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

项目摘要 肥胖现在超过吸烟，成为一个负面的健康风险因素。流行病学和遗传学分析 已证明超重是糖尿病、冠状动脉疾病、高血压 血脂异常、心力衰竭、多种癌症、膝关节骨关节炎和其他合并症， 并发症扩大对肥胖症病理生理学的理解是减少肥胖症的关键。 对人类健康的影响。我们正在提出实用和有影响力的生物标志物工具，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。我们将 采用自上而下（Aim 1）和自下而上的液相色谱-质谱（LC-MS）技术 (Aim 2）工作流程，其可以被缩放以包括其他潜在的候选标记物（目标3）。目标1侧重于 使用自上而下的靶向LC-MS多重测定进行肥胖相关肽激素处理。我们 假设小分子量（MW）生物活性激素的失调加工涉及 肥胖和改变其循环浓度。我们有两种方法来量化密钥的处理 肥胖症相关的生物活性肽：i）产生的内源性肽片段的自上而下的LC-MS分析 在胰岛素、IGF-1、胰高血糖素、GLP-1、GIP、胃饥饿素、胃动素、肥胖抑制素和生长抑素的处理（最初）期间， 第二靶点随后接近;和ii）评估血浆蛋白水解酶活性的新方法 以及特异性集中于GLP-11-41，GIP 1 -42， 促生长素释放肽和生长抑素-28以及由这些产生的低MW肽的生产。在目标2中， 假设脂肪细胞、肝脏、肠道和其他器官调节通过循环蛋白质影响肥胖 且反之亦然。为了解决这个问题，我们将开发一种自下而上的靶向多重检测方法，用于精确定量 瘦素、脂联素、胃泌素（及其修饰形式）、胃泌素和促胰液素，这些都与肥胖有关。 此外，我们将包括代表炎症的蛋白质标志物（CRP），心脏病风险 (ApoB/ApoA 1）、糖尿病（血红蛋白A1 C）和肾功能（胱抑素C）用于评估肥胖，因为 与共病有关在目标3中，我们将生产与肥胖相关的其他多重检测方法 在与我们的专家和NIDDK协商后分配。对于开发的每种检测方法，我们将证明分析 通过适当评估性能特征（例如，精确度， 准确性、线性、灵敏度、特异性等）。此外，我们还将努力提高可转让性和可访问性 向更广泛的肥胖研究界推广。总之，开发鲁棒蛋白质 代表广泛的肥胖病理生理学的生物标志物测定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肥胖的影响， 个体表型，并评估未来临床诊断生物标志物效用的潜力。

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.