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Journal ArticleDOI

An immune clock of human pregnancy.

TL;DR: These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies.
Abstract: The maintenance of pregnancy relies on finely tuned immune adaptations. We demonstrate that these adaptations are precisely timed, reflecting an immune clock of pregnancy in women delivering at term. Using mass cytometry, the abundance and functional responses of all major immune cell subsets were quantified in serial blood samples collected throughout pregnancy. Cell signaling-based Elastic Net, a regularized regression method adapted from the elastic net algorithm, was developed to infer and prospectively validate a predictive model of interrelated immune events that accurately captures the chronology of pregnancy. Model components highlighted existing knowledge and revealed previously unreported biology, including a critical role for the interleukin-2-dependent STAT5ab signaling pathway in modulating T cell function during pregnancy. These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies.
Citations
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Journal ArticleDOI
TL;DR: The multi-level mechanisms underlying SCI and several risk factors that promote this health-damaging phenotype, including infections, physical inactivity, poor diet, environmental and industrial toxicants and psychological stress are described.
Abstract: Although intermittent increases in inflammation are critical for survival during physical injury and infection, recent research has revealed that certain social, environmental and lifestyle factors can promote systemic chronic inflammation (SCI) that can, in turn, lead to several diseases that collectively represent the leading causes of disability and mortality worldwide, such as cardiovascular disease, cancer, diabetes mellitus, chronic kidney disease, non-alcoholic fatty liver disease and autoimmune and neurodegenerative disorders. In the present Perspective we describe the multi-level mechanisms underlying SCI and several risk factors that promote this health-damaging phenotype, including infections, physical inactivity, poor diet, environmental and industrial toxicants and psychological stress. Furthermore, we suggest potential strategies for advancing the early diagnosis, prevention and treatment of SCI.

1,708 citations

Journal ArticleDOI
TL;DR: The reason why pregnant women are more susceptible to COVID-19 and the potential maternal and fetal complications from an immunological viewpoint is focused on.

341 citations


Cites background from "An immune clock of human pregnancy...."

  • ...Innate immune cells, such as NK cells and monocytes, respond more strongly to viral challenges, while some adaptive immune responses are down-regulated during pregnancy, e.g. decreased numbers of T and B cells (Aghaeepour et al., 2017) ....

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  • ...Recently, Aghaeepour and colleagues (Aghaeepour et al., 2017 ) suggested a precise timing of immunological events in peripheral blood that occurred during full-term pregnancy, named "immune clock."...

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Journal ArticleDOI
TL;DR: What is known about the immunological changes that occur during a normal pregnancy is described and strategies to prevent maternal fatalities due to infections and optimize maternal vaccination to best protect the mother-fetus dyad and the infant after birth are described.
Abstract: The risk and severity of specific infections are increased during pregnancy due to a combination of physiological and immunological changes. Characterizing the maternal immune system during pregnancy is important to understand how the maternal immune system maintains tolerance towards the allogeneic fetus. This may also inform strategies to prevent maternal fatalities due to infections and optimize maternal vaccination to best protect the mother-fetus dyad and the infant after birth. In this review, we describe what is known about the immunological changes that occur during a normal pregnancy.

195 citations

Journal ArticleDOI
TL;DR: In this paper, the authors summarize guidelines for medical/obstetric care and outline future directions for optimization of treatment and preventive strategies for pregnant patients with COVID-19 with the understanding that relevant data are limited and rapidly changing.

156 citations

Journal ArticleDOI
TL;DR: This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities, which provides the frameworks for future studies examining deviations implicated in pregnancy‐related pathologies including preterm birth and preeclampsia.
Abstract: Motivation Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.

113 citations

References
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Journal ArticleDOI
TL;DR: A new method for estimation in linear models called the lasso, which minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant, is proposed.
Abstract: SUMMARY We propose a new method for estimation in linear models. The 'lasso' minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients that are exactly 0 and hence gives interpretable models. Our simulation studies suggest that the lasso enjoys some of the favourable properties of both subset selection and ridge regression. It produces interpretable models like subset selection and exhibits the stability of ridge regression. There is also an interesting relationship with recent work in adaptive function estimation by Donoho and Johnstone. The lasso idea is quite general and can be applied in a variety of statistical models: extensions to generalized regression models and tree-based models are briefly described.

40,785 citations


"An immune clock of human pregnancy...." refers methods in this paper

  • ...An L1 regularization (38) was applied on the b coefficients to reduce the model complexity, such that L(b) = |Y − Xb|(2) + l1|b|1, where l1 is selected by cross-validation....

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Journal Article
TL;DR: A new technique called t-SNE that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map, a variation of Stochastic Neighbor Embedding that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map.
Abstract: We present a new technique called “t-SNE” that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map. The technique is a variation of Stochastic Neighbor Embedding (Hinton and Roweis, 2002) that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map. t-SNE is better than existing techniques at creating a single map that reveals structure at many different scales. This is particularly important for high-dimensional data that lie on several different, but related, low-dimensional manifolds, such as images of objects from multiple classes seen from multiple viewpoints. For visualizing the structure of very large datasets, we show how t-SNE can use random walks on neighborhood graphs to allow the implicit structure of all of the data to influence the way in which a subset of the data is displayed. We illustrate the performance of t-SNE on a wide variety of datasets and compare it with many other non-parametric visualization techniques, including Sammon mapping, Isomap, and Locally Linear Embedding. The visualizations produced by t-SNE are significantly better than those produced by the other techniques on almost all of the datasets.

30,124 citations

Journal ArticleDOI
TL;DR: A method is described for the minimization of a function of n variables, which depends on the comparison of function values at the (n 41) vertices of a general simplex, followed by the replacement of the vertex with the highest value by another point.
Abstract: A method is described for the minimization of a function of n variables, which depends on the comparison of function values at the (n 41) vertices of a general simplex, followed by the replacement of the vertex with the highest value by another point. The simplex adapts itself to the local landscape, and contracts on to the final minimum. The method is shown to be effective and computationally compact. A procedure is given for the estimation of the Hessian matrix in the neighbourhood of the minimum, needed in statistical estimation problems.

27,271 citations


"An immune clock of human pregnancy...." refers methods in this paper

  • ...The four freeparameters of themodel (l1,l2 ,φ, andy)wereoptimized using a gradient-free optimization algorithm (39)....

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Journal ArticleDOI
TL;DR: It is shown that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation, and an algorithm called LARS‐EN is proposed for computing elastic net regularization paths efficiently, much like algorithm LARS does for the lamba.
Abstract: Summary. We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation. In addition, the elastic net encourages a grouping effect, where strongly correlated predictors tend to be in or out of the model together.The elastic net is particularly useful when the number of predictors (p) is much bigger than the number of observations (n). By contrast, the lasso is not a very satisfactory variable selection method in the

16,538 citations


"An immune clock of human pregnancy...." refers background or methods in this paper

  • ...The csEN algorithmwas adapted from the Elastic Net (EN) regularized regression method (18) and accounts for the influence of previous biological knowledge of receptor-specific signal transduction on the generation of single-cell mass cytometry data....

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  • ...This limitation is addressed by using an additionalL2 regularization (18) to allow the inclusion of highly correlated measurements: L(b) = |Y − Xb|(2) + l1|b|1 + l2|b|2, where l1 and l2 are selected by cross-validation....

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  • ...Statistical analysis Multivariate modeling of mass cytometry data using a cell signaling–based matrix The csEN algorithm was adapted from the existing EN algorithm (18) to allow accounting for the influence of previous knowledge of intracellular signal transduction on the generation of the mass cytometry data set....

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  • ...The highly correlated nature of the mass cytometry data suggested an EN method—a regularized regression method particularly suitable to the analysis of intercorrelated data (18)—as a primary candidate to determine whether dynamic changes occurring in peripheral immune cells during pregnancy could predict gestational age at time of sampling....

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Journal ArticleDOI
TL;DR: In this paper, the authors summarize the signalling and epigenetic mechanisms that regulate type I IFN-induced STAT activation and ISG transcription and translation and conclude that these regulatory mechanisms determine the biological outcomes of type I ILN responses and whether pathogens are cleared effectively or chronic infection or autoimmune disease ensues.
Abstract: Type I interferons (IFNs) activate intracellular antimicrobial programmes and influence the development of innate and adaptive immune responses. Canonical type I IFN signalling activates the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway, leading to transcription of IFN-stimulated genes (ISGs). Host, pathogen and environmental factors regulate the responses of cells to this signalling pathway and thus calibrate host defences while limiting tissue damage and preventing autoimmunity. Here, we summarize the signalling and epigenetic mechanisms that regulate type I IFN-induced STAT activation and ISG transcription and translation. These regulatory mechanisms determine the biological outcomes of type I IFN responses and whether pathogens are cleared effectively or chronic infection or autoimmune disease ensues.

2,273 citations


"An immune clock of human pregnancy...." refers background in this paper

  • ...Community 16, anchored in the csEN component “pSTAT1 response to IFN-a in CD16CD56NK cells,” was primarily populated by immune features related to STAT1 tyrosine phosphorylation in response to IFN-a, an essential pathway for type-I IFN signal transduction (23)....

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