Association of Modifiable Lifestyle and Metabolic Factors With the Risk of Developing Sepsis: 2-Sample Mendelian Randomized Study
Bibliographic record
Abstract
Background: Sepsis is a life-threatening condition characterized by organ dysfunction resulting from dysregulated host response to infections. Approximately 48.9 million people worldwide are diagnosed with sepsis annually, leading to 11 million deaths and representing 19.7% of all global deaths. No specific, effective treatments for sepsis, which has a poor prognosis, are available. Objective: The study aimed to systematically explore the association between genetically predicted modifiable risk factors and sepsis. Methods: Univariable 2-sample Mendelian randomization (MR) analysis was performed to explore the association between 30 modifiable risk factors (12 lifestyle, 3 educational and psychological, and 15 metabolic factors) and sepsis. Heterogeneity was evaluated using the Cochran Q analysis. Sensitivity analyses were conducted using the MR-Egger regression intercept tests and leave-one-out analyses. Additionally, multivariable MR analyses were performed to adjust for genetic associations between the instruments and obesity. Results: Genetically predicted smoking (odds ratio [OR] 1.20, 95% CI 1.06-1.36; P=.005), a higher number of cigarettes smoked daily (OR 1.70, 95% CI 1.29-2.23; P<.001), a higher overall health rating (OR 2.19, 95% CI 1.61-2.98; P<.001), BMI (OR 1.50, 95% CI 1.38-1.63; P<.001), waist circumference (OR 1.70, 95% CI 1.53-1.89; P<.001), whole body fat mass (OR 1.50, 95% CI 1.37-1.64; P<.001), trunk fat mass (OR 1.48, 95% CI 1.36-1.62; P<.001), arm fat mass (OR 1.57, 95% CI 1.43-1.71; P<.001), and leg fat mass (OR 1.69, 95% CI 1.51-1.90; P<.001) were associated with increased sepsis risk. However, light physical activity (OR 0.26, 95% CI 0.08-0.83; P=.03), higher education attainment (OR 0.52, 95% CI 0.40-0.67; P<.001), and high-density lipoprotein cholesterol (OR 0.91, 95% CI 0.84-0.98; P=.02) exhibited protective effects against sepsis. Using a multivariate analysis of obesity traits, the waist circumference (OR 2.16, 95% CI 1.18-3.96; P=.01) was an independent risk factor of sepsis. Conclusions: Our study demonstrated that genetic predictors of lifestyle (smoking and physical activity), educational level, and metabolic factors (waist circumference and high-density lipoprotein cholesterol) exhibited a causal association with sepsis risk. Future research should further investigate the underlying mechanisms of these associations to inform more effective preventive strategies against sepsis.
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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 | 0.021 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".