Platelet proteomics in diagnostic differentiation of primary immune thrombocytopenia using SELDI-TOF-MS

The Impact of Artificial Intelligence in the Odyssey of Rare Diseases

Emerging machine learning (ML) technologies have the potential to significantly improve the research and treatment of rare diseases, which constitute a vast set of diseases that affect a small proportion of the total population. Artificial Intelligence (AI) algorithms can help to quickly identify patterns and associations that would be difficult or impossible for human analysts to detect. Predictive modeling techniques, such as deep learning, have been used to forecast the progression of rare diseases, enabling the development of more targeted treatments. Moreover, AI has also shown promise in the field of drug development for rare diseases with the identification of subpopulations of patients who may be most likely to respond to a particular drug. This review aims to highlight the achievements of AI algorithms in the study of rare diseases in the past decade and advise researchers on which methods have proven to be most effective. The review will focus on specific rare diseases, as defined by a prevalence rate that does not exceed 1-9/100,000 on Orphanet, and will examine which AI methods have been most successful in their study. We believe this review can guide clinicians and researchers in the successful application of ML in rare diseases.

Identification of Candidate Biomarkers for Idiopathic Thrombocytopenic Purpura by Bioinformatics Analysis of Microarray Data

Idiopathic Thrombocytopenic Purpura (ITP) is a multifactorial disease with decreased count of platelet that can lead to bruising and bleeding manifestations. This study was intended to identify critical genes associated with chronic ITP. The gene expression profile GSE46922 was downloaded from the Gene Expression Omnibus database to recognize Differentially Expressed Genes (DEGs) by R software. Gene ontology and pathway analyses were performed by DAVID. The biological network was constructed using the Cytoscape. Molecular Complex Detection (MCODE) was applied for detecting module analysis. Transcription factors were identified by the PANTHER classification system database and the gene regulatory network was constructed by Cytoscape. One hundred thirty-two DEGs were screened from comparison newly diagnosed ITP than chronic ITP. Biological process analysis revealed that the DEGs were enriched in terms of positive regulation of autophagy and prohibiting apoptosis in the chronic phase. KEGG pathway analysis showed that the DEGs were enriched in the ErbB signaling pathway, mRNA surveillance pathway, Estrogen signaling pathway, and Notch signaling pathway. Additionally, the biological network was established, and five modules were extracted from the network. ARRB1, VIM, SF1, BUB3, GRK5, and RHOG were detected as hub genes that also belonged to the modules. SF1 also was identified as a hub-TF gene. To sum up, microarray data analysis could perform a panel of genes that provides new clues for diagnosing chronic ITP.

Autoimmune hemolytic anemia: current knowledge and perspectives

Autoimmune hemolytic anemia (AIHA) is an acquired, heterogeneous group of diseases which includes warm AIHA, cold agglutinin disease (CAD), mixed AIHA, paroxysmal cold hemoglobinuria and atypical AIHA. Currently CAD is defined as a chronic, clonal lymphoproliferative disorder, while the presence of cold agglutinins underlying other diseases is known as cold agglutinin syndrome. AIHA is mediated by autoantibodies directed against red blood cells (RBCs) causing premature erythrocyte destruction. The pathogenesis of AIHA is complex and still not fully understood. Recent studies indicate the involvement of T and B cell dysregulation, reduced CD4+ and CD25+ Tregs, increased clonal expansions of CD8 + T cells, imbalance of Th17/Tregs and Tfh/Tfr, and impaired lymphocyte apoptosis. Changes in some RBC membrane structures, under the influence of mechanical stimuli or oxidative stress, may promote autohemolysis. The clinical presentation and treatment of AIHA are influenced by many factors, including the type of AIHA, degree of hemolysis, underlying diseases, presence of concomitant comorbidities, bone marrow compensatory abilities and the presence of fibrosis and dyserthropoiesis. The main treatment for AIHA is based on the inhibition of autoantibody production by mono- or combination therapy using GKS and/or rituximab and, rarely, immunosuppressive drugs or immunomodulators. Reduction of erythrocyte destruction via splenectomy is currently the third line of treatment for warm AIHA. Supportive treatment including vitamin supplementation, recombinant erythropoietin, thrombosis prophylaxis and the prevention and treatment of infections is essential. New groups of drugs that inhibit immune responses at various levels are being developed intensively, including inhibition of antibody-mediated RBCs phagocytosis, inhibition of B cell and plasma cell frequency and activity, inhibition of IgG recycling, immunomodulation of T lymphocytes function, and complement cascade inhibition. Recent studies have brought about changes in classification and progress in understanding the pathogenesis and treatment of AIHA, although there are still many issues to be resolved, particularly concerning the impact of age-associated changes to immunity.

Significant reductions in apoptosis-related proteins (HSPA6, HSPA8, ITGB3, YWHAH, and PRDX6) are involved in immune thrombocytopenia

To investigate differences in the expression of plasma proteins in immune thrombocytopenia (ITP) and normal control groups, bone marrow samples were collected from 20 active ITP patients and 20 healthy controls. Quantitative proteomics analysis based on mass spectrometry was used to measure the protein levels and understand the protein networks. We found differentially expressed proteins in ITP patients and healthy controls. Parallel reaction monitoring (PRM), a targeted proteome quantification technique, was used to quantitatively confirm the identified target proteins and verify the proteomics data. In this study, a total of 829 proteins were identified, and the fold-change cut-off was set at 1.5 (patients vs controls); a total of 26 proteins were upregulated, and 69 proteins were downregulated. The bioinformatics analysis indicated that some differentially expressed proteins were associated with apoptosis. KEGG enrichment analysis showed that the apoptosis-related proteins were closely related to the PI3K-Akt signalling pathway. PRM demonstrated that apoptosis-related proteins were significantly decreased in ITP patients, which further confirmed the important effect of apoptosis on ITP pathogenesis. We hypothesised that apoptosis may be closely related to ITP pathogenesis through the PI3K-Akt signalling pathway.

Autoimmune Cytopenias in Chronic Lymphocytic Leukemia: Focus on Molecular Aspects

Autoimmune cytopenias, particularly autoimmune hemolytic anemia (AIHA) and immune thrombocytopenia (ITP), complicate up to 25% of chronic lymphocytic leukemia (CLL) cases. Their occurrence correlates with a more aggressive disease with unmutated VHIG status and unfavorable cytogenetics (17p and 11q deletions). CLL lymphocytes are thought to be responsible of a number of pathogenic mechanisms, including aberrant antigen presentation and cytokine production. Moreover, pathogenic B-cell lymphocytes may induce T-cell subsets imbalance that favors the emergence of autoreactive B-cells producing anti-red blood cells and anti-platelets autoantibodies. In the last 15 years, molecular insights into the pathogenesis of both primary and secondary AIHA/ITP has shown that autoreactive B-cells often display stereotyped B-cell receptor and that the autoantibodies themselves have restricted phenotypes. Moreover, a skewed T-cell repertoire and clonal T cells (mainly CD8+) may be present. In addition, an imbalance of T regulatory-/T helper 17-cells ratio has been involved in AIHA and ITP development, and correlates with various cytokine genes polymorphisms. Finally, altered miRNA and lnRNA profiles have been found in autoimmune cytopenias and seem to correlate with disease phase. Genomic studies are limited in these forms, except for recurrent mutations of KMT2D and CARD11 in cold agglutinin disease, which is considered a clonal B-cell lymphoproliferative disorder resulting in AIHA. In this manuscript, we review the most recent literature on AIHA and ITP secondary to CLL, focusing on available molecular evidences of pathogenic, clinical, and prognostic relevance.

MicroRNAs as potential regulators of platelet function and bleeding diatheses

Although a growing number of studies suggest that microRNAs (miRNAs) play a relevant role in platelet biology, their implications in bleeding diatheses are starting to be investigated. Indeed, several studies have shown that alterations in the intracellular levels of highly expressed platelet miRNAs provoke a thrombotic phenotype. On the other hand, primary immune thrombocytopenia (ITP), which is considered the hallmark of acquired bleeding disorders, has been recently associated with altered levels of miRNAs in peripheral blood mononuclear cells, plasma, and platelets. In this review, we will focus on miRNAs that may affect the hemostatic and thrombotic functions of platelets, and we will discuss the different studies that have attempted to associate miRNAs with regulatory mechanisms of ITP.

MicroRNA profiling of platelets from immune thrombocytopenia and target gene prediction

Immune thrombocytopenia (ITP) is an autoimmune disease characterized by a low platelet count and insufficient platelet production. Previous studies identified that microRNAs (miRNAs/miRs) are important for platelet function. However, the regulatory role of miRNAs in the pathogenesis of thrombocytopenia in ITP remains unclear. The aim of the present study is to isolate differentially expressed miRNAs, and identify their roles in platelets from ITP. A total of 5 ml blood from 22 patients with ITP and 8 healthy controls was isolated for platelet collection. A microarray assay was performed to analyze the differentially expressed miRNAs in the patients with ITP and healthy patients. Furthermore, the expression of differentially expressed miRNAs was verified by reverse transcription‑quantitative polymerase chain reaction. In addition, the target mRNAs of the differentially expressed miRNAs were predicted via miRWalk databases, and the target genes and miRNAs were classified by Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes analyses. In the present study, 115 miRNAs were identified to be differentially expressed in platelets from patients with ITP compared with the healthy controls (>3‑fold alteration; P<0.05). Among them, 57 miRNAs were upregulated in ITP, while 58 miRNAs were downregulated. Bioinformatic prediction demonstrated that hsa‑miR‑548a‑5p, hsa‑miR‑1185‑2‑3p, hsa‑miR‑30a‑3p, hsa‑miR‑6867‑5p, hsa‑miR‑765 and hsa‑miR‑3125 were associated with platelet apoptosis and adhesion in ITP. The present study performed miRNA profiling of platelets from patients with ITP and the results may aid in the understanding of the regulatory mechanism of ITP.