Determinants of the racial/ethnic disparity in MGUS risk: An epidemiologic study in 4 cohorts

多发性骨髓瘤(MM)是第二种最常见的血液系统恶性肿瘤，在很大程度上是无法治愈的。黑色 与白人相比，美国人经历了原因不明的额外风险2倍，而亚裔美国人 体验更低的风险。MM之前是一种前驱状态，其特征是良性积聚 分泌单克隆蛋白的单克隆性浆细胞(不明原因的单克隆性丙种球蛋白病 意义)，这与MM中看到的种族/民族差异相同。因此，解释了 MGUS中差异的原因将有助于揭示MM中差异的原因。 和Bertrand)正在提交这项提案，以回应标准19-279，MMDPQ1：“什么风险因素，特别是 或者通过合作，解释不同种族之间MGUS发病率的差异？我们的中心假设是 在浆细胞生长/血管生成因子、微生物易位、慢性 既往感染和生活方式因素引起的抗原刺激可以解释观察到的MGUS发病率 贫富差距。通过对4个多种族NCI流行病学队列的参与者进行筛查(黑人妇女健康研究， 妇女健康倡议、多民族队列、南方社区队列研究)，我们将识别844名黑人， 拥有实验室确认的MGU的844名非拉丁裔白人、146名拉丁裔和146名亚裔以及同等数量的 通过相同的实验室筛查，没有MGUS的年龄、性别、种族/民族匹配的对照。我们将衡量 18种反映浆细胞生长、血管生成、炎症和微生物易位的生物标志物水平 (IL6、IL17、XCL13、IL6-R、BAFF、APRIL、gp130、HGF、CCL-8、AngioProtein-2、LBP、sCD14、脂联素、BCMA、 IP-10、IL10、MIP1-a、CXCL12)(目标1)。我们还将检查与B细胞激活相关的暴露 通过测量抗体包括慢性免疫刺激剂的终生累积感染 同时在对乙型和丙型肝炎病毒、幽门螺杆菌、弓形虫、梅毒螺旋体、沙眼衣原体、 HPV和所有8种疱疹病毒家族病毒(目标2)，以及生活方式因素肥胖、体力活动、糖尿病和使用 抗炎药物二甲双胍、他汀类药物和阿司匹林，已知会影响B细胞反应(目标3)。至 确定给定的假定风险因素是否(至少部分)可以解释MGUS的种族差异，我们将 (1)确定该因素是否在所有四个种族中与MGUS一致，如果是，则确定；。(2) 在综合分析中估计这种关系的强度；和；(3)确定 MGUS相关因素因种族而异，其方向与已知的MGUS风险的种族差异一致。 我们将使用逻辑回归技术，将连续或二元因素(体重指数， 糖尿病、个人感染)到MGUS的对数赔率。与我们的多学科合作调查团队和 4个种族/民族不同的癌症流行病学队列的合作，我们处于独特的地位，能够 为了找出MGUS差距的原因，人们对此知之甚少。这项研究将提供关键的 关于MGUS种族/民族差异原因中存在的知识差距的信息。

Multiple myeloma (MM) is the second most common hematological malignancy and is largely incurable. Black Americans experience an unexplained 2-fold excess risk compared to White Americans, while Asian Americans experience a lower risk. MM is preceded by a precursor state characterized by an accumulation of benign monoclonal plasma cells that secrete a monoclonal protein (monoclonal gammopathy of undetermined significance, MGUS), which occurs with the same racial/ethnic disparity as seen in MM. Thus, explaining the causes of the disparity in MGUS will shed light on the causes of the disparity in MM. We (MPIs Cozen, Desai and Bertrand) are submitting this proposal in response to PAR 19-279, MMDPQ1: “What risk factors, singularly or in cooperation, explain the variation in MGUS incidence among different races?” Our central hypothesis is that racial and ethnic differences in plasma cell growth/angiogenic factors, microbial translocation, chronic antigenic stimulation due to previous infection and lifestyle factors can explain the observed MGUS incidence disparity. By screening participants in 4 multiethnic NCI epidemiology cohorts (Black Women's Health Study, Women's Health Initiative, Multiethnic Cohort, Southern Community Cohort Study), we will identify 844 Blacks, 844 Non-Latino Whites, 146 Latino and 146 Asians with laboratory validated MGUS and an equal number of age-, sex- race/ethnicity- matched controls without MGUS by the same laboratory screening. We will measure levels of 18 biomarkers reflecting plasma cell growth, angiogenesis, inflammation and microbial translocation (IL6, IL17, XCL13, IL6-R, BAFF, APRIL, gp130, HGF, CCL-8, Angioprotein-2, LBP, sCD14, adiponectin, BCMA, IP-10, IL10, MIP1-a, CXCL12) (Aim 1). We will also examine exposures associated with B-cell activation including lifetime cumulative infection from chronic immune stimulating agents by measuring antibodies simultaneously in a multiplex system to Hepatitis B and C viruses, H. pylori, T. gondii, T. pallidum, C. trachomatis, HPV, and all 8 Herpes family viruses (Aim 2), and lifestyle factors obesity, physical activity, diabetes and use of anti-inflammatory medications metformin, statins and aspirin, known to affect B-cell response (Aim 3). To determine whether a given putative risk factor can (at least partly) explain the racial disparities in MGUS we will (1) determine whether the factor is consistently related to MGUS within all four ethnic groups and if so then; (2) estimate the strength of the relationship in a combined analysis and; (3) determine whether the prevalence of an MGUS-associated factor differs by race in a direction consistent with the known racial differences in MGUS risk. We will use logistic regression techniques that relate either continuous or binary factors (body mass index, diabetes, individual infections) to the log odds of MGUS. With our multidisciplinary team of co-investigators and collaboration of 4 racially/ethnically diverse cancer epidemiology cohorts, we are uniquely positioned to be able to identify causes of the MGUS disparity, about which there is little known. This study will provide critical information on the knowledge gap that exists in the causes of racial/ethnic disparity for MGUS.