ReviewNature reviews. Nephrology2020
Unravelling the complex genetics of common kidney diseases: from variants to mechanisms.
Review in Nature reviews. Nephrology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed.
- New potential therapeutic targets of metabolic disorder-associated kidney disease and diabetic kidney disease.Kidney international · 2026Review
- Single-section multiplex spatial proteomics of immune microenvironments in kidney transplantation.Frontiers in immunology · 2026Article
- The proteogenomic landscape of the human kidney and implications for cardio-kidney-metabolic health.Nature medicine · 2025 · on this mapArticle
- Multi-omics analysis identifies diagnostic circulating biomarkers and potential therapeutic targets, revealing IQGAP1 as an oncogene in gastric cancer.NPJ precision oncology · 2025Article
- Depth-corrected multi-factor dissection of chromatin accessibility for scATAC-seq data with PACS.Nature communications · 2025Article
- siRNA-mediated therapeutic approaches improve acute kidney injury and limit its worsening.Frontiers in pharmacology · 2025Review
- Chromatin accessibility: biological functions, molecular mechanisms and therapeutic application.Signal transduction and targeted therapy · 2024Review
- TET2 germline variants promote kidney disease by impairing DNA repair and activating cytosolic nucleotide sensors.Nature communications · 2024Article
- Multi-scalar data integration decoding risk genes for chronic kidney disease.BMC nephrology · 2024Article
- Update: the role of epigenetics in the metabolic memory of diabetic complications.American journal of physiology. Renal physiology · 2024Review
- Unraveling the epigenetic code: human kidney DNA methylation and chromatin dynamics in renal disease development.Nature communications · 2024Article
- Identification of genetic variants associated with diabetic kidney disease in multiple Korean cohorts via a genome-wide association study mega-analysis.BMC medicine · 2023Article
- Mini-organs with big impact: Organoids in liver cancer studies.Oncology research · 2023Review
- Modelling metabolic diseases and drug response using stem cells and organoids.Nature reviews. Endocrinology · 2022Review
- Comprehensive transcriptional variability analysis reveals gene networks regulating seed oil content of Brassica napus.Genome biology · 2022Article
- Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression.Nature communications · 2022Article
- Epigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease.Nature genetics · 2022Article
- Donor and recipient polygenic risk scores influence the risk of post-transplant diabetes.Nature medicine · 2022Article
- From mapping kidney function to mechanism and prediction.Nature reviews. Nephrology · 2022Article
- Harnessing the Full Potential of Multi-Omic Analyses to Advance the Study and Treatment of Chronic Kidney Disease.Frontiers in nephrology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Genome-wide association studies (GWAS) have identified hundreds of loci associated with kidney-related traits such as glomerular filtration rate, albuminuria, hypertension, electrolyte and metabolite levels. However, these impressive, large-scale mapping approaches have not always translated into an improved understanding of disease or development of novel therapeutics. GWAS have several important limitations. Nearly all disease-associated risk loci are located in the non-coding region of the genome and therefore, their target genes, affected cell types and regulatory mechanisms remain unknown. Genome-scale approaches can be used to identify associations between DNA sequence variants and changes in gene expression (quantified through bulk and single-cell methods), gene regulation and other molecular quantitative trait studies, such as chromatin accessibility, DNA methylation, protein expression and metabolite levels. Data obtained through these approaches, used in combination with robust computational methods, can deliver robust mechanistic inferences for translational exploitation. Understanding the genetic basis of common kidney diseases means having a comprehensive picture of the genes that have a causal role in disease development and progression, of the cells, tissues and organs in which these genes act to affect the disease, of the cellular pathways and mechanisms that drive disease, and of potential targets for disease prevention, detection and therapy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.