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Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery
The location and type of adipose tissue is an important factor in metabolic syndrome. A database of picture archiving and communication system (PACS) derived abdominal computerized tomography (CT) images from a large health care provider, Geisinger, was used for large-scale research of the relations...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6180992/ https://www.ncbi.nlm.nih.gov/pubmed/30363675 http://dx.doi.org/10.1155/2018/3253096 |
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author | Cha, Elliot D. K. Veturi, Yogasudha Agarwal, Chirag Patel, Aalpen Arbabshirani, Mohammad R. Pendergrass, Sarah A. |
author_facet | Cha, Elliot D. K. Veturi, Yogasudha Agarwal, Chirag Patel, Aalpen Arbabshirani, Mohammad R. Pendergrass, Sarah A. |
author_sort | Cha, Elliot D. K. |
collection | PubMed |
description | The location and type of adipose tissue is an important factor in metabolic syndrome. A database of picture archiving and communication system (PACS) derived abdominal computerized tomography (CT) images from a large health care provider, Geisinger, was used for large-scale research of the relationship of volume of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) with obesity-related diseases and clinical laboratory measures. Using a “greedy snake” algorithm and 2,545 CT images from the Geisinger PACS, we measured levels of VAT, SAT, total adipose tissue (TAT), and adipose ratio volumes. Sex-combined and sex-stratified association testing was done between adipose measures and 1,233 disease diagnoses and 37 clinical laboratory measures. A genome-wide association study (GWAS) for adipose measures was also performed. SAT was strongly associated with obesity and morbid obesity. VAT levels were strongly associated with type 2 diabetes-related diagnoses (p = 1.5 × 10(−58)), obstructive sleep apnea (p = 7.7 × 10(−37)), high-density lipoprotein (HDL) levels (p = 1.42 × 10(−36)), triglyceride levels (p = 1.44 × 10(−43)), and white blood cell (WBC) counts (p = 7.37 × 10(−9)). Sex-stratified tests revealed stronger associations among women, indicating the increased influence of VAT on obesity-related disease outcomes particularly among women. The GWAS identified some suggestive associations. This study supports the utility of pursuing future clinical and genetic discoveries with existing imaging data-derived adipose tissue measures deployed at a larger scale. |
format | Online Article Text |
id | pubmed-6180992 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-61809922018-10-24 Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery Cha, Elliot D. K. Veturi, Yogasudha Agarwal, Chirag Patel, Aalpen Arbabshirani, Mohammad R. Pendergrass, Sarah A. J Obes Research Article The location and type of adipose tissue is an important factor in metabolic syndrome. A database of picture archiving and communication system (PACS) derived abdominal computerized tomography (CT) images from a large health care provider, Geisinger, was used for large-scale research of the relationship of volume of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) with obesity-related diseases and clinical laboratory measures. Using a “greedy snake” algorithm and 2,545 CT images from the Geisinger PACS, we measured levels of VAT, SAT, total adipose tissue (TAT), and adipose ratio volumes. Sex-combined and sex-stratified association testing was done between adipose measures and 1,233 disease diagnoses and 37 clinical laboratory measures. A genome-wide association study (GWAS) for adipose measures was also performed. SAT was strongly associated with obesity and morbid obesity. VAT levels were strongly associated with type 2 diabetes-related diagnoses (p = 1.5 × 10(−58)), obstructive sleep apnea (p = 7.7 × 10(−37)), high-density lipoprotein (HDL) levels (p = 1.42 × 10(−36)), triglyceride levels (p = 1.44 × 10(−43)), and white blood cell (WBC) counts (p = 7.37 × 10(−9)). Sex-stratified tests revealed stronger associations among women, indicating the increased influence of VAT on obesity-related disease outcomes particularly among women. The GWAS identified some suggestive associations. This study supports the utility of pursuing future clinical and genetic discoveries with existing imaging data-derived adipose tissue measures deployed at a larger scale. Hindawi 2018-09-27 /pmc/articles/PMC6180992/ /pubmed/30363675 http://dx.doi.org/10.1155/2018/3253096 Text en Copyright © 2018 Elliot D. K. Cha et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Cha, Elliot D. K. Veturi, Yogasudha Agarwal, Chirag Patel, Aalpen Arbabshirani, Mohammad R. Pendergrass, Sarah A. Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery |
title | Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery |
title_full | Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery |
title_fullStr | Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery |
title_full_unstemmed | Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery |
title_short | Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery |
title_sort | using adipose measures from health care provider-based imaging data for discovery |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6180992/ https://www.ncbi.nlm.nih.gov/pubmed/30363675 http://dx.doi.org/10.1155/2018/3253096 |
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