EBioMedicine最新文献

Background: The HIV reservoir was once considered to be transcriptionally silent. Evidence is emerging that a substantial portion of the reservoir is transcriptionally active. We explore the consequences of transcriptionally active proviruses on the infected T cell by longitudinally monitoring the fate of proviral clones.

Methods: We analysed proviral dynamics by monitoring ∼4000 HIV proviral sequences and ∼13,000 integration site sequences along with ∼2 million T cell receptor (TCR) sequences in up to 9 people living with HIV over time. This analysis includes 7 chronically treated and 2 elite controller participants, with paired TCR sequencing in 6 individuals. We also analysed 9 participants from published cohorts. Our analysis used a Morisita metric to capture contraction and expansion of proviral clones. The role of HIV expression was also investigated by studying the effect of integration site and orientation indirectly in vivo and directly in a cell line model.

Findings: We focus on cell-intrinsic forces and provide evidence that proviral clones contract and expand more in individuals treated during chronic infection compared to elite controllers. Moreover, proviral clones change more than TCR clones suggesting a subset of infected cells may turnover more than uninfected cells. We also provide evidence of two opposing forces, both initiated by HIV expression within the cell, likely contributing to proviral dynamics. These forces could explain the increased changes in proviral clones in a subset of infected cells. Evidence of an expansion force includes an enrichment of sense-oriented proviruses in growth-related genes among large clones. At the same time, there is depletion of sense-oriented proviruses in highly expressed genes, leading to an overall enrichment of antisense.

Interpretation: Our longitudinal analysis of HIV sequences suggests that a subset of HIV-infected cells may divide and die faster than uninfected T cells, contributing to a dynamic reservoir.

Funding: This work was funded by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, United States (R01AI176952, R01AI165368, and R37AI150556).

Background: The dynamic spectrum of tuberculosis (TB) often results in underdiagnosis warranting the need for better diagnostics to accurately detect Mycobacterium tuberculosis (Mtb) in persons with asymptomatic, paucibacillary or extrapulmonary TB, and to identify individuals at high risk of developing TB disease early. This study aimed to evaluate a dual target-based digital droplet PCR (ddPCR) assay to detect circulating cell-free Mtb DNA in plasma of individuals at high risk of developing TB disease and in those lacking a clear diagnosis of TB (asymptomatic or clinically diagnosed TB).

Methods: Forty-six healthy household contacts (HHCs) of patients with pulmonary TB who developed TB within two years of follow-up (Progressors), and 92 HHCs who did not progress to TB (Non-progressors) were included in the study. Plasma was obtained and subjected to testing using a ddPCR assay targeting two M. tuberculosis (Mtb)-specific insertion sequences, IS6110 and IS1081. Sensitivity, specificity, and ROC curves were used to assess the diagnostic performance of the test.

Findings: IS6110 and IS1081 targets were detected in 10/11 asymptomatic TB cases giving a sensitivity of 90.9% (95% CI: 62.3-99.5), and in 9/11 unconfirmed/possible TB cases giving a sensitivity of 81.8% (95% CI: 52.3-96.8). Further, the test detected Mtb-ccfDNA in 15/19 Progressors even at six months prior to TB diagnosis (79.0% sensitivity, 95% CI: 56.7-91.5; 97.8% specificity, 95% CI: 92.4-99.6). Detection rates at 12- and 18-months prior to onset of TB were 55.0% (95% CI: 34.2-74.2) and 50.0% (95% CI: 29.9-70.1), respectively. Notably, the test showed 100% sensitivity (95% CI: 43.9-100.0) in detecting extrapulmonary TB up to six months prior to clinical diagnosis.

Interpretation: The study highlights the potential of ddPCR-based detection of Mtb ccfDNA as a valuable tool for early identification of individuals at risk of developing active TB disease and for clarifying the diagnosis of TB in diagnostically challenging cases. Further validation in a larger cohort will confirm the findings of the study and endorse the utility of the test in clinical practice.

Funding: This work was supported by the Indian Council of Medical Research (Grant number:5/8/5/45/Adhoc/2022/ECD-1). The CTRIUMPh cohort study which provided samples for this study was supported by the NIH/DBT Indo-US Vaccine Action Programme.

Background: The significant clinical and molecular heterogeneity of pulmonary arterial hypertension (PAH) poses challenges in identifying effective therapies. Advanced multidimensional profiling offers an opportunity to capture molecular responses and assess biomarker stability, yet its application in randomised trials remains limited.

Methods: We evaluated the multi-omic profiles of participants with PAH in a randomised, placebo-controlled trial of famotidine. Plasma metabolomic and proteomic profiling was performed at enrolment and 24 weeks. Baseline profiles were compared between treatment arms to assess randomisation balance. Intraclass correlation coefficients quantified within-subject stability over time. Linear regression models adjusting for age, sex, body mass index and PAH aetiology evaluated famotidine's molecular effects. False discovery rate was controlled for multiple comparisons.

Findings: For the 79 participants, baseline multi-omic profiles were similar between groups. At 24 weeks, 34 and 37 participants remained in the famotidine and placebo groups respectively. The placebo group showed high molecular stability, while greater variability was observed in the famotidine group. Famotidine treatment was associated with significant changes across 191 proteomic pathways (q-value <0.05), but no metabolomic changes remained significant after multiple-testing correction.

Interpretation: Integrating multi-omics into a prospective clinical trial is feasible and yields stable longitudinal profiles in the absence of intervention. While famotidine did not yield clinical benefit, associated proteomic changes illustrate how molecular profiling can reveal treatment-related biology and inform future trial design. These findings highlight the broader utility of multi-omics for evaluating drug responses and identifying molecular endotypes in PAH and beyond.

Funding: US National Institutes of Health.

Background: SARS-CoV-2 infection could increase the long-term risk of recurrent chronic obstructive pulmonary disease (COPD) exacerbations. This study investigated the long-term risk of COPD exacerbations following SARS-CoV-2 infection, with comparisons by hospitalisation status.

Methods: We conducted a retrospective cohort study using data from a large urban academic health system (March 2020-February 2025). The final cohort comprised of 2268 hospitalised and 1471 non-hospitalised COVID-19 patients with pre-existing COPD, each matched 1:1 by propensity score with non-COVID controls. Adjusted hazard ratios (aHRs) were estimated using Andersen-Gill models, and adjusted incidence rate ratios (aIRRs) using negative binomial models. Cumulative hazards were derived from Nelson-Aalen curves. Secondary analyses evaluated socioeconomic factors and multiple sensitivity analyses assessed robustness.

Findings: Among hospitalised patients, the incidence rate of COPD exacerbations was 35.7 per 100 person-years in the COVID-19 cohort, compared to 15.9 in controls (aIRR 1.81 [95% CI, 1.45-2.26]). Among non-hospitalised patients, rates were 13.7 vs 10.6 (aIRR 1.23 [0.88-1.73]). Hospitalised patients had a higher overall hazard of recurrent COPD exacerbations (aHR 1.69 [1.36-2.10]; p < 0.001), with risk persisting over four years post-infection. No significant difference was observed among non-hospitalised patients. Unmet social needs increased the risk by 53% among hospitalised patients, while Medicaid or Medicare coverage more than doubled the risk among non-hospitalised patients relative to private insurance. Findings were consistent across multiple sensitivity analyses.

Interpretation: COVID-19 hospitalisation was associated with a sustained increased risk of recurrent COPD exacerbations, underscoring the need for long-term pulmonary follow-up and targeted interventions in this high-risk population.

Funding: None.

Background: Pregnancy requires precisely timed immune adaptations to maintain foetal tolerance while enabling timely initiation of labour, a process often conceptualised as the 'immune clock' of pregnancy. Disruption of this immune clock contributes to adverse obstetric outcomes. While maternal opioid use disorder (OUD) is a recognised risk factor for poor maternal and neonatal health, its impact on maternal immune landscape at delivery remains poorly understood.

Methods: We analysed peripheral blood collected from pregnant individuals with and without OUD at time of admission for delivery before the onset of active labour. We employed multiparameter flow cytometry, cytokine profiling, and single-cell-RNA sequencing to capture changes in cellular composition, functional responses, and intercellular signalling networks. Given the high prevalence of hepatitis C (HCV) in this population, we stratified our findings by maternal HCV status.

Findings: Clinically, maternal OUD was linked to greater use of labour induction and a smaller stature of newborns. Immunophenotyping revealed a shift toward systemic inflammation, with expansion of memory T and B cells, inflammatory monocytes, and NK cells. Cytokine assays demonstrated dysregulated responses to stimulation, consistent with immune tolerance or exhaustion. Single cell transcriptomic mapping identified disrupted communication networks, suggesting impaired cytokine crosstalk as a central mechanism of immune dysregulation.

Interpretation: Collectively, our findings demonstrate that maternal OUD, with or without HCV co-infection, is associated with altered circulating maternal immunity at term. This pro-inflammatory, dysregulated immune state may underlie increased obstetric morbidity and highlights potential immunologic pathways that can be targeted for intervention in high-risk pregnancies.

Funding: This study was supported by grants from the National Institutes of Health: 1R01DA059152-01 (IM and JO), 7R01AI145910-05S1(IM), TL1TR001997 (HT) and pilot funding from the University of Kentucky, including the Clinical and Translational Science Substance Use Disorder pilot grant 3210003238 (IM and JO). This research was indirectly supported by the Kentucky Opioid Response Effort (KORE) via Substance Abuse and Mental Health Services Administration (SAMHSA) Grants, H79TI081704, H79TI083283, as well as the data management system that is hosted by UK with grant support from NIH CTSA UL1TR001998. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the University of Kentucky.

Background: Sleep traits, including sleep apnoea (SA), insomnia, daytime sleepiness, and snoring, frequently co-occur with cardiometabolic diseases (CMDs), with shared genetic factors suspected to underlie these associations. However, the contribution of shared genetic determinants to these associations is not fully understood.

Methods: We conducted a genome-wide pleiotropic association study applying sequential genetic methods to identify shared genetic variants, genes, pathways and causal associations between the four sleep traits and seven CMDs, including LDSC, high-definition likelihood analysis, colocalisation, gene-based tests, enrichment analysis and Mendelian randomisation. Next, validation of those pleiotropic variants was performed in individuals from the All of Us and MVP studies.

Findings: Among 28 pairs of sleep traits and CMDs, 25 showed significant genetic correlations. Pleiotropic analysis identified 754 independent SNPs (691 unique) and 102 colocalized loci (85 unique). Among these, 47 SNPs (44 unique) were validated as significantly associated with both traits in the pairs, and notably, rs429358 (19q13.32, APOE) demonstrated pleiotropic effects across SA, insomnia and type 2 diabetes (T2D). Forty-eight annotated genes were validated by gene-based tests. Shared genes were enriched in phenotypes related to mortality and growth. Pathway analysis highlighted Cushing syndrome, hormone secretion, and cGMP-PKG, Ras and calcium signalling pathways. After adjusting for glycaemic traits and blood pressure, genetically predicted T2D increased risk of SA, sleepiness, and snoring. Conversely, SA was positively associated with heart failure and T2D independently.

Interpretation: This study of sleep traits and CMDs reveals shared genetic determinants that may partially explain their epidemiologic association and suggests potential treatment targets.

Funding: Described in Acknowledgements.

Background: Genetic diagnosis plays a critical role in enhancing the identification and clinical management of pediatric hearing loss, ultimately improving both physiological outcomes and social-emotional development. As one of the most prevalent sensory disorders characterized by substantial genetic heterogeneity, hearing loss requires the implementation of efficient diagnostic approaches to inform targeted clinical interventions and personalized care strategies.

Methods: Here, we recruited 3353 Han Chinese children with nonsyndromic hearing loss, including 598 multiplex cases with family history. We employed SNPscan, targeted panel sequencing (TPS), and whole-exome sequencing (WES) to delineate the mutation landscape.

Findings: Utilizing a tiered genomic testing strategy, we performed SNPscan for all 3353 participants, TPS for 675 cases, and WES for 204 multiplex cases. We achieved an overall diagnostic yield of 48.3% (1620/3353) in this cohort. Our analysis identified 87 previously unreported variants across 24 genes, including a de novo FOXI1 mutation (c.479_481del) linked to Mondini malformation and enlarged vestibular aqueduct, validated through knock-in mouse models. Additionally, we discovered NEU4 as a candidate gene related to hearing loss, with knockout mice and cellular models demonstrating its role in auditory dysfunction via disrupted neuraminidase activity and axonal development. These findings enrich the spectrum of deafness-related genes and provide a new theoretical foundation for diagnosing hearing loss.

Interpretation: This study not only expands the genetic spectrum of hearing loss but also underscores the clinical utility of advanced sequencing in guiding precision therapies and early syndromic surveillance. This study offers a detailed characterization of the genetic landscape of pathogenic variants associated with hearing loss in the Han Chinese population, which will contribute to the design of a cost-effective genetic screening scheme, and also provides valuable insights that contribute to the global understanding of the genetics of hearing loss.

Funding: This work was supported by the Key Program of National Natural Science Foundation of China, the National Key Research and Development Program of China, the National Natural Science Foundation of China and the Major Fundamental Research Program of the Natural Science Foundation of Shandong Province, China.

Background: Cerebral palsy (CP) is a complex neurodevelopmental disorder with both environmental and genetic contributors. Rare genetic variants explain a substantial proportion of CP, but the contribution of common variants remains unclear. We evaluated whether polygenic scores for CP and related traits explain the aetiology of CP.

Methods: We analysed two independent target cohorts: a case-control cohort including people with a confirmed clinical diagnosis of CP from the Australian CP Biobank and population-based controls; and MyCode, a United States healthcare cohort with CP status identified by electronic health records. Only participants of European genetic ancestry were included. CP polygenic scores were constructed using a publicly available discovery genome-wide association meta-analysis of Finnish and UK cohorts (n_cases = 624, n_controls = 495,687) and applied to the target cohorts for out-of-sample prediction. Additional polygenic scores were generated from publicly available genome-wide association studies for seven CP-related traits. Predictive performance was assessed using logistic regression, area under the receiver operating characteristic curve, and variance in CP liability explained.

Findings: The Australian cohort included 525 cases and 20,410 controls, and MyCode 322 cases and 1610 age-matched controls. The combined model of all eight polygenic scores significantly discriminated CP status, explaining 1·3% of CP liability in the Australian cohort (90% CI lower bound 0·82%, padj<0·0001), and 0·78% in MyCode (90% CI lower bound 0·35%, padj<0·0001). CP-specific polygenic scores demonstrated minimal predictive signal, likely reflecting limited GWAS power. Polygenic scores for known CP predisposing factors (birth weight, gestational duration, stroke) showed modest predictive performance, with some cohort differences. Results were similar when the Australian cohort was stratified by monogenic CP diagnosis.

Interpretation: Our findings demonstrate a measurable polygenic contribution to CP and shared genetic influences with predisposing factors, including those traditionally considered environmental, and comorbidities. Common variants appear to contribute broadly to CP susceptibility, highlighting a multifactorial landscape relevant for earlier diagnosis and intervention.

Funding: Cerebral Palsy Alliance Research Foundation, NICHD, NHMRC, MRFF, QIMR Berghofer.

Background: Accurate and equitable prediction of trauma-related in-hospital mortality is critical for guiding clinical decisions and optimising trauma care resources. Traditional severity scoring systems like the Injury Severity Score (ISS) do not account for demographic factors, potentially limiting their fairness and generalisability across diverse populations.

Methods: We developed and externally validated an artificial intelligence (AI) model based on ISS and integrated demographic features (age and sex) to predict in-hospital mortality after trauma. Data from the Korean Trauma Data Bank were used for model development and internal validation, comprising 121,418 patients with trauma aged ≥15 years treated at 19 trauma centres in South Korea (2017-2022). External validation was performed on an independent cohort of 7458 patients from five trauma centres (four in South Korea and one in Australia, 2022-2024). The primary outcome was trauma-related in-hospital mortality. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, accuracy, and balanced accuracy. Fairness was evaluated by comparing AUROC differences across age (<65 vs ≥65 years) and sex (female vs male) subgroups.

Findings: The ISS-based AI model incorporating age and sex achieved high predictive performance (internal validation AUROC, 0.934; external validation AUROC range, 0.901-0.920), outperforming conventional ISS-based methods. The model also demonstrated improved fairness, showing reduced AUROC differences across subgroups (age: 0.068 vs 0.091; sex: 0.021 vs 0.046 for AI model vs ISS, respectively).

Interpretation: Scaling an ISS-based AI model through demographic integration yielded accurate, fair, and generalisable predictions of trauma-related in-hospital mortality. This approach may enhance trauma care decision-making and enable more equitable resource allocation across diverse clinical settings.

Funding: This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2025-RS-2024-00438239) and the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (RS-2024-00509257, Global AI Frontier Lab). In addition, this research was supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (RS-2025-02220492).