Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery

Joint Authors

Cha, Elliot D. K.
Veturi, Yogasudha
Agarwal, Chirag
Patel, Aalpen
Arbabshirani, Mohammad R.
Pendergrass, Sarah A.

Source

Journal of Obesity

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-15, 15 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-09-27

Country of Publication

Egypt

No. of Pages

15

Main Subjects

Medicine

Abstract EN

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.

American Psychological Association (APA)

Cha, Elliot D. K.& Veturi, Yogasudha& Agarwal, Chirag& Patel, Aalpen& Arbabshirani, Mohammad R.& Pendergrass, Sarah A.. 2018. Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery. Journal of Obesity،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1195933

Modern Language Association (MLA)

Cha, Elliot D. K.…[et al.]. Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery. Journal of Obesity No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1195933

American Medical Association (AMA)

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. Journal of Obesity. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1195933

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1195933