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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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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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. |
format | Online Article Text |
id | pubmed-4390246 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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