Proteomic identification of differentially expressed proteins in vascular wall of patients with ruptured intracranial aneurysms

Impact of Sorbs2 dysfunction on cardiovascular diseases

Despite significant advancements in prevention and treatment over the past decades, cardiovascular diseases (CVDs) remain the leading cause of death worldwide. CVDs involve multifactorial inheritance, but our understanding of the genetic impact on these diseases is still incomplete. Sorbin and SH3 domain-containing protein 2 (Sorbs2) is ubiquitously expressed in various tissues, including the cardiovascular system. Increasing evidence suggests that Sorbs2 malfunction contributes to CVDs. This manuscript will review our current understanding of the potential mechanisms underlying Sorbs2 dysregulation in the development of CVDs.

TM9SF1 expression correlates with autoimmune disease activity and regulates antibody production through mTOR-dependent autophagy

BACKGROUND

Transmembrane 9 superfamily member 1 (TM9SF1) is involved in inflammation. Since both inflammatory and autoimmune diseases are linked to immune cells regulation, this study investigated the association between TM9SF1 expression and autoimmune disease activity. As B cell differentiation and autoantibody production exacerbate autoimmune disease, the signaling pathways involved in these processes were explored.

METHODS

Tm9sf1-/- mouse rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) models were used to verify the relationship between gene expression and disease severity. Peripheral blood mononuclear cells (PBMCs) from 156 RA and 145 SLE patients were used to explore the relationship between TM9SF1 expression and disease activity. The effectiveness of TM9SF1 as a predictor of disease activity was assessed using multiple logistic regression and receiver operating characteristic (ROC) curves. The signaling pathways regulated by TM9SF1 in B cell maturation and antibody production were conducted by plasma cell induction experiment in vitro.

RESULTS

The Tm9sf1-/- RA and SLE model mice produced fewer autoantibodies and showed reduced disease severity relative to wild-type (WT) mice. TM9SF1 levels in PBMCs of patients were higher than those in healthy controls, and were reduced in patients with low disease activity relative to those with active RA and SLE. Furthermore, TM9SF1 levels were positively linked with autoantibody titers and pro-inflammatory cytokine levels in both diseases. ROC analyses indicated TM9SF1 outperformed several important clinical indicators in predicting disease activity (area under the curve (AUC) were 0.858 and 0.876 for RA and SLE, respectively). In vitro experiments demonstrated that Tm9sf1 knockout blocked differentiation of B cells into antibody-producing plasma cells by activating mTOR and inhibiting autophagy, and mTOR inhibitors such as rapamycin could reverse this effect.

CONCLUSIONS

The primary finding was the identification of the molecular mechanism underlying autophagy regulation in B cells, in which Tm9sf1 knockout was found to modulate mTOR-dependent autophagy to block B cell differentiation into antibody-secreting plasma cells. It was also found that TM9SF1 expression level in PBMCs was an accurate indicator of disease activity in patients with RA and SLE, suggesting its clinical potential for monitoring disease activity in these patients.

TM9SF1 offers utility as an efficient predictor of clinical severity and mortality among acute respiratory distress syndrome patients

Introduction

Acute respiratory distress syndrome (ARDS) is a major cause of death among critically ill patients in intensive care settings, underscoring the need to identify biomarkers capable of predicting ARDS patient clinical status and prognosis at an early time point. This study specifically sought to explore the utility and clinical relevance of TM9SF1 as a biomarker for the early prediction of disease severity and prognostic outcomes in patients with ARDS.

Methods

This study enrolled 123 patients with severe ARDS and 116 patients with non-severe ARDS for whom follow-up information was available. The mRNA levels of TM9SF1 and cytokines in peripheral blood mononuclear cells from these patients were evaluated by qPCR. The predictive performance of TM9SF1 and other clinical indicators was evaluated using received operating characteristic (ROC) curves. A predictive nomogram was developed based on TM9SF1 expression and evaluated for its ability in the early prediction of severe disease and mortality in patients with ARDS.

Results

TM9SF1 mRNA expression was found to be significantly increased in patients with severe ARDS relative to those with non-severe disease or healthy controls. ARDS severity increased in correspondence with the level of TM9SF1 expression (odds ratio [OR] = 2.43, 95% confidence interval [CI] = 2.15-3.72, P = 0.005), and high TM9SF1 levels were associated with a greater risk of mortality (hazard ratio [HR] = 2.27, 95% CI = 2.20-4.39, P = 0.001). ROC curves demonstrated that relative to other clinical indicators, TM9SF1 offered superior performance in the prediction of ARDS severity and mortality. A novel nomogram incorporating TM9SF1 expression together with age, D-dimer levels, and C-reactive protein (CRP) levels was developed and was used to predict ARDS severity (AUC = 0.887, 95% CI = 0.715-0.943). A separate model incorporating TM9SF1 expression, age, neutrophil-lymphocyte ratio (NLR), and D-dimer levels (C-index = 0.890, 95% CI = 0.627-0.957) was also developed for predicting mortality.

Conclusion

Increases in ARDS severity and patient mortality were observed with rising levels of TM9SF1 expression. TM9SF1 may thus offer utility as a novel biomarker for the early prediction of ARDS patient disease status and clinical outcomes.

Identification of differentially expressed autophagy-related genes in cases of intracranial aneurysm: Bioinformatics analysis

OBJECTIVE

Recent research indicates that autophagy is essential for the rupture of intracranial aneurysm (IA). This study aimed to examine and validate potential autophagy-related genes (ARGs) in cases of IA using bioinformatics analysis.

METHODS

Two expression profiles (GSE54083 and GSE75436) were obtained from the Gene Expression Omnibus database. Differentially expressed ARGs (DEARGs) in cases of IA were screened using GSE75436, and enrichment analysis and Protein-Protein Interaction (PPI) networks were used to identify the hub genes and related pathways. Furthermore, a novel predictive diagnostic signature for IA based on the hub genes was constructed. The area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the signature performance in GSE75436.

RESULTS

In total, 75 co-expressed DEARGs were identified in the GSE75436 and GSE54083 dataset (28 upregulated and 47 downregulated genes). Enrichment analysis of DEARGs revealed several enriched terms associated with proteoglycans in cancer and human immunodeficiency virus 1 infection. PPI analysis revealed interactions between these genes. Hub DEARGs included insulin-like growth factor 1, clusters of differentiation 4, cysteine-aspartic acid protease 8, Bcl-2-like protein 11, mouse double mutant 2 homolog, toll-like receptor 4, growth factor receptor-bound protein 2, Jun proto-oncogene, AP-1 transcription factor subunit, hypoxia inducible factor 1 alpha, and erythroblastic oncogene B-2. Notably, the signature showed good performance in distinguishing IA (AUC = 0.87). The sig calibration curves showed good calibration.

CONCLUSION

Bioinformatic analysis identified 75 potential DEARGs in cases of IA. This study revealed that IA is affected by autophagy, which could explain the pathogenesis of IA and aid in its diagnosis and treatment. However, future research with experimental validation is necessary to identify potential DEARGs in cases of IA.

Mechanisms of FA-Phagy, a New Form of Selective Autophagy/Organellophagy

Focal adhesions (FAs) are adhesive organelles that attach cells to the extracellular matrix and can mediate various biological functions in response to different environmental cues. Reduced FAs are often associated with enhanced cell migration and cancer metastasis. In addition, because FAs are essential for preserving vascular integrity, the loss of FAs leads to hemorrhages and is frequently observed in many vascular diseases such as intracranial aneurysms. For these reasons, FAs are an attractive therapeutic target for treating cancer or vascular diseases, two leading causes of death world-wide. FAs are controlled by both their formation and turnover. In comparison to the large body of literature detailing FA formation, the mechanisms of FA turnover are poorly understood. Recently, autophagy has emerged as a major mechanism to degrade FAs and stabilizing FAs by inhibiting autophagy has a beneficial effect on breast cancer metastasis, suggesting autophagy-mediated FA turnover is a promising drug target. Intriguingly, autophagy-mediated FA turnover is a selective process and the cargo receptors for recognizing FAs in this process are context-dependent, which ensures the degradation of specific cargo. This paper mainly reviews the cargo recognition mechanisms of FA-phagy (selective autophagy-mediated FA turnover) and its disease relevance. We seek to outline some new points of understanding that will facilitate further study of FA-phagy and precise therapeutic strategies for related diseases associated with aberrant FA functions.

RNA Sequencing Data from Human Intracranial Aneurysm Tissue Reveals a Complex Inflammatory Environment Associated with Rupture

BACKGROUND

Intracranial aneurysm (IA) rupture leads to deadly subarachnoid hemorrhages. However, the mechanisms leading to rupture remain poorly understood. Altered gene expression within IA tissue is linked to the pathobiology of aneurysm development and progression. Here, we analyzed expression patterns of control tissue samples and compared them to those of unruptured and ruptured IA tissue samples using data from the Gene Expression Omnibus (GEO).

METHODS

FASTQ files for 21 ruptured IAs, 21 unruptured IAs, and 16 control tissue samples were accessed from the GEO database. DESeq2 was used for differential expression analysis in three comparisons: unruptured IA versus control, ruptured IA versus control, and ruptured versus unruptured IA. Genes that were differentially expressed in multiple comparisons were evaluated to find those progressively increasing/decreasing from control to unruptured to ruptured. Significance was tested by either analysis of variance/Gabriel or Brown-Forsythe/Games Howell (p < 0.05 was considered significant). We used additional RNA sequencing and proteomics datasets to evaluate if our differentially expressed genes (DEGs) were present in other studies. Bioinformatics analyses were performed with g:Profiler and Ingenuity Pathway Analysis.

RESULTS

In total, we identified 1768 DEGs, of which 318 were found in multiple comparisons. Unruptured versus control reflected vascular remodeling processes, while ruptured versus control reflected inflammatory responses and cell activation/signaling. When comparing ruptured to unruptured IAs, we found massive activation of inflammation, inflammatory responses, and leukocyte responses. Of the 318 genes in multiple comparisons, 127 were found to be significant in the multi-cohort correlation analysis. Those that progressively increased (70 genes) were associated with immune system processes, while those that progressively decreased (38 genes) did not return any gene ontology terms. Many of our DEGs were also found in the other IA tissue sequencing studies.

CONCLUSIONS

We found unruptured IAs relate more to remodeling processes, while ruptured IAs reflect more inflammatory and immune responses.

Peptidomic profiling of cerebrospinal fluid from patients with intracranial saccular aneurysms

Intracranial saccular aneurysms (ISA) represent 90%-95% of all intracranial aneurysm cases, characterizing abnormal pockets at arterial branch points. Ruptures lead to subarachnoid hemorrhages (SAH) and poor prognoses. We applied mass spectrometry-based peptidomics to investigate the peptidome of twelve cerebrospinal fluid (CSF) samples collected from eleven patients diagnosed with ISA. For peptide profile analyses, participants were classified into: 1) ruptured intracranial saccular aneurysms (RIA), 2) unruptured intracranial saccular aneurysms (UIA), and late-ruptured intracranial saccular aneurysms (LRIA). Altogether, a total of 2199 peptides were detected by both Mascot and Peaks software, from which 484 (22.0%) were unique peptides. All unique peptides presented conserved chains, domains, regions of protein modulation and/or post-translational modification sites related to human diseases. Gene Ontology (GO) analyses of peptide precursor proteins showed that 42% are involved in binding, 56% in cellular anatomical entities, and 39% in intercellular signaling molecules. Unique peptides identified in patients diagnosed with RIA have a larger molecular weight and a distinctive developmental process compared to UIA and LRIA (P ≤ 0.05). Continued investigations will allow the characterization of the biological and clinical significance of the peptides identified in the present study, as well as identify prototypes for peptide-based pharmacological therapies to treat ISA. SIGNIFICANCE.

Classification models using circulating neutrophil transcripts can detect unruptured intracranial aneurysm

Background

Intracranial aneurysms (IAs) are dangerous because of their potential to rupture. We previously found significant RNA expression differences in circulating neutrophils between patients with and without unruptured IAs and trained machine learning models to predict presence of IA using 40 neutrophil transcriptomes. Here, we aim to develop a predictive model for unruptured IA using neutrophil transcriptomes from a larger population and more robust machine learning methods.

Methods

Neutrophil RNA extracted from the blood of 134 patients (55 with IA, 79 IA-free controls) was subjected to next-generation RNA sequencing. In a randomly-selected training cohort (n = 94), the Least Absolute Shrinkage and Selection Operator (LASSO) selected transcripts, from which we constructed prediction models via 4 well-established supervised machine-learning algorithms (K-Nearest Neighbors, Random Forest, and Support Vector Machines with Gaussian and cubic kernels). We tested the models in the remaining samples (n = 40) and assessed model performance by receiver-operating-characteristic (ROC) curves. Real-time quantitative polymerase chain reaction (RT-qPCR) of 9 IA-associated genes was used to verify gene expression in a subset of 49 neutrophil RNA samples. We also examined the potential influence of demographics and comorbidities on model prediction.

Results

Feature selection using LASSO in the training cohort identified 37 IA-associated transcripts. Models trained using these transcripts had a maximum accuracy of 90% in the testing cohort. The testing performance across all methods had an average area under ROC curve (AUC) = 0.97, an improvement over our previous models. The Random Forest model performed best across both training and testing cohorts. RT-qPCR confirmed expression differences in 7 of 9 genes tested. Gene ontology and IPA network analyses performed on the 37 model genes reflected dysregulated inflammation, cell signaling, and apoptosis processes. In our data, demographics and comorbidities did not affect model performance.

Conclusions

We improved upon our previous IA prediction models based on circulating neutrophil transcriptomes by increasing sample size and by implementing LASSO and more robust machine learning methods. Future studies are needed to validate these models in larger cohorts and further investigate effect of covariates.

Intracranial Aneurysm Biomarker Candidates Identified by a Proteome-Wide Study

The scientific basis of intracranial aneurysm (IA) formation, its rupture and further development of cerebral vasospasm is incompletely understood. Aberrant protein expression may drive structural alterations of vasculature found in IA. Deciphering the molecular mechanisms underlying these events will lead to identification of early detection biomarkers and in turn, improved treatment outcomes. To unravel differential protein expression in three clinical subgroups of IA patients: (1) unruptured aneurysm, (2) ruptured aneurysm without vasospasm, (3) ruptured aneurysm who developed vasospasm, we performed untargeted quantitative proteomic analysis of aneurysm tissue and serum samples from three subgroups of IA patients and control subjects. Candidate molecules were then validated in a larger cohort of patients using enzyme-linked immunosorbent assay. A total of 937 and 294 proteins were identified from aneurysm tissue and serum samples, respectively. Several proteins that are known to maintain structural integrity of vasculature were found to be dysregulated in the context of aneurysm. ORM1, a glycoprotein, was significantly upregulated in both tissue and serum samples of unruptured aneurysm patients. We employed a larger cohort of subjects (n = 26) and validated ORM1 as a potential biomarker for screening of unruptured aneurysms. Samples from ruptured aneurysms with vasospasm showed significant upregulation of MMP9, a protease, compared with ruptured aneurysms without vasospasm. We validated MMP9 as a potential biomarker for vasospasm in a larger cohort (n = 52). This study reports the first global proteomic analysis of the entire clinical spectrum of IA. Furthermore, this study suggests ORM1 and MMP9 as potential biomarkers for unruptured aneurysm and cerebral vasospasm, respectively.

[Autophagy regulates the function of vascular smooth muscle cells in the formation and rupture of intracranial aneurysms]

Vascular smooth muscle cells (VSMC) are the main cellular component of vessel wall. The changes of VSMC functions including phenotypic transformation and apoptosis play a critical role in the pathogenesis of intracranial aneurysm (IA). Autophagy can participate in the regulation of vascular function by regulating cell function. In the initial stage of IA, the activation of autophagy can accelerate the phenotypic transformation of VSMC and inhibit VSMC apoptosis. With the progress of IA, the relationship between autophagy and apoptosis changes from antagonism to synergy or promotion, and a large number of apoptotic VSMC lead to the rupture of IA. In this review, we describe the role of autophagy regulating the function of VSMC in the occurrence, development and rupture of IA, for further understanding the pathogenesis of IA and finding molecular targets to prevent the formation and rupture of IA.

Quantitative proteomics analysis of differentially expressed proteins in ruptured and unruptured cerebral aneurysms by iTRAQ

The underlying pathophysiological mechanisms involved in cerebral aneurysms rupture remain unclear. This study was performed to investigate the differentially expressed proteins between ruptured and unruptured aneurysms using quantitative proteomics. The aneurysmal walls of six ruptured aneurysms and six unruptured aneurysms were collected during the surgical operation. The isobaric tags for relative and absolute quantification (iTRAQ) were used to identify the differentially expressed proteins and western blotting was performed to validate the expression of the proteins of interest. Bioinformatics analysis of the differentially expressed proteins was also performed using the KEGG database and GO database. Between ruptured and unruptured aneurysms, 169 proteins were found differently expressed, including 74 up-regulated proteins and 95 down-regulated proteins with a fold change ≥ 2 and p value ≤ .05. KEGG pathway analysis revealed that phagosome, focal adhesion and ECM-receptor interaction were the most common pathways involved in aneurysm rupture. In addition, the differential expressions of ITGB3, CRABP1 and S100A9 were validated by western blotting. Through the iTRAQ method, we found that inflammatory responses and cell-matrix interactions may play a significant role in the rupture of cerebral aneurysms. These findings provide a basis for better understanding of pathophysiological mechanisms associated with aneurysm rupture.

BIOLOGICAL SIGNIFICANCE

Intracranial aneurysm is the leading cause of life-threating subarachnoid hemorrhage which can cause 45% patients die within 30 days and severe morbidity in long-term survivors. With a high prevalence ranging from 1% to 5% in general population, cerebral aneurysm has become a widespread health hazard over past decades. Though great advances have been achieved in the diagnosis and treatment of this disease, the underlying pathophysiological mechanisms of aneurysm rupture remains undetermined and a lot of uncertainty still exists surrounding the treatment of unruptured cerebral aneurysms. Clarifying the mechanism associated with aneurysm rupture is important for estimating the rupture risk, as well as the development of new treatment strategy. Some previous studies have analyzed the molecular differences between ruptured and unruptured IAs at gene and mRNA levels, but further comprehensive proteomic studies are relatively rare. Here we performed a comparative proteomics study to investigate the differentially expressed proteins between ruptured IAs (RIAs) and unruptured IAs (UIAs). Results of our present study will provide more insights into the pathogenesis of aneurysm rupture at protein level. With a better understanding of pathophysiological mechanisms associated with aneurysm rupture, some noninvasive treatment strategies may be developed in the future.

NF-κB-Mediated Inflammation in the Pathogenesis of Intracranial Aneurysm and Subarachnoid Hemorrhage. Does Autophagy Play a Role?

The rupture of saccular intracranial aneurysms (IA) is the commonest cause of non-traumatic subarachnoid hemorrhage (SAH)—the most serious form of stroke with a high mortality rate. Aneurysm walls are usually characterized by an active inflammatory response, and NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) has been identified as the main transcription factor regulating the induction of inflammation-related genes in IA lesions. This transcription factor has also been related to IA rupture and resulting SAH. We and others have shown that autophagy interacts with inflammation in many diseases, but there is no information of such interplay in IA. Moreover, NF-κB, which is a pivotal factor controlling inflammation, is regulated by autophagy-related proteins, and autophagy is regulated by NF-κB signaling. It was also shown that autophagy mediates the normal functioning of vessels, so its disturbance can be associated with vessel-related disorders. Early brain injury, delayed brain injury, and associated cerebral vasospasm are among the most serious consequences of IA rupture and are associated with impaired function of the autophagy⁻lysosomal system. Further studies on the role of the interplay between autophagy and NF-κB-mediated inflammation in IA can help to better understand IA pathogenesis and to identify IA patients with an increased SAH risk.

Sustained Molecular Pathology Across Episodes and Remission in Major Depressive Disorder

BACKGROUND

Major depressive disorder (MDD) is a debilitating mental illness and a major cause of lost productivity worldwide. MDD patients often suffer from lifelong recurring episodes of increasing severity, reduced therapeutic response, and shorter remission periods, suggesting the presence of a persistent and potentially progressive pathology.

METHODS

Subgenual anterior cingulate cortex postmortem samples from four MDD cohorts (single episode, n = 20; single episode in remission, n = 15; recurrent episode, n = 20; and recurrent episode in remission, n = 15), and one control cohort (n = 20) were analyzed by mass spectrometry-based proteomics (n = 3630 proteins) combined with statistical analyses. The data was investigated for trait and state progressive neuropathologies in MDD using both unbiased approaches and tests of a priori hypotheses.

RESULTS

The data provided weak evidence for proteomic differences as a function of state (depressed/remitted) or number of previous episodes. Instead it suggested the presence of persistent MDD effects, regardless of episodes or remitted state, namely on proteomic measures related to presynaptic neurotransmission, synaptic function, cytoskeletal rearrangements, energy metabolism, phospholipid biosynthesis/metabolism, and calcium ion homeostasis. Selected proteins (dihydropyrimidinase-related protein 1, synaptosomal-associated protein 29, glutamate decarboxylase 1, metabotropic glutamate receptor 1, and excitatory amino acid transporter 3) were validated by Western blot analysis. The findings were independent of technical, demographic (sex or age), or other clinical parameters (death by suicide and drug treatment).

CONCLUSIONS

Collectively, the results provide evidence for persistent MDD effects across current episodes or remission, in the absence of detectable progressive neuropathology.

Recent advances and clinical insights into the use of proteomics in the study of atherosclerosis

INTRODUCTION

The application of new proteomics methods may help to identify new diagnostic/predictive molecular markers in an attempt to improve the clinical management of atherosclerosis. Areas covered: Technological advances in proteomics have enhanced its sensitivity and multiplexing capacity, as well as the possibility of studying protein interactions and tissue structure. These advances will help us better understand the molecular mechanisms at play in atherosclerosis as a biological system. Moreover, this should help identify new predictive/diagnostic biomarkers and therapeutic targets that may facilitate effective risk stratification and early diagnosis, with the ensuing rapid implementation of treatment. This review provides a comprehensive overview of the novel methods in proteomics, including state-of-the-art techniques, novel biological samples and applications for the study of atherosclerosis. Expert commentary: Collaboration between clinicians and researchers is crucial to further validate and introduce new molecular markers to manage atherosclerosis that are identified using the most up to date proteomic approaches.