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1.
J Neuroinflammation ; 21(1): 9, 2024 Jan 04.
Article in English | MEDLINE | ID: mdl-38178237

ABSTRACT

Sepsis is a life-threatening state that arises due to a hyperactive inflammatory response stimulated by infection and rarely other insults (e.g., non-infections tissue injury). Although changes in several proinflammatory cytokines and signals are documented in humans and small animal models, far less is known about responses within affected tissues of large animal models. We sought to understand the changes that occur during the initial stages of inflammation by administering intravenous lipopolysaccharide (LPS) to Yorkshire pigs and assessing transcriptomic alterations in the brain, kidney, and whole blood. Robust transcriptional alterations were found in the brain, with upregulated responses enriched in inflammatory pathways and downregulated responses enriched in tight junction and blood vessel functions. Comparison of the inflammatory response in the pig brain to a similar mouse model demonstrated some overlapping changes but also numerous differences, including oppositely dysregulated genes between species. Substantial changes also occurred in the kidneys following LPS with several enriched upregulated pathways (cytokines, lipids, unfolded protein response, etc.) and downregulated gene sets (tube morphogenesis, glomerulus development, GTPase signal transduction, etc.). We also found significant dysregulation of genes in whole blood that fell into several gene ontology categories (cytokines, cell cycle, neutrophil degranulation, etc.). We observed a strong correlation between the brain and kidney responses, with significantly shared upregulated pathways (cytokine signaling, cell death, VEGFA pathways) and downregulated pathways (vasculature and RAC1 GTPases). In summary, we have identified a core set of shared genes and pathways in a pig model of systemic inflammation.


Subject(s)
Endotoxemia , Humans , Mice , Swine , Animals , Endotoxemia/chemically induced , Lipopolysaccharides/toxicity , Cytokines/metabolism , Kidney/metabolism , Disease Models, Animal , Inflammation/metabolism , Brain/metabolism
2.
J Exp Med ; 221(2)2024 Feb 05.
Article in English | MEDLINE | ID: mdl-38226975

ABSTRACT

Aducanumab, an anti-amyloid immunotherapy for Alzheimer's disease, efficiently reduces Aß, though its plaque clearance mechanisms, long-term effects, and effects of discontinuation are not fully understood. We assessed the effect of aducanumab treatment and withdrawal on Aß, neuritic dystrophy, astrocytes, and microglia in the APP/PS1 amyloid mouse model. We found that reductions in amyloid and neuritic dystrophy during acute treatment were accompanied by microglial and astrocytic activation, and microglial recruitment to plaques and adoption of an aducanumab-specific pro-phagocytic and pro-degradation transcriptomic signature, indicating a role for microglia in aducanumab-mediated Aß clearance. Reductions in Aß and dystrophy were sustained 15 but not 30 wk after discontinuation, and reaccumulation of plaques coincided with loss of the microglial aducanumab signature and failure of microglia to reactivate. This suggests that despite the initial benefit from treatment, microglia are unable to respond later to restrain plaque reaccumulation, making further studies on the effect of amyloid-directed immunotherapy withdrawal crucial for assessing long-term safety and efficacy.


Subject(s)
Antibodies, Monoclonal, Humanized , Microglia , Animals , Mice , Immunotherapy , Phagocytes , Plaque, Amyloid
3.
Blood Cancer Discov ; 5(1): 34-55, 2024 01 08.
Article in English | MEDLINE | ID: mdl-37767768

ABSTRACT

Multiple myeloma (MM) is a malignancy that is often driven by MYC and that is sustained by IRF4, which are upregulated by super-enhancers. IKZF1 and IKZF3 bind to super-enhancers and can be degraded using immunomodulatory imide drugs (IMiD). Successful IMiD responses downregulate MYC and IRF4; however, this fails in IMiD-resistant cells. MYC and IRF4 downregulation can also be achieved in IMiD-resistant tumors using inhibitors of BET and EP300 transcriptional coactivator proteins; however, in vivo these drugs have a narrow therapeutic window. By combining IMiDs with EP300 inhibition, we demonstrate greater downregulation of MYC and IRF4, synergistic killing of myeloma in vitro and in vivo, and an increased therapeutic window. Interestingly, this potent combination failed where MYC and IRF4 expression was maintained by high levels of the AP-1 factor BATF. Our results identify an effective drug combination and a previously unrecognized mechanism of IMiD resistance. SIGNIFICANCE: These results highlight the dependence of MM on IKZF1-bound super-enhancers, which can be effectively targeted by a potent therapeutic combination pairing IMiD-mediated degradation of IKZF1 and IKZF3 with EP300 inhibition. They also identify AP-1 factors as an unrecognized mechanism of IMiD resistance in MM. See related article by Neri, Barwick, et al., p. 56. See related commentary by Yun and Cleveland, p. 5. This article is featured in Selected Articles from This Issue, p. 4.


Subject(s)
Multiple Myeloma , Humans , Multiple Myeloma/drug therapy , Multiple Myeloma/genetics , Lenalidomide/pharmacology , Lenalidomide/therapeutic use , Transcription Factor AP-1/therapeutic use , Drug Combinations , Immunomodulating Agents
4.
Mol Psychiatry ; 27(3): 1839-1847, 2022 03.
Article in English | MEDLINE | ID: mdl-34983929

ABSTRACT

The choroid plexus, a tissue responsible for producing cerebrospinal fluid, is found predominantly in the lateral and fourth ventricles of the brain. This highly vascularized and ciliated tissue is made up of specialized epithelial cells and capillary networks surrounded by connective tissue. Given the complex structure of the choroid plexus, this can potentially result in contamination during routine tissue dissection. Bulk and single-cell RNA sequencing studies, as well as genome-wide in situ hybridization experiments (Allen Brain Atlas), have identified several canonical markers of choroid plexus such as Ttr, Folr1, and Prlr. We used the Ttr gene as a marker to query the Gene Expression Omnibus database for transcriptome studies of brain tissue and identified at least some level of likely choroid contamination in numerous studies that could have potentially confounded data analysis and interpretation. We also analyzed transcriptomic datasets from human samples from Allen Brain Atlas and the Genotype-Tissue Expression (GTEx) database and found abundant choroid contamination, with regions in closer proximity to choroid more likely to be impacted such as hippocampus, cervical spinal cord, substantia nigra, hypothalamus, and amygdala. In addition, analysis of both the Allen Brain Atlas and GTEx datasets for differentially expressed genes between likely "high contamination" and "low contamination" groups revealed a clear enrichment of choroid plexus marker genes and gene ontology pathways characteristic of these ciliated choroid cells. Inclusion of these contaminated samples could result in biological misinterpretation or simply add to the statistical noise and mask true effects. We cannot assert that Ttr or other genes/proteins queried in targeted assays are artifacts from choroid contamination as some of these differentials may be due to true biological effects. However, for studies that have an unequal distribution of choroid contamination among groups, investigators may wish to remove contaminated samples from analyses or incorporate choroid marker gene expression into their statistical modeling. In addition, we suggest that a simple RT-qPCR or western blot for choroid markers would mitigate unintended choroid contamination for any experiment, but particularly for samples intended for more costly omic profiling. This study highlights an unexpected problem for neuroscientists, but it is also quite possible that unintended contamination of adjacent structures occurs during dissections for other tissues but has not been widely recognized.


Subject(s)
Brain , Choroid Plexus , Biomarkers/metabolism , Brain/metabolism , Choroid Plexus/metabolism , Folate Receptor 1/metabolism , Hippocampus/metabolism , Humans , Transcriptome/genetics
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