BACKGROUND:Social dysfunction is a core symptom of autism spectrum disorder (ASD), including fragile X syndrome (FXS), but its underlying neural circuits and molecular mechanisms remain poorly understood. Previous studies have implicated the amygdala and hippocampus in social behaviour, yet the specific pathways and signalling events linking genetic deficits to behavioural dysfunction have not been fully delineated. METHODS:Using activity-dependent c-Fos mapping, fibre photometry, closed-loop optogenetics, pharmacological inhibition, and shRNA-mediated knockdown, we investigated the role of the BLA-dCA3 projection and ERK signalling in male Fmr1 KO mice, complemented by re-analysis of human ASD snRNA-seq data and whole-cell patch-clamp recordings. FINDINGS:We found that BLA-dCA3 projecting neurons are aberrantly hyperactivated in Fmr1 KO mice during interactions with both novel and familiar mice, and that closed-loop activation of this pathway in WT mice during familiar interaction impairs social discrimination, whereas its inhibition in KO mice rescues the deficit. Additionally, ERK signalling is upregulated in the BLA of both patients with ASD and Fmr1 KO mice; knocking down FMR1 in the adult BLA recapitulates both the social deficit and ERK hyperactivation, while pharmacological ERK inhibition rescues social behaviour and normalises neuronal hyperexcitability. INTERPRETATION:These findings pinpoint the BLA-dCA3 circuit and BLA-specific ERK signalling as critical mediators of social discrimination deficits in FXS. Our study establishes a causal link from FMRP loss to circuit dysfunction and ERK pathway dysregulation, and suggests that targeting this pathway may offer a promising strategy for treating social dysfunction in ASD and FXS. FUNDING:This work was supported by grants from the National Science and Technology Major Project (2025ZD0214701), the National Natural Science Foundation of China (32171014, 31970940, and 32500889), Nanhu Brain-Computer Interface Institute (010904018), and the Zhejiang Provincial Natural Science Foundation of China (LMS25C090004).
BACKGROUND:Growing evidence indicates that early brain development is particularly vulnerable to environmental influences, with early-life air pollution exposure linked to attention problems, anxiety, and depression. In this study, we examined associations of early-life air pollution exposure with eye-tracking-derived measures of cognitive workload and emotion-related attentional bias in school-aged children, while also assessing whether recent exposure was associated with these outcomes. METHODS:This prospective cohort study was conducted within the ongoing ENVIRONAGE birth cohort, which has enrolled over 2400 mother-child pairs. The present study included 196 children aged 9-11 years who had reached the eligible age for follow-up and completed eye-tracking paradigms assessing cognitive workload and subconscious attention bias between September 2021 and November 2023. Residential black carbon (BC), nitrogen dioxide (NO2), and fine particulate matter (PM2.5) exposures were estimated using a high-resolution spatiotemporal modelling framework based on fixed-site monitoring data, land-use/land-cover information, and dispersion modelling. Associations between predefined exposure windows and eye-tracking outcomes were first assessed using multiple linear regression models, followed by Bayesian kernel machine regression distributed lag models (BKMR-DLM) to evaluate multi-pollutant and multi-window exposure-response patterns. FINDINGS:Higher recent residential air pollution exposure was most consistently associated with saccadic outcomes. After correction for multiple testing, an interquartile range (IQR) increase in last-month BC and NO2 exposure was associated with lower saccade velocity (BC: -10.97°/s; 95% CI -18.67, -3.26; NO2: -10.81°/s; 95% CI -18.13, -3.49), and last-month NO2 and PM2.5 exposure were associated with fewer saccades. Early-life exposure windows also showed associations mainly with saccade velocity, including first-trimester BC and PM2.5, whole-pregnancy PM2.5, and first-1000-days BC exposure. Associations with pupil diameter, fixation count, urinary BC, and emotion-related attention-bias outcomes did not remain statistically significant after correction for multiple testing. INTERPRETATION:Using objective eye-tracking outcomes within a prospective birth cohort, our findings suggest that residential air pollution exposure is associated with subtle oculomotor differences in school-aged children, particularly patterns consistent with increased cognitive workload. Emotion-related attention-bias findings were exploratory after correction for multiple testing. FUNDING:Special Research Fund (BOF), Flemish Scientific Research Fund (FWO), Methusalem, and Horizon Europe project MISTRAL.
Background Alterations in gut microbiome composition have been associated with multiple sclerosis (MS), but their impact on disease severity and early progression remains poorly understood. In this study we investigated whether gut microbiome profiling at diagnosis could identify microbial signatures associated with clinical and radiological features of early MS and provide prognostic information. Methods We analysed the gut microbiome of 53 treatment-naïve patients with MS (pwMS) and 55 healthy donors (HD) using shotgun metagenomic sequencing, combined with clinical features collected over 1 year from diagnosis. To clarify whether gut microbiome composition at MS onset could have prognostic relevance, pwMS were stratified according to lesion burden, lesion localisation, and magnetic resonance imaging (MRI) activity. Findings Overall beta diversity in Bacteria, Archaea, and Eukarya differed significantly between pwMS and HD (p-value <0.001, <0.02, <0.03, respectively). Within the MS group, glucocorticoid treatment at disease onset was the clinical factor most strongly associated with gut microbiota diversity. Stratification according to lesion burden, lesion localisation, and MRI activity identified two clinically distinct MS subgroups with different baseline clinical characteristics at onset (p-value <0.03) and different risk of early disease progression. The cluster associated with an unfavourable prognosis showed greater progression within 12 months and was enriched for motor symptoms and spinal cord lesions at diagnosis. Interpretation Our findings suggest that gut microbiome alterations are detectable at the earliest stages of MS and are associated with clinical and radiological features linked to short-term disease evolution. Gut microbial profiling may therefore represent a promising early prognostic biomarker and may help to identify candidate targets for early intervention and therapeutic development in MS, although further validation in larger longitudinal cohorts is needed. Funding This study was supported by grants from the Italian Multiple Sclerosis Foundation, the Cassa di Risparmio di Torino Foundation, and the Italian Ministry of University and Research.
BACKGROUND:Alzheimer's disease and related dementias (ADRD) affect nearly 6.9 million Americans, with the number expected to triple by 2050, while disease-modifying therapies remain unavailable. Drug repurposing, which identifies new indications for already approved medications, offers a more efficient and cost-effective pathway to accelerate development of effective therapies for ADRD. The aim of this study is to identify potential drug repurposing signals by systematically screening routinely prescribed drugs for associations with progression from mild cognitive impairment (MCI) to ADRD. METHODS:We conducted a multi-site target trial emulation using electronic health record (EHR) data from four decentralised databases: INSIGHT Clinical Research Network, OneFlorida + Clinical Research Consortium, the University of Pennsylvania Health System, and Yale New Haven Health System. We performed an independent validation using EHR data from the TriNetX Research Network and a genetic risk-stratified sensitivity analysis in the Penn Medicine BioBank (PMBB) database. Eligible participants were adults aged 50 years or older at the time of MCI diagnosis, with no prior diagnosis of ADRD and no prior use of the trial drugs. Initiation of each of 181 routinely prescribed drugs was compared with two active control groups defined by initiation of supplements or cardiovascular medications. Risk ratios (RRs) and 95% CIs were estimated using a federated target trial emulation framework (LATTE) with stabilised inverse probability of treatment weighting and Poisson regression. FINDINGS:A total of 122,972 eligible patients were identified from the four decentralised databases, 335,506 patients identified from the TriNetX network for validation and 898 from PMBB database. Federated, multi-site target trial emulation identified 20 drug repurposing hypotheses with statistically significant protective effects, including anti-inflammatory and pain-modulating agents (celecoxib: RR 0.43; 95% CI: 0.23-0.81; dexamethasone RR 0.46; 95% CI: 0.29-0.73; gabapentin: RR 0.55; 95% CI: 0.36-0.83; ketorolac: RR 0.50; 95% CI: 0.31-0.80; methylprednisolone: RR 0.43; 95% CI: 0.24-0.76; prednisone: RR 0.48; 95% CI: 0.28-0.83; pregabalin: RR 0.53; 95% CI: 0.35-0.79), antimicrobial and microbiome-associated agents (cefazolin: RR 0.62; 95% CI: 0.45-0.84; clavulanate: RR 0.56; 95% CI: 0.44-0.71; fluconazole: RR 0.36; 95% CI: 0.23-0.58), neuromodulators and adrenergic agents (epinephrine: RR 0.42; 95% CI: 0.31-0.56; propranolol: RR 0.56; 95% CI: 0.37-0.85; salmeterol: RR 0.49; 95% CI: 0.32-0.74; tizanidine: RR 0.29; 95% CI: 0.14-0.57), vascular, metabolic, and hormonal modulators (empagliflozin: RR 0.29; 95% CI: 0.17-0.50; oestradiol: RR 0.47; 95% CI: 0.28-0.81; ezetimibe: RR 0.69; 95% CI: 0.52-0.91; sodium bicarbonate: RR 0.49; 95% CI: 0.29-0.84; spironolactone: RR 0.43; 95% CI: 0.31-0.60), and histamine-related and gastrointestinal agents (famotidine: RR 0.64; 95% CI: 0.55-0.74). Results were consistent in the independent validation using TriNetX network and sensitivity analysis in PMBB database. INTERPRETATION:20 widely used medications may be associated with reduced progression from MCI to ADRD and represent promising candidates for clinical evaluation as repurposed therapies for dementia. FUNDING:National Institutes of Health.
Drug development is slow, costly, and prone to late-stage failure, in part because animal models poorly predict human responses. Two human-relevant technologies are maturing in parallel: biological avatars, defined as patient- or stem-cell-derived models such as organoids and organ-on-a-chip systems, and digital twins, defined as computational models that integrate a patient’s molecular and clinical data to forecast treatment responses. We propose the ex vivo clinical trial concept, in which an avatar and a digital twin are coupled in an iterative loop so that laboratory measurements refine the computational prediction and the prediction guides the next experiment, allowing candidate therapies to be tested and prioritised before a patient is exposed. We review the platforms, their predictive performance in cancer, cystic fibrosis, and liver toxicity, the conditions under which they fail, and the qualification, turnaround, and standardisation requirements that must be met before such trials can inform drug development or clinical care.
BACKGROUND:Diabetes mellitus is a common but incompletely characterised manifestation of mitochondrial diseases (MD). Data on risk factors, clinical course, and treatment recommendations are lacking. METHODS:In this multinational cohort study, we analysed longitudinal data of patients with a genetically confirmed MD from the GENOMIT registry included at German, Austrian, and Italian sites between 07/2009-01/2025. Our objectives were to (1) expand the genetic spectrum of mitochondrial diabetes mellitus (mDM), (2) identify risk factors, (3) delineate the clinical course, and (4) characterise real-world use of antidiabetic therapies. FINDINGS:Of 2399 patients, 1225 (51%) were female, and 281 (12%; 172 female) had mDM. Diabetes occurred across 31 genotypes and exhibited marked genotype dependence, with the highest prevalence in m.3243A>G carriers (177/360 [49%]). Only the m.3243A>G variant was associated with a significantly increased risk of mDM (HR = 10.3; 95% CI 5.2-20.4, p < 0.0001), whereas single mtDNA deletions, multiple mtDNA deletions, and primary LHON variants, as well as sex, BMI, ethnicity, smoking, hypertension and dyslipidaemia did not show a significant association. Median diabetes onset in patients with the m.3243A>G variant was at 47.7 years (SD 45.2-52.0). Among patients with mDM, 140/281 (50%) used insulin, and 111/281 (40%) received non-insulin antidiabetic drugs, most commonly metformin, which was discontinued in 8/50 users. Literature review revealed neurological events temporally linked to metformin application in m.3243A>G carriers, though long-term use without adverse events was likewise reported. INTERPRETATION:mDM is frequent in patients with MD, and the individual risk is strongly genotype dependent. While caution is warranted, our data do not justify universal avoidance of metformin; prospective, genotype-informed studies are needed to guide management. FUNDING:German Ministry of Research, Technology and Space; Italian Ministry of Health; European Union.
BACKGROUND:Novel diagnostic solutions using host-response-based gene signatures to differentiate between individuals infected with Mycobacterium tuberculosis presenting with active tuberculosis disease (ATB), individuals infected with the bacterium in the absence of active tuberculosis disease (TBI), and individuals with no evidence of ATB or TBI (no TB) have demonstrated limited utility. However, the impact of age-related immunological changes on diagnostic performance remains unclear. METHODS:Using blood samples collected from 119 'adolescent/young adults' aged 10-24 years, 259 'adults' aged 25-55 years, and 79 'older adults' aged 56 years and above we explored differences in expression of eight gene targets using a novel research-use-only Cepheid Xpert TB/LTBI assay. We plotted relative expression for each gene by age stratified by TB status, then constructed two composite classifiers using a subset of gene targets. These composite classifiers were compared using AUCs derived from logistic regression models fitted within each age stratum. FINDINGS:Expression of IL2, IFNG, and MIG appeared to best differentiate individuals who were classified as TBI or ATB from no TB and were used to construct an 'exposure' classifier which yielded an AUC of 0.89 (95% CI 0.83-0.96) among adolescent/young adults, 0.82 (95% CI 0.76-0.87) among adults, and 0.71 (95% CI 0.58-0.84) among older adults. Similarly, expression of SLPI, VEGFA, PLAU, and GBP5 appeared to best differentiate between individuals who were classified as ATB from TBI or no TB. The corresponding composite 'disease' classifier yielded an AUC of 0.88 (95% CI 0.80-0.96) among adolescent/young adults, 0.74 (95% CI 0.66-0.82) among adults, and 0.56 (95% CI 0.40-0.73) among older adults. INTERPRETATION:This study demonstrates the importance of considering age in the development and evaluation of host-response-based diagnostics for ATB and TBI and suggests that host-response-based diagnostics may prove most useful in differentiation of ATB, TBI, and no TB among adolescent/young adults. FUNDINGS:This study was supported by the US Department of Defence (award number W81XWH-18-1-0253) and National Institutes of Health (award number R01AI137681). Salary support was received from the National Institutes of Health (training grant number T32AI007384).
BACKGROUND:Patients with Major Depressive Disorder (MDD) exhibit biased information processing. This study investigates the clinical and neural efficacy of a cognitive bias modification (CBM) training in patients and healthy control (HCS), fostering processing of positive emotion stimuli. METHODS:In a single-blind randomised controlled trial (DRKS00029756), MDD outpatients and HCS, aged 18-60 years, were randomised to positivity training (PT) or control training (CT). Randomisation was carried out by study assistants, blinding researchers. Participants underwent 10 tablet-based dot-probe sessions over 14 days. PT implicitly redirected attention toward positive stimuli to improve depressive symptoms. Primary outcome was pre and post-training EEG-derived Early Posterior Negativity (EPN), investigating neural sensitivity towards positive stimuli. Secondary clinical outcomes included changes in depression symptoms. FINDINGS:From February 2023 to October 2024, 240 participants were included (119 MDD; 121 HCS). 62 MDD and 61 HCS underwent PT; 57 MDD and 60 HCS received CT. In MDD, EPN to positive high arousal stimuli revealed an interaction between time (pre/post) and training (PT/CT), F(1,97) = 5.017, p < 0.028, η2 = 0.049. The between-treatment difference was 1.65 μV, 95% CI [0.19, 3.11]. EPN amplitudes shifted towards negativity in PT and positivity in CT. Depression symptom decreased from pre to post and from pre to follow-up. With respect to adverse events, one patient in the control training was regularly admitted to hospital. INTERPRETATION:CBM positivity training was associated with neural changes in MDD, supporting its potential to target pre-attentive positive emotion processing. Further EEG follow-up and higher stimulus contrasts in the training conditions may clarify clinical relevance. FUNDING:Funded by DFG (ID: 507720021).
BACKGROUND:Incomplete postmenopausal breast involution leaves persistent epithelial-rich lobules and elevated breast density in about 40% of women and is associated with higher breast cancer risk, but why remodelling stalls remains unclear. METHODS:We studied a longitudinal cohort of 81 women with paired benign breast biopsies (baseline age 45-55 years; follow-up 2-10 years), all with baseline NanoString transcriptomics and two-timepoint digital morphometry, and with multiplex immunofluorescence in spatial-imaging subsets (baseline n = 14-16 depending on panel; follow-up n = 14). A separate postmenopausal endpoint cohort (12 women: eight noninvoluted, four completely involuted), profiled by genome-wide expression array and multiplex immunofluorescence, defined the persistent-lobule phenotype. FINDINGS:Noninvoluted postmenopausal tissue retained a proliferation-competent, tumour-associated epithelial state and showed immune accumulation at lobular boundaries with reduced access to p16+ (senescence-associated) epithelial foci. The same SASP and innate immune programmes that predicted slower involution across the menopausal transition predicted faster involution after menopause. Follow-up boundary CD45→p16 engagement was directionally consistent with this reversal in Pre→Post and Post→Post women. Spatial imaging resolved this reversal into a perimenopausal stall architecture and a postmenopausal clearance-associated architecture marked by direct CD16+ innate-effector engagement of p16+ epithelium; macrophage targeting provided convergent support (two-sided exact permutation interaction p = 0.0077). INTERPRETATION:Menopausal timing conditions whether senescent-immune programmes couple to productive clearance or to spatially uncoupled surveillance and persistent risk-associated tissue. Biomarker interpretation should therefore be anchored to menopausal timing. FUNDING:Casey DeSantis Cancer Fund and US National Cancer Institute.
Background Variants in STX1B/syntaxin-1B are linked to a spectrum of fever-associated epilepsy syndromes. While studies in murine models have provided mechanistic insights, their relevance to human disease in a heterozygous context may be limited. Methods We investigated two pathogenic STX1B variants using isolated single neurons and neuronal network cultures derived from patient-specific induced pluripotent stem cells. These carried either a de novo p.G226R variant, associated with severe developmental epilepsy, or an InDel variant (p.K45delinsRCMIE/p.L46M) linked to a transient familial seizure syndrome. Synaptic function and network excitability were assessed using patch-clamp and multi-electrode array recordings, alongside morphological and transcriptomic profiling. Findings G226R exhibited both gain- and loss-of-function characteristics, with increased miniature excitatory postsynaptic current frequency in networks but not in autapses, and synaptic failure during sustained high-frequency stimulation. For the InDel variant, the predicted loss-of-function phenotype based on reduced syntaxin-1B levels was not detectable at the single-cell level, likely masked by compensatory synaptic upregulation. At the network level, however, both variants were associated with neuronal hyperexcitability, characterised by more frequent and prolonged bursting activity, with a much stronger phenotype in G226R-containing networks. Transcriptomic profiling revealed a differential dysregulation of synaptic and other neuronal genes. Interpretation The divergence between morphological, electrophysiological and transcriptomic findings suggests that compensatory mechanisms may contribute to network hyperexcitability. Initially engaged to maintain homoeostasis, they may ultimately contribute to a pathological network state. The graded severity of network alterations across STX1B variants correlates with the clinical phenotypes. Funding BMBF (Treat ION-01GM2210A, SNAREopathies-01EW1809A), 2023 FEBS Summer Fellowship, Fortüne programme (2610-0-0), EKFS college precise.net, Open Access Publishing Fund of University of Tübingen.
BACKGROUND:Early differentiation of multiple system atrophy (MSA) from Parkinson's disease (PD) remains difficult, particularly within two years of symptom onset, when diagnostic uncertainty has major implications for prognosis, referral, and trial enrolment. Because MSA is rare, previous biomarker studies have often been limited by relatively small samples and restricted multicentre validation. We aimed to determine the diagnostic performance of plasma neurofilament light chain (NfL) for differentiating MSA from PD and to assess the incremental value of glial fibrillary acidic protein (GFAP), total tau (t-tau), and phosphorylated tau at threonine 217 (p-tau217). METHODS:In this multicentre cross-sectional diagnostic study, participants were enrolled from five movement-disorder referral centres in China between Jan 1, 2018, and June 30, 2024, and were divided by enrolment period into discovery and temporally separated validation datasets. Plasma NfL, GFAP, t-tau, and p-tau217 were measured using light-initiated chemiluminescence assays. Group comparisons used age- and sex-adjusted models, and discrimination was assessed using receiver-operating-characteristic analysis with sensitivity, specificity, predictive values, and robustness analyses. FINDINGS:The analysis included 2408 participants: 782 (32.5%) with PD, 796 (33.1%) with MSA, and 830 (34.5%) healthy controls. NfL was the best single biomarker for differentiating MSA from PD in the discovery dataset (AUC 0.920, 95% CI 0.903-0.936). The discovery-derived cutoff of 41.3 pg/mL yielded sensitivity of 90.5% and specificity of 83.4% in the discovery dataset, and sensitivity of 86.7% and specificity of 85.5% in the validation dataset (AUC 0.924, 95% CI 0.898-0.948). In the early-stage subgroup, NfL retained strong performance (AUC 0.943, 95% CI 0.915-0.966). Integrated multimarker models provided limited incremental discrimination over NfL alone. INTERPRETATION:Plasma NfL may support the differentiation between clinically diagnosed MSA and PD, including early in the disease course. The limited added value of multimarker panels supports a simpler and more immediately translatable NfL-first strategy for diagnostically uncertain parkinsonism. FUNDING:National Natural Science Foundation of China; the Capital's Fund for Health Improvement and Research; Beijing Natural Science Foundation; Beijing Municipal Science and Technology Commission; Beijing Neurosurgical Institute; Beijing Traditional Chinese Medicine Science and Technology Development Fund.
Background Hepatitis B virus (HBV) integration represents a major obstacle to curing HBV; however, the landscape of HBV integration and local immune response to transcriptionally active viral integration in children with chronic HBV infection remain unclear. Herein, we aimed to elucidate this landscape in this population. Methods Genomic analyses using a probe-based capture strategy were performed on 18 children and 28 adults with chronic HBV infection. Spatial transcriptomics (ST) was performed on 12 children from our cohort and 3 adults from a public database. Findings All patients were hepatitis B e antigen (HBeAg)-positive and treatment-naïve. Genomically, children exhibited significantly lower clonal expansion level of HBV-integrated hepatocytes than adults, despite comparable unique breakpoint counts. After adjusting for confounding variables, age was identified as an independent risk factor for total frequency of unique integration breakpoints (b = 3.22, P = 0.005). Spatially, ST revealed that spots with transcriptionally active viral integration exhibited a sparse distribution and accounted for a low proportion of all spots in children. Notably, at these spots, children showed reduced adaptive immune cells (e.g., CD8+ T cells) but increased innate components (myeloid cells, Kupffer cells, activated dendritic cells) and APC co-stimulation, whereas adults exhibited a uniform reduction of immune cell populations. Interpretation Compared with adults, children exhibit lower clonal expansion of HBV-integrated hepatocytes and distinct immune profiles in response to transcriptionally active viral integration, offering new insights into their differing clinical course. Funding Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education).
Background Single-cell and single-nucleus RNA sequencing have transformed our understanding of human skeletal muscle biology, yet reproducibility and cross-study comparison remain limited by the lack of a unified reference framework and consistent cell-type annotation. Methods We systematically searched for scRNA-seq and snRNA-seq datasets from adult human skeletal muscle. Seven eligible studies were retrieved and harmonised. We benchmarked multiple integration strategies to construct a joint reference atlas and derived modality-aware marker panels. Selected findings were validated by immunofluorescence in muscle biopsies. Findings We generated a harmonised atlas comprising 122,000 cells and 630,000 nuclei from 88 healthy individuals and resolved 17 major skeletal muscle cell populations, spanning mononuclear compartments and multinucleated myofibers. Cross-modality analysis identified tissue- and modality-aware marker panels and nominated both established and previously unrecognised markers. NOVA1 emerged as a selective marker of fibro-adipogenic progenitors and was validated at the transcript and protein levels. Focusing on myonuclei, pseudotime modelling reconstructed differentiation trajectories from quiescent muscle stem cells to mature type I and type II myofibers and revealed lineage-specific programs, including transient activation of protocadherin-γ genes during type I myofiber differentiation. We further provide an interactive web application for marker-based cell-type prediction using the reference atlas. Interpretation This integrated reference atlas and accompanying annotation tool establish a standardised framework for human muscle transcriptomics, promoting consistent cell-type assignment and providing a baseline for future studies of muscle development, ageing, and disease. Funding Else Kröner-Fresenius-Stiftung and the German Research Foundation.
BACKGROUND:A heterologous Ad26.Mos4.HIV and clade C gp140 vaccine regimen did not show overall significant efficacy against HIV-1 acquisition [point estimate 14.1%; 95% confidence interval (CI), -22.0 to 39.5] in the HVTN 705/HPX2008 trial in southern African women. We examined whether and how vaccine efficacy (VE) against HIV-1 diagnosis over 7-24 months post-first dose varied by HIV-1 Envelope (Env) amino acid sequence features. METHODS:HIV-1 viral sequences were generated by PacBio SMRT-UMI sequencing from the first RNA-positive sample of participants who acquired HIV-1. Env amino acid sequence features were prespecified for analyses based on 1) being hypothesised to impact VE; and 2) having sufficient variability. Sieve analyses assessed VE by a single representative sequence and by viral population composition. FINDINGS:The majority of Env features showed no evidence of differential VE, with only two signals having familywise error rate (FWER) P-values <0.10. In single-sequence analyses, VE declined with increasing physicochemical-weighted Hamming distance from the C97ZA vaccine insert in clade C broadly neutralising antibody resistance-associated signature positions (FWER P = 0.08). Sequence-predicted Env structural features showed no significant vaccine vs. placebo differences in structural divergence from the C97ZA vaccine-insert Env sequence. In multi-sequence analyses (median 121 sequences/individual), VE was higher against viral populations with ≥99% vs. <99% L832 prevalence (VE = 91.7%; 95% CI, 67.4-97.9 vs. VE = -7.0%; 95% CI, -55.5 to 26.4) (unadjusted P = 0.0002 for differential VE, FWER P = 0.023). INTERPRETATION:Despite extensive prespecified and exploratory analyses including Env features supported by prior studies to potentially impact VE, there was only limited, weak evidence that Env sequence features modified VE in HVTN 705. Although previous work suggested a protective role of IgG3 binding to V1V2 in a small subgroup of vaccine recipients, a V1V2 sieve signal was absent. FUNDING:National Institutes of Health and Johnson & Johnson.
Background The Pfizer-BioNTech coronavirus vaccine (BNT162b2) was among the first nanoparticle-based vaccines approved by the World Health Organisation (WHO) and demonstrated 95% efficacy against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. Despite its success, the precise immune mechanism behind its effectiveness remains poorly understood. This study investigated the early immune responses occurring in the draining lymph node (dLN) following vaccination. Methods A well-established murine vaccination model was used to investigate the distribution and immunological effects of BNT162b2 in vivo. Vaccine trafficking to the dLN, cellular uptake, and spike protein expression were assessed following immunisation. Single-cell transcriptomic analyses and functional in vivo experiments were performed to identify the immune cell populations involved in orchestrating vaccine-induced responses and to characterise their interactions with adaptive immune cells. Findings BNT162b2 was rapidly transported to the dLN, where it was predominantly captured by leukocytes that subsequently expressed the SARS-CoV-2 spike protein. Among these cells, plasmacytoid dendritic cells (pDCs) emerged as regulators involved in both inflammatory and humoural immune responses. Single-cell transcriptomic profiling revealed active interactions between pDCs and CD8+ T cells. Functional in vivo studies further demonstrated that pDCs promoted CD8+ T-cell activation and expansion, indicating an involvement in shaping adaptive immunity following vaccination. Interpretation These findings identify pDCs as antigen-presenting cells involved in coordinating the immune response to BNT162b2. By regulating both innate and adaptive immune pathways and facilitating CD8+ T-cell activation, pDCs appear to play a functional role in the efficacy of this mRNA vaccine. This study provides additional insights into the immunological processes underlying mRNA vaccine-induced protection and may inform the future design and optimisation of mRNA-based immunotherapies and vaccines. Funding Swiss National Science Foundation, Leonardo Foundation.
BACKGROUND:Insulin resistance is recognised as a midlife risk factor for cognitive decline, yet the pathways linking metabolic dysfunction to early brain changes remain unclear. METHODS:We cross-sectionally analysed 355 cognitively normal adults from the PREVENT cohort to test associations between insulin sensitivity (Homoeostatic Model Assessment for Insulin Resistance; HOMA-IR), frontal white matter hyperintensities (WMH), cerebral blood flow (CBF), hippocampal volume, and cognition. FINDINGS:Multivariable regression showed higher log-transformed HOMA-IR was associated with greater frontal WMH burden (β = 0.118, p = 0.026) and lower global cognitive performance (β = -0.132, p = 0.012). Decreased insulin sensitivity was not associated with global CBF (β = -0.019, p = 0.74). Adjusting for WMH burden, hippocampal volume, and CBF, lower insulin sensitivity remained associated with lower global cognition (β = -0.123, p = 0.021). Structural equation modelling (n = 328) demonstrated a direct negative association between higher HOMA-IR and cognition (β = -0.055, p = 0.042) and trended toward higher vascular burden (p = 0.06). The indirect pathway through vascular burden was non-significant (p = 0.23), as vascular burden, hippocampal volume, and CBF did not associate with cognition. INTERPRETATION:Decreased insulin sensitivity was linked to early small vessel disease and measurable cognitive differences, suggesting the cognitive association was largely direct rather than explained by vascular injury, hippocampal atrophy, or global perfusion. These findings point toward partially parallel metabolic and vascular pathways rather than a sequential process. These cross-sectional associations suggest that insulin sensitivity warrants investigation as a modifiable midlife factor for cognitive health; interventional studies are needed to determine whether targeting it preserves cognition before neurodegenerative markers emerge. FUNDING:MRC Dementias Platform UK, NIHR, Alzheimer's Society, Alzheimer's Association, Race Against Dementia, and HRB.
BACKGROUND:Multiple sclerosis (MS) is increasingly recognised as a disorder of large-scale brain network reorganisation rather than a disease explained solely by focal demyelinating lesions. However, the relevance of structural network abnormalities to clinical heterogeneity and progression remains unclear. METHODS:We analysed 3T magnetic resonance imaging (MRI) from two independent MS cohorts (total n = 635): Dataset 1 from the Chinese neuroimmunological diseases (NIDBase) cohort (163 MS and 248 healthy controls [HC]) and Dataset 2 from the UK Biobank (117 MS and 107 HC). A subset of Dataset 1 underwent 256-channel resting-state high-density electroencephalography (hd-EEG) (135 MS and 80 HC). We constructed structural covariance networks (iSCNs) from 3D T1-weighted MRI using Kullback-Leibler similarity across 170 Automated Anatomical Labelling atlas 3 (AAL3) regions. Patients were stratified by disability, cognition, and disease activity; a subgroup with no evidence of disease activity (NEDA) with 1-year follow-up MRI (n = 33) was analysed longitudinally. Linear support vector machine classifiers evaluated topological and connectivity features for diagnosis and clinical stratification. FINDINGS:MS showed reproducible topological and connectivity abnormalities, involving thalamic and subcortical hubs and altered visual-network-related couplings. Disability showed the broadest abnormalities, whereas cognitive impairment and disease activity were associated with more selective changes. Patients meeting NEDA criteria showed subtle longitudinal nodal changes. Connectivity features performed best for MS-vs-HC discrimination, whereas topological features performed better for clinical stratification. INTERPRETATION:The iSCN approach identified reliable patterns of topological and connectivity impairment across MS and its clinical stratifications, providing insight into MS neuropathology and guiding future diagnostic and therapeutic biomarker development. FUNDING:This work was funded by Beijing Research Ward Excellence Program (BRWEP2024W022010104, BRWEP2024W022010109), Beijing Scholar program (No. 106), the Project for Innovation and Development of Beijing Municipal Geriatric Medical Research Center (11000023T000002041657), Dengfeng Talent Program (DFL20220701), National Natural Science Foundation of China (82571539, 82501612), Xuanwu Hospital Talent Convergence Program-Leading Talents (HZ2021ZCLJ008), the Beijing Hospitals Authority's Ascent Plan (DFL20240801), and Beijing "Huizhi" Talent Program, Cultivation Program-Leading Talents (HZ2025PYLJ003).
BACKGROUND:Early cancer diagnosis in patients with non-specific symptoms is limited by the lack of discriminatory tests. Within the Oxfordshire Suspected CANcer (SCAN) pathway, exploratory biomarker work showed that serum 1H NMR-based metabolomics can identify cancer with high accuracy. SCAN2 evaluated whether integrating metabolomics with glycomics provides complementary molecular information and improves discrimination in a clinically complex, real-world population. METHODS:Serum from 369 SCAN patients (59 cancers) was analysed using AXINON® System-derived NMR metabolomics and HPLC-MS glycomics. Machine-learning models were trained to predict cancer status, with performance assessed by receiver operating characteristic (ROC) analysis of pooled cross-validated predictions. To place cancer risk in a broader clinical context, a second classifier modelling alternative non-cancer diagnosis was incorporated, and mean predicted probabilities from both models were jointly projected into a two-dimensional space, maintaining strict separation of training and test data. FINDINGS:In the full cohort, integration of glycomics with metabolomics achieved an AUC of 0.814 (95% CI 0.808-0.820). In a refined sub-cohort excluding major comorbidities and selected cancer types (32 cancers, 277 non-cancers), performance improved to an AUC of 0.884 (95% CI 0.879-0.890). Discriminatory features included cancer-associated biantennary fucosylated glycans alongside amino acid metabolites (glutamate, histidine) and lipoprotein-related measures. A classifier distinguishing metastatic from non-metastatic disease (n = 29 vs. 30) achieved an AUC of 0.80. Joint probability analysis in the full cohort preserved cancer-associated signatures across comorbidity burden, with projection-based classification achieving an accuracy of 89.2% (95% CI 85.7-92.6). INTERPRETATION:These findings validate the SCAN1 metabolomic signature in a more clinically complex cohort and indicate that integrating glycomics with metabolomics provides complementary biological information for cancer discrimination. Joint probability analysis provides an interpretable framework for cancer risk stratification within multimorbid diagnostic pathways, supporting the clinical potential of scalable multi-omics blood testing. FUNDING:EPSRC, EU Horizon 2020, Wellcome/MLSTF, Novo Nordisk Foundation.
BACKGROUND:Spinocerebellar Ataxia 27B (SCA27B) is a novel, frequent and likely treatable late-onset autosomal-dominant ataxia caused by GAA repeat-expansions in FGF14. For understanding disease evolution and imminent trial planning, metrics of the most widely used clinical outcome assessment (Scale for the Assessment and Rating of Ataxia/SARA), longitudinal progression and modifiers thereof are warranted. METHODS:Multicentre intercontinental observational study (2015-2024) of 661 assessments from 219 patients with SCA27B (age: 68 ± 10 years; SARA: 9 ± 6 points) with item-level distribution-based analyses to characterise SARA metrics relative to ageing-related impairment in 390 healthy controls; and linear mixed-effects modelling to determine longitudinal progression and demographic or genetic modifiers. FINDINGS:Ataxia severity in SCA27B as assessed by SARA was primarily attributable to gait, stance, and lower-limb impairment; other ataxia domains scored ≤1 SARA point in 79-94% of patients. Discrimination of SCA27B motor performance from controls decreased with age due to ageing-related motor variability captured by SARA, thus limiting potential metric response windows for symptomatic treatments. Disease progression was faster in the presence of interfering ageing-related comorbidities in 14 (6%) patients. Overall longitudinal progression of SCA27B was 0.54 SARA points/year [95% CI: 0.37-0.71]. Expansions of (GAA)> 180 repeats were frequent also on the shorter allele (n = 18 (8%), range: 196-348 repeats), and associated with faster progression (+1.6 SARA points/year, [95% CI: 0.9-2.2]), including also otherwise less affected ataxia domains speech and sitting. INTERPRETATION:Disease progression in SCA27B is characterised by mild progression, ageing-related motor variabilities and comorbidities, and associated with repeat size on both alleles. FUNDING:Else-Kröner-Fresenius-Stiftung, EU, DFG, BMBF, CIHR, NAF, Ataxia-UK, CSC.
