Evidence mapPaperPMID 29258237Full record

ArticleGenes2017

Deciphering the Relationship between Obesity and Various Diseases from a Network Perspective.

Lei Chen, Yu-Hang Zhang, JiaRui Li, ShaoPeng Wang, YunHua Zhang, Tao Huang, Yu-Dong Cai

Open access · goldAbstract read
In one paragraph

Article in Genes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Inherited Epigenetic Hallmarks of Childhood Obesity Derived from Prenatal Exposure to Obesogens.International journal of environmental research and public health · 2023
    Review
  4. 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 3 institutions in 1 country.

Lei ChenSchool of Life Sciences, Shanghai University, Shanghai 200444, China. chen_lei1@163.com.ORCID 0000-0003-3068-1583
Yu-Hang ZhangInstitute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. zhangyh825@163.com.
JiaRui LiSchool of Life Sciences, Shanghai University, Shanghai 200444, China. jiaruili@shu.edu.cn.ORCID 0000-0002-0684-287X
ShaoPeng WangSchool of Life Sciences, Shanghai University, Shanghai 200444, China. wsptfb@163.com.
YunHua ZhangAnhui Province Key Lab of Farmland Ecological Conversation and Pollution Prevention, School of Resources and Environment, Anhui Agricultural University, Hefei 230036, China. yunhua9681@163.com.
Tao HuangInstitute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. tohuangtao@126.com.ORCID 0000-0003-1975-9693
Yu-Dong CaiSchool of Life Sciences, Shanghai University, Shanghai 200444, China. cai_yud@126.com.ORCID 0000-0001-5664-7979
Shanghai University · CNAnhui Agricultural University · CNChinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The number of obesity cases is rapidly increasing in developed and developing countries, thereby causing significant health problems worldwide. The pathologic factors of obesity at the molecular level are not fully characterized, although the imbalance between energy intake and consumption is widely recognized as the main reason for fat accumulation. Previous studies reported that obesity can be caused by the dysfunction of genes associated with other diseases, such as myocardial infarction, hence providing new insights into dissecting the pathogenesis of obesity by investigating its associations with other diseases. In this study, we investigated the relationship between obesity and diseases from Online Mendelian Inheritance in Man (OMIM) databases on the protein-protein interaction (PPI) network. The obesity genes and genes of one OMIM disease were mapped onto the network, and the interaction scores between the two gene sets were investigated on the basis of the PPI of individual gene pairs, thereby inferring the relationship between obesity and this disease. Results suggested that diseases related to nutrition and endocrine are the top two diseases that are closely associated with obesity. This finding is consistent with our general knowledge and indicates the reliability of our obtained results. Moreover, we inferred that diseases related to psychiatric factors and bone may also be highly related to obesity because the two diseases followed the diseases related to nutrition and endocrine according to our results. Numerous obesity-disease associations were identified in the literature to confirm the relationships between obesity and the aforementioned four diseases. These new results may help understand the underlying molecular mechanisms of obesity-disease co-occurrence and provide useful insights for disease prevention and intervention.

Indexed as

disease geneobesityOMIM disease classprotein–protein interaction

Identifiers

PMID29258237
PMCPMC5748710
OpenAlexW2779443159

What Socratic holds

Textmetadata
LicenceCC BY
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.