Design and Validation of Easy-to-Adopt Mass Spectrometry Assays of Importance to Obesity

项目总结 肥胖现在已经超过吸烟，成为一种负面的健康风险因素。流行病学和基因分析表明 事实证明，超重是糖尿病、冠心病、高血压、 血脂异常、心力衰竭、多种癌症、膝骨性关节炎和其他并存疾病 并发症。迫切需要扩大对肥胖的病理生理学的理解，以减少其 对人类健康的影响。我们正在提出实用和有效的生物标记工具，使研究人员能够 从血清或血浆的复杂背景中破译循环肥胖蛋白质组特征。我们会 使用自上而下(目标1)和自下而上的液质联用(LC-MS)技术 (目标2)工作流程，可按比例调整，以包括其他潜在的候选标记(目标3)。目标1侧重于 利用自上而下的靶向LC-MS多重分析处理肥胖相关的多肽激素。我们 假设小分子量(MW)生物活性激素的异常处理参与了 肥胖并改变其循环中的浓度。我们有两种方法来量化密钥的处理 肥胖相关生物活性多肽：I)内源性多肽片段的自上而下LC-MS分析 在胰岛素、IGF-1、胰高血糖素、GLP-1、GIP、Grelin、胃动素、奥贝他汀和生长抑素的处理过程中(最初)， 随后接近次级目标；以及ii)一种评估血浆蛋白水解酶活性的新方法 同时产生/丢失特别集中于GLP-11-41，GIP1-42， Proghrelin和生长抑素-28以及由此产生的低分子量多肽的生产。在目标2中，我们 假设脂肪细胞、肝脏、肠道和其他器官的调节通过循环蛋白影响肥胖 反之亦然。为了解决这一问题，我们将开发一种自下而上的、用于精确定量的靶向多重分析。 瘦素、脂联素、胃泌素(及其修饰形式)、抵抗素和分泌素，这些都与肥胖有关。 此外，我们还将包括代表炎症(CRP)、心脏病风险的蛋白标记物 (载脂蛋白B/载脂蛋白A1)、糖尿病(血红蛋白A1C)和肾功能(胱抑素C)作为肥胖的评估指标 与并存情况有关。在目标3中，我们将生产与肥胖相关的额外的多重分析。 在与我们的专家和NIDDK协商后分配。对于开发的每一种分析方法，我们都将展示分析 有效性(遵循CPTAC准则)，通过适当评估性能特征(例如，精确度， 准确度、线性、灵敏度、特异度等)。我们还将努力提高可转让性和可获得性 更广泛的肥胖研究社区的化验结果。综上所述，粗壮蛋白质的发展 代表广泛肥胖病理生理的生物标记物分析将有助于研究人员进一步了解 肥胖调节途径，开发新的治疗方法，监测生活方式和遗传学对 个体表型，并评估未来临床诊断生物标记物的潜力。

PROJECT SUMMARY Obesity now surpasses smoking as a negative health risk factor. Epidemiologic and genetic analyses have demonstrated excess weight is a causal factor for diabetes, coronary artery disease, hypertension, dyslipidemia, heart failure, multiple types of cancer, knee osteoarthritis, and other co-morbidities and complications. Expanded understanding of the pathophysiology of obesity is critically needed to reduce its impact on human health. We are proposing practical and impactful biomarker tools that allow researchers to decipher circulating obesity proteomic signatures from the complex background of serum or plasma. We will apply liquid chromatography-mass spectrometry (LC-MS) techniques using top-down (Aim 1) and bottom-up (Aim 2) workflows, which can be scaled to include other potential candidate markers (Aim 3). Aim 1 focuses on obesity-related peptide hormone processing using top-down targeted LC-MS multiplexed assays. We hypothesize that dysregulated processing of small molecular weight (MW) bioactive hormones is involved in obesity and alters their circulating concentrations. We have two approaches to quantify the processing of key obesity related bioactive peptides: i) top-down LC-MS analysis of endogenous peptide fragments generated during processing (initially) for insulin, IGF-1, glucagon, GLP-1, GIP, ghrelin, motilin, obestatin, and somastatin, with secondary targets approached later; and ii) a novel method to assess plasma proteolytic enzyme activity and the simultaneous generation/loss of peptide fragments focusing specifically on GLP-11-41, GIP1-42, proghrelin and somatostatin-28 and the production of low MW peptides generated from these. In Aim 2, we hypothesize that regulation of adipocytes, liver, gut, and other organs impact obesity via circulating proteins and vice versa. To address this, we will develop a bottom-up targeted multiplex assay for precise quantification of leptin, adiponectin, gastrin (and modified forms), resistin, and secretin, which are all involved in obesity. Additionally, we will include protein markers representing inflammation (CRP), cardiac disease risk (ApoB/ApoA1), diabetes (hemoglobin A1C), and kidney function (cystatin C) for the assessment of obesity as it relates to comorbid conditions. In Aim 3 we will produce additional multiplex assays associated with obesity assigned in consult with our experts and NIDDK. For each assay developed we will demonstrate analytical validity (following CPTAC guidelines) by appropriately evaluating performance characteristics (e.g., precision, accuracy, linearity, sensitivity, specificity, etc.). We will additionally work to increase transferability and access of the assays to the broader obesity-research community. In summary, the development of robust protein biomarker assays that represent broad obesity pathophysiology will assist researchers in further understanding obesity regulatory pathways, developing new treatments, monitoring the effects of lifestyle and genetics on individual phenotypes, and evaluate the potential for future clinical diagnostic biomarker utility.