Prepubertal onset of diabetes prevents expression of renal cortical connective tissue growth factor

Langer, William J.; Devish, Kay; Carmines, Pamela K.; Lane, Pascale H.

doi:10.1007/s00467-007-0642-8

Cited by 5 publications

(5 citation statements)

References 56 publications

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“…These findings shed light on the roles of S100B in DN. The finding that high glucose increased S100B expression in mesangial cells is similar to two previous studies showing increased S100B mRNA levels in diabetic human glomeruli (19) or diabetic rat renal cortex (20) in the Gene Expression Omnibus microarray database (21), although the original studies did not mention it. High glucose and exogenous S100B were also found to induce the p21 WAF1 gene transcription and protein expression, type IV collagen and fibronectin expression and TGF-β gene transcription and bioactivity.…”

Section: Discussionsupporting

confidence: 87%

S100B is required for high glucose-induced pro-fibrotic gene expression and hypertrophy in mesangial cells

Chuang

Guh

et al. 2014

International Journal of Molecular Medicine

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The advanced glycation end‑product (AGE)‑receptor for AGE (RAGE) axis induces transforming growth factor‑β (TGF‑β) expression, cell hypertrophy and increases extracellular matrices that are indicated in the pathogenesis of diabetic nephropathy (DN). RAGE binds to numerous ligands besides AGE, including S100B. In the present study, the roles of S100B in high glucose‑induced p21WAF1, extracellular matrices, TGF‑βl and cell hypertrophy in mouse mesangial (MES13) cells were investigated. High glucose (30 mM) time‑dependently (24‑72 h) induced S100B expression. High glucose and exogenous S100B (1 µM) time‑dependently increased p21WAF1 gene transcription and protein expression, increased type IV collagen and fibronectin protein expression, and TGF‑β gene transcription and bioactivity. Exogenous S100B also time‑dependently activated the extracellular regulated kinases (ERK1/2), p38 kinase and c‑Jun N‑terminal kinase (JNK) signaling pathways. Exogenous S100B‑induced TGF‑β gene transcription and bioactivity were attenuated by SB203580 (p38 kinase inhibitor) and PD98059 (ERK1/2 inhibitor). Finally, the knockdown of S100B by small interfering RNA (siRNA) attenuated high glucose‑induced TGF‑β gene transcription and bioactivity, type IV collagen and fibronectin protein expression and p21WAF1 protein expression. Thus, S100B induced TGF‑β via the ERK1/2 and p38 kinase pathways in mesangial cells. Additionally, high glucose‑induced pro‑fibrotic genes (TGF‑β, type IV collagen and fibronectin) and cell hypertrophy‑related p21WAF1 are dependent on S100B.

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Section: Discussionsupporting

confidence: 87%

S100B is required for high glucose-induced pro-fibrotic gene expression and hypertrophy in mesangial cells

Chuang

Guh

et al. 2014

International Journal of Molecular Medicine

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“…In addition, the impact on kidney function of physiologic changes associated with pubertal growth and development in this population is unknown. These changes may accelerate the progression of calcineurin inhibitor induced nephrotoxicity as has been noted in other chronic nephropathies (15)(16)(17)(18).…”

Section: Introductionmentioning

confidence: 99%

Glomerular Filtration Rate Following Pediatric Liver Transplantation—The SPLIT Experience

Campbell

Martin

et al. 2010

American Journal of Transplantation

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Impaired kidney function is a well-recognized complication following liver transplantation (LT). Studies of this complication in children have been limited by small numbers and insensitive outcome measures.Our aim was to define the prevalence of, and identify risk factors for, post-LT kidney dysfunction in a multicenter pediatric cohort using measured glomerular filtration rate (mGFR). We conducted a crosssectional study of 397 patients enrolled in the Studies in Pediatric Liver Transplantation (SPLIT) registry, using mGFR < 90 mL/min/1.73 m 2 as the primary outcome measure. Median age at LT was 2.2 years. Primary diagnoses were biliary atresia (44.6%), fulminant liver failure (9.8%), metabolic liver disease (16.4%), chronic cholestatic liver disease (13.1%), cryptogenic cirrhosis (4.3%) and other (11.8%). At a mean of 5.2 years post-LT, 17.6% of patients had a mGFR < 90 mL/min/1.73 m 2 . In univariate analysis, factors associated with this outcome were transplant center, age at LT, primary diagnosis, calculated GFR (cGFR) at LT and 12 months post-LT, primary immunosuppression, early post-LT kidney complications, age at mGFR, height and weight Z-scores at 12 months post-LT. In multivariate analysis, independent variables associated with a mGFR <90 mL/min/1.73 m 2 were primary immunosuppression, age at LT, cGFR at LT and height Z-score at 12 months post-LT.

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“…Integrative bioinformatics analysis with larger sample sizes and more minor potential biases is superior to finding new molecular signatures ( 9 ). Different bioinformatics analyses for DKD have been reported ( 10 – 18 ). The datasets involved in those studies are either from type 1 diabetic kidney disease (T1DKD) ( 10 – 13 ) or type 2 kidney disease (T2DKD) samples ( 14 – 16 ).…”

Section: Introductionmentioning

confidence: 99%

“…Different bioinformatics analyses for DKD have been reported ( 10 – 18 ). The datasets involved in those studies are either from type 1 diabetic kidney disease (T1DKD) ( 10 – 13 ) or type 2 kidney disease (T2DKD) samples ( 14 – 16 ). Some genes, such as connective tissue growth factor (CTGF) ( 10 ), complement 3 (C3) ( 12 ), complement 5 (C5) ( 12 ), cyclin b2 (Ccnb2) ( 14 ), and nuclear receptor subfamily 1 group I member 2 (Nr1i2) ( 14 ), have been identified to be molecular signatures and showed great potential as therapeutic targets.…”

Section: Introductionmentioning

confidence: 99%

“…The datasets involved in those studies are either from type 1 diabetic kidney disease (T1DKD) ( 10 – 13 ) or type 2 kidney disease (T2DKD) samples ( 14 – 16 ). Some genes, such as connective tissue growth factor (CTGF) ( 10 ), complement 3 (C3) ( 12 ), complement 5 (C5) ( 12 ), cyclin b2 (Ccnb2) ( 14 ), and nuclear receptor subfamily 1 group I member 2 (Nr1i2) ( 14 ), have been identified to be molecular signatures and showed great potential as therapeutic targets. In 2020, systematic integrated analysis of genetic and epigenetic variation in DKD patients was reported, and functional annotation suggested the role of inflammation, specifically, apoptotic cell clearance and complement activation in kidney disease development ( 17 ).…”

Section: Introductionmentioning

confidence: 99%

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Identification of Novel Key Molecular Signatures in the Pathogenesis of Experimental Diabetic Kidney Disease

Diao

Yang

et al. 2022

Front. Endocrinol.

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Diabetic kidney disease (DKD) is a long-term major microvascular complication of uncontrolled hyperglycemia and one of the leading causes of end-stage renal disease (ESDR). The pathogenesis of DKD has not been fully elucidated, and effective therapy to completely halt DKD progression to ESDR is lacking. This study aimed to identify critical molecular signatures and develop novel therapeutic targets for DKD. This study enrolled 10 datasets consisting of 93 renal samples from the National Center of Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). Networkanalyst, Enrichr, STRING, and Cytoscape were used to conduct the differentially expressed genes (DEGs) analysis, pathway enrichment analysis, protein-protein interaction (PPI) network construction, and hub gene screening. The shared DEGs of type 1 diabetic kidney disease (T1DKD) and type 2 diabetic kidney disease (T2DKD) datasets were performed to identify the shared vital pathways and hub genes. Strepotozocin-induced Type 1 diabetes mellitus (T1DM) rat model was prepared, followed by hematoxylin & eosin (HE) staining, and Oil Red O staining to observe the lipid-related morphological changes. The quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was conducted to validate the key DEGs of interest from a meta-analysis in the T1DKD rat. Using meta-analysis, 305 shared DEGs were obtained. Among the top 5 shared DEGs, Tmem43, Mpv17l, and Slco1a1, have not been reported relevant to DKD. Ketone body metabolism ranked in the top 1 in the KEGG enrichment analysis. Coasy, Idi1, Fads2, Acsl3, Oxct1, and Bdh1, as the top 10 down-regulated hub genes, were first identified to be involved in DKD. The qRT-PCR verification results of the novel hub genes were mostly consistent with the meta-analysis. The positive Oil Red O staining showed that the steatosis appeared in tubuloepithelial cells at 6 w after DM onset. Taken together, abnormal ketone body metabolism may be the key factor in the progression of DKD. Targeting metabolic abnormalities of ketone bodies may represent a novel therapeutic strategy for DKD. These identified novel molecular signatures in DKD merit further clinical investigation.

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Prepubertal onset of diabetes prevents expression of renal cortical connective tissue growth factor

Cited by 5 publications

References 56 publications

S100B is required for high glucose-induced pro-fibrotic gene expression and hypertrophy in mesangial cells

S100B is required for high glucose-induced pro-fibrotic gene expression and hypertrophy in mesangial cells

Glomerular Filtration Rate Following Pediatric Liver Transplantation—The SPLIT Experience

Identification of Novel Key Molecular Signatures in the Pathogenesis of Experimental Diabetic Kidney Disease

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