ACTIV-3/TICO Study Group, Angela J Rogers, Deborah Wentworth, Andrew Phillips, Katy Shaw-Saliba, Robin L Dewar, Neil R Aggarwal, Abdel G Babiker, Weizhong Chang, Nila J Dharan, Victoria J Davey, Elizabeth S Higgs, Norman Gerry, Adit A Ginde, J W Awori Hayanga, Helene Highbarger, Jeroen L Highbarger, Mamta K Jain, Virginia Kan, Kami Kim, Perrine Lallemand, Bradley G Leshnower, Joseph K Lutaakome, Gail Matthews, Ahmad Mourad, Eleftherios Mylonakis, Ven Natarajan, Maria L Padilla, Lavannya M Pandit, Roger Paredes, Sarah Pett, Srikanth Ramachandruni, M Tauseef Rehman, Brad T Sherman, D Clark Files, Samuel M Brown, Michael A Matthay, B Taylor Thompson, James D Neaton, H Clifford Lane, Jens D Lundgren <<<

BACKGROUND: Levels of plasma SARS-CoV-2 nucleocapsid (N) antigen may be an important biomarker in patients with COVID-19 and enhance our understanding of the pathogenesis of COVID-19.OBJECTIVE: To evaluate whether levels of plasma antigen can predict short-term clinical outcomes and identify clinical and viral factors associated with plasma antigen levels in hospitalized patients with SARS-CoV-2.DESIGN: Cross-sectional study of baseline plasma antigen level from 2540 participants enrolled in the TICO (Therapeutics for Inpatients With COVID-19) platform trial from August 2020 to November 2021, with additional data on day 5 outcome and time to discharge.SETTING: 114 centers in 10 countries.PARTICIPANTS: Adults hospitalized for acute SARS-CoV-2 infection with 12 days or less of symptoms.MEASUREMENTS: Baseline plasma viral N antigen level was measured at a central laboratory. Delta variant status was determined from baseline nasal swabs using reverse transcriptase polymerase chain reaction. Associations between baseline patient characteristics and viral factors and baseline plasma antigen levels were assessed using both unadjusted and multivariable modeling. Association between elevated baseline antigen level of 1000 ng/L or greater and outcomes, including worsening of ordinal pulmonary scale at day 5 and time to hospital discharge, were evaluated using logistic regression and Fine-Gray regression models, respectively.RESULTS: Plasma antigen was below the level of quantification in 5% of participants at enrollment, and 1000 ng/L or greater in 57%. Baseline pulmonary severity of illness was strongly associated with plasma antigen level, with mean plasma antigen level 3.10-fold higher among those requiring noninvasive ventilation or high-flow nasal cannula compared with room air (95% CI, 2.22 to 4.34). Plasma antigen level was higher in those who lacked antispike antibodies (6.42 fold; CI, 5.37 to 7.66) and in those with the Delta variant (1.73 fold; CI, 1.41 to 2.13). Additional factors associated with higher baseline antigen level included male sex, shorter time since hospital admission, decreased days of remdesivir, and renal impairment. In contrast, race, ethnicity, body mass index, and immunocompromising conditions were not associated with plasma antigen levels. Plasma antigen level of 1000 ng/L or greater was associated with a markedly higher odds of worsened pulmonary status at day 5 (odds ratio, 5.06 [CI, 3.41 to 7.50]) and longer time to hospital discharge (median, 7 vs. 4 days; subhazard ratio, 0.51 [CI, 0.45 to 0.57]), with subhazard ratios similar across all levels of baseline pulmonary severity.LIMITATIONS: Plasma samples were drawn at enrollment, not hospital presentation. No point-of-care test to measure plasma antigen is currently available.CONCLUSION: Elevated plasma antigen is highly associated with both severity of pulmonary illness and clinically important patient outcomes. Multiple clinical and viral factors are associated with plasma antigen level at presentation. These data support a potential role of ongoing viral replication in the pathogenesis of SARS-CoV-2 in hospitalized patients.PRIMARY FUNDING SOURCE: U.S. government Operation Warp Speed and National Institute of Allergy and Infectious Diseases. <<<

Mahan Nekoui , James P. Pirruccello , Paolo Di Achille , Seung Hoan Choi , Samuel N. Friedman , Victor Nauffal , Kenney Ng , Puneet Batra , Jennifer E. Ho , Anthony A. Philippakis , Steven A. Lubitz , Mark E. Lindsay , Patrick T. Ellinor <<<

Background The left ventricular outflow tract (LVOT) and ascending aorta are spatially complex, with distinct pathologies and embryologic origins. Prior work examined the genetics of thoracic aortic diameter in a single plane. Objectives We sought to elucidate the genetic basis for the diameter of the LVOT, aortic root, and ascending aorta. Methods Using deep learning, we analyzed 2.3 million cardiac magnetic resonance images from 43,317 UK Biobank participants. We computed the diameters of the LVOT, the aortic root, and at 6 locations of ascending aorta. For each diameter, we conducted a genome-wide association study and generated a polygenic score. Finally, we investigated associations between these scores and disease incidence. Results A total of 79 loci were significantly associated with at least 1 diameter. Of these, 35 were novel, and most were associated with 1 or 2 diameters. A polygenic score of aortic diameter approximately 13 mm from the sinotubular junction most strongly predicted thoracic aortic aneurysm (n = 427,016; mean HR: 1.42 per SD; 95% CI: 1.34-1.50; P = 6.67 × 10−21). A polygenic score predicting a smaller aortic root was predictive of aortic stenosis (n = 426,502; mean HR: 1.08 per SD; 95% CI: 1.03-1.12; P = 5 × 10−6). Conclusions We detected distinct genetic loci underpinning the diameters of the LVOT, aortic root, and at several segments of ascending aorta. We spatially defined a region of aorta whose genetics may be most relevant to predicting thoracic aortic aneurysm. We further described a genetic signature that may predispose to aortic stenosis. Understanding genetic contributions to proximal aortic diameter may enable identification of individuals at risk for aortic disease and facilitate prioritization of therapeutic targets. <<<

Ao Chen, Sha Liao, Mengnan Cheng, Kailong Ma, Liang Wu, Yiwei Lai, Xiaojie Qiu, Jin Yang, Jiangshan Xu, Shijie Hao, Xin Wang, Huifang Lu, Xi Chen, Xing Liu, Xin Huang, Zhao Li, Yan Hong, Yujia Jiang, Jian Peng, Shuai Liu, Mengzhe Shen, Chuanyu Liu, Quanshui Li, Yue Yuan, Xiaoyu Wei, Huiwen Zheng, Weimin Feng, Zhifeng Wang, Yang Liu, Zhaohui Wang, Yunzhi Yang, Haitao Xiang, Lei Han, Baoming Qin, Pengcheng Guo, Guangyao Lai, Pura Muñoz-Cánoves, Patrick H Maxwell, Jean Paul Thiery, Qing-Feng Wu, Fuxiang Zhao, Bichao Chen, Mei Li, Xi Dai, Shuai Wang, Haoyan Kuang, Junhou Hui, Liqun Wang, Ji-Feng Fei, Ou Wang, Xiaofeng Wei, Haorong Lu, Bo Wang, Shiping Liu, Ying Gu, Ming Ni, Wenwei Zhang, Feng Mu, Ye Yin, Huanming Yang, Michael Lisby, Richard J Cornall, Jan Mulder, Mathias Uhlén, Miguel A Esteban, Yuxiang Li, Longqi Liu, Xun Xu, Jian Wang <<<

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development. <<<