High altitude pulmonary edema (HAPE) is a paradigm of pulmonary edema experienced by some people under hypobaric hypoxic condition of high altitude after rapidly ascending above 2500 m from sea level. The pathogenesis of HAPE is still debated. It is characterized by intense smooth muscle proliferation and exaggerated hypoxic vasoconstriction at decreased levels of alveolar oxygen, leading to sustained excessive pulmonary pressure and vascular leakage through over perfusion, resulting in abnormal buildup of fluid in the lung.[1,2] Many people will be at risk of high altitude sickness shortly to a moderately hypoxic environment, but not all affected individuals will develop HAPE, suggesting an innate contribution to HAPE susceptibility. Although the impact of altitude attained and rate of ascent on the etiology of HAPE is well known, there are clues to the contribution of a genetic background that influence the efficacy of altitude acclimatization.
Regulator of telomere elongation helicase1 (RTEL1) is a DNA helicase crucial for the regulation of telomere length that plays a role in a variety of fundamental cellular mechanisms such as DNA replication, genome stability, DNA repair, and telomere maintenance.[4,5] In the absence of RTEL1, shortened telomere length, chromosome breaks, and translocations were observed, indicating that RTEL1 protein contribute to genomic stability. Previous studies have found that genetic polymorphisms of RTEL1 were associated with glioma risk.[7–11] A recent study found that mutations in RTEL1 represent an important contributor to risk for pulmonary fibrosis. Defective telomere maintenance leading to telomere shortening is a cause of pulmonary fibrosis.[13–15] So we hypothesized the variants of RTEL1 may have a potential relevance with lung-related disease.
A previous study reported that telomere length was significantly longer at moderate attitude than at sea-level or at simulated high attitude. However, to date, little research directly focused on the association between RTEL1 polymorphisms and HAPE risk. The present study was undertaken to tentatively explore the potential relation between common single-nucleotide polymorphisms (SNPs) in RTEL1 and HAPE risk in Chinese Han population, aiming to shed a new light on the association between mutations in RTEL1 and HAPE susceptibility.
2 Materials and methods
A number of 265 HAPE cases were recruited from the Affiliated Hospital of Xizang Minzu University. We recruited a total of 303 healthy unrelated samples from the outpatient departments at the hospital. The individuals in the HAPE and control groups were all unrelated, and information of all the subjects has been critically reviewed. The cases (244 males, 21 females) and controls (289 males, 14 females) did not show a significantly different sex distribution (P = .102), while they showed a significantly different age distribution (P < .001). All of the subjects were Han Chinese and residents living in Northwest China. The diagnosis of HAPE patients was dependent on standard criteria, including patient interviews like cough, dyspnea, cyanosis at rest, imageological examination like X-ray radiograph, computed tomography (CT) of the patient chest or magnetic resonance imaging. All the HAPE patients eventually show that chest radiographic troves of infiltrates consistent with pulmonary edema. None of the participants who were included in the study had any kind of disorder, including diabetes, renal disease, hypertension, or cardiopulmonary or coronary disorders, which could have affected the study. We collected blood samples from all the participants, and the use of the samples was approved by the Human Research Committee of the Affiliated Hospital of Xizang Minzu University. The study protocol was reviewed and approved by the Ethics Committee of Xizang Minzu University.
2.2 Gene polymorphisms analyses
In this study, 4 SNPs in RTEL1 were selected from the previous study for analysis.[19,20] The lower frequency alleles were coded as the minor allele. Minor allele frequencies of all SNPs were > 5% in the HapMap of the Chinese Han Beijing population. Genomic DNA was isolated from whole blood samples using the GoldMag-Mini Purification Kit (GoldMagCo Ltd, Xian city, China), and DNA concentrations were measured using the NanoDrop2000 (Thermo Scientific, Waltham, MA). SequenomMassarrayAssay Design 3.0 software was used to design a multiplexed SNP Mass EXTENDED Assay.[21–23] Genotyping was performed using the SequenomMassARRAY RS1000 and analyzed using SequenomTyper 4.0 Software.
2.3 Statistical analyses
Fisher exact test was used to assess the variation in each SNP frequency from the Hardy–Weinberg equilibrium (HWD) in the control subjects. Differences in SNP genotype and allele distribution between cases and controls were compared using logistic regression. ORs and 95% CIs were determined using unconditional logistic regression analysis with adjustments for age and sex.. All the statistical analyses above were performed with Microsoft Excel and SPSS 20.0 (SPSS Inc, Chicago, IL). Finally, the patterns of linkage disequilibrium (LD) and haplotype construction were evaluated by Haploview software package (version 4.2). All P values were Bonferroni corrected, and statistical significance was set at P < .0025 (.05/20).
A number of 265 cases and 303 controls were enrolled for genetic association analyses in our study (Table 1). Our sample size was relatively small compared with the previous GWAS study. However, we calculate the expected sample size used the online calculation software (http://sampsize.sourceforge.net/iface/s3.html#ccp). If we wish to conduct a case-control study to assess whether HAPE risk may be associated with RTEL1 polymorphisms and we wish to detect an odds-ratio of 2 with power 90%, the number of cases and controls were 188 versus 188. So the present sample size was appropriate.
Four SNPs in RTEL1 gene were analyzed (Table 2). We compared the differences in frequency distributions of alleles between cases and controls by χ 2 test. We found that the allele “G” of rs6089953 and rs6010621 and the allele “A” of rs2297441 were associated with decreased risk of HAPE (rs6089953: OR = 0.70; 95% CI = 0.54–0.92; P = .009; rs6010621: OR = 0.60; 95% CI = 0.46–0.79; P < 0.001; rs2297441: OR = 0.74; 95% CI = 0.58–0.96; P = .021). SNPs rs6010621 remained significant after Bonferroni correction (P < .0025).
The genotype frequencies of the RTEL1 polymorphisms were shown in Table 3. We identified 2 SNPs associated with the decreased HAPE risk after adjusted for age and gender. Compared with the TT genotype, the “GG” and “GT” frequencies of rs6010621 polymorphism among cases were different from the controls (GG vs TT: OR = 0.41; 95% CI = 0.19–0.88; P = .021; GT vs TT: OR = 0.58, 95% CI = 0.40–0.83; P = .003; respectively), which suggested that the rs6010621 polymorphism had a decreased effect on HAPE risk. Additionally, compared with individuals with the rs4809324 TT genotype, individuals with CT genotype had a decreased HAPE risk (CT vs TT: OR = 0.58; 95% CI = 0.37–0.91; P = .018). However, neither of them was significant after Bonferroni correction (P < .0025).
We further analyzed the association of SNPs and HAPE risk using logistic regression including dominant model, recessive model, and additive model. We assumed the minor allele of each SNP as a risk factor compared with the wild-type allele (Table 4). We found that rs6010621, rs6089953, and rs2297441 were relevant to decreased HAPE risk under dominant model (rs6010621: OR = 0.55; 95% CI = 0.39–0.78; P = .001; rs6089953: OR = 0.68; 95% CI = 0.48–0.96; P = .027; rs2297441: OR = 0.63; 95% CI = 0.45–0.89; P = .008, respectively) and additive model (rs6010621: OR = 0.51; 95% CI = 0.46–0.81; P < .001; rs6089953: OR = 0.72; 95% CI = 0.55–0.95; P = .022; rs2297441: OR = 0.73; 95% CI = 0.57–0.95; P = .019, respectively). SNPs rs6010621 remained significant after Bonferroni correction (P < .0025).
Furthermore, the linkage D analysis for the 4 SNPs was performed, 1 block rs6089953-rs6010621 in RTEL1 gene showed strong linkage (Fig. 1). On the basis of the LD pattern of RTEL1 gene, we conducted haplotype-based analysis. Haplotype “GG” of rs6089953-rs6010621 was detected associated with a decreased risk of HAPE (OR = 0.60; 95% CI = 0.45–0.81; P = .001), while the haplotypes “GT” and “AT” were associated with increased risk of HAPE (GT: OR = 3.32; 95% CI = 1.42–7.80; P = .006; AT: OR = 1.40; 95% CI = 1.06–1.84; P = .019) (Table 5). However, only haplotype “GG” remained significant after Bonferroni correction (P < .0025).
In this case-control study, we estimated the relationship between RTEL1 and HAPE risk, confirmed by multivariate analysis adjusted for age and gender, the “G” of rs6089953, the“ G” of rs6010621, the “A” of rs2297441 in RTEL were associated with a decreased risk of HAPE, rs6010621 remained significant after Bonferroni correction. We also observed that the GG, GT, and AT haplotypes of rs6089953-rs6010621 in RTEL1 were significantly associated with decreased susceptibility to HAPE compared with the wild type, haplotype “GG” remained significant after Bonferroni correction. These results provided the first evidence that telomere length maintaining gene RTEL1 may play a potential part in the risk of HAPE in Chinese Han population.
RTEL1 is located in 20q13.3, regulates genomic stability and telomere maintenance. Inactivation of RTEL1 caused chromosome breaks, fusions, and telomere loss in mice. The human RTEL1 is an ortholog of the mouse RTEL1, and their protein products likely play similar roles. It is more likely to happen gene replacement and sister chromatid exchange when RTEL1 is deficient in cells. RTEL1-deficient stem cells were susceptible to localized chromosome breakage, and the proliferative ability was significantly decreased in cell differentiation. Additionally, RTEL1-deficient cell was more sensitive to several DNA damaging agents during the embryonal developmental stages. However, in the present study, carriers with these variants in RTEL1 showed a significantly decreased susceptibility to HAPE. Although our data offer clues for the association between RTEL1 and HAPE risk, comprehensive biochemical and functional analysis of RTEL1 polymorphisms is needed to confirm the results.
The Bonferroni correction is the most commonly used method when making multiple statistical tests. We determined that SNP rs6010621 remained significant after Bonferroni correction, while rs6089953 and rs2297441 were not significant. This may result from the strict SNP filtering criteria and small sample size. Additionally, the Bonferroni correction has its inherent defects, we adjusted the P values based on 4 SNPs and 5 genetic models, some significant differences may be deemed insignificant effects, and false-positive results may be generated.
Some possible limitations in this case- control analysis should be addressed. First, our sample size was relatively small, we did not do further subgroup analyses based on age or gender. Second, HAPE is a heterogeneous disease with many other risk factor, we did not investigate the gene–gene and gene–environment interactions because of the limited data. Third, all the samples were collected from hospital, type false positive error for association study may be generated. Based on the limitations of the present study listed above, detailed studies are warranted to confirm our findings. Moreover, more gene–gene and gene–environment interactions should also be considered in future analysis.
Our findings provide new evidence for the association between SNPs in RTEL1 and HAPE risk in the Chinese population for the first time. Because RTEL1 is required for genomic stability, we predict that changes in telomere stability may underlie the increased susceptibility to HAPE. Further functional studies are required to test this hypothesis.
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Keywords:Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.
case-control study; genomic stability; HAPE; RTEL1; single-nucleotide polymorphism (SNP); telomere length