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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...

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Autores principales: Cha, Elliot D. K., Veturi, Yogasudha, Agarwal, Chirag, Patel, Aalpen, Arbabshirani, Mohammad R., Pendergrass, Sarah A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
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.
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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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