Science Translational Medicine

Histopathological evaluation of skeletal muscle biopsies relies on subjective, semi-quantitative assessment with no standardized grading system. We developed a four-tissue deep learning segmentation pipeline using Cellpose-SAM for myofiber instance segmentation, a pixel classifier for fat infiltration, and watershed detection for nuclei. We applied this pipeline to 478 H&E whole-slide images from two independent cohorts: HuashanMuscle (n = 79; China; myotonic dystrophy type 1 [DM1], n = 28; limb-girdle muscular dystrophy type R1 [LGMDR1, calpainopathy], n = 12; type R2 [LGMDR2, dysferlinopathy], n = 22; controls, n = 17) and GTEx (n = 399; United States; three-level myopathy spectrum). Thirty-seven unique morphometric features were extracted per sample. Nuclear centralization index (NCI) and fiber size variability coefficient (fiber CV) discriminated myopathy from controls (p = 1.3E-05, rank-biserial r = 0.69; and p = 2.9E-04, r = 0.58, respectively). DM1 showed the highest NCI (median 0.121), consistent with its centronuclear pathology, and NCI correlated with CTG repeat count (Spearman rho = 0.46, p = 0.042, n = 20). In the GTEx cohort, both biomarkers exhibited significant dose-response trends across the myopathy spectrum (Jonckheere-Terpstra p < E-04). The MyoPath Score, a logistic regression composite of seven pathology indicators trained on GTEx, achieved AUC = 0.788 (LOO-CV 0.735) and transferred to the independent HuashanMuscle cohort with AUC = 0.873 without retraining. Segmentation achieved Dice coefficients of 0.92 (myofiber), 0.95 (fat), 0.87 (nucleus), and 0.88 (connective tissue), with intraclass correlation coefficients exceeding 0.88. NCI and fiber CV provide objective, reproducible quantitative biomarkers for skeletal muscle pathology severity assessment with potential as standardized grading criteria and clinical trial endpoints.

People with HIV exhibit elevated inflammation and cardiovascular risk despite antiretroviral therapy. To define the genetic architecture of inflammasome-associated inflammation, we performed whole-genome sequencing and quantified plasma IL-6, IL-1{beta}, and IL-18 in 1,000 ART-suppressed PWH from the U.S. Military HIV Natural History Study. Genome-wide analyses identified 14 loci implicating antiviral defense (DDX17, DDX41, EEA1, BCL11A), lipid metabolism (ABCA1, ABCA12, ABCC1, AGMO), and vascular remodeling (KLHL29, RNF213, ETV1). Transcriptome-wide analyses across cardiovascular and immune tissues identified regulatory programs linking interferon signaling, immune activation, and vascular biology to circulating cytokine levels. Mendelian randomization analyses supported causal relationships between inflammasome-associated cytokines and vascular events. Functional integration with genome-wide CRISPR perturbation datasets in primary CD4 T cells linked cytokine-associated loci to HIV antiviral pathways and cytokine regulatory networks. External validation in cohorts without HIV demonstrated pathway-level convergence despite limited variant-level overlap. These findings define genetic mechanisms linking inflammasome signaling, antiviral defense, and cardiovascular risk.

The PRESERVE trial (NCT04972097) is a prospective, single-arm pivotal IDE study evaluating focal irreversible electroporation (IRE) using the NanoKnife System for intermediate-risk prostate cancer. Men with Gleason Grade Group 2-3 disease underwent focal IRE and were followed for durability of oncologic control and safety. At 24 months, 68 patients completed follow-up with no new treatment failures identified. PSA levels were below baseline in 97% of patients, and one clinically triggered biopsy was negative for cancer. No new device- or procedure-related adverse events occurred beyond 12 months. These findings demonstrate durable efficacy and sustained safety of focal IRE.

Lupus nephritis (LN), a severe manifestation of systemic lupus erythematosus (SLE), features heterogeneous renal pathology and reliance on invasive biopsies for diagnosis, prognosis, and treatment selection. Current peripheral clinical markers inadequately capture disease activity and progression. Here, we performed comprehensive serum proteomic profiling of over 5,000 proteins in the large, longitudinal Accelerating Medicines Partnership Rheumatoid Arthritis/SLE cohort of 270 LN patients and 63 healthy controls. Machine learning identified distinct molecular signatures that classified LN versus controls, differentiated histological classes, and delineated activity- and chronicity-associated pathways, including inflammatory cytokine, PI3K/AKT, TGFb, and complement/coagulation pathways. An increase in VSIG4, CD27, HAVCR1, and LAIR1 consistently emerged as top biomarkers across multiple clinical contexts, and early decreases in these markers at 3 months were associated with complete treatment response at 1 year. By resolving coordinated serum protein modules linked to key inflammatory, PI3K/AKT, TGFb, and complement pathways, these signatures mechanistically connect circulating proteomic perturbations to intrarenal immune activation, tissue injury, and repair in LN. These findings demonstrate that serum proteomics reflect complex intrarenal immunopathology and offer a promising noninvasive "liquid biopsy" approach to refine LN classification and guide personalized management, potentially reducing the need for repeated invasive biopsies and improving therapeutic decision-making.

Adeno-associated virus (AAV)-delivered anti-HIV-1 broadly neutralizing antibodies (bNAbs) could prevent and treat HIV-1 infection but are limited by host immune responses, specifically anti-drug antibodies (ADA). We tested whether PD-L1-mediated immune shielding could improve the consistency of AAV-delivered bNAb expression from muscle tissue in rhesus macaques. AAV9.PD-L1 co-delivery with AAV9.3BNC117 reduced the occurrence of ADA and T cell responses and improved the durability of 3BNC117 expression for one year post administration. Importantly, 5 of 6 macaques that received co-delivered AAV9.PD-L1 vectors were protected against ten repeated SHIVAD8-EO challenges. Histopathological and spatial transcriptomic profiling showed that AAV9.PD-L1 co-delivery prevented severe local inflammation, muscle injury, and tertiary lymphoid structure formation at the administration site. Thus, immune shielding could serve as a strategy to prolong transgene expression from muscle-directed AAV-delivered biologics.

Vaccines to prevent infant group B streptococcus (GBS) disease are advancing, with licensure likely based on safety and immunologic endpoints rather than clinical efficacy data. This approach requires robust, generalisable serological thresholds of risk reduction (SToRRs). We combined data from six case-control studies in Europe and Africa to define SToRRs for early-onset (EOD) and late-onset (LOD) GBS disease. Across diverse epidemiological and healthcare settings, anti-capsular polysaccharide IgG concentrations were consistently higher in infants who remained disease free than in those who developed disease. Higher antibody concentrations were required to reduce the risk of EOD than LOD, and higher concentrations were required for serotype Ia than for serotype III. This study provides a quantitative framework to support correlates-based evaluation and potential licensure of maternal GBS vaccines.

The preclinical phase of Alzheimers disease (AD) is characterized by profound biological and structural heterogeneity, challenging our ability to map early pathology onto large-scale brain networks. To address this fundamental challenge, we introduce Functional Deviation Maps ({pi}z), an individualized neuroimaging framework for mapping participant-specific functional architecture to their unique structural atrophy landscape. By fitting a normative model to the voxel-based morphometry of amyloid-negative individuals, we extract personalized "atrophy seeds" (W-scores [&le;] -1.96) for amyloid-positive patients, subsequently obtaining their resting-state seed-based connectivity (SBC). By standardizing these participant-level SBC maps against a healthy reference distribution, we show that, despite the highly variable spatial origins of structural atrophy, individual functional deviations converge into a common "atrophy network". Spatial enrichment analyses show that the functional disruption is not random, but preferentially is dominated by the Default Mode Network. Furthermore, by projecting these populational functional deviations onto high-order cognitive topographies, we find a considerable alignment with the brains fundamental unimodal-transmodal and external-internal attentional gradients. Overall, the{pi} z framework transcends conventional group-level averages, offering a highly personalized, biologically meaningful signature of system-level network vulnerability in the earliest stages of AD.

Juvenile dermatomyositis (JDM) is characterized by a type I interferon (IFN-I) signature associated with disease activity. We previously identified a link between SARS-CoV-2 infection and the onset or relapse of JDM. Here, we show that newly diagnosed JDM patients display an overexpression of IFIH1 (encoding MDA5 protein) at baseline, coupled with an altered response to dsRNA stimulation at proteomic and transcriptomic levels, indicating abnormal activation of this antiviral sensing pathway. Single-cell transcriptomic and chromatin accessibility profiling of peripheral blood mononuclear cells (PBMCs) further revealed myeloid-specific enrichment of interferon-stimulated genes (ISGs) and preferential disruption of this pathway at disease onset, supporting a dysregulated IFN-I state in this cell type. We identified SARS-CoV-2 RNA in muscle biopsies of two Covid-19 pandemic-onset JDM patients, strongly implicating viral infection as a potential trigger of the dysregulated MDA5 immune response. To extend these observations beyond SARS-CoV-2, we screened two independent retrospective cohorts for antibodies against 27 common childhood infections. In our discovery cohort JDM patients showed significantly increased exposure to 4 RNA viruses in line with our immunological findings. Increased exposure to RSV B was confirmed in an independent replication cohort supporting a robust association with JDM pathophysiology. Together, these findings integrate systemic, single-cell, and tissue-level analyses implicating RNA viral infection and biased antiviral sensing in shaping IFN-I responses at JDM onset, providing mechanistic insight into environmentally triggered pathogenesis. One sentence summaryType I interferon dysregulation at juvenile dermatomyositis onset implicates altered dsRNA sensing and RNA viral exposure as potential disease triggers.

Complex human diseases exhibit substantial clinical heterogeneity driven by poorly understood molecular mechanisms, while many also lack sufficient molecular and omics data for mechanistic investigation, hindering therapeutic development. We introduce PiMInfer, a phenotype-to-mechanism framework that leveraged largely available real-world clinical data-based deep phenotypic characterizations with a biomedical knowledge graph approach to resolve disease clinical heterogeneity into phenotype-informed molecular modules, thereby accelerating therapeutic target discovery. We applied PiMInfer to investigate Hidradenitis Suppurativa (HS), an autoimmune skin disease with poorly understood pathogenesis and limited treatment options. PiMInfer identified a coherent, phenotype-informed HS gene module (PiHSM) and functional endotypes, which were validated using multimodal evidence. In silico drug repurposing using PiHSM prioritized Carfilzomib, targeting the immunoproteasome subunit PSMB9, essential for MHC Class I antigen presentation. Preclinical testing using human patient lesional skin explants confirmed its anti-inflammatory activity and demonstrated a significant downregulation of IFN-{gamma}, IL-17, and mTOR signaling pathways within HS lesional microenvironment through single-cell RNA sequencing. PiHSM-based network predictions further suggest a potential enhanced efficacy of combining Carfilzomib with approved HS agents. Collectively, PiMInfer provides a scalable framework that bridges real-world phenome-wide comorbid associations to mechanism-anchored therapeutic discovery, enabling a paradigm shift in precision medicine approaches for complex diseases with limited molecular characterization and in need of better therapeutic strategies.

BackgroundMarfan syndrome (MFS) is a life-threatening heritable connective tissue disorder caused by pathogenic variants in fibrillin-1, characterized by progressive cardiovascular disease. Current medical therapies slow disease progression but do not prevent major complications, underscoring the need for new treatment strategies and unbiased discovery approaches. MethodsWe used a zebrafish model of MFS lacking fibrillin-3 (fbn3-/-), which recapitulates key cardiovascular phenotypes including cardiac stress, valvular defects, arrhythmia, and aortic dilation. To enable sensitive, quantitative assessment of cardiac stress, we generated a novel transgenic zebrafish reporter expressing secreted nanoluciferase under control of the stress-responsive nppb promoter. This reporter was combined with morphological phenotyping and bulbus arteriosus (BA) imaging. We evaluated standard MFS therapies, targeted modulators of TGF-{beta} signaling, and performed an unbiased high-throughput drug screen of over 1 500 clinically approved compounds across multiple developmental treatment windows. Resultsfbn3-/- larvae exhibited markedly elevated nppb activity that correlated with phenotypic severity and peaked during stages of highest mortality. The nanoluciferase reporter provided a [~]1 000-fold dynamic range, substantially outperforming Firefly luciferase-based assays. Pharmacological inhibition of TGF-{beta} signaling produced transient or deleterious effects, while {beta}-blockers, losartan, and allopurinol failed to consistently improve cardiac stress, pericardial edema, or BA dilation. The unbiased high-throughput drug screen identified a small number of primary and secondary hits; however, none demonstrated reproducible phenotypic rescue upon rigorous multi-dose, multi-time window validation. ConclusionsThis study establishes a sensitive zebrafish-based platform for early, quantitative assessment of cardiovascular stress in MFS. Our findings highlight the limited efficacy of current therapies, the context-dependent nature of TGF-{beta} modulation, and the biological complexity underlying MFS pathogenesis. Although no definitive therapeutic candidates were identified, this work lays a robust foundation for expanded unbiased discovery efforts aimed at identifying disease-modifying interventions for MFS.

Although GLP1/GIP receptor agonists demonstrate unprecedented weight loss efficacy, their rapid clinical adoption has revealed significant real-world tolerability challenges. To evaluate their dynamic safety profiles, we developed a macro to micro pharmacovigilance framework by combining global FAERS reports with local UT Physician EHR. Macroscopically, we distilled 17 shared adverse events across the drug class from FAERS with disproportionality analysis. Microscopically, local EHR data (289,655 longitudinal treatment sessions across 71,316 patients) revealed 51.6% of GLP1 sessions terminated within 90 days. Furthermore, temporal stratified logistic regression demonstrated that initial exposure (0 to 30 days) correlated strongly with nausea and vomiting, which attenuated in extended sessions, whereas extended exposure (>2 years) uncovered late onset risks, notably incident hepatic steatosis. Ultimately, this time aware framework reveals that GLP1 safety profiles are profoundly duration dependent, providing critical insights into both acute intolerances and long-term medication safety.

Kidney injury is a frequent and serious complication of allogeneic hematopoietic cell transplantation (HCT), yet its pathophysiology remains poorly understood and effective treatments are lacking. Through analysis of kidney tissue from HCT recipients, we identified substantial acute tubular injury and T cell infiltration that correlated with extra-renal graft-versus-host disease (GVHD) severity, linking systemic alloreactivity and post-transplant renal pathology. In murine models, GVHD was similarly associated with acute kidney injury, renal Th1-type T cell infiltration, and hyperactivation of NF-{kappa}B and JAK-STAT signalling. Notably, galectin-3, a damage-associated lectin, was upregulated in both patient biopsies and experimental GVHD target organs. Leveraging this pathological feature, we engineered galectin-3-targeted lipid nanoparticles for tissue-specific delivery of ruxolitinib, an approved GVHD therapy. Galectin-3 upregulation was also identified in canonical acute GVHD target organs including the liver and intestinal tract, and nanoparticle-delivered ruxolitinib substantially enhanced renal function, reduced systemic GVHD, and minimized hematologic toxicity compared to conventional drug administration. Our findings demonstrate renal involvement in acute GVHD and establish a nanoparticle-based strategy for precision delivery of immunomodulatory therapies to affected tissues.

Glaucoma phenotyping remains challenging due to disease heterogeneity and single-modality limitations. We introduce a visual field (VF)-guided entangled learning framework that integrates structural and functional signals during training to learn functionally informed macular retinal nerve fiber layer (mRNFL) representations while enabling OCT-only inference. In 5,372 paired MEEI examinations, VF-guided phenotyping identified 9 clinically distinct mRNFL phenotypes with divergent progression rates (MD slopes -0.2 to -1.8 dB/year, P <0.001), improving clustering over OCT-only by 22% (FCM) and 11% (GMM). External evaluation in 74,077 UK Biobank images confirmed generalizability, with improved risk association (r=-0.33 vs r=0.04). Genetic analyses identified 12 additional glaucoma loci compared with OCT-only phenotyping. VF-guided entangled learning improves clinically and genetically coherent mRNFL phenotyping with broad applicability to multimodal medical imaging.

Macrophage activation syndrome (MAS) is driven by a hyperinflammatory response characterized by aberrant activation of lymphocytes and phagocytes. While monocytes and macrophages are thought to be important in MAS pathogenesis, their role remains poorly understood. We used bulk and single-cell RNA sequencing (RNA-Seq) on sorted monocytes from children with MAS and healthy controls to identify transcriptional changes during MAS. We defined a MAS signature in classical monocytes that correlated with ferritin and was elevated in monocytes from systemic lupus erythematosus and COVID-19 patients. We also identified a subset of classical monocytes with high levels of interferon-stimulated genes (ISGs) that expanded during MAS. Surprisingly, the transcriptional signature of these cells was driven by type I IFNs, rather than IFN{gamma}. Consistent with this finding, we detected increased levels of circulating IFN{beta} during MAS, suggesting that IFN{beta} plays an unrecognized role in driving MAS monocyte responses. We also identified a MAS-associated CD8+ T cell population with a distinctive transcriptional signature. We used cell-cell communication algorithms to predict increased immunoregulatory interactions between monocytes and T cells during MAS. Together, these results provide new evidence for a role for type I IFN during MAS and identify a unique CD8+ T cell population that may contribute to MAS pathophysiology.

Muscle health varies continuously from optimal function to severe pathology, yet no unified genetic framework quantifies this spectrum objectively. Here we develop MyoScore, a transcriptomic scoring system derived from transcriptome-wide association studies of 27 muscle-related phenotypes in over one million participants. TWAS selects genes whose genetically regulated expression in skeletal muscle associates with muscle-related traits, providing the genetic anchoring of the scoring system, while MyoScore itself is computed from measured bulk RNA-seq expression in new samples. From 1,116 transcriptome-wide association study (TWAS)-significant genes, 417 are expressed in skeletal muscle and form the basis of the scoring system. These genes are organized into five dimensions of muscle biology (Strength, Mass, LeanMuscle, Youth and Resilience), each scored from 0 to 100. Across 1,722 human skeletal muscle transcriptomes from four independent cohorts, MyoScore defines a continuous four-stage muscle health spectrum, discriminates healthy from diseased muscle (area under the curve 0.751-0.873), and correlates with histopathological severity, quantitative MRI and clinical outcomes. Functional validation through iPSC-to-myotube differentiation supports predicted expression changes for novel MyoScore genes. UK Biobank analysis of blood biomarker proxies in 467,123 participants demonstrates concordant associations with muscle phenotypes, and two-sample Mendelian randomization using skeletal muscle cis-eQTL supports causal directionality for 78% of gene-outcome pairs tested. Single-cell validation across 475,584 cells from two independent muscle ageing atlases shows that pseudobulk MyoScore declines with age, with type II myofibre nuclei most affected. Together, MyoScore establishes the first genetically anchored, dimension-resolved quantification of human muscle health, enabling objective assessment, patient stratification and biomarker discovery across the full spectrum from optimal function to severe disease.

Kawasaki disease (KD) is an acute pediatric vasculitis characterized by dysregulated host immune responses and risk of coronary artery injury. Although a two-transcript IFI27-MCEMP1 axis has been clinically validated to distinguish KD from other febrile illnesses, the long noncoding RNA (lncRNA) context of this interferon-myeloid imbalance remains incompletely understood. We evaluated whether peripheral blood mononuclear cell (PBMC)-derived lncRNAs are altered in KD and associated with the interferon and myeloid components of the IFI27-MCEMP1 transcriptomic axis. Children younger than 8 years with suspected KD were prospectively enrolled at the Children's Hospital of Fudan University from 2024 to 2025. The newly enrolled cohort included 55 children with KD and 48 febrile controls. For integrated immune-transcript association analyses, these data were combined with two previously characterized same-site cohorts, yielding 188 children with KD and 175 febrile controls. Expression of IFI27, MCEMP1, CHROMR, MALAT1, and NEAT1 was measured by reverse transcription quantitative PCR and normalized to GAPDH using {Delta}Ct values. In the newly enrolled cohort, the IFI27-MCEMP1 axis reproduced discrimination between KD and febrile controls, with an area under the receiver operating characteristic curve of 0.88; performance was similar in the integrated cohort, with an area under the curve of 0.89. In PBMC lncRNA analyses, CHROMR and MALAT1 {Delta}Ct values were significantly higher in KD than in febrile controls, indicating lower relative expression, whereas NEAT1 did not show a significant KD-specific differential-expression signal. CHROMR showed the strongest association with the IFI27 interferon-associated component, while MALAT1 showed weaker but directionally informative associations with both IFI27 and MCEMP1, including an inverse association with MCEMP1. These findings support an lncRNA-associated interferon-myeloid immune architecture in KD, marked by coordinated attenuation of IFI27, CHROMR, and MALAT1 together with increased MCEMP1. This PBMC RNA pattern provides a biologically interpretable framework for KD immune dysregulation and generates testable hypotheses regarding RNA-regulatory programs in KD vasculitis.

Normative models produce per-subject deviation scores that feed directly into downstream analyses, but typical pipelines (i) treat confounders with ad-hoc or purely linear adjustments, and (ii) pass point estimates of deviation scores directly to the downstream model, ignoring uncertainty. We propose an integrated, two-module Bayesian framework that aims to address both limitations. A normative module based on Bayesian Additive Regression Trees (BART) flexibly captures non-linear effects and higher-order interactions while marginalising over image-quality variables via counterfactual averaging. Crucially, we define individual deviation as di = E[Y|Xi,Zi] - (Zi) with (Z) the feature-conditional population mean, not as a residual. A SoftBART survival model then ingests the full posterior distribution of deviation scores via a cut-posterior construction, propagating upstream uncertainty while blocking feedback from the outcome model. Across challenging simulations and a large clinical data set of multiple sclerosis patients (N>8k), the integrated approach yields better calibration, prediction accuracy and time-varying hazard separation between groups than a two-step plug-in Cox regression model. Modularised inference with BART-based normative deviations improves both flexibility and uncertainty quantification, and extends naturally to other outcomes beyond survival.

While SARS-CoV-2 research has advanced rapidly since COVID-19, endemic human coronaviruses (HCoVs) remain comparatively understudied. Tools to phenotype spike (S), the primary antigenic target on coronaviruses, at the single-virion level could improve vaccine design by capturing variation in epitope availability and spike abundance. Here, we establish a calibrated flow virometry (FV) platform to quantify S antigenicity on native endemic (HCoV-229E, HCoV-OC43) and epidemic (SARS-CoV-2) coronaviruses directly in cell culture supernatants. FV revealed cell line-dependent differences in S antigenicity, including receptor-induced changes in epitope accessibility. Comparison of virion-associated S with recombinant stabilized S by ELISA and biolayer interferometry showed consistent binding for HCoV-OC43, MERS-CoV, and SARS-CoV-2, but differences for HCoV-229E, with FV resolving heterogeneity not captured by bulk assays. Finally, FV showed that HCoV-229E from patient-derived air-liquid interface cultures exhibited reduced antibody binding and distinct S antigenicity compared to cell line-derived virions. Together, these findings establish FV as a platform for single-virion analysis of HCoV antigenicity.

Immune checkpoint inhibitor-induced lichen planus (ICI-LP) is a cutaneous immune related adverse event (irAE) that shares key clinicopathologic features with spontaneous lichen planus (LP) but differs histologically and in the sex distribution of its incidence, and may therefore reflect a distinct tissue inflammatory state. To define the cellular programs that distinguish ICI-LP from LP, we profiled lesional skin by single cell and spatial transcriptomic approaches. We found few differences in the T cell and keratinocyte compartments between ICI-LP and LP, which shared similar inflammatory signatures. Rather, the dominant transcriptional features differentiating these two eruptions occurred within the fibroblast and myeloid cell compartments. Fibroblasts in ICI-LP were enriched for IGF1, FGF7, and androgen-response-associated programs, whereas myeloid cells exhibited amplified JAK-STAT and interferon-responsive states spanning both type I and type II interferon signatures. The potential role of androgen response in shaping lichenoid inflammation was supported by a striking loss of androgen receptor expression in lesional keratinocytes by immunohistochemistry. Furthermore, using spatial RNA and transcriptomic approaches, we identified anatomically segregated IFNG, IL17A, and IL13 niches within lesional skin, suggesting that regional immune compartmentalization with differences in local immunoregulation may explain the mixed inflammatory features reported in both ICI-LP and LP. Collectively, these data indicate that ICI-LP is not simply a more inflamed form of LP, but a distinct form of the disease with more prominent inflammatory perturbations within stromal and innate immune cell populations.

Understanding HIV transmission in densely populated urban settings is essential to mitigate ongoing epidemic spread. We present a comprehensive analysis of recent HIV transmission dynamics in Greater Mexico City, one of the worlds largest metropolitan areas comprising Mexico City and neighbouring municipalities of the State of Mexico. Drawing from over 7,000 complete pol gene sequences representing around 50% of new cases reported between 2019 and 2022 within the study region, we reconstructed the transmission network based on pairwise genetic distance. We identified ten large transmission clusters exhibiting sustained growth up to the most recent sampling period. We further analysed paired genetic and high- resolution human mobility data using an integrated phylogeographic approach. We observed a heterogeneous pattern of viral spread across the region, supported by an extensive mixing at a wider geographic scale. Across Greater Mexico City, displaying a high population density, HIV transmission is minimally spatially constrained, a pattern likely fuelled by intense human mobility. Thus, population movement weakens isolation by distance in large urban areas even for a chronic infection that is sexually and vertically transmitted. We demonstrate the value of integrating large-scale genetic, epidemiological, and mobility data to resolve contemporary HIV transmission dynamics in densely populated urban settings