The Alzheimer's Disease Centers' Uniform Data Set (UDS): the neuropsychologic test battery.

The neuropsychologic test battery from the Uniform Data Set (UDS) of the Alzheimer's Disease Centers (ADC) program of the National Institute on Aging consists of brief measures of attention, processing speed, executive function, episodic memory, and language. This paper describes development of the battery and preliminary data from the initial UDS evaluation of 3268 clinically cognitively normal men and women collected over the first 24 months of utilization. The subjects represent a sample of community-dwelling, individuals who volunteer for studies of cognitive aging. Subjects were considered "clinically cognitively normal" based on clinical assessment, including the Clinical Dementia Rating scale and the Functional Assessment Questionnaire. The results demonstrate performance on tests sensitive to cognitive aging and to the early stages of Alzheimer disease in a relatively well-educated sample. Regression models investigating the impact of age, education, and sex on test scores indicate that these variables will need to be incorporated in subsequent normative studies. Future plans include: (1) determining the psychometric properties of the battery; (2) establishing normative data, including norms for different ethnic minority groups; and (3) conducting longitudinal studies on cognitively normal subjects, individuals with mild cognitive impairment, and individuals with Alzheimer disease and other forms of dementia.

A multiancestral genome-wide exome array study of Alzheimer disease, frontotemporal dementia, and progressive supranuclear palsy.

IMPORTANCE: Previous studies have indicated a heritable component of the etiology of neurodegenerative diseases such as Alzheimer disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP). However, few have examined the contribution of low-frequency coding variants on a genome-wide level. OBJECTIVE: To identify low-frequency coding variants that affect susceptibility to AD, FTD, and PSP. DESIGN, SETTING, AND PARTICIPANTS: We used the Illumina HumanExome BeadChip array to genotype a large number of variants (most of which are low-frequency coding variants) in a cohort of patients with neurodegenerative disease (224 with AD, 168 with FTD, and 48 with PSP) and in 224 control individuals without dementia enrolled between 2005-2012 from multiple centers participating in the Genetic Investigation in Frontotemporal Dementia and Alzheimer's Disease (GIFT) Study. An additional multiancestral replication cohort of 240 patients with AD and 240 controls without dementia was used to validate suggestive findings. Variant-level association testing and gene-based testing were performed. MAIN OUTCOMES AND MEASURES: Statistical association of genetic variants with clinical diagnosis of AD, FTD, and PSP. RESULTS: Genetic variants typed by the exome array explained 44%, 53%, and 57% of the total phenotypic variance of AD, FTD, and PSP, respectively. An association with the known AD gene ABCA7 was replicated in several ancestries (discovery P=.0049, European P=.041, African American P=.043, and Asian P=.027), suggesting that exonic variants within this gene modify AD susceptibility. In addition, 2 suggestive candidate genes, DYSF (P=5.53×10(-5)) and PAXIP1 (P=2.26×10(-4)), were highlighted in patients with AD and differentially expressed in AD brain. Corroborating evidence from other exome array studies and gene expression data points toward potential involvement of these genes in the pathogenesis of AD. CONCLUSIONS AND RELEVANCE: Low-frequency coding variants with intermediate effect size may account for a significant fraction of the genetic susceptibility to AD and FTD. Furthermore, we found evidence that coding variants in the known susceptibility gene ABCA7, as well as candidate genes DYSF and PAXIP1, confer risk for AD.

The National Alzheimer's Coordinating Center (NACC) database: the Uniform Data Set.

The National Alzheimer's Coordinating Center (NACC) is responsible for developing and maintaining a database of participant information collected from the 29 Alzheimer's Disease Centers (ADCs) funded by the National Institute on Aging (NIA). The NIA appointed the ADC Clinical Task Force to determine and define an expanded, standardized clinical data set, called the Uniform Data Set (UDS). The goal of the UDS is to provide ADC researchers a standard set of assessment procedures, collected longitudinally, to better characterize ADC participants with mild Alzheimer disease and mild cognitive impairment in comparison with nondemented controls. NACC implemented the UDS (September 2005) by developing data collection forms for initial and follow-up visits based on Clinical Task Force definitions, a relational database, and a data submission system accessible by all ADCs. The NIA requires ADCs to submit UDS data to NACC for all their Clinical Core participants. Thus, the NACC web site (https://www.alz.washington.edu) was enhanced to provide efficient and secure access data submission and retrieval systems.

The National Alzheimer's Coordinating Center (NACC) Database: an Alzheimer disease database.

The National Alzheimer's Coordinating Center (NACC) is responsible for developing and maintaining a database of patient information collected from the 29 Alzheimer disease centers (ADCs) funded by the National Institute on Aging. Each of the centers collects center-determined data elements on patients enrolled into its center and transmits a minimum dataset to NACC. Data are managed differently at each center depending on that center's research needs. The centers' data systems vary from a single personal computer running spreadsheet software to a network of servers running an advanced data management system such as Oracle. The challenge for NACC is to expand and adjust previously collected data elements into an integrated database that could be used for administrative as well as research purposes. In addition, NACC sought to allow the centers to have the flexibility they needed for data submission. To accomplish this task, NACC designed a database that contained separate specific datasets each with individual data elements. NACC also designed a data management system to easily collect and manage these data. The NACC web site (www.alz.washington.edu) was created to allow access to the data.