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http://iadrp.nia.nih.gov/content/about-cadro
A classification system developed by the National Institute on Aging and the Alzheimer's Association that can be used to integrate and compare Alzheimer's disease (AD) research portfolios from public and private organizations supporting AD research in the US and abroad. The CADRO was constructed as a three-tier classification system organized around seven major categories: five in research and two resource-related: * Category A. Molecular Pathogenesis and Pathophysiology of Alzheimer's Disease * Category B. Diagnosis, Assessment and Disease Monitoring * Category C. Translational Research and Clinical Interventions * Category D. Epidemiology * Category E. Care, Support and Health Economics of Alzheimer's Diseases * Category F. Research Resources * Category G. Consortia and Public Private Partnerships * Category H. Alzheimer's Disease - Related Dementias Using information from project abstracts and research aims, the above categories were stratified into research topics and these were further divided into research themes. The three levels of classification are meant to enable a fine-grained portfolio analysis that can inform strategic planning and funding decisions. The CADRO was developed as a dynamic portfolio analysis tool that can be used to: (i) capture the changing landscape of AD research funded by different organizations, (ii) identify opportunities for coordination of support for AD research, and (iii) identify funding gaps as well as areas of overlap within and across organizations.
Proper citation: CADRO (RRID:SCR_004046) Copy
Cell repository for Alzheimer's disease that collects and maintains biological specimens and associated data. Its data is derived from large numbers of genetically informative, phenotypically well-characterized families with multiple individuals affected with Alzheimer's disease, as well as individuals for case-control studies.
Proper citation: National Cell Repository for Alzheimer's Disease (RRID:SCR_007313) Copy
Project aimed at making neuroimaging data sets of brain freely available to scientific community. By compiling and freely distributing neuroimaging data sets, future discoveries in basic and clinical neuroscience are facilitated.
Proper citation: Open Access Series of Imaging Studies (RRID:SCR_007385) Copy
http://www.nia.nih.gov/research/nonhuman-primate-tissue-bank-handbook
A repository of tissue collected from nonhuman primate (NHP) species under contractual arrangement with Wisconsin National Primate Research Center (WI NPRC). NIA''''s Nonhuman Primate Tissue Bank collects and archives tissue from necropsies performed at primate centers nationwide. The goal is to collect various tissues from aged monkeys with smaller amounts of the same tissues from young and middle-aged monkeys. Tissue will be provided as: (1) fresh frozen, stored at ����?��������??80 degrees Celsius; (2) formalin fixed; or (3) fresh frozen tissue in OCT medium.Most frozen tissues are provided in approximately 1 gram of tissue per vial. Fixed tissue is available as slides (sections) from paraffin-embedded blocks. Slides can be stained if requested. Tissue from NIA''''s Nonhuman Primate Tissue Bank is available to investigators at academic and nonprofit research institutions who are engaged in funded research on aging. The project name and funding source must accompany all orders. The NIA will not be able to ship non-human primate tissue outside of the United States or US territories. Investigators at for-profit entities are not eligible to purchase tissue from NIA''''s Nonhuman Primate Tissue Bank unless it is for a Small Business Innovation Research grant from NIA. NIA provides the health information as given by the donor site and cannot guarantee other aspects of the health status not explicitly stated in the Vital Statistics Information Sheet. Concerns about the specific health status of donor animals should be indicated on the order form.
Proper citation: NIA Nonhuman Primate Tissue Bank (RRID:SCR_007324) Copy
http://senselab.med.yale.edu/odordb
OdorDb is a database of odorant molecules, which can be searched in a few different ways. One can see odorant molecules in the OdorDB, and the olfactory receptors in ORDB that they experimentally shown to bind. You can search for odorant molecules based on their attributes or identities: Molecular Formula, Chemical Abstracts Service (CAS) Number and Chemical Class. Functional studies of olfactory receptors involve their interactions with odor molecules. OdorDB contains a list of odors that have been identified as binding to olfactory receptors.
Proper citation: Odor Molecules DataBase (RRID:SCR_007286) Copy
Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.
Proper citation: UniProt (RRID:SCR_002380) Copy
Database of polymorphisms and mutations of the human mitochondrial DNA. It reports published and unpublished data on human mitochondrial DNA variation. All data is curated by hand. If you would like to submit published articles to be included in mitomap, please send them the citation and a pdf.
Proper citation: MITOMAP - A human mitochondrial genome database (RRID:SCR_002996) Copy
http://www.dian-info.org/default.htm
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. An international research partnership of leading scientists determined to understand a rare form of Alzheimers disease that is caused by a gene mutation and to establish a research database and tissue repository to support research on Alzheimers disease by other investigators around the world. One goal of DIAN is to study possible brain changes that occur before Alzheimers disease is expressed in people who carry an Alzheimers disease mutation. Other family members without a mutation will serve as a comparison group. People in families in which a mutation has been identified will be tracked in order to detect physical or mental changes that might distinguish people who inherited the mutation from those who did not. DIAN currently involves eleven outstanding research institutions in the United States, United Kingdom, and Australia. John C. Morris, M.D., Friedman Distinguished Professor of Neurology at Washington University School of Medicine in St. Louis, is the principal investigator of the project., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: DIAN - Dominantly Inherited Alzheimer Network (RRID:SCR_000812) Copy
Data set of annual questionnaires of a long-term prospective study of 1,337 former Johns Hopkins University medical students to identify precursors of premature cardiovascular disease and hypertension. The purpose of the study has broadened, however, as the cohort has aged. The study has been funded for 15 years. Participants were an average of 22 years of age at entry and have been followed to an average age of 69 years. Data are collected through annual questionnaires, supplemented with phone calls and substudies. Self-reports of diseases and risk factors have been validated. Every year from 1988 to 2003, anywhere from 2 to 6 questionnaires have been administered, in categories such as the following, which repeat periodically: Morbidity, Supplemental Illness, Health Behavior, Family and Career, Retirement, Job Satisfaction, Blood Pressure and Weight, Medications, Work Environment, Social Network, Diabetes, Osteoarthritis, Health Locus of Control, Preventive Health Services, General Health, Functional Limitations, Memory Functioning, Smoking, Religious Beliefs and Practices, Links with Administrative Data, National Death Index searches for all nonrespondents * Dates of Study: 1946-2003 * Study Features: Longitudinal * Sample Size: 1,337 (1946)
Proper citation: Precursors of Premature Disease and Death (RRID:SCR_010483) Copy
https://portal.brain-map.org/explore/seattle-alzheimers-disease
Open atlas based on single cell profiling technologies with quantitative neuropathology and deep clinical phenotyping from middle temporal gyrus from neurotypical reference brains and brains from SEA-AD aged cohort that span spectrum of Alzheimer’s disease. Produced via collaboration between Allen Institute for Brain Science, University of Washington Alzheimer Disease Research Center and Kaiser Permanente Washington Health Research Institute.
Proper citation: Seattle Alzheimer Disease Brain Cell Atlas (RRID:SCR_023110) Copy
A dataset of a prospective panel study of health and aging in Mexico. The study was designed to ensure comparability with the U.S. Health and Retirement Study in many domains, and the NHANES III. The baseline survey in 2001 is nationally representative of the 13 million Mexicans born prior to 1951. The six Mexican states which are home to 40% of all migrants to the U.S. were over-sampled at a rate of 1.7:1. Spouse/partners of eligible respondents were interviewed also, even if the spouse was born after 1950. Completed interviews were obtained in 9,862 households, for a total of 15,186 individual interviews. All interviews were face-to-face, with average duration of 82 minutes. A direct interview (on the Basic questionnaire) was sought, and Proxy interviews were obtained when poor health or temporary absence precluded a direct interview. Questionnaire topics included the following: * HEALTH MEASURES: self-reports of conditions, symptoms, functional status, hygienic behaviors (e.g., smoking & drinking history), use/source/costs of health care services, depression, pain, reading and cognitive performance; * BACKGROUND: Childhood health and living conditions, education, ability to read/write and count, migration history, marital history; * FAMILY: rosters of all children (including deceased children); for each, demographic attributes, summary indicators of childhood and current health, education, current work status, migration. Parent and sibling migration experiences; * TRANSFERS: financial and time help given to and received by respondent from children, indexed to specific child; time and financial help to parent; * ECONOMIC: sources and amounts of income, including wages, pensions, and government subsidies; type and value of assets. All amount variables are bracketed in case of non-response. * HOUSING ENVIRONMENT: type, location, building materials, other indicators of quality, and ownership of consumer durables; * ANTHROPOMETRIC: for a 20% sub-sample, measured weight, height; waist, hip, and calf circumference; knee height, and timed one-leg stands. Current plans are to conduct another two follow-up surveys in 2012 and 2014 and will field the 3rd and 4th waves of survey data collection in Mexico. For the 2012 wave, interviews will be sought for: every person who was part of the panel in 2003 and their new spouse / partner, if applicable, and a new sample of persons born between 1952 and 1962. For the 2014 wave, we will follow-up the whole sample from 2012. Interviews will be conducted person-to-person. Direct interviews will be sought with all informants, but proxy interviews are allowed for those unable to complete their own interview for health or cognitive reasons. A next-of-kin interview will be completed with a knowledgeable respondent for those who were part of the panel but have died since the last interview. A sub-sample will be selected to obtain objective markers such as blood sample and anthropometric measures. Data Availability: The 2001 baseline data, 2003 follow-up data, and documentation can be downloaded. * Dates of Study: 2001-2003 * Study Features: Longitudinal, International, Anthropometric Measures * Sample Size: 2001: 15,186 (Baseline) Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00142
Proper citation: Mexican Health and Aging Study (RRID:SCR_000818) Copy
http://lgsun.grc.nia.nih.gov/cDNA/cDNA.html
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Project portal housing NIA Mouse EST Project, NIA Mouse cDNA Clone Sets, a NIA Mouse Gene Index, NIA Mouse cDNA Database, and NIA Mouse Microarrays. Characteristics of NIA 15K Mouse cDNA Clone Set * ~15,000 unique cDNA clones were rearrayed among 52,374 ESTs from pre- and periimplantation embryos, E12.5 female gonad/mesonephros, and newborn ovary. * Up to 50% are derived from novel genes. * ~1.5 kb average insert size. * Clones were sequenced from 5' and 3' termini to obtain longer reads and verify sequence. Sequence information is available at this Web Site. Clone names are from H3001A01 to H3159G07. * Handling of NIA 15k cDNA Clone Set(June3, 2000) Characteristics of NIA mouse 7.4K cDNA Clone Set * ~7407 cDNA clones with no redundancy within the set or with NIA Mouse 15K. * ~1.5 kb average insert size for short insert clones and ~2.5-3.0 kb average insert size for long-insert enriched clones.. * Clones were sequenced from 5' and 3' termini to obtain longer reads and verify sequence. Sequence information is available at this Web Site. Clone names are from H4001A01 to H4079G07. * Handling of NIA mouse 7.4k cDNA Clone Set (similar to handling of NIA mouse 15K, to be updated) Individual Clones are available from ATCC and MRC geneservice, UK. To obtain Clone, search the database using either the rearrayed clone name or GenBank accession number at the Key Word Search page. Follow the link to the sequence information page for the rearrayed clone to obtain source clone ATCC number. Clicking the ATCC number will bring up the ATCC ordering page for the source clone. There is essentially no overlap between the two clone sets (7.4K and 15K) said Minoru S.H. Ko, M.D., Ph.D., head of the Developmental Genomics and Aging Section in the NIA's Laboratory of Genetics. In addition, all cDNA clones in the NIA 7.4K set were purified by single colony isolation and sequence-verified, and more than half were prepared by a new procedure that yields long full-length cDNAs (average size 3-4 kb). The NIA Mouse 15k and 7.4k Clone Set Data and Published Microarray Data are available for download. NIA Mouse Microarrays *Microarray Data Download * 60-mer Oligo Array Platform ** (A) NIA 22k Oligo Microarray Gene List (21939 gene features) ( Carter et al 2003 ) ** (B) Agilent Mouse Development Oligo Microarray Gene List ** ( Subset of Microarray (A): 20,280 gene features ) * Data Analysis Tools
Proper citation: NIA Mouse cDNA Project Home Page (RRID:SCR_001472) Copy
http://cbl.uh.edu/ORION/research/software
ORION is our neuron reconstruction software package developed for the morphological reconstruction of neurons from confocal and multiphoton microscopy data. It accepts raw neuron stack data as input and it is capable of reconstructing the neuron structure, visualizing the output, and exporting the reconstruction in a variety of formats. We are developing tools that will enable Neuroscientists to explore single neuron function via sophisticated image analysis. Advanced optical imaging can produce both structural and functional data and is at the forefront of experimentally exploring the fast, small-scale dynamics of living neurons. Further, compartmental modeling of neuronal function enables rapid testing of hypotheses and estimating experimentally inaccessible parameters. Combining these two techniques will afford unprecedented capabilities in the study of single neuron function. Our software utility bridges the two Neuroscience techniques by rapidly, accurately, and robustly generating, from structural image data, a cylindrical morphology model suitable for simulating neuronal function.
Proper citation: ORION Software (RRID:SCR_004389) Copy
http://www.flinders.edu.au/sabs/fcas/alsa/alsa_home.cfm
The general purpose of ALSA is to examine how social, biomedical, psychological, economic, and environmental factors are associated with age-related changes in the health and wellbeing of persons aged 70 years and older. The aim is to analyze the complex relationships between individual and social factors and changes in health status, health care needs and service utilization dimensions, with emphasis given to the effects of social and economic factors on morbidity, disability, acute and long-term care service use, and mortality. The study was designed to have common instrumentation with US studies. ALSA collected data from a random, stratified sample of all persons (both community and institution-dwelling) aged 70 years and older living in the metropolitan area of Adelaide, South Australia, using the State Electoral Database as the sampling frame. Spouses aged 65 and older and other household members aged 70 years and older also were invited to participate. The initial baseline data collection for ALSA began in September 1992 and was completed in March 1993. In the first wave, personal interviews were carried out for 2,087 participants, including 566 couples (that is, persons 70 years of age and over and their spouse, if 65 and over). Clinical assessments were obtained for 1,620 of the participants. Respondents were recontacted by telephone a year after initial interview (wave 2). The third wave of the study began in September 1994 and involved a complete reassessment, with a total of 1,679 interviews and 1,423 clinical assessments. To date, eleven waves of data have been collected, with the latest collection in May 2010, from 168 participants. Six of these waves were conducted via face-to-face interviews and clinical assessments, and five were telephone interviews. Future waves are planned, however are dependent on grant funding. Ancillary data collection has been ongoing since the initiation of the study, e.g., from secondary providers. Lists of ALSA participants are compared biannually with the agencies'' lists to determine the prevalence and incidence of receipt of services from these organizations. Another source of information has been the collection of data from the participants'' general practitioners about the respondent''s health status, history of services received, medication use, referrals to specialists, and current services provided. Baseline Sample Size: 2087 Dates of Study: 1992����������2010 (potentially ongoing) Study Features: * Longitudinal * International * Anthropometric Measures * Biospecimens Waves 1-5 (ICPSR), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06707 Wave 6 (ICPSR), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03679
Proper citation: ALSA - The Australian Longitudinal Study of Ageing (RRID:SCR_013146) Copy
http://www.rand.org/labor/FLS/IFLS.html
A dataset of an on-going multi-level longitudinal survey in Indonesia that collects extensive information on socio-economic and demographic characteristics of respondents, as well as extremely comprehensive interviews with local leaders about community services and facilities. The survey is ideally suited for research on topics related to important dynamic aging processes such as the transition from self-sufficiency to dependency, the decline from robust health to frailty, labor force and earning dynamics, wealth accumulation and decumulation, living arrangements and intergenerational transfers. The first wave of IFLS was fielded in 1993 and collected information on over 30,000 individuals living in 7,200 households. The sample covers 321 communities in 13 provinces in Indonesia and is representative of about 83% of the population. These households were revisited in 1997 (IFLS2), 2000 (IFLS3), and 2007-8 (IFLS4). A 25% sub-sample of households was re-interviewed in 1998 (IFLS2+). Special attention is paid to the measurement of health, including the measurement of anthropometry, blood pressure, lung capacity, a mobility test and collection of dry blood spots by a nurse or doctor. In addition to comprehensive life history data on education, work, migration, marriage and child bearing, the survey collects very detailed information on economic status of individuals and households. Links with non co-resident family members are spelled out in conjunction with information on borrowing and transfers. Information is gathered on participation in community activities and in public assistance programs. Measurement of health is a major focus of the survey. In addition to detailed information about use of private and public health services along with insurance status, respondents provide a self-reported assessment of health status. Detailed information on the local economy and prices of goods and services are also collected. These data may be matched with the individual and household-level data. Considerable attention has been placed on minimizing attrition in IFLS. In each re-survey, about 95% of households have been re-contacted. Around 10-15% of respondents have moved from the location in which they were interviewed in the previous wave. In addition, individuals who split-off from the original households have been followed. They have added around 1,000 households to the sample in 1997 and about 3,000 households in 2000. Data Availability: IFLS1 data are available through ICPSR as study number 6706. Data from subsequent waves of the IFLS can be accessed from the RAND project Website. * Dates of Study: 1993-2008 * Study Features: Longitudinal, International, Anthropometric Measures, Biomarkers * Sample Size: ** 1993: 22,000 (IFLS1) ** 1997: 33,000 (IFLS2) ** 1998: 10,000 (IFLS2+) ** 2000: 37,000 (IFLS3) ** 2008: 44,103 (IFLS4) Links: * IFLS1 ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06706 * IFLS ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00184
Proper citation: Indonesia Family Life Survey (RRID:SCR_005695) Copy
http://www.alz.washington.edu/
A clinical research, neuropathological research and collaborative research database that uses data collected from 29 NIA-funded Alzheimer's Disease Centers (ADCs). The database consists of several datasets, and searches may be done on the entire database or on individual datasets. Any researcher, whether affiliated with an ADC or not, may request a data file for analysis or aggregate data tables. Requested aggregate data tables are produced and returned as soon as the queue allows (usually within 1-3 days depending on the complexity).
Proper citation: National Alzheimer's Coordinating Center (RRID:SCR_007327) Copy
A dataset of a panel study of a representative sample of all neighborhoods and households in Los Angeles County, with poor neighborhoods and families with children oversampled, for investigating the social and economic determinants of health and race and ethnic disparities. The study follows neighborhoods over time, as well as children and families. Two waves have been conducted to date, in 2000-2001 (L.A.FANS 1) and again beginning in 2006 through early 2009 (L.A. FANS 2). L.A.FANS-2 will significantly enhance the utility of the L.A.FANS data for studies of adult health disparities by: 1) Replicating self-reported health measures from L.A.FANS-1 and collecting new self-reports on treatment, health behaviors, functional limitations, quality and quantity of sleep, anxiety, health status vignettes, and changes in health status since the first interview; 2) Collecting physiological markers of disease and health status, including diabetes, hypertension, obesity, lung function, immune function, and cardiovascular disease; and 3) Expanding the data collected on adults'' work conditions, stressful experiences, and social ties. Wherever possible, L.A.FANS uses well-tested questions or sections from national surveys, such as the Health and Retirement Study (HRS), Panel Study of Income Dynamics (PSID), National Longitudinal Surveys (NLS), and National Health Interview Survey (NHIS), and other urban surveys, such as the Project on Human Development in Chicago Neighborhoods, to facilitate comparisons. Data Availability: Public use data, study design, and questionnaire content from L.A.FANS are available for downloading. Researchers can also apply for a restricted use version of the L.A.FANS-1 data that contain considerable contextual and geographically-referenced information. Application procedures are described at the project Website. L.A.FANS-2 fieldwork was completed at the end of 2008. The PIs anticipate L.A.FANS-2 public use data will be released in summer 2009. * Dates of Study: 2000-2008 * Study Features: Longitudinal, Minority Oversamples, Anthropometric Measures, Biospecimens * Sample Size: ** 2000-1: 2,548 (L.A.FANS 1) ** 2006-8: ~3,600 (L.A.FANS 2) Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00172
Proper citation: Los Angeles Family and Neighborhood Survey (RRID:SCR_008923) Copy
A study that characterizes the extent of change in body composition in older men and women, identifies clinical conditions accelerating these changes, and examines the health impact of these changes on strength, endurance, disability, and weight-related diseases of old age. The study population consists of 3,075 persons age 70-79 at baseline with about equal numbers of men and women. Thirty-three percent of the men are African-Americans as are 46% of the women. All persons in the study were selected to be free of disability in activities of daily living and free of functional limitation (defined as any difficulty walking a quarter of a mile or any difficulty walking up 10 steps without resting) at baseline. The core yearly examination for HEALTH ABC includes measurement of body composition by dual energy x-ray absorptio��������metry (DXA), walking ability, strength, an interview that includes self-report of limitations, a medication survey, and weight (Measurements in the Health ABC Study). Provision has been made for banking of blood specimens and extracted DNA (HealthABC repository). Study investigators are open to collaboration especially for measures focused on obesity and associated weight-related health conditions including osteoporosis, osteoarthritis, pulmonary function, cardiovascular disease, vascular disease, diabetes and glucose intolerance, and depression. The principal goals of the HEALTH ABC are: # To assess the association of baseline body weight, lean body mass, body fat, and bone mineral content, in relation to weight history, with: incident functional limitation; incidence and change in severity of weight-related health conditions; recovery of physical function after an acute event; baseline measures of strength, fitness and physical performance; gender, ethnicity and socioeconomic status # To access the contribution of episodes of severe acute illness in healthier older persons to changes in body weight, bone mineral content, lean body mass and body fat, and the relationship of these episodes to risk of functional limitation and recovery. # To assess the impact of weight-related co-morbid illness on the risk of functional limitation and recovery. # To assess the ways in which physiologic mediators of change in body composition influence and are influenced by changes in health in older adults and contribute to change in body composition; to understand how changes in body composition affect weight-related cardiovascular disease risk factors such as lipids, blood pressure and glucose tolerance. # To assess the interdependency of behavioral factors, such as nutrition and physical activity, co-morbid health conditions, and their association with change in body composition in old age. # To provide a firm scientific basis for understanding issues related to weight recommendations in old age through increased knowledge of the potential trade-offs between weight and risk of functional limitation, disability, morbidity and death; to provide information critical for developing effective strategies for the maintenance of health in older persons.
Proper citation: Dynamics of Health Aging and Body Composition (Health ABC) (RRID:SCR_008813) Copy
http://hrsonline.isr.umich.edu/
A data set of a longitudinal panel study of health, retirement, and aging that surveys a representative sample of more than 26,000 Americans over the age of 50 every two years. The HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. The study captures a dynamic picture of an aging America''s physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The sample in 2006 numbered over 22,000 persons in 13,100 households, with oversamples of Hispanics, Blacks and Florida residents. Beginning in 2006, half the sample received enhanced face-to-face follow-ups that included the collection of physical measures and biomarkers HRS provides a research data base that can simultaneously support continuous cross-sectional descriptions of the US population over the age of fifty-five, longitudinal studies of a given cohort over a substantial period of time (up to 18 years by 2010 for the original HRS cohort, following them from age 51-61 to age 69-79) and research on cross-cohort trends. By 2010 the HRS will be able to support cross-cohort comparisons of trajectories of health, labor supply, or wealth accumulation for persons who entered their 50s in 1992, 1998 and 2004. The HRS also has provided the sampling frame for targeted sub-studies. The Aging, Demographics, and Memory Study (ADAMS) supplement on dementia involved a field assessment of a sample of about 930 HRS panel members aged 75+ to clinically assess their dementia status and dementia severity. Special topics including consumption and time use, prescription drug use and the impact of Medicare Part D, parents'' human capital investments in children, and diabetes management by self-reported diabetics, have appeared on mail surveys that have used the HRS as a sampling frame. The HRS also can accommodate a number of experimental topics using Internet interviewing. The HRS is also characterized by links to a rich array of administrative data, including: Employer Pension Plans; National Death Index; Social Security Administration earnings and (projected) benefits data; W-2 self-employment data; and Medicare and Medicaid files. The HRS has actively collaborated with other longitudinal studies of aging in other countries (e.g., ELSA, SHARE, MHAS), providing both scientific and technical assistance. Data Availability: All publicly available data may be downloaded after registration. Early Release data files are typically available within three months of the end of each data collection, with the Final Release following at 24 months after the close of data collection activities. Files linked with administrative data are released only as restricted data through an application process, as outlined on the HRS website. * Dates of Study: 1992-present * Study Features: Longitudinal, Minority Oversamples, Anthropometric Measures, Biospecimens * Sample Size: 22,000+ Link * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06854
Proper citation: Health and Retirement Study (RRID:SCR_008930) Copy
http://neurogenetics.nia.nih.gov
A suite of web-based open source software programs for clinical and genetic study. The aims of this software development in the Laboratory of Neurogenetics, NIA, NIH are * Build retrievable clinical data repository * Set up genetic data bank * Eliminate redundant data entries * Alleviate experimental error due to sample mix-up and genotyping error. * Facilitate clinical and genetic data integration. * Automate data analysis pipelines * Facilitate data mining for genetic as well as environmental factors associated with a disease * Provide an uniformed data acquisition framework, regardless the type of a given disease * Accommodate the heterogeneity of different studies * Manage data flow, storage and access * Ensure patient privacy and data confidentiality/security. The GERON suite consists of several self contained and yet extensible modules. Currently implemented modules are GERON Clinical, Genotyping, and Tracking. More modules are planned to be added into the suite, in order to keep up with the dynamics of the research field. Each module can be used separately or together with others into a seamless pipeline. With each module special attention has been given in order to remain free and open to the academic/government user., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: GERON (RRID:SCR_008531) Copy
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