Evidence map›Paper›PMID 25853885›Full record

ArticlePloS one2015

Effect of genome and environment on metabolic and inflammatory profiles.

Marina Sirota, Gonneke Willemsen, Purnima Sundar, Steven J Pitts, Shobha Potluri, Edi Prifti, Sean Kennedy, S Dusko Ehrlich, Jacoline Neuteboom, Cornelis Kluft and 4 more

Open access · goldAbstract readTwin Study
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 16% 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

10 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
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  5. Article
  6. Article
  7. Heritability of telomere variation: it is all about the environment!Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018
    Review
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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

14 authors at 5 institutions in 4 countries.

Marina SirotaRinat-Pfizer, South San Francisco, California, United States of America.
Gonneke WillemsenDepartment of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands.
Purnima SundarRinat-Pfizer, South San Francisco, California, United States of America.
Steven J PittsRinat-Pfizer, South San Francisco, California, United States of America.
Shobha PotluriRinat-Pfizer, South San Francisco, California, United States of America.
Edi PriftiINRA, Institut National de la Recherche Agronomique, Metagenopolis, Jouy-en-Josas, France.
Sean KennedyINRA, Institut National de la Recherche Agronomique, Metagenopolis, Jouy-en-Josas, France.
S Dusko EhrlichINRA, Institut National de la Recherche Agronomique, Metagenopolis, Jouy-en-Josas, France.
Jacoline NeuteboomGood Biomarker Sciences, Leiden, Netherlands.
Cornelis KluftGood Biomarker Sciences, Leiden, Netherlands.
Karen E MaloneGood Biomarker Sciences, Leiden, Netherlands.
David R CoxRinat-Pfizer, South San Francisco, California, United States of America.
Eco J C de GeusDepartment of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands.
Dorret I BoomsmaDepartment of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands.
Pfizer (United States) · USGBS Leiden · NLVrije Universiteit Amsterdam · NLDépartement Génétique Animale · FRInstitut National de la Recherche Agronomique · MA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Twin and family studies have established the contribution of genetic factors to variation in metabolic, hematologic and immunological parameters. The majority of these studies analyzed single or combined traits into pre-defined syndromes. In the present study, we explore an alternative multivariate approach in which a broad range of metabolic, hematologic, and immunological traits are analyzed simultaneously to determine the resemblance of monozygotic (MZ) twin pairs, twin-spouse pairs and unrelated, non-cohabiting individuals. A total of 517 participants from the Netherlands Twin Register, including 210 MZ twin pairs and 64 twin-spouse pairs, took part in the study. Data were collected on body composition, blood pressure, heart rate, and multiple biomarkers assessed in fasting blood samples, including lipid levels, glucose, insulin, liver enzymes, hematological measurements and cytokine levels. For all 51 measured traits, pair-wise Pearson correlations, correcting for family relatedness, were calculated across all the individuals in the cohort. Hierarchical clustering techniques were applied to group the measured traits into sub-clusters based on similarity. Sub-clusters were observed among metabolic traits and among inflammatory markers. We defined a phenotypic profile as the collection of all the traits measured for a given individual. Average within-pair similarity of phenotypic profiles was determined for the groups of MZ twin pairs, spouse pairs and pairs of unrelated individuals. The average similarity across the full phenotypic profile was higher for MZ twin pairs than for spouse pairs, and lowest for pairs of unrelated individuals. Cohabiting MZ twins were more similar in their phenotypic profile compared to MZ twins who no longer lived together. The correspondence in the phenotypic profile is therefore determined to a large degree by familial, mostly genetic, factors, while household factors contribute to a lesser degree to profile similarity.

Indexed as

EnvironmentGenome, HumanAdultCluster AnalysisFemaleHematologic TestsHousingHumansInflammationMalePhenotypeTwins, Monozygotic

Identifiers

PMID25853885
PMCPMC4390246
OpenAlexW2084946878

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.