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Abstract Obesity can be categorized as metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). However, individuals with MHO are characterized by the absence of metabolic syndrome (MS) and appear to have lower inflammation levels compared to MUO. This study aimed to investigate the association of obesity phenotypes with leptin (LEP) and adiponectin (ADP). According to the inclusion and exclusion criteria, we selected 178 subjects from the previous cross-sectional survey. Based on the body mass index (BMI) and diagnostic criteria of MS, we divided the individuals into three groups, including healthy control group (HC group), metabolically healthy obesity group (MHO group) and metabolically unhealthy obesity group (MUO group). The concentrations of LEP and ADP in serum were measured, and the association of these two cytokines with different obesity phenotypes were subsequently analyzed. Compared to both the HC and MHO groups, the MUO group showed significantly higher BMI, waist circumference (WC), waist-hip ratio (WHR), triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance (Homa-IR) and blood pressure (P

Background: Differentially expressed genes/proteins (DEGs/DEPs) play critical roles in pulmonary tuberculosis (PTB) diagnosis and treatment. However, there is a scarcity of reports on DEGs/DEPs in lung tissues and blood samples in PTB patients. Objective: We aim to identify the DEGs/DEPs in lung tissues and blood samples of PTB patients and investigate their roles in PTB. Materials and Methods: The lung granulomas and normal tissues were collected from PTB patients for proteomic and transcriptomic analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses annotated the functions of DEGs/DEPs. The GSE107994 data set was downloaded to identify the DEGs/DEPs in peripheral blood. The common DEGs and DEPs were identified. A nomogram was established. Pearson correlation analysis was conducted. Results: Eighty‐three DEGs/DEPs were identified. These DEGs/DEPs were mainly enriched in the movement of cell or subcellular components, regulation of cellular component biogenesis, and actin filament‐based process as well as in the pathways of inositol phosphate metabolism, adherens junction, phosphatidylinositol signaling system, leukocyte transendothelial migration, regulation of actin cytoskeleton, and tight junction. There were eight common DEGs/DEPs (TYMP, LAP3, ADGRL2, SIL1, LMO7, SULF 1, ANXA3, and PACSIN3) between the lung tissues and blood samples. They were effective in predicting tuberculosis. Moreover, the activated dendritic cells, macrophages, monocytes, neutrophils, and regulatory T cells were significantly positively correlated with TYMP (r >.50), LAP3 (r >.50), SIL1 (r >.50), ANXA3 (r >.5), and PACSIN3 (r <.50), while negatively correlated with LMO7 (r < −0.50) (p <.05). ADGRL2 and SULF1 did not have a significant correlation (p >.05). Limitations: The sample size was small. Conclusions: Eight common DEGs/DEPs of lung tissues and blood samples were identified. They were correlated with immune cells and demonstrated predictive value for PTB. Our data may facilitate the diagnosis and treatment of PTB. [ABSTRACT FROM AUTHOR]