Lung adenocarcinoma (LUAD) is a major subtype of lung cancer, the prognosis of patients with which is associated with both lncRNAs and cancer immunity. In this study, we collected gene expression data of 585 LUAD patients from The Cancer Genome Atlas (TCGA) database and 605 subjects from the Gene Expression Omnibus (GEO) database. LUAD patients were divided into high and low immune-cell-infiltrated groups according to the single sample gene set enrichment analysis (ssGSEA) algorithm to identify differentially expressed genes (DEGs). Based on the 49 immune-related DE lncRNAs, a four-lncRNA prognostic signature was constructed by applying least absolute shrinkage and selection operator (LASSO) regression, univariate Cox regression, and stepwise multivariate Cox regression in sequence. Kaplan–Meier curve, ROC analysis, and the testing GEO datasets verified the effectiveness of the signature in predicting overall survival (OS). Univariate Cox regression and multivariate Cox regression suggested that the signature was an independent prognostic factor. The correlation analysis revealed that the infiltration immune cell subtypes were related to these lncRNAs.

To evaluate the correlation between various sleep and the risk of NAFLD\MAFLD\MASLD. This study included 4772 subjects from the National Health and Nutrition Examination Survey data from 2017 to 2020. Poor sleep factors were defined as: ①abnormal sleep duration (< 7 h or > 8 h); ②snoring; ③sleep apnea; ④self-reported sleep disorder; ⑤ daytime sleepiness. The frequency of each sleep factor was scored, and the scores of all components were summed to obtain a sleep score ranging from 0 to 12. The higher the score, the less healthy the sleep pattern. Then we divided the overall sleep pattern into mild (sleep score 0–3 points), moderate (sleep score 4–7 points) or severe (sleep score 8–12 points) sleep pattern according to the distribution of sleep scores. Multiple logistic regression and restricted cubic spline graph analysis were used to determine the association between sleep and NAFLD\MAFLD\MASLD. In Model 1 and Model 2, sleep score as a continuous or categorical variable had an effect on NAFLD\MAFLD\MASLD(p <0.05). The risk of NAFLD\MAFLD\MASLD was higher in subjects with severe sleep patterns (p < 0.05). Snoring and sleepy during day was associated with NAFLD\MAFLD\MASLD (p < 0.05). We then drew a restricted cubic spline plot and found that sleep duration was nonlinearly associated with MAFLD\MASLD (p < 0.01), and the risk of MAFLD\MASLD was lower when the sleep duration was 7.5 ~ 9.5 h/d. In this nationally representative survey, severe sleep patterns were associated with an increased risk of NAFLD/MAFLD/MASLD. It is worth noting that sleep duration was nonlinearly associated with MAFLD and MASLD.