Decreased Clearance of Low-Density Lipoprotein Cholesterol is Causally Associated With Increased Mortality of Septic Shock
Bibliographic record
Abstract
OBJECTIVE: To determine whether low-density lipoprotein cholesterol (LDL-C) levels, set by the balance of clearance and production, causally contribute to septic shock 28-day mortality. DESIGN: We measured LDL-C levels and genotypes in patients with septic shock. Using Genotyping and Genome-Wide Association Study summary statistics from over 150,000 Japanese participants, we genetically predicted pre-infection LDL-C levels. Two-sample Mendelian randomization was used to assess the causal relationship between predicted pre-infection LDL-C levels and 28-day mortality. We analyzed PCSK9 and 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) genotypes to determine if LDL-C clearance or production was the underlying mechanism. SETTING: Multicenter ICUs in Japan. PATIENTS: Genotyped septic shock patients ( n = 614). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Predicted pre-infection LDL-C levels were much higher than directly measured LDL-C levels at the onset of septic shock (141 mg/dL vs. 40 mg/dL, p < 0.001). Two-sample Mendelian randomization revealed that high predicted pre-infection LDL-C levels were causally associated with increased septic shock 28-day mortality (hazard ratio, 2.78; p = 0.039). PCSK9 genetic variants that increase LDL-C clearance via the LDL receptor (genetically proxied PCSK9 inhibitor treatment) were associated with decreased mortality ( p = 0.003) while HMGCR genetic variants that decrease LDL-C production (genetically proxied statin treatment) were not associated with decreased septic shock mortality (indeed the opposite effect was observed, p = 0.039). The two main genetic variants driving the association between high predicted pre-infection LDL-C levels and increased mortality were in apolipoprotein genes ( ApoB100 -rs13306206 and ApoE -rs7412), apolipoproteins involved in LDL-C binding to the LDL receptor. CONCLUSIONS: Low LDL-C clearance explains the causal association between high genetically predicted pre-infection LDL-C levels and increased septic shock mortality. PCSK9 , ApoB , and ApoE variants were identified as causal, all related to the LDL receptor or its interaction with LDL-C. Enhancing LDL receptor-mediated clearance of pathogen lipid toxins may improve septic shock outcomes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".