SomaScan® Platform confirmation and performance validation
The SomaScan® Platform for proteomic profiling uses 7,288 (7K) SOMAmer® reagents, single-stranded DNA aptamers, to 6,596 unique human protein targets. The modified aptamer binding reagents1, SomaScan Assay2, its performance characteristic for 5K3 and 7K4 content sets, and specificity5,6,7 to human targets have been previously described. We combine profiles of validation and performance metrics with orthogonal confirmation of specificity from published literature to provide a comprehensive view of the specificity and utility of the SomaScan Platform.
Validation of SOMAmer reagents results in a set of metrics that profile performance of the reagents to the protein standards used
for discovery. These include linear ranges and affinity measures: dose response 50 (apparent K D ), and solution K D . Validation of the SomaScan Platform includes replicates of individual and pooled samples over 15 assay runs in both plasma and serum.
Population ranges and performance are generated from matched plasma and serum drawn from more than 1,000 U.S. normal volunteers. Reproducibility and signaling metrics are summarized and reported. Production use of the SomaScan Platform includes replicates to monitor the accuracy and precision of the assay over time. Results from more than 3,000 replicates are aggregated and reported.
Secondary confirmation of specificity is explored using published outcomes from alternative proteomic or genomic profiling methods. Results are extracted from the literature and assembled by reagent identifier. Alternative experiments that confirm protein targets are described and reported separately.
The SomaScan® Platform for proteomic profiling relies on a deep validation workflow for reagents and for the platform. Transparency in the methods and results is critical to help users interpret platform results.
SomaLogic Operating Co., Inc., Boulder, CO USA
- Rohloff JC, Gelinas AD, Jarvis TC, et al. Nucleic Acid Ligands With Protein-like Side Chains: Modified Aptamers and Their Use as Diagnostic and Therapeutic Agents. Molecular Therapy Nucleic Acids 2014; 3: e201.
- Gold L, Ayers D, Bertino J, et al. Aptamer-based multiplexed proteomic technology for biomarker discovery. PLoSOne 2010; 5(12): e15004.
- Kim CH, Tworoger SS, Stampfer MJ, et al. Stability and reproducibility of proteomic profiles measured with an aptamer based platform. Sci Rep 2018; 8(1): 8382.
- Candia J, Daya GN, Tanaka T, et al. Assessment of variability in the plasma 7K SomaScan proteomics assay. Sci Rep 12, 17147 (2022).
- Sun BB, Maranville JC, Peters JE, et al. Genomic atlas of the human plasma proteome. Nature 2018; 558(7708): 73-9.
- Emilsson V, Ilkov M, Lamb JR, et al. Co-regulatory networks of human serum proteins link genetics to disease. Science 2018; 361(6404): 769-73.
- Pietzner M, et al. Mapping the proteo-genomic convergence of human diseases. Science 2021; Vol 374, Issue 6569
- Candia J, et al. Assessment of variability in the plasma 7K SomaScan proteomics assay. Sci Rep 2022, Oct 13;12(1):17147. doi: 10.1038/s41598-022-22116-0. PMID: 36229504; PMCID: PMC9561184.
PosterLatest research shows benefit of non-invasive, high-plex protein profiling for liver disease
Learn about using high-plex, aptamer-based protein profiling for NASH research through these three SomaLogic assets. Watch one webinar and download two posters that each highlight NASH research.
PosterProteomic Indicators of Metabolic Health in Diabetes and Social Deprivation
Understanding the health impacts of socioeconomic deprivation (SED) and its interaction with type 2 diabetes is important for patient care and effective public health initiatives. Large-scale proteomic profiling using aptamer-based technology to measure 7,000 proteins has facilitated the development of blood-based proteomic signatures for 11 cardiometabolic SomaSignalTM Tests (SST)
PosterHeritability, pQTLs, and environmental influence on proteins involved in age, cardiovascular risk, and glucose tolerance using the SomaScan® Assay
Protein quantitative trait locus (“pQTL”) studies identify genetic variants that are statistically associated with protein levels. Results from the growing number of pQTL studies can be combined with genome-wide association studies to identify proteins that underlie the genetic risk of disease, thus revealing the mechanisms of disease and potential drug targets.