Asthma is a diverse disease that can be categorized into various phenotypes and endotypes, including obesity-re-lated asthma and allergic asthma. "Treatable traits (TTs)" represent a new approach to managing asthma. Asthma accompanied by dyslipidemia would be a distinct asthma phenotype that is becoming increasingly common. Therefore, dyslipidemia can potentially serve as a target for the management of asthma. Nevertheless, it remains highly under-researched compared to other observable traits. Gaining knowledge about the clinical and inflammatory characteristics, underlying mechanisms, and potential therapeutic medications for asthma with dyslipidemia is crucial for its effective management. This review aimed to provide a comprehensive overview of asthma with dyslipidemia, consolidating existing knowledge and ongoing research.
Humans ; Asthma/complications* ; Dyslipidemias/epidemiology*

PURPOSE: Obesity is associated with metabolic dysregulation, but the underlying metabolic signatures involving clinical and inflammatory profiles of obese asthma are largely unexplored. We aimed at identifying the metabolic signatures of obese asthma. METHODS: Eligible subjects with obese (n = 11) and lean (n = 22) asthma underwent body composition and clinical assessment, sputum induction, and blood sampling. Sputum supernatant was assessed for interleukin (IL)-1β, -4, -5, -6, -13, and tumor necrosis factor (TNF)-α, and serum was detected for leptin, adiponectin and C-reactive protein. Untargeted gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolic profiles in sputum, serum and peripheral blood monocular cells (PBMCs) were analyzed by orthogonal projections to latent structures-discriminate analysis (OPLS-DA) and pathway topology enrichment analysis. The differential metabolites were further validated by correlation analysis with body composition, and clinical and inflammatory profiles. RESULTS: Body composition, asthma control, and the levels of IL-1β, -4, -13, leptin and adiponectin in obese asthmatics were significantly different from those in lean asthmatics. OPLS-DA analysis revealed 28 differential metabolites that distinguished obese from lean asthmatic subjects. The validation analysis identified 18 potential metabolic signatures (11 in sputum, 4 in serum and 2 in PBMCs) of obese asthmatics. Pathway topology enrichment analysis revealed that cyanoamino acid metabolism, caffeine metabolism, alanine, aspartate and glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, pentose phosphate pathway in sputum, and glyoxylate and dicarboxylate metabolism, glycerolipid metabolism and pentose phosphate pathway in serum are suggested to be significant pathways related to obese asthma. CONCLUSIONS: GC-TOF-MS-based metabolomics indicates obese asthma is characterized by a metabolic profile different from lean asthma. The potential metabolic signatures indicated novel immune-metabolic mechanisms in obese asthma with providing more phenotypic and therapeutic implications, which needs further replication and validation.
Adiponectin ; Alanine ; Aspartic Acid ; Asthma* ; Body Composition ; C-Reactive Protein ; Caffeine ; Chromatography, Gas ; Glutamic Acid ; Interleukins ; Leptin ; Mass Spectrometry ; Metabolism ; Metabolome ; Metabolomics ; Obesity ; Pentose Phosphate Pathway ; Phenylalanine ; Pilot Projects* ; Sputum ; Tryptophan ; Tumor Necrosis Factor-alpha ; Tyrosine