Evidence map›Paper›PMID 39716081›Full record

ArticleMolecular medicine (Cambridge, Mass.)2024

Uncovering the molecular networks of ferroptosis in the pathogenesis of type 2 diabetes and its complications: a multi-omics investigation.

Changqing Dong, Wuda Huoshen, Yunfeng Bai, Jiaona Liu, Bing Li, Yucan Guan, Ping Luo

Abstract read
In one paragraph

Article in Molecular medicine (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

8 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

7 authors.

Changqing DongDepartment of Nephrology, National Key Laboratory of Diabetes, The Second Hospital of Jilin University, No. 991 Yatai Street, Nanguan District, Changchun, Jilin, China.
Wuda HuoshenSchool of Stomatology, Southwest Medical University, Luzhou, Sichuan, China.
Yunfeng BaiDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China.
Jiaona LiuDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China.
Bing LiDepartment of Nephrology, National Key Laboratory of Diabetes, The Second Hospital of Jilin University, No. 991 Yatai Street, Nanguan District, Changchun, Jilin, China.
Yucan GuanDepartment of Nephrology, National Key Laboratory of Diabetes, The Second Hospital of Jilin University, No. 991 Yatai Street, Nanguan District, Changchun, Jilin, China.
Ping LuoDepartment of Nephrology, National Key Laboratory of Diabetes, The Second Hospital of Jilin University, No. 991 Yatai Street, Nanguan District, Changchun, Jilin, China. luoping@jlu.edu.cn.

Funding

National Natural Science Foundation of China 81970628National Natural Science Foundation of China 82200797Natural Science Foundation of Jilin Province YDZJ202401211ZYTS
6 · The paper itself

Abstract

backgroundDiabetes is a multi-factorial disorder and related complications constitute one of the principal causes of global mortality and disability. The role of ferroptosis in diabetes and its complications is intricate and significant. This study endeavors to disclose the role of ferroptosis in the aforementioned diseases from multiple perspectives through multi-omics.

methodsWe performed genetic correlation analyses via the Linkage Disequilibrium Score and High-Definition Likelihood approaches for type 2 diabetes (T2D) and its complications. The data concerning the expression of ferroptosis-related genes (FRGs) were obtained from the meta-analysis of studies on gene expression and protein abundance. Mendelian randomization analyses and cross-validation were implemented using the discovery cohort, replication cohort, and imaging genomics cohort of T2D and its complications. Moreover, we conducted colocalization analyses on T2D and tissue-specific single-cell RNA sequencing investigations on the complications to complement the results.

resultsGenetic association analysis indicated that the selected datasets could be incorporated into a secondary analysis of T2D complications. In the primary analysis, six FRGs (CDKN1A, ENO3, FURIN, RARRES2, TYRO3, and YTHDC2) were found to be positively associated with T2D risk. Conversely, eight FRGs (ARNTL, CAMKK2, CTSB, FADS2, KDM5A, MEG3, SREBF1, and STAT3) were inversely associated with T2D risk. The 14 FRGs were included in the secondary analysis. Within the FRGs, which received full support from both the discovery and replication cohorts, and were further validated by imaging genomics, higher levels of CDKN1A were positively associated with DKD risk. Higher levels of CAMKK2 and KDM5A were associated with a decreased risk of DKD. For DCM, higher levels of CTSB were positively associated with DCM risk. And genetically predicted higher levels of ARNTL and SREBF1 were associated with a decreased risk of NAFLD. Finally, we validated the tissue-specific expression of each complication with scRNA-seq datasets.

conclusionsThis study identified FRGs in relation to T2D and its complications, which may enhance the understanding of the pathogenic mechanisms of their development. Meanwhile, it offers cross-validation for imaging genomics and further indicates the direction for non-invasive diagnosis.

Indexed as

Diabetes Mellitus, Type 2FerroptosisComputational BiologyDiabetes ComplicationsFemaleGene Expression ProfilingGene Regulatory NetworksGenetic Association StudiesGenetic Predisposition to DiseaseGenomicsHumansMaleMultiomicsPolymorphism, Single NucleotideDiabetic complicationFerroptosisMendelian randomizationMulti-omicsNAFLDNon-invasive diagnosisType 2 diabetes

Identifiers

PMID39716081
PMCPMC11665190

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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.