Evidence map›Paper›PMID 36035184›Full record

ArticleFrontiers in genetics2022

Genetic association-based functional analysis detects

Myungsuk Kim, Kye Won Park, Yeongseon Ahn, Eun Bi Lim, Soo Heon Kwak, Ahmad Randy, No Joon Song, Kyong Soo Park, Chu Won Nho, Yoon Shin Cho

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Myungsuk KimNatural Product Research Center, Korea Institute of Science and Technology, Gangneung, South Korea.
Kye Won ParkDepartment of Food Science and Biotechnology, Sungkyunkwan University, Suwon, South Korea.
Yeongseon AhnDepartment of Biomedical Science, Hallym University, Chuncheon, South Korea.
Eun Bi LimDepartment of Biomedical Science, Hallym University, Chuncheon, South Korea.
Soo Heon KwakDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.
Ahmad RandyNatural Product Research Center, Korea Institute of Science and Technology, Gangneung, South Korea.
No Joon SongDepartment of Food Science and Biotechnology, Sungkyunkwan University, Suwon, South Korea.
Kyong Soo ParkDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.
Chu Won NhoSmart Farm Research Center, Korea Institute of Science and Technology, Gangneung, South Korea.
Yoon Shin ChoDepartment of Biomedical Science, Hallym University, Chuncheon, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although there are a number of discoveries from genome-wide association studies (GWAS) for obesity, it has not been successful in linking GWAS results to biology. We sought to discover causal genes for obesity by conducting functional studies on genes detected from genetic association analysis. Gene-based association analysis of 917 individual exome sequences showed that

Indexed as

3T3-L1adipogenesisassociation analysisexome sequencingfunctional studyHOGA1obesity

Identifiers

PMID36035184
PMCPMC9412052

What OpenQuestion holds

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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.