I_MDS: an inflammatory bowel disease molecular activity score to classify patients with differing disease-driving pathways and therapeutic response to anti-TNF treatment

Novel mRNA Signature for Anti-TNF-α Therapy Primary Response in Patients With Ulcerative Colitis

BACKGROUND

Ulcerative colitis (UC), an idiopathic, chronic inflammatory disorder of the colonic mucosa, is commonly treated with antitumor necrosis factor α (anti-TNF-α) agents. However, only approximately two-thirds have an initial response to these therapies.

METHODS

We integrated gene expression profiling from 3 independent data sets of 79 UC patients before they began anti-TNF-α therapy and calculated the differentially expressed genes between patient response and nonresponse to anti-TNF-α therapy and developed a de novo response-associated transcription signature score (logOR_Score) to demonstrate the predictive capability of anti-TNF-α therapy for therapeutic efficacy. Furthermore, we performed association analysis of the logOR_Score and clinical features, such as disease activity and immune microenvironment.

RESULTS

A total of 2522 responsive and 1824 nonresponsive genes were identified from the integrated data set. Responsive genes were significantly enriched in metabolism-related pathways, whereas nonresponsive ones were associated with immune response-related pathways. The logOR_Score enabled the accurate prediction of the therapeutic efficacy of anti-TNF-α in 4 independent patient cohorts and outperformed the predictions made based on 6 transcriptome-based signatures. In terms of clinical features, the logOR_Score correlated highly with the activity of UC. From an immune microenvironment perspective, logOR_Scores of CD8+IL-17+ T cells, follicular B cells, and innate lymphoid cells significantly decreased in inflamed UC tissue.

CONCLUSIONS

The de novo response-associated transcription signature may provide novel insights into the personalized treatment of patients with UC. Comprehensive analyses of the response-related subtypes and the association between logOR_Score and clinical features and immune microenvironment may provide insights into the underlying UC pathogenesis.

Integration of Vitreous Lipidomics and Metabolomics for Comprehensive Understanding of the Pathogenesis of Proliferative Diabetic Retinopathy

As a vision-threatening complication of diabetes mellitus (DM), proliferative diabetic retinopathy (PDR) is associated with sustained metabolic disorders. Herein, we collected the vitreous cavity fluid of 49 patients with PDR and 23 control subjects without DM for metabolomics and lipidomics analyses. Multivariate statistical methods were performed to explore relationships between samples. For each group of metabolites, gene set variation analysis scores were generated, and we constructed a lipid network by using weighted gene co-expression network analysis. The association between lipid co-expression modules and metabolite set scores was investigated using the two-way orthogonal partial least squares (O2PLS) model. A total of 390 lipids and 314 metabolites were identified. Multivariate statistical analysis revealed significant vitreous metabolic and lipid differences between PDR and controls. Pathway analysis showed that 8 metabolic processes might be associated with the development of PDR, and 14 lipid species were found to be altered in PDR patients. Combining metabolomics and lipidomics, we identified fatty acid desaturase 2 (FADS2) as an important potential contributor to the pathogenesis of PDR. Collectively, this study integrates vitreous metabolomics and lipidomics to comprehensively unravel metabolic dysregulation and identifies genetic variants associated with altered lipid species in the mechanistic pathways for PDR.

The module triad: a novel network biology approach to utilize patients' multi-omics data for target discovery in ulcerative colitis

Tumor necrosis factor-[Formula: see text] inhibitors (TNFi) have been a standard treatment in ulcerative colitis (UC) for nearly 20 years. However, insufficient response rate to TNFi therapies along with concerns around their immunogenicity and inconvenience of drug delivery through injections calls for development of UC drugs targeting alternative proteins. Here, we propose a multi-omic network biology method for prioritization of protein targets for UC treatment. Our method identifies network modules on the Human Interactome-a network of protein-protein interactions in human cells-consisting of genes contributing to the predisposition to UC (Genotype module), genes whose expression needs to be modulated to achieve low disease activity (Response module), and proteins whose perturbation alters expression of the Response module genes to a healthy state (Treatment module). Targets are prioritized based on their topological relevance to the Genotype module and functional similarity to the Treatment module. We demonstrate utility of our method in UC and other complex diseases by efficiently recovering the protein targets associated with compounds in clinical trials and on the market . The proposed method may help to reduce cost and time of drug development by offering a computational screening tool for identification of novel and repurposing therapeutic opportunities in UC and other complex diseases.

Longitudinal multi-omics analysis identifies early blood-based predictors of anti-TNF therapy response in inflammatory bowel disease

Background and aims

Treatment with tumor necrosis factor α (TNFα) antagonists in IBD patients suffers from primary non-response rates of up to 40%. Biomarkers for early prediction of therapy success are missing. We investigated the dynamics of gene expression and DNA methylation in blood samples of IBD patients treated with the TNF antagonist infliximab and analyzed the predictive potential regarding therapy outcome.

Methods

We performed a longitudinal, blood-based multi-omics study in two prospective IBD patient cohorts receiving first-time infliximab therapy (discovery: 14 patients, replication: 23 patients). Samples were collected at up to 7 time points (from baseline to 14 weeks after therapy induction). RNA-sequencing and genome-wide DNA methylation data were analyzed and correlated with clinical remission at week 14 as a primary endpoint.

Results

We found no consistent ex ante predictive signature across the two cohorts. Longitudinally upregulated transcripts in the non-remitter group comprised TH2- and eosinophil-related genes including ALOX15, FCER1A, and OLIG2. Network construction identified transcript modules that were coherently expressed at baseline and in non-remitting patients but were disrupted at early time points in remitting patients. These modules reflected processes such as interferon signaling, erythropoiesis, and platelet aggregation. DNA methylation analysis identified remission-specific temporal changes, which partially overlapped with transcriptomic signals. Machine learning approaches identified features from differentially expressed genes cis-linked to DNA methylation changes at week 2 as a robust predictor of therapy outcome at week 14, which was validated in a publicly available dataset of 20 infliximab-treated CD patients.

Conclusions

Integrative multi-omics analysis reveals early shifts of gene expression and DNA methylation as predictors for efficient response to anti-TNF treatment. Lack of such signatures might be used to identify patients with IBD unlikely to benefit from TNF antagonists at an early time point.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01112-z.

Current Progress and Future Perspectives on the Use of Bacillus clausii

Bacillus clausii is a probiotic that benefits human health. Its key characteristics include the ability to form spores; the resulting tolerance to heat, acid, and salt ensures safe passage through the human gastrointestinal tract with no loss of cells. Although B. clausii has been widely used for many decades, the beneficial properties of other probiotics, such as Lactobacillus spp. and Bifidobacterium spp., are better disseminated in the literature. In this review, we summarize the physiological, antimicrobial, and immunomodulatory properties of probiotic B. clausii strains. We also describe findings from studies that have investigated B. clausii probiotics from the perspective of quality and safety. We highlight innovative properties based on biochemical investigations of non-probiotic strains of B. clausii, revealing that B. clausii may have further health benefits in other therapeutic areas.

Proteomic Analysis of Potential Targets for Non-Response to Infliximab in Patients With Ulcerative Colitis

Background: Infliximab (IFX) is a potent therapeutic agent used for the treatment of conventional refractory ulcerative colitis (UC). However, the high non-response rate of IFX brings difficulties to clinical applications. In the context of proteomics research, our study of differentially expressed proteins (DEPs) is essential for non-response to IFX in UC patients and provides powerful insights into underlying drug resistance mechanisms.

Methods: A total of 12 UC patients were divided into responders to IFX (UCinfG), non-responders to IFX (UCinfL), severe UC (UCsevere) without an IFX treatment history, and mild UC (UCmild) without an IFX treatment history. Subsequently, DEPs were identified from intestinal biopsy tissue between responders and non-responders to IFX by a label-free proteomic quantitative approach, and the general principle of functional protein screening was followed to deduce the potential drug targets and predictors for non-response to IFX in UC patients. Meanwhile, these targets excluded DEPs caused by the severity of inflammation for the first time. The differential expressions of candidate protein targets were validated at the gene sequence level using GEO2R analysis of the GEO database and qRT-PCR in some independent cohorts.

Results: A total of 257 DEPs were screened out by mass spectrometry between UCinfG and UCinfL groups, excluding 22 DEPs caused by the severity of inflammation, and compared and verified at the gene sequence level in the Gene Expression Omnibus (GEO) database. Finally, five DEPs, including ACTBL2 (Q562R1), MBL2 (P11226), BPI (P17213), EIF3D (O15371), and CR1 (P17927), were identified as novel drug targets and predictive biomarkers for non-response to IFX. The drug targets were confirmed in the GEO database of the microarray results from three independent cohorts of 70 human intestinal biopsies and validated in qPCR data from 17 colonic mucosal biopsies. Among them, CR1 might affect the activation of the lectin pathway via complement-coated bacteria to play an opsonizing role in inflammation-related pathways closely associated with non-responders to IFX.

Conclusion: This is the first report of proteomics analysis for the identification of novel drug targets based on intestinal biopsy tissue, which is significant for hypotheses for mechanistic investigation that are responsible for non-response to IFX and the development of clinical new pharmaceutical drugs.

Evolving Short- and Long-Term Goals of Management of Inflammatory Bowel Diseases: Getting It Right, Making It Last

Short- and long-term treatment targets in inflammatory bowel diseases (IBDs) evolved during the last decade, shifting from symptom control to endoscopic healing and patient-centered parameters. The STRIDE-II consensus placed these targets on a timeline from initiating treatment and introduced additional targets, normalization of serum and fecal biomarkers, restoration of quality of life, prevention of disability, and, in children, restoration of growth. Transmural healing in Crohn's disease and histologic healing in ulcerative colitis currently serve as adjunct measures to gauge remission depth. However, whether early treatment according to a treat-to-target paradigm affects the natural course of IBD remains unclear, leading to the need for prospective disease-modification trials. The SPIRIT consensus defined the targets for these trials to assess the long-term impact of early treatment on quality of life, disability, disease complications, risk of neoplastic lesions, and mortality. As further data emerge about the risk-benefit balance of aiming toward deeper healing, the targets in treating IBDs may continue to shift.

Artificial Neural Network Analysis-Based Immune-Related Signatures of Primary Non-Response to Infliximab in Patients With Ulcerative Colitis

Infliximab (IFX) is an effective medication for ulcerative colitis (UC) patients. However, one-third of UC patients show primary non-response (PNR) to IFX. Our study analyzed three Gene Expression Omnibus (GEO) datasets and used the RobustRankAggreg (RRA) algorithm to assist in identifying differentially expressed genes (DEGs) between IFX responders and non-responders. Then, an artificial intelligence (AI) technology, artificial neural network (ANN) analysis, was applied to validate the predictive value of the selected genes. The results showed that the combination of CDX2, CHP2, HSD11B2, RANK, NOX4, and VDR is a good predictor of patients' response to IFX therapy. The range of repeated overall area under the receiver-operating characteristic curve (AUC) was 0.850 ± 0.103. Moreover, we used an independent GEO dataset to further verify the value of the six DEGs in predicting PNR to IFX, which has a range of overall AUC of 0.759 ± 0.065. Since protein detection did not require fresh tissue and can avoid multiple biopsies, our study tried to discover whether the key information, analyzed by RNA levels, is suitable for protein detection. Therefore, immunohistochemistry (IHC) staining of colonic biopsy tissues from UC patients treated with IFX and a receiver-operating characteristic (ROC) analysis were used to further explore the clinical application value of the six DEGs at the protein level. The IHC staining of colon tissues from UC patients confirmed that VDR and RANK are significantly associated with IFX efficacy. Total IHC scores lower than 5 for VDR and lower than 7 for RANK had an AUC of 0.828 (95% CI: 0.665-0.991, p = 0.013) in predicting PNR to IFX. Collectively, we identified a predictive RNA model for PNR to IFX and explored an immune-related protein model based on the RNA model, including VDR and RANK, as a predictor of IFX non-response, and determined the cutoff value. The result showed a connection between the RNA and protein model, and both two models were available. However, the composite signature of VDR and RANK is more conducive to clinical application, which could be used to guide the preselection of patients who might benefit from pharmacological treatment in the future.

The influence of cytokines on the complex pathology of ulcerative colitis

Ulcerative colitis (UC) specifically affects the colon and rectum through multifactorial mechanisms associated with genetic alterations, environmental factors, microbiota, and mucosal immune dysregulation. In patients with corticosteroid-refractory UC, current therapies primarily employ antibodies against tumor necrosis factor-α, α4β7 integrin, and interleukin (IL)-12/23 p40; and a small-molecule Janus kinase inhibitor. Despite these revolutionary molecular targeting therapies introduced during the last two decades, 30%-55% of patients fail to respond such molecular targeting agents in the induction phase, requiring changes in treatment. Here we review basic and clinical research aimed to address this problem, focusing on the pathogenic effects of cytokines produced by innate and adaptive immune cells. For example, IL-1β, IL-6, tumor necrosis factor-α, T helper (Th) 1-, Th2-, and Th17-associated cytokines are expressed at relatively higher levels in the intestinal tissues of patients with UC. However, their expression levels depend on disease stage and patient characteristics. The complex pathology of UC may induce differences in responses to therapy. The findings of such studies strongly support the argument that future targeted therapies must focus on differences in cytokine levels associated with the stages of UC as well as on the distinct cytokine expression profiles of individual patients.

A Multi-mRNA Prognostic Signature for Anti-TNFα Therapy Response in Patients with Inflammatory Bowel Disease

BACKGROUND

Anti-TNF-alpha (anti-TNFα) therapies have transformed the care and management of inflammatory bowel disease (IBD). However, they are expensive and ineffective in greater than 50% of patients, and they increase the risk of infections, liver issues, arthritis, and lymphoma. With 1.6 million Americans suffering from IBD and global prevalence on the rise, there is a critical unmet need in the use of anti-TNFα therapies: a test for the likelihood of therapy response. Here, as a proof-of-concept, we present a multi-mRNA signature for predicting response to anti-TNFα treatment to improve the efficacy and cost-to-benefit ratio of these biologics.

METHODS

We surveyed public data repositories and curated four transcriptomic datasets (n = 136) from colonic and ileal mucosal biopsies of IBD patients (pretreatment) who were subjected to anti-TNFα therapy and subsequently adjudicated for response. We applied a multicohort analysis with a leave-one-study-out (LOSO) approach, MetaIntegrator, to identify significant differentially expressed (DE) genes between responders and non-responders and then used a greedy forward search to identify a parsimonious gene signature. We then calculated an anti-TNFα response (ATR) score based on this parsimonious gene signature to predict responder status and assessed discriminatory performance via an area-under-receiver operating-characteristic curve (AUROC).

RESULTS

We identified 324 significant DE genes between responders and non-responders. The greedy forward search yielded seven genes that robustly distinguish anti-TNFα responders from non-responders, with an AUROC of 0.88 (95% CI: 0.70-1). The Youden index yielded a mean sensitivity of 91%, mean specificity of 76%, and mean accuracy of 86%.

CONCLUSIONS

Our findings suggest that there is a robust transcriptomic signature for predicting anti-TNFα response in mucosal biopsies from IBD patients prior to treatment initiation. This seven-gene signature should be further investigated for its potential to be translated into a predictive test for clinical use.

Sputum macrophage diversity and activation in asthma: Role of severity and inflammatory phenotype

BACKGROUND

Macrophages control innate and acquired immunity, but their role in severe asthma remains ill-defined. We investigated gene signatures of macrophage subtypes in the sputum of 104 asthmatics and 16 healthy volunteers from the U-BIOPRED cohort.

METHODS

Forty-nine gene signatures (modules) for differentially stimulated macrophages, one to assess lung tissue-resident cells (TR-Mφ) and two for their polarization (classically and alternatively activated macrophages: M1 and M2, respectively) were studied using gene set variation analysis. We calculated enrichment scores (ES) across severity and previously identified asthma transcriptome-associated clusters (TACs).

RESULTS

Macrophage numbers were significantly decreased in severe asthma compared to mild-moderate asthma and healthy volunteers. The ES for most modules were also significantly reduced in severe asthma except for 3 associated with inflammatory responses driven by TNF and Toll-like receptors via NF-κB, eicosanoid biosynthesis via the lipoxygenase pathway and IL-2 biosynthesis (all P < .01). Sputum macrophage number and the ES for most macrophage signatures were higher in the TAC3 group compared to TAC1 and TAC2 asthmatics. However, a high enrichment was found in TAC1 for 3 modules showing inflammatory pathways linked to Toll-like and TNF receptor activation and arachidonic acid metabolism (P < .001) and in TAC2 for the inflammasome and interferon signalling pathways (P < .001). Data were validated in the ADEPT cohort. Module analysis provides additional information compared to conventional M1 and M2 classification. TR-Mφ were enriched in TAC3 and associated with mitochondrial function.

CONCLUSIONS

Macrophage activation is attenuated in severe granulocytic asthma highlighting defective innate immunity except for specific subsets characterized by distinct inflammatory pathways.

Instability of sputum molecular phenotypes in U-BIOPRED severe asthma

The Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project has described phenotypic differences of severe asthma using a systems biology approach. We obtained three molecular phenotypes termed transcription-associated clusters (TACs) using hierarchical clustering of differentially expressed transcripts between T2-high and T2-low [1]. TAC1 was characterised by receptors IL33R, CCR3 and TSLPR, with the highest enrichment of gene signatures for IL-13/type-2 (T2) inflammation with sputum eosinophilia; TAC2 by inflammasome-associated genes, interferon-α (IFN-α) and tumour necrosis factor-α (TNF-α)-associated genes with sputum neutrophilia; and TAC3 by metabolic and mitochondrial function genes with pauci-granulocytic inflammation. Given that sputum eosinophilia may vary with time in many asthmatic subjects [2, 3], we hypothesised that TAC status may also change with time.

At 1 year, 45% of severe asthma change molecular phenotype as determined by sputum transcriptomic analysis. Together with concomitant shift in sputum granulocytic markers, this may indicate variability of driving mechanisms in this unstable group.https://bit.ly/35aj489

Vitamin D Metabolism Is Dysregulated in Asthma and Chronic Obstructive Pulmonary Disease

Rationale: Vitamin D deficiency is common in patients with asthma and chronic obstructive pulmonary disease (COPD). Low 25-hydroxyvitamin D (25[OH]D) levels may represent a cause or a consequence of these conditions.Objectives: To determine whether vitamin D metabolism is altered in asthma or COPD.Methods: We conducted a longitudinal study in 186 adults to determine whether the 25(OH)D response to six oral doses of 3 mg vitamin D₃, administered over 1 year, differed between those with asthma or COPD versus control subjects. Serum concentrations of vitamin D₃, 25(OH)D₃, and 1α,25-dihydroxyvitamin D₃ (1α,25[OH]₂D₃) were determined presupplementation and postsupplementation in 93 adults with asthma, COPD, or neither condition, and metabolite-to-parent compound molar ratios were compared between groups to estimate hydroxylase activity. Additionally, we analyzed 14 datasets to compare expression of 1α,25(OH)₂D₃-inducible gene expression signatures in clinical samples taken from adults with asthma or COPD versus control subjects.Measurements and Main Results: The mean postsupplementation 25(OH)D increase in participants with asthma (20.9 nmol/L) and COPD (21.5 nmol/L) was lower than in control subjects (39.8 nmol/L; P = 0.001). Compared with control subjects, patients with asthma and COPD had lower molar ratios of 25(OH)D₃-to-vitamin D₃ and higher molar ratios of 1α,25(OH)₂D₃-to-25(OH)D₃ both presupplementation and postsupplementation (P ≤ 0.005). Intergroup differences in 1α,25(OH)₂D₃-inducible gene expression signatures were modest and variable if statistically significant.Conclusions: Attenuation of the 25(OH)D response to vitamin D supplementation in asthma and COPD associated with reduced molar ratios of 25(OH)D₃-to-vitamin D₃ and increased molar ratios of 1α,25(OH)₂D₃-to-25(OH)D₃ in serum, suggesting that vitamin D metabolism is dysregulated in these conditions.

Integrated Gene Expression Profiling Analysis Reveals Probable Molecular Mechanism and Candidate Biomarker in Anti-TNFα Non-Response IBD Patients

Purpose

To explore the molecular mechanism and search for candidate biomarkers in the gene expression profile of IBD patients associated with the response to anti-TNFα agents.

Methods

Differentially expressed genes (DEGs) of response vs non-response IBD patients in datasets GSE12251, GSE16879, and GSE23597 were integrated using NetworkAnalyst. We conducted functional enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and extracted hub genes from the protein–protein interaction network. The proportion of immune cell types was estimated via CIBERSORT. ROC curve analysis and binomial Lasso regression were applied to assess the expression level of hub genes in datasets GSE12251, GSE16879, and GSE23597, and another two datasets GSE107865 and GSE42296.

Results

A total of 287 DEGs were obtained from the integrated dataset. They were enriched in 14 Gene Ontology terms and 11 KEGG pathways. Polarization from M2 to M1 macrophages was relatively high in non-response individuals. We found nine hub genes (TLR4, TLR1, TLR8, CCR1, CD86, CCL4, HCK, and FCGR2A), mainly related to the interaction between Toll-like Receptor (TLR) pathway and FcγR signaling in non-response anti-TNFα individuals. FCGR2A, HCK, TLR1, TLR4, TLR8, and CCL4 show great value for prediction in intestinal tissue. Besides, FCGR2A, HCK, and TLR8 might be candidate blood biomarkers of anti-TNFα non-response IBD patients.

Conclusion

Over-activated interaction between FcγR-TLR axis in the innate immune cells of IBD patients might be used to identify non-response individuals and increased our understanding of resistance to anti-TNFα therapy.

Transcriptional Effects of Ozone and Impact on Airway Inflammation

Epidemiological and challenge studies in healthy subjects and in individuals with asthma highlight the health impact of environmental ozone even at levels considered safe. Acute ozone exposure in man results in sputum neutrophilia in 30% of subjects particularly young children, females, and those with ongoing cardiopulmonary disease. This may be associated with systemic inflammation although not in all cases. Chronic exposure amplifies these effects and can result in the formation of asthma-like symptoms and immunopathology. Asthmatic patients who respond to ozone (responders) induce a greater number of genes in bronchoalveolar (BAL) macrophages than healthy responders with up-regulation of inflammatory and immune pathways under the control of cytokines and chemokines and the enhanced expression of remodeling and repair programmes including those associated with protease imbalances and cell-cell adhesion. These pathways are under the control of several key transcription regulatory factors including nuclear factor (NF)-κB, anti-oxidant factors such as nuclear factor (erythroid-derived 2)-like 2 NRF2, the p38 mitogen activated protein kinase (MAPK), and priming of the immune system by up-regulating toll-like receptor (TLR) expression. Murine and cellular models of acute and chronic ozone exposure recapitulate the inflammatory effects seen in humans and enable the elucidation of key transcriptional pathways. These studies emphasize the importance of distinct transcriptional networks in driving the detrimental effects of ozone. Studies indicate the critical role of mediators including IL-1, IL-17, and IL-33 in driving ozone effects on airway inflammation, remodeling and hyperresponsiveness. Transcription analysis and proof of mechanisms studies will enable the development of drugs to ameliorate the effects of ozone exposure in susceptible individuals.