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Article ; Online: SARS-CoV-2 strategically mimics proteolytic activation of human ENaC

Praveen Anand / Arjun Puranik / Murali Aravamudan / AJ Venkatakrishnan / Venky Soundararajan

eLife, Vol

2020 Volume 9

Abstract: Molecular mimicry is an evolutionary strategy adopted by viruses to exploit the host cellular machinery. We report that SARS-CoV-2 has evolved a unique S1/S2 cleavage site, absent in any previous coronavirus sequenced, resulting in the striking mimicry ... ...

Abstract	Molecular mimicry is an evolutionary strategy adopted by viruses to exploit the host cellular machinery. We report that SARS-CoV-2 has evolved a unique S1/S2 cleavage site, absent in any previous coronavirus sequenced, resulting in the striking mimicry of an identical FURIN-cleavable peptide on the human epithelial sodium channel α-subunit (ENaC-α). Genetic alteration of ENaC-α causes aldosterone dysregulation in patients, highlighting that the FURIN site is critical for activation of ENaC. Single cell RNA-seq from 66 studies shows significant overlap between expression of ENaC-α and the viral receptor ACE2 in cell types linked to the cardiovascular-renal-pulmonary pathophysiology of COVID-19. Triangulating this cellular characterization with cleavage signatures of 178 proteases highlights proteolytic degeneracy wired into the SARS-CoV-2 lifecycle. Evolution of SARS-CoV-2 into a global pandemic may be driven in part by its targeted mimicry of ENaC-α, a protein critical for the homeostasis of airway surface liquid, whose misregulation is associated with respiratory conditions.
Keywords	molecular mimicry ; ENaC ; acute respiratory distress syndrome ; SARS-CoV-2 ; COVID-19 ; coronavirus ; Medicine ; R ; Science ; Q ; Biology (General) ; QH301-705.5
Subject code	572
Language	English
Publishing date	2020-05-01T00:00:00Z
Publisher	eLife Sciences Publications Ltd
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Enoxaparin is associated with lower rates of mortality than unfractionated Heparin in hospitalized COVID-19 patients

Colin Pawlowski / AJ Venkatakrishnan / Christian Kirkup / Gabriela Berner / Arjun Puranik / John C. O'Horo / Andrew D. Badley / Venky Soundararajan

EClinicalMedicine, Vol 33, Iss , Pp 100774- (2021)

2021

Abstract: Background: Coagulopathies are a major class among COVID-19 associated complications. Although anticoagulants such as unfractionated Heparin and Enoxaparin are both being used for therapeutic mitigation of COVID associated coagulopathy (CAC), differences ...

Abstract	Background: Coagulopathies are a major class among COVID-19 associated complications. Although anticoagulants such as unfractionated Heparin and Enoxaparin are both being used for therapeutic mitigation of COVID associated coagulopathy (CAC), differences in their clinical outcomes remain to be investigated. Methods: We analyzed records of 1,113 patients in the Mayo Clinic Electronic Health Record (EHR) database who were admitted to the hospital for COVID-19 between April 4, 2020 and August 31, 2020, including 19 different Mayo Clinic sites in Arizona, Florida, Minnesota, and Wisconsin. Among this patient population, we compared cohorts of patients who received different types of anticoagulants, including 441 patients who received unfractionated Heparin and 166 patients who received Enoxaparin. Clinical outcomes at 28 days were compared, and propensity score matching was used to control for potential confounding variables including: demographics, comorbidities, ICU status, chronic kidney disease stage, and oxygenation status. Patients with a history of acute kidney injury and patients who received multiple types of anticoagulants were excluded from the study. Findings: We find that COVID-19 patients administered unfractionated Heparin but not Enoxaparin have higher rates of 28-day mortality (risk ratio: 4.3; 95% Confidence Interval [C.I.].: [1.8, 10.2]; p-value: 8.5e−4, Benjamini Hochberg [BH] adjusted p-value: 2.1e−3), after controlling for potential confounding factors. Interpretation: This study emphasizes the need for mechanistically investigating differential modulation of the COVID-associated coagulation cascades by Enoxaparin versus unfractionated Heparin. Funding: This work was supported by Nference, inc.
Keywords	Medicine (General) ; R5-920
Subject code	610
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Pre-existing conditions are associated with COVID-19 patients’ hospitalization, despite confirmed clearance of SARS-CoV-2 virus

Colin Pawlowski / AJ Venkatakrishnan / Eshwan Ramudu / Christian Kirkup / Arjun Puranik / Nikhil Kayal / Gabriela Berner / Akash Anand / Rakesh Barve / John C. O'Horo / Andrew D. Badley / Venky Soundararajan

EClinicalMedicine, Vol 34, Iss , Pp 100793- (2021)

2021

Abstract: Background: Consecutive negative SARS-CoV-2 PCR test results are being considered to estimate viral clearance in COVID-19 patients. However, there are anecdotal reports of hospitalization from protracted COVID-19 complications despite such confirmed ... ...

Abstract	Background: Consecutive negative SARS-CoV-2 PCR test results are being considered to estimate viral clearance in COVID-19 patients. However, there are anecdotal reports of hospitalization from protracted COVID-19 complications despite such confirmed viral clearance, presenting a clinical conundrum. Methods: We conducted a retrospective analysis of 222 hospitalized COVID-19 patients to compare those that were readmitted post-viral clearance (hospitalized post-clearance cohort, n = 49) with those that were not re-admitted post-viral clearance (non-hospitalized post-clearance cohort, n = 173) between February and October 2020. In order to differentiate these two cohorts, we used neural network models for the ‘augmented curation’ of comorbidities and complications with positive sentiment in the Electronic Hosptial Records physician notes. Findings: In the year preceding COVID-19 onset, anemia (n = 13 [26.5%], p-value: 0.007), cardiac arrhythmias (n = 14 [28.6%], p-value: 0.015), and acute kidney injury (n = 7 [14.3%], p-value: 0.030) were significantly enriched in the physician notes of the hospitalized post-clearance cohort. Interpretation: Overall, this retrospective study highlights specific pre-existing conditions that are associated with higher hospitalization rates in COVID-19 patients despite viral clearance and motivates follow-up prospective research into the associated risk factors. Funding: This work was supported by Nference, inc.
Keywords	Medicine (General) ; R5-920
Subject code	610
Language	English
Publishing date	2021-04-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Exploratory analysis of immunization records highlights decreased SARS-CoV-2 rates in individuals with recent non-COVID-19 vaccinations

Colin Pawlowski / Arjun Puranik / Hari Bandi / A. J. Venkatakrishnan / Vineet Agarwal / Richard Kennedy / John C. O’Horo / Gregory J. Gores / Amy W. Williams / John Halamka / Andrew D. Badley / Venky Soundararajan

Scientific Reports, Vol 11, Iss 1, Pp 1-

2021 Volume 20

Abstract: Abstract Clinical studies are ongoing to assess whether existing vaccines may afford protection against SARS-CoV-2 infection through trained immunity. In this exploratory study, we analyze immunization records from 137,037 individuals who received SARS- ... ...

Abstract	Abstract Clinical studies are ongoing to assess whether existing vaccines may afford protection against SARS-CoV-2 infection through trained immunity. In this exploratory study, we analyze immunization records from 137,037 individuals who received SARS-CoV-2 PCR tests. We find that polio, Haemophilus influenzae type-B (HIB), measles-mumps-rubella (MMR), Varicella, pneumococcal conjugate (PCV13), Geriatric Flu, and hepatitis A/hepatitis B (HepA–HepB) vaccines administered in the past 1, 2, and 5 years are associated with decreased SARS-CoV-2 infection rates, even after adjusting for geographic SARS-CoV-2 incidence and testing rates, demographics, comorbidities, and number of other vaccinations. Furthermore, age, race/ethnicity, and blood group stratified analyses reveal significantly lower SARS-CoV-2 rate among black individuals who have taken the PCV13 vaccine, with relative risk of 0.45 at the 5 year time horizon (n: 653, 95% CI (0.32, 0.64), p-value: 6.9e−05). Overall, this study identifies existing approved vaccines which can be promising candidates for pre-clinical research and Randomized Clinical Trials towards combating COVID-19.
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications

A. J. Venkatakrishnan / Colin Pawlowski / David Zemmour / Travis Hughes / Akash Anand / Gabriela Berner / Nikhil Kayal / Arjun Puranik / Ian Conrad / Sairam Bade / Rakesh Barve / Purushottam Sinha / John C. O‘Horo / Andrew D. Badley / John Halamka / Venky Soundararajan

npj Digital Medicine, Vol 4, Iss 1, Pp 1-

2021 Volume 11

Abstract: Abstract Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized ... ...

Abstract	Abstract Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0–30 days, 31–60 days, and 61–90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (89/1803 patients, 4.9%) followed by cardiac arrhythmia (45/1803 patients, 2.5%). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia, and anemia. The onset of new complications after 30 days is rare and most commonly involves pleural effusion (31–60 days: 11 patients, 61–90 days: 9 patients). Lastly, comparing the rates of complications with a propensity-matched COVID-negative hospitalized population confirmed the importance of hypertension as a risk factor for early-onset complications. Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	610 ; 616
Language	English
Publishing date	2021-07-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Knowledge synthesis from 100 million biomedical documents augments the deep expression profiling of coronavirus receptors

AJ Venkatakrishnan / Arjun Puranik / Akash Anand / David Zemmour / Xiang Yao / Xiaoying Wu / Ramakrishna Chilaka / Dariusz Murakowski K. / Kristopher Standish / Bharathwaj Raghunathan / Tyler Wagner / Enrique Garcia-Rivera / Hugo Solomon / Abhinav Garg / Rakesh Barve / Anuli Anyanwu-Ofili / Najat Khan / Venky Soundararajan

Abstract: The COVID-19 pandemic demands assimilation of all available biomedical knowledge to decode its mechanisms of pathogenicity and transmission. Despite the recent renaissance in unsupervised neural networks for decoding unstructured natural languages, a ... ...

Abstract	The COVID-19 pandemic demands assimilation of all available biomedical knowledge to decode its mechanisms of pathogenicity and transmission. Despite the recent renaissance in unsupervised neural networks for decoding unstructured natural languages, a platform for the real-time synthesis of the exponentially growing biomedical literature and its comprehensive triangulation with deep omic insights is not available. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations extracted from unstructured biomedical text, and their triangulation with Single Cell RNA-sequencing based insights from over 25 tissues. Using this platform, we identify intersections between the pathologic manifestations of COVID-19 and the comprehensive expression profile of the SARS-CoV-2 receptor ACE2. We find that tongue keratinocytes and olfactory epithelial cells are likely under-appreciated targets of SARS-CoV-2 infection, correlating with reported loss of sense of taste and smell as early indicators of COVID-19 infection, including in otherwise asymptomatic patients. Airway club cells, ciliated cells and type II pneumocytes in the lung, and enterocytes of the gut also express ACE2. This study demonstrates how a holistic data science platform can leverage unprecedented quantities of structured and unstructured publicly available data to accelerate the generation of impactful biological insights and hypotheses.
Keywords	covid19
Publisher	arxiv
Document type	Article
Database	COVID19

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Article ; Online: Knowledge synthesis of 100 million biomedical documents augments the deep expression profiling of coronavirus receptors

AJ Venkatakrishnan / Arjun Puranik / Akash Anand / David Zemmour / Xiang Yao / Xiaoying Wu / Ramakrishna Chilaka / Dariusz K Murakowski / Kristopher Standish / Bharathwaj Raghunathan / Tyler Wagner / Enrique Garcia-Rivera / Hugo Solomon / Abhinav Garg / Rakesh Barve / Anuli Anyanwu-Ofili / Najat Khan / Venky Soundararajan

eLife, Vol

2020 Volume 9

Abstract: The COVID-19 pandemic demands assimilation of all biomedical knowledge to decode mechanisms of pathogenesis. Despite the recent renaissance in neural networks, a platform for the real-time synthesis of the exponentially growing biomedical literature and ... ...

Abstract	The COVID-19 pandemic demands assimilation of all biomedical knowledge to decode mechanisms of pathogenesis. Despite the recent renaissance in neural networks, a platform for the real-time synthesis of the exponentially growing biomedical literature and deep omics insights is unavailable. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations from unstructured text, and triangulation with insights from single-cell RNA-sequencing, bulk RNA-seq and proteomics from diverse tissue types. A hypothesis-free profiling of ACE2 suggests tongue keratinocytes, olfactory epithelial cells, airway club cells and respiratory ciliated cells as potential reservoirs of the SARS-CoV-2 receptor. We find the gut as the putative hotspot of COVID-19, where a maturation correlated transcriptional signature is shared in small intestine enterocytes among coronavirus receptors (ACE2, DPP4, ANPEP). A holistic data science platform triangulating insights from structured and unstructured data holds potential for accelerating the generation of impactful biological insights and hypotheses.
Keywords	COVID-19 ; SARS-CoV-2 ; single cell RNA-seq ; natural language processing ; artificial intelligence ; machine learning ; Medicine ; R ; Science ; Q ; Biology (General) ; QH301-705.5
Language	English
Publishing date	2020-05-01T00:00:00Z
Publisher	eLife Sciences Publications Ltd
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Inference from longitudinal laboratory tests characterizes temporal evolution of COVID-19-associated coagulopathy (CAC)

Colin Pawlowski / Tyler Wagner / Arjun Puranik / Karthik Murugadoss / Liam Loscalzo / AJ Venkatakrishnan / Rajiv K Pruthi / Damon E Houghton / John C O'Horo / William G Morice II / Amy W Williams / Gregory J Gores / John Halamka / Andrew D Badley / Elliot S Barnathan / Hideo Makimura / Najat Khan / Venky Soundararajan

eLife, Vol

2020 Volume 9

Abstract: Temporal inference from laboratory testing results and triangulation with clinical outcomes extracted from unstructured electronic health record (EHR) provider notes is integral to advancing precision medicine. Here, we studied 246 SARS-CoV-2 PCR- ... ...

Abstract	Temporal inference from laboratory testing results and triangulation with clinical outcomes extracted from unstructured electronic health record (EHR) provider notes is integral to advancing precision medicine. Here, we studied 246 SARS-CoV-2 PCR-positive (COVIDpos) patients and propensity-matched 2460 SARS-CoV-2 PCR-negative (COVIDneg) patients subjected to around 700,000 lab tests cumulatively across 194 assays. Compared to COVIDneg patients at the time of diagnostic testing, COVIDpos patients tended to have higher plasma fibrinogen levels and lower platelet counts. However, as the infection evolves, COVIDpos patients distinctively show declining fibrinogen, increasing platelet counts, and lower white blood cell counts. Augmented curation of EHRs suggests that only a minority of COVIDpos patients develop thromboembolism, and rarely, disseminated intravascular coagulopathy (DIC), with patients generally not displaying platelet reductions typical of consumptive coagulopathies. These temporal trends provide fine-grained resolution into COVID-19 associated coagulopathy (CAC) and set the stage for personalizing thromboprophylaxis.
Keywords	laboratory tests ; COVID-19 ; electronic health record (EHR) ; SARS-CoV-2 ; coagulation ; thrombolytic agents ; Medicine ; R ; Science ; Q ; Biology (General) ; QH301-705.5
Subject code	610
Language	English
Publishing date	2020-08-01T00:00:00Z
Publisher	eLife Sciences Publications Ltd
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Augmented Curation of Unstructured Clinical Notes from a Massive EHR System Reveals Specific Phenotypic Signature of Impending COVID-19 Diagnosis

FNU Shweta / Karthik Murugadoss / Samir Awasthi / AJ Venkatakrishnan / Arjun Puranik / Martin Kang / Brian Pickering W. / John O'Horo C. / Philippe Bauer R. / Raymund Razonable R. / Paschalis Vergidis / Zelalem Temesgen / Stacey Rizza / Maryam Mahmood / Walter Wilson R. / Douglas Challener / Praveen Anand / Matt Liebers / Zainab Doctor /

Eli Silvert / Hugo Solomon / Tyler Wagner / Gregory Gores J. / Amy Williams W. / John Halamka / Venky Soundararajan / Andrew Badley D.

Abstract: Understanding the temporal dynamics of COVID-19 patient phenotypes is necessary to derive fine-grained resolution of pathophysiology. Here we use state-of-the-art deep neural networks over an institution-wide machine intelligence platform for the ... ...

Abstract	Understanding the temporal dynamics of COVID-19 patient phenotypes is necessary to derive fine-grained resolution of pathophysiology. Here we use state-of-the-art deep neural networks over an institution-wide machine intelligence platform for the augmented curation of 15.8 million clinical notes from 30,494 patients subjected to COVID-19 PCR diagnostic testing. By contrasting the Electronic Health Record (EHR)-derived clinical phenotypes of COVID-19-positive (COVIDpos, n=635) versus COVID-19-negative (COVIDneg, n=29,859) patients over each day of the week preceding the PCR testing date, we identify anosmia/dysgeusia (37.4-fold), myalgia/arthralgia (2.6-fold), diarrhea (2.2-fold), fever/chills (2.1-fold), respiratory difficulty (1.9-fold), and cough (1.8-fold) as significantly amplified in COVIDpos over COVIDneg patients. The specific combination of cough and diarrhea has a 3.2-fold amplification in COVIDpos patients during the week prior to PCR testing, and along with anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19 (4-7 days prior to typical PCR testing date). This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional knowledge captured in EHRs. The platform holds tremendous potential for scaling up curation throughput, with minimal need for retraining underlying neural networks, thus promising EHR-powered early diagnosis for a broad spectrum of diseases.
Keywords	covid19
Publisher	arxiv
Document type	Article
Database	COVID19

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Article ; Online: Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis

Tyler Wagner / FNU Shweta / Karthik Murugadoss / Samir Awasthi / AJ Venkatakrishnan / Sairam Bade / Arjun Puranik / Martin Kang / Brian W Pickering / John C O'Horo / Philippe R Bauer / Raymund R Razonable / Paschalis Vergidis / Zelalem Temesgen / Stacey Rizza / Maryam Mahmood / Walter R Wilson / Douglas Challener / Praveen Anand /

Matt Liebers / Zainab Doctor / Eli Silvert / Hugo Solomon / Akash Anand / Rakesh Barve / Gregory Gores / Amy W Williams / William G Morice II / John Halamka / Andrew Badley / Venky Soundararajan

eLife, Vol

2020 Volume 9

Abstract: Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 ... ...

Abstract	Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVIDpos; n = 2,317) versus COVID-19-negative (COVIDneg; n = 74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVIDpos over COVIDneg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVIDpos patients during the week prior to PCR testing, in addition to anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.
Keywords	electronic health record ; neural networks ; machine learning ; artificial intelligence ; COVID-19 ; SARS-CoV-2 ; Medicine ; R ; Science ; Q ; Biology (General) ; QH301-705.5
Subject code	610
Language	English
Publishing date	2020-07-01T00:00:00Z
Publisher	eLife Sciences Publications Ltd
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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