Cha Elliot D K, Veturi Yogasudha, Agarwal Chirag, Patel Aalpen, Arbabshirani Mohammad R, Pendergrass Sarah A
Biomedical and Translational Informatics Institute, Geisinger Research, Danville, PA, USA.
Department of Imaging Science and Innovation, Geisinger Research, Danville, PA, USA.
J Obes. 2018 Sep 27;2018:3253096. doi: 10.1155/2018/3253096. eCollection 2018.
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 ( = 1.5 × 10), obstructive sleep apnea ( = 7.7 × 10), high-density lipoprotein (HDL) levels ( = 1.42 × 10), triglyceride levels ( = 1.44 × 10), and white blood cell (WBC) counts ( = 7.37 × 10). 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.
脂肪组织的位置和类型是代谢综合征的一个重要因素。利用来自大型医疗服务机构盖辛格的图片存档与通信系统(PACS)导出的腹部计算机断层扫描(CT)图像数据库,对皮下脂肪组织(SAT)和内脏脂肪组织(VAT)的体积与肥胖相关疾病及临床实验室指标之间的关系进行了大规模研究。我们使用“贪婪蛇”算法和来自盖辛格PACS的2545张CT图像,测量了VAT、SAT、总脂肪组织(TAT)和脂肪比例体积的水平。在脂肪测量指标与1233种疾病诊断和37项临床实验室指标之间进行了性别合并和按性别分层的关联测试。还对脂肪测量指标进行了全基因组关联研究(GWAS)。SAT与肥胖和病态肥胖密切相关。VAT水平与2型糖尿病相关诊断(=1.5×10)、阻塞性睡眠呼吸暂停(=7.7×10)、高密度脂蛋白(HDL)水平(=1.42×10)、甘油三酯水平(=1.44×10)和白细胞(WBC)计数(=7.37×10)密切相关。按性别分层的测试显示女性之间的关联更强,这表明VAT对肥胖相关疾病结局的影响增加,尤其是在女性中。GWAS确定了一些提示性关联。本研究支持利用现有成像数据得出的脂肪组织测量指标在更大规模上进行部署,以推动未来临床和基因发现的实用性。