Transmission from vaccinated individuals in a large SARS-CoV-2 Delta variant outbreak.

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.

Donor Clonal Hematopoiesis and Recipient Outcomes After Transplantation.

PURPOSE: Clonal hematopoiesis (CH) can be transmitted from a donor to a recipient during allogeneic hematopoietic cell transplantation. Exclusion of candidate donors with CH is controversial since its impact on recipient outcomes and graft alloimmune function is uncertain. PATIENTS AND METHODS: We performed targeted error-corrected sequencing on samples from 1,727 donors age 40 years or older and assessed the effect of donor CH on recipient clinical outcomes. We measured long-term engraftment of 102 donor clones and cytokine levels in 256 recipients at 3 and 12 months after transplant. RESULTS: CH was present in 22.5% of donors, with DNMT3A (14.6%) and TET2 (5.2%) mutations being most common; 85% of donor clones showed long-term engraftment in recipients after transplantation, including clones with a variant allele fraction < 0.01. DNMT3A-CH with a variant allele fraction ≥ 0.01, but not smaller clones, was associated with improved recipient overall (hazard ratio [HR], 0.79; P = .042) and progression-free survival (HR, 0.72; P = .003) after adjustment for significant clinical variables. In patients who received calcineurin-based graft-versus-host disease prophylaxis, donor DNMT3A-CH was associated with reduced relapse (subdistribution HR, 0.59; P = .014), increased chronic graft-versus-host disease (subdistribution HR, 1.36; P = .042), and higher interleukin-12p70 levels in recipients. No recipient of sole DNMT3A or TET2-CH developed donor cell leukemia (DCL). In seven of eight cases, DCL evolved from donor CH with rare TP53 or splicing factor mutations or from donors carrying germline DDX41 mutations. CONCLUSION: Donor CH is closely associated with clinical outcomes in transplant recipients, with differential impact on graft alloimmune function and potential for leukemic transformation related to mutated gene and somatic clonal abundance. Donor DNMT3A-CH is associated with improved recipient survival because of reduced relapse risk and with an augmented network of inflammatory cytokines in recipients. Risk of DCL in allogeneic hematopoietic cell transplantation is driven by somatic myelodysplastic syndrome-associated mutations or germline predisposition in donors.

Evidence of transmission from fully vaccinated individuals in a large outbreak of the SARS-CoV-2 Delta variant in Provincetown, Massachusetts.

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.

Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings.

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.

Pooling for SARS-CoV2 Surveillance: Validation and Strategy for Implementation in K-12 Schools.

Repeated testing of a population is critical for limiting the spread of the SARS-CoV-2 virus and for the safe reopening of educational institutions such as kindergarten-grade 12 (K-12) schools and colleges. Many screening efforts utilize the CDC RT-PCR based assay which targets two regions of the novel Coronavirus nucleocapsid gene. The standard approach of testing each person individually, however, poses a financial burden to these institutions and is therefore a barrier to using testing for re-opening. Pooling samples from multiple individuals into a single test is an attractive alternate approach that promises significant cost savings-however the specificity and sensitivity of such approaches needs to be assessed prior to deployment. To this end, we conducted a pilot study to evaluate the feasibility of analyzing samples in pools of eight by the established RT-PCR assay. Participants (1,576) were recruited from amongst the Tufts University community undergoing regular screening. Each volunteer provided two swabs, one analyzed separately and the other in a pool of eight. Because the positivity rate was very low, we spiked approximately half of the pools with laboratory-generated swabs produced from known positive cases outside the Tufts testing program. The results of pooled tests had 100% correspondence with those of their respective individual tests. We conclude that pooling eight samples does not negatively impact the specificity or sensitivity of the RT-PCR assay and suggest that this approach can be utilized by institutions seeking to reduce surveillance costs.

Using viral load and epidemic dynamics to optimize pooled testing in resource constrained settings.

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.

Sensitive Detection of Minimal Residual Disease in Patients Treated for Early-Stage Breast Cancer.

PURPOSE: Existing cell-free DNA (cfDNA) methods lack the sensitivity needed for detecting minimal residual disease (MRD) following therapy. We developed a test for tracking hundreds of patient-specific mutations to detect MRD with a 1,000-fold lower error rate than conventional sequencing. EXPERIMENTAL DESIGN: We compared the sensitivity of our approach to digital droplet PCR (ddPCR) in a dilution series, then retrospectively identified two cohorts of patients who had undergone prospective plasma sampling and clinical data collection: 16 patients with ER+/HER2- metastatic breast cancer (MBC) sampled within 6 months following metastatic diagnosis and 142 patients with stage 0 to III breast cancer who received curative-intent treatment with most sampled at surgery and 1 year postoperative. We performed whole-exome sequencing of tumors and designed individualized MRD tests, which we applied to serial cfDNA samples. RESULTS: Our approach was 100-fold more sensitive than ddPCR when tracking 488 mutations, but most patients had fewer identifiable tumor mutations to track in cfDNA (median = 57; range = 2-346). Clinical sensitivity was 81% (n = 13/16) in newly diagnosed MBC, 23% (n = 7/30) at postoperative and 19% (n = 6/32) at 1 year in early-stage disease, and highest in patients with the most tumor mutations available to track. MRD detection at 1 year was strongly associated with distant recurrence [HR = 20.8; 95% confidence interval, 7.3-58.9]. Median lead time from first positive sample to recurrence was 18.9 months (range = 3.4-39.2 months). CONCLUSIONS: Tracking large numbers of individualized tumor mutations in cfDNA can improve MRD detection, but its sensitivity is driven by the number of tumor mutations available to track.

Outcomes of patient self-referral for the diagnosis of several rare inherited kidney diseases.

PURPOSE: To evaluate self-referral from the Internet for genetic diagnosis of several rare inherited kidney diseases. METHODS: Retrospective study from 1996 to 2017 analyzing data from an academic referral center specializing in autosomal dominant tubulointerstitial kidney disease (ADTKD). Individuals were referred by academic health-care providers (HCPs) nonacademic HCPs, or directly by patients/families. RESULTS: Over 21 years, there were 665 referrals, with 176 (27%) directly from families, 269 (40%) from academic HCPs, and 220 (33%) from nonacademic HCPs. Forty-two (24%) direct family referrals had positive genetic testing versus 73 (27%) families from academic HCPs and 55 (25%) from nonacademic HCPs (P = 0.72). Ninety-nine percent of direct family contacts were white and resided in zip code locations with a mean median income of $77,316 ± 34,014 versus US median income $49,445. CONCLUSION: Undiagnosed families with Internet access bypassed their physicians and established direct contact with an academic center specializing in inherited kidney disease to achieve a diagnosis. Twenty-five percent of all families diagnosed with ADTKD were the result of direct family referral and would otherwise have been undiagnosed. If patients suspect a rare disorder that is undiagnosed by their physicians, actively pursuing self-diagnosis using the Internet can be successful. Centers interested in rare disorders should consider improving direct access to families.

Noninvasive Immunohistochemical Diagnosis and Novel MUC1 Mutations Causing Autosomal Dominant Tubulointerstitial Kidney Disease.

BACKGROUND: Autosomal dominant tubulointerstitial kidney disease caused by mucin-1 gene (MUC1) mutations (ADTKD-MUC1) is characterized by progressive kidney failure. Genetic evaluation for ADTKD-MUC1 specifically tests for a cytosine duplication that creates a unique frameshift protein (MUC1fs). Our goal was to develop immunohistochemical methods to detect the MUC1fs created by the cytosine duplication and, possibly, by other similar frameshift mutations and to identify novel MUC1 mutations in individuals with positive immunohistochemical staining for the MUC1fs protein. METHODS: We performed MUC1fs immunostaining on urinary cell smears and various tissues from ADTKD-MUC1-positive and -negative controls as well as in individuals from 37 ADTKD families that were negative for mutations in known ADTKD genes. We used novel analytic methods to identify MUC1 frameshift mutations. RESULTS: After technique refinement, the sensitivity and specificity for MUC1fs immunostaining of urinary cell smears were 94.2% and 88.6%, respectively. Further genetic testing on 17 families with positive MUC1fs immunostaining revealed six families with five novel MUC1 frameshift mutations that all predict production of the identical MUC1fs protein. CONCLUSIONS: We developed a noninvasive immunohistochemical method to detect MUC1fs that, after further validation, may be useful in the future for diagnostic testing. Production of the MUC1fs protein may be central to the pathogenesis of ADTKD-MUC1.

Development and Validation of a Mass Spectrometry-Based Assay for the Molecular Diagnosis of Mucin-1 Kidney Disease.

Mucin-1 kidney disease, previously described as medullary cystic kidney disease type 1 (MCKD1, OMIM 174000), is an autosomal dominant tubulointerstitial kidney disease recently shown to be caused by a single-base insertion within the variable number tandem repeat region of the MUC1 gene. Because of variable age of disease onset and often subtle signs and symptoms, clinical diagnosis of mucin-1 kidney disease and differentiation from other forms of hereditary kidney disease have been difficult. The causal insertion resides in a variable number tandem repeat region with high GC content, which has made detection by standard next-generation sequencing impossible to date. The inherently difficult nature of this mutation required an alternative method for routine detection and clinical diagnosis of the disease. We therefore developed and validated a mass spectrometry-based probe extension assay with a series of internal controls to detect the insertion event using 24 previously characterized positive samples from patients with mucin-1 kidney disease and 24 control samples known to be wild type for the variant. Validation results indicate an accurate and reliable test for clinically establishing the molecular diagnosis of mucin-1 kidney disease with 100% sensitivity and specificity across 275 tests called.

The genomic landscape of pediatric Ewing sarcoma.

UNLABELLED: Pediatric Ewing sarcoma is characterized by the expression of chimeric fusions of EWS and ETS family transcription factors, representing a paradigm for studying cancers driven by transcription factor rearrangements. In this study, we describe the somatic landscape of pediatric Ewing sarcoma. These tumors are among the most genetically normal cancers characterized to date, with only EWS-ETS rearrangements identified in the majority of tumors. STAG2 loss, however, is present in more than 15% of Ewing sarcoma tumors; occurs by point mutation, rearrangement, and likely nongenetic mechanisms; and is associated with disease dissemination. Perhaps the most striking finding is the paucity of mutations in immediately targetable signal transduction pathways, highlighting the need for new therapeutic approaches to target EWS-ETS fusions in this disease. SIGNIFICANCE: We performed next-generation sequencing of Ewing sarcoma, a pediatric cancer involving bone, characterized by expression of EWS-ETS fusions. We found remarkably few mutations. However, we discovered that loss of STAG2 expression occurs in 15% of tumors and is associated with metastatic disease, suggesting a potential genetic vulnerability in Ewing sarcoma.

EGFR variant heterogeneity in glioblastoma resolved through single-nucleus sequencing.

UNLABELLED: Glioblastomas (GBM) with EGFR amplification represent approximately 50% of newly diagnosed cases, and recent studies have revealed frequent coexistence of multiple EGFR aberrations within the same tumor, which has implications for mutation cooperation and treatment resistance. However, bulk tumor sequencing studies cannot resolve the patterns of how the multiple EGFR aberrations coexist with other mutations within single tumor cells. Here, we applied a population-based single-cell whole-genome sequencing methodology to characterize genomic heterogeneity in EGFR-amplified glioblastomas. Our analysis effectively identified clonal events, including a novel translocation of a super enhancer to the TERT promoter, as well as subclonal LOH and multiple EGFR mutational variants within tumors. Correlating the EGFR mutations onto the cellular hierarchy revealed that EGFR truncation variants (EGFRvII and EGFR carboxyl-terminal deletions) identified in the bulk tumor segregate into nonoverlapping subclonal populations. In vitro and in vivo functional studies show that EGFRvII is oncogenic and sensitive to EGFR inhibitors currently in clinical trials. Thus, the association between diverse activating mutations in EGFR and other subclonal mutations within a single tumor supports an intrinsic mechanism for proliferative and clonal diversification with broad implications in resistance to treatment. SIGNIFICANCE: We developed a novel single-cell sequencing methodology capable of identifying unique, nonoverlapping subclonal alterations from archived frozen clinical specimens. Using GBM as an example, we validated our method to successfully define tumor cell subpopulations containing distinct genetic and treatment resistance profiles and potentially mutually cooperative combinations of alterations in EGFR and other genes.

Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer.

Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two patients with prostate cancer, including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were present in matched tissue. Moreover, we identified 10 early trunk and 56 metastatic trunk mutations in the non-CTC tumor samples and found 90% and 73% of these mutations, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.

Mutations causing medullary cystic kidney disease type 1 lie in a large VNTR in MUC1 missed by massively parallel sequencing.

Although genetic lesions responsible for some mendelian disorders can be rapidly discovered through massively parallel sequencing of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing and de novo assembly did we find that each of six families with MCKD1 harbors an equivalent but apparently independently arising mutation in sequence markedly under-represented in massively parallel sequencing data: the insertion of a single cytosine in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (∼1.5-5 kb), GC-rich (>80%) coding variable-number tandem repeat (VNTR) sequence in the MUC1 gene encoding mucin 1. These results provide a cautionary tale about the challenges in identifying the genes responsible for mendelian, let alone more complex, disorders through massively parallel sequencing.

DGAT1 mutation is linked to a congenital diarrheal disorder.

Congenital diarrheal disorders (CDDs) are a collection of rare, heterogeneous enteropathies with early onset and often severe outcomes. Here, we report a family of Ashkenazi Jewish descent, with 2 out of 3 children affected by CDD. Both affected children presented 3 days after birth with severe, intractable diarrhea. One child died from complications at age 17 months. The second child showed marked improvement, with resolution of most symptoms at 10 to 12 months of age. Using exome sequencing, we identified a rare splice site mutation in the DGAT1 gene and found that both affected children were homozygous carriers. Molecular analysis of the mutant allele indicated a total loss of function, with no detectable DGAT1 protein or activity produced. The precise cause of diarrhea is unknown, but we speculate that it relates to abnormal fat absorption and buildup of DGAT substrates in the intestinal mucosa. Our results identify DGAT1 loss-of-function mutations as a rare cause of CDDs. These findings prompt concern for DGAT1 inhibition in humans, which is being assessed for treating metabolic and other diseases.

High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing.

UNLABELLED: Knowledge of "actionable" somatic genomic alterations present in each tumor (e.g., point mutations, small insertions/deletions, and copy-number alterations that direct therapeutic options) should facilitate individualized approaches to cancer treatment. However, clinical implementation of systematic genomic profiling has rarely been achieved beyond limited numbers of oncogene point mutations. To address this challenge, we utilized a targeted, massively parallel sequencing approach to detect tumor genomic alterations in formalin-fixed, paraffin-embedded (FFPE) tumor samples. Nearly 400-fold mean sequence coverage was achieved, and single-nucleotide sequence variants, small insertions/deletions, and chromosomal copynumber alterations were detected simultaneously with high accuracy compared with other methods in clinical use. Putatively actionable genomic alterations, including those that predict sensitivity or resistance to established and experimental therapies, were detected in each tumor sample tested. Thus, targeted deep sequencing of clinical tumor material may enable mutation-driven clinical trials and, ultimately, "personalized" cancer treatment. SIGNIFICANCE: Despite the rapid proliferation of targeted therapeutic agents, systematic methods to profile clinically relevant tumor genomic alterations remain underdeveloped. We describe a sequencingbased approach to identifying genomic alterations in FFPE tumor samples. These studies affirm the feasibility and clinical utility of targeted sequencing in the oncology arena and provide a foundation for genomics-based stratification of cancer patients.

A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries.

Genome targeting methods enable cost-effective capture of specific subsets of the genome for sequencing. We present here an automated, highly scalable method for carrying out the Solution Hybrid Selection capture approach that provides a dramatic increase in scale and throughput of sequence-ready libraries produced. Significant process improvements and a series of in-process quality control checkpoints are also added. These process improvements can also be used in a manual version of the protocol.

Targeted exon sequencing by in-solution hybrid selection.

This unit describes a protocol for the targeted enrichment of exons from randomly sheared genomic DNA libraries using an in-solution hybrid selection approach for sequencing on an Illumina Genome Analyzer II. The steps for designing and ordering a hybrid selection oligo pool are reviewed, as are critical steps for performing the preparation and hybrid selection of an Illumina paired-end library. Critical parameters, performance metrics, and analysis workflow are discussed.

Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder.

To identify susceptibility loci for bipolar disorder, we tested 1.8 million variants in 4,387 cases and 6,209 controls and identified a region of strong association (rs10994336, P = 9.1 x 10(-9)) in ANK3 (ankyrin G). We also found further support for the previously reported CACNA1C (alpha 1C subunit of the L-type voltage-gated calcium channel; combined P = 7.0 x 10(-8), rs1006737). Our results suggest that ion channelopathies may be involved in the pathogenesis of bipolar disorder.

Two independent alleles at 6q23 associated with risk of rheumatoid arthritis.

To identify susceptibility alleles associated with rheumatoid arthritis, we genotyped 397 individuals with rheumatoid arthritis for 116,204 SNPs and carried out an association analysis in comparison to publicly available genotype data for 1,211 related individuals from the Framingham Heart Study. After evaluating and adjusting for technical and population biases, we identified a SNP at 6q23 (rs10499194, approximately 150 kb from TNFAIP3 and OLIG3) that was reproducibly associated with rheumatoid arthritis both in the genome-wide association (GWA) scan and in 5,541 additional case-control samples (P = 10(-3), GWA scan; P < 10(-6), replication; P = 10(-9), combined). In a concurrent study, the Wellcome Trust Case Control Consortium (WTCCC) has reported strong association of rheumatoid arthritis susceptibility to a different SNP located 3.8 kb from rs10499194 (rs6920220; P = 5 x 10(-6) in WTCCC). We show that these two SNP associations are statistically independent, are each reproducible in the comparison of our data and WTCCC data, and define risk and protective haplotypes for rheumatoid arthritis at 6q23.