Integrative metabolome and lipidome analyses of plasma in neovascular macular degeneration

Serum and plasma sphingolipids as biomarkers of chemotherapy-induced cardiotoxicity in female patients with breast cancer

Although effective as a chemotherapeutic, the utility of Doxorubicin (Dox) is hampered by cardiotoxicity. Despite this, the ability to predict and guide monitoring of patients receiving Dox is hampered by a lack of effective biomarkers to identify susceptible patients and detect early signs of subclinical cardiotoxicity. Based on their well-established roles in the response to Dox and other chemotherapies, we performed a retrospective analysis of serum and plasma sphingolipids (SLs) from female patients with breast cancer (BC) undergoing anthracycline-containing therapy, correlating with cardiac parameters assessed by echocardiography. Results showed substantial changes in both plasma and serum SL species during therapy including ceramide (Cer), deoxydihydroCer, and dihydrosphingosine with reversion toward baseline after treatment. Linear mixed-effects model analysis revealed that baseline levels of a number of SLs correlated with adverse cardiac outcomes. Here, serum sphingosine-1-phosphate (S1P), dihydroS1P, and plasma Cer performed comparably to the prognostic value of pro-NT-BNP, an established biomarker of cardiotoxicity. Intriguingly, while pro-NT-BNP had no predictive value at mid- and post-therapy timepoints, serum S1P and dihydroS1P, and plasma Cer levels showed a correlation with adverse outcomes, particularly at the post-therapy timepoint. Finally, analysis of plasma and serum C16:C24-Cer ratios-previously linked with adverse cardiac outcomes-showed no correlation in the context of chemotherapy treatment. Overall, this pilot study provides initial evidence that plasma and serum SLs may have benefits as both prognostic and diagnostic biomarkers for female BC patients undergoing anthracycline-containing chemotherapy. Consequently, diagnostic SL measurements-recently implemented for metabolic-associated cardiac disorders-could have wider utility.

Dysregulated lipid metabolism in a retinal pigment epithelial cell model and serum of patients with age-related macular degeneration

BACKGROUND

Age-related macular degeneration (AMD) is a leading cause of blindness, characterized by retinal pigment epithelium (RPE) dysfunction, extracellular deposit formation, and disrupted lipid metabolism. Understanding the molecular changes underlying AMD is essential for identifying diagnostic markers and therapeutic targets.

RESULTS

This multiomic study employed a primary RPE culture model to investigate age-related changes associated with AMD. Over 25 weeks, RPE cells exhibited phenotypic deterioration, including depigmentation, cell shape deformation, and barrier integrity loss, accompanied by extracellular deposit formation. Transcriptomic analysis revealed dysregulation of genes involved in lipid metabolism, including pathways for cholesterol transport, glycerophospholipids, and ceramide biosynthesis. Metabolomic profiling further identified significant changes in glycerophospholipid and sphingolipid metabolism, highlighting a decline in phospholipid species and ceramide accumulation. Serum analysis of AMD patients revealed altered levels of 18 lipids identified in RPE cultures. Four lipids showed significant differences compared to controls: GlcCer(d16:1/18:0) (1.23-fold increase, adj. p value < 0.001), PE(19:1(9Z)/22:2(13Z,16Z)) (0.34-fold decrease, adj. p value < 0.001), PE(15:0/20:3(5Z,8Z,11Z)) (0.66-fold decrease, adj. p value < 0.05), and PC(22:2(13Z,16Z)/13:0) (0.71-fold decrease, adj. p value < 0.05). These findings underscore the systemic nature of lipid dysregulation in AMD and the translational relevance of the RPE model.

CONCLUSIONS

This study highlights the significant role of lipid metabolism dysregulation in AMD pathogenesis. The consistent lipidomic alterations observed in RPE cultures and AMD patient serum reinforce their potential as biomarkers for disease progression and therapeutic targets. These findings provide a robust framework for understanding AMD-associated lipid metabolism changes and their systemic impact.

Metabolomic Characteristics of Aqueous Humor in Wet Age-Related Macular Degeneration and the Impact of Anti-VEGF Treatment

Purpose

To explore the alterations in metabolites of wet age-related macular degeneration (wAMD) by conducting metabolomics in aqueous humor from patients with wAMD and to assess the potential effects of anti-vascular endothelial growth factor (anti-VEGF) on these metabolites.

Methods

Metabolomic analysis was performed on the aqueous humor of 30 patients with wAMD receiving anti-VEGF treatments and 20 controls, via ultra-high performance liquid chromatography tandem mass spectrometry. The aqueous humor samples collected from untreated patients with wAMD were classified as the pre-wAMD group. Accordingly, the samples collected from patients with wAMD receiving one anti-VEGF treatment were designated as the post-wAMD group. Individuals were further classified into responders and nonresponders according to their reaction to the treatment. Principal component analysis, hierarchical cluster analysis, and the Kyoto Encyclopedia of Genes and Genomes annotation and enrichment analysis, were subsequently performed. Machine learning and receiver operating characteristic curve analyses were used to further analyze potential vital metabolites.

Results

Among the 1001 metabolites verified in the aqueous humor, 306 compounds separated patients with pre-wAMD from the control group, whereas 68 metabolites differentiated patients with post-wAMD and patients with pre-wAMD. Enrichment in metabolic pathways was noted in ABC transporters, thiamine metabolism, glycerophospholipid metabolism, mammalian target of rapamycin signaling pathway and tyrosine metabolism, and so on. Machine learning and receiver operating characteristic curves analysis suggested that δ-valerolactam could not only distinguish between patients with wAMD and the control group, but also differentiate between patients with post-wAMD and patients with pre-wAMD. Changes in acylcarnitine were observed in anti-VEGF responders with wAMD.

Conclusions

There were noticeable alterations in the aqueous humor of patients with wAMD involving many metabolites that are associated with ABC transporters, glycerophospholipid metabolism, and the mammalian target of rapamycin signaling pathway. It is possible that δ-valerolactam can be applied as a biomarker in wAMD.

Serum and Plasma Sphingolipids as Biomarkers of Anthracycline-Induced Cardiotoxicity

Although effective as a chemotherapy, the utility of Doxorubicin (Dox) is hampered by cardiotoxicity. Despite this, the ability to predict and guide monitoring of patients receiving Dox or other anthracyclines is hampered by a lack of effective biomarkers to identify susceptible patients, and to detect early signs of subclinical cardiotoxicity. Based on their well-established roles in the response to Dox and other chemotherapies, we performed a retrospective analysis of serum and plasma sphingolipids (SLs) from patients undergoing anthracycline-containing therapy, correlating with cardiac parameters assessed by echocardiography. Results showed there were substantial changes in both plasma and serum SL species during therapy including ceramide (Cer), deoxydihydroCer, and dihydrosphingosine with reversion towards baseline following treatment. Linear mixed-effects model analysis revealed that at baseline, a number of SLs correlated with adverse cardiac outcomes with serum sphingosine-1-phosphate (S1P) and dihydroS1P, and plasma Cer performing comparably to the prognostic value of pro-NT-BNP, an established biomarker of cardiotoxicity. Intriguingly, while pro-NT-BNP had no predictive value at mid- and post-therapy timepoints, serum S1P and dhS1P and plasma Cer levels showed correlation with adverse outcomes, particularly at the post-therapy timepoint. Finally, analysis of plasma and serum C16:C24- Cer ratios - previously reported as predictive of adverse cardiac outcomes - showed no correlation in the context of anthracycline treatment. Taken together, this pilot study provides supporting evidence that plasma and serum SLs may have benefit as both prognostic and diagnostic biomarkers for patients undergoing anthracycline-containing therapy. This suggests that diagnostic SL measurements - recently implemented for metabolic-associated cardiac disorders - could have wider utility.

Bioinformatics Analysis of Lactylation-related Biomarkers and Potential Pathogenesis Mechanisms in Age-related Macular Degeneration

Background

Lactylation is increasingly recognized to play a crucial role in human health and diseases. However, its involvement in age-related macular degeneration (AMD) remains largely unclear.

Objectives

The aim of this study was to identify and characterize the pivotal lactylation-related genes and explore their underlying mechanism in AMD.

Methods

Gene expression profiles of AMD patients and control individuals were obtained and integrated from the GSE29801 and GSE50195 datasets. Differentially expressed genes (DEGs) were screened and intersected with lactylation-related genes for lactylation-related DEGs. Machine learning algorithms were used to identify hub genes associated with AMD. Subsequently, the selected hub genes were subject to correlation analysis, and reverse transcription quantitative real-time PCR (RT-qPCR) was used to detect the expression of hub genes in AMD patients and healthy control individuals.

Results

A total of 68 lactylation-related DEGs in AMD were identified, and seven genes, including HMGN2, TOP2B, HNRNPH1, SF3A1, SRRM2, HIST1H1C, and HIST1H2BD were selected as key genes. RT-qPCR analysis validated that all 7 key genes were down-regulated in AMD patients.

Conclusion

We identified seven lactylation-related key genes potentially associated with the progression of AMD, which might deepen our understanding of the underlying mechanisms involved in AMD and provide clues for the targeted therapy.

Serum metabolite biomarkers for the early diagnosis and monitoring of age-related macular degeneration

INTRODUCTION

Age-related macular degeneration (AMD) is a leading cause of irreversible blindness worldwide, with significant challenges for early diagnosis and treatment.

OBJECTIVES

To identify new biomarkers that are important for the early diagnosis and monitoring of the severity/progression of AMD.

METHODS

We investigated the diagnostic and monitoring potential of blood metabolites in a cohort of 547 individuals (167 healthy controls, 240 individuals with other eye diseases as eye disease controls, and 140 individuals with AMD) from 2 centers over three phases: discovery phase 1, discovery phase 2, and an external validation phase. The samples were analyzed via a mass spectrometry-based, widely targeted metabolomic workflow. In discovery phases 1 and 2, we built a machine learning algorithm to predict the probability of AMD. In the external validation phase, we further confirmed the performance of the biomarker panel identified by the algorithm. We subsequently evaluated the performance of the identified biomarker panel in monitoring the progression and severity of AMD.

RESULTS

We developed a clinically specific three-metabolite panel (hypoxanthine, 2-furoylglycine, and 1-hexadecyl-2-azelaoyl-sn-glycero-3-phosphocholine) via five machine learning models. The random forest model effectively discriminated patients with AMD from patents in the other two groups and showed acceptable calibration (area under the curve (AUC) = 1.0; accuracy = 1.0) in both discovery phases 1 and 2. An independent validation phase confirmed the diagnostic model's efficacy (AUC = 0.962; accuracy = 0.88). The three-biomarker panel model demonstrated an AUC of 1.0 in differentiating the severity of AMD via RF machine learning, which was consistent across both the discovery and external validation phases. Additionally, the biomarker concentrations remained stable under repeated freeze-thaw cycles (P > 0.05).

CONCLUSIONS

This study reveals distinct metabolite variations in the serum of AMD patients, paving the way for the development of the first routine laboratory test for AMD.

Integrating Multi-omics to Identify Age-Related Macular Degeneration Subtypes and Biomarkers

Age-related macular degeneration (AMD) is one of the most common causes of irreversible vision loss in the elderly. Its pathogenesis is likely multifactorial, involving a complex interaction of metabolic and environmental factors, and remains poorly understood. Previous studies have shown that mitochondrial dysfunction and oxidative stress play a crucial role in the development of AMD. Oxidative damage to the retinal pigment epithelium (RPE) has been identified as one of the major mediators in the pathogenesis of age-related macular degeneration (AMD). Therefore, this article combines transcriptome sequencing (RNA-seq) and single-cell sequencing (scRNA-seq) data to explore the role of mitochondria-related genes (MRGs) in AMD. Firstly, differential expression analysis was performed on the raw RNA-seq data. The intersection of differentially expressed genes (DEGs) and MRGs was performed. This paper proposes a deep subspace nonnegative matrix factorization (DS-NMF) algorithm to perform a multi-layer nonlinear transformation on the intersection of gene expression profiles corresponding to AMD samples. The age of AMD patients is used as prior information at the network's top level to change the data distribution. The classification is based on reconstructed data with altered distribution. The types obtained significantly differ in scores of multiple immune-related pathways and immune cell infiltration abundance. Secondly, an optimal AMD diagnosis model was constructed using multiple machine learning algorithms for external and qRT-PCR verification. Finally, ten potential therapeutic drugs for AMD were identified based on cMAP analysis. The AMD subtypes identified in this article and the diagnostic model constructed can provide a reference for treating AMD and discovering new drug targets.

Metabolic Regulation of Endothelial Cells: A New Era for Treating Wet Age-Related Macular Degeneration

Wet age-related macular degeneration (wet AMD) is a primary contributor to visual impairment and severe vision loss globally, but the prevailing treatments are often unsatisfactory. The development of conventional treatment strategies has largely been based on the understanding that the angiogenic switch of endothelial cells (ECs) is mainly dictated by angiogenic growth factors. Even though treatments targeting vascular endothelial growth factor (VEGF), like ranibizumab, are widely administered, more than half of patients still exhibit inadequate or null responses, suggesting the involvement of other pathogenic mechanisms. With advances in research in recent years, it has become well recognized that EC metabolic regulation plays an active rather than merely passive responsive role in angiogenesis. Disturbances of these metabolic pathways may lead to excessive neovascularization in angiogenic diseases such as wet AMD, therefore targeted modulation of EC metabolism represents a promising therapeutic strategy for wet AMD. In this review, we comprehensively discuss the potential applications of EC metabolic regulation in wet AMD treatment from multiple perspectives, including the involvement of ECs in wet AMD pathogenesis, the major endothelial metabolic pathways, and novel therapeutic approaches targeting metabolism for wet AMD.

Integrative analysis of proteomics and lipidomic profiles reveal the fat deposition and meat quality in Duroc × Guangdong small spotted pig

Introduction

This study aims to explore the important factors affecting the characteristics of different parts of pork.

Methods

Lipidomics and proteomics methods were used to analyze DAL (differential lipids) and DAPs (differential proteins) in five different parts (longissimus dorsi, belly meat, loin, forelegs and buttocks) of Duhua pig (Duroc × Guangdong small spotted pig), to identify potential pathways affecting meat quality, investigating fat deposition in pork and its lipid-protein interactions.

Results

The results show that TG (triglyceride) is the lipid subclass with the highest proportion in muscle, and the pathway with the most significantly enriched lipids is GP. DAP clustered on several GO terms closely related to lipid metabolism and lipogenesis (lipid binding, lipid metabolism, lipid transport, and lipid regulation). In KEGG analysis, there are two main DAP aggregation pathways related to lipid metabolism, namely Fatty acid degradation and oxidative phosphorylation. In PPI analysis, we screened out 31 core proteins, among which NDUFA6, NDUFA9 and ACO2 are the most critical.

Discussion

PC (phosphatidylcholine) is regulated by SNX5, THBS1, ANXA7, TPP1, CAVIN2, and VDAC2 in the phospholipid binding pathway. TG is regulated by AUH/HADH/ACADM/ACADL/HADHA in the lipid oxidation and lipid modification pathways. Potential biomarkers are rich in SFA, MUFA and PUFA respectively, the amounts of SFA, MUFA and PUFA in the lipid measurement results are consistent with the up- and down-regulation of potential biomarker lipids. This study clarified the differences in protein and lipid compositions in different parts of Duhua pigs and provided data support for revealing the interactions between pork lipids and proteins. These findings provide contributions to the study of intramuscular fat deposition in pork from a genetic and nutritional perspective.