Polymorphisms of Angiotensin Converting Enzyme and Nitric Oxide Synthase 3 Genes as Risk Factors of High-Altitude Pulmonary Edema: A Case-Control Study and Meta-Analysis

Qing-Qing Wang; Lei Yu; Guo-Rong Huang; Lu Zhang; Ya-Qiong Liu; Tai-Wu Wang; Hui Lin; Qian Ren; Ping Liu; Lan Huang; Jun Qin; Guo-Ming Wu; Qian-Ning Li; Ya-Fei Li; Hong-Yan Xiong

doi:10.1620/tjem.229.255

Abstract

High-altitude pulmonary edema (HAPE) is a non-cardiogenic type of pulmonary edema developing altitudes >2,500 m. Angiotensin converting enzyme (ACE) and nitric oxide synthase 3 (NOS3) play important roles in regulating pulmonary vascular tone. To assess associations between genetic variants in the ACE and NOS3 genes and HAPE risk, 27 HAPE patients and 108 matched controls were genotyped and analyzed. The indicated HAPE association of the NOS3 G894T (Glu298Asp) single nucleotide polymorphism (SNP), which may change NO production, was further evaluated by a meta-analysis of six studies involving 399 HAPE patients and 495 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were determined with fixed-effects models. Stratification analyses of ethnicity and geographic location were performed. Significant associations were observed for the dominant model in two ACE tag SNPs influencing serum ACE concentrations (rs8066114 polymorphism: GG+CG vs. CC; rs4461142 polymorphism: TT+CT vs. CC). Furthermore, Single-locus analysis indicated significantly different distributions of G allele frequency between the cases (29.63%) and controls (17.13%) for the ACE rs8066114 polymorphism. The case-control distributions of genotype frequencies and T allele frequency of NOS3 G894T (Glu298Asp) polymorphism were significantly higher in the cases than controls, and the NOS3 G894T (Glu298Asp) SNP showed elevated HAPE risk under the dominant model (TT+GT vs. GG). Meta-analysis showed overall association of NOS3 G894T SNP with HAPE risk under the allele contrast and dominant genetic models, which remained significant for Asians. In conclusion, ACE rs8066114 and rs4461142 and NOS3 rs1799983 (G894T) polymorphisms may be associated with increased HAPE risk in Asians.

Introduction

High-altitude pulmonary edema (HAPE) is a non-cardiogenic type of pulmonary edema that may develop in otherwise healthy individuals upon ascent to altitudes above 2500 m (Hultgren 1996). It has emerged as a significant health issue among travelers to mountainous and high plain regions, including individuals traveling for business purposes (such as soldiers, miners, and disaster relief workers) and pleasure (such as skiers and mountaineers). Although it is well known that HAPE can be avoided by slow ascent and resolved in the early stages by rapid descent, these two protective strategies are not always feasible (due to urgent situations or the condition going unrecognized). Thus, the rates of morbidity and mortality remain relatively high (Bärtsch et al. 1990, 1991). Epidemiologic studies have revealed that individuals under identical ascent conditions show different levels of susceptibility to HAPE (Maloney and Broeckel 2005). Many subsequent studies have investigated the individual characteristics of HAPE cases to identify susceptibility factors. A genetic component appears to be involved (Maclnnis et al. 2010), but the precise genes and their independent and interconnected roles in HAPE development remain to be elucidated.

A systematic review of the HAPE-related scientific and medical literature published between 1998 and 2011 showed that 23 genes and 85 corresponding polymorphisms have been identified as putative genetic susceptibility factors. Among those genes, the two most frequently reported are angiotensin-converting enzyme (ACE) and nitric oxide synthase 3 (NOS3). The ACE-encoded protein, angiotensin-converting enzyme, is produced by many organs, including the lung (Phillips et al. 1993) where it mediates the degradation of vasodilator bradykinin and catalyzes the conversion of inactive angiotensin I to active angiotensin II. Angiotensin II stimulates the release of aldosterone, which in turn induces water and sodium retention and conditions that are amenable to HAPE development. The endothelial NOS (eNOS), encoded by the NOS3 gene, plays an essential role in production of the NO gaseous hormone that is a critical mediator of several physiological functions, including maintenance of pulmonary vascular tone and adaptation to altitude-related hypoxia (Beall et al. 2012). Thus, it is possible that these genes (and their encoded proteins) play a key role in HAPE pathogenesis.

To explore this hypothesis, we conducted a case-control study of ACE and NOS3 gene variants and their potential association with HAPE risk in a Han Chinese population. Specifically, an Alu insertion/deletion (I/D) polymorphism consisting of presence or absence of a 278-bp long fragment (rs4340), the single nucleotide polymorphisms (SNPs) A240T (rs4291) and A2350G (rs4343), three tag SNPs of the ACE gene, and the NOS3 gene G894T (rs1799983) SNP were systematically investigated. Several previous case-controlled studies have analyzed the association of the NOS3 G894T SNP with HAPE (Droma et al. 2002; Weiss et al. 2003; Ahsan et al. 2004, 2006; Sun et al. 2010), but the findings have been contradictory, possibly due to inadequate sample sizes and limitations in the case-control selection. Therefore, we expanded our analysis of this polymorphism to include a meta-analysis of published data from both the English and Chinese literature and our own unpublished data to further assess the association of NOS3 G894T SNP with HAPE.

Materials and Methods

Subjects

The study protocol was approved by the Human Ethics Committee of the Third Military Medical University, and written informed consent was obtained from all study volunteers prior to participation. All procedures involving the human subjects were carried out in accordance with the recommendations of the Helsinki Declaration.

A total of 27 HAPE patients (HAPE-p) were enrolled as cases for the study, including 21 men and six women with a mean age of 34.70 ± 11.85 years. All subjects were recruited between July 2011 and August 2012 from the 22nd Hospital of the Chinese People’s Liberation Army, which is the largest hospital located in the city of Golmud (altitude 2,780-4,500 m) in Qinghai, China. This hospital is the primary treatment center for individuals suffering from high altitude disease in this region, known to travelers as the Gateway to Tibet. Any patients with previous history of cardiopulmonary diseases, as identified by self-reported medical history or upon full examination carried out after HAPE recovery, were excluded from study participation.

HAPE diagnosis was based on standard diagnostic criteria (Hultgren and Marticorena 1978), which included onset of typical symptoms at high altitude (i.e. serious hypoxemia indicated by cough and dyspnea at rest, absence of infection, presence of pulmonary rales and cyanosis) and therapeutic response to supplemental oxygen treatment and bed rest (i.e. resolution of all symptoms and signs within three days of treatment initiation). In all cases, HAPE was confirmed by chest radiographic findings of infiltrates consistent with pulmonary edema.

One hundred and eight controls were recruited to the study based on their HAPE resistance (HAPE-r) status. The control cohort consisted of 84 men and 24 women with a mean age of 34.70 ± 11.52 years. These individuals were selected according to a 4:1 case-matching scheme using the variables sex, age, tourist type (i.e. vacationers, workers or soldiers), method of ascent (i.e. speed and ambulation type), and intensity of labor at the high altitude (Fig. 1). All control subjects were non-natives of a high altitude environment who had not developed any symptoms or signs of HAPE or related illness after exposure to high altitude. The Lake Louise scoring worksheet was used to rule out any symptoms of acute mountain sickness (AMS) among the HAPE-r controls (Hackett and Hao 1992). Similar to the case selection procedure, history of or current cardiopulmonary disorders were cause for study exclusion.

All subjects in the case and control groups were Han Chinese, and underwent routine clinical examination. Physiological variables, including blood pressure (BP), arterial oxygen saturation (SaO₂), and pulse rate (PR), were measured after 10 min of rest in the supine position. BP was measured by a mercury sphygmomanometer. SaO₂and PR were measured using a Finger-Pulse Oximeter 503 (Criticare Systems Inc., Waukesha, WI, USA). Body weight and height were measured and used to calculate the body mass index (BMI). Approximately 5 mL of venous blood was collected from each subject into Ethylene Diamine Tetraacetic Acid (EDTA) tubes. The whole blood was immediately separated into blood cells and plasma by centrifugation (2,000 rpm, 10 min, 4°C). The plasma samples were stored at −80°C until use for serological analysis, and the isolated blood cells were immediately processed to extract DNA for genetic analysis.

Fig. 1.

Selection schema of HAPE cases and matched controls.

DNA extraction

DNA extraction was carried out using the Sangon Ezup Column Blood Genomic DNA Extraction Kit (Shanghai, China) according to the manufacturer’s protocol. Extracted DNA was stored at −20°C until further use.

SNP selection and genotyping

As stated in the Introduction, the most commonly studied polymorphisms of the ACE gene (I/D (rs4340), A240T (rs4291), and A2350G (rs4343)) were selected for analysis. The I/D polymorphism is an Alu repeat located in intron 16 and has been associated with a wide spectrum of disease phenotypes, including HAPE (Charu et al. 2006; Stobdan et al. 2011). The A240T SNP is located in the promoter region −240 bp from the initiation codon (Qi et al. 2008). The A2350G SNP is located in exon 16 (Qi et al. 2008).

Tag SNPs for ACE were selected using Haploview software. Briefly, previously published genotyping data of the ACE gene from Han Chinese (CHB) HapMap samples were downloaded from the HapMap database (http://www.hapmap.org). Tag SNPs were selected according to the following criteria: aggressive tagging using two and three marker haplotypes, minor allele frequency of ≥ 0.1, r² of ≥ 0.8, and a logarithm (base 10) of odds (LOD) score of 3.0. Three tag SNPs were selected to capture 25 of 25 (100%) alleles. Thus, a total of six polymorphisms from the ACE gene were selected for analysis.

The G894T (rs1799983) polymorphism of the NOS3 gene is a guanine (G) to thymine (T) nucleotide substitution in the open reading frame (exon 7) that results in an amino acid substitution of glutamic acid (Glu) to aspartic acid (Asp) at the 298th position. This SNP is believed to contribute to HAPE development via its positive association with essential hypertension (Droma et al. 2002).

Table 1 lists the total seven polymorphisms analyzed in this study and summarizes their genomic information. The genotypes of the ACE gene I/D polymorphism were determined by polymerase chain reaction (PCR) and agarose gel electrophoresis as previously described (Rigat et al. 1992). All other selected SNPs were genotyped by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF). All genotyping procedures were carried out by Benegene Biotechnology Co., Ltd. Briefly, the DNA sample to be queried was diluted to 5 ng/µL, and 1 µL of that solution was then combined with 0.95 µL of water, 0.625 µL of PCR buffer (containing 15 mM MgCl₂), 1 µL of 2.5 mM dNTPs, 0.325 µL of 25 mM MgCl₂, 1 µL of PCR primers, and 0.1 µL of 5 U/µL HotStart Taq (Qiagen, Hilden, Germany). The reaction was incubated under the following thermal cycling conditions: 94°C for 15 min, followed by 45 cycles of 94°C for 20 s, 56°C for 30 s, and 72°C for 1 min, and a final extension at 72°C for 3 min. After PCR amplification, the remaining dNTPs were dephosphorylated by adding 1.53 µL of water, 0.17 µL of shrimp alkaline phosphatase (SAP) buffer, and 0.3 U of SAP (Sequenom, San Diego, CA, USA). The reaction was incubated at 37°C for 40 min, after which the enzyme was deactivated by incubating at 85°C for 5 min. After the SAP treatment, the single primer extension product encompassing the SNP was combined with 0.755 µL of water, 0.2 µL of 10 × iPLEX buffer, 0.2 µL of termination mix, 0.041 µL of iPLEX enzyme (Sequenom), and 0.804 µL of 10 µM extension primer. The single base extension reaction was carried out at 94°C for 30 s and then 94°C for 5 s, followed by five cycles of 52°C for 5 s and 80°C for 5 s and a total 40 cycles of 94°C for 5 s, 52°C for 5 s, and 80°C for 5 s, with a final extension cycle of 72°C for 3 min. The reaction mix was desalted by adding 6 mg of cation exchange resin (Sequenom), mixing, and resuspending in 25 µL of water. The completed genotyping reactions were spotted onto a 384-well spectroCHIP (Sequenom) using a MassARRAY Nanodispenser (Sequenom) and assessed by the MassARRAY matrix-assisted laser desorption ionization time-of-flight mass spectrometer (Sequenom). Genotype calling was performed in real time with the MassARRAY RT software (version 3.0.0.4) and analyzed using the MassARRAY Typer software (version 3.4; Sequenom). The performance of each SNP assay was assessed by evaluating signal intensities and reproducibility, and by calculating failure rates, tightness of clustering of heterozygotes in a normal population sample, and proportions of samples consistent with Hardy-Weinberg equilibrium (HWE).

Table 1. Characteristics of genotyped variants.

rs number^a	Allele type	Gene position	Function	MAF		P-value for HWE^c	Method of genotyping	Primer sequence	PCR product size, bp
rs number^a	Allele type	Gene position	Function	In database^b	Controls	P-value for HWE^c	Method of genotyping	Primer sequence	PCR product size, bp
ACE
rs4340	I/D	Intron 16	No coding	NA	0.28	0.75	PCR	F: CTGGAGACCACTCCCATCCTTTCT R: GATGTGGCCATCACATTCGTCAGAT	190; 490
rs4291	A/T	Promoter region	No coding	NA	0.33	1.00	MALDI-TOF	F: ACGTTGGATGTCGGGTGTTCCGGCAAACTG R: ACGTTGGATGCAGAGGAAGCTGGAGAAAGG R^d: AAGGGCCTCCTCTCTTT	90
rs4343	A/G	Exon 16	Synonymous	0.24	0.28	0.75	MALDI-TOF	F: ACGTTGGATGCCTACCAGATCTGACGAATG R: ACGTTGGATGCATGCCCATAACAGGTCTTC F^d: GATCTGACGAATGTGATGGCCAC	83
rs8066114	C/G	Intron 24	No coding	0.21	0.17	0.21	MALDI-TOF	F: ACGTTGGATGTCAAGCAATCCTCCCACATC R: ACGTTGGATGACCCTGATAACCTGAAGGTC R^d: TTGTAAAATGTCTATAAAATGGAA	199
rs4363	A/G	Intron 25	No coding	0.26	0.34	0.47	MALDI-TOF	F: ACGTTGGATGTGCCCATGCTGTCTCCTTG R: ACGTTGGATGAAGCTGACGCGGCCGCTGT R^d: CTTCTGAGCGAGCTGAG	94
rs4461142	C/T	Intron 13	No coding	0.33	0.38	0.16	MALDI-TOF	F: ACGTTGGATGCAGATCAGCCCTCTCACTTG R: ACGTTGGATGGGAGATGGGAGTTTTCAGTC F^d: ACTTGAGACAGGAAGAGGAC	100
NOS3
rs1799983	G/T	Exon 7	Missense	0.11	0.02	0.84	MALDI-TOF	F: ACGTTGGATGTGCTGCCCCTGCTGCTGC R: ACGTTGGATGACCTCAAGGACCAGCTCGG F^d: CTGCTGCAGGCCCCAGATGA	96

F, forward primer; NA, not available; MAF, minor allele frequency; MALDI-TOF, matrix-assisted laser desorption ionization time-of-flight mass spectrometry; PCR, polymerase chain reaction; R, reverse primer; SNP, single nucleotide polymorphism.

^aThe rs number shown is the cluster ID from NCBI dbSNP.

^bThe MAF from the Han Chinese (CHB) HapMap database.

^cThe Hardy-Weinberg equilibrium in the control group was tested using the χ ² goodness-of-fit test.

^dSingle base extension primer.

Statistical analysis of case-control data

All statistical analyses were carried out using the SPSS software (version 12.0; SPSS Inc., Chicago, IL, USA). HWE between the expected and observed genotype distribution in the controls and the differences in genotype and allele distributions between HAPE cases and control subjects were assessed using the Chi-squared (χ ²) goodness-of-fit test or Fisher’s exact test. Genotypes of ACE and NOS3 genes’ polymorphisms were compared by logistic regression analysis under assumptions of dominant and recessive genetic models. The mean values of continuous variables were compared by the paired Student’s t-test.

Meta-analysis

To generate more robust estimates of risk for the NOS3 G894T SNP and HAPE, a meta-analysis was carried out to derive a summary estimate of odds ratios (ORs) and P-values. First, a systematic search was conducted on the following electronic databases of English and Chinese language science and medical literature: PubMed, MEDLINE, Science Direct, Web of Science, EMBASE, the Cochrane Library Database, Chinese Biomedical Literature database (CBM), and the Chinese Journals Full-Text Database (Chinese National Knowledge Infrastructure; CNKI). Potentially relevant studies were queried using the following terms: “high altitude pulmonary edema”, “HAPE”, and “high altitude pulmonary edema”; or “HAPE” in single combination with “gene”, “genetic”, “genotype”, “allele”, “mutation”, “variant”, or “polymorphism”. The databases were searched from their inception up to the middle of October 2011. Two independent reviewers examined the list of identiﬁed articles, removed duplicates, and retrieved the publications.

Studies were selected for the meta-analysis if they met the following inclusion criteria: population-based case-controlled study design to assess the relationship between susceptibility genes and HAPE, HAPE diagnosis according to the international uniform standard criteria (Hultgren and Marticorena 1978), sufficient data, including sample size and subjects’ characteristics, and distribution of alleles and genotypes. Studies were excluded if the design was family-based with linkage considerations.

Crude ORs, with their corresponding 95% confidence intervals (CIs), were calculated for alleles and genotypes and used to evaluate the association between the polymorphisms in susceptibility genes and HAPE risk. The pooled ORs were applied to allele contrast modeling, dominant genetic modeling, and recessive genetic modeling. Heterogeneity was assessed by the χ ²-based Q-test and I² test, and considered significant when P was < 0.10. When no evidence of heterogeneity was found among studies, the pooled OR estimate of each study was calculated in the ﬁxed-effects model (Mantel-Haenszel) (Mantel and Haenszel 1959); otherwise, the random-effects model (DerSimonian and Laird) was used (DerSimonian and Laird 1986; DerSimonian and Kacker 2007). To identify potential influential studies, sensitivity analysis was carried out by sequentially removing individual studies and evaluating the effect on the overall estimate. The associations of particular ethnic/geographic subgroups were assessed by stratification analysis. Publication bias was tested by funnel plot and Begg’s test.

All statistical tests for the meta-analysis were carried out using the STATA software package (version 11.0; College Station, TX, USA). A P-value of ≤ 0.05 was considered to indicate statistical significance for all tests and models.

Results

Case-control characteristics

The characteristics of the study cohort are presented in Table 2. There was no significant difference between the HAPE-p and HAPE-r groups for sex, age, tourist type, region of origin, or method of ascent (all P > 0.05). Thus, the baseline characteristics were considered comparable between the two groups. Comparison of the cohort’s clinical features revealed that the HAPE-p group had significantly higher PR and lower SaO₂ than the HAPE-r group (both P < 0.05). However, the two groups showed similar BMI, systolic blood pressure (SBP), and diastolic blood pressure (DBP) (all P > 0.05).

Table 2. Characteristics of the case-control cohort.

	HAPE-p (n = 27)	HAPE-r (n = 108)	P-value
Baseline characteristics
Sex
Male	21 (77.78)	84 (77.78)	> 0.05
Female	6 (22.22)	24 (22.22)
Age	34.70 ± 11.85	34.70 ± 11.52	> 0.05
Tourist type
Vacationer	11 (40.74)	44 (40.74)	> 0.05
Worker	3 (11.11)	12 (11.11)
Soldier	13 (48.15)	52 (48.15)
Region of origin
South	19 (70.37)	76 (70.37)	> 0.05
North	8 (29.63)	32 (29.63)
Method of ascent	By train	By train
Clinical features
BMI, kg/m²	22.85 ± 7.56	22.67 ± 8.81	> 0.05
SaO₂, %	79.08 ± 13.60	91.82 ± 3.91	< 0.05
Pulse rate, rate/min	92.16 ± 22.97	80.02 ± 20.20	< 0.05
SBP, mmHg	118.7 ± 3.4	123.3 ± 1.3	> 0.05
DBP, mmHg	74.8 ± 3.3	77.9 ± 1.0	> 0.05

BMI, body mass index; DBP, diastolic blood pressure; SaO₂, arterial oxygen saturation; SBP, systolic blood pressure.

Data are presented as number of subjects (%) or mean ± s.d.

HWE of the genotyped polymorphisms among the cases and controls

The genotype distributions of all seven studied polymorphisms in the controls were in Hardy-Weinberg equilibrium (all P > 0.05; Table 1).

Single-locus analyses identified polymorphisms significantly associated with HAPE

Two polymorphisms in the ACE gene correlated with HAPE susceptibility: Four of the six polymorphisms in the ACE gene showed no significant association with HAPE for either the genotype or allele distributions. However, there was a significant difference in the distributions of G allele frequency of rs8066114 polymorphism between the cases and controls. Furthermore, rs8066114 and rs4461142 were significantly associated with HAPE risk under the dominant model of inheritance [OR (95% CI): 2.56(1.08-6.05) and 3.14(1.11-8.93), respectively; Table 3].

NOS3 rs1799983 (G894T) polymorphism correlated with HAPE susceptibility: For the NOS3 rs1799983 (G894T) polymorphism, the genotype frequencies for GG, GT, and TT were 96.30% (n = 104), 3.70% (n = 4), and 0% (n = 0), respectively, in the HAPE-r group, and 85.19% (n = 23), 14.81% (n = 4), and 0% (n = 0), respectively, in the HAPE-p group (Table 3). The distribution of the overall genotype frequency was significantly different between the two groups (P = 0.03), which indicated a significant association of the G894T genotype with HAPE-p. While the allele frequency of G was not significantly different between the two groups (HAPE-r: 98.15% vs. HAPE-p: 92.59%), the allele frequency of T was significantly different (HAPE-r: 1.85% vs. HAPE-p: 7.41%; P = 0.05). The NOS3 G894T SNP was associated with an elevated risk of HAPE only under the dominant model (OR(95% CI): 4.52(1.05-19.42)).

Table 3. Genotype and allele distributions of polymorphisms in the ACE and NOS3 genes between the cases and controls, and their association with HAPE risk.

	Genotype	HAPE-p n (%)	HAPE-r n (%)	χ²	P_χ² value	OR(95% CI)
ACE
rs4340
Genotype	II	9 (33.33)	57 (52.78)	3.49	0.18
	ID	14 (51.85)	42 (38.89)
	DD	4 (14.82)	9 (8.33)
Allele	I	32 (59.26)	156 (72.22)	3.43	0.06
	D	22 (40.74)	60 (27.78)
Dominant model
	II	9 (33.33)	57 (52.78)
	DD + ID	18 (66.67)	51 (47.22)	3.27	0.07	2.24 (0.92-5.42)
Recessive model
	II + ID	23 (85.18)	99 (91.67)
	DD	4 (14.82)	9 (8.33)	1.04	0.29	1.91 (0.54-6.76)
rs4291
Genotype	AA	9 (33.33)	48 (44.44)	1.14	0.57
	AT	14 (51.85)	48 (44.44)
	TT	4 (14.82)	12 (11.12)
Allele	A	32 (59.26)	144 (66.67)	1.04	0.31
	T	22 (40.74)	72 (33.33)
Dominant model
	AA	9 (33.33)	48 (44.44)
	TT + AT	18 (66.67)	60 (55.56)	1.09	0.30	1.60 (0.66-3.88)
Recessive model
	AA + AT	23 (85.18)	96 (88.88)
	TT	4 (14.82)	12 (11.12)	0.28	0.53	1.39 (0.41-4.71)
rs4343
Genotype	AA	9 (33.33)	57 (52.78)	3.49	0.18
	AG	14 (51.85)	42 (38.89)
	GG	4 (14.82)	9 (8.33)
Allele	A	32 (59.26)	156 (72.22)	3.43	0.06
	G	22 (40.74)	60 (27.78)
Dominant model
	AA	9 (33.33)	57 (52.78)
	GG + AG	18 (66.67)	51 (47.22)	3.27	0.07	2.24 (0.92-5.42)
Recessive model
	AA + AG	23 (85.19)	99 (91.67)
	GG	4 (14.81)	9 (8.33)	1.04	0.29	1.91 (0.54-6.76)
rs8066114
Genotype	CC	13 (48.15)	76 (70.37)	4.77	0.09
	CG	12 (44.44)	27 (25.00)
	GG	2 (7.41)	5 (4.63)
Allele	C	38 (70.37)	179 (82.87)	2.61	0.04	2.04 (1.03-4.03)
	G	16 (29.63)	37 (17.13)
Dominant model
	CC	13 (48.15)	76 (70.37)
	GG + CG	14 (51.85)	32 (29.63)	4.75	0.03	2.56 (1.08-6.05)
Recessive model
	CC + CG	25 (92.59)	103 (95.37)
	GG	2 (7.41)	5 (4.63)	0.34	0.63	1.65(0.30-8.99)

rs4363
Genotype	AA	7 (25.93)	49 (45.37)	3.50	0.17
	AG	16 (59.26)	45 (41.67)
	GG	4 (14.81)	14 (12.96)
Allele	A	30 (55.56)	143 (66.20)	2.13	0.15
	G	24 (44.44)	73 (33.80)
Dominant model
	AA	7 (25.93)	49 (45.37)
	GG + AG	20 (74.07)	59 (54.63)	3.36	0.07	2.37(0.93-6.08)
Recessive model
	AA + AG	23 (85.19)	94 (87.04)
	GG	4 (14.81)	14 (12.96)	0.06	0.76	1.17(0.35-3.88)

rs4461142
Genotype	CC	5 (18.52)	45 (41.67)	5.50	0.06
	CT	17 (62.96)	44 (40.74)
	TT	5 (18.52)	19 (17.59)
Allele	C	27 (50.00)	134 (62.04)	2.60	0.11
	T	27 (50.00)	82 (37.96)
Dominant model
	CC	5 (18.52)	45 (41.67)
	TT + CT	22 (81.48)	63 (58.33)	4.96	0.03	3.14(1.11-8.93)
Recessive model
	CC + CT	22 (81.48)	89 (82.41)
	TT	5 (18.52)	19 (17.59)	0.01	1.00	1.07(0.36-3.17)

NOS3
rs1799983
Genotype	GG	23 (85.19)	104 (96.30)	4.78	0.03
	GT	4 (14.81)	4 (3.70)
	TT	0 (0.00)	0 (0.00)
Allele	G	50 (92.59)	212 (98.15)	4.64	0.05
	T	4 (7.41)	4 (1.85)
Dominant model
	GG	23 (85.19)	104 (96.30)
	TT + GT	4 (14.81)	4 (3.70)	4.78	0.03	4.52(1.05-19.42)
Recessive model
	GG + GT	27 (100.00)	108 (100.00)
	TT	0 (0.00)	0 (0.00)	NA	> 0.05	NA

ACE, angiotensin converting enzyme; HAPE, high-altitude pulmonary edema; HAPE-p, HAPE patients; HAPE-r, HAPE resistance; NOS3, nitric oxide synthase 3; NA, not available.

Significant P-values are indicated in bold.

Meta-analysis of NOS3 gene rs1799983 (G894T) polymorphism and HAPE risk

Eligible studies: Five studies (Droma et al. 2002; Weiss et al. 2003; Ahsan et al. 2004, 2006; Sun et al. 2010) met the inclusion/exclusion criteria and were selected for meta-analysis. When the subjects from these studies were combined with our case-control cohort, a total of 399 HAPE cases and 495 non-HAPE controls were available for analysis. These cohorts represented five studies (including ours presented above) conducted in Asian countries (China, n = 2; Japan, n = 1; India, n = 2) and one in a European country. The baseline characteristics of the total six studies are presented in Table 4.

Quantitative synthesis: The meta-analysis of the overall population revealed some significant associations under the allele contrast model [T vs. G: OR (95% CI): 2.05(1.55-2.72); Fig. 2] and the dominant model [TT+GT vs. GG: OR (95% CI): 2.91(2.05-4.13); Fig. 3]. However, there were no significant associations found under the recessive model [TT vs. GT+GG: OR (95% CI): 1.10 (0.48-2.53)].

Subgroup analysis showed a significant association with HAPE susceptibility for the individuals of Asian descent in the allele contrast model [T vs. G: OR (95% CI): 2.31(1.67-3.19); Fig. 2] and the dominant model [TT+GT vs. GG: OR (95% CI): 3.47(2.34-5.15); Fig. 3]. However, there were no significant associations found in the recessive model [TT vs. GT+GG: OR(95% CI): 0.75(0.24-2.29)].

Sensitivity analysis: Neither the OR value nor the P-value were appreciably affected by the serial study removal sensitivity analysis, indicating that none of the studies exerted particular influence on the results of the meta-analysis.

Publication bias: As shown in Fig. 4, the shape of the funnel plot was symmetrical for data comparisons of the allele contrast model (T vs. G: P _{Begg’s test}= 0.45), the dominant model (P _{Begg’s test}= 0.71), or the recessive model (P _{Begg’s test}= 0.46).

Table 4. Baseline characteristics of studies included in the meta-analysis.

First author, year (citation)	Race	Location (altitude, meters)	Sample size		Sex, M/F		Average age, years		Genotypes of NOS3 G894T polymorphism
			Cases	Controls	Cases	Controls	Cases	Controls	Cases			Controls
			Cases	Controls	Cases	Controls	Cases	Controls	GG	GT	TT	GG	GT	TT
Droma, 2002 (Droma et al. 2002)	Japanese	Japan Alps (2,758-3,190)	41	51	39/2	43/8	31.30	38.60	20	21	0	43	6	2
Weiss, 2003 (Weiss et al. 2003)	Caucasian	Capanna Margherita (4,559)	51	52	44/7	37/15	42.00	37.00	20	24	7	24	22	4
Ahsan, 2004 (Ahsan et al. 2004)	Indian	Ladakh (3,500)	59	64	59/0	64/0	35.00	35.00	22	35	2	39	23	2
Ahsan, 2006 (Ahsan et al. 2006)	Indian	Ladakh (3,500)	72	60	72/0	60/0	35.00	35.00	25	45	2	36	22	2
Sun, 2010 (Sun et al. 2010)	Han Chinese	Qinghai-Tibet (4,000-5,072)	149	160	149/0	160/0	31.30	31.30	130	18	1	155	4	1
Our study	Han Chinese	Golmud (2,780-4,500)	27	108	21/6	84/24	34.70	34.70	23	4	0	104	4	0

Fig. 2.

NOS3 G894T T allele vs. G allele in association with HAPE. (A) Overall population. (B) Asian populations.

Fig. 3.

NOS3 G894T TT+GT vs. GG under the dominant model of inheritance. (A) Overall population. (B) Asian populations.

Fig. 4.

Funnel plot analysis of publication bias. Each point represents a separate study for the indicated association. (A) Allele contrast. (B) Dominant model. (C) Recessive model.

Discussion

In this study, the allele and genotype frequencies of six polymorphisms in the ACE gene of the renin-angiotensin-aldosterone-system pathway and one SNP in the NOS3 gene of the nitric oxide pathway were evaluated in a case-control study to determine their association with HAPE risk in a Han Chinese population. The ACE rs8066114 and rs4461142 polymorphisms and the NOS3 rs1799983 (G894T) polymorphism were found to be associated with HAPE development. Then, a meta-analysis was carried out to further assess the strength of association of the NOS3 SNP with HAPE in a larger, more heterogeneous population. This analysis confirmed the statistically significant association and revealed that the T allele carriers were at a 2.91-fold higher risk of developing HAPE than carriers of the GG genotype (under the dominant genetic model of inheritance). Finally, ethnicity stratification analysis indicated that the significant association of G894T polymorphism with HAPE susceptibility involved the Asian subgroups.

Since the ACE gene is highly polymorphic and HAPE is a complex syndrome showing varying degrees of association with several genetic factors, determining which genetic variants of the ACE gene functionally affect the bioavailability of ACE may eventually provide clinically relevant insight into HAPE development, treatment, and prevention. Several previous studies have assessed the association between HAPE susceptibility and the ACE I/D (rs4340) polymorphism, but the results have been inconsistent (Kumar et al. 2004; Hotta et al. 2004; Stobdan et al. 2011). Although the I/D polymorphism is intronic, it might act as a marker in linkage disequilibrium with other functional variants in the gene’s regulatory regions. The current case-control study also assessed the ACE polymorphisms of A240T (rs4291; in the promoter region), A2350G (rs4343; in exon 16) and three tag SNPs. Single-locus analysis suggested a positive association of the G allele of rs8066114 and the T allele of rs4461142 with HAPE under the dominant model of inheritance. Although no significant associations were found for any of the other four polymorphisms, their corresponding P-values were close to the significance cut-off of 0.05.

Variant alleles of NOS3 have been shown to result in reduced NO (Ahsan et al. 2006; Su et al. 2007), which may lead to HAPE. Although the association between NOS3 gene variants and HAPE susceptibility has been previously assessed in a number of studies, the results have not been consistent, especially for the NOS3 rs1799983 (G894T) polymorphism (Droma et al. 2002; Weiss et al. 2003; Ahsan et al. 2004, 2006; Sun et al. 2010). In our case-control cohort of Han Chinese, there was a significant association between the rs1799983 (G894T) polymorphism and HAPE susceptibility; this finding suggests that this particular SNP may be an Asian-specific risk factor of HAPE.

To derive a more precise estimate of the association between the NOS3 G894T SNP and HAPE, a meta-analysis was performed which included previous case-control cohorts from various ethnicities and geographic regions, and only one study was performed in Caucasians. The total sample of 399 HAPE cases and 495 controls showed significant association for the NOS3 G894T SNP, which remained significant for the Asian subgroups. The lack of association between NOS3 G894T SNP and HAPE in Caucasians may be due to ethnicity- or environment-related factors, or different linkage disequilibrium between Asians and Caucasians. In our study, the G894T polymorphism showed a statistically significant association with susceptibility to HAPE, implying that this missense mutation might either affect function of the eNOS enzyme or be closely linked to some undetected locus that affects HAPE susceptibility. Since the G894T variant is located in exon 7 of the eNOS gene, it may induce changes in eNOS activity, leading to an increase or decrease in NO production. Thus, the T allele of the NOS3 gene rs1799983 (G894T) polymorphism might be associated with increased risk for HAPE, and have implications for Asian populations in particular; however, further studies with larger populations of various ethnicities are required to confirm this hypothesis.

Two key limitations in our study design may have influenced our findings and should be carefully considered at interpretation. First, the sample size of our original case-control genetic association study was small due to the overall decreased incidence of HAPE in conjunction with increased preventive awareness. Second, the majority of the studies included in our current meta-analysis were composed of male subjects who were less than 50 years old. It is possible that environmental factors associated with this group (such as work type and load) contributed to the development of HAPE. Larger association studies of more heterogeneous HAPE populations will need to be carried out to confirm our findings.

Conclusion

This study demonstrates that the rs1799983 (G894T) polymorphism in exon 7 of the NOS3 gene and two tag SNPs, rs8066114 and rs4461142, of the ACE gene are significantly positively associated with HAPE susceptibility in Han Chinese. Further meta-analysis of the NOS3 G894T SNP confirmed the significant association with HAPE susceptibility and suggested that this polymorphism may be associated with increased risk for HAPE in Asians. Future large-scale studies are warranted to further assess the effects of ACE and NOS3 genetic variants on HAPE risk.

Funding

This work was supported by a grant from the Special Projects of Scientific Research in Health Service under the Ministry of Health (No. 2010002012), and a grant from No. CWS11J309.

Acknowledgements

We thank Medjaden Bioscience Limited for assisting in the preparation of this manuscript.

Conflict of Interest

All of the authors declare that they have no conflict of interest and no financial relationship with any commercial entity that has an interest in the subject of this manuscript.

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