Evidence map›Paper›PMID 31359159›Full record

ReviewCurrent diabetes reports2019

Genetics of Diabetic Retinopathy.

Jonathan Han, Leonardo Lando, Dorota Skowronska-Krawczyk, Daniel L Chao

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Current diabetes reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
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.

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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

4 authors.

Jonathan HanSchool of Medicine, University of California San Diego, La Jolla, San Diego, CA, USA.
Leonardo LandoShiley Eye Institute, Andrew Viterbi Department of Ophthalmology, University of California San Diego, 9415 Campus Point Dr, La Jolla, San Diego, CA, 92093, USA.
Dorota Skowronska-KrawczykShiley Eye Institute, Andrew Viterbi Department of Ophthalmology, University of California San Diego, 9415 Campus Point Dr, La Jolla, San Diego, CA, 92093, USA.
Daniel L ChaoShiley Eye Institute, Andrew Viterbi Department of Ophthalmology, University of California San Diego, 9415 Campus Point Dr, La Jolla, San Diego, CA, 92093, USA. dlchao@ucsd.edu.

Funding

Dissecting the role of ELOVL2 in Drusen Biogenesis and Age Related Macular DegenerationK08EY030510 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHAO, DANIEL L · 2019 to 2020
$482k
NEI NIH HHS K08 EY030510
6 · The paper itself

Abstract

purpose of reviewThe goal of this paper is to review the latest findings in understanding the genetics of diabetic retinopathy. We highlight recent literature using a variety of molecular genetic techniques to identify variants which contribute to genetic susceptibility for diabetic retinopathy. RECENT

findingsNew genome-wide association study (GWAS) and whole-exome sequencing approaches have been utilized to identify both common and rare variants associated with diabetic retinopathy. While variants have been identified in isolated studies, no variants have been replicated across multiple studies. The identification of genetic factors associated with diabetic retinopathy remains elusive. This is due to the multifactorial nature of the disease, small sample sizes for GWAS, and difficulty in controlling covariates of the disease. Larger populations as well as utilization of new sequencing and data analysis techniques may lead to new insights into genetic factors associated with diabetic retinopathy in the future.

Indexed as

Diabetic RetinopathyExome SequencingGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPharmacogeneticsDiabetic macular edemaDiabetic retinopathyGeneticsGWASWhole exome

Identifiers

PMID31359159
PMCPMC10292832

What Socratic 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 Socratic graph.