Brain bioenergetics as markers of vigilance failure in obstructive sleep apnoea
Caroline D Rae1, Haider Naqvi2, Andrew Vakulin2,3, Angela D'Rozario2, Michael Green1, Hannah Openshaw2, Keith Wong2,4, Jong-Won Kim5, Delwyn J Bartlett6, Doug McEvoy7, and Ronald R Grunstein6

1The University of New South Wales, Randwick, Australia, 2NHMRC Centers of Research Excellence, CIRUS and NeuroSleep, Woolcock Institute of Medical Research, The University of Sydney, Sydney, Australia, 33. Adelaide Institute for Sleep Health: A Flinders Centre of Research Excellence, School of Medicine, Flinders University, Adelaide, Australia, 4Sydney Medical School, The University of Sydney, Sydney, Australia, 5School of Physics, The University of Sydney, Sydney, Australia, 6NeuroSleep and Woolcock Institute of Medical Research, The University of Sydney, Sydney, Australia, 7Adelaide Institute for Sleep Health: A Flinders Centre of Research Excellence, School of Medicine, Flinders University, Adelaide, Australia

Synopsis

Here, we investigated the potential for MRS/MRI markers to differentiate between phenotypes of obstructive sleep apnea patients who are vulnerable, versus resistant to vigilance failure, an indicator of driving impairment and accident risk. Vulnerable patients (N = 15) and resistant patients (N = 30) were differentiated on the basis of left orbito-frontal glutamate and aspartate and also anterior cingulate glutathione levels. There was a trend towards lower orbitofrontal creatine levels in vulnerable OSA subjects, but no group differences in brain volumes.

Introduction

Obstructive sleep apnoea (OSA) is associated with driving impairment and accident risk [1]. However, not all patients are impaired and identifying individuals at risk is clinically challenging [2,3]. To help address this problem we used magnetic resonance spectroscopy (MRS) and imaging to examine brain metabolite levels and whole/regional brain volumes towards identifying potential markers to differentiate between phenotypes of OSA patients who are vulnerable vs resistant to vigilance failure.

Methods

Fifty-eight OSA patients underwent overnight polysomnography (PSG) followed by a 28h extended wakefulness challenge during which driving simulator and psychomotor vigilance (PVT) were examined. 1-2 weeks prior to the extended wakefulness experiment, 45 of the 58 patients had a successful MRS/MRI scan. Based on a combination of median split data from driving simulator crash and PVT lapse occurring following extended wakefulness, patients were defined as vulnerable (n=15) or resistant (n=30) to vigilance failure (Fig. 1). Baseline anthropometric, PSG variables, and brain bioenergetics (MRS) in the left-orbitofrontal cortex (LOFC), anterior cingulate cortex (ACC) and hippocampus (Hipp), as well as total grey, white matter and hippocampal volumes were compared between the vulnerable and resistant patient groups. Differences between groups were assessed using unpaired t-tests and Mann-Whitney U tests.

Results

Compared to resistant patients, vulnerable OSA patients exhibited greater sleepiness, more severe OSA and hypoxemia (all p <0.05, Table 1). Furthermore, vulnerable OSA group showed lower levels of ACC glutathione levels (2.0±1.1 vs 3.0±1.9, p=0.029), LOFC glutamate levels (10.9±3.3 vs 13.4±4.3, p=0.034) and LOFC Aspartate levels (18.3±1.7 vs 23.4±1.5, p=0.029). There was also a trend towards lower LOFC creatine level in the vulnerable patients (9.2±0.6 vs 10.7±0.3), but this did not reach statistical significance (p=0.052). There were no significant brain volume difference between the groups (Table 2).

Conclusions

Baseline PSG and MR spectroscopy may provide useful markers of vulnerability to vigilance failure and driving impairment in OSA patients. Further work is necessary using functional imaging, diffusion and fibre tracking to establish brain regions responsible for vigilance control and failure in clinical OSA populations.

Acknowledgements

This work has been funded by the National Health and Medical Research Council of Australia (NHMRC).

References

1. Tregear S, Reston J, Schoelles K, Phillips B. Obstructive sleep apnea and risk of motor vehicle crash: systematic review and meta-analysis. J Clin Sleep Med 2009;5:573-81.

2. McEvoy RD. Asleep at the wheel: who's at risk? Med J Aust 2003;178:365-6.

3. Vakulin A, Catcheside PG, Baulk SD, et al. Individual variability and predictors of driving simulator impairment in patients with obstructive sleep apnea. J Clin Sleep Med 2014;10:647-55.

Figures

Fig. 1. Defining vigilance failure vulnerability. OSA patients were defined as vulnerable or resistant to alertness failure based on median splits of crashes and PVT lapses after extended wakefulness they were in the top (worse) half of performance (red symbols) for both tasks

Table 1. Clinical measures.

Table 2. MRS/MRI variables



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
1189