Detection of Mpox Virus Using Microbial Cell-Free DNA: The Potential of Pathogen-Agnostic Sequencing for Rapid Identification of Emerging Pathogens.

BACKGROUND: The 2022 global outbreak of Monkeypox virus (MPXV) highlighted challenges with polymerase chain reaction detection as divergent strains emerged and atypical presentations limited the applicability of swab sampling. Recommended testing in the United States requires a swab of lesions, which arise late in infection and may be unrecognized. We present MPXV detections using plasma microbial cell-free DNA (mcfDNA) sequencing. METHODS: Fifteen plasma samples from 12 case-patients were characterized through mcfDNA sequencing. Assay performance was confirmed through in silico inclusivity and exclusivity assessments. MPXV isolates were genotyped using mcfDNA, and phylodynamic information was imputed using publicly available sequences. RESULTS: MPXV mcfDNA was detected in 12 case-patients. Mpox was not suspected in 5, with 1 having documented resolution of mpox >6 months previously. Six had moderate to severe mpox, supported by high MPXV mcfDNA concentrations; 4 died. In 7 case-patients, mcfDNA sequencing detected coinfections. Genotyping by mcfDNA sequencing identified 22 MPXV mutations at 10 genomic loci in 9 case-patients. Consistent with variation observed in the 2022 outbreak, 21 of 22 variants were G > A/C > T. Phylogenetic analyses imputed isolates to sublineages arising at different time points and from different geographic locations. CONCLUSIONS: We demonstrate the potential of plasma mcfDNA sequencing to detect, quantify, and, for acute infections with high sequencing coverage, subtype MPXV using a single noninvasive test. Sequencing plasma mcfDNA may augment existing mpox testing in vulnerable patient populations or in patients with atypical symptoms or unrecognized mpox. Strain type information may supplement disease surveillance and facilitate tracking emerging pathogens.

Plasma Microbial Cell-Free DNA Sequencing in Immunocompromised Patients With Pneumonia: A Prospective Observational Study.

BACKGROUND: Pneumonia is a common cause of morbidity and mortality, yet a causative pathogen is identified in a minority of cases. Plasma microbial cell-free DNA sequencing may improve diagnostic yield in immunocompromised patients with pneumonia. METHODS: In this prospective, multicenter, observational study of immunocompromised adults undergoing bronchoscopy to establish a pneumonia etiology, plasma microbial cell-free DNA sequencing was compared to standardized usual care testing. Pneumonia etiology was adjudicated by a blinded independent committee. The primary outcome, additive diagnostic value, was assessed in the Per Protocol population (patients with complete testing results and no major protocol deviations) and defined as the percent of patients with an etiology of pneumonia exclusively identified by plasma microbial cell-free DNA sequencing. Clinical additive diagnostic value was assessed in the Per Protocol subgroup with negative usual care testing. RESULTS: Of 257 patients, 173 met Per Protocol criteria. A pneumonia etiology was identified by usual care in 52/173 (30.1%), plasma microbial cell-free DNA sequencing in 49/173 (28.3%) and the combination of both in 73/173 (42.2%) patients. Plasma microbial cell-free DNA sequencing exclusively identified an etiology of pneumonia in 21/173 patients (additive diagnostic value 12.1%, 95% confidence interval [CI], 7.7% to 18.0%, P < .001). In the Per Protocol subgroup with negative usual care testing, plasma microbial cell-free DNA sequencing identified a pneumonia etiology in 21/121 patients (clinical additive diagnostic value 17.4%, 95% CI, 11.1% to 25.3%). CONCLUSIONS: Non-invasive plasma microbial cell-free DNA sequencing significantly increased diagnostic yield in immunocompromised patients with pneumonia undergoing bronchoscopy and extensive microbiologic and molecular testing. CLINICAL TRIALS REGISTRATION: NCT04047719.

Plasma Microbial Cell-Free DNA Sequencing from over 15,000 Patients Identified a Broad Spectrum of Pathogens.

Microbial cell-free DNA (mcfDNA) sequencing is an emerging infectious disease diagnostic tool which enables unbiased pathogen detection and quantification from plasma. The Karius Test, a commercial mcfDNA sequencing assay developed by and available since 2017 from Karius, Inc. (Redwood City, CA), detects and quantifies mcfDNA as molecules/µL in plasma. The commercial sample data and results for all tests conducted from April 2018 through mid-September 2021 were evaluated for laboratory quality metrics, reported pathogens, and data from test requisition forms. A total of 18,690 reports were generated from 15,165 patients in a hospital setting among 39 states and the District of Columbia. The median time from sample receipt to reported result was 26 h (interquartile range [IQR] 25 to 28), and 96% of samples had valid test results. Almost two-thirds (65%) of patients were adults, and 29% at the time of diagnostic testing had ICD-10 codes representing a diverse array of clinical scenarios. There were 10,752 (58%) reports that yielded at least one taxon for a total of 22,792 detections spanning 701 unique microbial taxa. The 50 most common taxa detected included 36 bacteria, 9 viruses, and 5 fungi. Opportunistic fungi (374 Aspergillus spp., 258 Pneumocystis jirovecii, 196 Mucorales, and 33 dematiaceous fungi) comprised 861 (4%) of all detections. Additional diagnostically challenging pathogens (247 zoonotic and vector-borne pathogens, 144 Mycobacterium spp., 80 Legionella spp., 78 systemic dimorphic fungi, 69 Nocardia spp., and 57 protozoan parasites) comprised 675 (3%) of all detections. This is the largest reported cohort of patients tested using plasma mcfDNA sequencing and represents the first report of a clinical grade metagenomic test performed at scale. Data reveal new insights into the breadth and complexity of potential pathogens identified.

Detection of Borrelia burgdorferi Cell-free DNA in Human Plasma Samples for Improved Diagnosis of Early Lyme Borreliosis.

BACKGROUND: Laboratory confirmation of early Lyme borreliosis (LB) is challenging. Serology is insensitive during the first days to weeks of infection, and blood polymerase chain reaction (PCR) offers similarly poor performance. Here, we demonstrate that detection of Borrelia burgdorferi (B.b.) cell-free DNA (cfDNA) in plasma can improve diagnosis of early LB. METHODS: B.b. detection in plasma samples using unbiased metagenomic cfDNA sequencing performed by a commercial laboratory (Karius Inc) was compared with serology and blood PCR in 40 patients with physician-diagnosed erythema migrans (EM), 28 of whom were confirmed to have LB by skin biopsy culture (n = 18), seroconversion (n = 2), or both (n = 8). B.b. sequence analysis was performed using investigational detection thresholds, different from Karius' clinical test. RESULTS: B.b. cfDNA was detected in 18 of 28 patients (64%) with laboratory-confirmed EM. In comparison, sensitivity of acute-phase serology using modified 2-tiered testing (MTTT) was 50% (P = .45); sensitivity of blood PCR was 7% (P = .0002). Combining B.b. cfDNA detection and MTTT increased diagnostic sensitivity to 86%, significantly higher than either approach alone (P ≤ .04). B.b. cfDNA sequences matched precisely with strain-specific sequence generated from the same individual's cultured B.b. isolate. B.b. cfDNA was not observed at any level in plasma from 684 asymptomatic ambulatory individuals. Among 3000 hospitalized patients tested as part of clinical care, B.b. cfDNA was detected in only 2 individuals, both of whom had clinical presentations consistent with LB. CONCLUSIONS: This is the first report of B.b. cfDNA detection in early LB and a demonstration of potential diagnostic utility. The combination of B.b. cfDNA detection and acute-phase MTTT improves clinical sensitivity for diagnosis of early LB.

Circulating microbial cell-free DNA is associated with inflammatory host-responses in severe pneumonia.

Host inflammatory responses predict worse outcome in severe pneumonia, yet little is known about what drives dysregulated inflammation. We performed metagenomic sequencing of microbial cell-free DNA (mcfDNA) in 83 mechanically ventilated patients (26 culture-positive, 41 culture-negative pneumonia, 16 uninfected controls). Culture-positive patients had higher levels of mcfDNA than those with culture-negative pneumonia and uninfected controls (p<0.005). Plasma levels of inflammatory biomarkers (fractalkine, procalcitonin, pentraxin-3 and suppression of tumorigenicity-2) were independently associated with mcfDNA levels (adjusted p<0.05) among all patients with pneumonia. Such host-microbe interactions in the systemic circulation of patients with severe pneumonia warrant further large-scale clinical and mechanistic investigations.

Rapid detection of invasive Mycobacterium chimaera disease via a novel plasma-based next-generation sequencing test.

BACKGROUND: There is an ongoing outbreak of Mycobacterium chimaera infections among patients exposed to contaminated heater-cooler devices used during cardiac surgery. Recognition of M. chimaera infection is hampered by its long latency and non-specific symptoms. Standard diagnostic methods using acid-fast bacilli (AFB) culture often require invasive sampling, have low sensitivity, and can take weeks to result. We describe the performance of a plasma-based next-generation sequencing test (plasma NGS) for the diagnosis of M. chimaera infection. METHODS: We conducted a retrospective study of 10 patients with a history of cardiac surgery who developed invasive M. chimaera infection and underwent testing by plasma NGS between February 2017 and April 2018. RESULTS: Plasma NGS detected M. chimaera in 9 of 10 patients (90%) with invasive disease in a median of 4 days from specimen collection, including all 8 patients with disseminated infection. In 7 of these 9 cases (78%), plasma NGS was the first test to provide microbiologic confirmation of M. chimaera infection. In contrast, AFB cultures required a median of 20 days to turn positive, and the median time for confirmation of M. chimaera was 41 days. Of 24 AFB blood cultures obtained in this cohort, only 4 (17%) were positive. Invasive procedures were performed in 90% of cases, and in 5 patients (50%), mycobacterial growth was achieved only by culture of these deep sites. CONCLUSIONS: Plasma NGS can accurately detect M. chimaera noninvasively and significantly faster than AFB culture, making it a promising new diagnostic tool.

Parente2: a fast and accurate method for detecting identity by descent.

Identity-by-descent (IBD) inference is the problem of establishing a genetic connection between two individuals through a genomic segment that is inherited by both individuals from a recent common ancestor. IBD inference is an important preceding step in a variety of population genomic studies, ranging from demographic studies to linking genomic variation with phenotype and disease. The problem of accurate IBD detection has become increasingly challenging with the availability of large collections of human genotypes and genomes: Given a cohort's size, a quadratic number of pairwise genome comparisons must be performed. Therefore, computation time and the false discovery rate can also scale quadratically. To enable accurate and efficient large-scale IBD detection, we present Parente2, a novel method for detecting IBD segments. Parente2 is based on an embedded log-likelihood ratio and uses a model that accounts for linkage disequilibrium by explicitly modeling haplotype frequencies. Parente2 operates directly on genotype data without the need to phase data prior to IBD inference. We evaluate Parente2's performance through extensive simulations using real data, and we show that it provides substantially higher accuracy compared to previous state-of-the-art methods while maintaining high computational efficiency.

Reveel: large-scale population genotyping using low-coverage sequencing data.

MOTIVATION: Population low-coverage whole-genome sequencing is rapidly emerging as a prominent approach for discovering genomic variation and genotyping a cohort. This approach combines substantially lower cost than full-coverage sequencing with whole-genome discovery of low-allele frequency variants, to an extent that is not possible with array genotyping or exome sequencing. However, a challenging computational problem arises of jointly discovering variants and genotyping the entire cohort. Variant discovery and genotyping are relatively straightforward tasks on a single individual that has been sequenced at high coverage, because the inference decomposes into the independent genotyping of each genomic position for which a sufficient number of confidently mapped reads are available. However, in low-coverage population sequencing, the joint inference requires leveraging the complex linkage disequilibrium (LD) patterns in the cohort to compensate for sparse and missing data in each individual. The potentially massive computation time for such inference, as well as the missing data that confound low-frequency allele discovery, need to be overcome for this approach to become practical. RESULTS: Here, we present Reveel, a novel method for single nucleotide variant calling and genotyping of large cohorts that have been sequenced at low coverage. Reveel introduces a novel technique for leveraging LD that deviates from previous Markov-based models, and which is aimed at computational efficiency as well as accuracy in capturing LD patterns present in rare haplotypes. We evaluate Reveel's performance through extensive simulations as well as real data from the 1000 Genomes Project, and show that it achieves higher accuracy in low-frequency allele discovery and substantially lower computation cost than previous state-of-the-art methods. AVAILABILITY AND IMPLEMENTATION: http://reveel.stanford.edu/ CONTACT: : serafim@cs.stanford.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Circulating microbial cell-free DNA is increased during neutropenia after hematopoietic stem cell transplantation.

We used a next-generation sequencing platform to characterize microbial cell-free DNA (mcfDNA) in plasma samples from patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HCT). In this observational study, we sought to characterize plasma mcfDNA in order to explore its potential association with the immunologic complications of transplantation. We compared serially collected patient samples with plasma collected from healthy control subjects. We observed changes in total mcfDNA burden in the plasma after transplantation, which was most striking during the early posttransplant neutropenic phase. This elevation could be attributed to a number of specific bacterial taxa, including Veillonella, Bacteroides, and Prevotella (genus level). For an additional cohort of patients, we compared the data of mcfDNA from plasma with 16s-ribosomal RNA sequencing data from stool samples collected at matched time points. In a number of patients, we confirmed that mcfDNA derived from specific microbial taxa (eg, Enterococcus) could also be observed in the matched stool sample. Quantification of mcfDNA may generate novel insights into mechanisms by which the intestinal microbiome influences systemic cell populations and, thus, has been associated with outcomes for patients with cancer.

Noninvasive diagnosis of secondary infections in COVID-19 by sequencing of plasma microbial cell-free DNA.

Secondary infection (SI) diagnosis in severe COVID-19 remains challenging. We correlated metagenomic sequencing of plasma microbial cell-free DNA (mcfDNA-Seq) with clinical SI assessment, immune response, and outcomes. We classified 42 COVID-19 inpatients as microbiologically confirmed-SI (Micro-SI, n = 8), clinically diagnosed-SI (Clinical-SI, n = 13, i.e., empiric antimicrobials), or no-clinical-suspicion-for-SI (No-Suspected-SI, n = 21). McfDNA-Seq was successful in 73% of samples. McfDNA detection was higher in Micro-SI (94%) compared to Clinical-SI (57%, p = 0.03), and unexpectedly high in No-Suspected-SI (83%), similar to Micro-SI. We detected culture-concordant mcfDNA species in 81% of Micro-SI samples. McfDNA correlated with LRT 16S rRNA bacterial burden (r = 0.74, p = 0.02), and biomarkers (white blood cell count, IL-6, IL-8, SPD, all p < 0.05). McfDNA levels were predictive of worse 90-day survival (hazard ratio 1.30 [1.02-1.64] for each log10 mcfDNA, p = 0.03). High mcfDNA levels in COVID-19 patients without clinical SI suspicion may suggest SI under-diagnosis. McfDNA-Seq offers a non-invasive diagnostic tool for pathogen identification, with prognostic value on clinical outcomes.

African ancestry allelic variation at the MYH9 gene contributes to increased susceptibility to non-diabetic end-stage kidney disease in Hispanic Americans.

Recent studies identified MYH9 as a major susceptibility gene for common forms of non-diabetic end-stage kidney disease (ESKD). A set of African ancestry DNA sequence variants comprising the E-1 haplotype, was significantly associated with ESKD. In order to determine whether African ancestry variants are also associated with disease susceptibility in admixed populations with differing genomic backgrounds, we genotyped a total of 1425 African and Hispanic American subjects comprising dialysis patients with diabetic and non-diabetic ESKD and controls, using 42 single nucleotide polymorphisms (SNPs) within the MYH9 gene and 40 genome-wide and 38 chromosome 22 ancestry informative markers. Following ancestry correction, logistic regression demonstrated that three of the E-1 SNPs are also associated with non-diabetic ESKD in the new sample sets of both African and Hispanic Americans, with a stronger association in Hispanic Americans. We also identified MYH9 SNPs that are even more powerfully associated with the disease phenotype than the E-1 SNPs. These newly associated SNPs, could be divided into those comprising a haplotype termed S-1 whose association was significant under a recessive or additive inheritance mode (rs5750248, OR 4.21, P < 0.01, Hispanic Americans, recessive), and those comprising a haplotype termed F-1 whose association was significant under a dominant or additive inheritance mode (rs11912763, OR 4.59, P < 0.01, Hispanic Americans, dominant). These findings strengthen the contention that a sequence variant of MYH9, common in populations with varying degrees of African ancestry admixture, and in strong linkage disequilibrium with the associated SNPs and haplotypes reported herein, strongly predisposes to non-diabetic ESKD.

Reconstruction of genealogical relationships with applications to Phase III of HapMap.

MOTIVATION: Accurate inference of genealogical relationships between pairs of individuals is paramount in association studies, forensics and evolutionary analyses of wildlife populations. Current methods for relationship inference consider only a small set of close relationships and have limited to no power to distinguish between relationships with the same number of meioses separating the individuals under consideration (e.g. aunt-niece versus niece-aunt or first cousins versus great aunt-niece). RESULTS: We present CARROT (ClAssification of Relationships with ROTations), a novel framework for relationship inference that leverages linkage information to differentiate between rotated relationships, that is, between relationships with the same number of common ancestors and the same number of meioses separating the individuals under consideration. We demonstrate that CARROT clearly outperforms existing methods on simulated data. We also applied CARROT on four populations from Phase III of the HapMap Project and detected previously unreported pairs of third- and fourth-degree relatives. AVAILABILITY: Source code for CARROT is freely available at http://carrot.stanford.edu. CONTACT: sofiakp@stanford.edu.

Alopecia, neurological defects, and endocrinopathy syndrome caused by decreased expression of RBM28, a nucleolar protein associated with ribosome biogenesis.

Single-gene disorders offer unique opportunities to shed light upon fundamental physiological processes in humans. We investigated an autosomal-recessive phenotype characterized by alopecia, progressive neurological defects, and endocrinopathy (ANE syndrome). By using homozygosity mapping and candidate-gene analysis, we identified a loss-of-function mutation in RBM28, encoding a nucleolar protein. RBM28 yeast ortholog, Nop4p, was previously found to regulate ribosome biogenesis. Accordingly, electron microscopy revealed marked ribosome depletion and structural abnormalities of the rough endoplasmic reticulum in patient cells, ascribing ANE syndrome to the restricted group of inherited disorders associated with ribosomal dysfunction.

Estimating genome-wide IBD sharing from SNP data via an efficient hidden Markov model of LD with application to gene mapping.

MOTIVATION: Association analysis is the method of choice for studying complex multifactorial diseases. The premise of this method is that affected persons contain some common genomic regions with similar SNP alleles and such areas will be found in this analysis. An important disadvantage of GWA studies is that it does not distinguish between genomic areas that are inherited from a common ancestor [identical by descent (IBD)] and areas that are identical merely by state [identical by state (IBS)]. Clearly, areas that can be marked with higher probability as IBD and have the same correlation with the disease status of identical areas that are more probably only IBS, are better candidates to be causative, and yet this distinction is not encoded in standard association analysis. RESULTS: We develop a factorial hidden Markov model-based algorithm for computing genome-wide IBD sharing. The algorithm accepts as input SNP data of measured individuals and estimates the probability of IBD at each locus for every pair of individuals. For two g-degree relatives, when g > or = 8, the computation yields a precision of IBD tagging of over 50% higher than previous methods for 95% recall. Our algorithm uses a first-order Markovian model for the linkage disequilibrium process and employs a reduction of the state space of the inheritance vector from being exponential in g to quadratic. The higher accuracy along with the reduced time complexity marks our method as a feasible means for IBD mapping in practical scenarios. AVAILABILITY: A software implementation, called IBDMAP, is freely available at http://bioinfo.cs.technion.ac.il/IBDmap.

Detection of microbial cell-free DNA in maternal and umbilical cord plasma in patients with chorioamnionitis using next generation sequencing.

BACKGROUND: Chorioamnionitis has been linked to spontaneous preterm labor and complications such as neonatal sepsis. We hypothesized that microbial cell-free (cf) DNA would be detectable in maternal plasma in patients with chorioamnionitis and could be the basis for a non-invasive method to detect fetal exposure to microorganisms. OBJECTIVE: The purpose of this study was to determine whether next generation sequencing could detect microbial cfDNA in maternal plasma in patients with chorioamnionitis. STUDY DESIGN: Maternal plasma (n = 94) and umbilical cord plasma (n = 120) were collected during delivery at gestational age 28-41 weeks. cfDNA was extracted and sequenced. Umbilical cord plasma samples with evidence of contamination were excluded. The prevalence of microorganisms previously implicated in choriomanionitis, neonatal sepsis and intra-amniotic infections, as described in the literature, were examined to determine if there was enrichment of these microorganisms in this cohort. Specific microbial cfDNA associated with chorioamnionitis was first detected in umbilical cord plasma and confirmed in the matched maternal plasma samples (n = 77 matched pairs) among 14 cases of histologically confirmed chorioamnionitis and one case of clinical chorioamnionitis; 63 paired samples were used as controls. A correlation of rank of a given microorganism across maternal plasma and matched umbilical cord plasma was used to assess whether signals found in umbilical cord plasma were also present in maternal plasma. RESULTS: Microbial DNA sequences associated with clinical and/or histological chorioamnionitis were enriched in maternal plasma in cases with suspected chorioamnionitis when compared to controls (12/14 microorganisms, p = 0.02). Analysis of the microbial cfDNA in umbilical cord plasma among the 1,251 microorganisms detectable with this assay identified Streptococcus mitis, Ureaplasma spp., and Mycoplasma spp. in cases of suspected chorioamnionitis. This assay also detected cfDNA from Lactobacillus spp. in controls. Comparison between maternal plasma and umbilical cord plasma confirmed these signatures were also present in maternal plasma. Unbiased analysis of microorganisms with significantly correlated signal between matched maternal plasma and umbilical cord plasma identified the above listed 3 microorganisms, all of which have previously been implicated in patients with chorioamnionitis (Mycoplasma hominis p = 0.0001; Ureaplasma parvum p = 0.002; Streptococcus mitis p = 0.007). These data show that the pathogen signal relevant for chorioamnionitis can be identified in both maternal and umbilical cord plasma. CONCLUSION: This is the first report showing the detection of relevant microbial cell-free cfDNA in maternal plasma and umbilical cord plasma in patients with clinical and/or histological chorioamnionitis. These results may lead to the development of a specific assay to detect perinatal infections for targeted therapy to reduce early neonatal sepsis complications.

Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease.

Thousands of pathogens are known to infect humans, but only a fraction are readily identifiable using current diagnostic methods. Microbial cell-free DNA sequencing offers the potential to non-invasively identify a wide range of infections throughout the body, but the challenges of clinical-grade metagenomic testing must be addressed. Here we describe the analytical and clinical validation of a next-generation sequencing test that identifies and quantifies microbial cell-free DNA in plasma from 1,250 clinically relevant bacteria, DNA viruses, fungi and eukaryotic parasites. Test accuracy, precision, bias and robustness to a number of metagenomics-specific challenges were determined using a panel of 13 microorganisms that model key determinants of performance in 358 contrived plasma samples, as well as 2,625 infections simulated in silico and 580 clinical study samples. The test showed 93.7% agreement with blood culture in a cohort of 350 patients with a sepsis alert and identified an independently adjudicated cause of the sepsis alert more often than all of the microbiological testing combined (169 aetiological determinations versus 132). Among the 166 samples adjudicated to have no sepsis aetiology identified by any of the tested methods, sequencing identified microbial cell-free DNA in 62, likely derived from commensal organisms and incidental findings unrelated to the sepsis alert. Analysis of the first 2,000 patient samples tested in the CLIA laboratory showed that more than 85% of results were delivered the day after sample receipt, with 53.7% of reports identifying one or more microorganisms.

Liquid biopsy for infectious diseases: sequencing of cell-free plasma to detect pathogen DNA in patients with invasive fungal disease.

Diagnosis of life-threatening deep-seated infections currently requires invasive sampling of the infected tissue to provide a microbiologic diagnosis. These procedures can lead to high morbidity in patients and add to healthcare costs. Here we describe a novel next-generation sequencing assay that was used to detect pathogen-derived cell-free DNA in peripheral blood of patients with biopsy-proven invasive fungal infections. The noninvasive nature of this approach could provide rapid, actionable treatment information for invasive fungal infections when a biopsy is not possible.

Plasma Cell-Free DNA Next-Generation Sequencing to Diagnose and Monitor Infections in Allogeneic Hematopoietic Stem Cell Transplant Patients.

Allogeneic hematopoietic stem cell transplant patients are at risk for common and atypical infections. Superior diagnostics can decrease infection-related morbidity and mortality. A novel plasma cell-free DNA next-generation sequencing test detected an uncommon presentation of Chlamydia trachomatis and recurrent and metastatic complications of Staphylococcus aureus bacteremia before standard microbiology.

An effective filter for IBD detection in large data sets.

Identity by descent (IBD) inference is the task of computationally detecting genomic segments that are shared between individuals by means of common familial descent. Accurate IBD detection plays an important role in various genomic studies, ranging from mapping disease genes to exploring ancient population histories. The majority of recent work in the field has focused on improving the accuracy of inference, targeting shorter genomic segments that originate from a more ancient common ancestor. The accuracy of these methods, however, is achieved at the expense of high computational cost, resulting in a prohibitively long running time when applied to large cohorts. To enable the study of large cohorts, we introduce SpeeDB, a method that facilitates fast IBD detection in large unphased genotype data sets. Given a target individual and a database of individuals that potentially share IBD segments with the target, SpeeDB applies an efficient opposite-homozygous filter, which excludes chromosomal segments from the database that are highly unlikely to be IBD with the corresponding segments from the target individual. The remaining segments can then be evaluated by any IBD detection method of choice. When examining simulated individuals sharing 4 cM IBD regions, SpeeDB filtered out 99.5% of genomic regions from consideration while retaining 99% of the true IBD segments. Applying the SpeeDB filter prior to detecting IBD in simulated fourth cousins resulted in an overall running time that was 10,000x faster than inferring IBD without the filter and retained 99% of the true IBD segments in the output.

Ancestry inference in complex admixtures via variable-length Markov chain linkage models.

Inferring the ancestral origin of chromosomal segments in admixed individuals is key for genetic applications, ranging from analyzing population demographics and history, to mapping disease genes. Previous methods addressed ancestry inference by using either weak models of linkage disequilibrium, or large models that make explicit use of ancestral haplotypes. In this paper we introduce ALLOY, an efficient method that incorporates generalized, but highly expressive, linkage disequilibrium models. ALLOY applies a factorial hidden Markov model to capture the parallel process producing the maternal and paternal admixed haplotypes, and models the background linkage disequilibrium in the ancestral populations via an inhomogeneous variable-length Markov chain. We test ALLOY in a broad range of scenarios ranging from recent to ancient admixtures with up to four ancestral populations. We show that ALLOY outperforms the previous state of the art, and is robust to uncertainties in model parameters.