Insulin-like growth factor binding protein 7 as a candidate biomarker for systemic sclerosis Y.-M. Yan1, J.-N. Zheng1, Y. Li2,3, Q.-R. Yang1, W.-Q. Shao4, Q. Wang1 1Department of Dermatology, Zhongshan ABSTRACT has the highest cause-specific mortality Hospital, Fudan University, Shanghai; Objectives. Systemic sclerosis (SSc) is among all the rheumatic diseases (3). 2 Department of Stomatology, Zhongshan an autoimmune disease clinically char- The cardiac factor is the leading cause Hospital, Fudan University, Shanghai; acterised by skin and internal organs fi- of mortality, followed by lung involve- 3State Key Laboratory of Molecular Engineering of Polymers, Fudan brosis with high mortality. However, the ment, both pulmonary hypertension University, Shanghai; pathogenesis of SSc is still controver- and/or pulmonary fibrosis (4). The ba- 4Department of Laboratory sial and the effect of the current treat- sic pathogenesis includes vascular dam- Medicine, Zhongshan Hospital, ment is far from satisfactory. We aimed age, inflammation and connective tissue Fudan University, Shanghai, China. to find out novel candidate genes relat- repair. Among them, the development Yue-Mei Yan, MD* ed to the pathological process in SSc. of progressive systemic fibroprolif- Ji-Na Zheng, MD* Methods. In this study, the weighted erative process characteristic is crucial. Yang Li, MD* correlation network analysis (WGC- However, it remains misty, which poses Qiao-Rong Yang, MD NA) was conducted to identify the key a threat to the effects of drugs for dis- Wen-Qi Shao, MD Qiang Wang, MD module and hub genes most related to ease remission and reversion. Recently, SSc in GSE58095, a microarray data- *These authors contributed equally. target treatment of fibrosis in systemic set from the Gene Expression Omnibus sclerosis shows its prospect inspired by Please address correspondence to: Qiang Wang, (GEO) database. Also, the key module extensive studies. For example, tocili- Department of Dermatology, was analysed by Gene Ontology (GO) zumab, a kind of monoclonal antibody, Zhongshan Hospital, analysis and Kyoto Encyclopedia of shows its effectiveness and safety in the Fudan University, Genes and Genomes (KEGG) analysis. treatment of SSc associated interstitial 180 Fenglin Road, Then we validated hub genes in other lung disease (5). Xuhui District, datasets (GSE32413, GSE125362, Thereby, confronted with SSc, such an Shanghai 200032, China GSE45485, GSE76885, GSE95065). intractable autoimmune disease, we E-mail: [email protected] The serum of 37 patients with SSc and may turn to large-scale gene expres- Received on April 15, 2020; accepted in 25 healthy control subjects (HCs) were sion analysis using systems biology revised form on August 31, 2020. recruited and detected by Enzyme- for some clues. Weighted correlation Clin Exp Rheumatol 2021; 39 (Suppl. 131): Linked Immunosorbent Assay (ELISA). network analysis (WGCNA) (6), an S66-S76. Results. Five interested genes (IG- R package for weighted correlation © Copyright CLINICAL AND FBP7, LRRC32, STMN2, C1QTNF5, network analysis, has been previously EXPERIMENTAL RHEUMATOLOGY 2021. CPXM1) were up-regulated in SSc successfully applied in various biologi- Key words: systemic sclerosis, microarray datasets from the GEO. cal contexts to reveal the relationship weighted correlation network analysis, And the level of serum IGFBP7, which between modules and clinical features insulin-like growth factor binding encodes a secreted protein, was up- and identify candidate biomarkers or protein 7, enzyme-linked regulated in SSc patients-also in dcSSc therapeutic targets in several diseases. immunosorbent assay, patients and SSc with ILD patients. The advantage of a weighted co-ex- gene expression omnibus Conclusions. Among the five interested pression network over an unweighted genes, the IGFBP7 was a novel candi- network lies in avoiding information date gene for SSc and may be served loss by setting artificial threshold pa- Funding: this study was supported by as potential target and early biomarker rameters in WGCNA (6). grants awarded to Q. Wang from the for accurate treatment, which also pro- In our study, we constructed a co-ex- National Natural Science Foundation of vides further insights into the patho- pression network of the expression pro- China (81641087), and the Research Fund genesis of SSc at the molecular level. file data GSE58095 downloaded from of Shanghai Municipal Commission of the Gene Expression Omnibus (GEO) Health and Family Planning (201640071). Introduction database in the environment of R (v. Data availability statement: Systemic sclerosis (SSc), or sclero- 3.6.1). Genes share similar biological the datasets[GSE58095 (9), GSE32413 (10), GSE125362 (11), GSE76885 (12), derma, is a heterogeneous connective function and biological processes are GSE45485 (13), GSE95065 (14)] for this tissue disease characterised by multi- divided into the same co-expression study can be found in the public GEO organ fibrosis (1, 2). It can be classi- module by clustering techniques. We (http://www.ncbi.nlm.nih.gov/geo/). fied as diffuse cutaneous SSc (dcSSc) confirmed the most SSc-related co- Competing interests: none declared. and limited cutaneous SSc (lcSSc). SSc expression module and identified po- S-66 Clinical and Experimental Rheumatology 2021 IGFBP7 as a candidate biomarker for SSc / Y.-M. Yan et al. tential functions of the genes within proved to possess a relatively satisfying control and 59 SSc skin samples. Other it by Gene Ontology (GO) and Kyoto diagnosis value through analysis. Based datasets were used for candidate genes Encyclopedia of Genes and Genomes on these findings, we identified IG- validation. Information about these 6 (KEGG) analyses. We also identified FBP7 a potential candidate biomarker datasets was summarised in Supple- 27 real hub genes that possibly play a for SSc. Our findings may point to the mentary Table S1. central role in SSc and constructed a potential candidate genes for accurate The probe annotation for GSE58095 protein-protein interaction (PPI) net- therapy of SSc and provide powerful was conducted under the R environment work to find key genes that interact evidences for better understanding the using the R package “limma” and “im- with many other genes. Among them, pathogenesis of SSc. pute” with the microarray platform file. we validated five genes, namely insu- The gene expression value of GSE58095 lin-like growth factor binding protein 7 Material and methods has already been log2 transformed. (IGFBP7), leucine-rich repeat-contain- Patients and controls ing 32 (LRRC32), stathmin 2 (STMN2), A total of 37 SSc patients diagnosed as Co-expression network construction complement C1q tumor necrosis fac- SSc according to ACR/EULAR 2013 We constructed a co-expression net- tor-related protein 5 (C1QTNF5), car- (7) were recruited at Zhongshan hos- work by using the R package “WGC- boxypeptidase X, M14 family member pital of Fudan University (Shanghai, NA” in the R environment. Firstly, 1 (CPXM1), that were barely studied. China) in our study. The patients’ clini- through variance analysis, we obtained Their biological functions have both cal data at the time of SSc diagnosis the top 25% most variant genes for sub- similarities and differences. Previous were obtained through medical record sequent analysis. Then, we constructed studies show that IGFBP7, STMN2, reviews. 25 persons with no history of an adjacency matrix based on Pearson’s C1QTNF5 are all related to cell adhe- pulmonary, autoimmune, cardiovas- correlation analysis of all pairs of genes. sion which is presented in the result cular, or other diseases were recruited Here, we needed to set soft-thresholding of functional analysis. And IGFBP7, as healthy control subjects (HCs). parameter β (15) to construct a scale- STMN2, CPXM1 all take part in the The study was carried out in accord- free co-expression network, namely a process of osteogenesis and osteoblast. ance with the recommendations of the topological overlap matrix (TOM) (16). Besides, IGFBP7 works in the activa- Zhongshan Hospital Research Ethics Using a dynamic tree-cutting algorithm tion and proliferation of fibroblasts; Committee. All subjects gave written (6) and the merging threshold function C1QTNF5 influences extracellular de- informed consent in accordance with at 0.40, we merged the close modules posits and participates in immune-me- the Declaration of Helsinki. into 13 modules. diated damage; CPXM1 acts on colla- gen and extracellular matrix; LRRC32 Data collection and preprocess Identification of key module activates Regulatory T cells (Treg All microarray datasets were obtained and hub genes cells) to induce immune response by from the NCBI Gene Expression Om- We considered “SSc” and “normal” as protecting FOXP3 expression. nibus (GEO) (http://www.ncbi.nlm. clinical traits and calculated their cor- By referring to related data, we found nih.gov/geo/), a public data repository relation with the modules. It is regarded that protein LRRC32, STMN2 can- providing functional genomic infor- to contribute to the pathogenesis of the not be secreted into the serum. As for mation (8). To eliminate the interfer- disease if the correlation between mod- CPXM1, C1QTNF5, they are missing in ence as far as possible, the screening ules and SSc trait is positive. Through GSE95065, which indicates their weak criteria we adopted were as follows: 1) principal component analysis, we ob- or unstable expression in human body. Both SSc and healthy control groups tained 13