The National Institute on Aging (NIA) Late Onset of Alzheimer's Disease (LOAD) Family-Based Study (FBS)

美国国家老龄化研究所晚发性阿尔茨海默病家庭为基础的研究（NIA-LOAD FBS） 开始于2003年，开始了更大的合作和共享临床和生物资源的趋势， 研究人员迄今为止，共招募了1，454个多发性迟发性AD（LOAD）家族，其中8，543个家族的年龄在12岁以下。 对家庭成员进行临床评估和DNA取样。我们还招募了1，030名对照。全基因 SNP阵列已在5，428个个体上生成，外显子组芯片基因分型在1，278个个体上生成，整体 1，484个外显子组测序和928个家族成员和对照的全基因组测序。到的转化率 NIA-LOAD FBS中未受影响的亲属中的LOAD是预期的三倍， 年龄相仿的人（见#67参考书目）。所有这些数据都已被置于公共领域， NIAGADS和dbGaP。NIA-LOAD FBS被广泛用于阿尔茨海默病遗传学研究，具有79个高水平 支持这一主张的出版物（参考书目）。 NIA-LOAD FBS提供了一个很好的机会来提高我们对临床和 老年人遗传变异的生物学影响。表型信息不断更新， 家属通过定期的认知评估和死亡时的尸检来确认LOAD的诊断。 我们已经开始招募更多的家庭成员，特别强调后代。 我们已经能够从家庭成员那里收集脑组织， 家族性负载。我们现在将扩大生物采样范围，包括RNA和外周血 单核细胞在选定的家庭。 随着更多的基因和变异被确定，NIA LOAD家族研究的成员将再次发挥作用。 我们探索的核心作用是：这些风险和保护性变异对疾病风险的影响是什么？是 遗传变异高度渗透？在后代中发展LOAD的风险是什么？能不能 变异用于将患者分层为临床试验的特定亚型？家庭数据可以 用于确定疾病风险、发病年龄或进展的新生物标志物？ NIA-LOAD FBS数据集是解决这些临床和生物学问题的唯一准备，因为 由于其体积大，确定标准严格，临床评估标准化， 特定的突变我们的努力使遗传数据的共享变得容易和无缝， 更多的研究人员获得作为NIA-LOAD FBS的一部分收集的数据和样本进行研究 问题研究这是迄今为止世界上最大的LOAD系列。几乎所有主要 阿尔茨海默病的遗传研究包括来自NIA-LOAD FBS数据集的患者和对照。的 密集的表型和遗传数据的可用性也将定位NIA-LOAD FBS，以确定 目前正在进行的全基因组和全外显子组测序项目中发现的变异的影响。

The National Institute of Aging Late Onset Alzheimer’s Disease Family Based Study (NIA-LOAD FBS) began in 2003, starting a trend of greater cooperation and sharing of clinical and biological resources among researchers. To date, a total of 1,454 multiplex late onset AD (LOAD) families have been recruited with 8,543 family members clinically assessed and DNA sampled. We have also recruited 1,030 controls. Genome-wide SNP arrays have been generated on 5,428 individuals, exome chip genotyping on 1,278 individuals, whole exome sequencing in 1,484 and whole genome in 928 family members and controls. The conversion rate of to LOAD among unaffected relatives in the NIA-LOAD FBS is three-fold higher than would be expected among individuals of similar age (see #67 Bibliography). All of these data have been placed in the public domain in NIAGADS and dbGaP. The NIA-LOAD FBS is widely used in Alzheimer disease genetics with 79 high level publications to support this claim (Bibliography). The NIA-LOAD FBS provides an excellent opportunity to improve our understanding of the clinical and biological impact of genetic variation in the elderly. Phenotypic information is continually updated in these families by regular cognitive evaluations and autopsy at the time of death to confirm the diagnosis of LOAD. We have begun to recruit additional family members with a particular emphasis on the offspring generation. We have been able to bank brain tissue from family members creating one of the largest collections of brain tissues for familial LOAD. We will now expand biological sampling to include RNA and peripheral blood mononuclear cells in selected families. As additional genes and variants are identified, the members of the NIA LOAD Family Study will again play a central role as we explore: What is the impact of these risk and protective variants on disease risk? Are the genetic variants highly penetrant? What is the risk of developing LOAD in offspring? Can the presence of variants be used for stratification of patients into specific subtypes for clinical trials? Can the family data be used to identify novel biomarkers of disease risk, age at onset onset or progression? The NIA-LOAD FBS dataset is uniquely poised to address these clinical and biological questions because of its large size, rigorous ascertainment criteria, standardized clinical assessment and lack of restriction to specific mutations. Our efforts have made it easy and seamless for the genetic data to be shared, allowing even more researchers to obtain the data and samples collected as part of the NIA-LOAD FBS for research studies. This is by far the largest collection of LOAD families available in the world. Virtually every major genetic study of Alzheimer’s disease has included patients and controls from the NIA-LOAD FBS dataset. The availability of dense phenotypic and genetic data will also position the NIA-LOAD FBS in to determine the impact of variants identified in whole genome and whole exome sequencing projects currently underway.