MétaCan
Menu
Back to cohort
Record W2100675461 · doi:10.2337/db08-1514

Genome-Wide Association Scan for Diabetic Nephropathy Susceptibility Genes in Type 1 Diabetes

2009· article· en· W2100675461 on OpenAlexafffund
Marcus G. Pezzolesi, G. David Poznik, Josyf C. Mychaleckyj, Andrew D. Paterson, Michelle T. Barati, Jon B. Klein, Daniel P. K. Ng, Grzegorz Placha, Luís Henrique Santos Canani, Jacek Bocheński, Daryl Waggott, Michael L. Merchant, Bozena Krolewski, Lucia Mirea, Krzysztof Wanic, Pisut Katavetin, Masahiko Kure, Paweł Wołkow, Jonathon S. Dunn, Adam M. Smiles, William H. Walker, Andrew P. Boright, Shelley B. Bull, Alessandro Doria, John Rogus, Stephen S. Rich, James H. Warram, Andrzej S. Królewski

Bibliographic record

VenueDiabetes · 2009
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity Health NetworkUniversity of TorontoSickKids FoundationHospital for Sick ChildrenPublic Health Ontario
FundersNational Center for Research ResourcesNational Institute of Diabetes and Digestive and Kidney DiseasesCenters for Disease Control and PreventionU.S. Public Health ServiceCanadian Institutes of Health ResearchNational Institutes of HealthDivision of Diabetes, Endocrinology, and Metabolic DiseasesFoundation for the National Institutes of Health
KeywordsSingle-nucleotide polymorphismDiabetic nephropathyGenome-wide association studyDiabetes mellitusNephropathyMedicineType 1 diabetesGenetic predispositionInternal medicineOdds ratioGeneticsBiologyEndocrinologyDiseaseGenotypeGene

Abstract

fetched live from OpenAlex

OBJECTIVE: Despite extensive evidence for genetic susceptibility to diabetic nephropathy, the identification of susceptibility genes and their variants has had limited success. To search for genes that contribute to diabetic nephropathy, a genome-wide association scan was implemented on the Genetics of Kidneys in Diabetes collection. RESEARCH DESIGN AND METHODS: We genotyped approximately 360,000 single nucleotide polymorphisms (SNPs) in 820 case subjects (284 with proteinuria and 536 with end-stage renal disease) and 885 control subjects with type 1 diabetes. Confirmation of implicated SNPs was sought in 1,304 participants of the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, a long-term, prospective investigation of the development of diabetes-associated complications. RESULTS: A total of 13 SNPs located in four genomic loci were associated with diabetic nephropathy with P < 1 x 10(-5). The strongest association was at the FRMD3 (4.1 protein ezrin, radixin, moesin [FERM] domain containing 3) locus (odds ratio [OR] = 1.45, P = 5.0 x 10(-7)). A strong association was also identified at the CARS (cysteinyl-tRNA synthetase) locus (OR = 1.36, P = 3.1 x 10(-6)). Associations between both loci and time to onset of diabetic nephropathy were supported in the DCCT/EDIC study (hazard ratio [HR] = 1.33, P = 0.02, and HR = 1.32, P = 0.01, respectively). We demonstratedexpression of both FRMD3 and CARS in human kidney. CONCLUSIONS: We identified genetic associations for susceptibility to diabetic nephropathy at two novel candidate loci near the FRMD3 and CARS genes. Their identification implicates previously unsuspected pathways in the pathogenesis of this important late complication of type 1 diabetes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.251
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations291
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueDiabetesSame topicChronic Kidney Disease and DiabetesFrench-language works237,207