HLA-C and KIR permutations influence chronic obstructive pulmonary disease risk

Machine Learning Reveals Impacts of Smoking on Gene Profiles of Different Cell Types in Lung

Smoking significantly elevates the risk of lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. This risk is attributed to the harmful chemicals in tobacco smoke that damage lung tissue and impair lung function. Current research on the impact of smoking on gene expression in specific lung cells is limited. This study addresses this gap by analyzing gene expression profiles at the single-cell level from 43,539 lung endothelial cells, 234,349 lung epithelial cells, 189,843 lung immune cells, and 16,031 lung stromal cells using advanced machine learning techniques. The data, categorized by different lung cell types, were classified into three smoking states: active smoker, former smoker, and never smoker. Each cell sample encompassed 28,024 feature genes. Employing an incremental feature selection method within a computational framework, several specific genes have been identified as potential markers of smoking status in different lung cell types. These include B2M, EEF1A1, and TPT1 in lung endothelial cells; FTL and MT-ATP8 in lung epithelial cells; HLA-B and HLA-C in lung immune cells; and HSP90B1 and LCN2 in lung stroma cells. Additionally, this study developed quantitative rules for representing the gene expression patterns related to smoking. This research highlights the potential of machine learning in oncology, enhancing our molecular understanding of smoking's harm and laying the groundwork for future mechanism-based studies.

Identification of molecular subtypes and immune infiltration in endometriosis: a novel bioinformatics analysis and In vitro validation

Introduction

Endometriosis is a worldwide gynacological diseases, affecting in 6-10% of women of reproductive age. The aim of this study was to investigate the gene network and potential signatures of immune infiltration in endometriosis.

Methods

The expression profiles of GSE51981, GSE6364, and GSE7305 were obtained from the Gene Expression Omnibus (GEO) database. Core modules and central genes related to immune characteristics were identified using a weighted gene coexpression network analysis. Bioinformatics analysis was performed to identify central genes in immune infiltration. Protein-protein interaction (PPI) network was used to identify the hub genes. We then constructed subtypes of endometriosis samples and calculated their correlation with hub genes. qRTPCR and Western blotting were used to verify our findings.

Results

We identified 10 candidate hub genes (GZMB, PRF1, KIR2DL1, KIR2DL3, KIR3DL1, KIR2DL4, FGB, IGFBP1, RBP4, and PROK1) that were significantly correlated with immune infiltration. Our study established a detailed immune network and systematically elucidated the molecular mechanism underlying endometriosis from the aspect of immune infiltration.

Discussion

Our study provides comprehensive insights into the immunology involved in endometriosis and might contribute to the development of immunotherapy for endometriosis. Furthermore, our study sheds light on the underlying molecular mechanism of endometriosis and might help improve the diagnosis and treatment of this condition.

Associations of Smoking, Cytomegalovirus Serostatus, and Natural Killer Cell Phenotypes in Smokers With and At Risk for COPD

Introduction

Chronic obstructive disease (COPD) risk factors, smoking, and chronic infection (cytomegalovirus [CMV]) may mold natural killer (NK) cell populations. What is not known is the magnitude of the effect CMV seropositivity imparts on populations of smokers with and at risk for COPD. We investigate the independent influence of CMV seropositivity on NK cell populations and differential effects when stratifying by COPD and degree of smoking history.

Methods

Descriptive statistics determine the relationship between cytotoxic NK cell populations and demographic and clinical variables. Multivariable linear regression and predictive modeling were performed to determine associations between positive CMV serology and proportions of CD57+ and natural killer group 2C (NKG2C)+ NK cells. We dichotomized our analysis by those with a heavy smoking history and COPD and described the effect size of CMV seropositivity on NK cell populations.

Results

When controlled for age, race, sex, pack-years smoked, body mass index, and lung function, CMV+ serostatus was independently associated with a higher proportion of CD57+, NKG2C+, and NKG2C+CD57+ NK cells. CMV+ serostatus was the sole predictor of larger NKG2C+ and CD57+NKG2C+ populations. Associations are more pronounced in those with COPD and heavy smokers.

Conclusions

Among Veterans who are current and former smokers, CMV+ serostatus was independently associated with larger CD57+ and NKG2C+ populations, with a larger effect in heavy smokers and those with COPD, and was the sole predictor for increased expression of NKG2C+ and CD57+NKG2C+ populations. These findings may be broadened to include the assessment of longitudinal NK cell population change, accrued inflammatory potential, and further identification of pro-inflammatory NK cell population clusters.

Immunity at maternal-fetal interface: KIR/HLA (Allo)recognition

Both KIR and HLA are the most variable gene families in the human genome. The recognition of the semi-allogeneic embryo-derived trophoblasts by maternal decidual NK (dNK) cells is essential for the establishment of the functional placenta. This recognition is based on the KIR-HLA interactions and trophoblast expresses a specific HLA profile that constitutes classical polymorphic HLA-C and non-classical oligomorphic HLA-E, HLA-F, and HLA-G molecules. This review highlights some features of the KIR/HLA-C (allo)recognition by decidual NK (dNK) cells as a main immune cell population specifically enriched at maternal-fetal interface during human early pregnancy. How KIR/HLA-C axis operates in pregnancy disorders and in the context of transplacental infections is discussed as well. We summarized old and new data on dNK-cell functional plasticity, their selective expression of KIR and fetal maternal/paternal HLA-C haplotypes present. Results showed that KIR-HLA-C combinations and the corresponding axis operate differently in each pregnancy, determined by the variability of both maternal KIR haplotypes and fetus' maternal/paternal HLA-C allotype combinations. Moreover, the maturation of NK cells strongly depends on if or not HLA allotypes for certain KIR are present. We suggest that the unique KIR/HLA combinations reached in each pregnancy (normal and pathological) should be studied according to well-defined guidelines and unified methodologies to have comparable results ease to interpret and use in clinics.

Pre-chronic obstructive pulmonary disease: a pathophysiologic process or an opinion term?

PURPOSE OF REVIEW

Current guidelines does not include current or former smokers who do not have spirometric airflow limitation in their diagnostic or therapeutic algorithms for chronic obstructive pulmonary disease (COPD). The purpose of this review is to outline the burden of respiratory morbidity in this population and to discuss the potential utility of their classification as pre-COPD.

RECENT FINDINGS

It is increasingly clear that patients with a history of exposure to cigarette smoke or other environmental pollutants may have substantial lung pathology and respiratory impairment even in the absence of airflow limitation, as detected by spirometry. Not all of these patients will develop airflow limitation, but many will have considerable respiratory morbidity and a comparable prognosis to those with classical, spirometrically defined COPD. The use of the term pre-COPD may allow for the identification of these individuals in order to target preventive and earlier therapeutic strategies.

SUMMARY

Spirometry is not adequately sensitive to identify many current and former smokers and other exposed populations with significant lung pathology and respiratory symptoms. Though the pathologic processes present in these patients differ, the earlier identification of this pre-COPD population may foster the development of more effective and disease-modifying treatments.