Networks in Metabolic Syndrome and Cancer Using Clinical Metabolites (KoGES Korea Cohort)

Metabolic syndrome (MetS) is characterized by a cluster of comorbidities, including obesity, hyperglycemia, hypertension, elevated triglycerides, and low HDL cholesterol, increasing the risk of cardiovascular diseases and type 2 diabetes. Additionally, MetS significantly influences the development and prevalence of various cancers, the second leading cause of death globally. The Korean Genome and Epidemiology Study (KoGES) by the Korea Disease Control and Prevention Agency (KDCA) estimates cancer burden linked to modifiable risk factors like obesity and alcohol consumption, but these estimates are not comprehensive for MetS.Using a systems biology approach, this study created a dataset of 21 blood and urinary metabolites to evaluate MetS, tracking 211,575 individuals over ten years, with a final sample of 76,916 participants. The dataset, derived from KoGES, maps metabolite networks across various diseases, including diabetes mellitus, hypertension, hyperlipidemia, obesity, thyroid disorders, and ten types of cancer. This extensive data aims to build a large-scale network for assessing MetS and cancer patients globally, promoting advanced visualizations and further analyses.

代谢综合征（Metabolic Syndrome, MetS）以一组合并症群为特征，涵盖肥胖、高血糖、高血压、高甘油三酯血症及高密度脂蛋白胆固醇水平降低，可增加心血管疾病与2型糖尿病的发病风险。此外，代谢综合征还会显著影响多种癌症的发生与流行——癌症是全球第二大死亡原因。
由韩国疾病控制与预防机构（Korea Disease Control and Prevention Agency, KDCA）牵头开展的韩国基因组与流行病学研究（Korean Genome and Epidemiology Study, KoGES），曾针对肥胖、饮酒等可改变危险因素相关的癌症负担进行估算，但此类估算并未全面覆盖代谢综合征相关范畴。本研究采用系统生物学（Systems Biology）方法，构建了包含21种血液与尿液代谢物的数据集以评估代谢综合征，对211575名个体开展了长达10年的追踪研究，最终纳入76916名参与者的有效样本。该数据集源自韩国基因组与流行病学研究（KoGES），绘制了覆盖多种疾病的代谢物网络图谱，涵盖糖尿病、高血压、高脂血症、肥胖、甲状腺疾病及10种癌症。本数据集旨在构建用于全球范围内评估代谢综合征与癌症患者的大规模网络，以推动高级可视化分析与后续深入研究。