Evidence map›Paper›PMID 34291138›Full record

ArticleGenes & diseases2021

Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes.

Fengji Liang, Yuan Quan, Andong Wu, Ying Chen, Ruifeng Xu, Yuexing Zhu, Jianghui Xiong

Open access · diamondAbstract read
In one paragraph

Article in Genes & diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

7 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Epigenetics in Precision Nutrition.Journal of personalized medicine · 2022
    Review
  5. Article
  6. Article
  7. 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

7 authors at 4 institutions in 1 country.

Fengji LiangLab of Epigenetics and Advanced Health Technology, SPACEnter Space Science and Technology Institute, Shenzhen, Guangdong Province, 518117, PR China.
Yuan QuanLab of Epigenetics and Advanced Health Technology, SPACEnter Space Science and Technology Institute, Shenzhen, Guangdong Province, 518117, PR China.
Andong WuLab of Epigenetics and Advanced Health Technology, SPACEnter Space Science and Technology Institute, Shenzhen, Guangdong Province, 518117, PR China.
Ying ChenLab of Epigenetics and Advanced Health Technology, SPACEnter Space Science and Technology Institute, Shenzhen, Guangdong Province, 518117, PR China.
Ruifeng XuSchool of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong Province, 518055, PR China.
Yuexing ZhuLab of Epigenetics and Advanced Health Technology, SPACEnter Space Science and Technology Institute, Shenzhen, Guangdong Province, 518117, PR China.
Jianghui XiongLab of Epigenetics and Advanced Health Technology, SPACEnter Space Science and Technology Institute, Shenzhen, Guangdong Province, 518117, PR China.
China Academy of Space Technology · CNHarbin Institute of Technology · CNShenzhen Institute of Information Technology · CNWuhan Engineering Science & Technology Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insulin-resistance (IR) is one of the most important precursors of type 2 diabetes (T2D). Recent evidence suggests an association of depression with the onset of T2D. Accumulating evidence shows that depression and T2D share common biological origins, and DNA methylation examination might reveal the link between lifestyle, disease risk, and potential therapeutic targets for T2D. Here we hypothesize that integrative mining of IR and depression cohort data will facilitate predictive biomarkers identification for T2D. We utilized a newly proposed method to extract gene-level information from probe level data on genome-wide DNA methylation array. We identified a set of genes associated with IR and depression in clinical cohorts. By overlapping the IR-related nutraceutical-gene network with depression networks, we identified a common subnetwork centered with Vitamin D Receptor (VDR) gene. Preliminary clinical validation of gene methylation set in a small cohort of T2D patients and controls was established using the Sequenome matrix-assisted laser desorption ionization-time flight mass spectrometry. A set of sites in the promoter regions of VDR showed a significant difference between T2D patients and controls. Using a logistic regression model, the optimal prediction performance of these sites was AUC = 0.902,and an odds ratio = 19.76. Thus, monitoring the methylation status of specific VDR promoter region might help stratify the high-risk individuals who could potentially benefit from vitamin D dietary supplementation. Our results highlight the link between IR and depression, and the DNA methylation analysis might facilitate the search for their shared mechanisms in the etiology of T2D.

Indexed as

DepressionDNA methylationInsulin resistanceNutraceuticalsType 2 DiabetesVitamin D receptor

Identifiers

PMID34291138
PMCPMC8278533
OpenAlexW3003439489

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.