Additional file 1: Figure S1. of Association between pulmonary function and renal function: findings from China and Australia

Dose-response relationship between adjusted estimated glomerular filtration rate (eGFR) and lung capacity measures among people with normal fasting glucose. Figure S2. Dose-response relationship between adjusted estimated glomerular filtration rate (eGFR) and lung capacity measures among people with metabolic syndrome or type 2 diabetes. Figure S3. Dose-response relationship between adjusted odds ratios for reduced renal function and lung capacity measures among people with normal fasting glucose. Figure S4. Dose-response relationship between adjusted odds ratios for reduced renal function and lung capacity measures among people with metabolic syndrome or type 2 diabetes. (DOCX 125040 kb

Image7_SGLT2 inhibitors suppress epithelial–mesenchymal transition in podocytes under diabetic conditions via downregulating the IGF1R/PI3K pathway.TIF

Loss of podocyte is a characteristic pathological change of diabetic nephropathy (DN) which is associated with increased proteinuria. Many studies have shown that novel inhibitors of sodium–glucose cotransporter 2 (SGLT2-is), such as dapagliflozin, exert nephroprotective effect on delaying DN progression. However, the mechanisms underlying SGLT2-associated podocyte injury are still not fully elucidated. Here, we generated streptozotocin-induced DN models and treated them with dapagliflozin to explore the possible mechanisms underlying SGLT2 regulation. Compared to mice with DN, dapagliflozin-treated mice exhibited remission of pathological lesions, including glomerular sclerosis, thickening of the glomerular basement membrane (GBM), podocyte injury in the glomeruli, and decreased nephrotoxin levels accompanied by decreased SGLT2 expression. The mRNA expression profiles of these treated mice revealed the significance of the insulin-like growth factor-1 receptor (IGF1R)/PI3K regulatory axis in glomerular injury. KEGG analysis confirmed that the phosphatidylinositol signaling system and insulin signaling pathway were enriched. Western blotting showed that SGLT2-is inhibited the increase of mesenchymal markers (α-SMA, SNAI-1, and ZEB2) and the loss of podocyte markers (nephrin and E-cad). Additionally, SGLT2, IGF1R, phosphorylated PI3K, α-SMA, SNAI-1, and ZEB2 protein levels were increased in high glucose-stimulated human podocytes (HPC) and significantly decreased in dapagliflozin-treated (50 nM and 100 nM) or OSI-906-treated (inhibitor of IGF1R, 60 nM) groups. However, the use of both inhibitors did not enhance this protective effect. Next, we analyzed urine and plasma samples from a cohort consisting of 13 healthy people and 19 DN patients who were administered with (n = 9) or without (n = 10) SGLT2 inhibitors. ELISA results showed decreased circulating levels of IGF1 and IGF2 in SGLT2-is-treated DN patients compared with DN patients. Taken together, our study reported the key role of SGLT2/IGF1R/PI3K signaling in regulating podocyte epithelial–mesenchymal transition (EMT). Modulating IGF1R expression may be a novel approach for DN therapy.</p

Table_1_Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes.docx

BackgroundImmunoglobulin A nephropathy (IgAN) is a highly prevalent glomerular disease. The diagnosis potential of the gut microbiome in IgAN has not been fully evaluated. Gut microbiota, serum metabolites, and clinical phenotype help to further deepen the understanding of IgAN.Patients and methodsCohort studies were conducted in healthy controls (HC), patients of IgA nephropathy (IgAN) and non-IgA nephropathy (n_IgAN). We used 16S rRNA to measure bacterial flora and non-targeted analysis methods to measure metabolomics; we then compared the differences in the gut microbiota between each group. The random forest method was used to explore the non-invasive diagnostic value of the gut microbiome in IgAN. We also compared serum metabolites and analyzed their correlation with the gut microbiome.ResultsThe richness and diversity of gut microbiota were significantly different among IgAN, n_IgAN and HC patients. Using a random approach, we constructed the diagnosis model and analysed the differentiation between IgAN and n_IgAN based on gut microbiota. The area under the receiver operating characteristic curve for the diagnosis was 0.9899. The metabolic analysis showed that IgAN patients had significant metabolic differences compared with HCs. In IgAN, catechol, l-tryptophan, (1H-Indol-3-yl)-N-methylmethanamine, and pimelic acid were found to be enriched. In the correlation analysis, l-tryptophan, blood urea nitrogen and Eubacterium coprostanoligenes were positively correlated with each other.ConclusionOur study demonstrated changes in the gut microbiota and established models for the non-invasive diagnosis of IgAN from HC and n_IgAN. We further demonstrated a close correlation between the gut flora, metabolites, and clinical phenotypes of IgAN. These findings provide further directions and clues in the study of the mechanism of IgAN.</p

Image_1_Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes.jpg

BackgroundImmunoglobulin A nephropathy (IgAN) is a highly prevalent glomerular disease. The diagnosis potential of the gut microbiome in IgAN has not been fully evaluated. Gut microbiota, serum metabolites, and clinical phenotype help to further deepen the understanding of IgAN.Patients and methodsCohort studies were conducted in healthy controls (HC), patients of IgA nephropathy (IgAN) and non-IgA nephropathy (n_IgAN). We used 16S rRNA to measure bacterial flora and non-targeted analysis methods to measure metabolomics; we then compared the differences in the gut microbiota between each group. The random forest method was used to explore the non-invasive diagnostic value of the gut microbiome in IgAN. We also compared serum metabolites and analyzed their correlation with the gut microbiome.ResultsThe richness and diversity of gut microbiota were significantly different among IgAN, n_IgAN and HC patients. Using a random approach, we constructed the diagnosis model and analysed the differentiation between IgAN and n_IgAN based on gut microbiota. The area under the receiver operating characteristic curve for the diagnosis was 0.9899. The metabolic analysis showed that IgAN patients had significant metabolic differences compared with HCs. In IgAN, catechol, l-tryptophan, (1H-Indol-3-yl)-N-methylmethanamine, and pimelic acid were found to be enriched. In the correlation analysis, l-tryptophan, blood urea nitrogen and Eubacterium coprostanoligenes were positively correlated with each other.ConclusionOur study demonstrated changes in the gut microbiota and established models for the non-invasive diagnosis of IgAN from HC and n_IgAN. We further demonstrated a close correlation between the gut flora, metabolites, and clinical phenotypes of IgAN. These findings provide further directions and clues in the study of the mechanism of IgAN.</p

Image_3_Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes.jpg

BackgroundImmunoglobulin A nephropathy (IgAN) is a highly prevalent glomerular disease. The diagnosis potential of the gut microbiome in IgAN has not been fully evaluated. Gut microbiota, serum metabolites, and clinical phenotype help to further deepen the understanding of IgAN.Patients and methodsCohort studies were conducted in healthy controls (HC), patients of IgA nephropathy (IgAN) and non-IgA nephropathy (n_IgAN). We used 16S rRNA to measure bacterial flora and non-targeted analysis methods to measure metabolomics; we then compared the differences in the gut microbiota between each group. The random forest method was used to explore the non-invasive diagnostic value of the gut microbiome in IgAN. We also compared serum metabolites and analyzed their correlation with the gut microbiome.ResultsThe richness and diversity of gut microbiota were significantly different among IgAN, n_IgAN and HC patients. Using a random approach, we constructed the diagnosis model and analysed the differentiation between IgAN and n_IgAN based on gut microbiota. The area under the receiver operating characteristic curve for the diagnosis was 0.9899. The metabolic analysis showed that IgAN patients had significant metabolic differences compared with HCs. In IgAN, catechol, l-tryptophan, (1H-Indol-3-yl)-N-methylmethanamine, and pimelic acid were found to be enriched. In the correlation analysis, l-tryptophan, blood urea nitrogen and Eubacterium coprostanoligenes were positively correlated with each other.ConclusionOur study demonstrated changes in the gut microbiota and established models for the non-invasive diagnosis of IgAN from HC and n_IgAN. We further demonstrated a close correlation between the gut flora, metabolites, and clinical phenotypes of IgAN. These findings provide further directions and clues in the study of the mechanism of IgAN.</p

Image_2_Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes.jpg

BackgroundImmunoglobulin A nephropathy (IgAN) is a highly prevalent glomerular disease. The diagnosis potential of the gut microbiome in IgAN has not been fully evaluated. Gut microbiota, serum metabolites, and clinical phenotype help to further deepen the understanding of IgAN.Patients and methodsCohort studies were conducted in healthy controls (HC), patients of IgA nephropathy (IgAN) and non-IgA nephropathy (n_IgAN). We used 16S rRNA to measure bacterial flora and non-targeted analysis methods to measure metabolomics; we then compared the differences in the gut microbiota between each group. The random forest method was used to explore the non-invasive diagnostic value of the gut microbiome in IgAN. We also compared serum metabolites and analyzed their correlation with the gut microbiome.ResultsThe richness and diversity of gut microbiota were significantly different among IgAN, n_IgAN and HC patients. Using a random approach, we constructed the diagnosis model and analysed the differentiation between IgAN and n_IgAN based on gut microbiota. The area under the receiver operating characteristic curve for the diagnosis was 0.9899. The metabolic analysis showed that IgAN patients had significant metabolic differences compared with HCs. In IgAN, catechol, l-tryptophan, (1H-Indol-3-yl)-N-methylmethanamine, and pimelic acid were found to be enriched. In the correlation analysis, l-tryptophan, blood urea nitrogen and Eubacterium coprostanoligenes were positively correlated with each other.ConclusionOur study demonstrated changes in the gut microbiota and established models for the non-invasive diagnosis of IgAN from HC and n_IgAN. We further demonstrated a close correlation between the gut flora, metabolites, and clinical phenotypes of IgAN. These findings provide further directions and clues in the study of the mechanism of IgAN.</p

Image4_SGLT2 inhibitors suppress epithelial–mesenchymal transition in podocytes under diabetic conditions via downregulating the IGF1R/PI3K pathway.TIF

Loss of podocyte is a characteristic pathological change of diabetic nephropathy (DN) which is associated with increased proteinuria. Many studies have shown that novel inhibitors of sodium–glucose cotransporter 2 (SGLT2-is), such as dapagliflozin, exert nephroprotective effect on delaying DN progression. However, the mechanisms underlying SGLT2-associated podocyte injury are still not fully elucidated. Here, we generated streptozotocin-induced DN models and treated them with dapagliflozin to explore the possible mechanisms underlying SGLT2 regulation. Compared to mice with DN, dapagliflozin-treated mice exhibited remission of pathological lesions, including glomerular sclerosis, thickening of the glomerular basement membrane (GBM), podocyte injury in the glomeruli, and decreased nephrotoxin levels accompanied by decreased SGLT2 expression. The mRNA expression profiles of these treated mice revealed the significance of the insulin-like growth factor-1 receptor (IGF1R)/PI3K regulatory axis in glomerular injury. KEGG analysis confirmed that the phosphatidylinositol signaling system and insulin signaling pathway were enriched. Western blotting showed that SGLT2-is inhibited the increase of mesenchymal markers (α-SMA, SNAI-1, and ZEB2) and the loss of podocyte markers (nephrin and E-cad). Additionally, SGLT2, IGF1R, phosphorylated PI3K, α-SMA, SNAI-1, and ZEB2 protein levels were increased in high glucose-stimulated human podocytes (HPC) and significantly decreased in dapagliflozin-treated (50 nM and 100 nM) or OSI-906-treated (inhibitor of IGF1R, 60 nM) groups. However, the use of both inhibitors did not enhance this protective effect. Next, we analyzed urine and plasma samples from a cohort consisting of 13 healthy people and 19 DN patients who were administered with (n = 9) or without (n = 10) SGLT2 inhibitors. ELISA results showed decreased circulating levels of IGF1 and IGF2 in SGLT2-is-treated DN patients compared with DN patients. Taken together, our study reported the key role of SGLT2/IGF1R/PI3K signaling in regulating podocyte epithelial–mesenchymal transition (EMT). Modulating IGF1R expression may be a novel approach for DN therapy.</p

Image9_SGLT2 inhibitors suppress epithelial–mesenchymal transition in podocytes under diabetic conditions via downregulating the IGF1R/PI3K pathway.TIF

Loss of podocyte is a characteristic pathological change of diabetic nephropathy (DN) which is associated with increased proteinuria. Many studies have shown that novel inhibitors of sodium–glucose cotransporter 2 (SGLT2-is), such as dapagliflozin, exert nephroprotective effect on delaying DN progression. However, the mechanisms underlying SGLT2-associated podocyte injury are still not fully elucidated. Here, we generated streptozotocin-induced DN models and treated them with dapagliflozin to explore the possible mechanisms underlying SGLT2 regulation. Compared to mice with DN, dapagliflozin-treated mice exhibited remission of pathological lesions, including glomerular sclerosis, thickening of the glomerular basement membrane (GBM), podocyte injury in the glomeruli, and decreased nephrotoxin levels accompanied by decreased SGLT2 expression. The mRNA expression profiles of these treated mice revealed the significance of the insulin-like growth factor-1 receptor (IGF1R)/PI3K regulatory axis in glomerular injury. KEGG analysis confirmed that the phosphatidylinositol signaling system and insulin signaling pathway were enriched. Western blotting showed that SGLT2-is inhibited the increase of mesenchymal markers (α-SMA, SNAI-1, and ZEB2) and the loss of podocyte markers (nephrin and E-cad). Additionally, SGLT2, IGF1R, phosphorylated PI3K, α-SMA, SNAI-1, and ZEB2 protein levels were increased in high glucose-stimulated human podocytes (HPC) and significantly decreased in dapagliflozin-treated (50 nM and 100 nM) or OSI-906-treated (inhibitor of IGF1R, 60 nM) groups. However, the use of both inhibitors did not enhance this protective effect. Next, we analyzed urine and plasma samples from a cohort consisting of 13 healthy people and 19 DN patients who were administered with (n = 9) or without (n = 10) SGLT2 inhibitors. ELISA results showed decreased circulating levels of IGF1 and IGF2 in SGLT2-is-treated DN patients compared with DN patients. Taken together, our study reported the key role of SGLT2/IGF1R/PI3K signaling in regulating podocyte epithelial–mesenchymal transition (EMT). Modulating IGF1R expression may be a novel approach for DN therapy.</p

Image_4_Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes.jpg

BackgroundImmunoglobulin A nephropathy (IgAN) is a highly prevalent glomerular disease. The diagnosis potential of the gut microbiome in IgAN has not been fully evaluated. Gut microbiota, serum metabolites, and clinical phenotype help to further deepen the understanding of IgAN.Patients and methodsCohort studies were conducted in healthy controls (HC), patients of IgA nephropathy (IgAN) and non-IgA nephropathy (n_IgAN). We used 16S rRNA to measure bacterial flora and non-targeted analysis methods to measure metabolomics; we then compared the differences in the gut microbiota between each group. The random forest method was used to explore the non-invasive diagnostic value of the gut microbiome in IgAN. We also compared serum metabolites and analyzed their correlation with the gut microbiome.ResultsThe richness and diversity of gut microbiota were significantly different among IgAN, n_IgAN and HC patients. Using a random approach, we constructed the diagnosis model and analysed the differentiation between IgAN and n_IgAN based on gut microbiota. The area under the receiver operating characteristic curve for the diagnosis was 0.9899. The metabolic analysis showed that IgAN patients had significant metabolic differences compared with HCs. In IgAN, catechol, l-tryptophan, (1H-Indol-3-yl)-N-methylmethanamine, and pimelic acid were found to be enriched. In the correlation analysis, l-tryptophan, blood urea nitrogen and Eubacterium coprostanoligenes were positively correlated with each other.ConclusionOur study demonstrated changes in the gut microbiota and established models for the non-invasive diagnosis of IgAN from HC and n_IgAN. We further demonstrated a close correlation between the gut flora, metabolites, and clinical phenotypes of IgAN. These findings provide further directions and clues in the study of the mechanism of IgAN.</p

Endothelin-receptor antagonist can reduce blood pressure in patients with hypertension: a meta-analysis

<p>The aim of this meta-analysis was to assess the effectiveness and safety of endothelin-receptor antagonist (ERA) in the patients with hypertension. Searches of the PubMed, EMBASE, and CENTRAL databases were conducted to include all the randomized control trials (RCTs). Eighteen trials including 4898 patients were used in the meta-analysis, of which nine were classified as low risk of bias and the other nine as unclear risk of bias. There was no statistically significant difference in all-cause mortality between ERA and placebo groups [6 trials, fixed effects model, RR 1.53 (0.89–2.62); random effects model, RR 1.45 (0.84–2.52)]. ERA significantly reduced 24-h ambulatory blood pressure and sitting blood pressure in patients with hypertension [5 trials, 24-h SBP: WMD −7.65 (−8.95 to −6.36), 24-h DBP: WMD −5.92 (−7.50 to −4.33); 18 trials, SBP: WMD −6.12 (−7.87 to −4.36), DBP: WMD −3.81 (−4.82 to −2.80)]. However, ERA had more adverse events [within 24 h: 3 trials, RR 1.16 (0.82–1.65); after 24 h, 13 trials, RR 1.21 (1.08–1.36)] and severe adverse events than placebo controls [SAE: 9 trials, RR 1.34 (1.13–1.60)]. In addition, there is a potential need for further RCTs that focus on the use of ERA in patients with hypertension.</p