Evidence map›Paper›PMID 24348998›Full record

ArticlePloS one2013

Genetic analysis of low BMI phenotype in the Utah Population Database.

William R Yates, Craig Johnson, Patrick McKee, Lisa A Cannon-Albright

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

William R YatesLaureate Institute for Brain Research, Tulsa, Oklahoma, United States of America ; University of Oklahoma College of Medicine, Tulsa, Tulsa, Oklahoma, United States of America.
Craig JohnsonEating Recovery Center, Denver, Colorado, United States of America.
Patrick McKeeLaureate Institute for Brain Research, Tulsa, Oklahoma, United States of America ; University of Oklahoma College of Medicine, Oklahoma City, Oklahoma, United States of America.
Lisa A Cannon-AlbrightDepartment of Medicine (Genetic Epidemiology), University of Utah School of Medicine, Salt Lake City, Utah, United States of America ; George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah, United States of America.

Funding

UTAH REGIONAL CANCER CENTERP30CA042014 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Jared P Rutter · 1986 to 2026
$72.6M
Analysis of the Familial Component to Disease in a Biomedical Resource w/Link...R01LM009331 · NLM · UNIVERSITY OF UTAH · PI ALBRIGHT, LISA CANNON · 2007 to 2010
$1.6M
NCI NIH HHS P30 CA042014NCI NIH HHS P30 CA42014NLM NIH HHS LM009331NLM NIH HHS R01 LM009331
6 · The paper itself

Abstract

The low body mass index (BMI) phenotype of less than 18.5 has been linked to medical and psychological morbidity as well as increased mortality risk. Although genetic factors have been shown to influence BMI across the entire BMI, the contribution of genetic factors to the low BMI phenotype is unclear. We hypothesized genetic factors would contribute to risk of a low BMI phenotype. To test this hypothesis, we conducted a genealogy data analysis using height and weight measurements from driver's license data from the Utah Population Data Base. The Genealogical Index of Familiality (GIF) test and relative risk in relatives were used to examine evidence for excess relatedness among individuals with the low BMI phenotype. The overall GIF test for excess relatedness in the low BMI phenotype showed a significant excess over expected (GIF 4.47 for all cases versus 4.10 for controls, overall empirical p-value<0.001). The significant excess relatedness was still observed when close relationships were ignored, supporting a specific genetic contribution rather than only a family environmental effect. This study supports a specific genetic contribution in the risk for the low BMI phenotype. Better understanding of the genetic contribution to low BMI holds promise for weight regulation and potentially for novel strategies in the treatment of leanness and obesity.

Indexed as

Body Mass IndexAdolescentAdultAgedAge DistributionDatabases, FactualFemaleGenetic Predisposition to DiseaseHumansMaleMiddle AgedPhenotypeUtahYoung Adult

Identifiers

PMID24348998
PMCPMC3859471

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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.