Gene Co-Expression Network Analysis Identifies Vitamin D-Associated Gene Modules in Adult Normal Rectal Epithelium Following Supplementation

Colorectal cancer (CRC) is a common, multifactorial disease. While observational studies have identified an association between lower vitamin D and higher CRC risk, supplementation trials have been inconclusive and the mechanisms by which vitamin D may modulate CRC risk are not well understood. We sought to perform a weighted gene co-expression network analysis (WGCNA) to identify modules present after vitamin D supplementation (when plasma vitamin D level was sufficient) which were absent before supplementation, and then to identify influential genes in those modules. The transcriptome from normal rectal mucosa biopsies of 49 individuals free from CRC were assessed before and after 12 weeks of 3200IU/day vitamin D (Fultium-D3) supplementation using paired-end total RNAseq. While the effects on expression patterns following vitamin D supplementation were subtle, WGCNA identified highly correlated genes forming gene modules. Four of the 17 modules identified in the post-vitamin D network were not preserved in the pre-vitamin D network, shedding new light on the biochemical impact of supplementation. These modules were enriched for GO terms related to the immune system, hormone metabolism, cell growth and RNA metabolism. Across the four treatment-associated modules, 51 hub genes were identified, with enrichment of 40 different transcription factor motifs in promoter regions of those genes, including VDR:RXR. Six of the hub genes were nominally differentially expressed in studies of vitamin D effects on adult normal mucosa organoids: LCN2, HLA-C, AIF1L, PTPRU, PDE4B and IFI6. By taking a gene-correlation network approach, we have described vitamin D induced changes to gene modules in normal human rectal epithelium in vivo, the target tissue from which CRC develops.

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Oral Vitamin D supplementation induces transcriptomic changes in rectal mucosa that are consistent with anti-tumour effects.

10.1101/2021.05.04.21255629 ◽

2021 ◽

Author(s):

Peter G Vaughan-Shaw ◽

Graeme Grimes ◽

James P Blackmur ◽

Maria Timofeeva ◽

Marion Walker ◽

...

Keyword(s):

Gene Expression ◽

Vitamin D ◽

Expression Patterns ◽

Rectal Mucosa ◽

Vitamin D Supplementation ◽

Gene Expression Patterns ◽

Blood Biomarkers ◽

Oral Vitamin ◽

Gene Set ◽

Transcriptomic Changes

Background Risk for several common cancers is influenced by the transcriptomic landscape of the respective tissue-of-origin. Vitamin D influences in-vitro gene expression and cancer cell growth. We sought to determine whether oral vitamin D induces beneficial gene expression effects in human rectal epithelium and identify biomarkers of response. Methods Blood and rectal mucosa was sampled from 191 human subjects and mucosa gene expression (HT12) correlated with plasma vitamin D (25-OHD) to identify differentially expressed genes. Fifty subjects were then administered 3200IU/day oral vitamin D3 and matched blood/mucosa resampled after 12 weeks. Transcriptomic changes (HT12/RNAseq) after supplementation were tested against the prioritised genes for gene-set and GO-process enrichment. To identify blood biomarkers of mucosal response, we derived receiver-operator curves and C-statistic (AUC) and tested biomarker reproducibility in an independent Supplementation Trial (BEST-D). Results 629 genes were associated with 25-OHD level (P<0.01), highlighting 453 GO-term processes (FDR<0.05). In the whole intervention cohort, vitamin D supplementation enriched the prioritised mucosal gene-set (upregulated gene-set P<1.0E-07; downregulated gene-set P<2.6E-05) and corresponding GO terms (P=2.90E-02), highlighting gene expression patterns consistent with anti-tumour effects. However, only 9 individual participants (18%) showed a significant response (NM gene-set enrichment P<0.001) to supplementation. Expression changes in HIPK2 and PPP1CC expression served as blood biomarkers of mucosal transcriptomic response (AUC=0.84 [95%CI:0.66-1.00]), and replicated in BEST-D trial subjects (HIPK2 AUC=0.83 [95%CI:0.77-0.89]; PPP1CC AUC=0.91 [95%CI:0.86-0.95]). Conclusions Higher plasma 25-OHD correlates with rectal mucosa gene expression patterns consistent with anti-tumour effects and this beneficial signature is induced by short-term vitamin D supplementation. Heterogenous gene expression responses to vitamin D may limit the ability of randomised trials to identify beneficial effects of supplementation on CRC risk. However, in the current study blood expression changes in HIPK2 and PPP1CC identify those participants with significant anti-tumor transcriptomic responses to supplementation in the rectum. These data provide compelling rationale for a trial of vitamin D and CRC prevention using easily assayed blood gene expression signatures as intermediate biomarkers of response.

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Oral vitamin D supplementation induces transcriptomic changes in rectal mucosa that are linked to anti-tumour effects

BMC Medicine ◽

10.1186/s12916-021-02044-y ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

P. G. Vaughan-Shaw ◽

G. Grimes ◽

J. P. Blackmur ◽

M. Timofeeva ◽

M. Walker ◽

...

Keyword(s):

Gene Expression ◽

Vitamin D ◽

Expression Patterns ◽

Rectal Mucosa ◽

Vitamin D Supplementation ◽

Gene Expression Patterns ◽

Blood Biomarkers ◽

Oral Vitamin ◽

Gene Set ◽

Transcriptomic Changes

Abstract Background The risk for several common cancers is influenced by the transcriptomic landscape of the respective tissue-of-origin. Vitamin D influences in vitro gene expression and cancer cell growth. We sought to determine whether oral vitamin D induces beneficial gene expression effects in human rectal epithelium and identify biomarkers of response. Methods Blood and rectal mucosa was sampled from 191 human subjects and mucosa gene expression (HT12) correlated with plasma vitamin D (25-OHD) to identify differentially expressed genes. Fifty subjects were then administered 3200IU/day oral vitamin D3 and matched blood/mucosa resampled after 12 weeks. Transcriptomic changes (HT12/RNAseq) after supplementation were tested against the prioritised genes for gene-set and GO-process enrichment. To identify blood biomarkers of mucosal response, we derived receiver-operator curves and C-statistic (AUC) and tested biomarker reproducibility in an independent Supplementation Trial (BEST-D). Results Six hundred twenty-nine genes were associated with 25-OHD level (P < 0.01), highlighting 453 GO-term processes (FDR<0.05). In the whole intervention cohort, vitamin D supplementation enriched the prioritised mucosal gene-set (upregulated gene-set P < 1.0E−07; downregulated gene-set P < 2.6E−05) and corresponding GO terms (P = 2.90E−02), highlighting gene expression patterns consistent with anti-tumour effects. However, only 9 individual participants (18%) showed a significant response (NM gene-set enrichment P < 0.001) to supplementation. Expression changes in HIPK2 and PPP1CC expression served as blood biomarkers of mucosal transcriptomic response (AUC=0.84 [95%CI 0.66–1.00]) and replicated in BEST-D trial subjects (HIPK2 AUC=0.83 [95%CI 0.77–0.89]; PPP1CC AUC=0.91 [95%CI 0.86–0.95]). Conclusions Higher plasma 25-OHD correlates with rectal mucosa gene expression patterns consistent with anti-tumour effects, and this beneficial signature is induced by short-term vitamin D supplementation. Heterogenous gene expression responses to vitamin D may limit the ability of randomised trials to identify beneficial effects of supplementation on CRC risk. However, in the current study blood expression changes in HIPK2 and PPP1CC identify those participants with significant anti-tumour transcriptomic responses to supplementation in the rectum. These data provide compelling rationale for a trial of vitamin D and CRC prevention using easily assayed blood gene expression signatures as intermediate biomarkers of response.

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Shared Blood Transcriptomic Signatures between Alzheimer’s Disease and Diabetes Mellitus

Biomedicines ◽

10.3390/biomedicines9010034 ◽

2021 ◽

Vol 9 (1) ◽

pp. 34

Author(s):

Taesic Lee ◽

Hyunju Lee

Keyword(s):

Diabetes Mellitus ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Protein Interactions ◽

Expression Patterns ◽

Protein Protein Interactions ◽

Hub Genes ◽

Gene Modules ◽

Gene Regulatory ◽

The Brain

Alzheimer’s disease (AD) and diabetes mellitus (DM) are known to have a shared molecular mechanism. We aimed to identify shared blood transcriptomic signatures between AD and DM. Blood expression datasets for each disease were combined and a co-expression network was used to construct modules consisting of genes with similar expression patterns. For each module, a gene regulatory network based on gene expression and protein-protein interactions was established to identify hub genes. We selected one module, where COPS4, PSMA6, GTF2B, GTF2F2, and SSB were identified as dysregulated transcription factors that were common between AD and DM. These five genes were also differentially co-expressed in disease-related tissues, such as the brain in AD and the pancreas in DM. Our study identified gene modules that were dysregulated in both AD and DM blood samples, which may contribute to reveal common pathophysiology between two diseases.

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Gene co-expression network analysis reveals key potential gene modules in utero-vaginal junction associated with duration of fertility trait of breeder hens

Scientific Reports ◽

10.1038/s41598-019-50148-6 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 1

Author(s):

Lantao Gu ◽

Ruoxi Jing ◽

Yanzhang Gong ◽

Mei Yu ◽

Abdelmotaleb Elokil ◽

...

Keyword(s):

Network Analysis ◽

Sperm Storage ◽

Production Performance ◽

Rt Pcr ◽

Hub Genes ◽

Breeder Hens ◽

Fertility Trait ◽

Gene Modules ◽

Highly Correlated ◽

Insight Into

Abstract The number of days (DN) when hens lay fertile eggs as well as the number of fertile eggs (FN) were produced after a single artificial insemination (AI), including the two duration of fertility (DF) traits. Indeed, they are the key production performance that associates with the production cost of hatching egg when its determination the interval between successive artificial inseminations. However, the relevant genes response for regulating the DF has not been uncovered yet. Therefore, we performed a weighted gene co-expression network analysis (WGCNA) to investigate the insight into co-expression gene modules on DF process in hens. The total mRNA was extracted from the utero-vaginal junction (UVJ, with the sperm storage function in hen’s oviduct which is the biological basis for DF) of 20 hens with several levels of DF traits, and performed transcriptome sequences of mRNA. As a result, three co-expression gene modules were identified to be highly correlated with DF traits. Moreover, the expression changes of top 5 hub genes in each module with DF traits were further confirmed in other 20 hens by RT-PCR. These findings highlighted the co-expression modules and their affiliated genes as playing important roles in the regulation of DF traits.

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Vitamin D in the Prevention and Treatment of Osteoarthritis: From Clinical Interventions to Cellular Evidence

Nutrients ◽

10.3390/nu11020243 ◽

2019 ◽

Vol 11 (2) ◽

pp. 243 ◽

Cited By ~ 3

Author(s):

Clara Yongjoo Park

Keyword(s):

Vitamin D ◽

Observational Studies ◽

Pilot Trial ◽

Clinical Results ◽

Vitamin D Supplementation ◽

Vitamin D Status ◽

Randomized Controlled ◽

The Relationship

Older adults are recommended vitamin D to prevent fractures. Though this population is also at risk of osteoarthritis (OA), the effect of vitamin D on OA is unclear and may differ by disease state. The relationship between vitamin D and OA during OA initiation and progression were considered in this narrative review of in vivo and in vitro studies. Regarding OA initiation in humans, the small number of published observational studies suggest a lack of association between induction of OA and vitamin D status. Most randomized controlled trials were performed in White OA patients with relatively high vitamin D status (>50 nmol/L). These studies found no benefit of vitamin D supplementation on OA progression. However, subset analyses and one randomized controlled pilot trial indicated that vitamin D supplementation may alleviate joint pain in OA patients with low vitamin D status (<50 nmol/L). As the etiology of OA is recently being more fully uncovered, better animal and cell models are needed. According to currently available clinical results, evidence is lacking to set a vitamin D level to prevent OA, and increasing vitamin D status above 50 nmol/L does not seem to benefit OA patients.

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SO004IDENTIFICATION OF HUB GENES, FOCUSED ON CHEMOKINES AND CHEMOKINE RECEPTORS, ASSOCIATED WITH THE DECLINE OF RENAL FUCTION OF DIABETIC KIDNEY DISEASE BY WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfaa139.so004 ◽

2020 ◽

Vol 35 (Supplement_3) ◽

Author(s):

Songtao Feng ◽

Bicheng Liu ◽

Linli Lv ◽

Gao Yueming ◽

Di Yin ◽

...

Keyword(s):

Renal Function ◽

Network Analysis ◽

Kidney Disease ◽

T Cell Activation ◽

Chemokine Receptors ◽

Diabetic Kidney Disease ◽

Expression Level ◽

Hub Genes ◽

Diabetic Kidney ◽

Gene Modules

Abstract Background and Aims The fact that activation of the innate immune system and chronic inflammation are closely involved in the pathogenesis of diabetic Kidney disease (DKD). Recent studies have suggested the inflammatory process plays a crucial role in the progression of DKD. Identifying novel inflammatory molecules closely related to the decline of renal function is of significance in diagnosing and predicting the progression of DKD. The weighted gene co-expression network analysis (WGCNA) algorithm represents a novel systems biology method that provide the approach of association between gene modules and clinical traits to find the genes involvement into the certain phenotypic trait. The goal of this study was to identify hub genes and their roles in DKD from the gene sets associated with the decline of renal function by WGCNA. Method The Gene Expression Omnibus (GEO) database and “Nephroseq” website were searched and transcriptome study from DN biopsies with well-established clinical phenotypic data were selected for analysis. Next, we constructed a weighted gene co-expression network and identified modules negatively correlated with eGFR by WGCNA in the data of glomerular tissue. Functional annotations of the genes in modules negatively correlated with eGFR were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Through protein-protein interaction (PPI) analysis and hub gene screening, the hub genes were obtained. Furthermore, we compared the expression level of hub genes between DKD and normal control and drew ROC curves to determine the diagnosis value to DKD of these genes. Results The microarray-based expression datasets GSE30528 were screened out for analysis, which included glomeruli tissue of 9 cases of DKD and 13 cases of control. This microarray platform represented the transcriptome profile of 12411 well-characterized genes. Using WGCNA, a total of 19 gene modules were identified. Then module eigengene were analyzed for correlation with clinical traits of age, sex, ethnicity and eGFR and the “MEhoneydew1” module showed negative associated with eGFR (r=-0.58). GO functional annotation showed that these 551 genes in the “MEhoneydew1” module mainly enriched in the T cell activation. KEGG annotation showed mainly enriched in chemokine signaling pathway. Except for C3, top 10 hub genes, CCR5, CXCR4, CCR7, CCL5, CXCL8, CCR2, CCR1, CX3CR1, C3AR1 and C3, are all members of chemokines or chemokine receptors. Furthermore, we compared the expression level of these 9 genes between DKD and control, and found that all of these 9 genes increased in the DKD group, and the differences of 6 genes, CCR5, CCR7, CCL5, CCR2, CCR1, C3AR1, were of statistical significance. Linear correlation analysis showed that the expression of these 6 genes was negatively correlated with eGFR, and the ROC curve showed that the area under the curve could reach 0.812∼1.0. Conclusion We identified a panel of 6 hub genes focused on chemokines and chemokine receptors critical for decline of renal function of DKD using WGCNA. These genes may serve as biomarkers for diagnosis/prognosis and as putative novel therapeutic targets for DKD.

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An Actinidia chinensis (kiwifruit) eFP browser and network analysis of transcription factors

10.21203/rs.3.rs-101514/v1 ◽

2020 ◽

Author(s):

Lara Brian ◽

Ben Warren ◽

Peter McAtee ◽

Jessica Rodrigues ◽

Niels Nieuwenhuizen ◽

...

Keyword(s):

Gene Expression ◽

Network Analysis ◽

Fruit Development ◽

Transcriptional Control ◽

Expression Patterns ◽

Gene Expression Patterns ◽

Actinidia Chinensis ◽

Knox Gene ◽

Hub Genes ◽

Flower And Fruit Development

Abstract BackgroundTranscriptomic studies combined with a well annotated genome have laid the foundations for new understanding of molecular processes. Tools which visualise gene expression patterns have further added to these resources. The manual annotation of the Actinidia chinensis (kiwifruit) genome has resulted in a high quality set of 33,044 genes. Here we investigate gene expression patterns in diverse tissues, visualised in an Electronic Fluorescent Pictograph (eFP) browser, to study the relationship of transcription factor (TF) expression using network analysis. ResultsSixty-one samples covering diverse tissues at different developmental time points were selected for RNAseq analysis and an eFP browser was generated to visualise this dataset. 2,839 TFs representing 57 different classes were identified and named. Network analysis of the TF expression patterns separated TFs into 14 different modules. Two modules consisting of 237 TFs were correlated with floral bud and flower development, a further two modules containing 160 TFs were associated with fruit development and maturation. A single module of 480 TFs was associated with ethylene-induced fruit ripening. Three “hub” genes correlated with flower and fruit development consisted of a HAF-like gene central to gynoecium development, an ERF and a DOF gene. Maturing and ripening hub genes included a KNOX gene that was associated with seed maturation, and a GRAS-like TF.ConclusionsThis study provides an insight into the complexity of the transcriptional control of flower and fruit development, as well as providing a new resource to the plant community. The eFP browser is provided in an accessible format that allows researchers to download and work internally.

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Detecting Hub Genes Associated With Lauren Subtype of Gastric Cancer by Weighted Gene Co-Expression Network Analysis

10.21203/rs.3.rs-61626/v1 ◽

2020 ◽

Author(s):

XU LIU ◽

Li Yao ◽

Jingkun Qu ◽

Lin Liu ◽

XU LIU ◽

...

Keyword(s):

Gastric Cancer ◽

Network Analysis ◽

Cancer Survival ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Diffuse Gastric Cancer ◽

Hub Genes ◽

Gene Modules

Abstract Background Gastric cancer is a rather heterogeneous type of malignant tumor. Among the several classification system, Lauren classification can reflect biological and pathological differences of different gastric cancer.Method to provide systematic biological perspectives, we employ weighted gene co-expression network analysis to reveal transcriptomic characteristics of gastric cancer. GSE15459 and TCGA STAD dataset were downloaded. Co-expressional network was constructed and gene modules were identified. Result Two key modules blue and red were suggested to be associated with diffuse gastric cancer. Functional enrichment analysis of genes from the two modules was performed. Validating in TCGA STAD dataset, we propose 10 genes TNS1, PGM5, CPXM2, LIMS2, AOC3, CRYAB, ANGPTL1, BOC and TOP2A to be hub-genes for diffuse gastric cancer. Finally these ten genes were associated with gastric cancer survival. Conclusion More attention need to be paid and further experimental study is required to elucidate the role of these genes.

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Identification of key gene modules and genes in colorectal cancer by weighted gene co-expression network analysis (WGCNA)

10.7287/peerj.preprints.27667v1 ◽

2019 ◽

Author(s):

Zheying Zhang ◽

Na Li ◽

Qingzu Gao ◽

Xinlai Qian

Keyword(s):

Colorectal Cancer ◽

Developing Countries ◽

Network Analysis ◽

Malignant Tumor ◽

Hub Genes ◽

Hub Gene ◽

Chip Data ◽

Qrt Pcr ◽

Gene Modules

Background: Colorectal cancer (CRC) is a malignant tumor particularly common in developing countries. In this study, we used Weighted Gene Co-Expression Network Analysis (WGCNA) of chip data and screened hub genes in CRC to find the gene modules specifically correlated with clinical traits. Methods: WGCNA was used to identify the gene modules specifically associated with metastasis in colorectal cancer. Cytoscape software was used to construct a co-expression network. The expression of CYTH1 was determined by qRT-PCR. Results: Based on the predicted co-expression network, we identified that the turquoise module was associated with CRC clinical metastasis traits. Turquoise module genes were analyzed, and we identified the hub gene CYTH1 using Cytoscape software. Additionally, we found CYTH1’s expression was lower in CRC tissue and cells when compared with normal counterparts.

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P0971IDENTIFICATION OF HUB GENES ASSOCIATED WITH THE DEPOSITION OF EXTRACELLULAR MATRIX AND SPECIFIC FOR DIABETIC NEPHROPATHY BY WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfaa142.p0971 ◽

2020 ◽

Vol 35 (Supplement_3) ◽

Author(s):

Songtao Feng ◽

Linli Lv ◽

Gao Yueming ◽

Cao Jingyuan ◽

Di Yin ◽

...

Keyword(s):

Gene Expression ◽

Extracellular Matrix ◽

Diabetic Nephropathy ◽

Network Analysis ◽

Expression Level ◽

Hub Genes ◽

Hub Gene ◽

Gene Screening ◽

Gene Modules ◽

Geo Database

Abstract Background and Aims Diabetic nephropathy (DN) and its most severe manifestation, end-stage renal disease (ESRD), remains one of the leading causes of reduced lifespan in people with diabetes. Identifying novel molecules that are involved in the pathogenesis of DN has both diagnostic and therapeutic implications. The gene co-expression network analysis (WGCNA) algorithm represents a novel systems biology approach that provide the approach of association between gene modules and clinical traits to find the module involvement into the certain phenotypic trait. The goal of this study was to identify hub genes and their roles in DN from the aspect of whole gene transcripts analysis. Method Various types of chronic kidney diseases (CKD), including DN, microarray-based mRNA gene expression data, listed in the Gene Expression Omnibus (GEO) database, were analyzed. Next, we constructed a weighted gene co-expression network and identified modules distinguishing DN from normal or other types of CKD by WGCNA. Functional annotations of the genes in modules specialized for DN were analyzed by Gene Ontology (GO) enrichment analysis. Through protein-protein interaction (PPI) analysis and hub gene screening, the hub genes specific for DN were obtained. Furthermore, we drew ROC curves to determine the diagnosis and differential diagnosis value to DN of hub genes. Finally, another study of microarray in the GEO database was selected to verify the expression level of hub genes and in the “Nephroseq” database, the correlation between the gene expression level and eGFR was analyzed. Results “GSE99339”, glomerular tissue microarray in 187 patients with a total of 10947 genes, was selected for analysis. After excluding the inappropriate cases, a total of 179 specimens were analyzed, including 14 cases of DN, 22 cases of focal segmental glomerulosclerosis (FSGS), 15 cases of hypertensive nephropathy (HT), 26 cases of IgA nephropathy (IgAN), 13 cases of minimal change disease (MCD), 21 cases of membranous nephropathy (MGN), 23 cases of rapidly progressive glomerulonephritis (RPGN), 30 cases of lupus nephritis (LN) and 14 cases of kidney tissue adjacent to tumor. Co-expression network analysis by WGCNA identified 23 distinct gene modules of the total 10947 genes and revealed “MEsaddlegreen” module was strongly correlated with DN (r=0,54), but not with other groups. GO functional annotation showed that these 64 genes in the “MEsaddlegreen” module mainly enriched in the deposition of extracellular matrix, which represents the specific and diagnostic pathophysiological process of DN. Further PPI and hub gene screening analysis revealed that LUM, ELN, FBLN1, MMP2, FBLN5 and FMOD can be served as hub genes, which had been proved to play an important role in the deposition of extracellular matrix. Furthermore, we found that the expression of hub genes was the highest in DN group and for the diagnosis value of DN by each gene, the area under the ROC curve is about 0.75∼0.95. The external verification of another study showed that compared with the normal control group, the expression of these hub genes was the highest in the DN group, and their expression level was negatively correlated with eGFR. Conclusion Using WGCNA and further bioinformatics approach, we identified six hub genes that appear to be identical to DN development. As such, they may represent potential diagnostic biomarkers as well as therapeutic targets with clinical utility.

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