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PubMed2026

Context-specific genetic effects inform endotypes and treatment in asthma.

BACKGROUND: Asthma has heterogeneous risk factors, subtypes, and treatments. It is often unclear how to stratify this heterogeneity in scientific studies and clinical care. Genetics could explain root causes of this clinical heterogeneity, called endotypes, but prior studies have used models that are not designed for complex diseases like asthma. OBJECTIVE: We aimed to find genetic effects that partly explain different asthma endotypes. METHODS: We used recent powerful and robust statistical models of context-specific genetic effects in complex traits. We identified genetic subtypes by clustering clinical asthma features in a case-control cohort, GALA II. We replicated the genetic endotypes in the UK Biobank with gene-context interaction tests. RESULTS: Asthma-associated single nucleotide polymorphisms, polygenic scores, and genome-wide heritability revealed subtype-specific genetic endotypes correlated with type 2 inflammation, allergy, and neuroticism. We validated the type 2 associations with molecular data including nasal RNA sequencing. In the UK Biobank, we replicated these endotypes and found they interact with several polygenic scores and drug-relevant genes. CONCLUSION: Our results show how context-specific genetic effects can unravel biomedically meaningful endotypes of complex disease and suggest novel precision treatment strategies.

Humans↗
PubMed2025

Integrating Imaging-Derived Clinical Endotypes with Plasma Proteomics and External Polygenic Risk Scores Enhances Coronary Microvascular Disease Risk Prediction.

Coronary microvascular disease (CMVD) is an underdiagnosed but significant contributor to the burden of ischemic heart disease, characterized by angina and myocardial infarction. The development of risk prediction models such as polygenic risk scores (PRS) for CMVD has been limited by a lack of large-scale genome-wide association studies (GWAS). However, there is significant overlap between CMVD and enrollment criteria for coronary artery disease (CAD) GWAS. In this study, we developed CMVD PRS models by selecting variants identified in a CMVD GWAS and applying weights from an external CAD GWAS, using CMVD-associated loci as proxies for the genetic risk. We integrated plasma proteomics, clinical measures from perfusion PET imaging, and PRS to evaluate their contributions to CMVD risk prediction in comprehensive machine and deep learning models. We then developed a novel unsupervised endotyping framework for CMVD from perfusion PET-derived myocardial blood flow data, revealing distinct patient subgroups beyond traditional case-control definitions. This imaging-based stratification substantially improved classification performance alongside plasma proteomics and PRS, achieving AUROCs between 0.65 and 0.73 per class, significantly outperforming binary classifiers and existing clinical models, highlighting the potential of this stratification approach to enable more precise and personalized diagnosis by capturing the underlying heterogeneity of CMVD. This work represents the first application of imaging-based endotyping and the integration of genetic and proteomic data for CMVD risk prediction, establishing a framework for multimodal modeling in complex diseases.

Cardiovascular Disease↗
PubMed2026

Mycosis Fungoides-Like Atopic Dermatitis Represents a Th22-Dominant Inflammatory Endotype.

BACKGROUND: Early-stage mycosis fungoides (MF) often presents diagnostic challenges because of its clinical overlap with atopic dermatitis (AD). In clinical practice, we encountered a subset of patients with severe AD who fulfilled the MF diagnostic criteria yet remained clinically indistinguishable from AD and presented refractoriness to advanced therapies. We termed this ambiguous entity "mycosis fungoides-like AD" (mfAD) and sought to determine whether it represents malignant transformation or a distinct inflammatory endotype of AD. METHODS: Skin biopsies were obtained from 7 patients with AD and 11 patients with mfAD. We performed paired single-cell RNA sequencing and single-cell T-cell receptor sequencing analyses. Publicly available MF and AD datasets were integrated for comparative analysis. Spatial transcriptomic profiling was used to contextualize single-cell findings within the tissue architecture. RESULTS: Comparative transcriptomic analysis revealed that T cells in mfAD were aligned with those in AD and lacked genomic instability. High-resolution profiling showed that mfAD was characterized by oligoclonal Th22 expansion rather than a single dominant malignant clone. Notably, all patients with mfAD achieved rapid clinical remission with selective JAK1 inhibition, indicating the therapeutic response characteristics of inflammatory dermatoses. CONCLUSION: Our findings demonstrate that mfAD is not a true malignancy, but rather a Th22-driven inflammatory endotype of AD. These results redefine mfAD as an inflammatory subtype within the AD spectrum, providing a mechanistic explanation for both the "pseudo-monoclonality" that leads to MF misdiagnosis and the failure of dupilumab. This study establishes a rationale for the use of JAK inhibitors in precision medicine for this patient population.

JAK inhibitor↗
PubMed2026

Bridging the airway microbiome and targeted therapy in bronchiectasis: multi-omics insights, endotypes and emerging therapies.

Bronchiectasis is a heterogeneous chronic airway disease primarily driven by persistent infection, microbial dysbiosis and dysregulated host immunity. While culture-based microbiology has historically informed clinical management, advances in high-throughput sequencing and multi-omic technologies have transformed our understanding of the airway ecosystem, revealing that disease activity is shaped not only by individual pathogens, but by complex and dynamic host-microbe interactions. Despite the breadth of descriptive microbiome data, translation into clinically actionable diagnostics or therapies has been limited. Importantly, cross-sectional correlations between microbiota and inflammation do not establish cause and effect, underscoring the need to embed host-microbiome profiling within both longitudinal and interventional therapeutic trials. In this review, we critically appraise current microbial and host multi-omics research in bronchiectasis, integrating microbiome studies with host inflammatory, proteomic and immunophenotyping data. We highlight themes emerging across cohorts, including low microbial diversity, pathogen dominance, loss of commensal networks and neutrophil-driven inflammation, and discuss how these features align with biological endotypes associated with exacerbations and treatment response. Drawing on lessons from host-directed therapeutic successes, we examine translational roadblocks limiting microbiome-guided care. We further review emerging microbiome-modulating strategies such as pathogen-specific biologics, bacteriophage therapy, live biotherapeutic products, biofilm-targeting adjuncts and precision antibiotic stewardship. Finally, we propose a roadmap toward microbiome-informed precision medicine through harmonised methodologies, integration of host and microbial biomarkers into clinical trials, and embedding multi-omics pipelines within large international registries. Collectively, these advances have the potential to shift bronchiectasis research and clinical management towards rationally designed, precision medicine-driven therapeutic strategies.

Humans↗
PubMed2024

Development of methodology to support molecular endotype discovery from synovial fluid of individuals with knee osteoarthritis: The STEpUP OA consortium.

OBJECTIVES: To develop a protocol for largescale analysis of synovial fluid proteins, for the identification of biological networks associated with subtypes of osteoarthritis. METHODS: Synovial Fluid To detect molecular Endotypes by Unbiased Proteomics in Osteoarthritis (STEpUP OA) is an international consortium utilising clinical data (capturing pain, radiographic severity and demographic features) and knee synovial fluid from 17 participating cohorts. 1746 samples from 1650 individuals comprising OA, joint injury, healthy and inflammatory arthritis controls, divided into discovery (n = 1045) and replication (n = 701) datasets, were analysed by SomaScan Discovery Plex V4.1 (>7000 SOMAmers/proteins). An optimised approach to standardisation was developed. Technical confounders and batch-effects were identified and adjusted for. Poorly performing SOMAmers and samples were excluded. Variance in the data was determined by principal component (PC) analysis. RESULTS: A synovial fluid standardised protocol was optimised that had good reliability (<20% co-efficient of variation for >80% of SOMAmers in pooled samples) and overall good correlation with immunoassay. 1720 samples and >6290 SOMAmers met inclusion criteria. 48% of data variance (PC1) was strongly correlated with individual SOMAmer signal intensities, particularly with low abundance proteins (median correlation coefficient 0.70), and was enriched for nuclear and non-secreted proteins. We concluded that this component was predominantly intracellular proteins, and could be adjusted for using an 'intracellular protein score' (IPS). PC2 (7% variance) was attributable to processing batch and was batch-corrected by ComBat. Lesser effects were attributed to other technical confounders. Data visualisation revealed clustering of injury and OA cases in overlapping but distinguishable areas of high-dimensional proteomic space. CONCLUSIONS: We have developed a robust method for analysing synovial fluid protein, creating a molecular and clinical dataset of unprecedented scale to explore potential patient subtypes and the molecular pathogenesis of OA. Such methodology underpins the development of new approaches to tackle this disease which remains a huge societal challenge.

Humans↗
PubMed2026

Multimodal Integration of Protein Interactomes With Genomic and Molecular Data Discovers Distinct Rheumatoid Arthritis Endotypes.

OBJECTIVE: Rheumatoid arthritis (RA) is a heterogeneous autoimmune disease characterized by clinical and molecular heterogeneity, notably in the presence of anti-cyclic citrullinated peptide (CCP) antibodies. Patients with CCP+ RA exhibit more severe disease progression and distinct treatment responses compared to patients with CCP- RA. Although previous studies have investigated cellular and molecular differences between these subtypes, their genetic differences are understudied. METHODS: We leveraged the Rheumatoid Arthritis Comparative Effectiveness Research cohort, comprising 555 patients with CCP+/rheumatoid factor (RF)+ RA and 384 patients with CCP-/RF+ RA. Using a novel framework, we integrated a network-based genome-wide association study (GWAS) with multiomic data to uncover corresponding genetic and molecular differences. RESULTS: We uncovered a significant heritability difference between these disease groups. Network-based GWAS uncovered 14 putative gene modules, including many genes outside the HLA loci, that explained genetic differences between CCP+/RF+ and CCP-/RF+ RA. Heritability partitioning and multivariate expression analyses validated four modules, highlighting novel genetic loci underlying phenotypic differences. Module functional significance was established using multiple orthogonal cohorts, underscoring their biologic relevance. CONCLUSION: Our findings demonstrate the use of network-based approaches in revealing differential genetic risk factors underlying CCP+/RF+ and CCP-/RF+ RA. Disease-associated gene modules detected in synovial tissue were also observed in peripheral blood, indicating joint-specific molecular programs are reflected systemically. This cross-tissue concordance highlights the potential for blood-based assays to capture pathogenic mechanisms active in the joints, enabling practical patient stratification. Our findings highlight why patients with CCP+/RF+ and CCP-/RF+ RA exhibit distinct clinical courses and therapeutic responses, supporting precision-guided treatment strategy development in RA.

Humans↗
PubMed2025

Blood from septic patients with necrotising soft tissue infection treated with hyperbaric oxygen reveal different gene expression patterns compared to standard treatment.

BACKGROUND: Sepsis and shock are common complications of necrotising soft tissue infections (NSTI). Sepsis encompasses different endotypes that are associated with specific immune responses. Hyperbaric oxygen (HBO2) treatment activates the cells oxygen sensing mechanisms that are interlinked with inflammatory pathways. We aimed to identify gene expression patterns associated with effects of HBO2 treatment in patients with sepsis caused by NSTI, and to explore sepsis-NSTI profiles that are more receptive to HBO2 treatment. METHODS: An observational cohort study examining 83 NSTI patients treated with HBO2 in the acute phase of NSTI, fourteen of whom had received two sessions of HBO2 (HBOx2 group), and another ten patients (non-HBO group) who had not been exposed to HBO2. Whole blood RNA sequencing and clinical data were collected at baseline and after the intervention, and at equivalent time points in the non-HBO group. Gene expression profiles were analysed using machine learning techniques to identify sepsis endotypes, treatment response endotypes and clinically relevant transcriptomic signatures of response to treatment. RESULTS: We identified differences in gene expression profiles at follow-up between HBO2-treated patients and patients not treated with HBO2. Moreover, we identified two patient endotypes before and after treatment that represented an immuno-suppressive and an immune-adaptive endotype respectively, and we characterized the genetic profile of the patients that transition from the immuno-suppressive to the immune-adaptive endotype after treatment. We discovered one gene MTCO2P12 that distinguished individuals who altered their endotype in response to treatment from non-responders. CONCLUSION: The global gene expression pattern in blood changed in response to HBO2 treatment in a direction associated with clinical biochemistry improvement, and the study provides potential novel biomarkers and pathways for monitoring HBO2 treatment effects and predicting an HBO2 responsive NSTI-sepsis profile. TRIAL REGISTRATION: Biological material was collected during the INFECT study, registered at ClinicalTrials.gov (NCT01790698) 04/02/2013.

Humans↗
PubMed2026

Stratified medicine with eplerenone for myocardial infarction or injury and no obstructive coronary arteries: A registry-based basket trial.

BACKGROUND: Myocardial Infarction with No Obstructive Coronary Arteries (MINOCA) or Nonischemic Myocardial Injury affects approximately 1 in 9 patients presenting with acute coronary syndrome, yet evidence-based therapies are lacking. Coronary microvascular dysfunction is implicated in the pathogenesis of suspected MINOCA, but its prevalence, prognostic implications and treatment are uncertain. The objectives are, first, to assess the prevalence of coronary microvascular dysfunction in patients with suspected MINOCA and, second, to implement endotype-informed stratified medicine involving patients with coronary microvascular dysfunction to treatment with eplerenone, a cardio- and vasculo-protective mineralocorticoid receptor antagonist. METHODS: This is a prospective, registry-based, multicenter, diagnostic study and nested, randomized, controlled, open-label, blinded-endpoint (PROBE) basket trial. Up to 400 patients with clinically suspected MINOCA and one or more cardiovascular risk factors will be enrolled into a registry-based diagnostic study. Coronary microvascular function will be assessed during invasive angiography using thermodilution. Patients with an index of coronary microvascular resistance (IMR) &#x2265; 25 will be randomized 1:1 to eplerenone (25-50 mg daily for 6 months) or standard care without eplerenone (control group) (n = 150 randomized). Final endotypes will be centrally adjudicated by a panel of blinded cardiologists. The primary outcome of the diagnostic study is the proportion of patients with IMR &#x2265; 25 during index coronary angiography. Secondary outcomes include coronary flow reserve, cardiovascular MRI parameters, patient-reported outcome measures, biomarkers of myocardial fibrosis and vascular inflammation, health outcomes and health economic assessments. The primary outcome of the randomized trial is the within-individual change in NT-proBNP at baseline, 1 month, and 6 months, based on intention-to-treat. Secondary outcomes include mechanistic blood biomarkers and patient-reported outcome measures. VALUE: This registry-based randomized trial will provide novel evidence on endotype-informed secondary prevention therapy with eplerenone for suspected MINOCA.

Humans↗
PubMed2026

Osteoarthritis phenotypes: advancing precision medicine through clinical, structural, and molecular stratification.

PURPOSE: Osteoarthritis (OA) is now understood as a heterogeneous syndrome driven by diverse biological, biomechanical, metabolic, genetic, and molecular mechanisms. This variability explains differences in disease progression and treatment response, challenging the traditional "one-size-fits-all" approach. This review highlights OA phenotyping as a key step toward precision medicine, focusing on clinical, structural, and molecular classifications that inform individualized care. METHODS: A narrative review was conducted using a non-systematic search of major databases and Osteoarthritis Research Society International sources (2010-2026). Evidence was thematically synthesized across clinical, imaging, and molecular domains to characterize OA phenotypes and their potential relevance to precision medicine. RESULTS: Multiple OA phenotypes were identified: inflammatory, metabolic, biomechanical, cartilage-subchondral, pain-sensitization, and aging/senescence. These exhibit distinct clinical features, risk factors, and therapeutic responses. Imaging-based phenotypes (e.g., inflammatory, meniscus-cartilage, subchondral bone, atrophic, hypertrophic) and molecular endotypes (low turnover, structural damage, systemic inflammation) further refine stratification. Pain-structure discordance is notable in sensitization phenotypes and may predict poorer surgical outcomes. Joint-specific variations and emerging genomic and epigenetic insights underscore disease complexity. Advances in imaging, biomarkers, and machine learning may enable earlier detection and patient clustering, though clinical application remains limited. CONCLUSION: Phenotype- and endotype-based classification represents a critical advancement toward precision OA management. Tailored interventions based on stratification hold promise for improving outcomes; however, clinical translation remains limited by overlapping phenotypes, lack of validated biomarkers, and inconsistent results from phenotype-driven trials. Wider clinical adoption requires standardized definitions, validation across joints, and integration of multimodal diagnostic tools into routine practice.

Humans↗
PubMed2025

Proteomic Profiling of the Large-Vessel Vasculitis Spectrum Identifying Shared Signatures of Innate Immune Activation and Stromal Remodeling.

OBJECTIVE: Takayasu arteritis (TAK) and giant cell arteritis (GCA), the most common forms of large-vessel vasculitis (LVV), can result in serious morbidity. Understanding the molecular basis of LVV should aid in developing better biomarkers and treatments. METHODS: Plasma proteomic profiling of 184 proteins was performed in two cohorts. Cohort 1 included patients with established TAK (n = 96) and large-vessel GCA (LV-GCA) (n = 35) in addition to healthy control participants (HCs) (n = 35). Cohort 2 comprised patients presenting acutely with possible cranial GCA (C-GCA) in whom the diagnosis was subsequently confirmed (C-GCA, n = 150) or excluded (Not C-GCA, n = 89). Proteomic findings were compared to published transcriptomic data from LVV-affected arteries. RESULTS: In cohort 1, comparison to HCs revealed 52 differentially abundant proteins (DAPs) in TAK and 72 DAPs in LV-GCA. Within-case analyses identified 16 and 18 disease activity-associated proteins in TAK and LV-GCA, respectively. In cohort 2, comparing C-GCA versus not C-GCA revealed 31 DAPs. Analysis within C-GCA cases suggested the presence of distinct endotypes, with more pronounced proteomic changes in the biopsy-proven subgroup. Cross-comparison of TAK, LV-GCA, and biopsy-proven C-GCA revealed highly similar plasma proteomic profiles, with 26 shared DAPs including interleukin 6 (IL-6), monocyte/macrophage-related proteins (CCL7, CSF1), tissue remodeling proteins (TIMP1, TNC), and novel associations (TNFSF14, IL-7R). Plasma proteomic findings reflected LVV arterial phenotype; for 42% of DAPs, the corresponding gene was differentially expressed in tissue. CONCLUSION: These findings suggest shared pathobiology across the LVV spectrum involving innate immunity, lymphocyte homeostasis, and tissue remodeling. Network-based analyses highlighted immune-stromal cross-talk and identified novel therapeutic targets (eg, TNFSF14).

Humans↗
PubMed2026

Single-cell RNA sequencing of peripheral blood defines two immunological subtypes of Sj&#xf6;gren's disease distinguished by anti-SSA antibodies and aberrant B cell populations.

OBJECTIVES: Sj&#xf6;gren's disease (SjD) is a heterogeneous autoimmune disorder characterized by substantial clinical and molecular diversity. This heterogeneity raises key questions regarding the existence of distinct pathogenic mechanisms underlying disease subtypes. The objective of this study was to comprehensively characterize peripheral immune cell states associated with SjD and to identify features that could enable better patient stratification for targeted treatments. METHODS: We performed single-cell RNA sequencing with surface protein profiling on 1.5 million peripheral blood mononuclear cells (PBMCs) from 333 participants. Individuals were stratified by SjD diagnosis and anti-SSA status to enable comparative analyses between disease subgroups and controls. RESULTS: Our analysis identified two immunological endotypes of SjD, with SSA-positive participants exhibiting a dominant and persistent IFN-I signature that was also associated with altered immune cell composition. Transitional B cells were particularly affected, displaying altered developmental states, reduced BCR diversity, shorter CDR3 regions, and increased predicted interactions with activated immune cell populations, findings consistent with perturbations of early B-cell selection processes. By contrast, SSA-negative SjD participants exhibited limited transcriptional differences compared with symptomatic non-SjD controls, highlighting substantial biological heterogeneity within SjD. CONCLUSIONS: These findings support a two-disease model of SjD and highlight transitional B cells as both a key biomarker and a therapeutic target.

Journal Article↗
PubMed2026

Genomic and integrative based progression biomarker discovery in adult sepsis: toward clinical stratification and precision medicine.

Sepsis is a life-threatening syndrome characterized by a heterogeneous host response to infection that remains a major cause of mortality worldwide. Current clinical scoring systems capture organ dysfunction but fail to reflect the underlying biological diversity, limiting their utility for patient stratification and targeted therapy. This review provides a comprehensive overview of molecular biomarker approaches used to predict sepsis course and prognosis in adult patients, covering genetic, transcriptomic, proteomic, and integrative strategies up to May 2026. Here, we summarize findings from genetic association studies, along with analyses based on polygenic risk scores to aggregate genetic effects, Mendelian randomization, and rare-variant sequencing approaches. We also review transcriptomic and proteomic strategies for endotyping, and diagnostic and prognostic discrimination. Lastly, we discuss how multi-omics integration is emerging as a promising framework to assist in distinguishing causal therapeutic targets from non-causal biomarkers. We also address the challenges that still constrain clinical translation towards precision medicine.

Biomarker↗
PubMed2026

Harnessing metabolomics and proteomics in a clinical trial for pulmonary arterial hypertension: insights from post-hoc analysis of the REHAB-PH trial.

BACKGROUND: The significant clinical and molecular heterogeneity of pulmonary arterial hypertension (PAH) poses challenges in identifying effective therapies. Advanced multidimensional profiling offers an opportunity to capture molecular responses and assess biomarker stability, yet its application in randomised trials remains limited. METHODS: We evaluated the multi-omic profiles of participants with PAH in a randomised, placebo-controlled trial of famotidine. Plasma metabolomic and proteomic profiling was performed at enrolment and 24 weeks. Baseline profiles were compared between treatment arms to assess randomisation balance. Intraclass correlation coefficients quantified within-subject stability over time. Linear regression models adjusting for age, sex, body mass index and PAH aetiology evaluated famotidine's molecular effects. False discovery rate was controlled for multiple comparisons. FINDINGS: For the 79 participants, baseline multi-omic profiles were similar between groups. At 24 weeks, 34 and 37 participants remained in the famotidine and placebo groups respectively. The placebo group showed high molecular stability, while greater variability was observed in the famotidine group. Famotidine treatment was associated with significant changes across 191 proteomic pathways (q-value <0.05), but no metabolomic changes remained significant after multiple-testing correction. INTERPRETATION: Integrating multi-omics into a prospective clinical trial is feasible and yields stable longitudinal profiles in the absence of intervention. While famotidine did not yield clinical benefit, associated proteomic changes illustrate how molecular profiling can reveal treatment-related biology and inform future trial design. These findings highlight the broader utility of multi-omics for evaluating drug responses and identifying molecular endotypes in PAH and beyond. FUNDING: US National Institutes of Health.

Humans↗
PubMed2026

Post-genome-wide association study variant-to-function challenges in asthma research.

Genome-wide association studies of asthma have identified nearly 200 independent loci, yet the mechanisms through which individual loci influence asthma risk remain largely unknown. A growing array of computational and experimental tools has begun to fill these gaps by identifying causal variants and effector genes and characterizing their functions. In parallel, emerging studies are exploring the translational applications of genetic and multiomics data in asthma, including defining molecular endotypes and predicting disease risk. Here we review the strengths and limitations of current approaches for addressing the post-genome-wide association study challenges and discuss the next tier of questions and directions for the field.

Humans↗
PubMed2026

Osteoarthritis Year in Review 2026: Genetics, genomics and epigenetics.

OBJECTIVE: The purpose of this narrative review is to highlight advances made over the past 12 months in the field of osteoarthritis (OA) genetics, genomics and epigenomics, with a particular focus on the interpretation of OA risk loci through functional genomic and regulatory approaches. DESIGN: PubMed and Europe PMC were searched to identify studies relevant to OA genetics, genomics and epigenomics published between 1st March 2025 and 30th April 2026. Searches used combinations of terms relating to genetics, genomics, epigenomics, functional genomics, molecular quantitative trait loci, chromatin accessibility and enhancer biology. Studies were limited to human subjects and English-language publications, with additional articles identified through citation screening and expert knowledge of the field. RESULTS: Over the past year, the field has continued to transition from large-scale locus discovery towards biological interpretation of OA genetic risk. Major advances included the largest OA genome-wide association study to date, further development of polygenic risk score approaches, and increasing integration of molecular quantitative trait loci, chromatin accessibility, and enhancer biology datasets to prioritise effector genes and elucidate regulatory mechanisms. Several studies highlighted the highly context-dependent nature of OA genetic risk mechanisms, demonstrating that distinct tissues, cell types, and regulatory layers can identify different candidate effector genes at the same locus. Additional developments included increasing application of singlecell and multi-omic technologies to study OA-relevant tissues. CONCLUSION: Recent advances in OA genetics have shifted the field from locus discovery towards mechanistic interpretation. Emerging evidence demonstrates that the biological consequences of genetic variation are highly dependent upon tissue, cell state and disease context, with different functional genomic approaches often prioritising distinct candidate genes and regulatory mechanisms at the same susceptibility locus. Together, these findings suggest that OA risk loci should increasingly be viewed as dynamic regulatory systems rather than simple variant-to-gene relationships, providing a framework for future studies aimed at resolving causal mechanisms, defining disease endotypes, and identifying therapeutic targets.

Genetics↗
PubMed2026

H3K9ac promoter profiling and their association with gene expression in immune cells of T2-high asthma patients.

BACKGROUND: Asthma is a heterogeneous chronic inflammatory syndrome, with the T2-high endotype defined by robust type 2 immune responses and skewed T helper polarization. Although H3K9 acetylation (H3K9ac) is a key activating histone mark in T helper differentiation, its genome-wide promoter landscape in circulating immune cells of T2-high asthma remains uncharacterized. METHODS: Integrated ChIP-seq and RNA-seq profiling was performed on peripheral blood mononuclear cells (PBMCs) from ten T2-high asthma patients and ten healthy controls. Differential H3K9ac enrichment and gene expression were analyzed, followed by concordance and Spearman correlation analyses to identify genes under H3K9ac-linked transcriptional regulation. Findings were contextualized using publicly available H3K27ac ChIP-seq datasets from asthmatic airway tissue and glucocorticoid-treated airway epithelial cells. RESULTS: We identified 2340 differential enrichment regions (DERs), 95.9% mapping to promoters, with nearly all showing H3K9ac loss and enrichment in T cell receptor signaling and Th1/Th2/Th17 differentiation pathways. Genes encoding histone-modifying enzymes, including HATs, HDACs, and HMTs, were overrepresented, suggesting a self-reinforcing epigenetic feedback loop. Integrated analysis identified 979 genes with concordant H3K9ac and expression changes: downregulated genes were enriched in lymphocyte activation and TNF signaling, whereas upregulated genes were enriched in AKT and MAPK pathways. Locus-specific analyses showed H3K9ac loss at Th1/Th17 genes (TBX21, IFNG, CCR6) and gain at Th2 genes (IL4, TSLP). Targeted RT-qPCR provided independent experimental support for reduced expression of Th1-associated genes, with significant decreases in STAT1 and STAT4 in T2-high asthma patients. Correlation analysis identified six genes with significant H3K9ac-expression associations. CONCLUSIONS: Promoter H3K9ac remodeling is a defining epigenetic feature of T2-high asthma, reflecting coordinated alterations at T helper lineage-defining loci and inflammatory pathways.

Asthma↗
PubMed2026

Longitudinal clinical proteomics reveals pneumonia type-specific protein biomarkers and autoantibodies.

Community-acquired pneumonia is a major cause of morbidity and mortality globally. Specific molecular endotypes are currently not well defined, and different viral or bacterial pathogens may trigger specific host responses and pathogenic mechanisms. We performed longitudinal proteomic profiling of bronchoalveolar lavage fluid and plasma from bacterial, influenza, and SARS-CoV-2-driven pneumonia. Our analysis revealed highly pneumonia type-specific proteomic signatures, including COVID-19-specific antibodies locally produced in the lung. These antibodies showed biased immunoglobulin V-domain usage, linked to a CD69/CD83 plasma cell state associated with disease severity and degree of autoimmunity. Using mass spectrometry-driven autoantibody profiling in 2 independent COVID-19 cohorts, we identified 177 putative autoantibodies targeting extracellular matrix, nuclear, and immune-related proteins. Of note, temporal changes in autoantibody profiles correlated with clinical markers of inflammation, organ dysfunction, and duration of hospitalization. These findings highlight the autoimmune aspects of COVID-19 and provide potential biomarkers and therapeutic targets to help improve patient outcomes.

Humans↗
PubMed2026

Mapping the plasma proteomic architecture of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a heterogeneous systemic autoimmune disease, yet the molecular basis underlying this variability remains incompletely understood. We profiled the plasma proteome in 260 SLE patients and 86 healthy volunteers (HVs) using the SomaScan v4.1 platform, quantifying 7,288 analytes corresponding to 6,595 unique proteins. We identified 215 proteins that were robustly differentially abundant between SLE patients and HVs in both discovery (n = 207 SLE, n = 45 HVs) and validation sets (n = 53 SLE, n = 41 HVs). Within-cases analyses identified 421 proteins associated with disease activity. Network-based clustering delineated correlated protein modules, including an interferon-associated (IFN-associated) module and a kidney-associated module. Autoantibody-stratified analyses further uncovered distinct proteomic endotypes; positivity for antibodies targeting RNA-binding proteins (anti-Sm, anti-Ro-60, anti-RNP68, anti-RNP-A) was associated with increased IFN-stimulated protein levels (e.g., MX1, ISG15, and CXCL10), independent of disease activity. Anti-Sm, anti-RNP-A, and anti-Ro52 antibodies were associated with reduced plasma levels of their respective autoantigens. Anti-dsDNA antibodies were associated with elevated levels of CD40 ligand (CD40LG) and the neutrophil protease, proteinase-3. Moreover, we identified an association between CD40LG and disease activity specific to the anti-dsDNA-positive subgroup. Together, these data define plasma protein signatures of SLE and disease activity, highlight autoantibody-specific molecular phenotypes, and provide a basis for precision medicine.

Humans↗