Evidence map›Paper›PMID 28687331›Full record

ArticleGene2017

A global evolutionary and metabolic analysis of human obesity gene risk variants.

Joseph J Castillo, Zachary S Hazlett, Robert A Orlando, William S Garver

Abstract read
In one paragraph

Article in Gene, 2017. 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

4 authors.

Joseph J CastilloDepartment of Biochemistry and Molecular Biology, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA.
Zachary S HazlettDepartment of Biochemistry and Molecular Biology, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA.
Robert A OrlandoDepartment of Biochemistry and Molecular Biology, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA.
William S GarverDepartment of Biochemistry and Molecular Biology, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA. Electronic address: wgarver@unm.edu.

Funding

UNM HSC Clinical and Translational Science CenterUL1TR001449 · NCATS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI CAMPEN, MATTHEW J, PANDHI, NANCY · 2015 to 2024
$36.9M
University of New Mexico Clinical and Translational Science CenterUL1TR000041 · NCATS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI LARSON, RICHARD S · 2012 to 2014
$9.8M
NCATS NIH HHS UL1 TR000041NCATS NIH HHS UL1 TR001449
6 · The paper itself

Abstract

It is generally accepted that the selection of gene variants during human evolution optimized energy metabolism that now interacts with our obesogenic environment to increase the prevalence of obesity. The purpose of this study was to perform a global evolutionary and metabolic analysis of human obesity gene risk variants (110 human obesity genes with 127 nearest gene risk variants) identified using genome-wide association studies (GWAS) to enhance our knowledge of early and late genotypes. As a result of determining the mean frequency of these obesity gene risk variants in 13 available populations from around the world our results provide evidence for the early selection of ancestral risk variants (defined as selection before migration from Africa) and late selection of derived risk variants (defined as selection after migration from Africa). Our results also provide novel information for association of these obesity genes or encoded proteins with diverse metabolic pathways and other human diseases. The overall results indicate a significant differential evolutionary pattern for the selection of obesity gene ancestral and derived risk variants proposed to optimize energy metabolism in varying global environments and complex association with metabolic pathways and other human diseases. These results are consistent with obesity genes that encode proteins possessing a fundamental role in maintaining energy metabolism and survival during the course of human evolution.

Indexed as

Evolution, MolecularGenetic Predisposition to DiseaseGenome, HumanMetabolic Networks and PathwaysPolymorphism, GeneticHumansObesityEnvironmentEvolutionMetabolismObesityVariants

Identifiers

PMID28687331
PMCPMC5558862

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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.