In-home evaluation of efficacy and titration of a mandibular advancement device for obstructive sleep apnea

There is increasing evidence that mandibular advancement devices (MADs) can be an effective treatment for some patients with obstructive sleep apnea, a highly prevalent chronic disease. In this study, the objectives were to objectively assess the effectiveness of MAD therapy using a limited channel recorder, and to develop a model for identifying patients who may be appropriate for MAD therapy as the initial treatment option. Thirty patients were prospectively recruited and studied at two independent dentist offices and the participants’ homes. Subjects wore the ARES Unicorder for two nights before insertion of the MAD, and again when the dentist determined that the patient had reached the titration endpoint. Self-reported measures of depression, sleepiness, and quality of life were obtained pre- and posttreatment. The reviewer was blinded to the study status while the physiological signals were being visually inspected. Significant reductions in the apnea/hypopnea index (AHI), hypoxemia measures, and snoring level were observed posttreatment. Twenty-seven of the 30 (90%) patients had a posttreatment AHI (using a 4% desaturation for hypopneas) below a clinical cut-off of 10. All but one patient (97%) exhibited at least a 50% decrease in AHI or had a posttreatment AHI ≤ 10. Significant differences in body mass index, weight, and neck circumference in patients with posttreatment AHIs above and below a clinical cut-off of five were identified. The linear regression used to predict the posttreatment AHI using pretreatment data resulted in an R2 of 0.68. The model correctly predicted two patients who were unable to obtain a posttreatment AHI of 10 or less. This study was designed to demonstrate two models of collaboration between a dental sleep medicine specialist and a sleep medicine physician in the monitoring of a patient treated with a MAD. The outcome data suggest that the limited channel recording system can be used as an alternative to laboratory polysomnography to reduce the cost of MAD treatment, and to improve the quality and consistency of posttreatment patient care.
Introduction
Obstructive sleep apnea (OSA) is the most common disorder observed in the practice of sleep medicine and is responsible for more mortality and morbidity than any other sleep disorder [1]. Although characterized over 40 years ago [2, 3], OSA has only recently gained recognition as one of the world’s most prevalent, underdiagnosed disorders [4, 5]. Due to associated morbidity, OSA has been identified as a major public health concern [6]. The disorder is characterized by frequent loud snoring and recurrent failures to breathe adequately during sleep (termed apneas or hypopneas), usually as a result of collapse of the upper airway.
Mandibular advancement devices (MADs) are being increasingly recognized as a treatment alternative to continuous positive airway pressure (CPAP), particularly for patients with mild to moderate OSA [7–12]. MADs are designed to protrude the mandible and thus the tongue and epiglottis during sleep, preventing airway occlusion [13]. Comparisons of MAD to CPAP have revealed that although MADs are less efficacious than CPAP in reducing the RDI they are, on average, used more frequently, preferred by more patients and more readily accepted than CPAP [14]. Recent studies demonstrated that both MADs and CPAP can reduce the 24-h diastolic blood pressure by an average of 3 mmHg after 4 weeks of treatment [15–17]. Similarly to CPAP, self-reported improvements in quality of life and decrease in sleepiness are reported in the majority of patients [14].
The primary goal of this study was to use a self-applied limited channel recorder to objectively assess the effectiveness of MAD therapy when the dentist determined the patient had reached the titration endpoint. A second goal was to determine factors which might predict successful treatment outcomes and provide a more refined method for identifying patients who may be appropriate for MAD therapy as the initial treatment option. Finally, we wanted to demonstrate two potential models of collaboration between the dentist and sleep medicine physician in monitoring MAD treatment outcomes.
Materials and methods
Eleven females and 19 males were recruited from two dental practices before treatment with an oral appliance and enrolled in the study. Twenty-five of the patients had failed CPAP therapy. After obtaining an informed consent (approved by the BioMed IRB, San Diego, CA, USA) patients completed a two-night pretreatment in-home study with the Apnea Risk Evaluation System (ARES TM) Unicorder  TM (Advanced Brain Monitoring, Carlsbad, CA, USA). This pretreatment recording was conducted between the time the dental impressions were taken and when the TAP II Mandibular Advancement Device (MAD) (Airway Management, Dallas, TX, USA) was fabricated and ready for insertion.
The TAP is a custom-made oral appliance with separate upper and lower appliances joined by a titration or advancement mechanism on the upper and a transverse bar or socket on the lower. The titration mechanism uses a hook to engage the bar or socket on the lower once each device is placed in the mouth. A jackscrew controls the position of the hook and thus the amount of protrusion. The patient can self-titrate the device using a removable hex key which engages the screw.
On the day of insertion of the MAD, patients completed the Beck depression index, Epworth sleepiness scale, and the Flemons’ quality of life questionnaire. At the insertion appointment, both study sites attempted to achieve a starting MAD titration position whereby the patient could just hook the lower tray with the upper tray using active protrusion with both trays in place. In the rare occasion that this level of advancement was not tolerated by the patient, the starting protrusion was reduced. Patients were instructed to begin adjusting the MAD in one-half turn increments as soon as it was tolerable, until a cessation in snoring or the symptoms had resolved. As a result, the titration endpoint was determined by the dentist based on the patient’s self-report. At the follow-up appointment, which was typically scheduled 3 to 4 weeks subsequent to the MAD insertion, the assessment questionnaires were completed again and the ARES Unicorder study was repeated. Twenty-seven of the 30 patients reached their endpoint within 34 days. The other three patients completed their endpoint in 40, 61, and 75 days; the delay in reaching the endpoint was due to patient illness unrelated to this study.
In between the time that treatment was initiated and the titration endpoint, each patient maintained a daily journal that recorded the time the appliance was inserted each night, and the time it was removed in the morning.
The pre- and posttreatment studies were conducted with the ARES Unicorder. From a single site on the forehead, the wireless recorder measures oxygen saturation, pulse rate, airflow, respiratory effort, snoring levels, head movement, and head position [18] (Fig. 1). Reflectance oximetry is used to obtain the SpO2 and pulse rate signals. Respiratory effort is derived from the measurement of changes in forehead venous pressure acquired using a combination of photoplethysmography and changes in surface pressure of the forehead reflectance oximetry sensor. Airflow is obtained via a cannula and nasal pressure transducer. A calibrated acoustic microphone is used to acquire quantified snoring levels (dB). Actigraphy is used to measure head movement and derive head position. The recorder was designed to be affixed by the patient, and provide alerts during the study if poor quality airflow or SpO2 is detected so the device could be adjusted.
Fig. 1Patient wearing a unicorder
The description and validation of this device in 284 valid comparisons of the in-laboratory simultaneous PSG and ARES and 187 valid comparisons of the in-laboratory PSG with a separate two nights unattended self-applied ARES Unicorder has been previously published [18]. Using a diagnostic AHI cutoff of >10, the concurrent in-lab comparison yielded a sensitivity of 97.4, a specificity of 85.6, a positive predictive value of 93.6, and a negative predictive value of 93.9. The in-home comparison sensitivity, specificity, positive predictive value, and negative predictive value were 91.5, 85.7, 91.5, and 85.7, respectively. The failure rate was 2%.
In an independent validation of 40 subjects (13 healthy controls and 27 patients with symptoms of EDS and/or snoring) using a clinical cut-off of 15, the sensitivity of the ARES compared to concurrent PSG was 100% (25/25 patients) and specificity 67% (10/15 subjects). The sensitivity for two-nights of ARES in-home compared to the PSG was 96%; specificity was 80%. The failure rate was 5% [19].
Automated scoring algorithms were applied off-line to detect sleep disordered breathing. The AHI was computed using a time-in-bed measure based on recording time with acceptable signal quality minus periods when the patient was upright or presumed to be awake based on actigraphy. Apneas, based on a 10-s cessation of airflow detected by the automated algorithms, were included in all apnea–hypopnea indexes (AHI). Hypopnea events required a 50% reduction and recovery in airflow and were further stratified based on the depth of desaturation. The AHI-4% criteria required a minimum 3.5% reduction in SpO2 and at least a 1.0% recovery. Hypopneas included in the AHI-3% and AHI-1% criteria required SpO2 desaturation and resaturation using stepped thresholds. For the AHI-3%, if the SpO2 at the point of maximum saturation before the event was greater than or equal to 95% then a 2.2% reduction and a 2.2% recovery in SpO2 was required. For maximum saturations of between 95–93% the required SpO2 change was a 2.5% reduction and 2.5% recovery; between 93–91% a 3.0% reduction and 2.7% recovery; between 91–88% a 3.5% reduction and 3.0% recovery; and below 88% a 4.0% reduction and 3.5% recovery. For the AHI-1%, if the point of maximum saturation before the event was greater than 93%, then a 1.0% reduction and 1.0% recovery was required; and for events with a starting SpO2 between 93–91%, a 1.2% reduction and 1.2% recovery was required. For an AHI-1% event to be called, the change in flow and desaturation needed to be associated with a behavioral arousal (i.e., an abrupt change in pulse rate, snoring sound or a head movement). After the automated scoring was applied, the full disclosure recordings were visually inspected by a sleep medicine physician to confirm the accuracy of the automated scoring, and to reclassify as central and/or exclude autodetected events if necessary. At the time of the review, the clinician was blinded to the study status (i.e., pre- or posttreatment). The physiological data, including AHI values, percent time with SpO2 below 90, 85, and 80%, and percentage time snoring greater than 30, 40, 50, and 60 dB were then calculated.
Responses to the Beck depression index and Flemons’ quality of life questionnaire were tallied in accordance with published methods [20, 21].
Paired t tests were used to identify significant changes in the pre- and posttreatment physiological data and questionnaire responses.
To identify anthropomorphic factors that may impact MAD treatment outcomes, patients were stratified into two groups. Group 1 included all patients with a posttreatment AHI-4% ≤ 5 (n = 18). The balance of patients with an AHI-4% > 5 were assigned to group 2 (n = 12). Paired t tests were used to identify significant group differences.
To develop and validate the prediction of the posttreatment AHI using pretreatment data, patients were paired and assigned into either the model development or cross validation group based on similarities in the pre- and post-4% AHI and 1% AHI. Correlation analysis was used to identify anthropomorphic variables and measures of obstructive breathing before treatment which might be useful in estimating the posttreatment 4% AHI (post-T 4%). Variables with significant correlations were then used in a linear regression to derive predicted posttreatment values (predict AHI).
Results
Overall effects of MAD treatment The mean ± SD and minimum pre- and posttreatment valid recording times were 9.6 ± 3.6 and 3.5 h; and 10.3 ± 2.4 and 4.6 h, respectively.Paired t tests revealed significant changes (p < 0.001) in all pre- vs posttreatment sleep disordered breathing measures, including: apnea–hypopnea index with a 4% (AHI-4%) and 1% (AHI-1%) desaturation (Fig. 2).
Fig. 2Mean + SE changes in pre- and posttreatment AHI-4% and AHI-1%A decrease in hypoxemia measures pre- and posttreatment were also observed including the percentage of time below 90% SpO2 (T% < 90%) (p < 0.05) and the mean percentage change in SpO2 across all AHI events (% Dip)(p < 0.001) (see Fig. 3).
Fig. 3Mean + SE changes in pre- and posttreatment percentage of time the SpO2 was <90%, and the percentage change in SpO2 resulting from sleep disordered breathingSignificant reduction in the average snoring levels at 30 and 40 dB across the valid recording time were also observed (p < 0.001) (Fig. 4).
Fig. 4Mean + SE changes in pre- and posttreatment snoring loudness above 30 and 40 dBBased on conventional outcome measures, the MAD therapy was highly efficacious. Twenty-seven of the 30 (90%) patients had a posttreatment AHI-4% < 10 (Fig. 5a). All but one patient (97%) exhibited at least a 50% decrease in AHI-4% or had a posttreatment AHI-4% ≤ 10.
Fig. 5Individual changes in pre- and posttreatment sleep disordered breathing using: a AHI-4% desaturation and b AHI-1% desaturationUsing an alternative measure of AHI-1% (used to identify residual sleep disordered breathing/upper airway resistance) 21 of the 30 patients (70%) had a posttreatment AHI-1% ≤ 15 (Fig. 5b). Eighty-seven percent (26 of 30) of the patients exhibited at least a 50% decrease in AHI-1% or had a posttreatment AHI-1% ≤ 15.Paired t tests applied to the pre- and posttreatment scores revealed statistically significant differences for Beck depression index, Flemons’ QOL, Epworth sleepiness score (all at the p ≤ 0.001 level) (Fig. 6). Seventy-six percent (23/30) of the patients showed a decrease in Epworth score; 60% had an Epworth score reduction of three or more. Seventy-three percent (22/30) of the patients reported a posttreatment reduction in depression; 53% had a Beck depression index score reduction of three or more. Eighty-seven percent of the patients reported an increase in the Flemons’ QOL index; 60% showed in improvement score of one or greater. All patients reported some level of subjective improvement on at least one of these subjective measures.
Fig. 6Pre- and posttreatment changes in Beck depression index, Epworth sleepiness scale, and Flemons’ quality of life indexThe correlation between the posttreatment percentage time snoring above 30 dB and the AHI-4% was computed because snoring is a principal measure used to assess the MAD titration endpoint. The results in Fig. 7 suggest that snoring is a good predictor of outcome when objectively measured.
Fig. 7Regression plot predicting posttreatment AHI-4% based on the posttreatment percentage of time the snoring loudness was above 30 dBDaily self-reported compliance for the MAD revealed that out of a total of 693 nights in bed recorded across all subjects, only 20 nights were reported as not wearing the MAD. The mean usage per night was 7.34 ± 1.3 h. Three of the 30 patients had incomplete paperwork due to either confusion on the part of the patient or problems in collecting the paperwork at the study sites. Although all three patients said that they had worn the MAD for the duration of the study, there was no written record available that allowed the investigators to assess compliance/usage.
Factors that affect treatment outcomes Analysis of variance was used to compare demographic and anthropomorphic measures of patients who had a posttreatment AHI-4% ≤ 5 and those who did not respond optimally to treatment (Table 1). Significant differences in the two groups were observed in the body mass index (p < 0.01), weight (p < 0.01), and neck circumference (p < 0.02).
Table 1Characteristics of group that was treated optimally and the group that was not treated optionally with a MAD (mean + SE) Treated optimally post-T AHI-4% < 5Did not treat optimally post-T AHI-4% > 5GenderFemales74Males118Age (years)48.3 + 2.550.9 + 3.4BMI (kg/m)**27.6 + 0.833.1 + 2.1Weight (kg)**84.4 + 3.0100.2 + 5.0Neck circumference (cm)*40.0 + 0.743.2 + 1.0*p < 0.05**p < 0.01
Prediction of successful treatment outcome Correlation analysis was applied to the entire data set (n = 30) identify pretreatment variables that had a significant relationship with the posttreatment AHI-4% (see Table 2).
Table 2Correlations between posttreatment AHI-4% and pretreatment measuresPearson r (p < 0.01)Pearson r (p < 0.05)Pretreatment 4% AHIr = 0.53Snoring >30 dBr = 0.44Pretreatment 3% AHIr = 0.44Neck circumferencer = 0.45Pretreatment 1% AHIr = 0.54Body mass indexr = 0.45Snoring >40 dBr = 0.52Weightr = 0.45% Time <90% SpO2r = 0.56Various combinations of variables were submitted to linear regression using the model development data set in an effort to predict the posttreatment AHI-4%. Limiting the number of variables to four (due to the small sample size), the variables AHI-4%, AHI-3%, AHI-1%, and percent time snoring >30 dB resulted in an R2 of 0.68. The coefficients derived from the linear regression were applied to the model development and cross-validation data sets.Twenty-seven of the 30 patients had predict-AHI suggesting a successful outcome would be attained using a clinical cutoff post-T 4% AHI ≤ 10 (Fig. 8). Two of the three patients were accurately predicted as unable to achieve a post-T AHI≤10. The Bland–Altman plots comparing the predicted-AHI and posttreatment AHI (Fig. 9) suggest a reasonable fit of the data given the small sample size used for the model development and cross validation data sets.
Fig. 8Comparison of pretreatment, posttreatment, and predicted posttreatment AHI-4% for a the model development, and b the cross validation groupsFig. 9Bland–Altman plot of the difference between the predicted posttreatment AHI-4% vs the actual posttreatment AHI for a the model development and b the cross validation groups
Discussion
Consecutive patients who were referred to the dentist for a MAD were provided the opportunity to enroll in the study. The only exclusion criteria applied were ages less than 18 or older than 70 years. The inclusion of 25 subjects who had previously failed CPAP therapy contributed to the wide OSA severity range: nine of the subjects (30%) were considered to have severe OSA (i.e., AHI-4% ≥ 30) and an additional 30% were considered to have moderate OSA (AHI-4%>15 and <30). Seventy-seven percent of the patients (23/30) had at AHI-1%>25, a clinical cut-off which was considered at least moderate.
In this study, a treatment efficacy rate for the MAD was 90% using an AHI-4% clinical cut-off of 10, and 97% when a 50% reduction in AHI was included in determining a successful outcome. Eighty-seven percent of the patients showed improvement using an AHI-1% with a clinical cut-off of 15 or a 50% reduction in AHI. Eighty percent of the patients (24/30) had a posttreatment AHI-1% ≤ 16.
A recent evidence-based review summarized results from 87 published studies (over 2,000 patients evaluated) including 15 Sackett Level I and Level II randomized controlled trials [14]. Using a definition of treatment success that required achieving a posttreatment respiratory disturbance index below 10, success was achieved on average across all studies for 52% of patients treated with oral appliances. When the more liberal criteria of a 50% reduction in RDI were applied to assess outcome, 65% of patients were shown to have a positive result with MAD.
In an attempt to compare these previous finding to this data set, a clinical cut-off of 10 was applied to the AHI-1%. The differences between the AHI-1% and RDI include a 50% reduction in flow vs 30%; a 1% desaturation vs no desaturation; arousal indicators based on changes in snoring, pulse rate, and head movement vs cortical arousals; and the use of time-in-bed vs total-sleep-time. Using this alternative clinical cut-off, 33% of the patients had a successful outcome. When a 50% reduction in AHI-1% was included, 77% had a successful outcome. Results are more consistent with the previous research.
The findings in this study were consistent with previous reports which found self-reported improvements in quality of life and decrease in sleepiness in the majority of patients [14]. No effort was made in this study to obtain objective measures of improvement. To date, only four studies have utilized objective measures of alertness or neurocognitive function to assess treatment outcomes with MAD therapy, with mixed results [22–25]. Further investigations need to be conducted to assess the effectiveness of MAD therapy in ameliorating cognitive impairments in OSA.
The strong correlation (r = 0.63) between posttreatment % time snoring >30 dB and the posttreatment AHI-4% suggests that the current clinical practice of relying on residual snoring to asses MAD titration is valid. It is interesting to note that there was no apparent correlation between snoring levels and pretreatment AHI values. Given the discrepancy between the self-reported and objectively measured snoring at the titration endpoint, it appears that the bed-partner or patient’s observation may not provide the most accurate means for titrating a MAD.
Several studies have reported increased efficacy for MADs in patients with supine positional OSA [7, 26]; however, the association has not been widely confirmed. This is due in part to the fact that the majority of studies on MAD therapy do not report the number of abnormal respiratory events by sleep position despite the recommendation of the ASDA Practice Parameters for separate calculations of supine and lateral RDIs [27, 28]. Supine positionality did not appear to influence the treatment outcome in our study, possibly, because there were so few MAD treatment failures. This may be a result of the appliance which was used or that the small sample size was not representative of the population treated with oral appliances.
A recent evidence-based review reported that median MAD treatment compliance across patients was 77% after 1 year [14]. In this study, compliance was only monitored during the titration period which may have contributed to the favorable finding (i.e., 97%). Other factors that may have influenced this outcome were a relatively small sample size and/or patient compensation being provided. Given that 80% of the study participants were CPAP failures, the influence of prior CPAP use on MAD compliance should be explored. While an objective measure of MAD compliance would eliminate potential bias contributed by self-reported use, practical methods are not currently available.
The suggested decrease in MAD efficacy with increasing body mass index (BMI) was confirmed [27, 28]. Weight and neck circumference also appeared to influence the posttreatment apnea/hypopnea index. These variables make sense: the upper airway tends to be narrower in patients with more fatty tissue around the neck and the additional mass combines with gravity to contribute to greater collapsibility when sleeping supine.
The successful treatment outcome of patients with severe sleep apnea suggests that a more quantitative approach should be investigated to identify candidates appropriate for a MAD therapy. The results from the predictive model, once fully validated, could provide the guidance needed for sleep medicine physicians to recommend an oral appliance as an initial treatment option for more severe patients. Alternatively, substantial differences between the predicted and actual posttreatment AHI could help dentists determine when a patient has not been fully titrated.
Given the small sample size of the model development data set (n = 15), only four variables were included in the regression model even though the correlations presented in Table 2 suggested additional variables would be predictive. It is expected that the error between the predicted and actual posttreatment AHI can be reduced with larger data sets. In addition to expanding the database used for the predictive model, future investigations should be conducted to determine if the accuracy of the predictive model is influenced by the type of MAD.
Dentists represent an important access point for identifying and treating patients with undiagnosed OSA. This study was designed to demonstrate two models of collaboration between a dental sleep medicine specialist and a sleep medicine physician. As recommended by the AASM, only patients with mild to moderate OSA were offered MAD therapy as the initial treatment choice in this study. Patients with severe sleep apnea were enrolled only after failure of CPAP therapy. In one model, the dentist referred the patient to the sleep medicine physician and his staff to obtain and review the pre- and posttreatment physiological data. In the second model, the dentist acquired the data and transmitted it to the sleep medicine physician for review. In both models, the physical and history was made available to the physician for interpretation of the data [29].
A follow-up PSG is generally not affordable in cases where it is not covered by an insurance company or health ministry; sleep centers do not tend to offer less expensive level III studies as an alternative. This creates a situation whereby treatment outcomes are simply not assessed, or the dentist conducts the study independently, without the assistance or oversight of the sleep medicine professional. Left on their own, many dentists rely upon oximetry and other level IV devices to monitor treatment outcomes, in part because of their limited experience in interpreting the more sophisticated signals obtained by level III devices. Although several level III devices have automated scoring algorithms, the physiological data should still be reviewed by a trained professional. In two patients, the review of the full disclosure recording allowed recognition of complex sleep apnea (i.e., central sleep apnea was revealed posttreatment after the obstructive breathing was resolved) suggesting the importance of having an experienced professional review the data. This study suggests an alternative approach for assessing MAD treatment outcomes that is based on a collaborative relationship between dentists and sleep medicine physician using a limited channel recording system.

mandibular advancement device
sleep apnea
sleep disordered breathing
home monitoring
outcome assessment


Patients with type 2 diabetes have normal mitochondrial function in skeletal muscle

Aims/hypothesis Insulin resistance and type 2 diabetes are associated with mitochondrial dysfunction. The aim of the present study was to test the hypothesis that oxidative phosphorylation and electron transport capacity are diminished in the skeletal muscle of type 2 diabetic subjects, as a result of a reduction in the mitochondrial content.
Introduction
It has been reported that insulin resistance is associated with mitochondrial dysfunction in several tissues. While mitochondria are considered central to altered metabolic pathways, leading to pathogenic processes in type 2 diabetes, the mechanisms by which mitochondrial function contributes to the disease remain to be elucidated. Whether it is insulin resistance per se, chronic hyperglycaemia, or accumulation of intracellular lipid and associated alterations in metabolic pathways that affect mitochondrial function, or vice versa, is also unclear.
In skeletal muscle, evidence for reduced oxidative capacity in type 2 diabetes has been provided by findings of reduced oxidative enzyme levels [1–4] and mismatches between glycolytic and oxidative enzyme activities [3, 5]. The activities of rotenone-sensitive NADH:O2 oxidoreductase and citrate synthase have been shown to be reduced by 40% in the skeletal muscle of type 2 diabetic patients, and transmission electron microscopy has revealed that these mitochondria have a reduced size and an altered morphology [1, 6]. A decrease in the expression of genes involved in oxidative phosphorylation has also been reported in muscle of type 2 diabetic patients [7, 8] and men on a high-fat diet [9]. It has been stated that impaired muscle mitochondrial function is linked to excess intramuscular lipid accumulation and reduced fatty acid oxidation defined by rates of oxidative phosphorylation and ratios of inorganic phosphate:phosphocreatine determined by magnetic resonance studies [6]. These studies suggest mitochondrial dysfunction in type 2 diabetes; however, to date, no direct measurements of mitochondrial O2 flux capacity in intact cells in human type 2 diabetes have been reported. We hypothesised that oxidative phosphorylation and electron transport capacity are diminished in the skeletal muscle of type 2 diabetic subjects, and that these changes are attributable to a reduction in muscle mitochondrial content. In the present study we tested these hypotheses by using high-resolution respirometry to quantify oxidative phosphorylation and electron transport capacity in permeabilised muscle fibres from biopsy samples of the quadriceps in healthy subjects and patients with type 2 diabetes.
Subjects and methods
Subjects Informed consent was obtained from all subjects. The study was conducted in accordance with the principles of the Declaration of Helsinki, and was approved by the local ethics committee for Frederiksberg and Copenhagen County. Mitochondrial respiration was measured in permeabilised skeletal muscle fibres obtained from needle biopsies of the vastus lateralis in men with (n = 11) or without (control; n = 8) type 2 diabetes. The characteristics of the subjects are provided in Table 1 and Fig. 1. All subjects were in good health but classified as living a typical Westernised sedentary lifestyle, participating only in routine activities of daily living (walking, gardening, etc.) and not engaged in regular structured or individualised aerobic or strength training programmes or athletics. None of the control subjects had a family history of diabetes and none was receiving treatment for a disease. The diabetic patients were treated for their diabetes with diet or oral glucose-lowering medicine. All medications were withheld 24 h prior to the experiment. The patients with type 2 diabetes had no clinical signs of long-term diabetic complications and were representative of patients treated in the primary care sector.
Table 1Characteristics of the subjects Type 2 diabetic subjects (n = 11)Control subjects (n = 8)Age (years)62 ± 258 ± 1Height (cm)177 ± 3179 ± 1BMI (kg/m2)32 ± 2*28 ± 1Time since diagnosis (years)5 ± 2–Fasting insulin (pmol/l)61 ± 9*34 ± 6Fasting glucose (mmol/l)9.0 ± 0.5*5.4 ± 0.1Complex I activity (nmol min−1 mg protein−1)50.8 ± 6.058.3 ± 4.7 Citrate synthase activity (pmol mg−1 s−1)1.6 ± 0.12.0 ± 0.2mtDNA (copies/μg tissue) ×103119 ± 7*147 ± 12mtDNA/genomic DNA2,773 ± 2523,030 ± 185Data are means±SEM. *p < 0.05 vs control subjectsFig. 1Glucose (a) and insulin (b) concentrations in venous plasma before (t = 0 min) and during an OGTT. The patients with type 2 diabetes had higher fasting glucose levels and were severely insulin resistant compared with healthy control subjects (*p < 0.05). Black and white symbols represent healthy control subjects and patients with type 2 diabetes, respectivelySubjects were fasted overnight prior to the experiment. A catheter was inserted into an antecubital vein for blood sampling. After local anaesthesia of the skin and the subcutis, a muscle biopsy was taken (Tru-Core; PBN-Medicals, Stenløse, Denmark) and then a 120-min OGTT (75 g glucose dissolved in 300 ml of water) was performed. At t = 30 min, a second muscle biopsy was taken.A portion of the obtained muscle tissue was frozen immediately in liquid nitrogen and stored at −80°C for later analysis (see below), and a smaller piece (2–6 mg) was placed onto a Petri dish on ice with 1 ml of relaxing solution containing Ca2+/EGTA buffer (10 mmol/l), free calcium (0.1 μmol/l), imidazole (20 mmol/l), K+/4-morpholinoethanesulfonic acid (MES) (50 mmol/l), dithiothreitol (DTT; 0.5 mmol/l), MgCl2 (6.56 mmol/l), ATP (5.77 mmol/l), phosphocreatine (15 mmol/l), pH 7.1, and individual fibre bundles were separated with two pairs of sharp forceps, achieving a high degree of fibre separation. The fibre bundles were permeabilised for 30 min in 3 ml of ice-cold relaxing solution containing saponin (50 μg/ml) [10]. After rinsing in respiration medium (MiR05; Oroboros, Innsbruck, Austria) containing sucrose (110 mmol/l), potassium lactobionate (60 mmol/l), EGTA (0.5 mmol/l), MgCl2.6H2O (3 mmol/l), taurine (20 mmol/l), KH2PO4 (10 mmol/l), HEPES (20 mmol/l), sucrose (110 mmol/l), BSA (1 g/l), pH 7.1, the muscle bundles were blotted and measured for wet weight in a balance controlled for constant relative humidity, so that all biopsy samples were hydrated to the same degree. The muscle bundles were then immediately transferred into a respirometer (Oxygraph-2k; Oroboros) containing air-saturated respiration medium at 37°C.The Oxygraph-2k is a two-chamber titration-injection respirometer with a limit of oxygen flux detection of 1 pmol s−1 ml−1. The instrumentation allows for O2 flux measurements with only 0.04 mg of mitochondrial protein or 1.5 mg of muscle fibres (wet weight). Standardised instrumental and chemical calibrations were performed to correct for back-diffusion of O2 into the chamber from the various components, leak from the exterior, O2 consumption by the chemical medium, and sensor O2 consumption [11]. O2 flux was resolved by software capable of converting nonlinear changes in the negative time derivative of the oxygen concentration signal.
Analysis of muscle tissue Citrate synthase activity and complex I activity were measured spectrophotometrically at 37°C. Citrate synthase activity was determined as described previously [12], and complex I activity was assessed by measuring the oxidation of NADH (300 μmol/l) using ubiquinone 1 (100 μmol/l) as the acceptor. The complex I rotenone-sensitive activity was measured by the addition of rotenone (1 μmol/l). The protein content, needed to calculate the specific activity, was measured using a commercially available assay (BCA, Sigma Chemicals, St Louis, MO, USA). For measurement of mitochondrial DNA (mtDNA) content, DNA was isolated from muscle biopsy samples (∼10 mg) by proteinase K digestion at 55°C for 3 days. The 100-μl digestion mix contained 50 mU proteinase K (PCR grade, Roche, Basel, Switzerland), 20 mmol/l Tris-HCl (pH 8.4) and 50 mmol/l KCl. After incubation at 80°C for 45 min, the remains were spun down and the supernatant fraction diluted ×200 in triethanolamine titanate (TE) plus 1 ng/μl salmon sperm DNA (Sigma). 5 μl of this dilution was amplified in a 25 μl PCR reaction containing 1×Quantitect SYBR Green Master Mix (Qiagen, Hilden, Germany) and 100 nmol/l of each primer. The amplification was monitored real-time using the MX3000P Real-time PCR machine (Stratagene, La Jolla, CA, USA). The primers were designed to target genomic DNA (Forward: AGG TGC TGT CAG GAA GCA AGG A, Reverse: TAG GGG GAG GAG GGA ACA AGG A) or mtDNA (Forward: CCC CTG CCA TAA CCC AAT ACC A, Reverse: CCA GCA GCT AGG ACT GGG AGA GA). The threshold cycle (Ct) values were related to a standard curve made with the cloned PCR products.
Respirometry protocol All measurements of respiration were made in duplicate, simultaneously. Resting, routine respiration (state 2, absence of adenylates) was assessed by the addition of malate (1.5 mmol/l) and glutamate (19 mmol/l) as the complex I substrate supply, and then state 3 respiration was assessed by the addition of ADP (4.8 mmol/l). The addition of succinate (9.5 mmol/l) provided state 3 respiration with parallel electron input to complexes I and II. The integrity of the outer mitochondrial membrane was established by the addition of cytochrome c (19 μmol/l); no stimulation of respiration was observed. We examined ADP control of coupled respiration and uncoupling control through addition of the protonophore carbonylcyanide-4-(trifluoromethoxy)-phenylhydrazone (FCCP) (0.7 μmol/l). The addition of rotenone (0.1 μmol/l) resulted in inhibition of complex I for examination of O2 flux with complex II substrate alone, while antimycin A (12 μmol/l) was added to inhibit complex III to observe non-mitochondrial respiration with small contributions from electron leak in the uncoupled state. The concentrations of substrates and inhibitors used were based on prior experiments conducted for optimisation of the titration protocols.
Data analysis All values are given as means±SEM for all experiments, run in duplicate or triplicate. For all statistical evaluations, a p value of less than 0.05 was considered significant. Statistical analysis of differences in oxygen flux between healthy control subjects and patients with type 2 diabetes was carried out with a two-way ANOVA for repeated measures. In the case of a significant main effect and interaction between the variables, the Holm-Sidak method was used for post hoc analysis. All other comparisons between the two groups were performed using the unpaired Student’s t test. SigmaStat version 3.11 (Systat software, Richmond, CA, USA) was used in all analyses.
Results
The sequential addition of substrates to the muscle tissue, obtained from both groups before an OGTT, always (p < 0.05) resulted in a stepwise increase in state 3 O2 flux (Fig. 2). Notably, the addition of succinate (stimulating parallel electron input from complexes I+II) resulted in a marked increase in O2 flux in both groups. The O2 flux per muscle mass was significantly (p < 0.05) lower in the patients compared with the healthy subjects during complex I and complex I+II respiration (Fig. 2). Further increases in flux capacity and preserved significant differences between the groups were observed with uncoupling by FCCP (109 ± 8 vs 86 ± 4 pmol mg−1 s−1 in control and diabetic subjects, respectively; p < 0.05). Subsequent inhibition of complex I and III with rotenone and antimycin A blunted the O2 flux (Fig. 2). The addition of cytochrome c did not result in significant increases in O2 flux (data not shown).
Fig. 2O2 flux in permeabilised skeletal muscle fibres from patients with type 2 diabetes and healthy control subjects. Data are shown as O2 flux per mg of tissue (a) and further normalised to the number of copies of mtDNA per μg of tissue ×10,000 (b). When data are expressed relative to mtDNA, any difference between the groups disappears. Data are means±SEM (*p < 0.05). Black and white bars represent healthy control subjects and patients with type 2 diabetes, respectively
The number of copies of mtDNA and citrate synthase activity (Table 1) indicated a lower mitochondrial density in the patients with type 2 diabetes. The O2 flux data were therefore recalculated relative to mtDNA content (Fig. 2b) and citrate synthase activity (data not shown). All differences in O2 flux between patients with type 2 diabetes and healthy control subjects disappeared following either normalisation procedure (Fig. 2b).
The increase in O2 consumption when ADP was added (complex I respiratory control ratio [state 3:state 2 respiration]) was not different between healthy subjects and patients with type 2 diabetes (Fig. 3).
Fig. 3a Respiratory control ratio for complex I (NADH supply from substrates glutamate + malate) measured as the ratio of O2 flux with (state 3) and without (state 2) ADP. b Electron transport capacity measured as O2 flux after FCCP-induced uncoupling relative to coupled O2 flux at state 3 with malate + glutamate + ADP + succinate (parallel electron input into both complex I and II). No significant difference between the groups was noted. Data are means±SEM
Mitochondrial respiration may be influenced by the prevailing level of glucose and/or insulin. However, none of the O2 flux rates measured with different substrates and inhibitors displayed significant correlations with these parameters, or the changes seen during the OGTT (data not shown).
The glucose and insulin concentrations were markedly increased in both groups at 30 min into the OGTT (Fig. 1). However, the measured O2 flux in the muscle tissue obtained at this time point deviated to a lesser extent (mean +2.4 ± 3.5%) from the O2 flux measured in the biopsies obtained during fasting (data not shown).
The activity of complex I was affected by rotenone to a similar extent in the two groups (Table 1). Furthermore, the biochemically measured activity of complex I was significantly (p < 0.02) correlated with O2 flux measured by respirometry during rotenone inhibition (r2 = 0.37).
Discussion
The primary novel findings in this study are that: (1) ADP-stimulated state 3 mitochondrial O2 flux capacity with electron flux through either complex I or II, or with parallel electron input through both complexes I and II, is substantially reduced in type 2 diabetic patients when expressed per unit mass of skeletal muscle; and (2) when O2 flux is normalised for mitochondrial DNA content or citrate synthase activity, levels of both oxidative phosphorylation and electron transport capacity are similar to those observed in age-matched healthy control subjects. These results provide direct experimental evidence for normal function of muscle mitochondria in type 2 diabetes and do not support other investigations reporting mitochondrial dysfunction in diabetes. The reduced mitochondrial capacity per unit muscle mass observed in this study is consistent with the concept of reduced mitochondrial content and volume, oxidative enzyme levels, mtDNA and decreased levels of co-regulators of mitochondrial biogenesis-such as peroxisome proliferator-activated receptor-γ coactivator-1 (PGC-1), nuclear respiratory factor (NRF-1 and NRF-2) and mitochondrial transcription factor A (mtTFA)-in insulin-resistant states, as found in some [7, 8] but not all studies [13]. Therefore, it could be argued that specific cellular signals that alter levels of mitochondria, and thus reduce electron transport (and oxidative phosphorylation capacity) per unit muscle mass, contribute to a variety of aberrant metabolic pathways, including intracellular fat accumulation, insulin resistance and glucose intolerance.
The various substrate and inhibitor titrations employed in this study permitted an examination of various steps of oxidative phosphorylation and electron transport under resting respiration and maximally ADP-stimulated O2 flux by ADP (state 3). Both resting (state 2) and ADP-stimulated (state 3) coupled respiration were substantially reduced (18–28%) in diabetic subjects, as was uncoupled O2 flux with parallel electron supply from both NADH (complex I) and FADH2 (complex II). These responses indicate a blunting of oxidative phosphorylation linked to ATP synthase and a decreased maximal electron flux capacity in the uncoupled state induced by addition of FCCP, respectively. The key finding, however, is that these values are comparable with those in healthy control subjects when they are normalised for mtDNA content or citrate synthase activity, both of which are used as indices of mitochondrial density per unit muscle mass. The 30% reduction in state 3 O2 flux capacity per mg of muscle in diabetic subjects with parallel electron input (glutamate + malate + succinate) suggests an attenuation of cellular VO2max. While the prevailing view is that O2 delivery is a factor that influences whole-body maximal O2 consumption, it remains to be determined if, and to what extent, the observed decrement in muscle state 3 mitochondrial O2 flux capacity in diabetic patients contributes to the lower systemic VO2max and substrate utilisation.
The patients with type 2 diabetes were in a chronic hyperglycaemic state and were clearly insulin resistant, but even so, mitochondrial function/mtDNA was not impaired. Furthermore, mitochondrial function was also measured in the biopsy samples obtained 30 min into the OGTT, at a time when both glucose and insulin were markedly increased (Fig. 1). This acute metabolic perturbation did not have any significant effect on mitochondrial respiration in any of the subjects (data not shown).
It has been proposed that chronic hyperglycaemia associated with insulin resistance results in the alteration of several metabolic pathways [14]. A central hypothesis involving the mitochondria focuses on an effect of hyperglycaemia providing increased reducing equivalents to the electron transport chain, resulting in a higher membrane potential, with consequent flow of electrons between coenzyme Q and complex III, forming superoxides in the mitochondrial matrix. Excess superoxide production can induce damage to mitochondrial structures, including several electron transport complexes, the mitochondrial lipid bilayer and mtDNA. A role for excess superoxide production is supported by findings of reduced glutathione and metallothionein antioxidant defence systems in type 2 diabetic subjects [15]. The results of this study do not preclude these concepts, but rather suggest the possibility that many pathogenic pathways associated with mitochondrial function in cellular energetics may result from conditions leading to a reduced number of mitochondria, which in turn could place the existing mitochondria under stress with subsequent production of reactive O2 species, impaired metabolism of intracellular lipids, and glucose uptake.
It is well known that exercise training increases mitochondrial content in skeletal muscle [16–19], and recent work has provided evidence for increased levels of transcriptional regulators of mitochondrial biogenesis in response to exercise [20, 21]. In addition, physical training can play a significant role in the prevention of insulin resistance and type 2 diabetes [22–25]. Physical training also substantially improves skeletal muscle insulin sensitivity in patients with overt type 2 diabetes [26], and many cellular adaptations responsible for the effect of training on insulin sensitivity in skeletal muscle have been described [27–31]. The cellular and mitochondrial changes in response to exercise training occur in parallel. In obese insulin-resistant subjects, exercise training has been shown to increase the percentage of skeletal muscle fibre volume occupied by mitochondria [32]. Thus, the present data support the hypothesis that type 2 diabetes is, to a large extent, a lifestyle disease, with insufficient exercise-induced gene expression and a surplus of energy intake contributing to its pathogenesis. Accordingly, studies on the effects of ‘de-training’ have provided evidence of reduced mitochondrial content. After cessation of an endurance training program, citrate synthase and succinate dehydrogenase activities in human muscle have been shown to decline with a half-time of only 12–14 days [33]. Cytochrome c protein concentration in rat muscles declines with a half-life of only 7–8 days [34], and the activity in human muscles has a half-time of similar magnitude. These decreases in the activities of cytochrome c and succinate dehydrogenase do not exactly follow the detraining decline in VO2max [35]. Taken together, these studies support the notion that lack of physical activity lowers mitochondrial concentration. The independent influences of exercise training and detraining, hyperglycaemia, intramuscular lipid accumulation and obesity on mitochondrial function remain to be elucidated.
In this study, the ability of the mitochondria to respond with increased O2 consumption following the addition of ADP, represented by the respiratory control ratio, was preserved in the diabetic muscle (Fig. 3). Thus, this index of mitochondrial phosphorylation capacity and coupling of electron transport to phosphorylation indicates that the respiratory chain of the mitochondria in type 2 diabetic subjects functions in a similar manner to that in the mitochondria in control subjects. This view is supported by similar data reported 40 years ago, albeit mostly from patients with ‘juvenile diabetes’ [36]. Similarly, an increase (1.3–1.4 fold) in O2 flux was seen in response to uncoupling by FCCP (Fig. 3). The fact that the increase was similar in the two groups also testifies that electron transport capacity is not impaired in type 2 diabetes, and that the phosphorylation system (adenine nucleotide transporter, phosphate transporter and ATP synthase) exerts control over electron transport in patients and control subjects to the same degree.
In conclusion, the results of the present study provide the first direct evidence of normal mitochondrial function in the skeletal muscle of type 2 diabetic subjects. An apparent impairment of oxidative phosphorylation and electron transport capacity is fully accounted for by a diminished mitochondrial content in the diabetic muscle.