Inflammation and LDL cholesterol contribute independently to the progression of early human atherosclerotic plaque
Bibliographic record
Abstract
Abstract Background The role of inflammatory processes in the risk of ischemic events (despite intensive lipid-lowering treatment) has received considerable attention in recent years, mainly amongst secondary prevention patients. Both dyslipidemia and inflammation contribute to the pathophysiology of atherosclerosis, and both predict future ischemic events. However, the interplay between lipids and inflammation in the early phases of human atherosclerosis [i.e., subclinical atherosclerosis (SA) and primary prevention] is largely unknown. Objectives To investigate the relative contribution of inflammation and LDLc as determinants of risk of SA progression in a cohort of middle-aged, asymptomatic individuals. Methods Participants from the PESA study (median age 45 years, 36% female) underwent 3 visits (at 3-year intervals) involving serial blood testing, physical examinations, 3D vascular ultrasound assessments of peripheral arteries (bilateral carotids and femorals), and coronary artery calcium scoring (CACS). Multiple linear regression models with global plaque volume (GPV, mm3) at 6-year follow-up (FU) as the primary outcome were performed to investigate its key determinants, first based on standard cardiovascular risk factors (i.e., smoking, diabetes, systolic blood pressure, and LDLc) and then followed by the potential additional role of mean levels of inflammatory markers [white blood cell count (WBC), fibrinogen, oxidized LDL (oxLDL), and high-sensitivity C reactive protein (hs-CRP)] and lipoprotein a [Lp(a)]. Results The 3,471 participants had mostly low risk lipid profiles according to current guidelines, and 2,013 (58%) had some SA (GPV >0mm3) at 6-year FU. Overall, mean WBC and mean fibrinogen had highly significant associations with the extent of GPV at 6-year FU after adjusting for age, sex and CVRFs. Mean oxLDL showed a weaker, yet significant association with greater GPV at 6-year FU, but hs-CRP and Lp(a) did not. WBC had the strongest statistical associations with extent of SA, equivalent in strength to the known link of LDLc with SA, followed by fibrinogen (Figure 1). For WBC the marked trend in risk only occurred at levels above its median. Baseline LDLc and the mean inflammatory marker levels predicted GPV at 6 years alongside each other but not in a synergistic manner (i.e., no statistical interactions in determining GPV at 6 years were found). Similar patterns were observed for separate analyses of femoral plaque, carotid plaque and CACS (Figure 2). Conclusion In a cohort of middle-aged, asymptomatic individuals without dyslipidemia according to current standards, both LDLc and inflammation (especially WBC) are associated with progression of SA, but independently of each other. Our results suggest inflammatory risk is relevant across the life continuum of atherosclerosis and should not be regarded as only a residual risk in secondary prevention.Figure 1 Figure 2
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".