RESUMEN
An outbreak of over 1,000 COVID-19 cases in Provincetown, Massachusetts (MA), in July 2021-the first large outbreak mostly in vaccinated individuals in the US-prompted a comprehensive public health response, motivating changes to national masking recommendations and raising questions about infection and transmission among vaccinated individuals. To address these questions, we combined viral genomic and epidemiological data from 467 individuals, including 40% of outbreak-associated cases. The Delta variant accounted for 99% of cases in this dataset; it was introduced from at least 40 sources, but 83% of cases derived from a single source, likely through transmission across multiple settings over a short time rather than a single event. Genomic and epidemiological data supported multiple transmissions of Delta from and between fully vaccinated individuals. However, despite its magnitude, the outbreak had limited onward impact in MA and the US overall, likely due to high vaccination rates and a robust public health response.
Asunto(s)
COVID-19/epidemiología , COVID-19/inmunología , COVID-19/transmisión , SARS-CoV-2/genética , SARS-CoV-2/inmunología , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , COVID-19/virología , Niño , Preescolar , Trazado de Contacto/métodos , Brotes de Enfermedades , Femenino , Genoma Viral , Humanos , Lactante , Recién Nacido , Masculino , Massachusetts/epidemiología , Persona de Mediana Edad , Epidemiología Molecular , Filogenia , SARS-CoV-2/clasificación , Vacunación , Secuenciación Completa del Genoma , Adulto JovenRESUMEN
Nearly all prostate cancer deaths are from metastatic castration-resistant prostate cancer (mCRPC), but there have been few whole-genome sequencing (WGS) studies of this disease state. We performed linked-read WGS on 23 mCRPC biopsy specimens and analyzed cell-free DNA sequencing data from 86 patients with mCRPC. In addition to frequent rearrangements affecting known prostate cancer genes, we observed complex rearrangements of the AR locus in most cases. Unexpectedly, these rearrangements include highly recurrent tandem duplications involving an upstream enhancer of AR in 70%-87% of cases compared with <2% of primary prostate cancers. A subset of cases displayed AR or MYC enhancer duplication in the context of a genome-wide tandem duplicator phenotype associated with CDK12 inactivation. Our findings highlight the complex genomic structure of mCRPC, nominate alterations that may inform prostate cancer treatment, and suggest that additional recurrent events in the non-coding mCRPC genome remain to be discovered.
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Neoplasias de la Próstata Resistentes a la Castración/patología , Receptores Androgénicos/genética , Secuenciación Completa del Genoma , Anciano , Anilidas/uso terapéutico , Quinasas Ciclina-Dependientes/genética , Quinasas Ciclina-Dependientes/metabolismo , Elementos de Facilitación Genéticos/genética , Duplicación de Gen , Reordenamiento Génico , Genes myc , Sitios Genéticos , Haplotipos , Humanos , Masculino , Persona de Mediana Edad , Metástasis de la Neoplasia , Fosfohidrolasa PTEN/genética , Fenotipo , Antígeno Prostático Específico/sangre , Neoplasias de la Próstata Resistentes a la Castración/tratamiento farmacológico , Neoplasias de la Próstata Resistentes a la Castración/genética , Inhibidores de Proteínas Quinasas/uso terapéutico , Piridinas/uso terapéuticoRESUMEN
The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and progression. By modeling the genesis of genomic rearrangements, we identified abundant DNA translocations and deletions that arise in a highly interdependent manner. This phenomenon, which we term "chromoplexy," frequently accounts for the dysregulation of prostate cancer genes and appears to disrupt multiple cancer genes coordinately. Our modeling suggests that chromoplexy may induce considerable genomic derangement over relatively few events in prostate cancer and other neoplasms, supporting a model of punctuated cancer evolution. By characterizing the clonal hierarchy of genomic lesions in prostate tumors, we charted a path of oncogenic events along which chromoplexy may drive prostate carcinogenesis.
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Aberraciones Cromosómicas , Regulación Neoplásica de la Expresión Génica , Genoma Humano , Neoplasias de la Próstata/genética , Adenocarcinoma/genética , Adenocarcinoma/patología , Estudios de Cohortes , Estudio de Asociación del Genoma Completo , Humanos , Masculino , Tumores Neuroendocrinos/genética , Tumores Neuroendocrinos/patología , Neoplasias de la Próstata/patologíaRESUMEN
Virological testing is central to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combined a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence and to ratify sensitivity losses against the time course of individual infections. We show that prevalence can be accurately estimated across a broad range, from 0.02 to 20%, using only a few dozen pooled tests and using up to 400 times fewer tests than would be needed for individual identification. We then exhaustively evaluated the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many true positives as individual testing with a given budget. Crucially, we confirmed that our theoretical results can be translated into practice using pooled human nasopharyngeal specimens by accurately estimating a 1% prevalence among 2304 samples using only 48 tests and through pooled sample identification in a panel of 960 samples. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.
Asunto(s)
COVID-19 , Epidemias , Humanos , SARS-CoV-2 , Pruebas Serológicas , Manejo de Especímenes , Carga ViralRESUMEN
Extensive virological testing is central to SARS-CoV-2 containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combine a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence, and to ratify losses in sensitivity against the time course of individual infections. Using this framework, we show that prevalence can be accurately estimated across four orders of magnitude using only a few dozen pooled tests without the need for individual identification. We then exhaustively evaluate the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many positives compared to individual testing with a given budget. We illustrate how pooling affects sensitivity and overall detection capacity during an epidemic and on each day post infection, finding that sensitivity loss is mainly attributed to individuals sampled at the end of infection when detection for public health containment has minimal benefit. Crucially, we confirm that our theoretical results can be accurately translated into practice using pooled human nasopharyngeal specimens. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect epidemiologically relevant infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.
RESUMEN
Multiple summer events, including large indoor gatherings, in Provincetown, Massachusetts (MA), in July 2021 contributed to an outbreak of over one thousand COVID-19 cases among residents and visitors. Most cases were fully vaccinated, many of whom were also symptomatic, prompting a comprehensive public health response, motivating changes to national masking recommendations, and raising questions about infection and transmission among vaccinated individuals. To characterize the outbreak and the viral population underlying it, we combined genomic and epidemiological data from 467 individuals, including 40% of known outbreak-associated cases. The Delta variant accounted for 99% of sequenced outbreak-associated cases. Phylogenetic analysis suggests over 40 sources of Delta in the dataset, with one responsible for a single cluster containing 83% of outbreak-associated genomes. This cluster was likely not the result of extensive spread at a single site, but rather transmission from a common source across multiple settings over a short time. Genomic and epidemiological data combined provide strong support for 25 transmission events from, including many between, fully vaccinated individuals; genomic data alone provides evidence for an additional 64. Together, genomic epidemiology provides a high-resolution picture of the Provincetown outbreak, revealing multiple cases of transmission of Delta from fully vaccinated individuals. However, despite its magnitude, the outbreak was restricted in its onward impact in MA and the US, likely due to high vaccination rates and a robust public health response.
RESUMEN
BACKGROUND: Structural variation (SV) influences genome organization and contributes to human disease. However, the complete mutational spectrum of SV has not been routinely captured in disease association studies. RESULTS: We sequenced 689 participants with autism spectrum disorder (ASD) and other developmental abnormalities to construct a genome-wide map of large SV. Using long-insert jumping libraries at 105X mean physical coverage and linked-read whole-genome sequencing from 10X Genomics, we document seven major SV classes at ~5 kb SV resolution. Our results encompass 11,735 distinct large SV sites, 38.1% of which are novel and 16.8% of which are balanced or complex. We characterize 16 recurrent subclasses of complex SV (cxSV), revealing that: (1) cxSV are larger and rarer than canonical SV; (2) each genome harbors 14 large cxSV on average; (3) 84.4% of large cxSVs involve inversion; and (4) most large cxSV (93.8%) have not been delineated in previous studies. Rare SVs are more likely to disrupt coding and regulatory non-coding loci, particularly when truncating constrained and disease-associated genes. We also identify multiple cases of catastrophic chromosomal rearrangements known as chromoanagenesis, including somatic chromoanasynthesis, and extreme balanced germline chromothripsis events involving up to 65 breakpoints and 60.6 Mb across four chromosomes, further defining rare categories of extreme cxSV. CONCLUSIONS: These data provide a foundational map of large SV in the morbid human genome and demonstrate a previously underappreciated abundance and diversity of cxSV that should be considered in genomic studies of human disease.