Multi-omic analysis of Huntington's disease reveals a compensatory astrocyte state.

The mechanisms underlying the selective regional vulnerability to neurodegeneration in Huntington's disease (HD) have not been fully defined. To explore the role of astrocytes in this phenomenon, we used single-nucleus and bulk RNAseq, lipidomics, HTT gene CAG repeat-length measurements, and multiplexed immunofluorescence on HD and control post-mortem brains. We identified genes that correlated with CAG repeat length, which were enriched in astrocyte genes, and lipidomic signatures that implicated poly-unsaturated fatty acids in sensitizing neurons to cell death. Because astrocytes play essential roles in lipid metabolism, we explored the heterogeneity of astrocytic states in both protoplasmic and fibrous-like (CD44+) astrocytes. Significantly, one protoplasmic astrocyte state showed high levels of metallothioneins and was correlated with the selective vulnerability of distinct striatal neuronal populations. When modeled in vitro, this state improved the viability of HD-patient-derived spiny projection neurons. Our findings uncover key roles of astrocytic states in protecting against neurodegeneration in HD.

Multimodal assessment of high-risk human papillomavirus in sinonasal squamous cell carcinoma.

High-risk human papillomavirus (hrHPV) is an emerging risk factor for sinonasal squamous cell carcinoma (SNSCC). The goal of this study was to assess the prevalence of hrHPV and subtype distribution in SNSCC and correlation with patient and clinical characteristics. This retrospective cohort study included 43 cases diagnosed with incident primary SNSCC at the University of Cincinnati Medical Center from 2010 to 2015. The prevalence of hrHPV was interrogated using a multi-assay approach that included p16 immunohistochemistry (IHC), RNA in-situ hybridization (ISH), and hrHPV DNA sequencing. The association of hrHPV with 5-year overall survival (OS) and 2-year disease-free survival (DFS) was assessed. Fourteen cases (32.6 %) were classified as hrHPV positive, based on the a priori definition of having either a positive RNAScope™ ISH test or hrHPV DNA and p16-positive IHC; 9 cases (20.9 %) were positive for all three tests. All cases that arose from an inverted sinonasal papilloma (ex-ISP) were negative for hrHPV. HPV16 was the most common subtype among hrHPV positive cases (58.8 %), followed by HPV18 (17.6 %). No significant association was observed between hrHPV and OS or DFS after adjusting for potential confounding. hrHPV is prevalent in a sizable fraction of SNSCC. Additional studies are needed to better elucidate the relationship with patient survival outcomes and determine the optimal testing modality for prognostication.

Sex-stratified analyses of comorbidities associated with an inpatient delirium diagnosis using real world data.

Delirium is a detrimental mental condition often seen in older, hospitalized patients and is currently hard to predict. In this study, we leverage electronic health records (EHR) to identify 7,492 UCSF patients and 19,417 UC health system patients with an inpatient delirium diagnosis and the same number of control patients without delirium. We found significant associations between comorbidities or laboratory values and an inpatient delirium diagnosis, including metabolic abnormalities and psychiatric diagnoses. Some associations were sex-specific, including dementia subtypes and infections. We further explored the associations with anemia and bipolar disorder by conducting longitudinal analyses from the time of first diagnosis to development of delirium, demonstrating a significant relationship across time. Finally, we show that an inpatient delirium diagnosis leads to increased risk of mortality. These results demonstrate the powerful application of the EHR to shed insights into prior diagnoses and laboratory values that could help predict development of inpatient delirium and the importance of sex when making these assessments.

Harnessing EHR data for health research.

With the increasing availability of rich, longitudinal, real-world clinical data recorded in electronic health records (EHRs) for millions of patients, there is a growing interest in leveraging these records to improve the understanding of human health and disease and translate these insights into clinical applications. However, there is also a need to consider the limitations of these data due to various biases and to understand the impact of missing information. Recognizing and addressing these limitations can inform the design and interpretation of EHR-based informatics studies that avoid confusing or incorrect conclusions, particularly when applied to population or precision medicine. Here we discuss key considerations in the design, implementation and interpretation of EHR-based informatics studies, drawing from examples in the literature across hypothesis generation, hypothesis testing and machine learning applications. We outline the growing opportunities for EHR-based informatics studies, including association studies and predictive modeling, enabled by evolving AI capabilities-while addressing limitations and potential pitfalls to avoid.

Herpes Simplex Virus Encephalitis in Patients With Autoimmune Conditions or Exposure to Immunomodulatory Medications.

BACKGROUND AND OBJECTIVES: Among infectious etiologies of encephalitis, herpes simplex virus type 1 (HSV-1) is most common, accounting for ∼15%-40% of adult encephalitis diagnoses. We aim to investigate the association between immune status and HSV encephalitis (HSVE). Using a US Medicaid database of 75.6 million persons, we evaluated the association between HSVE and autoimmune conditions, exposure to immunosuppressive and immunomodulatory medications, and other medical comorbidities. METHODS: We used the US Medicaid Analytic eXtract data between 2007 and 2010 from the 29 most populated American states. We first examined the crude incidence of HSVE in the population. We then age and sex-matched adult cases of HSVE with a sufficient enrollment period (12 months before HSVE diagnosis) to a larger control population without HSVE. In a case-control analysis, we examined the association between HSVE and exposure to both autoimmune disease and immunosuppressive/immunomodulatory medications. Analyses were conducted with conditional logistic regression progressively adjusting for sociodemographic factors, Charlson Comorbidity Index, and non-autoimmune comorbidities. RESULTS: Incidence of HSVE was ∼3.01 per 105 person-years among adults. A total of 951 HSVE cases and 95,100 age and sex-matched controls were compared. The HSVE population had higher rates of medical comorbidities than the control population. The association of HSVE and autoimmune conditions was strong (adjusted odds ratio (OR) 2.6; 95% CI 2.2-3.2). The association of HSVE and immunomodulating medications had an OR of 2.2 (CI 1.9-2.6), also after covariate adjustment. When both exposures were included in regression models, the associations remained robust: OR 2.3 (CI 1.9-2.7) for autoimmune disease and 2.0 (CI 1.7-2.3) for immunosuppressive and immunomodulatory medications. DISCUSSION: In a large, national population, HSVE is strongly associated with preexisting autoimmune disease and exposure to immunosuppressive and immunomodulatory medications. The role of antecedent immune-related dysregulation may have been underestimated to date.

Exposure to autoimmune disorders increases Alzheimer's disease risk in a multi-site electronic health record analysis.

Molecular studies of Alzheimer's disease (AD) implicate potential links between autoimmunity and AD, but the underlying clinical relationships between these conditions remain poorly understood. Electronic health records (EHRs) provide an opportunity to determine the clinical risk relationship between autoimmune disorders and AD and understand whether specific disorders and disorder subtypes affect AD risk at the phenotypic level in human populations. We evaluated relationships between 26 autoimmune disorders and AD across retrospective observational case-control and cohort study designs in the EHR systems at UCSF and Stanford. We quantified overall and sex-specific AD risk effects that these autoimmune disorders confer. We identified significantly increased AD risk in autoimmune disorder patients in both study designs at UCSF and at Stanford. This pattern was driven by specific autoimmunity subtypes including endocrine, gastrointestinal, dermatologic, and musculoskeletal disorders. We also observed increased AD risk from autoimmunity in both women and men, but women with autoimmune disorders continued to have a higher AD prevalence than men, indicating persistent sex-specificity. This study identifies autoimmune disorders as strong risk factors for AD that validate across several study designs and EHR databases. It sets the foundation for exploring how underlying autoimmune mechanisms increase AD risk and contribute to AD pathogenesis.

Early, precise, and safe clinical evaluation of the pharmacodynamic effects of novel agents in the intact human tumor microenvironment.

Introduction: Drug development is systemically inefficient. Research and development costs for novel therapeutics average hundreds of millions to billions of dollars, with the overall likelihood of approval estimated to be as low as 6.7% for oncology drugs. Over half of these failures are due to a lack of drug efficacy. This pervasive and repeated low rate of success exemplifies how preclinical models fail to adequately replicate the complexity and heterogeneity of human cancer. Therefore, new methods of evaluation, early in the development trajectory, are essential both to rule-in and rule-out novel agents with more rigor and speed, but also to spare clinical trial patients from the potentially toxic sequelae (high risk) of testing investigational agents that have a low likelihood of producing a response (low benefit). Methods: The clinical in vivo oncology (CIVO®) platform was designed to change this drug development paradigm. CIVO precisely delivers microdose quantities of up to 8 drugs or combinations directly into patient tumors 4-96 h prior to planned surgical resection. Resected tissue is then analyzed for responses at each site of intratumoral drug exposure. Results: To date, CIVO has been used safely in 6 clinical trials, including 68 subjects, with 5 investigational and 17 approved agents. Resected tissues were analyzed initially using immunohistochemistry and in situ hybridization assays (115 biomarkers). As technology advanced, the platform was paired with spatial biology analysis platforms, to successfully track anti-neoplastic and immune-modulating activity of the injected agents in the intact tumor microenvironment. Discussion: Herein we provide a report of the use of CIVO technology in patients, a depiction of the robust analysis methods enabled by this platform, and a description of the operational and regulatory mechanisms used to deploy this approach in synergistic partnership with pharmaceutical partners. We further detail how use of the CIVO platform is a clinically safe and scientifically precise alternative or complement to preclinical efficacy modeling, with outputs that inform, streamline, and de-risk drug development.

Proton Treatment Suppresses Exosome Production in Head and Neck Squamous Cell Carcinoma.

Proton therapy (PT) is emerging as an effective and less toxic alternative to conventional X-ray-based photon therapy (XRT) for patients with advanced head and neck squamous cell carcinomas (HNSCCs) owing to its clustered dose deposition dosimetric characteristics. For optimal efficacy, cancer therapies, including PT, must elicit a robust anti-tumor response by effector and cytotoxic immune cells in the tumor microenvironment (TME). While tumor-derived exosomes contribute to immune cell suppression in the TME, information on the effects of PT on exosomes and anti-tumor immune responses in HNSCC is not known. In this study, we generated primary HNSCC cells from tumors resected from HNSCC patients, irradiated them with 5 Gy PT or XRT, and isolated exosomes from cell culture supernatants. HNSCC cells exposed to PT produced 75% fewer exosomes than XRT- and non-irradiated HNSCC cells. This effect persisted in proton-irradiated cells for up to five days. Furthermore, we observed that exosomes from proton-irradiated cells were identical in morphology and immunosuppressive effects (suppression of IFN-γ release by peripheral blood mononuclear cells) to those of photon-irradiated cells. Our results suggest that PT limits the suppressive effect of exosomes on cancer immune surveillance by reducing the production of exosomes that can inhibit immune cell function.

Beta-defensin index: A functional biomarker for oral cancer detection.

There is an unmet clinical need for a non-invasive and cost-effective test for oral squamous cell carcinoma (OSCC) that informs clinicians when a biopsy is warranted. Human beta-defensin 3 (hBD-3), an epithelial cell-derived anti-microbial peptide, is pro-tumorigenic and overexpressed in early-stage OSCC compared to hBD-2. We validate this expression dichotomy in carcinoma in situ and OSCC lesions using immunofluorescence microscopy and flow cytometry. The proportion of hBD-3/hBD-2 levels in non-invasively collected lesional cells compared to contralateral normal cells, obtained by ELISA, generates the beta-defensin index (BDI). Proof-of-principle and blinded discovery studies demonstrate that BDI discriminates OSCC from benign lesions. A multi-center validation study shows sensitivity and specificity values of 98.2% (95% confidence interval [CI] 90.3-99.9) and 82.6% (95% CI 68.6-92.2), respectively. A proof-of-principle study shows that BDI is adaptable to a point-of-care assay using microfluidics. We propose that BDI may fulfill a major unmet need in low-socioeconomic countries where pathology services are lacking.

Gender inequities in ENT: Insights from women speakers at American Head and Neck Society meetings.

BACKGROUND: Gender inequity exists across national speakers at American Head and Neck Society (AHNS) conferences. This qualitative study explores potential causes of this disparity by surveying women invited to speak at AHNS between 2007 and 2019 and examining advice, resources, and meaningful actions from "those who made it." METHODS: An internet search for contact information for the 131 female AHNS was performed. An electronic survey was distributed via email. Deidentified qualitative responses were coded by two independent researchers into themes. Themes characterize barriers that female head and neck (HN) surgeons face and describe ways to mitigate the impact of these for the next generation. RESULTS: Contact information for 73/131 female AHNS speakers was obtained via internet search. Email responses were received from 22/73 (30%). Of those, respondents specialized in otolaryngology (n = 17), medical oncology (n = 2), palliative care (n = 1), vascular surgery (n = 1), and thoracic surgical oncology (n = 1). All speakers worked in academic settings at varying stages of their career with 81.8% (18/22) of respondents fellowship-trained (primarily HN surgery). Concerns about gender disparity in ENT were grouped into the following themes: (1) recruiting women to ENT, (2) removing barriers to career advancement, (3) diversifying ENT's national presence, and (4) improving the broader culture of HN surgery. Respondents emphasized a need for diversifying leadership, early exposure to otolaryngology in medical school, and connecting students with female role models. Outstanding research, involvement at annual meetings, and committee membership were consistently deemed important for establishing a national presence in the field. Implicit bias, "boys clubs" culture, and burdensome childcare responsibilities were described as barriers to career advancement. CONCLUSIONS: While encouraging more women to enter otolaryngology residencies, increasing the number female role models and establishing strong mentoring networks may help to mitigate challenges. Meaningful progress requires the efforts of both male and female allies within the specialty. Simple solutions, such as educating on implicit bias, removing demographics from applications, and eliminating hidden penalties for maternity leave, may help improve diversity and mitigate barriers to career progression for underrepresented groups within ENT.

Identifying therapeutic candidates for endometriosis through a transcriptomics-based drug repositioning approach.

Existing medical treatments for endometriosis-related pain are often ineffective, underscoring the need for new therapeutic strategies. In this study, we applied a computational drug repurposing pipeline to stratified and unstratified disease signatures based on endometrial gene expression data to identify potential therapeutics from existing drugs, based on expression reversal. Of 3,131 unique genes differentially expressed by at least one of six endometriosis signatures, only 308 (9.8%) were in common; however, 221 out of 299 drugs identified, (73.9%) were shared. We selected fenoprofen, an uncommonly prescribed NSAID that was the top therapeutic candidate for further investigation. When testing fenoprofen in an established rat model of endometriosis, fenoprofen successfully alleviated endometriosis-associated vaginal hyperalgesia, a surrogate marker for endometriosis-related pain. These findings validate fenoprofen as a therapeutic that could be utilized more frequently for endometriosis and suggest the utility of the aforementioned computational drug repurposing approach for endometriosis.

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights.

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

The effect of transfusion on survival in head and neck cancer after free tissue reconstruction.

Objective: To examine if perioperative blood transfusion affects overall survival (OS) and recurrence-free survival (RFS) in head and neck cancer patients who undergo free tissue reconstruction. Design: Retrospective cohort study. Methods: The medical records of free tissue flaps between 2007 and 2010 were reviewed. Differences in demographics and clinical factors based on the level of transfused packed red blood cells (PRBC) were examined using chi-squared tests, Kruskal-Wallis tests, and/or ANOVA tests. Survival time was compared using a Cox proportional hazard model. Results: Data were available for 183 patients. Patients who had PRBC transfusion significantly differed from the non-transfused group by flap type, flap with bone, Charlson Comorbidity Index (CCI), and hemoglobin and hematocrit. When stratified into three groups based on units of PRBC; flap type, flap with bone, CCI, preoperative hemoglobin, and hematocrit were found to differ significantly. The 2-year Kaplan-Meier plot demonstrated improved OS for those who did not receive any PRBC transfusion. The use of more than 3 units of blood decreased 2-year OS significantly when compared to the non-transfused group. Finally, after adjusting for CCI using a Cox proportional hazard model, survival was significantly affected by CCI. Conclusion: After controlling for patient age, oncologic stage, cancer subsite, histology, type of free flap, vascularized bone-containing flap, recurrence type, CCI, and preoperative hemoglobin and hematocrit, patients who received 3 or more units of PRBC in the perioperative period had significantly decreased OS. RFS did not differ between the transfused versus non-transfused groups. Level of Evidence: Level 4.

National Institutes of Health Funding for Tuberculosis Comorbidities Is Disproportionate to Their Epidemiologic Impact.

Tuberculosis (TB) is a leading infectious killer worldwide. We systematically searched the National Institutes of Health Research, Portfolio Online Reporting Tools Expenditures and Results (RePORTER) website to compare research funding for key TB comorbidities-undernutrition, alcohol use, human immunodeficiency virus, tobacco use, and diabetes-and found a large mismatch between the population attributable fraction of these risk factors and the funding allocated to them.

Microvascular Free Flap Outcomes in Maxillectomy Defects from Invasive Fungal Sinusitis.

OBJECTIVES: Microvascular free tissue transfer is routinely used for reconstructing midface defects in patients with malignancy, however, studies regarding reconstructive outcomes in invasive fungal sinusitis (IFS) are lacking. We aim to describe outcomes of free flap reconstruction for IFS defects, determine the optimal time to perform reconstruction, and if anti-fungal medications or other risk factors of an immunocompromised patient population affect reconstructive outcomes. METHODS: Retrospective review of reconstruction for IFS (2010-2022). Age, BMI, hemoglobin A1c, number of surgical debridements, and interval from the last debridement to reconstruction were compared between patients with delayed wound healing versus those without. Predictor variables for delayed wound healing and the effect of time on free flap reconstruction were analyzed. RESULTS: Twenty-seven patients underwent free flap reconstruction for IFS. Three patients were immunocompromised from leukemia and 21 had diabetes mellitus (DM). Patients underwent an average of four surgical debridements for treatment of IFS. The interval from the last IFS debridement to flap reconstruction was 5.58 months (±5.5). Seven flaps (25.9%) had delayed wound healing. A shorter interval of less than 2 months between the last debridement for IFS and reconstructive free flap procedure was associated with delayed wound healing (Fisher Exact Test p = 0.0062). Other factors including DM, BMI, HgA1c, and bone reconstruction were not associated with delayed wound healing. CONCLUSION: Patients with maxillectomy defects from IFS can undergo microvascular-free flap reconstruction with good outcomes while on anti-fungal medication. Early reconstruction in the first 2 months after the last IFS debridement is associated with delayed wound healing. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:1642-1647, 2024.

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.

Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; <37 weeks) or (2) early preterm birth (ePTB; <32 weeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth.

Associations with spontaneous and indicated preterm birth in a densely phenotyped EHR cohort.

Background: Preterm birth (PTB) is the leading cause of infant mortality and follows multiple biological pathways, many of which are poorly understood. Some PTBs result from medically indicated labor following complications from hypertension and/or diabetes, while many others are spontaneous with unknown causes. Previously, investigation of potential risk factors has been limited by lack of data on maternal medical history and the difficulty of classifying PTBs as indicated or spontaneous. Here, we leverage electronic health record (EHR) data (patient health information including demographics, diagnoses, and medications) and a supplemental curated pregnancy database to overcome these limitations. Novel associations may provide new insight into the pathophysiology of PTB as well as help identify individuals who would be at risk of PTB. Methods: We quantified associations between maternal diagnoses and preterm birth using logistic regression controlling for maternal age and socioeconomic factors within a University of California, San Francisco (UCSF), EHR cohort with 10,643 births ( nterm = 9692, nspontaneous_preterm = 449, nindicated_preterm = 418) and maternal pre-conception diagnosis phenotypes derived from International Classification of Diseases (ICD) 9 and 10 codes. Results: Eighteen conditions significantly and robustly (False Discovery Rate (FDR)<0.05) associated with PTBs compared to term. We discovered known (hypertension, diabetes, and chronic kidney disease) and less established (blood, cardiac, gynecological, and liver conditions) associations. Type 1 diabetes was the most significant overall association (adjusted p = 1.6×10 -14 , adjusted OR = 7 (95% CI 5, 12)), and the odds ratios for the significant phenotypes ranged from 3 to 13. We further carried out analysis stratified by spontaneous vs. indicated PTB. No phenotypes significantly associated with spontaneous PTB; however, the results for indicated PTB largely recapitulated the phenotype associations with all PTBs. Conclusions: Our study underscores the limitations of approaches that combine indicated and spontaneous births together. When combined, significant associations were almost entirely driven by indicated PTBs, although our spontaneous and indicated groups were of a similar size. Investigating the spontaneous population has the potential to reveal new pathways and understanding of the heterogeneity of PTB.

MaLiAmPi enables generalizable and taxonomy-independent microbiome features from technically diverse 16S-based microbiome studies.

For studies using microbiome data, the ability to robustly combine data from technically and biologically distinct microbiome studies is a crucial means of supporting more robust and clinically relevant inferences. Formidable technical challenges arise when attempting to combine data from technically diverse 16S rRNA gene variable region amplicon sequencing (16S) studies. Closed operational taxonomic units and taxonomy are criticized as being heavily dependent upon reference sets and with limited precision relative to the underlying biology. Phylogenetic placement has been demonstrated to be a promising taxonomy-free manner of harmonizing microbiome data, but it has lacked a validated count-based feature suitable for use in machine learning and association studies. Here we introduce a phylogenetic-placement-based, taxonomy-independent, compositional feature of microbiota: phylotypes. Phylotypes were predictive of clinical outcomes such as obesity or pre-term birth on technically diverse independent validation sets harmonized post hoc. Thus, phylotypes enable the rigorous cross-validation of 16S-based clinical prognostic models and associative microbiome studies.

Sex-stratified phenotyping of comorbidities associated with an inpatient delirium diagnosis using real world data.

Delirium is a heterogeneous and detrimental mental condition often seen in older, hospitalized patients and is currently hard to predict. In this study, we leverage large-scale, real- world data using the electronic health records (EHR) to identify two cohorts comprised of 7,492 UCSF patients and 19,417 UC health system patients (excluding UCSF patients) with an inpatient delirium diagnosis and the same number of propensity score-matched control patients without delirium. We found significant associations between comorbidities or laboratory test values and an inpatient delirium diagnosis which were validated independently. Most of these associations were those previously-identified as risk factors for delirium, including metabolic abnormalities, mental health diagnoses, and infections. Some of the associations were sex- specific, including those related to dementia subtypes and infections. We further explored the diagnostic associations with anemia and bipolar disorder by conducting longitudinal analyses from the time of first diagnosis of the risk factor to development of delirium demonstrating a significant relationship across time. Finally, we show that an inpatient delirium diagnosis leads to dramatic increases in mortality outcome across both cohorts. These results demonstrate the powerful application of leveraging EHR data to shed insights into prior diagnoses and laboratory test values that could help predict development of inpatient delirium and emphasize the importance of considering patient demographic characteristics including documented sex when making these assessments. One Sentence Summary: Longitudinal analysis of electronic health record data reveals associations between inpatient delirium, comorbidities, and mortality.

A non-canonical striatopallidal Go pathway that supports motor control.

In the classical model of the basal ganglia, direct pathway striatal projection neurons (dSPNs) send projections to the substantia nigra (SNr) and entopeduncular nucleus to regulate motor function. Recent studies have re-established that dSPNs also possess axon collaterals within the globus pallidus (GPe) (bridging collaterals), yet the significance of these collaterals for behavior is unknown. Here we use in vivo optical and chemogenetic tools combined with deep learning approaches in mice to dissect the roles of dSPN GPe collaterals in motor function. We find that dSPNs projecting to the SNr send synchronous motor-related information to the GPe via axon collaterals. Inhibition of native activity in dSPN GPe terminals impairs motor activity and function via regulation of Npas1 neurons. We propose a model by which dSPN GPe axon collaterals (striatopallidal Go pathway) act in concert with the canonical terminals in the SNr to support motor control by inhibiting Npas1 neurons.