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Data Brief. 2017 Jan 16;11:103-110. doi: 10.1016/j.dib.2017.01.005. eCollection 2017 Apr.

Evening and morning alterations in Obstructive Sleep Apnea red blood cell proteome.

Author information

1
Serviço de Pneumologia, Centro Hospitalar Lisboa Norte (CHLN), Lisboa, Portugal; Laboratório de Proteómica, Departamento de Genética Humana, Instituto Nacional de Saúde Dr Ricardo Jorge, Lisboa 1640-016, Portugal.
2
Laboratório de Proteómica, Departamento de Genética Humana, Instituto Nacional de Saúde Dr Ricardo Jorge, Lisboa 1640-016, Portugal; ToxOmics- Centre of Toxicogenomics and Human Health, Universidade Nova de Lisboa, Portugal.
3
Laboratório de Proteómica, Departamento de Genética Humana, Instituto Nacional de Saúde Dr Ricardo Jorge, Lisboa 1640-016, Portugal.
4
Departamento da Promoção da Saúde, Instituto Nacional de Saúde Dr Ricardo Jorge, Lisboa 1640-016, Portugal.
5
Pulmonary, Critical Care and Sleep Medicine Division, University of California San Diego, CA, USA.
6
Serviço de Pneumologia, Centro Hospitalar Lisboa Norte (CHLN), Lisboa, Portugal; Instituto de Saúde Ambiental (ISAMB), Faculdade de Medicina, Universidade de Lisboa, Portugal.

Abstract

This article presents proteomics data referenced in [1] Using proteomics-based evaluation of red blood cells (RBCs), we have identified differentially abundant proteins associated with Obstructive Sleep Apnea Syndrome (OSA). RBCs were collected from peripheral blood of patients with moderate/severe OSA or snoring at pre- (evening) and post-night (morning) polysomnography, so that proteome variations between these time points could be assessed. RBC cytoplasmic fraction depleted of hemoglobin, using Hemovoid system, were analyzed by two-dimensional fluorescence difference gel electrophoresis (2D-DIGE), the 2D image software-based analyzed and relevant differentially abundant proteins identified by mass spectrometry (MS). MS identified 31 protein spots differentially abundant corresponding to 21 unique proteins possibly due to the existence of post-translational modification regulations. Functional analysis by bioinformatics tools indicated that most proteins are associated with catalytic, oxidoreductase, peroxidase, hydrolase, ATPase and anti-oxidant activity. At morning a larger numbers of differential proteins including response to chemical stimulus, oxidation reduction, regulation of catalytic activity and response to stress were observed in OSA. The data might support further research in OSA biomarker discovery and validation.

KEYWORDS:

2D-DIGE; Biomarkers; Obstructive Sleep Apnea; Red blood cells

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