Biomarker Core

$274,062P30FY2025AGNIH

Stanford University, Stanford CA

Investigators

Linked publications, trials & patents

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Abstract

SUMMARY BIOMARKER CORE The Stanford ADRC Biomarker Core works to provide deep-genotyping and deep-phenotyping data to strengthen the biological evidence for clinical classifications of participants as healthy older controls, Alzheimerâs disease (AD) spectrum patients, and Lewy body disease (LBD) spectrum patients. To this end the Core will measures current consensus AD biomarkers such as pTau217 and the AÎ²42: AÎ²40 ratio in plasma of all ADRC participants as well as in the cerebrospinal fluid (CSF) of those who agree to lumbar puncture. All CSF samples will be also sent for the CLIA-approved alpha-synuclein seeding assay (Î±Syn-SAA), a new consensus biomarker for LBD. In addition to providing consensus biomarkers for AD and LBD, the Core will generate a large amount of multiomics dataâincluding proteomics, lipidomics, and glycomicsâfor discovery science. All Stanford ADRC participants will have high-coverage (~30x), whole-genome long-read sequencing data which will allow accurate calling of single nucleotide variants, structural variants and methylation profiles. The hope is that wide sharing of these data from these deeply-genotyped and deeply-phenotyped ADRC participants will accelerate discovery science leading to novel biomarkers, novel pathogenic insights, and novel drug targets. To maximize the impact of these datasets, the Biomarker Core will work closely with the Data Management and Statistics Core to provide quality-controlled summary data that will be queryable through a web portal. Raw datasets will be made available through the Alzheimerâs Disease Data Initiative, an NIH- supported data repository. The Biomarker Core faculty and senior staff will hold quarterly data showcases and provide training opportunities for scholars in the Research and Education Component as well as trainees and investigators new to multiomics research. Specific efforts will be made, in conjunction with the Justice, Equity, Diversity and Inclusion (JEDI) team, to support trainees and investigators from underrepresented in biomedical research groups in making full use of these data.

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