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An analysis of abnormalities in the B cell receptor repertoire in patients with systemic sclerosis using high-throughput sequencing.

ABSTRACT: Systemic sclerosis is a chronic multisystem autoimmune disease that is associated with polyclonal B cell hyperreactivity. The CDR3 of BCRs is the major site of antigen recognition. Therefore, we analyzed the BCR repertoire of patients with SSc. The BCR repertoires in 12 subjects including eight SSc patients and four healthy controls were characterized by high-throughput sequencing, and bioinformatics analysis were studied. The average CDR3 length in the SSc group was significantly shorter. The SSc patient displayed more diverse BCR. Moreover, SSc patients with mild skin sclerosis, anti-Scl70, interstitial lung disease or female sex were more diversified. B cells from the SSc patients showed a differential V and J gene usage. SSc patients had distinct BCR repertoires.These findings reflected the differences of BCR repertoires between SSc patients and controls. The higher-usage genes for the BCR sequence might be potential biomarkers of B cell-targeted therapies or diagnosis for SSc.

SUBMITTER: Shi X

PROVIDER: S-EPMC6968515 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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An analysis of abnormalities in the B cell receptor repertoire in patients with systemic sclerosis using high-throughput sequencing.

Shi Xiaodong X Shao Tihong T Huo Feifei F Zheng Chenqing C Li Wanyu W Jiang Zhenyu Z

PeerJ 20200114

Systemic sclerosis is a chronic multisystem autoimmune disease that is associated with polyclonal B cell hyperreactivity. The CDR3 of BCRs is the major site of antigen recognition. Therefore, we analyzed the BCR repertoire of patients with SSc. The BCR repertoires in 12 subjects including eight SSc patients and four healthy controls were characterized by high-throughput sequencing, and bioinformatics analysis were studied. The average CDR3 length in the SSc group was significantly shorter. The S ...[more]

PMID: 31988805

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Project description:BackgroundAs one of "γδ-high" species, chicken is an excellent model for the study of γδ T cells in non-mammalian animals. However, a comprehensive characterization of the TCRγδ repertoire is still missing in chicken. The objective of this study was to characterize the expressed TCRγ repertoire in chicken thymus using high-throughput sequencing.MethodsIn this study, we first obtained the detailed genomic organization of the TCRγ locus of chicken based on the latest assembly of the red jungle fowl genome sequences (GRCg6a) and then characterized the TCRγ repertoire in the thymus of four chickens by using 5' Rapid Amplification of cDNA Ends (5' RACE) along with high-throughput sequencing (HTS).ResultsThe chicken TCRγ locus contains a single Cγ gene, three functional Jγ segments and 44 Vγ segments that could be classified into six subgroups, each containing six, nineteen, nine, four, three and three members. Dot-plot analysis of the chicken TCRγ locus against itself showed that almost all the entire zone containing Vγ segments had arisen through tandem duplication events, and the main homology unit, containing 9 or 10 Vγ gene segments, has tandemly duplicated for four times. For the analysis of chicken TCRγ repertoire, more than 100,000 unique Vγ-region nucleotide sequences were obtained from the thymus of each chicken. After alignment to the germline Vγ and Jγ segments identified above, we found that the four chickens had similar repertoire profile of TCRγ. In brief, four Vγ segments (including Vγ3.7, Vγ2.13, Vγ1.6 and Vγ1.3) and six Vγ-Jγ pairs (including Vγ3.7-Jγ3, Vγ2.13-Jγ1, Vγ2.13-Jγ3, Vγ1.6-Jγ3, Vγ3.7-Jγ1 and Vγ1.6-Jγ1) were preferentially utilized by all four individuals, and vast majority of the unique CDR3γ sequences encoded 4 to 22 amino acids with mean 12.90 amino acids, which exhibits a wider length distribution and/or a longer mean length than CDR3γ of human, mice and other animal species.ConclusionsIn this study, we present the first in-depth characterization of the TCRγ repertoire in chicken thymus. We believe that these data will facilitate the studies of adaptive immunology in birds.

Project description:BackgroundSkin fibrosis is the clinical hallmark of systemic sclerosis (SSc), where collagen deposition and remodeling of the dermis occur over time. The most widely used outcome measure in SSc clinical trials is the modified Rodnan skin score (mRSS), which is a semi-quantitative assessment of skin stiffness at seventeen body sites. However, the mRSS is confounded by obesity, edema, and high inter-rater variability. In order to develop a new histopathological outcome measure for SSc, we applied a computer vision technology called a deep neural network (DNN) to stained sections of SSc skin. We tested the hypotheses that DNN analysis could reliably assess mRSS and discriminate SSc from normal skin.MethodsWe analyzed biopsies from two independent (primary and secondary) cohorts. One investigator performed mRSS assessments and forearm biopsies, and trichrome-stained biopsy sections were photomicrographed. We used the AlexNet DNN to generate a numerical signature of 4096 quantitative image features (QIFs) for 100 randomly selected dermal image patches/biopsy. In the primary cohort, we used principal components analysis (PCA) to summarize the QIFs into a Biopsy Score for comparison with mRSS. In the secondary cohort, using QIF signatures as the input, we fit a logistic regression model to discriminate between SSc vs. control biopsy, and a linear regression model to estimate mRSS, yielding Diagnostic Scores and Fibrosis Scores, respectively. We determined the correlation between Fibrosis Scores and the published Scleroderma Skin Severity Score (4S) and between Fibrosis Scores and longitudinal changes in mRSS on a per patient basis.ResultsIn the primary cohort (n =?6, 26 SSc biopsies), Biopsy Scores significantly correlated with mRSS (R?=?0.55, p =?0.01). In the secondary cohort (n =?60 SSc and 16 controls, 164 biopsies; divided into 70% training and 30% test sets), the Diagnostic Score was significantly associated with SSc-status (misclassification rate?=?1.9% [training], 6.6% [test]), and the Fibrosis Score significantly correlated with mRSS (R?=?0.70 [training], 0.55 [test]). The DNN-derived Fibrosis Score significantly correlated with 4S (R?=?0.69, p =?3?×?10-?17).ConclusionsDNN analysis of SSc biopsies is an unbiased, quantitative, and reproducible outcome that is associated with validated SSc outcomes.

Dataset Information

An analysis of abnormalities in the B cell receptor repertoire in patients with systemic sclerosis using high-throughput sequencing.

Publications

An analysis of abnormalities in the B cell receptor repertoire in patients with systemic sclerosis using high-throughput sequencing.

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