Polydrug use among patients on methadone medication treatment: Evidence from urine drug testing to inform patient safety.

AIMS: Patients in methadone medication treatment for opioid use disorder (M-MOUD) typically have a complex history of opioid use, often in combination with other drugs. It is unknown how frequently M-MOUD patients experience persistent substance or polysubstance use. We measured trends in illicit substance use in a large, multistate population of M-MOUD patients and persistence of substance use in the first year of treatment. DESIGN: Retrospective cohort study of United States (US) M-MOUD patients from 2017 to 2021, focused on urine drug specimens provided for testing to Millennium Health, a third-party laboratory. Specimens were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Generalized estimating equations (GEE) were used to estimate the average trends in positivity during time in treatment. SETTING: Specimens were obtained from clinics in 10 US states that provided at least 300 unique patients during the study period (Alaska, Arizona, Florida, Illinois, Kentucky, Minnesota, New Mexico, Ohio, Virginia and Washington). PARTICIPANTS: Patients with opioid use disorder receiving M-MOUD (n = 16 386). MEASUREMENTS: Positivity rates for heroin, fentanyl, methamphetamine and cocaine. FINDINGS: From 2017 to 2021, yearly crude positivity rates for first collected specimens increased for fentanyl (13.1%-53.0%, P < 0.001), methamphetamine (10.6%-27.2%, P < 0.001) and cocaine (13.8%-19.5%, P < 0.001); for heroin positivity did not significantly change (6.9%-6.5%, P = 0.74). In regression models estimating patient trajectories from week 1 to week 52, marginal fentanyl positivity declined from 21.8% to 17.1% (incidence rate ratio [IRR] = 0.78, P < 0.001) and heroin positivity declined from 8.4% to 4.3% (IRR = 0.51, P < 0.001), but positivity for methamphetamine and cocaine did not significantly change, remaining at an average of 17.7% (IRR = 0.98, P = 0.53) and 9.2% (IRR = 0.96, P = 0.36), respectively. CONCLUSIONS: Between 2017 and 2021, United States patients presenting to opioid treatment programs increasingly tested positive for fentanyl, methamphetamine and cocaine. Methadone medication treatment for opioid use disorder appears to remain an effective intervention for reducing illicit opioid use.

Accelerating Minimap2 for Accurate Long Read Alignment on GPUs.

Long read sequencing technology is becoming increasingly popular for Precision Medicine applications like Whole Genome Sequencing (WGS) and microbial abundance estimation. Minimap2 is the state-of-the-art aligner and mapper used by the leading long read sequencing technologies, today. However, Minimap2 on CPUs is very slow for long noisy reads. ~60-70% of the run-time on a CPU comes from the highly sequential chaining step in Minimap2. On the other hand, most Point-of-Care computational workflows in long read sequencing use Graphics Processing Units (GPUs). We present minimap2-accelerated (mm2-ax), a heterogeneous design for sequence mapping and alignment where minimap2's compute intensive chaining step is sped up on the GPU and demonstrate its time and cost benefits. We extract better intra-read parallelism from chaining without losing mapping accuracy by forward transforming Minimap2's chaining algorithm. Moreover, we better utilize the high memory available on modern cloud instances apart from better workload balancing, data locality and minimal branch divergence on the GPU. We show mm2-ax on an NVIDIA A100 GPU improves the chaining step with 5.41 - 2.57X speedup and 4.07 - 1.93X speedup : costup over the fastest version of Minimap2, mm2-fast, benchmarked on a Google Cloud Platform instance of 30 SIMD cores.

Association of Patients' Direct Addition of Buprenorphine to Urine Drug Test Specimens With Clinical Factors in Opioid Use Disorder.

Importance: The direct addition of buprenorphine to urine drug test specimens to mimic results suggestive of adherence is a clinically significant result, yet little is known about the phenomenon. Objective: To characterize factors associated with the direct addition of buprenorphine to urine specimens among patients prescribed buprenorphine for opioid use disorder. Design, Setting, and Participants: This cross-sectional study of urine drug test specimens was conducted from January 1, 2017, to April 30, 2022, using a national database of urine drug test specimens ordered by clinicians from primary care, behavioral health, and substance use disorder treatment clinics. Urine specimens with quantitative norbuprenorphine and buprenorphine concentrations from patients with opioid use disorder currently prescribed buprenorphine were analyzed. Exposures: Nonprescribed opioid or stimulant co-positive, clinical setting, collection year, census division, patient age, patient sex, and payor. Main Outcomes and Measures: Norbuprenorphine to buprenorphine ratio less than 0.02 identified direct addition of buprenorphine. Unadjusted trends in co-positivity for stimulants and opioids were compared between specimens consistent with the direct addition of buprenorphine. Factors associated with the direct addition of buprenorphine were examined with generalized estimating equations. Results: This study included 507 735 urine specimens from 58 476 patients. Of all specimens, 261 210 (51.4%) were obtained from male individuals, and 137 254 (37.7%) were from patients aged 25 to 34 years. Overall, 9546 (1.9%) specimens from 4550 (7.6%) patients were suggestive of the direct addition of buprenorphine. The annual prevalence decreased from 2.4% in 2017 to 1.2% in 2020. Opioid-positive with (adjusted odds ratio [aOR], 2.01; 95% CI, 1.85-2.18) and without (aOR, 2.02; 95% CI, 1.81-2.26) stimulant-positive specimens were associated with the direct addition of buprenorphine to specimens, while opioid-negative/stimulant-positive specimens were negatively associated (aOR, 0.78; 95% CI, 0.71-0.85). Specimens from patients aged 35 to 44 years (aOR, 1.59; 95% CI, 1.34-1.90) and primary care (aOR, 1.60; 95% CI, 1.44-1.79) were associated with the direct addition of buprenorphine. Differences by treatment setting decreased over time. Specimens from the South Atlantic census region had the highest association (aOR, 1.4; 95% CI, 1.25-1.56) and New England had the lowest association (aOR, 0.54; 95% CI, 0.46-0.65) with the direct addition of buprenorphine. Conclusions and Relevance: In this cross-sectional study, the direct addition of buprenorphine to urine specimens was associated with other opioid positivity and being collected in primary care settings. The direct addition of buprenorphine to urine specimens is a clinically significant finding, and best practices specific for this phenomenon are needed.

Definitive urine drug test findings in patients prescribed opioids for pain from a large national database.

OBJECTIVE: Clinicians and policymakers have been wrestling with the appropriateness and safety of opioid therapy during the opioid crisis. Policy and clinical decisions have often been made without much current data on trends in drug use in patients with pain. Thus, we evaluated definitive urine drug test (UDT) results in patients being treated for pain to see if those taking their prescribed opioids were less likely to be positive for the primary illicit drugs currently driving overdose deaths: cocaine, heroin, fentanyl, and methamphetamine. DESIGN, SETTING, AND PATIENTS: A cross-sectional study of UDT results from January 1, 2015 to September 30, 2021, from 600,000 patient specimens submitted for testing by pain management specialists. INTERVENTIONS: UDT by liquid chromatography-tandem mass spectrometry as ordered by the treating clinician. MAIN OUTCOME MEASURES: Presence of other substances stratified by whether a patient's prescribed opioid was found. RESULTS: The presence of cocaine, heroin, fentanyl, and methamphetamine for the total population was low (<5 percent). Of the 347,092 patients prescribed opioids, 76 percent (n = 264,961) were positive on UDT for their prescribed opioid ("consistent"). Compared to patients without their prescribed opioid present ("inconsistent"), patients consistent with therapy were 54 percent (incidence rate ratio (IRR) 1.54, 95 percent confidence interval (CI) 1.47-1.59) less likely to be positive for cocaine, 47 percent [IRR 1.47, 95 percent CI 1.34-1.57] less likely to be positive for heroin, and 35 percent [IRR 1.35, 95 percent CI 1.24-1.45] less likely to be positive for methamphetamine, p < 0.001. Differences between the groups for fentanyl were not significant. CONCLUSIONS: Overall positivity rates for cocaine, heroin, fentanyl, and methamphetamine were low. Patients with prescribed opioid present were less likely to be positive for cocaine, heroin, or methamphetamine. Patterns of substance use within this pain management population should be used to inform ongoing policy decisions.

Analysis of Urine Drug Test Results From Substance Use Disorder Treatment Practices and Overdose Mortality Rates, 2013-2020.

Importance: Drug overdose deaths in the US are currently the highest ever recorded; data collected from public health surveillance sources can help to identify emerging drug use patterns associated with overdose mortality rates, but the time lag in results often limits utility. Urine drug testing (UDT) is one potentially underused source that could augment surveillance efforts through timely data collection. Objective: To evaluate the correlation between real-time UDT results from a proprietary national database and overdose mortality data from the National Vital Statistics System. Design, Setting, and Participants: This retrospective cross-sectional study included 500 000 urine specimens submitted for UDT by substance use disorder (SUD) treatment health care practices and collected between January 1, 2013, and December 31, 2020. Real-time UDT data were obtained from the Millennium Health proprietary national database, and overdose mortality data were obtained from the National Vital Statistics System of the Centers for Disease Control and Prevention (CDC WONDER). Specimens were analyzed for specific drugs in 5 categories (cocaine, heroin, methamphetamine, synthetic opioids, and other opioids) using liquid chromatography-tandem mass spectrometry. Participants were adults aged 18 years and older who provided urine specimens at SUD treatment practices. Exposures: Urine drug testing. Main Outcomes and Measures: The primary outcome was the correlation between UDT positivity rates and overdose mortality rates at national, state, and county levels. Univariate and multivariate regression models were also used to evaluate the association between state- and county-level overdose mortality and standardized UDT positivity rates. Results: Among 500 000 unique patient specimens collected from SUD treatment practices between 2013 and 2020, 288 534 specimens (57.7%) were from men, and the median age of the study population was 34 years (IQR, 17-51 years). On a national level, synthetic opioids and methamphetamine were highly correlated with overdose mortality (Spearman ρ = 0.96 for both). When synthetic opioids were coinvolved, methamphetamine (ρ = 0.98), heroin (ρ = 0.78), cocaine (ρ = 0.94), and other opioids (ρ = 0.83) were also highly correlated with overdose mortality. In the absence of synthetic opioids, all drug categories were highly correlated (ρ = 0.75 for other opioids, 0.81 for heroin, and 0.88 for methamphetamine), with the exception of cocaine (ρ = -0.37). Synthetic opioids (ρ = 0.77) and methamphetamine (ρ = 0.80) had the strongest state-level correlations over time, whereas other opioids had the lowest correlation for both total positivity (ρ = 0.31) and positivity in the absence of synthetic opioids (ρ = 0.23). In Ohio, county-level correlation was strongest for synthetic opioids (ρ = 0.71), followed by heroin (ρ = 0.69) and methamphetamine (ρ = 0.67). At the state level, the multivariate incidence rate ratio (IRR) for synthetic opioids was 1.16 (95% CI, 1.14-1.19; P < .001), and at the county level, the IRR was 1.13 (95% CI, 1.09-1.17; P < .001), suggesting that for every 1-SD increase in the UDT positivity rate, there were 16.2% and 12.8% increases, respectively, in monthly overdose deaths. Both methamphetamine (11.7% increase per 1-SD increase in UDT positivity rate; IRR, 1.12; 95% CI, 1.09-1.14; P < .001) and cocaine (5.1% increase per 1-SD increase in UDT positivity rate; IRR, 1.05; 95% CI, 1.03-1.07; P < .001) also had significant positive associations with mortality rates, but the effect sizes were smaller than that of synthetic opioids (IRR, 1.16). Conclusions and Relevance: In this study, UDT results were highly correlated with mortality rates at national, state, and county levels. These findings suggest that real-time UDT surveillance can help to quickly identify changes in drug use patterns that might inform targeted harm reduction strategies designed to prevent overdose deaths.

A spectrum of free software tools for processing the VCF variant call format: vcflib, bio-vcf, cyvcf2, hts-nim and slivar.

Since its introduction in 2011 the variant call format (VCF) has been widely adopted for processing DNA and RNA variants in practically all population studies-as well as in somatic and germline mutation studies. The VCF format can represent single nucleotide variants, multi-nucleotide variants, insertions and deletions, and simple structural variants called and anchored against a reference genome. Here we present a spectrum of over 125 useful, complimentary free and open source software tools and libraries, we wrote and made available through the multiple vcflib, bio-vcf, cyvcf2, hts-nim and slivar projects. These tools are applied for comparison, filtering, normalisation, smoothing and annotation of VCF, as well as output of statistics, visualisation, and transformations of files variants. These tools run everyday in critical biomedical pipelines and countless shell scripts. Our tools are part of the wider bioinformatics ecosystem and we highlight best practices. We shortly discuss the design of VCF, lessons learnt, and how we can address more complex variation through pangenome graph formats, variation that can not easily be represented by the VCF format.

Impact of genetic variation in CYP2C19, CYP2D6, and CYP3A4 on oxycodone and its metabolites in a large database of clinical urine drug tests.

Urine drug testing (UDT) is a tool for monitoring drug use, including oxycodone. While variation in cytochrome P450 (CYP) genes is known to alter oxycodone metabolism, its impact on UDT results of oxycodone and its metabolites has not been well-studied. Here, multivariate analysis was performed on retrospective UDT results of 90,379 specimens collected from 14,684 genotyped patients prescribed oxycodone. Genetic variation in CYP2D6 and CYP2C19 had a significant impact on oxymorphone/oxycodone ratios, with a 6.9-fold difference between CYP2D6 ultrarapid metabolizers (UMs) and poor metabolizers (PMs; p < 10-300) and a 1.6-fold difference between CYP2C19 UMs and PMs (p = 1.50 × 10-4). CYP2D6 variation also significantly impacted noroxycodone/oxycodone ratios (p = 6.95 × 10-38). Oxycodone-positive specimens from CYP2D6 PMs were ~5-fold more likely to be oxymorphone-negative compared to normal metabolizers. These findings indicate that multivariate analysis of UDT data may be used to reveal the real-world impact of genetic and non-genetic factors on drug metabolism.

An international virtual hackathon to build tools for the analysis of structural variants within species ranging from coronaviruses to vertebrates.

In October 2020, 62 scientists from nine nations worked together remotely in the Second Baylor College of Medicine & DNAnexus hackathon, focusing on different related topics on Structural Variation, Pan-genomes, and SARS-CoV-2 related research.   The overarching focus was to assess the current status of the field and identify the remaining challenges. Furthermore, how to combine the strengths of the different interests to drive research and method development forward. Over the four days, eight groups each designed and developed new open-source methods to improve the identification and analysis of variations among species, including humans and SARS-CoV-2. These included improvements in SV calling, genotyping, annotations and filtering. Together with advancements in benchmarking existing methods. Furthermore, groups focused on the diversity of SARS-CoV-2. Daily discussion summary and methods are available publicly at  https://github.com/collaborativebioinformatics provides valuable insights for both participants and the research community.

Polysubstance Use Among Patients Treated With Buprenorphine From a National Urine Drug Test Database.

Importance: Polysubstance use is a concern for patients treated for opioid use disorder (OUD). While buprenorphine can curtail harmful opioid use, co-occurring use of nonprescribed substances, such as cocaine, methamphetamine, and other opioids, may negatively affect treatment outcomes. Objective: To characterize factors associated with urine drug positivity for nonprescribed substances among patients prescribed buprenorphine. Design, Setting, and Participants: This cross-sectional study included patients who had been prescribed buprenorphine and who provided urine specimens for urine drug testing (UDT), as ordered by clinicians in primary care or behavioral health or at substance use disorder treatment centers, from 2013 to 2019. Specimens were analyzed by liquid chromatography-tandem mass spectrometry to assess positivity for several commonly used substances. Exposures: Buprenorphine prescription. Main Outcomes and Measures: Positivity for buprenorphine and several nonprescribed substances. Unadjusted trends in positivity for each nonprescribed substance were compared between specimens that did and did not test positive for buprenorphine. Multivariable logistic regression was used to examine factors associated with positivity; factors included patient age, sex, setting of care, payer, collection year, and census division. Results: The study included first UDT specimens from 150 000 patients, of whom 82 107 (54.74%) were men and 77 300 (51.53%) were aged 18 to 34 years. Across all specimens, 128 240 (85.49%) were positive for buprenorphine, and 71 373 (47.58%) were positive for 1 or more nonprescribed substances. From 2013 to 2019, positivity rates increased for most substances (eg, fentanyl: from 131 of 21 412 [0.61%] to 1464 of 13 597 [10.77%]). Factors associated with positivity varied widely by substance; for example, fentanyl positivity was highest for men (OR, 1.13; 95% CI, 1.06-1.21), patients aged 18 to 24 years (OR for patients ≥55 years, 0.46; 95% CI, 0.39-0.54), patients living in New England (OR, 1.19; 95% CI, 1.07-1.33), and patients with Medicaid (OR, 1.20; 95% CI, 1.11-1.31), whereas oxycodone positivity was greatest for women (OR for men, 0.84; 95% CI, 0.79-0.89), patients older than 55 years (OR, 1.42; 95% CI, 1.22-1.64), patients living in the South Atlantic (OR, 1.45, 95% CI, 1.33-1.58), and patients with private insurance (OR for Medicaid, 0.78; 95% CI, 0.73-0.84). Patients whose specimens were positive for buprenorphine were significantly less likely to be positive for other opioids (eg, fentanyl: OR for buprenorphine-negative samples, 6.71; 95% CI, 6.29-7.16; heroin: OR for buprenorphine-negative samples, 9.93; 95% CI, 9.31-10.59). Conclusions and Relevance: In this cross-sectional study, patterns of nonprescribed substance positivity among patients prescribed buprenorphine varied widely. This study highlights the utility of UDT in public health surveillance efforts related to patients treated with buprenorphine for OUD.

Seasonal and Regional Influences on Alcohol Consumption: An Analysis of Near-Real-Time Urine Drug Test Results in Those Seeking Health Care.

AIMS: To examine the probability of detecting alcohol via urine drug testing (UDT) as influenced by age, gender, seasonality, geography, COVID-19, and time in those seeking health care. METHODS: A cross-sectional study of UDT results from January 1, 2013, to December 31, 2020, was conducted using adult patient specimens submitted for testing by health care professionals as part of routine care. The UDT analysis used LC-MS/MS to detect two alcohol metabolites, ethyl glucuronide and ethyl sulfate. Seasonal adjustment of positivity rates was accomplished using the STL method; trend analysis was performed on seasonally adjusted rates. Logistic regression was used to associate demographic features, and an interaction term for collection year and U.S. census division was included to help understand the changing nature of alcohol use over time and across divisions. RESULTS: Alcohol positivity rate shows strong seasonal changes with an oscillating profile that peaks in the summer and is at a low point in winter. The highest predicted positivity rate for alcohol was in male patients, 45-64 years of age, and from a primary care setting. Alcohol positivity peaked in 2016 and declined the following year. While remaining relatively steady since 2017, a small but significant increase was noted after the COVID-19 emergency declaration on March 13, 2020. The probability of being alcohol-positive varies significantly by geographic region, and not all regions are changing at the same rate. CONCLUSIONS: Alcohol positivity in UDT in patients seeking health care is influenced by multiple factors and has increased during the COVID-19 pandemic.

Radiation-related genomic profile of papillary thyroid carcinoma after the Chernobyl accident.

The 1986 Chernobyl nuclear power plant accident increased papillary thyroid carcinoma (PTC) incidence in surrounding regions, particularly for radioactive iodine (131I)-exposed children. We analyzed genomic, transcriptomic, and epigenomic characteristics of 440 PTCs from Ukraine (from 359 individuals with estimated childhood 131I exposure and 81 unexposed children born after 1986). PTCs displayed radiation dose-dependent enrichment of fusion drivers, nearly all in the mitogen-activated protein kinase pathway, and increases in small deletions and simple/balanced structural variants that were clonal and bore hallmarks of nonhomologous end-joining repair. Radiation-related genomic alterations were more pronounced for individuals who were younger at exposure. Transcriptomic and epigenomic features were strongly associated with driver events but not radiation dose. Our results point to DNA double-strand breaks as early carcinogenic events that subsequently enable PTC growth after environmental radiation exposure.

The Cyclical and Evolving Nature of Methamphetamine Use: An Evaluation of Near Real-time Urine Drug Test Results.

OBJECTIVE: To determine methamphetamine positivity and copositivity with other drugs in urine drug test (UDT) results geographically through time. METHODS: This cross-sectional study of UDT results from January 1, 2014, through December 31, 2019, included patient specimens submitted by health care professionals across the United States. The analysis used LC-MS/MS to detect cocaine, heroin, alcohol, marijuana and nonprescribed methamphetamine, fentanyl, methadone, buprenorphine, benzodiazepines, and other opioids. Logistic regression was used to evaluate association of demographic features and model yearly methamphetamine detection patterns across US census divisions. Odds ratios (OR) from logistic modeling were used to evaluate the impact of methamphetamine positivity on the spatio-temporal detection patterns of additional nonprescribed or illicit drugs. RESULTS: The probability of being positive for methamphetamine increased nationally from 0.010 [0.010-0.011] in 2014 to 0.044 [0.042-0.046] in 2019, a 340% increase after correction for demographic covariates. The highest predicted positivity rate was in male patients, 25- to 34-years-old, from the West North Central division and from substance use disorder treatment centers. Nationally, copositivity ORs for fentanyl, heroin, and other opioids with methamphetamine were highest in 2019. Increases in ORs from 2014 through 2019 were statistically significant for heroin (P = 0.024) and fentanyl (P = 0.0085). Copositivity ORs for methamphetamine and other substances varied by census division. CONCLUSIONS: The probability of being positive for methamphetamine in UDT increased nationwide between 2014 and 2019. Not all census divisions are increasing at the same rate. Copositivity with additional substances is increasing in some census divisions, which further increases the risk of overdose and poor treatment outcomes.

Genetic Testing for BCHE Variants Identifies Patients at Risk of Prolonged Neuromuscular Blockade in Response to Succinylcholine.

BACKGROUND: Genetic variants in the BCHE (butyrylcholinesterase) gene are associated with reduced BChE enzyme activity and prolonged post-succinylcholine neuromuscular blockade, which can lead to postanesthetic apnea and respiratory depression. Testing for BChE deficiency is usually performed by biochemical methods and is generally only offered to patients who have a personal or family history of prolonged post-succinylcholine neuromuscular blockade. PURPOSE: Using a clinical test, we investigated the frequencies of BCHE genotypes that are associated with increased risk for prolonged post-succinylcholine neuromuscular blockade. MATERIALS AND METHODS: Five BCHE variants, including the A (atypical, rs1799807), K (Kalow, rs1803274), F1 (fluoride-1, rs28933389), F2 (fluoride-2, rs28933390), and S1 (silent-1, rs398124632), were genotyped in a large (n = 13,301), multi-ethnic cohort in the United States. Subjects were recipients of pharmacogenetic testing ordered by their physicians as part of routine care. RESULTS: The minor allele frequencies of A, K, F1, F2, and S1 were 1.60%, 19.93%, 0.08%, 0.47%, and 0.04%, respectively, in this cohort. Based on a review of biochemical and clinical data of these variants, we grouped BCHE genotypes into four phenotypic categories to stratify the risk for prolonged post-succinylcholine neuromuscular blockade. Approximately 0.06% of patients were predicted to have severe BChE deficiency, 8% were predicted to have moderate BChE deficiency, and 29% were predicted to have mild BChE deficiency. Compared to other ethnic groups, Caucasians were predicted to have the highest frequency of BChE deficiency. CONCLUSION: While severe BChE deficiency is rare in the United States, approximately 8% of Americans are at moderate risk of prolonged post-succinylcholine neuromuscular blockade, suggesting that a sizable percentage of patients may benefit from preoperative genetic testing of BCHE.

Fentanyl analog positivity among near-real-time urine drug test results in patients seeking health care.

Overdose deaths involving synthetic opioids continue to climb. Fentanyl analogs have been identified as important contributors to these overdoses, but little is known about their prevalence in patients seeking health care. This cross-sectional study of urine drug test (UDT) results from July 15, 2019, through March 12, 2020, included patient specimens analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS), submitted by health care professionals as part of routine care to detect fentanyl and fentanyl analogs. A convenience sample approach was used to select patient specimens from diverse health care practices across all 50 states, then stratified by fentanyl prescription status. Positivity rates, geographic distribution, and co-occurrence were quantified. The total positivity rate for ten fentanyl analogs was 40.55% in the non-prescribed fentanyl-positive population. The most common fentanyl analogs in this population were 4-ANPP (4-anilino-N-phenethylpiperidine), 30.74%; acetyl fentanyl, 19.40%; and carfentanil, 3.13%. The total positivity rate for four fentanyl analogs was 8.93% in the prescribed fentanyl-positive population, including 4-ANPP, 8.85%; acetyl fentanyl, 0.19%; acryl fentanyl, 0.05%; and 4-FiBF, 0.03%. Counties in Ohio and Kentucky had the highest positivity rates. Acetyl fentanyl and 4-ANPP copositivity occurred in 11.36% of non-prescribed patient specimens. However, acetyl fentanyl and 4-ANPP positivity may not be consistent with fentanyl analog use since both are process impurities, and 4-ANPP is a metabolite of fentanyl. Near-real-time, definitive UDT results reveal fentanyl analogs in patients seeking health care, helping clinicians and public health officials better understand their contribution to overdoses and help mitigate the risks they pose.

A crowdsourced set of curated structural variants for the human genome.

A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is more challenging. In this study, we manually curated 1235 SVs, which can ultimately be used to evaluate SV callers or train machine learning models. We developed a crowdsourcing app-SVCurator-to help GIAB curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy. SVCurator displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002]. We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. 'Expert' curators were 93% concordant with each other, and 37 of the 61 curators had at least 78% concordance with a set of 'expert' curators. The curators were least concordant for complex SVs and SVs that had inaccurate breakpoints or size predictions. After filtering events with low concordance among curators, we produced high confidence labels for 935 events. The SVCurator crowdsourced labels were 94.5% concordant with the heuristic-based draft benchmark SV callset from GIAB. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies.

Genotyping structural variants in pangenome graphs using the vg toolkit.

Structural variants (SVs) remain challenging to represent and study relative to point mutations despite their demonstrated importance. We show that variation graphs, as implemented in the vg toolkit, provide an effective means for leveraging SV catalogs for short-read SV genotyping experiments. We benchmark vg against state-of-the-art SV genotypers using three sequence-resolved SV catalogs generated by recent long-read sequencing studies. In addition, we use assemblies from 12 yeast strains to show that graphs constructed directly from aligned de novo assemblies improve genotyping compared to graphs built from intermediate SV catalogs in the VCF format.

GFAKluge: A C++ library and command line utilities for the Graphical Fragment Assembly formats.

SUMMARY: GFA has emerged as a standard format for the exchange of genome assemblies and sequence graphs. To encourage further adoption in high-performance software we have developed an open-source C++ library for GFA and a set of utilities for summarizing and manipulating the format. AVAILABILITY: The gfakluge source code is freely available under the MIT license at https://github.com/edawson/gfakluge. It has been tested on both Mac OS X and Linux.

Viral coinfection analysis using a MinHash toolkit.

BACKGROUND: Human papillomavirus (HPV) is a common sexually transmitted infection associated with cervical cancer that frequently occurs as a coinfection of types and subtypes. Highly similar sublineages that show over 100-fold differences in cancer risk are not distinguishable in coinfections with current typing methods. RESULTS: We describe an efficient set of computational tools, rkmh, for analyzing complex mixed infections of related viruses based on sequence data. rkmh makes extensive use of MinHash similarity measures, and includes utilities for removing host DNA and classifying reads by type, lineage, and sublineage. We show that rkmh is capable of assigning reads to their HPV type as well as HPV16 lineage and sublineages. CONCLUSIONS: Accurate read classification enables estimates of percent composition when there are multiple infecting lineages or sublineages. While we demonstrate rkmh for HPV with multiple sequencing technologies, it is also applicable to other mixtures of related sequences.