- Academic Editor
Background: Environmental and genetic factors are jointly involved in
the development of chronic obstructive pulmonary disease (COPD). The
EGLN1 gene is a major factor in upstream regulation of the
hypoxia-inducible pathway. EGLN1 negatively regulates the
hypoxia-inducible factors HIF-l
The clinical manifestations of chronic obstructive pulmonary disease (COPD) are chronic respiratory symptoms (dyspnea, cough, sputum, acute exacerbations) due to airway (bronchitis, bronchiectasis) and/or alveolar anomalies (emphysema) that cause persistent and progressive exacerbation of airflow limitation [1]. Early COPD is asymptomatic or mildly symptomatic, meaning that diagnosis and treatment are easily delayed. Lung function damage such as fine bronchitis and destruction of the lung parenchyma (emphysema) has often already occurred when the diagnosis is confirmed [2, 3]. COPD is therefore a significant public health problem worldwide [4] and a major cause of mortality [5]. It presents a serious threat to patient survival and quality of life, as well as being a great burden to society [2].
COPD is the result of interactions between genes and the environment over time [6]. Epidemiologic investigations have shown a clear familial aggregation in some COPD patients [7, 8], thus revealing the importance of genetic factors. Genome-wide association studies (GWAS) have identified many candidate genes related to COPD pathogenesis [9], reinforcing the notion that genetic factors may play an important role in the development of COPD. Raguso et al. [10] found some similarities between chronic exposure to high altitude hypoxia in healthy people and chronic hypoxia in COPD patients, again suggesting that hypoxia has an important role in the development of COPD [11]. However, most of the current studies on candidate genes for COPD have focused on inflammation-related genes [12], with oxygen-sensitive genes deserving more in-depth investigation.
Egl-9 family hypoxia-inducible factor (EGLN1) acts as an oxygen sensor
and catalyzes prolyl hydroxylation of the transcription factor hypoxia-inducible
factor-1
The Gannan Tibetan Autonomous Prefecture is located on the northeastern edge of
the Qinghai-Tibetan Plateau [20] and is in a high elevation region [21]. A
previous study by our group found that the prevalence of COPD in Gannan was
23.4% (20.7%–26.4%) [22]. Here, we conducted a case-control study in this
Prefecture to investigate possible associations between EGLN1 single
nucleotide polymorphisms (SNPs) (rs41303095 A
A case-control study was conducted to assess the association between four
EGLN1 SNPs (rs41303095 A
All participants in this case-control study underwent pulmonary function tests and respiratory health questionnaires to collect information on their demographic characteristics and environmental exposures such as education, smoking and drinking status. After signing the informed consent form, 5 mL of peripheral blood was collected for genotyping.
The study was checked by the ethical committees of Xi’an Jiaotong University, Guangzhou Medical University and Gansu University of Chinese Medicine.
According to the Global Initiative for Chronic Obstructive Pulmonary Disease
2023 [23], COPD was diagnosed if participants experienced respiratory symptoms
such as cough, sputum, dyspnea, and wheezing in their daily lives, and if the
ratio of forced expiratory volume in one second (FEV1) to forced vital capacity
(FVC) was
Potential risk SNPs were identified in the dbSNP database
(http://www.ncbi.nlm.nih.gov/SNP) using the following criteria: SNPs located
between 2000 bp upstream and 2000 bp downstream of EGLN1, minor allele
frequency (MAF)
The Hardy-Weinberg equilibrium (HWE) test was performed on the observed genotype frequencies using the “SNPassoc” R package. The chi-square test was used to assess differences between cases and controls in terms of demographic characteristics and genotype frequency distribution. Associations between EGLN1 polymorphisms and COPD susceptibility were assessed using logistic regression analysis after adjusting for age, gender, BMI, literacy, hypertension, smoking and alcohol consumption. The method used for multiple comparisons was the false discovery rate (FDR) (q = 0.05). The analysis was then stratified by age, gender, BMI, literacy, hypertension, smoking and alcohol consumption. The consistency of odds ratios (ORs) between strata was examined using the Breslow-Day test. The rank sum test was used to evaluate the effect of genotype on lung function.
Data were analyzed using R 4.1.3 software (Lucent Technologies Corp., San Antonio, TX, USA). The OR and 95% confidence interval (95% CI) were used as evaluation metrics. All analyses were two-sided, with a significance level of 0.05.
Supplementary Table 1 shows the demographic characteristics of the 589
participants in this study. Of these, 293 (49.7%) were males and 296 (50.3%)
females, 248 (42.1%) were
Supplementary Table 2 shows the demographic characteristics of 292 COPD
patients and 297 healthy controls from Zhuoni County, Gannan Tibetan Autonomous
Prefecture, Gansu. The age distribution and smoking status were statistically
different between the case and control groups (p
As shown in Table 1, only the rs12097901 C
SNP | Base pair position | MAF | p |
rs41303095 | 231500238 | 0.112 | |
rs480902 | 231531627 | 0.437 | 0.002 |
rs12097901 | 231557255 | 0.485 | 0.484 |
rs2153364 | 231560220 | 0.490 |
SNP, single nucleotide polymorphisms; MAF, minor allele frequency.
Binary logistic regression was used to analyze the association between
EGLN1 rs12097901 C
Model | Genotype | Case (292) | Control (297) | Unadjusted OR | p | Adjusted OR | p | q |
n (%) | n (%) | (95% CI) | (95% CI) | |||||
Codominant | CC | 183 (63.7) | 170 (57.2) | 1.000 (ref.) | 1.000 (ref.) | |||
CG | 93 (31.8) | 109 (36.7) | 0.772 (0.544–1.094) | 0.146 | 0.830 (0.569–1.210) | 0.332 | 0.352 | |
GG | 16 (5.5) | 18 (6.1) | 0.853 (0.414–1.749) | 0.662 | 0.651 (0.295–1.420) | 0.280 | 0.352 | |
Dominant | CC | 183 (62.7) | 170 (57.2) | 1.000 (ref.) | 1.000 (ref.) | |||
CG+GG | 109 (37.3) | 127 (42.8) | 0.783 (0.561–1.092) | 0.150 | 0.801 (0.559–1.147) | 0.227 | 0.352 | |
Recessive | CC+CG | 276 (94.5) | 279 (93.9) | 1.000 (ref.) | 1.000 (ref.) | |||
GG | 16 (5.5) | 18 (6.1) | 0.938 (0.460–1.901) | 0.858 | 0.694 (0.318–1.498) | 0.352 | 0.352 | |
Additive | CC |
1.173 (0.572–2.416) | 0.227 | 1.537 (0.704–3.385) | 0.274 | 0.352 |
a. Adjustment for multiple comparisons using false discovery rate. COPD, chronic obstructive pulmonary disease; OR, odds ratio; 95% CI, 95% confidence interval.
The results of the stratification and interaction analyses are shown in Table 3.
The association between rs12097901 C
Variable | Unadjusted OR | Adjusted OR | p | q |
p |
RERI | AP | S | |
(95% CI) | (95% CI) | ||||||||
Age | 0.850 | –0.164 (–2.291–1.964) | –0.050 (–0.738–0.637) | 0.932 (0.362–2.401) | |||||
0.821 (0.568–1.185) | 0.808 (0.555–1.176) | 0.265 | 0.548 | ||||||
0.958 (0.611–1.504) | 0.904 (0.568–1.439) | 0.672 | 0.802 | ||||||
Sex | 0.138 | –0.783 (–1.474–0.119) | –0.691 (–1.649–0.268) | 0.145 (0.010–55.137) | |||||
Male | 0.627 (0.427–0.920) | 0.628 (0.414–0.951) | 0.028 | 0.196 | |||||
Female | 1.134 (0.772–1.664) | 1.165 (0.773–1.754) | 0.466 | 0.689 | |||||
BMI | 0.114 | 0.328 (–0.134–0.791) | 0.407 (–0.087–0.805) | 0.370 (0.022–6.289) | |||||
0.754 (0.523–1.088) | 0.711 (0.481–1.050) | 0.087 | 0.305 | ||||||
0.964 (0.647–1.435) | 1.022 (0.659–1.582) | 0.924 | 0.924 | ||||||
Education level | 0.568 | –0.140 (–0.617–0.338) | –0.246 (–1.226–0.734) | 1.479 (0.347–6.308) | |||||
Primary and below | 0.878 (0.654–1.178) | 0.886 (0.648–1.212) | 0.449 | 0.689 | |||||
Junior high school and above | 0.688 (0.346–1.368) | 0.643 (0.296–1.398) | 0.266 | 0.548 | |||||
Hypertension | 0.998 | –0.069 (–0.614–0.477) | –0.075 (–0.704–0.555) | 1.055 (0.536–2.073) | |||||
Yes | 0.835 (0.546–1.277) | 0.774 (0.488–1.226) | 0.274 | 0.548 | |||||
No | 0.865 (0.611–1.224) | 0.878 (0.605–1.273) | 0.492 | 0.689 | |||||
Smoking status | 0.175 | –1.638 (–3.102–0.126) | –0.861 (–2.198–0.476) | 0.355 (0.072–1.759) | |||||
Yes | 0.614 (0.356–1.058) | 0.526 (0.281–0.983) | 0.044 | 0.205 | |||||
No | 0.918 (0.671–1.254) | 0.969 (0.695–1.351) | 0.852 | 0.918 | |||||
Drink | 0.403 | –0.768 (–1.472–0.634) | –1.638 (–4.107–0.831) | 0.250 (0.207–2.662) | |||||
Yes | 0.361 (0.149–0.878) | 0.318 (0.115–0.879) | 0.027 | 0.196 | |||||
No | 0.938 (0.705–1.248) | 0.969 (0.690–1.277) | 0.687 | 0.802 |
a. Adjustment for multiple comparisons using false discovery rate.
b. Breslow-Day heterogeneity test.
BMI, body mass index; RERI, relative excess risk of interaction;
AP, attributable proportion; S, Synergy Index.
Possible associations of rs12097901 C
rs12097901 | p | |||
CC | CG | GG | ||
Pre-FEV1 | 2.48 (2.14–3.09) | 2.65 (2.20–3.17) | 2.51 (2.08–3.17) | 0.204 |
Pre-FVC | 3.03 (2.56–3.84) | 3.20 (2.61–3.97) | 3.02 (2.49–3.90) | 0.278 |
Pre-FEV1/Pre-FVC | 78.30 (76.60–80.50) | 78.60 (76.50–80.30) | 77.40 (75.95–78.78) | 0.028 |
a. Rank sum test. FEV1, forced expiratory volume in one second; FVC, forced vital capacity.
The development of GWAS in recent years has led to many studies showing that
genetic polymorphisms are associated with the development of various diseases.
This includes an association with COPD, thus providing a new direction for the
study of COPD susceptibility. To study whether EGLN1 polymorphisms are
involved in COPD, we investigated the association of four SNP loci in
EGLN1 (rs41303095 A
Positive selection genome-wide scans of Tibetan populations revealed the
EGLN1 genetic locus encodes prolyl hydroxylase 2 (PHD2), which may allow
for adaptive biological changes in humans in response to the low oxygen
environment found in high plateaus [24]. Alterations in the hypoxia-inducible
factor (HIF) pathway were shown to be the mechanism underlying this adaptive
change [25, 26, 27]. Moreover, the genomic region containing EGLN1 was shown
to be one of the strongest selection signals in Tibetans [14]. The EGLN
family is itself a member of the larger 2-oxoglutarate and ferrous iron-dependent
oxygenase family [28], which has a role in maintaining oxygen homeostasis in
oxygen-organized metabolism in biological cellular tissues. The EGLN1
gene is located on human chromosome 1 (1q42.2) [29], which is the actual oxygen
receptor in mammals [30]. Several studies have shown that under hypoxic
stimulation, EGLN1 reduces its own activity [31, 32, 33], which means that
HIF-1
Studies conducted by Mishra et al. [34] and Sharma et al. [37]
on an Indo-Aryan population from the Tibetan plateau region found a significant
difference in expression of the EGLN1 rs480902 variant between patients
with high altitude pulmonary edema (HAPE) and healthy controls (p
Online web tools such as NCBI and Ensembl were used in the present study to find
the SNP location and functional information for the 4 SNPs investigated here.
EGLN1 rs41303095 A
The prevalence of COPD in individuals aged 40 years or more in the Gannan region
was previously found by our group to be 23.4% (20.7%–26.4%) [22]. This is
considerably higher than the national incidence of 13.7% (12.1%–15.5%) [50].
Moreover, the current study found that EGLN1 rs12097901 C
In summary, it is reasonable to assume that EGLN1 may be involved in COPD pathogenesis. However, this study failed to show a statistically significant association between EGLN1 genetic variants and COPD. This may be due to the screening of only a few loci, insufficient sample size, recall bias in the case-control studies, and lack of quality control in the field work. Further studies will be conducted to overcome these shortcomings and to identify more relevant loci.
The present study found that the EGLN1 rs41303095 A
COPD, chronic obstructive pulmonary disease; EGLN1, Egl-9 family of hypoxia-inducible factors; GWAS, genome-wide association analysis; SNPs, single nucleotide polymorphisms; FEV1, forceful expiratory volume in 1 second; FVC, forceful lung capacity; MAFs, minor allele frequencies; PCR, TaqMan real-time polymerase chain reaction.
The data that support the findings of this study are available from the corresponding author upon reasonable request.
XZ designed the research study. XL wrote the main manuscript and revised it with JY, PZ. Statistical analysis of the results was done mainly by JY with the participation of XL. CZ, YS, XuW, HL and AL contributed to sample collection for the case-control and prevalence studies, and for electronic medical record entry. ZY provided assistance with experimental design and conduct. PZ has given a lot in the integration and utilization of literature searches. XiW and YW were responsible for the overall study design and quality control as well as directing the study methodology. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work to take public responsibility for appropriate portions of the content and agreed to be accountable for all aspects of the work in ensuring that questions related to its accuracy or integrity.
This study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Boards of Xi’an Jiaotong University, Faculty of Medicine (Approval No.: XJTU 2016-411) and Guangzhou Medical University (Approval No.: GZMC2007-07-0676). In Furthermore, we interpreted the purpose of the study to all participants at the beginning of the study and obtained their signed informed consent.
We thank the Institute of Public Health, Guangzhou Medical University for their help. We thank the researchers in our laboratory for their guidance on experimental techniques.
This research was funded by the following grants: Fund project of Gansu Provincial Department of Education 2022CYZC-53 (Xinhua Wang); National Key Research and Development Program Project of Gansu Urban and Rural Natural Population Cohort Construction and Tumor Follow-up Research 2017YFC0907202 (Xinhua Wang).
The authors declare no conflict of interest.
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