ReviewSeminars in nephrology2010
Linking variants from genome-wide association analysis to function via transcriptional network analysis.
Review in Seminars in nephrology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Molecular insights into genome-wide association studies of chronic kidney disease-defining traits.Nature communications · 2018Article
- Defining nephrotic syndrome from an integrative genomics perspective.Pediatric nephrology (Berlin, Germany) · 2015Review
- From single nucleotide polymorphism to transcriptional mechanism: a model for FRMD3 in diabetic nephropathy.Diabetes · 2013Article
- Genomic biomarkers for chronic kidney disease.Translational research : the journal of laboratory and clinical medicine · 2012Review
- Combining genome-wide association mapping and transcriptional networks to identify novel genes controlling glucosinolates in Arabidopsis thaliana.PLoS biology · 2011Article
- Integrative biology of renal disease: toward a holistic understanding of the kidney's function and failure.Seminars in nephrology · 2010Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
A current challenge in interpretation of genome-wide association studies is to establish the mechanistic links between the measured genotype and observed phenotype. The integration of gene expression with disease genome-wide association studies is emerging as an important strategy for deciphering these regulatory mechanisms. For renal disease, the availability of both tissue- and disease-specific expression data makes the strategy a compelling option. In this review, three approaches of integrating single nucleotide polymorphism (SNP) genotypes with transcriptional regulation are discussed as follows: (1) interpreting the functional role of transcripts affected by a SNP, (2) identifying the mechanistic role of noncoding SNPs in regulation, and (3) identifying regulatory candidate SNPs with expression associations. Combining these strategies in an integrative manner should allow the discovery of more extensive regulatory information. Linking genetics to systems biology more directly promises the opportunity to explain how genetic variants contribute to disease in a truly holistic manner.
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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.