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Effect of Genome and Environment on Metabolic and Inflammatory Profiles

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...

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Autores principales: Sirota, Marina, Willemsen, Gonneke, Sundar, Purnima, Pitts, Steven J., Potluri, Shobha, Prifti, Edi, Kennedy, Sean, Ehrlich, S. Dusko, Neuteboom, Jacoline, Kluft, Cornelis, Malone, Karen E., Cox, David R., de Geus, Eco J. C., Boomsma, Dorret I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390246/
https://www.ncbi.nlm.nih.gov/pubmed/25853885
http://dx.doi.org/10.1371/journal.pone.0120898
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author Sirota, Marina
Willemsen, Gonneke
Sundar, Purnima
Pitts, Steven J.
Potluri, Shobha
Prifti, Edi
Kennedy, Sean
Ehrlich, S. Dusko
Neuteboom, Jacoline
Kluft, Cornelis
Malone, Karen E.
Cox, David R.
de Geus, Eco J. C.
Boomsma, Dorret I.
author_facet Sirota, Marina
Willemsen, Gonneke
Sundar, Purnima
Pitts, Steven J.
Potluri, Shobha
Prifti, Edi
Kennedy, Sean
Ehrlich, S. Dusko
Neuteboom, Jacoline
Kluft, Cornelis
Malone, Karen E.
Cox, David R.
de Geus, Eco J. C.
Boomsma, Dorret I.
author_sort Sirota, Marina
collection PubMed
description 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.
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spelling pubmed-43902462015-04-21 Effect of Genome and Environment on Metabolic and Inflammatory Profiles Sirota, Marina Willemsen, Gonneke Sundar, Purnima Pitts, Steven J. Potluri, Shobha Prifti, Edi Kennedy, Sean Ehrlich, S. Dusko Neuteboom, Jacoline Kluft, Cornelis Malone, Karen E. Cox, David R. de Geus, Eco J. C. Boomsma, Dorret I. PLoS One Research Article 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. Public Library of Science 2015-04-08 /pmc/articles/PMC4390246/ /pubmed/25853885 http://dx.doi.org/10.1371/journal.pone.0120898 Text en © 2015 Sirota et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Sirota, Marina
Willemsen, Gonneke
Sundar, Purnima
Pitts, Steven J.
Potluri, Shobha
Prifti, Edi
Kennedy, Sean
Ehrlich, S. Dusko
Neuteboom, Jacoline
Kluft, Cornelis
Malone, Karen E.
Cox, David R.
de Geus, Eco J. C.
Boomsma, Dorret I.
Effect of Genome and Environment on Metabolic and Inflammatory Profiles
title Effect of Genome and Environment on Metabolic and Inflammatory Profiles
title_full Effect of Genome and Environment on Metabolic and Inflammatory Profiles
title_fullStr Effect of Genome and Environment on Metabolic and Inflammatory Profiles
title_full_unstemmed Effect of Genome and Environment on Metabolic and Inflammatory Profiles
title_short Effect of Genome and Environment on Metabolic and Inflammatory Profiles
title_sort effect of genome and environment on metabolic and inflammatory profiles
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390246/
https://www.ncbi.nlm.nih.gov/pubmed/25853885
http://dx.doi.org/10.1371/journal.pone.0120898
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