Integrative omics analysis identifies biomarkers of idiopathic pulmonary fibrosis

Mendelian randomization of plasma proteomics identifies novel ALS-associated proteins and their GO enrichment and KEGG pathway analyses

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neurological disorder with an increasing incidence rate. Despite advances in ALS research over the years, the precise etiology and pathogenic mechanisms remain largely elusive.

OBJECTIVE

To identify novel plasma proteins associated with ALS through Mendelian randomization methods in large-scale plasma proteomics and to provide potential biomarkers and therapeutic targets for ALS treatment.

METHODS

This study employed a large-scale plasma proteomic Mendelian randomization approach using genetic data from 80,610 individuals of European ancestry (including 20,806 ALS patients and 59,804 controls) derived from a genome-wide association study (GWAS). Protein quantitative trait loci (pQTLs) data were obtained from Ferkingstad et al. (2021), which measured 4,907 proteins in 35,559 Icelandic individuals. Multiple Mendelian randomization (MR) techniques were utilized, including weighted median, MR-Egger, Wald ratio, inverse-variance weighting (IVW), basic model, and weighted model. Heterogeneity was evaluated using Cochran's Q test. Horizontal pleiotropy was assessed through the MR-Egger intercept test and MR-PRESSO outlier detection. Sensitivity analysis was performed via leave-one-out analysis.

RESULTS

MR analysis revealed potential causal associations between 491 plasma proteins and ALS, identifying 19 novel plasma proteins significantly linked to the disease. Proteins such as C1QC, UMOD, SLITRK5, ASAP2, TREML2, DAPK2, ARHGEF10, POLM, SST, and SIGLEC1 showed positive correlations with ALS risk, whereas ADPGK, BTNL9, COLEC12, ADGRF5, FAIM, CRTAM, PRSS3, BAG5, and PSMD11 exhibited negative correlations. Reverse MR analyses confirmed that ALS negatively correlates with ADPGK and ADGRF5 expression. Enrichment analyses, including Gene Ontology (GO) functional analysis, indicated involvement in critical biological processes such as external encapsulating structure organization, extracellular matrix organization, chemotaxis, and taxis. KEGG pathway analysis highlighted significant enrichment in the PI3K-Akt signaling pathway, cytokine-cytokine receptor interactions, and axon guidance.

CONCLUSION

This study enhances the understanding of ALS pathophysiology and proposes potential biomarkers and mechanistic insights for therapeutic development. Future research should explore the clinical translation of these findings to improve ALS patient outcomes and quality of life.

Screened of long non-coding RNA related to wool development and fineness in Gansu alpine fine-wool sheep

Wool growth and fineness regulation is influenced by some factors such as genetics and environment. At the same time, lncRNA participates in numerous biological processes in animal production. In this research, we conducted a thorough analysis and characterization of the microstructure of wool, along with long non-coding RNAs (lncRNAs), their target genes, associated pathways, and Gene Ontology terms pertinent to the wool fineness development. The investigation utilized scanning electron microscopy and transcriptomic technology, focusing on two distinct types in Gansu alpine fine-wool sheep: coarse type (group C, MFD = 22.26 ± 0.69 μm, n = 6) and fine type (group F, MFD = 16.91 ± 0.29 μm, n = 6), which exhibit differing wool fiber diameters. The results showed that fine type wool fiber scales were more regularly distributed in rings with large scale spacing and smooth edges, while coarse type wool fiber scales were more irregularly arranged in tiles with relatively rougher edges, and the density of wool scales was greater than that of fine type wool. Furthermore, a comprehensive analysis revealed 164 differentially expressed lncRNAs along with 146 potential target genes linked to these lncRNAs in the skin tissues from groups C and F. Utilizing functional enrichment analysis on the target genes, we successfully identified a number of target genes might be associated with the improvement of wool fineness, such as FOXN1, LIPK, LOC101116068, LOC101106296, KRTAP5.4, KRT71, KRT82, DNASE1L2, which are related to hair follicle development, histidine metabolism, epidermal cell differentiation, oxidative phosphorylation and hair cycle process. Additionally, the interoperability network involving lncRNAs-mRNAs indicated lncRNAs (MSTRG.17445.2, XR_006060725.1, MSTRG.871.1, MSTRG.10907.4) might play a significant role in the wool growth development and fineness improvement process. In conclusion, the research enlarges the current lncRNAs database, providing a new insight for the investigation of wool fineness development in fine-wool sheep.

Precision medicine advances in cystic fibrosis: Exploring genetic pathways for targeted therapies

Personalized medicine has transformed the treatment of cystic fibrosis (CF), providing customized therapeutic approaches based on individual genetic profiles. This review explores the genetic foundations of CF, focusing on mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene and their implications for the development of the disease. The advent of genetic testing has enabled the association of specific mutations to disease severity, leading to the development of CFTR modulators like Ivacaftor, Lumacaftor, and Tezacaftor. Beyond CFTR mutations, genetic modifiers, including gene replacement therapy, genetic manipulation, lentivirus, and non-viral gene therapy formulations, along with environmental factors, play critical roles in influencing disease expression and outcomes. The identification of these modifiers is essential for optimizing therapeutic strategies. Emerging biomarkers, including inflammatory markers and pulmonary function indicators, aid in early disease detection and monitoring progression. Omics technologies are uncovering novel biomarkers, enabling more precise disease management. Pharmacogenomics has become integral to CF care, allowing for personalized approaches that consider genetic variations influencing drug metabolism, especially in antibiotics and anti-inflammatory therapies. The future of CF treatment lies in precision therapies, including CFTR modulators and cutting-edge techniques like gene therapy and CRISPR-Cas9 for mutation correction. As research evolves, these advances can improve patient outcomes while minimizing adverse effects. Ethical considerations and regulatory challenges remain critical as personalized medicine advances, ensuring equitable access and the long-term effectiveness of these innovative therapies.

The mechanism of action of Botrychium (Thunb.) Sw. for prevention of idiopathic pulmonary fibrosis based on 1H-NMR-based metabolomics

OBJECTIVES

This study aimed to reveal the anti-fibrotic effects of Botrychium ternatum (Thunb.) Sw. (BT) against idiopathic pulmonary fibrosis (IPF) and to preliminarily analyze its potential mechanism on bleomycin-induced IPF rats.

METHODS

The inhibition of fibrosis progression in vivo was assessed by histopathology combined with biochemical indicators. In addition, the metabolic regulatory mechanism was investigated using 1H-nuclear magnetic resonance-based metabolomics combined with multivariate statistical analysis.

KEY FINDINGS

Firstly, biochemical analysis revealed that BT notably suppressed the expression of hydroxyproline and transforming growth factor-β1 in the pulmonary tissue. Secondly, Masson's trichrome staining and hematoxylin and eosin showed that BT substantially improved the structure of the damaged lung and significantly inhibited the proliferation of collagen fibers and the deposition of extracellular matrix. Finally, serum metabolomic analysis suggested that BT may exert anti-fibrotic effects by synergistically regulating tyrosine metabolism; phenylalanine, tyrosine and tryptophan biosynthesis; and synthesis and degradation of ketone bodies.

CONCLUSIONS

Our study not only clarifies the potential anti-fibrotic mechanism of BT against IPF at the metabolic level but also provides a theoretical basis for developing BT as an effective anti-fibrotic agent.

Biomarkers in idiopathic pulmonary fibrosis: Current insight and future direction

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease with a dismal prognosis. Early diagnosis, accurate prognosis, and personalized therapeutic interventions are essential for improving patient outcomes. Biomarkers, as measurable indicators of biological processes or disease states, hold significant promise in IPF management. In recent years, there has been a growing interest in identifying and validating biomarkers for IPF, encompassing various molecular, imaging, and clinical approaches. This review provides an in-depth examination of the current landscape of IPF biomarker research, highlighting their potential applications in disease diagnosis, prognosis, and treatment response. Additionally, the challenges and future perspectives of biomarker integration into clinical practice for precision medicine in IPF are discussed.

Integration of Multi-Omics Data for the Classification of Glioma Types and Identification of Novel Biomarkers

Glioma is currently one of the most prevalent types of primary brain cancer. Given its high level of heterogeneity along with the complex biological molecular markers, many efforts have been made to accurately classify the type of glioma in each patient, which, in turn, is critical to improve early diagnosis and increase survival. Nonetheless, as a result of the fast-growing technological advances in high-throughput sequencing and evolving molecular understanding of glioma biology, its classification has been recently subject to significant alterations. In this study, we integrate multiple glioma omics modalities (including mRNA, DNA methylation, and miRNA) from The Cancer Genome Atlas (TCGA), while using the revised glioma reclassified labels, with a supervised method based on sparse canonical correlation analysis (DIABLO) to discriminate between glioma types. We were able to find a set of highly correlated features distinguishing glioblastoma from lower-grade gliomas (LGGs) that were mainly associated with the disruption of receptor tyrosine kinases signaling pathways and extracellular matrix organization and remodeling. Concurrently, the discrimination of the LGG types was characterized primarily by features involved in ubiquitination and DNA transcription processes. Furthermore, we could identify several novel glioma biomarkers likely helpful in both diagnosis and prognosis of the patients, including the genes PPP1R8, GPBP1L1, KIAA1614, C14orf23, CCDC77, BVES, EXD3, CD300A, and HEPN1. Collectively, this comprehensive approach not only allowed a highly accurate discrimination of the different TCGA glioma patients but also presented a step forward in advancing our comprehension of the underlying molecular mechanisms driving glioma heterogeneity. Ultimately, our study also revealed novel candidate biomarkers that might constitute potential therapeutic targets, marking a significant stride toward personalized and more effective treatment strategies for patients with glioma.

Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information

Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by severe lung fibrosis and a poor prognosis. Although the biomolecules related to IPF have been extensively studied, molecular mechanisms of the pathogenesis and their association with serum biomarkers and clinical findings have not been fully elucidated. We constructed a Bayesian network using multimodal data consisting of a proteome dataset from serum extracellular vesicles, laboratory examinations, and clinical findings from 206 patients with IPF and 36 controls. Differential protein expression analysis was also performed by edgeR and incorporated into the constructed network. We have successfully visualized the relationship between biomolecules and clinical findings with this approach. The IPF-specific network included modules associated with TGF-β signaling (TGFB1 and LRC32), fibrosis-related (A2MG and PZP), myofibroblast and inflammation (LRP1 and ITIH4), complement-related (SAA1 and SAA2), as well as serum markers, and clinical symptoms (KL-6, SP-D and fine crackles). Notably, it identified SAA2 associated with lymphocyte counts and PSPB connected with the serum markers KL-6 and SP-D, along with fine crackles as clinical manifestations. These results contribute to the elucidation of the pathogenesis of IPF and potential therapeutic targets.

Dasatinib: a potential tyrosine kinase inhibitor to fight against multiple cancer malignancies

Dasatinib is the 2nd generation TKI (Tyrosine Kinase Inhibitor) having the potential to treat numerous forms of leukemic and cancer patients and it is 300 times more potent than imatinib. Cancer is the major cause of death globally and need to enumerate novel strategies to coping with it. Various novel therapeutics introduced into the market for ease in treating various forms of cancer. We reviewed and evaluated all the related aspects of dasatinib, which can enhance the knowledge about dasatinib therapeutics methodology, pharmacodynamic and pharmacokinetics, side effects, advantages, disadvantages, various kinds of interactions and its novel formulations as well.

Proteomic Fingerprint of Lung Fibrosis Progression and Response to Therapy in Bleomycin-Induced Mouse Model

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by the aberrant accumulation of extracellular matrix in the lungs. nintedanib is one of the two FDA-approved drugs for IPF treatment; however, the exact pathophysiological mechanisms of fibrosis progression and response to therapy are still poorly understood. In this work, the molecular fingerprint of fibrosis progression and response to nintedanib treatment have been investigated by mass spectrometry-based bottom-up proteomics in paraffin-embedded lung tissues from bleomycin-induced (BLM) pulmonary fibrosis mice. Our proteomics results unveiled that (i) samples clustered depending on the tissue fibrotic grade (mild, moderate, and severe) and not on the time course after BLM treatment; (ii) the dysregulation of different pathways involved in fibrosis progression such as the complement coagulation cascades, advanced glycation end products (AGEs) and their receptors (RAGEs) signaling, the extracellular matrix-receptor interaction, the regulation of actin cytoskeleton, and ribosomes; (iii) Coronin 1A (Coro1a) as the protein with the highest correlation when evaluating the progression of fibrosis, with an increased expression from mild to severe fibrosis; and (iv) a total of 10 differentially expressed proteins (p_adj-value ≤ 0.05 and Fold change ≤-1.5 or ≥1.5), whose abundance varied in the base of the severity of fibrosis (mild and moderate), were modulated by the antifibrotic treatment with nintedanib, reverting their trend. Notably, nintedanib significantly restored lactate dehydrogenase B (Ldhb) expression but not lactate dehydrogenase A (Ldha). Notwithstanding the need for further investigations to validate the roles of both Coro1a and Ldhb, our findings provide an extensive proteomic characterization with a strong relationship with histomorphometric measurements. These results unveil some biological processes in pulmonary fibrosis and drug-mediated fibrosis therapy.

Detection of interstitial pneumonia with autoimmune features and idiopathic pulmonary fibrosis are enhanced by involvement of matrix metalloproteinases levels and clinical diagnosis

BACKGROUND

Higher detection of interstitial pneumonia with autoimmune features (IPAF), and idiopathic pulmonary fibrosis (IPF), has significant diagnostic and therapeutic implications. Some matrix metalloproteinases (MMPs) have become reliable diagnostic biomarkers in IPAF and IPF in previous studies, yet relevant reliability remains to be recognized.

MATERIALS AND METHODS

In this study, 36 ILDs patients, including 31 IPAF patients (Mean ± SD, 50.20 ± 5.10 years; 16 [51.6%] females) and five IPF patients (Mean ± SD, 61.20 ± 6.73 years; one [20.0%] females) were retrospectively enrolled. Serial serum samples were collected from patients with IPAF and IPF between January 2019 and December 2020. Notably, Serum MMPs levels were measured by U-PLEX Biomarker Group 1(Human) Multiplex Assays (MSD, USA).

RESULTS

A combination of MMPs and combinatorial biomarkers was strongly associated with clinical subjects in this study (AUC, 0.597 for Stability vs. Improvement and 0.756 for Stability vs. Exacerbation). Importantly, the AUC of MMP-12 reaches 0.730 (p < 0.05, Stability AUC vs. Improvement AUC) while MMP-13 reaches 0.741 (p < 0.05, Stability AUC vs. Exacerbation AUC) showed better performance than other MMPs in two comparisons.

CONCLUSIONS

Clinical risk factors and MMPs are strongly associated with either stratification of the disease of progression of IPAF or in two IPAF and IPF independent cohorts. To our knowledge, this is the first to illustrate that MMP-12 and MMP-13 may be expected to become typical promising biomarkers in Improvement - IPAF and Exacerbation - IPAF, respectively.