Evidence map›Paper›PMID 23900445›Full record

ArticleInternational journal of obesity (2005)2014

Genetic association analysis of 30 genes related to obesity in a European American population.

P Li, H K Tiwari, W-Y Lin, D B Allison, W K Chung, R L Leibel, N Yi, N Liu

Open access · bronzeAbstract read
In one paragraph

Article in International journal of obesity (2005), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 9% 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

50 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.

  1. Associations ofNutrients · 2019
    Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Association ofFrontiers in endocrinology · 2022
    Article
  12. Orexin, serotonin, and energy balance.WIREs mechanisms of disease · 2022
    Review
  13. Innate-Immunity Genes in Obesity.Journal of personalized medicine · 2021
    Review
  14. Article
  15. Dual Effect of theBalkan journal of medical genetics : BJMG · 2021
    Article
  16. Genetic Polymorphisms ofJournal of personalized medicine · 2021
    Article
  17. Article
  18. Review
  19. Article
  20. Review
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

8 authors at 3 institutions in 2 countries.

P LiDepartment of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.
H K TiwariDepartment of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.
W-Y LinInstitute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.
D B AllisonNutrition Obesity Research Center, University of Alabama at Birmingham, Birmingham, AL, USA.
W K Chung1] Columbia University Medical Center, New York, NY, USA [2] Naomi Berrie Diabetes Center, New York, NY, USA.
R L Leibel1] Columbia University Medical Center, New York, NY, USA [2] Naomi Berrie Diabetes Center, New York, NY, USA.
N YiDepartment of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.
N LiuDepartment of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.
University of Alabama at Birmingham · USColumbia University Irving Medical Center · USNational Taiwan University · TW

Funding

RESEARCH TRAININGP30DK026687 · NIDDK · ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS · PI Anthony W Ferrante, DYMPNA GALLAGHER · 1986 to 2026
$33.0M
Why is the prevalence of obesity so high in U.S. Southern States? Regional predictors of BMI and obesity treatment response.P30DK056336 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI James O Hill · 2000 to 2026
$31.9M
University of Alabama at Birmingham's Diabetes Research CenterP30DK079626 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Kirk Michael Habegger · 2013 to 2026
$19.5M
The molecular genetic analysis of human obesityR01DK052431 · NIDDK · ROCKEFELLER UNIVERSITY · PI CHUNG, WENDY K, LEIBEL, RUDOLPH L · 1996 to 2020
$11.6M
UAB Biostatistics Pre-doctoral Training ProgramT32HL079888 · NHLBI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI ALLISON, DAVID B, CUTTER, GARY R · 2005 to 2014
$2.3M
Genome Wide Haplotype Association AnalysisR01GM081488 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI LIU, NIANJUN · 2008 to 2012
$1.3M
Dell high performance computing cluster and associated Hitachi terabyte data storS10RR026723 · NCRR · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI ALLISON, DAVID B · 2010 to 2010
$500k
NCRR NIH HHS S10 RR026723NHLBI NIH HHS T32 HL079888NHLBI NIH HHS T32HL079888NIDDK NIH HHS P30 DK026687NIDDK NIH HHS P30 DK056336NIDDK NIH HHS P30 DK079626NIDDK NIH HHS P30 DK26687NIDDK NIH HHS R01 DK052431NIDDK NIH HHS R01DK52431NIGMS NIH HHS R01 GM081488NIGMS NIH HHS R01GM081488
6 · The paper itself

Abstract

objectiveObesity, which is frequently associated with diabetes, hypertension and cardiovascular diseases, is primarily the result of a net excess of caloric intake over energy expenditure. Human obesity is highly heritable, but the specific genes mediating susceptibility in non-syndromic obesity remain unclear. We tested candidate genes in pathways related to food intake and energy expenditure for association with body mass index (BMI).

methodsWe reanalyzed 355 common genetic variants of 30 candidate genes in seven molecular pathways related to obesity in 1982 unrelated European Americans from the New York Cancer Project. Data were analyzed by using a Bayesian hierarchical generalized linear model. The BMIs were log-transformed and then adjusted for covariates, including age, age(2), gender and diabetes status. The single-nucleotide polymorphisms (SNPs) were modeled as additive effects.

resultsWith the stipulated adjustments, nine SNPs in eight genes were significantly associated with BMI: ghrelin (GHRL; rs35683), agouti-related peptide (AGRP; rs5030980), carboxypeptidase E (CPE; rs1946816 and rs4481204), glucagon-like peptide-1 receptor (GLP1R; rs2268641), serotonin receptors (HTR2A; rs912127), neuropeptide Y receptor (NPY5R;Y5R1c52), suppressor of cytokine signaling 3 (SOCS3; rs4969170) and signal transducer and activator of transcription 3 (STAT3; rs4796793). We also found a gender-by-SNP interaction (rs1745837 in HTR2A), which indicated that variants in the gene HTR2A had a stronger association with BMI in males. In addition, NPY1R was detected as having a significant gene effect even though none of the SNPs in this gene was significant.

conclusionVariations in genes AGRP, CPE, GHRL, GLP1R, HTR2A, NPY1R, NPY5R, SOCS3 and STAT3 showed modest associations with BMI in European Americans. The pathways in which these genes participate regulate energy intake, and thus these associations are mechanistically plausible in this context.

Indexed as

AdultAgouti-Related ProteinBody CompositionBody Mass IndexCarbazolesEatingEnergy MetabolismFemaleGene FrequencyGenetic Predisposition to DiseaseGhrelinGlucagon-Like Peptide-1 ReceptorHumansMaleMorpholinesNew YorkAgouti-Related ProteinAGRP protein, humanCarbazolesGhrelinGHRL protein, humanGLP1R protein, humanGlucagon-Like Peptide-1 ReceptorMorpholinesneuropeptide Y-Y1 receptorNPY5RA 972Receptors, GlucagonReceptors, Neuropeptide YSOCS3 protein, humanSTAT3 protein, humanSTAT3 Transcription FactorSuppressor of Cytokine Signaling 3 ProteinSuppressor of Cytokine Signaling Proteins

Identifiers

PMID23900445
PMCPMC3909018
OpenAlexW2030427581

What OpenQuestion holds

Textmetadata
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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.