CN114333990A - Postmenopausal osteoporosis related gene screening and function analysis method - Google Patents
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Abstract
The invention discloses a postmenopausal osteoporosis related gene screening and function analysis method, which comprises the following steps: searching a gene expression chip related to postmenopausal osteoporosis from a GEO database, and obtaining a gene expression result; searching for overlapped differential genes in the two chip data sets by using a Venn diagram; gene enrichment functional analysis was performed using the Metascape and DAVID databases. The invention downloads the expression differential genes by utilizing various online databases, finds the differential genes which are commonly expressed in two chip data sets, and carries out bioinformatics analysis on the commonly expressed differential genes, thereby providing meaningful exploration and basis for screening markers, molecular pathogenesis and the like related to postmenopausal osteoporosis.
Description
Technical Field
The invention belongs to the technical field of biology, and relates to a postmenopausal osteoporosis related gene screening and function analysis method.
Background
Osteoporosis (OP) is a systemic skeletal disease characterized by decreased Bone Mineral Density (BMD), degenerated bone microarchitecture resulting in increased bone fragility and susceptibility to fracture. Osteoporosis in women following menopause due to ovarian failure, decreased estrogen levels, and increased bone loss is called postmenopausal osteoporosis (PMOP). The most serious consequence of osteoporosis is bone fracture, which is approximately 900 million clinical osteoporotic fractures worldwide per year. In women over 60 years old in China, the incidence rate of osteoporosis is up to 40-50%, 30-50% of osteoporosis fractures are suffered, the osteoporosis fractures have high incidence rate and mortality rate, and the medical cost is obviously increased. With the increase of human life and the coming of aging society, the incidence rate of osteoporosis is rising year by year, and has become a public health problem worldwide, and as the type of osteoporosis which is most researched and has the highest incidence rate at present, the prevention and treatment of postmenopausal osteoporosis has become an important health care subject.
Osteoporosis, which results from a disruption in the balance of the bone remodeling system, is the result of an imbalance between the bone resorption performed by Osteoclasts (OCs) and the bone formation performed by Osteoblasts (OB), and results from either overactive bone resorption or insufficient bone formation. Therapeutic strategies for osteoporosis include inhibiting bone resorption and/or promoting bone formation. The former is achieved by inhibiting osteoclast formation by an anti-bone resorption drug such as estrogen and Bisphosphonate (BP), and the latter is achieved by promoting osteoblast proliferation and differentiation by an anabolic agent (anabolic agent) such as parathyroid hormone (PTH) and sclerostin (sclerostin) inhibitor, etc. These drugs have certain side effects in long-term use, and the therapeutic effect of drugs for osteoporosis is not ideal.
Research shows that a series of signal pathways are related to postmenopausal osteoporosis, including regulation of osteoblast differentiation through a SIRT1-NF-kB signal pathway or through functional communication between a RANKL/RANK/OPG system and a Wnt/beta-catenin pathway, and influence of a Notch signal pathway on proliferation and differentiation of bone mesenchymal stem cells. Currently, a number of functional or potentially genetically related genes associated with osteoporosis are found in chinese postmenopausal women, such as the Osteoprotegerin (OPG) gene, the estrogen receptor beta (ESR2) gene, the human leukocyte antigen B (HLA-B) gene.
Therefore, the search for biomarkers related to postmenopausal osteoporosis becomes a hot problem in the research of early diagnosis and treatment of postmenopausal osteoporosis. The early diagnosis of postmenopausal osteoporosis can help doctors to make a reasonable early treatment strategy, improve the treatment effect, greatly reduce the treatment cost of patients and have important clinical and scientific significance.
The Gene Expression database (GEO) is the largest and most comprehensive public Gene Expression data resource at present, and comprises the wide classification of high-throughput experimental data, single-channel and double-channel microarray-based mRNA abundance measurement; experimental data for genomic DNA and protein molecules. To date, the GEO database contains data that covers roughly 10000 hybridization experiments and is derived from 30 different organisms. The database is simple to operate, comprehensive in data and free to share, and a good platform is provided for later-stage data mining and information popularization. The GEO database has wide application prospect in the field of molecular biology, and provides an optimal platform for the mining and screening of postmenopausal osteoporosis related genes.
Disclosure of Invention
The invention aims to provide a method for screening and functional analysis of related genes of postmenopausal osteoporosis, wherein the DEG (expression differential genes) closely related to the postmenopausal osteoporosis is screened by utilizing microarray data sets GSE56116 and GSE100609 of whole blood samples of postmenopausal osteoporosis women in a GEO database, differential genes shared by two chips are determined by Venn diagram preparation, the DAVID database is utilized to carry out GO function enrichment analysis and KEGG channel enrichment analysis on the screened differential genes, and the STRING database is utilized to carry out protein interaction analysis, so that meaningful exploration and basis are provided for screening of markers of the postmenopausal osteoporosis, molecular pathogenesis and the like.
In order to achieve the purpose, the specific technical scheme of the invention is as follows:
the invention firstly provides a postmenopausal osteoporosis related gene screening and function analysis method, which comprises the following steps:
1) screening a research chip series meeting the conditions by utilizing a GEO database: searching for postmenopausal osteoporosis related gene expression chip results from GEO database http:// www.ncbi.nlm.nih.gov/GEO/with the search conditions defined as: (1) postmenopausal osteoporosis; (2) a human source; (3) the research type is chip expression profile detection; (4) the sample source is a peripheral blood sample, and after screening, two chip series are brought into the research: GSE56116 and GSE100609, included in 14 postmenopausal osteoporosis peripheral blood samples and 7 normal control samples;
2) in gene expression database GEO (https: // www.ncbi.nlm.nih.gov/geo /) download the data set of the gene expression profile of peripheral blood samples for postmenopausal osteoporosis: GSE56116 and GSE100609, and based on the P value<0.05 and | log2FC | > 0.5 screening criteria for differential genes;
3) venn plots were used to find the same gene expression results in both chip datasets: selecting two chip series to express differential genes, finding 947 differential genes in GSE56116 and 413 differential genes in GSE 100609; generating a Venn diagram by using an online Venn diagram making tool, wherein 14 overlapped differential genes exist in two data sets;
4) carrying out GO functional enrichment analysis on 14 overlapped differential genes by using Metascape and DAVID databases;
5) collecting core genes related to postmenopausal osteoporosis by searching the CTD database;
in some embodiments, the method further comprises constructing a protein interaction network (PPI) of 14 overlapping difference genes using the STRING database.
In some embodiments, the biological process analyzed by the DAVID database in step 4) involves endothelial development, BMP signaling pathways, fibroblast growth factor receptor signaling pathways, phosphatidylinositol-mediated signaling, and peptidyl tyrosine phosphorylation; the enriched molecular function of the differential gene is protein tyrosine kinase activity and the enriched cellular component of the differential gene is an intracellular component of the plasma membrane;
the Metascape database analyses the prominent functions of major enrichment are chemotaxis, cellular response to growth factor stimulation and positive modulation of organelle tissue.
In some embodiments, the genes screened for association with postmenopausal osteoporosis in step 5) include CDH23, CKLF, CXXC5, and RGMA.
In some embodiments, dense modules containing CXXC5 and RGMA, in which CXXC5 interacts with KDR and RGMA interacts with BMP2, are selected according to the protein interaction network constructed above.
Further, the invention provides a group of markers for early diagnosis of postmenopausal osteoporosis, and the candidate markers for early diagnosis of postmenopausal osteoporosis are selected from one or more of the following CD1E, CDH23, CKLF, CXXC5, IRGC, RGMA, SDAD1 and WHAMMP3 genes.
In some preferred embodiments, the candidate markers for early diagnosis of postmenopausal osteoporosis comprise CDH23, CKLF, CXXC5, and/or RGMA genes.
In some embodiments, the CDH23, CKLF, CXXC5, and RGMA genes are up-regulated in blood samples of postmenopausal osteoporosis.
Furthermore, the invention provides application of the marker in preparing a kit for early diagnosis of postmenopausal osteoporosis.
In some embodiments, the kit comprises reagents to detect the expression level of CDH23, CKLF, CXXC5, and/or RGMA gene markers.
The invention utilizes microarray data sets GSE56116 and GSE100609 of postmenopausal osteoporosis women whole blood samples in a GEO database to analyze and screen DEG closely related to postmenopausal osteoporosis. Core Differentially Expressed Genes (DEGs), namely CDH23, CKLF, CXXC5 and RGMA, were screened in postmenopausal osteoporosis patients by functional enrichment analysis, PPI networks, core (hub) gene identification, and gene-disease relationship assessment. The biological properties of postmenopausal osteoporosis and the basic molecular mechanism in the occurrence and development processes of postmenopausal osteoporosis are expected to be deeply recognized, so that a detection marker and a new treatment point are provided for the diagnosis of postmenopausal osteoporosis, and a reliable scientific basis is provided for the prevention and treatment of diseases and the like.
Drawings
Fig. 1 overlaps the identification of DEG. The overlapping region represents a common gene between GSE56116 and GSE 100609; (A) DEG numbers in GSE56116 and GSE 100609; (B) 14 overlapping DEG in the two expression profiles;
FIG. 2 Rich functional analysis of DEG; (A) GO analysis enriches the pathways and functions of overlapping DEGs, involving the biological processes, molecular functions and cellular components of DEGs; (B) metascape mainly enriches the significant biological processes of DEGs;
FIG. 3 DEGs expression in healthy and osteoporotic women; (a, B) up-regulation of CXXC5 and CDH23 expression in osteoporotic female samples in GSE56116 and GSE 100609; (C, D) downregulation of CKLF and RGMA expression in osteoporotic female samples in GSE56116 and GSE 100609;
FIG. 4 relationship of DEGs to osteoporosis; assessing an inference score for DEG versus bone-related disease by comparing a toxicological genomics database; (A) inferred scores for CDH23, (B) CKLF, (C) CXXC5 and (D) RGMA were assessed as being associated with postmenopausal osteoporosis;
FIG. 5 relationship of DEGs to osteoporosis; (A) inferred scores for CD1E, (B) SDAD1, (C) IRGC and (D) WHAMMP3 were assessed by CTD;
PPI network analysis of fig. 6 deg.
Detailed Description
The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention. Unless otherwise specified, the technical means used in the examples are conventional means well known to those skilled in the art.
The invention aims to identify the obvious change of characteristic genes related to postmenopausal osteoporosis and carry out functional analysis through gene expression profiles.
Downloading from the GEO database gene expression profiles GSE56116 and GSE100609, samples in GSE56116 and GSE100609 were from whole blood samples from postmenopausal osteoporotic women. Differential Expression Genes (DEG) closely related to postmenopausal osteoporosis were determined by online software GEO2R, followed by GO enrichment analysis. The relationship of DEG to postmenopausal osteoporosis was also assessed by the CTD database. In addition, using the STRING database, protein-protein interaction (PPI) networks were constructed.
The results show that of 947 DEG in GSE56116 and 413 DEG in GSE100609, there were 14 overlapping DEG in the two expression profiles. The prominent functions of the overlapping DEG major enrichment are chemotaxis, cellular response to growth factor stimulation and positive regulation of organelle tissue. Further GO analysis also indicates that biological processes of DEG such as BMP signaling pathway and fibroblast growth factor receptor signaling pathway, molecular functions of DEG (such as protein tyrosine kinase activity) and cellular components of DEG (such as transmembrane components of plasma membrane) are involved. However, the trend of the 14 overlapping DEG's in GSE56116 and GSE100609 is not completely consistent. Of GSE56116 and GSE100609, only 8 DEG, CD1E, CDH23, CKLF, CXXC5, IRGC, RGMA, SDAD1 and WHAMMP3, were relatively up-regulated in postmenopausal osteoporosis samples. Meanwhile, the relative expression of the other 6 DEG's differs in GSE56116 and GSE 100609. Rational scores for the relationship of 8 consistent DEG to bone-related disease were evaluated to reveal DEG's relationship to postmenopausal osteoporosis. Only CDH23, CKLF, CXXC5 and RGMA were found to be associated with postmenopausal osteoporosis and osteoporosis.
Taken together, the four overlapping DEGs of CDH23, CKLF, CXXC5 and RGMA showed consistent trends in both expression profiles and were found to be closely associated with postmenopausal osteoporosis. The data can be used for identifying high-risk groups of osteoporosis and providing some meaningful guidance for targeted treatment of osteoporosis.
Example 1
1. Microarray data analysis
And (3) screening a research series meeting the conditions by utilizing a GEO database: searching for postmenopausal osteoporosis related gene expression chip results from GEO database http:// www.ncbi.nlm.nih.gov/GEO/with the search conditions defined as: (1) postmenopausal osteoporosis; (2) a human source; (3) the research type is chip expression profile detection; (4) the sample source is a peripheral blood sample, and after screening, two chip series are brought into the research: GSE56116 and GSE 100609.
In the present invention, there were 13 samples of perimenopausal blood in GSE56116, of which 3 were postmenopausal healthy women as a control group and 10 postmenopausal osteoporosis patients as a test group; there were 8 exceptions to the peri-weekly blood samples in GSE100609, with 4 healthy postmenopausal women as the control group and 4 postmenopausal osteoporosis patients as the experimental group.
2. Differential Gene (DEG) analysis
The genes were subjected to a group analysis using online analysis software GEO2R, and divided into a postmenopausal osteoporosis group and a normal group. Data of 2 mRNA chips (GSE 56116)&GSE100609) set P-value and fold difference (FC) for screening of differential genes. Is considered to be when p<0.05&|log2FC|>Differences in time of 0.5 are statistically significant.
Wenn plots were made online using venny (https:// bioinfogp. cnb. scic. es/tools/venny/index. html) and the intersection of the DEG's of the two datasets was selected for further analysis.
3. CTD database search for differential genes associated with postmenopausal osteoporosis
CTD database (C:)http://ctdbase.org/) I.e., comparative toxicant genomics databases, is a powerful, open research resource that contains a wealth of accurate data describing cross-species chemical gene/protein interactions and chemical-disease relationships as well as gene-disease relationships. The relationship of the target gene to the bone-related disease is evaluated by calculating a rational score.
4. Functional enrichment analysis of DEG
Metascape is a free online resource that provides an automated meta-analysis tool for understanding the biological significance of a large number of genes. Screening of postmenopausal osteoporosis related Gene sets with Metascape for functional enrichment analysis (http://metascape.org)。
The DAVID database is used for screening postmenopausal osteoporosis related genes to respectively analyze GO Biological Process (BP), Molecular Function (MF) and Cell Component (CC) and explore possible related biological path information of the different genes. P <0.05 was used as a criterion for significant gene enrichment.
5. Construction of protein interaction networks
The protein interaction network (PPI) for constructing overlapping differential genes was obtained using the STRING database (https:// STRING-db.org /).
6. As a result:
(1) consensus Differentially Expressed Gene (DEG) analysis
Gene expression profiles of GSE56116 and GSE100609 were used to analyze postmenopausal osteoporosis-related DEG in peripheral blood samples. Comparative analysis was performed on the above gene expression profiles, identifying 947 DEG's in GSE56116 and 413 DEG's in GSE100609, respectively (fig. 1A). Furthermore, there were approximately 14 overlapping DEG in both expression profiles, including NCBP2, SLC40a1, FGF8, CXXC5, RGMA, CDH23, IRGC, WHAMMP3, FAM13A, SDAD1, PTAFR, CD1E, CKLF, and KDR (fig. 1B).
(2) Enrichment functional analysis of differential genes
The enrichment pathways and functions of overlapping DEG were analyzed. As shown in fig. 2A, the results of GO analysis indicate that the biological processes of DEGs involve endothelial development, BMP signaling pathway, fibroblast growth factor receptor signaling pathway, phosphatidylinositol-mediated signaling and peptidyl tyrosine phosphorylation; the enriched molecular function of the DEGs is protein tyrosine kinase activity; the enriched cellular components of DEGs are the intracellular components of the plasma membrane. As shown in figure 2B, the prominent functions of Metascape's major enrichment are chemotaxis, cellular response to growth factor stimulation and positive modulation of organelle tissue.
(3) Expression of DEGs in healthy and osteoporotic women
Deg expression was analyzed in samples from healthy and osteoporotic women in GSE56116 and GSE 100609. The results show that the expression of the differential genes CD1E, CDH23 (fig. 3B), CKLF (fig. 3C), CXXC5 (fig. 3A), IRGC, RGMA (3D), SDAD1 and WHAMMP3 was significantly up-regulated in samples from postmenopausal osteoporotic women on both GSE56116 and GSE100609 chips. However, the expression of FAM13A, KDR, NCBP2, PTAFR, FGF8 and SLC40a1 genes in GSE56116 and GSE100609 chips were reversed.
(4) Relationship between DEG and osteoporosis
To reveal DEG's relationship to osteoporosis, inference scores for their relationship to bone-related diseases were evaluated by Comparing Toxicogenomics (CTD) databases.
In DEG, CD1E, CDH23, CKLF, CXXC5, IRGC, RGMA, SDAD1 and WHAMMP3 are associated with their consistent trend of change in GSE56116 and GSE 100609. The data show that only four DEGs, including CDH23 (fig. 4A), CKLF (fig. 4B), CXXC5 (fig. 4C) and RGMA (fig. 4D), are associated with postmenopausal osteoporosis and osteoporosis. CD1E and SDAD1 were evaluated to be associated with osteoporosis only, and no interaction of IRGC and WHAMMP3 with postmenopausal osteoporosis or osteoporosis was found (fig. 5).
Among them, CXXC5(CXXC finger protein 5, disulfide oxidoreductase zinc finger protein 5) is a retinoid-induced nuclear protein involved in bone marrow formation, regulating differentiation of myoblasts into myocytes, negatively regulating skin wound healing, and is essential for DNA damage-induced p53 activation. The Wnt/β -catenin signaling pathway has been shown to play an important role in the regulation of bone formation and osteoblast differentiation. CXXC5 is thought to be a negative feedback regulator of osteoblast differentiation through specific interactions with disheveled (dvl) proteins. The research of the invention shows that the interaction of CXXC5 and various bone-related diseases including postmenopausal osteoporosis, arthritis, bone diseases, bone resorption, osteolysis, osteomalacia and osteomyelitis is found, and genes which are closely related to CXXC5 postmenopausal osteoporosis are determined. Thus, CXXC5 is a potentially excellent candidate marker or therapeutic target for osteoporosis.
RGMA (regenerative guide molecule BMP co-receptor a), a glycoprotein whose encoded protein is a glycosylphosphatidylinositol anchor, has been shown to function as an axonal guidance protein in the developing adult central nervous system and to act as a cancer suppressor in certain cancers.
BMP2 is the most relevant molecule in PPI networks that interacts directly with RGMA (figure 6). The research result of the invention confirms that the RGMA is a closely related candidate marker of postmenopausal osteoporosis, which indicates that the RGMA has a new function in the osteoporosis. Abnormal levels of BMP2 have been reported to affect mesenchymal cell myogenesis, adipogenesis, chondrogenesis and osteogenesis. BMP2 can promote differentiation of myoblasts into osteoblasts, cartilage and bone formation. Therefore, it is estimated that RGMA may be involved in the regulation of osteoporosis through interaction with BMP 2.
(5) PPI network analysis of DEG
Based on PPI networks constructed from 14 overlapping difference genes, dense modules containing CXXC5 and RGMA were selected (fig. 6). The data indicate that CXXC5 interacts with KDR, while RGMA interacts with BMP 2.
Thus, the findings of the present invention provide potential and meaningful candidates for the mechanism and strategy exploration for postmenopausal osteoporosis.
In summary, the study was conducted by analyzing DEG of peripheral blood samples in GSE56116 and GSE100609 datasets. There were approximately 14 overlapping DEG's in the two expression profiles. However, only four overlapping DEG, i.e. CDH23, CKLF, CXXC5 and RGMA, showed consistent trends in variation in the two expression profiles and were found to be closely associated with postmenopausal osteoporosis.
Although the invention has been described in detail hereinabove with respect to a general description and specific embodiments thereof, it will be apparent to those skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.
Claims (10)
1. A postmenopausal osteoporosis related gene screening and function analysis method is characterized by comprising the following steps:
1) screening a research chip series meeting the conditions by utilizing a GEO database: searching for postmenopausal osteoporosis related gene expression chip results from GEO database http:// www.ncbi.nlm.nih.gov/GEO/with the search conditions defined as: (1) postmenopausal osteoporosis; (2) a human source; (3) the research type is chip expression profile detection; (4) the sample source is a peripheral blood sample, and after screening, two chip series are brought into the research: GSE56116 and GSE100609, included in 14 postmenopausal osteoporosis peripheral blood samples and 7 normal control samples;
2) in gene expression database GEO (https: // www.ncbi.nlm.nih.gov/geo /) download the data set of the gene expression profile of peripheral blood samples for postmenopausal osteoporosis: GSE56116 and GSE100609, and based on the P value<0.05 and | log2FC | > 0.5 screening criteria for differential genes;
3) venn plots were used to find the same gene expression results in both chip datasets: selecting two chip series to express differential genes, finding 947 differential genes in GSE56116 and 413 differential genes in GSE 100609; generating a Venn diagram by using an online Venn diagram making tool, wherein 14 overlapped differential genes exist in two data sets;
4) carrying out GO functional enrichment analysis on 14 overlapped differential genes by using Metascape and DAVID databases;
5) core genes associated with postmenopausal osteoporosis were collected by searching the CTD database.
2. The method for screening and functional analysis of genes associated with postmenopausal osteoporosis of claim 1, further comprising constructing a protein interaction network (PPI) of 14 overlapping differential genes using a STRING database.
3. The method for screening and functional analysis of genes related to postmenopausal osteoporosis of claim 1, wherein the biological processes analyzed in the DAVID database of step 4) involve endothelial development, BMP signaling pathways, fibroblast growth factor receptor signaling pathways, phosphatidylinositol-mediated signaling and peptidyl tyrosine phosphorylation; the enriched molecular function of the differential gene is protein tyrosine kinase activity and the enriched cellular component of the differential gene is an intracellular component of the plasma membrane;
the Metascape database analyses the prominent functions of major enrichment are chemotaxis, cellular response to growth factor stimulation and positive modulation of organelle tissue.
4. The method for screening and functional analysis of postmenopausal osteoporosis related genes according to claim 1, wherein the screening of postmenopausal osteoporosis related genes in step 5) comprises CDH23, CKLF, CXXC5 and RGMA.
5. The method for screening and functional analysis of postmenopausal osteoporosis-related genes according to claim 2, wherein dense modules containing CXXC5 and RGMA showing the interaction between CXXC5 and KDR and the interaction between RGMA and BMP2 are selected according to the protein interaction network constructed in claim 2.
6. A group of markers for early diagnosis of postmenopausal osteoporosis, wherein the candidate markers for early diagnosis of postmenopausal osteoporosis are selected from one or more of the following CD1E, CDH23, CKLF, CXXC5, IRGC, RGMA, SDAD1 and WHAMMP3 genes.
7. The marker of claim 6, wherein the candidate marker for early diagnosis of postmenopausal osteoporosis comprises the CDH23, CKLF, CXXC5 and/or RGMA genes.
8. The marker of claim 7, wherein the CDH23, CKLF, CXXC5 and RGMA genes are up-regulated in blood samples of postmenopausal osteoporosis.
9. Use of a marker according to any one of claims 6 to 8 in the manufacture of a kit for the early diagnosis of postmenopausal osteoporosis.
10. The use according to claim 9, wherein the kit comprises a reagent for detecting the gene expression level of the marker according to any one of claims 6 to 8.
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| CN108034713A (en) * | 2017-12-29 | 2018-05-15 | 北京泱深生物信息技术有限公司 | Postmenopausal Osteoporosis diagnosis and treatment target spot and its application |
| CN108866184A (en) * | 2018-08-27 | 2018-11-23 | 北京泱深生物信息技术有限公司 | Application of the gene marker in women osteoporosis |
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| CN108034713A (en) * | 2017-12-29 | 2018-05-15 | 北京泱深生物信息技术有限公司 | Postmenopausal Osteoporosis diagnosis and treatment target spot and its application |
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