cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28509796
title: Comprehensive profiling of cell type-specific expression and distribution of complement genes in mouse and human kidneys: insights into normal physiology and response to kidney transplantations

description: Recent studies innovatively revealed the localized expression of complement genes in kidneys and shed light on the vital roles of the intracellular complement system in the physiologic function and pathological conditions. However, a comprehensive analysis of the expression of complement genes in the context of the evolving cellular landscape of the kidney is not available. We analyzed single-cell RNA sequencing data from healthy human subjects, C57BL/6 mice, and kidney transplant-rejected mice. The data were sourced from the NCBI Gene Expression Omnibus and processed using quality control measures and unsupervised clustering. Differential gene analyses were based on expression levels. In total, 50 complement genes were categorized into pattern recognition molecules, proteases, complement components, receptors, and regulators. In normal mice kidneys, complement genes were expressed at relatively low levels. Among different complement gene categories, receptor genes were most widely expressed in kidney cells. Comparatively, macrophages and mesangial cells are the most abundant immune and nonimmune cell types for complement gene expression. A comparison of human and mouse data showed similar expression patterns, but human kidney complement gene expression was more abundant. Comparative analysis between mouse transplant-rejected and normal kidneys demonstrated stronger complement gene expression in transplant-rejected kidneys. This study illustrated significant similarities in complement gene expression between murine and human kidneys and highlighted the responsive nature of complement genes to kidney injury, underscoring the dynamic nature of local complement regulation. These findings enhance our understanding of the complex regulation of the complement system within the kidney, offering insights into its role in renal disease pathogenesis.
DOI: 10.6084/m9.figshare.28509796.v1
title: Comprehensive profiling of cell type-specific expression and distribution of complement genes in mouse and human kidneys: insights into normal physiology and response to kidney transplantations

description: Recent studies innovatively revealed the localized expression of complement genes in kidneys and shed light on the vital roles of the intracellular complement system in the physiologic function and pathological conditions. However, a comprehensive analysis of the expression of complement genes in the context of the evolving cellular landscape of the kidney is not available. We analyzed single-cell RNA sequencing data from healthy human subjects, C57BL/6 mice, and kidney transplant-rejected mice. The data were sourced from the NCBI Gene Expression Omnibus and processed using quality control measures and unsupervised clustering. Differential gene analyses were based on expression levels. In total, 50 complement genes were categorized into pattern recognition molecules, proteases, complement components, receptors, and regulators. In normal mice kidneys, complement genes were expressed at relatively low levels. Among different complement gene categories, receptor genes were most widely expressed in kidney cells. Comparatively, macrophages and mesangial cells are the most abundant immune and nonimmune cell types for complement gene expression. A comparison of human and mouse data showed similar expression patterns, but human kidney complement gene expression was more abundant. Comparative analysis between mouse transplant-rejected and normal kidneys demonstrated stronger complement gene expression in transplant-rejected kidneys. This study illustrated significant similarities in complement gene expression between murine and human kidneys and highlighted the responsive nature of complement genes to kidney injury, underscoring the dynamic nature of local complement regulation. These findings enhance our understanding of the complex regulation of the complement system within the kidney, offering insights into its role in renal disease pathogenesis.
DOI: 10.6084/m9.figshare.28122228
title: Proteomics reveals the key transcription-related factors mediating obstructive nephropathy in pediatric patients and mice

description: Obstructive nephropathy is one of the leading causes of kidney injury in infants and children. Increasing evidence has shown that transcription-related factors (TRFs), including transcription factors and cofactors, are associated with kidney diseases. However, a global landscape of dysregulated TRFs in pediatric patients with obstructive nephropathy is lacking. We mined the data from our previous proteomic study for the TRF profile in pediatric patients with obstructive nephropathy and unilateral ureteral obstruction (UUO) mice. Gene ontology (GO) analysis was performed to determine pathways that were enriched in the dysregulated TRFs. We then took advantage of kidney samples from patients and UUO mice to verify the selected TRFs by immunoblots. The proteomes identified a total of 140 human TRFs with 28 upregulated and 1 downregulated, and 160 murine TRFs with 88 upregulated and 1 downregulated (fold change &gt;2 or &lt;0.5). These dysregulated TRFs were enriched in the inflammatory signalings, such as janus kinase/signal transducer and activator of transcription (JAK-STAT) and tumor necrosis factor (TNF) pathways. Of note, the transforming growth factor (TGF)-β signaling pathway, which is the master regulator of organ fibrosis, was enriched in both patients and mice. Cross-species analysis showed 16 key TRFs that might mediate obstructive nephropathy in patients and UUO mice. Moreover, we verified a significant dysregulation of three previously unexplored TRFs; prohibitin (PHB), regulatory factor X 1 (RFX1), and activity-dependent neuroprotector homeobox protein (ADNP), in patients and mice. Our study uncovered key TRFs in the obstructed kidneys and provided additional molecular insights into obstructive nephropathy.
DOI: 10.6084/m9.figshare.28122228.v1
title: Proteomics reveals the key transcription-related factors mediating obstructive nephropathy in pediatric patients and mice

description: Obstructive nephropathy is one of the leading causes of kidney injury in infants and children. Increasing evidence has shown that transcription-related factors (TRFs), including transcription factors and cofactors, are associated with kidney diseases. However, a global landscape of dysregulated TRFs in pediatric patients with obstructive nephropathy is lacking. We mined the data from our previous proteomic study for the TRF profile in pediatric patients with obstructive nephropathy and unilateral ureteral obstruction (UUO) mice. Gene ontology (GO) analysis was performed to determine pathways that were enriched in the dysregulated TRFs. We then took advantage of kidney samples from patients and UUO mice to verify the selected TRFs by immunoblots. The proteomes identified a total of 140 human TRFs with 28 upregulated and 1 downregulated, and 160 murine TRFs with 88 upregulated and 1 downregulated (fold change &gt;2 or &lt;0.5). These dysregulated TRFs were enriched in the inflammatory signalings, such as janus kinase/signal transducer and activator of transcription (JAK-STAT) and tumor necrosis factor (TNF) pathways. Of note, the transforming growth factor (TGF)-β signaling pathway, which is the master regulator of organ fibrosis, was enriched in both patients and mice. Cross-species analysis showed 16 key TRFs that might mediate obstructive nephropathy in patients and UUO mice. Moreover, we verified a significant dysregulation of three previously unexplored TRFs; prohibitin (PHB), regulatory factor X 1 (RFX1), and activity-dependent neuroprotector homeobox protein (ADNP), in patients and mice. Our study uncovered key TRFs in the obstructed kidneys and provided additional molecular insights into obstructive nephropathy.
DOI: 10.6084/m9.figshare.28942403
title: Immune cells mediate the effect of plasma lipidomes on IgA nephropathy: a Mendelian randomization study

description: IgA nephropathy (IgAN) is a leading cause of chronic kidney disease, often associated with dyslipidemia and immune dysfunction. This study employs Mendelian randomization (MR) to investigate the causal relationship between plasma lipidomes and IgAN, with a focus on the potential mediating role of immune cells. We analyzed the 179 genetically predicted plasma lipidomes and the IgAN gene using two-sample Mendelian randomization (TSMR) and multivariable MR based on summary-level data from a genome-wide association study, and the results were validated by liquid chromatography-mass spectrometry. Furthermore, we quantified the proportional effect of immune cell-mediated lipidomes on IgAN using TSMR. This study identified significant causal relationships of 3 lipidomes on IgAN risk by examining 179 lipidome traits as exposures. To investigate whether the impact of the 3 lipid groups on IgAN is specific, we performed TSMR analyses using 3 lipidomes as exposure factors and 4 nephritides as outcomes. Specifically, only phosphatidylinositol (18:1_20:4) was found to have a significant negative relationship with IgAN incidence (IVW method, <i>p</i> = 0.01, OR = 0.71, 95% CI = 0.55 - 0.92). Our further analysis focused on 8 immune cells associated with IgAN. We identified 2 immune cell phenotypes that may contribute to phosphatidylinositol (18:1_20:4)-mediated IgAN by careful screening. Our findings provide robust genetic evidence supporting a causal link between plasma lipidomes and IgAN, with immune cells acting as potential mediators. Phosphatidylinositol (18:1_20:4) emerges as a promising biomarker for IgAN risk stratification, early detection, and therapeutic intervention. Modulating its plasma levels may offer novel avenues for IgAN management.
DOI: 10.6084/m9.figshare.28942403.v1
title: Immune cells mediate the effect of plasma lipidomes on IgA nephropathy: a Mendelian randomization study

description: IgA nephropathy (IgAN) is a leading cause of chronic kidney disease, often associated with dyslipidemia and immune dysfunction. This study employs Mendelian randomization (MR) to investigate the causal relationship between plasma lipidomes and IgAN, with a focus on the potential mediating role of immune cells. We analyzed the 179 genetically predicted plasma lipidomes and the IgAN gene using two-sample Mendelian randomization (TSMR) and multivariable MR based on summary-level data from a genome-wide association study, and the results were validated by liquid chromatography-mass spectrometry. Furthermore, we quantified the proportional effect of immune cell-mediated lipidomes on IgAN using TSMR. This study identified significant causal relationships of 3 lipidomes on IgAN risk by examining 179 lipidome traits as exposures. To investigate whether the impact of the 3 lipid groups on IgAN is specific, we performed TSMR analyses using 3 lipidomes as exposure factors and 4 nephritides as outcomes. Specifically, only phosphatidylinositol (18:1_20:4) was found to have a significant negative relationship with IgAN incidence (IVW method, <i>p</i> = 0.01, OR = 0.71, 95% CI = 0.55 - 0.92). Our further analysis focused on 8 immune cells associated with IgAN. We identified 2 immune cell phenotypes that may contribute to phosphatidylinositol (18:1_20:4)-mediated IgAN by careful screening. Our findings provide robust genetic evidence supporting a causal link between plasma lipidomes and IgAN, with immune cells acting as potential mediators. Phosphatidylinositol (18:1_20:4) emerges as a promising biomarker for IgAN risk stratification, early detection, and therapeutic intervention. Modulating its plasma levels may offer novel avenues for IgAN management.
DOI: 10.6084/m9.figshare.29039708
title: Circ-0069561 as a novel diagnostic biomarker for progression of diabetic kidney disease

description: Circular RNAs (circRNAs) are non-coding RNAs that are key regulators of the initiation and progression of various human diseases. However, the role of circRNAs in diabetic kidney disease (DKD) remains unknown. Whole high-throughput RNA sequencing (RNA-seq) was performed on kidney tissues from clinical DKD patients and controls. Circ-0069561 with significantly up-regulated expression level was selected by real-time PCR (RT-PCR) analysis. RT-PCR and fluorescent <i>in situ</i> hybridization (FISH) further validated the expression and subcellular localization of circ-0069561 in type 2 diabetic mice and DKD patients. The clinical significance of circ-0069561 in DKD was evaluated. The circRNA-miRNA-ferroptosis associated mRNA network was constructed. The biological function of circ-0069561 in mouse podocyte clone 5 (MPC5) was analyzed. The top 10 up-regulated circular RNAs were selected by RT-PCR validation, and the results demonstrated a significant elevation in the expression level of circ-0069561. The RT-PCR and FISH results demonstrated that the expression of circ-0069561 was elevated in renal tissues of type 2 diabetic mice and DKD patients, with a predominant localization in glomerulus. The ROC curves showed that circ-0069561 had a good diagnostic value in massive proteinuria (area under the curve = 0.889). Kaplan-Meier analysis showed that high expression of circ-0069561 was associated with an increased risk of primary endpoints. The circRNA-miRNA-mRNA network indicated that ferroptosis might be involved in the pathogenesis of DKD. <i>In vitro</i> experiments demonstrated that circ-0069561 aggravated glucose-induced podocyte damage and ferroptosis. Circ-0069561 has the potential to be an ideal biomarker and therapeutic target for DKD progression.
DOI: 10.6084/m9.figshare.29039708.v1
title: Circ-0069561 as a novel diagnostic biomarker for progression of diabetic kidney disease

description: Circular RNAs (circRNAs) are non-coding RNAs that are key regulators of the initiation and progression of various human diseases. However, the role of circRNAs in diabetic kidney disease (DKD) remains unknown. Whole high-throughput RNA sequencing (RNA-seq) was performed on kidney tissues from clinical DKD patients and controls. Circ-0069561 with significantly up-regulated expression level was selected by real-time PCR (RT-PCR) analysis. RT-PCR and fluorescent <i>in situ</i> hybridization (FISH) further validated the expression and subcellular localization of circ-0069561 in type 2 diabetic mice and DKD patients. The clinical significance of circ-0069561 in DKD was evaluated. The circRNA-miRNA-ferroptosis associated mRNA network was constructed. The biological function of circ-0069561 in mouse podocyte clone 5 (MPC5) was analyzed. The top 10 up-regulated circular RNAs were selected by RT-PCR validation, and the results demonstrated a significant elevation in the expression level of circ-0069561. The RT-PCR and FISH results demonstrated that the expression of circ-0069561 was elevated in renal tissues of type 2 diabetic mice and DKD patients, with a predominant localization in glomerulus. The ROC curves showed that circ-0069561 had a good diagnostic value in massive proteinuria (area under the curve = 0.889). Kaplan-Meier analysis showed that high expression of circ-0069561 was associated with an increased risk of primary endpoints. The circRNA-miRNA-mRNA network indicated that ferroptosis might be involved in the pathogenesis of DKD. <i>In vitro</i> experiments demonstrated that circ-0069561 aggravated glucose-induced podocyte damage and ferroptosis. Circ-0069561 has the potential to be an ideal biomarker and therapeutic target for DKD progression.
DOI: 10.6084/m9.figshare.28449086.v1
title: Real-world assessment of sparsentan’s drug safety framework

description: Sparsentan has been approved for reducing proteinuria in adult patients with primary IgA nephropathy (IgAN) at risk of rapid disease progression, yet comprehensive studies evaluating its drug safety framework are lacking. Adverse event (AE) reports following the market release of sparsentan were collected from the U.S. Food and Drug Administration AE Reporting System. Disproportionate analysis was used to identify previously unrecognized positive novel signals at both the system organ class and preferred term levels. Additionally, analysis on clinical priorities and subgroup analysis were conducted. A total of 504 patients with IgAN were included. Two novel system organ classes and 14 novel preferred terms were identified. Hypotension and dizziness were established as moderate clinical priority events. Males had a higher relative risk of nausea, peripheral edema, feeling abnormal, decreased blood pressure, and hypotension, while females were at greater risk for fatigue, pain, increased blood creatinine, dizziness, and somnolence. Among those aged 18–45, the relative risk of experiencing fatigue, pain, and dizziness was higher, individuals aged 45 and older had a higher relative risk of peripheral edema, decreased blood pressure, and hypotension. Based on the available AE reporting data, sparsentan exhibits a favorable safety profile, with no high-priority clinical events identified. Our findings offer valuable insights to optimize the use of sparsentan and understand its potential side effects.
DOI: 10.6084/m9.figshare.29039714
title: Development and external validation of a machine learning model for cardiac valve calcification early screening in dialysis patients: a multicenter study

description: Cardiac valve calcification (CVC) is common in dialysis patients and associated with increased cardiovascular risk. However, early screening has been limited by cost concerns. This study aimed to develop and validate a machine learning model to enhance early detection of CVC. Data were collected at four centers between 2020 and 2023, including 852 dialysis patients in the development dataset and 661 in the external validation dataset. Predictive factors were selected using LASSO regression combined with univariate and multivariate analyses. Machine learning models including CatBoost, XGBoost, decision tree, support vector machine, random forest, and logistic regression were used to develop the CVC risk model. Model performance was evaluated in both validation sets. Risk thresholds were defined using the Youden index and validated in the external dataset. In the development dataset, 32.9% of patients were diagnosed with CVC. Age, dialysis duration, alkaline phosphatase, apolipoprotein A1, and intact parathyroid hormone were selected to construct the CVC risk prediction model. CatBoost exhibited the best performance in the training dataset. The logistic regression model demonstrated the best predictive performance in both internal and external validation sets, with AUROCs of 0.806 (95% CI 0.750–0.863) and 0.757 (95% CI 0.720–0.793), respectively. Calibration curves and decision curves confirmed its predictive accuracy and clinical applicability. The logistic regression model was selected as the optimal model and achieved excellent risk stratification in CVC risk prediction. The predictive model effectively identifies CVC risk in dialysis patients and offers a robust tool for early detection and improved management.
DOI: 10.6084/m9.figshare.29039714.v1
title: Development and external validation of a machine learning model for cardiac valve calcification early screening in dialysis patients: a multicenter study

description: Cardiac valve calcification (CVC) is common in dialysis patients and associated with increased cardiovascular risk. However, early screening has been limited by cost concerns. This study aimed to develop and validate a machine learning model to enhance early detection of CVC. Data were collected at four centers between 2020 and 2023, including 852 dialysis patients in the development dataset and 661 in the external validation dataset. Predictive factors were selected using LASSO regression combined with univariate and multivariate analyses. Machine learning models including CatBoost, XGBoost, decision tree, support vector machine, random forest, and logistic regression were used to develop the CVC risk model. Model performance was evaluated in both validation sets. Risk thresholds were defined using the Youden index and validated in the external dataset. In the development dataset, 32.9% of patients were diagnosed with CVC. Age, dialysis duration, alkaline phosphatase, apolipoprotein A1, and intact parathyroid hormone were selected to construct the CVC risk prediction model. CatBoost exhibited the best performance in the training dataset. The logistic regression model demonstrated the best predictive performance in both internal and external validation sets, with AUROCs of 0.806 (95% CI 0.750–0.863) and 0.757 (95% CI 0.720–0.793), respectively. Calibration curves and decision curves confirmed its predictive accuracy and clinical applicability. The logistic regression model was selected as the optimal model and achieved excellent risk stratification in CVC risk prediction. The predictive model effectively identifies CVC risk in dialysis patients and offers a robust tool for early detection and improved management.
DOI: 10.6084/m9.figshare.28319893
title: Prevalence of acute kidney injury in Mexico; a systematic review and meta-analysis of pre-pandemic reports

description: Acute Kidney Injury (AKI) is a health problem worldwide, accounting for high hospital morbidity and mortality. There is little available information regarding the characteristics and incidence of AKI in Latin America (LA), especially in Mexico. Systematically search the literature and perform a meta-analysis of the epidemiology of AKI in Mexico, to provide data on AKI and kidney replacement therapy (KRT) that would contribute to general knowledge in this matter. We performed a systematic search for articles in pediatric and adult patients admitted to the general ward, Emergency Room or Intensive Care Unit published between January 1, 2000, and September 30, 2024. MEDLINE LILIACS, EMBASE and SciELO were searched, as additional reports from supplements, abstracts, and conference sessions. We performed a random-effects meta-analysis for clinically and methodologically comparable studies to estimate the frequency of AKI and KRT. We calculated pooled estimates stratified by age group, year of publication, and setting. 83 full-text articles were included. The percentage of AKI was calculated at 35% (95% CI, 28–42). Mortality for AKI adult patients was 36% (95% CI, 28–45). An overall KRT rate was 7% (95% CI, 6–9), all-cause mortality for AKI requiring KRT was 49% (95% CI, 42–56), with a global Ι2 estimated in 99.87% (<i>p</i> &lt; 0.01). AKI is common in Mexico and remains a main public health problem that needs to be addressed at every level of care. Efforts should be made to reinitiate AKI research and control in Mexico and LA.