"origin":"","legend":"\u003cp\u003eClonal distribution of the BCR H-CDR3 repertoire in the different age groups. \u003cstrong\u003ea\u003c/strong\u003e Clonal distribution of BCR H-CDR3 receptor repertoire in different age groups. \u003cstrong\u003eb\u003c/strong\u003e Statistical analysis of BCR H-CDR3 receptor repertoire clones in different age groups. \u003cstrong\u003ec \u003c/strong\u003eDistribution of clone proportions in each sample across different age groups. \u003cstrong\u003ed \u003c/strong\u003eStatistical analysis of the distribution of clone proportions in each sample across different age groups.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7535948/v1/ec1a9d2455326b2ae514c38f.png"},{"id":90653050,"identity":"8f214009-f1ec-4da2-a83e-e2ea1a67c5b2","added_by":"auto","created_at":"2025-09-05 09:11:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":214413,"visible":true,"origin":"","legend":"\u003cp\u003eClonal distribution of the sample. \u003cstrong\u003ea\u003c/strong\u003e Statistics on D50 Values of Sample Clone Distribution. \u003cstrong\u003eb\u003c/strong\u003e Heatmap Distribution of Amino Acid Sequence Overlap Between Samples. \u003cstrong\u003ec\u003c/strong\u003e Cluster Analysis of Geometric Distance of Clone Overlap Between Samples. \u003cstrong\u003ed \u003c/strong\u003eVenn Diagram of Shared Clones in the Youth Group Samples.\u003cstrong\u003e e\u003c/strong\u003e Venn Diagram of Shared Clones in the Middle-aged Group Samples.\u003cstrong\u003e f\u003c/strong\u003e Venn Diagram of Shared Clones in the Elderly Group Samples.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7535948/v1/5655f26c050eb98f365eef8f.png"},{"id":90653258,"identity":"3e249303-3e14-4825-ad4b-5e6faeadd2bf","added_by":"auto","created_at":"2025-09-05 09:19:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":233028,"visible":true,"origin":"","legend":"\u003cp\u003eStatistics were performed on single-base mutations (insertion, deletion, substitution) in the CDR3 region of B cells.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7535948/v1/5a7cf00a20b512239049c775.png"},{"id":94988945,"identity":"a6f52ca6-4fcf-4c5d-a68e-1a2291d27038","added_by":"auto","created_at":"2025-11-03 07:11:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1752559,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7535948/v1/b0152021-fef5-4908-b5b8-458b0282b819.pdf"},{"id":90653259,"identity":"3c2e0441-791d-4dde-8db8-5b2e1ffc23ea","added_by":"auto","created_at":"2025-09-05 09:19:14","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1022045,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7535948/v1/faf8311fe5c20daae36b6dc4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of the heterogeneity of the BCR H-CDR3 repertoire in peripheral blood B cells of adult women with increasing age in Central China","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eImmunosenescence is a complex process involving multiple changes in recombination, development, and regulation, rather than a simple decline in function. However, the significant reduction of certain immunological indicators in the elderly is often closely related to good functional and health status. The elderly immune system is characterized by decreased sensitivity to vaccines and infections, and increased incidence of autoimmune diseases and cancer [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eStudies on age-related changes in the quantity, subsets, and functions of B cells play an important role in aging and vaccine development. When the body ages, the quantity and quality of antibodies produced differ from those in the young stage. With increasing age, the immune effect of vaccines decreases significantly. Under the same intensity of antigen stimulation, the number of B cells produced by elderly animals is less than that by adult animals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Studies on immunoglobulin gene repertoires suggest dynamic changes with age [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Age-related immune system defects may be due to restrictions on bone marrow B cell production or migration to peripheral lymphoid tissues caused by peripheral homeostasis pressure [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The total number of B cells remains unchanged for most of life [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, it is generally believed that it is the quality of B cells or antibody repertoires that changes with age, leading to a decline in the effectiveness of antibody responses with increasing age. Although most studies on the impact of aging on hematopoietic stem cell function have used mouse models, recent work has demonstrated similarities in aging effects between mice and humans [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The ability of hematopoietic stem cells to generate lymphoid progenitors is impaired in the elderly, and differences in bone marrow output are observed. In addition, like in mice, the absolute number of human hematopoietic stem cells increases with age, and genes responsible for myeloid differentiation are upregulated. Thus, age-related changes in hematopoietic stem cell potential in mice and humans may share some common characteristics [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAntibodies are a class of globulins produced by plasma cells, which are derived from B cells that recognize antigens, become activated, proliferate, and differentiate. They can specifically bind to corresponding antigens and are important effector molecules in immune responses. Immunoglobulins are globulins with a chemical structure similar to antibodies. They mainly exist in body fluids, called secreted Ig (SIg), and a small part exists on the surface of B cells, called membrane Ig (MIg), i.e., B cell surface antigen receptors (BCR). BCR is a tetramer composed of two homologous heavy chains and two homologous light chains, which is divided into the variable region (V region), constant region (C region), and hinge region (H region). Among them, the AA composition and sequence of 3 subregions in the V region are highly variable, which are called Complementarity Determining Regions, namely CDR1, CDR2, and CDR3. The non-CDR regions in the V region with relatively small changes are called framework regions (FRs); 4 FRs separate the 3 CDRs and serve to maintain the spatial configuration of the CDRs. The key part of BCR for recognizing antigen peptides is the most diverse CDR3 region [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The gene sequence encoding the human BCR heavy chain CDR3 region is composed of the rearrangement of discontinuous \u003cem\u003eIGHV\u003c/em\u003e (56 functional gene segments) terminal - \u003cem\u003eIGHD\u003c/em\u003e (23 functional gene segments) - \u003cem\u003eIGHJ\u003c/em\u003e front-end (6 functional gene segments) gene segments, as well as the nucleotides (N/P base sequences) inserted or deleted during \u003cem\u003eV-D\u003c/em\u003e and \u003cem\u003eD-J\u003c/em\u003e joining. Moreover, when B cells migrate to the periphery for further development after central rearrangement and selection, class switching and somatic hypermutation occur in the germinal center. These factors endow BCR with extremely high diversity, which enables B cells to respond to almost all antigens [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. B cells recognize specific antigens and produce antibodies through BCR. The diversity of the BCR H-CDR3 repertoire is related to antigen recognition ability. Detection of the BCR H-CDR3 repertoire in B cells can determine the ability of B cells to recognize antigens, thereby reflecting the immune status of the body. When mature B cells are induced by peripheral antigens, high-frequency point mutations occur in the heavy and light chain \u003cem\u003eV\u003c/em\u003e genes of germinal center cells, which will greatly increase the diversity of BCR. In mice and humans, this mechanism is called somatic hypermutation (SHM).\u003c/p\u003e\u003cp\u003eCurrently, HTS has been widely applied to monitor the T/B cell repertoires in normal and diseased individuals, and systematic analysis methods for T/B cell repertoires have been established [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. To better understand the diversity of human BCR repertoires, many studies have performed deep sequencing on BCR sequences, especially the heavy chain CDR3 region sequences, to estimate the diversity of human B cell receptor repertoires and analyze their compositional characteristics. It is currently believed that the initial stage of human \u003cem\u003eV (D) J\u003c/em\u003e gene segment rearrangement is not completely random, but has a certain genetic bias in the selection of \u003cem\u003eV-D-J\u003c/em\u003e pairing. The diversity of BCR H-CDR3 ranges from 3\u0026ndash;9\u0026times;10\u003csup\u003e9\u003c/sup\u003e, and there are some consistent sequences among different individuals [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. At present, monitoring the peripheral blood B cell receptor repertoire of the same individual at different times through HTS can help discover the dynamic changes of human peripheral blood B cell receptor repertoire [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The above studies provide a research basis for exploring the correlation between the formation of BCR repertoires and genetic and environmental factors. Currently, the emergence of HTS enables comprehensive research on changes in the Ig gene repertoire. Studies on identical twins have shown that the selection of immunoglobulin gene segments is strongly influenced by genetic and environmental factors [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, any observed age- or disease-related changes in gene usage, especially changes in the CDR3 region, may reflect environmental influences or may be caused by individual differences. For this reason, we used HTS to analyze the BCR H-CDR3 repertoire of B cells in healthy adults of different ages, aiming to understand the dynamic changes of the BCR H-CDR3 repertoire of B cells. In this study, we selected peripheral blood from healthy adults of three age groups and used HTS to obtain the sequences of B cell BCR H-CDR3 repertoires, in order to preliminarily explore the homogeneity and heterogeneity of B cells in healthy adults and gain an in-depth understanding of the composition and characteristics of human peripheral blood B cell repertoires.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eCDR3 length distribution\u003c/h2\u003e\n \u003cp\u003eAn important determinant of B-cell repertoire diversity is the length of the BCR H-CDR3 loop. In this study, the length distribution of the AA sequences in the CDR3 region of all clones from each sample was analyzed. It was found that the length of the BCR H-CDR3 region in all nine volunteers followed a Gaussian distribution centered around 16–18 AA. Statistical analysis revealed that the percentage of 37-amino acid sequences in the middle-aged group was significantly higher than that in the young and elderly groups (P \u0026lt; 0.05, Fig.\u0026nbsp;1). The average CDR3 length in the young group was 18.38 AA, in the middle-aged group it was 18.81 AA, and in the elderly group it was 18.25 AA. The middle-aged group exhibited longer CDR3 lengths compared to both the young and elderly groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eGene usage frequency in the BCR H-CDR3 repertoire\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eIGHV\u003c/strong\u003e \u003cstrong\u003egene usage(\u003c/strong\u003eFig.\u0026nbsp;2a\u003cstrong\u003e)\u003c/strong\u003e:(1)In the BCR H-CDR3 repertoire, the \u003cem\u003eIGHV\u003c/em\u003e gene families were analyzed across nine samples. The top 20 \u003cem\u003eIGHV\u003c/em\u003e genes used were: \u003cem\u003eIGHV1-18\u003c/em\u003e, \u003cem\u003eIGHV1-2\u003c/em\u003e, \u003cem\u003eIGHV1-3\u003c/em\u003e, \u003cem\u003eIGHV1-46\u003c/em\u003e, \u003cem\u003eIGHV1-69\u003c/em\u003e, \u003cem\u003eIGHV1-8\u003c/em\u003e, \u003cem\u003eIGHV2-5\u003c/em\u003e, \u003cem\u003eIGHV3-23\u003c/em\u003e, \u003cem\u003eIGHV3-30\u003c/em\u003e, \u003cem\u003eIGHV3-33\u003c/em\u003e, \u003cem\u003eIGHV3-53\u003c/em\u003e, \u003cem\u003eIGHV3-7\u003c/em\u003e, \u003cem\u003eIGHV3-74\u003c/em\u003e, \u003cem\u003eIGHV3-9\u003c/em\u003e, \u003cem\u003eIGHV4-34\u003c/em\u003e, \u003cem\u003eIGHV4-39\u003c/em\u003e, \u003cem\u003eIGHV4-4\u003c/em\u003e, \u003cem\u003eIGHV4-61\u003c/em\u003e, \u003cem\u003eIGHV5-51\u003c/em\u003e, and \u003cem\u003eIGHV7-81\u003c/em\u003e.༈2༉High-frequency usage: \u003cem\u003eIGHV1-8\u003c/em\u003e usage was significantly higher in the middle-aged group compared to the young and elderly groups. \u003cem\u003eIGHV3-30\u003c/em\u003e and \u003cem\u003eIGHV4-4\u003c/em\u003e usage was notably higher in the elderly group compared to the young and middle-aged groups. \u003cem\u003eIGHV3-7\u003c/em\u003e showed significant differences in usage with increasing age. \u003cem\u003eIGHV5-51\u003c/em\u003e was more frequently used in the young group compared to the middle-aged and elderly groups (P \u0026lt; 0.05).༈3༉Low-frequency usage: With increasing age, \u003cem\u003eIGHV1-67\u003c/em\u003e, \u003cem\u003eIGHV1-68\u003c/em\u003e, \u003cem\u003eIGHV3-16\u003c/em\u003e, \u003cem\u003eIGHV3-20\u003c/em\u003e, \u003cem\u003eIGHV3-49\u003c/em\u003e, and \u003cem\u003eIGHV3-72\u003c/em\u003e exhibited statistically significant differences (P \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIGHJ\u003c/em\u003e gene usage(Fig.\u0026nbsp;2b)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIGHJ4\u003c/em\u003e and \u003cem\u003eIGHJ6\u003c/em\u003e genes are frequently used in all 9 samples. Statistical analysis reveals that there are no significant differences among the six \u003cem\u003eIGHJ\u003c/em\u003e gene families.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIGHV-IGHJ\u003c/em\u003e pairing in the BCR H-CDR3 repertoire(Fig. S1)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe recombination of \u003cem\u003eV-J\u003c/em\u003e gene segments encodes the CDR3 region, contributing to its extensive diversity. The pairing usage of \u003cem\u003eV-J\u003c/em\u003e genes reflects the diversity of the CDR3 repertoire. We compared the \u003cem\u003eV-J\u003c/em\u003e gene pairing usage in the BCR H-CDR3 repertoire across different age groups. The results indicate that there are many similarities in the usage of \u003cem\u003eV-J\u003c/em\u003e gene combinations among the groups, while certain differences in expression levels were also observed.\u003c/p\u003e\n\u003ch3\u003eClonal diversity and clonal frequency distribution\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of clonal expansion in BCR H-CDR3 repertoire\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe inverse Simpson’s diversity index (1/DS) is widely recognized for evaluating the diversity changes in T/B cell CDR3 repertoires between diseased and healthy individuals [16, 17]. The corrected formula for the inverse Simpson’s index is calculated as 1/DS = 1/∑{ni*(ni-1)}/{n*(n-1)}, where ni represents the total number of the i-th sequence. A higher 1/DS value indicates greater diversity and lower clonal expansion [18]. The frequency of unique CDR3 sequences was sorted from high to low, with the Y-axis displayed on a Log10 scale to represent frequency magnitude. The clonal distribution of the three BCR H-CDR3 repertoires was similar, as shown in Fig.\u0026nbsp;3a. Statistical analysis of the 1/DS values across the three groups revealed no significant differences ,as shown in Fig.\u0026nbsp;3b(P \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003eThe clonal expansion frequencies of each sample were divided into three intervals based on the total distribution range: Highly Expanded Clones (HEC): Frequency \u0026gt; 0.1%. Intermediate Expanded Clones (MEC): Frequency between 0.03% and 0.1%. Low Expanded Clones (LEC): Frequency \u0026lt; 0.03%. The results showed that the majority of sequences in the repertoires of all three groups belonged to LEC with frequencies below 0.03%, as shown in Fig.\u0026nbsp;3c. Subsequent statistical analysis of the differences between the three groups revealed no significant disparities, indicating high similarity among the groups. Smaller differences suggest greater similarity, and no notable variations were observed. See Fig.\u0026nbsp;3d for details.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClonal frequency distribution and D50 analysis\u003c/strong\u003e: The clonal frequency distribution graph provides a visual representation of the frequency distribution of all clonal types within each sample. D50 is a recently introduced metric that reflects the clonal population structure of a sample. A lower D50 value indicates a more concentrated clonal frequency distribution, while a higher value suggests a more dispersed distribution [19]. For detailed data, refer to supplementary Fig.\u0026nbsp;2. Among the three groups, the young group exhibited the highest D50 values, indicating a more dispersed clonal frequency distribution. The middle-aged group showed slightly lower D50 values, while the elderly group had the lowest D50 values, reflecting the most concentrated clonal frequency distribution. However, statistical analysis revealed no significant differences among the groups. The clonal frequency distributions for all samples are shown in Fig.\u0026nbsp;4a.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eShared Clones\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe shared clones among samples intuitively reflect the commonalities between two samples, and the evaluation of shared clones can be carried out by comparing the nucleotide sequences (nt) and amino acid sequences (aa). The heatmap of shared clones between two samples, characterized by the percentage of shared aa clone numbers in the total, has both X-axis and Y-axis representing each sample. The color represents the number or percentage of shared clones between two samples (the lighter the color, the more clones, and vice versa). It can be seen from the figure that the proportion of common clones in the group is slightly higher, while that between groups is lower. However, sample B1 has more common clones with the three samples in group A, and sample B1 is more similar to the samples in group A (Fig.\u0026nbsp;4b).\u003c/p\u003e\n\u003cp\u003eThere are various indicators to measure the similarity between samples, including the Pearson correlation coefficient of clone frequency (P), the relative clone overlap between samples (D), the geometric distance of clone overlap between samples (F), and the clonotype-wise geometric distance of clone overlap (F2) [20]. These indicators are used to calculate the distance between samples for hierarchical clustering. In this project, the geometric distance of clone overlap (F) was adopted for evaluation. The same color represents the same group, and samples that are closer to each other have higher similarity.Cluster analysis revealed that the young, middle-aged, and elderly groups all followed the age distribution. The three samples in group A were relatively close to each other. Among the three samples in group B, samples B2 and B3 were closer, while sample B1 was farther away, showing a certain difference in similarity from the other samples in group B, but was closer to and more similar to the samples in group A. The three samples in group C were close to each other and relatively similar (Fig.\u0026nbsp;4c).\u003c/p\u003e\n\u003cp\u003eThe shared clones among samples directly reflect the commonalities between two samples. We can intuitively observe the commonalities of AA sequences among different age groups by using Venn diagrams. In this experiment, an analysis was conducted on the shared AA sequences in the BCR H-CDR3 repertoire of peripheral blood B cells from different age groups. The number of shared AA sequences in the BCR H-CDR3 repertoire of peripheral blood B cells in the young group was 186; that in the middle-aged group was 237; and that in the elderly group was 246. As can be seen from the figures, the number of shared amino acids among samples in each group increases with age (Fig.\u0026nbsp;4d, 4e, 4f).\u003c/p\u003e\n\u003ch3\u003eB cell SHM (Somatic Hypermutation) statistics\u003c/h3\u003e\n\u003cp\u003eNucleotide truncation and insertion: The BCR H-CDR3 receptor repertoire undergoes not only \u003cem\u003eV(D)J\u003c/em\u003e rearrangement but also nucleotide truncation and insertion at the \u003cem\u003eV(D)J\u003c/em\u003e junctions, mainly mediated by terminal deoxynucleotidyl transferase (TdT). This further enriches the diversity of the CDR3 receptor repertoire on the basis of the diversity from random rearrangement. The diversity of CDR3 arises from \"N\" nucleotide insertions at the \u003cem\u003eV→D\u003c/em\u003e (N1) and \u003cem\u003eD→J\u003c/em\u003e (N2) junctions, exonucleolytic truncations (3'\u003cem\u003eV\u003c/em\u003e truncation, 5'\u003cem\u003eD\u003c/em\u003e truncation, and 5'\u003cem\u003eJ\u003c/em\u003e truncation), and additions of palindromic \"P\" nucleotides (P3'\u003cem\u003eV\u003c/em\u003e, P5'\u003cem\u003eD\u003c/em\u003e, and P5'\u003cem\u003eJ\u003c/em\u003e) [21]. Statistics were conducted on single-base mutations in the B cell CDR3 region, and the results are shown in Table\u0026nbsp;3. Statistical analysis revealed no significant differences (Fig.\u0026nbsp;5).\u003c/p\u003e\n\u003cdiv\u003e\n\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWe analyzed the distribution of CDR3 lengths in an average of 92.9844 filtered sequencing reads per sample, which provides extensive information on the BCR repertoires across different age groups. For instance, we identified the most frequently observed lengths. Variable rearrangements result in different CDR3 lengths, and the characteristics of BCR clonality can be determined by measuring the lengths of the CDR3 repertoire. Generally, the range of CDR3 lengths is related to the degree of CDR3 diversity. For the same species, the wider the range of CDR3 lengths and the closer it is to a normal distribution, the higher the diversity of the CDR3 repertoire [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In our study, the percentage of 37-amino-acid length in the middle-aged group was significantly higher than that in the young and elderly groups. It has been reported in the literature that the length of CDR3 in BCR on B cells is longer in adults than in infants [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Another literature reported that the CDR3 length in humans is similar to that in mice, and the CDR3 region in the elderly is longer than that in young people, mainly due to the response to recognized antigens, mutations, and clonal proliferation [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The average AA length in the young group was 18.38, 18.81 in the middle-aged group, and 18.25 in the elderly group, with no significant differences. However, the fact that the average AA length in the young group was shorter than that in the middle-aged group may be because the young group encounters limited antigens during growth, and the number of cell subsets is smaller than that in the middle-aged group, resulting in shorter AA lengths and lower diversity than the middle-aged group. The elderly group had a shorter length than the young and middle-aged groups, with reduced diversity, which may be caused by immune aging; it may also be due to individual differences caused by the small sample size, which requires further research. There was no significant difference in the AA length distribution of the peripheral blood BCR H-CDR3 repertoires among the three age groups, further suggesting that the external environment has no impact on the AA length distribution of the CDR3 receptor repertoire, which is consistent with previous studies [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Rubelt F et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] found that the length of inserted and deleted nucleotide sequences in the naive BCR H-CDR3 receptor repertoire is not affected by genetic factors, while the formation of nucleotide sequences in the memory BCR H-CDR3 receptor repertoire is mainly related to external antigen stimulation.\u003c/p\u003e\u003cp\u003eThe usage of \u003cem\u003eIGHV\u003c/em\u003e in the BCR H-CDR3 repertoire varies among the 9 samples. \u003cem\u003eIGHV1-67\u003c/em\u003e, \u003cem\u003eIGHV1-68\u003c/em\u003e, \u003cem\u003eIGHV1-8\u003c/em\u003e, \u003cem\u003eIGHV3-16\u003c/em\u003e, \u003cem\u003eIGHV3-20\u003c/em\u003e, \u003cem\u003eIGHV3-30\u003c/em\u003e, \u003cem\u003eIGHV3-49\u003c/em\u003e, \u003cem\u003eIGHV3-7\u003c/em\u003e, \u003cem\u003eIGHV3-72\u003c/em\u003e, \u003cem\u003eIGHV4-4\u003c/em\u003e, and \u003cem\u003eIGHV5-51\u003c/em\u003e show significant statistical differences. Among them, \u003cem\u003eIGHV1-8\u003c/em\u003e, \u003cem\u003eIGHV3-30\u003c/em\u003e, \u003cem\u003eIGHV3-7\u003c/em\u003e, \u003cem\u003eIGHV4-4\u003c/em\u003e, and \u003cem\u003eIGHV5-51\u003c/em\u003e are not only used at high frequencies but also exhibit significant differences. The significant differences in \u003cem\u003eIGHV\u003c/em\u003e genes suggest that \u003cem\u003eIGHV\u003c/em\u003e usage is affected by age.\u003c/p\u003e\u003cp\u003eThere is no difference in \u003cem\u003eIGHJ\u003c/em\u003e usage with increasing age among the three groups, indicating that \u003cem\u003eIGHJ\u003c/em\u003e usage is less affected by age. \u003cem\u003eIGHJ4\u003c/em\u003e and \u003cem\u003eIGHJ6\u003c/em\u003e genes are used at high frequencies in all three groups with no significant differences. Theoretically, the usage frequency of \u003cem\u003eV(D)J\u003c/em\u003e gene segments is random in pro-B cells or during pro-B cell recombination (before the selection of self-antigens). However, in vitro experiments conducted in B cell lines have confirmed that the contribution of \u003cem\u003eV(D)J\u003c/em\u003e gene segments to the main components is uneven, and the consensus heptamer and nonamer sequences of the recombination signal sequence (RSS) are considered the main factors [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This result suggests that \u003cem\u003eIGHJ4\u003c/em\u003e and \u003cem\u003eIGHJ6\u003c/em\u003e may be related to the regulation of RSS, and the specific mechanism needs further research to confirm.\u003c/p\u003e\u003cp\u003eThe usage trend of \u003cem\u003eV\u003c/em\u003e and \u003cem\u003eJ\u003c/em\u003e genes in peripheral blood is roughly the same among people of different ages. This is due to the same reasons as the reported similarity in \u003cem\u003eV\u003c/em\u003e and \u003cem\u003eJ\u003c/em\u003e gene usage between neonatal and adult peripheral blood, namely, the same species, similar genetic background, and little difference in living environment [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Glanville J et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] found that the usage frequency of \u003cem\u003eIGHV\u003c/em\u003e differs among unrelated individuals, while the usage frequency of \u003cem\u003eIGHJ\u003c/em\u003e shows no significant genetic differences regardless of whether there is a relationship between individuals. Glanville J et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] further analyzed Ig transcripts from class-switch recombination regions that have experienced antigens and found that \u003cem\u003eIGHV\u003c/em\u003e usage during class switching is significantly related to the profile of their respective naive repertoire \u003cem\u003eIGHV\u003c/em\u003e usage. Even when variations occur, the usage frequency of most gene segments in class switching and the naive repertoire is similar.\u003c/p\u003e\u003cp\u003eThe human adaptive immune response controls defense against pathogens by expressing a variety of specific antigen receptors. During early developmental stages, a unique B cell receptor repertoire is ultimately formed through the combination of a randomly selected set of \u003cem\u003eV(D)J\u003c/em\u003e gene segments from the initial genes, a process known as \u003cem\u003eV(D)J\u003c/em\u003e gene rearrangement [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Although the process of selecting gene segments for rearrangement is largely random, some gene segments are used more frequently than others [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Studies have shown that the overall bias in gene segment usage is caused by multiple factors, including preferential recombination between \u003cem\u003eV\u003c/em\u003e and \u003cem\u003e(D)J\u003c/em\u003e segments, selection based on self-tolerance during development, and the distance between \u003cem\u003eV(D)J\u003c/em\u003e gene segments [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Rubelt F et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] used the \"Repertoire Dissimilarity Index (RDI)\" as a measure of the distance between receptor repertoires and quantified that genetic factors have a significant impact on the gene recombination process and receptor repertoire formation of naive B cells, CD4\u0026thinsp;+\u0026thinsp;T cells, and CD8\u0026thinsp;+\u0026thinsp;T cells. They also showed that genetic differences in the naive cell repertoire can be observed in the memory cell repertoire, which also proves from the perspective of the CDR3 receptor repertoire that individual genetic factors have differential effects on the cell receptor repertoire.\u003c/p\u003e\u003cp\u003eStudies have reported that the clonal diversity of peripheral B cell repertoires decreases with age in the human body, and this reduction may already occur in the bone marrow [\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In this experiment, a comparative analysis of the clonal diversity of peripheral blood B cell repertoires among humans of different ages was conducted, revealing that the clonal diversity of peripheral blood B cell repertoires decreases with age. However, statistical analysis of 1/DS among 9 volunteers showed no significant differences, indicating that there is no correlation in the clonal diversity of the CDR3 receptor repertoire regardless of the age relationship between individuals. The changing trends of HEC, MEC, and LEC among the 9 volunteers were similar, with no statistical differences. The main reason is that the diversity of the BCR H-CDR3 receptor repertoire stems from the diversity of \u003cem\u003eV (D) J\u003c/em\u003e gene rearrangement and the joining diversity of nucleotide insertions and deletions, and gene rearrangement as well as nucleotide insertions and deletions are completed during the recombination stage. This also explains that environmental factors have minimal impact on the diversity of the BCR H-CDR3 receptor repertoire, which is consistent with previous studies [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Rubelt F et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] found that genetic factors influence the formation of the naive B cell repertoire, and this influence is transmitted to the memory B cell repertoire, suggesting that the proliferative clonal sequences of the BCR H-CDR3 receptor repertoire are greatly affected by genetic factors. However, since the 9 volunteers belong to the same species with little difference in genetic background, the differences in the peripheral blood repertoires are small. From the perspective of clonal distribution, there are differences in the clonal distribution of the 9 samples with increasing age. The younger the age, the more dispersed the clonal frequency, and the higher the diversity of the immune system; with increasing age, the clonal frequency becomes concentrated, reflecting the specific response of the immune system to antigens. However, statistical analysis showed no significant differences, suggesting that in the same species, age has little impact on clonal frequency, mainly due to the small differences in genetic background and living environment.\u003c/p\u003e\u003cp\u003eEach unique CDR3 sequence represents a type of B cell and can specifically recognize antigens. The overlapping sequences between samples are the common sequences among the samples, which respond to the same antigenic epitopes [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The analysis results showed that the number of shared AA sequences in the peripheral blood of people of different ages increases with age. This is mainly because the number of antigens encountered in human life increases with age, and people living in the same environment will encounter similar antigens, thus leading to an increase in overlapping sequences. However, these overlapping sequences account for a small proportion of the total individual sequences. The formation of overlapping sequences is related to three factors: nucleotide insertion, deletion, and TdT. Consistent with previous studies, the number of shared clonal proliferation sequences in the CDR3 receptor repertoire between two individuals is small regardless of whether they are related [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Rubelt F et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] found that the length of inserted and deleted nucleotide sequences in the naive BCR H-CDR3 receptor repertoire is not affected by genetic factors, while the formation of nucleotide sequences in the memory BCR H-CDR3 receptor repertoire is mainly related to stimulation by external antigens. This indirectly reflects that the number of overlapping AA sequences in the BCR H-CDR3 receptor repertoire between individuals accounts for a small proportion of the total number. From the analysis of shared clones and multi-sample clustering, it can be seen that the clonal overlaps among the three samples in group A are relatively similar, and the clonal overlaps among the three samples in group C are also relatively similar, suggesting that clonal overlap is affected by age. However, sample B1 is quite different from the other two samples in group B, which may be related to stimulation by external antigens or individual differences.\u003c/p\u003e\u003cp\u003eThe classic \"clonal selection theory\" holds that during the development of T cells in the thymus and B cells in the bone marrow, various \u003cem\u003eV\u003c/em\u003e, \u003cem\u003eD\u003c/em\u003e, and \u003cem\u003eJ\u003c/em\u003e gene segments of germline genes undergo \"completely random\" rearrangement to generate TCR and BCR CDR3 receptor repertoires [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Nucleotide insertions and deletions are also \"random\" and occur during the \"completely random\" rearrangement of \u003cem\u003eV(D)J\u003c/em\u003e, mainly accomplished by exonucleases and TdT [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Under the stimulation of peripheral antigens, recombination or mutation may occur in the \u003cem\u003eV-D-J\u003c/em\u003e gene segments of BCR, a mechanism known as somatic hypermutation [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The results of this experiment suggest that age factors have little impact on nucleotide insertions and deletions in the peripheral blood BCR H-CDR3 receptor repertoire. \u003cem\u003eV-D-J\u003c/em\u003e recombination is a random process that generates the initial diversity of the repertoire. The adaptive immune system relies on the functional sequences generated by this initial diversity and the specificity of the receptor repertoire. Previous studies on human repertoires have shown that compared with adults, the diversity of neonatal repertoires is limited, mainly through recombination or a small number of \u0026ldquo;N\u0026rdquo; insertions [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. As the body ages, more nucleotide insertions and deletions occur. Our comparison of nucleotide insertions and deletions among people of different ages found that, in terms of the overall trend, the same insertions and deletions show roughly similar trends across different age groups, which is consistent with previously reported information.\u003c/p\u003e\u003cp\u003eThrough systematic analysis of the BCR immune repertoire in healthy adults of different age groups, we have not only deepened the understanding of the characteristics of the immune repertoire in the normal population in central China but also laid a scientific foundation for exploring age-related diseases and therapeutic monitoring, thereby providing a basis for the optimization of future treatment strategies. Although this study is limited by the sample size, with the decrease in the cost of HTS, future studies are expected to expand the sample size, cover more age groups, populations and health statuses, and further reveal the role of the BCR repertoire in aging, immune response and immune-related diseases. These research results are expected to be transformed into disease markers, contributing to the development of early diagnosis and personalized medicine.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis experiment employed HTS to preliminarily investigate the impact of aging on the characteristics of the BCR H-CDR3 repertoire in human peripheral blood B cells. It revealed that the BCR H-CDR3 repertoire exhibits temporal heterogeneity. With the increase of human age, certain changes occur in the usage of individual gene families within the BCR H-CDR3 repertoire, suggesting that there is a certain genetic bias in the usage of \u003cem\u003eIGHV\u003c/em\u003e during the initial \u003cem\u003eV (D) J\u003c/em\u003e rearrangement. This bias may affect the composition and characteristics of an individual's peripheral naive B cell receptor repertoire, thereby influencing the individual's immune response to peripheral antigens. Nucleotide insertions and deletions did not show significant changes with increasing age; the diversity of the B cell BCR H-CDR3 repertoire decreased with age, yet without a marked difference; the length of AA sequences gradually increased as human age advanced, also with no significant difference. In summary, as humans age, the B cell repertoire in the aging body undergoes little change, meaning it is less affected by the external environment.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy subjects\u003c/h2\u003eIn accordance with the principles of obtaining volunteers\u0026apos; informed consent and ethical approval, peripheral blood samples were collected from 9 healthy adults belonging to three different age groups, with 3 cases in each group (young, middle-aged, and elderly). The age selection criteria for the three groups of healthy adults were based on the classification by the World Health Organization of the United Nations. Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eClinical characteristics of the study sample.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eSample\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eAge(years)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eSex\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePermanent residence\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eA1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eWuhan, Hubei province\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eA2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eWuhan, Hubei province\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eA3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eWuhan, Hubei province\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eB1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e50\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eWuhan, Hubei province\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eB2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e46\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eWuhan, Hubei province\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eB3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e50\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eWuhan, Hubei province\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eC1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e74\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eWuhan, Hubei province\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eC2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e81\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eWuhan, Hubei province\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eC3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e86\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eWuhan, Hubei province\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003eSample Preparation\u003cbr\u003e\n \u003cp\u003ePreparation of single-cell suspension: 2 ml of venous blood was drawn from each volunteer to prepare a single-cell suspension, after which DNA was extracted from the lymphocyte samples.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eHigh-Throughput Sequencing\u003c/h2\u003e\n \u003cp\u003e\u003cem\u003eV\u003c/em\u003e-region primers and \u003cem\u003eJ\u003c/em\u003e-region primers containing Illumina sequencing adapter sequences were added to the extracted DNA samples, and a multiplex PCR reaction was performed using the QIAGEN kit. The multiplex PCR products were purified with magnetic beads. The purified DNA was subjected to fragment screening using Agencourt AMPure XP magnetic beads. Then, the recovered DNA products were subjected to a second round of amplification using primers with Illumina Flow Cell sequences. The PCR products were subjected to agarose gel electrophoresis, and after cutting out the fragments of the target size, gel purification and recovery were performed using the QIAquick Gel Extraction Kit, which were then dissolved in Elution Buffer and labeled with library tags, thus completing the library construction. After passing the library quality inspection, sequencing was performed on the Illumina platform.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eData Analysis\u003c/h2\u003e\n \u003cp\u003eIn this project, the BGISEQ-500 platform was used to sequence the immune repertoires of 9 samples. Each sample yielded an average of 4816.75 Mb of data. The raw sequencing data contained reads with low quality, adapter contamination, and excessively high content of unknown base N. After removing these reads, each sample obtained an average of 92.9844 Mb of data. Each sample had high Q20 and Q30 values, reflecting good sequencing quality of the sequencing data (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The filtered reads are shown in supplement Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. After obtaining clean reads, the alignment software MiXCR was used in this project to align the clean reads to the BCR reference gene sequences. For successfully aligned sequences, each clone sequence was obtained after assembly, and sequences with low quality values needed further correction. Finally, sequences with completely identical clone sequences were clustered together to obtain a tab-delimited text file containing all alignment and clone information for each sample. The statistics of alignment results are shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eIGH sequence statistics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eSample\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eClean fragments\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eAligned fragments\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eAlign rate(%)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eFragments used\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eClonetype.no\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eWith stop codons\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eOut of frame\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eA1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15857049\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14765906\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e93.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e12495261\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15894\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1459\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5838\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eA2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15970209\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15033008\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e94.13\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e13050269\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e28396\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3816\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e12265\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eA3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e16003657\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15004715\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e93.76\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e13230465\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e17290\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2192\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e6972\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eB1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15905789\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14860591\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e93.43\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e12900699\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e17385\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2495\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e7111\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eB2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15976951\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14838619\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e92.88\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e12815531\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e21560\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2927\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e8088\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eB3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e16473433\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15484859\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e94.00\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e13530968\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e30810\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3297\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e13944\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eC1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e16433944\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14732124\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e89.64\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e12457615\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e17202\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1995\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e6911\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eC2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e16318181\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15376012\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e94.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e13195347\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e32207\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3585\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14684\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eC3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e16624374\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e15502088\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e93.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e13295775\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e21678\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2409\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e9147\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Statistical table of SHM in B cells.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eSamples\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eCDR3 mutation(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003eVmutation(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eDmutation(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eJmutation(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003eDeletion(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eInsertion(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eSubstitution(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e54.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e14.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e25.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e30.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e7.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e49.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e62.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e19.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e30.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e37.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e57.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e68.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e18.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e34.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e40.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e9.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e10.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e63.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eB1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e61.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e16.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e32.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e35.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e6.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e57.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eB2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e60.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e19.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e29.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e34.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e56.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eB3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e61.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e16.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e25.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e38.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e56.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e63.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e16.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e31.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e35.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e7.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e58.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e58.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e18.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e21.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e34.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e52.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e64.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e17.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e39.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e41.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e5.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e6.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e60.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eSPSS (one-way ANOVA) test was used to compare the expression levels and expression diversity among the three groups. For statistical significance, ∗indicates P \u0026lt; 0.05 .\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHTS: High-Throughput Sequencing; BCR: B Cell Receptor; H-CDR3: Heavy chain Complementarity Determining Region 3; \u003cem\u003eIGHV\u003c/em\u003e: Immunoglobulin Heavy chain Variable gene; \u003cem\u003eIGHJ\u003c/em\u003e: Immunoglobulin Heavy chain Jointing gene; SHM: somatic hypermutation; 1/DS: The inverse Simpson\u0026rsquo;s diversity index; HEC: \u003cstrong\u003eHighly Expanded Clones\u003c/strong\u003e\u003cstrong\u003e;\u003c/strong\u003eMEC: \u003cstrong\u003eIntermediate Expanded Clones\u003c/strong\u003e\u003cstrong\u003e;\u003c/strong\u003e LEC: \u003cstrong\u003eLow Expanded Clones\u003c/strong\u003e\u003cstrong\u003e; TdT: \u003c/strong\u003e\u003cstrong\u003edeoxynucleotidyl transferase. \u003c/strong\u003e\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003eSupplementary information\u003c/p\u003e\n\u003cp\u003eSupplemental Information can be found online at immunity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe are grateful to all for supporting this study,and we thank all the authors, BGI for using their HTS data for analysis.\u003c/p\u003e\n\u003cp\u003eAuthors contributions\u003c/p\u003e\n\u003cp\u003eLina Ma and Ming Li were responsible for designing the research work. Lina Ma analyzed the data and wrote the paper. Hu Zhang, Wenyi Wang，Lili Chen，Xinrui Lei，Lijuan Fan，Yan Tan assisted with the interpretation of the findings and development of the manuscript. all authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis project was supported by the Young and Middle-aged Talents Project of the Science and Technology Research Program of Hubei Provincial Department of Education, China (Q20221109).\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the author on reasonable reqest.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the hospital responsible for clinical affairs. All volunteers provided written informed consent, and the research protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eFormal permission for publication has been obtained from Tianyou Hospital Affiliated to Wuhan University of Science and Technology.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDuchowny, K.A., Zhang, Y.S., Stebbins, R.C. et al. The aging immune system and all-cause mortality in older Americans: differences across sex and race/ethnicity[J]. Immun Ageing 22, 25 (2025).\u003c/li\u003e\n\u003cli\u003eElene A Clemens, Martha A Alexander-Miller. Understanding Antibody Responses in Early Life: Baby Steps towards Developing an Effective Influenza Vaccine [J]. 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The Usage of Human IGHJ Genes Follows a Particular Non-random Selection: The Recombination Signal Sequence May Affect the Usage of Human IGHJ Genes[J]. Front Genet. 2020 Dec 8; 11: 524413.\u003c/li\u003e\n\u003cli\u003eGlanville J, Kuo T C, von Budingen H C, et al. Naive antibody gene-segment frequencies are heritable and unaltered by chronic lymphocyte ablation[J]. Proc Natl Acad Sci U S A, 2011, 108(50): 20066-20071.\u003c/li\u003e\n\u003cli\u003eSchatz D G, Ji Y. Recombination centres and the orchestration of V(D)J recombination[J]. Nat Rev Immunol, 2011, 11(4): 251-263. \u003c/li\u003e\n\u003cli\u003eLanwei Zhu, Qi Peng, Yingjie Wu , et al. scBCR-seq revealed a special and novel IG H\u0026amp;L V(D)J allelic inclusion rearrangement and the high proportion dual BCR expressing B cells[J]. Cell Mol Life Sci. 2023 Oct 7; 80(11): 319.\u003c/li\u003e\n\u003cli\u003eMarie J Kidd, Katherine J L Jackson , Scott D Boyd, et al. 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Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing date[J]. PLoS Comput Biol. 2020 Jun 23; 16(6): e1007977.\u003c/li\u003e\n\u003cli\u003eMarie J Kidd, Katherine J L Jackson, Scott D Boyd. DJ pairing during VDJ recombination shows positional biases that vary between individuals with differing IGHD locus immunogenotypes[J]. J Immunol. 2016 Feb 1; 196(3): 1158-64.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7535948/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7535948/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWith the intensification of population aging, the health issues of the elderly have attracted increasing attention. The structure and function of the immune system decline with age, and changes in the quantity, subsets, and functionality of B cells are closely associated with aging. In this study, high-throughput sequencing (HTS) was employed to analyze the diversity and dynamic changes of the B-cell receptor (BCR) H-CDR3 repertoire in peripheral blood samples from nine healthy adults across different age groups (young, middle-aged, and elderly). The results revealed that the CDR3 amino acid(AA) length in the middle-aged group was significantly longer than that in the young and elderly groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, significant differences in \u003cem\u003eIGHV\u003c/em\u003e gene usage were observed among the age groups, suggesting that \u003cem\u003eIGHV\u003c/em\u003e gene usage is strongly influenced by age. Furthermore, the number of shared AA sequences in the BCR increased with age, reflecting the cumulative effects of antigen exposure. Although no significant differences in clonal diversity or clonal frequency distribution were detected among the age groups, the elderly group exhibited a more concentrated clonal frequency distribution, indicating that the immune system's antigen-specific response becomes more focused with aging. This study provides new insights into the impact of age on the BCR and lays a foundation for future research on age-related diseases and personalized therapies.\u003c/p\u003e","manuscriptTitle":"Analysis of the heterogeneity of the BCR H-CDR3 repertoire in peripheral blood B cells of adult women with increasing age in Central China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-05 09:11:09","doi":"10.21203/rs.3.rs-7535948/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"771da7b3-19cd-4c7c-bbe7-c22bcee5fc05","owner":[],"postedDate":"September 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-12T14:23:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-05 09:11:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7535948","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7535948","identity":"rs-7535948","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}