Evidence map›Paper›PMID 33520806›Full record

ArticleJournal of diabetes and metabolic disorders2020

Mechanistic dissection of diabetic retinopathy using the protein-metabolite interactome.

Ambrose Teru Patrick, Weilue He, Joshua Madu, Srinivas R Sripathi, Seulggie Choi, Kook Lee, Faith Pwaniyibo Samson, Folami L Powell, Manuela Bartoli, Donghyun Jee and 2 more

Open access · greenAbstract read
In one paragraph

Article in Journal of diabetes and metabolic disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

11 citing papers in PubMed, 11 citations in OpenAlex.

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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

12 authors at 5 institutions in 3 countries.

Ambrose Teru PatrickRetina Proteomics Laboratory, Department of Petroleum Chemistry, American University of Nigeria, Yola, Nigeria.
Weilue HeDepartment of Biomedical Engineering, Michigan Technological University, Houghton, MI USA.
Joshua MaduRetina Proteomics Laboratory, Department of Petroleum Chemistry, American University of Nigeria, Yola, Nigeria.
Srinivas R SripathiDepartment of Ophthalmology, Wilmer Eye Institute, The Johns Hopkins University School of Medicine, Baltimore, MD USA.
Seulggie ChoiDivision of Vitreous and Retina, Department of Ophthalmology, College of Medicine, St. Vincent's Hospital, The Catholic University of Korea, Suwon, Korea.
Kook LeeDivision of Vitreous and Retina, Department of Ophthalmology, College of Medicine, St. Vincent's Hospital, The Catholic University of Korea, Suwon, Korea.
Faith Pwaniyibo SamsonRetina Proteomics Laboratory, Department of Petroleum Chemistry, American University of Nigeria, Yola, Nigeria.
Folami L PowellDepartment of Biochemistry and Molecular Biology, Augusta University, Augusta, GA USA.
Manuela BartoliDepartment of Ophthalmology, Augusta University, Augusta, GA USA.
Donghyun JeeDivision of Vitreous and Retina, Department of Ophthalmology, College of Medicine, St. Vincent's Hospital, The Catholic University of Korea, Suwon, Korea.
Diana R GutsaevaDepartment of Ophthalmology, Augusta University, Augusta, GA USA.
Wan Jin JahngRetina Proteomics Laboratory, Department of Petroleum Chemistry, American University of Nigeria, Yola, Nigeria.
American University of Nigeria · NGAugusta University · USSt. Vincent's Hospital · KRJohns Hopkins University · USMichigan Technological University · US

Funding

Regulation of endogenous antioxidant systems in diabetic retinopathyR01EY022416 · NEI · AUGUSTA UNIVERSITY · PI BARTOLI, MANUELA · 2013 to 2017
$1.9M
NEI NIH HHS R01 EY022416
6 · The paper itself

Abstract

purposeThe current study aims to determine the molecular mechanisms of diabetic retinopathy (DR) using the protein-protein interactome and metabolome map. We examined the protein network of novel biomarkers of DR for direct (physical) and indirect (functional) interactions using clinical target proteins in different models.

methodsWe used proteomic tools including 2-dimensional gel electrophoresis, mass spectrometry analysis, and database search for biomarker identification using in vivo murine and human model of diabetic retinopathy and in vitro model of oxidative stress. For the protein interactome and metabolome mapping, various bioinformatic tools that include STRING and OmicsNet were used.

resultsWe uncovered new diabetic biomarkers including prohibitin (PHB), dynamin 1, microtubule-actin crosslinking factor 1, Toll-like receptor (TLR 7), complement activation, as well as hypothetical proteins that include a disintegrin and metalloproteinase (ADAM18), vimentin III, and calcium-binding C2 domain-containing phospholipid-binding switch (CAC2PBS) using a proteomic approach. Proteome networks of protein interactions with diabetic biomarkers were established using known DR-related proteome data. DR metabolites were interconnected to establish the metabolome map. Our results showed that mitochondrial protein interactions were changed during hyperglycemic conditions in the streptozotocin-treated murine model and diabetic human tissue.

conclusionsOur interactome mapping suggests that mitochondrial dysfunction could be tightly linked to various phases of DR pathogenesis including altered visual cycle, cytoskeletal remodeling, altered lipid concentration, inflammation, PHB depletion, tubulin phosphorylation, and altered energy metabolism. The protein-metabolite interactions in the current network demonstrate the etiology of retinal degeneration and suggest the potential therapeutic approach to treat DR.

Indexed as

ADAM18CAC2PBSDiabetic retinopathyInteractomeMetabolomeMitochondriaProhibitinProteomicsTubulin

Identifiers

PMID33520806
PMCPMC7843730
OpenAlexW3035985393

What Socratic holds

Textmetadata
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.