Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
Plasma proteomic Alzheimer's risk score: Biological age clock and pseudotime trajectory.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
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Liu Shiwei, Huang Yen-Ning, Park Tamina, Lee Eun Hye, Chaudhuri Soumilee, Adzibolosu Nicholas, Bice Paula J, Dage Jeffrey L, Brosch Jared R, Gao Sujuan, Apostolova Liana G, Wilcock Donna M, Risacher Shannon L, Saykin Andrew J, Nho Kwangsik
Аннотация
INTRODUCTION: Alzheimer's disease (AD) involves progressive cognitive decline. Plasma proteomics data may provide insights into disease risk and mechanisms.
METHODS: Plasma proteomics data (N = 498) by the SomaScan 7k platform from the Indiana AD Research Center was used to calculate proteomics-based Alzheimer's risk scores: organ-specific aging clocks and pseudotime trajectory. The Alzheimer's risk scores were investigated for associations with plasma- and imaging-based biomarkers for AD and diagnosis and evaluated for classification performance for diagnosis and biomarker positivity status.
RESULTS: Cognition-optimized brain and liver age acceleration showed significant associations with AD diagnosis and biomarkers. Pseudotime showed a molecular trajectory from cognitively normal to AD individuals, in association with plasma and imaging biomarkers. Previously known plasma biomarkers yielded better classification performance with inclusion of proteomics-based Alzheimer's risk scores.
DISCUSSION: The findings highlight proteomics-derived biological aging clocks and pseudotime trajectory as potential biomarkers to complement current biomarker frameworks and identify disease mechanisms.
HIGHLIGHTS: Plasma proteomic aging clocks and pseudotime provide potential markers for Alzheimer's disease (AD) risk. Cognition-optimized brain aging and pseudotime link to diagnosis and AD biomarkers. Brain aging clock and pseudotime improve the diagnosis classification performance. Pseudotime outperformed established plasma biomarkers for diagnosis classification.
METHODS: Plasma proteomics data (N = 498) by the SomaScan 7k platform from the Indiana AD Research Center was used to calculate proteomics-based Alzheimer's risk scores: organ-specific aging clocks and pseudotime trajectory. The Alzheimer's risk scores were investigated for associations with plasma- and imaging-based biomarkers for AD and diagnosis and evaluated for classification performance for diagnosis and biomarker positivity status.
RESULTS: Cognition-optimized brain and liver age acceleration showed significant associations with AD diagnosis and biomarkers. Pseudotime showed a molecular trajectory from cognitively normal to AD individuals, in association with plasma and imaging biomarkers. Previously known plasma biomarkers yielded better classification performance with inclusion of proteomics-based Alzheimer's risk scores.
DISCUSSION: The findings highlight proteomics-derived biological aging clocks and pseudotime trajectory as potential biomarkers to complement current biomarker frameworks and identify disease mechanisms.
HIGHLIGHTS: Plasma proteomic aging clocks and pseudotime provide potential markers for Alzheimer's disease (AD) risk. Cognition-optimized brain aging and pseudotime link to diagnosis and AD biomarkers. Brain aging clock and pseudotime improve the diagnosis classification performance. Pseudotime outperformed established plasma biomarkers for diagnosis classification.