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

Area of Science:

• Medical imaging
• Radiology
• Metabolic syndrome research

Background:

• Adipose tissue distribution, specifically visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT), plays a crucial role in metabolic syndrome.
• Large-scale analysis of medical imaging data can reveal significant associations between adipose tissue volumes and health outcomes.

Purpose of the Study:

• To investigate the relationship between VAT and SAT volumes and various obesity-related diseases and clinical laboratory measures.
• To explore sex-specific differences in these associations.
• To assess the utility of existing Picture Archiving and Communication System (PACS) data for adipose tissue research.

Main Methods:

• Utilized a "greedy snake" algorithm to quantify VAT, SAT, total adipose tissue (TAT), and adipose ratio volumes from 2,545 abdominal computerized tomography (CT) images.
• Performed sex-combined and sex-stratified association testing between adipose measures and 1,233 disease diagnoses and 37 clinical laboratory measures.
• Conducted a genome-wide association study (GWAS) for adipose measures.

Main Results:

• SAT was strongly associated with obesity and morbid obesity.
• VAT showed significant associations with type 2 diabetes diagnoses, obstructive sleep apnea, and altered levels of HDL, triglycerides, and white blood cell counts.
• Associations between VAT and disease outcomes were stronger in women, suggesting a greater influence of visceral fat in this demographic.

Conclusions:

• Adipose tissue measures derived from medical imaging data are valuable for large-scale research into metabolic syndrome and obesity-related conditions.
• Further clinical and genetic discoveries can be facilitated by leveraging existing imaging datasets.
• The findings underscore the importance of adipose tissue distribution, particularly VAT, in metabolic health, with notable sex-specific differences.