Genome-Wide Multiple Sclerosis Association Data and Coagulation

Biological and technical factors affecting the point-of-care diagnostics in not-oncological chronic diseases

Inexpensive point-of-care (POC) analytical solutions have the potential to allow the implementation of large-scale screening campaigns aimed at identifying the initial stages of pathologies in the population, reducing morbidity, mortality and, indirectly, also the costs for the healthcare system. At global level, the most common preventive screening schemes address some cancer pathologies or are used to monitor the spread of some infective diseases. However, systematic testing might become decisive to improve the care response even in the case of chronic pathologies and, in this review, we analyzed the state-of-the-art of the POC diagnostics for Chronic Kidney Disease, Chronic Obstructive Pulmonary Disease and Multiple Sclerosis. The different technological options used to manufacture the biosensors and evaluate the produced data have been described and this information has been integrated with the present knowledge relatively to the biomarkers that have been proposed to monitor such diseases, namely their availability and reliability. Finally, the nature of the macromolecules used to capture the biomarkers has been discussed in relation to the biomarker nature.

Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data

BACKGROUND

Expression quantitative trait loci (eQTL) studies show how genetic variants affect downstream gene expression. Single-cell data allows reconstruction of personalized co-expression networks and therefore the identification of SNPs altering co-expression patterns (co-expression QTLs, co-eQTLs) and the affected upstream regulatory processes using a limited number of individuals.

RESULTS

We conduct a co-eQTL meta-analysis across four scRNA-seq peripheral blood mononuclear cell datasets using a novel filtering strategy followed by a permutation-based multiple testing approach. Before the analysis, we evaluate the co-expression patterns required for co-eQTL identification using different external resources. We identify a robust set of cell-type-specific co-eQTLs for 72 independent SNPs affecting 946 gene pairs. These co-eQTLs are replicated in a large bulk cohort and provide novel insights into how disease-associated variants alter regulatory networks. One co-eQTL SNP, rs1131017, that is associated with several autoimmune diseases, affects the co-expression of RPS26 with other ribosomal genes. Interestingly, specifically in T cells, the SNP additionally affects co-expression of RPS26 and a group of genes associated with T cell activation and autoimmune disease. Among these genes, we identify enrichment for targets of five T-cell-activation-related transcription factors whose binding sites harbor rs1131017. This reveals a previously overlooked process and pinpoints potential regulators that could explain the association of rs1131017 with autoimmune diseases.

CONCLUSION

Our co-eQTL results highlight the importance of studying context-specific gene regulation to understand the biological implications of genetic variation. With the expected growth of sc-eQTL datasets, our strategy and technical guidelines will facilitate future co-eQTL identification, further elucidating unknown disease mechanisms.

Role of Fibrinogen in Type-2 Diabetes Mellitus with Diabetic Neuropathy and its Preliminary Mechanism

INTRODUCTION

Diabetic peripheral neuropathy (DN) is the most common complication of type 2 diabetes mellitus (T2DM).

OBJECTIVE

This study aimed to explore the role of fibrinogen (FIB) in T2DM neuropathy and its preliminary mechanism.

METHODS

Ten male Sprague-Dawley rats were divided into a normal control group (NC group) and a T2DM neuropathy model group (DN group). The DN group was given a high-energy diet and streptozotocin, while the NC group was given a normal diet and a citric acid buffer. The expression levels of related proteins were analysed.

RESULTS

Electrophysiology: Compared with the NC group, the conduction latency of the somatosensory-evoked potential and nerve conduction velocity was prolonged in the DN group, while the motor nerve action potential was decreased. As seen under a light microscope, the peripheral nerve fibres in the DN group were swollen, and the nerve fibres in the posterior funiculus of the spinal cord were loose or missing. Moreover, as seen under an electron microscope, the peripheral nerve demyelination of the DN group was severe, with microvascular blood coagulation, luminal stenosis, and collapse. Compared with the NC group, in the DN group, the expression of FIB was positively correlated with the expression of both ionised calcium-binding adaptor molecule-1 and glial fibrillary acidic protein. Compared with the NC group, in the DN group, the expression of platelet/endothelial cell adhesion molecule-1 and B-cell lymphoma 2 was negatively correlated.

CONCLUSION

The increased concentration of FIB may be the cause of neuropathy, and its mechanism may be related to its promotion of inflammatory response, blood coagulation, and vascular stenosis.

Neurocoagulation from a Mechanistic Point of View in the Central Nervous System

Coagulation mechanisms are critical for maintaining homeostasis in the central nervous system (CNS). Thrombin, an important player of the coagulation cascade, activates protease activator receptors (PARs), members of the G-protein coupled receptor family. PAR1 is located on neurons and glia. Following thrombin activation, PAR1 signals through the extracellular signal-regulated kinase pathway, causing alterations in neuronal glutamate release and astrocytic morphological changes. Similarly, the anticoagulation factor activated protein C (aPC) can cleave PAR1, following interaction with the endothelial protein C receptor. Both thrombin and aPC are expressed on endothelial cells and pericytes in the blood-brain barrier (BBB). Thrombin-induced PAR1 activation increases cytosolic Ca²⁺ concentration in brain vessels, resulting in nitric oxide release and increasing F-actin stress fibers, damaging BBB integrity. aPC also induces PAR1 activation and preserves BBB vascular integrity via coupling to sphingosine 1 phosphate receptors. Thrombin-induced PAR1 overactivation and BBB disruption are evident in CNS pathologies. During epileptic seizures, BBB disruption promotes thrombin penetration. Thrombin induces PAR1 activation and potentiates N-methyl-D-aspartate receptors, inducing glutamate-mediated hyperexcitability. Specific PAR1 inhibition decreases status epilepticus severity in vivo. In stroke, the elevation of brain thrombin levels further compromises BBB integrity, with direct parenchymal damage, while systemic factor Xa inhibition improves neurological outcomes. In multiple sclerosis (MS), brain thrombin inhibitory capacity correlates with clinical presentation. Both thrombin inhibition by hirudin and the use of recombinant aPC improve disease severity in an MS animal model. This review presents the mechanisms underlying the effects of coagulation on the physiology and pathophysiology of the CNS.

RNA Sequencing of CD4+ T Cells in Relapsing-Remitting Multiple Sclerosis Patients at Relapse: Deciphering the Involvement of Novel genes and Pathways

CD4⁺ T cells are known as a noteworthy potential modulator of inflammation in multiple sclerosis (MS). In the current study, we investigated the transcriptome profile of CD4⁺ T cells in patients with relapsing-remitting MS (RRMS) at the relapse phase. We performed RNA sequencing of CD4⁺ T cells isolated from four relapsing-remitting MS (RRMS) patients at the relapse phase and four age- and sex-matched healthy controls. The edgeR statistical method was employed to determine differentially expressed genes (DEGs). Gene set enrichment analysis was subsequently performed. Applying a physical interaction network, genes with higher degrees were selected as hub genes. A total of 1278 and 1034 genes were defined at significantly higher or lower levels, respectively, in CD4⁺ T cells of RRMS patients at the relapse phase as compared with healthy controls. The top up- and downregulated genes were JAML and KDM3A. The detected DEGs were remarkable on chromosomes 1 and 2, respectively. The DEGs were mainly enriched in the pathways "regulation of transcription, DNA-templated," "regulation of B cell receptor signaling pathway," "protein phosphorylation," "epidermal growth factor receptor signaling pathway," and "positive regulation of neurogenesis." Moreover, 16 KEGG pathways mostly associated with the immune system and viral infections were enriched. In the constructed physical interaction networks, UBA52 and TP53 were shown to be the most highly ranked hub genes among upregulated and downregulated genes, respectively. By applying global transcriptome profiling of CD4⁺ T cells, we deciphered the involvement of several novel genes and pathways in MS pathogenesis. The present results must be confirmed by in vivo and in vitro studies.

SARS-CoV-2 meta-interactome suggests disease-specific, autoimmune pathophysiologies and therapeutic targets

Background: Severe coronavirus disease 2019 (COVID-19) is associated with multiple comorbidities and is characterized by an auto-aggressive inflammatory state leading to massive collateral damage. To identify preventive and therapeutic strategies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is important to ascertain the molecular interactions between virus and host, and how they translate into disease pathophysiology. Methods: We matched virus-human protein interactions of human coronaviruses and other respiratory viruses with lists of genes associated with autoimmune diseases and comorbidities associated to worse COVID-19 course. We then selected the genes included in the statistically significant intersection between SARS-CoV-2 network and disease associated gene sets, identifying a meta-interactome. We analyzed the meta-interactome genes expression in samples derived from lungs of infected humans, and their regulation by IFN-β. Finally, we performed a drug repurposing screening to target the network's most critical nodes. Results: We found a significant enrichment of SARS-CoV-2 interactors in immunological pathways and a strong association with autoimmunity and three prognostically relevant conditions (type 2 diabetes, coronary artery diseases, asthma), that present more independent physiopathological subnetworks. We observed a reduced expression of meta-interactome genes in human lungs after SARS-CoV-2 infection, and a regulatory potential of type I interferons. We also underscored multiple repurposable drugs to tailor the therapeutic strategies. Conclusions: Our data underscored a plausible genetic background that may contribute to the distinct observed pathophysiologies of severe COVID-19. Also, these results may help identify the most promising therapeutic targets and treatments for this condition.

Reworking GWAS Data to Understand the Role of Nongenetic Factors in MS Etiopathogenesis

Genome-wide association studies have identified more than 200 multiple sclerosis (MS)-associated loci across the human genome over the last decade, suggesting complexity in the disease etiology. This complexity poses at least two challenges: the definition of an etiological model including the impact of nongenetic factors, and the clinical translation of genomic data that may be drivers for new druggable targets. We reviewed studies dealing with single genes of interest, to understand how MS-associated single nucleotide polymorphism (SNP) variants affect the expression and the function of those genes. We then surveyed studies on the bioinformatic reworking of genome-wide association studies (GWAS) data, with aggregate analyses of many GWAS loci, each contributing with a small effect to the overall disease predisposition. These investigations uncovered new information, especially when combined with nongenetic factors having possible roles in the disease etiology. In this context, the interactome approach, defined as “modules of genes whose products are known to physically interact with environmental or human factors with plausible relevance for MS pathogenesis”, will be reported in detail. For a future perspective, a polygenic risk score, defined as a cumulative risk derived from aggregating the contributions of many DNA variants associated with a complex trait, may be integrated with data on environmental factors affecting the disease risk or protection.