A Workflow of Integrated Resources to Catalyze Network Pharmacology Driven COVID-19 Research.

In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, host-pathogen, and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy. Here, we describe a workflow we designed for a semiautomated integration of rapidly emerging data sets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 63 278 host-host protein, and 1221 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is made publicly accessible via a web interface and via API calls based on the Bolt protocol. Details for accessing the database are provided on a landing page (https://neo4covid19.ncats.io/). We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19.

A Text Messaging Intervention With Financial Incentive for Adolescents With Type 1 Diabetes.

BACKGROUND: Adolescents with type 1 diabetes (T1D) have higher hemoglobin A1C (HbA1c) levels than others. In general, adolescents engage with text messaging (TM) and financial incentives, both associated with improved diabetes outcomes. This study aimed to assess the impact of a TM intervention with financial incentives on self-care behaviors and HbA1c. METHODS: A six-month randomized controlled trial compared MyDiaText™, a TM education and support application, with standard care. The sample included 166 teens with T1D, 12-18 years old, attending a diabetes clinic. The intervention group received one daily TM and were instructed to respond. Participants who responded to TMs for the most consecutive days were eligible for a financial reward biweekly via lottery. All participants received prompts to complete the self-care inventory (SCI) at baseline, 90, and 180 days. HbA1c was collected at clinic visits. Changes in SCI and HbA1c were analyzed using a multilevel mixed-effects linear regression model. Intention-to-treat and per-protocol analyses were performed. RESULTS: The median TM response rate was 59% (interquartile range 40.1%-85.2%) and decreased over time. After adjustment for baseline characteristics, in per-protocol analysis, there was a statistically significant difference in SCI score increase in those receiving one TM per day vs control (P = .035). HbA1c decreased overall, without significant difference between groups (P = .786). CONCLUSIONS: A TM intervention with financial incentives for adolescents with T1D in suboptimal control was associated with increasing self-care report; however, glycemic control did not differ from controls. Further research is needed to develop digital health interventions that will impact glycemic control.

Undiagnosed SARS-CoV-2 seropositivity during the first 6 months of the COVID-19 pandemic in the United States.

Asymptomatic SARS-CoV-2 infection and delayed implementation of diagnostics have led to poorly defined viral prevalence rates in the United States and elsewhere. To address this, we analyzed seropositivity in 9089 adults in the United States who had not been diagnosed previously with COVID-19. Individuals with characteristics that reflected the U.S. population (n = 27,716) were selected by quota sampling from 462,949 volunteers. Enrolled participants (n = 11,382) provided medical, geographic, demographic, and socioeconomic information and dried blood samples. Survey questions coincident with the Behavioral Risk Factor Surveillance System survey, a large probability-based national survey, were used to adjust for selection bias. Most blood samples (88.7%) were collected between 10 May and 31 July 2020 and were processed using ELISA to measure seropositivity (IgG and IgM antibodies against SARS-CoV-2 spike protein and the spike protein receptor binding domain). The overall weighted undiagnosed seropositivity estimate was 4.6% (95% CI, 2.6 to 6.5%), with race, age, sex, ethnicity, and urban/rural subgroup estimates ranging from 1.1% to 14.2%. The highest seropositivity estimates were in African American participants; younger, female, and Hispanic participants; and residents of urban centers. These data indicate that there were 4.8 undiagnosed SARS-CoV-2 infections for every diagnosed case of COVID-19, and an estimated 16.8 million infections were undiagnosed by mid-July 2020 in the United States.

Mapping a Pandemic: SARS-CoV-2 Seropositivity in the United States.

Asymptomatic SARS-CoV-2 infection and delayed implementation of diagnostics have led to poorly defined viral prevalence rates. To address this, we analyzed seropositivity in US adults who have not previously been diagnosed with COVID-19. Individuals with characteristics that reflect the US population (n = 11,382) and who had not previously been diagnosed with COVID-19 were selected by quota sampling from 241,424 volunteers (ClinicalTrials.gov NCT04334954). Enrolled participants provided medical, geographic, demographic, and socioeconomic information and 9,028 blood samples. The majority (88.7%) of samples were collected between May 10th and July 31st, 2020. Samples were analyzed via ELISA for anti-Spike and anti-RBD antibodies. Estimation of seroprevalence was performed by using a weighted analysis to reflect the US population. We detected an undiagnosed seropositivity rate of 4.6% (95% CI: 2.6 - 6.5%). There was distinct regional variability, with heightened seropositivity in locations of early outbreaks. Subgroup analysis demonstrated that the highest estimated undiagnosed seropositivity within groups was detected in younger participants (ages 18-45, 5.9%), females (5.5%), Black/African American (14.2%), Hispanic (6.1%), and Urban residents (5.3%), and lower undiagnosed seropositivity in those with chronic diseases. During the first wave of infection over the spring/summer of 2020 an estimate of 4.6% of adults had a prior undiagnosed SARS-CoV-2 infection. These data indicate that there were 4.8 (95% CI: 2.8-6.8) undiagnosed cases for every diagnosed case of COVID-19 during this same time period in the United States, and an estimated 16.8 million undiagnosed cases by mid-July 2020.

A Workflow of Integrated Resources to Catalyze Network Pharmacology Driven COVID-19 Research.

MOTIVATION: In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, hostpathogen and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy. RESULTS: Here, we describe a workflow we designed for a semi-automated integration of rapidly emerging datasets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 74,805 host-host protein and 1,265 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is accessible via a web interface and via API calls based on the Bolt protocol. We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19. AVAILABILITY: https://neo4covid19.ncats.io.

MyDiaText™: Feasibililty and Functionality of a Text Messaging System for Youth With Type 1 Diabetes.

PURPOSE: The purpose of this study was to determine the feasibility and functionality of MyDiaText™, a website and text messaging platform created to support behavior change in adolescents with type 1 diabetes (T1DM) and to evaluate user satisfaction of the application. METHODS: This study was a nonrandomized, prospective, pilot trial to test the feasibility and user interface with MyDiaText, a text message system for 10- to 17-year-old youths with newly diagnosed T1DM. Feasibility was evaluated by assessing for the user's ability to create a profile on the website. Functionality was defined by assessing whether a subject responded to at least 2 text messages per week and by their accumulating points on the website. User satisfaction of the text messaging system was assessed using an electronic survey. The 4 phases of this study were community engagement-advisory sessions, screening and enrollment, intervention, and follow-up. RESULTS: Twenty subjects (14 male, 6 female) were enrolled. All subjects were able to create a profile, and of these, 86% responded to at least 2 text messages per week. A survey administered during follow-up showed that users enjoyed reading text messages, found them useful, and thought the frequency of messages was appropriate. CONCLUSION: MyDiaText is a feasible, functional behavioral support tool for youth with T1DM. Users of the application reported high satisfaction with text messages and the reward system.