Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy.

MotivationMultiple 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.ResultsWe performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.Availability and implementationDatasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.Supplementary informationSupplementary data are available at Bioinformatics online

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy

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. Results We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation Datasets and scripts for reproduction of results are available through: Https://nalab.stanford.edu/multiomics-pregnancy/

Impaired Hepatitis C Virus-Specific T Cell Responses and Recurrent Hepatitis C Virus in HIV Coinfection

BACKGROUND: Hepatitis C virus (HCV)-specific T cell responses are critical for spontaneous resolution of HCV viremia. Here we examined the effect of a lymphotropic virus, HIV-1, on the ability of coinfected patients to maintain spontaneous control of HCV infection. METHODS AND FINDINGS: We measured T cell responsiveness by lymphoproliferation and interferon-γ ELISPOT in a large cohort of HCV-infected individuals with and without HIV infection. Among 47 HCV/HIV-1-coinfected individuals, spontaneous control of HCV was associated with more frequent HCV-specific lymphoproliferative (LP) responses (35%) compared to coinfected persons who exhibited chronic HCV viremia (7%, p = 0.016), but less frequent compared to HCV controllers who were not HIV infected (86%, p = 0.003). Preservation of HCV-specific LP responses in coinfected individuals was associated with a higher nadir CD4 count (r (2) = 0.45, p < 0.001) and the presence and magnitude of the HCV-specific CD8(+) T cell interferon-γ response (p = 0.0014). During long-term follow-up, recurrence of HCV viremia occurred in six of 25 coinfected individuals with prior control of HCV, but in 0 of 16 HIV-1-negative HCV controllers (p = 0.03, log rank test). In these six individuals with recurrent HCV viremia, the magnitude of HCV viremia following recurrence inversely correlated with the CD4 count at time of breakthrough (r = −0.94, p = 0.017). CONCLUSIONS: These results indicate that HIV infection impairs the immune response to HCV—including in persons who have cleared HCV infection—and that HIV-1-infected individuals with spontaneous control of HCV remain at significant risk for a second episode of HCV viremia. These findings highlight the need for repeat viral RNA testing of apparent controllers of HCV infection in the setting of HIV-1 coinfection and provide a possible explanation for the higher rate of HCV persistence observed in this population

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission

This 1:30,000 scale geological map describes Oxia Planum, Mars, the landing site for the ExoMars Rosalind Franklin rover mission. The map represents our current understanding of bedrock units and their relationships prior to Rosalind Franklin’s exploration of this location. The map details 15 bedrock units organised into 6 groups and 7 textural and surficial units. The bedrock units were identified using visible and near-infrared remote sensing datasets. The objectives of this map are (i) to identify where the most astrobiologically relevant rocks are likely to be found, (ii) to show where hypotheses about their geological context (within Oxia Planum and in the wider geological history of Mars) can be tested, (iii) to inform both the long-term (hundreds of metres to ∼1 km) and the short-term (tens of metres) activity planning for rover exploration, and (iv) to allow the samples analysed by the rover to be interpreted within their regional geological context.The ExoMars Rosalind Franklin Mission is a partnership between ESA and NASA. The Rosalind Franklin Rover has eight instruments in its ‘Pasteur’ Payload, with Principal Investigators from seven countries all of whom we would like to thank for there support of this project. We would like to acknowledge the following funding bodies, people and institutions supporting the lead authors of this work. We thank the UK Space Agency (UK SA) for funding P. Fawdon, on grants; ST/W002736/1, ST/L00643X/1 and ST/R001413/1, MRB on grants; ST/T002913/1, ST/V001965/1, ST/R001383/1, ST/R001413/1, P. Grindrod on grants; ST/L006456/1, ST/R002355/1, ST/V002678/1 and J. Davis on grants ST/K502388/1, ST/R002355/1, ST/V002678/1 through the ongoing Aurora space exploration programme. C. Orgel was supported by the ESA Research Fellowship Program. Alessandro Frigeri: was funded by the Italian Space Agency (ASI) grant ASI-INAF number 2017-412-H.0 (ExoMars/Ma_MISS) and D. Loizeau was funded by the H2020-COMPET-2015 programme (grant 687302), C. Quantin-Nataf was supported by the French space agency CNES, I. Torres was supported by an ESA Young Graduate Traineeship, A. Nass was supported by Helmholtz Metadata Projects (#ZT-I-PF-3-008). We thank NASA and the HiRISE camera team for data collection support throughout the ExoMars landing site selection and charectorisation process. The USGS for the HiRISE DTM data and maintaining the ISIS and SOCET SET DEM workflows. The authors wish to thank the CaSSIS spacecraft and instrument engineering teams. CaSSIS is a project of the University of Bern and funded through the Swiss Space Office via ESA's PRODEX programme. The instrument hardware development was also supported by the Italian Space Agency (ASI) (ASI-INAF agreement no. I/2020-17-HH.0), INAF/Astronomical Observatory of Padova, and the Space Research Center (CBK) in Warsaw. Support from SGF (Budapest), the University of Arizona (Lunar and Planetary Lab.) and NASA are also gratefully acknowledged. Operations support from the UK Space Agency under grant ST/R003025/1 is also acknowledged. This research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS) Technical support for setup of the Multi-Mission Geographic Information System for concurrent team mapping was provided by F. Calef (III) and T. Soliman at NASA JPL and S. de Witte at ESA-ESTEC.This work was supported by Agencia Estatal de Investigación [grant number ID2019-107442RB-C32, MDM-2017-0737]; Agenzia Spaziale Italiana [grant number 2017-412-H.0]; Bundesministerium für Wirtschaft und Technologie [grant number 50 QX 2002]; Centre National de la Recherche Scientifique; Centre National d’Etudes Spatiales; Euskal Herriko Unibertsitatea [grant number PES21/88]; Istituto Nazionale di Astrofisica [grant number I/ 060/10/0]; Ministerio de Economía y Competitividad [grant number PID2019-104205GB-C21]; Ministry of Science and Higher Education of the Russian Federation [grant number AAAA-A18-118012290370-6]; National Aeronautics and Space Administration [grant number NNX15AH46G]; Norges Forskningsråd [grant number 223272]; European Union's Horizon 2020 (H2020-COMPET-2015) [grant number 687302 (PTAL)]; Sofja Kovalevskaja Award of the Alexander von Humboldt Foundation; MINECO [grant number PID2019-107442RB-C32]; The Open University [grant number Space Strategic Research Area]; European Union's Horizon 2020 research and innovation programme [grant number 776276]; H2020-COMPET-2015 [grant number 687302]; The Research Council of Norway, Centres of Excellence funding scheme [grant number 223272]; Helmholtz Metadata Projects [grant number ZT-I-PF-3-008]; The Research Council of Norway [grant number 223272]; Swiss Space Office via ESA's PRODEX programme; Ines Torres was supported by an ESA Young Graduate Traineeship; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung [grant number 200021_197293]; Science and Technology Facilities Council [grant number 1967420]; UK Space Agency [grant number ST/K502388/1, ST/R002355/1, ST/V002678/1]. The ExoMars Rosalind Franklin Mission is a partnership between ESA and NASA. The Rosalind Franklin Rover has eight instruments in its ‘Pasteur’ Payload, with Principal Investigators from seven countries all of whom we would like to thank for there support of this project. We would like to acknowledge the following funding bodies, people and institutions supporting the lead authors of this work. We thank the UK Space Agency (UK SA) for funding P. Fawdon, on grants; ST/W002736/1, ST/L00643X/1 and ST/R001413/1, MRB on grants; ST/T002913/1, ST/V001965/1, ST/R001383/1, ST/R001413/1, P. Grindrod on grants; ST/L006456/1, ST/R002355/1, ST/V002678/1 and J. Davis on grants ST/K502388/1, ST/R002355/1, ST/V002678/1 through the ongoing Aurora space exploration programme. C. Orgel was supported by the ESA Research Fellowship Program. Alessandro Frigeri: was funded by the Italian Space Agency (ASI) grant ASI-INAF number 2017-412-H.0 (ExoMars/Ma_MISS) and D. Loizeau was funded by the H2020-COMPET-2015 programme (grant 687302), C. Quantin-Nataf was supported by the French space agency CNES, I. Torres was supported by an ESA Young Graduate Traineeship, A. Nass was supported by Helmholtz Metadata Projects (#ZT-I-PF-3-008). We thank NASA and the HiRISE camera team for data collection support throughout the ExoMars landing site selection and charectorisation process. The USGS for the HiRISE DTM data and maintaining the ISIS and SOCET SET DEM workflows. The authors wish to thank the CaSSIS spacecraft and instrument engineering teams. CaSSIS is a project of the University of Bern and funded through the Swiss Space Office via ESA's PRODEX programme. The instrument hardware development was also supported by the Italian Space Agency (ASI) (ASI-INAF agreement no. I/2020-17-HH.0), INAF/Astronomical Observatory of Padova, and the Space Research Center (CBK) in Warsaw. Support from SGF (Budapest), the University of Arizona (Lunar and Planetary Lab.) and NASA are also gratefully acknowledged. Operations support from the UK Space Agency under grant ST/R003025/1 is also acknowledged. This research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS) Technical support for setup of the Multi-Mission Geographic Information System for concurrent team mapping was provided by F. Calef (III) and T. Soliman at NASA JPL and S. de Witte at ESA-ESTEC.Peer reviewe

The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission

This 1:30,000 scale geological map describes Oxia Planum, Mars, the landing site for the ExoMars Rosalind Franklin rover mission. The map represents our current understanding of bedrock units and their relationships prior to Rosalind Franklin’s exploration of this location. The map details 15 bedrock units organised into 6 groups and 7 textural and surficial units. The bedrock units were identified using visible and near-infrared remote sensing datasets. The objectives of this map are (i) to identify where the most astrobiologically relevant rocks are likely to be found, (ii) to show where hypotheses about their geological context (within Oxia Planum and in the wider geological history of Mars) can be tested, (iii) to inform both the long-term (hundreds of metres to ∼1 km) and the short-term (tens of metres) activity planning for rover exploration, and (iv) to allow the samples analysed by the rover to be interpreted within their regional geological context