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.

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.

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.

Optimized Translocator Protein Ligand for Optical Molecular Imaging and Screening.

Translocator protein (TSPO) is a validated target for molecular imaging of a variety of human diseases and disorders. Given its involvement in cholesterol metabolism, TSPO expression is commonly elevated in solid tumors, including glioma, colorectal cancer, and breast cancer. TSPO ligands capable of detection by optical imaging are useful molecular tracers for a variety of purposes that range from quantitative biology to drug discovery. Leveraging our prior optimization of the pyrazolopyrimidine TSPO ligand scaffold for cancer imaging, we report herein a new generation of TSPO tracers with superior binding affinity and suitability for optical imaging and screening. In total, seven candidate TSPO tracers were synthesized and vetted in this study; the most promising tracer identified (29, Kd = 0.19 nM) was the result of conjugating a high-affinity TSPO ligand to a fluorophore used routinely in biological sciences (FITC) via a functional carbon linker of optimal length. Computational modeling suggested that an n-alkyl linker of eight carbons in length allows for positioning of the bulky fluorophore distal to the ligand binding domain and toward the solvent interface, minimizing potential ligand-protein interference. Probe 29 was found to be highly suitable for in vitro imaging of live TSPO-expressing cells and could be deployed as a ligand screening and discovery tool. Competitive inhibition of probe 29 quantified by fluorescence and 3H-PK11195 quantified by traditional radiometric detection resulted in equivalent affinity data for two previously reported TSPO ligands. This study introduces the utility of TSPO ligand 29 for in vitro imaging and screening and provides a structural basis for the development of future TSPO imaging ligands bearing bulky signaling moieties.

Limited utility of residue masking for positive-selection inference.

Errors in multiple sequence alignments (MSAs) can reduce accuracy in positive-selection inference. Therefore, it has been suggested to filter MSAs before conducting further analyses. One widely used filter, Guidance, allows users to remove MSA positions aligned with low confidence. However, Guidance's utility in positive-selection inference has been disputed in the literature. We have conducted an extensive simulation-based study to characterize fully how Guidance impacts positive-selection inference, specifically for protein-coding sequences of realistic divergence levels. We also investigated whether novel scoring algorithms, which phylogenetically corrected confidence scores, and a new gap-penalization score-normalization scheme improved Guidance's performance. We found that no filter, including original Guidance, consistently benefitted positive-selection inferences. Moreover, all improvements detected were exceedingly minimal, and in certain circumstances, Guidance-based filters worsened inferences.

2-Substituted Nγ-glutamylanilides as novel probes of ASCT2 with improved potency.

Herein, we report the discovery and structure-activity relationships (SAR) of 2-substituted glutamylanilides as novel probes of the steric environment comprising the amino acid binding domain of alanine-serine-cysteine transporter subtype 2 (ASCT2). Focused library development led to three novel, highly potent ASCT2 inhibitors, with N-(2-(morpholinomethyl)phenyl)-L-glutamine exhibiting the greatest potency in a live-cell glutamine uptake assay. This level of potency represents a three-fold improvement over the most potent, previously reported inhibitor in this series, GPNA. Furthermore, this and other compounds in the series exhibit tractable chemical properties for further development as potential therapeutic leads.

Predicting evolutionary site variability from structure in viral proteins: buriedness, packing, flexibility, and design.

Several recent works have shown that protein structure can predict site-specific evolutionary sequence variation. In particular, sites that are buried and/or have many contacts with other sites in a structure have been shown to evolve more slowly, on average, than surface sites with few contacts. Here, we present a comprehensive study of the extent to which numerous structural properties can predict sequence variation. The quantities we considered include buriedness (as measured by relative solvent accessibility), packing density (as measured by contact number), structural flexibility (as measured by B factors, root-mean-square fluctuations, and variation in dihedral angles), and variability in designed structures. We obtained structural flexibility measures both from molecular dynamics simulations performed on nine non-homologous viral protein structures and from variation in homologous variants of those proteins, where they were available. We obtained measures of variability in designed structures from flexible-backbone design in the Rosetta software. We found that most of the structural properties correlate with site variation in the majority of structures, though the correlations are generally weak (correlation coefficients of 0.1-0.4). Moreover, we found that buriedness and packing density were better predictors of evolutionary variation than structural flexibility. Finally, variability in designed structures was a weaker predictor of evolutionary variability than buriedness or packing density, but it was comparable in its predictive power to the best structural flexibility measures. We conclude that simple measures of buriedness and packing density are better predictors of evolutionary variation than the more complicated predictors obtained from dynamic simulations, ensembles of homologous structures, or computational protein design.

Genomic characterization of cervical lymph node metastases in papillary thyroid carcinoma following the Chornobyl accident.

Childhood radioactive iodine exposure from the Chornobyl accident increased papillary thyroid carcinoma (PTC) risk. While cervical lymph node metastases (cLNM) are well-recognized in pediatric PTC, the PTC metastatic process and potential radiation association are poorly understood. Here, we analyze cLNM occurrence among 428 PTC with genomic landscape analyses and known drivers (131I-exposed = 349, unexposed = 79; mean age = 27.9 years). We show that cLNM are more frequent in PTC with fusion (55%) versus mutation (30%) drivers, although the proportion varies by specific driver gene (RET-fusion = 71%, BRAF-mutation = 38%, RAS-mutation = 5%). cLNM frequency is not associated with other characteristics, including radiation dose. cLNM molecular profiling (N = 47) demonstrates 100% driver concordance with matched primary PTCs and highly concordant mutational spectra. Transcriptome analysis reveals 17 differentially expressed genes, particularly in the HOXC cluster and BRINP3; the strongest differentially expressed microRNA also is near HOXC10. Our findings underscore the critical role of driver alterations and provide promising candidates for elucidating the biological underpinnings of PTC cLNM.

Ancestry and somatic profile predict acral melanoma origin and prognosis.

Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, here we characterise the genome and transcriptome of 128 acral melanoma tumours from 96 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF , NRAS or NF1 . While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower number of structural variants. These BRAF -mutated tumours have a transcriptional profile similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and transcriptional profiling defined three expression clusters; these characteristics were associated with overall survival. We highlight novel low-frequency drivers, such as SPHKAP , which correlate with a distinct genomic profile and clinical characteristics. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

Discovery of N-(benzo[1,2,3]triazol-1-yl)-N-(benzyl)acetamido)phenyl) carboxamides as severe acute respiratory syndrome coronavirus (SARS-CoV) 3CLpro inhibitors: identification of ML300 and noncovalent nanomolar inhibitors with an induced-fit binding.

Herein we report the discovery and SAR of a novel series of SARS-CoV 3CLpro inhibitors identified through the NIH Molecular Libraries Probe Production Centers Network (MLPCN). In addition to ML188, ML300 represents the second probe declared for 3CLpro from this collaborative effort. The X-ray structure of SARS-CoV 3CLpro bound with a ML300 analog highlights a unique induced-fit reorganization of the S2-S4 binding pockets leading to the first sub-micromolar noncovalent 3CLpro inhibitors retaining a single amide bond.

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.

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.

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.

A conserved asparagine residue in transmembrane segment 1 (TM1) of serotonin transporter dictates chloride-coupled neurotransmitter transport.

Na(+)- and Cl(-)-dependent uptake of neurotransmitters via transporters of the SLC6 family, including the human serotonin transporter (SLC6A4), is critical for efficient synaptic transmission. Although residues in the human serotonin transporter involved in direct Cl(-) coordination of human serotonin transport have been identified, the role of Cl(-) in the transport mechanism remains unclear. Through a combination of mutagenesis, chemical modification, substrate and charge flux measurements, and molecular modeling studies, we reveal an unexpected role for the highly conserved transmembrane segment 1 residue Asn-101 in coupling Cl(-) binding to concentrative neurotransmitter uptake.

Discovery of a new molecular probe ML228: an activator of the hypoxia inducible factor (HIF) pathway.

Hypoxia and ischemia are linked to several serious public health problems that affect most major organ systems. Specific examples include diseases of the cardiovascular, pulmonary, renal, neurologic, and musculoskeletal systems. The most significant pathway for cellular response to hypoxia is the hypoxia inducible factor (HIF) pathway. HIFs are transcription factors responsible for the activation of genes which encode proteins that mediate adaptive responses to reduced oxygen availability. A high-throughput cell-based HIF-mediated gene reporter screen was carried out using the NIH's Molecular Libraries Small Molecule Repository to identify activators of the HIF pathway. This communication describes the subsequent medicinal chemistry optimization of a triazine scaffold that led to the identification of the new molecular probe ML228. A discussion of HIF activation SAR within this chemotype as well as detailed in vitro characterization of the probe molecule is presented here.

Discovery and SAR of a novel series of non-MPEP site mGlu5 PAMs based on an aryl glycine sulfonamide scaffold.

Herein we report the discovery and SAR of a novel series of non-MPEP site metabotropic glutamate receptor 5 (mGlu(5)) positive allosteric modulators (PAMs) based on an aryl glycine sulfonamide scaffold. This series represents a rare non-MPEP site mGlu(5) PAM chemotype.

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.

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.