Cross-species transcriptomic signatures predict response to MK2 inhibition in mouse models of chronic inflammation

Translational disease modeling of peripheral blood identifies type 2 diabetes biomarkers predictive of Alzheimer's disease

Type 2 diabetes (T2D) is a significant risk factor for Alzheimer's disease (AD). Despite multiple studies reporting this connection, the mechanism by which T2D exacerbates AD is poorly understood. It is challenging to design studies that address co-occurring and comorbid diseases, limiting the number of existing evidence bases. To address this challenge, we expanded the applications of a computational framework called Translatable Components Regression (TransComp-R), initially designed for cross-species translation modeling, to perform cross-disease modeling to identify biological programs of T2D that may exacerbate AD pathology. Using TransComp-R, we combined peripheral blood-derived T2D and AD human transcriptomic data to identify T2D principal components predictive of AD status. Our model revealed genes enriched for biological pathways associated with inflammation, metabolism, and signaling pathways from T2D principal components predictive of AD. The same T2D PC predictive of AD outcomes unveiled sex-based differences across the AD datasets. We performed a gene expression correlational analysis to identify therapeutic hypotheses tailored to the T2D-AD axis. We identified six T2D and two dementia medications that induced gene expression profiles associated with a non-T2D or non-AD state. We next assessed our blood-based T2DxAD biomarker signature in post-mortem human AD and control brain gene expression data from the hippocampus, entorhinal cortex, superior frontal gyrus, and postcentral gyrus. Using partial least squares discriminant analysis, we identified a subset of genes from our cross-disease blood-based biomarker panel that significantly separated AD and control brain samples. Finally, we validated our findings using single cell RNA-sequencing blood data of AD and healthy individuals and found erythroid cells contained the most gene expression signatures to the T2D PC. Our methodological advance in cross-disease modeling identified biological programs in T2D that may predict the future onset of AD in this population. This, paired with our therapeutic gene expression correlational analysis, also revealed alogliptin, a T2D medication that may help prevent the onset of AD in T2D patients.

Computational Translation of Mouse Models of Osteoarthritis Predicts Human Disease

Objective

Translation of biological insights from preclinical studies to human disease is a pressing challenge in biomedical research, including in osteoarthritis. Translatable Components Regression (TransComp-R) is a computational framework that has previously been used to synthesize preclinical and human OA data to identify biological pathways predictive of human disease conditions. We aimed to evaluate the translatability of two common murine models of post-traumatic osteoarthritis - surgical destabilization of the medial meniscus (DMM) and noninvasive anterior cruciate ligament rupture (ACLR) - to transcriptomics cartilage data from human OA outcomes.

Design

Transcriptomics cartilage data of DMM and ACLR mouse and human data was acquired from Gene Expression Omnibus. TransComp-R was used to project human OA data into a mouse model (DMM or ACLR) principal component analysis space. The principal components (PCs) were regressed against human OA conditions using increasing complexity of linear regression models incorporating human demographic covariates of OA, sex, and age. Biological pathways of the mouse PCs that significantly stratified human OA and control groups were then interpreted using Gene Set Enrichment Analysis.

Results

From the TransComp-R model, we identified different enriched biological pathways across DMM and ACLR models. While PCs among the DMM models revealed pathways associated with cell signaling and metabolism, ACLR PCs represented immune function and cellular pathways associated with OA condition. The immune pathways presented in the ACLR further highlighted the potential relevance of the OA pathways observed in human conditions.

Conclusions

The ACLR mouse model more successfully predicted human OA conditions, particularly with the human control groups without a history of joint injury or disease. Cross-species translational approaches support the selection of preclinical models intended for therapeutic discovery and pathway analysis in humans.

MK2 Inhibition in CD4+ T Cells Protects Against IFNγ and IL-17A, Chronic Inflammation, and Fibrosis in Inflammatory Bowel Disease Models

BACKGROUND

CD4+ T cells contribute to chronic inflammation and fibrosis in inflammatory bowel disease (IBD), but the cellular mechanisms remain elusive. We have found that the mitogen-activated protein kinase 2 (MK2) pathway plays a major role in inflammation and overall pathology in IBD. Thus, here, we examined the role of MK2 in regulating CD4+ T cell responses in IBD models.

METHODS

Interleukin-10 (IL-10) knockout (KO) mice treated with MK2 inhibitors (MK2i) and CD4-specific MK2 knockdown mice treated with chronic dextran sodium sulfate (DSS) treatments were used to examine inflammation and fibrosis by multiplex array, gene expression, flow cytometry, and histology. Human tissues were treated with MK2i to examine Th1 and Th17 markers.

RESULTS

IL-10 KO mice treated with MK2i therapeutically showed significantly reduced interferon gamma (IFNγ) and interleukin-17A (IL-17A) and a significantly reduced number of IFNγ+ and IL-17A+ producing CD4+ T cells by flow cytometry. To investigate the direct role of MK2 in CD4+ T cells during IBD, we utilized CD4-specific MK2 knockdown mice in chronic DSS colitis. A decrease in colonic inflammation, IFNγ and IL-17, pro-fibrotic genes, and extracellular matrix deposition was observed in mice with MK2 knockdown in CD4+ T cells compared to control mice. Additionally, IL-17A and IFNγ directly regulated the expression of fibrosis genes in colon tissues.

CONCLUSIONS

The MK2 pathway regulates inflammatory CD4+ T cells and fibrosis in IBD models and is a potential therapeutic target.

Mouse-to-human modeling of microglia single-nuclei transcriptomics identifies immune signaling pathways and potential therapeutic candidates associated with Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by memory loss and behavior change. Studies have found that dysregulation of microglial cells is pivotal to AD pathology. These mechanisms have been studied in mouse models to uncover potential therapeutic biomarkers. Despite these findings, there are limitations to the translatable biological information from mice to humans due to differences in physiology, timeline of disease, and the heterogeneity of humans. To address the inter-species discrepancies, we developed a novel implementation of the Translatable Components Regression (TransComp-R) framework, which integrated microglia single-nuclei mouse and human transcriptomics data to identify biological pathways in mice predictive of human AD. We compared model variations with sparse and traditional principal component analysis. We found that both dimensionality reduction techniques encoded similar AD disease biology on mouse principal components with limited differences in technical performance. Several mouse sparse principal components explained high amounts of variance in humans and significantly differentiated human AD from control microglial cells. Additionally, we identified FDA-approved medications that induced gene expression profiles correlated with projections of healthy human microglia on mouse principal components. Such medications included cabergoline, selumetinib, and palbociclib. This computational framework may support uncovering cross-species disease insights and candidate pharmacological solutions from single-cell datasets.

Cross-disease modeling of peripheral blood identifies biomarkers of type 2 diabetes predictive of Alzheimer's disease

Type 2 diabetes (T2D) is a significant risk factor for Alzheimer's disease (AD). Despite multiple studies reporting this connection, the mechanism by which T2D exacerbates AD is poorly understood. It is challenging to design studies that address co-occurring and comorbid diseases, limiting the number of existing evidence bases. To address this challenge, we expanded the applications of a computational framework called Translatable Components Regression (TransComp-R), initially designed for cross-species translation modeling, to perform cross-disease modeling to identify biological programs of T2D that may exacerbate AD pathology. Using TransComp-R, we combined peripheral blood-derived T2D and AD human transcriptomic data to identify T2D principal components predictive of AD status. Our model revealed genes enriched for biological pathways associated with inflammation, metabolism, and signaling pathways from T2D principal components predictive of AD. The same T2D PC predictive of AD outcomes unveiled sex-based differences across the AD datasets. We performed a gene expression correlational analysis to identify therapeutic hypotheses tailored to the T2D-AD axis. We identified six T2D and two dementia medications that induced gene expression profiles associated with a non-T2D or non-AD state. Finally, we assessed our blood-based T2DxAD biomarker signature in post-mortem human AD and control brain gene expression data from the hippocampus, entorhinal cortex, superior frontal gyrus, and postcentral gyrus. Using partial least squares discriminant analysis, we identified a subset of genes from our cross-disease blood-based biomarker panel that significantly separated AD and control brain samples. Our methodological advance in cross-disease modeling identified biological programs in T2D that may predict the future onset of AD in this population. This, paired with our therapeutic gene expression correlational analysis, also revealed alogliptin, a T2D medication that may help prevent the onset of AD in T2D patients.

Increased Activity of MAPKAPK2 within Mesenchymal Cells as a Target for Inflammation-Associated Fibrosis in Crohn's Disease

BACKGROUND

Mesenchymal stromal cells are suggested to play a critical role in Crohn's disease [CD]-associated fibrosis. MAPKAPK2 [MK2] has emerged as a potential therapeutic target to reduce inflammation in CD. However, the cell-specific pattern of phospho-MK2 activation and its role in CD-associated fibrosis are unknown. The objectives of this study were to evaluate cell-specific changes in MK2 activity between predominantly inflammatory CD vs CD with fibrotic complications and define the role of stromal cell-specific MK2 activation in CD-associated fibrosis.

METHODS

CD tissue, CD tissue-derived mesenchymal stromal cells known as myo-/fibroblasts [CD-MFs], and fibroblast-specific MK2 conditional knockout [KO] mice were used.

RESULTS

In the inflamed area of predominantly inflammatory CD, high MK2 activity was equally distributed between mesenchymal and haematopoietic cells. By contrast, in CD with fibrotic complications, high MK2 activity was mostly associated with mesenchymal stromal cells. Using ex vivo CD tissue explants and an IL-10KO murine colitis model, we demonstrated that pro-fibrotic responses are significantly reduced by treatment with the MK2 inhibitor PF-3644022. Inhibition of MK2 activity in primary cultures of CD-MFs significantly reduced basal and TGF-β1-induced profibrotic responses. Using fibroblast-specific MK2 knockout mice in chronic dextran saline sulphate colitis, we demonstrated that fibroblast intrinsic MK2 signalling is among the key processes involved in the chronic inflammation-induced profibrotic responses.

CONCLUSIONS

Our data suggest that activation of MK2 within fibroblasts contributes to the chronic inflammation-induced fibrosis in CD and that targeting MK2 has potential for the development of novel therapeutic approaches for fibrosis in CD.

Key advances in vaccine development for tuberculosis-success and challenges

Breakthrough findings in the clinical and preclinical development of tuberculosis (TB) vaccines have galvanized the field and suggest, for the first time since the development of bacille Calmette-Guérin (BCG), that a novel and protective TB vaccine is on the horizon. Here we highlight the TB vaccines that are in the development pipeline and review the basis for optimism in both the clinical and preclinical space. We describe immune signatures that could act as immunological correlates of protection (CoP) to facilitate the development and comparison of vaccines. Finally, we discuss new animal models that are expected to more faithfully model the pathology and complex immune responses observed in human populations.