Lower plasma choline levels are associated with sleepiness symptoms

Accepted Manuscript Lower Plasma Choline Levels are Associated with Sleepiness Symptoms Victoria M. Pak, M.S., M.T.R., Ph.D., Feng Dai, M.S., Ph.D, Brendan T. Keenan, M.S., Nalaka Gooneratne, M.D. M.Sc., Allan I. Pack, M.B.Ch.B., Ph.D PII:

S1389-9457(17)30412-4

DOI:

10.1016/j.sleep.2017.10.004

Reference:

SLEEP 3549

To appear in:

Sleep Medicine

Received Date: 17 May 2017 Revised Date:

6 September 2017

Accepted Date: 6 October 2017

Please cite this article as: Pak VM, Dai F, Keenan BT, Gooneratne N, Pack AI, Lower Plasma Choline Levels are Associated with Sleepiness Symptoms, Sleep Medicine (2017), doi: 10.1016/ j.sleep.2017.10.004. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Lower Plasma Choline Levels are Associated with Sleepiness Symptoms

Nalaka Gooneratne, M.D. M.Sc. a, Allan I. Pack, M.B.Ch.B., Ph.D a

RI PT

Victoria M. Pak, M.S., M.T.R., Ph.D.a,b, Feng Dai, M.S., Ph.Dc, Brendan T. Keenan, M.S. a,

School of Medicine, Philadelphia, PA

SC

a. Center for Sleep and Circadian Neurobiology, University of Pennsylvania Perelman

b. Emory University, Nell Hodgson Woodruff School of Nursing; Atlanta, GA

Corresponding author: Victoria M. Pak, Ph.D.

M AN U

c. Yale School of Public Health; New Haven, CT

AC C

EP

TE D

E-mail: [email protected] Telephone : 404-712-6849 Present address: Emory University 1520 Clifton Road Room 243 Atlanta, GA 30322

ACCEPTED MANUSCRIPT

ABSTRACT Sleepiness and cardiovascular disease share common molecular pathways; thus, metabolic risk factors for sleepiness may also predict cardiovascular disease risk. Daytime sleepiness predicts

RI PT

mortality and cardiovascular disease, although the mechanism is unidentified. This study

explored the associations between subjective sleepiness and metabolite concentrations in human blood plasma within the oxidative and inflammatory pathways, in order to identify mechanisms

SC

that may contribute to sleepiness and cardiovascular disease risk. METHODS

M AN U

An exploratory case-control sample of 36 subjects, categorized based on the Epworth Sleepiness Scale (ESS) questionnaire as sleepy (ESS≥10) or non-sleepy (ESS<10), was recruited among subjects undergoing an overnight sleep study for suspected sleep apnea at the University of Pennsylvania Sleep Center. The average age was 42.4±10.5 years, the mean body mass index

TE D

(BMI) was 40.0±9.36 kg/m2, median Apnea Hypopnea Index (AHI) was 8.2 (IQR: 2.5-26.5), and 52% were male. Fasting morning blood plasma samples were collected after an overnight sleep study. Biomarkers were explored in subjects with sleepiness versus those without using the

EP

multiple linear regression adjusting for age, BMI, smoking, Apnea Hypopnea Index (sleep apnea severity), study cohort, and hypertension.

AC C

RESULTS

The level of choline is significantly lower (P=0.003) in sleepy subjects (N=18; mean plasma choline concentration of 8.19±2.62 µmol/L) compared with non-sleepy subjects (N=18; mean plasma choline concentration of 9.14±2.25 µmol/L). Other markers with suggestive differences (P<0.1) include Isovalerylcartinine, Alpha-Amino apidipic acid, Spingosine 1 Phosphate, Aspartic Acid, Propionylcartinine, and Ceramides (fatty acids; C14-C16 and C-18).

ACCEPTED MANUSCRIPT

CONCLUSION This pilot study is the first to show that lower levels of plasma choline metabolites are associated

with sleepiness will guide targeted symptom management.

RI PT

with sleepiness. Further exploration of choline and other noted metabolites and their associations

AC C

EP

TE D

M AN U

SC

KEYWORDS sleepiness, metabolites, obstructive sleep apnea, humans

ACCEPTED MANUSCRIPT 4 INTRODUCTION Sleepiness and cardiovascular disease share common mechanistic pathways; thus, metabolic factors that place one at risk for sleepiness may also predict cardiovascular disease

RI PT

risk. Both daytime sleepiness and excessive daytime sleepiness symptoms are associated with a higher risk of adverse cardiac events, such as stroke and coronary heart disease (CHD), as well as total and cardiovascular-specific mortality (1-5). Excessive daytime sleepiness is also a

SC

frequently reported symptom in obstructive sleep apnea (OSA), a common sleep disorder with an increased risk of cardiovascular disease (6). This increased risk in OSA is likely due to increased

M AN U

oxidative stress and inflammation caused by frequent and cyclic reductions in oxygen and rapid reoxygenation during sleep (i.e., cyclical intermittent hypoxia) (7). No prior study has explored the differential plasma metabolome of subjects with suspected OSA who complain of sleepiness versus those without. We explored important metabolites within the inflammatory, oxidative

TE D

stress, and neuronal pathways within key panels: Acylcartinines, Ceramides (Cer), trimethylamine N oxide (TMAO), Neurotransmitters and Amino Acids (AA). Panels explored

EP

Acylcartinines were chosen given their link to proinflammatory signaling pathways (8) and their potential role in cognition and memory (9). The Ceramides panel was explored given

AC C

their roles in both inflammation (10), and oxidative stress (11), specifically, involving Sphingosine-1-phosphate (S1P) (12-15), C14-cer (16), and C16-cer (17) and C18:1 (10). We explored the panel trimethylamine N oxide (TMAO) as circulating TMAO has been found to be associated with atherosclerosis (18). TMAO is derived from dietary choline through the action of gut flora (18). Sleep deprivation has been found to be associated with diminished choline plasmalogen levels (19). Choline is a precursor to acetylcholine, and acetylcholine is known to

ACCEPTED MANUSCRIPT 5 play a complex and significant role in memory formation and coordination, and lowered activity within the cholinergic pathway has been associated with memory impairment, as in Alzheimer’s disease (20, 21). As amino acids are known for their role in obesity-related diseases and have

RI PT

independent associations with cardiovascular disease (22-26), we also explored this panel in our study. In addition, aspartic acid intake has been positively correlated with subjective napping (through a daily sleep diary), which may be used as a proxy for subjective sleepiness (27). N-

paradoxical sleep, and an increase in wakefulness (28).

SC

methyl-aspartic acid has been shown to cause a dose-dependent decrease in slow-wave sleep and

M AN U

The objectives of this study are to gain an initial understanding of the biological basis for sleepiness symptoms. We focused on metabolites within inflammatory/oxidative stress, and neuronal pathways and provide evidence that levels of choline are associated with sleepiness.

Sample collection

TE D

METHODS

Two different patient cohorts, the Mechanisms of Sleepiness Symptoms Study (MOSS;

EP

N=16) and Biomarkers of Obstructive Sleep Apnea study (BOSA2; N=20) were included to evaluate biomarker differences in subjects with suspected sleep apnea and normal cognitive

AC C

functioning. All subjects underwent an overnight sleep study for suspected sleep apnea and were recruited from the University of Pennsylvania Sleep Center (Figure 1). Both studies were approved by the University of Pennsylvania Institutional Review Board. Fasting morning blood plasma samples were collected after an overnight sleep study. A

schematic illustration of the panels analyzed and metabolites suggestively linked to sleepiness (P<0.10) are shown in Figure 2.

ACCEPTED MANUSCRIPT 6

Overnight polysomnography All study participants had in-laboratory sleep recordings, which included

RI PT

electroencephalogram, electrooculogram, electrocardiogram, chin and limb electromyelogram, chest and abdominal piezo belts, finger oximeter and oral and nasal thermistors. The American Academy of Sleep Medicine alternative scoring method was used to score the studies (29). Sleep

SC

technicians scored polysomnograms and computed AHI as the number of apneas plus hypopneas divided by hours of sleep time. An apnea was 10 sec or more of airflow cessation, and a

M AN U

hypopnea was associated with a ≥ 3 % fall in oxyhemoglobin saturation and/or an arousal. Sleepiness measurement

The Epworth Sleepiness Scale (ESS), a widely used standardized self-report instrument that assesses tendency to doze (30), was used to measure sleepiness. This questionnaire asks subjects to rate their chance of dozing during 8 common situations. The responses are based on a

TE D

Likert-type scale ranging from 0 to 3, with 0 indicating no chance of dozing and 3 indicating a high chance of dozing. The sum of these responses determines the total ESS score, with higher

EP

scores indicating greater sleepiness (30). Subjects were categorized as having subjective daytime

AC C

sleepiness if they had an ESS score ≥10, based on prior studies (31, 32).

Panel of metabolites explored and mechanistic pathways We used a targeted metabolomics strategy to profile subjects with suspected sleep apnea

in a case-control study of subjects categorized by level of sleepiness. See Supplemental Table 1 for significant metabolites and their mechanistic pathways. Acyl Carnitines UPLC-MS

ACCEPTED MANUSCRIPT 7 Acyl carnitines (specifically C0-C18:1) were measured by Liquid chromatography-mass spectrometry (LC-MS). Briefly, 25uL of plasma was spiked with a purchased internal standard consisting of isotopically labeled acyl carnitines. The samples were then extracted with cold

RI PT

MeOH:DCM (1:1) followed by centrifugation at 12,000 g for 10 minutes. The supernatant was transferred to another vial, dried down and reconstituted in running buffer. A calibration curve was made from a purchased acyl carnitine mix aliquoted at various concentrations and spiked

SC

with the same internal standard as the samples. The samples and calibration standards were analyzed on Thermo TSQ Quantiva mass spectrometer (West Palm Beach, FL) coupled with a

M AN U

Waters Acquity UPLC system (Milford, MA). Data acquisition was done using selective ion monitoring (SRM). Concentrations of each unknown were calculated against their respective standard curves (33). Ceramides

TE D

Plasma ceramides, sphinganine, sphingosine, sphingosine-1-phosphate (S1P), were measured by previously described technique (34). Briefly a 25ul aliquot of plasma was spiked with an internal standards mixture prior to undergoing extraction. Data acquisition was done

EP

using a select ion monitor (SRM) after chromatographic separation and electron ionization on the Thermo TSQ Quantum Ultra mass spectrometer (West Palm Beach, FL), coupled with a Waters

AC C

Acquity UPLC system (Milford, MA). Concentrations of each analyte were calculated against each respective calibration curve. Coefficient of variation of plasma analyzed with each batch of 40 samples over a one month period are 6.3%, 6.2%, 3.1%, 5.0%, 5.7%, 3.2%, 4.9% and 3.3% for sphingosine, sphingosine-1-phosphate, C16:0-ceramides, C18:0-ceramides, C20:0-ceramide, C22:0-ceramide, C24:1-ceramide and C24:0-ceramide respectively (34). Trimethylamine N-oxide (TMAO)

ACCEPTED MANUSCRIPT 8 Plasma betaine, choline, carnitine, TMA and TMAO concentrations were determined by LC-MS as described in Koeth et al. (35) and Kirsch et al with a few modifications (36). Briefly, a solution of D9-isotopes was spiked in plasma samples as internal standard. The mixture was

RI PT

deproteinized with cold methanol. Supernatant was dried down and resuspend in running buffer prior to injecting on a Sciex 6500 triple quadrupole mass spectrometer (Framingham, MA)

coupled with a Cohesive TX2 LC system (Franklin, MA). Analytes were separated on a Grace

SC

Altima HP HILIC 150mm x 2.1mm, 5µm column prior to analyzing on the mass spectrometer via electrospray ionization mode. Data acquisition was done using selective ion monitoring

respective analyte (35, 36). Neurotransmitters and Amino Acids

M AN U

(SRM). Concentration of each analyte was calculated against an 8-point standard curve for each

Neurotransmitters and some amino acids such as Tryptophan and Taurine were measured

TE D

by LCMS as previously described (37). Briefly, plasma samples were spiked with an internal standard mix consisting of isotopically labeled amino acids. They were then deproteinized with cold methanol followed by centrifugation at 12,000 g for 10 minutes. The supernatant was

EP

transferred to a different vial, dried down and derivatized with 6-aminoquinolyl-Nhydroxysuccinimidyl carbamate according to Waters’ MassTrak kit. A 11-point calibration

AC C

standard curve was spiked with the same internal standard mix and underwent the same derivatization procedure. Both derivatized standards and samples were analyzed on a Thermo TSQ Quantum Ultra mass spectrometer (West Palm Beach, FL) coupled with a Waters Acquity UPLC system (Milford, MA). Data acquisition was done using selective ion monitor (SRM). Concentrations of the analytes of each unknown were calculated against their respective calibration curves (37).

ACCEPTED MANUSCRIPT 9

Statistical analysis Patient demographics, clinical characteristics, and biomarker values were summarized

RI PT

using mean (SD) or median (interquartile range) for continuous variables, and n (%) for

categorical variables. To help visualize the relative magnitude of biomarker values, we generated a heatmap of normalized (set to same scale) biomarker values by sleepiness status using the

SC

heatmap function in R statistical software (www.r-project.org; R Core Team 2013).

Univariate analyses were first performed to compare differences between patients with

M AN U

and without sleepiness, with a two-sample t-test or Wilcoxon rank sum test used for continuous variables, and a Chi-square or Fisher’s exact test used for categorical variables. The normality of biomarker values was checked using the Shapiro-Wilk test, and biomarkers whose values were not normally distributed were transformed using the Box-Cox transformation method. To

TE D

examine the association between biomarkers and sleepiness (ESS≥10 vs. ESS<10), we applied multiple linear regression models in which each dependent variable (i.e., each biomarker separately as the outcome) was regressed against the binary sleepiness factor, adjusting for the

EP

following covariates: study cohort, age, BMI, smoking, Apnea Hypopnea Index (sleep apnea severity), and presence or absence of hypertension. All the statistical analyses were performed

AC C

using the SAS version 9.4 (SAS Institute, Cary, NC). Given the exploratory nature of this study a two-sided p-value of less than 0.05 was considered to be statistically significant and a p-value < 0.10 suggestive of an association with sleepiness. RESULTS

Summary statistics of patient demographics are presented in Table 1. The mean (SD) age was 43.3 (10.2) years in 18 sleepiness subjects and 41.4 (11.1) in 18 non-sleepiness subjects. No

ACCEPTED MANUSCRIPT 10 statistically significant difference in age was found between two groups (p = 0.60). As expected, the average ESS score in the non-sleepiness group was much lower than that in the sleepiness group [5.1 (2.2) vs. 14.1 (3.5); p < 0.001]. There were equal proportions of male and female in

RI PT

each group and in the overall sample. The hypertension rate in the sleepiness group was

statistically higher than that in the non-sleepiness group (55.6% vs. 12.5%, p = 0.009). Other demographics including BMI, AHI, smoking, presence of cardiovascular disease and/or stroke,

SC

and use of exercise were comparable between the two groups (see Table 1).

Supplemental Figure 1 illustrates a heat map of normalized and color-coded expression

M AN U

values (Z scores) of all metabolites (X-axis) in 36 subjects (Y-axis), in which the green values indicate higher values with red color representing lower values. Clustering was done at the biomarker level (Y-axis). No significant patterns were identified in the Figure. Results for biomarkers showing suggestive differences (p<0.10) between sleepy and non-

TE D

sleepy individuals are shown in Table 2, after adjusting for relevant covariates. We also ran models with ESS treated continuously and the effect is reduced (data not shown), thus the data are not linear and categorical ESS is a better predictor. Association results of sleepiness status

EP

with the complete list of biomarkers are presented in Supplemental Table 2. Choline showed the most significant association with sleepiness status; levels were found to be significantly

AC C

lower in sleepy subjects compared to non-sleepy subjects [adjusted mean difference (SE) = 2.674 (0.804) µM; p=0.003; Table 2, Figure 3]. A similar direction of effect (e.g., lower values in sleepy patients) was observed for all significant or suggestive biomarkers presented in Table 2, including the following which showed significant differences (p<0.05): Alpha-AminoadipicAcid (p=0.022), Sphingosine-1-Phosphate (S1P; p=0.026), Isovalercylcartine (p=0.035), Aspartic Acid (p=0.039), and Ceramides C14 (p=0.040), C16 (p=0.040) and C18 (p=0.046).

ACCEPTED MANUSCRIPT 11 DISCUSSION The associations between choline and sleepiness may reflect previously established associations, as sleep restriction has been found to impact lipid concentrations in plasma (i.e.

RI PT

fatty acids) (38, 39), and a decrease in choline plasmalogen levels during sleep deprivation is consistent with prior work demonstrating lipids are susceptible to degradation by oxidative stress (19). This exploratory study is the first to show that lower levels of plasma choline metabolites

SC

are linked with sleepiness.

Choline is an important nutrient and precursor for the neurotransmitter acetylcholine and

M AN U

for phosphatidylcholine, a structural component of VLDL (40), and a key mechanism to export triacylglycerol from the liver. Choline may be obtained via the diet (41) and from endogenous biosynthesis predominantly in the liver through the action of phosphatidylethanolamine Nmethytransferase (PEMT) (42). Choline is present in the human diet as lecithin, which is a

pork (41, 43, 44).

TE D

common name for phosphatidylcholine, with the main food sources as eggs, liver, soybeans, and

Acetylcholine plays a significant role in memory formation and coordination, and

EP

lowered activity within the cholinergic pathway has been associated with memory impairment such as in Alzheimer’s disease (21, 45, 46). In humans, a randomized, double blind, placebo-

AC C

controlled study demonstrated that verbal memory (as measured by a logical memory passage from the Logical Memory subtest of the Wechsler Memory Scale-Revised) in older adults improves with 1000 mg/d dietary citicoline (CDP choline) supplementation (47). In another double-blind placebo controlled trial, patients with AD (average duration of illness being 4 years) given phosphatidylcholine (20-25 g/day of purified soya lecithin containing 90% phosphatidyl plus lysophosphatidyl choline) for six months demonstrated moderate

ACCEPTED MANUSCRIPT 12 improvements on multiple memory tests (48). It will be important to explore whether dietary supplementation will similarly improve sleepiness. Our overall population had mild sleep apnea, which is important to recognize, as a prior

RI PT

study that exposed rats to severe intermittent hypoxia (IH) during sleep demonstrated reduced choline acetyltransferase (ChAT) immunoreactivity (49). IH treated animals demonstrated

impaired working memory and significant reductions in CHAT-stained neurons after 14 days of

SC

IH exposure (49). In a mouse model of Alzheimer’s Disease (AD), Tg2576 genetically engineered AD mice with age-dependent ß deposition in their brains displayed sleep

M AN U

abnormalities compared to control mice, and the authors of this study hypothesized that this may be due to cholinergic deficiencies in AD mice (50). Interestingly, when timed-pregnant SpragueDawley rats (Charles River Breeding, Raleigh, NC) were choline deficient, this significantly decreased the rate of mitosis in the neuroepithelium adjacent to the hippocampus in the fetal

TE D

brain (51). Dietary choline availability alters the timing of migration, commitment to differentiation of progenitor neuronal-type cells in fetal brain hippocampal regions known to be associated with learning and memory (51). Choline appears to play a critical role in attentional

EP

processes (and by extension, learning processes), as well as memory (52). The exploration of choline levels and ChAT/AChE activity in humans with and without sleep apnea will be

AC C

important to explore in order to clarify the link to sleepiness. Overall, our findings are consistent with previous reports of choline playing a significant

role in cognitive processes. The high-affinity choline uptake transporter (CHT) brings in choline from the extracellular space to presynaptic terminals, thereby enabling normal acetylcholine synthesis and cholinergic transmission (52). Thus, abnormalities in CHT capacity have been associated with decreased ability to perform tasks that require attentional processes (52), which

ACCEPTED MANUSCRIPT 13 suggest regulating CHT capacity may be a target for new pharmacological treatments for cognitive disorders (52). Cortical ACh release was higher in rats performing sustained attention tasks compared to rats conducting control tasks, highlighting the important role of choline in

RI PT

attentional processing (53). In another experiment, infusions of the cholinotoxin 192 IgG-saporin induced loss of cortical cholinergic inputs, which resulted in rats’ impaired performance in a sustained attention test, while performance on non-attention related control activities remained

SC

unaffected (54).

Other metabolites that were related to sleepiness (P<0.1) in this study were

M AN U

Isovalercylcartine, Alpha-Amino apidipic acid, Spingosine 1 Phosphate (S1P), Aspartic Acid, and Ceramides and warrant further study. Of the acylcartinines explored, lower isovalercylcartinine levels were found to be related to sleepiness.

Although isovalercylcartinine has not been studied in relation to sleepiness previously,

TE D

isovaleric acidemia is a genetic condition that causes elevated levels of isovalerylcarnitine in plasma. One of the symptoms of this condition includes lethargy (55), thus if isovalerylcarnitine levels in plasma are elevated, sleepiness may potentially be increased. However, this theory

EP

conflicts with a recent study showing that isovalerylcarnitine serum levels were previously found to be lower in Inflammatory Bowel disease patients compared to controls (56). This finding

AC C

suggests that a deficiency in isovalerycarnitine may be associated with inflammation, which may explain our results showing that a lower level of isovalerylcarnitine is related to subjective sleepiness and our hypothesis that increased inflammation is associated with sleepiness. Lower levels of alpha-amino adipic acid were also found to be associated with sleepiness

in our study, and although not previously studied in the context of sleepiness, alpha-amino adipic acid has previously been found to be linked to oxidative stress (57). Prior studies have shown

ACCEPTED MANUSCRIPT 14 that accumulation of alpha-amino adipic acid in astrocytes and glial cells results in reduced intracellular cysteine, followed by “lethal oxidative stress” caused by glutathione synthesis in these cells (58, 59). These results conflict with our findings showing a lower alpha-amino adipic

RI PT

acid level and link to sleepiness, however, due to the lack of human studies on this metabolite in relation to sleepiness, our results are not directly comparable and further exploration in this area is warranted.

SC

S1P has not previously been explored in relation to sleepiness in prior studies. However, S1P has been shown to protect against hypoxia-induced cell death in neonatal rat

M AN U

cardiomyocytes, as well as against ischemia-induced cardiac damage in mice, suggesting that S1P protects the heart from the deleterious effects of TNF-α (14). This suggests that S1P may have a protective effect against oxidative stress, which may explain our results showing lower levels of S1P are linked to subjective sleepiness, and warrants further exploration.

TE D

Lower plasma aspartic acid levels were found to be linked to sleepiness in our study. A prior study showed that aspartic acid intake, which was extrapolated from a subjective food frequency questionnaire, was also previously linked with subjective napping via sleep diary

EP

(used as a proxy for sleepiness) in a study of 459 post-menopausal women (27). The authors noted that the relationships of subjectively reported dietary intake of nutrients to subjective

AC C

napping should be interpreted with caution as these nutrients may reflect intake of meat. The differences in study populations (post-menopausal women), sleepiness measurement technique, and extrapolation of dietary nutrients such as aspartic acid from a subjective food frequency questionnaire may account for the differences seen in our results that show lower plasma aspartic acid is associated with sleepiness.

ACCEPTED MANUSCRIPT 15 Lower plasma ceramides (C:14, C:16, and C:18:1) were also associated with sleepiness in ourstudy. There is no existing literature on ceramides as it relates to sleepiness, however,ceramides have previously been linked to oxidative stress (17). Ceramides are linked to

RI PT

inflammatory conditions such as obesity, as adipose tissue from ob/ob (genetically obese) mice contained 54% more C14-cer than lean mice (16). C16-cer levels are higher in the lower airway epithelium of lung donors with advanced cystic fibrosis lung disease (60). These findings of an

SC

increase in C:16 in advanced cystic fibrosis are not directly comparable to our work as ceramide levels were determined from dissected human tissue and we measured human plasma levels in

M AN U

subjects with suspected sleep apnea. Individual C:18:1-cer plasma concentrations were found to be correlated with plasma TNF- α in controls and type 2 diabetic patients, although authors indicate it may not be of any physiological relevance as the concentration was close to the lower limit of detection and was not different between control subjects and type 2 diabetics (10). The

TE D

findings of an increase in ceramides and correlations with an increase in plasma TNF- α are inconsistent with our finding that lower plasma ceramides are linked with sleepiness. The limitation of this prior study was that ceramides were measured in a postabsorptive state and

EP

feeding has been shown to influence plasma ceramide levels (10), whereas fasting levels of plasma ceramides were collected in our study, which may explain the discrepant findings.

AC C

Overall, the findings in these preliminary studies suggest that metabolism is altered in

inflammatory conditions, and there is a need to use consistent measures of metabolite and sleepiness measurements in order to reduce conflicting results and clarify the role of metabolites in the context of sleepiness in human subjects with sleep apnea in future studies. The strengths of this study are that this is the first study exploring the plasma metabolic profiles of suspected sleep apnea subjects with and without sleepiness. We were able to obtain

ACCEPTED MANUSCRIPT 16 robust clinical information such as apnea hypopnea index. One of the limitations of this study is that the sample size was small, thus the statistical power to detect small to moderate effects was limited and findings should be interpreted with caution. We did not adjust for multiple

RI PT

comparisons when interpreting the p-values, as this is a hypothesis generating study. Another limitation is that in the BOSA study, the ESS questionnaire was administered either in the AM or PM, and for the MOSS study, questionnaires were administered in the AM. As the ESS is meant

SC

to recall sleepiness across a wide range of activities over the past month (30), not immediate sleepiness, the administration of the questionnaire either AM or PM should not differ

M AN U

significantly. Although, one prior study showed that repeating Epworth Sleepiness Scale (night of the overnight sleep study and re-administration in the morning) increases its score and diagnostic accuracy and correlation with SDB variables without changing the psychometric properties of the scale (61). The authors noted that in individual cases, ESS may be

TE D

inappropriately understood which may impact score. As the ESS was administered at one time point for both cohorts in our study, any potential learning effect is not applicable. There were differences in the exclusion criteria between the two patient cohorts that should be noted.

EP

Chronic obstructive pulmonary disease, liver cirrhosis, thyroid dysfunction, chronic renal failure and/or psychiatric disorders were listed exclusion criteria for MOSS and not for BOSA, thus

AC C

these variables may act as potential confounders and impact sleepiness. As the measurement of sleepiness phenotype was subjective, the sleepiness scores are also subject to misclassification bias. Further, the study was cross-sectional in nature and had a targeted population of subjects with suspected sleep apnea, thus preventing broad generalization of results. The mechanism through which inadequate sleep and sleep apnea may impair the cholinergic pathway and influence sleepiness warrants further study. Although previous studies

ACCEPTED MANUSCRIPT 17 have shown that AHI is not significantly correlated with any of the subjective measures of sleepiness (62, 63), there is a need to uncover the mechanistic differences of plasma metabolites between OSA versus non-OSA subjects in the context of sleepiness in a larger future study.

RI PT

Furthermore, it will be important to identify the impact of nighttime sleep architecture on plasma metabolites as it is unclear why sleep disruption in sleep apnea does not always lead to daytime sleepiness (64). Specifically, studies should explore choline and other significant metabolites in

SC

this study and the correlation to time spent in sleep stages. Future studies should also consider the collective impact of dietary choline, genetics (i.e. SNPs in genes involved in choline

M AN U

metabolism), inflammation, and oxidative stress on attentional processes, sleepiness, and cardiovascular disease risk. The continued exploration of choline and other noted metabolites and their associations with objectively measured neurobehavioral deficits and sleepiness would

AC C

EP

TE D

guide targeted symptom management, which may include dietary/supplement recommendations.

ACCEPTED MANUSCRIPT 18 Acknowledgements

AC C

EP

TE D

M AN U

SC

RI PT

The authors express their thanks to the Mayo Clinic Metabolomics Core for their support and assistance during the study. This work was supported by the Mayo Clinic Metabolomics Resource Core through grant number U24DK100469 from the National Institute of Diabetes and Digestive and Kidney Diseases and originates from the National Institutes of Health Director's Common Fund, 1K99NR014675-01, R00NR014675-03 NIH Pathway to Independence Award and NIH Program Project Grant P01HL094307.

ACCEPTED MANUSCRIPT 19

AC C

EP

TE D

M AN U

SC

RI PT

1. Newman AB, Spiekerman CF, Enright P, Lefkowitz D, Manolio T, Reynolds CF, et al. Daytime sleepiness predicts mortality and cardiovascular disease in older adults. The Cardiovascular Health Study Research Group. J Am Geriatr Soc. 2000;48(2):115-23. 2. Boden-Albala B, Roberts ET, Bazil C, Moon Y, Elkind MS, Rundek T, et al. Daytime sleepiness and risk of stroke and vascular disease: findings from the Northern Manhattan Study (NOMAS). Circ Cardiovasc Qual Outcomes. 2012;5(4):500-7. 3. Qureshi AI, Giles WH, Croft JB, Bliwise DL. Habitual sleep patterns and risk for stroke and coronary heart disease: a 10-year follow-up from NHANES I. Neurology. 1997;48(4):904-11. 4. Lee CH, Ng WY, Hau W, Ho HH, Tai BC, Chan MY, et al. Excessive daytime sleepiness is associated with longer culprit lesion and adverse outcomes in patients with coronary artery disease. J Clin Sleep Med. 2013;9(12):1267-72. 5. Empana JP, Dauvilliers Y, Dartigues JF, Ritchie K, Gariepy J, Jouven X, et al. Excessive daytime sleepiness is an independent risk indicator for cardiovascular mortality in community-dwelling elderly: the three city study. Stroke. 2009;40(4):1219-24. 6. Pack AI, Gislason T. Obstructive sleep apnea and cardiovascular disease: a perspective and future directions. Prog Cardiovasc Dis. 2009;51(5):434-51. 7. Pak VM, Grandner MA, Pack AI. Circulating Adhesion Molecules in Sleep Apnea and Cardiovascular Disease. Sleep Med Rev. 2013;Epub ahead of print(Journal Article). 8. Rutkowsky JM, Knotts TA, Ono-Moore KD, McCoin CS, Huang S, Schneider D, et al. Acylcarnitines activate proinflammatory signaling pathways. Am J Physiol Endocrinol Metab. 2014;306(12):E1378-87. 9. Cristofano A, Sapere N, La Marca G, Angiolillo A, Vitale M, Corbi G, et al. Serum Levels of Acyl-Carnitines along the Continuum from Normal to Alzheimer's Dementia. PLoS One. 2016;11(5):e0155694. 10. Haus JM, Kashyap SR, Kasumov T, Zhang R, Kelly KR, DeFronzo RA, et al. Plasma Ceramides Are Elevated in Obese Subjects With Type 2 Diabetes and Correlate With the Severity of Insulin Resistance. Diabetes. 2009;58(2):337-43. 11. Zigdon H, Kogot-Levin A, Park J-W, Goldschmidt R, Kelly S, Merrill AH, et al. Ablation of ceramide synthase 2 causes chronic oxidative stress due to disruption of the mitochondrial respiratory chain. J Biol Chem. 2013;288(7):4947-56. 12. Sattler K, Levkau B. Sphingosine-1-phosphate as a mediator of high-density lipoprotein effects in cardiovascular protection. Cardiovasc Res. 2009;82(2):201-11. 13. Takuwa Y, Okamoto Y, Yoshioka K, Takuwa N. Sphingosine-1-phosphate signaling and biological activities in the cardiovascular system. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 2008;1781(9):483-8. 14. Alewijnse AE, Peters SLM, Michel MC. Cardiovascular effects of sphingosine-1phosphate and other sphingomyelin metabolites. Br J Pharmacol. 2004;143(6):666-84. 15. Keul P, Lucke S, von Wnuck Lipinski K, Bode C, Gräler M, Heusch G, et al. Sphingosine-1-Phosphate Receptor 3 Promotes Recruitment of Monocyte/Macrophages in Inflammation and Atherosclerosis. Circ Res. 2011;108(3):314-23. 16. Samad F, Hester KD, Yang G, Hannun YA, Bielawski J. Altered adipose and plasma sphingolipid metabolism in obesity: a potential mechanism for cardiovascular and metabolic risk. Diabetes. 2006;55(9):2579-87.

ACCEPTED MANUSCRIPT 20

AC C

EP

TE D

M AN U

SC

RI PT

17. Zigdon H, Kogot-Levin A, Park JW, Goldschmidt R, Kelly S, Merrill AH, Jr., et al. Ablation of ceramide synthase 2 causes chronic oxidative stress due to disruption of the mitochondrial respiratory chain. J Biol Chem. 2013;288(7):4947-56. 18. Bennett BJ, de Aguiar Vallim TQ, Wang Z, Shih DM, Meng Y, Gregory J, et al. Trimethylamine-N-oxide, a metabolite associated with atherosclerosis, exhibits complex genetic and dietary regulation. Cell Metab. 2013;17(1):49-60. 19. Chua EC-P, Shui G, Cazenave-Gassiot A, Wenk MR, Gooley JJ. Changes in plasma lipids during exposure to total sleep deprivation. Sleep. 2015;38(11):1683. 20. Hasselmo ME. Neuromodulation: acetylcholine and memory consolidation. Trends Cogn Sci. 1999;3(9):351-9. 21. Micheau J, Marighetto A. Acetylcholine and memory: A long, complex and chaotic but still living relationship. Behav Brain Res. 2011;221(2):424-9. 22. Felig P, Marliss E, Cahill GF, Jr. Plasma amino acid levels and insulin secretion in obesity. N Engl J Med. 1969;281(15):811-6. 23. Newgard CB, An J, Bain JR, Muehlbauer MJ, Stevens RD, Lien LF, et al. A branchedchain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metab. 2009;9(4):311-26. 24. Cheng S, Rhee EP, Larson MG, Lewis GD, McCabe EL, Shen D, et al. Metabolite profiling identifies pathways associated with metabolic risk in humans. Circulation. 2012;125(18):2222-31. 25. Huffman KM, Shah SH, Stevens RD, Bain JR, Muehlbauer M, Slentz CA, et al. Relationships between circulating metabolic intermediates and insulin action in overweight to obese, inactive men and women. Diabetes Care. 2009;32(9):1678-83. 26. Tang WH, Wang Z, Cho L, Brennan DM, Hazen SL. Diminished global arginine bioavailability and increased arginine catabolism as metabolic profile of increased cardiovascular risk. J Am Coll Cardiol. 2009;53(22):2061-7. 27. Grandner MA, Kripke DF, Naidoo N, Langer RD. Relationships among dietary nutrients and subjective sleep, objective sleep, and napping in women. Sleep Med. 2010;11(2):180-4. 28. Crochet S, Onoe H, Sakai K. A potent non-monoaminergic paradoxical sleep inhibitory system: a reverse microdialysis and single-unit recording study. Eur J Neurosci. 2006;24(5):1404-12. 29. Iber C A-IS, Chesson A, Quan S The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications. American Academy of Sleep Medicine. 2007(1st edn.). 30. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14(6):540-5. 31. Yüksel P, Helena G, Christine E, Karl W, Johan H, Erik T. Effect of Positive Airway Pressure on Cardiovascular Outcomes in Coronary Artery Disease Patients with Nonsleepy Obstructive Sleep Apnea. The RICCADSA Randomized Controlled Trial. Am J Respir Crit Care Med. 2016;194(5):613-20. 32. Hogl B, Saletu M, Brandauer E, Glatzl S, Frauscher B, Seppi K, et al. Modafinil for the treatment of daytime sleepiness in Parkinson's disease: a double-blind, randomized, crossover, placebo-controlled polygraphic trial. Sleep. 2002;25(8):905-9. 33. Chace DH, DiPerna JC, Mitchell BL, Sgroi B, Hofman LF, Naylor EW. Electrospray tandem mass spectrometry for analysis of acylcarnitines in dried postmortem blood

ACCEPTED MANUSCRIPT 21

AC C

EP

TE D

M AN U

SC

RI PT

specimens collected at autopsy from infants with unexplained cause of death. Clin Chem. 2001;47(7):1166-82. 34. Blachnio-Zabielska AU, Persson XM, Koutsari C, Zabielski P, Jensen MD. A liquid chromatography/tandem mass spectrometry method for measuring the in vivo incorporation of plasma free fatty acids into intramyocellular ceramides in humans. Rapid Commun Mass Spectrom. 2012;26(9):1134-40. 35. Koeth RA, Wang Z, Levison BS, Buffa JA, Org E, Sheehy BT, et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat Med. 2013;19(5):576-85. 36. Kirsch SH, Herrmann W, Rabagny Y, Obeid R. Quantification of acetylcholine, choline, betaine, and dimethylglycine in human plasma and urine using stable-isotope dilution ultra performance liquid chromatography-tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci. 2010;878(32):3338-44. 37. Lanza IR, Zhang S, Ward LE, Karakelides H, Raftery D, Nair KS. Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes. PLoS One. 2010;5(5):e10538. 38. Bell LN, Kilkus JM, Booth JN, 3rd, Bromley LE, Imperial JG, Penev PD. Effects of sleep restriction on the human plasma metabolome. Physiol Behav. 2013;122:25-31. 39. Weljie AM, Meerlo P, Goel N, Sengupta A, Kayser MS, Abel T, et al. Oxalic acid and diacylglycerol 36:3 are cross-species markers of sleep debt. Proc Natl Acad Sci U S A. 2015;112(8):2569-74. 40. Olthof MR, Brink EJ, Katan MB, Verhoef P. Choline supplemented as phosphatidylcholine decreases fasting and postmethionine-loading plasma homocysteine concentrations in healthy men. Am J Clin Nutr. 2005;82(1):111-7. 41. Zeisel SH, Mar MH, Howe JC, Holden JM. Concentrations of choline-containing compounds and betaine in common foods. J Nutr. 2003;133(5):1302-7. 42. Reo NV, Adinehzadeh M, Foy BD. Kinetic analyses of liver phosphatidylcholine and phosphatidylethanolamine biosynthesis using (13)C NMR spectroscopy. Biochim Biophys Acta. 2002;1580(2-3):171-88. 43. Canty DJ, Zeisel SH. Lecithin and choline in human health and disease. Nutr Rev. 1994;52(10):327-39. 44. Zeisel SH. Dietary choline: biochemistry, physiology, and pharmacology. Annu Rev Nutr. 1981;1:95-121. 45. Francis PT. The interplay of neurotransmitters in Alzheimer's disease. CNS spectrums. 2005;10(11 Suppl 18):6-9. 46. Giacobini E. Cholinergic function and Alzheimer's disease. Int J Geriatr Psychiatry. 2003;18(Suppl 1):S1-5. 47. Spiers PA, Myers D, Hochanadel GS, Lieberman HR, Wurtman RJ. Citicoline improves verbal memory in aging. Arch Neurol. 1996;53(5):441-8. 48. Little A, Levy R, Chuaqui-Kidd P, Hand D. A double-blind, placebo controlled trial of high-dose lecithin in Alzheimer's disease. J Neurol Neurosurg Psychiatry. 1985;48(8):73642. 49. Row BW, Kheirandish L, Cheng Y, Rowell PP, Gozal D. Impaired spatial working memory and altered choline acetyltransferase (CHAT) immunoreactivity and nicotinic receptor binding in rats exposed to intermittent hypoxia during sleep. Behav Brain Res. 2007;177(2):308-14.

ACCEPTED MANUSCRIPT 22

AC C

EP

TE D

M AN U

SC

RI PT

50. Wisor JP, Edgar DM, Yesavage J, Ryan HS, McCormick CM, Lapustea N, et al. Sleep and circadian abnormalities in a transgenic mouse model of Alzheimer's disease: a role for cholinergic transmission. Neuroscience. 2005;131(2):375-85. 51. Albright CD, Tsai AY, Friedrich CB, Mar MH, Zeisel SH. Choline availability alters embryonic development of the hippocampus and septum in the rat. Brain Res Dev Brain Res. 1999;113(1-2):13-20. 52. Sarter M, Parikh V. Choline transporters, cholinergic transmission and cognition. Nat Rev Neurosci. 2005;6(1):48-56. 53. Arnold HM, Burk JA, Hodgson EM, Sarter M, Bruno JP. Differential cortical acetylcholine release in rats performing a sustained attention task versus behavioral control tasks that do not explicitly tax attention. Neuroscience. 2002;114(2):451-60. 54. McGaughy J, Kaiser T, Sarter M. Behavioral vigilance following infusions of 192 IgGsaporin into the basal forebrain: selectivity of the behavioral impairment and relation to cortical AChE-positive fiber density. Behav Neurosci. 1996;110(2):247-65. 55. Pearl PL, Chapman, KA. Isovaleric Acidemia: Demos Medical Publishing; 2013. 56. Danese C, Cirene M, Colotto M, Aratari A, Amato S, Di Bona S, et al. Cardiac involvement in inflammatory bowel disease: role of acylcarnitine esters. Clin Ter. 2011;162(4):e105-9. 57. Cannizzo ES, Clement CC, Sahu R, Follo C, Santambrogio L. Oxidative stress, inflammaging and immunosenescence. J Proteomics. 2011;74(11):2313-23. 58. Guidetti P, Schwarcz R. Determination of α-aminoadipic acid in brain, peripheral tissues, and body fluids using GC/MS with negative chemical ionization. Molecular brain research. 2003;118(1):132-9. 59. Brown DR, Kretzschma HA. The glio-toxic mechanism of α-aminoadipic acid on cultured astrocytes. J Neurocytol. 1998;27(2):109-18. 60. Malcolm B, Michael CM, Gail EJ, Joe G, Andrew JF, Paul AC, et al. Ceramide Is Increased in the Lower Airway Epithelium of People with Advanced Cystic Fibrosis Lung Disease. Am J Respir Crit Care Med. 2010;182(3):369-75. 61. Martinez D, Breitenbach TC, Lumertz MS, Alcantara DL, da Rocha NS, Cassol CM, et al. Repeating administration of Epworth Sleepiness Scale is clinically useful. Sleep & breathing = Schlaf & Atmung. 2011;15(4):763-73. 62. Macey PM, Woo MA, Kumar R, Cross RL, Harper RM. Relationship between obstructive sleep apnea severity and sleep, depression and anxiety symptoms in newlydiagnosed patients. PLoS One. 2010;5(4):e10211. 63. Bausmer U, Gouveris H, Selivanova O, Goepel B, Mann W. Correlation of the Epworth Sleepiness Scale with respiratory sleep parameters in patients with sleep-related breathing disorders and upper airway pathology. Eur Arch Otorhinolaryngol. 2010;267(10):1645-8. 64. Ye L, Pien GW, Ratcliffe SJ, Bjornsdottir E, Arnardottir ES, Pack AI, et al. The different clinical faces of obstructive sleep apnoea: a cluster analysis. Eur Respir J. 2014;44(6):16007. 65. Ferrara F, Bertelli A, Falchi M. Evaluation of carnitine, acetylcarnitine and isovalerylcarnitine on immune function and apoptosis. Drugs Exp Clin Res. 2005;31(3):109-14. 66. Benuck M, Banay-Schwartz M, Ramacci MT, Lajtha A. Peroxidative stress effects on calpain activity in brain of young and adult rats. Brain Res. 1992;596(1–2):296-8.

ACCEPTED MANUSCRIPT 23

AC C

EP

TE D

M AN U

SC

RI PT

67. Pettegrew JW, Klunk WE, Panchalingam K, Kanfer JN, McClure RJ. Clinical and neurochemical effects of acetyl-L-carnitine in Alzheimer's disease. Neurobiol Aging. 1995;16(1):1-4. 68. Sano M, Bell K, Cote L, Dooneief G, Lawton A, Legler L, et al. Double-blind parallel design pilot study of acetyl levocarnitine in patients with Alzheimer's disease. Arch Neurol. 1992;49(11):1137-41. 69. Thal LJ, Carta A, Clarke WR, Ferris SH, Friedland RP, Petersen RC, et al. A 1-year multicenter placebo-controlled study of acetyl-L-carnitine in patients with Alzheimer's disease. Neurology. 1996;47(3):705-11. 70. Hudson S, Tabet N. Acetyl-L-carnitine for dementia. The Cochrane database of systematic reviews. 2003(2):Cd003158. 71. Stoica BA, Movsesyan VA, Lea Iv PM, Faden AI. Ceramide-induced neuronal apoptosis is associated with dephosphorylation of Akt, BAD, FKHR, GSK-3β, and induction of the mitochondrial-dependent intrinsic caspase pathway. Molecular and Cellular Neuroscience. 2003;22(3):365-82. 72. Podbielska M, Szulc ZM, Kurowska E, Hogan EL, Bielawski J, Bielawska A, et al. Cytokine-induced release of ceramide-enriched exosomes as a mediator of cell death signaling in an oligodendroglioma cell line. J Lipid Res. 2016;57(11):2028-39. 73. Flavin MP, Yang Y, Ho G. Hypoxic forebrain cholinergic neuron injury: role of glucose, excitatory amino acid receptors and nitric oxide. Neurosci Lett. 1993;164(1-2):5-8. 74. McKinney M, Jacksonville MC. Brain cholinergic vulnerability: Relevance to behavior and disease. Biochem Pharmacol. 2005;70(8):1115-24. 75. Bartus RT, Dean RL, Goas JA, Lippa AS. Age-related changes in passive avoidance retention: modulation with dietary choline. Science. 1980;209(4453):301-3. 76. D'Aniello A. d-Aspartic acid: An endogenous amino acid with an important neuroendocrine role. Brain Research Reviews. 2007;53(2):215-34. 77. Topo E, Soricelli A, Di Maio A, D’Aniello E, Di Fiore MM, D’Aniello A. Evidence for the involvement of D-aspartic acid in learning and memory of rat. Amino Acids. 2010;38(5):1561-9.

ACCEPTED MANUSCRIPT 24 Table 1. Summary statistics of patient demographics and clinical characteristics by Sleepiness status Sleepiness No (N = 18) Yes (N = 18) 41.44 (11.05) 43.33 (10.15)

EP

AC C

9.81 (5.43)

10.05 (1-23.80) 35.63 (9.09)

35.96 (9.36) 358.8 (325.0 – 428.2)

<0.001

0.64 0.84

0.36

18 (50.00%) 18 (50.00%)

0.99

11 (061.11%) 07 (038.89%)

25 (73.53%) 09 (26.47%)

0.13

08 (044.44%) 10 (055.56%)

22 (64.71%) 12 (35.29%)

0.009

18 (100.00%) 00 (000.00%)

34 (97.14%) 01 (02.86%)

0.49

18 (100.00%) 00 (000.00%)

34 (97.14%) 01 (02.86%)

0.49

18 (100.00%) 00 (000.00%)

34 (97.14%) 01 (02.86%)

0.49

01 (016.67%) 05 (083.33%)

06 (40.00%) 09 (60.00%)

0.29

M AN U

09 (050.00%) 09 (050.00%)

8.2 (2.5-26.5)

SC

384.5 (357.0 – 434.1)

P-Value 0.60

RI PT

Total (N = 36) 42.39 (10.50)

14.10 (3.53)

TE D

Age Epworth Sleepiness 5.08 (2.20) Scale (ESS) Apnea Hypopnea 8.2 (3-28.10) Index, events/hr BMI, kg/m2 36.29 (9.88) Total minutes 356.0 (300.0 – sleep time 422.2) Gender Female 09 (050.00%) Male 09 (050.00%) Smoking No 14 (087.50%) Yes 02 (012.50%) Hypertension No 14 (087.50%) Yes 02 (012.50%) Cardiovascular disease No 16 (094.12%) Yes 01 (005.88%) Stroke No 16 (094.12%) Yes 01 (005.88%) Heart Failure No 16 (094.12%) Yes 01 (005.88%) Exercise No 05 (055.56%) Yes 04 (044.44%)

Data are presented as mean (SD) or median (IQR: 25th - 75th percentile) or N (%). Significant values are in bold.

ACCEPTED MANUSCRIPT 25

Table 2. Results of the multiple regression analyses of biomarkers as a function of Sleepiness (Yes vs. No) and adjusted covariates.

C16- Ceramides (uM)* C14-Ceramides (uM)* C18:1- Ceramides (uM)*

-0.234

0.097

0.022

-0.235 -0.151 -0.799

0.100 0.067 0.368

0.026 0.035 0.039

-0.008 -0.030 -0.008

0.004 0.017 0.004

0.040 0.040 0.046

RI PT

Estimate SE P-value -2.674 0.804 0.003

SC

Dependent Variables choline (uM) alpha-Aminoadipic-acid* (uM)* Sphingosine 1 Phosphate*(uM)* Isovalerylcarnitine (uM)* Aspartic Acid(uM)*

AC C

EP

TE D

M AN U

*: Biomarker values are normalized before regression analysis. Note: adjusted covariates include study center, age, BMI, smoking, Apnea Hypopnea Index (sleep apnea severity), and hypertension.

ACCEPTED MANUSCRIPT

26 Supplemental Table 1: Panel of significant (p<0.1) metabolites linked to sleepiness and mechanistic pathways

•

Inflammation/Oxidative Stress o

Isovalerylcarnitine has an important role in immune function and that it may be a caspase-activating, pro-apoptotic factor (65).

o

After addition of a pro-oxidant to rat brains, calpain (proteins important in longterm potentiation in neurons and cell fusion in myoblasts) activity was significantly lower in the brains of young rats after three hours. In adult rats, calpain activity did not decrease. The addition of isovalerylcarnitine to the incubation medium increased calpain activity by 5-7 times, thereby counteracting the effect of the pro-oxidant. This suggests an anti-oxidant effect of isovalerylcarnitine (66).

o

.

Neuronal

AC C

EP

o

Sphingolipids/

RI PT

•

SC

Isovalerylcartine,

Pathway (Inflammatory/Oxidative Stress/Neuronal)

M AN U

Acyl Cartinines

Metabolite (P<0.1)

TE D

Panel

o

Acyl-L-carnitine serum levels declined significantly along a continuum from healthy subjects (n= 46) to subjects with subjective memory complaint (n=24), to those with mild cognitive impairment (n=18), to those with Alzheimer’s disease (n=29) (9). In smaller studies, supplementation with acetyl-L-carnitine has been shown to slow cognitive decline (67, 68), although, a larger clinical trial and metaanalysis of studies on acetyl-L-carnitine have not found enough evidence of acetyl-L-carnitine’s benefits to recommend it as an Alzheimer’s treatment (69, 70).

• Inflammation/Oxidative Stress

ACCEPTED MANUSCRIPT

27

o

S1P helps HDL mediate endothelial nitric oxide production, cardioprotection, and vasodilation, indicating that S1P analogues and S1P receptor subtypespecific interventions could hold potential benefits for cardiovascular treatment (12, 13).

o

S1P has been shown to protect against hypoxia-induced cell death in neonatal rat cardiomyocytes, as well as against ischemia-induced cardiac damage in mice, suggesting that S1P protects the heart from the deleterious effects of TNF-α (14).

o

S1P may also have harmful effects when it binds to specific subtypes of S1P receptors; for example, when it binds to the S1P3 receptor, it can promote inflammatory macrophage and monocyte recruitment, in turn playing a causal role in atherosclerosis (15).

o

Adipose tissue from ob/ob (genetically obese) mice contained 54% more C14cer than lean mice (16).

o

Increased sphingolipids in plasma of obese mice, combined with plasma sphingolipids’ role in atherosclerosis, suggests connection between higher levels of ceramides and cardiovascular risk (16). o ob/ob mice had 55% higher plasma levels of C16-cer than lean mice (16) o ob/ob mice had 86% higher C18-cer plasma levels than lean mice (16)

RI PT

Sphingosine-1phosphate

EP

TE D

C18-cer

M AN U

C16-cer

SC

C14-cer

o

AC C

Ceramides

•

C18:1-cer was found to be correlated with TNF- α, although the levels were not different between control and type 2 diabetics (10).

Neuronal o

C16-cer may induce apoptosis and caspase-3-like activity in cortical neuronal cells (71) and may replicate and intensify the effects of cytokines on the apoptosis of oligodendroglioma cells (72).

ACCEPTED MANUSCRIPT

•

Inflammation/Oxidative Stress

Sleep deprivation has been shown to diminish choline plasmalogen levels in a small study of 20 healthy Chinese males (19). Findings suggest that sleep loss modulates lipid metabolism (19).

o

Oxidative stress has been found to decrease ChAT activity and degrade cholinergic neurons in culture – ChAT decreased in a dose-dependent manner as glucose depletion increased sensitivity to oxidative stress (73).

o

Oxidative stress caused by inflammation (arising from tumor necrosis factoralpha infusion for 20 days) leads to cholinergic degeneration in both transgenic AD Tg2576 mice that express the Swedish double mutation of the human amyloid precursor protein (APPswe) and nontransgenic control mice (74).

M AN U

SC

o

TE D

•

Neuronal o

EP

Choline

AC C

Trimethylamine N oxide (TMAO)

RI PT

28

Sleep deprivation and associated oxidative stress may lead to impaired memory function through their effects on the cholinergic pathway (19). Acetylcholine is known to play a complex and significant role in memory formation and coordination, lowered activity within the cholinergic pathway, and has been associated with memory impairment, as in Alzheimer’s disease (20, 21).

o

In a study of adult mice, those with choline deficient diets exhibited memory loss, while mice with choline-rich diets showed less memory loss (75).

o

In humans, a randomized, double blind, placebo-controlled study demonstrated that verbal memory in older adults improves with 1000 mg/d dietary citicoline supplementation (47).

ACCEPTED MANUSCRIPT

29

•

Inflammation/Oxidative stress

Following reactive oxygen species and reactive nitrogen species-mediated oxidative stress, alpha-aminoadipic acid monoisotopic mass in proteins increased by 14.9632 (57).

o

Accumulation of alpha-amino adipic acid in astrocytes and radial glial cells results in reduced intracellular cysteine, followed by “lethal oxidative stress” caused by glutathione synthesis in these cells
alpha-amino adipic acid is neurotoxic in high concentrations (58, 59).

o

Amino acids have been associated independently with cardiovascular disease (22-26).

SC

o

TE D

Aspartic Acid

M AN U

Neuromodulators in plasma (uM) and Alpha-Amino adipic acid Amino Acids

In another double-blind study, patients with early-stage AD given phosphatidylcholine for six months exhibited moderate improvements on multiple memory tests (48).

RI PT

o

EP

o

AC C

o

•

Aspartic acid intake (based on subjective food frequency questionnaire) has been positively correlated with subjective napping (through a daily sleep diary), as a proxy for subjective sleepiness, in a study of 459 postmenopausal women. This study suggests that aspartic acid is correlated with subjective sleepiness (27).

Reverse microdyalisis and polygraphic recordings were used in freely moving cats after applying amino acids to the periaqueductal grey and adjacent mesopontine tegmentum. N-methyl-aspartic acid led to a dose-dependent decrease in slow-wave sleep and paradoxical sleep, and an increase in wakefulness (28).

Neuronal o

D-aspartic acid acts as a neurotransmitter/neuromodulator—it’s an

ACCEPTED MANUSCRIPT

30

D-aspartic acid has been found to play a significant role in learning and memory in rats. The treatment group was fed sodium D-aspartate for 12-16 days, and displayed a significant improvement in their ability to find a hidden platform in the Morris water maze system. The rats’ hippocampi were examined, and D-aspartic acid had increased by 2.7 times, compared to controls (77).

AC C

EP

TE D

M AN U

SC

o

RI PT

endogenous amino acid that has been detected in synaptosomes and synaptic vesicles. It also increases cylic adenosine monophosphate (cAMP) in neuronal cells (76).

ACCEPTED MANUSCRIPT 31 Supplemental Table 2. Results of the multiple regression analyses of biomarkers as a function of Sleepiness (Yes vs. No) and adjusted covariates. Labels

Estimate

StdErr

choline__uM_

choline (uM)

-2.67

0.80

0.003

Talpha_Aminoadipic_a

alpha-Aminoadipic-acid Transformation*

-0.23

0.10

0.022

TS1P

S1P Transformation*

TIsovalerylcarnitine

Isovalerylcarnitine Transformation*

Aspartic_Acid

Aspartic_Acid

TC16_Cer

C16-Cer Transformation*

TC14_Cer

C14-Cer Transformation*

TC18_1_Cer

C18:1-Cer Transformation*

TSPA

SPA Transformation*

TPropionylcarnitine

Propionylcarnitine Transformation*

TNorepinephrine

Norepinephrine Transformation*

VAR50

RI PT

Dependent

P-value

0.10

0.026

-0.15

0.07

0.035

-0.80

0.37

0.039

-0.01

0.00

0.040

-0.03

0.01

0.040

-0.01

0.00

0.046

-0.06

0.03

0.068

-0.03

0.02

0.074

-0.05

0.03

0.125

alpha-Amino-N-butyric-acid

-3.08

2.02

0.139

TIsovaleric

Isovaleric Transformation*

-0.14

0.10

0.154

TCystathionine_1

Cystathionine 1 Transformation*

0.40

0.28

0.170

TGlutamic_Acid

Glutamic Acid Transformation*

-0.09

0.06

0.174

Proline

Proline

-22.59

16.36

0.179

C20_Cer

C20_Cer

-15.29

11.59

0.198

THydroxylysine_2

Hydroxylysine 2 Transformation*

0.54

0.42

0.210

TIsocaproic

Isocaproic Transformation*

0.13

0.11

0.231

C18_Cer

C18_Cer

-19.87

16.29

0.234

T_1_Methylhistidine

1-Methylhistidine Transformation*

-0.22

0.19

0.254

TSarcosine

Sarcosine Transformation*

-0.22

0.20

0.267

TPhosphoethanolamine

Phosphoethanolamine Transformation*

-0.02

0.02

0.272

Ttmao__uM_

tmao (uM) Transformation*

-0.12

0.11

0.290

Glutamine

35.79

33.43

0.294

Butyrylcarnitine Transformation*

-0.20

0.20

0.312

M AN U

TE D

AC C

TButyrylcarnitine

EP

Glutamine

SC

-0.23

Threonine

Threonine

9.40

9.51

0.332

TOctanoylcarnitine

Octanoylcarnitine Transformation*

0.03

0.03

0.352

C22_cer

C22_cer

-22.49

25.00

0.377

Lysine

Lysine

-10.57

11.88

0.382

0.02

0.02

0.386

TGlycine

Glycine Transformation*

TSeratonin

Seratonin Transformation*

-0.07

0.08

0.391

Tbeta_alanine

beta-alanine Transformation*

-0.15

0.18

0.399

Leucine

Leucine

7.40

8.83

0.410

TLauroylcarnitine

Lauroylcarnitine Transformation*

0.55

0.66

0.413

ACCEPTED MANUSCRIPT 32 0.18

0.22

0.420

Acetylcholine

Acetylcholine

-0.25

0.38

0.509

Sph

Sph

24.85

37.25

0.511

Isoleucine

Isoleucine

3.20

5.07

0.534

Ethanolamine

Ethanolamine

0.35

0.58

0.556

TMyristoylcarnitine

Myristoylcarnitine Transformation*

0.08

0.14

0.559

Tryptophan

Tryptophan

2.03

3.46

0.561

Valine

Valine

9.92

17.05

0.566

TSerine

Serine Transformation*

0.00

0.00

0.567

Methionine

Methionine

1.16

2.07

0.581

TST

TST

36.99

65.42

0.589

Histidine

Histidine

1.79

3.31

0.593

Oleoylcarnitine

TCystine

Cystine Transformation*

0.00

0.00

0.610

-0.02

0.04

0.616

TC24_Cer

C24-Cer Transformation*

-0.06

0.14

0.662

VAR45

gamma-Amino-N-butyric-acid

0.00

0.01

0.663

Ornithine

Ornithine

-1.77

4.13

0.671

Tbeta_Aminoisobutyri

beta-Aminoisobutyric-acid Transformation*

-0.07

0.18

0.684

Arginine

Arginine

-3.00

7.65

0.698

Alanine

Alanine

-15.35

41.22

0.713

Stearoylcarnitine

Stearoylcarnitine

0.00

0.00

0.750

T_3_Methylhistidine

_3_Methylhistidine Transformation*

0.00

0.01

0.754

Taurine

Taurine

-1.78

6.04

0.771

TAcetyl_carnitine

Acetyl carnitine Transformation*

0.00

0.00

0.775

THydroxyproline

Hydroxyproline Transformation*

0.00

0.01

0.788

THomocystine

Homocystine Transformation*

-0.07

0.29

0.806

Palmitoylcarnitine

0.00

0.01

0.808

Taurine Transformation*

0.00

0.00

0.809

Tyrosine

1.26

5.43

0.818

-0.64

2.77

0.819

TTaurine

TE D

AC C

Tyrosine

EP

Palmitoylcarnitine

M AN U

Oleoylcarnitine

RI PT

allo_Isoleucine

SC

allo_Isoleucine

Carnitine

Carnitine

carnitine__uM_

carnitine (uM)

0.56

2.91

0.849

THexanoic

Hexanoic Transformation*

0.00

0.03

0.896

TButyric

Butyric Transformation*

0.01

0.10

0.900

TAdenosine

Adenosine Transformation*

0.01

0.06

0.917

Citrulline

Citrulline

-0.29

2.84

0.920

Phenylalanine

Phenylalanine

-0.26

2.60

0.922

C24_1_Cer

C24_1_Cer

3.96

48.67

0.936

tma__uM_

tma (uM)

-0.08

1.06

0.941

TValeric

Valeric Transformation*

-0.01

0.07

0.941

ACCEPTED MANUSCRIPT 33 betaine__uM_

betaine (uM)

0.11

2.53

0.966

TIsobutyric

Isobutyric Transformation*

0.00

0.03

0.976

Asparagine

Asparagine

-0.05

2.74

0.985

AC C

EP

TE D

M AN U

SC

RI PT

Transformation*: Biomarker values are normalized before regression analysis. Significant values are in bold. Note: adjusted covariates including study center, age, BMI, smoking, Apnea Hypopnea Index (sleep apnea severity), and hypertension

ACCEPTED MANUSCRIPT

Supplemental Figure 1. Heatmap of normalized biomarker values stratified by the sleepiness status

AC C

EP

TE D

M AN U

SC

metabolite expression value: red: lowest; light green: highest.

RI PT

Rows: represent the biomarkers explored; columns: subject samples. Color key indicates

ACCEPTED MANUSCRIPT

AC C

EP

TE D

M AN U

SC

RI PT

Figure 2: Panels analyzed and metabolites linked to sleepiness (P<0.10 in adjusted models)

ACCEPTED MANUSCRIPT

Figure 3. Differences in plasma choline concentration between subjects with sleepiness versus those without sleepiness.

Adjusted p-value = 0.003

RI PT

16

SC

8

0 No

Yes

EP

TE D

Sleepiness (ESS ≥ 10)

M AN U

4

AC C

Choline (uM)

12

ACCEPTED MANUSCRIPT

Figure 1: Study cohorts included from the University of Pennsylvania

BOSA 2 (N=20)

MOSS (N=16)

Study Location: 3624 Market Street sleep lab or

of the University of Pennsylvania sleep lab for overnight

Sheraton hotel sleep lab, Philadelphia, PA for overnight

sleep study

sleep study

Inclusion Criteria: 1– Subjects with suspected sleep apnea (witnessed

Inclusion Criteria: 1– All new patients referred for diagnostic PSG for

apneas, snoring, obesity–

evaluation of OSA

New patients referred for diagnostic PSG for

2–

Age 26

evaluation of OSA

3–

Stable medical history (defined in exclusion criteria–

3– Age 25 70 Exclusion Criteria: 1– Unable/unwilling to provide informed consent No telephone access

3–

Presence of chronic obstructive pulmonary

4– Able to undergo phlebotomy procedures Exclusion Criteria: 1– Previous diagnosis of other sleep disorder 2–

disease, liver cirrhosis, thyroid dysfunction, rheumatoid arthritis, chronic renal failure and/or

participate in protocol

3–

A clinically unstable chronic medical condition as defined by a new diagnosis or change in medical

psychiatric disorders, since these conditions may

management in the previous 2 months (e.g.

confound the relationship between OSA and

myocardial infarction, congestive heart failure,

inflammation; Presence of another sleep disorder in addition to OSA based on PSG, such as

Cheyne-Stokes breathing, unstable angina–

4–

disorder

Night shift workers or those in situations where

Any acute or active infection 3 weeks prior to the diagnostic study

TE D

restless legs syndrome or periodic limb movement

5–

Cognitive impairment

6–

Previous treatment with continuous positive airway

they regularly experience jet lag, or have irregular

pressure (CPAP– in the last 1 year, home oxygen

work schedules.

therapy, tracheotomy, uvulopalatopharyngoplasty or

AC C

EP

4–

Any medical disorder that limits their ability to

M AN U

2–

65

SC

2–

RI PT

Study Location: 11 Gates, 3624 Market Street, Hospital

Epworth Sleepiness Scale Questionnaire Obtained in the AM

7–

other surgery for OSA Inability to perform tests due to inability to communicate verbally, write and read in English, or less than 5th grade reading level

8–

No telephone access or inability to return for followup study

Epworth Sleepiness Scale Questionnaire Obtained in AM or PM (patient preference)

Blood draw for plasma: AM

Sample Analysis at Mayo Clinic

ACCEPTED MANUSCRIPT

As sleepiness and cardiovascular disease share common molecular pathways, metabolic risk factors for sleepiness may predict cardiovascular disease risk.

•

This is the first study to explore the association of metabolites and sleepiness in subjects with suspected sleep apnea.

•

Lower plasma choline is present in subjects with sleepiness (Epworth Sleepiness Scale score ≥10) with suspected sleep apnea, which highlights a potential target for treatment options.

AC C

EP

TE D

M AN U

SC

RI PT

•