Cholesterol-Ester Transfer Protein Alters M1 and M2 Macrophage Polarization and Worsens Experimental Elastase-Induced Pulmonary Emphysema

Association of lipid-modifying therapy with risk of obstructive sleep apnea: A drug-target mendelian randomization study

BACKGROUND

Obstructive sleep apnea (OSA) is considered to be an important contributor of dyslipidemia. However, there lacks observational studies focusing on the potential effect of lipid management on OSA risk. Thus, we aimed to investigate the genetic association of lipid-modifying therapy with risk of OSA.

METHODS

A drug-target mendelian randomization (MR) study using both cis-variants and cis-expression quantitative trait loci (eQTLs) of lipid-modifying drug targets was performed. The MR analyses used summary-level data of genome wide association studies (GWAS). Primary MR analysis was conducted using inverse-variance-weighted (IVW) method. Sensitivity analysis was performed using weighted median (WM) and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods.

RESULTS

Genetically proxied low-density lipoprotein cholesterol (LDL-C)-lowering effect of cholesteryl ester transfer protein (CETP) was associated with reduced risk of OSA (odds ratio [OR] =0.75, 95% confidence interval [CI]: 0.60-0.94, false discovery rate [FDR] q value = 0.046). A significant MR association with risk of OSA was observed for CETP expression in subcutaneous adipose tissue (OR = 0.94, 95%CI: 0.89-1.00, FDR q value = 0.049), lung (OR = 0.94, 95%CI: 0.89-1.00, FDR q value = 0.049) and small intestine (OR = 0.96, 95%CI: 0.93-1.00, FDR q value = 0.049). No significant effects of high-density lipoprotein cholesterol (HDL-C)-raising effect of CETP inhibition, LDL-C-lowering and triglycerides-lowering effect of other drug targets on OSA risk were observed.

CONCLUSIONS

The present study presented genetic evidence supporting the association of LDL-C-lowering therapy by CETP inhibition with reduced risk of OSA. These findings provided novel insights into the role of lipid management in patients with OSA and encouraged further clinical validations and mechanistic investigations.

The 'analysis of gene expression and biomarkers for point-of-care decision support in Sepsis' study; temporal clinical parameter analysis and validation of early diagnostic biomarker signatures for severe inflammation andsepsis-SIRS discrimination

Introduction

Early diagnosis of sepsis and discrimination from SIRS is crucial for clinicians to provide appropriate care, management and treatment to critically ill patients. We describe identification of mRNA biomarkers from peripheral blood leukocytes, able to identify severe, systemic inflammation (irrespective of origin) and differentiate Sepsis from SIRS, in adult patients within a multi-center clinical study.

Methods

Participants were recruited in Intensive Care Units (ICUs) from multiple UK hospitals, including fifty-nine patients with abdominal sepsis, eighty-four patients with pulmonary sepsis, forty-two SIRS patients with Out-of-Hospital Cardiac Arrest (OOHCA), sampled at four time points, in addition to thirty healthy control donors. Multiple clinical parameters were measured, including SOFA score, with many differences observed between SIRS and sepsis groups. Differential gene expression analyses were performed using microarray hybridization and data analyzed using a combination of parametric and non-parametric statistical tools.

Results

Nineteen high-performance, differentially expressed mRNA biomarkers were identified between control and combined SIRS/Sepsis groups (FC>20.0, p<0.05), termed 'indicators of inflammation' (I°I), including CD177, FAM20A and OLAH. Best-performing minimal signatures e.g. FAM20A/OLAH showed good accuracy for determination of severe, systemic inflammation (AUC>0.99). Twenty entities, termed 'SIRS or Sepsis' (S°S) biomarkers, were differentially expressed between sepsis and SIRS (FC>2·0, p-value<0.05).

Discussion

The best performing signature for discriminating sepsis from SIRS was CMTM5/CETP/PLA2G7/MIA/MPP3 (AUC=0.9758). The I°I and S°S signatures performed variably in other independent gene expression datasets, this may be due to technical variation in the study/assay platform.

A comprehensive analysis of the potential role of necroptosis in hepatocellular carcinoma using single-cell RNA Seq and bulk RNA Seq

PURPOSE

Necroptosis plays an essential role in oncogenesis and tumor progression in hepatocellular carcinoma (HCC). This study aimed to investigate the role of necroptosis in the development and progression of HCC. Specifically, we constructed a prognostic prediction model using necroptosis-associated genes (NAGs) to predict patient outcomes.

METHODS

Using data from The Cancer Genome Atlas (TCGA) database, we analyzed gene expression and clinical data. We identified a 5-gene model associated with NAGs and explored genetic features and immune cell infiltration using the CIBERSORT algorithm. In addition, we conducted single-cell RNA sequencing to investigate the potential role of necroptosis in HCC.

RESULTS

We constructed a 5-gene prognostic model based on NAGs that demonstrated excellent predictive accuracy in both training and validation sets. Using multifactorial cox regression analysis, we confirmed the risk score derived from the model as an independent predictor of prognosis, surpassing other clinical characteristics. Patients with high risk scores had significantly worse prognosis than those with low risk scores. To enhance the clinical utility of the necroptosis score, we constructed an accurate nomogram. Additionally, we compared metabolic pathway and immune microenvironment differences between HCC tumors with high and low risk scores. Our single-cell RNA sequencing analyses revealed that necroptosis in HCC was primarily associated with a specific subset of macrophages.

CONCLUSIONS

Our study revealed the presence of two distinct necroptosis subtypes in HCC and developed a robust prognostic model with exceptional predictive accuracy. We observed significantly higher infiltration of M0 macrophages in the high-risk group. We propose that rescuing cytochrome c metabolism in HCC could serve as a potential therapeutic strategy. Furthermore, at a single-cell resolution, our analysis identified myeloid cells as the primary cells exhibiting necroptosis. Specifically, macrophages expressing CD5L, CETP, and MARCO, which may belong to a subset of tissue-resident macrophages, were found to be highly susceptible to necroptosis. These findings suggest the involvement of this specific macrophage subset in potential antitumor therapies. Our study provides novel insights into predicting patient prognosis and developing personalized therapeutic approaches for HCC.

Genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer

Colorectal cancer (CRC) shows high incidence and mortality, partly due to the tumor microenvironment (TME), which is viewed as an active promoter of disease progression. Macrophages are among the most abundant cells in the TME. These immune cells are generally categorized as M1, with inflammatory and anti-cancer properties, or M2, which promote tumor proliferation and survival. Although the M1/M2 subclassification scheme is strongly influenced by metabolism, the metabolic divergence between the subtypes remains poorly understood. Therefore, we generated a suite of computational models that characterize the M1- and M2-specific metabolic states. Our models show key differences between the M1 and M2 metabolic networks and capabilities. We leverage the models to identify metabolic perturbations that cause the metabolic state of M2 macrophages to more closely resemble M1 cells. Overall, this work increases understanding of macrophage metabolism in CRC and elucidates strategies to promote the metabolic state of anti-tumor macrophages.

Association of CETP Gene Polymorphisms and Haplotypes with Cardiovascular Risk

Cholesteryl ester transfer protein (CETP) is known to influence HDL-C levels, potentially altering the profile of HDL subfractions and consequently cardiovascular risk (CVR). This study aimed to investigate the effect of five single-nucleotide polymorphisms (SNPs; rs1532624, rs5882, rs708272, rs7499892, and rs9989419) and their haplotypes (H) in the CETP gene on 10-year CVR estimated by the Systematic Coronary Risk Evaluation (SCORE), the Framingham Risk Score for Coronary Heart Disease (FRS_CHD) and Cardiovascular Disease (FRS_CVD) algorithms. Adjusted linear and logistic regression analyses were used to investigate the association of SNPs and 10 haplotypes (H1-H10) on 368 samples from the Hungarian general and Roma populations. The T allele of rs7499892 showed a significant association with increased CVR estimated by FRS. H5, H7, and H8 showed a significant association with increased CVR based on at least one of the algorithms. The impact of H5 was due to its effect on TG and HDL-C levels, while H7 showed a significant association with FRS_CHD and H8 with FRS_CVD mediated by a mechanism affecting neither TG nor HDL-C levels. Our results suggest that polymorphisms in the CETP gene may have a significant effect on CVR and that this is not mediated exclusively by their effect on TG and HDL-C levels but also by presently unknown mechanisms.

Ensemble-based genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer

1Colorectal cancer (CRC) shows high incidence and mortality, partly due to the tumor microenvironment, which is viewed as an active promoter of disease progression. Macrophages are among the most abundant cells in the tumor microenvironment. These immune cells are generally categorized as M1, with inflammatory and anti-cancer properties, or M2, which promote tumor proliferation and survival. Although the M1/M2 subclassification scheme is strongly influenced by metabolism, the metabolic divergence between the subtypes remains poorly understood. Therefore, we generated a suite of computational models that characterize the M1- and M2-specific metabolic states. Our models show key differences between the M1 and M2 metabolic networks and capabilities. We leverage the models to identify metabolic perturbations that cause the metabolic state of M2 macrophages to more closely resemble M1 cells. Overall, this work increases understanding of macrophage metabolism in CRC and elucidates strategies to promote the metabolic state of anti-tumor macrophages.

Screening and identification of tissue-infiltrating immune cells and genes for patients with emphysema phenotype of COPD

Objective

To study the tissue-infiltrating immune cells of the emphysema phenotype of chronic obstructive pulmonary disease (COPD) and find the molecular mechanism related to the development of emphysema to offer potential targets for more precise treatment of patients with COPD.

Methods

Combined analyses of COPD emphysema phenotype lung tissue-related datasets, GSE47460 and GSE1122, were performed. CIBERSORT was used to assess the distribution of tissue-infiltrating immune cells. Weighted gene co-expression network analysis (WGCNA) was used to select immune key genes closely related to clinical features. Rt-qPCR experiments were used for the validation of key genes. Emphysema risk prediction models were constructed by logistic regression analysis and a nomogram was developed.

Results

In this study, three immune cells significantly associated with clinical features of emphysema (FEV1 post-bronchodilator % predicted, GOLD Stage, and DLCO) were found. The proportion of neutrophils (p=0.025) infiltrating in the emphysema phenotype was significantly increased compared with the non-emphysema phenotype, while the proportions of M2 macrophages (p=0.004) and resting mast cells (p=0.01) were significantly decreased. Five immune-related differentially expressed genes (DEGs) were found. WGCNA and clinical lung tissue validation of patients with emphysema phenotype were performed to further screen immune-related genes closely related to clinical features. A key gene (SERPINA3) was selected and included in the emphysema risk prediction model. Compared with the traditional clinical prediction model (AUC=0.923), the combined prediction model, including SERPINA3 and resting mast cells (AUC=0.941), had better discrimination power and higher net benefit.

Conclusion

This study comprehensively analyzed the tissue-infiltrating immune cells significantly associated with emphysema phenotype, including M2 macrophages, neutrophils, and resting mast cells, and identified SERPINA3 as a key immune-related gene.

Novel Role of CETP in Macrophages: Reduction of Mitochondrial Oxidants Production and Modulation of Cell Immune-Metabolic Profile

Plasma cholesteryl ester transfer protein (CETP) activity diminishes HDL-cholesterol levels and thus may increase atherosclerosis risk. Experimental evidence suggests CETP may also exhibit anti-inflammatory properties, but local tissue-specific functions of CETP have not yet been clarified. Since oxidative stress and inflammation are major features of atherogenesis, we investigated whether CETP modulates macrophage oxidant production, inflammatory and metabolic profiles. Comparing macrophages from CETP-expressing transgenic mice and non-expressing littermates, we observed that CETP expression reduced mitochondrial superoxide anion production and H2O2 release, increased maximal mitochondrial respiration rates, and induced elongation of the mitochondrial network and expression of fusion-related genes (mitofusin-2 and OPA1). The expression of pro-inflammatory genes and phagocytic activity were diminished in CETP-expressing macrophages. In addition, CETP-expressing macrophages had less unesterified cholesterol under basal conditions and after exposure to oxidized LDL, as well as increased HDL-mediated cholesterol efflux. CETP knockdown in human THP1 cells increased unesterified cholesterol and abolished the effects on mitofusin-2 and TNFα. In summary, the expression of CETP in macrophages modulates mitochondrial structure and function to promote an intracellular antioxidant state and oxidative metabolism, attenuation of pro-inflammatory gene expression, reduced cholesterol accumulation, and phagocytosis. These localized functions of CETP may be relevant for the prevention of atherosclerosis and other inflammatory diseases.

High-Density Lipoproteins: A Role in Inflammation in COPD

Chronic obstructive pulmonary disease (COPD) is a widespread disease associated with high rates of disability and mortality. COPD is characterized by chronic inflammation in the bronchi as well as systemic inflammation, which contributes significantly to the clinically heterogeneous course of the disease. Lipid metabolism disorders are common in COPD, being a part of its pathogenesis. High-density lipoproteins (HDLs) are not only involved in lipid metabolism, but are also part of the organism’s immune and antioxidant defense. In addition, HDL is a versatile transport system for endogenous regulatory agents and is also involved in the removal of exogenous substances such as lipopolysaccharide. These functions, as well as information about lipoprotein metabolism disorders in COPD, allow a broader assessment of their role in the pathogenesis of heterogeneous and comorbid course of the disease.

Persistence of Lipoproteins and Cholesterol Alterations after Sepsis: Implication for Atherosclerosis Progression

(1) Background: Sepsis is one of the most common critical care illnesses with increasing survivorship. The quality of life in sepsis survivors is adversely affected by several co-morbidities, including increased incidence of dementia, stroke, cardiac disease and at least temporary deterioration in cognitive dysfunction. One of the potential explanations for their progression is the persistence of lipid profile abnormalities induced during acute sepsis into recovery, resulting in acceleration of atherosclerosis. (2) Methods: This is a targeted review of the abnormalities in the long-term lipid profile abnormalities after sepsis; (3) Results: There is a well-established body of evidence demonstrating acute alteration in lipid profile (HDL-c ↓↓, LDL-C -c ↓↓). In contrast, a limited number of studies demonstrated depression of HDL-c levels with a concomitant increase in LDL-C -c in the wake of sepsis. VLDL-C -c and Lp(a) remained unaltered in few studies as well. Apolipoprotein A1 was altered in survivors suggesting abnormalities in lipoprotein metabolism concomitant to overall lipoprotein abnormalities. However, most of the studies were limited to a four-month follow-up and patient groups were relatively small. Only one study looked at the atherosclerosis progression in sepsis survivors using clinical correlates, demonstrating an acceleration of plaque formation in the aorta, and a large metanalysis suggested an increase in the risk of stroke or acute coronary event between 3% to 9% in sepsis survivors. (4) Conclusions: The limited evidence suggests an emergence and persistence of the proatherogenic lipid profile in sepsis survivors that potentially contributes, along with other factors, to the clinical sequel of atherosclerosis.