{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Xiong C"],"funding":["Research and Development","NIBIB NIH HHS","NIA NIH HHS","Alzheimer&apos;s Association","Science and Industry Endowment Fund","National Institute on Aging","Deutsches Zentrum für Neurodegenerative Erkrankungen","Dementia Collaborative Research Centres, Australia","Alzheimer&apos;s Drug Discovery Foundation","Japan Agency for Medical Research and Development","Korea Health Industry Development Institute","National Health and Medical Research Council","NINDS NIH HHS","McCusker Alzheimer&apos;s Research Foundation"],"pagination":["1448-1457"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6874758"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(11)"],"pubmed_abstract":["<h4>Introduction</h4>Large longitudinal biomarkers database focusing on middle age is needed for Alzheimer's disease (AD) prevention.<h4>Methods</h4>Data for cerebrospinal fluid analytes, molecular imaging of cerebral fibrillar β-amyloid with positron emission tomography, magnetic resonance imaging-based brain structures, and clinical/cognitive outcomes were harmonized across eight AD biomarker studies. Statistical power was estimated.<h4>Results</h4>The harmonized database included 7779 participants with clinical/cognitive data: 3542 were 18∼65 years at the baseline, 5865 had longitudinal cognitive data for a median of 4.7 years, 2473 participated in the cerebrospinal fluid studies (906 had longitudinal data), 2496 participated in the magnetic resonance imaging studies (1283 had longitudi"],"journal":["Alzheimer's & dementia : the journal of the Alzheimer's Association"],"pubmed_title":["A harmonized longitudinal biomarkers and cognition database for assessing the natural history of preclinical Alzheimer's disease from young adulthood and for designing prevention trials."],"pmcid":["PMC6874758"],"funding_grant_id":["R01 AG059869","R01 AG053550","UF1AG032438","R01 AG027161","UF1 AG032438","P50 AG033514","P50 AG005681","P01AG026276","U19 AG032438","P30 AG066507","P01 AG0399131","P30 AG062715","P50AG033514","U19 AG033655","RF1 AG059869","P30 NS098577","RF1 AG053550","RF1 AG027161","R01 EB009352","P01 AG026276","R01 AG021155","R01‐AG027161","P01 AG003991","U19‐AGO33655"],"pubmed_authors":["Koscik RL","Agboola F","Hassenstab J","Dominantly Inherited Alzheimer Network","Fagan AM","Villemagne VL","Bateman RJ","Masters CL","Soldan A","Morris JC","Massoumzadeh P","Albert M","Benzinger T","Li Y","Johnson SC","McDade EM","Luo J","Li QX","Xiong C"],"additional_accession":[]},"is_claimable":false,"name":"A harmonized longitudinal biomarkers and cognition database for assessing the natural history of preclinical Alzheimer's disease from young adulthood and for designing prevention trials.","description":"<h4>Introduction</h4>Large longitudinal biomarkers database focusing on middle age is needed for Alzheimer's disease (AD) prevention.<h4>Methods</h4>Data for cerebrospinal fluid analytes, molecular imaging of cerebral fibrillar β-amyloid with positron emission tomography, magnetic resonance imaging-based brain structures, and clinical/cognitive outcomes were harmonized across eight AD biomarker studies. Statistical power was estimated.<h4>Results</h4>The harmonized database included 7779 participants with clinical/cognitive data: 3542 were 18∼65 years at the baseline, 5865 had longitudinal cognitive data for a median of 4.7 years, 2473 participated in the cerebrospinal fluid studies (906 had longitudinal data), 2496 participated in the magnetic resonance imaging studies (1283 had longitudi","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Nov","modification":"2026-04-30T06:27:28.712Z","creation":"2020-11-03T08:03:18Z"},"accession":"S-EPMC6874758","cross_references":{"pubmed":["31506247"],"doi":["10.1016/j.jalz.2019.06.4955"]}}