Peripheral Biomarkers in Familial Alzheimer's Disease

描述（由申请人提供）：我们之前的研究（发表在初步结果中）表明，与炎症反应和细胞应激相关的转录本的多变量分析可以区分阿尔茨海默病外周血白细胞和对照白细胞。这种根据容易获得的样本的表达谱来区分临床诊断的AD与对照的能力提出了一个问题；我们能否根据外周血白细胞的基因表达谱来区分临床前AD ？要回答这个问题，需要从一组非痴呆患者中获取血液样本，然后对他们进行多年的纵向跟踪，以发现队列中新的阿尔茨海默病病例。通过选择有风险的人，可以丰富队列，就像在ADAPT研究中所做的那样，该研究根据年龄和一级亲属的AD定义风险。在这里提出的研究中，我们在携带一种明确的家族性基因突变的基础上，丰富了具有阿尔茨海默病风险的非痴呆人群，这种突变不可避免地导致随后的阿尔茨海默病。在这个建议中，我们主要关注突变基因PS1，因为它是FAD基因突变中经常发生突变的基因。那么，这里提出的研究要检验的中心假设是；那些有FAD突变但没有诊断为AD的人代表“临床前”AD，他们的基因表达谱与具有相同突变并患有AD的家庭成员的AD基因表达谱相似，因此可以预测随后的AD。我们将从三种人的外周血白细胞中提取RNA: 1)有FAD突变并诊断为AD， 2)有FAD突变但诊断为非AD， 3)没有FAD突变但诊断为非AD的野生型。在可能的情况下，这三个类将派生自同一家族。提取的RNA中的基因表达将通过定量RT-PCR （qRT-PCR）进行检测，目标是我们在早期工作中定义的与炎症反应和细胞应激相关的转录本。对这些数据的统计分析将采用多元判别分析的方法，正如我们在早期工作中所做的那样。此外，我们将使用标准的和新开发的统计方法来分析在这些相同样本上收集的阵列数据，目的是确定炎症和细胞应激（以及其他类别）类别中的替代转录本是否优于我们先前定义的转录本。本文提出的研究数据将在这些相同FAD病例中蛋白质表达分析的平行研究框架内进行解释（Timothy Mhyre），以及在我们几乎完成的（Quad）晚发型AD （LOAD）研究框架内使用本文提出的相同方法进行解释。四组研究分为四组，每组约20人：AD、MCI、PD和对照组。我们还在太阳健康研究所启动了一项外周白细胞基因表达的研究，在那里我们有超过15万名老年人。公共卫生相关性：阿尔茨海默病是美国乃至全世界的一个主要公共卫生问题。在美国，病例数量为450万至500万，每年的医疗保险费用约为1000亿美元。随着美国人口的老龄化，到2050年，阿尔茨海默氏症患者的数量预计将增长到1600万，随之而来的是医疗费用的大幅增加。显然，迫切需要更有效的早期诊断，以及更有效的治疗，以减缓或阻止疾病进展。这里提出的研究解决了这些需求的诊断部分。许多研究已经证实，阿尔茨海默病在症状变得足够明显、需要医学关注之前，已经对大脑造成了数十年的损害。不幸的是，到那时，大脑中与记忆、判断和认知技能有关的关键区域的大部分神经细胞已经丢失。这强调了尽早发现阿尔茨海默病的重要性，以便在发生重大脑损伤之前开始治疗。我们已经获得的数据表明，根据容易获得的外周血白细胞的基因表达谱，能够区分已经诊断出的阿尔茨海默病和对照病例。这里提交的提案所解决的问题是，我们在区分已经诊断的疾病方面取得成功的方法是否能够在多年后成功地预测阿尔茨海默病的临床诊断。为了做到这一点，我们建议研究导致早期阿尔茨海默病的基因突变的家庭。一些有这种突变的家庭成员已经患有阿尔茨海默病，其他有这种突变的家庭成员尚未被临床诊断为阿尔茨海默病，还有一些家庭成员既没有这种突变，也没有阿尔茨海默病。分析这三类家族成员外周血中的基因表达将告诉我们，具有该突变但尚未表现出临床检测到的阿尔茨海默病的家族成员是否与已诊断为AD的具有该突变的家族成员具有相似的基因表达谱。如果是这样，这将构成一项发现，即在家族性AD病例出现临床可检测的症状之前发现阿尔茨海默病是可能的，并将为将这些研究扩展到更常见的晚发性阿尔茨海默病提供基础。

DESCRIPTION (provided by applicant): Our previous studies (presented in Preliminary Results) have shown that multivariate analysis of transcripts related to inflammatory response and to cellular stress can distinguish Alzheimer's disease peripheral blood leukocytes from control leukocytes. This ability to distinguish clinically diagnosed AD from controls on the basis of expression profile of easily obtained samples raises the question; can we distinguish preclinical AD on the basis of gene expression profiles of peripheral blood leukocytes? To answer this question requires obtaining blood samples from a cohort of non-demented persons then following them longitudinally for years to detect new AD cases in the cohort. The cohort may be enriched by selecting persons at risk, as was done in the ADAPT study which defined risk on the basis of age and of AD in a first degree relative. In the study proposed here we enrich our cohort of non-demented persons at risk for AD on the basis of carrying one of the well-defined familial gene mutations that lead, inevitably, to subsequent AD. In this proposal we focus largely on the mutated gene for PS1 since it is a frequently mutated gene among the FAD gene mutations. The central hypothesis to be tested by the research proposed here is, then; that those persons with an FAD mutation but diagnosis of no AD represent "preclinical" AD and that they will present a gene expression profile that will be predictive of subsequent AD by virtue of being similar to the AD gene expression profile of family members with the same mutation and with AD. We will extract RNA from peripheral blood leukocytes obtained from three classes of persons: 1) with an FAD mutation and with diagnosed AD, 2) with an FAD mutation and diagnosis of no AD and 3) wild type with no FAD mutation and a diagnosis of no AD. Where possible, these three classes will be derived from the same family. Gene expression in the extracted RNA will be examined by quantitative RT-PCR (qRT-PCR) with the targets being those transcripts related to inflammatory response and cellular stress that we have defined in our earlier work. Statistical analysis of these data will be by means of multivariate discriminant analysis, as we have done in our earlier work. Additionally, we will use standard and newly developed statistical methods for the analysis of array data to be collected on these same samples with the aim of determining whether alternate transcripts within the classes of inflammatory and cell stress (as well as other classes) may be superior to those we have previously defined. Data from the study proposed here will be interpreted within the framework of parallel study of analysis of protein expression in these same FAD cases (by Timothy Mhyre), as well as within the framework of our almost completed (Quad) study of late onset AD (LOAD) using the same methods as proposed here. The Quad Study has four groups of ~20 each: AD, MCI, PD and control. We have also initiated a study of gene expression in peripheral leukocytes in LOAD at Sun Health Research Institute where we have access to over 150,000 elderly. PUBLIC HEALTH RELEVANCE: Alzheimer's disease is a major public health problem in the United States, as well as world-wide. In the U.S. the number of cases is 4.5 - 5 million with an annual Medicare cost of about $100 billion. As the population of the U.S. ages, the number of Alzheimer's cases is projected to grow to 16 million by 2050, with consequent immense increased expenses. The need for more effective and early diagnosis, coupled with more effective treatment that would slow or halt disease progression is clearly a pressing need. The study proposed here addresses the diagnosis arm of these needs. A number of studies have established that Alzheimer's disease has been damaging the brain for decades before symptoms become evident enough to come to medical attention. Unfortunately, by that time a large percentage of nerve cells have been lost in critical areas of the brain concerned with memory, judgment and cognitive skills. This emphasizes the importance of detecting Alzheimer's disease as early as possible so that treatment can be initiated before significant brain damage has taken place. We have obtained data that demonstrates the ability to distinguish already diagnosed Alzheimer's disease from control cases on the basis of a profile of gene expression by easily obtained peripheral blood leukocytes. The question addressed by the proposal submitted here is whether our method which has been successful at distinguishing already diagnosed disease can be successful at predicting a clinical diagnosis of Alzheimer's disease years later. In order to do this we propose to study families with gene mutations that cause early Alzheimer's disease. Some family members with such a mutation will already have AD, other family members with the mutation will not yet have been clinically diagnosed with AD, while still other family members will have neither the mutation nor Alzheimer's disease. Profiling gene expression in peripheral blood cells of these three classes of family members will tell us whether family members with the mutation but not yet showing clinically detected Alzheimer's disease show a gene expression profile similar to that of family members with the mutation who have been diagnosed with AD. If this is so, it would constitute a finding that it is possible to detect Alzheimer's disease prior to the appearance of clinically detectable symptoms in cases of familial AD, and will provide a basis for extension of these studies to the more common late onset Alzheimer's disease.