Apolipoprotein A-I: A favorable prognostic marker in infective endocarditis

Utilize proteomic analysis to identify potential therapeutic targets for combating sepsis and sepsis-related death

Background

Sepsis is an inflammatory disease that leads to severe mortality, highlighting the urgent need to identify new therapeutic strategies for sepsis. Proteomic research serves as a primary source for drug target identification. We employed proteome-wide Mendelian randomization (MR), genetic correlation analysis, and colocalization analysis to identify potential targets for sepsis and sepsis-related death.

Methods

Genetic data for plasma proteomics were obtained from 35,559 Icelandic individuals and an initial MR analysis was conducted using 13,531 sepsis cases from the FinnGen R10 cohort to identify associations between plasma proteins and sepsis. Subsequently, significant proteins underwent genetic correlation analysis, followed by replication in 54,306 participants from the UK Biobank Pharma Proteomics Project and validation in 11,643 sepsis cases from the UK Biobank. The identified proteins were then subjected to colocalization analysis, enrichment analysis, and protein-protein interaction network analysis. Additionally, we also investigated a MR analysis using plasma proteins on 1,896 sepsis cases with 28-day mortality from the UK Biobank.

Results

After FDR correction, MR analysis results showed a significant causal relationship between 113 plasma proteins and sepsis. Genetic correlation analysis revealed that only 8 proteins had genetic correlations with sepsis. In the UKB-PPP replication analysis, only 4 proteins were found to be closely associated with sepsis, while validation in the UK Biobank sepsis cases found overlaps for 21 proteins. In total, 30 proteins were identified in the aforementioned analyses, and colocalization analysis revealed that only 2 of these proteins were closely associated with sepsis. Additionally, in the 28-day mortality MR analysis of sepsis, we also found that only 2 proteins were significant.

Conclusions

The identified plasma proteins and their associated metabolic pathways have enhanced our understanding of the complex relationship between proteins and sepsis. This provides new avenues for the development of drug targets and paves the way for further research in this field.

High-density lipoprotein cholesterol to apolipoprotein A1 ratio and all-cause mortality among incident peritoneal dialysis patients

BACKGROUND AND AIMS

The ratio of high-density lipoprotein cholesterol to apolipoprotein A1 (HAR) is associated with all-cause mortality in nonchronic kidney disease patients, but its role in predicting all-cause mortality in patients undergoing peritoneal dialysis (PD) is still unclear. The purpose of this study was to investigate the relationship between HAR and all-cause mortality in patients with PD.

METHODS AND RESULTS

The medical records of 1199 patients with PD from November 1, 2005, to August 31, 2019, were collected retrospectively. The main outcome was defined as all-cause mortality. The HAR was divided into three groups by X-tile software. The association between HAR and all-cause mortality was evaluated by Cox models. The Kaplan-Meier method was used for the survival curve. The median follow-up period was 35 months (interquartile range: 20-57 months), with a total of 326 deaths recorded. After multiple adjustments, the risk of all-cause mortality in the high HAR group was 1.96-fold higher than that in the low HAR group (hazard ratio: 1.96; 95% CI, 1.22 to 3.15; P = 0.005). The restricted cubic splines showed that the risk of all-cause mortality increased gradually when HAR was >0.37. In the stratified analysis, a high HAR was linked to a high risk of all-cause mortality in males, patients under 55 years old, and patients without diabetes or cardiovascular disease (CVD).

CONCLUSION

This study suggests that HAR is independently related to all-cause mortality in PD patients, especially in males, patients under 55 years old, and patients without diabetes or CVD.

Lipid and lipoprotein predictors of functional outcomes and long-term mortality after surgical sepsis

RATIONALE

Sepsis is a life-threatening, dysregulated response to infection. Lipid biomarkers including cholesterol are dynamically regulated during sepsis and predict short-term outcomes. In this study, we investigated the predictive ability of lipid biomarkers for physical function and long-term mortality after sepsis.

METHODS

Prospective cohort study of sepsis patients admitted to a surgical intensive-care unit (ICU) within 24 h of sepsis bundle initiation. Samples were obtained at enrollment for lipid biomarkers. Multivariate regression models determined independent risk factors predictive of poor performance status (Zubrod score of 3/4/5) or survival at 1-year follow-up.

MEASUREMENTS AND MAIN RESULTS

The study included 104 patients with surgical sepsis. Enrollment total cholesterol and high-density lipoprotein (HDL-C) levels were lower, and myeloperoxidase (MPO) levels were higher for patients with poor performance status at 1 year. A similar trend was seen in comparisons based on 1-year mortality, with HDL-C and ApoA-I levels being lower and MPO levels being higher in non-survivors. However, multivariable logistic regression only identified baseline Zubrod and initial SOFA score as significant independent predictors of poor performance status at 1 year. Multivariable Cox regression modeling for 1-year survival identified high Charlson comorbidity score, low ApoA-I levels, and longer vasopressor duration as predictors of mortality over 1-year post-sepsis.

CONCLUSIONS

In this surgical sepsis study, lipoproteins were not found to predict poor performance status at 1 year. ApoA-I levels, Charlson comorbidity scores, and duration of vasopressor use predicted 1 year survival. These data implicate cholesterol and lipoproteins as contributors to the underlying pathobiology of sepsis.

Neutrophil-Lymphocyte Ratio in Predicting Infective Endocarditis: A Case-Control Retrospective Study

Background

Infective endocarditis (IE) is a complex infectious disease with high morbidity and mortality. The inflammation mechanism of IE is a complex network including interactions of inflammatory cytokines and other components of host response. As an important inflammation marker, the prediction ability of neutrophil-to-lymphocyte ratio (NLR) in IE deserves further investigation.

Methods

NLR values were measured and compared between IE patients and healthy controls, good and bad clinical outcome groups. The receiver operating characteristic curves (ROCs) of NLR and cut-off values were measured in IE patients, pathogen-subgroups, and different clinical outcome groups.

Results

There were 678 IE patients and 2520 healthy controls enrolled in our study. The number of good and bad clinical outcome patients was 537 and 141, respectively. The value of NLR was significantly higher in IE patients than healthy controls (6.29 ± 9.36 vs. 1.87 ± 0.34, p < 0.001), and the area under the ROC (AUC) was 0.817 (95% CI (0.794, 0.839), p < 0.001). The critical value of NLR for diagnosis of IE was 2.68, with a sensitivity of 69%, and a specificity of 88%. The value of NLR was significantly higher in bad clinical outcome patients than in good clinical outcome patients (5.8 ± 6.02 vs. 3.62 ± 2.61, p < 0.001). The critical value of NLR to predict the outcome of IE was 5.557, with a sensitivity of 39.0% and a specificity of 85.3%.

Conclusions

NLR is a predictive marker for IE patients, especially in Gram-negative bacteria and Gram-positive bacteria-infected IE patients. NLR also can predict the outcome of IE. Early detecting NLR upon admission may assist in early diagnosis and risk stratification of patients with IE.

Early-Stage Staphylococcus aureus Bloodstream Infection Causes Changes in the Concentrations of Lipoproteins and Acute-Phase Proteins and Is Associated with Low Antibody Titers against Bacterial Virulence Factors

S. aureus sepsis has a high complication and mortality rate. Given the limited therapeutic possibilities, effective prevention strategies, e.g., a vaccine, or the early identification of high-risk patients would be important but are not available. Our study showed an acute-phase response in patients with S. aureus bloodstream infection and evidence that lipoproteins are downregulated in plasma. Using immunoproteomics, stratification of patients appears to be achievable, since at the early stages of systemic S. aureus infection patients had low preexisting anti-S. aureus antibody levels. This strengthens the notion that a robust immune memory for S. aureus protects against infections with the pathogen.

Systemic and quantitative investigations of human plasma proteins (proteomics) and Staphylococcus aureus-specific antibodies (immunoproteomics) provide complementary information and hold promise for the discovery of biomarkers in Staphylococcus aureus bloodstream infection (SABSI). Usually, data-dependent acquisition (DDA) is used for proteome analysis of serum or plasma, but data-independent acquisition (DIA) is more comprehensive and reproducible. In this prospective cohort study, we aimed to identify biomarkers associated with the early stages of SABSI using a serum DIA proteomic and immunoproteomic approach. Sera from 49 SABSI patients and 43 noninfected controls were analyzed. In total, 608 human serum proteins were identified with DIA. A total of 386 proteins could be quantified, of which 9 proteins, mainly belonging to acute-phase proteins, were significantly increased, while 7 high-density lipoproteins were lower in SABSI. In SABSI, total anti-S. aureus serum IgG was reduced compared with controls as shown by immunoproteomic quantification of IgG binding to 143 S. aureus antigens. IgG binding to 48 of these anti-S. aureus proteins was significantly lower in SABSI, while anti-Ecb IgG was the only one increased in SABSI. Serum IgG binding to autoinducing peptide MsrB, FadB, EsxA, Pbp2, FadB, SspB, or SodA was very low in SABSI. This marker panel discriminated early SABSI from controls with 95% sensitivity and 100% specificity according to random forest prediction. This holds promise for patient stratification according to their risk of S. aureus infection, underlines the protective function of the adaptive immune system, and encourages further efforts in the development of a vaccine against S. aureus.

IMPORTANCES. aureus sepsis has a high complication and mortality rate. Given the limited therapeutic possibilities, effective prevention strategies, e.g., a vaccine, or the early identification of high-risk patients would be important but are not available. Our study showed an acute-phase response in patients with S. aureus bloodstream infection and evidence that lipoproteins are downregulated in plasma. Using immunoproteomics, stratification of patients appears to be achievable, since at the early stages of systemic S. aureus infection patients had low preexisting anti-S. aureus antibody levels. This strengthens the notion that a robust immune memory for S. aureus protects against infections with the pathogen.