Jianbo Qing

Area of research

Nephrology · Molecular Biology

Research interest

Research topics from publications: A practical guide for nephrologist peer reviewers: understanding and appraising Mendelian randomization studies; Fucose as a potential therapeutic molecule against the immune-mediated inflammation in IgA nepharopathy: An unrevealed link; A review of the pharmacological activities and protective effects of Inonotus obliquus triterpenoids in kidney diseases; Gut microbiota implication in diabetic kidney disease: mechanisms and novel therapeutic strategies; Identification of Unique Genetic Biomarkers of Various Subtypes of Glomerulonephritis Using Machine Learning and Deep Learning; Deciphering the causal link between gut microbiota and membranous nephropathy: insights into potential inflammatory mechanisms. Representative work: Identifying risk factors for disease onset and progression has been a core focus in nephrology research. Mendelian Randomization (MR) has emerged as a powerful genetic epidemiological approach, utilizing genome-wide association studies (GWAS) to establish causal relationships between modifiable risk factors and kidney disease outcomes. MR uses genetic variants as instrumental variables to infer causal relationships between exposures and disease outcomes. This method leverages the natural randomization of genetic variants to balance confounders, akin to matched cohorts in observational research. The rapid increase in MR studies on kidney disease poses challenges for journals and peer reviewer Background: IgA nephropathy (IgAN) is an autoimmune disease that affects people of any age and is an important cause of end-stage renal disease. However, the pathogenesis and pathophysiology of IgAN is not clear. This article aimed to explore the immune-mediated inflammation and genetic mechanisms in IgAN. Methods: The transcriptome sequencing data of IgAN glomeruli in the Gene Expression Omnibus database were downloaded. Single-sample gene set enrichment analysis was used to estimate the immune microenvironment of the merged microarray data and GSE141295. IgAN samples were divided into two clusters by cluster analysis. "limma" and "DEseq2" package in R were used to identify differentially e

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