Correlation between Olink and SomaScan proteomics platforms in adults with a Fontan circulation
Bibliographic record
Abstract
High-throughput proteomics platforms using aptamers (SomaScan) or proximity extension assay (Olink) provide novel opportunities for improving diagnostic and risk stratification tools in cardiovascular diseases, including understudied congenital heart diseases. The correlation between these proteomics approaches has not yet been studied among individuals with a Fontan circulation. The correlation of plasma protein measurements between SomaScan and Olink platforms was evaluated in adults with a Fontan circulation. We measured 491 proteins in plasma of 71 adults with a Fontan circulation using Olink and SomaScan. Missing Olink measurements (0.13%, 47/34,861) were imputed using non-parametric imputation. Spearman's rank correlation coefficient for absolute values of protein expression between platforms was calculated. Protein correlation frequencies were compared to 3 cohorts reported in the literature using Pearson's Chi-squared test of independence. Overall, protein correlations between Olink and SomaScan measurements were moderately strong for most proteins, (rho > 0.4 for 57.2%), but with substantial variability (median correlation = 0.457, IQR = 0.538). The distribution of protein correlations was qualitatively similar to published literature in non-Fontan cohorts. Both Olink and SomaScan identified proteins with sex-based differences; both identified differences in myostatin and leptin, but each identified additional nonoverlapping sexually dimorphic proteins (n = 14 Olink, n = 5 SomaScan). In adults with a Fontan circulation, correlations between plasma proteins measured by Olink and SomaScan varied widely, approximately in line with prior reports in other populations. While these tools may be uniquely useful to generate hypotheses, specifically regarding potential molecular mechanisms, more definitive inference requires independent validation. In this study, we performed high throughput plasma proteomics profiling using Olink and SomaScan platforms on a cohort of patients with single ventricle Fontan circulation. Key results for measurement correlations between Olink and SomaScan, a comparison of protein correlation frequency to literature reports, and phenotypic validation of differential expression of sex proteins are summarized. Illustration created via BioRender (BioRender, Toronto, Canada, biorender.com ). Abbreviations: Rho = Spearman's rank correlation coefficient; NHS = Nurses' Health Study [4]; ARIC = Atherosclerosis Risk in Communities [7]; HCM = hypertrophic cardiomyopathy patients undergoing septal ablation [6]. • Plasma proteomics platforms may provide insights into the pathophysiology of the Fontan circulation, a state associated with adverse outcomes and poorly understood mechanisms. • We studied the correlation between the Olink and SomaScan proteomic platforms, describing moderate correlation; the results were qualitatively similar to other reported cohorts of biventricular patients. • This suggests that the validity of these platforms in the Fontan circulation may be similar to that seen in cohorts with biventricular patients. Tweet Summarizing this Article: @CincyChildrens @BostonChildrens @BIDMCHealth researchers have investigated how well high-throughput proteomics @SomaLogic @OlinkProteomics correlate in Fontan patients. These platforms may provide unique opportunities for developing cardiovascular risk stratification models.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".