29 research outputs found

    The fatal trajectory of pulmonary COVID-19 is driven by lobular ischemia and fibrotic remodelling

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    BACKGROUND: COVID-19 is characterized by a heterogeneous clinical presentation, ranging from mild symptoms to severe courses of disease. 9-20% of hospitalized patients with severe lung disease die from COVID-19 and a substantial number of survivors develop long-COVID. Our objective was to provide comprehensive insights into the pathophysiology of severe COVID-19 and to identify liquid biomarkers for disease severity and therapy response. METHODS: We studied a total of 85 lungs (n = 31 COVID autopsy samples; n = 7 influenza A autopsy samples; n = 18 interstitial lung disease explants; n = 24 healthy controls) using the highest resolution Synchrotron radiation-based hierarchical phase-contrast tomography, scanning electron microscopy of microvascular corrosion casts, immunohistochemistry, matrix-assisted laser desorption ionization mass spectrometry imaging, and analysis of mRNA expression and biological pathways. Plasma samples from all disease groups were used for liquid biomarker determination using ELISA. The anatomic/molecular data were analyzed as a function of patients' hospitalization time. FINDINGS: The observed patchy/mosaic appearance of COVID-19 in conventional lung imaging resulted from microvascular occlusion and secondary lobular ischemia. The length of hospitalization was associated with increased intussusceptive angiogenesis. This was associated with enhanced angiogenic, and fibrotic gene expression demonstrated by molecular profiling and metabolomic analysis. Increased plasma fibrosis markers correlated with their pulmonary tissue transcript levels and predicted disease severity. Plasma analysis confirmed distinct fibrosis biomarkers (TSP2, GDF15, IGFBP7, Pro-C3) that predicted the fatal trajectory in COVID-19. INTERPRETATION: Pulmonary severe COVID-19 is a consequence of secondary lobular microischemia and fibrotic remodelling, resulting in a distinctive form of fibrotic interstitial lung disease that contributes to long-COVID. FUNDING: This project was made possible by a number of funders. The full list can be found within the Declaration of interests / Acknowledgements section at the end of the manuscript

    A Phosphoproteomic Approach towards the Understanding of the Role of TGF-ÎČ in Trypanosoma cruzi Biology

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    Transforming growth factor beta (TGF-ÎČ) plays a pivotal role in Chagas disease, not only in the development of chagasic cardiomyopathy, but also in many stages of the T. cruzi life cycle and survival in the host cell environment. The intracellular signaling pathways utilized by T. cruzi to regulate these mechanisms remain unknown. To identify parasite proteins involved in the TGF-ÎČ response, we utilized a combined approach of two-dimensional gel electrophoresis (2DE) analysis and mass spectrometry (MS) protein identification. Signaling via TGF-ÎČ is dependent on events of phosphorylation, which is one of the most relevant and ubiquitous post-translational modifications for the regulation of gene expression, and especially in trypanosomatids, since they lack several transcriptional control mechanisms. Here we show a kinetic view of T. cruzi epimastigotes (Y strain) incubated with TGF-ÎČ for 1, 5, 30 and 60 minutes, which promoted a remodeling of the parasite phosphorylation network and protein expression pattern. The altered molecules are involved in a variety of cellular processes, such as proteolysis, metabolism, heat shock response, cytoskeleton arrangement, oxidative stress regulation, translation and signal transduction. A total of 75 protein spots were up- or down-regulated more than twofold after TGF-ÎČ treatment, and from these, 42 were identified by mass spectrometry, including cruzipain–the major T. cruzi papain-like cysteine proteinase that plays an important role in invasion and participates in the escape mechanisms used by the parasite to evade the host immune system. In our study, we observed that TGF-ÎČ addition favored epimastigote proliferation, corroborating 2DE data in which proteins previously described to be involved in this process were positively stimulated by TGF-ÎČ

    Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications.

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    To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases

    Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci

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    Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure.

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    Numerous genetic loci have been associated with systolic blood pressure (SBP) and diastolic blood pressure (DBP) in Europeans. We now report genome-wide association studies of pulse pressure (PP) and mean arterial pressure (MAP). In discovery (N = 74,064) and follow-up studies (N = 48,607), we identified at genome-wide significance (P = 2.7 × 10(-8) to P = 2.3 × 10(-13)) four new PP loci (at 4q12 near CHIC2, 7q22.3 near PIK3CG, 8q24.12 in NOV and 11q24.3 near ADAMTS8), two new MAP loci (3p21.31 in MAP4 and 10q25.3 near ADRB1) and one locus associated with both of these traits (2q24.3 near FIGN) that has also recently been associated with SBP in east Asians. For three of the new PP loci, the estimated effect for SBP was opposite of that for DBP, in contrast to the majority of common SBP- and DBP-associated variants, which show concordant effects on both traits. These findings suggest new genetic pathways underlying blood pressure variation, some of which may differentially influence SBP and DBP

    Stimulation of the vagus nerve reduces learning in a go/no-go reinforcement learning task

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    When facing decisions to approach rewards or to avoid punishments, we often figuratively go with our gut, and the impact of metabolic states such as hunger on motivation are well documented. However, whether and how vagal feedback signals from the gut influence instrumental actions is unknown. Here, we investigated the effect of non-invasive transcutaneous auricular vagus nerve stimulation (taVNS) vs. sham (randomized cross-over design) on approach and avoidance behavior using an established go/no-go reinforcement learning paradigm in 39 healthy human participants (23 female) after an overnight fast. First, mixed-effects logistic regression analysis of choice accuracy showed that taVNS acutely impaired decision-making, p = .041. Computational reinforcement learning models identified the cause of this as a reduction in the learning rate through taVNS (∆α = -0.092, pboot = .002), particularly after punishment (∆αPun = -0.081, pboot = .012 vs. ∆αRew =-0.031, pboot = .22). However, taVNS had no effect on go biases, Pavlovian response biases or response time. Hence, taVNS appeared to influence learning rather than action execution. These results highlight a novel role of vagal afferent input in modulating reinforcement learning by tuning the learning rate according to homeostatic needs
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