Evidence map›Paper›PMID 36624208›Full record

ArticleCommunications medicine2023

Identification of serum metabolome signatures associated with retinal and renal complications of type 2 diabetes.

Yoshihiko Tomofuji, Ken Suzuki, Toshihiro Kishikawa, Nobuhiro Shojima, Jun Hosoe, Kyoko Inagaki, Sunao Matsubayashi, Hisamitsu Ishihara, Hirotaka Watada, Yasushi Ishigaki and 7 more

Open access · goldAbstract read
In one paragraph

Article in Communications medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
5.9field-weighted citation impact, top 3% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 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

17 authors at 17 institutions in 2 countries.

Yoshihiko Tomofuji *Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan.ORCID http://orcid.org/0000-0002-1661-0941
Ken Suzuki *Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan.
Toshihiro KishikawaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan.
Nobuhiro ShojimaDepartment of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Jun HosoeDepartment of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Kyoko InagakiDivision of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Nippon Medical School, Tokyo, Japan.
Sunao MatsubayashiFukuoka Tokushukai Hospital, Fukuoka, Japan.
Hisamitsu IshiharaDivision of Diabetes and Metabolism, Nihon University School of Medicine, Tokyo, Japan.
Hirotaka WatadaDepartment of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Yasushi IshigakiDivision of Diabetes, Metabolism and Endocrinology, Iwate Medical University, Iwate, Japan.
BioBank Japan Project
Hidenori InoharaDepartment of Otorhinolaryngology-Head and Neck Surgery, Osaka University Graduate School of Medicine, Osaka, Japan.
Yoshinori MurakamiDivision of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
Koichi MatsudaDepartment of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
Yukinori OkadaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan. yokada@sg.med.osaka-u.ac.jp.ORCID http://orcid.org/0000-0002-0311-8472
Toshimasa YamauchiDepartment of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. tyamau@m.u-tokyo.ac.jp.
Takashi KadowakiDepartment of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. t-kadowaki@toranomon.kkr.or.jp.
The University of Tokyo · JPNihon University · JPFukuoka Tokushukai Hospital · JPIwate Medical University · JPJapan Agency for Medical Research and Development · JPJapan Anti Tuberculosis Association · JPJuntendo University · JPNippon Medical School · JPOsaka National Hospital · JPShiga University of Medical Science · JPUniversity of Tokyo Hospital · JPAichi Cancer Center · JPArthritis UK · GBAso Iizuka Hospital · JPThe University of Osaka · JPTokyo Metropolitan Geriatric Hospital · JPToranomon Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundType 2 diabetes is a common disease around the world and its major complications are diabetic retinopathy (DR) and diabetic kidney disease (DKD). Persons with type 2 diabetes with complications, especially who have both DR and DKD, have poorer prognoses than those without complications. Therefore, prevention and early identification of the complications of type 2 diabetes are necessary to improve the prognosis of persons with type 2 diabetes. The aim of this study is to identify factors associated with the development of multiple complications of type 2 diabetes.

methodsWe profiled serum metabolites of persons with type 2 diabetes with both DR and DKD (N = 141) and without complications (N = 159) using a comprehensive non-targeted metabolomics approach with mass spectrometry. Based on the serum metabolite profiles, case-control comparisons and metabolite set enrichment analysis (MSEA) were performed.

resultsHere we show that five metabolites (cyclohexylamine, P = 4.5 × 10

conclusionsOur metabolome analysis identifies the serum metabolite features of the persons with type 2 diabetes with multiple complications, which could potentially be used as biomarkers.

Identifiers

PMID36624208
PMCPMC9829655
OpenAlexW4313815603

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.