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ImportanceMost research to understand postacute sequelae of SARS-CoV-2 infection (PASC), or long COVID, has focused on adults, with less known about this complex condition in children. Research is needed to characterize pediatric PASC to enable studies of underlying mechanisms that will guide future treatment.ObjectiveTo identify the most common prolonged symptoms experienced by children (aged 6 to 17 years) after SARS-CoV-2 infection, how these symptoms differ by age (school-age [6-11 years] vs adolescents [12-17 years]), how they cluster into distinct phenotypes, and what symptoms in combination could be used as an empirically derived index to assist researchers to study the likely presence of PASC.Design, setting, and participantsMulticenter longitudinal observational cohort study with participants recruited from more than 60 US health care and community settings between March 2022 and December 2023, including school-age children and adolescents with and without SARS-CoV-2 infection history.ExposureSARS-CoV-2 infection.Main outcomes and measuresPASC and 89 prolonged symptoms across 9 symptom domains.ResultsA total of 898 school-age children (751 with previous SARS-CoV-2 infection [referred to as infected] and 147 without [referred to as uninfected]; mean age, 8.6 years; 49% female; 11% were Black or African American, 34% were Hispanic, Latino, or Spanish, and 60% were White) and 4469 adolescents (3109 infected and 1360 uninfected; mean age, 14.8 years; 48% female; 13% were Black or African American, 21% were Hispanic, Latino, or Spanish, and 73% were White) were included. Median time between first infection and symptom survey was 506 days for school-age children and 556 days for adolescents. In models adjusted for sex and race and ethnicity, 14 symptoms in both school-age children and adolescents were more common in those with SARS-CoV-2 infection history compared with those without infection history, with 4 additional symptoms in school-age children only and 3 in adolescents only. These symptoms affected almost every organ system. Combinations of symptoms most associated with infection history were identified to form a PASC research index for each age group; these indices correlated with poorer overall health and quality of life. The index emphasizes neurocognitive, pain, and gastrointestinal symptoms in school-age children but change or loss in smell or taste, pain, and fatigue/malaise-related symptoms in adolescents. Clustering analyses identified 4 PASC symptom phenotypes in school-age children and 3 in adolescents.Conclusions and relevanceThis study developed research indices for characterizing PASC in children and adolescents. Symptom patterns were similar but distinguishable between the 2 groups, highlighting the importance of characterizing PASC separately for these age ranges.

IMPORTANCE: The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or Long COVID) in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults. OBSERVATIONS: We describe the protocol for the Pediatric Observational Cohort Study of the NIHs REsearching COVID to Enhance Recovery (RECOVER) Initiative. RECOVER-Pediatrics is an observational meta-cohort study of caregiver-child pairs (birth through 17 years) and young adults (18 through 25 years), recruited from more than 100 sites across the US. This report focuses on two of four cohorts that comprise RECOVER-Pediatrics: 1) a de novo RECOVER prospective cohort of children and young adults with and without previous or current infection; and 2) an extant cohort derived from the Adolescent Brain Cognitive Development (ABCD) study (n = 10,000). The de novo cohort incorporates three tiers of data collection: 1) remote baseline assessments (Tier 1, n = 6000); 2) longitudinal follow-up for up to 4 years (Tier 2, n = 6000); and 3) a subset of participants, primarily the most severely affected by PASC, who will undergo deep phenotyping to explore PASC pathophysiology (Tier 3, n = 600). Youth enrolled in the ABCD study participate in Tier 1. The pediatric protocol was developed as a collaborative partnership of investigators, patients, researchers, clinicians, community partners, and federal partners, intentionally promoting inclusivity and diversity. The protocol is adaptive to facilitate responses to emerging science. CONCLUSIONS AND RELEVANCE: RECOVER-Pediatrics seeks to characterize the clinical course, underlying mechanisms, and long-term effects of PASC from birth through 25 years old. RECOVER-Pediatrics is designed to elucidate the epidemiology, four-year clinical course, and sociodemographic correlates of pediatric PASC. The data and biosamples will allow examination of mechanistic hypotheses and biomarkers, thus providing insights into potential therapeutic interventions. CLINICAL TRIALS.GOV IDENTIFIER: Clinical Trial Registration: http://www.clinicaltrials.gov. Unique identifier: NCT05172011.

African Americans are disproportionately exposed to adversity across the lifespan, which includes both stressful and traumatic events. Adversity, in turn, is associated with alterations in pain responsiveness. Racial differences in pain responsiveness among healthy adults are well established. However, the extent to which adversity type and timing are associated with alterations in pain responsiveness among healthy African-American adults is not well understood. The present study included 160 healthy African-American adults (98 women), ages 18 to 45. Outcome measures included pain tolerance and temporal summation of pain to evoked thermal pain. Composite scores were created for early-life adversity (childhood trauma, family adversity) and recent adversity (perceived stress, chronic stress burden). A measure of lifetime racial discrimination was also included. Higher levels of recent adversity were associated with higher temporal summation of pain, controlling for gender, age, and education. Neither early-life adversity nor lifetime racial discrimination were associated with temporal summation of pain. The present findings suggest that heightened temporal summation of pain among healthy African-American adults is associated with exposure to recent adversity events. Improved understanding of how recent adversity contributes to heightened temporal summation of pain in African Americans could help to mitigate racial disparities in pain experiences by identifying at-risk individuals who could benefit from early interventions.

INTRODUCTION: Prior research suggests that African Americans (AAs) have more frequent, intense, and debilitating pain and functional disability compared with non-Hispanic Whites (NHWs). Potential contributing factors to this disparity are physical activity and sedentary behavior, given that AAs are less physically active, and physical activity is associated with antinociception (whereas sedentary behavior is linked to pronociception). However, impact of these factors on pain processing has largely been unexplored in AAs, especially before chronic pain onset. OBJECTIVE: This study examined relationships between physical activity, sedentary behavior (sitting time), and laboratory measures of pain and pain modulation in adult AAs. These included heat pain threshold and tolerance, temporal summation of pain (TSP, a marker of central sensitization), and conditioned pain modulation (CPM, a marker of descending pain inhibition). METHODS: Multiple regressions were conducted to examine the effects of physical activity and sitting time on heat threshold and tolerance. Multilevel models were conducted to assess the relationship between physical activity, sitting time, and temporal summation of pain. Additional multilevel models were conducted to assess the relationship between physical activity, sitting time, and conditioned pain modulation. RESULTS: Higher level of physical activity, but not sitting time, was associated with reduced TSP slopes. Neither physical activity nor sitting time was associated with CPM slopes. No significant relationships between physical activity or sitting time and heat pain threshold or tolerance were detected. CONCLUSIONS: These findings suggest that physical activity is associated with reduced TSP, an effect which may be driven by reduced spinal hyperexcitability in more active individuals. Thus, structural and individual interventions designed to increase physical activity in healthy, young AAs may be able to promote antinociceptive processes (ie, reduced TSP/reduced pain facilitation) potentially protective against chronic pain.

Objective: To summarize the prevalence of Long COVID symptoms among the general population reported in published articles from the pre-omicron SARS-CoV2 era. This narrative review examined 21 symptoms. Methods: A PubMed/manual search returned 114 articles on general Long COVID symptoms. Manuscripts were excluded if they were not research studies, did not report symptom prevalence, or used a pediatric population. Ninety-eight studies were selected for review and fifty-nine met the criteria for inclusion. The risk of bias was assessed with the Hoy critical appraisal tool. Results: After excluding studies with a high risk of bias, meta-analysis of prevalence for 21 symptom categories ranged from 2.6–28.7% in studies based on surveys to 0.3–7.1% in studies based on electronic health record data. Conclusions: Long COVID symptom studies are limited by the variability in study design and representation of the general population. Further research is needed to effectively cluster symptoms in meaningful ways that enable focused treatment.

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed the effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N = 491,111) and African (N = 21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best- and worst-performing quintiles for certain covariates. Twenty-eight covariates had significant PGSBMI–covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects – across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account nonlinear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge genome-wide association studies effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

Purpose The coronavirus disease 2019 (COVID-19) pandemic has led to an association between COVID-19 and pediatric diabetes. Studies have indicated the increased likelihood of children with COVID-19 infection developing diabetes. Our objective was to assess not only the increase in pediatric diabetes at our hospital and identify possible risk factors, but also to correlate the psychosocial changes resulting from the pandemic with new-onset diabetes. Methods We analyzed data from 58 children aged 1 to 18 years admitted to our hospital with new-onset diabetes between March 2020 and December 2021. The data included inflammatory biomarkers and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies (Abs), as well as the results of a lifestyle questionnaire. Results The average number of hospital admissions per month for new-onset diabetes increased from 10 to 18 with the start of the pandemic. Of the 58 children in our analysis, 33% had positive SARS-CoV-2 IgG Ab, 31% had type 1 diabetes mellitus, and 62% had type 2 diabetes mellitus (T2DM). More than half (54%) were experiencing diabetic ketoacidosis. Those with T2DM were older, majority African American, had higher median body mass index (BMI) percentiles, and lower vitamin D levels. There were no significant correlations between any psychosocial risk factors and either diabetes type or SARS-CoV2 Ab status. Conclusions Despite the increased incidence of new-onset diabetes among children in Mississippi during the pandemic, this study was unable to demonstrate a significant correlation between COVID-19 infection and new-onset diabetes. The findings of this study highlighted the correlation between increased BMI and type 2 diabetes, underscoring the significant problems of obesity and diabetes in our study region. Further research is warranted.

Abstract: Importance: SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis. Methods: RECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility– and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross– validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms. Discussion: RECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options.

Accurate, highly specific immunoassays for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are needed to evaluate seroprevalence. This study investigated the concordance of results across four immunoassays targeting different antigens for sera collected at the beginning of the SARS-CoV-2 pandemic in the United States. Specimens from All of Us participants contributed between January and March 2020 were tested using the Abbott Architect SARS-CoV-2 IgG (immunoglobulin G) assay (Abbott) and the EuroImmun SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA) (EI). Participants with discordant results, participants with concordant positive results, and a subset of concordant negative results by Abbott and EI were also tested using the Roche Elecsys anti-SARS-CoV-2 (IgG) test (Roche) and the Ortho-Clinical Diagnostics Vitros anti-SARS-CoV-2 IgG test (Ortho). The agreement and 95% confidence intervals were estimated for paired assay combinations. SARS-CoV-2 antibody concentrations were quantified for specimens with at least two positive results across four immunoassays. Among the 24,079 participants, the percent agreement for the Abbott and EI assays was 98.8% (95% confidence interval, 98.7%, 99%). Of the 490 participants who were also tested by Ortho and Roche, the probability-weighted percentage of agreement (95% confidence interval) between Ortho and Roche was 98.4% (97.9%, 98.9%), that between EI and Ortho was 98.5% (92.9%, 99.9%), that between Abbott and Roche was 98.9% (90.3%, 100.0%), that between EI and Roche was 98.9% (98.6%, 100.0%), and that between Abbott and Ortho was 98.4% (91.2%, 100.0%). Among the 32 participants who were positive by at least 2 immunoassays, 21 had quantifiable anti-SARS-CoV-2 antibody concentrations by research assays. The results across immunoassays revealed concordance during a period of low prevalence. However, the frequency of false positivity during a period of low prevalence supports the use of two sequentially performed tests for unvaccinated individuals who are seropositive by the first test. IMPORTANCE What is the agreement of commercial SARS-CoV-2 immunoglobulin G (IgG) assays during a time of low coronavirus disease 2019 (COVID-19) prevalence and no vaccine availability? Serological tests produced concordant results in a time of low SARS-CoV-2 prevalence and no vaccine availability, driven largely by the proportion of samples that were negative by two immunoassays. The CDC recommends two sequential tests for positivity for future pandemic preparedness. In a subset analysis, quantified antinucleocapsid and antispike SARS-CoV-2 IgG antibodies do not suggest the need to specify the antigen targets of the sequential assays in the CDC's recommendation because false positivity varied as much between assays targeting the same antigen as it did between assays targeting different antigens.

Abstract Nitrogen isotope analyses of amino acids (δ15N‐AA) are being increasingly used to decipher trophic dynamics. Interpretation of δ15N‐AA in consumers relies on the assumption that consumer physiological status and nutritional status of prey have negligible influences on the trophic discrimination factor (TDF), hence a constant TDF value is used in trophic position (TP) equations. Recent experiments have shown that this is not always the case and there is also a need to validate derived TP estimates in the field. We take advantage of the uniquely long time series of environmental monitoring data and archived (frozen) samples from the species‐poor Baltic Sea. We analyzed δ15N‐AA in similar sized individuals of cod and in its prey herring from four decades, 1980–2018; including time periods where dramatic reduction in condition status of cod has occurred. We expected that TDF in trophic AAs would increase during periods of poor cod condition, resulting in inflated TP estimates. We found that calculated TP and empirical estimates of TDF (difference in δ15N in trophic AAs between cod and herring) for cod increased in recent decades and that this was linked to condition status, herring (prey) lipid content and the hypoxic state of the ecosystem. Statistically adjusting TP for condition and prey lipid content as well as environmental stress (hypoxia) resulted in lower cod TP which better resembled the observed decrease in herring TP in recent decades. TP calculated from stomach analysis data in cod individuals over the same period showed no trend over time and confirmed that adjusted TP estimates mirror the real dietary TP better than unadjusted. By simultaneously measuring condition/nutritional status in both predator and prey it is possible to adjust for them as confounding variables and decipher actual consumer TP, partly overcoming the issues of unknown and variable TDF‐values. Our study also highlights the importance of including environmental stressors (here hypoxia) when interpreting TP and reconstructing food webs.

The All of Us Research Program seeks to engage at least one million diverse participants to advance precision medicine and improve human health. We describe here the cloud-based Researcher Workbench that uses a data passport model to democratize access to analytical tools and participant information including survey, physical measurement, and electronic health record (EHR) data. We also present validation study findings for several common complex diseases to demonstrate use of this novel platform in 315,000 participants, 78% of whom are from groups historically underrepresented in biomedical research, including 49% self-reporting non-White races. Replication findings include medication usage pattern differences by race in depression and type 2 diabetes, validation of known cancer associations with smoking, and calculation of cardiovascular risk scores by reported race effects. The cloud-based Researcher Workbench represents an important advance in enabling secure access for a broad range of researchers to this large resource and analytical tools.

The study of the mammalian microbiome serves as a critical tool for understanding host-microbial diversity and coevolution and the impact of bacterial communities on host health. While studies of specific microbial systems (e.g., in the human gut) have rapidly increased, large knowledge gaps remain, hindering our understanding of the determinants and levels of variation in microbiomes across multiple body sites and host species. Here, we compare microbiome community compositions from eight distinct body sites among 17 phylogenetically diverse species of nonhuman primates (NHPs), representing the largest comparative study of microbial diversity across primate host species and body sites. Analysis of 898 samples predominantly acquired in the wild demonstrated that oral microbiomes were unique in their clustering, with distinctive divergence from all other body site microbiomes. In contrast, all other body site microbiomes clustered principally by host species and differentiated by body site within host species. These results highlight two key findings: (i) the oral microbiome is unique compared to all other body site microbiomes and conserved among diverse nonhuman primates, despite their considerable dietary and phylogenetic differences, and (ii) assessments of the determinants of host-microbial diversity are relative to the level of the comparison (i.e., intra-/inter-body site, -host species, and -individual), emphasizing the need for broader comparative microbial analyses across diverse hosts to further elucidate host-microbial dynamics, evolutionary and biological patterns of variation, and implications for human-microbial coevolution. IMPORTANCE The microbiome is critical to host health and disease, but much remains unknown about the determinants, levels, and evolution of host-microbial diversity. The relationship between hosts and their associated microbes is complex. Most studies to date have focused on the gut microbiome; however, large gaps remain in our understanding of host-microbial diversity, coevolution, and levels of variation in microbiomes across multiple body sites and host species. To better understand the patterns of variation and evolutionary context of host-microbial communities, we conducted one of the largest comparative studies to date, which indicated that the oral microbiome was distinct from the microbiomes of all other body sites and convergent across host species, suggesting conserved niche specialization within the Primates order. We also show the importance of host species differences in shaping the microbiome within specific body sites. This large, comparative study contributes valuable information on key patterns of variation among hosts and body sites, with implications for understanding host-microbial dynamics and human-microbial coevolution.

BackgroundWith limited severe acute respiratory syndrome coronavirus (SARS-CoV-2) testing capacity in the United States at the start of the epidemic (January-March 2020), testing was focused on symptomatic patients with a travel history throughout February, obscuring the picture of SARS-CoV-2 seeding and community transmission. We sought to identify individuals with SARS-CoV-2 antibodies in the early weeks of the US epidemic.MethodsAll of Us study participants in all 50 US states provided blood specimens during study visits from 2 January to 18 March 2020. Participants were considered seropositive if they tested positive for SARS-CoV-2 immunoglobulin G (IgG) antibodies with the Abbott Architect SARS-CoV-2 IgG enzyme-linked immunosorbent assay (ELISA) and the EUROIMMUN SARS-CoV-2 ELISA in a sequential testing algorithm. The sensitivity and specificity of these ELISAs and the net sensitivity and specificity of the sequential testing algorithm were estimated, along with 95% confidence intervals (CIs).ResultsThe estimated sensitivities of the Abbott and EUROIMMUN assays were 100% (107 of 107 [95% CI: 96.6%-100%]) and 90.7% (97 of 107 [83.5%-95.4%]), respectively, and the estimated specificities were 99.5% (995 of 1000 [98.8%-99.8%]) and 99.7% (997 of 1000 [99.1%-99.9%]), respectively. The net sensitivity and specificity of our sequential testing algorithm were 90.7% (97 of 107 [95% CI: 83.5%-95.4%]) and 100.0% (1000 of 1000 [99.6%-100%]), respectively. Of the 24 079 study participants with blood specimens from 2 January to 18 March 2020, 9 were seropositive, 7 before the first confirmed case in the states of Illinois, Massachusetts, Wisconsin, Pennsylvania, and Mississippi.ConclusionsOur findings identified SARS-CoV-2 infections weeks before the first recognized cases in 5 US states.

IntroductionNational obesity prevention strategies may benefit from precision health approaches involving diverse participants in population health studies. We used cohort data from the National Institutes of Health All of Us Research Program (All of Us) Researcher Workbench to estimate population-level obesity prevalence.MethodsTo estimate state-level obesity prevalence we used data from physical measurements made during All of Us enrollment visits and data from participant electronic health records (EHRs) where available. Prevalence estimates were calculated and mapped by state for 2 categories of body mass index (BMI) (kg/m2): obesity (BMI >30) and severe obesity (BMI >35). We calculated and mapped prevalence by state, excluding states with fewer than 100 All of Us participants.ResultsData on height and weight were available for 244,504 All of Us participants from 33 states, and corresponding EHR data were available for 88,840 of these participants. The median and IQR of BMI taken from physical measurements data was 28.4 (24.4- 33.7) and 28.5 (24.5-33.6) from EHR data, where available. Overall obesity prevalence based on physical measurements data was 41.5% (95% CI, 41.3%-41.7%); prevalence of severe obesity was 20.7% (95% CI, 20.6-20.9), with large geographic variations observed across states. Prevalence estimates from states with greater numbers of All of Us participants were more similar to national population-based estimates than states with fewer participants.ConclusionAll of Us participants had a high prevalence of obesity, with state-level geographic variation mirroring national trends. The diversity among All of Us participants may support future investigations on obesity prevention and treatment in diverse populations.

Abstract Clostridioides difficile (C. diff.) infection (CDI) is a leading cause of hospital acquired diarrhea in North America and Europe and a major cause of morbidity and mortality. Known risk factors do not fully explain CDI susceptibility, and genetic susceptibility is suggested by the fact that some patients with colons that are colonized with C. diff. do not develop any infection while others develop severe or recurrent infections. To identify common genetic variants associated with CDI, we performed a genome-wide association analysis in 19,861 participants (1349 cases; 18,512 controls) from the Electronic Medical Records and Genomics (eMERGE) Network. Using logistic regression, we found strong evidence for genetic variation in the DRB locus of the MHC (HLA) II region that predisposes individuals to CDI (P > 1.0 × 10–14; OR 1.56). Altered transcriptional regulation in the HLA region may play a role in conferring susceptibility to this opportunistic enteric pathogen.