Correlations Within and Between Highly Multiplexed Proteomic Assays of Human Plasma
Open accessAbstract
Introduction: The number of assays on proteomic platforms has grown rapidly. The leading platforms, SomaScan and Olink, have strengths and limitations. Comparisons of precision on the latest platforms—SomaScan 11k and Olink Explore HT—have not yet been established. Methods: Among 102 participants in the Atherosclerosis Risk in Communities Study (mean age 74 years, 53% women, 47% Black), we used split plasma samples to measure platform precision. CV and Spearman correlations were calculated for each assay. Cross-platform agreement was assessed for overlapping proteins. Results: SomaScan 11k demonstrated a median correlation of 0.85 for the 10 778 assays and a median CV of 6.8%, similar precision to earlier versions. The 5420 assays on Olink Explore HT exhibited a median correlation of 0.65 and median CV of 35.7%, which was higher than observed in its predecessors (e.g., 19.8% for Olink Explore 3072). Precision of Olink assays was inversely correlated with the percentage of samples above the limit of detection (LOD) (r = −0.77). Upon replacing Olink values below the LOD with values half the LOD, the median correlation for Olink assays measured in duplicate increased to 0.79; the median CV decreased to 13.3%. The distribution of between-platform correlations for the 4443 overlapping proteins had peaks at r approximately 0 and at r approximately 0.8. One-tenth of the protein pairs had cross-platform correlations r ≥ 0.8. Conclusions: Precision of these 2 proteomics platforms in human plasma has diverged as the coverage has increased. These results highlight the need for careful consideration in platform selection based on specific research requirements.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Proteins with >50% measures above LOD were modestly correlated (N = 1361, median Pearson's r = 0.43, SD = 0.32), while proteins with <50% measures above LOD exhibited low inter-platform correlation (N = 796, median Pearson's r = 0.04, SD = 0.32).
“While proteins with >50% measures above LOD were modestly correlated (N = 1361, median Pearson’s r = 0.43, SD = 0.32), proteins with <50% measures above LOD exhibited low inter-platform correlation (N = 796, median Pearson’s r = 0.04, SD = 0.32), consistent with prior reports (Supplementary Data 15 and 16)26.”
From Cross-ancestry comparison of aptamer and antibody protein measures (2026) · cites this paper as [26]
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Synergistic insights into human health from aptamer- and antibody-based proteomic profiling
Pietzner, M., Wheeler, E., Carrasco-Zanini, J., Kerrison, N. D., Oerton, E., Koprulu, M., Luan, J., Hingorani, A. D., Williams, S. A., Wareham, N. J., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27164-0 · Cited by 234 · see citing works
Comparison of Proteomic Assessment Methods in Multiple Cohort Studies
Raffield, L. M., Dang, H., Pratte, K. A., Jacobson, S., Gillenwater, L. A., Ampleford, E., Barjaktarevic, I., Basta, P., Clish, C. B., Comellas, A. P., et al. (2020) · PROTEOMICS · doi:10.1002/pmic.201900278 · Cited by 184 · see citing works
Flagged first, then by citations
Research works printed but not linked: 13
- [1]Eldjarn GH, Ferkingstad E, Lund SH, Helgason H, Magnusson OT, Gunnarsdottir K, Olafsdottir TA, Halldorsson BV, Olason PI, Zink F, Gudjonsson SA, Sveinbjornsson G, Magnusson MI, Helgason A, Oddsson A, Halldorsson GH, Magnusson MK, Saevarsdottir S, Eiriksdottir T, Masson G, Stefansson H, Jonsdottir I, Holm H, Rafnar T, Melsted P, Saemundsdottir J, Norddahl GL, Thorleifsson G, Ulfarsson MO, Gudbjartsson DF, Thorsteinsdottir U, Sulem P, Stefansson K. Large-scale plasma proteomics comparisons through genetics and disease associations. Nature. 2023; 622(7982): 348– 58. 37794188 PMC10567571
- [2]Eldjarn GH, Ferkingstad E, Lund SH, Helgason H, Magnusson OT, Gunnarsdottir K, Olafsdottir TA, Halldorsson BV, Olason PI, Zink F, Gudjonsson SA, Sveinbjornsson G, Magnusson MI, Helgason A, Oddsson A, Halldorsson GH, Magnusson MK, Saevarsdottir S, Eiriksdottir T, Masson G, Stefansson H, Jonsdottir I, Holm H, Rafnar T, Melsted P, Saemundsdottir J, Norddahl GL, Thorleifsson G, Ulfarsson MO, Gudbjartsson DF, Thorsteinsdottir U, Sulem P, Stefansson K. Author Correction: Large-scale plasma proteomics comparisons through genetics and disease associations. Nature. 2024; 630(8015): E3– E. 38778117 PMC11153164
- [3]Wright JD, Folsom AR, Coresh J, Sharrett AR, Couper D, Wagenknecht LE, Mosley TH Jr., Ballantyne CM, Boerwinkle EA, Rosamond WD, Heiss G. The ARIC (Atherosclerosis Risk In Communities) Study: JACC Focus Seminar 3/8. Journal of the American College of Cardiology. 2021; 77(23): 2939– 59. 34112321 PMC8667593
- [4]Rooney MR, Chen J, Ballantyne CM, Hoogeveen RC, Tang O, Grams ME, Tin A, Ndumele CE, Zannad F, Couper DJ, Tang W, Selvin E, Coresh J. Comparison of Proteomic Measurements Across Platforms in the Atherosclerosis Risk in Communities (ARIC) Study. Clinical chemistry. 2023; 69(1): 68– 79. 36508319 PMC9812856
- [5]White AD, Folsom AR, Chambless LE, Sharret AR, Yang K, Conwill D, Higgins M, Williams OD, Tyroler HA. Community surveillance of coronary heart disease in the Atherosclerosis Risk in Communities (ARIC) Study: methods and initial two years’ experience. Journal of clinical epidemiology. 1996; 49(2): 223– 33. 8606324
- [6]Rosamond WD, Folsom AR, Chambless LE, Wang CH, McGovern PG, Howard G, Copper LS, Shahar E. Stroke incidence and survival among middle-aged adults: 9-year follow-up of the Atherosclerosis Risk in Communities (ARIC) cohort. Stroke; a journal of cerebral circulation. 1999; 30(4): 736– 43. 10187871
- [7]Rosamond WD, Chang PP, Baggett C, Johnson A, Bertoni AG, Shahar E, Deswal A, Heiss G, Chambless LE. Classification of heart failure in the atherosclerosis risk in communities (ARIC) study: a comparison of diagnostic criteria. Circulation Heart failure. 2012; 5(2): 152– 9. 22271752 PMC3326579
- [10]Bland JM, Altman DG. Measurement error proportional to the mean. BMJ (Clinical research ed). 1996; 313(7049): 106. PMC2351517 8688716
- [13]Haslam DE, Li J, Dillon ST, Gu X, Cao Y, Zeleznik OA, Sasamoto N, Zhang X, Eliassen AH, Liang L, Stampfer MJ, Mora S, Chen ZZ, Terry KL, Gerszten RE, Hu FB, Chan AT, Libermann TA, Bhupathiraju SN. Stability and reproducibility of proteomic profiles in epidemiological studies: comparing the Olink and SOMAscan platforms. Proteomics. 2022; 22(13–14): e2100170. 35598103 PMC9923770
- [14]Wang B, Pozarickij A, Mazidi M, Wright N, Yao P, Said S, Iona A, Kartsonaki C, Fry H, Lin K, Chen Y, Du H, Avery D, Schmidt DV, Yu C, Sun D, Lv J, Hill M, Li L, Bennett DA, Collins R, Walters RG, Clarke R, Millwood IY, Chen Z. Comparative studies of genetic and phenotypic associations for 2,168 plasma proteins measured by two affinity-based platforms in 4,000 Chinese adults. medRxiv. 2023:2023.12.01.23299236.
- [15]Katz DH, Robbins JM, Deng S, Tahir UA, Bick AG, Pampana A, Yu Z, Ngo D, Benson MD, Chen Z-Z, Cruz DE, Shen D, Gao Y, Bouchard C, Sarzynski MA, Correa A, Natarajan P, Wilson JG, Gerszten RE. Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods. Science Advances. 2022; 8(33): eabm5164. 35984888 PMC9390994
- [16]Candia J, Fantoni G, Delgado-Peraza F, Shehadeh N, Tanaka T, Moaddel R, Walker KA, Ferrucci L. Variability of 7K and 11K SomaScan Plasma Proteomics Assays. J Proteome Res. 2024; 23(12): 5531– 9. 39473295 PMC11629374
- [17]Candia J, Fantoni G, Delgado-Peraza F, Shehadeh N, Tanaka T, Moaddel R, Walker KA, Ferrucci L. Variability of 7K and 11K SomaScan plasma proteomics assays. bioRxiv. 2024:2024.08.06.606813. PMC11629374 39473295
Cited by
Sorted by citations
Cross-ancestry comparison of aptamer and antibody protein measures
Nicholas, J. C., Katz, D. H., Tahir, U. A., Debban, C. L., Aguet, F., Blackwell, T., Bowler, R. P., Broadaway, K. A., Chen, J., Clish, C. B., et al. (2026) · Nature Communications · doi:10.1038/s41467-025-67814-1 · Cited by 13 · see citing works
Self-citation
- Authors
- Rooney, M. R., Chen, J., Ballantyne, C. M., Hoogeveen, R. C., Boerwinkle, E., Yu, B., Walker, K. A., Schlosser, P., Selvin, E., Chatterjee, N., Couper, D., Grams, M. E., & Coresh, J.
- Affiliations
- Johns Hopkins University (US)
- Baylor College of Medicine (US)
- The University of Texas Health Science Center at Houston (US)
- National Institute on Aging (US)
- University of North Carolina at Chapel Hill (US)
- New York University (US)
- Corresponding author
- Coresh, Josef
- ORCID
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 2025-04-02
- Volume
- 71
- Issue
- 6
- Pages
- 677-687
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- PMC
- PMC12129588
- OpenAlex
- W4409118908
- Cited by
- 33
- References
- 2
- Citations by year
- 2026: 19 · 2025: 14
- FWCI
- 9.86
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Clinical Chemistry (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- PubMed Central (submittedVersion)
- FreiDok plus (Universitätsbibliothek Freiburg) (submittedVersion)
- Funders
- National Heart, Lung, and Blood Institute
- National Institutes of Health
- Department of Health and Human Services (75N92022D00001, 75N92022D00002, 75N92022D00003, 75N92022D00004, 75N92022D00005)
- German Research Foundation (530592017)
- National Institute on Aging’s Intramural Research Program (AG000348-01, AG000349-01)
- NIH/NHLBI (K24 HL152440, R01DK108803, K24HL155861)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced Biosensing Techniques and Applications
- Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- human plasma, assay precision, detection limit, coefficient of variation, protein biomarkers, platform selection, Atherosclerosis Risk in Communities Study
- MeSH terms
- Aged, Blood Proteins, Female, Humans, Male, Proteomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
