Evidence map›Paper›PMID 20347642›Full record

ReviewSeminars in nephrology2010

Insights to the genetics of diabetic nephropathy through a genome-wide association study of the GoKinD collection.

Marcus G Pezzolesi, Jan Skupien, Josyf C Mychaleckyj, James H Warram, Andrzej S Krolewski

Open access · greenAbstract readReview
In one paragraph

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 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 17% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Review
  5. Multidrug resistance-associated protein 4 (Mrp4) is a novel genetic factor in the pathogenesis of obesity and diabetes.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2021
    Article
  6. Diabetic Kidney Disease: Challenges, Advances, and Opportunities.Kidney diseases (Basel, Switzerland) · 2020
    Review
  7. Article
  8. Review
  9. Aquaporin 11 variant associates with kidney disease in type 2 diabetic patients.American journal of physiology. Renal physiology · 2016
    Article
  10. Review
  11. Article
  12. Article
  13. Perspectives on systems biology applications in diabetic kidney disease.Journal of cardiovascular translational research · 2012
    Review
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Marcus G PezzolesiSection on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA.
Jan Skupien
Josyf C Mychaleckyj
James H Warram
Andrzej S Krolewski
Harvard University · USJoslin Diabetes Center · USOffice of Public Health Genomics · US

Funding

SPECIAL ASSAY COREP30DK036836 · NIDDK · JOSLIN DIABETES CENTER · PI JEAN E. SCHAFFER · 1986 to 2026
$50.5M
TRAINING IN DIABETES AND METABOLISMT32DK007260 · NIDDK · JOSLIN DIABETES CENTER · PI LAURIE J GOODYEAR · 1986 to 2026
$13.6M
Mapping Genes for End-Stage Renal Disease in Type 1 DiabetesR01DK077532 · NIDDK · JOSLIN DIABETES CENTER · PI KROLEWSKI, ANDRZEJ S · 2006 to 2008
$1.7M
NIDDK NIH HHS DK77532NIDDK NIH HHS P30 DK036836NIDDK NIH HHS R01 DK077532NIDDK NIH HHS T32 DK007260NIDDK NIH HHS T32 DK007260-31PHS HHS 106-554PHS HHS 107-360PHS HHS PL 105-33
6 · The paper itself

Abstract

The Genetics of Kidneys in Diabetes (GoKinD) study was initiated to facilitate research aimed at identifying genes involved in diabetic nephropathy (DN) in type 1 diabetes. In this review, we present an overview of this study and the various reports that have used its collection. At the forefront of these efforts is the recent genome-wide association scan implemented on the GoKinD collection. We highlight the results from our analysis of these data and describe compelling evidence from animal models that further support the potential role of associated loci in the susceptibility of DN. To enhance our analysis of genetic associations in GoKinD, using genome-wide imputation, we expanded our analysis of this collection to include genotype data from more than 2.4 million common single nucleotide polymorphisms. We illustrate the added utility of this enhanced dataset through the comprehensive fine-mapping of candidate genomic regions previously linked with DN and the targeted investigation of genes involved in candidate pathways implicated in its pathogenesis. Collectively, genome-wide association and genome-wide imputation data from the GoKinD collection will serve as a springboard for future investigations into the genetic basis of DN in type 1 diabetes.

Indexed as

AnimalsDiabetic NephropathiesDisease Models, AnimalGenome-Wide Association StudyHumansRegistries

Identifiers

PMID20347642
PMCPMC2847588
OpenAlexW2060134681

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.