DFU Clinical Research Unit

DFU 临床研究单位

• 批准号: 10219889
• 负责人: RODICA BUSUI (POP-BUSUI)
• 金额: $ 38.87万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10219889
• 关键词: 2019-nCoV; Acute; Acute Renal Failure with Renal Papillary Necrosis; Admission activity; Affect; Ambulatory Care Facilities; Assessment tool; Biological Markers; Blood Vessels; COVID-19; COVID-19 pandemic; Cardiovascular Diseases; Cardiovascular system; Cessation of life; Chronic; Clinical; Clinical Data; Clinical Research; Clinical Trials; Complication; Complications of Diabetes Mellitus; Computerized Medical Record; Dangerousness; Data; Data Set; Diabetes Mellitus; Diabetic Nephropathy; Diabetic Neuropathies; Disease; Ethnic Origin; Funding; Future; Goals; Guidelines; Hospitals; Hyperglycemia; Hypertension; Individual; Infection; Inflammation; Inflammatory; Inpatients; Intervention Trial; Kidney; Knowledge; Light; Link; Measures; Medicine; Michigan; Neurologic; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Organ; Outcome; Outpatients; Participant; Patients; Persons; Pharmaceutical Preparations; Phenotype; Population; Prevalence; Psychosocial Factor; Race; Reporting; Research; Respiratory Failure; Risk; Risk Assessment; Risk Factors; Risk stratification; Secondary to; Socioeconomic Status; Survivors; Syndrome; Testing; Triage; Vascular Diseases; Visit; adverse outcome; biomarker panel; clinical application; clinical phenotype; clinical predictors; cohort; comorbidity; cytokine; cytokine release syndrome; evidence based guidelines; heart damage; high risk; infection rate; knowledge base; multidisciplinary; oxidative damage; pandemic disease; patient population; personalized management; predictive signature; psychosocial; relating to nervous system; social disparities; social health determinants; tool

ABSTRACT The ongoing COVID-19 pandemic disproportionately affects type 2 diabetes (T2D) patients, who are especially susceptible to SARS-CoV-2-induced adverse outcomes and complications. T2D patients have several comorbidities that increases their vulnerability: obesity, chronic inflammation, and vascular complications, i.e., diabetic kidney disease (DKD), diabetic neuropathy (DN), and cardiovascular disease (CVD). T2D patients are also predisposed to the cytokine storm syndrome (CSS), an acute inflammation state triggered by COVID-19. CSS releases a cascade of inflammatory cytokines that causes dangerous hyperglycemic surges and perpetuates a vicious cycle of cytokine release. Yet, there is a critical knowledge gap on how the initial CSS that occurs with the onset of COVID-19 disease superimposes on chronic T2D inflammation to contribute to adverse outcomes and what are the cytokines that most strongly predict the clinical course in COVID-19 T2D patients. Given the T2D prevalence, high COVID-19 infection rate, and lack of therapies, there is an urgent unmet need to identify risk-factors and inflammatory biomarker profiles that predict the most critical incoming COVID-19 T2D cases to prepare us for the next pandemic wave.We also urgently need evidence-based guidelines for managing complications in survivors from the first wave. Our objective is to establish the knowledge base needed to meet this clinical need by developing risk-assessment tools to inform management of current COVID-19 T2D patients and prepare for future waves. Our overall hypothesis is that acute inflammatory surges, secondary to SARS- CoV-2-induced CSS, raise the risk of acute adverse outcomes and accelerate progression of chronic diabetic complications. We will test this hypothesis in an ongoing cohort of ~500 severe COVID-19 patients admitted at Michigan Medicine, of whom 208 have T2D. Known as the Michigan Medicine COVID-19 Cohort (M2C2, PI: Hayek), clinical data and biosamples were collected on admission and throughout the hospital course. Our one- year short term goals are to: (i) identify inflammatory signatures that correlate to inpatient outcomes in the M2C2, (ii) deeply phenotype M2C2 participants 3-6 months post-hospitalization for chronic vascular complications (DKD, DN, CVD), and longer term inflammatory signatures, (iii) assess the 3-6 month psychosocial outcomes of M2C2 participants. Our Specific Aims are:1) Identify an inflammatory biomarker signature linked to acute complications in T2D M2C2 patients; b) Define the post-discharge clinical course by inflammatory biomarker signatures in T2D M2C2 patients. Our proposed research will have immediate significant impact by generating the knowledge based required for much needed, and immediately applicable clinical guidelines for managing current and future COVID-19 T2D patients. It will also establish an informative biomarker panels that correlate with acute and chronic T2D COVID-19 clinical phenotypes and inform outpatient management of T2D patients post-COVID-19 infection. Data from this proposal are urgently needed to treat our T2D population in light of their particular vulnerability.

抽象的 持续的 COVID-19 大流行对 2 型糖尿病 (T2D) 患者的影响尤为严重，他们尤其是 容易受到 SARS-CoV-2 引起的不良后果和并发症的影响。 T2D 患者有几个 增加其脆弱性的合并症：肥胖、慢性炎症和血管并发症，即 糖尿病肾病（DKD）、糖尿病神经病变（DN）和心血管疾病（CVD）。 T2D 患者是 还易患细胞因子风暴综合征 (CSS)，这是一种由 COVID-19 引发的急性炎症状态。 CSS 释放一系列炎症细胞因子，导致危险的高血糖激增 使细胞因子释放形成恶性循环。然而，对于最初的 CSS 如何 随着 COVID-19 疾病的发作而发生，叠加慢性 T2D 炎症，导致不良反应 结果以及最有力地预测 COVID-19 T2D 患者临床病程的细胞因子是什么。 鉴于 T2D 患病率、COVID-19 感染率高且缺乏治疗方法，迫切需要满足未满足的需求 识别风险因素和炎症生物标志物谱，预测最关键的新冠肺炎 (COVID-19) T2D 的发生 我们还迫切需要基于证据的管理指南 第一波幸存者的并发症。我们的目标是建立满足以下要求所需的知识库 通过开发风险评估工具来为当前 COVID-19 T2D 患者的管理提供信息，以满足这一临床需求 并为未来的浪潮做好准备。我们的总体假设是继发于 SARS 的急性炎症激增 CoV-2 诱导的 CSS，增加急性不良后果的风险并加速慢性糖尿病的进展 并发症。我们将在一个由约 500 名重症 COVID-19 患者组成的持续队列中检验这一假设。 密歇根医学，其中 208 名患有 T2D。被称为密歇根医学 COVID-19 队列（M2C2，PI： Hayek），在入院时和整个住院期间收集临床数据和生物样本。我们的一—— 今年的短期目标是：(i) 识别与 M2C2 住院患者结果相关的炎症特征， (ii) 因慢性血管并发症（DKD、 DN、CVD）和长期炎症特征，(iii) 评估 M2C2 的 3-6 个月心理社会结果 参与者。我们的具体目标是：1) 识别与急性并发症相关的炎症生物标志物特征 T2D M2C2 患者； b) 通过 T2D 炎症生物标志物特征定义出院后临床病程 M2C2 患者。我们提出的研究将产生基于知识的直接重大影响 需要急需且立即适用的临床指南来管理当前和未来 COVID-19 T2D 患者。它还将建立一个与急性和慢性疾病相关的信息丰富的生物标志物组。 慢性 T2D COVID-19 临床表型并为 COVID-19 后 T2D 患者的门诊管理提供信息 感染。鉴于我们的 T2D 人群的特殊情况，迫切需要来自该提案的数据来治疗他们 脆弱性。