van Bilsen Jolanda H M, van den Brink Willem, van den Hoek Anita M, Dulos Remon, Caspers Martien P M, Kleemann Robert, Wopereis Suzan, Verschuren Lars
Department of Risk Assessment for Products in Development, The Netherlands Organization for Applied Scientific Research (TNO), Utrecht, Netherlands.
Department of Microbiology and Systems Biology, The Netherlands Organization for Applied Scientific Research (TNO), Zeist, Netherlands.
Front Physiol. 2021 Nov 10;12:703370. doi: 10.3389/fphys.2021.703370. eCollection 2021.
Metabolic disorders, such as obesity and type 2 diabetes have a large impact on global health, especially in industrialized countries. Tissue-specific chronic low-grade inflammation is a key contributor to complications in metabolic disorders. To support therapeutic approaches to these complications, it is crucial to gain a deeper understanding of the inflammatory dynamics and to monitor them on the individual level. To this end, blood-based biomarkers reflecting the tissue-specific inflammatory dynamics would be of great value. Here, we describe an approach to select candidate biomarkers for tissue-specific inflammation by using mechanistic knowledge from pathways and tissue-derived molecules. The workflow resulted in a list of candidate markers, in part consisting of literature confirmed biomarkers as well as a set of novel, more innovative biomarkers that reflect inflammation in the liver and adipose tissue. The first step of biomarker verification was on murine tissue gene-level by inducing hepatic inflammation and adipose tissue inflammation through a high-fat diet. Our data showed that predicted hepatic markers had a strong correlation to hepatic inflammation in the absence of a relation to adipose tissue inflammation, while others had a strong correlation to adipose tissue inflammation in the absence of a relation to liver inflammation. Secondly, we evaluated the human translational value by performing a curation step in the literature using studies that describe the regulation of the markers in human, which identified 9 hepatic (such as Serum Amyloid A, Haptoglobin, and Interleukin 18 Binding Protein) and 2 adipose (Resistin and MMP-9) inflammatory biomarkers at the highest level of confirmation. Here, we identified and pre-clinically verified a set of predicted biomarkers for liver and adipose tissue inflammation which can be of great value to study future development of therapeutic/lifestyle interventions to combat metabolic inflammatory complications.
代谢紊乱,如肥胖和2型糖尿病,对全球健康有重大影响,尤其是在工业化国家。组织特异性慢性低度炎症是代谢紊乱并发症的关键促成因素。为了支持针对这些并发症的治疗方法,深入了解炎症动态并在个体层面上对其进行监测至关重要。为此,反映组织特异性炎症动态的血液生物标志物将具有巨大价值。在这里,我们描述了一种利用来自信号通路和组织衍生分子的机制知识来选择组织特异性炎症候选生物标志物的方法。该工作流程产生了一份候选标志物清单,部分由文献证实的生物标志物以及一组反映肝脏和脂肪组织炎症的新颖、更具创新性的生物标志物组成。生物标志物验证的第一步是在小鼠组织基因水平上,通过高脂饮食诱导肝脏炎症和脂肪组织炎症。我们的数据表明,预测的肝脏标志物与肝脏炎症有很强的相关性,而与脂肪组织炎症无关,而其他标志物与脂肪组织炎症有很强的相关性,而与肝脏炎症无关。其次,我们通过在文献中进行筛选步骤来评估其在人类中的转化价值,该步骤使用描述人类中标志物调节的研究,从而在最高确认水平上鉴定出9种肝脏(如血清淀粉样蛋白A、触珠蛋白和白细胞介素18结合蛋白)和2种脂肪(抵抗素和基质金属蛋白酶-9)炎症生物标志物。在这里,我们鉴定并在临床前验证了一组用于肝脏和脂肪组织炎症的预测生物标志物,这对于研究对抗代谢性炎症并发症的治疗/生活方式干预的未来发展可能具有巨大价值。