Biomarkers may contribute to our understanding of the pathophysiology of various diseases. Type 2 diabetes (T2D) and coronary heart disease (CHD) share many clinical and lifestyle risk factors and several biomarkers are associated with both diseases. The current analysis aims to assess the relevance of biomarkers combined to pathway groups for the development of T2D and CHD in the same cohort. Forty-seven serum biomarkers were measured in the MONICA/KORA case-cohort study using clinical chemistry assays and ultrasensitive molecular counting technology. The T2D (CHD) analyses included 689 (568) incident cases and 1850 (2004) non-cases from three population-based surveys. At baseline, the study participants were 35–74 years old. The median follow-up was 14 years. We computed Cox regression models for each biomarker, adjusted for age, sex, and survey. Additionally, we assigned the biomarkers to 19 etiological pathways based on information from literature. One age-, sex-, and survey-controlled average variable was built for each pathway. We used the R2PM coefficient of determination to assess the explained disease risk. The associations of many biomarkers, such as several cytokines or the iron marker soluble transferrin receptor (sTfR), were similar in strength for T2D and CHD, but we also observed important differences. Lipoprotein (a) (Lp(a)) and N-terminal pro B-type natriuretic peptide (NT-proBNP) even demonstrated opposite effect directions. All pathway variables together explained 49% of the T2D risk and 21% of the CHD risk. The insulin-like growth factor binding protein 2 (IGFBP-2, IGF/IGFBP system pathway) best explained the T2D risk (about 9% explained risk, independent of all other pathway variables). For CHD, the myocardial-injury- and lipid-related-pathways were most important and both explained about 4% of the CHD risk. The biomarker-derived pathway variables explained a higher proportion of the T2D risk compared to CHD. The ranking of the pathways differed between the two diseases, with the IGF/IGFBP-system-pathway being most strongly associated with T2D and the myocardial-injury- and lipid-related-pathways with CHD. Our results help to better understand the pathophysiology of the two diseases, with the ultimate goal of pointing out targets for lifestyle intervention and drug development to ideally prevent both T2D and CHD development.

中文翻译：

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生物标志物定义的2型糖尿病和冠心病事件的途径-在MONICA / KORA研究中进行比较。

生物标志物可能有助于我们对各种疾病的病理生理学的理解。2型糖尿病（T2D）和冠心病（CHD）具有许多临床和生活方式风险因素，并且两种生物标志物均与这两种疾病相关。目前的分析旨在评估在同一队列中，结合生物标志物与途径群发展T2D和CHD的相关性。在MONICA / KORA病例队列研究中，使用临床化学测定法和超灵敏分子计数技术测量了47种血清生物标志物。T2D（CHD）分析包括来自三个基于人口的调查的689（568）个事件案例和1850（2004）个非案例。基线时，研究参与者年龄在35-74岁之间。中位随访时间为14年。我们针对每种生物标记物计算了Cox回归模型，并根据年龄，性别和调查进行了调整。此外，我们根据文献资料将生物标志物分配给了19种病因学途径。为每种途径建立一个年龄，性别和调查控制的平均变量。我们使用测定的R2PM系数来评估解释的疾病风险。许多生物标志物的关联，例如几种细胞因子或铁标志物可溶性转铁蛋白受体（sTfR），在T2D和CHD的强度上相似，但我们也观察到了重要的区别。脂蛋白（a）（Lp（a））和N端前B型利尿钠肽（NT-proBNP）甚至显示出相反的作用方向。所有途径变量共同解释了49％的T2D风险和21％的CHD风险。胰岛素样生长因子结合蛋白2（IGFBP-2，IGF / IGFBP系统途径）最能解释T2D风险（约9％的解释风险，独立于所有其他途径变量）。对于冠心病，心肌损伤和脂质相关途径最为重要，两者均解释了约4％的冠心病风险。与冠心病相比，源自生物标志物的途径变量可解释更高比例的T2D风险。两种疾病之间的途径排名不同，IGF / IGFBP系统途径与T2D密切相关，而CHD则与心肌损伤和脂质相关的途径密切相关。我们的结果有助于更好地了解这两种疾病的病理生理，其最终目标是指出生活方式干预和药物开发的目标，以理想地预防T2D和CHD的发展。与冠心病相比，源自生物标志物的途径变量可解释更高比例的T2D风险。两种疾病之间的途径排名不同，IGF / IGFBP系统途径与T2D密切相关，而CHD则与心肌损伤和脂质相关的途径密切相关。我们的结果有助于更好地了解这两种疾病的病理生理，其最终目标是指出生活方式干预和药物开发的目标，以理想地预防T2D和CHD的发展。与冠心病相比，源自生物标志物的途径变量可解释更高比例的T2D风险。两种疾病之间的途径排名不同，IGF / IGFBP系统途径与T2D密切相关，而CHD则与心肌损伤和脂质相关的途径密切相关。我们的结果有助于更好地了解这两种疾病的病理生理，最终目的是指出生活方式干预和药物开发的目标，以理想地预防T2D和CHD的发展。