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Background: Obstructive sleep apnea (OSA) is associated with a recurrent cardiovascular event (CVE) risk in patients with a first acute coronary syndrome (ACS). However, the pathological pathways by which OSA promotes this deleterious role are unknown. We aim to explore the proteomic profile associated with OSA that promote the recurrent CVE risk in severe OSA patients with ACS without previous cardiovascular diseases., Methods: This post-hoc analysis from the ISAACC study (NCT01335087) included 86 patients admitted for ACS. Patients underwent respiratory polygraphy for the first 24-72 h to OSA diagnosis. We analyzed of 276 cardiovascular and inflammatory related proteins in baseline fasting plasma samples using proximity expression assay technology (Olink®, Sweden). Protein levels were compared between severe OSA patients with/without recurrent CVEs during follow-up. Random forest was conducted to select relevant proteins and generate a predictive model of recurrent CVE., Results: We included 86 patients (median age: 61 years, median BMI: 29.4 kg/m 2 and 86 % males) admitted for ACS with severe OSA (56 without recurrent CVE/30 with recurrent CVE). The plasma levels of 38 proteins were differentially expressed between groups. Additionally, 12 proteins had a significant association with respiratory polygraphy parameters. Three proteins discriminate with an AUC of 0.81 (95 % CI of 0.71-0.9) between severe OSA patients with and without recurrent CVE. These proteins were implicated in cell proliferation, communication and apoptosis, and regulation/response to the inflammatory and immune systems., Conclusion: In ACS patients with severe OSA, a proteomic profile was associated with recurrent CVEs. This proteomic profile was correlated with specific OSA parameters from respiratory polygraphy. Proteomic profiling may provide an new direction for patient risk stratification and clinical management., Competing Interests: Conflict of interest statement FB received a research grant from ResMed (an Australian company that develops products related to sleep apnea), the Health Research Fund, the Spanish Ministry of Health, the Spanish Respiratory Society, the Catalonian Cardiology Society, Esteve-Teijin (Spain), Oxigen Salud (Spain), and ALLER to develop the ISAACC trial. ResMed partly funded the ISAACC study but did not participate in nor was involved in decisions regarding study development or the present manuscript. All other authors declare no competing interests., (Copyright © 2022 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Background: Up to 80% of patients surviving acute respiratory distress syndrome (ARDS) secondary to SARS-CoV-2 infection present persistent anomalies in pulmonary function after hospital discharge. There is a limited understanding of the mechanistic pathways linked to post-acute pulmonary sequelae., Aim: To identify the molecular underpinnings associated with severe lung diffusion involvement in survivors of SARS-CoV-2-induced ARDS., Methods: Survivors attended to a complete pulmonary evaluation 3 months after hospital discharge. RNA sequencing (RNA-seq) was performed using Illumina technology in whole-blood samples from 50 patients with moderate to severe diffusion impairment (D LCO <60%) and age- and sex-matched individuals with mild-normal lung function (D LCO ≥60%). A transcriptomic signature for optimal classification was constructed using random forest. Transcriptomic data were analyzed for biological pathway enrichment, cellular deconvolution, cell/tissue-specific gene expression and candidate drugs., Results: RNA-seq identified 1357 differentially expressed transcripts. A model composed of 14 mRNAs allowed the optimal discrimination of survivors with severe diffusion impairment (AUC=0.979). Hallmarks of lung sequelae involved cell death signaling, cytoskeleton reorganization, cell growth and differentiation and the immune response. Resting natural killer (NK) cells were the most important immune cell subtype for the prediction of severe diffusion impairment. Components of the signature correlated with neutrophil, lymphocyte and monocyte counts. A variable expression profile of the transcripts was observed in lung cell subtypes and bodily tissues. One upregulated gene, TUBB4A, constitutes a target for FDA-approved drugs., Conclusions: This work defines the transcriptional programme associated with post-acute pulmonary sequelae and provides novel insights for targeted interventions and biomarker development., (Copyright © 2022 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Introduction: Obstructive sleep apnea (OSA) is a chronic, heterogeneous and multicomponent disorder with associated cardiovascular and metabolic alterations. Despite being the most common sleep-disordered breathing, it remains a significantly undiagnosed condition., Objective: We examined the plasma metabolome and lipidome of patients with suspected OSA, aiming to identify potential diagnosis biomarkers and to provide insights into the pathophysiological mechanisms underlying the disease. Additionally, we evaluated the impact of continuous positive airway pressure (CPAP) treatment on the circulating metabolomic and lipidomic profile., Material and Methods: Observational-prospective-longitudinal study including 206 consecutive subjects referred to the sleep unit. OSA was defined as an apnea-hypopnoea index ≥ 15 events/h after polysomnography (PSG). Patients treated with CPAP were followed-up for 6 months. Untargeted plasma metabolomic and lipidomic profiling was performed using liquid chromatography coulpled to massspectrometry., Results: A plasma profile composed of 33 metabolites (mainly glycerophospholipids and bile acids) was identified in OSA vs. non-OSA patients. This profile correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Machine learning analyses disclosed a 4-metabolites-signature that provided an accuracy (95% CI) of 0.98 (0.95-0.99) for OSA detection. CPAP treatment was associated with changes in 5 plasma metabolites previously altered by OSA., Conclusions: This analysis of the circulating metabolome and lipidome reveals a molecular fingerprint of OSA, which was modulated after effective CPAP treatment. Our results suggest blood-based biomarker candidates with potential application in the personalized management of OSA and suggest the activation of adaptive mechanisms in response to OSA-derived hypoxia., (Copyright © 2021 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)