ArticleHuman molecular genetics2012
Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function.
Article in Human molecular genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 4 of them syntheses that pooled it.
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
45 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- A catalog of genetic loci associated with kidney function from analyses of a million individuals.Nature genetics · 2019Pooled it
- 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function.Scientific reports · 2017Pooled it
- Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.Nature communications · 2016Pooled it
- Common variants in Mendelian kidney disease genes and their association with renal function.Journal of the American Society of Nephrology : JASN · 2013Pooled it
- Human C-terminal CUBN variants associate with chronic proteinuria and normal renal function.The Journal of clinical investigation · 2020Trial
- Evaluation of the Interaction of Amino Acid Infusion onClinical pharmacokinetics · 2019Trial
- Article
- Proximity Labeling Reveals How Lrp2 Interacts with the Endocytic Machine.Journal of proteome research · 2026Article
- Transcriptome- and proteome-wide association studies nominate determinants of kidney function and damage.Genome biology · 2023Article
- Article
- Analysis of Serum Advanced Glycation Endproducts Reveals Methylglyoxal-Derived Advanced Glycation MG-H1 Free Adduct Is a Risk Marker in Non-Diabetic and Diabetic Chronic Kidney Disease.International journal of molecular sciences · 2022Article
- AGEomics Biomarkers and Machine Learning-Realizing the Potential of Protein Glycation in Clinical Diagnostics.International journal of molecular sciences · 2022Review
- The genomic landscape of pediatric renal cell carcinomas.iScience · 2022Article
- Discovery of novel eGFR-associated multiple independent signals using a quasi-adaptive method.Frontiers in genetics · 2022Article
- Protein glycation - biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine.Redox biology · 2021Article
- Engulfment and cell motility 1 (ELMO1) and apolipoprotein A1 (APOA1) as candidate genes for sickle cell nephropathy.British journal of haematology · 2021Article
- Beyond the tubule: pathological variants ofAmerican journal of physiology. Renal physiology · 2020Article
- High fractional excretion of glycation adducts is associated with subsequent early decline in renal function in type 1 diabetes.Scientific reports · 2020Article
- Galnt11 regulates kidney function by glycosylating the endocytosis receptor megalin to modulate ligand binding.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Genome-Wide Association Study of Diabetic Kidney Disease Highlights Biology Involved in Glomerular Basement Membrane Collagen.Journal of the American Society of Nephrology : JASN · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
168 authors.
Funding
Abstract
In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10(-9)) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10(-4)-2.2 × 10(-7). Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.
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.