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Omic personality: implications of stable transcript and methylation profiles for personalized medicine
BACKGROUND: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4578259/ https://www.ncbi.nlm.nih.gov/pubmed/26391122 http://dx.doi.org/10.1186/s13073-015-0209-4 |
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author | Tabassum, Rubina Sivadas, Ambily Agrawal, Vartika Tian, Haozheng Arafat, Dalia Gibson, Greg |
author_facet | Tabassum, Rubina Sivadas, Ambily Agrawal, Vartika Tian, Haozheng Arafat, Dalia Gibson, Greg |
author_sort | Tabassum, Rubina |
collection | PubMed |
description | BACKGROUND: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N = 1 phenotypes. METHODS: Whole blood samples from four African American women, four Caucasian women, and four Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNA-Seq, miRNA-Seq, and Illumina Methylation 450 K arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. RESULTS: Longitudinal omic profiles were in general highly consistent over time, with an average of 67 % variance in transcript abundance, 42 % in CpG methylation level (but 88 % for the most differentiated CpG per gene), and 50 % in miRNA abundance among individuals, which are all comparable to 74 % variance among individuals for 74 clinical traits. One third of the variance could be attributed to differential blood cell type abundance, which was also fairly stable over time, and a lesser amount to expression quantitative trait loci (eQTL) effects. Seven conserved axes of covariance that capture diverse aspects of immune function explained over half of the variance. These axes also explained a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that were significantly up-regulated or down-regulated in each person and were in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes had individually divergent methylation levels, but these did not overlap with the transcripts, and fewer than 20 % of genes had significantly correlated methylation and gene expression. CONCLUSIONS: People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-015-0209-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4578259 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45782592015-09-23 Omic personality: implications of stable transcript and methylation profiles for personalized medicine Tabassum, Rubina Sivadas, Ambily Agrawal, Vartika Tian, Haozheng Arafat, Dalia Gibson, Greg Genome Med Research BACKGROUND: Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N = 1 phenotypes. METHODS: Whole blood samples from four African American women, four Caucasian women, and four Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNA-Seq, miRNA-Seq, and Illumina Methylation 450 K arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. RESULTS: Longitudinal omic profiles were in general highly consistent over time, with an average of 67 % variance in transcript abundance, 42 % in CpG methylation level (but 88 % for the most differentiated CpG per gene), and 50 % in miRNA abundance among individuals, which are all comparable to 74 % variance among individuals for 74 clinical traits. One third of the variance could be attributed to differential blood cell type abundance, which was also fairly stable over time, and a lesser amount to expression quantitative trait loci (eQTL) effects. Seven conserved axes of covariance that capture diverse aspects of immune function explained over half of the variance. These axes also explained a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that were significantly up-regulated or down-regulated in each person and were in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes had individually divergent methylation levels, but these did not overlap with the transcripts, and fewer than 20 % of genes had significantly correlated methylation and gene expression. CONCLUSIONS: People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-015-0209-4) contains supplementary material, which is available to authorized users. BioMed Central 2015-08-13 /pmc/articles/PMC4578259/ /pubmed/26391122 http://dx.doi.org/10.1186/s13073-015-0209-4 Text en © Tabassum et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Tabassum, Rubina Sivadas, Ambily Agrawal, Vartika Tian, Haozheng Arafat, Dalia Gibson, Greg Omic personality: implications of stable transcript and methylation profiles for personalized medicine |
title | Omic personality: implications of stable transcript and methylation profiles for personalized medicine |
title_full | Omic personality: implications of stable transcript and methylation profiles for personalized medicine |
title_fullStr | Omic personality: implications of stable transcript and methylation profiles for personalized medicine |
title_full_unstemmed | Omic personality: implications of stable transcript and methylation profiles for personalized medicine |
title_short | Omic personality: implications of stable transcript and methylation profiles for personalized medicine |
title_sort | omic personality: implications of stable transcript and methylation profiles for personalized medicine |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4578259/ https://www.ncbi.nlm.nih.gov/pubmed/26391122 http://dx.doi.org/10.1186/s13073-015-0209-4 |
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