Decreased lung function is associated with elevated ferritin but not iron or transferrin saturation in 42,927 healthy Korean men: A cross-sectional study

Jonghoo Lee; Hye kyeong Park; Min-Jung Kwon; Soo-Youn Ham; Joon Mo Kim; Si-Young Lim; Jae-Uk Song

doi:10.1371/journal.pone.0231057

. 2020 Apr 2;15(4):e0231057. doi: 10.1371/journal.pone.0231057

Decreased lung function is associated with elevated ferritin but not iron or transferrin saturation in 42,927 healthy Korean men: A cross-sectional study

Jonghoo Lee ^1,^#, Hye kyeong Park ^2,^#, Min-Jung Kwon ³, Soo-Youn Ham ⁴, Joon Mo Kim ⁵, Si-Young Lim ⁶, Jae-Uk Song ^6,^*

Editor: Yu Ru Kou⁷

PMCID: PMC7117746 PMID: 32240239

Abstract

Objectives

Though elevated ferritin level and decreased lung function both predispose people to cardio-metabolic disease, few reports have investigated the association between them. Furthermore, it remains unclear whether the association reflects a change in iron stores or an epiphenomenon reflecting metabolic stress. Therefore, we looked for possible associations between ferritin, iron, and transferrin saturation (TSAT) and lung function to clarify the role of iron-related parameters in healthy men.

Methods

We conducted a cohort study of 42,927 healthy Korean men (mean age: 38.6 years). Percent predicted forced expiratory volume in one second (FEV1%) and forced vital capacity (FVC%) were categorized into quartiles. Adjusted odds ratios (aORs) and 95% confidence intervals (using the highest quartile as reference) were calculated for hyperferritinemia, high iron, and high TSAT after controlling for potential confounders.

Results

The median ferritin level was 199.8 (141.5–275.6) ng/mL. The prevalence of hyperferritinemia (defined as >300 ng/mL) was 19.3%. Subjects with hyperferritinemia had lower FEV1% and FVC% than those with normal ferritin level with a slight difference, but those were statistically significant (99.22% vs.99.61% for FEV1%, p = 0.015 and 98.43% vs. 98.87% for FVC, p = 0.001). However, FEV1/FVC ratio was not significantly different between groups (P = 0.797). Compared with the highest quartile, the aORs for hyperferritinemia across decreasing quartiles were 1.081 (1.005–1.163), 1.100 (1.007–1.200), and 1.140 (1.053–1.233) for FEV1% (p for trend = 0.007) and 1.094 (1.018–1.176), 1.101 (1.021–1.188), and 1.150 (1.056–1.252) for FVC% (p for trend = 0.001). However, neither FEV1% nor FVC% was associated with iron or TSAT.

Conclusions

Hyperferritinemia was associated with decreased lung function in healthy Korean men, but iron and TSAT were not. Longitudinal follow-up studies are required to validate our findings.

Introduction

Iron is essential for multiple metabolic processes, but it is hazardous in excess amounts because its ability to catalyze the generation of reactive oxygen species can cause oxidative stress and damage cellular membranes [1]. Ferritin is a specialized iron storage protein that regulates body iron homeostasis and reflects iron stores in the body. Ferritin also can become elevated in the presence of oxidative stress and inflammation irrespective of iron status and can contribute to various clinical diseases, especially pulmonary and cardio-metabolic diseases [2,3]. Moreover, decreased lung function is associated with oxidative stress and systemic inflammation [4] and increased risk of insulin resistance, diabetes, and cardiovascular disease [5]. This suggests that decreased lung function could be associated with elevated serum ferritin level in pathological conditions.

Even in healthy subjects, airway epithelial cells could be exposed to oxidative stress and inflammation because of ambient air pollution aerosols, which recently have increased rapidly as a consequence of regional urbanization and industrialization [6]. Air pollution particulate matter (PM) contains transition metals such as iron (usually most abundant), which can be mobilized from the PM to lung epithelial cells and disrupt iron homeostasis both in the lung and systemically [7,8]. Iron overabundance relative to metabolic needs inside lung epithelial cells can result in ferritin release from damaged cells, which could result in elevated serum ferritin concentration and loss of lung function under normal physiological conditions [6–8].

Nevertheless, epidemiological evidence to support that hypothesis is scarce. To date, only four reports have investigated a potential association between ferritin and lung function [9–12]; two of them found a positive association [9,10], and the other two found no association [11,12]. However, these previous studies were not conducted only in healthy subjects. Recent studies have continuously shown that pulmonary [2] and cardio-metabolic diseases [13–18] are a recognized complication of excess iron accumulation, and such patients are prone to poor lung function [2,5]. This suggests that inclusion of patients with clinical disease could distort the magnitude of association between lung function and ferritin. Thus, the exact nature of the relationship between ferritin and lung function, if one exists, remains unclear. It also remains unclear whether the previous results reflect a relationship between lung function and a recognized marker of iron status or an epiphenomenon in which an increased ferritin level reflects overall inflammation. Therefore, we investigated the relationships between lung function and ferritin and lung function and other biomarkers of iron metabolism, including transferrin saturation (TSAT), in healthy Korean men.

Materials and methods

Study design and population

This study began with data from 189,154 individuals who underwent a comprehensive health examination at Kangbuk Samsung Hospital Health Screening Centers in 2015. Initially, we extracted 188,596 participants with a recorded serum ferritin level and spirometry data. We excluded 85,455 participants who had a ventilation disorder (pure restriction: forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) [FEV1/FVC] ≥ 0.7 and FVC < 80% predicted; pure obstruction: FEV1/FVC < 0.7 and FVC ≥80% predicted and mixed ventilation disorder: FEV1/FVC < 0.7 and FVC < 80% predicted) [19] and self-reported history of disease or were currently receiving medication for any disease to 1) test our hypothesis with robustness, 2) yield more meaningful results, and 3) minimize potential confounders. Specific details of comorbidities were unavailable because the medical history questionnaire required only yes/no responses. We also excluded 11,942 subjects with missing medical history data or data about smoking habits or alcohol consumption. Because some subjects had more than more than one exclusion criterion, 91,199 subjects were ultimately eligible for initial inclusion in the study. The reference range for serum ferritin is usually from 30 to 300 ng/mL in men and from 15 to 200 ng/mL in women. These ranges seem to vary across reference populations and according to age and sex, which are the most important determinants of serum ferritin [20]. There has been no consensus on criteria for hyperferritinemia. Our cohort consisted of mostly middle aged Asians with higher socioeconomic and education levels and urban habitation with the highest annual PM concentrations in the world. Thus, these characteristics can contribute to more increase in the amount of mobilized iron especially in men than women in our cohort [8,21–26]. The large difference in serum ferritin level between men and women can contribute to much higher lifetime iron stores in men than in women. Therefore, the prevalence of hyperferrtinemia can be markedly different between men and women. Accordingly, we excluded women due to the small proportion (451, 0.9%) with hyperferritinemia, defined as > 200 ng/mL, leaving too few women for us to obtain statistically valid results. Thus, we decided to analyze the data from 42,927 men (Fig 1)

Fig 1 — BA = bronchial asthma; COPD = chronic obstructive pulmonary disease; HBsAg = hepatitis B virus surface antigen; HCV = hepatitis C virus.

The study was approved by the Institutional Review Board of Kangbuk Samsung Hospital, which waived the requirement for informed consent because we retrospectively accessed a de-identified database for our analyses.

Anthropometric and laboratory measurements

Data on demographic characteristics, history of smoking and alcohol use, medical history, current regular use of medications, and any clinical symptoms were collected through a self-administered questionnaire. Smoking habits were classified as follows: non-smokers, ex-smokers (no current smoking but regular smoking in the past), and current smokers (at least one cigarette per day). Alcohol history was considered positive if the subject had used alcohol in the past, even if they had stopped drinking.

Physical characteristics and serum biochemical parameters were measured by trained nurses, as previously reported [27,28]. Obesity was defined as Body mass index (BMI) ≥25 kg/m² [29]. Insulin resistance was assessed using the homeostasis model assessment of insulin resistance (HOMA-IR) equation: fasting blood insulin (μU/ml) × fasting blood glucose (mmol/l)/22.5 [30]. Serum iron concentration was measured using an automatic chemistry analyzer (Cobas 8000 c702; Roche Diagnostics, Tokyo, Japan) and a colorimetric assay. The serum ferritin was determined using an electrochemiluminescence immunoassay (Cobas 8000 e602; Roche Diagnostics) based on the sandwich principle. We defined subjects with ferritin > 300 ng/mL, TSAT > 50%, and iron > 175 μg/dL as having hyperferritinemia, high TSAT, and high iron, respectively [20,31]. The Laboratory Medicine Department at Kangbuk Samsung Hospital has been accredited and participates annually in inspections and surveys by the Korean Association of Quality Assurance for Clinical Laboratories.

Lung function measurement

Spirometry was performed as recommended by the American Thoracic Society [32] using the Vmax22 system (Sensor-Medics, Yorba Linda, CA). A bronchodilator was not administered prior to spirometry. The highest forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) values from three or more tests with acceptable curves were used for further analyses. The predicted values for FEV1 and FVC were calculated from equations to obtain in a representative Korean population sample [33]. To calculate the predicted FVC% and predicted FEV1%, we divided the measured value (L) by the predicted value (L) and converted the quotient into a percentage. Subjects were divided into quartiles of FVC% and FEV1%.

Statistical analyses

Continuous variables are described as the mean ± standard deviation or median and interquartile range, and categorical variables are expressed as number and percentage. The normality of variables was assessed with the Kolmogorov-Smirnov test. The baseline data stratified by upper normal limit values for biomarkers of iron metabolism and quartiles of ventilator function were compared using t-tests or Mann–Whitney U tests for two-group comparisons and one-way analysis of variance or Kruskal-Wallis tests for comparisons among quartiles. Chi-square tests or Fisher’s exact tests were used for categorical variables.

To analyze the significance of differences between subjects stratified by upper normal limit values for biomarkers of iron metabolism, all covariates were transformed into categorical variables: high or low and with or without. Chi-square tests or Fisher’s exact tests were used to assess the significance of differences between dichotomous variables.

Binary logistic regression was used to assess the association between FVC% and FEV1% quartiles and above the upper normal limit values for biomarkers of iron metabolism: model 1 was adjusted for age, BMI, and MBP; model 2 was adjusted as in model 1 plus smoking and alcohol; model 3 was adjusted as in model 2 plus variables with a p value<0.05 in the univariate analyses. Because FVC (L) and FEV1 (L) were strongly correlated (r = 0.947, p<0.001), these parameters were assessed separately to avoid confounding effects. The strength of associations was estimated using odds ratios (ORs) and 95% confidence intervals (CIs). All tests were two-sided, and a p value <0.05 was considered statistically significant. Data were analyzed using IBM SPSS Statistics 19.0 (IBM, Armonk, NY, USA).

Results

Table 1 compares the baseline characteristics of the enrolled subjects between the groups with and without hyperferritinemia. The mean age was 38.6 years. The median ferritin level was 199.3 (141.5–275.5) ng/mL, and the prevalence of hyperferritinemia was 19.3%. Comparison of clinical variables between the two groups showed small, but significant difference in age, smoking habit, alcohol intake, liver function, CRP, blood pressure and a variety of metabolic parameters, including BMI, fasting glucose, and HbA1c. Compared with the normal ferritin group, subjects in the hyperferritinemia group had lower values of spirometry with a narrow margin, although those were statistically significant. However, the difference in FEV1 (L)/FVC (L) between the groups was not statistically significant (p = 0.797). Conventional cardio-metabolic parameters (glucose, HbA1c, total cholesterol, triglycerides, LDL-cholesterol, insulin, HOMA-IR, and hsCRP) were adversely affected in subjects with hyperferritinemia compared with subjects with normal ferritin (Table 2).

Table 1. Comparison of the demographic and clinical characteristics of the study subjects.

	All subjects (n = 42,927)	Normal ferritin (ferritin ≤300 ng/mL) (n = 34,743, 80.7%)	Hyperferritinemia (ferritin >300 ng/mL) (n = 8,184, 19.3%)
Age (years) ^*	38.6 ± 7.0	38.7 ± 7.0	38.1 ± 6.7
19–30	5,267 (12.3)	4,281 (12.3)	986 (12.0)
31–40	20,981 (48.9)	16,691 (48.0)	4,290 (52.4)
41–50	14,369 (33.5)	11,821 (34.0)	2,548 (31.1)
51–60	2164 (5.0)	1,823 (5.2)	341 (4.2)
≥61	146 (0.3)	127 (0.4)	19 (0.2)
BMI (kg/m²) ^*	24.3 ± 2.7	24.1 ± 2.7	25.2 ± 2.9
Smoking status^†
Non-smoker	16,953 (39.5)	13,831 (39.8)	3,122 (38.1)
Former smoker	13,745 (32.0)	11,031 (31.8)	2,714 (33.2)
Current smoker	12,229 (28.5)	9,881 (28.4)	2,348 (28.7)
No alcohol drinking^*	5,109 (11.9)	4,390 (12.6)	719 (8.8)
Total cholesterol (mg/dL)^*	194 ± 30	193 ± 30	200 ± 32
Triglycerides (mg/dl)^*	106 (76–150)	102 (74–143)	124 (88–178)
LDL-C (mg/dl)^*	128 ± 29	127 ± 28	133 ± 30
Total bilirubin (mg/dL) (n = 42,926)^*	0.9 ± 0.4	0.9 ± 0.4	1.0 ± 0.4
ALT (U/L) (n = 42,925)^*	21 (18–25)	20 (17–24)	23 (19–30)
Serum creatinine (mg/dL)	0.9 ± 0.1	0.9 ± 0.1	0.9 ± 0.1
Fasting glucose (mg/dl)^*	96 ± 11	95 ± 9	98 ± 16
Insulin (μIU/ml) (n = 42,871)^*	5.6 (3.9–8.0)	5.4 (3.8–7.7)	6.4 (4.4–9.3)
HOMA-IR (n = 42,871)^*	1.31 (0.89–1.93)	1.27 (0.86–1.84)	1.53 (1.02–2.28)
HbA1c (%) (n = 42,921)^*	5.5 ± 0.4	5.5 ± 0.3	5.6 ± 0.5
hsCRP (mg/l) (n = 34,979)^*	0.05 (0.03–0.09)	0.05 (0.03–0.09)	0.06 (0.03–0.11)
SBP (mmHg) (n = 42,924)^*	114 ± 11	113 ± 10	116 ± 11
DBP (mmHg) (n = 42,924)^*	73 ± 9	73 ± 9	75 ± 9
MBP (mmHg) (n = 42,924)^*	87 ± 9	86 ± 9	88 ± 9
Spirometry values
FVC (L) ^†	4.734 ± 0.556	4.745 ± 0.545	4.730 ± 0.557
FEV1(L) ^†	3.884 ± 0.474	3.891 ± 0.467	3.879 ± 0.477
FEV1(L)/FVC(L) ratio	0.81 ± 0.02	0.81 ± 0.02	0.81 ± 0.02
FVC% predicted^†	98.62 ± 8.83	98.87 ± 8.88	98.43 ± 8.63
FEV1% predicted^†	99.54 ± 9.32	99.61 ± 9.36	99.22 ± 9.12
Ferritin level (ng/mL)^*	199.3 (141.5–275.5)	176.9 (129.9–227.2)	368.7 (329.0–434.2)
Iron (μg/dL) (n = 35,890)	129 (104–156)	129 (104–157)	129 (105–154)
Transferrin saturation (%) (n = 34,873)^†	43 (34–53)	43 (34–53)	43 (35–53)

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Continuous variables are expressed as mean ± standard deviation or median and interquartile range. Categorical variables are described as number and percentage. We recorded subject numbers with available clinical parameters. Unless otherwise indicated, the available subject number was 42,927.

*p<0.001 compared with hyperferritinemia;

^†p<0.05 compared with hyperferritinemia.

ALT = alanine aminotransferase; BMI = body mass index; DBP = diastolic blood pressure; FVC% predicted = percent predicted forced vital capacity; FEV1% predicted = percent predicted forced expiratory volume in 1s; HbA1c = hemoglobin A1c; HOMA-IR = homeostasis model assessment of insulin resistance; hsCRP = high-sensitivity C-reactive protein; LDL = low-density lipoprotein; MBP = mean blood pressure; SBP = systolic blood pressure.

MBP = diastolic BP + (average systolic BP—average diastolic BP)/3.

Table 2. Comparison of parameters between groups with and without hyperferritinemia.

Parameters	Overall subjects (n = 42,927)		p value
Parameters	Normal ferritin (n = 34,743)	Hyperferritinemia (n = 8,184)	p value
Age (>39 years)	15,723 (45.3)	3,341 (40.8)	<0.001
BMI (≥25 kg/m²)	11,880 (34.2)	3,989 (48.7)	<0.001
Non-smokers	13,830 (39.8)	3,122 (38.1)	0.006
No alcohol use	4,390 (12.6)	719 (8.8)	<0.001
Hypercholesterolemia (≥220 mg/dL)	6,055 (17.4)	1,967 (24.0)	<0.001
Hypertriglyceridemia (≥250 mg/dL)	1,473 (4.2)	826 (10.1)	<0.001
High LDL cholesterol (≥159 mg/dL)	4,458 (12.8)	1,531 (18.7)	<0.001
Elevated bilirubin (>1.9 mg/dL) (n = 42,926)	578 (1.7)	216 (2.6)	<0.001
Elevated ALT (>40 U/L) (n = 42,925)	940 (2.7)	802 (9.8)	<0.001
Elevated creatinine (>1.2 mg/dL)	1,158 (3.3)	309 (3.8)	0.047
Hyperglycemia at fasting (>100 mg/dL)	8,674 (25.0)	2,664 (32.6)	<0.001
Elevated HbA1c (≥6.5%) (n = 42,921)	211 (0.6)	195 (2.4)	<0.001
Elevated insulin (>25μIU/ml) (n = 42,871)	66 (0.2)	44 (0.5)	<0.001
Elevated HOMA-IR (>1.31) (n = 42,871)	16,522 (47.6)	4,852 (59.3)	<0.001
Elevated hsCRP (>0.5 mg/dL) (n = 34,979)	522 (1.8)	177 (2.7)	<0.001
MBP (≥87 mmHg) (n = 42,924)	14,578 (42.0)	4,238 (51.8)	<0.001
Quartile for FVC% predicted			0.018
Q1 (≤92%, n = 10,539, 24.6%)	8,517 (24.5)	2,022 (24.7)
Q2 (93–97%, n = 9,203, 21.4%)	7,350 (21.2)	1,853 (22.6)
Q3 (98–104%, n = 11,702, 27.3%)	9,489 (27.3)	2,213 (27.0)
Q4 (≥105%, n = 11,483, 26.8%)	9,387 (27.0)	2,096 (25.6)
Quartile for FEV1% predicted			<0.001
Q1 (≤93%, n = 10,875, 25.3%)	8,764(25.2)	2,111 (25.8)
Q2 (94–98%, n = 8,943, 20.8%)	7,126 (20.5)	1,817 (22.2)
Q3 (99–105%, n = 11,627, 27.1%)	9,426 (27.1)	2,201 (26.9)
Q4 (≥106%, n = 11,482, 26.8%)	9,427 (27.1)	2,055 (25.1)

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Hyperferritinemia was defined as serum ferritin level > 300 ng/mL. Data are presented as number of subjects with percentage in parentheses. Continuous variables were transformed into categorical variables using median or mean cut-off values or upper normal limit values for the univariate analyses.

ALT = alanine aminotransferase; BMI = body mass index; FVC% predicted = percent predicted forced vital capacity; FEV1% predicted = percent predicted forced expiratory volume in 1s; HbA1c = hemoglobin A1c; HOMA-IR = homeostasis model assessment of insulin resistance; hsCRP = high-sensitivity C-reactive protein; LDL = low-density lipoprotein; MBP = mean blood pressure.

MBP = diastolic BP + (average systolic BP—average diastolic BP)/3.

A comparison of clinical characteristics between subjects with and without high iron or TSAT is shown in Table 3. Subjects with high iron and TSAT were more likely than others to drink and smoke with a slight difference. However, both high iron and TSAT were inversely associated with hsCRP and metabolic values, including BMI, HbA1c, insulin, and HOMA-IR, although insulin was only related to TSAT. Compared with lowest quartiles of lung function, the prevalence of high iron or TSAT was not significantly different in accordance with an increase in lung function quartile, except for the prevalence of high TSAT according to quartile of FVC%.

Table 3. Univariate analyses to identify factors predictive of high iron and transferrin saturation.

Parameters	Iron (n = 35,890)			Transferrin saturation (n = 34,873)
Parameters	Low or normal iron (≤175 μg/dL) (n = 30,934)	High iron (>175 μg/dL) (n = 4,956)	p value	Low or normal TSAT (≤ 50%) (n = 24,378)	High TSAT (>50%) (n = 10,495)	p value
Age (≥38 years)	14,328 (46.3)	2,402 (48.5)	0.005	11,095(45.5)	4,980 (47.5)	0.001
BMI (>25 kg/m²)	11,534 (37.3)	1,743 (35.2)	0.004	9,400 (38.6)	3,489 (33.2)	<0.001
Non-smoker	12,948 (41.9)	1,512 (30.5)	<0.001	10,2296 (42.2)	3,826 (36.5)	<0.001
Non-alcohol use	3,797 (12.3)	425 (8.6)	<0.001	2,984 (12.2)	1,094 (10.4)	<0.001
Hypercholesterolemia (≥220 mg/dL)	5,614 (18.1)	903 (18.2)	0.903	4,630 (19.0)	1,652 (15.7)	<0.001
Hypertriglyceridemia (≥250 mg/dL)	1,637 (5.3)	233 (4.7)	0.082	1,419 (5.8)	383 (3.6)	<0.001
High LDL cholesterol (≥159 mg/dL)	4,243 (13.7)	614 (12.4)	0.011	3,515 (14.4)	1,147 (10.9)	<0.001
Elevated bilirubin (>1.9 mg/dL)	470 (1.5)	215 (4.3)	<0.001	328 (1.3)	341 (3.2)	<0.001
Elevated ALT (>40 U/L)	1,209 (3.9)	253 (5.1)	<0.001	1,013 (4.2)	397 (3.8)	0.105
Elevated creatinine (>1.2 mg/dL)	1.011 (3.3)	199 (4.0)	0.007	794 (3.3)	359 (3.4)	0.433
Hyperglycemia at fasting (≥100 mg/dl)	7,814 (25.3)	1,313 (26.5)	0.064	6,309 (25.9)	2,482 (23.6)	<0.001
Elevated HbA1c (≥6.5%)	286 (0.9)	31 (0.6)	0.037	243 (1.0)	55 (0.5)	<0.001
Elevated insulin (>25 μIU/ml)	80 (0.3)	7 (0.1)	0.119	74 (0.3)	1.0 (0.1)	<0.001
Elevated HOMA-IR (>1.31)	15,624 (50.5)	2,250 (45.4)	<0.001	12,803 (52.6)	4,557 (43.4)	<0.001
Elevated hsCRP (>0.5 mg/l)	688 (2.3)	11 (0.2)	<0.001	633 (2.7)	44 (0.4)	<0.001
MBP (≥86)	14,415 (46.6)	2,488 (50.2)	<0.001	11,559 (47.4)	4,798 (45.7)	0.004
Quartile of FVC% predicted			0.097			0.011
Q1 (≤92%)	7,552 (24.4)	1,167 (23.5)		5,965 (24.5)	2,473 (23.6)
Q2 (93–97%)	6,648 (21.5)	1,030 (20.8)		5,292 (21.7)	2,187 (20.8)
Q3 (98–104%)	8,376 (27.1)	1,399 (28.2)		6,556 (26.9)	2,939 (28.0)
Q4 (≥105%)	8,358 (27.0)	1,360 (27.4)		6,565 (26.9)	2,896 (27.6)
Quartile of FEV1% predicted			0.387			0.061
Q1 (≤93%)	7,801 (25.2)	1,243 (25.1)		6,152 (25.2)	2,594 (24.7)
Q2 (92–98%)	6,384 (20.6)	1,019 (20.6)		5,088 (20.9)	2,120 (20.0)
Q3 (99–105%)	8,436 (27.3)	1,305 (26.3)		6,585 (27.0)	2,879 (27.4)
Q4 (≥106%)	8,313 (26.9)	1,389 (28.0)		6,553 (26.9)	2,902 (27.7)

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High iron and high transferrin saturation were defined as an iron level > 175 μg/dL and transferrin saturation > 50%, respectively. Data are presented as the number of subjects with percentage in parenthesis. Continuous variables were transformed into categorical variables using median or mean cut-off values or upper normal limit values for the univariate analyses.

MBP = diastolic BP + (average systolic BP—average diastolic BP)/3.

We analyzed the associations between lung function and prevalence of hyperferritinemia, high iron, and high TSAT to investigate whether lung function was independently associated with ferritin and other biomarkers of iron metabolism (Table 4 and Fig 2). Compared with the highest quartile (the reference group) of FVC%, the aORs for hyperferritinemia across the decreasing quartile of lung function were 1.094 (1.018–1.176), 1.101 (1.021–1.188), and 1.150 (1.056–1.252), respectively (p for trend = 0.001). Similar results were observed across FEV1% quartiles (p for trend = 0.007). The aORs for high TSAT are lower for subjects with lower FVC% according to model 1 and model 2. However, there was no significant relationship between quartiles of lung function and high iron in model 1 and model 2. Additionally, neither high iron nor TSAT was significantly associated with FEV1% or FVC% in model 3.

Table 4. Multiple logistic regression analysis of the odds of hyperferritinemia, high transferrin saturation, and high iron by quartile of lung function.

	Model 1			Model 2			Model 3
	OR (95% CI)	p value	p for trend	OR (95% CI)	p value	p for trend	OR (95% CI)	p value	p for trend
Hyperferritinemia (n = 42,927)
Quartile of FVC% predicted			<0.001			<0.001			0.001
Q1 (≤92%, n = 10,539, 24.6%)	1.145 (1.062–1.234)	<0.001		1.157 (1.073–1.247)	<0.001		1.150 (1.056–1.252)	0.001
Q2 (93–97%, n = 9,203, 21.4%)	1.137 (1.064–1.216)	<0.001		1.146 (1.072–1.226)	<0.001		1.101 (1.021–1.188)	0.013
Q3 (98–104%, n = 11,702, 27.3%)	1.087 (1.019–1.159)	0.011		1.090 (1.023–1.163)	0.008		1.094 (1.018–1.176)	0.015
Q4 (≥105%, n = 11,483, 26.8%)	1			1			1
Quartile of FEV1% predicted			<0.001			<0.001			0.007
Q1 (≤93%, n = 10,875, 25.3%)	1.164 (1.085–1.248)	<0.001		1.167 (1.088–1.251)	<0.001		1.140 (1.053–1.233)	0.001
Q2 (94–98%, n = 8,943, 20.8%)	1.133 (1.049–1.223)	0.001		1.138 (1.054–1.229)	0.001		1.100 (1.007–1.200)	0.033
Q3 (99–105%, n = 11,627, 27.1%)	1.098 (1.030–1.171)	0.004		1.098 (1.030–1.171)	0.004		1.081 (1.005–1.163)	0.035
Q4 (≥106%, n = 11,482, 26.8%)	1			1			1
High iron (n = 37,873)
FVC% predicted			0.087			0.396			0.901
Q1: ≤92% (n = 8,719, 24.3%)	0.947 (0.871–1.031)	0.209		0.981 (0.901–1.067)	0.652		1.011 (0.927–1.103)	0.802
Q2: 93–97% (n = 7,678, 21.4%)	0.950(0.870–1.036)	0.247		0.974 (0.892–1.063)	0.549		0.995 (0.910–1.089)	0.916
Q3: 98–104% (n = 9,775, 27.2%)	1.024 (0.945–1.110)	0.566		1.036 (0.956–1.123)	0.391		1.052 (0.969–1.143)	0.229
Q4: ≥105% (n = 9.718, 27.1%)	1			1			1
FEV1% predicted			0.366			0.477			0.980
Q1: ≤93% (n = 9,044, 25.2%)	0.925 (0.853–1.004)	0.062		0.928 (0.855–1.007)	0.074		0.947 (0.871–1.030)	0.203
Q2:92–98% (n = 7,403, 20.6%)	0.953 (0.873–1.040)	0.277		0.960 (0.880–1.048)	0.363		0.994 (0.908–1.087)	0.887
Q3:99–105% (n = 9,741, 27.1%)	0.953 (0.877–1.035)	0.249		0.959 (0.883–1.042)	0.327		0.987 (0.907–1.075)	0.765
Q4: ≥106% (n = 9,702, 27.0%)	1			1			1
High TSAT (n = 38,818)
FVC% predicted			0.002			0.014			0.227
Q1: ≤92% (n = 8,438, 24.2%)	1.011 (0.950–1.075)	0.732		1.017 (0.956–1.082)	0.589		1.033 (0.970–1.101)	0.310
Q2: 93–97% (n = 7,479, 21.4%)	0.930 (0.870–0.994)	0.032		0.942 (0.882–1.007)	0.080		0.975 (0.911–1.044)	0.467
Q3: 98–104% (n = 9,495, 27.2%)	0.924 (0.866–0.985)	0.016		0.941 (0.882–1.003)	0.063		0.975 (0.913–1.042)	0.456
Q4: ≥105% (n = 9,461, 27.1%)	1			1			1
FEV1% predicted			0.062			0.083			0.772
Q1: ≤93% (n = 8,746, 25.1%)	0.986 (0.927–1.049)	0.659		0.988 (0.929–1.051)	0.707		1.006 (0.944–1.072)	0.857
Q2:92–98% (n = 7,208, 20.7%)	0.942 (0.881–1.007)	0.079		0.945 (0.884–1.011)	0.101		0.982 (0.917–1.052)	0.604
Q3:99–105% (n = 9,464, 27.1%)	0.952 (0.893–1.014)	0.125		0.955 (0.896–1.018)	0.158		0.997 (0.934–1.064)	0.930
Q4: ≥106% (n = 9,455, 27.1%)	1			1			1

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Model 1 was adjusted for age, BMI, and MBP. Model 2 was adjusted as in model 1 plus smoking and alcohol. Model 3 was adjusted as in model 2 plus variables with a P value < 0.05 in the univariate analyses (liver function test, lipid battery, hsCRP level, glucose level, insulin level, HbA1c level, and HOMA-IR).

CI = confidence interval; FVC% predicted = percent predicted forced vital capacity; FEV1% predicted = percent predicted forced expiratory volume in 1s; HbA1c = hemoglobin A1c; HOMA-IR = homeostasis model assessment of insulin resistance; hsCRP = high-sensitivity C-reactive protein; OR = odds ratio; TSAT = transferrin saturation.

Fig 2 — The aOR for hyperferritinemia increased with decreasing quartiles of FEV1% and FVC% (A) in a dose-response manner. The reference values were set as the highest quartile of FEV1% and FVC%. Neither high iron nor TSAT was significantly associated with FEV1% or FVC% (B and C). Models were adjusted for potential covariates and metabolic laboratory markers (age, BMI, mean blood pressure, alcohol intake, smoking, liver function test, lipid battery, hsCRP level, glucose level, insulin level, HbA1c level, and HOMA-IR). FVC% predicted = percent predicted forced vital capacity; FEV1% predicted = percent predicted forced expiratory volume in 1s; HbA1c = hemoglobin A1c; HOMA-IR = homeostasis model assessment of insulin resistance; hsCRP = high-sensitivity C-reactive protein; OR = odds ratio; TSAT = transferrin saturation.

Discussion

In this study, we demonstrated that hyperferritinemia is significantly associated with decreased FVC% and FEV1%, whereas iron and TSAT are not. To the best of our knowledge, this study is the first to describe an inverse association between lung function and hyperferritinemia.

Previously, four studies had evaluated the relationship between ferritin and lung function in the general population [9–12]. Contrary to our findings, a positive relationship between ferritin and lung function was found in two studies [9,10], although the other previous studies showed that lung function did not correlate with ferritin [11,12]. However, careful consideration is required when evaluating the relation between lung function and ferritin because various parameters, including inflammation markers and cardio-metabolic diseases, are associated with both ferritin level [3,10,13,14,16,24,34–36] and lung function [4,5,37,38]. Considering that, our study clearly differs from the previous studies [9–12]. The serum ferritin levels in this study were higher (199.3 ng/mL) than in the previous studies (36.4–129.3 ng/mL), possibly because of differences in age and sex distributions of the study participants. The median age of the enrolled subjects in this study was younger than in previous studies [9,10,12]. Furthermore, all the previous studies enrolled females, who represented more than half of the total number of subjects, in contrast to this study. Although serum ferritin decreases with age in males and increases with age in females, the factor with the greatest effect on the discrepant level of ferritin is sex [24,36]. Hormonal effects and increased iron loss can cause physiological differences in iron homeostasis and biomarker distributions between males and females. Consequently, sex segregation analyses are needed to yield meaningful results and minimize potential confounding factors. Moreover, the previous studies included subjects with cardio-metabolic diseases [9,12]. In Brigham’s study [11], about 16% of the subjects had a history of asthma, while subjects with FEV1/FVC < 0.7 were included in Lee et al.’s study (13.4%). [10] Because FEV1/FVC < 0.7 predominantly reflects obstruction of middle sized airways, it is possible that Lee et al.’s study [10] contained more subjects with functional and structural lung debilities than ours. Ghio’s study [9] evaluated the correlation between lung function and ferritin without adjusting for confounding factors, and two studies [10,11] adjusted for only a few variables, without adjusting for other relevant confounders that affect ferritin level [3,13,14,16] and lung function [4,5,37–39]. Failing to adjust for those confounders could have distorted the outcomes of the previous studies. We excluded subjects with overt cardio-metabolic and pulmonary diseases. Additionally, we adjusted for many relevant confounders associated with ferritin and lung function and examined only males. After fully adjusting for potential confounders, we found a robust negative association between hyperferritinemia and lung function in healthy men. These results indicate that healthy subjects with hyperferritinemia may have early perturbations of lung function. This finding is important. Reduced lung function is a marker of an individual’s increased susceptibility to COPD and a major risk factor for cardiovascular morbidity and mortality, which are potentially preventable diseases with significant health and economic impacts worldwide [40]. Further, reduced lung function is a powerful predictor of mortality [41]. Therefore, the current study is important, given the projected growing public health impact of lung function and outdoor air pollution [6].

The mixed results from the previous studies [9,10] and this study complicate a conclusion on whether ferritin may have a beneficial or noxious effect on lung function. The reasons for the mixed results are unclear. However, serum ferritin level in a different composition of study subjects might explain the disagreement. Actually, serum ferritin level in our study was about three times higher than those in previous studies. Interestingly, previous studies showed a threshold effect of ferritin with incident type 2 diabetes [42,43]. Like this, the biological effects of ferritin on lung function may also be attributed to a threshold effect in which the cohort including more individuals with low serum ferritin level showed a positive association [9,10] between lung function and ferritin level by enhancing detoxification of iron, and vice versa. There is a biologically plausible explanation for this relationship and our findings. Iron must bind to proteins to prevent tissue damage from free radical formation [1,3]. Ferritin is a key protein in iron homeostasis and presents a paradox. The capacity of ferritin to prevent iron’s pro-oxidant activity by oxidizing and sequestering the metal suggests that it might play an important role as an antioxidant within the range of homeostasis and be a marker of iron-related oxidative toxicity after disruption of iron homeostasis [1,3,8]. Consequently, a delicate homeostasis of iron is vitally important, perhaps more so in lung than in any other organs, given the compounded damage of ferritin and high local oxygen tensions in the lung. If exceeding the limit for cellular iron regulation irrespective of iron store regulation, ferritin released from damaged cells could result in elevated serum ferritin concentration, losing most of its iron and leaving free iron [3]. Free iron beyond what the body can adequately detoxify could accumulate both locally in the airway epithelium and systemically [7], causing subsequent oxidative damage [1,3], through superoxide generation and leading to permanent loss of lung function over time [4,44]. Thus, iron-related oxidative damage might be the link between hyperferritinemia and early perturbations in lung function. The biological effects of ferritin on lung function may be attributed to a threshold effect on protection from respiratory damage.

On the other hand, previous studies showed that serum iron was positively associated with lung function [9,11,12]. Brigham’s study [11] showed that higher ferritin was associated with a lower risk of asthma only in the reference range strongly correlated with iron storage (20–300 ng/ml) [45]. The question remains whether elevated serum iron has a protective or detrimental effect on the lungs. Lung inflammation in response to noxious inhalants could involve active repletion from serum iron [7]. Continually decreased iron seems to worsen hypoxemia, producing lung functional and structural debilities [46]. However, iron is potentially hazardous in the range that exceeds the iron-detoxification capacity of ferritin [1]. Therefore, tight regulation over iron metabolism is necessary to prevent both iron deficits and overloads. Perhaps only subjects with homeostatic ferritin level that counteracts free iron are protected against the decline in lung function caused by continuous exposure to oxidative stress. However, we observed a threshold effect above levels within the reference range for biomarkers of iron metabolism on the lung function. Unlike in previous studies [9,11,12], we found that high iron and TSAT were not significantly associated with lung function in the fully adjusted models that included inflammatory markers and cardio-metabolic risk factors. Similarly, several studies adjusting for various confounders showed that ferritin was an independent risk factor for cardio-metabolic diseases [13–18], whereas other biomarkers of iron metabolism were not always statistically significant, especially in men [13–17]. This reflects the possibility that ferritin could affect lung function and cardio-metabolic diseases regardless of a body’s iron status. Ferritin is not only a marker of body iron stores, but also an acute-phase reactant that can fluctuate in response to inflammatory mediators and metabolic stress [3]. Systemic inflammation could be an important mediator of hyperferritinemia [42,47] and decreased lung function [4]. However, the association of lung function with hyperferritinemia remained significant in the current study, even after adjusting for several other markers related to systemic inflammation, in line with previous studies [14,42]. The bioavailable iron is responsible for reactive oxygen species (oxidative stress) and IL-8 induction (inflammatory mediator) [8]. IL-8 is highly chemo-attractive for neutrophils, eosinophils, and T lymphocytes [48,49], in contrast to IL-6, which is the chief stimulator of CRP production. This might indicate that ferritin increases the risk of decline in lung function through metabolic oxidative stress other than systemic inflammation. Therefore, ferritin is a robust biomarker for lung function in our study population, but no associations were noted for other biomarkers of iron metabolism with lung function. These results lead us to postulate that the elevated ferritin levels seen with cardio-metabolic diseases and decreased lung function could result primarily from metabolic stress that reflects oxidative damage independent of iron stores.

Our study has several strengths and limitations. A major strength of our study is its large sample size, with subjects drawn from a healthy population without overt disease. Another strength is that we conducted analyses adjusting for various confounders that affect lung function and ferritin. This gave us sufficient statistical power and could be more relevant to healthy population with normal lung functions. However, it should be considered that it is possible to show statistical significance for small differences in the large sample sized studies. And, our study demonstrated modest association between hyperferritinemia and lung function parameters. There also have been discordant results on this issue among studies [9–12], although those were undertaken in populations where the serum ferritin level were lower than the current study. It is suggested that a variety of factors are likely to have more influence on lung function than ferritin in the real world, and vice versa. Therefore, we cannot exclude the possibility of some unmeasured or residual confounding factors in the association between ferritin and lung function. Furthermore, there has been no consensus on criteria for hyperferritinemia and, there could be debate about whether our definition of hyperferritinemia may be appropriate threshold for protection from respiratory damage. Even if our study with the large sample size demonstrated significant association between hyperferritinemia and lung function parameters, further prospective studies are needed to determine whether ferritin is an independent risk of lung function deterioration and what the threshold level is appropriate. Our study also had several limitations. First, we cannot infer causation due to the cross-sectional nature of our study. Therefore, further studies are needed to elucidate the precise mechanism underlying the phenomena we observed. Second, there is the possibility of selection bias in participant recruitment because the study participants were mostly middle-aged Korean men in an urban community who all received a health screening at a single university hospital. Therefore, our findings cannot be generalized to other populations or ethnic groups. Third, we measured biomarkers of iron metabolism, including ferritin, at a single time point. Therefore, we cannot exclude the possibility of intra-individual changes in those levels because ferritin varies widely within an individual's lifetime [36], and iron shows diurnal variation without changes in total body iron [50]. Fourth, the true incidence of pulmonary and cardio-metabolic diseases could have been underestimated in our study due to the questionnaire-based collection of medical histories. Some individuals with subclinical disease processes could have also be included, although we excluded subjects with overt medical diseases and ventilation pattern. Such inclusion might be significant, because the relationship between subclinical pulmonary and cardio-metabolic disease can contribute to a decline in lung function, especially among individuals with abnormal ferritin level. Finally, this study was not hospital-based. Lack of data on genetic and environmental variations that could have influenced our results, including daily dietary iron, is another potential limitation of this study. Additionally, lack of measurements of oxygen saturation and partial pressure of oxygen in the blood (PaO₂), which could affect iron metabolism [51], are also potential limitations, although we excluded those with any known evidence of clinical medical diseases including lung disease.

In conclusion, hyperferritinemia was independently associated with decreased lung function because of inflammatory mechanisms independent of iron stores. However, longitudinal follow-up studies and prospective interventional studies are needed to validate our findings.

Data Availability

Due to ethical restrictions imposed by the Institutional Review Board of Kangbuk Samsung Hospital, the patient data are not available for distribution outside of the Kangbuk Samsung Hospital. For additional information, please contact JiinAhn (Jiin57.ahn@samsung.com) or the Institutional Review Board of Kangbuk Samsung Hospital (contact information below). - Address: 29 Saemunan-ro, Jongno-Gu, Seoul, Korea (03181) - E-mail: irb. kbsmc@samsung.com - Telephone: 82-2-2001-1943, 1945 - Fax: 82-2-2001-1946

Funding Statement

The 2020 scientific promotion program funded by Jeju National University.

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PLoS One. doi: 10.1371/journal.pone.0231057.r001

Decision Letter 0

Iratxe Puebla

11 Nov 2019

PONE-D-19-26396

Decreased lung function is associated with elevated ferritin, but not iron or transferrin saturation in 47,981 healthy Korean men: a cross-sectional study

PLOS ONE

Dear Dr. Song,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The manuscript has been assessed by two reviewers; their comments are available below.

One of the reviewers is positive about the study but the second has raised some methodological concerns. The reviewer notes concerns about the exclusion of participants with any lung condition and about the exclusion of women from the sample, the reviewer recommend further analyses including the women population. The reviewer also notes concerns about the FVC and FEV1 results reported, and both reviewers recommend more in-depth discussion of related literature.

Could you please carefully revise the manuscript to address the concerns raised by the reviewers?

We would appreciate receiving your revised manuscript by Dec 24 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Iratxe Puebla

Senior Managing Editor, PLOS ONE

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1. We noticed you have some minor occurrence(s) of overlapping text with the following previous publication(s), which needs to be addressed:

https://doi.org/10.1371/journal.pone.0208736

https://doi.org/10.1111/resp.13370

https://doi.org/10.1080/14397595.2017.1285981

In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the Methods section. Further consideration is dependent on these concerns being addressed.

2. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Authors in this study conducted a cohort study of 47,981 healthy Korean men, and found hyperferritinemia was associated with decreased lung function in healthy Korean men, whereas iron and TSAT were not. In general, this finding is interesting and useful, even though longitudinal follow-up studies and prospective interventional studies are needed to validate it. It better to discuss the relationship between iron and oxygen concentration in discussion, as it was mentioned previously that different iron need under different oxygen concentration. (Cancer Lett. 2019 Nov 1;464:56-61.)

Reviewer #2: Overview

This study looks at the relationship of ferritin, iron and iron saturaturation in relationship to lung function and other parameters of systemic inflammation. The study population is ~47000 men representing ~25% of a large screening program from a single Korean hospital, after excluding all with history of any disease or taking any medication. Unlike other, population based, studies of this question which have looked at correlations to the spectrum of ferritin levels, the authors have chosen to focus on the likelihood of a ferritin level above the upper limit of normal (ULN). Women were excluded because <1% exceeded the chosen ULN. The results in relationship to lung function appear discordant with prior studies and potential reasons for this are discussed.

Major comments:

1.The study premise is that elevated ferritin is associated with systemic inflammation and pulmonary injury and thus may be associated with decreased lung function, in what would presumably be a pathologic process. However, the study population excluded those with any known evidence of lung disease so the lung function data available are nearly all within the normal range of a healthy population where most of the variation above and below the predicted value is considered to be random rather than pathologic. Certainly, some individuals with early disease processes will have low normal values, but this choice would seem to create a low signal to noise situation. The rationale for the choice to exclude even mild airflow limitation from the study population should be explained.

2.Since women are known to have different ferritin levels and behaviors (eg, with age) than men, it is unfortunate that this population was excluded by the choice to consider only hyper-ferritinemia rather than a median, mean or correlation to the range of values. Since this was essentially a normal, disease free population one might expect 2.5% to be above the ULN (assuming a 95% range and false positives at both ends) so the finding of <1% suggest the ULN chosen for women may be too high. Similarly, the finding of nearly 20% of these healthy men to be above the ULN (rather than the expected 2.5%) needs some discussion, starting with the source and derivation of these cut points (general population or “healthy” pop, smokers excluded or not, appropriate to Korean ethnicity?). An alternative analysis of “hyper” ferritin, that would allow inclusion of women, would be to divide the groups at the 80th %iles for men and women of the study population.

3.The FVC and FEV1 results are transposed between the results stated in the Abstract and those shown in Table 1. Whichever is correct, it would be very unusual in a near normal population to have a 20% difference (93% vs 113%) between the mean %predicted FEV1 and FVC. This would mean that the average FEV1/FVC ratio would have to be either very high or very low, but the reported value of 82 is normal, assuming that is the actual ratio (not %pred). Preferably, it could be reported as 0.82 to eliminate any potential uncertainty for the reader. It seems likely that there is an error in the formula or calculation of the predicted values (although it is recognized that, if the error is consistent, this would not affect the quartile analysis). It would be helpful to add the actual mean FVC and FEV1 values to Table 1, and the authors also might consider comparing these predictions to the North Asia data from the GLI-2012 predictions (Quanjer. Eur Respir J 2012; 40:1324-43).

(Although I cannot access Ms ref 17, the prediction equations reported in the Ms appear to be correct. Calculations for a 40yo, 170cm, 70kg male result in reasonable values for FVC 4.78, FEV1 3.97 for a ratio of 0.83, so for this example an FVC of 100%pred and an FEV1 of 100%pred would give a ratio of .83, but 93%-113%, either way, would be very different).

4.DISCUSSION. The discussion of the different findings between this study and Ms refs 5 and 6 should note that these population-based studies looked at lung function in relationship to the full range of ferritin values or to mean/median values, whereas this study looks at the likelihood of very high values. While it is reasonable to think that these two approaches might correlate, that is uncertain and should be discussed along with stating the rationale for the choice made for this study. This data could also be analysed in a fashion similar to ref 5 to make a more ‘apples to apples’ comparison.

5.CONCLUSION. The introduction proposes a dichotomy of hyper-ferritinemia as a marker of iron stores vs as a marker of systemic inflammation. The absence of an association of iron and iron saturation with lower lung function leads to the conclusion (p24 line 150) that the observed relationship of hyper-ferritinemia to lower lung function is “a result of inflammation”. However, Model 3 adjusted for several other markers of systemic inflammation which might be expected to eliminate the association, but instead only reduced the positive odds ratios modestly (21 and 30% for FEV1 and FVC). The implications of this deserves comment in Discussion.

Minor Comments:

Table 1 Ferritin level by quartiles for FEV1 shows units of ng/mL while for FVC and elsewhere mg/dL is used. Terminology should be consistent throughout the Ms, tables and figures.

Table 2 It appears that no exclusions were made based upon lung function data. <3% with FEV1/FVC <70 were included. No mention is made of possible early restrictive disease (which has also been associated with higher ferritin levels) in the study population. With a mean FVC of 92+/-10 %pred and a 1st quartile < 86%pred it is likely that some would meet a spirometric criteria for restriction, but as noted in comment 3 above the accuracy of those %pred values is uncertain.

p21 line 67 The sentence “Although a positive relationship between ferritin and lung function was found…” is accurate, but may not convey its meaning to the reader – could it mean a positive relationship with a decrement in lung function? (I pulled the ref to be sure.) Perhaps the sentence might begin “Contrary to our findings, a positive relationship…” or end explicitly “….two studies, with increased ferritin associated with higher lung function.”

p22 line 95 Since this study is not designed to show causality, it would be more accurate to state “whether ferritin may have a beneficial or noxious effect…”

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2020 Apr 2;15(4):e0231057. doi: 10.1371/journal.pone.0231057.r002

Author response to Decision Letter 0

21 Dec 2019

We already uploaded the file named "Response to Reviewers"

Actually our response is too long to respond in this area

Wolud you please refer to reference (as we attach PDF files) for your comment 3

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(67.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0231057.r003

Decision Letter 1

Yu Ru Kou

6 Feb 2020

PONE-D-19-26396R1

Manuscript ID: PONE-D-19-26396

Decreased lung function is associated with elevated ferritin, but not iron or transferrin saturation in 42,927 healthy Korean men: a cross-sectional study

PLOS ONE

Dear Dr. Song,

Specifically, the reviewer 2 still had some concerns that need to be adequately addressed. I hope the authors can effectively respond to these comments.

We would appreciate receiving your revised manuscript by Mar 22 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

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An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Yu Ru Kou, PhD

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

The authors have revised this manuscript carefully,and there are no question now.

Reviewer #2: The revised study has been modified by the exclusion of subjects with low measured lung function, just over 10% of the prior study group. A new source of reference equations has been chosen resulting in %predicted values which are much more reasonable than the prior report.

Specific Comments

P4 Study Design The criteria used for PFT exclusion should be stated

(eg, FVC <80%, FEV1<80%, FEV1/FVC <0.70).

P5 Lung Fxn measurement Thank you for changing the Reference data source (although I think there was also a calculation error in the prior version); the predicted values now look much more reasonable. The source is cited (and available online) so it is not necessary to include the equations in the Ms.

The last sentence re FEV1/FVC can be deleted here and stated earlier (prior comment).

Results With the large number of subjects it is possible to show statistical significance for very small differences. Whether or not these are clinically or physiologically important is another matter that should be addressed. This would be most appropriate in Discussion, but the presentation of results can also be tempered.

eg, “subjects in the hyperferritinemia group were more likely to be younger”, yet a mean age of 38.7 v 38.1, with wide overlap of SDs, is hardly compelling. Similarly, for smoking (~62% v 60%) and alcohol use (91.2 v 87.4%). The message might be how similar these exposures are despite the wide difference in ferritin levels. These results would be appropriately preceded by “Small but significant differences were seen….” or similar acknowledgement of the small magnitude.

More importantly, the differences in the primary comparison of lung function are also very small in both absolute terms (FVC 4.75 v 4.73; FEV1 3.89 v 3.88) and when adjusted for age and height by % predicted. The latter should be reported to at least one additional place so that rounding does not influence the apparent difference. It seems mathematically odd here that the FVC and FEV1 values shown for the combined groups match that of the smaller hyper- group rather than that of the normal group making up over 80% of the study population.

Rounding is also an issue for bilirubin and creatinine, where the reported numbers for the two groups appear identical, but for bilirubin the star indicates a highly significant difference.

The lower portion of Table 1 shows a slight inverse relationship of the ferritin levels vs FVC and FEV1 quartiles. This is seen in both the normal and hyper ferritin groups, contrary to the idea that there may be a threshold effect for ferritin to affect lung function. It is not clear what the significance test (“compared with hyperferritinemia”) means here; is there a difference in the relationship between the two?...and if so, which is stronger? For both FVC and FEV1, the % difference in ferritin level from quartile 1 to 4 is greater for the normal group, although the absolute differences are larger in the hyper- group.

Table 2

The % numbers in title are confusing and should be removed. They show the distribution between groups, while the similarly displayed % values in the table do not, but are based upon the total in each group.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

PLoS One. 2020 Apr 2;15(4):e0231057. doi: 10.1371/journal.pone.0231057.r004

Author response to Decision Letter 1

21 Feb 2020

TO THE COMMENTS OF THE REVIEWER 2.

The revised study has been modified by the exclusion of subjects with low measured lung function, just over 10% of the prior study group. A new source of reference equations has been chosen resulting in %predicted values which are much more reasonable than the prior report.

Specific comments:

C1. Study Design

The criteria used for PFT exclusion should be stated (eg, FVC <80%, FEV1<80%, FEV1/FVC< 0.70).

The last sentence re FEV1/FVC can be deleted here and stated earlier (prior comment).

R1.

We do appreciate the reviewer’s comment. We apologize for our carelessness and the lack of clarity.

As reviewer pointed out, we stated the criteria used for PFT exclusion in the manuscript as follows;

(from line 85 to line 86 on page 4 );

We excluded 85,455 participants who had a ventilation disorder on the basis of spirometric results [1]

�

We excluded 85,455 participants who had an impaired lung function (a ventilation disorder) (the subjects without normal lung function defined as forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) [FEV1/FVC] ≥ 0.7 and FVC ≥80% predicted) [2]

C2. Lung Fxn measurement

Thank you for changing the Reference data source (although I think there was also a calculation error in the prior version); the predicted values now look much more reasonable. The source is cited (and available online) so it is not necessary to include the equations in the Ms. The last sentence re FEV1/FVC can be deleted here and stated earlier (prior comment).

R2.

Thank you for your advice to improved our manuscript much more. As you recommended, we removed the reference equations in the manuscript. (from line 138 to line 139 on page 6)

And, we apologize for our carelessness. Thank you for pointing our mistakes.

We omitted last sentence in the lung function measurement section. (from line 143 on page 6)

C3. Results

C3-1.

With the large number of subjects it is possible to show statistical significance for very small differences. Whether or not these are clinically or physiologically important is another matter that should be addressed. This would be most appropriate in Discussion, but the presentation of results can also be tempered.

R3-1.

Thank you for your reasonable comments. The reviewer makes a very important point. We fully understand reviewer’s concern. We also agree that it could not be clinically meaningful, although it show statistical significance in a large study population. So, we need to tone the presentation of results down, as reviewer pointed out. We modified result section to reflect reviewer’s concern.

(from line 168 to line 172 on page 7 );

Compared with the normal ferritin group, subjects in the hyperferritinemia group were more likely to be younger, to have smoked, to drink alcohol, and have higher blood pressure. Serum ferritin level was negatively associated with a quartile increase in FVC% (p=0.001) and FEV1% (p<0.001), but the difference in FEV1 (L)/FVC (L) between the groups was not statistically significant (p=0.797).

�

When compared clinical variables between two groups, small but significant differences were seen in age, smoking habit, alcohol intake, liver function, CRP, blood pressure and a variety of metabolic parameters, including BMI, fasting glucose, and HbA1c. Compared with the normal ferritin group, subjects in the hyperferritinemia group were to have lower value of spirometry with a narrow margin, although those were statistically significant. However, the difference in FEV1 (L)/FVC (L) between the groups was not statistically significant (p=0.797).

(from line 176 on page 7 to line 180 on page 8 );

�

We also described reviewer’s concern in discussion section of the revised manuscripts as below;

(from line 340 to line 342 on page 26);

This gave us sufficient statistical power and could be more relevant to healthy population with normal lung functions.

�

C3-2.

It seems mathematically odd here that the FVC and FEV1 values shown for the combined groups match that of the smaller hyper- group rather than that of the normal group making up over 80% of the study population.

R3-2.

We believe the odd FVC and FEV1 values in table 1 might be the rounding off the numbers to three decimal places, as you can see below table. Therefore, we reported the value of FVC and FEV1 to three decimal places to decrease the mathematical add.

All subjects (n=42,927) Normal ferritin Hyperferritinemia

(ferritin ≤300 ng/mL) (n=34,743, 80.7%) (ferritin >300 ng/mL) (n=8,184, 19.3%)

FVC (L) † 4.73±0.56 4.75±0.55 4.73±0.56

4.734±0.556 4.745±0.545 4.730±0.557

FEV1(L) † 3.88±0.47 3.89±0.47 3.88±0.48

3.884±0.474 3.891±0.467 3.879±0.477

FVC% predicted† 99 ± 9 99 ± 9 98 ± 9

98.62±8.83 98.87±8.88 98.43±8.63

FEV1% predicted† 100 ± 9 100 ± 9 99 ± 9

99.54±9.32 99.61±9.36 99.22±9.12

C3-3.

Rounding is also an issue for bilirubin and creatinine, where the reported numbers for the two groups appear identical, but for bilirubin the star indicates a highly significant difference.

R3-3.

And we apologize for our typo. Originally, the value of total bilirubin in hyperferritinemia group was 1.0 ± 0.4 in table 1. We changed the value of total bilirubin in table 1 as bellow;

All subjects (n=42,927) Normal ferritin Hyperferritinemia p value

(ferritin ≤300 ng/mL) (n=34,743, 80.7%) (ferritin >300 ng/mL) (n=8,184, 19.3%)

Total bilirubin (mg/dL) (n=47,980)* 0.9 ± 0.4 0.9 ± 0.4 0.9 ± 0.4 <0.001

Total bilirubin (mg/dL) (n=47,980)* 0.9 ± 0.4 0.9 ± 0.4 1.0 ± 0.4 <0.001

C4.

R4.

We apologize for the lack of clarity. We believe that wrong presentation for significance test could be a result of confusion. Serum ferritin level was decreased across increasing quartile of FVC% (p=0.001) and FEV1% (p<0.001) in all subjects, using Kruskal-Wallis tests. So, marks such as “†” and “*” did not mean significant difference between the two groups (normal ferritin vs. hyperferritinemia). Therefore, we had better remove the lower portion of Table 1 to avoid the confusion. We really appreciate that we had a chance to revise this. Interestingly, inverse relationship of the ferritin levels across increasing quartile of FVC% and FEV1% showed statistical significance in both two groups. Therefore, it seems to be contrary to the idea that there may be a threshold effect for ferritin to affect lung function, as you pointed out. We can’s fully explain the reasons for this. However, the median and mean level of ferritin in our subjects with normal ferritin level was 177ng/ml which was still much higher than Ghio’s study (mean: 74ng/ml) [3] and Lee’s study (median: 62.3 ng/mL) [4] showing a contrary effect for ferritin on the lung function to ours. Thus, the association between ferritin (not dichotomizing ferritin) and lung function might be depend on serum ferritin level of study subjects. Consequently, we still believed threshold effect or double-edged characteristics for ferritin on lung function which could be hypothesis that might explain mixed findings and different serum ferritin level among studies. However, unfortunately the accurate threshold level is not known and there has been no consensus on criteria for hyperfrritinemia till now. Therefore, there could be debate about whether our definition of hyperferritinemia may be appropriate threshold for protection from respiratory damage. We also do not thick that our definition of hyperferritinemia may be appropriate threshold value. We just selected this level, based on the usual upper normal limits of ferritin commonly used in the literature [7] and our center. Besides, careful consideration is required when interpretating the findings from the large sample sized studies, because it is possible to show statistical significance for small differences, as you pointed earlier. Slight inverse relationship of the ferritin levels vs FVC and FEV1 quartiles in the normal ferritin group could not be clinically meaningful, although it show statistical significance. Therefore, further prospective studies are needed to determine whether ferritin is an independent risk of lung function deterioration and what the threshold level is appropriate.

We remove the lower portion of Table 1 to avoid the confusion. Instead, we add some sentences on the our definition of hyperferritinemia and the uncertainty for appropriate threshold level, to reflect your concerns

(from line 342 on page 26);

�

This gave us sufficient statistical power and could be more relevant to healthy population with normal lung functions. However, it should be considered that it is possible to show statistical significance for small differences in the large sample sized studies. And, our study demonstrated modest association between hyperferritinemia and lung function parameters. There also have been discordant results on this issue among studies [3-6], although those were undertaken in populations where the serum ferritin level were lower than the current study. It is suggested that a variety of factors are likely to have more influence on lung function than ferritin in the real world, and vice versa. Therefore, we cannot exclude the possibility of some unmeasured or residual confounding factors in the association between ferritin and lung function. Furthermore, there has been no consensus on criteria for hyperfrritinemia and, there could be debate about whether our definition of hyperferritinemia may be appropriate threshold for protection from respiratory damage. Even if our study with the large sample size demonstrated significant association between hyperferritinemia and lung function parameters, further prospective studies are needed to determine whether ferritin is an independent risk of lung function deterioration and what the threshold level is appropriate. Our study also had several limitations.

We removed below sentence from line 306 on page 24 to avoid overlapping.

“although the accurate threshold level is not known.”

C5. Table 2

R5.

As you recommended, we removed the % numbers in title. And, we also removed the % numbers at title in table 3. Thank you for your advice.

And we apologize for our typo in table 3. The number of subjects with iron value was 35,890 not 34,873

References

1. (1995) Standardization of Spirometry, 1994 Update. American Thoracic Society. Am J Respir Crit Care Med 152: 1107-1136.

2. West JB (2013) GOLD Executive Summary. Am J Respir Crit Care Med 188: 1366-1367.

3. Ghio AJ, Hilborn ED (2017) Indices of iron homeostasis correlate with airway obstruction in an NHANES III cohort. Int J Chron Obstruct Pulmon Dis 12: 2075-2084.

4. Lee CH, Goag EK, Lee SH, Chung KS, Jung JY, Park MS, et al. (2016) Association of serum ferritin levels with smoking and lung function in the Korean adult population: analysis of the fourth and fifth Korean National Health and Nutrition Examination Survey. Int J Chron Obstruct Pulmon Dis 11: 3001-3006.

5. Brigham EP, McCormack MC, Takemoto CM, Matsui EC (2015) Iron status is associated with asthma and lung function in US women. PLoS One 10: e0117545.

6. McKeever TM, Lewis SA, Smit HA, Burney P, Cassano PA, Britton J (2008) A multivariate analysis of serum nutrient levels and lung function. Respir Res 9: 67.

7. Adams PC, Barton JC (2011) A diagnostic approach to hyperferritinemia with a non-elevated transferrin saturation. J Hepatol 55: 453-458.

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PLoS One. doi: 10.1371/journal.pone.0231057.r005

Decision Letter 2

Yu Ru Kou

5 Mar 2020

PONE-D-19-26396R2

Manuscript ID: PONE-D-19-26396

Decreased lung function is associated with elevated ferritin, but not iron or transferrin saturation in 42,927 healthy Korean men: a cross-sectional study

PLOS ONE

Dear Dr. Song,

The reviewer still had some minor comments regarding the presentation and grammar errors.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #2: Abstract

The FVC and FEV1 values are now more accurately stated in Table 1, but no change was made in the Abstract so that the rounded numbers indicate differences of 1% which is more than double the actual values of ~ 0.4%. These should be restated with the same values as in the table.

Study design

In describing the excluded subjects it would be more straightforward to state the exclusion (rather than inclusion) criteria, ie

…participants who had lung function impairment, defined as forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) [FEV1/FVC] < 0.7 and FVC < 80% predicted [19], …

Lung Function measurement

The deletion of the equations, requires proofreading for appropriate changes in the accompanying text, ie

delete “the following” and change : to .

Results

3rd and 4th sentences are awkwardly stated. Suggest:

Comparison of clinical variables between the two groups showed small, but significant, differences in age, …..

Compared with the normal ferritin group, subjects in the hyperferritinemia group had lower values of spirometry….

Discussion

p13 line 154 typo hyperferritinemia

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

PLoS One. 2020 Apr 2;15(4):e0231057. doi: 10.1371/journal.pone.0231057.r006

Author response to Decision Letter 2

10 Mar 2020

C1. Abstract

R1.

We do appreciate the reviewer’s comment. We apologize for our carelessness.

As reviewer pointed out, we restated with the values of predicted FVC and FEV1 to three decimal places as in the table 1, to avoid the confusion.

(from line 39 to line 40 on page 2 );

Subjects with hyperferritinemia had lower FEV1% and FVC% than those with normal ferritin level (99% vs.100% for FEV1%, p = 0.015 and 98% vs. 99% for FVC, p = 0.001).

�

Subjects with hyperferritinemia had lower FEV1% and FVC% than those with normal ferritin level with a slight difference, but those were statistically significant (99.22% vs.99.61% for FEV1%, p = 0.015 and 98.43% vs. 98.87% for FVC, p = 0.001).

C2. Study design

In describing the excluded subjects it would be more straightforward to state the exclusion (rather than inclusion) criteria, ie

…participants who had lung function impairment, defined as forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) [FEV1/FVC] < 0.7 and FVC < 80% predicted.

R2-A

We do appreciate the reviewer’s comment.

As reviewer pointed out, we stated the exclusion criteria rather than inclusion criteria in the manuscript as follows;

(from line 86 to line 89 on page 4 );

We excluded 85,455 participants who had an impaired lung function (the subjects without normal lung function defined as forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) [FEV1/FVC] ≥ 0.7 and FVC ≥80% predicted) [1]

�

We excluded 85,455 participants who had a ventilation disorder (pure restriction: forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) [FEV1/FVC] ≥ 0.7 and FVC < 80% predicted; pure obstruction: FEV1/FVC < 0.7 and FVC ≥80% predicted and mixed ventilation disorder: FEV1/FVC < 0.7 and FVC < 80% predicted) [1]

C3. Lung Function measurement

The deletion of the equations, requires proofreading for appropriate changes in the accompanying text, ie

delete “the following” and change : to

R3.

We apologize for our carelessness. Thank you for pointing our mistakes.

As you recommended, we removed “the following” and modified as follows;

And we modified reference because reference article was published officially.

(J Korean Med Sci. 2019 Dec 9; 34(47):e304)

(from line 139 to line 141 on page 6 );

The predicted values for FEV1 and FVC were calculated from the following equations obtained in a representative Korean population sample [2];

�

The predicted values for FEV1 and FVC were calculated from equations to obtain in a representative Korean population sample [2].

C4. Results

3rd and 4th sentences are awkwardly stated. Suggest:

Comparison of clinical variables between the two groups showed small, but significant, differences in age, …..

Compared with the normal ferritin group, subjects in the hyperferritinemia group had lower values of spirometry….

R4.

Thank you for your advice. We apologize for our awkward presentation.

As you recommended, we modified sentences as follows;

(from line 169 to line 173 on page 7 );

�

Comparison of clinical variables between the two groups showed small, but significant difference in age, smoking habit, alcohol intake, liver function, CRP, blood pressure and a variety of metabolic parameters, including BMI, fasting glucose, and HbA1c. Compared with the normal ferritin group, subjects in the hyperferritinemia group had lower values of spirometry with a narrow margin, although those were statistically significant.

C5. Discussion

p13 line 154 typo hyperferritinemia

R5.

We apologize for our carelessness and the lack of clarity Thank you for pointing our typo out.

We changed “hyperfrritinemia” into “hyperferritinemia” in discussion section (from line 348 on page 24 ).

Attachment

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Click here for additional data file.^{(20KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0231057.r007

Decision Letter 3

Yu Ru Kou

16 Mar 2020

Manuscript ID: PONE-D-19-26396

Decreased lung function is associated with elevated ferritin, but not iron or transferrin saturation in 42,927 healthy Korean men: a cross-sectional study

PONE-D-19-26396R3

Dear Dr. Song,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

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With kind regards,

Yu Ru Kou, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #2: Thank you for the revisions and corrections. I have no additional comments.

I have nothing more so say but must type 100 characters!@%$

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #2: No

PLoS One. doi: 10.1371/journal.pone.0231057.r008

Acceptance letter

Yu Ru Kou

18 Mar 2020

PONE-D-19-26396R3

Decreased lung function is associated with elevated ferritin but not iron or transferrin saturation in 42,927 healthy Korean men: A cross-sectional study

Dear Dr. Song:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Yu Ru Kou

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

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Data Availability Statement

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PERMALINK

Decreased lung function is associated with elevated ferritin but not iron or transferrin saturation in 42,927 healthy Korean men: A cross-sectional study

Jonghoo Lee

Hye kyeong Park

Min-Jung Kwon

Soo-Youn Ham

Joon Mo Kim

Si-Young Lim

Jae-Uk Song

Roles

Abstract

Objectives

Methods

Results

Conclusions

Introduction

Materials and methods

Study design and population

Fig 1. Flow chart of study participants.

Anthropometric and laboratory measurements

Lung function measurement

Statistical analyses

Results

Table 1. Comparison of the demographic and clinical characteristics of the study subjects.

Table 2. Comparison of parameters between groups with and without hyperferritinemia.

Table 3. Univariate analyses to identify factors predictive of high iron and transferrin saturation.

Table 4. Multiple logistic regression analysis of the odds of hyperferritinemia, high transferrin saturation, and high iron by quartile of lung function.

Fig 2. Multivariable-adjusted odds ratio (aOR) for high biomarkers of iron metabolism according to quartile of lung function.

Discussion

Data Availability

Funding Statement

References

Decision Letter 0

Iratxe Puebla

Roles

Author response to Decision Letter 0

Decision Letter 1

Yu Ru Kou

Roles

Author response to Decision Letter 1

Decision Letter 2

Yu Ru Kou

Roles

Author response to Decision Letter 2

Decision Letter 3

Yu Ru Kou

Roles

Acceptance letter

Yu Ru Kou

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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