This study aimed to identify biomarkers associated with obstructive sleep apnea (OSA) severity and treatment effectiveness. The researchers measured biomarkers related to glucose regulation in patients before and after continuous positive airway pressure (CPAP) therapy. They found that levels of DHEA, cortisol and 17-OH progesterone were lower in OSA patients compared to normal ranges and did not change with CPAP. Serum glucose, HDL and triglycerides were not reliable markers of treatment response. The study was conducted at a comprehensive neurology and sleep center using patient medical records and biochemical analysis to obtain biomarker measurements.

1. Obstructive sleep apnea (OSA) is a known risk factor for metabolic
disturbances, such as diabetes mellitus or dyslipidemia. Continuous positive
airway pressure (CPAP) therapy, the standard treatment for patients with OSA,
may improve various metabolic variables, such as insulin sensitivity, glucose
metabolism, lipids, fat distribution and adipokines. Several observational and
uncontrolled clinical studies claim an improvement of these metabolic variables
through the use of CPAP. However, only a limited number of clinical
randomized controlled trials (RCTs) have evaluated the effect of CPAP on
metabolic variables, and remain inconclusive.
EENA’s point-of-care speciality practice offers a unique OPPORTUNITY
to research into biomarkers of OSA eliminating the time consuming and costly
steps to randomize patient selection and to minimize bias. This practice based
research will take advantage of its comprehensive electronic health record
system (EHR) to facilitate participant recruitment and data collection,
minimizing study overhead and streamlining the experience for patients.
Point-of-care research, particularly in small practice setting is gaining
recognition as a vehicle to deliver the best care to patients while learning from
each experience and redefining that care. This ‘learning and improving’ loop
will enable EENA to more rapidly fold improvements into its practice and may
serve as a prototype for other small independent medical practices or
institutions.
The research objective at EENA Comprehensive Neurology and Sleep
Center is to identify and develop a panel of biomarkers with measurable
biochemical characteristics associated with the severity of OSA, and to
evaluate the effect of CPAP on these variables.
The goal of obtaining measureable panel of biomarkers is to develop
strategies that will facilitate the use of existing or easily attainable and cost
effective data from immunologic, metabolic and hormonal markers, for the
assessment of the onset/severity of OSA/sleep disorders, and efficacy of CPAP
treatment. Of particular interest are biomarker candidates involved in the
regulation of glucose, since there have been some reported associations
between OSA and glucose metabolism.
We hypothesize that OSA is associated with impaired glucose tolerance
as a result of modifications of factors involved in glucose metabolism or
dys-regulation of glucose metabolism due to chronic sleep deprivation.
Introduction
Methods
Hypothesis
Results
Conclusions
Percentage of new patients diagnosed with OSA in 2014
References
Pilot study of Biomarkers for predicting obstructive sleep apnea (OSA)
and effectiveness of CPAP treatment-correlation with Glucose Regulation
1
Edith Mensah MD PhD MBA, 2
Miriam Isma BS, 3
Vadine Eugene BS and 4
Nadir Osman MD MS CADAS
1,2,3,4
EENA Comprehensive Neurology & Sleep Center, Boynton Beach FL; 1,4
Affiliate Faculty @ The Charles E. Schmidt College of Medicine-FAU, Boca Raton FL
Levels of blood pressure (BP) and neck circumference
Correlation of BMI & BP in patients with OSA vrs other patients
Study Population (Subjects): Adult volunteer patients were recruited for the study. Overall
well-being was assessed via a questionnaire survey at the beginning and at follow up during
the study. Additionally data from health records were collected, recorded, analyzed and
compared for changes in blood pressure, body weight, serum glucose and lipids, and urine
glucose and ketones at initial diagnosis of OSA, before and after CPAP treatment. Data from
volunteers without diagnosis of OSA were analyzed and used for sensitivity and specificity
determination.
Measurements: The questionnaire survey assessment tool was divided into three sections:
socio-demographic factors, anthropometric measures and biochemistry. The questionnaire
gathered information on demographics such as age, gender, and educational background; risk
factors of chronic diseases such as smoking, alcohol intake, diet and physical exercise;
prevalence of chronic diseases including hypertension, diabetes mellitus, and dyslipidemia.
The anthropometric measures evaluated height, body weight as measured in the upright
position to the nearest 0.5cm and 0.1kg respectively. Volunteers underwent measurement of
neck or waist circumference taken at specified times throughout the study. Blood pressure for
each subject was taken in the sitting position after 30 minutes of rest and will recorded in their
medical chart three times a month for the duration of the study. Subjects were asked to refrain
from smoking, or ingesting alcohol and caffeine containing products a day before all BP
measurements. Three readings each of systolic and diastolic blood pressures were recorded
with an interval of five minutes at the least and the mean of each measure will be used for the
data analysis.
Biochemical analysis: Sampling of easily accessible bodily fluids before and during CPAP
treatment collected by ACCESS LABS-Jupiter FL, for biochemical analysis.
EPSS in patients with known OSA compared to all others
1. There was greater correlative variation neck circumference with systolic and diastolic
pressures in the general pool of patients compared to patients with primary diagnosis
of OSA .
2. Patients with primary diagnosis of OSA had a BMI greater than 27.53; however the
BMI of OSA patients did not correlate with high BP.
3. Epworth Sleepiness Scale (EPSS) is not a good predictive of OSA in these patients .
4. Serum glucose, HDL and triglyceride levels were not reliable markers for predicting
effectiveness of CPAP treatment
5. Levels of DHEA, afternoon cortisol and 17-OH progesterone in saliva of patients
diagnosed with OSA were significantly lower when compared to the normal reference
ranges for each marker
Serum glucose, HDL and triglycerides in OSA patients
DHEA, afternoon cortisol and 17-OH progesterone in
OSA patients
0
20
40
60
80
100
120
140
160
180
200
Systolic
Diastolic
Neck Size (cm)
Arbitraryunits
Arbitrary units
Relative values of BP vr neck circumference in patients diagnosed with OSA
0
20
40
60
80
100
120
140
160
180
200
Systolic
Diastolic
Neck Size (cm)
Arbitraryunits
Arbitrary units
Relative values of BP vrs neck circumference in all patients
0
20
40
60
80
100
120
140
160
180
200
Systolic
Diastolic
BMI
Arbitraryunits
Arbitrary units
BP vs BMI Primay OSA
0
20
40
60
80
100
120
140
160
180
200
Systolic
Diastolic
BMI
Arbitraryunits
Arbitrary units
BP vs BMI general participants
# of patients
EPSSscore
1. Lam, D.C., K.S. Lam, and M.S. Ip, Obstructive sleep apnoea, insulin resistance and adipocytokines. Clin Endocrinol (Oxf), 2014.
2. Kim, N.H., et al., Association of obstructive sleep apnea and glucose metabolism in subjects with or without obesity. Diabetes Care, 2013. 36(12): p. 3909-
15.
3. American Diabetes, A., Economic costs of diabetes in the U.S. In 2007. Diabetes Care, 2008. 31(3): p. 596-615.
4. American Diabetes, A., Economic costs of diabetes in the U.S. in 2012. Diabetes Care, 2013. 36(4): p. 1033-46.
5. Herman, W.H., The economic costs of diabetes: is it time for a new treatment paradigm? Diabetes Care, 2013. 36(4): p. 775-6.
6. Lin, Q.C., et al., Obstructive sleep apnea syndrome is associated with metabolic syndrome and inflammation. Eur Arch Otorhinolaryngol, 2014. 271(4): p.
825-31.
7. Gami, A.S., S.M. Caples, and V.K. Somers, Obesity and obstructive sleep apnea. Endocrinol Metab Clin North Am, 2003. 32(4): p. 869-94.
8. Tassone, F., et al., Obstructive sleep apnoea syndrome impairs insulin sensitivity independently of anthropometric variables. Clin Endocrinol (Oxf), 2003.
59(3): p. 374-9.
9. Kubota, N., et al., Dynamic functional relay between insulin receptor substrate 1 and 2 in hepatic insulin signaling during fasting and feeding. Cell Metab,
2008. 8(1): p. 49-64.