Literature DB >> 28255238

Sarcopenia correlates with systemic inflammation in COPD.

Min Kwang Byun1, Eun Na Cho1, Joon Chang2, Chul Min Ahn1, Hyung Jung Kim1.   

Abstract

BACKGROUND: Muscle wasting and chronic inflammation are predominant features of patients with COPD. Systemic inflammation is associated with an accelerated decline in lung function. In this study, the prevalence of sarcopenia and the relationships between sarcopenia and systemic inflammations in patients with stable COPD were investigated.
MATERIALS AND METHODS: In a cross-sectional design, muscle strength and muscle mass were measured by handgrip strength (HGS) and bioelectrical impedance analysis in 80 patients with stable COPD. Patients (≥40 years old) diagnosed with COPD were recruited from outpatient clinics, and then COPD stages were classified. Sarcopenia was defined as the presence of both low muscle strength (by HGS) and low muscle mass (skeletal muscle mass index [SMMI]). Levels of circulating inflammatory biomarkers (IL-6 and high-sensitivity TNFα [hsTNFα]) were measured.
RESULTS: Sarcopenia was prevalent in 20 (25%) patients. Patients with sarcopenia were older, had lower body mass index, and a higher percentage of cardiovascular diseases. In addition, they had significantly higher modified Medical Research Council scores and lower 6-minute walk distance than those without sarcopenia. HGS was significantly correlated with age, modified Medical Research Council score, and COPD Assessment Test scores. Both HGS and SMMI had associations with IL-6 and hsTNFα (HGS, r=-0.35, P=0.002; SMMI, r=-0.246, P=0.044) level. In multivariate analysis, old age, lower body mass index, presence of cardiovascular comorbidities, and higher hsTNFα levels were significant determinants for sarcopenia in patients with stable COPD.
CONCLUSION: Sarcopenia is very common in patients with stable COPD, and is associated with more severe dyspnea-scale scores and lower exercise tolerance. Systemic inflammation could be an important contributor to sarcopenia in the stable COPD population.

Entities:  

Keywords:  COPD; handgrip strength; muscle wasting; sarcopenia; systemic inflammation

Mesh:

Substances:

Year:  2017        PMID: 28255238      PMCID: PMC5325093          DOI: 10.2147/COPD.S130790

Source DB:  PubMed          Journal:  Int J Chron Obstruct Pulmon Dis        ISSN: 1176-9106


Introduction

COPD is a leading cause of morbidity and mortality worldwide. It is characterized by persistent, progressive limitations in airflow, which are usually associated with enhanced airway and lung-inflammatory responses to noxious particles or gases.1 Systemic inflammation is associated with an accelerated decline in lung function, and is heightened during episodes of exacerbation.2,3 Systemic inflammation is now a recognized risk factor for other complications commonly observed in patients with COPD, including atherosclerosis,4 cachexia,5 anorexia,6 and osteoporosis.7 It is present not only in acutely exacerbated COPD but also in stable COPD.8 Muscle wasting is another characteristic feature of COPD,9 and evaluation of both muscle quality and quantity are essential. Physical inactivity is involved in the early loss of muscle function in COPD, and muscle wasting can further decrease physical activity, exercise tolerance, and quality of life. Previous studies have reported that muscle wasting is closely associated with higher rates of COPD exacerbation and lower survival rates.10,11 The BODE index (body mass index [BMI], obstruction of airways as measured by forced expiratory volume in 1 second [FEV1], dyspnea as measured by the modified Medical Research Council [mMRC] dyspnea scale, and exercise capacity as measured by 6-minute walk distance [6MWD]) was originally designed to predict mortality in COPD. It also demonstrates the prognostic significance of muscle mass and exercise capacity (as assessed by BMI and 6MWD) in predicting long-term outcomes.12 This concept recently defined as sarcopenia a clinical syndrome comprised of multiple factors, including physical inactivity, malnutrition, inflammation, and chronic illness.13,14 The European Working Group on Sarcopenia in Older People (EWGSOP) recommends using the presence of both low muscle mass and low muscle function (strength or performance) for the diagnosis of sarcopenia.13 Initially, sarcopenia used to describe age-related loss of muscle mass and power. However, catabolic inflammatory processes often observed in chronic illnesses can enhance sarcopenia. As such, it has recently been recognized as a syndrome in various chronic conditions. Also, in the COPD population the prevalence of sarcopenia is reported to be 15%, and is associated with impaired lung function and poor health status. No studies, however, have yet shown a direct association between sarcopenia and levels of inflammatory biomarkers in this group. We measured muscle mass and muscle strength in South Korean patients with stable COPD to determine the prevalence of sarcopenia using handgrip strength (HGS) and bioelectrical impedance analysis (BIA). In addition, we evaluated relationships between sarcopenia, biomarkers of systemic inflammation, disease severity, and other clinical features.

Materials and methods

Study design and populations

Patients (≥40 years old) diagnosed with COPD according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) and attending outpatient clinics between June 2012 and June 2014 at Gangnam Severance Hospital were considered eligible. Investigators explained the aim and protocol of the study to patients who fulfilled the inclusion criteria. Written informed consent and medical history were obtained at the visit. This was a cross-sectional study, and all measurements were completed at a single visit for each participants. Exclusion criteria were age <40 years, presence of active lung disease, diagnosis of bronchial asthma, lung resection or transplantation, presence of severe cardiovascular disease, an episode of COPD exacerbation within the last month, inability to perform a 6MWD test due to severe dyspnea, lower-leg trauma, severe muscle weakness, and inability to read or understand informed consent documents. All consenting subjects completed a Korean version of the COPD Assessment Test (CAT) questionnaire (GlaxoSmithKline, London, UK). Subjects were evaluated using the mMRC dyspnea scale and postbronchodilator FEV1 in a pulmonary function test (Vmax 229; SensorMedics, Yorba Linda, CA, USA), 6MWD, muscle measurements, and venous blood sampling at a single visit. We evaluated history of exacerbations in the last year, the BODE index, and disease severity according to a 2011 GOLD revision; the revised document recommends assessment of symptoms, lung function, and risk of exacerbation.1 This study was performed in accordance with the Declaration of Helsinki and South Korean good clinical practice guidelines. All protocols were approved by the institutional review board of Gangnam Severance Hospital (3-2011-0300).

Measurement of muscle mass and muscle strength

Muscle mass was quantified with BIA (Body Composition Analysis 1000; MediGate, Seoul, South Korea). Height (cm), body weight (kg), and BMI (kg/m2) were also measured. Fat mass index (FMI) and fat-free mass index (FFMI) were calculated as fat mass or fat-free mass (FFM) divided by the square of the patient’s height (kg/height2). Skeletal muscle mass index (SMMI) was calculated as skeletal muscle mass (SMM) divided by the square of patient’s height (kg/height2). Low MM was defined as having an SMMI at least two standard deviations (SDs) below normal sex-specific means in young persons. Data were compared with the 2008–2011 Korean National Health and Nutrition Examination Survey IV and V, a nationally representative survey conducted by the South Korean Ministry of Health and Welfare. To determine muscle strength, HGS was measured using a Jamar handheld dynamometer (Patterson Medical, Warrenville, IL, USA), the reliability of which has been previously established in community-dwelling older adults. Subjects were seated with shoulders at 0° adduction and neutral rotation, elbows at 90° flexion, and forearms in neutral position. Three trials were performed with a rest period of 1 minute between trials, and average values were recorded. Low muscle strength was defined as HGS values ≤30 kg in men and ≤20 kg in women. According to the recommendation of the EWGSOP,13 sarcopenia was defined when patients had both low MM (assessed by decreased SMMI lower than cutoff values) and low muscle strength (measured by low HGS values).

Measurement of dyspnea and quality of life

The mMRC dyspnea scale, which uses a 0–4 scoring system, was used to assess shortness of breath. To assess functional status and exercise capacity, we used patients’ 6MWD,15 which measures the distance that a patient can quickly walk along a corridor. Using these data, we measured patients’ BODE index. The BODE index ranges from 0 to 10 points, with higher scores indicating a greater risk of death in COPD.12 To evaluate quality of life, we used the Korean version of the CAT, as previously mentioned. This questionnaire consists of eight questions scored on a 0–5 scale.

Measurement of biomarkers of systemic inflammation

Venous blood was drawn from subjects, and circulating levels of biomarkers of systemic inflammation were measured using a high-sensitivity TNFα (hsTNFα) enzyme-linked immunosorbent assay kit (Quantikine®; R&D Systems, Minneapolis, MN, USA) and a chemiluminescence assay to measure IL-6 (Immulite 2000; Siemens, Munich, Germany).

Statistical analyses

Statistical analyses were performed using SPSS software (version 23.0; IBM, Armonk, NY, USA). All data are expressed as means ± SD or medians with interquartile ranges. The Kolmogorov–Smirnov test was used to analyze normality of distribution. For skewed data, including serum IL-6, natural log values were used. Continuous variables are described as means ± SD, and Student’s t-test was used for comparative analysis. Categorical variables were analyzed using χ2 and t-tests with 95% confidence intervals (CIs). Pearson’s correlation analysis was used to determine relationships among HGS, SMMI, and other clinical or inflammatory parameters. Multiple logistic regression analysis was performed to find significant determinants of sarcopenia. P<0.05 was deemed to indicate statistical significance.

Results

Patient characteristics

Table 1 shows 80 patients with stable COPD were included. Subjects were 68.4±8.9 (range 42–88) years old and 83.8% (67) were male. Sarcopenia was prevalent in 20 (25%) patients. Patients with sarcopenia were significantly older, showed lower BMI values, and had a higher percentage of cardiovascular disease. FFM, FFMI, SMM, and SMMI were markedly decreased in sarcopenic patients with BIA. HGS was also lower in patients with sarcopenia. There was no significant difference in COPD severity between patients with and without sarcopenia.
Table 1

Baseline characteristics of study subjects

VariableTotal(n=80)With sarcopenia(n=20, 25%)Without sarcopenia(n=60, 75%)P-value
Age (years)68.4±8.973.1±866.8±8.70.006
Male (%)67 (83.8)17 (85)50 (83.3)0.585
BMI (kg/m2)23.3±3.221.1±1.724.1±3.2<0.001
Comorbidities (%)
 Diabetes20 (25)6 (30)14 (23.3)0.374
 Hypertension38 (47.5)12 (60)26 (43.3)0.181
 Cardiovascular disease19 (23.8)10 (50)9 (15)0.003
 Tuberculosis26 (32.5)6 (30)20 (33.3)0.507
 Bronchiectasis/emphysema19 (23.8)3 (15)16 (26.7)0.228
Body composition and strength
 WHR0.92±0.040.90±0.160.91±0.050.464
 Fat mass (kg)15.7±5.313.8±3.616.4±5.60.056
 FMI (kg/m2)5.8±1.95.1±1.46±2.10.087
 Body fat (%)24.6±5.924.1±5.124.7±6.50.729
 FFM (kg)47.4±6.942.8±4.649±7.4<0.001
 FFMI (kg/m2)17.4±1.615.9±117.9±1.5<0.001
 SMM (kg)25.9±4.722.8±3.527±4.60.001
 SMMI (kg/m2)9.5±1.28.5±0.89.8±1.1<0.001
 HGS (kg)30.6±9.325.4±6.132.9±9.80.002
Pulmonary function*
 FEV1 (%)61.2±14.358±13.962.3±13.90.253
 FEV1/FVC (%)51±12.946.1±1352.6±12.80.05
GOLD stage, 2011 revised# (%)0.624
 A24 (30)4 (20)20 (33.3)
 B31 (38.8)9 (45)22 (36.7)
 C5 (6.2)2 (10)3 (5)
 D20 (25)5 (25)15 (25)

Notes:

Postbronchodilator;

According to 2011 GOLD revision. Data expressed as mean ± standard deviation or n (%).

Abbreviations: BMI, body mass index; WHR, waist:hip ratio; FMI, fat mass index; FFM, fat-free mass; FFMI, FFM index; SMM, skeletal muscle mass; SMMI, SMM index; HGS, handgrip strength; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; GOLD, Global Initiative for Chronic Obstructive Lung Disease.

Clinical outcomes associated with sarcopenia

Table 2 shows that compared with patients without sarcopenia, patients with sarcopenia had significantly more severe symptoms of dyspnea and higher mMRC scores, but CAT scores were not significantly different between the two groups. These patients exhibited poorer exercise tolerance, as indicated by the shorter 6MWD values. The median score in the BODE index was also significantly higher in patients with sarcopenia. There was no significant difference in the frequency of acute exacerbation of COPD between the two groups. Among inflammatory biomarkers, hsTNFα (P=0.013) and IL-6 (P=0.044) levels were significantly higher in patients with sarcopenia than patients without sarcopenia.
Table 2

Clinical outcomes according to presence or absence of sarcopenia

VariableWith sarcopenia(n=20, 25%)Without sarcopenia(n=60, 75%)P-value
mMRC score0.95±0.860.62±0.710.044
 0–115 (75%)51 (85%)0.059
 2–45 (25%)9 (15%)
CAT score15 (7–22)14 (8.75–21.25)0.678
 <106 (30)26 (43.3)0.216
 ≥1014 (70)34 (56.7)
BODE index3 (0–6)1 (0–4)0.001
6MWD (m)350.8±78389.3±66.90.042
Acute exacerbations ≥1/year (n)9 (45)22 (36.7)0.343
Inflammatory biomarkers
 IL-6*1.36±0.810.64±0.690.044
 hsTNFα*0.72±1.01−0.03±1.160.013

Notes:

Log-transformed value. All data expressed as mean ± SD or n (%) except for CAT score, BODE index, and number of acute exacerbation in the previous year (median with inter-quartile ranges).

Abbreviations: mMRC, modified Medical Research Council; CAT, COPD Assessment Test; 6MWD, 6-minute walk distance; hsTNFα, high-sensitivity TNFα; BODE, body (mass index), (airflow) obstruction, dyspnea, exercise (capacity); SD, standard deviation.

Correlations among HGS, SMM, and inflammatory biomarkers

As shown in Table 3, HGS showed positive correlations with FFMI, SMMI, and 6MWD and significant negative correlations with age, FMI, mMRC score, CAT scores, IL-6, and hsTNFα; SMMI positively correlated with BMI, HGS, FFMI, and FMI, and negatively correlated with BODE index, IL-6, and hsTNFα.
Table 3

Correlations among HGS, SMMI, and inflammatory biomarkers

VariableHGS
SMMI
CoefficientP-valueCoefficientP-value
Age−0.415<0.001−0.0740.527
BMI0.0010.9980.852<0.001
HGS10.427<0.001
FFMI0.3460.0020.99<0.001
FMI−0.3250.0040.2750.017
SMMI0.427<0.0011
FEV1*−0.1030.3670.0180.88
FEV1/FVC*−0.130.3670.0790.498
mMRC score−0.3460.002−0.0620.595
6MWD0.44<0.0010.0150.899
BODE index−0.2160.045−0.2570.026
CAT score−0.2360.048−0.1320.275
IL-6#−0.2730.018−0.2270.048
hsTNFα#−0.350.002−0.2460.044

Notes:

Postbronchodilator;

log-transformed value.

Abbreviations: BMI, body mass index; HGS, handgrip strength; FFMI, fat-free mass index; FMI, fat mass index; SMMI, skeletal muscle mass index; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; mMRC, modified Medical Research Council; 6MWD, 6-minute walk distance; CAT, COPD Assessment Test; hsTNFα, high-sensitivity TNFα; BODE, body (mass index), (airflow) obstruction, dyspnea, exercise (capacity).

Figure 1 shows HGS (r=−0.35, P=0.002) and SMMI (r=0.246, P=0.044) levels were very closely associated with hsTNFα as a systemic inflammatory parameter. In addition, values for the BODE index tended to correlate with HGS and SMMI. However, FEV116 did not correlate with HGS or SMMI in this study.
Figure 1

Correlation of handgrip strength and skeletal muscle mass index with high-sensitivity TNFα.

Abbreviation: TNFα, Tumor necrosis factor alpha.

Factors associated with sarcopenia in patients with COPD

As shown in Table 4, cardiovascular disease, a common comorbidity in patients with COPD, was associated with the presence of sarcopenia. GOLD classification (revised in 2011) was not associated with sarcopenia. As a systemic inflammatory biomarker, hsTNFα levels showed significant negative correlations with the presence of sarcopenia in our analysis. In multivariate analysis, significant determinants for the presence of sarcopenia in patients with stable COPD were old age (odds ratio [OR] 1.19, 95% CI 1.03–1.36), low BMI (OR 0.52, 95% CI 0.35–0.78), presence of previous cardiovascular disease (OR 4.66, 95% CI 1.01–18.31), and higher hsTNFα levels (OR 1.99, 95% CI 1.04–3.81).
Table 4

Factors associated with sarcopenia

VariableSarcopenia
Univariate analysis
Multivariate analysis
OR (95% CI) P-valueOR (95% CI)P-value
Age
 Years1.11 (1.03–1.22) 0.0091.19 (1.03–1.36)0.017
Sex
 Male vs female1.13 (0.28–4.6) 0.861
BMI
 kg/m20.63 (0.48–0.82) 0.0010.52 (0.35–0.78)0.001
Diabetes
 Presence1.41 (0.38–3.02) 0.552
Cardiovascular disease
 Presence5.66 (1.8–12.65) 0.0034.66 (1.01–18.31)0.048
GOLD stage
 A–B1
 C–D1.26 (0.43–3.67) 0.676
hsTNFα*1.81 (1.1–2.99) 0.0191.99 (1.04–3.81)0.038

Notes:

Log-transformed value. Multivariate logistic analysis was performed after adjusting for age, sex, BMI, and diabetes.

Abbreviations: OR, odds ratio; CI, confidence interval; BMI, body mass index; GOLD, Global Initiative for Chronic Obstructive Lung Disease; hsTNFα, high-sensitivity TNFα.

Discussion

To summarize, the prevalence of sarcopenia in South Korean patients with stable COPD was 25%, which was consistent with previous studies reporting prevalence rates of 20%–40%.17–19 Patients with sarcopenia tended to be older, have a higher percentage of cardiovascular comorbidity, more severe mMRC dyspnea scores, higher BODE index scores, and lower exercise tolerance in the 6MWD than those without sarcopenia. Sarcopenia in male and female patients was 25.4% (17 of 67) and 23.1% (three of 13). There was no difference in sex. The proportion of male sex among COPD patients was far higher in our study. However, it was not different from other South Korean COPD data. According to the representative South Korean COPD cohort data of nearly 1,000 COPD patients, 91.2% were male, higher than our data.20 MM measured by SMMI correlated with BMI and body-composition parameters, whereas muscle strength assessed by HGS significantly correlated with mMRC dyspnea scale, CAT score, and 6MWD as COPD clinical parameters. Low HGS and SMMI showed positive correlations with the BODE index. These results suggest sarcopenia is closely correlated with the BODE index, predicting higher risk of mortality. Consistent with our findings, Swallow et al reported that muscle strength is important in patient prognosis.21 A recent study of patients with stable COPD using prospective multi-center data also found that HGS correlated significantly with mortality.22 Therefore, HGS might provide critical prognostic information for patients with COPD. In addition, the presence of sarcopenia was highly associated with levels of systemic inflammation. The mechanisms by which patients with COPD develop systemic inflammation are currently unknown. The presence of systemic inflammation, however, is closely associated with complications that affect prognosis, such as weight loss,23,24 cachexia,25,26 and cardiovascular disease.27,28 In a review of inflammatory markers in patients with COPD, CRP, fibrinogen, leukocytes, TNFα, IL-6, and IL-8 levels were significantly elevated in patients with COPD compared with healthy controls.8 In this study, we assessed correlations of sarcopenia with the systemic inflammatory biomarkers IL-6 and hsTNFα. Muscle strength assessed by HGS and MM measured by SMMI showed significant correlations with levels of IL-6 and hsTNFα. In multivariate analysis, higher hsTNFα was a significant determinant for the presence of sarcopenia. The strength of this study was that most of patients in our study had milder COPD severity (GOLD A/B, 68.8%) and all patients had stable status, not exacerbated, and significant correlations of HGS and SMMI with levels of systemic inflammatory biomarkers is a noteworthy result. In the elderly and patients with COPD, physical inactivity is a key factor in the development of sarcopenia and a predictor of mortality and disability.29 The causes and prevalence of systemic inflammation and the mechanisms by which it leads to muscle wasting in COPD patients are uncertain. Previous studies have suggested that severe muscle wasting can lead to cachexia during systemic inflammation.24,30 We found that various factors were associated with sarcopenia, including age, BMI, and systemic inflammation. COPD severity, however, was not associated with the presence or absence of sarcopenia in this study, and the frequency of acute exacerbations of COPD was not different between the two groups. Considering the clinical complexity of COPD, however, we propose that multiple biomarkers are required to characterize pathogenic factors and clinical outcomes in this disease.31 There are several limitations to our study. We utilized a cross-sectional design, the study population was small, and recruitment was limited to outpatient clinics at a single tertiary hospital. Sample composition in terms of disease severity according to GOLD stage and FEV1 was not well balanced.

Conclusion

Nearly a quarter of South Korean patients with stable COPD have sarcopenia, and sarcopenic patients presented with more severe dyspnea, showed lower exercise tolerance, and predicted poor prognosis. In addition, sarcopenia was highly associated with levels of systemic inflammation. The presence of systemic inflammation was a main determinant of sarcopenia in a stable COPD population.
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Review 3.  Age-related and disease-related muscle loss: the effect of diabetes, obesity, and other diseases.

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Journal:  Eur Respir J       Date:  2009-05       Impact factor: 16.671

9.  Evidence for a relation between metabolic derangements and increased levels of inflammatory mediators in a subgroup of patients with chronic obstructive pulmonary disease.

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10.  Airway and systemic inflammation and decline in lung function in patients with COPD.

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1.  Body composition and sarcopenia in patients with chronic obstructive pulmonary disease.

Authors:  Tatiana Munhoz da Rocha Lemos Costa; Fabio Marcelo Costa; Thaísa Hoffman Jonasson; Carolina Aguiar Moreira; César Luiz Boguszewski; Victória Zeghbi Cochenski Borba
Journal:  Endocrine       Date:  2018-02-05       Impact factor: 3.633

Review 2.  Long-Term Outcome of Chronic Obstructive Pulmonary Disease: A Review.

Authors:  Yong Suk Jo
Journal:  Tuberc Respir Dis (Seoul)       Date:  2022-07-13

Review 3.  Integrating Mechanisms of Exacerbated Atrophy and Other Adverse Skeletal Muscle Impact in COPD.

Authors:  Tanja Taivassalo; Russell T Hepple
Journal:  Front Physiol       Date:  2022-06-03       Impact factor: 4.755

4.  Association Between Anthropometric Indices and Skeletal-Muscle Atrophy in Chinese Patients with Stable Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study.

Authors:  Yanxia Han; Zhenyun Wu; Qian Zhao; Bo Jiang; Xiaolang Miao; Xiangmin Lu; Hongying Qian; Meie Niu
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2022-10-11

5.  Sarcopenia is a Novel Predictor of the Need for Rescue Therapy in Hospitalized Ulcerative Colitis Patients.

Authors:  Kelly C Cushing; Hamed Kordbacheh; Michael S Gee; Avinash Kambadakone; Ashwin N Ananthakrishnan
Journal:  J Crohns Colitis       Date:  2018-08-29       Impact factor: 9.071

6.  Metabolomic profiling of anaerobic and aerobic energy metabolic pathways in chronic obstructive pulmonary disease.

Authors:  Mingshan Xue; Yifeng Zeng; Runpei Lin; Hui-Qi Qu; Teng Zhang; Xiaohua Douglas Zhang; Yueting Liang; Yingjie Zhen; Hao Chen; Zhifeng Huang; Haisheng Hu; Peiyan Zheng; Hakon Hakonarson; Luqian Zhou; Baoqing Sun
Journal:  Exp Biol Med (Maywood)       Date:  2021-05-06

7.  Sarcopenia Is an Independent Risk Factor for NAFLD in COPD: A Nationwide Survey (KNHANES 2008-2011).

Authors:  Kyung Soo Hong; Min Cheol Kim; June Hong Ahn
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2020-05-07

Review 8.  Food Pyramid for Subjects with Chronic Obstructive Pulmonary Diseases.

Authors:  Mariangela Rondanelli; Milena Anna Faliva; Gabriella Peroni; Vittoria Infantino; Clara Gasparri; Giancarlo Iannello; Simone Perna; Tariq AbdulKarim Alalwan; Salwa Al-Thawadi; Angelo Guido Corsico
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2020-06-19

9.  Relationship between skeletal muscle mass and lung function in Korean adults without clinically apparent lung disease.

Authors:  Chul-Hyun Park; Youbin Yi; Jong Geol Do; Yong-Taek Lee; Kyung Jae Yoon
Journal:  Medicine (Baltimore)       Date:  2018-09       Impact factor: 1.817

10.  Low alanine aminotransferase as a risk factor for chronic obstructive pulmonary disease in males.

Authors:  Yong Jun Choi; Do Sun Kwon; Taehee Kim; Jae Hwa Cho; Hyung Jung Kim; Min Kwang Byun; Hye Jung Park
Journal:  Sci Rep       Date:  2021-07-21       Impact factor: 4.379

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