Weighted Gene Co-expression Network Analysis of Key Biomarkers Associated With Bronchopulmonary Dysplasia

Time-resolved transcriptomic profiling of the developing rabbit's lungs: impact of premature birth and implications for modelling bronchopulmonary dysplasia

BACKGROUND

Premature birth, perinatal inflammation, and life-saving therapies such as postnatal oxygen and mechanical ventilation are strongly associated with the development of bronchopulmonary dysplasia (BPD); these risk factors, alone or combined, cause lung inflammation and alter programmed molecular patterns of normal lung development. The current knowledge on the molecular regulation of lung development mainly derives from mechanistic studies conducted in newborn rodents exposed to postnatal hyperoxia, which have been proven useful but have some limitations.

METHODS

Here, we used the rabbit model of BPD as a cost-effective alternative model that mirrors human lung development and, in addition, enables investigating the impact of premature birth per se on the pathophysiology of BPD without further perinatal insults (e.g., hyperoxia, LPS-induced inflammation). First, we characterized the rabbit's normal lung development along the distinct stages (i.e., pseudoglandular, canalicular, saccular, and alveolar phases) using histological, transcriptomic and proteomic analyses. Then, the impact of premature birth was investigated, comparing the sequential transcriptomic profiles of preterm rabbits obtained at different time intervals during their first week of postnatal life with those from age-matched term pups.

RESULTS

Histological findings showed stage-specific morphological features of the developing rabbit's lung and validated the selected time intervals for the transcriptomic profiling. Cell cycle and embryo development, oxidative phosphorylation, and WNT signaling, among others, showed high gene expression in the pseudoglandular phase. Autophagy, epithelial morphogenesis, response to transforming growth factor β, angiogenesis, epithelium/endothelial cells development, and epithelium/endothelial cells migration pathways appeared upregulated from the 28th day of gestation (early saccular phase), which represents the starting point of the premature rabbit model. Premature birth caused a significant dysregulation of the inflammatory response. TNF-responsive, NF-κB regulated genes were significantly upregulated at premature delivery and triggered downstream inflammatory pathways such as leukocyte activation and cytokine signaling, which persisted upregulated during the first week of life. Preterm birth also dysregulated relevant pathways for normal lung development, such as blood vessel morphogenesis and epithelial-mesenchymal transition.

CONCLUSION

These findings establish the 28-day gestation premature rabbit as a suitable model for mechanistic and pharmacological studies in the context of BPD.

Ultra-low-coverage genome-wide association study-insights into gestational age using 17,844 embryo samples with preimplantation genetic testing

BACKGROUND

Very low-coverage (0.1 to 1×) whole genome sequencing (WGS) has become a promising and affordable approach to discover genomic variants of human populations for genome-wide association study (GWAS). To support genetic screening using preimplantation genetic testing (PGT) in a large population, the sequencing coverage goes below 0.1× to an ultra-low level. However, the feasibility and effectiveness of ultra-low-coverage WGS (ulcWGS) for GWAS remains undetermined.

METHODS

We built a pipeline to carry out analysis of ulcWGS data for GWAS. To examine its effectiveness, we benchmarked the accuracy of genotype imputation at the combination of different coverages below 0.1× and sample sizes from 2000 to 16,000, using 17,844 embryo PGT samples with approximately 0.04× average coverage and the standard Chinese sample HG005 with known genotypes. We then applied the imputed genotypes of 1744 transferred embryos who have gestational ages and complete follow-up records to GWAS.

RESULTS

The accuracy of genotype imputation under ultra-low coverage can be improved by increasing the sample size and applying a set of filters. From 1744 born embryos, we identified 11 genomic risk loci associated with gestational ages and 166 genes mapped to these loci according to positional, expression quantitative trait locus, and chromatin interaction strategies. Among these mapped genes, CRHBP, ICAM1, and OXTR were more frequently reported as preterm birth related. By joint analysis of gene expression data from previous studies, we constructed interrelationships of mainly CRHBP, ICAM1, PLAGL1, DNMT1, CNTLN, DKK1, and EGR2 with preterm birth, infant disease, and breast cancer.

CONCLUSIONS

This study not only demonstrates that ulcWGS could achieve relatively high accuracy of adequate genotype imputation and is capable of GWAS, but also provides insights into the associations between gestational age and genetic variations of the fetal embryos from Chinese population.

Network module function enrichment analysis of lung squamous cell carcinoma and lung adenocarcinoma

BACKGROUND

Lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) are the two major subtypes of non-small cell lung cancer that pose a serious threat to human health. However, both subtypes currently lack effective indicators for early diagnosis.

METHODS

To identify tumor-specific indicators and predict cancer-related signaling pathways, LUSC and LUAD gene weighted co-expression networks were constructed. Combined with clinical data, core genes in LUSC and LUAD modules were then screened using protein-protein interaction networks and their functions and pathways were analyzed. Finally, the effect of core genes on survival of LUSC and LUAD patients was evaluated.

RESULTS

We identified 12 network modules in LUSC and LUAD, respectively. LUSC modules "purple" and "green" and LUAD modules "brown" and "pink" are significantly associated with overall survival and clinical traits of tumor node metastasis, respectively. Eleven genes from LUSC and eight genes from LUAD were identified as candidate core genes, respectively. Survival analysis showed that high expression of SLIT3, ABI3BP, MYOCD, PGM5, TNXB, and DNAH9 are associated with decreased survival in LUSC patients. Furthermore, high expression of BUB1, BUB1B, TTK, and UBE2C are associated with lower patient survival.

CONCLUSIONS

We found biomarker genes and biological pathways for LUSC and LUAD. These network hub genes are associated with clinical characteristics and patient outcomes and they may play important roles in LUSC and LUAD.

Big Data for Tiny Patients: A Precision Medicine Approach to Bronchopulmonary Dysplasia

Bronchopulmonary dysplasia (BPD) is the most common chronic lung disease of extreme prematurity. Despite more than 50 years of research, current treatments are ineffective, and clinicians are largely unable to accurately predict which neonates the condition will develop in. A deeper understanding of the molecular mechanisms underlying the characteristic arrest in lung development are warranted. Integrating high-fidelity technology from precision medicine approaches may fill this gap and provide the tools necessary to identify biomarkers and targetable pathways. In this review, we describe insights garnered from current studies using omics for BPD prediction and stratification. We conclude by describing novel programs that will integrate multi-omics in efforts to better understand and treat the pathogenesis of BPD. [Pediatr Ann. 2022;51(10):e396-e404.].

Lef1 is transcriptionally activated by Klf4 and suppresses hyperoxia-induced alveolar epithelial cell injury

PURPOSE

Bronchopulmonary dysplasia (BPD) is a long-term respiratory condition. More than a quarter of extremely premature newborns are harmed by BPD. At present, there are no apparent effective drugs or treatments for the condition. In this study, we aimed to investigate the functional role and mechanism of lymphoid enhancer-binding factor 1 (Lef1) in BPD in vitro.

MATERIALS AND METHODS

Blood samples from BPD patients and healthy volunteers were gathered, and an in vitro model of BPD was developed in alveolar epithelial cells (AECs) MLE-12 induced by hyperoxia. Then expression of krüppel-like factor 4 (KLF4/Klf4) and LEF1/Lef1 were evaluated. After Lef1 overexpressing plasmid and the vector were transfected into hyperoxia-induced MLE-12 cells, cell proliferation assays were carried out. Cell apoptosis was investigated by a flow cytometry assay, and apoptosis related proteins Bcl-2, cleaved-caspase 3 and 9 were analyzed by a western blot assay. The binding between Klf4 and Lef1 promoter predicted on the JASPAR website was verified using luciferase and ChIP assays. For further study of the mechanism of Klf4 and Lef1 in BPD, gain-of-function experiments were performed.

RESULTS

The mRNA levels of KLF4/Klf4 and LEF1/Lef1 were diminished in clinical BPD serum samples and hyperoxia-induced MLE-12 cells. Overexpression of Lef1 stimulated AEC proliferation and suppressed AEC apoptosis induced by hyperoxia. Mechanically, Klf4 bound to Lef1's promoter region and aids transcription. Moreover, the results of gain-of-function experiments supported that Klf4 could impede AEC damage induced by hyperoxia via stimulating Lef1.

CONCLUSION

Klf4 and Lef1 expression levels were declined in hyperoxia-induced AECs, and Lef1 could be transcriptionally activated by Klf4 and protect against hyperoxia-induced AEC injury in BPD. As a result, Lef1 might become a prospective therapeutic target for BPD.

Identification of Key Genes Associated With Early Calf-Hood Nutrition in Subcutaneous and Visceral Adipose Tissues by Co-Expression Analysis

Background

Substantive evidence has confirmed that nutrition state is associated with health risk and the onset of pubertal and metabolic profile. Due to heterogeneity, adipose tissues in different anatomical positions tend to show various metabolic mechanisms for nutrition. To date, the complicated molecular mechanisms of early calf-hood nutrition on bovine adipose tissue are still largely unknown. This study aimed to identify key genes and functionally enriched pathways associated with early calf-hood nutrition in visceral and subcutaneous adipose tissue.

Results

The RNA-seq data of visceral and subcutaneous adipose tissues of calves feeding on low and high dietary nutrition for more than 100 days were downloaded and analyzed by weighted gene co-expression network analysis (WGCNA). Two modules that positively associated with a low plane of nutrition diet and two modules with a high plane of nutrition diet were identified in the subcutaneous adipose tissue. The blue and yellow modules, most closely associated with low and high nutrition, were selected for the functional enrichment analysis and exploration of hub genes. The results showed that genes in the blue module were significantly enriched in pathways that related to fat metabolism, reproduction, and cell communication. Genes in the yellow module were enriched in pathways related to fat metabolism, reproduction, cell proliferation, and senescence. Meanwhile, the blue and brown modules in visceral adipose tissue were most closely associated with low and high nutrition, respectively. Notably, genes of the blue module were significantly enriched in pathways related to substance metabolism, and genes in the brown module were significantly enriched in energy metabolism and disease pathways. Finally, key genes in subcutaneous adipose tissue for low nutrition (PLCG1, GNA11, and ANXA5) and high nutrition (BUB1B, ASPM, RRM2, PBK, NCAPG, and MKI67), and visceral adipose tissue for low nutrition (RPS5, RPL4, RPL14, and RPLP0) and high nutrition (SDHA and AKT1) were obtained and verified.

Conclusion

The study applied WGCNA to identify hub genes and functionally enriched pathways in subcutaneous and visceral adipose tissue and provided a basis for studying the effect of early calf-hood nutrition on the two adipose tissue types.

ForkJoinPcc Algorithm for Computing the Pcc Matrix in Gene Co-Expression Networks

High-throughput microarrays contain a huge number of genes. Determining the relationships between all these genes is a time-consuming computation. In this paper, the authors provide a parallel algorithm for finding the Pearson’s correlation coefficient between genes measured in the Affymetrix microarrays. The main idea in the proposed algorithm, ForkJoinPcc, mimics the well-known parallel programming model: the fork–join model. The parallel MATLAB APIs have been employed and evaluated on shared or distributed multiprocessing systems. Two performance metrics—the processing and communication times—have been used to assess the performance of the ForkJoinPcc. The experimental results reveal that the ForkJoinPcc algorithm achieves a substantial speedup on the cluster platform of 62× compared with a 3.8× speedup on the multicore platform.

Network Pharmacology and Molecular Docking Elucidate the Pharmacological Mechanism of the OSTEOWONDER Capsule for Treating Osteoporosis

Background: Osteoporosis (OP) is a serious and common bone metabolic disease with bone mass loss and bone microarchitectural deterioration. The OSTEOWONDER capsule is clinically used to treat OP. However, the potential regulatory mechanism of the OSTEOWONDER capsule in treatment of OP remains largely unknown.

Methods: The bioactive compounds of herbs and their targets were identified using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. The speculative targets of OP were screened out based on GeneCards, DisGeNET, and Online Mendelian Inheritance in Man (OMIM) databases. The gene modules and hub genes of OP were identified using a weighted gene co-expression network analysis (WGCNA). Then, an herb-compound-target network was constructed based on the above analyses. The biological function of targets was subsequently investigated, and a protein–protein interaction (PPI) network was constructed to identify hub targets of OP. Finally, molecular docking was performed to explore the interaction between compounds and targets.

Results: A total of 148 compounds of eight herbs and the corresponding 273 targets were identified based on the TCMSP database. A total of 4,929 targets of OP were obtained based on GeneCards, DisGeNET, and OMIM databases. In addition, six gene modules and 4,235 hub genes of OP were screened out based on WGCNA. Generally, an herb-compound-target network, including eight herbs, 84 compounds, and 58 targets, was constructed to investigate the therapeutic mechanism of the OSTEOWONDER capsule for OP. The biofunction analysis indicated 58 targets mainly associated with the bone metabolism, stimulation response, and immune response. EGFR, HIF1A, MAPK8, IL6, and PPARG were identified as the hub therapeutic targets in OP. Moreover, the interaction between EGFR, HIF1A, MAPK8, IL6, PPARG, and the corresponding compounds (quercetin and nobiletin) was analyzed using molecular docking.

Conclusion: Our finding discovered the possible therapeutic mechanisms of the OSTEOWONDER capsule and supplied the potential therapeutic targets for OP.

Co-expression network analysis for identification of novel biomarkers of bronchopulmonary dysplasia model

BACKGROUND

Bronchopulmonary dysplasia (BPD) is the most common neonatal chronic lung disease. However, its exact molecular pathogenesis is not understood. We aimed to identify relevant gene modules that may play crucial roles in the occurrence and development of BPD by weighted gene co-expression network analysis (WGCNA).

METHODS

We used RNA-Seq data of BPD and healthy control rats from our previous studies, wherein data from 30 samples was collected at days 1, 3, 7, 10, and 14. Data for preprocessing analysis included 17,613 differentially expressed genes (DEGs) with false discovery rate <0.05.

RESULTS

We grouped the highly correlated genes into 13 modules, and constructed a network of mRNA gene associations, including the 150 most associated mRNA genes in each module. Lgals8, Srpra, Prtfdc1, and Thap11 were identified as the key hub genes. Enrichment analyses revealed Golgi vesicle transport, coated vesicle, actin-dependent ATPase activity and endoplasmic reticulum pathways associated with these genes involved in the pathological process of BPD in module.

CONCLUSIONS

This is a study to analyze data obtained from BPD animal model at different time-points using WGCNA, to elucidate BPD-related susceptibility modules and disease-related genes.

Role of the LRP1-pPyk2-MMP9 pathway in hyperoxia-induced lung injury in neonatal rats

OBJECTIVES

To study the role of the low-density lipoprotein receptor-related protein 1 (LRP1)-proline-rich tyrosine kinase 2 phosphorylation (pPyk2)-matrix metalloproteinases 9 (MMP9) pathway in hyperoxia-induced lung injury in neonatal rats.

METHODS

A total of 16 neonatal rats were randomly placed in chambers containing room air (air group) or 95% medical oxygen (hyperoxia group) immediately after birth, with 8 rats in each group. All of the rats were sacrificed on day 8 of life. Hematoxylin and eosin staining was used to observe the pathological changes of lung tissue. ELISA was used to measure the levels of soluble LRP1 (sLRP1) and MMP9 in serum and bronchoalveolar lavage fluid (BALF). Western blot was used to measure the protein expression levels of LRP1, MMP9, Pyk2, and pPyk2 in lung tissue. RT-PCR was used to measure the mRNA expression levels of LRP1 and MMP9 in lung tissue.

RESULTS

The hyperoxia group had significantly higher levels of sLRP1 and MMP9 in serum and BALF than the air group (P<0.05). Compared with the air group, the hyperoxia group had significant increases in the protein expression levels of LRP1, MMP9, and pPyk2 in lung tissue (P<0.05). The hyperoxia group had significantly higher relative mRNA expression levels of LRP1 and MMP9 in lung tissue than the air group (P<0.05).

CONCLUSIONS

The activation of the LRP1-pPyk2-MMP9 pathway is enhanced in hyperoxia-induced lung injury in neonatal rats, which may be involved in the pathogenesis of bronchopulmonary dysplasia.