Expression Profile of Peripheral Immune Cells-derived Coding and Long Non-coding RNAs in Patients With Proliferative Vitreoretinopathy

Expression Profile of Peripheral Immune Cells-derived Coding and Long Non-coding RNAs in Patients With Proliferative Vitreoretinopathy | 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 Expression Profile of Peripheral Immune Cells-derived Coding and Long Non-coding RNAs in Patients With Proliferative Vitreoretinopathy Yao Ni, Fangyuan Liu, Xiao Hu, Yingyan Qin, Zhaotian Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-74786/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Jan, 2021 Read the published version in BMC Medical Genomics → Version 1 posted 10 You are reading this latest preprint version Abstract Introduction: Peripheral immune response has been revealed to play a critical role in proliferative vitreoretinopathy (PVR). However, the reliable immune-related factors that are acting as prognostic indicators or therapeutic targets for PVR remain to explore further. Methods: In the current study, we applied whole-transcriptome sequencing to profile peripheral blood mononuclear cells (PBMCs) from PVR patients and also analyzed lncRNA-mRNA interactions in peripheral immune cells to explore the pathways that might mediate immunopathology and resultant retinal damage in PVR. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and Ingenuity Pathway Analysis (IPA) were employed to classify the function of these differentially expressed genes (DEGs). Results: Compared to the controls, there were 319 genes upregulated, and 191 genes downregulated in PVR patients. GO, and KEGG enrichment analyses as well as IPA showed that these upregulated genes were significantly enriched in immune-related and infection-relate terms. Immune-related gene NFKBIA , CXCL2 , and CXCL8 were detected as hub-genes in the co-expression network, while lncRNAs such as AC007032.1 , AC037198.2 , AL929472.2 , and SLED1 were highly co-expressed with them. lncRNA-mRNA interactions analysis also showed that putative targeted genes of these differentially expressed lncRNAs were also significantly enriched in immune-related or infection-relate pathways . Conclusion: Our study highlights the transformation of immune-related genes/pathways in PVR by comparing controls, and validates several critical genes and lncRNAs, which are serving as potential diagnostic markers for PVR patients. Epigenetics & Genomics proliferative vitreoretinopathy gene expression profile long non-coding RNAs immune-related pathway Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Proliferative vitreoretinopathy (PVR) is a critically blinding complication that occurs during rhegmatogenous retinal detachment (RRD), before or after surgery. It is caused by the proliferation of glial cells or RPE cells to form a fibrous membrane at the neural retinal surface or even in the retina. 1 Immune cells involved in the pathogenesis of PVR, such as monocyte/macrophage infiltration and activity contributed to the progress of PVR. 2 And, some inflammatory-related genes are identified that can predict the susceptibility of PVR in populations. 3 Recently, the interaction of long non-coding RNAs (lncRNAs) and protein-coding RNAs (mRNAs) has been revealed playing a significant role in diseases related to inflammation and immunity. 4 , 5 However, despite some lncRNAs, such as MALAT1 that had been unveiled by some publications, 6 , 7 there are no reliable lncRNAs currently implicating in clinical practice acting as prognostic indicators or therapeutic targets for PVR patients. Thus, subsequent studies to identify more critical lncRNAs associated with PVR are warranted. In the present study, we hypothesized that transcriptomes of peripheral immune cells in PVR might be altered, which are the potential cause for the initiation or progression of PVR. Peripheral blood samples were taken from patients undergoing standard three-port pars plana vitrectomy for indications of PVR secondary to RRD and the entire transcriptome sequencing was performed. Patients with idiopathic epiretinal membrane (iERM) underwent pars plana vitrectomy were used as controls. 8 , 9 Patients were excluded from analysis if they were with systemic diseases (e.g., diabetes, immunological diseases, infections, etc.) that could influence systemic inflammation. With the sequencing data, we applied Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Ingenuity Pathway Analysis (IPA), as well as gene-lncRNA co-expression analysis to see the differences in transcriptome level between PVR patients and controls. We also validated some selected differentially expressed lncRNAs by quantitative real-time polymerase chain reaction (qPCR) assay. The results of the current study provide novel insights into PVR pathogenesis and treatment therapeutic targets. Methods And Design Ethics statement and clinical sample collection This study was approved by the ethics committees of the Zhongshan Ophthalmic Center. The peripheral blood samples were taken in accordance with the Declaration of Helsinki and written consent was obtained from all participants. Patients diagnosed as primary rhegmatogenous retinal detachment (RRD) with serious PVR (≥ Grade C), 10 and were scheduled to have pars plana vitrectomy (PPV) from October 2018 to February 2019 were included (PVR group). Patients diagnosed as idiopathic epiretinal membrane (iERM) and scheduled to have PPV during the same period were included as negative controls (iERM group). The blood samples were collected from patients before surgery. RNA extraction and cDNA library construction Using Ficoll-Paque™ PREMIUM Media (GE Healthcare Life Sciences, Massachusetts, America) and SepMate™-50 (STEMCELL Technologies, Vancouver, Canada), approximately 5 mL of anticoagulated peripheral blood was centrifuged at 500 g for 30 min, and the thin white layer was collected as PBMC. RNeasy Mini Kit (Qiagen Corporation, Hilden, Germany) was used to extract the total RNA from PBMC. After using Agilent 4200 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) to determine the RNA integrity number and quantity, the rRNA was removed by Epicentre Ribo-zero rRNA Removal Kit (Epicentre, Madison, WI, USA). Subsequently, the DNA was cleaned by DNase and then captured and purified by magnet beads (Vazyme, Nanjing, China). The purified RNA was interrupted into short fragments by adding fragmentation buffer, then the first-strand cDNA was synthesized and double-strand cDNA was obtained thereafter with VAHTS Universal V6 RNA-seq Library Prep Kit for Illumina (Vazyme, Nanjing, China). Adapters were then connected to the cDNAs and Agilent 4200 Bioanalyzer, as well as qPCR, were used to verify the fragment size and amplify the templates. The constructed library was then loaded on the Illumina HiSeq X Ten system for sequencing. Sequence analysis and functional annotation We used FastQC first to check the quality of raw reads and then processed with Cutadapt software to generate clean reads by trim adaptor sequences and removed the low-quality sequences. 11 HISAT2 was used to align the clean reads to the hg19 human reference genome. 12 Mapped reads used the featureCount software to obtain gene expression profiles, 13 – 15 and then the differential expression analysis was executed via the DESeq2 package on R programmer. 16 |Fold change| > 1.5 and P -value < .05 were decided upon as the significance of differentially expressed genes. GO and KEGG enrichment analyses were then performed using the Clusterprofiler R package. 17 For further functional analysis, differentially expressed transcriptome between PVR and iERM patients, including gene symbols and expression values were uploaded into IPA software (Qiagen, Germany). The canonical pathways, diseases and biofunctions as well as gene networks analysis were processed. QPCR validation Total RNA was isolated as mentioned above, and the cDNA was then synthesized with HiScript II Q Select RT SuperMix for qPCR (Vazyme, Nanjing, China). Roche lightcycler 96 was then used to perform qPCR. Beta-actin was used as the internal control. The melting curve was used to confirm reaction specificity and relative expression was calculated by the 2 −ΔΔCt method. Primer sequences and product length were listed in Table 1 . Table 1 Primers of the validated lncRNAs Gene Primer Sequence (5’−3’) Product length AC037198.1 F: CCTCATACTCGCGCATTCTT R: GCCTTCCCACAGTGTATGCT 139 bp ZNF433-AS1 F: CCGGAATATCTGGAAGCTGA R: GTCTCAATGGCACCCAGATT 111 bp Beta-actin F: CTCTTCCAGCCTTCCTTCCT R: AGCACTGTGTTGGCGTACAG 116 bp Statistical analyses GraphPad Prism 7.0 (GraphPad company, San Diego, USA) was used to compare the lncRNA expression differences obtained by qPCR assay referring to the Mann-Whitney U test between PVR and iERM groups. A P -value ≤ .05 was considered statistically significant. Results Characteristics of the subjects There were six males and six females in the PVR group, and eight males and five females in the iERM group. The average age of the PVR group was 53.3 ± 10.6 years old, and that of the iERM group was 60.0 ± 9.7 years old. The differences in age and gender between PVR and iERM groups were not statistically different ( P > .05). Identification of differentially expressed transcriptome Using 1.5-fold expression difference as a cutoff, 510 genes were found differentially expressed between PVR patients and iERM patients, among which 319 were upregulated and 191 were downregulated (Fig. 1 A). As expected, these two kinds of patients could be clustered into separated groups using the differentially expressed genes (DEGs) (Fig. 1 B), highlighting the apparent transcriptomic difference between PVR and iERM. Differentially expressed transcripts between PVR and iERM was also analyzed in this study. Besides, for the 5,138 differentially expressed transcripts (DETs) ( Figure S1; supplementary file), 64.38% of them were protein-coding RNAs, whereas 19.26% were lncRNAs (Figure S2A; supplementary file). The length of lncRNA varies from 1,000 to larger than 10,000 ( Figure S2B; supplementary file). We also performed an unsupervised cluster analysis with the DETs. Similar to the gene clustering analysis, samples were significantly separated in accordance with two patient groups. Gene Ontology analysis and KEGG analysis To explore the biology underlying the deferentially expressed gene further, we performed an overrepresentation analysis of GO terms and KEGG pathways using the R program with the ClusterProfiler package. It is very interesting to note that most of the upregulated genes were enriched in immune system-related terms, including immunoglobulin, complement, and immune response (Fig. 2 A); while the downregulated GO terms were irrelevant to the immune system ( Figure S3A; supplementary file). Upregulated genes of PVR patients compared with iERM patients were enriched in many pathways from KEGG (Fig. 2 B). To our surprise, many infectious pathways, including malaria, legionellosis, and Chagas disease, were involved with high significance. Besides, pathways affecting the immune system, including IL-17 signaling, TNF signaling, as well as rheumatoid arthritis, were enriched. Much different from the upregulated genes, the downregulated genes were poorly enriched in KEGG pathway enrichment ( Figure S3B; supplementary file). Enriched Pathway, diseases, biofunctions and interaction network by IPA analysis We used IPA to analysis the significant changed 752 transcriptomes (P 1.5) between patient PVR and iERM patients. With IPA, we revealed these changed genes are closely related to 26 canonical pathways. The most significant of those are shown in Table 2 . 5 out of top ten pathways are related to innate and adaptive immune cells especially Th17 cells and its cytokines IL-17A and IL-17F. With IPA, we also found similar change as we revealed in GO and KEGG analysis: Pathways related to immune reaction were also enriched. For the top four scored networks ( Table S1 , supplementary file), 2 of them were immune function related. These two networks are shown in Fig. 3 : Cell-To-Cell Signaling and Interaction, Cellular Movement, Immune Cell Trafficking (score 23, Fig. 3 A); and Gastrointestinal Disease, Inflammatory Disease, Inflammatory Response (score 21, Fig. 3 B). Table 2 Top significantly enriched canonical pathways of protein coding RNAs in PVR patients Ingenuity Canonical Pathways -log(p-value) Ratio Molecules Communication between Innate and Adaptive Immune Cells 3.53 0.0625 CCL3,CXCL8,IGHA1,IGHE,IGHG2,IL1B Differential Regulation of Cytokine Production in Macrophages and T Helper Cells by IL-17A and IL-17F 3.22 0.167 CCL3,CXCL1,IL1B Differential Regulation of Cytokine Production in Intestinal Epithelial Cells by IL-17A and IL-17F 2.9 0.13 CCL3,CXCL1,IL1B Role of IL-17A in Arthritis 2.75 0.0727 CXCL1,CXCL2,CXCL8,NFKBIA Airway Pathology in Chronic Obstructive Pulmonary Disease 2.63 0.25 CXCL2,CXCL8 Glutathione-mediated Detoxification 2.48 0.0938 GSTM1,GSTM4,HPGDS TREM1 Signaling 2.26 0.0533 CCL3,CXCL2,CXCL8,IL1B Role of IL-17A in Psoriasis 2.2 0.154 CXCL1,CXCL8 Atherosclerosis Signaling 2.17 0.0397 COL1A1,CXCL8,IL1B,PLAAT2,TPSAB1/TPSB2 Role of IL-17F in Allergic Inflammatory Airway Diseases 2.15 0.0714 CXCL1,CXCL8,IL1B mRNA and lncRNA co-expression analysis As LncRNAs are also important participants in disease process. Based on the correlation of the significantly regulated protein-coding mRNA with lncRNA, we constructed co-expression networks to analyze their interaction and to find out the potential therapeutic target. Pearson correlation coefficient was calculated for each pair and significantly correlated RNA pairs were chosen (r > 0.8, P < .05 as the threshold). As shown in Fig. 4 , immune-related gene NFKBIA , and chemokines CXCL2 and CXCL8 were of high hubness in the co-expression network, highlighting their important biological role in the difference between PVR and iERM. Besides, we found several lncRNAs were highly co-expressed with these genes, including AC007032.1 , AC037198.2 , AL929472.2 , SLED1 , etc., indicating the key regulation values of them. We searched further to look for the lncRNA-mRNA interactions, inspecting the chromosome location of regulated lncRNAs to see if they had up- or down-stream 10 kb or overlapping mRNAs. As a result, 630 lncRNAs that had nearby DEGs were found, including 290 upregulated and 340 downregulated lncRNAs. GO, and KEGG analyses and also IPA were conducted as above (Fig. 5 and Table 3 ). Like that of DETs GO analysis, the upregulated lncRNAs had more enriched GO terms compared to the downregulated lncRNAs though few of which was immune related (Fig. 5 A and Figure S4A ). For the KEGG analysis, fewer pathways were enriched(Figure 5 B and Figure S4B ). results above might due to many functions of lncRNA that are still unclear. However, in IPA analysis, though none of the top ten enriched pathways were immune related pathways, we found Virus Entry via Endocytic Pathways were enriched. Further, the top 2 scored networks are relate to Ophthalmic Disease or Immunological Disease respectively ( Table S2; supplementary file). Table 3 Top significantly enriched canonical pathways of LncRNAs in PVR patients Ingenuity Canonical Pathways -log(p-value) Ratio Molecules D-myo-inositol-5-phosphate Metabolism 2.85 0.0641 DOT1L,INPP5B,MDP1,NUDT5,PLCG1,PPIP5K1,PPP2R5A,PTPN6,PTPRM,SET Superpathway of Inositol Phosphate Compounds 2.12 0.0505 DOT1L,INPP5B,MDP1,NUDT5,PLCG1,PPIP5K1,PPP2R5A,PTPN6,PTPRM,SET Endocannabinoid Cancer Inhibition Pathway 2.04 0.0559 ATF3,CREB1,GNB1L,LEF1,MAP2K4,PRKACA,SPTLC1,TCF4 Heme Biosynthesis II 1.87 0.222 HMBS,UROD Folate Transformations I 1.87 0.222 MTHFD2,MTHFR Salvage Pathways of Pyrimidine Ribonucleotides 1.84 0.0619 CSNK1D,GRK4,MAP2K4,MAPK6,PRKCH,UCKL1 Protein Kinase A Signaling 1.76 0.0377 ADD1,ADD3,APEX1,CHP1,CREB1,FLNA,GNB1L,LEF1,PLCG1,PRKACA,PRKCH,PTPN4,PTPN6,PTPRM,TCF4 Amyloid Processing 1.73 0.08 CAPN2,CSNK1D,PRKACA,PSEN2 Androgen Signaling 1.66 0.0515 GNA12,GNB1L,KAT7,NCOA1,POLR2J2/POLR2J3,PRKACA,PRKCH Virus Entry via Endocytic Pathways 1.65 0.0561 AP2A1,FLNA,ITGAL,ITGB1,PLCG1,PRKCH Validation of differentially expressed lncRNAs We used qPCR assay to validate the deferentially expressed lncRNAs, while AC037198.2 , and ZNF433-AS1 were selected based on differential expression and co-expression analyses. As shown in Fig. 6 , these lncRNAs were significantly different among PVR and iERM patients. Discussion PVR is still the leading cause of vitreoretinal surgery failure, mainly through retina re-detachment and even intraretinal fibrosis. The incidence of PVR is estimated to be 5–10%. 18 However, as the mechanisms of PVR are still not very clear, it is difficult to predict or treat the condition despite the many efforts that are still being made. In the present study, our results identified differentially expressed mRNA and lncRNA in PBMCs of PVR patients and revealed that gene expression profile and molecular signature of PVR patients. The proliferation of cells, mainly RPE and glial cells, is the essential point of PVR development. Clinicians have tried for more than four decades to inhibit the proliferation of cells in the vitreous to prevent PVR but have not had impressive progress. 18 This situation has raised the question of whether there is anything abnormal out of the eye in this disease. The answer to this might come from the immune system. In the review by Pastor et al., the authors proposed that ischemia, blood-retina barrier breakdown, and inflammation lead to the final PVR based on the collaborative genetic study named “Retina 4 Project”, which found 30 inflammatory-related genes were responsible for PVR. 4 Further, a single nucleotide polymorphism (SNP) analysis in peripheral blood from PVR patients shown that TNF locus which encompasses the gene of TNFα contributes to the development of PVR. 19 It is suggested that PVR might not only be a “local inflammatory condition’’, but also could be affected by system regulation. Compare with these studies, with RNA from peripheral blood mononuclear cells and with GO, KEGG and IPA analysis, we revealed that the immune related pathways or components are closely related to PVR change. We found immunoglobulin and its receptors as well as antigen binding were all up regulated in PBMC from PVR patient. Further, RNAs related to biological process of adaptive immune response and lymphocytes activation were also up regulated indicating microbial infection might play a role in the disease process. In IPA analysis, we found in enriched canonical pathways, CCL1, CCL3, CXCL8 and especially Th17 cells and its related cytokines IL-17A and IL-17F were emphasized. In previous publication, Th17 and its cytokines are inflammatory mediator to RPE cells, 20 and RPE cells in inflammatory condition were thought to be a key point to PVR formation. 18 Infection had long been considered as a trigger to immune disease. In the KEGG analysis, to our surprise, rather than immune pathways, infectious related pathways related to amoebiasis, malaria or chagas disease were enriched. As in uveitis, Forrester et al. agreed that infection may directly or indirectly related to noninfectious uveitis in the eye. 21 In this consideration, remind us that infection might be a potential cause of PVR. LncRNAs are widely expressed in monocytes, macrophages, neutrophils and implicated in the process of inflammation and immunity. Various molecular functions have been ascribed to lncRNAs, including gene regulation in cis, regulation of mRNA stability, and modulation of protein function. In PVR patients, Zhou et al. not only demonstrated that the expression of MALAT1 was significantly upregulated in the proliferating membrane, also found MALAT1 was significantly up-regulated in the peripheral blood. 6 MALAT1 can inhibit the DNA binding activity of NF- κB, reduce the production of inflammatory cytokines, and down-regulate the autoimmune inflammatory response. The knockdown of MALAT1 can increase lipopolysaccharide (LPS)-induced expression of TNFα and IL-6. 22 However, to our surprise, we did not find MALAT1 were upregulated in PBMC in PVR patient. In our research, by analysis the mRNA and lncRNA co-expression in PBMC, we found immune-related gene NFKBIA , and chemokines CXCL2 and CXCL8 and their associate LncRNA AC007032.1 , AC037198.2 , AL929472.2 , SLED1 were highly associated with PVR. AC007032.1 is associated with immunomodulatory cytokine Nampt, 23 while SLED1 was found up regulated in peripheral blood cells of systemic lupus erythematosus patients. 24 Additionally, within IPA analysis, virus infection relate pathways and immune relate networks were highlighted in PVR patients. Further, the most obvious changed LncRNA AC037198.2 and ZNF433-AS1 were selected to verify and were proved their actual change in PBMC from PVR patients. LncRNA AC037198.2 is associate with THBS1(thrombospondin 1) gene, which encoded a secreted protein to mediate cell-to-cell and cell-to-matrix interactions. As for ZNF433-AS1 , this LncRNA can suppress ZNF433, which belongs to transcriptional factors with the zinc finger motif, and was found that play an important role in multiple sclerosis, which is an autoimmune disease. 25 Conclusions In summary, we provide a landscape of differential expression profile of mRNAs and lncRNAs between PVR and controls and construct an mRNA-lncRNA co-expression network based on the DETs. Pathway enrichment analyses offer novel insights into the pathogenesis of PVR, indicating that PVR might be related with abnormal immune system or previous infection. More importantly, some deferentially expressed lncRNAs, like LncRNA- AC037198.2 and ZNF433-AS1 were appeared in our study, which might be potential molecular signatures for PVR. These results will provide hence our understanding of this disease and provide novel therapeutic targets for PVR patients. Declarations ACKNOWLEDGEMENTS Funding: This study was supported by the Fundamental Research Funds for the Central Universities (20ykpy147) and Natural Science Foundation of Guangdong Province of China (2019A1515010189). Authorship: All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published. Disclosures: Yao Ni, Fangyuan Liu, Xiao Hu, Yingyan Qin and Zhaotian Zhang declare that they have no conflict of interest. Ethical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. 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Supplementary Files TableS1.docx TableS2.docx Supplementaryfileandthecorrespondingfigurelegends.docx Cite Share Download PDF Status: Published Journal Publication published 28 Jan, 2021 Read the published version in BMC Medical Genomics → Version 1 posted Editorial decision: Minor revision 10 Dec, 2020 Reviewer # 2 agreed at journal 09 Dec, 2020 Review # 2 received at journal 09 Dec, 2020 Review # 1 received at journal 12 Oct, 2020 Reviewer # 1 agreed at journal 28 Sep, 2020 Editor assigned by journal 24 Sep, 2020 Reviewers invited by journal 24 Sep, 2020 Submission checks completed at journal 18 Sep, 2020 Editor invited by journal 18 Sep, 2020 First submitted to journal 09 Sep, 2020 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. 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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-74786","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":2504458,"identity":"80165b4b-32e6-4f9c-bb7e-bfe58583c99d","order_by":0,"name":"Yao Ni","email":"","orcid":"","institution":"State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center of Sun Yat-sen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yao","middleName":"","lastName":"Ni","suffix":""},{"id":2504459,"identity":"21de0620-be1b-44b6-a2fe-47bf22914b87","order_by":1,"name":"Fangyuan Liu","email":"","orcid":"","institution":"State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center of Sun Yat-sen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fangyuan","middleName":"","lastName":"Liu","suffix":""},{"id":2504460,"identity":"7664ada2-f328-4605-b669-13d4f2882bbb","order_by":2,"name":"Xiao Hu","email":"","orcid":"","institution":"State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center of Sun Yat-sen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Hu","suffix":""},{"id":2504461,"identity":"e1d44bc3-2a1c-4678-979d-bc7d32ca5ea6","order_by":3,"name":"Yingyan Qin","email":"","orcid":"","institution":"State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center of Sun Yat-sen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yingyan","middleName":"","lastName":"Qin","suffix":""},{"id":2504462,"identity":"635ce07a-4b0d-4127-a465-109a12b9d7c5","order_by":4,"name":"Zhaotian Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYDACCTB5AIgZGxgYKkjSwgbScoY0LSCL2ojQIT+7+dnDL3/uyPPLNzd+LpxXay/f3vyA4UfFNpxaGOccMzeW4XlmOLONsVl65rbjzIw9xwwYe87cxqmFWSLBTFpC4jDjhmOMDdK8246xMUvkMDAztuHWwiaR/k1awuCwPVBL82/eOcd42Ahp4ZHIMZP8kHA4EailTZq3oUaCh5AWCYmcMmmGA4eTZ7YltlnzHDtgIMFzzOAgPr/Iz0jfJvnjz2Hbfubjj2/z1NSBQuzhgx8VuLWAg4AHwT4MJg/gVQ8EjD8Q7DpCikfBKBgFo2AEAgBKFVO22uD1XgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-0436-3338","institution":"State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University Add: 54S Xianlie Road, Guangzhou, 510060, China ","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Zhaotian","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2020-09-09 10:28:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-74786/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-74786/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12920-021-00875-5","type":"published","date":"2021-01-28T15:01:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":2519436,"identity":"2a1983c5-4dfd-4d78-8c77-63a7bbbc8311","added_by":"auto","created_at":"2020-09-21 18:28:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":125072,"visible":true,"origin":"","legend":"Differential gene expression. (A) Volcano plot assessment of gene expression between iERM and PVR patients (blue dots indicate downregulated transcriptome and red dots indicate upregulated transcriptome), and (B) Heatmap showing unsupervised cluster analysis of differentially expressed gene between iERM (Blue) and PVR (Red) patients. iERM, idiopathic epiretinal membrane; PVR, proliferative vitreoretinopathy.","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/Fig1.jpg"},{"id":2519437,"identity":"a893b6f9-4bf1-4db6-bcbe-c6f66872fbd4","added_by":"auto","created_at":"2020-09-21 18:28:05","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":184295,"visible":true,"origin":"","legend":"Pathway analysis of upregulated genes between iERM and PVR patients. (A) GO analysis data and (B) KEGG analysis data. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/Fig2.jpg"},{"id":2519438,"identity":"ed69f684-2848-4d40-9d68-a901f9dbfa57","added_by":"auto","created_at":"2020-09-21 18:28:05","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":520288,"visible":true,"origin":"","legend":"Ingenuity Pathway Analysis (IPA)-identified immune related gene networks with score \u003e20. A. Cell-To-Cell Signaling and Interaction, Cellular Movement, Immune Cell Trafficking; B. Gastrointestinal Disease, Inflammatory Disease, Inflammatory Response.","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/Fig3.jpg"},{"id":2519439,"identity":"c08d396a-d691-4043-8f13-dc1f12a0d5f4","added_by":"auto","created_at":"2020-09-21 18:28:05","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":418170,"visible":true,"origin":"","legend":"Co-expression network of gene-lncRNA network. Red dots indicate upregulated gene/lncRNA and blue dots indicate downregulated gene/lncRNA; solid line represents positive relation, and the dotted line represents negative relation.","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/Fig4.jpg"},{"id":2519440,"identity":"794d4496-7a3d-4b06-9c83-516e935c6856","added_by":"auto","created_at":"2020-09-21 18:28:05","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":157840,"visible":true,"origin":"","legend":"Pathway analysis of upregulated lncRNAs between iERM and PVR patients. (A) GO analysis data and (B) KEGG analysis data. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/Fig5.jpg"},{"id":2519441,"identity":"3eb08b21-c5a8-43c8-b651-b66db4c20b71","added_by":"auto","created_at":"2020-09-21 18:28:05","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":51550,"visible":true,"origin":"","legend":"Validation of two selected lncRNAs. The expression level was normalized to the housekeeping gene beta-actin (*P \u003c .05).\t","description":"","filename":"Fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/Fig6.jpg"},{"id":13594495,"identity":"72936676-1ac8-4aca-9b3a-ff3c7dead20b","added_by":"auto","created_at":"2021-09-17 05:20:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":822075,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/43e8b1e2-ffd1-4ba7-b548-ff97317951c0.pdf"},{"id":2519443,"identity":"f0810b47-1c94-4b3d-9f44-1f02876ba2a2","added_by":"auto","created_at":"2020-09-21 18:28:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15997,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/TableS1.docx"},{"id":2519444,"identity":"b899cfd5-0c4e-45e4-bc52-99a87f93ea49","added_by":"auto","created_at":"2020-09-21 18:28:06","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16330,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/TableS2.docx"},{"id":2519445,"identity":"cf40628d-535e-41cb-87f2-4d76727b7a43","added_by":"auto","created_at":"2020-09-21 18:28:07","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":14709291,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfileandthecorrespondingfigurelegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-74786/v1/Supplementaryfileandthecorrespondingfigurelegends.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eExpression Profile of Peripheral Immune Cells-derived Coding and Long Non-coding RNAs\u0026nbsp;in Patients With Proliferative Vitreoretinopathy\u003c/p\u003e","fulltext":[{"header":"Introduction","content":" \u003cp\u003eProliferative vitreoretinopathy (PVR) is a critically blinding complication that occurs during rhegmatogenous retinal detachment (RRD), before or after surgery. It is caused by the proliferation of glial cells or RPE cells to form a fibrous membrane at the neural retinal surface or even in the retina.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Immune cells involved in the pathogenesis of PVR, such as monocyte/macrophage infiltration and activity contributed to the progress of PVR.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e And, some inflammatory-related genes are identified that can predict the susceptibility of PVR in populations.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Recently, the interaction of long non-coding RNAs (lncRNAs) and protein-coding RNAs (mRNAs) has been revealed playing a significant role in diseases related to inflammation and immunity.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e However, despite some lncRNAs, such as \u003cem\u003eMALAT1\u003c/em\u003e that had been unveiled by some publications,\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e there are no reliable lncRNAs currently implicating in clinical practice acting as prognostic indicators or therapeutic targets for PVR patients. Thus, subsequent studies to identify more critical lncRNAs associated with PVR are warranted.\u003c/p\u003e \u003cp\u003eIn the present study, we hypothesized that transcriptomes of peripheral immune cells in PVR might be altered, which are the potential cause for the initiation or progression of PVR. Peripheral blood samples were taken from patients undergoing standard three-port pars plana vitrectomy for indications of PVR secondary to RRD and the entire transcriptome sequencing was performed. Patients with idiopathic epiretinal membrane (iERM) underwent pars plana vitrectomy were used as controls.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Patients were excluded from analysis if they were with systemic diseases (e.g., diabetes, immunological diseases, infections, etc.) that could influence systemic inflammation. With the sequencing data, we applied Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Ingenuity Pathway Analysis (IPA), as well as gene-lncRNA co-expression analysis to see the differences in transcriptome level between PVR patients and controls. We also validated some selected differentially expressed lncRNAs by quantitative real-time polymerase chain reaction (qPCR) assay. The results of the current study provide novel insights into PVR pathogenesis and treatment therapeutic targets.\u003c/p\u003e "},{"header":"Methods And Design","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthics statement and clinical sample collection\u003c/h2\u003e \u003cp\u003eThis study was approved by the ethics committees of the Zhongshan Ophthalmic Center. The peripheral blood samples were taken in accordance with the Declaration of Helsinki and written consent was obtained from all participants. Patients diagnosed as primary rhegmatogenous retinal detachment (RRD) with serious PVR (\u0026ge;\u0026thinsp;Grade C), \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e and were scheduled to have pars plana vitrectomy (PPV) from October 2018 to February 2019 were included (PVR group). Patients diagnosed as idiopathic epiretinal membrane (iERM) and scheduled to have PPV during the same period were included as negative controls (iERM group). The blood samples were collected from patients before surgery.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction and cDNA library construction\u003c/h2\u003e \u003cp\u003eUsing Ficoll-Paque\u0026trade; PREMIUM Media (GE Healthcare Life Sciences, Massachusetts, America) and SepMate\u0026trade;-50 (STEMCELL Technologies, Vancouver, Canada), approximately 5\u0026nbsp;mL of anticoagulated peripheral blood was centrifuged at 500\u0026nbsp;g for 30\u0026nbsp;min, and the thin white layer was collected as PBMC. RNeasy Mini Kit (Qiagen Corporation, Hilden, Germany) was used to extract the total RNA from PBMC. After using Agilent 4200 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) to determine the RNA integrity number and quantity, the rRNA was removed by Epicentre Ribo-zero rRNA Removal Kit (Epicentre, Madison, WI, USA). Subsequently, the DNA was cleaned by DNase and then captured and purified by magnet beads (Vazyme, Nanjing, China). The purified RNA was interrupted into short fragments by adding fragmentation buffer, then the first-strand cDNA was synthesized and double-strand cDNA was obtained thereafter with VAHTS Universal V6 RNA-seq Library Prep Kit for Illumina (Vazyme, Nanjing, China). Adapters were then connected to the cDNAs and Agilent 4200 Bioanalyzer, as well as qPCR, were used to verify the fragment size and amplify the templates. The constructed library was then loaded on the Illumina HiSeq X Ten system for sequencing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSequence analysis and functional annotation\u003c/h2\u003e \u003cp\u003eWe used FastQC first to check the quality of raw reads and then processed with Cutadapt software to generate clean reads by trim adaptor sequences and removed the low-quality sequences.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e HISAT2 was used to align the clean reads to the hg19 human reference genome.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Mapped reads used the featureCount software to obtain gene expression profiles,\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and then the differential expression analysis was executed \u003cem\u003evia\u003c/em\u003e the DESeq2 package on R programmer.\u003csup\u003e16\u003c/sup\u003e |Fold change| \u0026gt; 1.5 and \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;.05 were decided upon as the significance of differentially expressed genes. GO and KEGG enrichment analyses were then performed using the Clusterprofiler R package.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e For further functional analysis, differentially expressed transcriptome between PVR and iERM patients, including gene symbols and expression values were uploaded into IPA software (Qiagen, Germany). The canonical pathways, diseases and biofunctions as well as gene networks analysis were processed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eQPCR validation\u003c/h2\u003e \u003cp\u003eTotal RNA was isolated as mentioned above, and the cDNA was then synthesized with HiScript II Q Select RT SuperMix for qPCR (Vazyme, Nanjing, China). Roche lightcycler 96 was then used to perform qPCR. Beta-actin was used as the internal control. The melting curve was used to confirm reaction specificity and relative expression was calculated by the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. Primer sequences and product length were listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimers of the validated lncRNAs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimer Sequence (5\u0026rsquo;\u0026minus;3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProduct length\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAC037198.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: CCTCATACTCGCGCATTCTT\u003c/p\u003e \u003cp\u003eR: GCCTTCCCACAGTGTATGCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139\u0026nbsp;bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZNF433-AS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: CCGGAATATCTGGAAGCTGA\u003c/p\u003e \u003cp\u003eR: GTCTCAATGGCACCCAGATT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111\u0026nbsp;bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta-actin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: CTCTTCCAGCCTTCCTTCCT\u003c/p\u003e \u003cp\u003eR: AGCACTGTGTTGGCGTACAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116\u0026nbsp;bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eGraphPad Prism 7.0 (GraphPad company, San Diego, USA) was used to compare the lncRNA expression differences obtained by qPCR assay referring to the Mann-Whitney U test between PVR and iERM groups. A \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026le;\u0026thinsp;.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of the subjects\u003c/h2\u003e \u003cp\u003eThere were six males and six females in the PVR group, and eight males and five females in the iERM group. The average age of the PVR group was 53.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6\u0026nbsp;years old, and that of the iERM group was 60.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u0026nbsp;years old. The differences in age and gender between PVR and iERM groups were not statistically different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of differentially expressed transcriptome\u003c/h2\u003e \u003cp\u003eUsing 1.5-fold expression difference as a cutoff, 510 genes were found differentially expressed between PVR patients and iERM patients, among which 319 were upregulated and 191 were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). As expected, these two kinds of patients could be clustered into separated groups using the differentially expressed genes (DEGs) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), highlighting the apparent transcriptomic difference between PVR and iERM. Differentially expressed transcripts between PVR and iERM was also analyzed in this study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBesides, for the 5,138 differentially expressed transcripts (DETs) (\u003cb\u003eFigure S1;\u003c/b\u003e supplementary file), 64.38% of them were protein-coding RNAs, whereas 19.26% were lncRNAs \u003cb\u003e(Figure S2A;\u003c/b\u003e supplementary file). The length of lncRNA varies from 1,000 to larger than 10,000 (\u003cb\u003eFigure S2B;\u003c/b\u003e supplementary file). We also performed an unsupervised cluster analysis with the DETs. Similar to the gene clustering analysis, samples were significantly separated in accordance with two patient groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eGene Ontology analysis and KEGG analysis\u003c/h2\u003e \u003cp\u003eTo explore the biology underlying the deferentially expressed gene further, we performed an overrepresentation analysis of GO terms and KEGG pathways using the R program with the ClusterProfiler package. It is very interesting to note that most of the upregulated genes were enriched in immune system-related terms, including immunoglobulin, complement, and immune response (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA); while the downregulated GO terms were irrelevant to the immune system (\u003cb\u003eFigure S3A;\u003c/b\u003e supplementary file).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUpregulated genes of PVR patients compared with iERM patients were enriched in many pathways from KEGG (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). To our surprise, many infectious pathways, including malaria, legionellosis, and Chagas disease, were involved with high significance. Besides, pathways affecting the immune system, including IL-17 signaling, TNF signaling, as well as rheumatoid arthritis, were enriched. Much different from the upregulated genes, the downregulated genes were poorly enriched in KEGG pathway enrichment (\u003cb\u003eFigure S3B;\u003c/b\u003e supplementary file).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEnriched Pathway, diseases, biofunctions and interaction network by IPA analysis\u003c/h2\u003e \u003cp\u003eWe used IPA to analysis the significant changed 752 transcriptomes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and fold-change\u0026thinsp;\u0026gt;\u0026thinsp;1.5) between patient PVR and iERM patients. With IPA, we revealed these changed genes are closely related to 26 canonical pathways. The most significant of those are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. 5 out of top ten pathways are related to innate and adaptive immune cells especially Th17 cells and its cytokines IL-17A and IL-17F. With IPA, we also found similar change as we revealed in GO and KEGG analysis: Pathways related to immune reaction were also enriched. For the top four scored networks (\u003cb\u003eTable S1\u003c/b\u003e, supplementary file), 2 of them were immune function related. These two networks are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e: Cell-To-Cell Signaling and Interaction, Cellular Movement, Immune Cell Trafficking (score 23, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA); and Gastrointestinal Disease, Inflammatory Disease, Inflammatory Response (score 21, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop significantly enriched canonical pathways of protein coding RNAs in PVR patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIngenuity Canonical Pathways\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-log(p-value)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRatio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMolecules\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication between Innate and Adaptive Immune Cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCCL3,CXCL8,IGHA1,IGHE,IGHG2,IL1B\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifferential Regulation of Cytokine Production in Macrophages and T Helper Cells by IL-17A and IL-17F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCCL3,CXCL1,IL1B\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifferential Regulation of Cytokine Production in Intestinal Epithelial Cells by IL-17A and IL-17F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCCL3,CXCL1,IL1B\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole of IL-17A in Arthritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXCL1,CXCL2,CXCL8,NFKBIA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAirway Pathology in Chronic Obstructive Pulmonary Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXCL2,CXCL8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlutathione-mediated Detoxification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGSTM1,GSTM4,HPGDS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTREM1 Signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCCL3,CXCL2,CXCL8,IL1B\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole of IL-17A in Psoriasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXCL1,CXCL8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtherosclerosis Signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOL1A1,CXCL8,IL1B,PLAAT2,TPSAB1/TPSB2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole of IL-17F in Allergic Inflammatory Airway Diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXCL1,CXCL8,IL1B\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003emRNA and lncRNA co-expression analysis\u003c/h2\u003e \u003cp\u003eAs LncRNAs are also important participants in disease process. Based on the correlation of the significantly regulated protein-coding mRNA with lncRNA, we constructed co-expression networks to analyze their interaction and to find out the potential therapeutic target. Pearson correlation coefficient was calculated for each pair and significantly correlated RNA pairs were chosen (r\u0026thinsp;\u0026gt;\u0026thinsp;0.8, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05 as the threshold). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, immune-related gene \u003cem\u003eNFKBIA\u003c/em\u003e, and chemokines \u003cem\u003eCXCL2\u003c/em\u003e and \u003cem\u003eCXCL8\u003c/em\u003e were of high hubness in the co-expression network, highlighting their important biological role in the difference between PVR and iERM. Besides, we found several lncRNAs were highly co-expressed with these genes, including \u003cem\u003eAC007032.1\u003c/em\u003e, \u003cem\u003eAC037198.2\u003c/em\u003e, \u003cem\u003eAL929472.2\u003c/em\u003e, \u003cem\u003eSLED1\u003c/em\u003e, etc., indicating the key regulation values of them.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe searched further to look for the lncRNA-mRNA interactions, inspecting the chromosome location of regulated lncRNAs to see if they had up- or down-stream 10\u0026nbsp;kb or overlapping mRNAs. As a result, 630 lncRNAs that had nearby DEGs were found, including 290 upregulated and 340 downregulated lncRNAs. GO, and KEGG analyses and also IPA were conducted as above (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Like that of DETs GO analysis, the upregulated lncRNAs had more enriched GO terms compared to the downregulated lncRNAs though few of which was immune related (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and \u003cb\u003eFigure S4A\u003c/b\u003e). For the KEGG analysis, fewer pathways were enriched(Figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB and \u003cb\u003eFigure S4B\u003c/b\u003e). results above might due to many functions of lncRNA that are still unclear. However, in IPA analysis, though none of the top ten enriched pathways were immune related pathways, we found Virus Entry via Endocytic Pathways were enriched. Further, the top 2 scored networks are relate to Ophthalmic Disease or Immunological Disease respectively (\u003cb\u003eTable S2;\u003c/b\u003e supplementary file).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop significantly enriched canonical pathways of LncRNAs in PVR patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIngenuity Canonical Pathways\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-log(p-value)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRatio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMolecules\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-myo-inositol-5-phosphate Metabolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDOT1L,INPP5B,MDP1,NUDT5,PLCG1,PPIP5K1,PPP2R5A,PTPN6,PTPRM,SET\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuperpathway of Inositol Phosphate Compounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDOT1L,INPP5B,MDP1,NUDT5,PLCG1,PPIP5K1,PPP2R5A,PTPN6,PTPRM,SET\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndocannabinoid Cancer Inhibition Pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0559\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATF3,CREB1,GNB1L,LEF1,MAP2K4,PRKACA,SPTLC1,TCF4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeme Biosynthesis II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHMBS,UROD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFolate Transformations I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMTHFD2,MTHFR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalvage Pathways of Pyrimidine Ribonucleotides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCSNK1D,GRK4,MAP2K4,MAPK6,PRKCH,UCKL1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein Kinase A Signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eADD1,ADD3,APEX1,CHP1,CREB1,FLNA,GNB1L,LEF1,PLCG1,PRKACA,PRKCH,PTPN4,PTPN6,PTPRM,TCF4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmyloid Processing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCAPN2,CSNK1D,PRKACA,PSEN2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAndrogen Signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGNA12,GNB1L,KAT7,NCOA1,POLR2J2/POLR2J3,PRKACA,PRKCH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVirus Entry via Endocytic Pathways\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAP2A1,FLNA,ITGAL,ITGB1,PLCG1,PRKCH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eValidation of differentially expressed lncRNAs\u003c/h2\u003e \u003cp\u003eWe used qPCR assay to validate the deferentially expressed lncRNAs, while \u003cem\u003eAC037198.2\u003c/em\u003e, and \u003cem\u003eZNF433-AS1\u003c/em\u003e were selected based on differential expression and co-expression analyses. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, these lncRNAs were significantly different among PVR and iERM patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e "},{"header":"Discussion","content":" \u003cp\u003ePVR is still the leading cause of vitreoretinal surgery failure, mainly through retina re-detachment and even intraretinal fibrosis. The incidence of PVR is estimated to be 5\u0026ndash;10%.\u003csup\u003e18\u003c/sup\u003e However, as the mechanisms of PVR are still not very clear, it is difficult to predict or treat the condition despite the many efforts that are still being made. In the present study, our results identified differentially expressed mRNA and lncRNA in PBMCs of PVR patients and revealed that gene expression profile and molecular signature of PVR patients.\u003c/p\u003e \u003cp\u003eThe proliferation of cells, mainly RPE and glial cells, is the essential point of PVR development. Clinicians have tried for more than four decades to inhibit the proliferation of cells in the vitreous to prevent PVR but have not had impressive progress.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e This situation has raised the question of whether there is anything abnormal out of the eye in this disease. The answer to this might come from the immune system.\u003c/p\u003e \u003cp\u003eIn the review by Pastor et al., the authors proposed that ischemia, blood-retina barrier breakdown, and inflammation lead to the final PVR based on the collaborative genetic study named \u0026ldquo;Retina 4 Project\u0026rdquo;, which found 30 inflammatory-related genes were responsible for PVR.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Further, a single nucleotide polymorphism (SNP) analysis in peripheral blood from PVR patients shown that TNF locus which encompasses the gene of TNFα contributes to the development of PVR.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e It is suggested that PVR might not only be a \u0026ldquo;local inflammatory condition\u0026rsquo;\u0026rsquo;, but also could be affected by system regulation.\u003c/p\u003e \u003cp\u003eCompare with these studies, with RNA from peripheral blood mononuclear cells and with GO, KEGG and IPA analysis, we revealed that the immune related pathways or components are closely related to PVR change. We found immunoglobulin and its receptors as well as antigen binding were all up regulated in PBMC from PVR patient. Further, RNAs related to biological process of adaptive immune response and lymphocytes activation were also up regulated indicating microbial infection might play a role in the disease process. In IPA analysis, we found in enriched canonical pathways, CCL1, CCL3, CXCL8 and especially Th17 cells and its related cytokines IL-17A and IL-17F were emphasized. In previous publication, Th17 and its cytokines are inflammatory mediator to RPE cells,\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and RPE cells in inflammatory condition were thought to be a key point to PVR formation.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eInfection had long been considered as a trigger to immune disease. In the KEGG analysis, to our surprise, rather than immune pathways, infectious related pathways related to amoebiasis, malaria or chagas disease were enriched. As in uveitis, Forrester et al. agreed that infection may directly or indirectly related to noninfectious uveitis in the eye.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e In this consideration, remind us that infection might be a potential cause of PVR.\u003c/p\u003e \u003cp\u003eLncRNAs are widely expressed in monocytes, macrophages, neutrophils and implicated in the process of inflammation and immunity. Various molecular functions have been ascribed to lncRNAs, including gene regulation in cis, regulation of mRNA stability, and modulation of protein function. In PVR patients, Zhou et al. not only demonstrated that the expression of MALAT1 was significantly upregulated in the proliferating membrane, also found MALAT1 was significantly up-regulated in the peripheral blood.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e MALAT1 can inhibit the DNA binding activity of NF- κB, reduce the production of inflammatory cytokines, and down-regulate the autoimmune inflammatory response. The knockdown of MALAT1 can increase lipopolysaccharide (LPS)-induced expression of TNFα and IL-6.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e However, to our surprise, we did not find MALAT1 were upregulated in PBMC in PVR patient.\u003c/p\u003e \u003cp\u003eIn our research, by analysis the mRNA and lncRNA co-expression in PBMC, we found immune-related gene \u003cem\u003eNFKBIA\u003c/em\u003e, and chemokines \u003cem\u003eCXCL2\u003c/em\u003e and \u003cem\u003eCXCL8\u003c/em\u003e and their associate LncRNA \u003cem\u003eAC007032.1\u003c/em\u003e, \u003cem\u003eAC037198.2\u003c/em\u003e, \u003cem\u003eAL929472.2\u003c/em\u003e, \u003cem\u003eSLED1\u003c/em\u003e were highly associated with PVR. \u003cem\u003eAC007032.1\u003c/em\u003e is associated with immunomodulatory cytokine Nampt,\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e while \u003cem\u003eSLED1\u003c/em\u003e was found up regulated in peripheral blood cells of systemic lupus erythematosus patients.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Additionally, within IPA analysis, virus infection relate pathways and immune relate networks were highlighted in PVR patients.\u003c/p\u003e \u003cp\u003eFurther, the most obvious changed LncRNA \u003cem\u003eAC037198.2\u003c/em\u003e and \u003cem\u003eZNF433-AS1\u003c/em\u003e were selected to verify and were proved their actual change in PBMC from PVR patients. LncRNA AC037198.2 is associate with THBS1(thrombospondin 1) gene, which encoded a secreted protein to mediate cell-to-cell and cell-to-matrix interactions. As for \u003cem\u003eZNF433-AS1\u003c/em\u003e, this LncRNA can suppress ZNF433, which belongs to transcriptional factors with the zinc finger motif, and was found that play an important role in multiple sclerosis, which is an autoimmune disease.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e "},{"header":"Conclusions","content":" \u003cp\u003eIn summary, we provide a landscape of differential expression profile of mRNAs and lncRNAs between PVR and controls and construct an mRNA-lncRNA co-expression network based on the DETs. Pathway enrichment analyses offer novel insights into the pathogenesis of PVR, indicating that PVR might be related with abnormal immune system or previous infection. More importantly, some deferentially expressed lncRNAs, like LncRNA-\u003cem\u003eAC037198.2\u003c/em\u003e and \u003cem\u003eZNF433-AS1\u003c/em\u003ewere appeared in our study, which might be potential molecular signatures for PVR. These results will provide hence our understanding of this disease and provide novel therapeutic targets for PVR patients.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was supported by the Fundamental Research Funds for the Central Universities (20ykpy147) and Natural Science Foundation of Guangdong Province of China (2019A1515010189).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship:\u003c/strong\u003e All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosures: \u003c/strong\u003eYao Ni, Fangyuan Liu, Xiao Hu, Yingyan Qin and Zhaotian Zhang declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval: \u003c/strong\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability: \u003c/strong\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e \u003cspan\u003ePennock S, Haddock LJ, Eliott D, Mukai S, Kazlauskas A. Is neutralizing vitreal growth factors a viable strategy to prevent proliferative vitreoretinopathy? Prog Retin Eye Res. 2014;40:16\u0026ndash;34.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eWang X, Miller EB, Goswami M, et al. Rapid monocyte infiltration following retinal detachment is dependent on non-canonical IL6 signaling through gp130. J Neuroinflammation. 2017;14:121.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003ePastor JC, Rojas J, Pastor-Idoate S, Di Lauro S, Gonzalez-Buendia L, Delgado-Tirado S. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical consequences. Prog Retin Eye Res. 2016;51:125\u0026ndash;55.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChen J, Ao L, Yang J. Long non-coding RNAs in diseases related to inflammation and immunity. Ann Transl Med. 2019;7:494.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eCarpenter S, Fitzgerald KA. Cytokines and Long Noncoding RNAs. Cold Spring Harb Perspect Biol 2018;10.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eZhou RM, Wang XQ, Yao J, et al. Identification and characterization of proliferative retinopathy-related long noncoding RNAs. Biochem Biophys Res Commun. 2015;465:324\u0026ndash;30.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eYang S, Yao H, Li M, Li H, Wang F. Long Non-Coding RNA MALAT1 Mediates Transforming Growth Factor Beta1-Induced Epithelial-Mesenchymal Transition of Retinal Pigment Epithelial Cells. Plos One. 2016;11:e0152687.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eZandi S, Tappeiner C, Pfister IB, Despont A, Rieben R, Garweg JG. Vitreal Cytokine Profile Differences Between Eyes With Epiretinal Membranes or Macular Holes. Invest Ophthalmol Vis Sci. 2016;57:6320\u0026ndash;6.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMaier R, Weger M, Haller-Schober EM, et al. Multiplex bead analysis of vitreous and serum concentrations of inflammatory and proangiogenic factors in diabetic patients. Mol Vis. 2008;14:637\u0026ndash;43.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eThe classification of. retinal detachment with proliferative vitreoretinopathy. Ophthalmology. 1983;90:121\u0026ndash;5.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eKechin A, Boyarskikh U, Kel A, Filipenko M. cutPrimers:. A New Tool for Accurate Cutting of Primers from Reads of Targeted Next Generation Sequencing. J Comput Biol. 2017;24:1138\u0026ndash;43.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eKim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015;12:357\u0026ndash;60.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLiao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30:923\u0026ndash;30.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLiao Y, Smyth GK, Shi W. The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads. Nucleic Acids Res. 2019;47:e47.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLiao Y, Smyth GK, Shi W. The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote. Nucleic Acids Res. 2013;41:e108.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLove MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eYu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. Omics. 2012;16:284\u0026ndash;7.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eIdrees S, Sridhar J, Kuriyan AE. Proliferative Vitreoretinopathy: A Review. Int Ophthalmol Clin. 2019;59:221\u0026ndash;40.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eBanerjee S, Savant V, Scott RA, Curnow SJ, Wallace GR, Murray PI. Multiplex bead analysis of vitreous humor of patients with vitreoretinal disorders. Invest Ophthalmol Vis Sci. 2007;48:2203\u0026ndash;7.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChen Y, Yang P, Li F, Kijlstra A. The effects of Th17 cytokines on the inflammatory mediator production and barrier function of ARPE-19 cells. Plos One. 2011;6:e18139.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eForrester JV, Kuffova L, Dick AD. Autoimmunity, Autoinflammation, and Infection in Uveitis. Am J Ophthalmol. 2018;189:77\u0026ndash;85.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eZhao G, Su Z, Song D, Mao Y, Mao X. The long noncoding RNA MALAT1 regulates the lipopolysaccharide-induced inflammatory response through its interaction with NF-kappaB. Febs Lett. 2016;590:2884\u0026ndash;95.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eGarten A, Petzold S, Korner A, Imai S, Kiess W. Nampt: linking NAD biology, metabolism and cancer. Trends Endocrinol Metab. 2009;20:130\u0026ndash;8.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eIshii T, Onda H, Tanigawa A, et al. Isolation and expression profiling of genes upregulated in the peripheral blood cells of systemic lupus erythematosus patients. Dna Res. 2005;12:429\u0026ndash;39.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNischwitz S, Cepok S, Kroner A, et al. Evidence for VAV2 and ZNF433 as susceptibility genes for multiple sclerosis. J Neuroimmunol. 2010;227:162\u0026ndash;6.\u003c/span\u003e \u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mgnm","sideBox":"Learn more about [BMC Medical Genomics](http://bmcmedgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mgnm/default.aspx","title":"BMC Medical Genomics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"proliferative vitreoretinopathy, gene expression profile, long non-coding RNAs, immune-related pathway","lastPublishedDoi":"10.21203/rs.3.rs-74786/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-74786/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction:\u003c/strong\u003e Peripheral immune response has been revealed to play a critical role in proliferative vitreoretinopathy (PVR). However, the reliable immune-related factors that are acting as prognostic indicators or therapeutic targets for PVR remain to explore further.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e In the current study, we applied whole-transcriptome sequencing to profile peripheral blood mononuclear cells (PBMCs) from PVR patients and also analyzed lncRNA-mRNA interactions in peripheral immune cells to explore the pathways that might mediate immunopathology and resultant retinal damage in PVR. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and Ingenuity Pathway Analysis (IPA) were employed to classify the function of these differentially expressed genes (DEGs).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Compared to the controls, there were 319 genes upregulated, and 191 genes downregulated in PVR patients. GO, and KEGG enrichment analyses as well as IPA showed that these upregulated genes were significantly enriched in immune-related and infection-relate terms. Immune-related gene \u003cem\u003eNFKBIA\u003c/em\u003e, \u003cem\u003eCXCL2\u003c/em\u003e, and \u003cem\u003eCXCL8\u003c/em\u003e were detected as hub-genes in the co-expression network, while lncRNAs such as \u003cem\u003eAC007032.1\u003c/em\u003e, \u003cem\u003eAC037198.2\u003c/em\u003e, \u003cem\u003eAL929472.2\u003c/em\u003e, and \u003cem\u003eSLED1\u003c/em\u003e were highly co-expressed with them. lncRNA-mRNA interactions analysis also showed that putative targeted genes of these differentially expressed lncRNAs were also significantly enriched in immune-related or infection-relate pathways\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eOur study highlights the transformation of immune-related genes/pathways in PVR by comparing controls, and validates several critical genes and lncRNAs, which are serving as potential diagnostic markers for PVR patients.\u003c/p\u003e","manuscriptTitle":"Expression Profile of Peripheral Immune Cells-derived Coding and Long Non-coding RNAs\u0026nbsp;in Patients With Proliferative Vitreoretinopathy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-09-21 18:28:03","doi":"10.21203/rs.3.rs-74786/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2020-12-11T00:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-12-10T00:00:00+00:00","index":2,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-12-10T00:00:00+00:00","index":2,"fulltext":"Recommendation: Accept after minor essential revisions\nForm responses:\n---\n\nComments to Author:\n---\nNi et al in their manuscript titled \"expression profile of peripheral immune cells-derived coding and long non-coding RNAs in patients with proliferative vitreoretinopathy\" applied whole-transcriptome sequencing to profile peripheral blood mononuclear cells (PBMCs) from proliferative vitreoretinopathy (PVR) patients and also analyzed lncRNA-mRNA interactions in peripheral immune cells to explore the pathways that might mediate immunopathology and resultant retinal damage in PVR. They used Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and Ingenuity Pathway Analysis (IPA) to classify the function of differentially expressed genes (DEGs).\nThe authors found 319 genes upregulated, and 191 genes down regulated in PVR patients. From GO, and KEGG enrichment analyses and s IPA they showed that the upregulated genes were significantly enriched in immune-related and infection-relate terms. Immune-related genes NFKBIA, CXCL2, and CXCL8 were detected as hub-genes in the co-expression network, while lncRNAs such as AC007032.1, AC037198.2, AL929472.2, and SLED1 were highly co-expressed with them. lncRNA-mRNA interactions analysis showed that putative targeted genes of these differentially expressed lncRNAs were also significantly enriched in immune related or infection-relate pathways. The authors conclude that the immune-related genes/pathways were transformed in PVR compared to controls, and validated several critical genes and lncRNAs, which are serving as potential diagnostic markers for PVR patients.\n\nThe concept is good but the sample numbers are too small to make any meaningful conclusions. The figure quality is very bad. The authors should clearly undertone their conclusions with clear warrant for more experiments with large number of samples in validation experiments.\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Declaration of competing interests: **'I declare that I have no competing interests'**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"editorInvitedReview","content":"","date":"2020-10-12T12:00:00+00:00","index":1,"fulltext":"Recommendation: Accept after minor essential revisions\nForm responses:\n---\n\nComments to Author:\n---\nThe overall message conveyed by the manuscript sounds fine. I have the following concerns:\n\n1. Please change the title of the manuscript. The title should reflect the resultant message of the work done on PVR that is conveyed in this manuscript.\n2. In order to identify differentially expressed genes/lncRNAs, please change from using p-value\u003c0.05 to FDR\u003c0.05 to take into account errors from multiple testing. Please revise the manuscript by updating the differential expression and pathway results after this change.\n3. How were differentially expressed transcripts or DETs obtained? In Methods, it is mentioned that featureCount was used to report expression at gene level and then DESeq2 for differential expression. There is no mention about how DETs were obtained. Please clarify.\n4. In several places in the manuscript, the term 'transcriptome' is used. Do the authors mean 'genes' instead? This is very confusing to the reader and not clear whether the authors are talking about the entire transcriptome, genes or transcripts. Please clarify and make necessary corrections.\n5. Please clarify whether fold change on linear scale or log2 scale was used? For example, page 7 line 118. Please make necessary corrections.\n6. The pathway analysis on lncRNAs is confusing. Essentially the authors identified genes that are in proximity to these lncRNAs and used those genes to perform pathway analysis. If this is true, then the authors need to re-phrase and say pathway analysis of genes associated with lncRNAs.\n7. Please add a supplementary table showing the results of differentially expressed genes and lncRNAs obtained from this analysis\n8. For the two experimentally validated lncRNAs, please indicate their magnitude of fold change so that readers get an idea of how up-regulated they are in the PVR group\n9. All figures are of extremely poor resolution and I believe they do not adhere to the journal requirements. Please consider revising the quality of the main and supplementary figures\n10. Grammatical corrections and sentence improvements would benefit the manuscript\n11. I would suggest the authors deposit the raw files and make their data publicly available to the research community.\n12. In Methods, please mention the source of the reference GTF (for example, Ensembl, Gencode, RefSeq etc.) used as input to the featureCount software.\n13. In Methods, include how or what tool was used to perform co-expression network analysis was done between mRNAs and lncRNAs.\n\n\nMinor issues:\n- page 5, line 96 - change \u003c.05 to \u003c0.05\n- page 7, line 128 - mention Figure S1B\n- page 9, line 157 - how many mRNA-lncRNA pairs were obtained that had Pearson correlation \u003e0.8? Please provide the number.\n\n\n\n\n\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. 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(default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **No**\n* Is the use of statistics and treatment of uncertainties appropriate?: **No**\n* Is the presentation of the work clear?: **No**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"reviewerAgreed","content":"","date":"2020-09-28T12:00:00+00:00","index":1,"fulltext":""},{"type":"editorAssigned","content":"","date":"2020-09-24T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-09-24T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-09-18T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-09-18T12:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2020-09-09T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mgnm","sideBox":"Learn more about [BMC Medical Genomics](http://bmcmedgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mgnm/default.aspx","title":"BMC Medical Genomics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"286ab5af-a9be-4c2e-b479-feaca80c72c4","owner":[],"postedDate":"September 21st, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":569043,"name":"Epigenetics \u0026 Genomics"}],"tags":[],"updatedAt":"2021-01-31T15:02:39+00:00","versionOfRecord":{"articleIdentity":"rs-74786","link":"https://doi.org/10.1186/s12920-021-00875-5","journal":{"identity":"bmc-medical-genomics","isVorOnly":false,"title":"BMC Medical Genomics"},"publishedOn":"2021-01-28 15:01:28","publishedOnDateReadable":"January 28th, 2021"},"versionCreatedAt":"2020-09-21 18:28:03","video":"","vorDoi":"10.1186/s12920-021-00875-5","vorDoiUrl":"https://doi.org/10.1186/s12920-021-00875-5","workflowStages":[]},"version":"v1","identity":"rs-74786","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-74786","identity":"rs-74786","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}