Recent studies have provided insights into the pathogenesis of coronavirus disease 2019 (COVID-19)1-4. However, the longitudinal immunological correlates of disease outcome remain unclear. Here we serially analysed immune responses in 113 patients with moderate or severe COVID-19. Immune profiling revealed an overall increase in innate cell lineages, with a concomitant reduction in T cell number. An early elevation in cytokine levels was associated with worse disease outcomes. Following an early increase in cytokines, patients with moderate COVID-19 displayed a progressive reduction in type 1 (antiviral) and type 3 (antifungal) responses. By contrast, patients with severe COVID-19 maintained these elevated responses throughout the course of the disease. Moreover, severe COVID-19 was accompanied by an increase in multiple type 2 (anti-helminths) effectors, including interleukin-5 (IL-5), IL-13, immunoglobulin E and eosinophils. Unsupervised clustering analysis identified four immune signatures, representing growth factors (A), type-2/3 cytokines (B), mixed type-1/2/3 cytokines (C), and chemokines (D) that correlated with three distinct disease trajectories. The immune profiles of patients who recovered from moderate COVID-19 were enriched in tissue reparative growth factor signature A, whereas the profiles of those with who developed severe disease had elevated levels of all four signatures. Thus, we have identified a maladapted immune response profile associated with severe COVID-19 and poor clinical outcome, as well as early immune signatures that correlate with divergent disease trajectories.

/pdf/longitudinal-analyses-reveal-immunological-misfiring-in-517lj9vqyx.pdf

Longitudinal analyses reveal immunological misfiring in severe COVID-19.

INTRODUCTION Embryonic development and tissue homeostasis depend on cooperation between specialized cell types. Resident macrophages are professional phagocytes that survey their surroundings; eliminate unfit cells, microorganisms, and metabolic waste; and produce a large range of bioactive molecules and growth factors. Resident macrophages also serve tissue-specific purposes: For example, microglia in the central nervous system support neuronal circuit development, Kupffer cells scavenge blood particles and dying red blood cells in the liver, and alveolar macrophages uptake surfactant and remove airborne pollutants and microbes from the airways. Resident macrophage diversity in adult mice is reflected in tissue-specific gene expression profiles, which may be due to responses to specific cues from their microenvironment, different developmental processes, and the contribution of distinct progenitors cell types. Altogether, the mechanisms responsible for the generation of tissue-resident macrophage diversity remain unclear. RATIONALE Tissue-resident macrophages originate, at least in part, from mesodermal erythro-myeloid progenitors (EMPs) from the yolk sac, which invade the embryo proper at the onset of organogenesis. These tissue-resident macrophages are also self-maintained in postnatal tissues, independently of definitive hematopoietic stem cells (HSCs) in a steady state. We therefore hypothesized that resident macrophages represent a founding cell type within most organ anlagen. In this model, the generation of macrophage diversity, as observed in the tissues of postnatal mice, may be integral to organogenesis. RESULTS To test this hypothesis and explore the molecular basis of macrophage diversity in mammals, we performed a spatiotemporal analysis of macrophage development in mice, from embryonic day 9 (E9) to 3 weeks after birth. Unbiased single-cell RNA sequencing (RNA-seq) analysis of CD45 + cells, combined with RNA-seq analyses of sorted cell populations, genetic fate mapping, and in situ analyses, revealed that EMPs give rise to a population of premacrophages (pMacs) that colonize the whole embryo from E9.5, as they acquire a core macrophage differentiation program that includes pattern recognition, scavengers, and cytokine receptors. The chemokine receptor Cx3cr1 is up-regulated in pMacs and is important for embryo colonization, which is delayed in Cx3cr1 -deficient embryos. Fate mapping of pMacs using a Tnfrsf11a –Cre reporter labels homogeneously fetal and adult tissue-resident macrophages but not HSCs and their progeny. Transcriptional regulators that identify postnatal tissue-resident macrophages in the brain, liver, kidney, skin, and lung were specifically up-regulated immediately after colonization. These dynamic changes mark the onset of diversification into adult macrophages. We identified Id3 as a Kupffer cell–specific transcriptional regulator. Deletion of Id3 in pMacs resulted in Kupffer cell deficiency but did not affect development of microglia and kidney macrophages. CONCLUSION Our study shows that EMP-derived precursors colonize embryonic tissues and simultaneously acquire a full core macrophage program. This is followed by their diversification into tissue-specific macrophages during organogenesis, likely via the expression of distinct sets of transcriptional regulators. These results indicate that differentiation of tissue-resident macrophages is an integral part of organogenesis and identify a spatiotemporal molecular road map for the generation of macrophage diversity in vivo. Our findings provide a conceptual framework to analyze and understand the consequence(s) of genetic variation for macrophage contribution to development, homeostasis, and disease pathogenesis in different tissues and will support efforts to differentiate specialized macrophages in vitro.

Specification of tissue-resident macrophages during organogenesis

https://archive-ouverte.unige.ch/unige:112261/ATTACHMENT01

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review.

https://flore.unifi.it/bitstream/2158/941731/1/JOURNAL%20OF%20FUNCTIONAL%20FOODS%202014%20-%201-s2.0-S1756464613003009.pdf

Nutraceuticals and dyslipidaemia: Beyond the common therapeutics

Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments, such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, and generally lacked quantitative measurements. Here, we report the development, implementation, and initial results of a multilingual, international questionnaire to assess self-reported quantity and quality of perception in 3 distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, and 8 others, aged 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste, and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change ±100) revealed a mean reduction of smell (-79.7 ± 28.7, mean ± standard deviation), taste (-69.0 ± 32.6), and chemesthetic (-37.3 ± 36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell but also affects taste and chemesthesis. The multimodal impact of COVID-19 and the lack of perceived nasal obstruction suggest that severe acute respiratory syndrome coronavirus strain 2 (SARS-CoV-2) infection may disrupt sensory-neural mechanisms.

/pdf/more-than-smell-covid-19-is-associated-with-severe-3khmdi67ge.pdf

More Than Smell-COVID-19 Is Associated With Severe Impairment of Smell, Taste, and Chemesthesis.

Clustering is the partitioning of a set of objects into groups (clusters) so that objects within a group are more similar to each others than objects in different groups. Most of the clustering algorithms depend on some assumptions in order to define the subgroups present in a data set. As a consequence, the resulting clustering scheme requires some sort of evaluation as regards its validity.
The evaluation procedure has to tackle difficult problems such as the quality of clusters, the degree with which a clustering scheme fits a specific data set and the optimal number of clusters in a partitioning. In the literature, a wide variety of indices have been proposed to find the optimal number of clusters in a partitioning of a data set during the clustering process. However, for most of indices proposed in the literature, programs are unavailable to test these indices and compare them.
The R package NbClust has been developed for that purpose. It provides 30 indices which determine the number of clusters in a data set and it offers also the best clustering scheme from different results to the user. In addition, it provides a function to perform k-means and hierarchical clustering with different distance measures and aggregation methods. Any combination of validation indices and clustering methods can be requested in a single function call. This enables the user to simultaneously evaluate several clustering schemes while varying the number of clusters, to help determining the most appropriate number of clusters for the data set of interest.

NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set

Clustering is the partitioning of a set of objects into groups (clusters) so that objects within a group are more similar to each others than objects in different groups. 
Most of the clustering algorithms depend on certain assumptions in order to define the subgroups present in a data set. As a consequence, in most applications the resulting clustering scheme requires some sort of evaluation as regards its validity. In general terms, there are three approaches to investigate cluster validity. The first is based on external criteria, which consist in comparing the results of cluster analysis to externally known results, such as externally provided class labels. The second approach is based on internal criteria which use the information obtained from within the clustering process to evaluate how well the results of cluster analysis fit the data without reference to external information. The third approach of clustering validity is based on relative criteria. Here the basic idea is the evaluation of a clustering structure by comparing it with other clustering schemes, resulting by the same algorithm but with different parameters values, e.g. the number of clusters.
In the literature, a wide variety of indices have been proposed to find the optimal number of clusters in a partitioning of a data set during the clustering process. Although a vast number of references exist, few comparative studies have been performed on these indices (Milligan and Cooper,1985). Moreover, for most of indices proposed in the literature, programs are unavailable to test these indices and compare them. 
The R package, NbClust, has been developped specifically for that purpose. It implements 30 indices for cluster validation ready to apply on outputs produced by clustering algorithms, Hierarchical clustering and Kmeans, coming from the same package. Most of these indices are described in Milligan and Cooper study (Milligan and Cooper, 1985). The NbClust function allows to apply one or 30 indices simultaneously and proposes to user the best clustering scheme from the different results obtained by varying all combinations of number of clusters, distance measures ("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"), and clustering methods ("ward", "single", "complete", "average", "mcquitty", "median", "centroid").

NbClust package: finding the relevant number of clusters in a dataset

Background: Methylmercury (MeHg) exposure has been linked to an increased risk of coronary heart disease (CHD). Paraoxonase 1 (PON1), an enzyme located in the high-density–lipoprotein (HDL) fraction of blood lipids, may protect against CHD by metabolizing toxic oxidized lipids associated with low-density liproprotein and HDL. MeHg has been shown to inhibit PON1 activity in vitro, but this effect has not been studied in human populations.

Objectives: This study was conducted to determine whether blood mercury levels are linked to decreased plasma PON1 activities in Inuit people who are highly exposed to MeHg through their seafood-based diet.

Methods: We measured plasma PON1 activity using a fluorogenic substrate and blood concentrations of mercury and selenium by inductively coupled plasma mass spectrometry in 896 Inuit adults. Sociodemographic, anthropometric, clinical, dietary, and lifestyle variables as well as PON1 gene variants (rs705379, rs662, rs854560) were considered as possible confounders or modifiers of the mercury–PON1 relation in multivariate analyses.

Results: In a multiple regression model adjusted for age, HDL cholesterol levels, omega-3 fatty acid content of erythrocyte membranes, and PON1 variants, blood mercury concentrations were inversely associated with PON1 activities [β-coefficient = –0.063; 95% confidence interval (CI), –0.091 to –0.035; p < 0.001], whereas blood selenium concentrations were positively associated with PON1 activities (β-coefficient = 0.067; 95% CI, 0.045–0.088; p < 0.001). We found no interaction between blood mercury levels and PON1 genotypes.

Conclusions: Our results suggest that MeHg exposure exerts an inhibitory effect on PON1 activity, which seems to be offset by selenium intake.

Relation between Methylmercury Exposure and Plasma Paraoxonase Activity in Inuit Adults from Nunavik

The Inuit population is often described as being protected against CVD due to their traditional dietary patterns and their unique genetic background. The objective of the present study was to examine gene-diet interaction effects on plasma lipid levels in the Inuit population. Data from the Qanuippitaa Nunavik Health Survey (n 553) were analysed via regression models which included the following: genotypes for thirty-five known polymorphisms (SNP) from twenty genes related to lipid metabolism; dietary fat intake including total fat (TotFat) and saturated fat (SatFat) estimated from a FFQ; plasma lipid levels, namely total cholesterol (TC), LDL-cholesterol (LDL-C), HDL-cholesterol (HDL-C) and TAG. The results demonstrate that allele frequencies were different in the Inuit population compared with the Caucasian population. Further, seven SNP (APOA1 - 75G/A (rs670), APOB XbAI (rs693), AGT M235T (rs699), LIPC 480C/T (rs1800588), APOA1 84T/C (rs5070), PPARG2 - 618C/G (rs10865710) and APOE 219G/T (rs405509)) in interaction with TotFat and SatFat were significantly associated with one or two plasma lipid parameters. Another four SNP (APOC3 3238C>G (rs5128), CETP I405V (rs5882), CYP1A1 A4889G (rs1048943) and ABCA1 Arg219Lys (rs2230806)) in interaction with either TotFat or SatFat intake were significantly associated with one plasma lipid variable. Further, an additive effect of these SNP in interaction with TotFat or SatFat intake was significantly associated with higher TC, LDL-C or TAG levels, as well as with lower HDL-C levels. In conclusion, the present study supports the notion that gene-diet interactions play an important role in modifying plasma lipid levels in the Inuit population.

/pdf/gene-diet-interactions-on-plasma-lipid-levels-in-the-inuit-34iy3xmzej.pdf

Gene–diet interactions on plasma lipid levels in the Inuit population

Background
Tissue concentrations of fatty acids (FAs) and genetic variations are well-known factors which affect the cardiovascular disease (CVD) risk. The objective was to examine whether the genetic variability of 20 candidate genes and red blood cells (RBCs) percentage of total n-3 polyunsaturated fatty acids (PUFA), a biomarker of dietary n-3 PUFA intake, modulate lipid related CVD risk factors in the Inuit population.

/pdf/omega-3-fatty-acids-polymorphisms-and-lipid-related-smxmkwxd57.pdf

Véronique Boiteau

Papers

NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set

NbClust package: finding the relevant number of clusters in a dataset

Relation between Methylmercury Exposure and Plasma Paraoxonase Activity in Inuit Adults from Nunavik

Gene–diet interactions on plasma lipid levels in the Inuit population

Omega-3 fatty acids, polymorphisms and lipid related cardiovascular disease risk factors in the Inuit population