Non-invasive molecular typing system and method for primary sicca syndrome

Abstract

The invention discloses a non-invasive molecular typing system and method for primary sicca syndrome. The method comprises the following steps: respectively acquiring lip gland tissue transcriptome sequencing data of a primary sicca syndrome patient and a control group; based on transcriptome sequencing data, through KEGG pathway analysis of a whole genome, a non-negative matrix factorization (NMF) algorithm is used for carrying out disease molecular typing on pSS. According to the invention, a gene expression pathway is taken as an entry point, contributions of all genes on one pathway are concerned, but not only the action of differential expression genes, module analysis is carried out by utilizing a bioinformatics technology, and different molecular types of pSS are identified.

Description

Technical Field

[0001] The present invention belongs to the field of molecular typing, and particularly relates to a non-invasive molecular typing system and method for primary Sjögren's syndrome. Background Art

[0002] Sjögren's syndrome ( SS) is a chronic inflammatory autoimmune disease characterized by lymphocyte proliferation and progressive damage to exocrine glands. Clinically, in addition to impaired salivary and lacrimal gland functions, multiple systems and organs can also be involved, and autoantibodies and hypergammaglobulinemia are present in the serum. According to whether it is accompanied by other connective tissue diseases, SS is divided into secondary SS and primary SS (primary SS, pSS), and the former is often secondary to systemic lupus erythematosus, rheumatoid arthritis, etc.

[0003] Common classification criteria for Sjögren's syndrome include the 2002 international classification criteria, the 2012 international clinical cooperation alliance classification criteria, and the 2016 American College of Rheumatology / European League Against Rheumatism (ACR / EULAR) classification criteria. The 2016 ACR / EULAR classification criteria have relatively high sensitivity and specificity and are easy to operate, and are currently widely used in clinical practice. Whether it is primary Sjögren's syndrome or secondary Sjögren's syndrome, a histological examination must be included for a definite diagnosis. The histological examination is a lip biopsy, in which a small piece of lip gland lobule tissue of the patient's lower lip is surgically excised under local anesthesia for microscopic analysis, and the number of lymphocyte foci per unit area of the pathological section is observed (the number of lymphocyte infiltrations within 4 mm 2 ≥50 is one focus). The pathological grade of the lip biopsy is divided into grades I, II, III, and IV according to the Chisholm criteria. In the case of less than one lymphocyte focus, a small amount of lymphocyte infiltration is grade I, moderate infiltration is grade II, the presence of one lymphocyte focus is grade III, and two or more are grade IV. The diagnostic criteria for pSS are complex and the examination types are diverse, and comprehensive analysis of various indicators is required.

[0004] Currently, there is no clear molecular typing method for primary Sjögren's syndrome (pSS) internationally. The commonly used clinical typing of pSS is divided into two major categories, glandular type and systemic type, according to the involvement of tissues and organs, but there is an overlapping genetic and immune background between the two, and the two types cannot be completely independent. Moreover, when tissue and organ involvement occurs, it is often in the late stage of the disease. Some scholars have tried to classify the disease according to the symptoms of the patients to evaluate different responses to immunomodulatory therapy, but this typing method still cannot reflect the differences in its pathogenesis. The molecular typing based on the pathogenesis of the most important target organ of pSS - the salivary gland is still in the exploratory stage. Currently, there is still a lack of an effective typing method for the molecular mechanism of primary Sjögren's syndrome. Summary of the Invention

[0005] To solve the above technical problems, the present invention proposes a non-invasive molecular typing system and method for primary Sjögren's syndrome, which uses bioinformatics technology for module analysis to identify different molecular types of pSS.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A non-invasive molecular typing system for primary Sjögren's syndrome, comprising a sequencing module and a typing module;

[0008] The sequencing module is used to obtain the transcriptome sequencing data of the labial gland tissues of primary Sjögren's syndrome patients and the control group respectively;

[0009] The analysis module is used to perform molecular typing of the disease for pSS by using the non-negative matrix factorization algorithm through the KEGG pathway analysis of the whole genome based on the transcriptome sequencing data.

[0010] Preferably, the typing module includes a KEGG unit and a calculation unit;

[0011] The KEGG unit is used to perform KEGG pathway analysis of the whole genome on the transcriptome sequencing data;

[0012] The calculation unit is used to perform molecular typing of the disease for pSS by using the non-negative matrix factorization algorithm.

[0013] Preferably, in the calculation unit, IFN pathway typing is used as the basis for disease molecular typing, and primary Sjögren's syndrome patients are divided into IFN-dominant type and non-IFN-dominant type.

[0014] Preferably, in the calculation unit, the IFN-score value of each sample is calculated according to the FPKM of interferon pathway-related genes to type all primary Sjögren's syndrome patients;

[0015] The calculation method is:

[0016]

[0017] where i is the IFN pathway gene, Gene ipSS represents the gene expression level of each primary Sjögren's syndrome patient, and Gene inonpSS represents the gene expression level of each non-pSS control.

[0018] Preferably, the normalmixEM function is used to simulate the Gaussian bimodal distribution of the IFN-score values of all samples, and the cut-off value is set to the score value of 13 when the two peaks intersect. When the IFN-score of a primary Sjögren's syndrome patient > 13, it is the IFN-dominant group, and when the IFN-score <= 13, it is the non-IFN-dominant type.

[0019] The present application also provides a non-invasive molecular typing method for primary Sjögren's syndrome, comprising the following steps:

[0020] Respectively obtain the transcriptome sequencing data of the labial gland tissues of primary Sjögren's syndrome patients and the control group;

[0021] Based on the transcriptome sequencing data, through the KEGG pathway analysis of the whole genome, the non-negative matrix factorization algorithm is used to perform molecular typing of the disease for pSS.

[0022] Preferably, IFN pathway typing is used as the basis for disease molecular typing, and primary Sjögren's syndrome patients are divided into IFN-dominant type and non-IFN-dominant type.

[0023] Preferably, the IFN-score value of each sample is calculated according to the FPKM of genes related to the interferon pathway to type all primary Sjögren's syndrome patients;

[0024] The calculation method is:

[0025]

[0026] where i is the IFN pathway gene, Gene ipSS represents the gene expression level of each primary Sjögren's syndrome patient, and Gene inonpSS represents the gene expression level of each non-pSS control.

[0027] Preferably, the normalmixEM function is used to simulate the Gaussian bimodal distribution of the IFN-score values of all samples, and the cut-off value is set to the score value of 13 when the two peaks intersect. When the IFN-score of a primary Sjögren's syndrome patient > 13, it is the IFN-dominant group, and when the IFN-score <= 13, it is the non-IFN-dominant type.

[0028] The beneficial effects of the present invention are as follows:

[0029] The present invention takes the gene expression pathway as the entry point, pays attention to the contributions of all genes on one pathway, rather than just the roles of differentially expressed genes, and uses bioinformatics technology for module analysis to identify different molecular typings of pSS. The present invention accurately identifies different types of pSS patients through a more comprehensive gene analysis method. Detailed implementation mode

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0031] Embodiment 1

[0032] A non-invasive molecular typing system for primary Sjögren's syndrome mainly includes a sequencing module and a typing module.

[0033] Among them, the sequencing module is used to obtain the transcriptome sequencing data of the labial gland tissues of primary Sjögren's syndrome patients and the control group respectively. The analysis module is used to perform molecular typing of the disease for pSS by performing KEGG pathway analysis of the whole genome based on the transcriptome sequencing data and using the non-negative matrix factorization (NMF) algorithm.

[0034] Next, the analysis module will be specifically described:

[0035] In this embodiment, the typing module includes a KEGG unit and a calculation unit. Specifically, the KEGG unit is used to perform KEGG pathway analysis of the whole genome on the transcriptome sequencing data. KEGG is a database resource of practical programs for understanding advanced functions and biological systems (such as cells, organisms, and ecosystems) from molecular level information, especially genomic sequencing and other high-throughput experimental technologies generated from large molecular datasets. The calculation unit is used to perform molecular typing of the disease for pSS using the non-negative matrix factorization (NMF) algorithm.

[0036] In this embodiment, based on the evaluation of the typing efficacy, the calculation unit uses IFN pathway typing as the best molecular typing of the disease, and classifies primary Sjögren's syndrome patients pSS into IFN-dominant type (IFN-pos type) and non-IFN-dominant type (IFN-neg type). Specifically, the IFN-score value of each sample is calculated according to the FPKM (i.e., fragments per million mapped reads per kilobase of transcript) of 39 interferon (IFN) pathway-related genes to type all primary Sjögren's syndrome patients.

[0037] The calculation method is as follows:[[]]

[0038]

[0039] Among them, Gene ipSS represents the gene expression level of each primary Sjögren's syndrome patient, Gene inonpSSIndicates the gene expression levels of each control group non-pSS control. i represents 39 IFN pathway genes, which are as follows in this example: CXCL10, GBP5, HERC5, IFI44, IFI44L, IFIT1, IFIT2, IFITM3, ISG15, LY6E, MX1, OAS2, OAS3, OASL, RSAD2, STAT1, USP18, BATF2, DTX3L, GBP1, HLA-B, HLA-DMA, HLA-DPA1, HLA-E, HLA-F, IFI27, IFI6, IFITM1, IL18BP, IL32, LAMP3, PSMB9, SP110, STAT2, TAP1, TRIM22, UBD, UBE2L6, WARS.

[0040] The R package mixtools is used to analyze the finite mixture model. The normalmixEM function is used to simulate the Gaussian bimodal distribution of the IFN-score values of all samples. The cut-off value is set to the score value 13 when the two peaks intersect. That is, when the IFN-score of primary Sjögren's syndrome patients > 13, it is defined as the IFN-dominant group (IFN-pos type), and when IFN-score <= 13, it is defined as the non-IFN-dominant group (IFN-neg type).

[0041] The present invention takes the gene expression pathway as the starting point, focuses on the contributions of all genes on one pathway, rather than just the roles of differentially expressed genes, and uses bioinformatics techniques for module analysis to identify different molecular subtypes of pSS. The present invention accurately identifies different types of pSS patients through a more comprehensive gene analysis method.

[0042] Example 2

[0043] A non-invasive molecular typing method for primary Sjögren's syndrome, comprising the following steps:

[0044] S1. Respectively obtain the transcriptome sequencing data of the labial gland tissues of primary Sjögren's syndrome patients and the control group.

[0045] S2. Based on the transcriptome sequencing data, through the KEGG pathway analysis of the whole genome, use the non-negative matrix factorization (NMF) algorithm to perform molecular typing of the disease for pSS. Among them, KEGG is a practical program database resource for understanding advanced functions and biological systems (such as cells, organisms, and ecosystems), from molecular-level information, especially genomic sequencing and other high-throughput experimental technologies generated by large molecular datasets.

[0046] In this embodiment, based on the evaluation of the typing efficiency, the IFN pathway typing is used as the best disease molecular typing, and primary Sjögren's syndrome patients (pSS) are divided into IFN-dominant type (IFN-pos type) and non-IFN-dominant type (IFN-neg type). Specifically, the IFN-score value of each sample is calculated according to the FPKM (i.e., fragments per kilobase of exon model per million mapped reads) of 39 interferon (IFN) pathway-related genes to type all primary Sjögren's syndrome patients.

[0047] The calculation method is as follows:

[0048]

[0049] where i is one of the 39 IFN pathway genes, Gene ipSS represents the gene expression level of each primary Sjögren's syndrome patient, and Gene inonpSS represents the gene expression level of each non-pSS control.

[0050] The R package mixtools is used to analyze the finite mixture model, and the normalmixEM function is used to simulate the Gaussian bimodal distribution of the IFN-score values of all samples. The cut-off value is set to the score value 13 when the two peaks intersect. That is, when the IFN-score of a primary Sjögren's syndrome patient > 13, it is defined as the IFN-dominant type group (IFN-pos type), and when IFN-score <= 13, it is defined as the non-IFN-dominant type group (IFN-neg type). The present invention takes the gene expression pathway as the entry point, focuses on the contributions of all genes on one pathway, rather than just the roles of differentially expressed genes, and uses bioinformatics techniques for module analysis to identify different molecular typings of pSS. The present invention accurately identifies different types of pSS patients through a more comprehensive gene analysis method.

[0051] The above-described embodiments are only descriptions of the preferred embodiments of the present invention and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A non-invasive molecular typing system for primary Sjögren's syndrome, characterized in that: Includes sequencing module and typing module; The sequencing module is used to obtain the transcriptome sequencing data of the labial gland tissue of the primary Sjögren's syndrome patients and the control group respectively; The analysis module is used to perform molecular disease typing of pSS based on the transcriptome sequencing data through genome-wide KEGG pathway analysis using a non-negative matrix decomposition algorithm.

2. The molecular typing system according to claim 1, characterized in that: The typing module includes a KEGG unit and a calculation unit; The KEGG unit is used to perform genome-wide KEGG pathway analysis on the transcriptome sequencing data; The computing unit is used to perform molecular typing of the disease on pSS using a non-negative matrix decomposition algorithm.

3. The molecular typing system according to claim 2, characterized in that: In the calculation unit, IFN pathway typing is used as the basis for molecular typing of the disease, and primary Sjögren's syndrome patients are divided into IFN-dominant type and non-IFN-dominant type.

4. The molecular typing system according to claim 3, characterized in that: In the calculation unit, the IFN-score value of each sample is calculated according to the FPKM of interferon pathway related genes to classify all primary Sjögren's syndrome patients; The calculation method is: Among them, i is the IFN pathway gene, Gene ipSS Represents the gene expression level of each patient with primary Sjögren's syndrome. inonpSS The gene expression level of each non-pSS control is shown.

5. The molecular typing method according to claim 4, characterized in that: The normalmixEM function was used to simulate the Gaussian bimodal distribution of the IFN-score values ​​of all samples, and the cutoff value was set to the score value of 13 when the two peaks intersected. When the IFN-score of patients with primary Sjögren's syndrome was > 13, they were in the IFN-dominant group, and when the IFN-score was <= 13, they were in the non-IFN-dominant group.

6. A non-invasive molecular typing method for primary Sjögren's syndrome, characterized in that: The following steps are involved: The transcriptome sequencing data of labial gland tissues of patients with primary Sjögren's syndrome and controls were obtained respectively; Based on the transcriptome sequencing data, the molecular typing of pSS disease was performed by whole genome KEGG pathway analysis using non-negative matrix decomposition algorithm.

7. The molecular typing method according to claim 6, characterized in that: Using IFN pathway typing as the basis for molecular classification of the disease, patients with primary Sjögren's syndrome were divided into IFN-dominant type and non-IFN-dominant type.

8. The molecular typing method according to claim 7, characterized in that: The IFN-score value of each sample was calculated according to the FPKM of interferon pathway-related genes to classify all patients with primary Sjögren's syndrome; The calculation method is: Among them, i is the IFN pathway gene, Gene ipSS Represents the gene expression level of each patient with primary Sjögren's syndrome. inonpSS The gene expression level of each non-pSS control is shown.

9. The molecular typing method according to claim 8, characterized in that: The normalmixEM function was used to simulate the Gaussian bimodal distribution of the IFN-score values ​​of all samples, and the cutoff value was set to the score value of 13 when the two peaks intersected. When the IFN-score of patients with primary Sjögren's syndrome was > 13, they were in the IFN-dominant group, and when the IFN-score was <= 13, they were in the non-IFN-dominant group.

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