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

Correlation Between Hemoglobin Levels and Polycystic Ovary Syndrome Metabolic Disorder

Objective

The purpose of this study was to explore the relationship between hemoglobin levels and metabolic disorders in patients with PCOS.

Methods

A total of 573 patients were selected, based on the hemoglobin level; 342 patients with PCOS were divided into two groups as follows: Group A (normal Hb group, n = 269) and Group B (high Hb group, n = 73); 231 non-PCOS patients were divided into two groups as follows: Group C (normal Hb group, n = 199), and Group D (high Hb group, n = 32). The general information, glucose and lipid metabolism indicators, and uric acid levels of all patients were compiled for data analysis.

Results

(1) Hb, HGB concentration in mean red blood cells and RDW in PCOS patients were higher than those in non-PCOS patients, and MCV was lower than that in non-PCOS patients (P < 0.05); (2) Compared with Group A, patients in Group B had higher BMI, Hb, 2-hPG, FINS, 2-hINS, HOMA-IR, LDL-C, and uric acid levels while the QUICKI was lower; in Group C, the age, FSH, HDL-C, and LDL-C were higher, and AMH, BMI, T, TG, and uric acid level were lower (P<0.05); compared with Group D, AMH, BMI, FINS, HOMA-IR, TG, uric acid level increased, while age, FSH, and QUICKI decreased in Group B; and Hb and T decreased in Group C (P<0.05); (3) Pearson's correlation analysis indicated that Hb in PCOS patients was positively correlated with BMI, FPG, 2-hPG, FINS, 2-hINS, and HOMA-IR, and negatively correlated with the QUICKI (P<0.05); (4) Multi-factor logistic regression analysis suggested that the high Hb level in PCOS patients was an independent risk factor of IR (P<0.05).

Conclusion

Hb level in patients with PCOS was associated with BMI and glucose metabolism indicators; a high Hb level may be an independent risk factor for IR.

[The role of biomarkers in the detection of the OSA syndrome. A narrative review of the literature]

INTRODUCTION

Obstructive sleep apnoea (OSA) is a common sleep-related breath disorder associated with cardiovascular and cerebrovascular complications, such as hypertension, arrhythmia, coronary artery disease and stroke. Unfortunately, OSA is underdiagnosed.

BACKGROUND

Because of its clinical and therapeutic variability, OSA could benefit a personalized medicine approach. Diagnosis with polysomnography is expensive and access is limited. Clinical scoring systems allow screening of OSA, but many limitations exist. Because of this, biomarkers could be useful for the detection of OSA.

OUTLOOK

Biomarkers specific to OSA would allow for better mass screening and more personalized treatment of the disease. This narrative review of the literature aims to summarize the biomarkers already described for the diagnosis of OSA and clarify both their advantages and limitations in daily practice.

CONCLUSIONS

Our review of the literature did not actually identify an ideal biomarker even if promising research is ongoing.

Proteomic biomarkers of sleep apnea

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is characterized by recurrent partial to complete upper airway obstructions during sleep, leading to repetitive arousals and oxygen desaturations. Although many OSA biomarkers have been reported individually, only a small subset have been validated through both cross-sectional and intervention studies. We sought to profile serum protein biomarkers in OSA in unbiased high throughput assay.

METHODS

A highly multiplexed aptamer array (SomaScan) was used to profile 1300 proteins in serum samples from 713 individuals in the Stanford Sleep Cohort, a patient-based registry. Outcome measures derived from overnight polysomnography included Obstructive Apnea Hypopnea Index (OAHI), Central Apnea Index (CAI), 2% Oxygen Desaturation index, mean and minimum oxygen saturation indices during sleep. Additionally, a separate intervention-based cohort of 16 individuals was used to assess proteomic profiles pre- and post-intervention with positive airway pressure.

RESULTS

OAHI was associated with 65 proteins, predominantly pathways of complement, coagulation, cytokine signaling, and hemostasis which were upregulated. CAI was associated with two proteins including Roundabout homolog 3 (ROBO3), a protein involved in bilateral synchronization of the pre-Bötzinger complex and cystatin F. Analysis of pre- and post intervention samples revealed IGFBP-3 protein to be increased while LEAP1 (Hepicidin) to be decreased with intervention. An OAHI machine learning classifier (OAHI >=15 vs OAHI<15) trained on SomaScan protein measures alone performed robustly, achieving 76% accuracy in a validation dataset.

CONCLUSIONS

Multiplex protein assays offer diagnostic potential and provide new insights into the biological basis of sleep disordered breathing.

Redox-Oligomeric State of Peroxiredoxin-2 and Glyceraldehyde-3-Phosphate Dehydrogenase in Obstructive Sleep Apnea Red Blood Cells under Positive Airway Pressure Therapy

In this study, we examined the effect of six months of positive airway pressure (PAP) therapy on Obstructive Sleep Apnea (OSA) red blood cell (RBC) proteome by two dimensional difference gel electrophoresis (2D-DIGE) - based proteomics followed by Western blotting (WB) validation. The discovered dysregulated proteins/proteoforms are associated with cell death, H2O2 catabolic/metabolic process, stress response, and protein oligomerization. Validation by nonreducing WB was performed for peroxiredoxin-2 (PRDX2) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) by using antibodies against the sulfinylated/sulfonylated cysteine of these proteins to better evaluate their redox-oligomeric states under OSA and/or in response to PAP therapy. The results indicated that the redox-oligomeric state of GAPDH and PRDX2 involving overoxidation by sulfinic/sulfonic acids were differentially modulated in OSA RBC, which might be compromising RBC homeostasis. PAP therapy by restoring this modulation induced a higher oligomerization of overoxidized GAPDH and PRDX2 in some patients that could be associated with eryptosis and the chaperone "gain" of function, respectively. This varied response following PAP may result from the complex interplay between OSA and OSA metabolic comorbidity. Hence, information on the redox status of PRDX2 and GAPDH in RBC will help to better recognize OSA subtypes and predict the therapeutic response in these patients. GAPDH monomer combined with body mass index (BMI) and PRDX2 S-S dimer combined with homeostatic model assessment for insulin resistance (HOMA-IR) showed to be very promising biomarkers to predict OSA and OSA severity, respectively.

Advances and challenges in pursuing biomarkers for obstructive sleep apnea: Implications for the cardiovascular risk

Obstructive sleep apnea (OSA) is a common clinical condition associated with increased cardiovascular morbidity and mortality. Recent evidence from clinical studies and animal models suggest that OSA can promote cardiovascular disease by inducing autonomic, hemodynamic, inflammatory and metabolic dysregulation. However, most of the evidence addressing hard endpoints in humans is derived from observational studies. Several challenges have been noted in the pursuit of a comprehensive knowledge base about the impact of OSA including: 1) the precise mechanisms by which OSA causes metabolic and cardiovascular consequences are not clear, which limits our current ability to address potential targets in OSA; 2) several patients with OSA, even with severe forms, present with no or mild daytime symptoms. Beyond the obvious challenges for obtaining good adherence for conventional OSA treatments, there is evidence that symptomatic vs. asymptomatic patients with OSA do not necessarily have the same metabolic and cardiovascular outcomes; and 3) the cardiovascular response to OSA treatment may vary even in those patients with good adherence. In this scenario, there is an obvious need to develop biomarkers in the OSA research area. This review focuses on describing the advances that have occurred so far in exploring potential OSA biomarkers with clear emphasis for the cardiovascular risk. Particular attention will be devoted to discuss molecular biomarkers including the potential role of microRNAs, proteomics and metabolomics. We also discuss the major challenges and perspectives in this growing research field.

Evening and morning peroxiredoxin-2 redox/oligomeric state changes in obstructive sleep apnea red blood cells: Correlation with polysomnographic and metabolic parameters

We have examined the effects of Obstructive Sleep Apnea (OSA) on red blood cell (RBC) proteome variation at evening/morning day time to uncover new insights into OSA-induced RBC dysfunction that may lead to OSA manifestations. Dysregulated proteins mainly fall in the group of catalytic enzymes, stress response and redox regulators such as peroxiredoxin 2 (PRDX2). Validation assays confirmed that at morning the monomeric/dimeric forms of PRDX2 were more overoxidized in OSA RBC compared to evening samples. Six month of positive airway pressure (PAP) treatment decreased this overoxidation and generated multimeric overoxidized forms associated with chaperone/transduction signaling activity of PRDX2. Morning levels of overoxidized PRDX2 correlated with polysomnographic (PSG)-arousal index and metabolic parameters whereas the evening level of disulfide-linked dimer (associated with peroxidase activity of PRDX2) correlated with PSG parameters. After treatment, morning overoxidized multimer of PRDX2 negatively correlated with fasting glucose and dopamine levels. Overall, these data point toward severe oxidative stress and altered antioxidant homeostasis in OSA RBC occurring mainly at morning time but with consequences till evening. The beneficial effect of PAP involves modulation of the redox/oligomeric state of PRDX2, whose mechanism and associated chaperone/transduction signaling functions deserves further investigation. RBC PRDX2 is a promising candidate biomarker for OSA severity and treatment monitoring, warranting further investigation and validation.