Dataset Information

Assessment of Variability in the SOMAscan Assay.

ABSTRACT: SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human protein analytes in serum, plasma, and other biological matrices with high sensitivity and specificity. In this work, we present a comprehensive meta-analysis of performance based on multiple serum and plasma runs using the current 1.3?k assay, as well as the previous 1.1?k version. We discuss normalization procedures and examine different strategies to minimize intra- and interplate nuisance effects. We implement a meta-analysis based on calibrator samples to characterize the coefficient of variation and signal-over-background intensity of each protein analyte. By incorporating coefficient of variation estimates into a theoretical model of statistical variability, we also provide a framework to enable rigorous statistical tests of significance in intervention studies and clinical trials, as well as quality control within and across laboratories. Furthermore, we investigate the stability of healthy subject baselines and determine the set of analytes that exhibit biologically stable baselines after technical variability is factored in. This work is accompanied by an interactive web-based tool, an initiative with the potential to become the cornerstone of a regularly updated, high quality repository with data sharing, reproducibility, and reusability as ultimate goals.

SUBMITTER: Candia J

PROVIDER: S-EPMC5660188 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Assessment of Variability in the SOMAscan Assay.

Candia Julián J Cheung Foo F Kotliarov Yuri Y Fantoni Giovanna G Sellers Brian B Griesman Trevor T Huang Jinghe J Stuccio Sarah S Zingone Adriana A Ryan Bríd M BM Tsang John S JS Biancotto Angélique A

Scientific reports 20171027 1

SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human protein analytes in serum, plasma, and other biological matrices with high sensitivity and specificity. In this work, we present a comprehensive meta-analysis of performance based on multiple serum and plasma runs using the current 1.3 k assay, as well as the previous 1.1 k version. We discuss normalization procedures and examine different strategies to minimize intra- and interplate nuisance effects. We implement a m ...[more]

PMID: 29079756

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Project description:Nonalcoholic steatohepatitis (NASH) is a major cause of liver-related morbidity and mortality worldwide. Liver fibrosis stage, a key component of NASH, has been linked to the risk of mortality and liver-related clinical outcomes. Currently there are no validated noninvasive diagnostics that can differentiate between fibrosis stages in patients with NASH; many existing tests do not reflect underlying disease pathophysiology. Noninvasive biomarkers are needed to identify patients at high-risk of NASH with advanced fibrosis. This was a retrospective study of patients with histologically proven NASH with fibrosis stages 0-4. The SOMAscan proteomics platform was used to quantify 1,305 serum proteins in a discovery cohort (n = 113). In patients with advanced (stages 3-4) versus early fibrosis (stages 0-2), 97 proteins with diverse biological functions were differentially expressed. Next, fibrosis-stage classification models were explored using a machine learning-based approach to prioritize the biomarkers for further evaluation. A four-protein model differentiated patients with stage 0-1 versus stage 2-4 fibrosis (area under the receiver operating characteristic curve [AUROC] = 0.74), while a 12-protein classifier differentiated advanced versus early fibrosis (AUROC = 0.83). Subsequently, the model's performance was validated in two independent cohorts (n = 71 and n = 32) with similar results (AUROC = 0.74-0.78). Our advanced fibrosis model performed similarly to or better than Fibrosis-4 index, aspartate aminotransferase-to-platelet ratio index, and nonalcoholic fatty liver disease (NAFLD) fibrosis score-based models for all three cohorts. Conclusion: A SOMAscan proteomics-based exploratory classifier for advanced fibrosis, consisting of biomarkers that reflect the complexity of NASH pathophysiology, demonstrated similar performance in independent validation cohorts and performed similarly or better than Fibrosis-4 index, aspartate aminotransferase-to-platelet ratio index, and NAFLD fibrosis score. Further studies are warranted to evaluate the clinical utility of these biomarker panels in patients with NAFLD.

Dataset Information

Assessment of Variability in the SOMAscan Assay.

Publications

Assessment of Variability in the SOMAscan Assay.

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