Clinical and Experimental Immunology

BackgroundImmune dysfunction in sepsis and critical illness is biologically heterogeneous, yet available stratification frameworks leave many patients unclassified. We hypothesized that ex vivo cytokine-induction responses would define a continuous axis of functional immune responsiveness and identify a low-response state enriched in sepsis. MethodsIn this prospective observational study, 39 critically ill adults enrolled within 48 hours of ICU admission and 6 healthy controls underwent standardized whole-blood stimulation with lipopolysaccharide, anti-CD3/anti-CD28 antibodies, and PMA/ionomycin, with selected wells additionally supplemented with interleukin-7 or granulocyte-macrophage colony-stimulating factor. Interleukin-6, tumor necrosis factor, and interferon-gamma responses were quantified and referenced to subject-specific unstimulated baselines. A patient-anchored primary feature matrix was used to derive a continuous immune axis by principal component analysis, and a cross-validated 5-feature MiniResponder score was developed as a portable summary measure. ResultsAmong critically ill patients, induced cytokine responses organized along a dominant continuous axis of functional immune responsiveness; the first principal component explained 53.3% of between-patient variance. MiniResponder captured this axis and showed a lower-shifted distribution in sepsis. Using a control-referenced threshold defined by the 10th percentile of the healthy-control distribution, 19 of 39 patients (48.7%) were classified as low-response, including 15 of 21 patients with sepsis (71.4%) and 4 of 18 critically ill patients without sepsis (22.2%) (odds ratio 8.75, Fisher exact P=0.004). In exploratory analyses, lower MiniResponder scores were associated with greater unadjusted improvement in Sequential Organ Failure Assessment score from day 1 to days 3-9 (rho=-0.33; P=0.046), but this association attenuated after adjustment for baseline SOFA score (beta=-0.10; 95% CI-0.36 to 0.27). ConclusionsEx vivo immune profiling identified a continuous patient-anchored axis of functional immune responsiveness in critical illness that can be summarized by a compact 5-feature score. A control-referenced low-response state was enriched in sepsis. This framework may complement existing biomarker-based stratification approaches and support future enrichment strategies in sepsis trials.

RationaleSepsis is a life-threatening syndrome causing significant morbidity and mortality especially in the aging population. Clonal hematopoiesis of indeterminate potential (CHIP) is an age-related condition of clonal expansion of hematopoietic stem cells harboring somatic mutations associated with increased incidence of chronic illness and all-cause mortality. ObjectiveEvaluate the association of pre-illness CHIP with mortality and morbidity in patients admitted to the ICU with sepsis. MethodsWe performed a retrospective study using a de-identified electronic health record linked with a DNA biorepository. We identified adult patients with sepsis who had DNA collected prior to ICU admission. We tested the association between CHIP status, determined from whole-genome sequencing, and ICU mortality, organ support-free days, and long-term survival adjusting for age, sex, race and Sequential Organ Failure Assessment (SOFA) score on ICU admission. Measurements and Main ResultsPre-illness CHIP was associated with increased sepsis mortality (OR = 1.54, 95% CI 1.13 to 2.07, P = 0.005) and fewer days alive and free of organ support (-1.7 days, 95% CI -3.2 to -0.2, P = 0.028) after adjusting for age, sex, race, and SOFA score. In sepsis survivors, CHIP was also associated with increased long-term mortality after discharge (HR 1.40, 95% CI 1.01 to 1.93, P = 0.041). ConclusionsPre-illness CHIP was independently associated with increased mortality and morbidity in critically-ill adults with sepsis. These findings suggest that CHIP is a risk factor for sepsis severity. Elucidating the mechanism underlying this association could uncover new therapeutic interventions for sepsis.

Red blood cell (RBC) alloimmunization is a clinically significant complication in transfused patients whose immunological determinants remain incompletely understood. Type I interferon (IFN-I) signaling drives RBC alloimmunization in murine models, and systemic lupus erythematosus (SLE) is characterized by constitutive IFN-I hyperactivation alongside elevated alloimmunization rates. We analyzed three publicly available SLE RNA-seq cohorts (GSE72509, GSE112087, GSE122459; whole blood and PBMC; total n = 150 SLE) in a pre-specified discovery-replication-validation design. A 14-gene IFN-I signature score was computed per sample; differential expression, gene set enrichment analysis, and Spearman correlation were performed independently per cohort. IFN-I scores were significantly elevated in SLE versus healthy controls in all three cohorts (p < 0.01 each). IFN-high SLE patients showed 665 differentially expressed genes, with enrichment of alloimmunization-associated and plasmablast differentiation gene sets confirmed by GSEA. The alloimmunization signature score correlated significantly with IFN-I score across all three independent cohorts ({rho} = +0.77, +0.51, +0.60; all FDR q < 0.05); Tfh differentiation showed no association in any cohort. To our knowledge, this represents the first human transcriptomic evidence that IFN-I pathway activity in SLE is coupled to alloimmunization-associated immune programs in vivo. These findings identify IFN-I score as a candidate biomarker of alloimmunization susceptibility in SLE and provide translational rationale for prospective studies incorporating transfusion outcome data.

Severe forms of inflammation-induced acute and chronic myocarditis have a poor prognosis. Promising therapeutic efforts focused on monoclonal antibodies (mAbs) inhibiting inflammation-inducing molecules. However, most mAbs target only one or a limited number of such molecules. Since inflammation involves multiple redundant pathways, we postulated that an mAb inhibiting multiple inflammatory pathways would be a potent therapeutic agent. We initially tested the commercially available anti-natural killer (NK) cell mAb (anti-NK1.1), which binds a receptor expressed on NK cells and depletes them. Since NK cells are key cellular orchestrators of inflammation, by reducing their number, we aimed to inhibit multiple inflammatory pathways. Our initial studies demonstrated that administration of this antibody significantly improved myocardial outcomes in mouse models of acute myocardial infarction and of heart failure. Since NK1.1 is not expressed in human cells, we built on these promising preclinical results by developing a novel mAb targeting CD160 on human NK cells for evaluation as an immunosuppressive therapy. We found that the anti-CD160 mAb depletes both murine and human NK cells. We also found that, while CD160+ cells were largely present in the NK population, they also occurred among CD8+ and {gamma}/{delta} T cell subsets in human cells. Anti-CD160 therapy entirely prevented the deterioration of the myocardial function of mice with autoimmune-induced acute myocarditis. This outcome suggests our novel approach for inhibiting multiple inflammatory pathways may provide a potent strategy for improving outcomes of inflammation-driven myocarditis, as well as of other inflammation-driven diseases. Key PointsO_ST_ABSQuestionC_ST_ABSCan the depletion of CD160+ cells prevent autoimmune-induced myocarditis? FindingsIn this study we found that CD160 is expressed by mouse and human natural killer cells and other subtypes of cytotoxic T cells, and that a monoclonal antibody targeting CD160 depletes NK cells. In a preclinical model of experimental autoimmune myocarditis, administration of the anti-CD160 monoclonal antibody prevented myocardial dysfunction and systemic inflammation. MeaningOur results are compatible with the hypothesis that early autoimmune-induced myocardial dysfunction is promoted by CD160+ cells, which elevate inflammation-induced circulating factors (or factors released by tissue-resident cytotoxic immune cells) that cause myocardial dysfunction in the absence of myocardial necrosis or fibrosis, and further, that targeting CD160+cells with a mAb that depletes NK cells (and probably CD160 expressing cytotoxic T cells) entirely prevents the deterioration of myocardial function in such mice. This outcome suggests our novel approach for inhibiting multiple inflammatory pathways may provide a potent strategy for improving outcomes of inflammation-driven myocarditis, as well as of other inflammation-driven diseases.

Objective: To characterize genome-wide DNA methylation patterns associated with sepsis using the Infinium Methylation EPIC v2.0 platform and to evaluate the feasibility of pooled methylation profiling in a pilot critical care cohort. Design: Single-center pilot epigenome-wide association study using pooled whole-blood genomic DNA and pool-level bioinformatic analysis. Setting: Academic medical center. Patients: Fifty critically ill adults enrolled within 48 hours of illness onset and 20 healthy controls. Interventions: None. Measurements and Main Results: Critically ill patients required mechanical ventilation and/or vasopressor support. Sepsis was defined according to Sepsis-3 criteria. Seventy individual samples were organized into 14 intended pools of 5 individuals each: 7 sepsis pools, 3 critically ill non-septic pools, and 4 healthy-control pools. One critically ill non-septic pool was excluded because of poor DNA quality, yielding 13 analyzable pools. For the primary pooled comparison, 7 sepsis pools were compared with 6 non-sepsis comparator pools comprising 2 critically ill non-septic and 4 healthy-control pools. After quality control and preprocessing with SeSAMe, 876,094 CpG sites were retained. The initial pool-level screen identified 170,897 candidate differentially methylated regions. Application of stringent secondary filters (false discovery rate <= 1%, absolute delta-beta >= 7.5%, and >= 5 CpGs per region) yielded a high-confidence subset with marked directional skewing, including 155 hypomethylated and 32 hypermethylated regions in sepsis. Differentially methylated region-associated genes were enriched in myeloid leukocyte activation, myeloid leukocyte-mediated immunity, defense response to bacterium, neutrophil granule biology, and hematopoietic cell lineage pathways. Additional signals involved microRNA-associated targets, ribosome biogenesis, RNA processing, long noncoding RNAs, and previously uncharacterized loci. Conclusions: In this pilot pooled EPIC v2.0 study, sepsis was associated with a biologically coherent, predominantly hypomethylated methylation signature enriched in myeloid and host-defense pathways. These findings support the feasibility of pooled methylation profiling for discovery-oriented sepsis biobank studies but should be interpreted as hypothesis-generating given the pool-level design, limited effective sample size, heterogeneous comparator group, and lack of direct validation against individual-level methylation profiles.

ObjectivesPatients with Systemic lupus erythematosus (SLE) who carry a high genetic burden often experience more severe disease. To understand the molecular consequences of polygenic risk, we analyzed single-cell gene expression profiles in SLE patients stratified by genetic risk. MethodsSingle-cell RNA sequencing (scRNA-seq) was performed on fresh peripheral blood mononuclear cells (PBMCs) from 16 female SLE patients, stratified by a weighted polygenic risk score (PRS), and 6 healthy controls (HCs). All patients were in low disease activity (LLDAS) and treated with antimalarials only. We assessed differential gene expression, interferon (IFN) signatures, transcription factor (TF) activity, and pathway enrichment across groups. ResultsPatients with High-PRS had significantly elevated IFN scores compared to HCs (p<0.001), whereas no significant difference was observed between Low-PRS patients and HCs (p>0.05) This pattern held across multiple immune cell types, including T cells, NK cells, and monocytes. Notable genes with increased expression in High-PRS patients included ISG15 and USP18 in plasmacytoid dendritic cells (pDCs), and IFI27 and RSAD2 in monocytes. IFN-related pathways were enriched in pDCs and monocytes in High-PRS patients, and only in monocytes in Low-PRS patients. TF analysis identified IRF7 and BATF3 as key candidate regulators in High-PRS of both cell types. ConclusionsHigh polygenic risk in SLE is associated with persistent activation of IFN signaling pathways, indicating that antimalarial treatment alone is insufficient to fully suppress IFN activity, even during remission or low disease activity.

Introduction: Incomplete recovery from relapses contributes to long-term disability accumulation in relapsing remitting multiple sclerosis (RRMS), yet the relationship between immune regulation and relapse recovery remains poorly defined. Objective: To longitudinally characterize regulatory/effector immune cell dynamics in untreated RRMS patients and assess their association with immune balance and relapse recovery. Methods: Monocytic myeloid-derived suppressor cells (M MDSCs), regulatory T cells (Treg), and effector CD4 T cell subsets were measured in blood from 69 untreated RRMS patients sampled during relapse or remission and reevaluated after 12 months. Associations with clinical recovery after relapse were examined. Results: During relapse, patients exhibited higher M MDSC and Treg frequencies than in remission, while effector T cell subsets remained unchanged. Over one year, M-MDSCs increased consistently regardless of baseline clinical status, whereas Treg frequencies remained stable. Effector to M MDSC ratios were markedly elevated during relapse and declined over time, while effector-to-Treg ratios showed minimal variation. M MDSC levels during relapse were associated with sustained regulatory features at 12 month follow up. Importantly, higher baseline M MDSC levels, but not Treg frequencies, were associated with complete relapse recovery at one year. Conclusion: These findings suggest that circulating M-MDSCs, but not Treg, reflect interindividual differences in immune regulation and clinical recovery after relapse in early RRMS.

ObjectivesThe aetiopathogenesis of SLE encompasses genetic, environmental and epigenetic factors. We investigated associations between an SLE methylation risk score (MRS), HLA-DRB1*03:01, a non-HLA polygenic risk score (PRS) and clinical and immunological phenotypes. MethodsDNA methylation in whole blood from patients fulfilling [&ge;]4 ACR-82 criteria and controls were investigated using the Illumina HM450K array. The discovery cohort included 311 patients and 400 controls, and the replication cohort comprised 175 patients and 187 controls. Seventeen independent, top differentially methylated CpG sites ({Delta}{beta} of [&ge;]0.1) from case-control comparisons, were used to calculate the MRS. Genotyping was performed using the Immunochip, and the PRS included 57 non-HLA SLE SNVs. Clinical data were collected from patient charts, and serum IFN-2 was measured using Simoa. ResultsHigher MRS was strongly associated with serum IFN-2 levels (p=1.04x10-14). In both cohorts, higher MRS associated with discoid lupus, immunologic involvement, and anti-SSA/SSB/RNP/Sm autoantibodies (all p<0.05), and with higher disease activity in the discovery cohort (p=1.50x10-). MRS was also elevated in patients with multiple autoantibodies (p<1.0x10-15) and in HLA-DRB1*03:01 carriers (p<1.0x10-3). In contrast, higher PRS was associated with nephritis, anti-dsDNA positivity, and lower prevalence of anti-SSB antibodies (all p<0.05). No correlation was observed between the MRS and the PRS (p=0.35). ConclusionThe MRS defines an interferon-high, HLA-DRB1*03:01-linked SLE subset with multiple autoantibodies, partly distinct from PRS-associated nephritis risk, highlighting potentially divergent pathogenic pathways. These findings underscore the value of integrating genetic and epigenetic data to better understand underlying disease mechanisms in SLE. Key MessagesO_LIHigher MRS, but not PRS, correlated with increased levels of serum IFN-. C_LIO_LIThe MRS was associated with discoid rash, hematologic disorder, hypocomplementemia, antibodies including anti-SSA and HLA-DRB1*03:01. C_LIO_LIHigher PRS was linked to nephritis and anti-dsDNA positivity, and did not associate with the MRS. C_LI

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID are complex chronic conditions that often follow infectious triggers with overlapping clinical features but poorly defined pathophysiological relationships. This study aimed to identify disease-specific immune signatures through multiparameter immunophenotyping of monocytes, dendritic cells, and T-cell subsets. A total of 207 participants were included (ME/CFS: n = 103; long COVID: n = 63; healthy controls: n = 41). Peripheral blood mononuclear cells were analyzed using multiparameter flow cytometry. Statistical analyses included non-parametric testing, age-adjusted ANCOVA, correlation network analysis, and principal component analysis (PCA). Long COVID was characterized by increased M2-like monocyte polarization, elevated CD80 expression across monocyte subsets, expansion of dendritic cells, and reduced expression of activation markers, indicating persistent immune activation with features of immune exhaustion. In contrast, ME/CFS exhibited reduced costimulatory molecule expression, impaired CCR7-mediated immune cell trafficking, and less coordinated activation patterns, consistent with a state of immune suppression. Correlation network analysis revealed more extensive and integrated immune interactions in long COVID, while PCA identified distinct immunophenotypic components and enabled moderate discrimination between the two conditions. These findings demonstrate that ME/CFS and long COVID are characterized by distinct immune profiles, supporting the concept of divergent immunopathological mechanisms. The identified signatures may contribute to biomarker development and guide targeted therapeutic approaches.

Haemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening hyperinflammatory syndrome characterised by uncontrolled immune activation. Reduced high- and low-density lipoprotein cholesterol and hypertriglyceridaemia are reported in HLH, suggesting lipid metabolism disturbances although in-depth serum metabolomic analysis is lacking in HLH. Here a lipid-focused NMR spectroscopy platform was used to define the serum metabolomic landscape of adults hospitalised with HLH compared to adults with sepsis (HLH-mimic) and rheumatic disease (potential HLH drivers/triggers), following surgical resection of solid organ cancer (non-infectious acute inflammation controls) and healthy controls (HCs). Serum metabolites distinguished HLH from HCs with high accuracy (>91.36%) using multiple machine learning models. The top classifying features included elevated apolipoprotein-B (ApoB)-containing low, intermediate, and very low-density lipoprotein particles; and lipoprotein remodelling towards triglyceride enrichment and cholesterol depletion. Differentially abundant metabolites in HLH compared to all control groups were enriched in pathways related to lipid metabolism including: 'Lipid particles composition', 'Plasma lipoprotein clearance', 'Plasma lipoprotein remodelling', 'Glucose homeostasis' and 'Amino acid metabolism'. Metabolomic results were validated using matched whole blood RNA-sequencing which identified differentially expressed genes enriched in metabolic modules associated with lipid, amino acid, and glucose metabolism, supporting a coordinated metabolic dysregulation in HLH from a transcriptomic to metabolomic level. Finally, twenty-seven metabolites including ApoB-containing, triglyceride-rich lipoproteins and saturated fatty acids distinguished HLH from all disease controls (AUC>0.70) either alone or combined as a metabolomic signature. Elevated ApoB and ApoB:ApoA1 ratio in HLH vs sepsis and HCs were validated by ELISA, supporting their utility as biomarkers to distinguish HLH from other hyperinflammatory syndromes.

Purpose: Aicardi-Goutieres syndrome (AGS) is a type I interferonopathy presently associated with nine genes. PTPN1 is a negative regulator of the interferon pathway previously associated with chronic inflammation and recently type 1 IFN autoinflammation. Methods: Genomic data from undiagnosed individuals with suspected AGS were interrogated for PTPN1 variants, and predicted loss-of-function (pLOF) and damaging missense variants in PTPN1 were sought in two additional academic databases as well as the All of Us database. Results: We identified 13 cases with ultra-rare heterozygous pLOF or highly damaging missense variants in PTPN1. Nine cases were identified in a cohort of 53 individuals (~ 17%) with clinical, imaging and persistent biochemical features of AGS. Median age of onset is 1.75 years (IQR 0.67), significantly later (p< 0.0001) than other AGS genotypes. Four additional cases were identified in academic datasets with variable clinical features suggestive of autoinflammation. Additionally, 49 individuals with ultra-rare, damaging PTPN1 variants were identified in the All of Us database, none had features suggestive of AGS, but autoimmunity was highly prevalent (~21.6%). Conclusion: Our data implicate PTPN1 as a cause of later-onset presentations of AGS within a broader spectrum of autoinflammatory phenotypes. Segregation and biobank data demonstrate reduced penetrance, with carriers being enriched for autoimmune disorders.

Background: Accurate early identification of sepsis remains a major clinical challenge due to its heterogeneous presentation and overlap of clinical signs with the non-infectious systemic inflammatory response syndrome (SIRS). Timely differentiation is crucial for improving patient outcomes, meeting sepsis bundle requirements and reducing inappropriate antimicrobial use. We hypothesized that clinical and laboratory data available within the first 3 hours of patient presentation could be used to identify patients with sepsis to an actionable level of accuracy, in lieu of traditional microbiology results which would not become available until at least 12-24 hours. Data from two independent studies were used to quantify the diagnostic value of demographic, vital, clinical-laboratory, and microbiological data available at three time points for distinguishing retrospectively diagnosed critically ill patients with either sepsis or non-infectious SIRS. A particular focus of this work was an assessment of the utility of SeptiCyte RAPID (Immunexpress Inc., Seattle, Washington, USA) as an aid to sepsis diagnosis, producing actionable data within 1 hour. Methods: Data from two independent study cohorts were analysed. The 510k cohort consisted of 419 adult patients in intensive care (ICU) (MARS, VENUS, and NEPTUNE trials). The Andalusian cohort consisted of 353 ICU patients from the PANGEA study. Logistic regression models, selected by a greedy search algorithm and validated by repeated cross-validation, were used to determine the contributions of different variables to diagnostic accuracy. Diagnostic performance was quantified by area under the receiver operating characteristic curve (AUC). Results: For the 510k cohort, a baseline AUC of 0.69-0.73 was observed using 5-7 vital and demographic variables assessed immediately upon presentation (time T1). The addition of clinical-laboratory variables, in particular SeptiCyte RAPID, within 1-3 hours post-presentation (time T2) increased the AUC to 0.83-0.85). Finally, the addition of microbiological data 12-24 hours post-presentation (time T3) further improved the AUC to 0.90-0.91. Similar results were obtained for the Andalusian cohort. AUC values at the three time points were as follows: At time T1, AUC = 0.67 based solely on vital signs and demographics; at time T2, AUC = 0.87 based on vitals + demographics + SeptiCyte RAPID or other clinical laboratory data; at time T3, AUC = 0.93 based on vitals + demographics + SeptiCyte RAPID or other clinical laboratory data + microbiology results). For both cohorts, the most significant variables included temperature, mean arterial pressure, respiratory rate, suspected infection site; SeptiCyte RAPID, procalcitonin, confirmed bacterial infection and positive blood culture confirmation. Conclusions: Accuracy of identification of sepsis increases markedly as demographics and vital signs are supplemented with clinical-laboratory information, and ultimately with microbiological culture results. The fastest improvement occurs within the first 3 hours when laboratory data, and in particular SeptiCyte RAPID results, become available. Integrating rapid host-response testing with SeptiCyte RAPID into time-based diagnostic frameworks may enhance early sepsis recognition, improve antimicrobial stewardship, and support guideline-driven clinical decisions.

Overview: SeptiCyte RAPID is an FDA-cleared gene expression test that quantifies host immune response to aid in the diagnosis of sepsis. The test yields a score (the SeptiScore) ranging from 0-15, distributed across four bands (1-4) based on increased likelihood of sepsis. Each band can be characterized by average positive and negative likelihood ratios (LR+, LR- respectively) for the discrimination of sepsis versus the non-infectious systemic inflammatory response syndrome (SIRS). Methods: A retrospective analysis of prospectively collected data from a combined cohort of critically ill patients suspected of sepsis (N=889), recruited across 19 hospitals in the USA and Europe. The analysis quantified the LR+ and LR- parameters as a function of SeptiScore, for discrimination of sepsis vs. SIRS in patients admitted to ICU. Hypotheses: (1) The likelihood ratio (LR) framework provides a clinically useful interpretive approach that complements the previously used SeptiScore banding scheme; (2) Low Band 1 SeptiScores are associated with sufficiently small LR- to support the use of SeptiCyte RAPID as a rule-out test for sepsis; (3) High Band 4 SeptiScores are associated with sufficiently large LR+ to support the use of SeptiCyte RAPID as a rule-in test for sepsis; and (4) SeptiScore-derived LR+ and LR- values can be combined with estimates of pre-test probability (derived from patient characteristics and/or other diagnostic tests) to generate individualized, patient-specific post-test probabilities of sepsis. Results: The SeptiCyte RAPID test demonstrates strong diagnostic performance in distinguishing sepsis from SIRS. The likelihood ratios across different score bands provide clear clinical utility: the median LR+ was 3.26 (range 2.57-4.24) for Band 3, and 6.97 (range 4.35-15.57) for Band 4 providing evidence toward ruling in sepsis at high SeptiScores. Conversely, the median LR- was 0.16 (range 0.14-0.20) for Band 2 and 0.085 (range 0.014-0.16) for Band 1, providing evidence toward ruling out sepsis at low SeptiScores. A higher-resolution analysis of SeptiCyte RAPID performance confirmed these trends by evaluating LR+ and LR- at specific values within each band. The sepsis group was further stratified according to whether patients were classified as blood-culture positive (BC+) or blood culture negative (BC-), and the detailed LR+ and LR- analyses were repeated. A monotonic increase in likelihood ratio with increasing SeptiScore was consistently observed, independent of whether sepsis patients were culture-positive, culture-negative, or unstratified with respect to blood culture status. Conclusion: High SeptiScores have correspondingly high LR+ values, and low SeptiScores have correspondingly low LR- values, both of which may have clinical utility. High likelihood ratios for band 4 SeptiScores, which precede traditional microbiology results, may provide clinicians with early confidence of a sepsis diagnosis and microbiology diagnostic stewardship. Low likelihood ratios for band 1 SeptiScores may prompt clinicians to consider an alternate diagnosis to sepsis. Such results, obtained early in the diagnostic workup process, may lead to fewer missed diagnoses and more efficient use of hospital resources.

Background & Aims: ACLF is defined differently by APASL (acute hepatic dysfunction) and by organ failure-based frameworks including EASL-CLIF and the recently developed A-TANGO score. Whether these definitions identify competing populations or sequential stages of the same syndrome remains unresolved, with direct implications for the timing of intervention. We tested whether APASL-defined ACLF can be integrated into the A-TANGO framework to identify a clinically actionable patient population. Methods: 4,024 patients hospitalised with acute decompensation of cirrhosis in a multicentre cohort were classified simultaneously by APASL and A-TANGO criteria. Mortality, progression to A-TANGO ACLF among A-TANGO-negative patients, and reversal of ACLF were assessed using Fine-Gray competing-risk models with death as a competing event. EASL-CLIF analyses were performed as sensitivity analyses. Results: A-TANGO-negative/APASL-positive patients comprised 8.7% of the cohort and had higher 90-day mortality than A-TANGO-negative/APASL-negative patients (22.3% vs 14.4%, p=0.001), despite similar 28-day mortality. Once A-TANGO ACLF was established, 28-day mortality was high irrespective of APASL status (45.4% in APASL-positive and 56.0% in APASL-negative patients). Among A-TANGO-negative patients, 53.5% of APASL-positive vs 27.9% of APASL-negative patients progressed to A-TANGO ACLF within 28 days, with APASL positivity independently predicting progression (adjusted sHR: 2.30, 95%CI: 1.90-2.77). Within A-TANGO-negative/APASL-negative patients an A-TANGO OF score [&ge;]8 independently enriched for progression (52% vs 19%). A-TANGO reversal occurred in 17.1% and was independently reduced by APASL positivity (adjusted sHR: 0.756, 95%CI: 0.586-0.975), while APASL reversal was rare (4.0%). EASL-CLIF sensitivity analyses were directionally consistent. Conclusions: APASL-defined ACLF does not compete with A-TANGO; it occupies an upstream position on the same disease trajectory. A-TANGO-negative/APASL-positive patients and A-TANGO-negative/APASL-negative patients with A-TANGO OF [&ge;]8 represent complementary pre-ACLF populations suitable for prevention trials and enrichment strategies.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterised by sustained type I interferon signalling and widespread immune dysregulation. Low-density neutrophils (LDNs) are expanded in SLE and display pro-inflammatory and tissue-damaging properties. However, their metabolic phenotype remains poorly defined. Here, we performed a comprehensive metabolic characterisation of circulating LDNs and normal-density neutrophils (NDNs) from patients with SLE and matched healthy individuals (HC). Neutrophil subsets were isolated from peripheral blood of SLE patients and HC donors using a two-step protocol of negative selection and Percoll density centrifugation. Immunophenotyping phenotype was carried out by flow cytometry to assess phenotypic expression of common neutrophil markers CD15, CD16, CD10, CD66b, CD62L, MPO, and IL-1{beta}. Bioenergetic profiling of LDNs and NDNs was performed in situ using the Seahorse MitoStress test to measure oxygen consumption rate (OCR) and extracellular acidification rate (ECAR). Metabolic flexibility and phenotypic alterations were assessed in LDNs and NDNs following inhibiting mitochondrial metabolism with oligomycin and glycolysis with 2DG. We found that SLE LDNs exhibit an immature phenotype compared with autologous and healthy NDNs, as determined transcriptionally by C/EBP{varepsilon} and by surface protein expression levels of CD10. Both LDNs and NDNs from SLEDAI[&ge;]4 patients demonstrated significantly elevated ECAR relative to HC neutrophils. Further, SLE LDNs displayed enhanced metabolic flexibility, with the capacity to switch towards a glycolytic phenotype under metabolic stress conditions. Inhibition of glycolysis altered the inflammatory and maturation-associated phenotype of both SLE neutrophil subsets, indicating a direct link between cellular metabolism and pathogenic neutrophil function. Collectively, these findings identify fundamental metabolic alterations in SLE neutrophil subsets and support neutrophil immunometabolism as a potential therapeutic target in SLE.

Background & Aims: People with HIV (PWH) who achieve hepatitis C virus (HCV) cure may retain persistent metabolic alterations, particularly those with advanced fibrosis or cirrhosis. This study aimed to characterize plasma metabolomic and lipidomic profiles associated with cirrhosis in PWH at one and five years post-HCV therapy. Methods: Two cross-sectional studies evaluated PWH one (n=48) and five (n=30) years post-HCV therapy. Cirrhosis was defined as a liver stiffness measurement (LSM)[&ge;]12.5 kPa. Metabolomics and lipidomics were performed using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS), respectively. Data were analyzed using orthogonal partial least squares discriminant analysis (OPLS-DA) and generalized linear models (GLM), adjusting for relevant covariates. Results: At one and five years, 32 (66.7%) and 10 (33.3%) participants, respectively, had cirrhosis. OPLS-DA identified 235 and 229 metabolites with variable importance in projection (VIP)scores >1. At one year, cirrhosis was associated with elevated levels of glycerophospholipids, sphingomyelins, and amino acids, and lower levels of triglycerides. At five years, cirrhotic PWH exhibited higher levels of glycerophospholipids and acyl-carnitines, together with lower levels of triglycerides and amino acids. Conclusions: PWH with cirrhosis post-HCV cure exhibits a persistently altered metabolic profile stable for five years, suggesting ongoing liver disease progression. These findings underscore the need for continued long-term monitoring of this population.

Background & AimsRare cases of non-hepatotropic virus (NHV) infection in humans can cause severe hepatitis and even acute liver failure. Clinically relevant animal models of NHV-induced hepatitis are limited, contributing to the incomplete understanding of pathological mechanisms. Murine norovirus (MNV) elicits hepatosplenomegaly in mice lacking the antiviral immune effector Signal Transducer and Activator of Transcription-1 (STAT1), providing a model to investigate mechanisms of NHV-induced hepatic pathology. MethodsSTAT1-sufficient and -deficient (Stat1Het, Stat1KO) littermates infected intravenously (i.v.) with MNV strain CR6 were assessed for hepatic inflammation and viral burden. Cell types and molecular pathways associated with hepatic pathology in CR6-infected Stat1KO mice were identified by flow cytometry and RNAseq of liver tissue. The relative importance of hematopoietic vs non-hematopoietic expression of STAT1 in restricting CR6 replication and maintaining tissue homeostasis was assessed in bone marrow chimeras. ResultsMNV CR6 Stat1KO mice developed severe hepatitis with patchy hepatocellular necrosis and localized enrichment of CR6-infected myeloid cells, particularly macrophages. Gene set enrichment analysis (GSEA) of hepatic biopsies isolated from CR6-infected Stat1KO mice suggested dysregulated myeloid cell activation and indicated similarities between murine and human hepatic pathologies. STAT1 expression in hematopoietic cells was protective against hepatic viral dissemination, but hematopoietic STAT1-deficiency permitted persistent hepatic MNV infection, facilitating dysregulated myeloid cell activation and hepatic fibrosis. ConclusionsThese results demonstrate that the role of STAT1 extends beyond restricting MNV dissemination and suggest that STAT1-dependent regulation of myeloid cell activation prevents acute hepatic necroinflammation and secondary fibrosis. This model of MNV-induced hepatitis may prove valuable in elucidating mechanisms of rare clinical complications. SynopsisMechanisms driving acute hepatitis caused by non-hepatotropic viruses are not well understood. We describe a model of non-hepatotropic murine norovirus infection that reliably induces liver pathology and identify a requirement for STAT1 expression in myeloid cells to promote antiviral immunity and hepatic tissue protection. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/720966v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@4ef59forg.highwire.dtl.DTLVardef@1dfac58org.highwire.dtl.DTLVardef@1abe41dorg.highwire.dtl.DTLVardef@d59e9_HPS_FORMAT_FIGEXP M_FIG C_FIG

Rheumatoid arthritis is a prototypical autoimmune disease, characterised by prolonged systemic autoimmunity prior to organ-specific tissue inflammation. To achieve the contemporary goal of autoimmune disease prevention, a nuanced understanding of the transition from systemic autoimmunity to tissue-specific inflammation is critical. Here, we sought to identify immune signatures associated with the transition to subclinical joint inflammation detected by multi-joint ultrasound in anti-citrullinated protein antibodies (ACPA+)-positive individuals who imminently progress to RA. To achieve this, we performed single-cell transcriptomic and proteomic profiling on prospectively collected blood samples from high-risk ACPA+ imminent progressors, who were further stratified by the presence or absence of ultrasound (US)-detectable subclinical synovitis and compared them with ACPA+ non-progressors. We found type-1 interferon (IFN-I) activation in circulating CD14+ classical monocyte and GZMK+ CD8+ T cells preceding subclinical joint inflammation in ultrasound-negative (USneg) future progressors. In contrast, US-positive (USpos) future progressors exhibited a phenotypic shift in CD14+ classical monocytes towards IL1B+ expression and clonal expansion of GZMB+ cytotoxic CD8+ T cells at the onset of subclinical synovitis. Plasma proteomics also revealed a shift from Toll-like receptor-associated innate pathways in USneg future progressors toward effector and tissue-remodeling signatures in USpos future progressors. These findings suggest IFN-I-driven immune priming in specific immune subsets precedes the onset of subclinical joint inflammation, whereas tissue-directed inflammatory and cytotoxic programmes emerge at the onset of joint inflammation when clinical RA is imminent.

Background & AimsEarly identification of decompensation in patients with cirrhosis is important to enable timely detection, management of complications and for effective treatment. This study investigates the biology of decompensation and aim to identify protein biomarkers for identification of high-risk patients. MethodsThe primary analysis included plasma samples from 46 patients with metabolic dysfunction associated steatotic liver disease (MASLD) related cirrhosis. Plasma samples were depleted for the top 14 most abundant proteins and the proteome was measured by liquid chromatography tandem mass spectrometry. The dataset was divided into a training (14 compensated, 10 decompensated) and a test cohort of compensated patients (11 progressing to decompensation, 11 remaining compensated). Changes in protein levels were determined by ANCOVA and a prognostic model was developed using logistic regression. External validation was performed in an independent cohort of 120 patients with alcohol-related cirrhosis. Time-to-event analyses were conducted in this cohort using Cox regression. Results52 proteins involved in impaired hepatic function, fibrogenesis, immune activation, and metabolic changes were significantly different between compensated and decompensated patients. A prognostic model with four proteins (NBL1, LTBP4, APOC4, GHR), demonstrated predictive ability for future decompensation (AUC=0.93, 73% sensitivity, 100% specificity). In the external validation cohort, the model demonstrated generalizability (AUC=0.78, 72% sensitivity, 82% specificity). Validation cohort time-to-event analyses showed that higher baseline scores were associated with shorter time to liver-related events (HR 1.32; log-rank p = 0.027), underscoring the panels prognostic value. ConclusionOur study indicates that patients with decompensated cirrhosis are characterized by proteomic signatures of fibrogenesis and metabolic dysfunction. Capturing these signatures could help identify patients at risk of complications and potentially those eligible for aetiology directed treatment. Impact and ImplicationsAddressing a critical unmet need for early detection of cirrhosis decompensation, our proteomic study identifies a four-protein panel with predictive ability for decompensation. These findings hold significant implications for hepatologists, clinical researchers, and healthcare systems, offering a novel tool to enhance prognostication and refine treatment strategies, potentially facilitating targeted patient monitoring. However, considering the small discovery sample size and the distinct aetiology of the external validation cohort, further validation is essential before broad clinical integration. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=183 SRC="FIGDIR/small/709475v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@6620e2org.highwire.dtl.DTLVardef@f8dfe4org.highwire.dtl.DTLVardef@1331101org.highwire.dtl.DTLVardef@1a195ca_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background and AimsAlterations in immunoglobulin G (IgG) N-glycosylation are implicated in inflammatory bowel disease (IBD); however, the robustness of IgG glycan signatures across IBD cohorts with diverse demographics and geographic origins remains underexplored. We aimed to determine whether compositional data analysis (CoDA) and machine learning (ML) can identify IBD-related IgG N-glycan signatures and whether these signatures capture disease-associated acceleration of biological aging. MethodsWe analyzed the IgG glycome profiles of 1,367 plasma samples collected from healthy controls (HC), symptomatic controls (SC), and people with newly diagnosed Crohns (CD), and ulcerative colitis (UC) across four cohorts (UK, Italy, United States, and Netherlands). IgG glycosylation was analyzed by ultra-high-performance liquid chromatography, yielding 24 total-area-normalized glycan peaks (GPs). Analyses were performed using cross-sectional data obtained at baseline. CoDA-powered association analyses were used to identify disease-related effects on GPs while controlling for demographic covariates. ML models were trained and evaluated to assess generalizability to unseen cohorts and demographic subgroups, with a focus on discrimination and reliability. ResultsAcross all cohorts, people with IBD demonstrated accelerated biological aging as quantified by the GlycanAge index. This was accompanied by consistent reductions in IgG galactosylation, with effects partially modulated by age. Classification models trained on glycomics and demographics achieved robust discrimination (AUROC{approx}0.80) between non-IBD (HC+SC) and IBD across cohorts. ConclusionThese findings reveal accelerated biological aging in people with IBD and support the translational potential of IgG glycans as biomarkers and a novel route toward clinically interpretable personalized risk estimates.