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Multicohort Analysis Identifies Monocyte Gene Signatures to Accurately Monitor Subset-Specific Changes in Human Diseases.

ABSTRACT: Monocytes are crucial regulators of inflammation, and are characterized by three distinct subsets in humans, of which classical and non-classical are the most abundant. Different subsets carry out different functions and have been previously associated with multiple inflammatory conditions. Dissecting the contribution of different monocyte subsets to disease is currently limited by samples and cohorts, often resulting in underpowered studies and poor reproducibility. Publicly available transcriptome profiles provide an alternative source of data characterized by high statistical power and real-world heterogeneity. However, most transcriptome datasets profile bulk blood or tissue samples, requiring the use of in silico approaches to quantify changes in cell levels. Here, we integrated 853 publicly available microarray expression profiles of sorted human monocyte subsets from 45 independent studies to identify robust and parsimonious gene expression signatures, consisting of 10 genes specific to each subset. These signatures maintain their accuracy regardless of disease state in an independent cohort profiled by RNA-sequencing and are specific to their respective subset when compared to other immune cells from both myeloid and lymphoid lineages profiled across 6160 transcriptome profiles. Consequently, we show that these signatures can be used to quantify changes in monocyte subsets levels in expression profiles from patients in clinical trials. Finally, we show that proteins encoded by our signature genes can be used in cytometry-based assays to specifically sort monocyte subsets. Our results demonstrate the robustness, versatility, and utility of our computational approach and provide a framework for the discovery of new cellular markers.

SUBMITTER: Vallania F

PROVIDER: S-EPMC8160521 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundTo understand how Plasmodium falciparum malaria is controlled, it is essential to elucidate the transcriptomic responses of the human host in naturally-exposed populations. Various individual studies of the human transcriptomic responses to naturally transmitted P. falciparum infections have been reported with varying results. Multicohort gene expression analysis by aggregating data from diverse populations into a single analysis will increase the reproducibility and reliability of the results.MethodsIn this study, discovery cohorts GSE1124-GPL96, GSE34404, GSE117613, and validation cohort GSE35858 were obtained from the Gene Expression Omnibus. A meta-analysis using data from the multicohort studies was performed to identify the differentially expressed genes (DEGs) between malaria-infected and noninfected individuals using the MetaIntegrator R package. Subsequently, the protein-protein interaction (PPI) networks of the DEGs were constructed using Cytoscape software. Significant modules were selected, and the hub genes were identified using the CytoHubba and MCODE plug-ins. Multicohort WGCNA was conducted to find a correlation between modules and malaria infection. Furthermore, the immune cell profile of the peripheral blood in different groups was identified using ssGSEA.ResultsThese analyses reveal that neutrophil activation, neutrophil-mediated immunity, and neutrophil degranulation are involved in the human response to natural malaria infection. However, neutrophil cell enrichment and activation were not significantly different between mild malaria and severe malaria groups. Malaria infection also downregulates host genes in ribosome synthesis and protein translation and upregulates host cell division-related genes. Furthermore, immune cell profiling analysis shows that activated dendritic cells and type 2 T helper cells are upregulated, while activated B cells, immature B cells, and monocytes are downregulated in the malaria-infected patients relative to the noninfected individuals. Significantly higher enrichment of activated dendritic cell-related genes and significantly lower enrichment of monocyte-related genes are also observed in the peripheral blood of the severe malaria group than in the mild malaria group.ConclusionThese results reveal important molecular signatures of host responses to malaria infections, providing some bases for developing malaria control strategies and protective vaccines.

Project description:Adjuvants boost vaccine responses, enhancing protective immunity against infections that are most common among the very young. Many adjuvants activate innate immunity, some via Toll-Like Receptors (TLRs), whose activities varies with age. Accordingly, characterization of age-specific adjuvant-induced immune responses may inform rational adjuvant design targeting vulnerable populations. In this study, we employed proteomics to characterize the adjuvant-induced changes of secretomes from human newborn and adult monocytes in response to Alum, the most commonly used adjuvant in licensed vaccines; Monophosphoryl Lipid A (MPLA), a TLR4-activating adjuvant component of a licensed Human Papilloma Virus vaccine; and R848 an imidazoquinoline TLR7/8 agonist that is a candidate adjuvant for early life vaccines. Monocytes were incubated in vitro for 24 h with vehicle, Alum, MPLA, or R848 and supernatants collected for proteomic analysis employing liquid chromatography-mass spectrometry (LC-MS) (data available via ProteomeXchange, ID PXD003534). 1894 non-redundant proteins were identified, of which ?30 - 40% were common to all treatment conditions and ?5% were treatment-specific. Adjuvant-stimulated secretome profiles, as identified by cluster analyses of over-represented proteins, varied with age and adjuvant type. Adjuvants, especially Alum, activated multiple innate immune pathways as assessed by functional enrichment analyses. Release of lactoferrin, pentraxin 3, and matrix metalloproteinase-9 was confirmed in newborn and adult whole blood and blood monocytes stimulated with adjuvants alone or adjuvanted licensed vaccines with distinct clinical reactogenicity profiles. MPLA-induced adult monocyte secretome profiles correlated in silico with transcriptome profiles induced in adults immunized with the MPLA-adjuvanted RTS,S malaria vaccine (Mosquirix™). Overall, adjuvants such as Alum, MPLA and R848 give rise to distinct and age-specific monocyte secretome profiles, paralleling responses to adjuvant-containing vaccines in vivo Age-specific in vitro modeling coupled with proteomics may provide fresh insight into the ontogeny of adjuvant action thereby informing targeted adjuvanted vaccine development for distinct age groups.

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Multicohort Analysis Identifies Monocyte Gene Signatures to Accurately Monitor Subset-Specific Changes in Human Diseases.

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