Premium
Urinary proteomics in obstructive sleep apnoea and obesity
Author(s) -
Seetho Ian W.,
Siwy Justyna,
Albalat Amaya,
Mullen William,
Mischak Harald,
Parker Robert J.,
Craig Sonya,
Duffy Nick,
Hardy Kevin J.,
Burniston Jatin G.,
Wilding John P. H.
Publication year - 2014
Publication title -
european journal of clinical investigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.164
H-Index - 107
eISSN - 1365-2362
pISSN - 0014-2972
DOI - 10.1111/eci.12346
Subject(s) - sleep (system call) , urinary system , obesity , medicine , proteomics , biology , computer science , biochemistry , gene , operating system
Abstract Background Obstructive sleep apnoea ( OSA ) is a common complication of obesity and can have a substantial negative impact on a patient's quality of life and risk of cardiovascular disease. The aim of this case–control study was to undertake discovery profiling of urinary peptides using capillary electrophoresis–mass spectrometry ( CE ‐ MS ) in obese subjects with and without OSA , without a history of coronary artery disease. Materials and methods Urinary samples were analysed by CE ‐ MS . Body composition and blood pressure measurements were recorded. Overnight polysomnography was conducted to confirm or refute OSA . OSA patients were naïve to continuous positive airway pressure treatment. Results Sixty‐one subjects with OSA (age 47 ± 9 years, BMI 43 ± 8 kg/m 2 ) and 31 controls (age 49 ± 10 years, BMI 40 ± 5 kg/m 2 ) were studied; P = ns for age and BMI . Apnoea–hypopnoea Index was higher in patients with OSA (24 ± 18·6) than controls without OSA (non‐ OSA ) (2·6 ± 1·1; P < 0·0001). Metabolic syndrome was present in 35 (57%) of those with OSA compared with 4 (13%) of controls ( P < 0·0001). Twenty‐four polypeptides were candidates for differential distribution ( P < 0·01), although these differences did not reach significance after multiple testing. Sequences were determined for eight peptides demonstrating origins from collagens and fibrinogen alpha. Conclusions In this study, we report for the first time, urinary proteomic profile analyses using CE ‐ MS in OSA and non‐ OSA obese groups. The differences in urinary proteomic profiles prior to adjustment for multiple testing, with increased metabolic syndrome in obese OSA subjects, suggest that there may be a role for CE ‐ MS in characterising urinary profiles in severely obese populations with OSA .