Publications

@article{10.2147/rmi.s292314,

title = {Artificial Intelligence in Predicting Clinical Outcome in COVID-19 Patients from Clinical, Biochemical and a Qualitative Chest X-Ray Scoring System},

author = {Andrea Esposito and Elena Casiraghi and Francesca Chiaraviglio and Alice Scarabelli and Elvira Stellato and Guido Plensich and Giulia Lastella and Letizia Di Meglio and Stefano Fusco and Emanuele Avola and Alessandro Jachetti and Caterina Giannitto and Dario Malchiodi and Marco Frasca and Afshin Beheshti and Peter N Robinson and Giorgio Valentini and Laura Forzenigo and Gianpaolo Carrafiello},

doi = {10.2147/rmi.s292314},

year  = {2021},

date = {2021-01-01},

journal = {Reports in Medical Imaging},

volume = {Volume 14},

pages = {27--39},

keywords = {Publications from COV-IRT},

pubstate = {published},

tppubtype = {article}

}

@article{10.1101/2021.07.02.450920,

title = {Betacoronavirus-specific alternate splicing},

author = {Guy Karlebach and Bruce Aronow and Stephen B Baylin and Daniel Butler and Jonathan Foox and Shawn Levy and Cem Meydan and Christopher Mozsary and Amanda M Saravia-Butler and Deanne M Taylor and Eve Wurtele and Christopher E Mason and Afshin Beheshti and Peter N Robinson},

doi = {10.1101/2021.07.02.450920},

year  = {2021},

date = {2021-01-01},

journal = {bioRxiv},

pages = {2021.07.02.450920},

abstract = {Viruses can subvert a number of cellular processes in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 published experimental and clinical datasets related to SARS-CoV-2 infection as well as datasets from the betacoronaviruses SARS-CoV and MERS as well as Streptococcus pneumonia, HCV, Zika virus, Dengue virus, influenza H3N2, and RSV. We show that genes showing differential alternative splicing in SARS-CoV-2 have a similar functional profile to those of SARS-CoV and MERS and affect a diverse set of genes and biological functions, including many closely related to virus biology. Additionally, the differentially spliced transcripts of cells infected by coronaviruses were more likely to undergo intron-retention, contain a pseudouridine modification and a smaller number of exons than differentially spliced transcripts in the control groups. Viral load in clinical COVID-19 samples was correlated with isoform distribution of differentially spliced genes. A significantly higher number of ribosomal genes are affected by DAS and DGE in betacoronavirus samples, and the betacoronavirus differentially spliced genes are depleted for binding sites of RNA-binding proteins. Our results demonstrate characteristic patterns of differential splicing in cells infected by SARS-CoV-2, SARS-CoV, and MERS, potentially modifying a broad range of cellular functions and affecting a diverse set of genes and biological functions.},

keywords = {Publications from COV-IRT},

pubstate = {published},

tppubtype = {article}

}

@article{10.1101/gr.268961.120,

title = {Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission},

author = {Nicolae Sapoval and Medhat Mahmoud and Michael Jochum and Yunxi Liu and Leo R A Elworth and Qi Wang and Dreycey Albin and Huw Ogilvie and Michael D Lee and Sonia Villapol and Kyle Hernandez and Irina Maljkovic Berry and Jonathan Foox and Afshin Beheshti and Krista Ternus and Kjersti Aagaard and David Posada and Christopher Mason and Fritz J Sedlazeck and Todd J Treangen},

doi = {10.1101/gr.268961.120},

issn = {1088-9051},

year  = {2021},

date = {2021-01-01},

journal = {Genome Research},

volume = {31},

number = {4},

pages = {gr.268961.120},

abstract = {The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq datasets and 6,928 consensus genomes to contrast the intrahost and interhost diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with differences in C>U changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of insertions and deletions contribute to the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.},

keywords = {Publications from COV-IRT},

pubstate = {published},

tppubtype = {article}

}

@article{10.1101/2021.03.08.434433,

title = {Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps},

author = {Jiwoon Park and Jonathan Foox and Tyler Hether and David Danko and Sarah Warren and Youngmi Kim and Jason Reeves and Daniel J Butler and Christopher Mozsary and Joel Rosiene and Alon Shaiber and Ebrahim Afshinnekoo and Matthew MacKay and Yaron Bram and Vasuretha Chandar and Heather Geiger and Arryn Craney and Priya Velu and Ari M Melnick and Iman Hajirasouliha and Afshin Beheshti and Deanne Taylor and Amanda Saravia-Butler and Urminder Singh and Eve Syrkin Wurtele and Jonathan Schisler and Samantha Fennessey and André Corvelo and Michael C Zody and Soren Germer and Steven Salvatore and Shawn Levy and Shixiu Wu and Nicholas Tatonetti and Sagi Shapira and Mirella Salvatore and Massimo Loda and Lars F Westblade and Melissa Cushing and Hanna Rennert and Alison J Kriegel and Olivier Elemento and Marcin Imielinski and Alain C Borczuk and Cem Meydan and Robert E Schwartz and Christopher E Mason},

doi = {10.1101/2021.03.08.434433},

year  = {2021},

date = {2021-01-01},

journal = {bioRxiv},

pages = {2021.03.08.434433},

abstract = {The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.},

keywords = {Publications from COV-IRT},

pubstate = {published},

tppubtype = {article}

}

@article{10.1101/2021.04.23.441024,

title = {The Great Deceiver: miR-2392’s Hidden Role in Driving SARS-CoV-2 Infection},

author = {Tyson J McDonald and Francisco Javier Enguita and Deanne Taylor and Robert J Griffin and Waldemar Priebe and Mark R Emmett and Marisa McGrath and Mohammad M Sajadi and Anthony D Harris and Jean Clement and Joseph M Dybas and Nukhet Aykin-Burns and Joseph W Guarnieri and Larry N Singh and Peter Grabham and Stephen B Baylin and Aliza Yousey and Andrea N Pearson and Peter M Corry and Amanda Saravia-Butler and Thomas R Aunins and Prashant Nagpal and Cem Meydan and Jonathan Foox and Christopher Mozsary and Bianca Cerqueira and Viktorija Zaksas and Urminder Singh and Eve Syrkin Wurtele and Sylvain V Costes and Diego Galeano and Alberto Paccanaro and Suzanne L Meinig and Robert S Hagan and Natalie M Bowman and UNC COVID-19 Pathobiology Consortium and Matthew C Wolfgang and Selin Altinok and Nicolae Sapoval and Todd J Treangen and Matthew Frieman and Charles Vanderburg and Douglas C Wallace and Jonathan Schisler and Christopher E Mason and Anushree Chatterjee and Robert Meller and Afshin Beheshti},

doi = {10.1101/2021.04.23.441024},

year  = {2021},

date = {2021-01-01},

journal = {bioRxiv},

pages = {2021.04.23.441024},

abstract = {MicroRNAs (miRNAs) are small non-coding RNAs involved in post-transcriptional gene regulation that have a major impact on many diseases and provides an exciting avenue towards antiviral therapeutics. From patient transcriptomic data, we have discovered a circulating miRNA, miR-2392, that is directly involved with SARS-CoV-2 machinery during host infection. Specifically, we found that miR-2392 was key in driving downstream suppression of mitochondrial gene expression, increasing inflammation, glycolysis, and hypoxia as well as promoting many symptoms associated with COVID-19 infection. We demonstrate miR-2392 is present in the blood and urine of COVID-19 patients tested, but not detected in COVID-19 negative patients. These findings indicate the potential for developing a novel, minimally invasive, COVID-19 detection method. Lastly, using both in vitro human and in vivo hamster models, we have developed a novel miRNA-based antiviral therapeutic targeting miR-2392 that significantly reduces SARS-CoV-2 viability and may potentially inhibit a COVID-19 disease state in the host.},

keywords = {Publications from COV-IRT},

pubstate = {published},

tppubtype = {article}

}

@article{10.1101/2020.08.29.20184176,

title = {Estimating Unreported Deaths from Natural Causes during COVID-19},

author = {Benjamin Stear and Kyle M Hernandez and Vidya Manian and Deanne Taylor and Catharine A Conley},

doi = {10.1101/2020.08.29.20184176},

year  = {2020},

date = {2020-01-01},

journal = {medRxiv},

pages = {2020.08.29.20184176},

abstract = {Efforts to mitigate the spread of coronavirus disease 2019 (COVID-19) in the United States require an accurate understanding of how the epidemic is progressing. The National Center for Health Statistics (NCHS) releases weekly numbers of deaths attributed to a set of ‘select causes’, including deaths from COVID-19 in the entire United States (US), by state, and cumulatively for individual counties. Comparing US and state level deaths from select causes recorded in 2020 with values from 2014-2019 identifies a number of differences that exceeded 95% confidence limits on historical mean values, including three states with deaths possibly from COVID-19 in December 2019. Comparing county-level NCHS datasets with county-level data on deaths from COVID-19 compiled by four public pandemic tracking sites suggests that a large number of COVID-19 deaths have not yet been reported to the NCHS. Dividing the numbers of COVID-19 deaths counted by the public tracking sites by the percentage of COVID-19 deaths reported to the NCHS suggests that approximately 20% of all US deaths from Natural Causes, as many as 200,000, may not yet have been reported to the NCHS. Evaluating changes in the fractions of deaths attributed to COVID-19 and other specific causes or nonspecific outcomes during the epidemic, relative to 2020 totals or historical mean values, can provide a valuable perspective on the public health consequences of COVID-19. Estimating total deaths from natural causes using the percentage of natural cause deaths from COVID-19 reported to the CDC and the number of COVID-19 deaths counted by public tracking sites suggests that up to 200,000 deaths from natural causes between 22 April and 15 August, 2020, around 20% of the total recorded as of 26 August, have not yet been reported to the CDC.},

keywords = {Publications from COV-IRT},

pubstate = {published},

tppubtype = {article}

}