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Histopathological Image QTL Discovery of Immune Infiltration Variants
Genotype-to-phenotype association studies typically use macroscopic physiological measurements or molecular readouts as quantitative traits. There are comparatively few suitable quantitative traits available between cell and tissue length scales, a limitation that hinders our ability to identify var...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6123851/ https://www.ncbi.nlm.nih.gov/pubmed/30240647 http://dx.doi.org/10.1016/j.isci.2018.07.001 |
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author | Barry, Joseph D. Fagny, Maud Paulson, Joseph N. Aerts, Hugo J.W.L. Platig, John Quackenbush, John |
author_facet | Barry, Joseph D. Fagny, Maud Paulson, Joseph N. Aerts, Hugo J.W.L. Platig, John Quackenbush, John |
author_sort | Barry, Joseph D. |
collection | PubMed |
description | Genotype-to-phenotype association studies typically use macroscopic physiological measurements or molecular readouts as quantitative traits. There are comparatively few suitable quantitative traits available between cell and tissue length scales, a limitation that hinders our ability to identify variants affecting phenotype at many clinically informative levels. Here we show that quantitative image features, automatically extracted from histopathological imaging data, can be used for image quantitative trait loci (iQTLs) mapping and variant discovery. Using thyroid pathology images, clinical metadata, and genomics data from the Genotype-Tissue Expression (GTEx) project, we establish and validate a quantitative imaging biomarker for immune cell infiltration. A total of 100,215 variants were selected for iQTL profiling and tested for genotype-phenotype associations with our quantitative imaging biomarker. Significant associations were found in HDAC9 and TXNDC5. We validated the TXNDC5 association using GTEx cis-expression QTL data and an independent hypothyroidism dataset from the Electronic Medical Records and Genomics network. |
format | Online Article Text |
id | pubmed-6123851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-61238512018-09-17 Histopathological Image QTL Discovery of Immune Infiltration Variants Barry, Joseph D. Fagny, Maud Paulson, Joseph N. Aerts, Hugo J.W.L. Platig, John Quackenbush, John iScience Article Genotype-to-phenotype association studies typically use macroscopic physiological measurements or molecular readouts as quantitative traits. There are comparatively few suitable quantitative traits available between cell and tissue length scales, a limitation that hinders our ability to identify variants affecting phenotype at many clinically informative levels. Here we show that quantitative image features, automatically extracted from histopathological imaging data, can be used for image quantitative trait loci (iQTLs) mapping and variant discovery. Using thyroid pathology images, clinical metadata, and genomics data from the Genotype-Tissue Expression (GTEx) project, we establish and validate a quantitative imaging biomarker for immune cell infiltration. A total of 100,215 variants were selected for iQTL profiling and tested for genotype-phenotype associations with our quantitative imaging biomarker. Significant associations were found in HDAC9 and TXNDC5. We validated the TXNDC5 association using GTEx cis-expression QTL data and an independent hypothyroidism dataset from the Electronic Medical Records and Genomics network. Elsevier 2018-07-06 /pmc/articles/PMC6123851/ /pubmed/30240647 http://dx.doi.org/10.1016/j.isci.2018.07.001 Text en © 2018 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Barry, Joseph D. Fagny, Maud Paulson, Joseph N. Aerts, Hugo J.W.L. Platig, John Quackenbush, John Histopathological Image QTL Discovery of Immune Infiltration Variants |
title | Histopathological Image QTL Discovery of Immune Infiltration Variants |
title_full | Histopathological Image QTL Discovery of Immune Infiltration Variants |
title_fullStr | Histopathological Image QTL Discovery of Immune Infiltration Variants |
title_full_unstemmed | Histopathological Image QTL Discovery of Immune Infiltration Variants |
title_short | Histopathological Image QTL Discovery of Immune Infiltration Variants |
title_sort | histopathological image qtl discovery of immune infiltration variants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6123851/ https://www.ncbi.nlm.nih.gov/pubmed/30240647 http://dx.doi.org/10.1016/j.isci.2018.07.001 |
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