T-cell cellular stress and reticulocyte signatures, but not loss of naïve T lymphocytes, characterize severe COVID-19 in older adults

Analysis of COPD: Distinguishing Characteristics and Management of Smoking vs Never Smoking Patients

Background

Chronic obstructive pulmonary disease (COPD) is a significant public health issue characterized by gradually worsening airflow limitation. It is a leading cause of mortality and morbidity worldwide, yet research on COPD patients who have never smoked is limited. This study aims to document the demographic, symptomatic, and therapeutic characteristics of COPD patients receiving outpatient pulmonary care in Hungary, focusing on smoking history, and evaluate their distribution according to the GOLD A/B/E classification.

Methods

The study recorded demographic data, symptom severity, occurrence of severe and moderate exacerbations, treatment, comorbidities, quality of life, and COVID-19 vaccination status among COPD patients from November 2021 to January 2023. A total of 6974 patients were categorized into current smokers, former smokers, and never smokers.

Results

Patients had an average age of 67.2±8.9 years, with 48.2% male and 51.8% female. Of participants, 86.1% had a smoking history, while 13.9% had never smoked. COPD patients who had never smoked showed significantly better quality of life (CAT: 15.2±7.6 vs 15.8±6.9; p=0.006), oxygen saturation (SpO2%: 96.7±2.3 vs 95.8±2.4; p<0.001), higher body mass index (BMI: 29.4±5.9 vs 27.1±6.3; p<0.001), and better lung function (FEV1ref%: 67.9±20.7 vs 58.9±18.1; p<0.001) compared to smokers. However, non-smoking COPD patients had a higher frequency of comorbidities (3.5±2.2 vs 2.9±2.1; p<0.05). These differences may arise from complex genetic and environmental interactions.

Conclusion

COPD patients who have never smoked exhibited better quality of life, nutritional status, and lung function compared to smokers, indicating the need for tailored treatment approaches. Further long-term studies are essential to validate these differences in quality of life and lung function between smoking and non-smoking COPD patients.

Identification of shared and disease-specific intratumoral microbiome-host gene associations in gastrointestinal tumors

Intratumoral microbiota and host genes interact to promote gastrointestinal disorders, but how the two interact to influence host tumorigenesis remains unclear. Here, we utilized a machine learning-based framework to jointly dissect the paired intratumoral microbiome and host transcriptome profiles in patients with colon adenocarcinoma, hepatocellular carcinoma, and gastric cancer. We identified associations between intratumoral microbes and host genes that depict shared as well as cancer type-specific patterns. We found that a common set of host genes and pathways implicated in cell proliferation and energy metabolism are associated with cancer type-specific intratumoral microbes. In addition, we also found that intratumoral microbes that have been implicated in three gastrointestinal tumors, such as Lachnoclostridium, are correlated with different host pathways in each tumor, indicating that similar microbes can influence host tumorigenesis in a cancer type-specific manner by regulation of different host genes. Our study reveals patterns of association between intratumoral microbiota and host genes in gastrointestinal tumors, providing new insights into the biology of gastrointestinal tumors.NEW & NOTEWORTHY Our study constitutes a pivotal advancement in elucidating the intricate relationship between the intratumoral microbiome and host gene regulation, thereby gaining insights into the pivotal role that the intratumoral microbiome plays in the etiology of gastrointestinal tumors.

Systems-wide view of host-pathogen interactions across COVID-19 severities using integrated omics analysis

The mechanisms explaining the variability in COVID-19 clinical manifestations (mild, moderate, and severe) are not fully understood. To identify key gene expression markers linked to disease severity, we employed an integrated approach, combining host-pathogen protein-protein interaction data and viral-induced host gene expression data. We analyzed an RNA-seq dataset from peripheral blood mononuclear cells across 12 projects representing the spectrum of disease severity. We identified genes showing differential expression across mild, moderate, and severe conditions. Enrichment analysis of the pathways in host proteins targeted by each of the SARS-CoV-2 proteins revealed a strong association with processes related to ribosomal biogenesis, translation, and translocation. Interestingly, most of these pathways and associated cellular machinery, including ribosomal biogenesis, ribosomal proteins, and translation, were upregulated in mild conditions but downregulated in severe cases. This suggests that COVID-19 exhibits a paradoxical host response, boosting host/viral translation in mild cases but slowing it in severe cases.