<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Xiong C</submitter><funding>Research and Development</funding><funding>NIBIB NIH HHS</funding><funding>NIA NIH HHS</funding><funding>Alzheimer&amp;apos;s Association</funding><funding>Science and Industry Endowment Fund</funding><funding>National Institute on Aging</funding><funding>Deutsches Zentrum für Neurodegenerative Erkrankungen</funding><funding>Dementia Collaborative Research Centres, Australia</funding><funding>Alzheimer&amp;apos;s Drug Discovery Foundation</funding><funding>Japan Agency for Medical Research and Development</funding><funding>Korea Health Industry Development Institute</funding><funding>National Health and Medical Research Council</funding><funding>NINDS NIH HHS</funding><funding>McCusker Alzheimer&amp;apos;s Research Foundation</funding><pagination>1448-1457</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6874758</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>15(11)</volume><pubmed_abstract>&lt;h4>Introduction&lt;/h4>Large longitudinal biomarkers database focusing on middle age is needed for Alzheimer's disease (AD) prevention.&lt;h4>Methods&lt;/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.&lt;h4>Results&lt;/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</pubmed_abstract><journal>Alzheimer's &amp; dementia : the journal of the Alzheimer's Association</journal><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.</pubmed_title><pmcid>PMC6874758</pmcid><funding_grant_id>R01 AG059869</funding_grant_id><funding_grant_id>R01 AG053550</funding_grant_id><funding_grant_id>UF1AG032438</funding_grant_id><funding_grant_id>R01 AG027161</funding_grant_id><funding_grant_id>UF1 AG032438</funding_grant_id><funding_grant_id>P50 AG033514</funding_grant_id><funding_grant_id>P50 AG005681</funding_grant_id><funding_grant_id>P01AG026276</funding_grant_id><funding_grant_id>U19 AG032438</funding_grant_id><funding_grant_id>P30 AG066507</funding_grant_id><funding_grant_id>P01 AG0399131</funding_grant_id><funding_grant_id>P30 AG062715</funding_grant_id><funding_grant_id>P50AG033514</funding_grant_id><funding_grant_id>U19 AG033655</funding_grant_id><funding_grant_id>RF1 AG059869</funding_grant_id><funding_grant_id>P30 NS098577</funding_grant_id><funding_grant_id>RF1 AG053550</funding_grant_id><funding_grant_id>RF1 AG027161</funding_grant_id><funding_grant_id>R01 EB009352</funding_grant_id><funding_grant_id>P01 AG026276</funding_grant_id><funding_grant_id>R01 AG021155</funding_grant_id><funding_grant_id>R01‐AG027161</funding_grant_id><funding_grant_id>P01 AG003991</funding_grant_id><funding_grant_id>U19‐AGO33655</funding_grant_id><pubmed_authors>Koscik RL</pubmed_authors><pubmed_authors>Agboola F</pubmed_authors><pubmed_authors>Hassenstab J</pubmed_authors><pubmed_authors>Dominantly Inherited Alzheimer Network</pubmed_authors><pubmed_authors>Fagan AM</pubmed_authors><pubmed_authors>Villemagne VL</pubmed_authors><pubmed_authors>Bateman RJ</pubmed_authors><pubmed_authors>Masters CL</pubmed_authors><pubmed_authors>Soldan A</pubmed_authors><pubmed_authors>Morris JC</pubmed_authors><pubmed_authors>Massoumzadeh P</pubmed_authors><pubmed_authors>Albert M</pubmed_authors><pubmed_authors>Benzinger T</pubmed_authors><pubmed_authors>Li Y</pubmed_authors><pubmed_authors>Johnson SC</pubmed_authors><pubmed_authors>McDade EM</pubmed_authors><pubmed_authors>Luo J</pubmed_authors><pubmed_authors>Li QX</pubmed_authors><pubmed_authors>Xiong C</pubmed_authors></additional><is_claimable>false</is_claimable><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.</name><description>&lt;h4>Introduction&lt;/h4>Large longitudinal biomarkers database focusing on middle age is needed for Alzheimer's disease (AD) prevention.&lt;h4>Methods&lt;/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.&lt;h4>Results&lt;/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</description><dates><release>2019-01-01T00:00:00Z</release><publication>2019 Nov</publication><modification>2026-04-30T06:27:28.712Z</modification><creation>2020-11-03T08:03:18Z</creation></dates><accession>S-EPMC6874758</accession><cross_references><pubmed>31506247</pubmed><doi>10.1016/j.jalz.2019.06.4955</doi></cross_references></HashMap>