Evidence map›Paper›PMID 31167214›Full record

ArticleHuman heredity2018

The Promise of Selecting Individuals from the Extremes of Exposure in the Analysis of Gene-Physical Activity Interactions.

Oyomoare L Osazuwa-Peters, Karen Schwander, R J Waken, Lisa de las Fuentes, Tuomas O Kilpeläinen, Ruth J F Loos, Susan B Racette, Yun Ju Sung, D C Rao

Abstract read
In one paragraph

Article in Human heredity, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Oyomoare L Osazuwa-PetersDivision of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA, oosazuwa-peters@wustl.edu.
Karen SchwanderDivision of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA.
R J WakenDivision of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA.
Lisa de las FuentesDivision of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA.
Tuomas O KilpeläinenNovo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Ruth J F LoosIcahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, New York, USA.
Susan B RacetteProgram in Physical Therapy, Washington University School of Medicine, St. Louis, Missouri, USA.
Yun Ju SungDivision of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA.
D C RaoDivision of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA.

Funding

A Multi-Ethnic Study of Gene-Lifestyle Interactions in Cardiovascular TraitsR01HL118305 · NHLBI · WASHINGTON UNIVERSITY · PI RAO, DABEERU C · 2014 to 2017
$8.3M
Post-Doctoral Research Training in Genetic EpidemiologyT32HL091823 · NHLBI · WASHINGTON UNIVERSITY · PI RAO, DABEERU C · 2008 to 2017
$2.1M
SLEEP AND ENTRAINMENT OF SCN FUNCTIONR01HL064278 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI STROHL, KINGMAN PERKINS · 1999 to 2002
$871k
STATISTICAL METHODS FOR GENOMIC DISSECTION OF CARDIOVASCULAR DISEASESK25HL121091 · NHLBI · WASHINGTON UNIVERSITY · PI SUNG, YUNJU · 2014 to 2018
$760k
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NHLBI NIH HHS K25 HL121091NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N02 HL064278NHLBI NIH HHS R01 HL118305NHLBI NIH HHS T32 HL091823
6 · The paper itself

Abstract

backgroundDichotomization using the lower quartile as cutoff is commonly used for harmonizing heterogeneous physical activity (PA) measures across studies. However, this may create misclassification and hinder discovery of new loci.

objectivesThis study aimed to evaluate the performance of selecting individuals from the extremes of the exposure (SIEE) as an alternative approach to reduce such misclassification.

methodFor systolic and diastolic blood pressure in the Framingham Heart Study, we performed a genome-wide association study with gene-PA interaction analysis using three PA variables derived by SIEE and two other dichotomization approaches. We compared number of loci detected and overlap with loci found using a quantitative PA variable. In addition, we performed simulation studies to assess bias, false discovery rates (FDR), and power under synergistic/antagonistic genetic effects in exposure groups and in the presence/absence of measurement error.

resultsIn the empirical analysis, SIEE's performance was neither the best nor the worst. In most simulation scenarios, SIEE was consistently outperformed in terms of FDR and power. Particularly, in a scenario characterized by antagonistic effects and measurement error, SIEE had the least bias and highest power.

conclusionSIEE's promise appears limited to detecting loci with antagonistic effects. Further studies are needed to evaluate SIEE's full advantage.

Indexed as

ExerciseGenome-Wide Association StudyBiasBlood PressureComputer SimulationData AnalysisGenetic LociHumansSystoleComputer simulationsDichotomizationGene-physical activity interactionsMisclassificationSelecting individuals at extremes of exposure

Identifiers

PMID31167214
PMCPMC6662918

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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.