Evaluating Specimen Quality and Results from a Community-Wide, Home-Based Respiratory Surveillance Study.

While influenza and other respiratory pathogens cause significant morbidity and mortality, the community-based burden of these infections remains incompletely understood. The development of novel methods to detect respiratory infections is essential for mitigating epidemics and developing pandemic-preparedness infrastructure. From October 2019 to March 2020, we conducted a home-based cross-sectional study in the greater Seattle, WA, area, utilizing electronic consent and data collection instruments. Participants received nasal swab collection kits via rapid delivery within 24 hours of self-reporting respiratory symptoms. Samples were returned to the laboratory and were screened for 26 respiratory pathogens and a housekeeping gene. Participant data were recorded via online survey at the time of sample collection and 1 week later. Of the 4,572 consented participants, 4,359 (95.3%) received a home swab kit and 3,648 (83.7%) returned a nasal specimen for respiratory pathogen screening. The 3,638 testable samples had a mean RNase P relative cycle threshold (Crt ) value of 19.0 (SD, 3.4), and 1,232 (33.9%) samples had positive results for one or more pathogens, including 645 (17.7%) influenza-positive specimens. Among the testable samples, the median time between shipment of the home swab kit and completion of laboratory testing was 8.0 days (interquartile range [IQR], 7.0 to 14.0). A single adverse event occurred and did not cause long-term effects or require medical attention. Home-based surveillance using online participant enrollment and specimen self-collection is a safe and feasible method for community-level monitoring of influenza and other respiratory pathogens, which can readily be adapted for use during pandemics.

SwabExpress: An End-to-End Protocol for Extraction-Free COVID-19 Testing.

BACKGROUND: The urgent need for massively scaled clinical testing for SARS-CoV-2, along with global shortages of critical reagents and supplies, has necessitated development of streamlined laboratory testing protocols. Conventional nucleic acid testing for SARS-CoV-2 involves collection of a clinical specimen with a nasopharyngeal swab in transport medium, nucleic acid extraction, and quantitative reverse-transcription PCR (RT-qPCR). As testing has scaled across the world, the global supply chain has buckled, rendering testing reagents and materials scarce. To address shortages, we developed SwabExpress, an end-to-end protocol developed to employ mass produced anterior nares swabs and bypass the requirement for transport media and nucleic acid extraction. METHODS: We evaluated anterior nares swabs, transported dry and eluted in low-TE buffer as a direct-to-RT-qPCR alternative to extraction-dependent viral transport media. We validated our protocol of using heat treatment for viral inactivation and added a proteinase K digestion step to reduce amplification interference. We tested this protocol across archived and prospectively collected swab specimens to fine-tune test performance. RESULTS: After optimization, SwabExpress has a low limit of detection at 2-4 molecules/µL, 100% sensitivity, and 99.4% specificity when compared side by side with a traditional RT-qPCR protocol employing extraction. On real-world specimens, SwabExpress outperforms an automated extraction system while simultaneously reducing cost and hands-on time. CONCLUSION: SwabExpress is a simplified workflow that facilitates scaled testing for COVID-19 without sacrificing test performance. It may serve as a template for the simplification of PCR-based clinical laboratory tests, particularly in times of critical shortages during pandemics.

Effects of weather-related social distancing on city-scale transmission of respiratory viruses: a retrospective cohort study.

BACKGROUND: Unusually high snowfall in western Washington State in February 2019 led to widespread school and workplace closures. We assessed the impact of social distancing caused by this extreme weather event on the transmission of respiratory viruses. METHODS: Residual specimens from patients evaluated for acute respiratory illness at hospitals in the Seattle metropolitan area were screened for a panel of respiratory viruses. Transmission models were fit to each virus to estimate the magnitude reduction in transmission due to weather-related disruptions. Changes in contact rates and care-seeking were informed by data on local traffic volumes and hospital visits. RESULTS: Disruption in contact patterns reduced effective contact rates during the intervention period by 16 to 95%, and cumulative disease incidence through the remainder of the season by 3 to 9%. Incidence reductions were greatest for viruses that were peaking when the disruption occurred and least for viruses in an early epidemic phase. CONCLUSION: High-intensity, short-duration social distancing measures may substantially reduce total incidence in a respiratory virus epidemic if implemented near the epidemic peak. For SARS-CoV-2, this suggests that, even when SARS-CoV-2 spread is out of control, implementing short-term disruptions can prevent COVID-19 deaths.

Evidence for Limited Early Spread of COVID-19 Within the United States, January-February 2020.

From January 21 through February 23, 2020, public health agencies detected 14 U.S. cases of coronavirus disease 2019 (COVID-19), all related to travel from China (1,2). The first nontravel-related U.S. case was confirmed on February 26 in a California resident who had become ill on February 13 (3). Two days later, on February 28, a second nontravel-related case was confirmed in the state of Washington (4,5). Examination of four lines of evidence provides insight into the timing of introduction and early transmission of SARS-CoV-2, the virus that causes COVID-19, into the United States before the detection of these two cases. First, syndromic surveillance based on emergency department records from counties affected early by the pandemic did not show an increase in visits for COVID-19-like illness before February 28. Second, retrospective SARS-CoV-2 testing of approximately 11,000 respiratory specimens from several U.S. locations beginning January 1 identified no positive results before February 20. Third, analysis of viral RNA sequences from early cases suggested that a single lineage of virus imported directly or indirectly from China began circulating in the United States between January 18 and February 9, followed by several SARS-CoV-2 importations from Europe. Finally, the occurrence of three cases, one in a California resident who died on February 6, a second in another resident of the same county who died February 17, and a third in an unidentified passenger or crew member aboard a Pacific cruise ship that left San Francisco on February 11, confirms cryptic circulation of the virus by early February. These data indicate that sustained, community transmission had begun before detection of the first two nontravel-related U.S. cases, likely resulting from the importation of a single lineage of virus from China in late January or early February, followed by several importations from Europe. The widespread emergence of COVID-19 throughout the United States after February highlights the importance of robust public health systems to respond rapidly to emerging infectious threats.

Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants.

Establishing the age of each mutation segregating in contemporary human populations is important to fully understand our evolutionary history and will help to facilitate the development of new approaches for disease-gene discovery. Large-scale surveys of human genetic variation have reported signatures of recent explosive population growth, notable for an excess of rare genetic variants, suggesting that many mutations arose recently. To more quantitatively assess the distribution of mutation ages, we resequenced 15,336 genes in 6,515 individuals of European American and African American ancestry and inferred the age of 1,146,401 autosomal single nucleotide variants (SNVs). We estimate that approximately 73% of all protein-coding SNVs and approximately 86% of SNVs predicted to be deleterious arose in the past 5,000-10,000 years. The average age of deleterious SNVs varied significantly across molecular pathways, and disease genes contained a significantly higher proportion of recently arisen deleterious SNVs than other genes. Furthermore, European Americans had an excess of deleterious variants in essential and Mendelian disease genes compared to African Americans, consistent with weaker purifying selection due to the Out-of-Africa dispersal. Our results better delimit the historical details of human protein-coding variation, show the profound effect of recent human history on the burden of deleterious SNVs segregating in contemporary populations, and provide important practical information that can be used to prioritize variants in disease-gene discovery.

A statin-dependent QTL for GATM expression is associated with statin-induced myopathy.

Statins are prescribed widely to lower plasma low-density lipoprotein (LDL) concentrations and cardiovascular disease risk and have been shown to have beneficial effects in a broad range of patients. However, statins are associated with an increased risk, albeit small, of clinical myopathy and type 2 diabetes. Despite evidence for substantial genetic influence on LDL concentrations, pharmacogenomic trials have failed to identify genetic variations with large effects on either statin efficacy or toxicity, and have produced little information regarding mechanisms that modulate statin response. Here we identify a downstream target of statin treatment by screening for the effects of in vitro statin exposure on genetic associations with gene expression levels in lymphoblastoid cell lines derived from 480 participants of a clinical trial of simvastatin treatment. This analysis identified six expression quantitative trait loci (eQTLs) that interacted with simvastatin exposure, including rs9806699, a cis-eQTL for the gene glycine amidinotransferase (GATM) that encodes the rate-limiting enzyme in creatine synthesis. We found this locus to be associated with incidence of statin-induced myotoxicity in two separate populations (meta-analysis odds ratio = 0.60). Furthermore, we found that GATM knockdown in hepatocyte-derived cell lines attenuated transcriptional response to sterol depletion, demonstrating that GATM may act as a functional link between statin-mediated lowering of cholesterol and susceptibility to statin-induced myopathy.

Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations.

It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes--so-called sporadic or simplex families--we sequenced all coding regions of the genome (the exome) for parent-child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 677 individual exomes from 209 families. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected ß-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics.

Exome Sequencing of Phenotypic Extremes Identifies CAV2 and TMC6 as Interacting Modifiers of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis.

Discovery of rare or low frequency variants in exome or genome data that are associated with complex traits often will require use of very large sample sizes to achieve adequate statistical power. For a fixed sample size, sequencing of individuals sampled from the tails of a phenotype distribution (i.e., extreme phenotypes design) maximizes power and this approach was recently validated empirically with the discovery of variants in DCTN4 that influence the natural history of P. aeruginosa airway infection in persons with cystic fibrosis (CF; MIM219700). The increasing availability of large exome/genome sequence datasets that serve as proxies for population-based controls affords the opportunity to test an alternative, potentially more powerful and generalizable strategy, in which the frequency of rare variants in a single extreme phenotypic group is compared to a control group (i.e., extreme phenotype vs. control population design). As proof-of-principle, we applied this approach to search for variants associated with risk for age-of-onset of chronic P. aeruginosa airway infection among individuals with CF and identified variants in CAV2 and TMC6 that were significantly associated with group status. These results were validated using a large, prospective, longitudinal CF cohort and confirmed a significant association of a variant in CAV2 with increased age-of-onset of P. aeruginosa airway infection (hazard ratio = 0.48, 95% CI=[0.32, 0.88]) and variants in TMC6 with diminished age-of-onset of P. aeruginosa airway infection (HR = 5.4, 95% CI=[2.2, 13.5]) A strong interaction between CAV2 and TMC6 variants was observed (HR=12.1, 95% CI=[3.8, 39]) for children with the deleterious TMC6 variant and without the CAV2 protective variant. Neither gene showed a significant association using an extreme phenotypes design, and conditions for which the power of an extreme phenotype vs. control population design was greater than that for the extreme phenotypes design were explored.

Rare variation facilitates inferences of fine-scale population structure in humans.

Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European-American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies.

Quantifying rare, deleterious variation in 12 human cytochrome P450 drug-metabolism genes in a large-scale exome dataset.

The study of genetic influences on drug response and efficacy ('pharmacogenetics') has existed for over 50 years. Yet, we still lack a complete picture of how genetic variation, both common and rare, affects each individual's responses to medications. Exome sequencing is a promising alternative method for pharmacogenetic discovery as it provides information on both common and rare variation in large numbers of individuals. Using exome data from 2203 AA and 4300 Caucasian individuals through the NHLBI Exome Sequencing Project, we conducted a survey of coding variation within 12 Cytochrome P450 (CYP) genes that are collectively responsible for catalyzing nearly 75% of all known Phase I drug oxidation reactions. In addition to identifying many polymorphisms with known pharmacogenetic effects, we discovered over 730 novel nonsynonymous alleles across the 12 CYP genes of interest. These alleles include many with diverse functional effects such as premature stop codons, aberrant splicesites and mutations at conserved active site residues. Our analysis considering both novel, predicted functional alleles as well as known, actionable CYP alleles reveals that rare, deleterious variation contributes markedly to the overall burden of pharmacogenetic alleles within the populations considered, and that the contribution of rare variation to this burden is over three times greater in AA individuals as compared with Caucasians. While most of these impactful alleles are individually rare, 7.6-11.7% of individuals interrogated in the study carry at least one newly described potentially deleterious alleles in a major drug-metabolizing CYP.

Recurrent gain-of-function mutation in PRKG1 causes thoracic aortic aneurysms and acute aortic dissections.

Gene mutations that lead to decreased contraction of vascular smooth-muscle cells (SMCs) can cause inherited thoracic aortic aneurysms and dissections. Exome sequencing of distant relatives affected by thoracic aortic disease and subsequent Sanger sequencing of additional probands with familial thoracic aortic disease identified the same rare variant, PRKG1 c.530G>A (p.Arg177Gln), in four families. This mutation segregated with aortic disease in these families with a combined two-point LOD score of 7.88. The majority of affected individuals presented with acute aortic dissections (63%) at relatively young ages (mean 31 years, range 17-51 years). PRKG1 encodes type I cGMP-dependent protein kinase (PKG-1), which is activated upon binding of cGMP and controls SMC relaxation. Although the p.Arg177Gln alteration disrupts binding to the high-affinity cGMP binding site within the regulatory domain, the altered PKG-1 is constitutively active even in the absence of cGMP. The increased PKG-1 activity leads to decreased phosphorylation of the myosin regulatory light chain in fibroblasts and is predicted to cause decreased contraction of vascular SMCs. Thus, identification of a gain-of-function mutation in PRKG1 as a cause of thoracic aortic disease provides further evidence that proper SMC contractile function is critical for maintaining the integrity of the thoracic aorta throughout a lifetime.

Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies.

We propose in this paper a unified approach for testing the association between rare variants and phenotypes in sequencing association studies. This approach maximizes power by adaptively using the data to optimally combine the burden test and the nonburden sequence kernel association test (SKAT). Burden tests are more powerful when most variants in a region are causal and the effects are in the same direction, whereas SKAT is more powerful when a large fraction of the variants in a region are noncausal or the effects of causal variants are in different directions. The proposed unified test maintains the power in both scenarios. We show that the unified test corresponds to the optimal test in an extended family of SKAT tests, which we refer to as SKAT-O. The second goal of this paper is to develop a small-sample adjustment procedure for the proposed methods for the correction of conservative type I error rates of SKAT family tests when the trait of interest is dichotomous and the sample size is small. Both small-sample-adjusted SKAT and the optimal unified test (SKAT-O) are computationally efficient and can easily be applied to genome-wide sequencing association studies. We evaluate the finite sample performance of the proposed methods using extensive simulation studies and illustrate their application using the acute-lung-injury exome-sequencing data of the National Heart, Lung, and Blood Institute Exome Sequencing Project.

A human homeotic transformation resulting from mutations in PLCB4 and GNAI3 causes auriculocondylar syndrome.

Auriculocondylar syndrome (ACS) is a rare, autosomal-dominant craniofacial malformation syndrome characterized by variable micrognathia, temporomandibular joint ankylosis, cleft palate, and a characteristic "question-mark" ear malformation. Careful phenotypic characterization of severely affected probands in our cohort suggested the presence of a mandibular patterning defect resulting in a maxillary phenotype (i.e., homeotic transformation). We used exome sequencing of five probands and identified two novel (exclusive to the patient and/or family studied) missense mutations in PLCB4 and a shared mutation in GNAI3 in two unrelated probands. In confirmatory studies, three additional novel PLCB4 mutations were found in multigenerational ACS pedigrees. All mutations were confirmed by Sanger sequencing, were not present in more than 10,000 control chromosomes, and resulted in amino-acid substitutions located in highly conserved protein domains. Additionally, protein-structure modeling demonstrated that all ACS substitutions disrupt the catalytic sites of PLCB4 and GNAI3. We suggest that PLCB4 and GNAI3 are core signaling molecules of the endothelin-1-distal-less homeobox 5 and 6 (EDN1-DLX5/DLX6) pathway. Functional studies demonstrated a significant reduction in downstream DLX5 and DLX6 expression in ACS cases in assays using cultured osteoblasts from probands and controls. These results support the role of the previously implicated EDN1-DLX5/6 pathway in regulating mandibular specification in other species, which, when disrupted, results in a maxillary phenotype. This work defines the molecular basis of ACS as a homeotic transformation (mandible to maxilla) in humans.

Genome-wide studies of copy number variation and exome sequencing identify rare variants in BAG3 as a cause of dilated cardiomyopathy.

Dilated cardiomyopathy commonly causes heart failure and is the most frequent precipitating cause of heart transplantation. Familial dilated cardiomyopathy has been shown to be caused by rare variant mutations in more than 30 genes but only ~35% of its genetic cause has been identified, principally by using linkage-based or candidate gene discovery approaches. In a multigenerational family with autosomal dominant transmission, we employed whole-exome sequencing in a proband and three of his affected family members, and genome-wide copy number variation in the proband and his affected father and unaffected mother. Exome sequencing identified 428 single point variants resulting in missense, nonsense, or splice site changes. Genome-wide copy number analysis identified 51 insertion deletions and 440 copy number variants > 1 kb. Of these, a 8733 bp deletion, encompassing exon 4 of the heat shock protein cochaperone BCL2-associated athanogene 3 (BAG3), was found in seven affected family members and was absent in 355 controls. To establish the relevance of variants in this protein class in genetic DCM, we sequenced the coding exons in BAG3 in 311 other unrelated DCM probands and identified one frameshift, two nonsense, and four missense rare variants absent in 355 control DNAs, four of which were familial and segregated with disease. Knockdown of bag3 in a zebrafish model recapitulated DCM and heart failure. We conclude that new comprehensive genomic approaches have identified rare variants in BAG3 as causative of DCM.

Genetic variants associated with warfarin dose in African-American individuals: a genome-wide association study.

BACKGROUND: VKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans. METHODS: We did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 -1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p<5×10(-8) in the discovery cohort and p<0·0038 in the replication cohort. FINDINGS: The discovery cohort contained 533 participants and the replication cohort 432 participants. After the prespecified conditioning in the discovery cohort, we identified an association between a novel single nucleotide polymorphism in the CYP2C cluster on chromosome 10 (rs12777823) and warfarin dose requirement that reached genome-wide significance (p=1·51×10(-8)). This association was confirmed in the replication cohort (p=5·04×10(-5)); analysis of the two cohorts together produced a p value of 4·5×10(-12). Individuals heterozygous for the rs12777823 A allele need a dose reduction of 6·92 mg/week and those homozygous 9·34 mg/week. Regression analysis showed that the inclusion of rs12777823 significantly improves warfarin dose variability explained by the IWPC dosing algorithm (21% relative improvement). INTERPRETATION: A novel CYP2C single nucleotide polymorphism exerts a clinically relevant effect on warfarin dose in African Americans, independent of CYP2C9*2 and CYP2C9*3. Incorporation of this variant into pharmacogenetic dosing algorithms could improve warfarin dose prediction in this population. FUNDING: National Institutes of Health, American Heart Association, Howard Hughes Medical Institute, Wisconsin Network for Health Research, and the Wellcome Trust.

Detection of structural variants and indels within exome data.

We report an algorithm to detect structural variation and indels from 1 base pair (bp) to 1 Mbp within exome sequence data sets. Splitread uses one end-anchored placements to cluster the mappings of subsequences of unanchored ends to identify the size, content and location of variants with high specificity and sensitivity. The algorithm discovers indels, structural variants, de novo events and copy number-polymorphic processed pseudogenes missed by other methods.

High-throughput sequencing of T-cell receptors reveals a homogeneous repertoire of tumour-infiltrating lymphocytes in ovarian cancer.

The cellular adaptive immune system mounts a response to many solid tumours mediated by tumour-infiltrating T lymphocytes (TILs). Basic measurements of these TILs, including total count, show promise as prognostic markers for a variety of cancers, including ovarian and colorectal. In addition, recent therapeutic advances are thought to exploit this immune response to effectively fight melanoma, with promising studies showing efficacy in additional cancers. However, many of the basic properties of TILs are poorly understood, including specificity, clonality, and spatial heterogeneity of the T-cell response. We utilize deep sequencing of rearranged T-cell receptor beta (TCRB) genes to characterize the basic properties of TILs in ovarian carcinoma. Due to somatic rearrangement during T-cell development, the TCR beta chain sequence serves as a molecular tag for each T-cell clone. Using these sequence tags, we assess similarities and differences between infiltrating T cells in discretely sampled sections of large tumours and compare to T cells from peripheral blood. Within the limits of sensitivity of our assay, the TIL repertoires show strong similarity throughout each tumour and are distinct from the circulating T-cell repertoire. We conclude that the cellular adaptive immune response within ovarian carcinomas is spatially homogeneous and distinct from the T-cell compartment of peripheral blood.

Exome sequencing identifies a spectrum of mutation frequencies in advanced and lethal prostate cancers.

To catalog protein-altering mutations that may drive the development of prostate cancers and their progression to metastatic disease systematically, we performed whole-exome sequencing of 23 prostate cancers derived from 16 different lethal metastatic tumors and three high-grade primary carcinomas. All tumors were propagated in mice as xenografts, designated the LuCaP series, to model phenotypic variation, such as responses to cancer-directed therapeutics. Although corresponding normal tissue was not available for most tumors, we were able to take advantage of increasingly deep catalogs of human genetic variation to remove most germline variants. On average, each tumor genome contained ~200 novel nonsynonymous variants, of which the vast majority was specific to individual carcinomas. A subset of genes was recurrently altered across tumors derived from different individuals, including TP53, DLK2, GPC6, and SDF4. Unexpectedly, three prostate cancer genomes exhibited substantially higher mutation frequencies, with 2,000-4,000 novel coding variants per exome. A comparison of castration-resistant and castration-sensitive pairs of tumor lines derived from the same prostate cancer highlights mutations in the Wnt pathway as potentially contributing to the development of castration resistance. Collectively, our results indicate that point mutations arising in coding regions of advanced prostate cancers are common but, with notable exceptions, very few genes are mutated in a substantial fraction of tumors. We also report a previously undescribed subtype of prostate cancers exhibiting "hypermutated" genomes, with potential implications for resistance to cancer therapeutics. Our results also suggest that increasingly deep catalogs of human germline variation may challenge the necessity of sequencing matched tumor-normal pairs.