Immune System Processes Research Articles

Use of Transcriptomics to Reveal the Joint Immunotoxicity Mechanism Initiated by Difenoconazole and Chlorothalonil in the Human Jurkat T-Cell Line.

It is very important to evaluate the immunotoxicity and molecular mechanisms of pesticides. In this study, difenoconazole and chlorothalonil were evaluated for immunotoxicity by using the human Jurkat T-cell line, and the EC50 were 24.66 and 1.17 mg/L, respectively. The joint exposure of difenoconazole and chlorothalonil showed a synergistic effect at low concentrations (lower than 10.58 mg/L) but an antagonistic effect at high concentrations (higher than 10.58 mg/L). With joint exposure at a concentration of EC10, the proportion of late apoptotic cells was 2.26- and 2.91-fold higher than that with exposure to difenoconazole or chlorothalonil alone, respectively. A transcriptomics analysis indicated that the DEGs for single exposure are associated with immunodeficiency disease. Single exposure to chlorothalonil was mainly involved in cation transportation, extracellular matrix organization, and leukocyte cell adhesion. Single exposure to difenoconazole was mainly involved in nervous system development, muscle contraction, and immune system processes. However, when the joint exposure dose was EC10, the DEGs were mainly involved in the formation of cell structures, but the DEGs were mainly involved in cellular processes and metabolism when the joint exposure dose was EC25. The results indicated that the immunotoxicological mechanisms underlying joint exposure to difenoconazole and chlorothalonil are different under low and high doses.

Identification of diagnostic immune-related gene biomarkers for predicting heart failure after acute myocardial infarction.

Post-myocardial infarction heart failure (HF) is a major public health concern. Previous studies have reported the critical role of immune response in HF pathogenesis. However, limited studies have reported predictive immune-associated biomarkers for HF. So we attempted to identify potential immune-related indicators for HF early diagnosis and therapy guidance. This study identified two potential immune-related hub genes (IRHGs), namely CXCR5 and FOS, using bioinformatic approaches. The expression levels of CXCR5 and FOS and their ability to predict long-term HF were analyzed. Functional enrichment analysis revealed that the hub genes were enriched in immune system processes, including the interleukin-17 and nuclear factor-kappa B signaling pathways, which are involved in the pathogenesis of HF. Quantitative real-time polymerase chain reaction revealed that the Fos mRNA levels, but not the Cxcr5 mRNA levels, were downregulated in the mice of the HF group. This study successfully identified two IRHGs that were significantly and differentially expressed in the HF group and could predict long-term HF, providing novel insights for future studies on HF and developing novel therapeutic targets for HF.

Gene expression profiling and protein–protein network analysis revealed prognostic hub biomarkers linking cancer risk in type 2 diabetic patients

Type 2 diabetes mellitus (T2DM) and cancer are highly prevalent diseases imposing major health burden globally. Several epidemiological studies indicate increased susceptibility to cancer in T2DM patients. However, genetic factors linking T2DM with cancer have been poorly studied. In this study, we followed computational approaches using the raw gene expression data of peripheral blood mononuclear cells of T2DM and cancer patients available in the gene expression omnibus (GEO) database. Our analysis identified shared differentially expressed genes (DEGs) in T2DM and three common cancer types, namely, pancreatic cancer (PC), liver cancer (LC), and breast cancer (BC). The functional and pathway enrichment analysis of identified common DEGs highlighted the involvement of critical biological pathways, including cell cycle events, immune system processes, cell morphogenesis, gene expression, and metabolism. We retrieved the protein–protein interaction network for the top DEGs to deduce molecular-level interactions. The network analysis found 7, 6, and 5 common hub genes in T2DM vs. PC, T2DM vs. LC, and T2DM vs. BC comparisons, respectively. Overall, our analysis identified important genetic markers potentially able to predict the chances of PC, LC, and BC onset in T2DM patients.

Genetic analysis of the blood transcriptome of young healthy pigs to improve disease resilience

BackgroundDisease resilience is the ability of an animal to maintain productive performance under disease conditions and is an important selection target. In pig breeding programs, disease resilience must be evaluated on selection candidates without exposing them to disease. To identify potential genetic indicators for disease resilience that can be measured on selection candidates, we focused on the blood transcriptome of 1594 young healthy pigs with subsequent records on disease resilience. Transcriptome data were obtained by 3’mRNA sequencing and genotype data were from a 650 K genotyping array.ResultsHeritabilities of the expression of 16,545 genes were estimated, of which 5665 genes showed significant estimates of heritability (p < 0.05), ranging from 0.05 to 0.90, with or without accounting for white blood cell composition. Genes with heritable expression levels were spread across chromosomes, but were enriched in the swine leukocyte antigen region (average estimate > 0.2). The correlation of heritability estimates with the corresponding estimates obtained for genes expressed in human blood was weak but a sizable number of genes with heritable expression levels overlapped. Genes with heritable expression levels were significantly enriched for biological processes such as cell activation, immune system process, stress response, and leukocyte activation, and were involved in various disease annotations such as RNA virus infection, including SARS-Cov2, as well as liver disease, and inflammation. To estimate genetic correlations with disease resilience, 3205 genotyped pigs, including the 1594 pigs with transcriptome data, were evaluated for disease resilience following their exposure to a natural polymicrobial disease challenge. Significant genetic correlations (p < 0.05) were observed with all resilience phenotypes, although few exceeded expected false discovery rates. Enrichment analysis of genes ranked by estimates of genetic correlations with resilience phenotypes revealed significance for biological processes such as regulation of cytokines, including interleukins and interferons, and chaperone mediated protein folding.ConclusionsThese results suggest that expression levels in the blood of young healthy pigs for genes in biological pathways related to immunity and endoplasmic reticulum stress have potential to be used as genetic indicator traits to select for disease resilience.

A pilot study on the immune cell proteome of long COVID patients shows changes to physiological pathways similar to those in myalgic encephalomyelitis/chronic fatigue syndrome

Of those infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ~ 10% develop the chronic post-viral debilitating condition, long COVID (LC). Although LC is a heterogeneous condition, about half of cases have typical post-viral fatigue with onset and symptoms that are very similar to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). A key question is whether these conditions are closely related. ME/CFS is a post-stressor fatigue condition that arises from multiple triggers. To investigate the pathophysiology of LC, a pilot study of patients (n = 6) and healthy controls (n = 5) has used quantitative proteomics to discover changes in peripheral blood mononuclear cell (PBMC) proteins. A principal component analysis separated all long COVID patients from healthy controls. Analysis of 3131 proteins identified 162 proteins differentially regulated, of which 37 were related to immune functions, and 21 to mitochondrial functions. Markov cluster analysis identified clusters involved in immune system processes, and two aspects of gene expression-spliceosome and transcription. These results were compared with an earlier dataset of 346 differentially regulated proteins in PBMC’s from ME/CFS patients (n = 9) analysed by the same methodology. There were overlapping protein clusters and enriched molecular pathways particularly in immune functions, suggesting the two conditions have similar immune pathophysiology as a prominent feature, and mitochondrial functions involved in energy production were affected in both conditions.

Intercellular adhesion molecule 1 and selectin l play crucial roles in ulcerative colitis.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease that primarily affects the mucosal layer of the colon (large intestine). However, the relationship between Intercellular Adhesion Molecule-1 (ICAM1), SELL and UC is unclear. The UC datasets, GSE87466 and GSE36807, were downloaded from the gene expression omnibus database. The R package limma was utilized to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis was conducted. The construction and analysis of protein-protein interaction network, functional enrichment analysis, gene set enrichment analysis, and comparative toxicogenomics database analysis were performed. TargetScan was employed to screen miRNAs regulating central DEGs. Western blot (WB) was used to verify. A total of 2118 DEGs were identified in our study. Gene ontology analysis indicated their enrichment primarily in immune system processes, cellular responses to chemical stimuli, responses to organic substances, responses to external stimuli, and immune responses. Kyoto Encyclopedia of Genes and Genomes analysis revealed that the target cells were mainly enriched in chemokine signaling pathways and TNF signaling pathways. Gene set enrichment analysis enrichment analysis showed significant enrichment in chemokine signaling pathways and cell adhesion molecules. In the Metascape enrichment project, gene ontology terms included regulation of cell activation and positive regulation of immune response. Through the construction and analysis of a protein-protein interaction network, we identified 11 core genes (ICAM1, SELL, CD44, CD40, CCR7, CXCL8, CD19, CCL4, CD274, IL7R, IL1B). We found that the core genes (ICAM1, SELL) were highly expressed in UC samples and lowly expressed in normal samples, suggesting their potential regulatory roles in UC. These core genes were associated with lymphoproliferative disorders, inflammation and necrosis. WB results confirmed the high expression of ICAM1 and SELL in UC. ICAM1 and SELL are highly expressed in UC, and the higher the ICAM1 and SELL genes, the worse the prognosis.

Screening of four lysosome-related genes in sepsis based on RNA sequencing technology

PurposeScreening of lysosome-related genes in sepsis patients to provide direction for lysosome-targeted therapy.MethodsPeripheral blood samples were obtained from 22 patients diagnosed with sepsis and 10 normal controls for the purpose of RNA sequencing and subsequent analysis of differential gene expression. Concurrently, lysosome-related genes were acquired from the Gene Ontology database. The intersecting genes between the differential genes and lysosome-related genes were then subjected to PPI, GO and KEGG analyses. Core genes were identified through survival analysis, and their expression trends in different groups were determined using meta-analysis. Single-cell RNA sequencing was used to clarify the cellular localization of core genes.ResultsThe intersection of 1328 sepsis-differential genes with 878 lysosome-related genes yielded 76 genes. PPI analysis showed that intersecting genes were mainly involved in Cellular process, Response to stimulus, Immune system process, Signal transduction, Lysosome. GO and KEGG analysis showed that intersecting genes were mainly involved in leukocyte mediated immunity, cell activation involved in immune response, lytic vacuole, lysosome. Survival analysis screened four genes positively correlated with sepsis prognosis, namely GNLY, GZMB, PRF1 and RASGRP1. The meta-analysis revealed that the expression levels of these four genes were significantly higher in the normal control group compared to the sepsis group, which aligns with the findings from RNA sequencing data. Furthermore, single-cell RNA sequencing demonstrated that T cells and NK cells exhibited high expression levels of GNLY, GZMB, PRF1, and RASGRP1.ConclusionGNLY, GZMB, PRF1, and RASGRP1, which are lysosome-related genes, are closely linked to the prognosis of sepsis and could potentially serve as novel research targets for sepsis, offering valuable insights for the development of lysosome-targeted therapy. The clinical trial registration number is ChiCTR1900021261, and the registration date is February 4, 2019.

RNA-Sequencing Analysis and Expression of Lymphocyte-Specific Protein Tyrosine Kinase, Linker for Activation of T Cells, and 70-kDa T-Cell Receptor Zeta-Chain Associated Protein Kinase in Rat Liver Transplant Rejection.

The prevention and treatment of liver transplant rejection remain challenging. We investigated the pathophysiological mechanisms of liver transplant rejection in rats and screened candidate genes to determine their degree of rejection response for possible development of potential therapeutic targets. Brown Norway-Brown Norway transplant tolerant models and Lewis-Brown Norway transplant rejection models were established. We collected liver tissue and venous blood at 7 days posttransplant for hematoxylin and eosin staining and RNA sequencing analysis, respectively. We conducted differential expression gene analysis, KEGG and GO enrichment analysis. We performed immunohistochemistry to detect highly expressed immunerelated proteins, including lymphocyte-specific protein tyrosine kinase, linker for activation of T cells, and 70-kDa T-cell receptor zeta-chain-associated protein kinase. Significant differences were found in liver function and Banff scores between rejection and tolerant groups, indicating the successful establishment of liver transplant models. RNA-sequencing screened 7521 differentially expressed genes, with 3355 upregulated and 3058 downregulated. KEGG analysis of upregulated genes showed that 8 of the top 20 enrichment pathways were associated with immune system processes and 5 were related to immune system diseases. Among these immune pathways, 289 genes were upregulated; of these, 147 genes were removed after comparison with the IMMPORT database, of which 97 genes were significantly changed. Our GO analysis showed upregulated genes mainly participating in immune response processes, with downregulated genes mainly participating in metabolic processes. Real-time polymerase chain reaction and immunohistochemistry verified expression of the immune-related proteins, consistent with RNAsequencing results, which were mainly expressed in inflammatory cells in sinus and portal vein. Immune-related genes were found to be associated with liver transplant rejection. The 3 immune-related genes that we analyzed may play a role in liver transplant rejection and can possibly serve as candidate markers for monitoring the degree of liver transplant rejection.

Protein expression changes in Tibetan middle-to-long distance runners after the transition from high altitude to low altitude: Implications for enhancing endurance training

The study aims to investigate the differences in protein expressions in Xizang's (Tibetan) middle-to-long distance runners after the transition from high altitude to low altitude and reveal the molecular mechanisms underlying their enhanced middle-to-long distance running performance. In the study, eleven subjects were selected from native Tibetan middle-to-long distance runners to participate in an 8-week pre-competition exercise training program consisting of a 6-week training stage in Kangding City at an altitude of 2 560 meters (m) and a subsequent 2-week training stage in Leshan City at an altitude of 360 ​m. Blood samples were collected twice from the runners before beginning altitude exercise training in Kangding and after going to sea level - Leshan City. Using a label-free quantitative method, peptides in the samples were analyzed by mass spectrometry. Proteomic analysis was performed to identify differentially expressed proteins and predict their biological functions. A total of 846 proteins were identified in the 21 samples, including 719 quantified proteins. In total, 49 significantly differentially expressed proteins (p ​< ​0.05) were identified, including twenty-eight 0.2-fold up-regulated proteins or twenty-one 0.17-fold down-regulated proteins. The up-regulated proteins, including cystic fibrosis transmembrane conductance regulator (CFTR) and carbonic anhydrase I (CAI), were of particular interest due to their role in regulating the oxygen saturation in deep tissues. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that these proteins were mainly involved in regulating actin cytoskeleton, local adhesion, biotin absorption and metabolism, immune system, cancer, and membrane transport processes. In conclusion, Tibetan middle-to-long distance runners who resided in high-altitude areas benefited from repeated plateau-plain alternate training mode during the pre-competition period. The training mode induced positive changes in peripheral blood plasma proteins (CFTR and CAI), the biomarkers associated with aerobic capacity. Among the 11 runners, one female athlete won the gold medal in the 3 000-m running event in this competition, demonstrating that the plateau-plain alternate training mode could enhance the aerobic capacity of athletes.

Multi-omics analysis of functional substances and expression verification in cashmere fineness.

Numerous factors influence the growth and development of cashmere. Existing research on cashmere has predominantly emphasized a single omics level. Integrating multi-omics analyses can offer a more comprehensive understanding by encompassing the entire spectrum. This study more accurately and comprehensively identified the key factors influencing cashmere fineness using multi-omics analysis. This study used skin tissues of coarse cashmere type (CT_LCG) and fine cashmere type Liaoning cashmere goats (FT_LCG) for the analysis. This study employed an integrated approach involving transcriptomics, translatomics, proteomics, and metabolomics to identify substances associated with cashmere fineness. The findings were validated using parallel reaction monitoring (PRM) and multiple reaction monitoring (MRM) techniques. The GO functional enrichment analysis identified three common terms: multicellular organismal process, immune system process, and extracellular region. Furthermore, the KEGG enrichment analysis uncovered the involvement of the arachidonic acid metabolic pathway. Protein expression trends were verified using PRM technology. The expression trends of KRT79, as confirmed by PRM, were consistent with those observed in TMT proteomics and exhibited a positive regulatory effect on cashmere fineness. Metabolite expression trends were confirmed using MRM technology. The expression trends of 9 out of 15 validated metabolites were in agreement with those identified in the non-targeted metabolomics analysis. This study employed multi-omics analysis to identify key regulators of cashmere fineness, including PLA2G12A, KRT79, and prostaglandin B2. The findings of this study offer valuable data and establish a theoretical foundation for conducting comprehensive investigations into the molecular regulatory mechanisms and functional aspects of cashmere fineness.

Deregulation of HLA-Class I and Class II Genes in Chip, MDS, and Acute Leukemia and Similarity between Chip and MDS in HLA Profile

Introduction: Human leukocyte antigen (HLA) plays a major role in the interaction between the immune system and oncogenic process in various types of tumors. Emerging data suggests that the HLA system may have profound effects on response to immunotherapy and other types of therapy. Structural defects in HLA genes and variation in methylation have been reported to play a role in the expression of various HLA-I and HLA-II genes. Furthermore, an association between the expression of specific HLA-I or HLA-II genes and prognosis and outcome has been reported in some types of leukemia. Since HLA-I is expressed on all cells while HLA-II is expressed mainly in antigen presenting cells, we hypothesized that profiling the expression levels of both HLA-I and HLA-II in the bone marrow of patients with various myeloid neoplasms may provide information on the interaction between the microenvironment and the leukemic cell in these diseases. We used next generation sequencing to evaluate the expression level of HLA-I and HLA-II genes in myeloid neoplasms and compared these levels to normal bone marrow control. We used targeted next generation sequencing (NGS) for quantification of the RNA expression of 15 HLA-I and HLA-II genes. Methods: RNA was extracted from fresh bone marrow aspiration samples from 115 acute myeloid leukemia (AML), 196 clonal hematopoiesis of indeterminate potential (CHIP), 84 myeloproliferative neoplasm (MPN), 177 myelodysplastic syndrome (MDS), 40 acute lymphoblastic leukemia (ALL), and 279 normal bone marrow cases. RNA sequencing was performed using a targeted hybrid capture panel. The sequenced HLA-I genes were HLA-A, HLA-B, HLA-C, HLA-E, HLA-F, and HLA-H. The sequenced HLA-II genes were: HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DQB2, HLA-DRA, HLA-DRB1, HLA-DRB5, and HLA-DRB6. Salmon v1.4.0 software was used for expression quantification (TPM). To evaluate the depth of the significance in variation of the expression profiles between diseases we tested machine learning algorithm (random forest) incorporating the expression of all 15 genes in blindly classifying diseases. Two thirds of samples were used for training the random forest algorithm and one third was used for testing. Results: Bone marrow samples with CHIP showed no significant difference from normal bone marrow in level of expression of HLA-I genes but showed significantly (P &amp;lt;0.001) lower level of most HLA-II markers (DMB, DQA1, DQB2, DRB1, and DRB5). The same pattern was observed in MDS samples. In contrast, AML showed significant (P &amp;lt; 0.001) increase in the expression of both HLA-1 genes (A, C, and F) and HLA-II genes (DQA1, DPA1, DQB1, DRB6, and DPB1). Bone marrow samples from ALL patients showed significantly (P&amp;lt; 0.001) higher expression levels in DRB1 and DQA1 as compared with normal bone marrow. MPN samples showed no statistically significant difference from normal BM in any of the HLA-I or HLA-II genes, after adjusting for multiple testing. Machine leaning algorithm poorly classified MDS and AML and suggests complex overlap between the two diseases in HLA response. In contrast, the machine learning algorithm showed significant difference between MPN, MDS, and AML, and ability to distinguish all MPN cases with AUC of 0.738 (95% CI : 0.546-0.930) in the testing set (see figure). Conclusions: These findings show that the bone marrow microenvironment immune profile in MDS and CHIP likely plays a major role in the disease. Furthermore, this data suggests that this immune microenvironment is critical in CHIP and perhaps that therapeutic approaches supporting this immune microenvironment may help in preventing CHIP from progressing to MDS. The data also supports that AML is a disease that completely overwhelms the HLA immune system. In contrast, MPN appears to evade the HLA system and perhaps activating this system may help in the therapy of MPN.

Cadmium levels and soil pH drive structure and function differentiation of endophytic bacterial communities in Sedum plumbizincicola: A field study

Sedum plumbizincicola is a promising hyperaccumulator for heavy metal phytoremediation. It grows in heavy metal polluted soil and stores specific endophyte resources with heavy metal tolerance or growth promotion characteristics. In this study, the endophyte communities of S. plumbizincicola, growing naturally in the field (two former mining locations and one natural location) were investigated, and their structure and function were comparatively studied. The bioaccumulation and translocation characteristics of cadmium (Cd) and selenium (Se) in S. plumbizincicola were also evaluated. The results showed that the heavy metal pollution reduced the richness and diversity of endophyte communities. Soil pH and Cd concentration could be the key factors affecting the composition of the endophyte community. Co-occurrence network analysis identified that 22 keystone taxa belonging to Actinobacteriota, Firmicutes, Myxococcota and Proteobacteria were positively correlated with Cd bioaccumulation and translocation. The predicted endophyte metabolic pathways were enriched in physiological metabolism, immune system, and genetic Information processing. These findings may help to understand how endophytes assist host plants to enhance their adaptability to harsh environments, and provide a basis for further exploration of plant-endophyte interactions and improvement in phytoremediation efficiency.

Hubungan Tingkat Pendidikan Ibu dengan Penanganan Demam pada Anak Di Wilayah Kerja Puskesmas Kronjo Tahun 2022

Fever is a sign or symptom of disease with an adaptive regulatory response of the body to stimuli in the immune system, autonomic system, behavior and neuroendocrine processes. Handling fever in children really depends on the role of parents, especially mothers. Mothers who know about fever and have a good attitude in providing care can determine the best fever management for their child. The aim of this study was to determine the relationship between maternal education level and the treatment of fever in children in the Kronjo Community Health Center Working Area. This research is an analytical survey research using a cross sectional design, the sampling technique in this research is nonprobability sampling. The results of the research show that there is a significant relationship between the level of maternal education and the treatment of fever in children in the Kronjo Health Center working area. These results were obtained based on the chi square test, with a value of p = 0.007 &lt; 0.05. Maternal education has been proven to influence the treatment of fever in children, so mothers need to be aware of the treatment of fever in children in order to provide appropriate treatment for fever in children.

Lung transcriptomics of K18-hACE2 mice highlights mechanisms and genes involved in the MVA-S vaccine-mediated immune response and protection against SARS-CoV-2 infection

Unravelling the molecular mechanism of COVID-19 vaccines through transcriptomic pathways involved in the host response to SARS-CoV-2 infection is key to understand how vaccines work, and for the development of optimized COVID-19 vaccines that can prevent the emergence of SARS-CoV-2 variants of concern (VoCs) and future outbreaks. In this study, we investigated the effects of vaccination with a modified vaccinia virus Ankara (MVA)-based vector expressing the full-length SARS-CoV-2 spike protein (MVA-S) on the lung transcriptome from susceptible K18-hACE2 mice after SARS-CoV-2 infection. One dose of MVA-S regulated genes related to viral infection control, inflammation processes, T-cell response, cytokine production and IFN-γ signalling. Down-regulation of Rhcg and Tnfsf18 genes post-vaccination with one and two doses of MVA-S may represent a mechanism for controlling infection immunity and vaccine-induced protection. One dose of MVA-S provided partial protection with a distinct lung transcriptomic profile to healthy animals, while two doses of MVA-S fully protected against infection with a transcriptomic profile comparable to that of non-vaccinated healthy animals. This suggests that the MVA-S booster generates a robust and rapid antigen-specific immune response preventing virus infection. Notably, down-regulation of Atf3 and Zbtb16 genes in mice vaccinated with two doses of MVA-S may contribute to vaccine control of innate immune system and inflammation processes in the lungs during SARS-CoV-2 infection. This study shows host transcriptomic mechanisms likely involved in the MVA-S vaccine-mediated immune response against SARS-CoV-2 infection, which could help in improving vaccine dose assessment and developing novel, well-optimized SARS-CoV-2 vaccine candidates against prevalent or emerging VoCs.

Sex Differences in the Serum Proteomic Profile During Acute Low Back Pain—A Preliminary Study of the Relationship to Future Low Back Pain

The molecular processes driving the transition from acute to chronic low back pain (LBP) remain poorly understood and are likely to be sexually dimorphic. This study aimed to explore sex differences in the serum proteomic profile of people experiencing an acute LBP episode and determine if serum protein concentrations were associated with three-month outcome. Serum samples were collected through venepuncture from 30 female and 29 male participants experiencing an acute LBP episode. Serum samples underwent trypsin digestion and fractionation using hydrophobic interaction chromatography and were then analysed using mass-spectrometry. Mass-spectrometry spectra were searched in the Swissprot database for protein identification. Sex differences in protein abundance changes were evident upon inspection of fold changes. Multivariable data analysis identified 21 serum proteins during the acute episode that correctly classified 93% of males and 23 serum proteins that correctly classified 90% of females with ongoing LBP at 3 months. Pathway analysis suggested the differentially expressed proteins during acute LBP were frequently involved in immune, inflammatory, complement, or coagulation responses. This data provides preliminary evidence that biological processes during an acute LBP episode may contribute to the resolution, or persistence, of LBP symptoms at 3 months, however, these processes differ between males and females. PerspectiveDifferential expression of serum proteins was observed between male and female participants during an acute LBP episode. This preliminary work provides a foundation for future research targeting distinct immune system processes in males and females that may interfere with the transition from acute to chronic LBP.

PSXII-9 Identifying Selection Signatures for Immune Response and Resilience to Aleutian Disease in Mink Using Genotypes Data

Abstract Aleutian disease (AD), a severe immune-complex disease, brings tremendous financial losses to the mink industry. Resilience is the ability of an animal to minimize the influences caused by disturbances and maintain its performance under pathogen exposure. Many AD-positive farms have selected AD-resilient mink based on AD tests and/or AD-resilience indicator traits, such as growth, pelt quality, and reproduction. Selection based on these indicator traits may have changed the patterns of genetic variation and potentially represent a genomic signature that can be used to identify genes subjected to selection. Therefore, the main objective of this study was to identify the selection signatures related to immune response (IRE) and resilience to AD. . A total of 1,411 mink in five color types (black, demi, mahogany, pastel, and stardust) from the Canadian Centre for Fur Animal Research (Truro, Nova Scotia, Canada), which is an AD-positive facility, were genotyped using the Axiom Affymetrix Mink 70K single nucleotide polymorphism (SNP) panel. For the IRE trait, 264 mink were grouped into pairwise groups based on the combined results of counter-immunoelectrophoresis (CIEP) and enzyme-linked immunosorbent assay (ELISA) tests. Individuals in black (n = 29), demi (n = 131), mahogany (n = 76), and pastel (36) color types were also grouped based on combined results of CIEP and ELISA tests, respectively. For resilience traits, two methods were used to group CIEP-positive individuals into pairwise groups: 1) based on their general resilience performance (GRP, n = 30), which was measured by considering individual performance for feed conversion ratio, Kleiber ratio, and pelt quality, and 2) based on female reproductive performance (FRP, CIEP-positive dams only, n = 36), which was measured by the number of kits alive 24h after birth. The pairwise fixation index, nucleotide diversity, and cross-population extended haplotype homozygosity were used to detect selection signatures. Only SNPs detected by at least two methods were considered selection signatures candidates, including 619, 569, and 526 SNPs for IRE, GRP, and FRP traits, respectively. The genes annotated from the candidate SNPs were associated with previously reported traits influenced by AD, including immune system process, growth, reproduction, and pigmentation. Notably, two olfactory-related gene ontology (GO) terms were significant (q &amp;lt; 0.05) for all studied traits, suggesting AD might cause loss of smell in infected mink. Additionally, the differences in genes and GO terms detected across different color types for IRE indicated that mink of different color types may differ in immune response to AD. The mitogen-activated protein kinase (MAPK) signalling pathway was significant (q &amp;lt; 0.05) in Kyoto Encyclopedia of Genes and Genomes pathway analyses for FRP, indicating AD infection may disorder the MAPK signalling pathway, in turn influencing female reproductive performance. Our study has enhanced the understanding of genomic architecture underlying resilience of mink to AD and sheds light on the underlying biological mechanisms involved.

Analysis of molecular mechanisms of the development of experimental diabetes in Wistar rats under conditions of intermittent hypoxia

There is strong evidence that hypoxic training, within the context of diabetes, constitutes a specialized form of exercise performed under conditions of intermittent hypoxia. This approach holds promise for effectively managing and enhancing diabetes outcomes, as it has the potential to influence metabolism and physiological processes within the body significantly. The key elements of hypoxic training in diabetes encompass activities geared toward activating metabolic pathways, enhancing mitochondrial function, and regulating blood glucose levels. Such interventions can potentially lead to improvements in insulin resistance, a reduction in glycemia, and an overall enhancement of cardiorespiratory function. Hypoxic training achieves these benefits by heightening insulin sensitivity and reducing blood glucose levels, which can be particularly advantageous for individuals with diabetes. The aim of the work is to determine changes in the expression of genes associated with the course of diabetes under conditions of exposure to intermittent hypoxia in pancreatic tissue samples of Wistar rats. Materials and methods. Analysis of gene expression was used by the polymerase chain reaction method with reverse transcription in real-time using the RT2 Profiler™ PCR Array Rat Diabetes kit (QIAGEN, Germany), where the pancreas of experimental animals was studied. Results. According to the results of the PCR study of animals with experimental diabetes and the influence of hypoxic training on its course, the activity of the studied genes can be divided as follows: genes with low expression compared to the control group of animals, where ∆∆Cт &lt;30 (Ace; Cd28; Ctla4; Dusp4 ; Enpp1; Foxp3; G6pc; Gcgr; Glp1r; Gpd1; Gsk3b; Hmox1; Ide; Ikbkb; Il10; Il6; Ins1; Nfkb1; Nkx2-1; Parp1; Pdx1; Pik3cd; Pik3r1; Ppargc1a; Ptpn1; Rab4a; Retn; Slc14a2 ; Snap25; Sod2; Stx4; Stxbp1; Stxbp2; Tnf; Tnfrsf1a; Tnfrsf1b; Ucp2; Vamp2; Vegfa); genes in which no significant changes were detected in the samples in relation to the control group (Acly; Adra1a; Adrb3; Agt; Akt2; Aqp2; Ccl5; Ccr2; Ceacam1; Cebpa; Dpp4; Fbp1; Foxc2; Foxg1; Gcg; Gck; Hnf1b; Hnf4a ; Icam1; Ifng; Igfbp5; Il12b; Il4r; Inppl1; Irs1; Irs2; Mapk14; Mapk8; Neurod1; Nos3; Nrf1; Nsf; Ppara; Pparg; Pygl; Sell; Serpine1; Slc2a4; Snap23; Srebf1; Stxbp4; Tgfb1; Trib3 ; Vamp3; Vapa); there are no genes with high expression compared to the control group. Conclusions. The Nkx2-1 genes, Pik3r1, and Slc14a2 in rats subjected to experimental diabetes displayed notably reduced protein expression activity. Hypoxic training demonstrated an impact on mitigating the expression of the Nkx2-1 protein, which suggests that it might affect the mitochondrial muscle respiratory chain, modulate insulin signaling, and potentially rectify molecular deficiencies associated with diabetic nephropathy. Expression of Dpp4 genes, Gck, Ifng, Mapk8, Nsf and Sell in rats with experimental diabetes and the effect of hypoxic training on it were reduced to the level of control (intact) rats. As a result of the normalization of Dpp4 gene expression, Gck, Ifng, Mapk8, Nsf and Sell may be the influence of the effects of hypoxic training on molecular mechanisms of regulation of hormones and signals related to metabolism and the endocrine system, effects on the immune system and inflammatory processes, as well as insulin resistance.

Polygenic HLA-Class I and HLA-Class II Models Define Various Types of Lymphoma

Introduction: Human leukocyte antigen (HLA) plays a major role in the interaction between the immune system and oncogenic process in various types of tumors including lymphoma. Mono-allelic and bi-allelic loss of the HLA-I has been reported in diffuse large B-cell lymphoma (DLBCL) and other types of lymphoma. Poor outcome was also reported with the loss of the HLA-I system in lymphoma. Since HLA-I and HLA-II are both critical for healthy immune response and both can be expressed in the lymphoma cells as well as in the lymphoma responding microenvironment, analyzing both systems is crucial for deciphering the role of the HLA system in lymphoma. Toward this goal, we evaluated the expression level of various HLA-I and HLA-II genes and compared these levels between subtypes of lymphoma. We quantified RNA expression levels of 15 HLA-I and HLA-II genes using next generation sequencing (NGS) and used machine learning algorithm (random forest) to evaluate the depth of the significance in variation of the expression profiles between various types of lymphoma. Methods: RNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissue from 99 diffuse large B-cell lymphoma (DLBCL), 79 T-cell lymphoma, 40 follicular lymphoma, 28 mantle cell lymphoma, and 14 Hodgkin lymphoma samples. RNA sequencing was performed using a targeted hybrid capture panel. The sequenced HLA-I genes were HLA-A, HLA-B, HLA-C, HLA-E, HLA-F, and HLA-H. The sequenced HLA-II genes were HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DQB2, HLA-DRA, HLA-DRB1, HLA-DRB5, and HLA-DRB6. Salmon v1.4.0 software was used for expression quantification (TPM). Random forest machine learning system was used for predicting subtypes. Two thirds of samples were used for training the random forest algorithm and one third was used for testing. Results: RNA levels of individual HLA-I and HLA-II genes varied mildly between various B-cell lymphoma subtypes without specific pattern, especially after adjusting for multiple testing. However, T-cell lymphoma showed overall significantly (P&amp;lt; 0.0001) higher HLA-I (B, C, and F) and lower HLA-II (DRB1 and DRB5) expression levels as compared with B-cell lymphoma. In contrast, using machine learning algorithm to evaluate combination of HLA-I and HLA-II expression profiles showed discrete and significant differences between various types of lymphoma. The levels of expression of HLA-I and HLA-II genes were adequate to distinguish between DLBCL and follicular lymphoma with AUC of 0.778 (95% CI: 0.46-1.00), and between DLBCL and T-cell lymphoma with AUC of 0.833 (95% CI: 0.624-1.00). The number of Hodgkin lymphoma and mantle cell cases was small but the random forest distinguished between DLBCL and Hodgkin lymphoma with AUC of 0.833 (95% CI: 0.294-1.00), and between DLBCL and mantle cell lymphoma with AUC of 0.778 (95% CI: 0.416-1.00). Conclusions: This data confirms the polygenic effects of the HLA-I and HLA-II on various types of lymphoma. The HLA-I and HLA-II combined expression profiles are significantly different between various types of lymphoma. More importantly, this data suggests that immune modulating therapy should consider the polygenic effects of both the HLA-I and HLA-II systems.

Transcriptomic Profiling to Understand Inhibitor Development in Previously Untreated Patients with Severe Hemophilia a

Background: When starting treatment with factor VIII (FVIII) concentrate in individuals with severe hemophilia A, minimizing the risk of FVIII inhibitor development is an important concern for clinicians, patients and their families. Despite increased understanding of some of the genetic and environmental risk factors for inhibitor formation from epidemiological studies, identification of previously untreated patients (PUPs) at risk of developing inhibitors remains a challenge. Prediction of inhibitor development may help optimize care in PUPs with hemophilia A. RNA sequencing (RNA-Seq) with next-generation sequencing (NGS) could be used to investigate the underlying mechanisms of inhibitor development. Aims: Toevaluate peripheral blood transcriptomic profiles prior to and during early FVIII treatment in severe hemophilia A patients who did or did not develop inhibitors to simoctocog alfain the prospective NuProtect study. Methods: The NuProtect study (NCT01712438; EudraCT 2012-002554-23) was a multicenter, multinational, open-label, non-controlled, phase III study that enrolled male PUPs with severe hemophilia A (FVIII:C &amp;lt;1%) of any age and ethnicity. Patients received simoctocog alfa for prophylaxis or on-demand treatment, as well as for surgical prophylaxis. RNA-Seq was performed on blood samples collected from baseline and every 3-4 exposure days (ED) up to 20 EDs or until inhibitor development to assess messenger RNA (mRNA) expression profiles. Bioinformatics analyses were performed for the following timepoints: baseline, early treatment and a later timepoint on treatment. Principal component analysis (PCA) was performed to identify differences in global mRNA expression profiles between inhibitor and non-inhibitor patients. Gene ontology (GO) analyses were performed to detect differences in GO clusters between inhibitor and non-inhibitor patients. Results: Within this first analysis of the full dataset, transcriptomic profiles from 78 of 108 severe hemophilia A PUPs were analyzed (inhibitors n=22, non-inhibitors n=56). Median (range) age at ED1 was 13 (0.5-146) months; 44.9% of patients had the intron 22 inversion F8 gene mutation. Although the PCA indicated no strong global signal for differential expression profiles between non-inhibitor and inhibitor patients, GO analyses demonstrated differences between these patient groups. Inhibitor patients demonstrated increased gene expression of metabolic processes (GO:0008152) and cellular processes (GO:0009987) at baseline. Upregulation of immune system processes (GO:0002376) was seen in inhibitor patients at the early timepoint compared with non-inhibitor patients. Expression of ribosomal proteins, including RPL17 and RPS8 were significantly upregulated at baseline in inhibitor patients (p&amp;lt;0.05). Inhibitor patients further demonstrated upregulation of proteins involved in adaptive immune responses: IGHV1-69-2 at all timepoints (p&amp;lt;0.01) and IGHV2-70D at baseline and the early timepoint (p&amp;lt;0.01) compared with non-inhibitor patients. Upregulation of the B-cell related factors DPP4 at baseline and the early timepoint (p&amp;lt;0.05) and CD20 at the late timepoint (p&amp;lt;0.05) was observed in inhibitor patients compared with non-inhibitor patients. Conclusion: Differential transcriptomic profiles were seen in severe hemophilia A patients who developed inhibitors compared with those who do not, even before commencing FVIII treatment. Inhibitor patients demonstrated alterations in ribosomal protein expression that could disrupt protein synthesis efficiency, protein folding and quality control processes, and trigger cellular stress responses. Inhibitor patients also showed an upregulation of B-cell mediated factors involved in adaptive immune mechanisms. Additional analyses are ongoing to evaluate dynamic changes in gene expression during commencement of FVIII replacement to further identify patients at risk of inhibitor development.

ScDiffCom: a tool for differential analysis of cell–cell interactions provides a mouse atlas of aging changes in intercellular communication

Dysregulation of intercellular communication is a hallmark of aging. To better quantify and explore changes in intercellular communication, we present scDiffCom and scAgeCom. scDiffCom is an R package, relying on approximately 5,000 curated ligand–receptor interactions, that performs differential intercellular communication analysis between two conditions from single-cell transcriptomics data. Built upon scDiffCom, scAgeCom is an atlas of age-related cell–cell communication changes covering 23 mouse tissues from 58 single-cell RNA sequencing datasets from Tabula Muris Senis and the Calico murine aging cell atlas. It offers a comprehensive resource of tissue-specific and sex-specific aging dysregulations and highlights age-related intercellular communication changes widespread across the whole body, such as the upregulation of immune system processes and inflammation, the downregulation of developmental processes, angiogenesis and extracellular matrix organization and the deregulation of lipid metabolism. Our analysis emphasizes the relevance of the specific ligands, receptors and cell types regulating these processes. The atlas is available online (https://scagecom.org).