UBR5 forms ligand-dependent complexes on chromatin to regulate nuclear hormone receptor stability.

Nuclear hormone receptors (NRs) are ligand-binding transcription factors that are widely targeted therapeutically. Agonist binding triggers NR activation and subsequent degradation by unknown ligand-dependent ubiquitin ligase machinery. NR degradation is critical for therapeutic efficacy in malignancies that are driven by retinoic acid and estrogen receptors. Here, we demonstrate the ubiquitin ligase UBR5 drives degradation of multiple agonist-bound NRs, including the retinoic acid receptor alpha (RARA), retinoid x receptor alpha (RXRA), glucocorticoid, estrogen, liver-X, progesterone, and vitamin D receptors. We present the high-resolution cryo-EMstructure of full-length human UBR5 and a negative stain model representing its interaction with RARA/RXRA. Agonist ligands induce sequential, mutually exclusive recruitment of nuclear coactivators (NCOAs) and UBR5 to chromatin to regulate transcriptional networks. Other pharmacological ligands such as selective estrogen receptor degraders (SERDs) degrade their receptors through differential recruitment of UBR5 or RNF111. We establish the UBR5 transcriptional regulatory hub as a common mediator and regulator of NR-induced transcription.

The complete sequence and comparative analysis of ape sex chromosomes.

Apes possess two sex chromosomes-the male-specific Y chromosome and the X chromosome, which is present in both males and females. The Y chromosome is crucial for male reproduction, with deletions being linked to infertility1. The X chromosome is vital for reproduction and cognition2. Variation in mating patterns and brain function among apes suggests corresponding differences in their sex chromosomes. However, owing to their repetitive nature and incomplete reference assemblies, ape sex chromosomes have been challenging to study. Here, using the methodology developed for the telomere-to-telomere (T2T) human genome, we produced gapless assemblies of the X and Y chromosomes for five great apes (bonobo (Pan paniscus), chimpanzee (Pan troglodytes), western lowland gorilla (Gorilla gorilla gorilla), Bornean orangutan (Pongo pygmaeus) and Sumatran orangutan (Pongo abelii)) and a lesser ape (the siamang gibbon (Symphalangus syndactylus)), and untangled the intricacies of their evolution. Compared with the X chromosomes, the ape Y chromosomes vary greatly in size and have low alignability and high levels of structural rearrangements-owing to the accumulation of lineage-specific ampliconic regions, palindromes, transposable elements and satellites. Many Y chromosome genes expand in multi-copy families and some evolve under purifying selection. Thus, the Y chromosome exhibits dynamic evolution, whereas the X chromosome is more stable. Mapping short-read sequencing data to these assemblies revealed diversity and selection patterns on sex chromosomes of more than 100 individual great apes. These reference assemblies are expected to inform human evolution and conservation genetics of non-human apes, all of which are endangered species.

Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis.

The function of some genetic variants associated with brain-relevant traits has been explained through colocalization with expression quantitative trait loci (eQTL) conducted in bulk postmortem adult brain tissue. However, many brain-trait associated loci have unknown cellular or molecular function. These genetic variants may exert context-specific function on different molecular phenotypes including post-transcriptional changes. Here, we identified genetic regulation of RNA editing and alternative polyadenylation (APA) within a cell-type-specific population of human neural progenitors and neurons. More RNA editing and isoforms utilizing longer polyadenylation sequences were observed in neurons, likely due to higher expression of genes encoding the proteins mediating these post-transcriptional events. We also detected hundreds of cell-type-specific editing quantitative trait loci (edQTLs) and alternative polyadenylation QTLs (apaQTLs). We found colocalizations of a neuron edQTL in CCDC88A with educational attainment and a progenitor apaQTL in EP300 with schizophrenia, suggesting that genetically mediated post-transcriptional regulation during brain development leads to differences in brain function.

An endothelial regulatory module links blood pressure regulation with elite athletic performance.

The control of transcription is crucial for homeostasis in mammals. A previous selective sweep analysis of horse racing performance revealed a 19.6 kb candidate regulatory region 50 kb downstream of the Endothelin3 (EDN3) gene. Here, the region was narrowed to a 5.5 kb span of 14 SNVs, with elite and sub-elite haplotypes analyzed for association to racing performance, blood pressure and plasma levels of EDN3 in Coldblooded trotters and Standardbreds. Comparative analysis of human HiCap data identified the span as an enhancer cluster active in endothelial cells, interacting with genes relevant to blood pressure regulation. Coldblooded trotters with the sub-elite haplotype had significantly higher blood pressure compared to horses with the elite performing haplotype during exercise. Alleles within the elite haplotype were part of the standing variation in pre-domestication horses, and have risen in frequency during the era of breed development and selection. These results advance our understanding of the molecular genetics of athletic performance and vascular traits in both horses and humans.

The intrinsically disordered CARDs-Helicase linker in RIG-I is a molecular gate for RNA proofreading.

The innate immune receptor RIG-I provides a first line of defense against viral infections. Viral RNAs are recognized by RIG-I's C-terminal domain (CTD), but the RNA must engage the helicase domain to release the signaling CARD (Caspase Activation and Recruitment Domain) domains from their autoinhibitory CARD2:Hel2i interactions. Because the helicase itself lacks RNA specificity, mechanisms to proofread RNAs entering the helicase domain must exist. Although such mechanisms would be crucial in preventing aberrant immune responses by non-specific RNAs, they remain largely uncharacterized to date. This study reveals a previously unknown proofreading mechanism through which RIG-I ensures that the helicase engages RNAs explicitly recognized by the CTD. A crucial part of this mechanism involves the intrinsically disordered CARDs-Helicase Linker (CHL), which connects the CARDs to the helicase subdomain Hel1. CHL uses its negatively charged regions to antagonize incoming RNAs electrostatically. In addition to this RNA gating function, CHL is essential for stabilization of the CARD2:Hel2i interface. Overall, we uncover that the CHL and CARD2:Hel2i interface work together to establish a tunable gating mechanism that allows CTD-chosen RNAs to bind the helicase domain, while at the same time blocking non-specific RNAs. These findings also indicate that CHL could represent a novel target for RIG-I-based therapeutics.

IL-18-secreting multiantigen targeting CAR T cells eliminate antigen-low myeloma in an immunocompetent mouse model.

ABSTRACT: Multiple myeloma is a plasma cell malignancy that is currently incurable with conventional therapies. Following the success of CD19-targeted chimeric antigen receptor (CAR) T cells in leukemia and lymphoma, CAR T cells targeting B-cell maturation antigen (BCMA) more recently demonstrated impressive activity in relapsed and refractory myeloma patients. However, BCMA-directed therapy can fail due to weak expression of BCMA on myeloma cells, suggesting that novel approaches to better address this antigen-low disease may improve patient outcomes. We hypothesized that engineered secretion of the proinflammatory cytokine interleukin-18 (IL-18) and multiantigen targeting could improve CAR T-cell activity against BCMA-low myeloma. In a syngeneic murine model of myeloma, CAR T cells targeting the myeloma-associated antigens BCMA and B-cell activating factor receptor (BAFF-R) failed to eliminate myeloma when these antigens were weakly expressed, whereas IL-18-secreting CAR T cells targeting these antigens promoted myeloma clearance. IL-18-secreting CAR T cells developed an effector-like T-cell phenotype, promoted interferon-gamma production, reprogrammed the myeloma bone marrow microenvironment through type-I/II interferon signaling, and activated macrophages to mediate antimyeloma activity. Simultaneous targeting of weakly-expressed BCMA and BAFF-R with dual-CAR T cells enhanced T-cell:target-cell avidity, increased overall CAR signal strength, and stimulated antimyeloma activity. Dual-antigen targeting augmented CAR T-cell secretion of engineered IL-18 and facilitated elimination of larger myeloma burdens in vivo. Our results demonstrate that combination of engineered IL-18 secretion and multiantigen targeting can eliminate myeloma with weak antigen expression through distinct mechanisms.

Sex Differences in Dopamine Release in Nucleus Accumbens and Dorsal Striatum Determined by Chronic Fast-Scan Cyclic Voltammetry: Effects of Social Housing and Repeated Stimulation.

We investigated sex differences in dopamine (DA) release in the nucleus accumbens (NAc) and dorsolateral striatum (DLS) using a chronic 16-channel carbon fiber electrode and fast-scan cyclic voltammetry (FSCV). Electrical stimulation-induced (ES; 60 Hz) DA release was recorded in the NAc of single- or pair-housed male and female rats. When core (NAcC) and shell (NAcS) were recorded simultaneously, there was greater ES DA release in NAcC of pair-housed females compared with single females and males. Housing did not affect ES NAc DA release in males. In contrast, there was significantly more ES DA release from the DLS of female rats than male rats. This was true prior to and after treatment with methamphetamine. Furthermore, in castrated (CAST) males and ovariectomized (OVX) females, there were no sex differences in ES DA release from the DLS, demonstrating the hormone dependence of this sex difference. However, in the DLS of both intact and gonadectomized rats, DA reuptake was slower in females than that in males. Finally, DA release following ES of the medial forebrain bundle at 60 Hz was studied over 4 weeks. ES DA release increased over time for both CAST males and OVX females, demonstrating sensitization. Using this novel 16-channel chronic FSCV electrode, we found sex differences in the effects of social housing in the NAcS, sex differences in DA release from intact rats in DLS, and sex differences in DA reuptake in DLS of intake and gonadectomized rats, and we report sensitization of ES-induced DA release in DLS in vivo.

Qmatey: an automated pipeline for fast exact matching-based alignment and strain-level taxonomic binning and profiling of metagenomes.

Metagenomics is a powerful tool for understanding organismal interactions; however, classification, profiling and detection of interactions at the strain level remain challenging. We present an automated pipeline, quantitative metagenomic alignment and taxonomic exact matching (Qmatey), that performs a fast exact matching-based alignment and integration of taxonomic binning and profiling. It interrogates large databases without using metagenome-assembled genomes, curated pan-genes or k-mer spectra that limit resolution. Qmatey minimizes misclassification and maintains strain level resolution by using only diagnostic reads as shown in the analysis of amplicon, quantitative reduced representation and shotgun sequencing datasets. Using Qmatey to analyze shotgun data from a synthetic community with 35% of the 26 strains at low abundance (0.01-0.06%), we revealed a remarkable 85-96% strain recall and 92-100% species recall while maintaining 100% precision. Benchmarking revealed that the highly ranked Kraken2 and KrakenUniq tools identified 2-4 more taxa (92-100% recall) than Qmatey but produced 315-1752 false positive taxa and high penalty on precision (1-8%). The speed, accuracy and precision of the Qmatey pipeline positions it as a valuable tool for broad-spectrum profiling and for uncovering biologically relevant interactions.

Leveraging insect-specific viruses to elucidate mosquito population structure and dynamics.

Several aspects of mosquito ecology that are important for vectored disease transmission and control have been difficult to measure at epidemiologically important scales in the field. In particular, the ability to describe mosquito population structure and movement rates has been hindered by difficulty in quantifying fine-scale genetic variation among populations. The mosquito virome represents a possible avenue for quantifying population structure and movement rates across multiple spatial scales. Mosquito viromes contain a diversity of viruses, including several insect-specific viruses (ISVs) and "core" viruses that have high prevalence across populations. To date, virome studies have focused on viral discovery and have only recently begun examining viral ecology. While nonpathogenic ISVs may be of little public health relevance themselves, they provide a possible route for quantifying mosquito population structure and dynamics. For example, vertically transmitted viruses could behave as a rapidly evolving extension of the host's genome. It should be possible to apply established analytical methods to appropriate viral phylogenies and incidence data to generate novel approaches for estimating mosquito population structure and dispersal over epidemiologically relevant timescales. By studying the virome through the lens of spatial and genomic epidemiology, it may be possible to investigate otherwise cryptic aspects of mosquito ecology. A better understanding of mosquito population structure and dynamics are key for understanding mosquito-borne disease ecology and methods based on ISVs could provide a powerful tool for informing mosquito control programs.

RIG-I recognizes metabolite-capped RNAs as signaling ligands.

The innate immune receptor RIG-I recognizes 5'-triphosphate double-stranded RNAs (5' PPP dsRNA) as pathogenic RNAs. Such RNA-ends are present in viral genomes and replication intermediates, and they activate the RIG-I signaling pathway to produce a potent interferon response essential for viral clearance. Endogenous mRNAs cap the 5' PPP-end with m7G and methylate the 2'-O-ribose to evade RIG-I, preventing aberrant immune responses deleterious to the cell. Recent studies have identified RNAs in cells capped with metabolites such as NAD+, FAD and dephosphoCoA. Whether RIG-I recognizes these metabolite-capped RNAs has not been investigated. Here, we describe a strategy to make metabolite-capped RNAs free from 5' PPP dsRNA contamination, using in vitro transcription initiated with metabolites. Mechanistic studies show that metabolite-capped RNAs have a high affinity for RIG-I, stimulating the ATPase activity at comparable levels to 5' PPP dsRNA. Cellular signaling assays show that the metabolite-capped RNAs potently stimulate the innate antiviral immune response. This demonstrates that RIG-I can tolerate diphosphate-linked, capped RNAs with bulky groups at the 5' RNA end. This novel class of RNAs that stimulate RIG-I signaling may have cellular roles in activating the interferon response and may be exploited with proper functionalities for RIG-I-related RNA therapeutics.

Identification and functional validation of super-enhancers in Arabidopsis thaliana.

Super-enhancers (SEs) are exceptionally large enhancers and are recognized to play prominent roles in cell identity in mammalian species. We surveyed the genomic regions containing large clusters of accessible chromatin regions (ACRs) marked by deoxyribonuclease (DNase) I hypersensitivity in Arabidopsis thaliana. We identified a set of 749 putative SEs, which have a minimum length of 1.5 kilobases and represent the top 2.5% of the largest ACR clusters. We demonstrate that the genomic regions associating with these SEs were more sensitive to DNase I than other nonpromoter ACRs. The SEs were preferentially associated with topologically associating domains. Furthermore, the SEs and their predicted cognate genes were frequently associated with organ development and tissue identity in A. thaliana. Therefore, the A. thaliana SEs and their cognate genes mirror the functional characteristics of those reported in mammalian species. We developed CRISPR/Cas-mediated deletion lines of a 3,578-bp SE associated with the thalianol biosynthetic gene cluster (BGC). Small deletions (131-157 bp) within the SE resulted in distinct phenotypic changes and transcriptional repression of all five thalianol genes. In addition, T-DNA insertions in the SE region resulted in transcriptional alteration of all five thalianol genes. Thus, this SE appears to play a central role in coordinating the operon-like expression pattern of the thalianol BGC.

Evolution of Spatial Risk of Malaria Infection After a Pragmatic Chemoprevention Program in Response to Severe Flooding in Rural Western Uganda.

BACKGROUND: Malaria epidemics result from extreme precipitation and flooding, which are increasing with global climate change. Local adaptation and mitigation strategies will be essential to prevent excess morbidity and mortality. METHODS: We investigated the spatial risk of malaria infection at multiple timepoints after severe flooding in rural western Uganda employing longitudinal household surveys measuring parasite prevalence and leveraging remotely sensed information to inform spatial models of malaria risk in the 3 months after flooding. RESULTS: We identified clusters of malaria risk emerging in areas (1) that showed the greatest changes in Normalized Difference Vegetation Index from pre- to postflood and (2) where residents were displaced for longer periods of time and had lower access to long-lasting insecticidal nets, both of which were associated with a positive malaria rapid diagnostic test result. The disproportionate risk persisted despite a concurrent chemoprevention program that achieved high coverage. CONCLUSIONS: The findings enhance our understanding not only of the spatial evolution of malaria risk after flooding, but also in the context of an effective intervention. The results provide a "proof of concept" for programs aiming to prevent malaria outbreaks after flooding using a combination of interventions. Further study of mitigation strategies-and particularly studies of implementation-is urgently needed.

Re-Evaluating the Conventional Wisdom about Binding Assays.

Analytical technologies based on binding assays have evolved substantially since their inception nearly 60 years ago, but our conceptual understanding of molecular recognition has not kept pace. Contemporary technologies, such as single-molecule and digital measurements, have challenged, or even rendered obsolete, core concepts behind conventional binding assay design. Here, we explore the fundamental principles underlying molecular recognition systems, which we consider in terms of signals generated through concentration-dependent shifts in equilibrium. We challenge certain orthodoxies related to binding-based detection assays, including the primary importance of a low dissociation constant (KD) and the extent to which this parameter constrains dynamic range and limit of detection. Lastly, we identify key principles for designing binding assays that are optimally suited for a given detection application.

Reverse Phase Proteomic Array Profiling of Asparagine Synthetase Expression in Newly Diagnosed Acute Myeloid Leukemia.

Asparaginase-based therapy is a cornerstone in acute lymphoblastic leukemia (ALL) treatment, capitalizing on the methylation status of the asparagine synthetase (ASNS) gene, which renders ALL cells reliant on extracellular asparagine. Contrastingly, ASNS expression in acute myeloid leukemia (AML) has not been thoroughly investigated, despite studies suggesting that AML with chromosome 7/7q deletions might have reduced ASNS levels. Here, we leverage reverse phase protein arrays to measure ASNS expression in 810 AML patients and assess its impact on outcomes. We find that AML with inv(16) has the lowest overall ASNS expression. While AML with deletion 7/7q had ASNS levels slightly lower than those of AML without deletion 7/7q, this observation was not significant. Low ASNS expression correlated with improved overall survival (46 versus 54 weeks, respectively, p = 0.011), whereas higher ASNS levels were associated with better response to venetoclax-based therapy. Protein correlation analysis demonstrated association between ASNS and proteins involved in methylation and DNA repair. In conclusion, while ASNS expression was not lower in patients with deletion 7/7q as initially predicted, ASNS levels were highly variable across AML patients. Further studies are needed to assess whether patients with low ASNS expression are susceptible to asparaginase-based therapy due to their inability to augment compensatory ASNS expression upon asparagine depletion.

Mapping the Ecological Terrain of Stroke Prehospital Delay: A Nationwide Registry Study.

BACKGROUND: Delays in hospital presentation limit access to acute stroke treatments. While prior research has focused on patient-level factors, broader ecological and social determinants have not been well studied. We aimed to create a geospatial map of prehospital delay and examine the role of community-level social vulnerability. METHODS: We studied patients with ischemic stroke who arrived by emergency medical services in 2015 to 2017 from the American Heart Association Get With The Guidelines-Stroke registry. The primary outcome was time to hospital arrival after stroke (in minutes), beginning at last known well in most cases. Using Geographic Information System mapping, we displayed the geography of delay. We then used Cox proportional hazard models to study the relationship between community-level factors and arrival time (adjusted hazard ratios [aHR] <1.0 indicate delay). The primary exposure was the social vulnerability index (SVI), a metric of social vulnerability for every ZIP Code Tabulation Area ranging from 0.0 to 1.0. RESULTS: Of 750 336 patients, 149 145 met inclusion criteria. The mean age was 73 years, and 51% were female. The median time to hospital arrival was 140 minutes (Q1: 60 minutes, Q3: 458 minutes). The geospatial map revealed that many zones of delay overlapped with socially vulnerable areas (https://harvard-cga.maps.arcgis.com/apps/webappviewer/index.html?id=08f6e885c71b457f83cefc71013bcaa7). Cox models (aHR, 95% CI) confirmed that higher SVI, including quartiles 3 (aHR, 0.96 [95% CI, 0.93-0.98]) and 4 (aHR, 0.93 [95% CI, 0.91-0.95]), was associated with delay. Patients from SVI quartile 4 neighborhoods arrived 15.6 minutes [15-16.2] slower than patients from SVI quartile 1. Specific SVI themes associated with delay were a community's socioeconomic status (aHR, 0.80 [95% CI, 0.74-0.85]) and housing type and transportation (aHR, 0.89 [95% CI, 0.84-0.94]). CONCLUSIONS: This map of acute stroke presentation times shows areas with a high incidence of delay. Increased social vulnerability characterizes these areas. Such places should be systematically targeted to improve population-level stroke presentation times.

Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models.

This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing data sets. In an earlier work by other researchers, an annotation workflow and quality checklist for computational pathology annotations were proposed. In this manuscript, we operationalize this workflow into an evaluable quality checklist that applies to any reader-interpreted medical images, and we demonstrate its use for an annotation effort in digital pathology. We refer to this quality framework as the Collection and Evaluation of Annotations for Reproducible Reporting of Artificial Intelligence (CLEARR-AI).

PROVIDENT: Development and Validation of a Machine Learning Model to Predict Neighborhood-level Overdose Risk in Rhode Island.

BACKGROUND: Drug overdose persists as a leading cause of death in the United States, but resources to address it remain limited. As a result, health authorities must consider where to allocate scarce resources within their jurisdictions. Machine learning offers a strategy to identify areas with increased future overdose risk to proactively allocate overdose prevention resources. This modeling study is embedded in a randomized trial to measure the effect of proactive resource allocation on statewide overdose rates in Rhode Island (RI). METHODS: We used statewide data from RI from 2016 to 2020 to develop an ensemble machine learning model predicting neighborhood-level fatal overdose risk. Our ensemble model integrated gradient boosting machine and super learner base models in a moving window framework to make predictions in 6-month intervals. Our performance target, developed a priori with the RI Department of Health, was to identify the 20% of RI neighborhoods containing at least 40% of statewide overdose deaths, including at least one neighborhood per municipality. The model was validated after trial launch. RESULTS: Our model selected priority neighborhoods capturing 40.2% of statewide overdose deaths during the test periods and 44.1% of statewide overdose deaths during validation periods. Our ensemble outperformed the base models during the test periods and performed comparably to the best-performing base model during the validation periods. CONCLUSIONS: We demonstrated the capacity for machine learning models to predict neighborhood-level fatal overdose risk to a degree of accuracy suitable for practitioners. Jurisdictions may consider predictive modeling as a tool to guide allocation of scarce resources.

A generalized expression for accelerating beamlet decomposition simulations.

Paraxial diffraction modeling based on the Fourier transform has seen widespread implementation for simulating the response of a diffraction-limited optical system. For systems where the paraxial assumption is not sufficient, a class of algorithms has been developed that employs hybrid propagation physics to compute the propagation of an elementary beamlet along geometric ray paths. These "beamlet decomposition" algorithms include the well-known Gaussian beamlet decomposition (GBD) algorithm, of which several variants have been created. To increase the computational efficiency of the GBD algorithm, we derive an alternative expression of the technique that utilizes the analytical propagation of beamlets to tilted planes. We then use this accelerated algorithm to conduct a parameter-space search to find the optimal combination of free parameters in GBD to construct the analytical Airy function. The experiment is conducted on a consumer-grade CPU, and a high-performance GPU, where the new algorithm is 34 times faster than the previously published algorithm on CPUs, and 67,513 times faster on GPUs.

Training pathologists to assess stromal tumour-infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research.

A growing body of research supports stromal tumour-infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin-stained slides. Artificial intelligence/machine-learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment. Visual TIL assessment may suffer from significant interobserver variability. To improve interobserver agreement, regulatory science experts at the US Food and Drug Administration partnered with academic pathologists internationally to create a freely available online continuing medical education (CME) course to train pathologists in assessing breast cancer stromal TILs using an interactive format with expert commentary. Here we describe and provide a user guide to this CME course, whose content was designed to improve pathologist accuracy in scoring breast cancer TILs. We also suggest subsequent steps to translate knowledge into clinical practice with proficiency testing.

Association of Opioid Use Disorder Diagnosis with Management of Acute Low Back Pain: A Medicare Retrospective Cohort Analysis.

BACKGROUND: Practice guidelines recommend nonpharmacologic and nonopioid therapies as first-line pain treatment for acute pain. However, little is known about their utilization generally and among individuals with opioid use disorder (OUD) for whom opioid and other pharmacologic therapies carry greater risk of harm. OBJECTIVE: To determine the association between a pre-existing OUD diagnosis and treatment of acute low back pain (aLBP). DESIGN: Retrospective cohort study using 2016-2019 Medicare data. PARTICIPANTS: Fee-for-service Medicare beneficiaries with a new episode of aLBP. MAIN MEASURES: The main independent variable was OUD diagnosis measured prior to the first LBP claim (i.e., index date). Using multivariable logistic regressions, we assessed the following outcomes measured within 30 days of the index date: (1) nonpharmacologic therapies (physical therapy and/or chiropractic care), and (2) prescription opioids. Among opioid recipients, we further assessed opioid dose and co-prescription of gabapentin. Analyses were conducted overall and stratified by receipt of physical therapy, chiropractic care, opioid fills, or gabapentin fills during the 6 months before the index date. KEY RESULTS: We identified 1,263,188 beneficiaries with aLBP, of whom 3.0% had OUD. Two-thirds (65.8%) did not receive pain treatments of interest at baseline. Overall, nonpharmacologic therapy receipt was less prevalent and opioid and nonopioid pharmacologic therapies were more common among beneficiaries with OUD than those without OUD. Beneficiaries with OUD had lower odds of receiving nonpharmacologic therapies (aOR = 0.62, 99%CI = 0.58-0.65) and higher odds of prescription opioid receipt (aOR = 2.24, 99%CI = 2.17-2.32). OUD also was significantly associated with increased odds of opioid doses ≥ 90 morphine milligram equivalents/day (aOR = 2.43, 99%CI = 2.30-2.56) and co-prescription of gabapentin (aOR = 1.15, 99%CI = 1.09-1.22). Similar associations were observed in stratified groups though magnitudes differed. CONCLUSIONS: Medicare beneficiaries with aLBP and OUD underutilized nonpharmacologic pain therapies and commonly received opioids at high doses and with gabapentin. Complementing the promulgation of practice guidelines with implementation science could improve the uptake of evidence-based nonpharmacologic therapies for aLBP.