Cystic fibrosis (CF) is an autosomal recessive disorder caused by mutations in the gene encoding the CF transmembrane conductance regulator (CFTR), which affects 1 in 3419 white individuals and 1 in 12,163 nonwhite individuals (21). CFTR helps to maintain airway surface fluid depth through secretion of Cl−; the impairment in CFTR results in a depletion of the airway surface fluid. There are several mutations that result in CF, with the ΔF508 mutation being the most common (13). The ΔF508 mutation is a deletion of phenylalanine at amino acid 508, which causes defective trafficking of CFTR and results in the inability of CFTR to be inserted into the apical membrane of the cell (25).
Extravascular lung water has been estimated to be 3.6 mL·kg−1 in healthy individuals, and maintenance of extravascular lung water is important for proper gas diffusion to occur (37). The diffusing capacity of the lung is reduced in disease states such as CF where the lungs are dry, whereas if extravascular lung water increases, such as during rapid saline loading or in heart failure, the diffusing capacity of the lung is also reduced (28,30,39). Airway surface fluid depth is of vital importance in pulmonary defense and function by aiding in mucus clearance in the airways. In the alveoli, the maintenance of optimal airway surface fluid depth is also essential in gas diffusion across the respiratory membrane (12). Increases in surface fluid depth not only are mediated primarily by Cl− secretion by CFTR but also occur through Cl− secretion by Ca2+-dependent Cl− channels (5,8). Surface fluid depth is decreased primarily through Na+ reabsorption by the epithelial Na+ channel (ENaC) (9,11). Sodium is brought into the epithelial cell by ENaC where it is subsequently moved across the basolateral membrane by Na+/K+ ATPase into the interstitial space. Fluid follows through tight junctions and aquaporin channels where it is then cleared by the lymphatic system. Not only is Cl− secretion impaired in CF but also Na+ absorption via ENaC is dramatically increased because of the loss of CFTR-mediated ENaC inhibition, potentiating the decreased surface liquid volume seen in CF, as well as impairing mucociliary clearance, leading to airway obstruction, inflammation, recurrent infections, and decreasing the diffusing capacity of gases across the respiratory membrane (39).
Previous work has shown that exercise increases the diffusing capacity of gases in the lungs of both healthy individuals and those with CF (39). Individuals with CF demonstrated lower diffusing capacity of the lungs at rest and during exercise as compared with healthy individuals (39). Exercise can not only activate ENaC through the adrenergic pathway but also inhibit ENaC through the purinergic pathway, which is activated by turbulent air flow in the airways during exercise (1). Several functional polymorphisms in the gene encoding ENaC (SCNN1A) have been reported, including a common variant resulting in an alanine (A) to threonine (T) substitution at amino acid 663 in the C-terminus of the α-subunit. The more common variant (αA663) demonstrated lower channel activity as compared with the αT663 variant because of decreased ENaC expression (27,35). In humans, the αT663 variant has been associated with hypertension, suggesting its increased channel activity resulted in increased Na+ reabsorption in the kidneys (2). Genetic variation of SCNN1A has also previously been shown to influence the diffusing capacity of the lungs in response to β2-adrenergic stimulation (3). Healthy individuals with the αA663 ENaC variant demonstrated a greater increase in lung diffusing capacity in response to exercise as compared with those with at least one copy of the αT663 variant (3). In addition, in response to albuterol, an exogenous β2-receptor agonist, individuals with the αA663 ENaC variant had less Na+ in their exhaled breath condensate 90 min after β2-agonist administration as compared with those with the αT663 ENaC variant, suggesting a greater removal of Na+ from the airways after activation (14).
In this study, we sought to determine the influence of genetic variation at amino acid 663 of the α-subunit of ENaC on diffusing capacity of the lungs at rest and during exercise in patients with CF. Exercise was used as a means to endogenously alter ion and fluid regulation in the lung. We predicted that patients with the αT663 ENaC variant, which has shown greater basal activity in previous work (27,35), would show a greater increase in diffusing capacity with exercise, because of a larger attenuation of Na+ reabsorption, and subsequent hydration of the airways.
Eighteen subjects with mild to moderate CF, with a positive sweat test (≥60 mmol·L−1) and at least one ΔF508 allele, were recruited for study through the Arizona Respiratory Center and its affiliated CF clinic at the University of Arizona Medical Center. To ensure subjects were clinically stable to participate in the study, exclusion criteria included the following: forced expiratory volume in 1 s (FEV1) ≤40% predicted, experimental CF drugs, pulmonary exacerbation within the last 6 months resulting in ≥50 mL of blood in the sputum, antibiotics for pulmonary exacerbation, pregnancy, smoking, inability to exercise, or cardiovascular abnormalities. The protocol was reviewed and approved by the University of Arizona Institutional Review Board, and all subjects provided written informed consent before participation in the study. All aspects of the study were performed according to the Declaration of Helsinki.
Upon arrival to the laboratory in a 2-h fasted state, subjects were consented and a buccal swab was performed for assessment of the amino acid at position 663 of αENaC and verification of ΔF508 mutation on CFTR. A venous blood sample was drawn for the assessment of hemoglobin concentration. Subjects were outfitted with a 12-lead ECG (Marquette Electronics, Milwaukee, WI) to monitor heart rhythms, and pulmonary function tests were completed according to the American Thoracic Society standards (23). Predicted values for pulmonary function tests were calculated according to equations from National Health and Nutrition Examination Survey III (17). Baseline simultaneous measurements of the diffusing capacity of the lungs for carbon monoxide (DLCO) and the diffusing capacity of the lungs for nitric oxide (DLNO) were taken in triplicate. Baseline peripheral oxygen saturation (SaO2) was assessed via pulse oximetry with a finger sensor (N-600 Pulse Oximeter; Nellcor, Boulder, CO). Subjects then completed a subject-specific maximal exercise capacity test on a cycle ergometer (Corival Lode B.V., The Netherlands) based on their body size, reported type, speed and intensity of exercise training, and predicted oxygen consumption (V˙O2) (18). DLCO and DLNO were taken during each stage of exercise and recovery. Subjects exercised at an initial workload that ranged from 15 to 40 W (mean initial workload was 24 ± 6 W), and the workload was increased by this same amount every 3 min until exhaustion (i.e., initial workload of 25 W with a 25-W increase in workload every 3 min). The exercise test ended with a 3-min recovery period at the initial workload. Exhaustion was determined by an inability to maintain a pedal rate of 60–80 rpm, an RPE of at least 18 of 20, or an RER greater than or equal to 1.15.
V˙O2, carbon dioxide production, respiratory rate (RR), tidal volume (VT), minute ventilation (V˙E), HR, and oxygen saturation (SaO2) were monitored continuously and averaged every 3 s throughout the test via a metabolic cart (Medical Graphics CPX/D, St. Paul, MN) interfaced with a PerkinElmer MGA-1100 mass spectrometer (PerkinElmer, Wesley, MA) as described previously (30,31). Accurate SaO2 values were ensured by instructing the subjects to maintain a relaxed grip and verifying that there were no discrepancies in HR between the pulse oximeter HR and that on the ECG.
Measurement of cardiac output, alveolar–capillary membrane conductance, and pulmonary capillary blood volume.
Cardiac output, pulmonary capillary blood volume (VC), and alveolar–capillary membrane conductance (DM) were determined using a rebreathe technique by measuring the disappearance of acetylene, carbon monoxide (CO), and nitric oxide (NO) with respect to helium, as previously described (16,30–33). Triplicate maneuvers of cardiac output (Q˙), DLCO, and DLNO were performed at baseline and during recovery. Single maneuvers of Q, DLCO, and DLNO were performed during each stage of exercise.
Measures of Q˙, DLCO, and DLNO were taken in an upright and seated position on the cycle ergometer using a rebreathing technique, with gases sampled by a PerkinElmer MGA-1100 mass spectrometer and Sievers Instruments NO analyzer (Sievers Instruments, Boulder, CO) integrated with custom analysis software, as described previously (29,31,38,39). Subjects breathed into a 5-L rebreathing bag containing 9% helium, 0.7% acetylene, 0.3% carbon monoxide (C18O), 40-ppm NO, and 35% O2 with an RR controlled at 32 breaths per minute via metronome. The 40-ppm NO was diluted in the anesthesia bag immediately before each maneuver from an 800-ppm NO tank. C18O was used instead of the more common C16O to enable the mass spectrometer to distinguish between C16O and N2, which have similar molecular weights. The total volume of gas used in the rebreathing maneuver was standardized at 1575 mL at rest and was based off of the tidal volume of the subject during exercise. Consistent bag volumes were ensured using a timed switching circuit, which resulted in the desired volume, given a constant rate of flow from the tank. The switching circuit and tank were calibrated for accurate volumes before each test. At the end of a normal expiration (end-expiratory lung volume), subjects were switched into the rebreathing bag and breathed the test gas for 8 to 10 breaths. After each maneuver, the rebreathing bag was completely emptied via vacuum and refilled immediately before the next maneuver.
Custom software was used to calculate the rate of disappearance of the gases with each breath calculated from the slope of the exponential disappearance for each gas with respect to helium (31). Membrane conductance and binding of carbon monoxide to hemoglobin contribute to the diffusion capacity of the lungs for carbon monoxide (33). Unlike DLCO, DLNO is based primarily on membrane conductance (DMNO) because nitric oxide is scavenged 280 times faster by hemoglobin than carbon monoxide, causing the uptake of NO to be instantaneous (DLNO ≈ DMNO). Therefore, DLNO is considered a direct measure of membrane conductance because the diffusion resistance of the blood is insignificant (19,20,26,33). DMNO was then used to calculate the DM for carbon monoxide (DMCO) by correcting for their different diffusion constants on the basis of molecular weight and solubility as described previously (19,20,26,33). The correction factor based on molecular weight and solubility is 1.93 (16); however, this correction factor is too low to produce values of VC that are physiologically plausible. Correction factors used in previous work have been as high as 2.49 (24,33,36,41). More recently, Ceridon et al. (6) demonstrated that a correction factor of 2.11 is most appropriate during exercise by comparing the DLNO with the more traditional DLCO to calculate DM and VC using DLCO at multiple oxygen tensions. Because this study used exercise, we have used 2.11 as the correction factor. VC was then calculated from the DLCO measured by subtracting the resistance to diffusion associated with alveolar–capillary barrier (DMCO). Finally, we corrected for individual differences in the rate of gas uptake and binding to hemoglobin because of each individual’s hemoglobin concentration and alveolar partial pressure of oxygen.
Assessment of hemoglobin.
Hemoglobin concentration was assessed at the University of Arizona Medical Center Pathology Laboratory using a cyanide-free hemoglobin method on an ADVIA 2120 Hematology system (Siemens, Munich, Germany). The subject’s hemoglobin concentration (assessed from the baseline blood draw) was used in the calculation of VC, as described previously.
SCNN1A genotyping and subject grouping.
The inside of each cheek of the subject was swabbed, and the swabs were immediately placed in a stabilizing buffer for storage purposes. SCNN1A was genotyped, and the αENaC amino acid at position 663 encoded by each SCNN1A allele was determined at the University of Arizona Genetics Core Laboratory using a TaqMan SNP assay for rs#2228576. Briefly, initial DNA quantitation and quality control were performed using PicoGreen (Life Technologies, Carlsbad, CA). Prevalidated primers and probe sets for TaqMan Allelic Discrimination Assay were obtained from Life Technologies. Reactions were run at 10 μL, containing TaqMan Universal PCR Master Mix, No AmpEraseR UNG (Life Technologies), 10 ng total DNA, and 1X Assay Mix. All samples were processed and analyzed on 7900 Real-Time PCR System (Life Technologies) with cycling conditions (95°C for 10 min, 50 cycles of 92°C for 15 s, and 60°C for 1 min) and Genotyper software (SDS system, version 2.3; Applied Biosystems, Carlsbad, CA). Subjects were then grouped according the amino acid at position 663 of αENaC. Individuals homozygous for SCNN1A alleles encoding alanine at amino acid 663 were grouped in the AA genotype, and individuals with at least one SCNN1A allele encoding threonine at amino acid 663 of αENaC were grouped into the AT/TT genotype, because only one subject was homozygous for threonine at amino acid 663.
The SPSS statistical software package (v.19; SPSS, Inc., Chicago, IL) was used for all statistical analyses. After confirming equality of variance with a Levene test, a one-sided independent samples t-test was used to determine significance between genotype groups at rest and peak exercise, to determine significance between genotype groups in percentage change from rest to peak exercise and also to determine significance from rest to peak exercise within genotype groups. Using Bonferroni correction, an α level of 0.025 or lower was used for determining statistical significance. All data are presented as mean ± SD unless stated otherwise.
Eighteen individuals with CF participated in the study (subject demographics, Table 1). Ten subjects were homozygous for alleles resulting in an alanine at amino acid 663 (AA genotype group), and eight subjects had at least one allele resulting in a threonine (AT/TT genotype group) at amino acid 663. Only one subject was homozygous for threonine at amino acid 663 and that subject was included in the AT/TT group. There were no differences in age, height, or FEV1 over forced vital capacity (FVC) between genotype groups. Weight, body mass index (BMI), FVC, and FEV1 were significantly lower in the AT/TT genotype group than that in the AA genotype group (Table 1).
Table 2 depicts the cardiopulmonary measures taken at rest and during peak exercise. No differences were seen in cardiopulmonary parameters at rest or in response to peak exercise between the AA and AT/TT groups (Table 2). Both groups reached similar peak workloads, and similar significant increases in HR, cardiac output, systolic blood pressure, V˙O2, RR, and minute ventilation in response to peak exercise were seen in both groups (Table 2).
No significant differences were seen in absolute lung diffusion measures at rest or during peak exercise, although at rest, the AA group tended to have higher DM and DLNO/alveolar volume (VA) than the AT/TT group (Table 3). The AA group demonstrated an attenuated percentage increase in DLNO, DM, and DLNO/VA from rest to peak compared with the AT/TT group (% increase: DLNO = 17.8 ± 3.5 vs 40.6 ± 13.4; DLNO/VA = 13.8 ± 6.8 vs 39.7 ± 13.0; DM = 14.6 ± 3.5 vs 40.7 ± 13.4, AA vs AT/TT, P < 0.025 for DM, Figs. 1A–C). In addition, the AA group had a larger percentage increase in VC with exercise than the AT/TT group (% increase: 87.2 ± 17.2 vs 44.9 ± 16.2, AA vs AT/TT, Fig. 1D).
In the present study, we demonstrate that genetic variation of SCNN1A manifested by changes at amino acid 663 is associated with differences in diffusing capacity of the lung in response to peak exercise in individuals with CF. Similar to previous studies, we have demonstrated an increase in both DLCO and DLNO with exercise in both groups (19,33,38,39). Individuals with at least one allele resulting in a threonine at amino acid 663 (AT/TT group) demonstrated a significantly greater percentage increase from rest to peak exercise in DLNO, DM, and DLNO/VA than individuals homozygous for alleles encoding the alanine variant. The AA group had a significantly greater percentage increase from rest to peak exercise in VC. Interestingly, individuals in the AT/TT group had a significantly lower body weight, BMI, and baseline pulmonary function (FVC, FEV1, and forced expiratory flow at 50% of FVC percent predicted). The lower resting pulmonary function in the AT/TT group may be due to the more functional ENaC resulting in a drier lung at rest, which could reduce mucus clearance and result in the lower pulmonary function seen in the AT/TT group.
During exercise, the surface area for diffusion increases because of airway and capillary recruitment, and VC tends to drive the increase in DLCO and DLNO because of increases in cardiac output and ventilation. Individuals in the AT/TT group demonstrated a significantly greater percentage increase from rest to peak exercise in DLNO, DM, and DLNO/VA, bringing the AT/TT group to similar levels of conductance as the AA group. The AT/TT group demonstrated this greater percentage increase in these diffusing capacity parameters despite a significantly smaller percentage increase in VC. Given that the groups have similar maximal voluntary ventilation and VA, it is likely that these differences reflect alterations in the alveolar–capillary membrane. This suggests that the increase in conduction may be due to increased surface liquid volume in response to exercise. Improved airway hydration, by hypertonic saline, has previously been shown to increase pulmonary function (FVC and FEV1) in individuals with CF, although no diffusing capacity data were available (12). Interestingly, recent studies have demonstrated an important relationship between DLNO and computed tomography-derived structural abnormalities in patients with CF, suggesting that this technique strongly represents lung damage in this patient population (10).
There are various pathways that influence ion and, therefore, fluid regulation during exercise in the lungs. During exercise, epinephrine levels increase by up to 1000-fold, causing stimulation of the β2-adrenergic receptor (9). Activation of the β2-adrenergic receptor causes the release of Gαs subunit, which activates adenylyl cyclase, resulting in the conversion of adenosine triphosphate (ATP) to cyclic adenosine monophosphate. Cyclic AMP subsequently activates protein kinase A, which phosphorylates CFTR, causing channel activation and movement of Cl− to the apical side of the airway epithelial cells and a CFTR-mediated inhibition of ENaC activity (4,7). In addition, ENaC can be directly activated by protein kinase A during exercise. ENaC activity can also be up-regulated during exercise through direct activation as a result of increases in shear stress in response to increased ventilation (11,15,34,40).
During exercise, ENaC activity can be inhibited via activation of the purinergic (P2Y2) pathway by ATP and adenosine, which are released from the epithelia in response to the mechanical stress of increased ventilation during exercise (8). The application of nucleotides to the airway lumen causes increased secretion and hydration of the airway surface liquid in both healthy and CF epithelia (5). ATP and adenosine interact with P2Y2 receptors on the apical side of the membrane, causing a breakdown in phosphatidylinositol 4,5-bisphosphate (PIP2). Because PIP2 is required for protein kinase C–mediated ENaC activation, the breakdown of PIP2 results in the inhibition of ENaC. Purinergic stimulation during exercise can also increase calcium-activated chloride channel activity through inositol trisphosphate–mediated release of Ca2+ from the endoplasmic reticulum Ca2+ stores (8,22). This is important because even small changes in apical Cl− and, therefore, fluid can improve pulmonary function in patients with CF. The differences seen in DLCO and DLNO from rest to peak exercise between the genetic variants at amino acid 663 of ENaC may have resulted from the response to adrenergic stimulation of CFTR, resulting in ENaC inhibition or more likely through purinergic inhibition of ENaC and Ca2+-dependent Cl− channels activation.
In healthy individuals, exercise resulted in opposite changes in diffusing capacity; AA individuals demonstrated a greater increase in diffusing capacity in response to peak exercise, whereas in CF, AT/TT individuals demonstrated a greater increase in diffusing capacity (3). We hypothesize that in healthy individuals, the AA group has a greater capacity to increase ENaC activity in response to adrenergic stimulation, leading to fluid clearance and a greater increase in diffusing capacity. In individuals with CF, exercise may lead to inhibition of the more active T663 ENaC, resulting in an increased surface liquid volume, which may provide beneficial improvements in diffusing capacity.
This study suggests that genetic variation of the α-subunit of ENaC is associated with differences in the diffusing capacity response to exercise in CF. We hypothesize that the greater positive change in lung diffusion in the AT/TT group, which brought this group to overall levels similar to the AA group, could be due to exercise-induced inhibition of ENaC activity being more influential for improving surface liquid depth in the AT/TT group who have what was shown to be a more active ENaC in cell work.
Support for this work was provided by HL108962-01, the University of Arizona Clinical Scholars program, and 5-T32-GM08400 Graduate Training Grant in Systems and Integrative Physiology.
We are sincerely grateful to the CF subjects who donated both their time and effort to be a part of this study.
The authors have no conflict of interest to disclose.
The results of this study do not constitute endorsement by the American College of Sports Medicine.
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Keywords:©2012The American College of Sports Medicine
EXERCISE; CYSTIC FIBROSIS; DIFFUSING CAPACITY; DLNO; DLCO; ENaC POLYMORPHISM