Fine Particulate Matter Constituents, Nitric Oxide ... - ACS Publications

Sep 15, 2015 - School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, & Key Lab of Health Technology Assessment...
0 downloads 0 Views 973KB Size
Subscriber access provided by - Access paid by the | UCSB Libraries

Article

Fine particulate matter constituents, nitric oxide synthase DNA methylation and exhaled nitric oxide Renjie Chen, Liping Qiao, Huichu Li, Yan Zhao, Yunhui Zhang, Wenxi Xu, Cuicui Wang, Hongli Wang, Zhuohui Zhao, Xiaohui Xu, Hui Hu, and Haidong Kan Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b02527 • Publication Date (Web): 15 Sep 2015 Downloaded from http://pubs.acs.org on September 17, 2015

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 34

Environmental Science & Technology

Fine particulate matter constituents, nitric nitric oxide synthase DNA methylation and exhaled nitric oxide

Renjie Chen,†‡¶ Liping Qiao,§¶ Huichu Li,† Yan Zhao,† Yunhui Zhang,† Wenxi Xu,



Cuicui Wang,† Hongli Wang,

§

Zhuohui Zhao,† Xiaohui Xu,⊥ Hui Hu,#

Haidong Kan†‡*



School of Public Health, Key Lab of Public Health Safety of the Ministry of

Education, & Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China ‡

Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention

(LAP3), Fudan University, Shanghai, China §

State Environmental Protection Key Lab of the Formation and Prevention of

Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China ∥

Huangpu District Center for Disease Control and Prevention, Shanghai,

China ⊥

Department of Epidemiology & Biostatistics, Texas A&M School of Public

Health, Texas, USA. #

Department of epidemiology, College of Public Health and Health

Professionals, College of Medicine, University of Florida, Gainesville, Florida, USA. 1

ACS Paragon Plus Environment

Environmental Science & Technology



Page 2 of 34

Renjie Chen and Liping Qiao contributed equally to this work.

*Corresponding

author:

Tel/fax:

+86

(21)

54237908;

e-mail:

[email protected]; mail: P.O. Box 249, 130 Dong-An Road, Shanghai 200032, China.

2

ACS Paragon Plus Environment

Page 3 of 34

Environmental Science & Technology

1

ABSTRACT (199 words)

2

It remains unknown how fine particulate matter (PM2.5) constituents affect

3

differently the fractional concentration of exhaled nitric oxide (FeNO, a

4

biomarker of airway inflammation) and the DNA methylation of its encoding

5

gene (NOS2A). We aimed to investigate the short-term effects of PM2.5

6

constituents on NOS2A methylation and FeNO. We designed a longitudinal

7

study among chronic obstructive pulmonary disease (COPD) patients with 6

8

repeated health measurements in Shanghai, China. We applied linear

9

mixed-effect models to evaluate the associations. We observed that the

10

inverse association between PM2.5 and methylation at position 1 was limited

11

within 24 hours, and the positive association between PM2.5 and FeNO was

12

the strongest at lag 1 day. Organic carbon, element carbon, NO3- and NH4+

13

were robustly and significantly associated with decreased methylation and

14

elevated FeNO. An interquartile range increase in total PM2.5 and the four

15

constituents was associated with decreases of 1.19, 1.63, 1.62, 1.17 and 1.14

16

in

17

13.30%,16.93%, 8.97%, 18.26% and 11.42% in FeNO, respectively. Our

18

results indicated that organic carbon, element carbon, NO3- and NH4+ might be

19

mainly responsible for the effects of PM2.5 on the decreased NOS2A DNA

20

methylation and elevated FeNO in COPD patients.

21

Key words: fine particulate matter; constituent; DNA methylation; airway

22

inflammation

percent

methylation

of

NOS2A,

respectively,

3

ACS Paragon Plus Environment

and

increases

of

Environmental Science & Technology

23

Main text (3973 words)

24

INTRODUCTION

25

A large number of epidemiological studies have reported the hazardous

26

respiratory effects of short-term exposure to fine particulate matter

27

(aerodynamic diameter less than 2.5 micrometer, PM2.5) air pollution, including

28

increased risks of respiratory mortality and hospitalization.1 Elevated

29

inflammation in the respiratory tract is one of the key mechanisms involved in

30

the development of PM2.5-related outcomes.2 As a well-known noninvasive

31

biomarker for assessing airway inflammation, fractional concentration of

32

exhaled nitric oxide (FeNO) has been positively linked to an exposure to PM2.5

33

in recent human studies.2-5 These findings suggest that FeNO is a useful

34

intermediary phenotype in the pathophysiological process of airway

35

inflammation triggered by PM2.5.3

36

The underlying mechanisms linking PM2.5 and FeNO are not fully

37

characterized. There is increasing evidence that epigenetic alternations,

38

typically DNA methylation, can change the expression and function of a gene

39

under exogenous stimuli without changing in its DNA sequence.6 Inducible

40

nitric oxide synthase (iNOS; encoded by nitric oxide synthase isoform 2A

41

[NOS2A], Genbank accession number AF017634) is the major enzyme

42

responsible for nitric oxide synthesis in the respiratory tract.7 Hypomethylation

43

in the promoter of NOS2A gene was previously shown to be inversely related

44

to iNOS.8, 9 Several prior studies have revealed a potential downward influence 4

ACS Paragon Plus Environment

Page 4 of 34

Page 5 of 34

Environmental Science & Technology

45

of PM2.5 on the promoter DNA methylation of NOS2A,3, 10, 11 but the time-lag

46

patterns of PM2.5, NOS2A methylation and FeNO are largely unclear.

47

Furthermore, PM2.5 has a very complex chemical composition, which raises

48

the question of how these constituents affect differently the levels of NOS2A

49

DNA methylation and FeNO. One investigation in the Boston area Normative

50

Aging Study evaluated the association between two components (black carbon

51

and sulfate) and global DNA methylation.6 However, this knowledge remains

52

quite limited. Therefore, we aimed to investigate the short-term effects of PM2.5

53

constituents on the DNA methylation of NOS2A promoter and FeNO in

54

Shanghai, a Chinese city with high PM2.5 levels. We tested these hypotheses

55

in a panel of chronic obstructive pulmonary disease (COPD) patients because

56

respiratory inflammation plays an important role in the development and

57

exacerbation of this disease.

58 59

MATERIALS AND METHODS

60

Design and population. population. This is a longitudinal panel study with repeated

61

measurements on the exposure and health. We initially recruited 30 retired

62

COPD patients from a central urban community in Shanghai with a total area

63

of 1.9 km2. All COPD diagnoses were confirmed by physicians before they

64

were finally included in this study. To reduce the influence of respiratory

65

medication on our results, we only included the stable patients with

66

mild-to-moderate COPD in this study according to the classification of Global 5

ACS Paragon Plus Environment

Environmental Science & Technology

67

Initiative for Chronic Obstructive Lung Disease based on the baseline test of

68

spirometry.12 We excluded those who were current active or passive smokers

69

(living with a current smoker); former smokers (quit smoking for at least 3

70

years); consumed any alcohol; or had severe comorbidities or inflammatory

71

diseases. To reduce the inherent seasonal variations of FeNO and DNA methylation

72 73

13,

six weekly follow-up visits were scheduled from May 27th to July 5th, 2014.

74

To fully capture the variations in the exposure and biomarkers, we arranged

75

health examinations on various weekdays (i.e., Tuesday, Thursday, and

76

Saturday). For each patient, physical examinations were scheduled at the

77

same time (1:30 p.m. to 2:30 p.m.) on the same day of the week in order to

78

control for possible circadian rhythm and day-of-week effects. Data on

79

individual demographic and medical characteristics, such as age, gender,

80

height, weight, education attainment, income, medication use, duration of

81

COPD and chronic comorbidities, were collected during the baseline visit.

82

Study subjects were asked to record any use of medications, acute

83

exacerbation of COPD, and whether they went out of the central urban areas

84

during the study period. The Institutional Review Board in the School of Public

85

Health at Fudan University approved the study protocol. We obtained written

86

consent forms from all subjects.

87

FeNO measurements. measurements. All physical examinations were conducted at the

88

Community Health Center. We measured FeNO levels using a portable NIOX 6

ACS Paragon Plus Environment

Page 6 of 34

Page 7 of 34

Environmental Science & Technology

89

MINO machine (Aerocrine AB, Solna, Sweden) according to standardized

90

procedures by the American Thoracic Society and the European Respiratory

91

Society. A maximum of 5 repeated tests with 5 minutes rest between testes

92

were allowed for subjects who could not complete the test at the first time.

93

Foods, beverages, and intense exercises were not allowed at least within one

94

hour before the FeNO measurements.

95

Collection of buccal samples. Buccal samples were collected directly after the

96

FeNO test. Specifically, the subjects were asked to rinse the mouth using

97

purified water. They were provided with two tooth-brushes and instructed to

98

brush the teeth using the first one. Then, they were instructed to moderately

99

brush the bilateral buccal mucosa 20 times at each side with the second

100

toothbrush. The brush was then placed in a container that was filled with 10-ml

101

phosphate buffer solution (Recipe: NaCl 137mmol/L, KCl 2.7mmol/L, Na2HPO4

102

10 mmol/L and KH2PO4 4.2mmol/L). At last, patients swished liquid (10 ml)

103

throughout their mouths and expelled the fluid into the container. Buccal-cell

104

suspensions were immediately centrifuged at 1,000 r/min in the laboratory,

105

and the pellets were stored frozen at –80°C until used for DNA extraction.

106

DNA methylation. Genomic DNA was extracted using the QIAmp DNA Mini Kit

107

(Qiagen, Hilden, Germany) according to the manufacturer’s instructions.

108

Purified DNA was quantified using a ND1000 spectrophotometer (Nanodrop,

109

Wilmington, DE, USA) and about 300 ng DNA was bisulfite modified using the

110

EZ Methylation Gold-Kit (Zymo Research, Orange, CA, USA). Final elution 7

ACS Paragon Plus Environment

Environmental Science & Technology

111

was performed with a 10 μl M-Elution Buffer.

112

We examined three CpG loci located in NOS2A according to previous

113

studies. To be specific, positions 1 and 2 were in a non-CpG island region of

114

the promoter because the promoter was previously shown to be inversely

115

related to iNOS.9,

116

between exon 1 and exon 2.10 We performed DNA methylation analyses using

117

a bisulfite-PCR and pyrosequencing assay. We evaluated the levels of DNA

118

methylation at 2 loci (position 1 and 2) in the non-CpG island regions of

119

NOS2A promoter, which have been negatively associated with PM2.5 exposure

120

in previous studies.10, 14 The detailed method, location of the gene promoter,

121

amplified regions, and CpG sites that were evaluated have been published

122

previously.10 Methylation level of each CpG dinucleotide was expressed as

123

methylated cytosines over the sum of methylated and unmethylated cytosines,

124

i.e., the percentage of 5-methylcytosine (%5mC). Each sample was tested in

125

triplicate and the average was used for statistical analysis. Ten controls were

126

included in every pyrosequencing run. To ensure that pyrosequencing was

127

sequencing the correct pattern, two wells were filled with oligonucleotide with

128

known sequence. To verify bisulfite conversion efficiency, built-in controls were

129

used in every assay. Moreover, a human unmethylated (0%) standard and fully

130

methylated (100%) standard were used as sample controls.

131

Environmental data. Real-time concentrations of PM2.5 and its constituents

132

were measured by a fixed-site monitor located on the rooftop of a five-story

10

Position 3 was located in a non-CpG island region

8

ACS Paragon Plus Environment

Page 8 of 34

Page 9 of 34

Environmental Science & Technology

133

building (about 15 m high above the ground) at Shanghai Academy of

134

Environmental Sciences, which was about 4 km away from the community

135

where the subjects resided. Both the sites were not in direct vicinity of major

136

sources of air pollution including main roads. The mass concentration of PM2.5

137

was measured by an online particulate monitor (FH 62 C14 series, Thermo

138

Fisher Scientific Inc.) using beta attenuation techniques equipped with a

139

verified PM2.5 cyclone. The carbonaceous concentrations [i.e., organic carbon

140

(OC) and elemental carbon (EC)] in PM2.5 were measured by a

141

semicontinuous OC/EC analyzer (model RT-4, Sunset Laboratory Inc.)

142

equipped with a PM2.5 cyclone and an upstream parallel-plate organic denuder

143

(Sunset Laboratory Inc.). The concentrations of 8 major water-soluble

144

inorganic ions in PM2.5 (Cl−, NO3−, SO42−, NH4+, Na+, K+, Mg2+, Ca2+) were

145

measured by a commercial instrument for online monitoring of aerosols and

146

gases (MARGA, model ADI 2080, Applikon Analytical B.V.). The principle and

147

operation of this instrument has been given in detail elsewhere15,

148

obtained daily mean temperature and mean relative humidity from Shanghai

149

Meteorological Bureau to allow for controlling for the confounding effects of

150

weather conditions.

151

Statistical analyses. Before statistical analyses, FeNO levels were natural

152

log-transformed because they were not normally distributed, but such

153

transformation was not required for the NOS2A promoter methylation because

154

the data were normally distributed. Environmental and individual data were 9

ACS Paragon Plus Environment

16.

We

Environmental Science & Technology

155

merged by the time of physical examinations (rounded to the integer hour).

156

We applied the linear mixed-effect model to evaluate the FeNO-PM2.5

157

association and methylation-PM2.5 association.11 In the basic model, PM2.5 and

158

its components were incorporated as the fixed-effect terms one at a time; a

159

random intercept for each patient was added to account for correlations among

160

multiple repeated measurements collected per person. We also included

161

several covariates as fixed-effect terms: (1) an indicator variable of “week” of

162

physical examinations to exclude any unknown weekly time trends in the levels

163

of FeNO and DNA methylation; (2) an indicator variable of “day of the week” to

164

exclude any variations of the response variables in one week; (3) the moving

165

average of mean temperature and relative humidity on the present day and

166

previous 3 days to control for the confounding effects of weather conditions 17;

167

and (4) individual characteristics including age, gender, body mass index,

168

education, duration of COPD and chronic comorbidities.

169

In addition to the above basic single-constituent model, we also built a

170

“constituent-PM2.5 adjustment model” after controlling for the confounding

171

effects of total PM2.5 mass, as well as a “constituent-residual model” after

172

accounting for the collinearity between a constituent and total PM2.5.18 For the

173

third model, we firstly obtained the residual of each constituent by establishing

174

a linear regression model between total PM2.5 and a constituent, and then

175

introduced the residual into the basic model replacing the individual

176

constituents. The constituent residual can be interpreted as a crude measure 10

ACS Paragon Plus Environment

Page 10 of 34

Page 11 of 34

Environmental Science & Technology

177

of the “independent” contribution of each constituent to the effects of PM2.5

178

after excluding its collinearity of the remaining constituents.19

179

In order to fully investigate the time-lag patterns for the effects of PM2.5, we

180

examined the above models using multiple periods preceding the time of

181

physical examinations, i.e., single lags of 0–6 hour (h), 7–12 h, 13–24 h, 0–24 h

182

(0 d), 25–48 h (1 d), 2 d and 3–7 d.

183

As an additional analysis, we included a multiplicative interaction term for

184

PM2.5 or its constituent and methylation in single-pollutant model or each

185

single-constituent models to examine whether the association between PM2.5

186

(or its constituents) and FeNO can be modified by NOS2A methylation.3

187

The statistical tests were two-sided, and values of P