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

多发性骨髓瘤（MM）是第二常见的血液恶性肿瘤，并且在很大程度上是不可治愈的。黑色 与白色美国人相比，美国人经历了无法解释的2倍超额风险，而亚裔美国人 体验更低的风险。MM之前是一种前驱状态，其特征在于良性肿瘤的积累。 分泌单克隆蛋白质的单克隆浆细胞（未确定的单克隆丙种球蛋白病） 显著性，MGUS），这与MM中所见的种族/民族差异相同。因此， MGUS差异的原因将揭示MM差异的原因。我们（MPI Cozen，Desai 和Bertrand）提交了本提案，以响应PAR 19-279，MMDPQ 1：“什么风险因素，特别是 或者合作解释不同种族间MGUS发病率的差异？”我们的核心假设是 在浆细胞生长/血管生成因子、微生物易位、慢性 由于先前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 差距通过筛选4个多种族NCI流行病学队列的参与者（黑人妇女健康研究， 妇女健康倡议，多种族队列，南方社区队列研究），我们将确定844名黑人， 844名非拉丁裔白人、146名拉丁裔和146名亚洲人，经实验室验证的MGUS和相同数量的 年龄、性别、人种/种族匹配的对照组，通过相同的实验室筛选而未进行MGUS。我们将测量 反映浆细胞生长、血管生成、炎症和微生物易位的18种生物标志物水平 (IL6、IL 17、XCL 13、IL 6-R、BAFF、APRIL、gp 130、HGF、CCL-8、血管蛋白-2、LBP、sCD 14、脂联素、BCMA、 IP-10、IL 10、MIP 1-a、CXCL 12）（目的1）。我们还将研究与B细胞活化相关的暴露 包括通过测量抗体来测量来自慢性免疫刺激剂的终生累积感染 同时在多重系统中对B和C型肝炎病毒，H. pylori、T. gondii、弓形虫T. pallidum、C.沙眼， HPV和所有8种疱疹家族病毒（Aim 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）。到 确定一个给定的假定风险因素是否可以（至少部分）解释MGUS中的种族差异，我们将 (1)确定该因素是否与所有四个种族群体中的MGUS一致相关，如果是，则;（2） 在综合分析中估计关系的强度;（3）确定 MGUS相关因素因种族而异，其方向与MGUS风险的已知种族差异一致。 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，个体感染）与MGUS的对数几率。与我们的多学科团队的合作研究者和 4个种族/民族多样化的癌症流行病学队列的合作，我们处于独特的地位，能够 确定MGUS差异的原因，对此知之甚少。这项研究将提供关键的 关于性别、年龄和性别平等部在种族/族裔不平等原因方面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.