Central Memory CD4 Research Articles

Immune signature of patients with cardiovascular disease predicts increased risk for a severe course of COVID-19.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. So far, however, there are hardly any strategies for predicting the course of SARS-CoV-2 infection in CVD patients at hospital admission. Thus, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 nonvaccinated participants, including uninfected and acutely SARS-CoV-2-infected CVD patients and healthy donors, using a 36-colour spectral flow cytometry panel. Unsupervised data analysis revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts but fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T-cell subsets. Moreover, we identified an immune signature characterised by CD161+ T cells, intermediate effector CD8+ T cells, and natural killer T (NKT) cells that is predictive for CVD patients with a severe course of COVID-19. Thus, intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.

The dynamics and longevity of circulating CD4+ memory T cells depend on cell age and not the chronological age of the host.

Quantifying the kinetics with which memory T cell populations are generated and maintained is essential for identifying the determinants of the duration of immunity. The quality and persistence of circulating CD4 effector memory (TEM) and central memory (TCM) T cells in mice appear to shift with age, but it is unclear whether these changes are driven by the aging host environment, by cell age effects, or both. Here, we address these issues by combining DNA labelling methods, established fate-mapping systems, a novel reporter mouse strain, and mathematical models. Together, these allow us to quantify the dynamics of both young and established circulating memory CD4 T cell subsets, within both young and old mice. We show that that these cells and their descendents become more persistent the longer they reside within the TCM and TEM pools. This behaviour may limit memory CD4 T cell diversity by skewing TCR repertoires towards clones generated early in life, but may also compensate for functional defects in new memory cells generated in old age.

Detection of a Diagnostic Model and Comprehensive Examination of Diabetic Retinopathy Utilizing Genes Linked to Endoplasmic Reticulum Stress.

The aim of this study was to reveal the biological functionalities associated with endoplasmic reticulum stress (ERS)-related genes (ERSGs) in the context of diabetic retinopathy (DR). Differentially expressed genes (DEGs) within the DR group and the Control group were identified and then integrated with ERSGs. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) methodologies were used to investigate potential biological mechanisms. A diagnostic model for ERS and a nomogram were formulated based on biomarkers selected through the Least Absolute Shrinkage and Selection Operator method. The diagnostic efficacy of this model was thoroughly evaluated. ERS-associated subtypes were identified, and the Single-Sample GSEA (ssGSEA) and CIBERSORT algorithms were used to assess immune infiltration. We identified 10 ERS-related DEGs (ERSRDEGs) within the DR Group. Subsequently, a diagnostic model was constructed based on 5 ERS genes, namely CCND1, IGFBP2, TLR4, TXNIP, and VIM. The validation analysis demonstrated the commendable diagnostic performance of the model. Analysis of the ssGSEA immune characteristics revealed a positive correlation in the DR group between myeloid-derived suppressor cells (MDSC), regulatory T cells (Tregs), and CCND1 TXNIP. Furthermore, a significant negative correlation was observed between central memory CD4 T cells and CCND1. In the context of CIBERSORT, the results indicated a positive correlation between macrophages and IGFBP2, as well as Tregs and IGFBP2 in the DR group. Notably, a conspicuous negative correlation was identified between resting mast cells and IGFBP2. The present study provides novel diagnostic biomarkers for DR from an ERS perspective.

Elucidating the causal nexus and immune mediation between frailty and chronic kidney disease: integrative multi-omics analysis

Background Empirical research has consistently documented the concurrent manifestation of frailty and chronic kidney disease (CKD). However, the existence of a reverse causal association or the influence of confounding variables on these correlations remains ambiguous. Methods Our analysis of 7,078 participants from National Health and Nutrition Examination Survey(NHANES) (1999–2018) applied weighted logistic regression and Mendelian Randomization (MR) to investigate the correlation between the frailty index (FI) and renal function. The multivariate MR analysis was specifically adjusted for type 2 diabetes and hypertension. Further analysis explored 3282 plasma proteins to link FI to CKD. A two-step network MR highlighted immune cells’ mediating roles in the FI-CKD relationship Result Genetically inferred FI and various renal function markers are significantly correlated, as supported by NHANES analyses. Multivariate MR analysis revealed a direct causal association between the FI and CKD. Additionally, our investigation into plasma proteins identified Tmprss11D and MICB correlated with FI and CKD, respectively. A two-step network MR to reveal 15 immune cell types, notably Central Memory CD4+ T cells and Lymphocytes, as crucial mediators between FI and CKD. Conclusion Our work establishes a causal connection between frailty and CKD, mediated by specific immune cell profiles. These findings highlight the importance of immune mechanisms in the frailty-CKD interplay and suggest that targeting shared risk factors and immune pathways could improve management strategies for these conditions. Our research contributes to a more nuanced understanding of frailty and CKD, offering new avenues for intervention and patient care in an aging population.

Lrp10 suppresses IL7R limiting CD8 T cell homeostatic expansion and anti-tumor immunity

Signals emanating from the T-cell receptor (TCR), co-stimulatory receptors, and cytokine receptors each influence CD8 T-cell fate. Understanding how these signals respond to homeostatic and microenvironmental cues can reveal new ways to therapeutically direct T-cell function. Through forward genetic screening in mice, we discover that loss-of-function mutations in LDL receptor-related protein 10 (Lrp10) cause naive and central memory CD8 T cells to accumulate in peripheral lymphoid organs. Lrp10 encodes a conserved cell surface protein of unknown immunological function. T-cell activation induces Lrp10 expression, which post-translationally suppresses IL7 receptor (IL7R) levels. Accordingly, Lrp10 deletion enhances T-cell homeostatic expansion through IL7R signaling. Lrp10-deficient mice are also intrinsically resistant to syngeneic tumors. This phenotype depends on dense tumor infiltration of CD8 T cells, which display increased memory cell characteristics, reduced terminal exhaustion, and augmented responses to immune checkpoint inhibition. Here, we present Lrp10 as a new negative regulator of CD8 T-cell homeostasis and a host factor that controls tumor resistance with implications for immunotherapy.

Development of a Spectral Flow Cytometry Analysis Pipeline for High-Dimensional Immune Cell Characterization.

Flow cytometry is a widely used technique for immune cell analysis, offering insights into cell composition and function. Spectral flow cytometry allows for high-dimensional analysis of immune cells, overcoming limitations of conventional flow cytometry. However, analyzing data from large antibody panels can be challenging using traditional bi-axial gating strategies. Here, we present a novel analysis pipeline designed to improve analysis of spectral flow cytometry. We employ this method to identify rare T cell populations in aging. We isolated splenocytes from young (2-3 months) and aged (18-19 months) female mice then stained these with a panel of 20 fluorescently labeled antibodies. Spectral flow cytometry was performed, followed by data processing and analysis using Python within a Jupyter Notebook environment to perform batch correction, unsupervised clustering, dimensionality reduction, and differential expression analysis. Our analysis of 3,776,804 T cells from 11 spleens revealed 34 distinct T cell clusters identified by surface marker expression. We observed significant differences between young and aged mice, with certain clusters enriched in one age group over the other. Naïve, effector memory, and central memory CD8+ and CD4+ T cell subsets exhibited age-associated changes in abundance and marker expression. Additionally, γδ T cell clusters showed differential abundance between age groups. By leveraging high-dimensional analysis methods borrowed from single-cell RNA sequencing analysis, we identified age-related differences in T cell subsets, providing insights into the immune aging process. This approach offers a robust, free, and easily implemented analysis pipeline for spectral flow cytometry data that may facilitate the discovery of novel therapeutic targets for age-related immune dysfunction.

Elucidating sleep disorders: a comprehensive bioinformatics analysis of functional gene sets and hub genes.

Sleep disorders (SD) are known to have a profound impact on human health and quality of life although their exact pathogenic mechanisms remain poorly understood. The study first accessed SD datasets from the GEO and identified DEGs. These DEGs were then subjected to gene set enrichment analysis. Several advanced techniques, including the RF, SVM-RFE, PPI networks, and LASSO methodologies, were utilized to identify hub genes closely associated with SD. Additionally, the ssGSEA approach was employed to analyze immune cell infiltration and functional gene set scores in SD. DEGs were also scrutinized in relation to miRNA, and the DGIdb database was used to explore potential pharmacological treatments for SD. Furthermore, in an SD murine model, the expression levels of these hub genes were confirmed through RT-qPCR and Western Blot analyses. The findings of the study indicate that DEGs are significantly enriched in functions and pathways related to immune cell activity, stress response, and neural system regulation. The analysis of immunoinfiltration demonstrated a marked elevation in the levels of Activated CD4+ T cells and CD8+ T cells in the SD cohort, accompanied by a notable rise in Central memory CD4 T cells, Central memory CD8 T cells, and Natural killer T cells. Using machine learning algorithms, the study also identified hub genes closely associated with SD, including IPO9, RAP2A, DDX17, MBNL2, PIK3AP1, and ZNF385A. Based on these genes, an SD diagnostic model was constructed and its efficacy validated across multiple datasets. In the SD murine model, the mRNA and protein expressions of these 6 hub genes were found to be consistent with the results of the bioinformatics analysis. In conclusion, this study identified 6 genes closely linked to SD, which may play pivotal roles in neural system development, the immune microenvironment, and inflammatory responses. Additionally, the key gene-based SD diagnostic model constructed in this study, validated on multiple datasets showed a high degree of reliability and accuracy, predicting its wide potential for clinical applications. However, limited by the range of data sources and sample size, this may affect the generalizability of the results.

A Mendelian randomization study investigating the causal relationships between inflammation and immunoglobulin A nephropathy

BackgroundImmunoglobulin A nephropathy (IgAN) is an autoimmune disease characterized by the production of galactose‑deficient IgA1 (Gd‑IgA1) and the deposition of immune complexes in the kidney. Exploring the landscape of immune dysregulation in IgAN is valuable for pathogenesis and disease treatment. We conducted Mendelian randomization (MR) to assess the causal correlations between inflammation and IgAN. MethodsBased on available genetic datasets, we investigated potential causal links between inflammation and the risk of IgAN using two-sample MR. We used genome-wide association study (GWAS) summary statistics of 5 typical inflammation markers, 41 inflammatory cytokines, and 731 immune cell signatures, accessed from the public GWAS Catalog. The primary method employed for MR analysis was Inverse Variance Weighted (IVW). To confirm consistency across results, four supplementary MR methods were also conducted: MR-Egger, Weighted Median, Weighted Mode, and Simple Mode. To assess pleiotropy, we used the MR-Egger regression intercept test and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test. Cochrane’s Q statistic was applied to evaluate heterogeneity. Additionally, the stability of the MR findings was verified through the leave-one-out sensitivity analysis. ResultsThis study revealed that interleukin-7 (IL-7) and stem cell growth factor beta (SCGF-β) were possibly associated with the risk of IgAN according to the IVW approach, with estimated odds ratios (OR) of 1.059 (95 % confidence interval [CI] 1.015 to 1.104, P = 0.008) and 1.043 (95 % CI 1.002 to 1.085, P = 0.037). Five immune traits were identified that might be linked to IgAN risk, each with P-values below 0.01, including natural killer T %T cell (OR = 1.058, 95 % CI: 1.020 to 1.097, P = 0.002), natural killer T %lymphocyte (OR = 1.055, 95 % CI: 1.016 to 1.096, P = 0.006), CD25++ CD8+ T cell %T cell (OR = 1.057, 95 % CI: 1.016 to 1.099, P = 0.006), CD3 on effector memory CD4+ T cell (OR = 1.045, 95 % CI: 1.019 to 1.071, P = 0.001), and CD3 on CD28+ CD45RA+ CD8+ T cell (OR = 1.042, 95 % CI: 1.016 to 1.068, P = 0.001). CD4 on central memory CD4+ T cell might be a protective factor for IgAN (OR = 0.922, 95 % CI: 0.875 to 0.971, P = 0.002). Moreover, IgAN may be implicated in a high risk of elevated granulocyte colony-stimulating factor (G-CSF) (OR = 1.114, 95 % CI 1.002 to 1.239, P = 0.046). ConclusionOur study revealed exposures among typical inflammation markers, inflammatory cytokines, and immune cell signatures that may potentially linked to IgAN risk by MR analysis. This insight may advance our understanding of the etiology of IgAN and support the development of targeted therapeutic strategies.

Central memory CD4+ T cells play a protective role against immune checkpoint inhibitor-associated myocarditis.

The widespread use of immune checkpoint inhibitors (ICIs) has demonstrated significant survival benefits for cancer patients and also carries the risk of immune-related adverse events. ICI-associated myocarditis is a rare and serious adverse event with a high mortality rate. Here, we explored the mechanism underlying ICI-associated myocarditis. Using the peripheral blood of patients with ICI therapy and of ICI-treated mice with transplanted tumours, we dissect the immune cell subsets and inflammatory factors associated with myocarditis. Compared to the control group, patients with myocarditis after ICI therapy showed an increase in NK cells and myeloid cells in the peripheral blood, while T cells significantly decreased. Among T cells, there was an imbalance of CD4/CD8 ratio in the peripheral blood of myocarditis patients, with a significant decrease in central memory CD4+ T (CD4+ TCM) cells. RNA sequencing revealed that CD4+ TCM cells in myocarditis patients were immunosuppressive cell subsets, which highly express the immunosuppressive factor IL-4I1. To elucidate the potential mechanism of the decrease in CD4+ TCM cells, protein array was performed and revealed that several inflammatory factors gradually increased with the severity of myocarditis in the myocarditis group, such as IL-1B/CXCL13/CXCL9, while the myocardial protective factor IL-15 decreased. Correlation analysis indicated a positive correlation between IL-15 and CD4+ TCM cells, with high expression of IL-15 receptor IL15RA. Furthermore, in vivo studies using an anti-PDL1 antibody in a mouse tumour model indicated a reduction in CD4+ TCM cells and an increase in effector memory-expressing CD45RA CD8+ T (TEMRA) cells, alongside evidence of cardiac fibrosis. Conversely, combining anti-PDL1 antibody treatment with IL-15 led to a resurgence of CD4+ TCM cells, a reduction in CD8+ TEMRA cells, and a mitigated risk of cardiac fibrosis. Our data highlight CD4+ TCM cells' crucial role in cardiac protection during ICI therapy. IL-15, IL-4I1, and CD4+ TCM cells can serve as therapeutic targets to reduce ICI-associated myocarditis in cancer patients.

KSHV infection of B cells primes protective T cell responses in humanized mice

Kaposi sarcoma associated herpesvirus (KSHV) is associated with around 1% of all human tumors, including the B cell malignancy primary effusion lymphoma (PEL), in which co-infection with the Epstein Barr virus (EBV) can almost always be found in malignant cells. Here, we demonstrate that KSHV/EBV co-infection of mice with reconstituted human immune systems (humanized mice) leads to IgM responses against both latent and lytic KSHV antigens, and expansion of central and effector memory CD4+ and CD8+ T cells. Among these, KSHV/EBV dual-infection allows for the priming of CD8+ T cells that are specific for the lytic KSHV antigen K6 and able to kill KSHV/EBV infected B cells. This suggests that K6 may represent a vaccine antigen for the control of KSHV and its associated pathologies in high seroprevalence regions, such as Sub-Saharan Africa.

Calcineurin inhibition rescues alloantigen-specific central memory T cell subsets that promote chronic GVHD.

Calcineurin inhibitors (CNIs) constitute the backbone of modern acute graft-versus-host disease (aGVHD) prophylaxis regimens but have limited efficacy in the prevention and treatment of chronic GVHD (cGVHD). We investigated the effect of CNIs on immune tolerance after stem cell transplantation with discovery-based single-cell gene expression and T cell receptor (TCR) assays of clonal immunity in tandem with traditional protein-based approaches and preclinical modeling. While cyclosporin and tacrolimus suppressed the clonal expansion of CD8+ T cells during GVHD, alloreactive CD4+ T cell clusters were preferentially expanded. Moreover, CNIs mediated reversible dose-dependent suppression of T cell activation and all stages of donor T cell exhaustion. Critically, CNIs promoted the expansion of both polyclonal and TCR-specific alloreactive central memory CD4+ T cells (TCM) with high self-renewal capacity that mediated cGVHD following drug withdrawal. In contrast to posttransplant cyclophosphamide (PT-Cy), CSA was ineffective in eliminating IL-17A-secreting alloreactive T cell clones that play an important role in the pathogenesis of cGVHD. Collectively, we have shown that, although CNIs attenuate aGVHD, they paradoxically rescue alloantigen-specific TCM, especially within the CD4+ compartment in lymphoid and GVHD target tissues, thus predisposing patients to cGVHD. These data provide further evidence to caution against CNI-based immune suppression without concurrent approaches that eliminate alloreactive T cell clones.

T-cell responses in COVID-19 survivors 6-8 months after infection: A longitudinal cohort study in Pune.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune response is crucial for disease management, although diminishing immunity raises the possibility of reinfection. We examined the immunological response to SARS-CoV-2 in a cohort of convalescent COVID-19 patients in matched samples collected at 1 and 6-8 months after infection. The peripheral blood mononuclear cells were isolated from enrolled study participants and flow cytometry analysis was done to assess the lymphocyte subsets of naive, effector, central memory, and effector memory CD4+ or CD8+ T cells in COVID-19 patients at 1 and 6-8 months after infection. Immunophenotypic characterization of immune cell subsets was performed on individuals who were followed longitudinally for 1 month (n = 44) and 6-8 months (n = 25) after recovery from COVID infection. We observed that CD4 +T cells in hospitalized SARS-CoV-2 patients tended to decrease, whereas CD8+ T cells steadily recovered after 1 month, while there was a sustained increase in the population of effector T cells and effector memory T cells. Furthermore, COVID-19 patients showed persistently low B cells and a small increase in the NK cell population. Our findings show that T cell responses were maintained at 6-8 months after infection. This opens new pathways for further research into the long-term effects in COVID-19 immunopathogenesis.

Glycolysis inhibition induces anti-tumor central memory CD8+T cell differentiation upon combination with microwave ablation therapy

Minimally invasive thermal therapy is a successful alternative treatment to surgery in solid tumors with high complete ablation rates, however, tumor recurrence remains a concern. Central memory CD8+ T cells (TCM) play important roles in protection from chronic infection and cancer. Here we find, by single-cell RNA analysis of human breast cancer samples, that although the memory phenotype of peripheral CD8+ T cells increases slightly after microwave ablation (MWA), the metabolism of peripheral CD8+ T cells remains unfavorable for memory phenotype. In mouse models, glycolysis inhibition by 2-deoxy-D-glucose (2DG) in combination with MWA results in long-term anti-tumor effect via enhancing differentiation of tumor-specific CD44hiCD62L+CD8+ TCM cells. Enhancement of CD8+ TCM cell differentiation determined by Stat-1, is dependent on the tumor-draining lymph nodes (TDLN) but takes place in peripheral blood, with metabolic remodeling of CD8+ T cells lasting the entire course of the the combination therapy. Importantly, in-vitro glycolysis inhibition in peripheral CD8+ T cells of patients with breast or liver tumors having been treated with MWA thrice leads to their differentiation into CD8+ TCM cells. Our work thus offers a potential strategy to avoid tumor recurrence following MWA therapy and lays down the proof-of-principle for future clinical trials.

T Cell Homeostasis Disturbances in a Cohort of Long-Term Elite Controllers of HIV Infection.

Elite controllers (ECs) are people living with HIV (PLWH) able to control HIV replication without antiretroviral therapy and have been proposed as a model of a functional HIV cure. Much evidence suggests that this spontaneous control of HIV has a cost in terms of T cell homeostasis alterations. We performed a deep phenotypic study to obtain insight into T cell homeostasis disturbances in ECs maintaining long-term virologic and immunologic control of HIV (long-term elite controllers; LTECs). Forty-seven PLWH were included: 22 LTECs, 15 non-controllers under successful antiretroviral therapy (onART), and 10 non-controllers not receiving ART (offART). Twenty uninfected participants (UCs) were included as a reference. T cell homeostasis was analyzed by spectral flow cytometry and data were analyzed using dimensionality reduction and clustering using R software v3.3.2. Dimensionality reduction and clustering yielded 57 and 54 different CD4 and CD8 T cell clusters, respectively. The offART group showed the highest perturbation of T cell homeostasis, with 18 CD4 clusters and 15 CD8 clusters significantly different from those of UCs. Most of these alterations were reverted in the onART group. Interestingly, LTECs presented several disturbances of T cell homeostasis with 15 CD4 clusters and 13 CD8 clusters different from UC. Moreover, there was a specific profile of T cell homeostasis alterations associated with LTECs, characterized by increases in clusters of naïve T cells, increases in clusters of non-senescent effector CD8 cells, and increases in clusters of central memory CD4 cells. These results demonstrate that, compared to ART-mediated control of HIV, the spontaneous control of HIV is associated with several disturbances in CD4 and CD8 T cell homeostasis. These alterations could be related to the existence of a potent and efficient virus-specific T cell response, and to the ability to halt disease progression by maintaining an adequate pool of CD4 T cells.

Chronic immune activation and accelerated immune aging among HIV-infected adults receiving suppressive antiretroviral therapy for at least 12 years in an African cohort

BackgroundHIV-associated alterations innate and adaptive immune cell compartments are reminiscent of the process of immune aging. ObjectivesWe described immune aging phenotypes among ART-treated HIV-infected adults relative to age-matched HIV-negative counterparts. MethodsIn a cross-sectional comparative study of HIV-infected adults with CD4≥500 cells/μl after at least 12 years of suppressive ART and age-and-gender-matched HIV-negative individuals, immune activation and immune aging phenotypes were measured, using multi-color flowcytometry. ResultsART-treated HIV-infected individuals had higher body mass index (P = 0.004), waist-hip circumference (P = 0.041), hip circumference (P < 0.001), and diastolic blood pressure (P = 0.012) and immune activation (CD4+CD38+HLADR+; median 4.15,IQR(1.030,14.6)] relative to the HIV-negative age-matched individuals [median 3.14,IQR(1.030, 6.68)]; P=0.0034. Immune aging markers [CD4+CD57+T-cells; median 13.00 IQR (0.45,64.1)] were higher among HIV-infected ART-treated adults<50 years relative to HIV-negative<50 years[median 8.020,IQR(0.004,21.2)]; P=0.0010. Naïve CD4 T-cells, Central memory CD4 T-cells, Terminal Effector Memory T cells (TEMRA: CD27−CD45RA + CCR7-) and immune senescence CD4/CD8+CD28-/CD57+ T-cells were similar among ART-treated HIV-infected individuals<45 years relative to 60 years-and-older HIV-negative counterparts≥; p = 0.0932, p = 0.05357, p = 0.0950 and p = 0.5714 respectively. ConclusionART-treated adults are immunologically two decades older than their HIV-negative counterparts. Accelerated immune aging among individuals aging with HIV underscores the need for an HIV cure to avert the unprecedented complications of accelerated immune senescence and the associated NCD risk in African settings with protracted exposure to endemic co-infections.

#1779 Assessment of inflammation score in immune cells of atypical hemolytic uremic syndrome using single-cell sequencing analysis

Abstract Background and Aims Atypical hemolytic uremic syndrome (aHUS) is a rare and life-threatening form of thrombotic microangiopathy (TMA) characterized by a complex interplay of genetic and immunological factors. Historically, research into aHUS has primarily focused on genes associated with complement activation and coagulation pathways. Our previous studies, employing single cell sequencing analysis, have revealed a significant association between aHUS and various immune cell types [1]. The clinical manifestation of aHUS is often initiated by infections, autoimmune diseases, or pregnancy, with many instances not reverting to a stable state even after the elimination of these triggering factors. Additionally, a significant portion of patients, despite lacking identifiable anomalies in complement or coagulation genes, respond positively to anti-complement therapy. This observation suggests a potential role for inflammation-related genes in the pathogenesis of aHUS. Given the extensive array of genes linked to inflammation, our study is designed to quantitatively assess inflammation gene expression, converting these measures into an inflammation score for each immune cell type in aHUS patients, their nuclear families, and healthy controls. This approach allows for a detailed comparison of disease activity variations within aHUS cases, aiming to deepen our understanding of aHUS and explore new avenues for therapeutic intervention. Method This study enrolled 13 aHUS patients, 3 nuclear families without aHUS, and 4 healthy subjects from Taiwan. Peripheral blood samples were collected for single-cell RNA sequencing analysis. aHUS patients were categorized into stable and unstable groups. The definition of stable disease activity is characterized by consistent TMA-related organ involvement and normal markers of hemolysis. Single-cell RNA sequencing data was processed using CellRanger and analyzed using the Seurat package in R. We obtained inflammatory genes from the Molecular Signatures Database, and we used the AddModuleScore function in Seurat to calculate inflammation score (IS). Results Our analysis demonstrated that non-switch memory B cells, classical monocytes, intermediate monocytes, non-classical monocytes, low-density basophils, naïve CD8 T cells, central memory CD8 T cells, terminal effector CD4 T cells, Th1 cells, Th17 cells, Th1/Th17 cells, and follicular helper T cells had the highest IS in aHUS patients, followed by aHUS patients' nuclear family members without aHUS and healthy control subjects. Furthermore, we observed that the IS of classical monocytes, non-switch memory B cells (Fig. 1), intermediate monocytes, non-classical monocytes, naïve CD8 T cells, central memory CD8 T cells, non-vd2 gd T cells, terminal effector CD4 T cells, Th17 cells, and follicular helper T cells were highest in aHUS patients with unstable disease activity, followed by aHUS patients with stable disease activity, aHUS patients' nuclear family members without aHUS, and healthy control subjects. Conclusion Our study underscores a pivotal link between elevated inflammation scores and aHUS severity aHUS. This finding not only emphasizes the critical role of inflammation in disease progression but also opens new avenues for therapeutic intervention, particularly in cases of unstable aHUS. By highlighting inflammation as a key factor in aHUS pathophysiology, our research offers fresh insights for disease management and future investigations. Moreover, exploring anti-inflammatory pathways presents promising therapeutic possibilities, potentially leading to improved patient outcomes and enhanced management strategies for aHUS.

Exclusive enteral nutrition impacts peripheral blood mononuclear cell profile of children with Crohn's disease.

The immunological effects of exclusive enteral nutrition (EEN) in the treatment of active Crohn's disease (CD) are yet to be unveiled. The present study investigated changes in peripheral blood mononuclear cell profiles in children with active CD following 8-week treatment with EEN. In nine children, EEN significantly decreased the number and frequency of circulating effector memory CD8+ T cells re-expressing CD45RA (TEMRA), with corresponding increases observed in the frequency of circulating central and effector memory CD8+ T cells. These signals were conserved when looking at a subgroup of patients who achieved remission, and another who demonstrated the highest level of compliance to EEN. We speculate that the increases in circulating central and effector memory CD8+ T cells may be related to the extensive microbiome-modifying effects of EEN dampening immune response within the gastrointestinal tract.

Analysis of prognostic value of lactate metabolism-related genes in ovarian cancer based on bioinformatics

BackgroundRecent studies have provided evidence supporting the functional role and mechanism of lactate in suppressing anticancer immunity. However, there is no systematic analysis of lactate metabolism-related genes (LMRGs) and ovarian cancer (OV) prognosis.ResultsSix genes (CCL18, CCND1, MXRA5, NRBP2, OLFML2B and THY1) were selected as prognostic genes and a prognostic model was utilized. Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) analyses were further performed and indicated that the prognostic model was effective. Subsequently, the neoplasm_cancer_status and RiskScore were determined as independent prognostic factors, and a nomogram was established with relatively accurate forecasting ability. Additionally, 2 types of immune cells (Central memory CD8 T cell and Immature B cell), 4 types of immune functions (APC co inhibition, DCs, Tfh and Th1 cells), 9 immune checkpoints (BTLA, CTLA4, IDO1, LAG3, VTCN1, CXCL10, CXCL9, IFNG, CD27) and tumor immune dysfunction and exclusion (TIDE) scores were significantly different between risk groups. The expression of 6 genes were verified by quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and the expression of 6 genes were higher in the high-grade serous carcinoma (HGSC) samples.ConclusionA prognostic model related to lactate metabolism was established for OV based on six genes (CCL18, CCND1, MXRA5, NRBP2, OLFML2B and THY1) that could provide new insights into therapy.

Single-cell analysis of bronchoalveolar cells in inflammatory and fibrotic post-COVID lung disease.

Persistent radiological lung abnormalities are evident in many survivors of acute coronavirus disease 2019 (COVID-19). Consolidation and ground glass opacities are interpreted to indicate subacute inflammation whereas reticulation is thought to reflect fibrosis. We sought to identify differences at molecular and cellular level, in the local immunopathology of post-COVID inflammation and fibrosis. We compared single-cell transcriptomic profiles and T cell receptor (TCR) repertoires of bronchoalveolar cells obtained from convalescent individuals with each radiological pattern, targeting lung segments affected by the predominant abnormality. CD4 central memory T cells and CD8 effector memory T cells were significantly more abundant in those with inflammatory radiology. Clustering of similar TCRs from multiple donors was a striking feature of both phenotypes, consistent with tissue localised antigen-specific immune responses. There was no enrichment for known SARS-CoV-2-reactive TCRs, raising the possibility of T cell-mediated immunopathology driven by failure in immune self-tolerance. Post-COVID radiological inflammation and fibrosis show evidence of shared antigen-specific T cell responses, suggesting a role for therapies targeting T cells in limiting post-COVID lung damage.

Analysis and validation of biomarkers of immune cell-related genes in postmenopausal osteoporosis: An observational study.

Postmenopausal osteoporosis (PMOP) is a common metabolic inflammatory disease. In conditions of estrogen deficiency, chronic activation of the immune system leads to a hypo-inflammatory phenotype and alterations in its cytokine and immune cell profile, although immune cells play an important role in the pathology of osteoporosis, studies on this have been rare. Therefore, it is important to investigate the role of immune cell-related genes in PMOP. PMOP-related datasets were downloaded from the Gene Expression Omnibus database. Immune cells scores between high bone mineral density (BMD) and low BMD samples were assessed based on the single sample gene set enrichment analysis method. Subsequently, weighted gene co-expression network analysis was performed to identify modules highly associated with immune cells and obtain module genes. Differential analysis between high BMD and low BMD was also performed to obtain differentially expressed genes. Module genes are intersected with differentially expressed genes to obtain candidate genes, and functional enrichment analysis was performed. Machine learning methods were used to filter out the signature genes. The receiver operating characteristic (ROC) curves of the signature genes and the nomogram were plotted to determine whether the signature genes can be used as a molecular marker. Gene set enrichment analysis was also performed to explore the potential mechanism of the signature genes. Finally, RNA expression of signature genes was validated in blood samples from PMOP patients and normal control by real-time quantitative polymerase chain reaction. Our study of PMOP patients identified differences in immune cells (activated dendritic cell, CD56 bright natural killer cell, Central memory CD4 T cell, Effector memory CD4 T cell, Mast cell, Natural killer T cell, T follicular helper cell, Type 1 T-helper cell, and Type 17 T-helper cell) between high and low BMD patients. We obtained a total of 73 candidate genes based on modular genes and differential genes, and obtained 5 signature genes by least absolute shrinkage and selection operator and random forest model screening. ROC, principal component analysis, and t-distributed stochastic neighbor embedding down scaling analysis revealed that the 5 signature genes had good discriminatory ability between high and low BMD samples. A logistic regression model was constructed based on 5 signature genes, and both ROC and column line plots indicated that the model accuracy and applicability were good. Five signature genes were found to be associated with proteasome, mitochondria, and lysosome by gene set enrichment analysis. The real-time quantitative polymerase chain reaction results showed that the expression of the signature genes was significantly different between the 2 groups. HIST1H2AG, PYGM, NCKAP1, POMP, and LYPLA1 might play key roles in PMOP and be served as the biomarkers of PMOP.