Identification of Circulating Proteins Associated With Blood Pressure Using Mendelian Randomization
Bibliographic record
Abstract
Background: Hypertension is a common modifiable risk factor for cardiovascular disease and mortality. Pathophysiological mechanisms leading to hypertension remain incompletely understood. Mendelian randomization (MR) allows the evaluation of the causal role of markers by minimizing the risk of biases such as reverse causation and confounding. We aimed to identify novel circulating proteins associated with blood pressure through a comprehensive screen of 227 blood biomarkers using MR. Methods: Genetic determinants of 227 biomarkers were identified in ORIGIN (Outcome Reduction With Initial Glargine Intervention; URL: http://www.clinicaltrials.gov . Unique identifier: NCT00069784) participants (N=4147) and combined with genetic effects on systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure from the International Consortium for Blood Pressure (74 064 individuals) using MR. Results were replicated in the UK Biobank (up to 319 103 individuals) and using another biomarker dataset (N=3301). MR analyses with cardiovascular risk factors and outcomes as well as other biomarkers were performed to further evaluate the mechanisms involved. Results: Six biomarkers were associated with blood pressure using MR after adjustment for multiple hypothesis testing. Relationships between NT-proBNP (N-terminal Pro-B-type natriuretic peptide), systolic blood pressure, and diastolic blood pressure confirmed previous reports. Novel circulating proteins associated with blood pressure were also identified. uPA (urokinase-type plasminogen activator) was related to systolic blood pressure; ADM (adrenomedullin) was related to systolic blood pressure and pulse pressure; IL (interleukin) 16 was related to diastolic blood pressure; cFn (cellular fibronectin) and IGFBP3 (insulin-like growth factor-binding protein 3) were related to pulse pressure. With the exception of IL16 and diastolic blood pressure ( P =0.58), these relationships were validated in the UK Biobank ( P <0.0001). Further MR analyses with cardiovascular risk factors and outcomes showed relationships between NT-proBNP and large-artery atherosclerotic stroke, IGFBP3 and diabetes mellitus as well as cFn and body mass index. Conclusions: We identified novel biomarkers associated with blood pressure using MR. These markers could prove useful for risk assessment and as potential therapeutic targets.
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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 | 0.029 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".