Untargeted lipidomics of bronchopulmonary dysplasia induced by hyperoxia exposure in rats
Original Article

Untargeted lipidomics of bronchopulmonary dysplasia induced by hyperoxia exposure in rats

Yubai Li#, Qian Su#, Xudong Yan, Jie Qi, Huiying Tu, Jinjie Huang, Zhangbin Yu, Boshi Yu

Division of Neonatology, Department of Pediatrics, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China

Contributions: (I) Conception and design: Z Yu, B Yu; (II) Administrative support: Z Yu, B Yu; (III) Provision of study materials or patients: Y Li, Q Su; (IV) Collection and assembly of data: X Yan, J Qi; (V) Data analysis and interpretation: H Tu, J Huang; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work as co-first authors.

Correspondence to: Zhangbin Yu, PhD; Boshi Yu, MD. Division of Neonatology, Department of Pediatrics, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, First Affiliated Hospital of Southern University of Science and Technology, 1017 Dongmen North Road, Shenzhen 518020, China. Email: yuzhangbin@126.com; yuboshi@njmu.edu.cn.

Background: Bronchopulmonary dysplasia (BPD), characterized by impaired lung development, remains a leading cause of morbidity and mortality in premature infants. The synthesis and metabolism of lipids play a critical role in normal lung development, such as dipalmitoylphosphatidylcholine, a key component of pulmonary surfactant (PS). Therefore, we conducted a lipidomics study of rat lung tissue to explore the changes of pulmonary lipid composition in the progression of BPD disease.

Methods: In this study, we exposed neonatal Sprague-Dawley (SD) rats to hyperoxia for 14 days. After hyperoxia exposure, the lung tissues of rats were analyzed pathologically, and untargeted lipidomics was analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS).

Results: Hematoxylin-eosin (H&E) staining showed that the alveoli enlarged, the number of alveoli decreased and the pulmonary surfactant-associated protein D (SFTPD) decreased in hyperoxia-exposed rats. A total of 620 pulmonary lipids were detected by LC-MS/MS, covering 27 lipid categories. The most common lipids were triacylglycerol (TAG), followed by phosphatidylcholine (PC) and phosphatidylethanolamine (PE).

Conclusions: Compared with those rats exposed to normoxic conditions, the lipid levels in the lungs of rats exposed to hyperoxia for 14 days generally decreased, with the levels of TAG and PC decreasing most significantly. In short, our results provide a clue for finding therapeutic targets and biomarkers of a BPD rat model lung liposome.

Keywords: Bronchopulmonary dysplasia (BPD); lipidomics; rats; preterm; liquid chromatography-tandem mass spectrometry (LC-MS/MS)

Submitted Nov 08, 2023. Accepted for publication May 07, 2024. Published online May 24, 2024.

doi: 10.21037/tp-23-546

Highlight box

Key findings

• After 14 days of hyperoxia exposure in newborn rats, their alveoli showed bronchopulmonary dysplasia (BPD) like changes, and there were significant differences in lipid composition of lung tissue between the two groups.

What is known and what is new?

• BPD is characterized by impaired lung development. lipid metabolism is known to be closely related to lung development.

• We detected the lipidomics of lung tissue of rats exposed to hyperoxia for 14 days, which was closer to the lipidomics changes in clinical BPD lung tissue.

What is the implication, and what should change now?

• This means that children with BPD may be widely deficient in lipids. We should further detect lipid changes in children with BPD at the clinical level, and supplement corresponding lipids at the animal and clinical levels to evaluate BPD phenotypic changes.


Bronchopulmonary dysplasia (BPD) is a chronic lung disease that occurs in newborns and is the most common complication associated with premature birth (1). In recent years, with the improvement of neonatal nursing technology, effective respiratory support, and the application of prenatal corticosteroids and pulmonary surfactants (PSs), the survival rates of premature infants have significantly improved. Incidence of BPD leading to impaired lung development and diminished lung function in adulthood has increased (2). To expediate diagnosis and aid efficient treatment, a robust method for early identification of clinical biomarkers and identification of key, druggable, biological targets is necessary.

Lipids are the main component of biological membranes, and also play a role in signal transmission, regulation of cell growth, differentiation, proliferation, ferroptosis, and other signal transduction processes (3,4). In addition, lipids are an important component of PSs, which reduce alveolar surface tension and prevent alveolar atrophy during exhalation. PSs are mainly synthesized by Alveolar type II epithelial (AT2) cells, but the number of proliferating AT2 cells in the lung tissue of premature infants with BPD is reduced (5,6). Therefore, the synthesis of PS in premature infants with BPD may be hindered. Meanwhile, early application of PSs can reduce the mortality of premature infants and the incidence of BPD (7).

Treatment for preterm often includes the use of oxygen, which can either be administered as a nasal canula, continuous positive airway pressure (CPAP) or a ventilator. However, prolonged use of high concentration of oxygen can lead to excess oxygen supply in organs and tissues of premature infants, which may lead to the occurrence of BPD (8). Therefore, hyperoxia exposure is often used to induce the animal model of BPD.

At birth, the lung development of premature infants is likely to be in the cystic stage (9). Rodents are the only other animals with cystic lung development at birth, therefore newborn rats or mice are suitable for simulation of the physiological conditions of premature infants (10). Studies have found that rodents born at postnatal day (PND) 1 then exposed to 85% oxygen for 14 days can reproduce the clinical characteristics of BPD, such as simplification of alveoli, reduction in the number of alveoli and infiltration of inflammatory cells (11-13).

Previous study has found that neonatal mice at PND 1 were exposed to hyperoxia for 3 days then raised in a normoxic environment until either the 7th or 14th day. Lung tissue lipidomics were measured at PND 7 and PND 14. It was found that when compared with mice exposed to normoxic conditions, the range of lipid species present in the lung tissue of hyperoxia mice was reduced (14). However, investigations upon lipid composition variation in rat lung tissue following 14-day hyperoxia exposure are not yet available.

Thus, hyperoxia exposure for 14 days in rodents is often used to simulate clinical BPD lung injury, and no studies have reported the liposome changes in the lung tissue of neonatal rats in this model. Therefore, we used untargeted liposome to analyze the changes of lipids in lung tissue of neonatal rats after hyperoxia exposure. In this study, we examined lung lipid alterations in neonatal rats exposed to hyperoxia for 14 days using liquid chromatography-tandem mass spectrometry (LC-MS/MS). We present this article in accordance with the ARRIVE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-23-546/rc).



Newborn Sprague-Dawley (SD) rats were obtained from Guangdong Vital River Laboratory Animal Technology Company. Experiments were performed under a project license (No. AUP-220516-YZB-0295-01) granted by the Institutional Animal Care and Use Committee of Shenzhen People’s Hospital. Rats were treated in accordance with the National Institutes of Health (NIH) Guide for the Care and Use of Laboratory Animals. All rats were reared in a specific pathogen-free (SPF) animal laboratory with a temperature of between 20 and 26 ℃, a relative humidity of between 50% and 60%, and following natural circadian rhythms.

The establishment of BPD model

Newborn rats after birth within 24 hours from SD pregnant rats were divided into the normoxia group (n=10) and the hyperoxia group (n=10). These two groups were exposed to either 21% oxygen or 85% oxygen, respectively, postnatally for up to 14 days. To maintain a constant level of 85% oxygen, rats in the hyperoxia group were housed in chambers into which 85% oxygen was pumped. The hyperoxia group of rats were exposed to normoxia for 4 hours each day to prevent oxygen toxicity.

Lung preparation, histology, and immunohistochemistry

After the hyperoxia exposure ended on the 14th day, the rats were sacrificed and lung tissues were collected. The left lung was divided into three parts and fixed with 4% paraformaldehyde (pH 7.4, 20 cmH2O) for 2–24 hours. After immersion and embedding in wax, the sections were cut into 5 µm thick sections, dewaxed, and stained with hematoxylin-eosin (H&E). For immunohistochemistry, wax blocks were cut into 5 µm thick sections and subjected to deparaffinization, antigen retrieval, and endogenous peroxidase blocking. Use phosphate-buffered saline (PBS) containing 1.5% rabbit serum to block for 30 minutes at room temperature, then add goat anti-rabbit antibody the pulmonary surfactant-associated protein D (SFTPD; Proteintech, Wuhan, China; 1:100 dilution) to the slide and incubate overnight at 4 ℃. Next, the secondary antibody was dropped on the slide and incubated at room temperature for 50 minutes, and then 3,3'-diaminobenzidine (DAB) chromogenic solution was used and the nuclei were counterstained with hematoxylin. The right upper lung was simultaneously frozen in liquid nitrogen and subjected to lipidomic analysis. The radial alveolar count (RAC) method is used to count the number of alveoli in the terminal bronchi. Briefly, a line was drawn from the terminal bronchioles to the nearest interlobular septum and the number of distal air spaces traversed by the line was counted. Immunohistochemical quantification is to use Image J software to count the proportion of SFTPD-positive cells.

Metabolites extraction

The tissue sample (25 mg) was added to an eppendorf (EP) tube. Sequentially, water (200 µL) and the extract solution (480 µL, MTBE: MeOH, 5:1) were added. Following agitation for 30 seconds in a vortex mixer, samples were homogenized at 35 Hz for four minutes and then sonicated in an ice-water bath for 5 minutes. Three cycles of homogenization and sonication were carried out for each sample. Following a 1-hour incubation period at −40 ℃, the samples were centrifuged for 15 minutes at 4 ℃ at 3,000 rpm (RCF =900 ×g, R =8.6 cm). After being transferred to a new tube, the supernatant (300 µL) was dried at 37 ℃ in a vacuum concentrator. The dried samples were then reconstituted by sonicating for 10 minutes in an ice-water bath in a solution of 50% methanol in dichloromethane (200 µL). Following a 15-minute centrifugation at 13,000 rpm (RCF =16,200 ×g, R =8.6 cm) at 4 ℃, the supernatant (100 µL) was transferred to an LC/MS vial for analysis. The quality control (QC) sample comprised equal volumes (20 µL) of the supernatants from each sample.

LC-MS/MS analysis

An UHPLC system (1290, Agilent Technologies, Santa Clara, CA, USA) fitted with a Kinetex C18 column (2.1 mm × 100 mm, 1.7 µm, Phenomen) was utilized to conduct LC-MS/MS analysis. The mobile phase comprised an acetonitrile: water (60:40) solvent system, with ten mmol of ammonium formate per liter. For every liter of mixed solvent, acetonitrile: isopropanol (10:90, 50 mL) were added; mobile phase B.

Elution gradients of 0–1.0 minutes, 40% B; 1.0–12.0 minutes, 40–100% B; 12.0–13.5 minutes, 100% B; 13.5–13.7 minutes, 100–40% B; and 13.7–18.0 minutes, 40% B were used in the analysis. The column temperature was set to 55 ℃, the injection volume in both positive and negative-ion mode was 2 µL, and the auto-sampler temperature was 4 ℃.

Due to the capacity to collect MS-MS spectra in data-dependent acquisition (DDA) mode under the direction of the acquisition software (Xcalibur 4.0.27, Thermo, Waltham, MA, USA), a Thermo Q Exactive Orbitrap (QE) mass spectrometer was employed and the acquisition program constantly assessed the entire scan-range of the instrument. The following parameters were set for the electroencephalography source imaging (ESI) source: collision energy of 15/30/45 V in normalized collision energy (NCE) mode; sheath gas flow rate of 30 arb; auxiliary gas flow rate of 10 arb; capillary temperature of 320 ℃ (positive-ion mode) and 300 ℃ (negative-ion mode); full MS resolution of 70,000; MS/MS resolution of 17,500; spray voltage of 5 kV (positive-ion mode) or −4.5 kV (negative-ion mode), respectively.

Statistical analysis

The raw data files were converted to files in mzXML format using the ‘msconvert’ program from ProteoWizard. The CentWave algorithm in XCMS was used for peak detection, extraction, alignment, and integration. The minfrac for annotation was set at 0.5 and the cut-off for annotation was set at 0.3. Lipid identification was achieved through a spectroscopic match using LipidBlast library, which was developed using R packages based on XCMS. We applied the principal component analysis (PCA) and the orthogonal partial least square-discriminant analysis (OPLS-DA) to the lipidomics data for analyzing the differences between normoxia- and hyperoxia-exposed rats lung. The variable importance in projection (VIP) of the OPLS-DA model were employed to measure the influence intensity and interpretation ability of metabolite accumulation difference on sample classification and discrimination of each group. Statistical distinctness was established using the Student’s t-test, with P<0.05 signifying significance.


Alveolarization is impaired in rats with hyperoxia

To estimate the effect of hyperoxia on alveolarization, we harvested lung tissue from hyperoxia and normoxia groups. The results of H&E staining showed that after hyperoxia exposure, the pulmonary septum was broken and the inflammatory cells infiltrated. The lungs of hyperoxia-exposed rats exhibited enlarged alveoli, but a decreased number of alveoli (Figure 1A,1B).

Figure 1 Alveoli in rats is impaired with hyperoxia. (A) Representative images of H&E-stained tissue slices describing alveolation 14 days after birth in rats. Arrowheads represent rat alveolar area. (B) Summary data of quantitative histomorphometric analyses: RAC. (C) Representative images of histochemical stained tissue slices describing the expression of the pulmonary SFTPD 14 days after birth in rats. The arrowheads represent cells that express SFTPD protein. (D) Quantitative analysis of immunohistochemistry results. t-test; ***, P<0.001. H&E, hematoxylin-eosin; SFTPD, surfactant-associated protein D; RAC, radial alveolar count.

The damage to alveoli due to hyperoxia via expression of SFTPD, which is the surface marker of type II alveolar epithelial cells, was evaluated. Analysis of histochemical data showed that expression of SFTPD in lung tissues from the hyperoxia group was significantly reduced compared to the lung tissues from the normoxia group (Figure 1C,1D). These results indicate that rats developed a BPD-like phenotype that was characterized by impaired alveolarization and damaged alveolar epithelial cells upon exposure to 85% oxygen for 14 days.

Multivariate statistical analysis of lipids

LC-MS/MS was used to profile the rat lung tissues lipids in normoxia and hyperoxia groups. Deviation filtering, missing value filtering, missing value filling, and normalization were utilized during preprocessing of the original data, with 17,812 peaks retained after preprocessing. Twenty-seven lipid categories, comprising 620 lipids, were detected and identified across both positive-ion mode and negative-ion mode.

The QC program demonstrates that data are repeatable in both positive- and negative-ion modes. The QC samples were closely clustered together, as shown by PCA, demonstrating the stability and dependability of the experimental apparatus and data (Figure 2A).

Figure 2 Multivariate statistical analysis of lipids. (A) Scattered point plots of PCA for all samples (including QC samples). The abscissa represents the score of the first principal component, and the ordinate represents the score of the second principal component. (B) Score scatter plot of PCA model for the normoxia group versus the hyperoxia group. The abscissa represents the score of the first principal component, and the ordinate represents the score of the second principal component. (C) Score scatter plot of OPLS-DA model for the normoxia group versus the hyperoxia group. The abscissa represents the predicted principal component score of the first principal component showing the difference between sample groups, and the vertical coordinate indicates the orthogonal principal component score, showing the difference within sample groups. (D) Permutation plot test of OPLS-DA model for the normoxia group versus the hyperoxia group. The abscissa indicates the permutation retention degree of the permutation test, and the ordinate indicates the value of R2Y or Q2, the green dot represents the R2Y value obtained by permutation test, the blue square dot represents the Q2 value obtained by permutation test, and the two dotted lines represent the regression lines of R2Y and Q2, respectively. QC, quality control; PC, principal component; PCA, principal component analysis; OPLS-DA, orthogonal partial least square-discriminant analysis.

PCA was performed to highlight the overall distribution-trend of metabonomic data and the degree of difference between the normoxia and hyperoxia groups. It was shown that all samples were within 95% confidence interval (CI), and there was significant difference between normoxia group and hyperoxia group (Figure 2B). Since PCA was an unsupervised classification model, these data would likely be affected by many variables independent of the grouping information, therefore OPLS-DA was further used to analyze the results. The OPLS-DA score plots showed that lipid metabolism differs significantly between the normoxia and hyperoxia groups (Figure 2C). These findings suggest that newborn rats exposed to hyperoxia experience considerable lipid profile abnormalities.

In order to further validate the OPLS-DA model, a permutation test was undertaken (n=200). The R2Y and Q2 regression lines were located at (0, 0.39) and (0, −1.18) (Figure 2D). As the greatest R2Y and Q2 in the current sample cluster, the OPLS-DA model was shown to be robust and did not exhibit overfitting.

Suppression of lung lipid levels after hyperoxia was exposed

After analysis, different metabolites were identified using a combination of the unit variable and multivariate statistical analysis results. Volcano plots were used to visualize the overall distribution of metabolite differences following hyperoxia exposure. There were 1,574 significantly different metabolites (VIP >1.5, P<0.01) between hyperoxia- and normoxia-exposed rats, including 1546 upregulated metabolites and 28 downregulated metabolites across both positive- and negative-ion modes (Figure 3A). A Z-score plot further displayed the distribution of each differential lipid in both normoxic and hyperoxic environments (Figure 3B). As shown in Figure 3C, 50 lipids were downregulated in the hyperoxia group, resulting in significantly different lipid ratios. The significantly different lipids are shown in Table S1.

Figure 3 Suppression of lung lipid levels after hyperoxia exposure. (A) Volcano map of differential metabolites screening for the modeling group by control group. The abscissa represents the multiple change of each substance in the group, the ordinate represents the P value, and the scatter size represents the VIP value. Significantly up-regulated metabolites are indicated in red, significantly down-regulated metabolites in blue, and non-significantly different metabolites in gray. (B) Z-score plot of the normoxia group versus the hyperoxia group. The Z-score plot is to normalize the differential metabolites in different samples by calculating the Z-score value, the abscissa represents the Z value, the ordinate represents the differential metabolite, and the points of different colors represent different groups of samples. (C) Hierarchical cluster analysis of heat maps of the normoxia group and the hyperoxia group. The abscissa represents different experimental groups, and ordinate represents differential metabolites of this group. Red indicates that the substance is highly expressed in the group in which it is located, and blue indicates that the content of the substance in the group is low. (D) Matchstick diagram of the normoxia group versus the hyperoxia group. The abscissa is the multiple of change after logarithmic conversion, and the color of the point represents the VIP value. t-test; **, P<0.01; ***, P<0.001. VIP, variable importance in projection; TAG, triacylglycerol; HexCer/AP, hexosylceramide alpha-hydroxy fatty acid-phytosphingosine; DGTS, diacylglyceryl trimethylhomoserine; PC, phosphatidylcholine.

Using the fold change (FC) as standard, we showed the 10 lipids that changed most in terms of ratio (Figure 3D) included: diacylglyceryl trimethylhomoserine (DGTS) (27:0/20:3), triacylglycerol (TAG) (13:0/22:5/22:5), phosphatidylcholine (PC) (14:0e/22:0), TAG (12:1/19:0/19:0), TAG (18:4/18:5/19:0), TAG (17:3/18:5/20:0), DGTS (27:0/22:5), hexosylceramide alpha-hydroxy fatty acid-phytosphingosine (HexCer/AP) (t15:0/34:2), TAG (13:1/19:3/19:3), and TAG (17:1/22:6/22:6). In addition, the intrapulmonary lipid levels in the rats’ lungs generally reduced after being exposed to hyperoxia for 14 days.

TAG and PC prevalence decreased most significantly in hyperoxia-induced lung injury

Bar plot and bubble plots showed the degree and significance in change of different lipid categories after hyperoxia exposure. Overall, 27 lipid subclasses including TAG, sulfoquinovosyl diacylglycerol (SQDG), sphingomyelin (SM), sulfur hexosylceramide hydroxy fatty acid (SHexCer), phosphatidylserine (PS), phosphatidylinositol (PI), phosphatidylglycerol (PG), phosphatidylethanolamine (PE), PC, oxidized PS (OxPS), oxidized PI (OxPI), oxidized PC (OxPC), lysophosphatidylserine (LPS), lysophosphatidylglycerol (LPG), lysophosphatidylethanolamine (LPE), lysophosphatidylcholine (LPC), hexosylceramide non-hydroxy fatty acid-sphingosine (HexCer/NS), hexosylceramide non-hydroxy fatty acid-dihydrosphingosine (HexCer/NDS), HexCer/AP, glucuronosyl diacylglycerol (GlcADG), free fatty acid (FA), DGTS, diacylglycerol (DAG), ceramide non-hydroxy fatty acid-sphingosine (Cer/NS), ceramide non-hydroxy fatty acid-dihydrosphingosine (Cer/NDS), acylcarnitine (ACar), and acylglucuronosyl diacylglycerol (AcylGlcADG) were significantly different between the normorxia and hyperoxia groups. TAG and PC downregulated drastically in hyperoxia group (Figure 4A,4B). The five TAGs that were most significantly down-regulated in the hyperoxia group included TAG (13:0/22:5/22:5), TAG (12:1/19:0/19:0), TAG (18:4/18:5/19:0), TAG (17:3/18:5/20:0), TAG (13:1/19:3/19:3) (Figure 5A). The five PCs that were most significantly down-regulated in the hyperoxia group included PC (14:0e/22:0), PC (13:0/13:0), PC (14:0e/26:4), PC (14:0/14:0), PC (18:5e/19:2) (Figure 5B).

Figure 4 The relative difference of lipids in lung tissue of rats after hyperoxia exposure. (A) A bar plot of the normoxia group versus the hyperoxia group. Each column in the bar plot represents a metabolite. The vertical coordinate represents the relative percentage change of the content of each substance in the group, and the horizontal coordinate represents the classification information of lipids. (B) Bubble plot of the normoxia group versus the hyperoxia group. Each point in the bubble plot of the lipid group represents a metabolite. The size of the dot represents the P value of the Student’s t-test. The gray dots represent the non-significant differences with P value not less than 0.05, and the colored dots represent the significant differences with P value less than 0.05. The abscissa represents the relative change percentage of each substance content in the group, and the ordinate represents the classification information of lipids. The black line at the bottom shows the distribution density of metabolites.
Figure 5 TAG and PC decreased most significantly in hyperoxia-induced lung injury. (A) The five TAGs most significantly down-regulated in the hyperoxia group. (B) The five PCs most significantly down-regulated in the hyperoxia group. TAG, triacylglycerol; PC, phosphatidylcholine.

Identification of a lipid fingerprint specific for BPD rat model

We next explored whether any lipids could serve as a fingerprint to discriminate BPD from other diseases. To address this, we computed the area under the curve (AUC) for each of the 50 significantly different lipids to assess discriminating accuracy in a BPD rat model. The 50 lipids ranked by AUCs, 95% CI, and P value are listed in Table S2. AUCs of 50 lipids were between 0.89 and 1, which showed that these 50 different lipids had significant associations with BPD in the rat model. It was noted that among the 10 lipids that attained the highest AUCs and lowest P value, there were six members of the TAG family [TAG (13:0/22:5/22:5), TAG (13:1/19:3/19:3), TAG (14:2/19:3/22:5), TAG (15:1/16:0/22:7), TAG (15:3/21:4/21:4), TAG (17:3/17:3/21:3)], two members of the PC family [PC (13:0/13:0), PC (15:1/19:2)] and two members of the DGTS family [DGTS (24:0/26:4), DGTS (27:0/18:3)] (Figure 6). The AUC of PC (13:0/13:0) was 1, which means PC (13:0/13:0) was a specific fingerprint for BPD rat model.

Figure 6 The AUC of the top 10 significant differences in lipids based on P value. The AUC is between 1.0 and 0.5. The closer the AUC to 1, the better the diagnostic effect. DGTS, diacylglyceryl trimethylhomoserine; AUC, area under the curve; CI, confidence interval; PC, phosphatidylcholine; TAG, triacylglycerol.


This study described the pathological and liposomal characteristics of lung tissue of rats exposed to hyperoxia for 14 days, allowing for a murine BPD model. The main findings of our study are as follows: (I) compared with normoxia, the numbers of alveoli are reduced, although the size of each alveolus is increased, and the pulmonary septum is broken after hyperoxia exposure; (II) after hyperoxia exposure for 14 days, the lipids levels in lung tissue of rats were reduced, among which TAG and PC decreased most significantly; and (III) PC (13:0/13:0) can be used as a unique fingerprint to predict the BPD model caused by hyperoxia exposure.

Study has reported changes in lipidomics in the lungs of mice after being exposed to hyperoxia for 3 days and returning to normoxia on the 7th or 14th day (14). This study examined the lipidomics changes in rats exposed to hyperoxia for 14 days. Hyperoxia exposure is now the mainstream choice for animal modeling of BPD. Different oxygen concentrations and durations also have different effects on the lung damage caused by hyperoxia (15). Study has reported that 85% O2 is the only oxygen concentration that affects both the number of alveoli and the alveolar interval and at 85% oxygen concentration, hyperoxia exposure for 14 days showed more obvious BPD-like changes than hyperoxia exposure for 3 days (16). Therefore, our study can better simulate the changes in lipidomics under clinical BPD lung injury.

Our data show that the expression of 27 lipid categories, comprising 620 lipids, in the lung tissue of rats was inhibited after hyperoxia exposure. It is worth noting that the decrease in levels of TAG and PC are most significant. TAG is the main source of energy within the body, with metabolic disorders of TAG easily leading to insulin resistance and cardiovascular disease (17). In the stage from embryonic development to newborn birth, TAG can be obtained from the mother and is continuously decomposed and metabolized during embryogenesis (18-20). Fetuses continue to increase the synthesis of their own TAG as they approach delivery but preterm delivery may break the fetus’ own TAG reserve, resulting in low levels of TAG in premature infants. In addition, study has reported that the TAG content in the lung tissue of mice gradually increases after birth and reaches a peak 14 days after birth (21). But in our study, we found that the TAG content in the lung tissue of rats decreased significantly after 14 days of hyperoxia exposure. A large amount of TAG is required in the early stages of neonatal life, but hyperoxic exposure inhibits the TAG content in neonates, suggesting that TAG may play an important role in the occurrence of BPD. Therefore, screening appropriate TAG intervention models for BPD will be our next step. PC is an important component of PS, and is secreted by AT2 cells to prevent alveolar collapse and reduce alveolar surface tension. The lung buds derived from the precursors of the embryonic foregut endoderm invade the visceral mesenchymal cells and undergo branching morphogenesis to form conductive airways (22). In the late stage of embryonic development, alveolar alveoli begin to develop at the end of the dendritic terminal trachea. at the same time, alveolar epithelial progenitor cells differentiate into type I alveolar epithelial cells and type II alveolar epithelial cells (23). Type 2 alveolar epithelial cells of premature infants are not fully differentiated at birth, resulting in a lack of PS at birth. Other study has shown that the composition of lipids in PS can activate macrophages and affect the defense response of lung hosts (24).

With the improvement of prenatal corticosteroids and perinatal nursing techniques, the survival rate of premature and low-weight newborns is significantly improved, but this has resulted in an increased incidence of BPD (2). However, there is a lack of means to monitor biomarkers for early diagnosis of BPD. Our research has shown that in a BPD rat model, ten lipids are significantly down-regulated in neonatal rat lungs, and these could potentially be used to monitor BPD. In addition, differential lipid receiver operating characteristic (ROC) analysis showed that the AUC of PC (13:0/13:0) was 1.0, and could be used to distinguish between BPD rats exposed to hyperoxia and newborn rats growing in normoxic environment. Therefore, PC (13:0/13:0) could be used as a biomarker for early diagnosis of BPD.

Our research still has some limitations. We screened 10 lipids including DGTS (27:0/20:3), TAG (13:0/22:5/22:5), PC (14:0e/22:0), TAG (12:1/19:0/19:0), TAG (18:4/18:5/19:0), TAG (7:3/18:5/20:0), DGTS (27:0/22:5), HexCer/AP (t15:0/34:2), TAG (13:1/19:3/19:3), and TAG (7:1/22:6/22:6), with the greatest change after hyperoxia exposure identified by lipogenomics analysis. However, we did not verify the role of these lipids in BPD animal model. Secondly, we did not verify the changes of PC in the early lung tissue of the BPD model, and did not analyze the relationship between PC and BPD in clinical blood samples and bronchoalveolar lavage fluid.

In summary, this study provides a comprehensive picture of lipids in the lung tissue of BPD rats by analyzing the lipids in the lungs of rats exposed to normoxic and hyperoxic environments for 14 days. At present, there is no lipogenomic analysis of lung tissue in a BPD model. Our study exposes the changes of lipid composition in lung tissue in a BPD model, and provides clues for finding intervention targets and diagnostic markers of BPD.


Hyperoxic exposure in neonatal rats can lead to simplification of alveoli and generalized suppression of lipid expression in lung tissue, especially the decrease of TAG and PC.


Funding: This study was supported by the Shenzhen Science and Technology Program (Nos. JCYJ20220530152415031, JCYJ20220530152415034, and JCYJ20230807112405011).


Reporting Checklist: The authors have completed the ARRIVE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-23-546/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-23-546/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-23-546/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-23-546/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Experiments were performed under a project license (No. AUP-220516-YZB-0295-01) granted by the Institutional Animal Care and Use Committee of Shenzhen People’s Hospital, in compliance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


  1. Cassady SJ, Lasso-Pirot A, Deepak J. Phenotypes of Bronchopulmonary Dysplasia in Adults. Chest 2020;158:2074-81. [Crossref] [PubMed]
  2. Kotecha S, Doull I, Wild J, et al. Prematurity-associated lung disease: looking beyond bronchopulmonary dysplasia. Lancet Respir Med 2022;10:e46. [Crossref] [PubMed]
  3. Chen W, Zheng D, Yang C. The Emerging Roles of Ferroptosis in Neonatal Diseases. J Inflamm Res 2023;16:2661-74. [Crossref] [PubMed]
  4. Qiu B, Zandkarimi F, Bezjian CT, et al. Phospholipids with two polyunsaturated fatty acyl tails promote ferroptosis. Cell 2024;187:1177-1190.e18. [Crossref] [PubMed]
  5. Fan LC, McConn K, Plataki M, et al. Alveolar type II epithelial cell FASN maintains lipid homeostasis in experimental COPD. JCI Insight 2023;8:e163403. [Crossref] [PubMed]
  6. Gao F, Li C, Danopoulos S, et al. Hedgehog-responsive PDGFRa(+) fibroblasts maintain a unique pool of alveolar epithelial progenitor cells during alveologenesis. Cell Rep 2022;39:110608. [Crossref] [PubMed]
  7. Moraes LHA, Coelho RMD, Neves Dos Santos Beozzo GP, et al. Use of budesonide associated with a pulmonary surfactant to prevent bronchopulmonary dysplasia in premature newborns - A systematic review. J Pediatr (Rio J) 2023;99:105-11. [Crossref] [PubMed]
  8. Gilfillan M, Bhandari A, Bhandari V. Diagnosis and management of bronchopulmonary dysplasia. BMJ 2021;375:n1974. [Crossref] [PubMed]
  9. Thébaud B, Goss KN, Laughon M, et al. Bronchopulmonary dysplasia. Nat Rev Dis Primers 2019;5:78. [Crossref] [PubMed]
  10. Berger J, Bhandari V. Animal models of bronchopulmonary dysplasia. The term mouse models. Am J Physiol Lung Cell Mol Physiol 2014;307:L936-47. [Crossref] [PubMed]
  11. Hirani D, Alvira CM, Danopoulos S, et al. Macrophage-derived IL-6 trans-signalling as a novel target in the pathogenesis of bronchopulmonary dysplasia. Eur Respir J 2022;59:2002248. [Crossref] [PubMed]
  12. Willis GR, Fernandez-Gonzalez A, Anastas J, et al. Mesenchymal Stromal Cell Exosomes Ameliorate Experimental Bronchopulmonary Dysplasia and Restore Lung Function through Macrophage Immunomodulation. Am J Respir Crit Care Med 2018;197:104-16. [Crossref] [PubMed]
  13. Sucre JMS, Vickers KC, Benjamin JT, et al. Hyperoxia Injury in the Developing Lung Is Mediated by Mesenchymal Expression of Wnt5A. Am J Respir Crit Care Med 2020;201:1249-62. [Crossref] [PubMed]
  14. Peterson AL, Carr JF, Ji X, et al. Hyperoxic Exposure Caused Lung Lipid Compositional Changes in Neonatal Mice. Metabolites 2020;10:340. [Crossref] [PubMed]
  15. Silva DM, Nardiello C, Pozarska A, et al. Recent advances in the mechanisms of lung alveolarization and the pathogenesis of bronchopulmonary dysplasia. Am J Physiol Lung Cell Mol Physiol 2015;309:L1239-72. [Crossref] [PubMed]
  16. Nardiello C, Mižíková I, Silva DM, et al. Standardisation of oxygen exposure in the development of mouse models for bronchopulmonary dysplasia. Dis Model Mech 2017;10:185-96. [Crossref] [PubMed]
  17. Karantonis HC, Nomikos T, Demopoulos CA. Triacylglycerol metabolism. Curr Drug Targets 2009;10:302-19. [Crossref] [PubMed]
  18. Carvalho M, Sampaio JL, Palm W, et al. Effects of diet and development on the Drosophila lipidome. Mol Syst Biol 2012;8:600. [Crossref] [PubMed]
  19. Guan XL, Cestra G, Shui G, et al. Biochemical membrane lipidomics during Drosophila development. Dev Cell 2013;24:98-111. [Crossref] [PubMed]
  20. Tennessen JM, Bertagnolli NM, Evans J, et al. Coordinated metabolic transitions during Drosophila embryogenesis and the onset of aerobic glycolysis. G3 (Bethesda) 2014;4:839-50. [Crossref] [PubMed]
  21. Dautel SE, Kyle JE, Clair G, et al. Lipidomics reveals dramatic lipid compositional changes in the maturing postnatal lung. Sci Rep 2017;7:40555. [Crossref] [PubMed]
  22. Metzger RJ, Klein OD, Martin GR, et al. The branching programme of mouse lung development. Nature 2008;453:745-50. [Crossref] [PubMed]
  23. Li J, Wang Z, Chu Q, et al. The Strength of Mechanical Forces Determines the Differentiation of Alveolar Epithelial Cells. Dev Cell 2018;44:297-312.e5. [Crossref] [PubMed]
  24. da Costa Loureiro L, da Costa Loureiro L, Gabriel-Junior EA, et al. Pulmonary surfactant phosphatidylcholines induce immunological adaptation of alveolar macrophages. Mol Immunol 2020;122:163-72. [Crossref] [PubMed]
Cite this article as: Li Y, Su Q, Yan X, Qi J, Tu H, Huang J, Yu Z, Yu B. Untargeted lipidomics of bronchopulmonary dysplasia induced by hyperoxia exposure in rats. Transl Pediatr 2024;13(5):748-759. doi: 10.21037/tp-23-546

Download Citation