Assessing accuracy of protein measurements across multiple analytical platforms. Our NIA funded project, UH2AG064704 “Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategies”, is a phased UH2/UH3 project. We are currently in the UH2 phase, in which we achieve specific milestones to set the stage for and facilitate the conduct of the UH3 phase. Among the major UH2 milestones, we are recruiting and enrolling 1,400 centenarians and their offspring, and we are collecting their phenotype data, blood and fecal samples. In the UH3 phase, we will generate multi-omics profiles of those samples and correlate them with extreme human longevity phenotypes. Other major milestones of the UH2 phase include planning for the generation of omics data and developing analyses pipelines that we will use in the UH3 phase of the project. We have made substantial progress toward enrollment, data management, and plans for the majority of omics data and we also realized the importance of using an accurate data generating platform that is well harmonized with those used by other studies of human extreme longevity such as the Long Life Family Study and the Longevity Consortium. In our parent application, we proposed to use the SOMAscan technology to generate serum proteomics. Alternative proteomics approaches include labelled mass spectrometry and the Olink Explore platforms. These three mainstream technologies have pros and cons in terms of required sample preparation, coverage of the human proteome, accuracy of protein abundance assessment, and specificity of proteins detection and their performance has not been compared in a comprehensive way. In this request for an administrative supplement we propose to generate data that will inform the choice of the best proteomic platform to be used in the UH3 phase of the project. We have the opportunity to join forces with other studies of human extreme longevity to compare mass spectrometry, SOMAscan and Olink platforms using a well-designed spike-in experiment. We propose two specific aims. Specific Aim 1: To generate SOMAlogic-based proteomic profiles of 250 samples that represent triplicates of one control condition, and 6 pools including 8 different proteins spiked at 13 different abundance, for a total of 3 + 3𝑥6𝑥13 = 237 samples. We will add an additional 13 blank samples for quality control. Specific Aim 2: To conduct quality control analysis of the proteomic profiles generated using the SOMAscan, Olink and Mass-spectrometry technologies. Cleaned and normalized data will be used to analyze the dosage-based trajectories of protein abundance to detect proteins that change in the different pools and to estimate sensitivity and specificity of protein detection of the SOMAscan, Olink and mass-spectrometry technologies. The comparison of data generated with the Somascan technology versus alternative technology will provide critical information to guide the selection o...