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Stability and reproducibility of proteomic profiles in epidemiological studies: comparing the Olink and SOMAscan platforms |
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| Authors: | Danielle E. Haslam Jun Li Simon T. Dillon Xuesong Gu Yin Cao Oana A. Zeleznik Naoko Sasamoto Xuehong Zhang A. Heather Eliassen Liming Liang Meir J. Stampfer Samia Mora Zsu-Zsu Chen Kathryn L. Terry Robert E. Gerszten Frank B. Hu Andrew T. Chan Towia A. Libermann Shilpa N. Bhupathiraju |
| Affiliation: | 1. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA;2. Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA;3. Genomics, Proteomics, Bioinformatics and Systems Biology Center, Department of Medicine, Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA;4. Division of Public Health Sciences, Department of Surgery, Washington University in St. Louis, St. Louis, Missouri, USA Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA Division of Gastroenterology, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA;5. Department of Obstetrics and Gynecology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA;6. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA;7. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA;8. Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA;9. Division of Preventive Medicine and Cardiovascular Division of Medicine and Center for Lipid Metabolomics, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA;10. Department of Internal Medicine, Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA;11. Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA Department of Obstetrics and Gynecology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA;12. Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA Broad Institute of MIT and Harvard Program in Metabolism, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA;13. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA |
| Abstract: | Limited data exist on the performance of high-throughput proteomics profiling in epidemiological settings, including the impact of specimen collection and within-person variability over time. Thus, the Olink (972 proteins) and SOMAscan7Kv4.1 (7322 proteoforms of 6596 proteins) assays were utilized to measure protein concentrations in archived plasma samples from the Nurses’ Health Studies and Health Professionals Follow-Up Study. Spearman's correlation coefficients (r) and intraclass correlation coefficients (ICCs) were used to assess agreement between (1) 42 triplicate samples processed immediately, 24-h or 48-h after blood collection from 14 participants; and (2) 80 plasma samples from 40 participants collected 1-year apart. When comparing samples processed immediately, 24-h, and 48-h later, 55% of assays had an ICC/r ≥ 0.75 and 87% had an ICC/r ≥ 0.40 in Olink compared to 44% with an ICC/r ≥ 0.75 and 72% with an ICC/r ≥ 0.40 in SOMAscan7K. For both platforms, >90% of the assays were stable (ICC/r ≥ 0.40) in samples collected 1-year apart. Among 817 proteins measured with both platforms, Spearman's correlations were high (r > 0.75) for 14.7% and poor (r < 0.40) for 44.8% of proteins. High-throughput proteomics profiling demonstrated reproducibility in archived plasma samples and stability after delayed processing in epidemiological studies, yet correlations between proteins measured with the Olink and SOMAscan7K platforms were highly variable. |
| Keywords: | Aptamers biomarkers epidemiology studies laboratory methods and tools multiplexing systems biology |