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Molecular Reclassification of Crohn’s Disease: A Cautionary Note on Population Stratification

Complex human diseases commonly differ in their phenotypic characteristics, e.g., Crohn’s disease (CD) patients are heterogeneous with regard to disease location and disease extent. The genetic susceptibility to Crohn’s disease is widely acknowledged and has been demonstrated by identification of ov...

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Autores principales: Maus, Bärbel, Jung, Camille, Mahachie John, Jestinah M., Hugot, Jean-Pierre, Génin, Emmanuelle, Van Steen, Kristel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798408/
https://www.ncbi.nlm.nih.gov/pubmed/24147066
http://dx.doi.org/10.1371/journal.pone.0077720
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author Maus, Bärbel
Jung, Camille
Mahachie John, Jestinah M.
Hugot, Jean-Pierre
Génin, Emmanuelle
Van Steen, Kristel
author_facet Maus, Bärbel
Jung, Camille
Mahachie John, Jestinah M.
Hugot, Jean-Pierre
Génin, Emmanuelle
Van Steen, Kristel
author_sort Maus, Bärbel
collection PubMed
description Complex human diseases commonly differ in their phenotypic characteristics, e.g., Crohn’s disease (CD) patients are heterogeneous with regard to disease location and disease extent. The genetic susceptibility to Crohn’s disease is widely acknowledged and has been demonstrated by identification of over 100 CD associated genetic loci. However, relating CD subphenotypes to disease susceptible loci has proven to be a difficult task. In this paper we discuss the use of cluster analysis on genetic markers to identify genetic-based subgroups while taking into account possible confounding by population stratification. We show that it is highly relevant to consider the confounding nature of population stratification in order to avoid that detected clusters are strongly related to population groups instead of disease-specific groups. Therefore, we explain the use of principal components to correct for population stratification while clustering affected individuals into genetic-based subgroups. The principal components are obtained using 30 ancestry informative markers (AIM), and the first two PCs are determined to discriminate between continental origins of the affected individuals. Genotypes on 51 CD associated single nucleotide polymorphisms (SNPs) are used to perform latent class analysis, hierarchical and Partitioning Around Medoids (PAM) cluster analysis within a sample of affected individuals with and without the use of principal components to adjust for population stratification. It is seen that without correction for population stratification clusters seem to be influenced by population stratification while with correction clusters are unrelated to continental origin of individuals.
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spelling pubmed-37984082013-10-21 Molecular Reclassification of Crohn’s Disease: A Cautionary Note on Population Stratification Maus, Bärbel Jung, Camille Mahachie John, Jestinah M. Hugot, Jean-Pierre Génin, Emmanuelle Van Steen, Kristel PLoS One Research Article Complex human diseases commonly differ in their phenotypic characteristics, e.g., Crohn’s disease (CD) patients are heterogeneous with regard to disease location and disease extent. The genetic susceptibility to Crohn’s disease is widely acknowledged and has been demonstrated by identification of over 100 CD associated genetic loci. However, relating CD subphenotypes to disease susceptible loci has proven to be a difficult task. In this paper we discuss the use of cluster analysis on genetic markers to identify genetic-based subgroups while taking into account possible confounding by population stratification. We show that it is highly relevant to consider the confounding nature of population stratification in order to avoid that detected clusters are strongly related to population groups instead of disease-specific groups. Therefore, we explain the use of principal components to correct for population stratification while clustering affected individuals into genetic-based subgroups. The principal components are obtained using 30 ancestry informative markers (AIM), and the first two PCs are determined to discriminate between continental origins of the affected individuals. Genotypes on 51 CD associated single nucleotide polymorphisms (SNPs) are used to perform latent class analysis, hierarchical and Partitioning Around Medoids (PAM) cluster analysis within a sample of affected individuals with and without the use of principal components to adjust for population stratification. It is seen that without correction for population stratification clusters seem to be influenced by population stratification while with correction clusters are unrelated to continental origin of individuals. Public Library of Science 2013-10-17 /pmc/articles/PMC3798408/ /pubmed/24147066 http://dx.doi.org/10.1371/journal.pone.0077720 Text en © 2013 Maus 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
Maus, Bärbel
Jung, Camille
Mahachie John, Jestinah M.
Hugot, Jean-Pierre
Génin, Emmanuelle
Van Steen, Kristel
Molecular Reclassification of Crohn’s Disease: A Cautionary Note on Population Stratification
title Molecular Reclassification of Crohn’s Disease: A Cautionary Note on Population Stratification
title_full Molecular Reclassification of Crohn’s Disease: A Cautionary Note on Population Stratification
title_fullStr Molecular Reclassification of Crohn’s Disease: A Cautionary Note on Population Stratification
title_full_unstemmed Molecular Reclassification of Crohn’s Disease: A Cautionary Note on Population Stratification
title_short Molecular Reclassification of Crohn’s Disease: A Cautionary Note on Population Stratification
title_sort molecular reclassification of crohn’s disease: a cautionary note on population stratification
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798408/
https://www.ncbi.nlm.nih.gov/pubmed/24147066
http://dx.doi.org/10.1371/journal.pone.0077720
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