Integrative Metabolic Pathway Analysis Reveals Novel Therapeutic Targets in Osteoarthritis

Phosphatidylcholine Ameliorates Palmitic Acid-Induced Lipotoxicity by Facilitating Endoplasmic Reticulum and Mitochondria Contacts in Intervertebral Disc Degeneration

Background

Intervertebral disc degeneration (IDD) is a prevalent musculoskeletal disorder with substantial socioeconomic impacts. Despite its high prevalence, the pathogenesis of IDD remains unclear, and effective pharmacological interventions are lacking. This study aimed to investigate metabolic alterations in IDD and explore potential therapeutic targets by analyzing lipotoxicity-related mechanisms in nucleus pulposus (NP) cells.

Methods

Metabolomics and magnetic resonance spectroscopy were utilized to profile metabolic changes in NP tissues from advanced-stage IDD. Transcriptomics and metabolomics integration were performed to identify key regulatory pathways. In vitro experiments using human NP cells exposed to palmitic acid were conducted to evaluate endoplasmic reticulum (ER) stress, mitochondrial dysfunction, lipid droplet accumulation, and senescence. Phosphatidylcholine supplementation was tested for its ability to mitigate lipotoxicity, with ER-mitochondria interactions and mitochondrial oxidation capacity assessed as mechanistic endpoints.

Results

Our findings revealed an abnormal lipotoxic condition in NP cells from advanced-stage IDD. Furthermore, we identified abnormal accumulation of triglycerides and palmitic acid in NP cells from IDD. The palmitic acid accumulation resulted in endoplasmic reticulum stress, mitochondrial damage, lipid droplet accumulation, and senescence of NP cells. By integrating transcriptomics and metabolomics analyses, we discovered that phosphatidylcholine plays a role in regulating palmitic acid-induced lipotoxicity. Notably, phosphatidylcholine level was found to be low in the endoplasmic reticulum and mitochondria of advanced-stage NP cells. Phosphatidylcholine treatment alleviated palmitic acid-induced lipid droplet accumulation and senescence of NP cells by modulating ER-mitochondria contacts and mitochondrial oxidation capacity.

Conclusion

Phosphatidylcholine emerges as a potential therapeutic agent to counteract lipotoxic stress by modulating organelle interactions and mitochondrial function. These findings advance our understanding of IDD pathogenesis and provide a novel metabolic target for therapeutic development.

Progress in multi-omics studies of osteoarthritis

Osteoarthritis (OA), a ubiquitous degenerative joint disorder, is marked by pain and disability, profoundly impacting patients' quality of life. As the population ages, the global prevalence of OA is escalating. Omics technologies have become instrumental in investigating complex diseases like OA, offering comprehensive insights into its pathogenesis and progression by uncovering disease-specific alterations across genomics, transcriptomics, proteomics, and metabolomics levels. In this review, we systematically analyzed and summarized the application and recent achievements of omics technologies in OA research by scouring relevant literature in databases such as PubMed. These studies have shed light on new potential therapeutic targets and biomarkers, charting fresh avenues for OA diagnosis and treatment. Furthermore, in our discussion, we highlighted the immense potential of spatial omics technologies in unraveling the molecular mechanisms of OA and in the development of novel therapeutic strategies, proposing future research directions and challenges. Collectively, this study encapsulates the pivotal advances in current OA research and prospects for future investigation, providing invaluable references for a deeper understanding and treatment of OA. This review aims to synthesize the recent progress of omics technologies in the realm of OA, aspiring to furnish theoretical foundations and research orientations for more profound studies of OA in the future.

Gut microbiota and blood biomarkers in IBD-Related arthritis: insights from mendelian randomization

With the ongoing rise in the incidence of inflammatory bowel disease (IBD), its extraintestinal manifestations have garnered significant attention. IBD-related arthritis is notable for its insidious onset and unpredictability, presenting considerable challenges for clinical diagnosis and management. Factors such as gut microbiota, plasma proteins, inflammatory proteins, and biomarkers found in blood and urine may be closely associated with IBD-related arthritis. However, the mechanisms by which these factors influence this condition remain poorly understood and require urgent investigation. We employed the method of linkage disequilibrium and the two-sample Mendelian randomization (MR) approach, utilizing single nucleotide polymorphisms (SNPs) identified from large-scale genome-wide association studies as instrumental variables. In this scientifically rigorous manner, we explored the potential causal relationship between gut microbiota, plasma proteins, inflammatory proteins, and blood and urine biomarkers in relation to arthritis resulting from inflammatory bowel disease (IBD). This method aids in elucidating the potential roles of these biomarkers in the development of arthritis following IBD, while minimizing the confounding factors and reverse causality commonly encountered in observational studies. To further verify and strengthen our findings, we conducted subsequent sensitivity analyses. These analyses will evaluate the strength of the association between SNPs and the studied biomarkers, as well as post-IBD arthritis, while accounting for variations in SNP distribution among populations and other potential genetic influencing factors. Through these rigorous analytical steps, our objective is to enhance the robustness and credibility of the research findings and provide more reliable scientific evidence regarding the pathogenesis of post-IBD arthritis. MR analysis provides evidence for the association between genetically predicted gut microbiota, plasma proteins, inflammatory proteins, and blood and urine biomarkers with the risk of IBD-related arthritis. This analysis investigates the characteristics of the associations between specific gut microbiota, plasma proteins, inflammatory proteins, and blood and urine biomarkers in relation to IBD-related arthritis. Among the plasma proteins, pterin-4-alpha-carbinolamine dehydratase, aldo-keto reductase family 1 member C4, cathepsin L2, angiostatin, hepatocyte growth factor-like protein, hepatitis A virus cellular receptor 2, protein O-linked mannose beta-1,4-N-acetylglucosaminyltransferase 2, epididymal-specific alpha-mannosidase, and platelet-derived growth factor receptor-like protein are associated with Crohn's disease-related arthritis. In contrast, agrin, methylenetetrahydrofolate synthetase domain-containing protein, neurotrophin-3 (NT-3) growth factor receptor, and neuropilin-1 are associated with ulcerative colitis-related arthritis. Furthermore, regarding gut bacterial pathway abundance, adenosylcobalamin, N-acetylglucosamine, N-acetylmannosamine, and N-acetylneuraminic acid degradation, as well as glycolysis metabolism and degradation pathways, are associated with Crohn's disease-related arthritis. Meanwhile, gut bacterial pathway abundance (pentose phosphate pathway) and gut microbiota abundance (Bacteroidetes, Bacteroidia, Bacteroidales, Porphyromonadaceae, Faecalibacterium, Eubacterium eligens) are linked to ulcerative colitis-related arthritis. Notably, we did not identify any connections between inflammatory protein factors, blood and urine biomarkers, and IBD-related arthritis. Lastly, in the reverse MR study, the insufficient number of SNPs available for analysis precluded the detection of a reverse causal relationship. This study employs the MR method to elucidate the potential causal relationships among gut microbiota, plasma proteins, inflammatory proteins, and blood and urine biomarkers in relation to the occurrence and progression of IBD-related arthritis. This research offers a novel perspective for a deeper understanding of the pathogenesis of IBD-related arthritis and highlights future directions for the diagnosis and treatment strategies of this condition.

Deciphering S1P downregulation and sphingolipid homeostasis disruption in fungal keratitis via multi-omics and MALDI-MSI analysis

PURPOSE

The absence of effective treatment strategies in Fungal Keratitis (FK) emphasizes the critical need to understand the pathogenic mechanisms to enhance therapeutic outcomes. Sphingolipids have been proved to play a pivotal role in the pathogenesis of fungal infections, but the specific alteration in sphingolipids and regulatory pathways remain elusive. Our aim is to gain insight into the pathophysiological mechanisms of sphingolipid homeostasis in FK through multi-omics analysis.

METHODS

Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) was performed in FK patients and mouse model. Furthermore, time-course RNA-seq was performed and Weighted gene co-expression network analysis (WGCNA) was used to reveal the driver genes in FK. We further investigated the effect of FTY-720, a mimetic of sphingosine 1-phosphate (S1P), on the progression of FK.

RESULTS

MALDI-MSI analysis of FK patients revealed a downregulation of sphingolipids, with sphingolipid metabolism identified as the most prominently enriched pathway. These alterations were validated in mouse model, in which S1P, ceramide, ceramide 1-phosphate and sphingomyelin were found to be downregulated. Time-course transcriptomic analysis suggests that degradation of sphingolipids by specific enzymes drives the progression of FK, involving phospholipid degradation, downregulation of TOR pathway, and activation of innate immune response. Consequently, epithelial cell function was inhibited and cell death increased. Importantly, restoring sphingolipid homeostasis by FTY-720 reversed the level of S1P and relieved the progression of FK.

CONCLUSION

In summary, this study reveals that disruption of sphingolipid homeostasis promotes disease progression in FK. Furthermore, restoring sphingolipid homeostasis emerges as a promising strategy to mitigate the progression of FK.

Multiomics analysis reveals the potential of LPCAT1-PC axis as a therapeutic target for human intervertebral disc degeneration

Intervertebral disc degeneration (IDD) is a highly prevalent musculoskeletal disorder that is associated with considerable morbidity. However, there is currently no drug available that has a definitive therapeutic effect on IDD. In this study, we aimed to identify the molecular features and potential therapeutic targets of IDD through a comprehensive multiomics profiling approach. By integrating transcriptomics, proteomics, and ultrastructural analyses, we discovered dysfunctions in various organelles, including mitochondria, the endoplasmic reticulum, the Golgi apparatus, and lysosomes. Metabolomics analysis revealed a reduction in total phosphatidylcholine (PC) content in IDD. Through integration of multiple omics techniques with disease phenotypes, a pivotal pathway regulated by the lysophosphatidylcholine acyltransferase 1 (LPCAT1)-PC axis was identified. LPCAT1 exhibited low expression levels and exhibited a positive correlation with PC content in IDD. Suppression of LPCAT1 resulted in inhibition of PC synthesis in nucleus pulposus cells, leading to a notable increase in nucleus pulposus cell senescence and damage to cellular organelles. Consequently, PC exhibits potential as a therapeutic agent, as it facilitates the repair of the biomembrane system and alleviates senescence in nucleus pulposus cells via reversal of downregulation of the LPCAT1-PC axis.

Palmitic acid induces lipid droplet accumulation and senescence in nucleus pulposus cells via ER-stress pathway

Intervertebral disc degeneration (IDD) is a highly prevalent musculoskeletal disorder affecting millions of adults worldwide, but a poor understanding of its pathogenesis has limited the effectiveness of therapy. In the current study, we integrated untargeted LC/MS metabolomics and magnetic resonance spectroscopy data to investigate metabolic profile alterations during IDD. Combined with validation via a large-cohort analysis, we found excessive lipid droplet accumulation in the nucleus pulposus cells of advanced-stage IDD samples. We also found abnormal palmitic acid (PA) accumulation in IDD nucleus pulposus cells, and PA exposure resulted in lipid droplet accumulation and cell senescence in an endoplasmic reticulum stress-dependent manner. Complementary transcriptome and proteome profiles enabled us to identify solute carrier transporter (SLC) 43A3 involvement in the regulation of the intracellular PA level. SLC43A3 was expressed at low levels and negatively correlated with intracellular lipid content in IDD nucleus pulposus cells. Overexpression of SLC43A3 significantly alleviated PA-induced endoplasmic reticulum stress, lipid droplet accumulation and cell senescence by inhibiting PA uptake. This work provides novel integration analysis-based insight into the metabolic profile alterations in IDD and further reveals new therapeutic targets for IDD treatment.

State-of-the-art mass spectrometry imaging applications in biomedical research

Mass spectrometry imaging has advanced from a niche technique to a widely applied spatial biology tool operating at the forefront of numerous fields, most notably making a significant impact in biomedical pharmacological research. The growth of the field has gone hand in hand with an increase in publications and usage of the technique by new laboratories, and consequently this has led to a shift from general MSI reviews to topic-specific reviews. Given this development, we see the need to recapitulate the strengths of MSI by providing a more holistic overview of state-of-the-art MSI studies to provide the new generation of researchers with an up-to-date reference framework. Here we review scientific advances for the six largest biomedical fields of MSI application (oncology, pharmacology, neurology, cardiovascular diseases, endocrinology, and rheumatology). These publications thereby give examples for at least one of the following categories: they provide novel mechanistic insights, use an exceptionally large cohort size, establish a workflow that has the potential to become a high-impact methodology, or are highly cited in their field. We finally have a look into new emerging fields and trends in MSI (immunology, microbiology, infectious diseases, and aging), as applied MSI is continuously broadening as a result of technological breakthroughs.

Matrix-assisted laser desorption/ionization mass spectrometry imaging sample preparation using wet-interface matrix deposition for lipid analysis

RATIONALE

Sample preparation is one of the most crucial steps for matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Scientists beginning their study with this technique may be overwhelmed by the variety of matrices, solvents, and concentrations; the methods of their applications; and the lack of widely available knowledge of the effect of these parameters on the results. Here we present in depth the aspects of matrix deposition, which will be helpful for the scientific community.

METHODS

In this study, we tested several MALDI matrices, such as 2,5-dihydroxybenzoic acid (DHB), norharmane, N-(1-naphthyl)ethylenediamine dihydrochloride (NEDC), and 9-aminoacridine (9AA), using the SunCollect system: wet-interface matrix deposition in the context of lipid analysis. We optimized the number of matrix layers and nozzle settings in terms of spectral intensity and the overall quality of the obtained ion maps.

RESULTS

Our research presents the effect of the number of matrix layers and nozzle settings on the results and allows for choosing the optimal parameters for the analyses. In positive ionization mode, DHB matrix could be chosen first. In the negative ionization mode, 1,5-diaminonaphthalene matrix produces a higher peak intensity in a lower mass range and seems to provide more information than 9AA. We recommend NEDC for particular processes such as glucose analysis. Compared to the remaining matrices, norharmane shows significant changes in the obtained ion maps.

CONCLUSIONS

Such a large amount of data allow us to observe an interesting conclusion: the obtained ion image for a particular ion could differ dramatically with a change in the matrix, the solvent composition, or even the number of matrix layers. This must be considered when interpreting the result, impelling us to compare the results obtained with different matrices with caution.

The influence of matrix concentration and solvent composition on the results of MALDI MSI, with the aid of wet-interface matrix deposition

Imaging mass spectrometry is a powerful technique for the molecular analysis of tissue sections. As in many analytical methods, sample preparation is one of the main and most important steps to obtain results of good quality. Usually, the matrix concentration and solvent composition in different studies are taken for granted without any further consideration. In our studies, we aimed to find how matrix concentration and a type of solvent influence the signal. Moreover, we also aimed to find the relationship between these parameters, how they influence the spectra, and how they influence obtained ion maps. In our experiments, we used SunCollect®, which is a commercially available wet-interface system for matrix deposition. We decided to choose two matrix concentrations (2,5-dihydroxybenzoic acid [DHB]: 15 and 25 mg/mL; 9-aminoacridine [9AA]: 7 and 5 mg/mL) and two different water solutions of solvents in two different percentages for the matrices (DHB: 50% and 70% of methanol [MeOH] and acetonitrile [ACN]; 9AA 70% and 50% of ethanol [EtOH] and MeOH). In the end, the influence of these parameters on obtained spectra and ion maps was assessed.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Identification of crucial salivary proteins/genes and pathways involved in pathogenesis of temporomandibular disorders

Temporomandibular disorder (TMD) is a collective term for a group of conditions that lead to impairment of the function of the temporomandibular joint. The proteins/genes and signaling pathways associated with TMD are still poorly understood. The aim of this study was to identify key differentially expressed salivary proteins/genes (DEGs) associated with TMD progression using LC-MS/MS coupled with a bioinformatics approach. The protein–protein interaction network was obtained from the STRING database and the hub genes were identified using Cytoscape including cytoHubba and MCODE plug-ins. In addition, enrichment of gene ontology functions and the Reactome signaling pathway was performed. A total of 140 proteins/genes were differentially expressed. From cluster analysis, a set of 20 hub genes were significantly modulated: ALB, APOA1, B2M, C3, CAT, CLU, CTSD, ENO1, GSN, HBB, HP, HSPA8, LTF, LYZ, MMP9, S100A9, SERPINA1, TF, TPI1, and TXN. Two enriched signaling pathways, glycolysis and gluconeogenesis, and tryptophan signaling pathway involving the hub genes CAT, ENO1, and TPI1 have been identified. The rest of the hub genes were mainly enriched in the innate immune system and antimicrobial peptides signaling pathways. In summary, hub DEGs and the signaling pathways identified here have elucidated the molecular mechanisms of TMD pathogenesis.

Epigenetic regulation by long noncoding RNAs in osteo-/adipogenic differentiation of mesenchymal stromal cells and degenerative bone diseases

Bone is a complex tissue that undergoes constant remodeling to maintain homeostasis, which requires coordinated multilineage differentiation and proper proliferation of mesenchymal stromal cells (MSCs). Mounting evidence indicates that a disturbance of bone homeostasis can trigger degenerative bone diseases, including osteoporosis and osteoarthritis. In addition to conventional genetic modifications, epigenetic modifications (i.e., DNA methylation, histone modifications, and the expression of noncoding RNAs) are considered to be contributing factors that affect bone homeostasis. Long noncoding RNAs (lncRNAs) were previously regarded as 'transcriptional noise' with no biological functions. However, substantial evidence suggests that lncRNAs have roles in the epigenetic regulation of biological processes in MSCs and related diseases. In this review, we summarized the interactions between lncRNAs and epigenetic modifiers associated with osteo-/adipogenic differentiation of MSCs and the pathogenesis of degenerative bone diseases and highlighted promising lncRNA-based diagnostic and therapeutic targets for bone diseases.

In situ metabolic profile and spatial distribution of ocular tissues: New insights into dry eye disease

PURPOSE

Dry eye disease (DED) is a chronic multifactorial disorder affecting millions of people, yet the pathogenesis mechanisms still remain unclear. Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) is a novel in situ visualization approach combined high-throughput mass spectrometry and molecular imaging. We aimed to explore the in situ ocular metabolic changes via MALDI-MSI to accelerate the recognition of DED pathogenesis.

METHODS

Experimental dry eye was established in Wistar rats by subcutaneous injection of scopolamine. The induction of DED was assessed by tear film breakup time, sodium fluorescein, histopathological staining and cell apoptosis. MALDI-MSI was applied to explore in situ ocular metabolomic in DED rats, and histopathological staining from same sections were used for side-by-side comparison with MALDI to annotate different tissue structures in the eye.

RESULTS

Considering the complexity of ocular tissue, we visualized the metabolites in specific ocular regions (central cornea, peripheral cornea, fornix conjunctiva, eyelid conjunctiva and aqueous humor), and identified metabolites related to DED, with information of relative abundance and spatial signatures. In addition, integrative pathway analysis illustrated that, several metabolic pathways such as glycerophospholipid, sphingolipid phenylalanine, and metabolism of glycine, serine and threonine were significantly altered in certain regions in the dry eye tissue. Moreover, we discussed how the metabolic pathways with spatiotemporal signatures might be involved in the DED process.

CONCLUSIONS

Our data exploit the advantages of in situ analysis of MALDI-MSI to accurately analyze the region-specific metabolic behaviors in DED, and provide new clues to uncover DED pathogenesis.

Chondrocyte protein co-synthesis network analysis links ECM mechanosensing to metabolic adaptation in osteoarthritis

BACKGROUND

Knee osteoarthritis (OA) is one of the most common structural OA disorders globally. Incomplete understanding of the fundamental biological aspects of osteoarthritis underlies the current lack of effective treatment or disease modifying drugs.

RESEARCH DESIGN AND METHODS

We implemented a systems approach by making use of the statistical network concepts in Weighted Gene Co-expression Analysis to reconstruct the organization of the core proteome network in chondrocytes obtained from OA patients and healthy individuals. Protein modules reflect groups of tightly co-ordinated changes in protein abundance across healthy and OA chondrocytes.

RESULTS

The unbiased systems analysis identified extracellular matrix (ECM) mechanosensing and glycolysis as two modules that are most highly correlated with ΟΑ. The ECM module was enriched in the OA genetic risk factors tenascin-C (TNC) and collagen 11A1 (COL11A1), as well as in cartilage oligomeric matrix protein (COMP), a biomarker associated with cartilage integrity. Mapping proteins that are unique to OA or healthy chondrocytes onto the core interactome, which connects microenvironment sensing and regulation of glycolysis, identified differences in metabolic and anti-inflammatory adaptation.

CONCLUSION

The interconnection between cartilage ECM remodeling and metabolism is indicative of the dynamic chondrocyte states and their significance in osteoarthritis.

Metabolomics in Bone Research

Identifying the changes in endogenous metabolites in response to intrinsic and extrinsic factors has excellent potential to obtain an understanding of cells, biofluids, tissues, or organisms' functions and interactions with the environment. The advantages provided by the metabolomics strategy have promoted studies in bone research fields, including an understanding of bone cell behaviors, diagnosis and prognosis of diseases, and the development of treatment methods such as implanted biomaterials. This review article summarizes the metabolism changes during osteogenesis, osteoclastogenesis, and immunoregulation in hard tissue. The second section of this review is dedicated to describing and discussing metabolite changes in the most relevant bone diseases: osteoporosis, bone injuries, rheumatoid arthritis, and osteosarcoma. We consolidated the most recent finding of the metabolites and metabolite pathways affected by various bone disorders. This collection can serve as a basis for future metabolomics-driven bone research studies to select the most relevant metabolites and metabolic pathways. Additionally, we summarize recent metabolic studies on metabolomics for the development of bone disease treatment including biomaterials for bone engineering. With this article, we aim to provide a comprehensive summary of metabolomics in bone research, which can be helpful for interdisciplinary researchers, including material engineers, biologists, and clinicians.

Can metabolic profiling provide a new description of osteoarthritis and enable a personalised medicine approach?

Osteoarthritis (OA) is a multifactorial disease contributing to significant disability and economic burden in Western populations. The aetiology of OA remains poorly understood, but is thought to involve genetic, mechanical and environmental factors. Currently, the diagnosis of OA relies predominantly on clinical assessment and plain radiographic changes long after the disease has been initiated. Recent advances suggest that there are changes in joint fluid metabolites that are associated with OA development. If this is the case, biochemical and metabolic biomarkers of OA could help determine prognosis, monitor disease progression and identify potential therapeutic targets. Moreover, for focussed management and personalised medicine, novel biomarkers could sub-stratify patients into OA phenotypes, differentiating metabolic OA from post-traumatic, age-related and genetic OA. To date, OA biomarkers have concentrated on cytokine action and protein signalling with some progress. However, these remain to be adopted into routine clinical practice. In this review, we outline the emerging metabolic links to OA pathogenesis and how an elucidation of the metabolic changes in this condition may provide future, more descriptive biomarkers to differentiate OA subtypes.