Evidence map›Paper›PMID 33164750›Full record

SynthesiseLife2020

Integration of genomics and transcriptomics predicts diabetic retinopathy susceptibility genes.

Andrew D Skol, Segun C Jung, Ana Marija Sokovic, Siquan Chen, Sarah Fazal, Olukayode Sosina, Poulami P Borkar, Amy Lin, Maria Sverdlov, Dingcai Cao and 5 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
3.6field-weighted citation impact, top 7% 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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 44 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Observational
  13. Review
  14. Review
  15. Review
  16. Multi-omics in exploring the pathophysiology of diabetic retinopathy.Frontiers in cell and developmental biology · 2024
    Review
  17. Article
  18. Long Non-Coding RNAs in Retinal Ganglion Cell Apoptosis.Cellular and molecular neurobiology · 2023
    Review
  19. Article
  20. 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

15 authors at 7 institutions in 1 country.

Andrew D SkolDepartment of Pathology and Laboratory Medicine, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, United States.
Segun C JungResearch and Development, NeoGenomics Laboratories, Aliso Viejo, United States.
Ana Marija SokovicUniversity of Illinois at Chicago, Chicago, United States.
Siquan ChenCellular Screening Center, Office of Shared Research Facilities, The University of Chicago, Chicago, United States.
Sarah FazalCellular Screening Center, Office of Shared Research Facilities, The University of Chicago, Chicago, United States.
Olukayode SosinaDepartment of Biostatistics, Johns Hopkins University, Baltimore, United States.
Poulami P BorkarUniversity of Illinois at Chicago, Chicago, United States.
Amy LinUniversity of Illinois at Chicago, Chicago, United States.
Maria SverdlovUniversity of Illinois at Chicago, Chicago, United States.
Dingcai CaoUniversity of Illinois at Chicago, Chicago, United States.
Anand SwaroopNational Eye Institute, National Institutes of Health (NIH), Bethesda, United States.ORCID 0000-0002-1975-1141
Ionut BebuThe George Washington University, Biostatistics Center, Rockville, United States.
DCCT/EDIC Study group
Barbara E StrangerDepartment of Pharmacology, Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, United States.
Michael A GrassiUniversity of Illinois at Chicago, Chicago, United States.ORCID 0000-0002-8467-3223
University of Illinois Chicago · USNational Institutes of Health · USNorthwestern University · USUniversity of Chicago · USGeorge Washington University · USLurie Children's Hospital · USNeoGenomics (United States) · US

Funding

Mechanisms, modeling and therapies of retinal and macular neurodegenerationZIAEY000546 · NEI · NATIONAL EYE INSTITUTE · PI SWAROOP, ANAND · 2015 to 2025
$36.3M
Translational Core for Therapeutic and Diagnostic DevelopmentP30EY001792 · NEI · UNIVERSITY OF ILLINOIS AT CHICAGO · PI SHUKLA, DEEPAK · 1985 to 2025
$14.8M
Role of Leukocyte-endothelial Adhesion in Diabetic RetinopathyR01EY023644 · NEI · UNIVERSITY OF ILLINOIS AT CHICAGO · PI GRASSI, MICHAEL A. · 2015 to 2019
$1.9M
Intramural NIH HHS ZIA EY000546NEI NIH HHS P30 EY001792NEI NIH HHS R01 EY023644
6 · The paper itself

Abstract

We determined differential gene expression in response to high glucose in lymphoblastoid cell lines derived from matched individuals with type 1 diabetes with and without retinopathy. Those genes exhibiting the largest difference in glucose response were assessed for association with diabetic retinopathy in a genome-wide association study meta-analysis. Expression quantitative trait loci (eQTLs) of the glucose response genes were tested for association with diabetic retinopathy. We detected an enrichment of the eQTLs from the glucose response genes among small association p-values and identified folliculin (

Indexed as

Gene Expression ProfilingPolymorphism, Single NucleotideTranscriptomeAdultCase-Control StudiesCell Line, TransformedDiabetes Mellitus, Type 1Diabetic RetinopathyFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyGlucoseHumansLymphocytesMaleMendelian Randomization AnalysisFLCN protein, humanGlucoseProto-Oncogene ProteinsTumor Suppressor Proteinsdiabetic retinopathyeQTLfolliculingene expressiongeneticsgenomicshumanLCLsmendelian randomization

Identifiers

PMID33164750
PMCPMC7728435
OpenAlexW3100904923

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.