Lung DOI 10.1007/s00408-014-9582-9
Association Between Vitamin D Status and COPD Phenotypes Mia Moberg • Thomas Ringbaek • Nassim Bazeghi Roberts • Jørgen Vestbo
Received: 15 October 2013 / Accepted: 2 April 2014 Ó Springer Science+Business Media New York 2014
Abstract Background It has been suggested that identifying phenotypes in chronic obstructive pulmonary disease (COPD) might improve treatment outcome and the accuracy of prediction of prognosis. In observational studies vitamin D deficiency has been associated with decreased pulmonary function, presence of emphysema and osteoporosis, upper respiratory tract infections, and systemic inflammation. This could indicate a relationship between vitamin D status and COPD phenotypes. The aim of this study was to assess the association between vitamin D levels and COPD phenotypes. In addition, seasonality of vitamin D levels was examined. Methods A total of 91 patients from a Danish subpopulation of the ‘‘Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points’’ cohort took part in a biomarker substudy. Vitamin D concentration was measured from blood samples taken at two visits, approximately 6 months apart. The participants were 40–75-year-
old patients with COPD and had a smoking history of [10 pack-years. Results Fifty-six patients had 25-hydroxyvitamin D measured from blood samples from both visits. In the final model of the multivariate analyses, the factors that were associated with vitamin D deficiency at the first visit were age (OR: 0.89, p = 0.02) and summer season (OR: 3.3, p = 0.03). Factors associated with vitamin D level also at the first visit were age (B: 0.9, p = 0.02) and 6 min walking distance (B: 0.05, p = 0.01). Conclusion Vitamin D was not associated with COPD phenotypes and season did not seem to be a determinant of vitamin D levels in patients with moderate to severe COPD. Keywords 25(OH)D Biomarker Seasonality COPD Vitamin D Phenotypes
Introduction M. Moberg (&) T. Ringbaek N. B. Roberts Section of Respiratory Medicine, Hvidovre University Hospital, Kettegaard Alle´ 30, 2650 Hvidovre, Denmark e-mail: [email protected] J. Vestbo Department of Respiratory Medicine, Odense University Hospital, Sdr. Boulevard 29, 5000 Odense C, Denmark J. Vestbo Manchester Academic Health Science Centre, University Hospital South Manchester NHS Foundation Trust, The University of Manchester, Manchester, UK J. Vestbo NIHR South Manchester Respiratory and Allergy Clinical Research Facility, Southmoor Road, Manchester M23 9LT, UK
Chronic obstructive pulmonary disease (COPD) continues to be one of the leading causes of morbidity and mortality worldwide [1]. Several therapeutic approaches are available, yet treatment and prediction of prognosis still need to be improved. Because of the heterogeneous nature of the disease, it has been suggested that treatment outcomes could be improved by characterizing patients by COPD phenotypes. In this context, a phenotype is defined as ‘‘a single or combination of disease attributes that describe differences between individuals as they relate to clinically meaningful outcomes’’ [2]. Vitamin D deficiency is common in patients with COPD [3], and in observational studies vitamin D deficiency has been associated with decreased lung function [4], emphysema [5], osteoporosis
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[6], upper respiratory tract infection [7], and systemic inflammation [8]. This could indicate that vitamin D status is associated with specific COPD phenotypes. The primary aim of this study was to describe the relationship between vitamin D and predefined COPD phenotypes. The secondary aim was to examine if vitamin D levels varied with the seasons in patients with COPD.
Methods A total of 91 patients from a Danish subpopulation of the ‘‘Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points’’ (ECLIPSE) cohort took part in a biomarker substudy using blood samples taken at follow-up visits after 3, 6, 9, 12, 18, and 24 months [9, 10]. The participants were 40–75-year-old patients with COPD and had a smoking history of [10 pack-years, a post-bronchodilator forced expiratory volume in 1 s (FEV1) \80 % predicted, and a ratio of FEV1 to forced vital capacity (FVC) \0.7. At baseline, all patients had stable disease. Clinical assessments included pulmonary function (FEV1, FVC, and FEV1/FVC), exercise capacity (6-min walk test), amount of emphysema [percentage of low attenuation area on chest computed tomographic (CT) scans], smoking status (current smoking defined as self-reported or exhaled carbon monoxide [12 ppm), dyspnea score [modified Medical Research Council (mMRC) dyspnea scale (grades 0–4)], body mass index (BMI), and fat-free mass index (FFMI) using bioelectrical impedance analysis [9]. Registration and definition of exacerbations have been described previously [11]. The reported age of the subjects was that at the first visit in the Danish substudy [10]. The Danish part of the ECLIPSE study was approved by the Regional Research Ethics Committee in Denmark. The study complied with the current laws of Denmark. Phenotypes The following phenotypes of COPD, which were predefined in the Danish subpopulation of the ECLIPSE study, were examined: (1) severe emphysema, defined as[10 % of lung tissue with low attenuation (-950 HU) on CT; (2) chronic bronchitis, defined as cough and phlegm for 3 months per year for at least 2 years according to the ATS-DLD questionnaire; (3) frequent exacerbations, defined as having two or more exacerbations in the year prior to inclusion; (4) any cardiovascular disease (CVD), defined as self-reported current or previous CVD, including arrhythmia, cerebrovascular attack, myocardial infarction, deep venous thrombosis, or thrombosis in ocular vessels; and (5) low fat-free mass, defined as FFMI \16 kg/m2 for men and \15 kg/m2 for women.
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Biochemistry Blood samples were drawn at all six visits of the Danish substudy. The samples were centrifuged and the plasma (Heparin) was frozen and stored at -80 °C. The samples used in the present study were drawn at visit 3 (visit A) and visit 4 (visit B) of the Danish substudy. The visits were approximately 6 months apart. Vitamin D (25-hydroxyvitamin D [25(OH)D]) was analyzed in September 2012 in one batch. 25(OH)D was measured by means of a direct, competitive chemiluminescence immunoassay using the DiaSorin LIAISON 25(OH)D Total Assay (DiaSorin, Inc., Stillwater, MN, USA). The assay measured both 25-hydroxyvitamin D3 and 25-hydroxyvitamin D2. Statistical Analyses We analyzed the relationship between 25(OH)D levels at visit A and several variables by linear and logistic regression. The cutoff level for vitamin D deficiency was defined as\50 nmol/L for the logistic model. We also analyzed the relationship between the changes in vitamin D from visit A to visit B (D vitamin D) and the variables listed below. A manual backward stepwise method was used for both the linear and the logistic models; variables with a p \ 0.1 remained in the model. The following variables were used in both the logistic and the linear model: season, age, sex, BMI, smoking, GOLD stage, mMRC grade, 6 min walking distance (6MWD), and pack-years. The different phenotypes were added individually to the final model. In our analyses BMI was categorized according to the World Health Organization (WHO) classification as follows: underweight (BMI \ 18.5), normal (BMI = 18.5–24.99), overweight (BMI = 25.0–29.99), and obese (BMI C 30). Seasons were defined as winter: October–March and summer: April–September. In the linear regression with change in vitamin D as outcome, the season variable was entered as change of the season in which the blood sample was drawn; i.e., change from summer to winter or winter to summer. Dyspnea grade was entered as a dichotomous variable (mMRC \ 2 and mMRC C 2). Patient characteristics were expressed as median and (25, 75) percentile, or n (%). Statistical analyses were performed using SPSS 20.0 (SPSS, Inc., Chicago, IL, USA).
Results Of the 91 patients in the Danish substudy, 87 had 25(OH)D measured on blood samples taken at visit A or B, 70 patients had 25(OH)D measured at visit A, and 56 patients had samples taken at both visit A and B (Table 1). Missing
Lung Table 1 Patient characteristics at visit A and B Visit A or B (n = 87)
Visit A (n = 70)
Visit B (n = 73)
Visit A and B (n = 56)
Age (years)
63 (57, 67)
64 (57, 67)
63 (57, 67)
63.5 (57, 67)
Women
45 (51.7)
41 (58.6)
35 (47.9)
31 (55.4)
FEV1 % predicted
46 (34, 64)
46 (34, 62)
46 (36, 63)
46 (36, 61)
25(OH)D visit A (nmol/L)
41 (28, 57)
41 (28, 57)
–
40 (27, 57)
25(OH)D visit B (nmol/L)
48 (33, 71)
–
48 (33, 71)
54 (36, 72)
D 25(OH)D (nmol/L)
–
–
–
9.0 (-1.3, 26.8)
25(OH)D summer (nmol/L)
–
38.5 (27.5, 47.3)
61.0 (38.5, 83)
–
25(OH)D winter (nmol/L)
–
43.5 (27.8, 47.3)
37.5 (30.5, 62.8)
–
Pack-years
42 (34, 53)
41 (32, 52)
41 (31, 52)
39 (29, 50)
Current smokers
32 (36.8)
28 (40)
26 (35.6)
34 (60.7)
BMI (kg/m2) mMRC (0–4)
25.7 (22.4, 28.2) 1.0 (1.0, 2.0)
25.7 (22.6, 28.2) 1.0 (1.0, 2.0)
25.8 (22.7, 28.6) 1.0 (1.0, 2.0)
26.6 (22.7, 28.7) 1.0 (1.0, 2.0)
6MWD (m)
435 (360, 501)
419 (354, 496)
444 (378, 503)
438 (362, 497)
Values for continuous variables are median (25, 75 percentile), and values for categorical variables are n (%)
values were due to too little plasma for measurement of 25(OH)D or missing blood samples. All patients were Caucasian. At visit A, 45 patients (64 %) were vitamin D deficient [25(OH)D \ 50 nmol/L] and at visit B this was the case for 37 patients (51 %) (Table 1). Univariate Analysis None of the variables (age, sex, GOLD stage, pack-years, smoking, season, 6MWD, BMI, or mMRC) was associated with the vitamin D level at visit A in the univariate analyses. Summer was associated with an increased risk of vitamin D deficiency at visit A in the univariate analysis [OR: 2.9 (95 % CI: 1.04–8.1), p = 0.042], whereas the risk of vitamin D deficiency at visit B was greater in the winter [OR: 2.9 (95 % CI: 1.1–7.6), p = 0.028]. Multivariate Analysis
Table 2 Factors independently associated with vitamin D deficiency at visit A OR (95 % CI)
p
Age (years)
0.89 (0.81–0.98)
0.02
Summer
3.34 (1.12–10.08)
0.03
6MWD (m)
0.995 (0.99–1.00)
0.09
Multivariate analysis, logistic regression
Table 3 Factors independently associated with vitamin D level at visit A B (95 % CI)
p
6MWD (m)
0.05 (0.01–0.10)
0.01
Age (years)
0.90 (0.17–1.63)
0.02
GOLD IV
10.9 (–1.3 to 23.0)
0.08
Pack-years
–0.2 (–0.4 to 0.2)
0.08
Multivariate analysis, linear regression
In the final model of the multivariate analysis, the factors associated vitamin D deficiency at visit A were age [OR: 0.89 (95 % CI: 0.81–0.98), p = 0.02] and summer [OR: 3.34 (95 % CI: 1.12–10.08), p = 0.03] (Table 2). 6MWD and age were related to the vitamin D level at visit A (Table 3). Vitamin D levels increased for every additional meter walked, i.e., 10 nmol/L for every 200 m. Levels also increased with every additional year in age, i.e., 10 nmol/L for every 11 years. Season was not associated with vitamin D levels (p = 0.23) in the multivariate analysis. The change in vitamin D from visit A to visit B was associated with mMRC grade. With an increase in dyspnea grade, the change of vitamin D level decreased; if the
patients were categorized as mMRC \ 2, the predicted decrease in vitamin D level was 12 nmol/L compared with patients with mMRC C 2. Change in vitamin D level was also associated with pack-years, i.e., 1 nmol/L for every 3.8 pack-years. If visit A was in the winter and visit B in the summer, the change in vitamin D was approximately 10 nmol/L higher than if the blood tests from visit A and B were from the same season (Table 4). For the 56 patients who had blood samples available from both visit A and visit B, the median (25, 75 percentile) of vitamin D level was lower at visit A [40 nmol/L (27, 57)] compared with that at visit B [54 nmol/L (36, 72)]
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Lung Table 4 Factors independently associated with change in vitamin D B (95 % CI)
p
mMRC C 2
-10 (-20 to -0.2)
0.045
Pack-years
0.34 (0.14–0.55)
0.002
10 (0.2–20)
0.046
Visit A: winter and visit B: Summer Multivariate analysis, linear regression
and vitamin D deficiency was more frequent at visit A [38 (67.9 %)] compared with that at visit B [25 (44.6 %)] (Table 1). Vitamin D level at visit A, vitamin D deficiency at visit A, and vitamin D change were not associated with any of the predefined phenotypes.
[19], who reported that vitamin D levels measured from March–October compared with levels measured from November–February were considerably higher in controls, whereas this difference was not seen in the patients with COPD. Similarly, in a Danish study of 462 patients with COPD, no seasonality was found [15]. In conclusion, in a cohort of patients with moderate to severe COPD, no association was found between vitamin D and COPD phenotypes. Also, season was not a strong determinant of vitamin D levels in COPD patients. Acknowledgments
Mia Moberg was funded by TrygFonden.
Conflict of interest The authors have no conflict of interest to declare. Ethical standards Denmark.
The study complies with the currents laws of
Discussion In this study we did not find any association between selected COPD phenotypes and vitamin D levels or vitamin D deficiency. There are several possible reasons for these negative results. First, it is possible that vitamin D has no specific biological role in COPD. It remains uncertain whether vitamin D deficiency plays a role in the development of several noncommunicable diseases or whether it is merely a marker of poor health [12]. It is commonly accepted that vitamin D has positive effects on bone health, but the importance of vitamin D in extraskeletal health is less clear. Results from clinical studies have been conflicting or inconclusive. The few randomized placebocontrolled clinical studies of the effect of vitamin D supplementation in patients with COPD have been negative with respect to prevention of exacerbations [13] and improvement of physical performance [14]. Furthermore, vitamin D status does not seem to predict mortality in COPD [15]. However, even if the role of vitamin D in COPD is unclear, there is a case for examining its role in COPD phenotypes. COPD is a heterogeneous disease. Failure to subclassify it into phenotypes may mask a relationship that exists in one type but the association is lost when all subtypes are grouped together. However, our data do not support an association between vitamin D and COPD phenotypes, but larger studies are needed. In most studies, season has been shown to be a strong predictor of vitamin D levels in patients with COPD [16] and in healthy adults in Europe [17] and the United States [18]. Our results on seasonality were at variance with these observations. We hypothesized that seasonality would not have an impact on vitamin D levels because the vitamin D obtained from sunlight plays a smaller role for people who are sedentary and spend less time outside, such as patients with severe COPD. This has been shown by Jackson et al.
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References 1. Vestbo J, Hurd SS, Agusti AG, Jones PW, Vogelmeier C, Anzueto A, Barnes PJ, Fabbri LM, Martinez FJ, Nishimura M, Stockley RA, Sin DD, Rodriguez-Roisin R (2013) Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD Executive Summary. Am J Respir Crit Care Med 187(4):347–365. doi:10.1164/rccm. 201204-0596PP 2. Han MK, Agusti A, Calverley PM, Celli BR, Criner G, Curtis JL, Fabbri LM, Goldin JG, Jones PW, MacNee W, Make BJ, Rabe KF, Rennard SI, Sciurba FC, Silverman EK, Vestbo J, Washko GR, Wouters EFM, Martinez FJ (2010) Chronic obstructive pulmonary disease phenotypes. Am J Respir Crit Care Med 182(5):598–604. doi:10.1164/rccm.200912-1843CC 3. Janssens W, Bouillon R, Claes B, Carremans C, Lehouck A, Buysschaert I, Coolen J, Mathieu C, Decramer M, Lambrechts D (2010) Vitamin D deficiency is highly prevalent in COPD and correlates with variants in the vitamin D-binding gene. Thorax 65(3):215–220. doi:10.1136/thx.2009.120659 4. Black PN, Scragg R (2005) Relationship between serum 25-hydroxyvitamin D and pulmonary function in the third national health and nutrition examination survey. Chest 128(6):3792–3798. doi:10.1378/chest.128.6.3792 5. Berg I, Hanson C, Sayles H, Romberger D, Nelson A, Meza J, Miller B, Wouters EF, Macnee W, Rutten EP, Romme EA, Vestbo J, Edwards L, Rennard S (2013) Vitamin D, vitamin D binding protein, lung function and structure in COPD. Respir Med 107(10):1578–1588. doi:10.1016/j.rmed.2013.05.010 6. Biskobing DM (2002) COPD and osteoporosis. Chest 121(2): 609–620 7. Ginde AA, Mansbach JM, Camargo CA Jr (2009) Association between serum 25-hydroxyvitamin D level and upper respiratory tract infection in the Third National Health and Nutrition Examination Survey. Arch Intern Med 169(4):384–390. doi:10. 1001/archinternmed.2008.560 8. Guillot X, Semerano L, Saidenberg-Kermanac’h N, Falgarone G, Boissier MC (2010) Vitamin D and inflammation. Joint Bone Spine 77(6):552–557. doi:10.1016/j.jbspin.2010.09.018 9. Vestbo J, Anderson W, Coxson HO, Crim C, Dawber F, Edwards L, Hagan G, Knobil K, Lomas DA, MacNee W, Silverman EK, Tal-Singer R (2008) Evaluation of COPD longitudinally to
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identify predictive surrogate end-points (ECLIPSE). Eur Respir J 31(4):869–873. doi:10.1183/09031936.00111707 Bazeghi N, Gerds TA, Budtz-Jorgensen E, Hove J, Vestbo J (2011) Exhaled nitric oxide measure using multiple flows in clinically relevant subgroups of COPD. Respir Med 105(9):1338–1344. doi:10.1016/j.rmed.2011.03.015 Hurst JR, Vestbo J, Anzueto A, Locantore N, Mullerova H, TalSinger R, Miller B, Lomas DA, Agusti A, Macnee W, Calverley P, Rennard S, Wouters EF, Wedzicha JA (2010) Susceptibility to exacerbation in chronic obstructive pulmonary disease. N Engl J Med 363(12):1128–1138. doi:10.1056/NEJMoa0909883 Jacobs ET, Martinez ME, Jurutka PW (2011) Vitamin D: marker or mechanism of action? Cancer Epidemiol Biomarkers Prev 20(4):585–590. doi:10.1158/1055-9965.epi-10-1257 Lehouck A, Mathieu C, Carremans C, Baeke F, Verhaegen J, Van Eldere J, Decallonne B, Bouillon R, Decramer M, Janssens W (2012) High doses of vitamin D to reduce exacerbations in chronic obstructive pulmonary disease: a randomized trial. Ann Intern Med 156(2):105–114. doi:10.1059/0003-4819-156-2201201170-00004 Bjerk SM, Edgington BD, Rector TS, Kunisaki KM (2013) Supplemental vitamin D and physical performance in COPD: a pilot randomized trial. Int J Chron Obstruct Pulmon Dis 8:97–104. doi:10.2147/copd.s40885
15. Holmgaard DB, Mygind LH, Titlestad IL, Madsen H, Fruekilde PB, Pedersen SS, Pedersen C (2013) Serum vitamin D in patients with chronic obstructive lung disease does not correlate with mortality—results from a 10-year prospective cohort study. PLoS One 8(1):e53670. doi:10.1371/journal.pone.0053670 16. Persson LJ, Aanerud M, Hiemstra PS, Hardie JA, Bakke PS, Eagan TM (2012) Chronic obstructive pulmonary disease is associated with low levels of vitamin D. PLoS One 7(6):e38934. doi:10.1371/journal.pone.0038934 17. Klenk J, Rapp K, Denkinger MD, Nagel G, Nikolaus T, Peter R, Koenig W, Bohm BO, Rothenbacher D (2013) Seasonality of vitamin D status in older people in Southern Germany: implications for assessment. Age Ageing 42(3):404–408. doi:10.1093/ ageing/aft042 18. Looker AC, Pfeiffer CM, Lacher DA, Schleicher RL, Picciano MF, Yetley EA (2008) Serum 25-hydroxyvitamin D status of the US population: 1988–1994 compared with 2000–2004. Am J Clin Nutr 88(6):1519–1527. doi:10.3945/ajcn.2008.26182 19. Jackson AS, Shrikrishna D, Kelly JL, Kemp SV, Hart N, Moxham J, Polkey MI, Kemp P, Hopkinson NS (2013) Vitamin D and skeletal muscle strength and endurance in COPD. Eur Respir J 41(2):309–316. doi:10.1183/09031936.00043112
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Association Between Vitamin D Status and COPD Phenotypes Mia Moberg • Thomas Ringbaek • Nassim Bazeghi Roberts • Jørgen Vestbo
Received: 15 October 2013 / Accepted: 2 April 2014 Ó Springer Science+Business Media New York 2014
Abstract Background It has been suggested that identifying phenotypes in chronic obstructive pulmonary disease (COPD) might improve treatment outcome and the accuracy of prediction of prognosis. In observational studies vitamin D deficiency has been associated with decreased pulmonary function, presence of emphysema and osteoporosis, upper respiratory tract infections, and systemic inflammation. This could indicate a relationship between vitamin D status and COPD phenotypes. The aim of this study was to assess the association between vitamin D levels and COPD phenotypes. In addition, seasonality of vitamin D levels was examined. Methods A total of 91 patients from a Danish subpopulation of the ‘‘Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points’’ cohort took part in a biomarker substudy. Vitamin D concentration was measured from blood samples taken at two visits, approximately 6 months apart. The participants were 40–75-year-
old patients with COPD and had a smoking history of [10 pack-years. Results Fifty-six patients had 25-hydroxyvitamin D measured from blood samples from both visits. In the final model of the multivariate analyses, the factors that were associated with vitamin D deficiency at the first visit were age (OR: 0.89, p = 0.02) and summer season (OR: 3.3, p = 0.03). Factors associated with vitamin D level also at the first visit were age (B: 0.9, p = 0.02) and 6 min walking distance (B: 0.05, p = 0.01). Conclusion Vitamin D was not associated with COPD phenotypes and season did not seem to be a determinant of vitamin D levels in patients with moderate to severe COPD. Keywords 25(OH)D Biomarker Seasonality COPD Vitamin D Phenotypes
Introduction M. Moberg (&) T. Ringbaek N. B. Roberts Section of Respiratory Medicine, Hvidovre University Hospital, Kettegaard Alle´ 30, 2650 Hvidovre, Denmark e-mail: [email protected] J. Vestbo Department of Respiratory Medicine, Odense University Hospital, Sdr. Boulevard 29, 5000 Odense C, Denmark J. Vestbo Manchester Academic Health Science Centre, University Hospital South Manchester NHS Foundation Trust, The University of Manchester, Manchester, UK J. Vestbo NIHR South Manchester Respiratory and Allergy Clinical Research Facility, Southmoor Road, Manchester M23 9LT, UK
Chronic obstructive pulmonary disease (COPD) continues to be one of the leading causes of morbidity and mortality worldwide [1]. Several therapeutic approaches are available, yet treatment and prediction of prognosis still need to be improved. Because of the heterogeneous nature of the disease, it has been suggested that treatment outcomes could be improved by characterizing patients by COPD phenotypes. In this context, a phenotype is defined as ‘‘a single or combination of disease attributes that describe differences between individuals as they relate to clinically meaningful outcomes’’ [2]. Vitamin D deficiency is common in patients with COPD [3], and in observational studies vitamin D deficiency has been associated with decreased lung function [4], emphysema [5], osteoporosis
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[6], upper respiratory tract infection [7], and systemic inflammation [8]. This could indicate that vitamin D status is associated with specific COPD phenotypes. The primary aim of this study was to describe the relationship between vitamin D and predefined COPD phenotypes. The secondary aim was to examine if vitamin D levels varied with the seasons in patients with COPD.
Methods A total of 91 patients from a Danish subpopulation of the ‘‘Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points’’ (ECLIPSE) cohort took part in a biomarker substudy using blood samples taken at follow-up visits after 3, 6, 9, 12, 18, and 24 months [9, 10]. The participants were 40–75-year-old patients with COPD and had a smoking history of [10 pack-years, a post-bronchodilator forced expiratory volume in 1 s (FEV1) \80 % predicted, and a ratio of FEV1 to forced vital capacity (FVC) \0.7. At baseline, all patients had stable disease. Clinical assessments included pulmonary function (FEV1, FVC, and FEV1/FVC), exercise capacity (6-min walk test), amount of emphysema [percentage of low attenuation area on chest computed tomographic (CT) scans], smoking status (current smoking defined as self-reported or exhaled carbon monoxide [12 ppm), dyspnea score [modified Medical Research Council (mMRC) dyspnea scale (grades 0–4)], body mass index (BMI), and fat-free mass index (FFMI) using bioelectrical impedance analysis [9]. Registration and definition of exacerbations have been described previously [11]. The reported age of the subjects was that at the first visit in the Danish substudy [10]. The Danish part of the ECLIPSE study was approved by the Regional Research Ethics Committee in Denmark. The study complied with the current laws of Denmark. Phenotypes The following phenotypes of COPD, which were predefined in the Danish subpopulation of the ECLIPSE study, were examined: (1) severe emphysema, defined as[10 % of lung tissue with low attenuation (-950 HU) on CT; (2) chronic bronchitis, defined as cough and phlegm for 3 months per year for at least 2 years according to the ATS-DLD questionnaire; (3) frequent exacerbations, defined as having two or more exacerbations in the year prior to inclusion; (4) any cardiovascular disease (CVD), defined as self-reported current or previous CVD, including arrhythmia, cerebrovascular attack, myocardial infarction, deep venous thrombosis, or thrombosis in ocular vessels; and (5) low fat-free mass, defined as FFMI \16 kg/m2 for men and \15 kg/m2 for women.
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Biochemistry Blood samples were drawn at all six visits of the Danish substudy. The samples were centrifuged and the plasma (Heparin) was frozen and stored at -80 °C. The samples used in the present study were drawn at visit 3 (visit A) and visit 4 (visit B) of the Danish substudy. The visits were approximately 6 months apart. Vitamin D (25-hydroxyvitamin D [25(OH)D]) was analyzed in September 2012 in one batch. 25(OH)D was measured by means of a direct, competitive chemiluminescence immunoassay using the DiaSorin LIAISON 25(OH)D Total Assay (DiaSorin, Inc., Stillwater, MN, USA). The assay measured both 25-hydroxyvitamin D3 and 25-hydroxyvitamin D2. Statistical Analyses We analyzed the relationship between 25(OH)D levels at visit A and several variables by linear and logistic regression. The cutoff level for vitamin D deficiency was defined as\50 nmol/L for the logistic model. We also analyzed the relationship between the changes in vitamin D from visit A to visit B (D vitamin D) and the variables listed below. A manual backward stepwise method was used for both the linear and the logistic models; variables with a p \ 0.1 remained in the model. The following variables were used in both the logistic and the linear model: season, age, sex, BMI, smoking, GOLD stage, mMRC grade, 6 min walking distance (6MWD), and pack-years. The different phenotypes were added individually to the final model. In our analyses BMI was categorized according to the World Health Organization (WHO) classification as follows: underweight (BMI \ 18.5), normal (BMI = 18.5–24.99), overweight (BMI = 25.0–29.99), and obese (BMI C 30). Seasons were defined as winter: October–March and summer: April–September. In the linear regression with change in vitamin D as outcome, the season variable was entered as change of the season in which the blood sample was drawn; i.e., change from summer to winter or winter to summer. Dyspnea grade was entered as a dichotomous variable (mMRC \ 2 and mMRC C 2). Patient characteristics were expressed as median and (25, 75) percentile, or n (%). Statistical analyses were performed using SPSS 20.0 (SPSS, Inc., Chicago, IL, USA).
Results Of the 91 patients in the Danish substudy, 87 had 25(OH)D measured on blood samples taken at visit A or B, 70 patients had 25(OH)D measured at visit A, and 56 patients had samples taken at both visit A and B (Table 1). Missing
Lung Table 1 Patient characteristics at visit A and B Visit A or B (n = 87)
Visit A (n = 70)
Visit B (n = 73)
Visit A and B (n = 56)
Age (years)
63 (57, 67)
64 (57, 67)
63 (57, 67)
63.5 (57, 67)
Women
45 (51.7)
41 (58.6)
35 (47.9)
31 (55.4)
FEV1 % predicted
46 (34, 64)
46 (34, 62)
46 (36, 63)
46 (36, 61)
25(OH)D visit A (nmol/L)
41 (28, 57)
41 (28, 57)
–
40 (27, 57)
25(OH)D visit B (nmol/L)
48 (33, 71)
–
48 (33, 71)
54 (36, 72)
D 25(OH)D (nmol/L)
–
–
–
9.0 (-1.3, 26.8)
25(OH)D summer (nmol/L)
–
38.5 (27.5, 47.3)
61.0 (38.5, 83)
–
25(OH)D winter (nmol/L)
–
43.5 (27.8, 47.3)
37.5 (30.5, 62.8)
–
Pack-years
42 (34, 53)
41 (32, 52)
41 (31, 52)
39 (29, 50)
Current smokers
32 (36.8)
28 (40)
26 (35.6)
34 (60.7)
BMI (kg/m2) mMRC (0–4)
25.7 (22.4, 28.2) 1.0 (1.0, 2.0)
25.7 (22.6, 28.2) 1.0 (1.0, 2.0)
25.8 (22.7, 28.6) 1.0 (1.0, 2.0)
26.6 (22.7, 28.7) 1.0 (1.0, 2.0)
6MWD (m)
435 (360, 501)
419 (354, 496)
444 (378, 503)
438 (362, 497)
Values for continuous variables are median (25, 75 percentile), and values for categorical variables are n (%)
values were due to too little plasma for measurement of 25(OH)D or missing blood samples. All patients were Caucasian. At visit A, 45 patients (64 %) were vitamin D deficient [25(OH)D \ 50 nmol/L] and at visit B this was the case for 37 patients (51 %) (Table 1). Univariate Analysis None of the variables (age, sex, GOLD stage, pack-years, smoking, season, 6MWD, BMI, or mMRC) was associated with the vitamin D level at visit A in the univariate analyses. Summer was associated with an increased risk of vitamin D deficiency at visit A in the univariate analysis [OR: 2.9 (95 % CI: 1.04–8.1), p = 0.042], whereas the risk of vitamin D deficiency at visit B was greater in the winter [OR: 2.9 (95 % CI: 1.1–7.6), p = 0.028]. Multivariate Analysis
Table 2 Factors independently associated with vitamin D deficiency at visit A OR (95 % CI)
p
Age (years)
0.89 (0.81–0.98)
0.02
Summer
3.34 (1.12–10.08)
0.03
6MWD (m)
0.995 (0.99–1.00)
0.09
Multivariate analysis, logistic regression
Table 3 Factors independently associated with vitamin D level at visit A B (95 % CI)
p
6MWD (m)
0.05 (0.01–0.10)
0.01
Age (years)
0.90 (0.17–1.63)
0.02
GOLD IV
10.9 (–1.3 to 23.0)
0.08
Pack-years
–0.2 (–0.4 to 0.2)
0.08
Multivariate analysis, linear regression
In the final model of the multivariate analysis, the factors associated vitamin D deficiency at visit A were age [OR: 0.89 (95 % CI: 0.81–0.98), p = 0.02] and summer [OR: 3.34 (95 % CI: 1.12–10.08), p = 0.03] (Table 2). 6MWD and age were related to the vitamin D level at visit A (Table 3). Vitamin D levels increased for every additional meter walked, i.e., 10 nmol/L for every 200 m. Levels also increased with every additional year in age, i.e., 10 nmol/L for every 11 years. Season was not associated with vitamin D levels (p = 0.23) in the multivariate analysis. The change in vitamin D from visit A to visit B was associated with mMRC grade. With an increase in dyspnea grade, the change of vitamin D level decreased; if the
patients were categorized as mMRC \ 2, the predicted decrease in vitamin D level was 12 nmol/L compared with patients with mMRC C 2. Change in vitamin D level was also associated with pack-years, i.e., 1 nmol/L for every 3.8 pack-years. If visit A was in the winter and visit B in the summer, the change in vitamin D was approximately 10 nmol/L higher than if the blood tests from visit A and B were from the same season (Table 4). For the 56 patients who had blood samples available from both visit A and visit B, the median (25, 75 percentile) of vitamin D level was lower at visit A [40 nmol/L (27, 57)] compared with that at visit B [54 nmol/L (36, 72)]
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Lung Table 4 Factors independently associated with change in vitamin D B (95 % CI)
p
mMRC C 2
-10 (-20 to -0.2)
0.045
Pack-years
0.34 (0.14–0.55)
0.002
10 (0.2–20)
0.046
Visit A: winter and visit B: Summer Multivariate analysis, linear regression
and vitamin D deficiency was more frequent at visit A [38 (67.9 %)] compared with that at visit B [25 (44.6 %)] (Table 1). Vitamin D level at visit A, vitamin D deficiency at visit A, and vitamin D change were not associated with any of the predefined phenotypes.
[19], who reported that vitamin D levels measured from March–October compared with levels measured from November–February were considerably higher in controls, whereas this difference was not seen in the patients with COPD. Similarly, in a Danish study of 462 patients with COPD, no seasonality was found [15]. In conclusion, in a cohort of patients with moderate to severe COPD, no association was found between vitamin D and COPD phenotypes. Also, season was not a strong determinant of vitamin D levels in COPD patients. Acknowledgments
Mia Moberg was funded by TrygFonden.
Conflict of interest The authors have no conflict of interest to declare. Ethical standards Denmark.
The study complies with the currents laws of
Discussion In this study we did not find any association between selected COPD phenotypes and vitamin D levels or vitamin D deficiency. There are several possible reasons for these negative results. First, it is possible that vitamin D has no specific biological role in COPD. It remains uncertain whether vitamin D deficiency plays a role in the development of several noncommunicable diseases or whether it is merely a marker of poor health [12]. It is commonly accepted that vitamin D has positive effects on bone health, but the importance of vitamin D in extraskeletal health is less clear. Results from clinical studies have been conflicting or inconclusive. The few randomized placebocontrolled clinical studies of the effect of vitamin D supplementation in patients with COPD have been negative with respect to prevention of exacerbations [13] and improvement of physical performance [14]. Furthermore, vitamin D status does not seem to predict mortality in COPD [15]. However, even if the role of vitamin D in COPD is unclear, there is a case for examining its role in COPD phenotypes. COPD is a heterogeneous disease. Failure to subclassify it into phenotypes may mask a relationship that exists in one type but the association is lost when all subtypes are grouped together. However, our data do not support an association between vitamin D and COPD phenotypes, but larger studies are needed. In most studies, season has been shown to be a strong predictor of vitamin D levels in patients with COPD [16] and in healthy adults in Europe [17] and the United States [18]. Our results on seasonality were at variance with these observations. We hypothesized that seasonality would not have an impact on vitamin D levels because the vitamin D obtained from sunlight plays a smaller role for people who are sedentary and spend less time outside, such as patients with severe COPD. This has been shown by Jackson et al.
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