Evidence map›Paper›PMID 28989171›Full record

ArticleNature reviews. Genetics2017

Convergence between biological, behavioural and genetic determinants of obesity.

Sujoy Ghosh, Claude Bouchard

Abstract read
PubMed Publisher
In one paragraph

Article in Nature reviews. Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
12.3field-weighted citation impact, top 1% 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

53 citing papers in PubMed, 109 citations in OpenAlex.

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  17. Resting energy expenditure of a diverse group of South African men and women.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2022
    Article
  18. A Hybrid MCDM Approach Based on Fuzzy-Logic and DEMATEL to Evaluate Adult Obesity.International journal of environmental research and public health · 2022
    Article
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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

2 authors at 2 institutions in 2 countries.

Sujoy GhoshCardiovascular and Metabolic Disorders Program and Center for Computational Biology, Duke-National University of Singapore Graduate Medical School, Singapore 169857, Singapore.
Claude BouchardHuman Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808-4124, USA.
National University of Singapore · SGPennington Biomedical Research Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.

Indexed as

AnimalsEpigenomicsFood PreferencesGene Expression RegulationHumansLife StyleObesityQuantitative Trait Loci

Identifiers

PMID28989171
OpenAlexW2761280283

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.