<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Zeng X</submitter><funding>NIA NIH HHS</funding><funding>National Institutes of Health</funding><funding>NIH HHS</funding><pagination>40</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11095038</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>19(1)</volume><pubmed_abstract>Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD t</pubmed_abstract><journal>Molecular neurodegeneration</journal><pubmed_title>Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting.</pubmed_title><pmcid>PMC11095038</pmcid><funding_grant_id>P30 AG066468</funding_grant_id><funding_grant_id>R01 AG083874</funding_grant_id><pubmed_authors>Klunk WE</pubmed_authors><pubmed_authors>Cohen AD</pubmed_authors><pubmed_authors>Lee J</pubmed_authors><pubmed_authors>Zeng X</pubmed_authors><pubmed_authors>Tudorascu DL</pubmed_authors><pubmed_authors>Villemagne VL</pubmed_authors><pubmed_authors>Lopez OI</pubmed_authors><pubmed_authors>Zetterberg H</pubmed_authors><pubmed_authors>Berman SB</pubmed_authors><pubmed_authors>Ikonomovic MD</pubmed_authors><pubmed_authors>Kamboh MI</pubmed_authors><pubmed_authors>Sehrawat A</pubmed_authors><pubmed_authors>Pascoal TA</pubmed_authors><pubmed_authors>Snitz BE</pubmed_authors><pubmed_authors>Chen Y</pubmed_authors><pubmed_authors>Kofler J</pubmed_authors><pubmed_authors>Sweet RA</pubmed_authors><pubmed_authors>Pfister A</pubmed_authors><pubmed_authors>Lafferty TK</pubmed_authors><pubmed_authors>Karikari TK</pubmed_authors><pubmed_authors>Blennow K</pubmed_authors></additional><is_claimable>false</is_claimable><name>Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting.</name><description>Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD t</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 May</publication><modification>2026-07-16T07:33:54.813Z</modification><creation>2026-07-09T10:44:04.255Z</creation></dates><accession>S-EPMC11095038</accession><cross_references><pubmed>38750570</pubmed><doi>10.1186/s13024-024-00711-1</doi></cross_references></HashMap>