Background: There is an association between LUAD and TB, and TB increases the risk of lung adenocarcinogenesis. However, the role of TB in the development of lung adenocarcinoma has not been clarified. Methods: DEGs from TB and LUAD lung samples were obtained to identify TB-LUAD-shared DEGs. Consensus Clustering was performed on the TCGA cohort to characterize unique changes in TB transcriptome-derived lung adenocarcinoma subtypes. Prognostic models were constructed based on TB signatures to explore the characterization of subgroups. Finally, experimental validation and single-cell analysis of potential markers were performed. Results: We characterized three molecular subtypes with unique clinical features, cellular infiltration, and pathway change manifestations. We constructed and validated TB-related Signature in six cohorts. TB-related Signature has characteristic alterations, and can be used as an effective predictor of immunotherapy response. Prognostically relevant novel markers KRT80, C1QTNF6, and TRPA1 were validated by RT-qPCR. The association between KRT80 and lung adenocarcinoma disease progression was verified in Bulk transcriptome and single-cell transcriptome. Conclusion: For the first time, a comprehensive bioinformatics analysis of tuberculosis signatures was used to identify subtypes of lung adenocarcinoma. The TB-related Signature predicted prognosis and identified potential markers. This result reveals a potential pathogenic association of tuberculosis in the progression of lung adenocarcinoma.

UNASSIGNED: Thyroid-associated ophthalmopathy (TAO) is considered to be an organ-specific autoimmune disease. Polymorphonuclear neutrophils (PMN) have been implicated in the pathogenesis of TAO. However, little is known about the role of PMN in the development of TAO, much less the relationship between PMN with B cells and CD4+T cells in TAO.
UNASSIGNED: This study aims to investigate the phenotypic characteristics of PMN and the relationship between PMN with CD4+T cell and B cell subsets in the pathogenesis of TAO.
UNASSIGNED: Blood routine information was collected from 135 TAO patients, 95 Grave\'s disease without TAO (GD) patients, and 116 normal controls (NC), while surface marker expression of PMN and the level of CD4+T cell and B cell subsets in peripheral blood from 40 TAO patients, 17 GD patients, and 45 NC was assessed by flow cytometry.
UNASSIGNED: The level of PMN, CD62L+PMN, CD54+PMN, CD4+T cells, and Th17 cells displayed an increase in TAO patients than NC, while Treg cells were lower in the TAO group compared to NC. There was no statistical difference in Th1 and plasma cells among the groups. PMN were positively correlated with Th17 cells, but not the Th1, Treg, and plasma cells.
UNASSIGNED: In the present study, we found that the percentage of PMN and PMN subset cells was significantly higher in TAO than in NC, and PMN were positively correlated with Th17 cells. It suggests that PMN may be involved in the immunopathogenesis of TAO and modulate the Th17 cell response during this process.

肾上腺皮质癌（ACC）是一种罕见的肾上腺恶性肿瘤。目前，ACC的诊断标准尚未统一，有包括Weiss评分系统在内的多个诊断标准，包含核分裂象、坏死及血管侵犯等增殖及侵袭性相关组织学特征。近年来关于ACC免疫表型的研究逐渐发展，网状纤维染色及免疫组织化学标志物Ki-67、胰岛素样生长因子2、β-catenin、p53、CYP11B1、DAXX/ATRX及错配修复相关蛋白等均被发现用于辅助ACC的诊断。.

目的： 探讨血管免疫母细胞性T细胞淋巴瘤（AITL）伴单克隆性浆细胞增生的临床病理学特征。 方法： 收集福建医科大学附属龙岩第一医院2019和2021年期间诊断的2例AITL伴单克隆性浆细胞增生病例，采用HE、免疫组织化学染色，观察组织学形态、免疫表型特征，原位杂交的方法检测EB病毒编码RNA，聚合酶链反应（PCR）检测免疫球蛋白（Ig）基因和T细胞受体（TCR）基因克隆性重排，并结合文献进行复习。 结果： 2例AITL伴单克隆性浆细胞增生的病例均为女性，例1和例2患者年龄分别为72岁和48岁；例1为腹股沟淋巴结，例2为颈部淋巴结。主要临床症状为全身淋巴结无痛性肿大，例1伴低热和胸腹腔积液，例2伴卵巢受累。光镜下，淋巴结结构完全或部分破坏，瘤细胞中等到大，胞质丰富、淡染，核不规则、扭曲或圆形，背景见多种炎性细胞浸润，其中浆细胞数量突出，例2伴有较多B免疫母细胞增生。在免疫表型上，CD21示紊乱增生的滤泡树突细胞网，肿瘤细胞表达多个T细胞标志物CD4（2/2）、CD3（2/2）、CD2（2/2）、CD7（2/2）和CD5（1/2）；大部分肿瘤细胞表达滤泡辅助T细胞标志物CXCL13、bcl-6、PD1和ICOS，局灶表达CD10。背景中的浆细胞例1呈Lambda轻链限制性、例2为Kappa轻链限制性。分子检测显示例1 IgH基因克隆性重排检测阳性，例2为TCR基因克隆性重排检测阳性。 结论： AITL伴单克隆性浆细胞增生罕见，病变淋巴结内可伴有明显B免疫母细胞增生，IgH基因可呈克隆性重排，易误诊为浆细胞病变或B细胞淋巴瘤，充分认识AITL多样的形态学及基因重排特征有助于避免误诊。.

Monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL), also known as type II enteropathy-associated T-cell lymphoma, is a rare malignant lymphoma of the extranodal lymphoid tissue derived from interepithelial T lymphocytes. MEITL is a primary intestinal T-cell lymphoma with a challenging diagnosis and aggressive progression, and it can invade other extraintestinal sites. In this study, we report four patients diagnosed with MEITL. All patients presented with abdominal pain, and one patient was admitted because of acute intestinal perforation. Two patients presented with unformed defecation and diarrhea. All patients carried the immunophenotypes CD3, CD7, CD8, CD20, and CD56, and the Ki-67 index ranged 60% to 90%. Three cases were analyzed using next-generation sequencing. One case displayed possibly relevant alterations of CREBBP, NOTCH2, SETD2, and STAT5B, and another case exhibited definite alteration of NOTCH1, possibly relevant alterations of CCND1 and DNMT3A, and potentially relevant alterations of HISTH3B, IGLL5, KMT2C, and KRAS. Different chemotherapy regimens were used, but the prognosis was poor. Hence, we illustrated that because of its low incidence, challenging diagnosis, and difficult treatment, further therapeutic improvements are urgently warranted.

OBJECTIVE: Heterozygous STAT1 Gain-of-Function (GOF) mutations are the most common cause of chronic mucocutaneous candidiasis (CMC) among Inborn Errors of Immunity. Clinically, these mutations manifest as a broad spectrum of immune dysregulation, including autoimmune diseases, vascular disorders, and malignancies. The pathogenic mechanisms of immune dysregulation and its impact on immune cells are not yet fully understood. In treatment, JAK inhibitors have shown therapeutic effectiveness in some patients.
METHODS: We analyzed clinical presentations, cellular phenotypes, and functional impacts in five Taiwanese patients with STAT1 GOF.
RESULTS: We identified two novel GOF mutations in 5 patients from 2 Taiwanese families, presenting with symptoms of CMC, late-onset rosacea, and autoimmunity. The enhanced phosphorylation and delayed dephosphorylation were displayed by the patients\' cells. There are alterations in both innate and adaptive immune cells, including expansion of CD38+HLADR +CD8+ T cells, a skewed activated Tfh cells toward Th1, reduction of memory, marginal zone and anergic B cells, all main functional dendritic cell lineages, and a reduction in classical monocyte. Baricitinib showed therapeutic effectiveness without side effects.
CONCLUSIONS: Our study provides the first comprehensive clinical and molecular characteristics in STAT1 GOF patient in Taiwan and highlights the dysregulated T and B cells subsets which may hinge the autoimmunity in STAT1 GOF patients. It also demonstrated the therapeutic safety and efficacy of baricitinib in pediatric patient. Further research is needed to delineate how the aberrant STAT1 signaling lead to the changes in cellular populations as well as to better link to the clinical manifestations of the disease.

OBJECTIVE: To confirm the causal relationship between immune cells and Ovarian Hyperstimulation Syndrome.
METHODS: Obtaining data, collecting single nucleotide polymorphisms, detecting instrumental variables heterogeneity, assessing causality, and assessing bidirectional causality.
METHODS: A two sample Mendelian study to confirm the causal relationship between immune cells and Ovarian Hyperstimulation Syndrome.
METHODS: Immune cell phenotype (including 22 million SNPs from GWAS on 3757 European individuals).
METHODS: Inverse variance weighting, one-sample analysis, MR-Egger, weighted median and weighted mode are used to assess the causal relationship between 731 immunophenotypes and Ovarian Hyperstimulation Syndrome. The weighted median and Mendelian Randomization multi-effect residuals and Mendelian Randomization multi-effect residuals and outlier tests are used to assess bidirectional causality between this two.
RESULTS: After False Discovery Rate correction, 9 immunophenotypes were found to be significantly associated with the risk of Ovarian Hyperstimulation Syndrome. B cell panel: IgD+ AC (OR, 0.90) 、CD19 on CD24+ CD27+ (OR, 0.86) 、BAFF-R on CD20- CD38 (OR, -1.22); Mature T cell group panel: EM DN (CD4 -CD8-) AC (OR, 1.46); Myeloid cell panel: Mo MDSC AC (OR, 1.13) 、CD45 on CD33br HLA-DR+ (OR, 0.87); Monocyte panel: HLA-DR on monocyte (OR, 0.86) 、CCR2 on CD14+ CD16+ monocyte (OR, 1.15) 、cDC panel: HLA-DR on myeloid DC (OR, 0.89).
CONCLUSIONS: This study shows the potential link between OHSS and immune cells by genetic means, providing new ideas for future clinical and basic research.

UNASSIGNED: DKD, a leading cause of chronic kidney and end-stage renal disease, lacks robust immunological research. Recent GWAS utilizing SNPs and CNVs has shed light on immune mechanisms of kidney diseases. However, DKD\'s immunological basis remains elusive. Our goal is to unravel cause-effect relationships between immune cells and DKD using Mendelian randomization.
UNASSIGNED: We analyzed FinnGen data (1032 DKD cases, 451,248 controls) with 731 immunocyte GWAS summaries (MP=32, MFI=389, AC=118, RC=192). We employed forward and reverse Mendelian randomization to explore causal links between immune cell traits and DKD. Sensitivity analysis ensured robustness, heterogeneity checks, and FDR correction minimized false positives.
UNASSIGNED: Our study explored the causal link between diabetic nephropathy (DKD) and immunophenotypes using two-sample Mendelian Randomization (MR) with IVW. Nine immunophenotypes were significantly associated with DKD at p<0.05 after FDR correction. Elevated CD24, CD3 in Treg subsets, CD39+ CD4+, and CD33- HLA DR- AC correlated positively with DKD risk, while CD27 in B cells and SSC-A in CD4+ inversely correlated. Notably, while none showed significant protection, further research on immune cells\' role in DKD may provide valuable insights.
UNASSIGNED: The results of this study show that the immune cells are closely related to DKD, which may be helpful in the future clinical study.

BACKGROUND: Existing studies have presented limited and disparate findings on the nexus between immune cells, plasma metabolites, and metabolic dysfunction-associated steatotic liver disease (MASLD). The aim of this study was to investigate the causal relationship between immune cells and MASLD. Additionally, we aimed to identify and quantify the potential mediating role of metabolites.
METHODS: A Mendelian randomization (MR) analysis was conducted using two samples of pooled data from genome-wide association studies on MASLD that included 2568 patients and 409,613 control individuals. Additionally, a mediated MR study was employed to quantify the metabolite-mediated immune cell effects on MASLD.
RESULTS: In this study, eight immunophenotypes were linked to the risk of MASLD, and thirty-five metabolites/metabolite ratios were linked to the occurrence of MASLD. Furthermore, a total of six combinations of immunophenotypic and metabolic factors demonstrated effects on the occurrence of MASLD, although the mediating effects of metabolites were not significant.
CONCLUSIONS: Our study demonstrated that certain immunophenotypes and metabolite/metabolite ratios have independent causal relationships with MASLD. Furthermore, we identified specific metabolites/metabolite ratios that are associated with an increased risk of MASLD. However, their mediating role in the causal association between immunophenotypes and MASLD was not significant. It is important to consider immune and metabolic disorders among patients with MASLD in clinical practice.

UNASSIGNED: The clinical presentation of Community-acquired pneumonia (CAP) in hospitalized patients exhibits heterogeneity. Inflammation and immune responses play significant roles in CAP development. However, research on immunophenotypes in CAP patients is limited, with few machine learning (ML) models analyzing immune indicators.
UNASSIGNED: A retrospective cohort study was conducted at Xinhua Hospital, affiliated with Shanghai Jiaotong University. Patients meeting predefined criteria were included and unsupervised clustering was used to identify phenotypes. Patients with distinct phenotypes were also compared in different outcomes. By machine learning methods, we comprehensively assess the disease severity of CAP patients.
UNASSIGNED: A total of 1156 CAP patients were included in this research. In the training cohort (n=809), we identified three immune phenotypes among patients: Phenotype A (42.0%), Phenotype B (40.2%), and Phenotype C (17.8%), with Phenotype C corresponding to more severe disease. Similar results can be observed in the validation cohort. The optimal prognostic model, SuperPC, achieved the highest average C-index of 0.859. For predicting CAP severity, the random forest model was highly accurate, with C-index of 0.998 and 0.794 in training and validation cohorts, respectively.
UNASSIGNED: CAP patients can be categorized into three distinct immune phenotypes, each with prognostic relevance. Machine learning exhibits potential in predicting mortality and disease severity in CAP patients by leveraging clinical immunological data. Further external validation studies are crucial to confirm applicability.