Abstract 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.