Evidence map›Paper›PMID 27575456›Full record

ArticleGene2016

Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.

Shijian Liu, James G Wilson, Fan Jiang, Michael Griswold, Adolfo Correa, Hao Mei

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Gene, 2016. 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
0.9field-weighted citation impact, top 18% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

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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

6 authors at 3 institutions in 2 countries.

Shijian LiuShanghai Children's Medical Center, School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai 200127, China. Electronic address: arrow64@163.com.
James G WilsonPhysiology & Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA. Electronic address: jgwilson2@umc.edu.
Fan JiangShanghai Children's Medical Center, School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai 200127, China. Electronic address: fanjiang@shsmu.edu.cn.
Michael GriswoldDepartment of Data Science, University of Mississippi Medical Center, Jackson, MS 39216, USA. Electronic address: mgriswold@umc.edu.
Adolfo CorreaJackson Heart Study, University of Mississippi Medical Center, Jackson, MS 39216, USA. Electronic address: ACorrea@umc.edu.
Hao MeiShanghai Children's Medical Center, School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai 200127, China; Department of Data Science, University of Mississippi Medical Center, Jackson, MS 39216, USA. Electronic address: hmei@umc.edu.
Jackson Memorial Hospital · USShanghai Children's Medical Center · CNUniversity of Mississippi Medical Center · US

Funding

NHLBI NIH HHS HHSN268201300046CNHLBI NIH HHS HHSN268201300047CNHLBI NIH HHS HHSN268201300048CNHLBI NIH HHS HHSN268201300049CNHLBI NIH HHS HHSN268201300050C
6 · The paper itself

Abstract

objectiveGenome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes.

methodsOur analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes.

resultsSingle-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk.

conclusionsOur study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes.

Indexed as

Polymorphism, Single NucleotideAdenylyl CyclasesBlack or African AmericanBlack PeopleBrain-Derived Neurotrophic FactorCase-Control StudiesCell Adhesion Molecules, NeuronalFemaleGPI-Linked ProteinsHaplotypesHumansMaleMembrane ProteinsNerve Tissue ProteinsObesityReceptor, Melanocortin, Type 4adenylate cyclase 3Adenylyl CyclasesBDNF protein, humanBrain-Derived Neurotrophic FactorCell Adhesion Molecules, Neuronalgastric inhibitory polypeptide receptorGPI-Linked ProteinsMC4R protein, humanMembrane ProteinsNEGR1 protein, humanNerve Tissue Proteinsneurexin IIIalphaReceptor, Melanocortin, Type 4Receptors, Gastrointestinal HormoneReceptors, NicotinicTFAP2B protein, humanTMEM18 protein, humanTranscription Factor AP-2Gene-gene interactionGenetic risk scoreHaplotypeObesitySNP association

Identifiers

PMID27575456
PMCPMC5235348
OpenAlexW2511458568

What OpenQuestion holds

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Registered trials

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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.