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BackgroundInfection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2.MethodsWe performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs.ResultsAmong 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001).ConclusionsIP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

Pediatric COVID-19 vaccination is effective in preventing COVID-19-related hospitalization, but duration of protection of the original monovalent vaccine during SARS-CoV-2 Omicron predominance merits evaluation, particularly given low coverage with updated COVID-19 vaccines. During December 19, 2021-October 29, 2023, the Overcoming COVID-19 Network evaluated vaccine effectiveness (VE) of ≥2 original monovalent COVID-19 mRNA vaccine doses against COVID-19-related hospitalization and critical illness among U.S. children and adolescents aged 5-18 years, using a case-control design. Too few children and adolescents received bivalent or updated monovalent vaccines to separately evaluate their effectiveness. Most case-patients (persons with a positive SARS-CoV-2 test result) were unvaccinated, despite the high frequency of reported underlying conditions associated with severe COVID-19. VE of the original monovalent vaccine against COVID-19-related hospitalizations was 52% (95% CI = 33%-66%) when the most recent dose was administered

BACKGROUND AND OBJECTIVES: In June 2022, the mRNA COVID-19 vaccination was recommended for young children. We examined clinical characteristics and factors associated with vaccination status among vaccine-eligible young children hospitalized for acute COVID-19. METHODS: We enrolled inpatients 8 months to

Circular extrachromosomal DNA (ecDNA) in patient tumors is an important driver of oncogenic gene expression, evolution of drug resistance and poor patient outcomes. Applying computational methods for the detection and reconstruction of ecDNA across a retrospective cohort of 481 medulloblastoma tumors from 465 patients, we identify circular ecDNA in 82 patients (18%). Patients with ecDNA-positive medulloblastoma were more than twice as likely to relapse and three times as likely to die within 5 years of diagnosis. A subset of tumors harbored multiple ecDNA lineages, each containing distinct amplified oncogenes. Multimodal sequencing, imaging and CRISPR inhibition experiments in medulloblastoma models reveal intratumoral heterogeneity of ecDNA copy number per cell and frequent putative 'enhancer rewiring' events on ecDNA. This study reveals the frequency and diversity of ecDNA in medulloblastoma, stratified into molecular subgroups, and suggests copy number heterogeneity and enhancer rewiring as oncogenic features of ecDNA.

Infants aged

BackgroundSchools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown.MethodsThe objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 to March 2021.FindingsIn 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88%-98%); 67% were associated with a positive wastewater sample (95% CI: 57%-77%), and 40% were associated with a positive surface sample (95% CI: 29%-52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples.InterpretationPassive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy.FundingCounty of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

Soil-transmitted helminths (STHs) are endemic in resource-limited settings worldwide. Because of its subtropical climate and socioeconomic factors, the southeastern United States historically has been at elevated risk for STH diseases. [...]

A reported increase of hookworm and strongyloidiasis transmission in rural Alabama, USA, in 2017 (1) has led to more interest in isolated cases of autochthonous transmission of soil-transmitted helminths in [...]

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph-based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly "Question-of-the-Month (QotM) Challenge" series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

OBJECTIVE: To identify risk factors for persistent impairments after pediatric hospitalization for acute coronavirus disease 2019 (COVID-19) or multisystem inflammatory syndrome in children (MIS-C) during the SARS-CoV-2 pandemic. METHODS: Across 25 U.S. Overcoming COVID-19 Network hospitals, we conducted a prospective cohort study of patients

Ependymoma is a tumor of the brain or spinal cord. The two most common and aggressive molecular groups of ependymoma are the supratentorial ZFTA-fusion associated and the posterior fossa ependymoma group A. In both groups, tumors occur mainly in young children and frequently recur after treatment. Although molecular mechanisms underlying these diseases have recently been uncovered, they remain difficult to target and innovative therapeutic approaches are urgently needed. Here, we use genome-wide chromosome conformation capture (Hi-C), complemented with CTCF and H3K27ac ChIP-seq, as well as gene expression and DNA methylation analysis in primary and relapsed ependymoma tumors, to identify chromosomal conformations and regulatory mechanisms associated with aberrant gene expression. In particular, we observe the formation of new topologically associating domains ('neo-TADs') caused by structural variants, group-specific 3D chromatin loops, and the replacement of CTCF insulators by DNA hyper-methylation. Through inhibition experiments, we validate that genes implicated by these 3D genome conformations are essential for the survival of patient-derived ependymoma models in a group-specific manner. Thus, this study extends our ability to reveal tumor-dependency genes by 3D genome conformations even in tumors that lack targetable genetic alterations.

Newborn screening (NBS) dramatically improves outcomes in severe childhood disorders by treatment before symptom onset. In many genetic diseases, however, outcomes remain poor because NBS has lagged behind drug development. Rapid whole-genome sequencing (rWGS) is attractive for comprehensive NBS because it concomitantly examines almost all genetic diseases and is gaining acceptance for genetic disease diagnosis in ill newborns. We describe prototypic methods for scalable, parentally consented, feedback-informed NBS and diagnosis of genetic diseases by rWGS and virtual, acute management guidance (NBS-rWGS). Using established criteria and the Delphi method, we reviewed 457 genetic diseases for NBS-rWGS, retaining 388 (85%) with effective treatments. Simulated NBS-rWGS in 454,707 UK Biobank subjects with 29,865 pathogenic or likely pathogenic variants associated with 388 disorders had a true negative rate (specificity) of 99.7% following root cause analysis. In 2,208 critically ill children with suspected genetic disorders and 2,168 of their parents, simulated NBS-rWGS for 388 disorders identified 104 (87%) of 119 diagnoses previously made by rWGS and 15 findings not previously reported (NBS-rWGS negative predictive value 99.6%, true positive rate [sensitivity] 88.8%). Retrospective NBS-rWGS diagnosed 15 children with disorders that had been undetected by conventional NBS. In 43 of the 104 children, had NBS-rWGS-based interventions been started on day of life 5, the Delphi consensus was that symptoms could have been avoided completely in seven critically ill children, mostly in 21, and partially in 13. We invite groups worldwide to refine these NBS-rWGS conditions and join us to prospectively examine clinical utility and cost effectiveness.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1-3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

MotivationCpG sites within the same genomic region often share similar methylation patterns and tend to be co-regulated by multiple genetic variants that may interact with one another.ResultsWe propose a multi-trait methylation random field (multi-MRF) method to evaluate the joint association between a set of CpG sites and a set of genetic variants. The proposed method has several advantages. First, it is a multi-trait method that allows flexible correlation structures between neighboring CpG sites (e.g. distance-based correlation). Second, it is also a multi-locus method that integrates the effect of multiple common and rare genetic variants. Third, it models the methylation traits with a beta distribution to characterize their bimodal and interval properties. Through simulations, we demonstrated that the proposed method had improved power over some existing methods under various disease scenarios. We further illustrated the proposed method via an application to a study of congenital heart defects (CHDs) with 83 cardiac tissue samples. Our results suggested that gene BACE2, a methylation quantitative trait locus (QTL) candidate, colocalized with expression QTLs in artery tibial and harbored genetic variants with nominal significant associations in two genome-wide association studies of CHD.Availability and implementationhttps://github.com/chenlyu2656/Multi-MRF.Supplementary informationSupplementary data are available at Bioinformatics online.

Obstructive heart defects (OHDs) share common structural lesions in arteries and cardiac valves, accounting for ~25% of all congenital heart defects. OHDs are highly heritable, resulting from interplay among maternal exposures, genetic susceptibilities, and epigenetic phenomena. A genome-wide association study was conducted in National Birth Defects Prevention Study participants (Ndiscovery  = 3978; Nreplication  = 2507), investigating the genetic architecture of OHDs using transmission/disequilibrium tests (TDT) in complete case-parental trios (Ndiscovery_TDT  = 440; Nreplication_TDT  = 275) and case-control analyses separately in infants (Ndiscovery_CCI  = 1635; Nreplication_CCI  = 990) and mothers (case status defined by infant; Ndiscovery_CCM  = 1703; Nreplication_CCM  = 1078). In the TDT analysis, the SLC44A2 single nucleotide polymorphism (SNP) rs2360743 was significantly associated with OHD (pdiscovery  = 4.08 × 10-9 ; preplication  = 2.44 × 10-4 ). A CAPN11 SNP (rs55877192) was suggestively associated with OHD (pdiscovery  = 1.61 × 10-7 ; preplication  = 0.0016). Two other SNPs were suggestively associated (p

Congenital syphilis (CS), caused by infection with the bacterium Treponema pallidum, is a severe disease with potential for immediate and long-term health complications. Infection in pregnant mothers can lead to [...]

COVID-19 vaccination is recommended for persons who are pregnant, breastfeeding, trying to get pregnant now, or who might become pregnant in the future, to protect them from COVID-19.§ Infants are at risk for life-threatening complications from COVID-19, including acute respiratory failure (1). Evidence from other vaccine-preventable diseases suggests that maternal immunization can provide protection to infants, especially during the high-risk first 6 months of life, through passive transplacental antibody transfer (2). Recent studies of COVID-19 vaccination during pregnancy suggest the possibility of transplacental transfer of SARS-CoV-2-specific antibodies that might provide protection to infants (3-5); however, no epidemiologic evidence currently exists for the protective benefits of maternal immunization during pregnancy against COVID-19 in infants. The Overcoming COVID-19 network conducted a test-negative, case-control study at 20 pediatric hospitals in 17 states during July 1, 2021-January 17, 2022, to assess effectiveness of maternal completion of a 2-dose primary mRNA COVID-19 vaccination series during pregnancy against COVID-19 hospitalization in infants. Among 379 hospitalized infants aged

Multisystem inflammatory syndrome in children (MIS-C) is a severe postinfectious hyperinflammatory condition, which generally occurs 2-6 weeks after a typically mild or asymptomatic infection with SARS-CoV-2, the virus that causes COVID-19 (1-3). In the United States, the BNT162b2 (Pfizer-BioNTech) COVID-19 vaccine is currently authorized for use in children and adolescents aged 5-15 years under an Emergency Use Authorization and is fully licensed by the Food and Drug Administration for persons aged ≥16 years (4). Prelicensure randomized trials in persons aged ≥5 years documented high vaccine efficacy and immunogenicity (5),§ and real-world studies in persons aged 12-18 years demonstrated high vaccine effectiveness (VE) against severe COVID-19 (6). Recent evidence suggests that COVID-19 vaccination is associated with lower MIS-C incidence among adolescents (7); however, VE of the 2-dose Pfizer-BioNTech regimen against MIS-C has not been evaluated. The effectiveness of 2 doses of Pfizer-BioNTech vaccine received ≥28 days before hospital admission in preventing MIS-C was assessed using a test-negative case-control design¶ among hospitalized patients aged 12-18 years at 24 pediatric hospitals in 20 states** during July 1-December 9, 2021, the period when most MIS-C patients could be temporally linked to SARS-CoV-2 B.1.617.2 (Delta) variant predominance. Patients with MIS-C (case-patients) and two groups of hospitalized controls matched to case-patients were evaluated: test-negative controls had at least one COVID-19-like symptom and negative SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) or antigen-based assay results, and syndrome-negative controls were hospitalized patients without COVID-19-like illness. Among 102 MIS-C case-patients and 181 hospitalized controls, estimated effectiveness of 2 doses of Pfizer-BioNTech vaccine against MIS-C was 91% (95% CI = 78%-97%). All 38 MIS-C patients requiring life support were unvaccinated. Receipt of 2 doses of the Pfizer-BioNTech vaccine is associated with a high level of protection against MIS-C in persons aged 12-18 years, highlighting the importance of vaccination among all eligible children.

While many genetic diseases have effective treatments, they frequently progress rapidly to severe morbidity or mortality if those treatments are not implemented immediately. Since front-line physicians frequently lack familiarity with these diseases, timely molecular diagnosis may not improve outcomes. Herein we describe Genome-to-Treatment, an automated, virtual system for genetic disease diagnosis and acute management guidance. Diagnosis is achieved in 13.5 h by expedited whole genome sequencing, with superior analytic performance for structural and copy number variants. An expert panel adjudicated the indications, contraindications, efficacy, and evidence-of-efficacy of 9911 drug, device, dietary, and surgical interventions for 563 severe, childhood, genetic diseases. The 421 (75%) diseases and 1527 (15%) effective interventions retained are integrated with 13 genetic disease information resources and appended to diagnostic reports ( https://gtrx.radygenomiclab.com ). This system provided correct diagnoses in four retrospectively and two prospectively tested infants. The Genome-to-Treatment system facilitates optimal outcomes in children with rapidly progressive genetic diseases.

The diagnostic and clinical utility of rapid whole genome sequencing (rWGS) for critically ill children in the intensive care unit (ICU) has been substantiated by multiple studies, but comprehensive cost-effectiveness evaluation of rWGS in the ICU outside of the neonatal age group is lacking. In this study, we examined cost data retrospectively for a cohort of 38 children in a regional pediatric ICU (PICU) who received rWGS. We identified seven of 17 patients who received molecular diagnoses by rWGS and had resultant changes in clinical management with sufficient clarity to permit cost and quality adjusted life years (QALY) modeling. Cost of PICU care was estimated to be reduced by $184,846 and a total of 12.1 QALYs were gained among these seven patients. The total cost of rWGS for patients and families for the entire cohort (38 probands) was $239,400. Thus, the net cost of rWGS was $54,554, representing $4,509 per QALY gained. This quantitative, retrospective examination of healthcare utilization associated with rWGS-informed medicine interventions in the PICU revealed approximately one-third of a QALY gained per patient tested at a cost per QALY that was approximately one-tenth of that typically sought for cost-effective new medical interventions. This evidence suggests that performance of rWGS as a first-tier test in selected PICU children with diseases of unknown etiology is associated with acceptable cost-per-QALY gained.

Neutralization capacity of antibodies against Omicron after a prior SARS-CoV-2 infection in children and adolescents is not well studied. Therefore, we evaluated virus-neutralizing capacity against SARS-CoV-2 Alpha, Beta, Gamma, Delta and Omicron variants by age-stratified analyses (5 years of age. As expected, convalescent pediatric COVID-19 and MIS-C cohorts demonstrate higher neutralization titers than hospitalized acute COVID-19 patients. Overall, children and adolescents show some loss of cross-neutralization against all variants, with the most pronounced loss against Omicron. In contrast to SARS-CoV-2 infection, children vaccinated twice demonstrated higher titers against Alpha, Beta, Gamma, Delta and Omicron. These findings can influence transmission, re-infection and the clinical disease outcome from emerging SARS-CoV-2 variants and supports the need for vaccination in children.

BackgroundMost congenital heart defects (CHDs) result from complex interactions among genetic susceptibilities, epigenetic modifications, and maternal environmental exposures. Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation will enhance our understanding of pathogenesis in this important type of congenital disorder. We investigated cis-acting effects of genetic single nucleotide polymorphisms (SNPs) on local DNA methylation patterns within 83 cardiac tissue samples and prioritized their contributions to CHD risk by leveraging results of CHD genome-wide association studies (GWAS) and their effects on cardiac gene expression.ResultsWe identified 13,901 potential methylation quantitative trait loci (mQTLs) with a false discovery threshold of 5%. Further co-localization analyses and Mendelian randomization indicated that genetic variants near the HLA-DRB6 gene on chromosome 6 may contribute to CHD risk by regulating the methylation status of nearby CpG sites. Additional SNPs in genomic regions on chromosome 10 (TNKS2-AS1 gene) and chromosome 14 (LINC01629 gene) may simultaneously influence epigenetic and transcriptomic variations within cardiac tissues.ConclusionsOur results support the hypothesis that genetic variants may influence the risk of CHDs through regulating the changes of DNA methylation and gene expression. Our results can serve as an important source of information that can be integrated with other genetic studies of heart diseases, especially CHDs.

DNA methylation may be regulated by genetic variants within a genomic region, referred to as methylation quantitative trait loci (mQTLs). The changes of methylation levels can further lead to alterations of gene expression, and influence the risk of various complex human diseases. Detecting mQTLs may provide insights into the underlying mechanism of how genotypic variations may influence the disease risk. In this article, we propose a methylation random field (MRF) method to detect mQTLs by testing the association between the methylation level of a CpG site and a set of genetic variants within a genomic region. The proposed MRF has two major advantages over existing approaches. First, it uses a beta distribution to characterize the bimodal and interval properties of the methylation trait at a CpG site. Second, it considers multiple common and rare genetic variants within a genomic region to identify mQTLs. Through simulations, we demonstrated that the MRF had improved power over other existing methods in detecting rare variants of relatively large effect, especially when the sample size is small. We further applied our method to a study of congenital heart defects with 83 cardiac tissue samples and identified two mQTL regions, MRPS10 and PSORS1C1, which were colocalized with expression QTL in cardiac tissue. In conclusion, the proposed MRF is a useful tool to identify novel mQTLs, especially for studies with limited sample sizes.

The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.

Genetic disorders are a leading contributor to mortality in neonatal and pediatric intensive care units (ICUs). Rapid whole-genome sequencing (rWGS)-based rapid precision medicine (RPM) is an intervention that has demonstrated improved clinical outcomes and reduced costs of care. However, the feasibility of broad clinical deployment has not been established. The objective of this study was to implement RPM based on rWGS and evaluate the clinical and economic impact of this implementation as a first line diagnostic test in the California Medicaid (Medi-Cal) program. Project Baby Bear was a payor funded, prospective, real-world quality improvement project in the regional ICUs of five tertiary care children's hospitals. Participation was limited to acutely ill Medi-Cal beneficiaries who were admitted November 2018 to May 2020, were

Background Successful containment strategies for SARS-CoV-2, the causative virus of the COVID-19 pandemic, have involved widespread population testing that identifies infections early and enables rapid contact tracing. In this study, we developed a rapid and inexpensive RT- qPCR testing pipeline for population-level SARS-CoV-2 detection, and used this pipeline to establish a clinical laboratory dedicated to COVID-19 testing at the University of California San Diego (UCSD) with a processing capacity of 6,000 samples per day and next-day result turnaround times. Methods and findings Using this pipeline, we screened 6,786 healthcare workers and first responders, and 21,220 students, faculty, and staff from UCSD. Additionally, we screened 6,031 preschool-grade 12 students and staff from public and private schools across San Diego County that remained fully or partially open for in-person teaching during the pandemic. Between April 17, 2020 and February 5, 2021, participants provided 161,582 nasal swabs that were tested for the presence of SARS-CoV-2. Overall, 752 positive tests were obtained, yielding a test positivity rate of 0.47%. While the presence of symptoms was significantly correlated with higher viral load, most of the COVID-19 positive participants who participated in symptom surveys were asymptomatic at the time of testing. The positivity rate among preschool-grade 12 schools that remained open for in-person teaching was similar to the positivity rate at UCSD and lower than that of San Diego County, with the children in private schools being less likely to test positive than the adults at these schools. Conclusions Most schools across the United States have been closed for in-person learning for much of the 2020-2021 school year, and their safe reopening is a national priority. However, as there are no vaccines against SARS-CoV-2 currently available to the majority of school-aged children, the traditional strategies of mandatory masking, physical distancing, and repeated viral testing of students and staff remain key components of risk mitigation in these settings. The data presented here suggest that the safety measures and repeated testing actions taken by participating healthcare and educational facilities were effective in preventing outbreaks, and that a similar combination of risk-mitigation strategies and repeated testing may be successfully adopted by other healthcare and educational systems.

Summary As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Understanding causes of infant mortality shapes public health policy and prioritizes diseases for investments in surveillance, intervention and medical research. Rapid genomic sequencing has created a novel opportunity to decrease infant mortality associated with treatable genetic diseases. Herein, we sought to measure the contribution of genetic diseases to mortality among infants by secondary analysis of babies enrolled in two clinical studies and a systematic literature review. Among 312 infants who had been admitted to an ICU at Rady Children's Hospital between November 2015 and September 2018 and received rapid genomic sequencing, 30 (10%) died in infancy. Ten (33%) of the infants who died were diagnosed with 11 genetic diseases. The San Diego Study of Outcomes in Mothers and Infants platform identified differences between in-hospital and out-of-hospital causes of infant death. Similarly, in six published studies, 195 (21%) of 918 infant deaths were associated with genetic diseases by genomic sequencing. In 195 infant deaths associated with genetic diseases, locus heterogeneity was 70%. Treatment guidelines existed for 70% of the genetic diseases diagnosed, suggesting that rapid genomic sequencing has substantial potential to decrease infant mortality among infants in ICUs. Further studies are needed in larger, comprehensive, unbiased patient sets to determine the generalizability of these findings.

The second Newborn Sequencing in Genomic Medicine and Public Health (NSIGHT2) study was a randomized, controlled trial of rapid whole-genome sequencing (rWGS) or rapid whole-exome sequencing (rWES) in infants with diseases of unknown etiology in intensive care units (ICUs). Gravely ill infants were not randomized and received ultra-rapid whole-genome sequencing (urWGS). Herein we report results of clinician surveys of the clinical utility of rapid genomic sequencing (RGS). The primary end-point-clinician perception that RGS was useful- was met for 154 (77%) of 201 infants. Both positive and negative tests were rated as having clinical utility (42 of 45 [93%] and 112 of 156 [72%], respectively). Physicians reported that RGS changed clinical management in 57 (28%) infants, particularly in those receiving urWGS (p = 0.0001) and positive tests (p < 0.00001). Outcomes of 32 (15%) infants were perceived to be changed by RGS. Positive tests changed outcomes more frequently than negative tests (p < 0.00001). In logistic regression models, the likelihood that RGS was perceived as useful increased 6.7-fold when associated with changes in management (95% CI 1.8-43.3). Changes in management were 10.1-fold more likely when results were positive (95% CI 4.7-22.4) and turnaround time was shorter (odds ratio 0.92, 95% CI 0.85-0.99). RGS seldom led to clinician-perceived confusion or distress among families (6 of 207 [3%]). In summary, clinicians perceived high clinical utility and low likelihood of harm with first-tier RGS of infants in ICUs with diseases of unknown etiology. RGS was perceived as beneficial irrespective of whether results were positive or negative.

The second Newborn Sequencing in Genomic Medicine and Public Health study was a randomized, controlled trial of the effectiveness of rapid whole-genome or -exome sequencing (rWGS or rWES, respectively) in seriously ill infants with diseases of unknown etiology. Here we report comparisons of analytic and diagnostic performance. Of 1,248 ill inpatient infants, 578 (46%) had diseases of unknown etiology. 213 infants (37% of those eligible) were enrolled within 96 h of admission. 24 infants (11%) were very ill and received ultra-rapid whole-genome sequencing (urWGS). The remaining infants were randomized, 95 to rWES and 94 to rWGS. The analytic performance of rWGS was superior to rWES, including variants likely to affect protein function, and ClinVar pathogenic/likely pathogenic variants (p < 0.0001). The diagnostic performance of rWGS and rWES were similar (18 diagnoses in 94 infants [19%] versus 19 diagnoses in 95 infants [20%], respectively), as was time to result (median 11.0 versus 11.2 days, respectively). However, the proportion diagnosed by urWGS (11 of 24 [46%]) was higher than rWES/rWGS (p = 0.004) and time to result was less (median 4.6 days, p < 0.0001). The incremental diagnostic yield of reflexing to trio after negative proband analysis was 0.7% (1 of 147). In conclusion, rapid genomic sequencing can be performed as a first-tier diagnostic test in inpatient infants. urWGS had the shortest time to result, which was important in unstable infants, and those in whom a genetic diagnosis was likely to impact immediate management. Further comparison of urWGS and rWES is warranted because genomic technologies and knowledge of variant pathogenicity are evolving rapidly.

In Mississippi, USA, infant hospitalization with congenital syphilis (CS) spiked by 1,000%, from 10 in 2016 to 110 in 2022. To determine the causes of this alarming development, we analyzed Mississippi hospital discharge data to evaluate trends, demographics, outcomes, and risk factors for infants diagnosed with CS hospitalized during 2016-2022. Of the 367 infants hospitalized with a CS diagnosis, 97.6% were newborn, 92.6% were covered by Medicaid, 71.1% were African American, and 58.0% were nonurban residents. Newborns with CS had higher odds of being affected by maternal illicit drug use, being born prematurely (<37 weeks), and having very low birthweight (<1,500 g) than those without CS. Mean length of hospital stay (14.5 days vs. 3.8 days) and mean charges ($56,802 vs. $13,945) were also higher for infants with CS than for those without. To address escalation of CS, Mississippi should invest in comprehensive prenatal care and early treatment of vulnerable populations. [ABSTRACT FROM AUTHOR]

Surveillance for soil-transmitted helminths, strongyloidiasis, cryptosporidiosis, and giardiasis was conducted in Mississippi, USA. PCR performed on 224 fecal samples for all soil-transmitted helminths and on 370 samples for only Necator [...]

Family-based association studies are commonly used in genetic research because they can be robust to population stratification (PS). Recent advances in high-throughput genotyping technologies have produced a massive amount of genomic data in family-based studies. However, current family-based association tests are mainly focused on evaluating individual variants one at a time. In this article, we introduce a family-based generalized genetic random field (FB-GGRF) method to test the joint association between a set of autosomal SNPs (i.e., single-nucleotide polymorphisms) and disease phenotypes. The proposed method is a natural extension of a recently developed GGRF method for population-based case-control studies. It models offspring genotypes conditional on parental genotypes, and, thus, is robust to PS. Through simulations, we presented that under various disease scenarios the FB-GGRF has improved power over a commonly used family-based sequence kernel association test (FB-SKAT). Further, similar to GGRF, the proposed FB-GGRF method is asymptotically well-behaved, and does not require empirical adjustment of the type I error rates. We illustrate the proposed method using a study of congenital heart defects with family trios from the National Birth Defects Prevention Study (NBDPS).