Abstract 4137457: Cross-sectional Investigation of Proteomic Signatures of Blood Pressure Traits.
Bibliographic record
Abstract
Background: Hypertension is a major risk factor for cardiovascular disease affecting one third of the adult population worldwide. Over 90% cases of hypertension are without a distinct etiology. Identification of protein biomarkers of hypertension may provide insight into disease pathophysiology and highlight novel therapeutic targets. Methods: We conducted association analyses between 2922 plasma proteins (exposure) and blood pressure (BP) traits (outcome) in 45,926 UK Biobank participants (aged 57 ± 8 years; 54% women). We employed linear mixed models to study protein associations with systolic and diastolic BP and logistic mixed models to test abundance of proteins in hypertensive vs. normal individuals. The associations were adjusted for age, sex, body mass index, estimated glomerular filtration rate, smoking and alcohol drinking status, and batch effects. Hypertension was defined as systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg) or current use of anti-hypertensive medication. Sensitivity analysis excluded individuals taking BP medication (n=10,229). Functional enrichment analysis was performed to elucidate biological functions and tissue specificity of significant protein signatures ( P < 0.00017). We further performed Mendelian randomization (MR) to infer causal relations of protein biomarkers and BP. Results: We identified 1469 proteins associated with systolic BP and 1638 with diastolic BP. The corresponding numbers were 1410 and 1566 after excluding treated individuals. Plasma levels of 1215 proteins (1105 upregulated, 110 downregulated) differed in individuals with hypertension (N=24,724) compared to normal (N= 21,202). Most of these proteins were specific to liver, adipose tissue, renal cortex and coronary artery. Protein signatures of hypertension showed enrichment in pathways involved in inflammatory response, cholesterol homeostasis, complement and coagulation cascades, and hemostasis. Putatively causal associations were observed for 141 proteins with SBP and 142 with DBP. Discussion: This study elucidates protein signatures associated with BP and hypertension. Systemic inflammation and cholesterol homeostasis play important roles in the pathophysiology of hypertension.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".