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.

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.

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.

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.

673. Unbiased Microbial Cell-free DNA Next-Generation Sequencing Resolves HHV6 Variant Specificity and Demonstrates a Predominance of HHV6B over HHV6A in Real-World Clinical Experience

Background

Human herpesvirus 6 (HHV6) has been classified in two distinct variants, HHV6A and HHV6B. Although distinct epidemiology, disease association, biological and immunological properties, their genomes are 90% homologous. Less is known about HHV6A which is typically asymptomatic but can cause severe infection in patients with neurological disorders or HIV. HHV6B infection occurs during childhood, but can reactivate after solid organ and stem cell transplantation. Antibody assays may indicate previous, recent or current infection. Quantitative PCR cannot differentiate active from latent infections and some available qualitative PCR assays are unable to differentiate the two variants. A single open-ended test through plasma-based microbial cell-free DNA (mcfDNA) metagenomic next-generation sequencing (NGS) may overcome these limitations.

Methods

Karius TestTM (KT) developed and validated in Karius’s CLIA certified/CAP accredited lab, detects mcfDNA from plasma. mcfDNA is extracted, NGS performed, human sequences removed and remaining sequences aligned to a curated pathogen database of &gt; 1500 organisms. Organisms present above a statistical threshold are reported and quantified. For &gt; 85% of tests the time to result reporting is the next day from sample receipt. KT results were reviewed from November-2018 to May-2021 for detections of HHV6A and HHV6B. The comparative incidence of HHV6A and HHVB detections, their age distributions and their quantitative viral concentration in molecules/µL (MPM) were assessed.

Results

KT detected 322 cases of HHV6; 10% (n=32) were HHV6A and 90% (n=290) HHV6B (Table 1). HHV6B had a higher relative abundance in children (with a distribution into adolescence) compared to adults (Figure 1). The average HHV6A MPM was 860 (range 27 - 10,472); the average HHV6B MPM was 3,361 (range 21 - 131,518).

Table 1. Summary of HHV-6 Detections

Conclusion

The distribution of the HHV6 variants detected through KT shows an overwhelming 9:1 predominance of HHV6B to HHV6A. The application of mcfDNA metagenomic sequencing for open-ended detection, variant determination and quantification of HHV6 provides more specific resolution than serological and PCR methods. KT may lend important insights into the association of specific HHV6 variants with clinical syndromes affecting vulnerable populations.

Disclosures

Jose Alexander, MD, D(ABMM), FCCM, CIC, SM, MB(ASCP), BCMAS, Karius (Employee) Sivan Bercovici, PhD, Karius (Employee) Nicholas R. Degner, MD, MPH, MS, Karius Inc. (Employee, Shareholder) Ricardo Castillo-Galvan, MD MPH, Karius Inc. (Consultant) Aparna Arun, MD, Karius (Employee) Ann Macintyre, DO, Karius, Inc. (Employee) Bradley Perkins, MD, Karius, Inc. (Employee) Asim A. Ahmed, MD, Karius, Inc. (Employee) Matthew Smollin, PharmD, Karius, Inc. (Employee)

928. Clinical Characteristics and Microbiology Testing Patterns Among Transplant Recipients Admitted to Acute Care Hospitals for Suspected Infection

Background

Solid organ transplant (SOT) is a growing option for patients with end-stage organ diseases. Immunosuppressive therapy (IT) is utilized in this population to minimize risk of allograft rejection, which increases infection risk particularly of atypical pathogens that can complicate the infection-related diagnostic journey. The purpose of this analysis was to evaluate baseline clinical characteristics and microbiological testing utilization patterns among a cohort of patients with a history of SOT and IT.

Methods

This retrospective cohort study utilized a US hospital-based, service-level database. Patients were selected from a subsample of database facilities utilizing plasma microbial cell-free DNA diagnostic assays. The study period was 1/1/2017-3/21/2020. Eligible patients were identified by 1^st observation of SOT status and IT. Subsequent inpatient admissions for suspected infection were analyzed.

Results

We identified 749 patients with SOT history and use of IT, 56.4% were male, and the mean age was 52.8 (18.7) years. Kidney was the most prevalent transplant category (49.1%), followed by liver (14.1%), lung (10.9%), and heart (10.3%), and 9.7% were multi-organ. Patients experiencing multiple transplants had the most chronic conditions with a mean Elixhauser comorbidity score of 26.3 (14.7). The median length of stay was 4 [3-7] days. The median number of tests per encounter was 6 [IQR=3-11]. Culture was the most utilized test category (2 [1-4]). Blood culture was the highest utilized culture and overall test at 13.5% of all tests observed, while CMV PCR (7.8%) and multi-panel EIA (2.7%) were the most frequent molecular and antigen tests, respectively. Lung transplant recipients had the greatest utilization of tests overall (9 [3.5-17]) versus other transplant categories (6 [3-10]), consistent with the observed test rate in the 1^st 48 hours of presentation (4 [1-7] vs. 2 [1-5]).

Conclusion

This analysis suggests that the infection-related diagnostic journey among patients with a history of SOT involves high utilization of microbiological testing, with greater utilization among lung transplant recipients versus other SOT recipients. Variation in clinical characteristics and microbiological testing patterns were observed across SOT categories.

Disclosures

T Matthew Hill, PharmD, PhD, Karius, Inc (Employee, Shareholder) Erick R. Scott, MD, MHS, Karius, Inc (Employee, Shareholder) Sivan Bercovici, PhD, Karius (Employee)

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.

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.

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.

810. Diagnosis of BCG Aortitis by Plasma Metagenomic Sequencing

Background

The use of intra-vesicular Bacille Calmette-Guerin (BCG) for bladder cancer can result in disseminated/endovascular BCG infection. The diagnosis of BCGosis in this setting is complicated by the risks of biopsy of an endovascular focus and the long duration of acid-fast bacilli (AFB) cultures.

Methods

A 68-year-old male with a history of hypertension, aortic aneurysm (status post repair), and bladder cancer treated with intravesicular BCG complicated by BCGosis presented several years later with two weeks of fevers, chills, night sweats, and back pain. Computed tomography (CT) scan demonstrated aortitis with periaortic abscess. There was concern for BCG aortitis given the antecedent BCG exposure and prior BCGosis. Blood cultures were negative; AFB blood cultures were contaminated. A sample of plasma was sent to Karius (Redwood City, CA) for next-generation sequencing (NGS). Cell-free DNA was extracted and NGS performed. Human sequences were removed and remaining sequences were aligned to a curated pathogen database of >1,000 organisms. Organisms present above a statistical threshold were reported. The patient underwent surgical replacement of the infected endograft; endovascular samples were sent for AFB culture.

Results

Plasma-based NGS of cell free DNA detected M. tuberculosis (Mtb) complex at 48 hours (within 28 hours of sample receipt). Within the Mtb complex, the majority of sequences aligned to M. bovis with five reads aligning uniquely to M. bovis. No reads aligned to the region of deletion 1 (RD1) deleted in BCG. Surgical AFB cultures were positive for Mtb complex by PCR probe at nine days; Mtb complex was recovered in culture at 19 days.

Conclusion

Plasma metagenomic sequencing can be used to rapidly diagnose BCG-associated endovascular infection.

Disclosures

C. Cooper, Karius, Inc.: Consultant, Consulting fee. D. Hong, Karius, Inc.: Employee, Salary. L. Blair, Karius: Employee, Salary. S. Bercovici, Karius, Inc.: Employee, Salary. A. Ahmed, Karius, Inc.: Employee, Salary.

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.

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.

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.

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.

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.

Population-specific association between a polymorphic variant in ST18, encoding a pro-apoptotic molecule, and pemphigus vulgaris

Pemphigus vulgaris (PV) is a severe autoimmune blistering disease caused by anti-epithelial antibodies, leading to disruption of cell-cell adhesion. Although the disease is exceedingly rare worldwide, it is known to be relatively prevalent in Jewish populations. The low prevalence of the disease represents a significant obstacle to a genome-wide approach to the mapping of susceptibility genes. We reasoned that the study of a genetically homogeneous cohort characterized by a high prevalence of PV may help exposing associated signals while reducing spurious results due to population sub-structure. We performed a genome-wide association study using 300K single-nucleotide polymorphisms (SNPs) in a case-control study of 100 PV patients of Jewish descent and 397 matched control individuals, followed by replication of significantly associated SNPs in three additional cohorts of Jewish, Egyptian, and German origin. In addition to the major histocompatibility complex locus, a genomic segment on 8q11.23 that spans the ST18 gene was also found to be significantly associated with PV. This association was confirmed in the Jewish and Egyptian replication sets but not in the German sample, suggesting that ST18-associated variants may predispose to PV in a population-specific manner. ST18 regulates apoptosis and inflammation, two processes of direct relevance to the pathogenesis of PV. Further supporting the relevance of ST18 to PV, we found this gene to be overexpressed in the skin of PV patients as compared with healthy individuals.

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.

Pathway-based functional analysis of metagenomes

Metagenomic data enables the study of microbes and viruses through their DNA as retrieved directly from the environment in which they live. Functional analysis of metagenomes explores the abundance of gene families, pathways, and systems, rather than their taxonomy. Through such analysis, researchers are able to identify those functional capabilities most important to organisms in the examined environment. Recently, a statistical framework for the functional analysis of metagenomes was described that focuses on gene families. Here we describe two pathway level computational models for functional analysis that take into account important, yet unaddressed issues such as pathway size, gene length, and overlap in gene content among pathways. We test our models over carefully designed simulated data and propose novel approaches for performance evaluation. Our models significantly improve over the current approach with respect to pathway ranking and the computations of relative abundance of pathways in environments.

Admixture mapping of end stage kidney disease genetic susceptibility using estimated mutual information ancestry informative markers

BACKGROUND

The question of a genetic contribution to the higher prevalence and incidence of end stage kidney disease (ESKD) among African Americans (AA) remained unresolved, until recent findings using admixture mapping pointed to the association of a genomic locus on chromosome 22 with this disease phenotype. In the current study we utilize this example to demonstrate the utility of applying a multi-step admixture mapping approach.

METHODS

A multi-step case only admixture mapping study, consisted of the following steps was designed: 1) Assembly of the sample dataset (ESKD AA); 2) Design of the estimated mutual information ancestry informative markers (n = 2016) screening panel 3); Genotyping the sample set whose size was determined by a power analysis (n = 576) appropriate for the initial screening panel; 4) Inference of local ancestry for each individual and identification of regions with increased AA ancestry using two different ancestry inference statistical approaches; 5) Enrichment of the initial screening panel; 6) Power analysis of the enriched panel 7) Genotyping of additional samples. 8) Re-analysis of the genotyping results to identify a genetic risk locus.

RESULTS

The initial screening phase yielded a significant peak using the ADMIXMAP ancestry inference program applying case only statistics. Subgroup analysis of 299 ESKD patients with no history of diabetes yielded peaks using both the ANCESTRYMAP and ADMIXMAP ancestry inference programs. The significant peak was found on chromosome 22. Genotyping of additional ancestry informative markers on chromosome 22 that took into account linkage disequilibrium in the ancestral populations, and the addition of samples increased the statistical significance of the finding.

CONCLUSIONS

A multi-step admixture mapping analysis of AA ESKD patients replicated the finding of a candidate risk locus on chromosome 22, contributing to the heightened susceptibility of African Americans to develop non-diabetic ESKD, and underscores the importance of using mutual information and multiple ancestry inference approaches to achieve a robust analysis, using relatively small datasets of "affected" only individuals. The current study suggests solutions to some limitations of existing admixture mapping methodologies, such as considerations regarding the distribution of ancestry information along the genome and its effects on power calculations and sample size.

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.

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.

Inferring ancestries efficiently in admixed populations with linkage disequilibrium

Much effort has recently been invested in developing methods for determining the ancestral origin of chromosomal segments in admixed individuals. Motivations for this task are the study of population history such as bottleneck effects and migration, the assessment of population stratification for adequate adjustment of association studies, and the enhancement of mapping by admixture linkage disequilibrium (MALD). In this article, we present a novel framework for the inference of ancestry at each chromosomal location. The uniqueness of our method stems from the ability to incorporate complex probability models that account for linkage-disequilibrium in the ancestral populations. We provide an inference algorithm that is polynomial in the number of markers even though the underlying problem seems to be inherently exponential in nature. We demonstrate the validity of our model and conclude that, with sufficient ancestral haplotypes, this framework can provide higher accuracy in inferring ancestral origin.

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.

Panel construction for mapping in admixed populations via expected mutual information

Mapping by admixture linkage disequilibrium (MALD) is an economical and powerful approach for the identification of genomic regions harboring disease susceptibility genes in recently admixed populations. We develop an information-theory-based measure, called expected mutual information (EMI), which computes the impact of a set of markers on the ability to infer ancestry at each chromosomal location. We then present a simple and effective algorithm for the selection of panels that strives to maximize the EMI score. Finally, we demonstrate via well-established simulation tools that our panels provide more power and accuracy for inferring disease gene loci via the MALD method in comparison to previous methods.

Transformation of human diploid cells by adenovirus type 4 irradiated with ultraviolet light

Inoculation of ultraviolet (UV)-irradiated adenovirus type 4 (Ad4) led to in vitro transformation of human diploid cells (HDC). Two transformed cell lines could be established: cell line H 1418, from HDC inoculated with the 10(-3) dilution of Ad4 UV-irradiated for 20 min at a distance of 20 cm, co-cultivated with uninfected HDC, and cell line H 1557, from HDC inoculated with the 10(-2) dilution of Ad4 irradiated at the same distance for 12 min. Both transformed cell lines were resistant to superinfection with homologous virus. Virus-specific antigen could be made evident by the indirect immunofluorescence technique in the nuclei of both H 1418 and H 1557 cells.