Proteomic profiling for prediction of recurrent cardiovascular event in patients with acute coronary syndrome and obstructive sleep apnea: A post-hoc analysis from the ISAACC study.

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/m2 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.