Clinical and Genomic Epidemiology of Coxsackievirus A21 and Enterovirus D68 in Homeless Shelters, King County, Washington, USA, 2019-2021.

Congregate homeless shelters are disproportionately affected by infectious disease outbreaks. We describe enterovirus epidemiology across 23 adult and family shelters in King County, Washington, USA, during October 2019-May 2021, by using repeated cross-sectional respiratory illness and environmental surveillance and viral genome sequencing. Among 3,281 participants >3 months of age, we identified coxsackievirus A21 (CVA21) in 39 adult residents (3.0% [95% CI 1.9%-4.8%] detection) across 7 shelters during October 2019-February 2020. We identified enterovirus D68 (EV-D68) in 5 adult residents in 2 shelters during October-November 2019. Of 812 environmental samples, 1 was EV-D68-positive and 5 were CVA21-positive. Other enteroviruses detected among residents, but not in environmental samples, included coxsackievirus A6/A4 in 3 children. No enteroviruses were detected during April 2020-May 2021. Phylogenetically clustered CVA21 and EV-D68 cases occurred in some shelters. Some shelters also hosted multiple CVA21 lineages.

Assigning credit where it is due: an information content score to capture the clinical value of multiplexed assays of variant effect.

BACKGROUND: A variant can be pathogenic or benign with relation to a human disease. Current classification categories from benign to pathogenic reflect a probabilistic summary of the current understanding. A primary metric of clinical utility for multiplexed assays of variant effect (MAVE) is the number of variants that can be reclassified from uncertain significance (VUS). However, a gap in this measure of utility is that it underrepresents the information gained from MAVEs. The aim of this study was to develop an improved quantification metric for MAVE utility. We propose adopting an information content approach that includes data that does not reclassify variants will better reflect true information gain. We adopted an information content approach to evaluate the information gain, in bits, for MAVEs of BRCA1, PTEN, and TP53. Here, one bit represents the amount of information required to completely classify a single variant starting from no information. RESULTS: BRCA1 MAVEs produced a total of 831.2 bits of information, 6.58% of the total missense information in BRCA1 and a 22-fold increase over the information that only contributed to VUS reclassification. PTEN MAVEs produced 2059.6 bits of information which represents 32.8% of the total missense information in PTEN and an 85-fold increase over the information that contributed to VUS reclassification. TP53 MAVEs produced 277.8 bits of information which represents 6.22% of the total missense information in TP53 and a 3.5-fold increase over the information that contributed to VUS reclassification. CONCLUSIONS: An information content approach will more accurately portray information gained through MAVE mapping efforts than by counting the number of variants reclassified. This information content approach may also help define the impact of guideline changes that modify the information definitions used to classify groups of variants.

Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements.

CRISPR-based gene activation (CRISPRa) is a strategy for upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis-regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to a library of 493 gRNAs targeting candidate cis-regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically upregulating intended target genes and no other neighboring genes within 1 Mb, including gRNAs yielding upregulation of six autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes in neurons. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans-acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate genes in a cell type-specific manner.

"I probably shouldn't go in today": Inequitable access to paid sick leave and its impacts on health behaviors during the emergence of COVID-19 in the Seattle area.

This study examines inequities in access to paid sick leave (PSL) by race/ethnicity, income, and sex and the role of PSL access on leave-taking and care-seeking behaviors among Seattle-area workers in the months leading up to and during the emergence of COVID-19 in the region. Survey responses were collected online and in-person from individuals experiencing acute respiratory illness symptoms between November 2019 and March 2020 as part of a community-based respiratory viral surveillance study. Chi-square tests and log-binomial models were used to assess the association between PSL access and various socioeconomic indicators. A total of 66.6% (n = 2,276) respondents reported access to PSL. Proportionally, access to PSL was highest in respondents identifying as Asian (70.5%), followed by White (68.7%), Latine (58.4%), Multiracial (57.1%), Black (47.1%), and Other (43.1%). Access to PSL increased with household income. Eighty three percent of high-income respondents reported access compared to 52.9% of low-income households. Only 23.3% of the lowest-income households reported access to PSL. Fewer females (65.2%) than males (70.7%) reported access to PSL. Access to PSL is inequitably distributed across income, race/ethnicity, and sex. This study reinforces the vast body of knowledge on how socioeconomic inequalities increase individual and community-level vulnerability to the impacts of infectious disease outbreaks. It also supports the role of labor and economic policy in mitigating (or exacerbating) these impacts. Exemplified by the COVID-19 pandemic, universal access to PSL, especially for marginalized populations, benefits all.

The proteomic landscape and temporal dynamics of mammalian gastruloid development.

Gastrulation is the highly coordinated process by which the early embryo breaks symmetry, establishes germ layers and a body plan, and sets the stage for organogenesis. As early mammalian development is challenging to study in vivo, stem cell-derived models have emerged as powerful surrogates, e.g. human and mouse gastruloids. However, although single cell RNA-seq (scRNA-seq) and high-resolution imaging have been extensively applied to characterize such in vitro embryo models, a paucity of measurements of protein dynamics and regulation leaves a major gap in our understanding. Here, we sought to address this by applying quantitative proteomics to human and mouse gastruloids at four key stages of their differentiation (naïve ESCs, primed ESCs, early gastruloids, late gastruloids). To the resulting data, we perform network analysis to map the dynamics of expression of macromolecular protein complexes and biochemical pathways, including identifying cooperative proteins that associate with them. With matched RNA-seq and phosphosite data from these same stages, we investigate pathway-, stage- and species-specific aspects of translational and post-translational regulation, e.g. finding peri-gastrulation stages of human and mice to be discordant with respect to the mitochondrial transcriptome vs. proteome, and nominating novel kinase-substrate relationships based on phosphosite dynamics. Finally, we leverage correlated dynamics to identify conserved protein networks centered around congenital disease genes. Altogether, our data (https://gastruloid.brotmanbaty.org/) and analyses showcase the potential of intersecting in vitro embryo models and proteomics to advance our understanding of early mammalian development in ways not possible through transcriptomics alone.

Calibration of variant effect predictors on genome-wide data masks heterogeneous performance across genes.

In silico variant effect predictions are available for nearly all missense variants but played a minimal role in clinical variant classification because they were deemed to provide only supporting evidence. Recently, the ClinGen Sequence Variant Interpretation (SVI) Working Group updated recommendations for variant effect prediction use. By analyzing control pathogenic and benign variants across all genes, they were able to compute evidence strength for predictor score intervals with some intervals generating moderate, strong, or even very strong evidence. However, this genome-wide approach could obscure heterogeneous predictor performance in different genes. We quantified the gene-by-gene performance of two top predictors, REVEL and BayesDel, by analyzing control variants in each predictor score interval in 3,668 disease-relevant genes. Approximately 10% of intervals had sufficient control variants for analysis, and ∼70% of these intervals exceeded the maximum number of incorrect predictions implied by the SVI recommendations. These trending discordant intervals arose owing to the divergence of the gene-specific distribution of predictions from the genome-wide distribution, suggesting that gene-specific calibration is needed in many cases. Approximately 22% of ClinVar missense variants of uncertain significance in genes we analyzed (REVEL = 100,629, BayesDel = 71,928) had predictions in trending discordant intervals. Thus, genome-wide calibrations could result in many variants receiving inappropriate evidence strength. To facilitate a review of the SVI's calibrations, we developed a web application enabling visualization of gene-specific predictions and trending concordant and discordant intervals.

Absenteeism and Health Behavior Trends Associated With Acute Respiratory Illness Before and During the COVID-19 Pandemic in a Community Household Cohort, King County, Washington.

Introduction: Longitudinal data on how acute respiratory illness (ARI) affects behavior, namely school or work participation, and nonpharmaceutical intervention (NPI) usage before and during the COVID-19 pandemic is limited. The authors assessed how ARIs and specific symptoms affected school, work, and health-related behaviors over time. Methods: From November 2019 to June 2021, participating households with children in King County, Washington, were remotely monitored for ARI symptoms weekly. Following ARIs, participants reported illness-related effects on school, work, and NPI use. Using logistic regression with generalized estimating equations, the authors examined associations between symptoms and behaviors. Results: Of 1,861 participants, 581 (31%) from 293 households reported 884 ARIs and completed one-week follow-up surveys. Compared with the prepandemic period, during the period of the pandemic pre-COVID-19 vaccine, ARI-related school (56% vs 10%, p<0.001) absenteeism decreased and masking increased (3% vs 28%, p<0.001). After vaccine authorization in December 2020, more ARIs resulted in masking (3% vs 48%, p<0.001), avoiding contact with non-household members (26% vs 58%, p<0.001), and staying home (37% vs 69%, p<0.001) compared with the prepandemic period. Constitutional symptoms such as fever were associated with work disruptions (OR=1.91; 95% CI=1.06, 3.43), staying home (OR=1.55; 95% CI=1.06, 2.27), and decreased contact with non-household members (OR=1.58; 95% CI=1.05, 2.36). Conclusions: This remote household study permitted uninterrupted tracking of behavioral changes in families with children before and during the COVID-19 pandemic, identifying increased use of some NPIs when ill but no additional illness-associated work or school disruptions.

Evaluation of a novel university-based testing platform to increase access to SARS-CoV-2 testing during the COVID-19 pandemic in a cohort study.

OBJECTIVE: We aimed to evaluate the feasibility and utility of an unsupervised testing mechanism, in which participants pick up a swab kit, self-test (unsupervised) and return the kit to an on-campus drop box, as compared with supervised self-testing at staffed locations. DESIGN: University SARS-CoV-2 testing cohort. SETTING: Husky Coronavirus Testing provided voluntary SARS-CoV-2 testing at a university in Seattle, USA. OUTCOME MEASURES: We computed descriptive statistics to describe the characteristics of the study sample. Adjusted logistic regression implemented via generalised estimating equations was used to estimate the odds of a self-swab being conducted through unsupervised versus supervised testing mechanisms by participant characteristics, including year of study enrolment, pre-Omicron versus post-Omicron time period, age, sex, race, ethnicity, affiliation and symptom status. RESULTS: From September 2021 to July 2022, we received 92 499 supervised and 26 800 unsupervised self-swabs. Among swabs received by the laboratory, the overall error rate for supervised versus unsupervised swabs was 0.3% vs 4%, although this declined to 2% for unsupervised swabs by the spring of the academic year. Results were returned for 92 407 supervised (5% positive) and 25 836 unsupervised (4%) swabs from 26 359 participants. The majority were students (79%), 61% were female and most identified as white (49%) or Asian (34%). The use of unsupervised testing increased during the Omicron wave when testing demand was high and stayed constant in spring 2022 even when testing demand fell. We estimated the odds of using unsupervised versus supervised testing to be significantly greater among those <25 years of age (p<0.001), for Hispanic versus non-Hispanic individuals (OR 1.2, 95% CI 1.0 to 1.3, p=0.01) and lower among individuals symptomatic versus asymptomatic or presymptomatic (0.9, 95% CI 0.8 to 0.9, p<0.001). CONCLUSIONS: Unsupervised swab collection permitted increased testing when demand was high, allowed for access to a broader proportion of the university community and was not associated with a substantial increase in testing errors.

Guidelines for releasing a variant effect predictor.

Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released to date, and there is tremendous variability in their underlying algorithms and outputs, and in the ways in which the methodologies and predictions are shared. This leads to considerable challenges for end users in knowing which VEPs to use and how to use them. Here, to address these issues, we provide guidelines and recommendations for the release of novel VEPs. Emphasising open-source availability, transparent methodologies, clear variant effect score interpretations, standardised scales, accessible predictions, and rigorous training data disclosure, we aim to improve the usability and interpretability of VEPs, and promote their integration into analysis and evaluation pipelines. We also provide a large, categorised list of currently available VEPs, aiming to facilitate the discovery and encourage the usage of novel methods within the scientific community.

Impacts of human mobility on the citywide transmission dynamics of 18 respiratory viruses in pre- and post-COVID-19 pandemic years.

Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.

Defining and Reducing Variant Classification Disparities.

Background: Multiplexed Assays of Variant Effects (MAVEs) can test all possible single variants in a gene of interest. The resulting saturation-style data may help resolve variant classification disparities between populations, especially for variants of uncertain significance (VUS). Methods: We analyzed clinical significance classifications in 213,663 individuals of European-like genetic ancestry versus 206,975 individuals of non-European-like genetic ancestry from All of Us and the Genome Aggregation Database. Then, we incorporated clinically calibrated MAVE data into the Clinical Genome Resource's Variant Curation Expert Panel rules to automate VUS reclassification for BRCA1, TP53, and PTEN . Results: Using two orthogonal statistical approaches, we show a higher prevalence ( p ≤5.95e-06) of VUS in individuals of non-European-like genetic ancestry across all medical specialties assessed in all three databases. Further, in the non-European-like genetic ancestry group, higher rates of Benign or Likely Benign and variants with no clinical designation ( p ≤2.5e-05) were found across many medical specialties, whereas Pathogenic or Likely Pathogenic assignments were higher in individuals of European-like genetic ancestry ( p ≤2.5e-05). Using MAVE data, we reclassified VUS in individuals of non-European-like genetic ancestry at a significantly higher rate in comparison to reclassified VUS from European-like genetic ancestry ( p =9.1e-03) effectively compensating for the VUS disparity. Further, essential code analysis showed equitable impact of MAVE evidence codes but inequitable impact of allele frequency ( p =7.47e-06) and computational predictor ( p =6.92e-05) evidence codes for individuals of non-European-like genetic ancestry. Conclusions: Generation of saturation-style MAVE data should be a priority to reduce VUS disparities and produce equitable training data for future computational predictors.

Comparative Diagnostic Utility of SARS-CoV-2 Rapid Antigen and Molecular Testing in a Community Setting.

BACKGROUND: SARS-CoV-2 antigen-detection rapid diagnostic tests (Ag-RDTs) have become widely utilized but longitudinal characterization of their community-based performance remains incompletely understood. METHODS: This prospective longitudinal study at a large public university in Seattle, WA utilized remote enrollment, online surveys, and self-collected nasal swab specimens to evaluate Ag-RDT performance against real-time reverse transcription polymerase chain reaction (rRT-PCR) in the context of SARS-CoV-2 Omicron. Ag-RDT sensitivity and specificity within 1 day of rRT-PCR were evaluated by symptom status throughout the illness episode and Orf1b cycle threshold (Ct). RESULTS: From February to December 2022, 5757 participants reported 17 572 Ag-RDT results and completed 12 674 rRT-PCR tests, of which 995 (7.9%) were rRT-PCR positive. Overall sensitivity and specificity were 53.0% (95% confidence interval [CI], 49.6%-56.4%) and 98.8% (95% CI, 98.5%-99.0%), respectively. Sensitivity was comparatively higher for Ag-RDTs used 1 day after rRT-PCR (69.0%), 4-7 days after symptom onset (70.1%), and Orf1b Ct ≤20 (82.7%). Serial Ag-RDT sensitivity increased with repeat testing ≥2 (68.5%) and ≥4 (75.8%) days after an initial Ag-RDT-negative result. CONCLUSIONS: Ag-RDT performance varied by clinical characteristics and temporal testing patterns. Our findings support recommendations for serial testing following an initial Ag-RDT-negative result, especially among recently symptomatic persons or those at high risk for SARS-CoV-2 infection.

Remote surveillance and detection of SARS-CoV-2 transmission among household members in King County, Washington.

BACKGROUND: Early during the COVID-19 pandemic, it was important to better understand transmission dynamics of SARS-CoV-2, the virus that causes COVID-19. Household contacts of infected individuals are particularly at risk for infection, but delays in contact tracing, delays in testing contacts, and isolation and quarantine posed challenges to accurately capturing secondary household cases. METHODS: In this study, 346 households in the Seattle region were provided with respiratory specimen collection kits and remotely monitored using web-based surveys for respiratory illness symptoms weekly between October 1, 2020, and June 20, 2021. Symptomatic participants collected respiratory specimens at symptom onset and mailed specimens to the central laboratory in Seattle. Specimens were tested for SARS-CoV-2 using RT-PCR with whole genome sequencing attempted when positive. SARS-CoV-2-infected individuals were notified, and their household contacts submitted specimens every 2 days for 14 days. RESULTS: In total, 1371 participants collected 2029 specimens that were tested; 16 individuals (1.2%) within 6 households tested positive for SARS-CoV-2 during the study period. Full genome sequences were generated from 11 individuals within 4 households. Very little genetic variation was found among SARS-CoV-2 viruses sequenced from different individuals in the same household, supporting transmission within the household. CONCLUSIONS: This study indicates web-based surveillance of respiratory symptoms, combined with rapid and longitudinal specimen collection and remote contact tracing, provides a viable strategy to monitor households and detect household transmission of SARS-CoV-2. TRIAL REGISTRATION IDENTIFIER: NCT04141930, Date of registration 28/10/2019.

Local-scale phylodynamics reveal differential community impact of SARS-CoV-2 in a metropolitan US county.

SARS-CoV-2 transmission is largely driven by heterogeneous dynamics at a local scale, leaving local health departments to design interventions with limited information. We analyzed SARS-CoV-2 genomes sampled between February 2020 and March 2022 jointly with epidemiological and cell phone mobility data to investigate fine scale spatiotemporal SARS-CoV-2 transmission dynamics in King County, Washington, a diverse, metropolitan US county. We applied an approximate structured coalescent approach to model transmission within and between North King County and South King County alongside the rate of outside introductions into the county. Our phylodynamic analyses reveal that following stay-at-home orders, the epidemic trajectories of North and South King County began to diverge. We find that South King County consistently had more reported and estimated cases, COVID-19 hospitalizations, and longer persistence of local viral transmission when compared to North King County, where viral importations from outside drove a larger proportion of new cases. Using mobility and demographic data, we also find that South King County experienced a more modest and less sustained reduction in mobility following stay-at-home orders than North King County, while also bearing more socioeconomic inequities that might contribute to a disproportionate burden of SARS-CoV-2 transmission. Overall, our findings suggest a role for local-scale phylodynamics in understanding the heterogeneous transmission landscape.

Multiplexed Functional Assessments of MYH7 Variants in Human Cardiomyocytes.

BACKGROUND: Pathogenic autosomal-dominant missense variants in MYH7 (myosin heavy chain 7), which encodes the sarcomeric protein (ß-MHC [beta myosin heavy chain]) expressed in cardiac and skeletal myocytes, are a leading cause of hypertrophic cardiomyopathy and are clinically actionable. However, ≈75% of MYH7 missense variants are of unknown significance. While human-induced pluripotent stem cells (hiPSCs) can be differentiated into cardiomyocytes to enable the interrogation of MYH7 variant effect in a disease-relevant context, deep mutational scanning has not been executed using diploid hiPSC derivates due to low hiPSC gene-editing efficiency. Moreover, multiplexable phenotypes enabling deep mutational scanning of MYH7 variant hiPSC-derived cardiomyocytes are unknown. METHODS: To overcome these obstacles, we used CRISPRa On-Target Editing Retrieval enrichment to generate an hiPSC library containing 113 MYH7 codon variants suitable for deep mutational scanning. We first established that ß-MHC protein loss occurs in a hypertrophic cardiomyopathy human heart with a pathogenic MYH7 variant. We then differentiated the MYH7 missense variant hiPSC library to cardiomyocytes for multiplexed assessment of ß-MHC variant abundance by massively parallel sequencing and hiPSC-derived cardiomyocyte survival. RESULTS: Both the multiplexed assessment of ß-MHC abundance and hiPSC-derived cardiomyocyte survival accurately segregated all known pathogenic variants from synonymous variants. Functional data were generated for 4 variants of unknown significance and 58 additional MYH7 missense variants not yet detected in patients. CONCLUSIONS: This study leveraged hiPSC differentiation into disease-relevant cardiomyocytes to enable multiplexed assessments of MYH7 missense variants for the first time. Phenotyping strategies used here enable the application of deep mutational scanning to clinically actionable genes, which should reduce the burden of variants of unknown significance on patients and clinicians.

Utilizing a university testing program to estimate relative effectiveness of monovalent COVID-19 mRNA booster vaccine versus two-dose primary series against symptomatic SARS-CoV-2 infection.

Vaccine effectiveness (VE) studies utilizing the test-negative design are typically conducted in clinical settings, rather than community populations, leading to bias in VE estimates against mild disease and limited information on VE in healthy young adults. In a community-based university population, we utilized data from a large SARS-CoV-2 testing program to estimate relative VE of COVID-19 mRNA vaccine primary series and monovalent booster dose versus primary series only against symptomatic SARS-CoV-2 infection from September 2021 to July 2022. We used the test-negative design and logistic regression implemented via generalized estimating equations adjusted for age, calendar time, prior SARS-CoV-2 infection, and testing frequency (proxy for test-seeking behavior) to estimate relative VE. Analyses included 2,218 test-positive cases (59 % received monovalent booster dose) and 9,615 test-negative controls (62 %) from 9,066 individuals, with median age of 21 years, mostly students (71 %), White (56 %) or Asian (28 %), and with few comorbidities (3 %). More cases (23 %) than controls (6 %) had COVID-19-like illness. Estimated adjusted relative VE of primary series and monovalent booster dose versus primary series only against symptomatic SARS-CoV-2 infection was 40 % (95 % CI: 33-47 %) during the overall analysis period and 46 % (39-52 %) during the period of Omicron circulation. Relative VE was greater for those without versus those with prior SARS-CoV-2 infection (41 %, 34-48 % versus 33 %, 9 %-52 %, P < 0.001). Relative VE was also greater in the six months after receiving a booster dose (41 %, 33-47 %) compared to more than six months (27 %, 8-42 %), but this difference was not statistically significant (P = 0.06). In this relatively young and healthy adult population, an mRNA monovalent booster dose provided increased protection against symptomatic SARS-CoV-2 infection, overall and with the Omicron variant. University testing programs may be utilized for estimating VE in healthy young adults, a population that is not well-represented by routine VE studies.

homeRNA self-blood collection enables high-frequency temporal profiling of pre-symptomatic host immune kinetics to respiratory viral infection: a prospective cohort study.

Background: Early host immunity to acute respiratory infections (ARIs) is heterogenous, dynamic, and critical to an individual's infection outcome. Due to limitations in sampling frequency/timepoints, kinetics of early immune dynamics in natural human infections remain poorly understood. In this nationwide prospective cohort study, we leveraged a self-blood collection tool (homeRNA) to profile detailed kinetics of the pre-symptomatic to convalescence host immunity to contemporaneous respiratory pathogens. Methods: We enrolled non-symptomatic adults with recent exposure to ARIs who subsequently tested negative (exposed-uninfected) or positive for respiratory pathogens. Participants self-collected blood and nasal swabs daily for seven consecutive days followed by weekly blood collection for up to seven additional weeks. Symptom burden was assessed during each collection. Nasal swabs were tested for SARS-CoV-2 and common respiratory pathogens. 92 longitudinal blood samples spanning the pre-shedding to post-acute phase of eight SARS-CoV-2-infected participants and 40 interval-matched samples from four exposed-uninfected participants were subjected to high-frequency longitudinal profiling of 773 host immune genes. Findings: Between June 2021 - April 2022, 68 participants across 26 U.S. states completed the study and self-collected a total of 691 and 466 longitudinal blood and nasal swab samples along with 688 symptom surveys. SARS-CoV-2 was detected in 17 out of 22 individuals with study-confirmed respiratory infection. With rapid dissemination of home self-collection kits, two and four COVID-19+ participants started collection prior to viral shedding and symptom onset, respectively, enabling us to profile detailed expression kinetics of the earliest blood transcriptional response to contemporaneous variants of concern. In pre-shedding samples, we observed transient but robust expression of T-cell response signatures, transcription factor complexes, prostaglandin biosynthesis genes, pyrogenic cytokines, and cytotoxic granule genes. This is followed by a rapid induction of many interferon-stimulated genes (ISGs), concurrent to onset of viral shedding and increase in nasal viral load. Finally, we observed increased expression of host defense peptides (HDPs) in exposed-uninfected individuals over the 4-week observational window. Interpretation: We demonstrated that unsupervised self-collection and stabilization of capillary blood can be applied to natural infection studies to characterize detailed early host immune kinetics at a temporal resolution comparable to that of human challenge studies. The remote (decentralized) study framework enables conduct of large-scale population-wide longitudinal mechanistic studies. Expression of cytotoxic/T-cell signatures in pre-shedding samples preceding expansion of innate ISGs suggests a potential role for T-cell mediated pathogen control during early infection. Elevated expression of HDPs in exposed-uninfected individuals warrants further validation studies to assess their potential role in protective immunity during pathogen exposure. Funding: This study was funded by R35GM128648 to ABT for in-lab developments of homeRNA, Packard Fellowship from the David and Lucile Packard Foundation to ABT, and R01AI153087 to AW.

Tiny swabs: nasal swabs integrated into tube caps facilitate large-scale self-collected SARS-CoV-2 testing.

The COVID-19 pandemic spurred the development of innovative solutions for specimen collection and molecular detection for large-scale community testing. Among these developments is the RHINOstic nasal swab, a plastic anterior nares swab built into the cap of a standard matrix tube that facilitates automated processing of up to 96 specimens at a time. In a study of unsupervised self-collection utilizing these swabs, we demonstrate comparable analytic performance and shipping stability compared to traditional anterior nares swabs, as well as significant improvements in laboratory processing efficiency. The use of these swabs may allow laboratories to accommodate large numbers of sample collections during periods of high testing demand. Automation-friendly nasal swabs are an important tool for high-throughput processing of samples that may be adopted in response to future respiratory viral pandemics.