Neuron

Patterns of locus coeruleus (LC) activity and norepinephrine (NE) release during non-rapid-eye-movement (NREM) sleep suggest a critical role for the LC-NE system in offline modulation of forebrain circuits. NE transmission promotes synaptic plasticity and is required for memory consolidation, but the field has only begun to uncover how LC activity contributes to coordinated forebrain network dynamics. Hippocampal ripples, a hallmark of memory replay, are temporally coupled with thalamocortical oscillations; however, the circuit mechanisms underlying systems-level consolidation across larger brain networks remain incompletely understood. Here, using multi-site electrophysiology, we examined LC firing in relation to hippocampal ripples in freely behaving rats. LC activity and ripple occurrence were state-dependent and inversely related: heightened arousal was associated with increased LC firing and reduced ripple rates. At finer timescales, LC spiking decreased {approx}1-2 seconds before ripple onset, with the strongest modulation during awake ripples but minimal change during ripple- spindle coupling. These findings reveal state-dependent dynamics of LC-hippocampal interactions, positioning the LC as a key component of a cortical-subcortical network supporting systems-level memory consolidation.

Neuronal migration is a vital process that positions billions of neurons to create a functional brain. To navigate the constrained microenvironments within the cortex, precise control over the nuclear mechanics in migrating neurons is indispensable. Here, we show that Lamin B1 (LB1) regulates neuronal migration by modulating nuclear deformability. Excess LB1 in neurons halted migration without altering laminar identity or overall gene expressions in vivo, while in vitro, it elevated nuclear stiffness and impaired neuronal motility in confined spaces. Moreover, mispositioned neurons resulted in electrophysiological defects in the brain. Computational modeling predicted a temporal relationship between nuclear deformation and enhanced migration velocity, which was validated experimentally through live imaging. Notably, cerebral organoid assays using iPS cells established from patients with LMNB1 duplication exhibited impaired neuronal migration in a human model. Collectively, these findings demonstrate that LB1 is a critical regulator of nuclear mechanics, ensuring the accurate spatiotemporal positioning of neurons.

Dementia incidence has been declining in Western societies for decades, but whether this reflects higher cognitive capacity entering old age, slower cognitive decline, or both remains unresolved. Analysing ~783,000 episodic memory assessments from ~219,000 individuals across five longitudinal cohorts, we find that later-born cohorts benefit from a double dividend: higher memory levels entering old age and slower rates of decline. The projected 20-year cohort advantage at age 80 is of sufficient magnitude to plausibly account for the observed 13% per-decade decline in dementia incidence reported in meta-analyses. Generational gains are disproportionately concentrated among the fastest-declining individuals, and are reflected in lower hippocampal atrophy rates in an independent sample. A formal bounding analysis shows that the double dividend is robust across a range of plausible period assumptions, consistent with environmental conditions operating across the lifespan having reshaped the architecture of human cognitive aging.

How embryonic cells generate large clones of cells in the adult represents a fundamental question in biology. Here, using melanocyte stem cells (McSCs) in the zebrafish as a model, we explore the function of the master melanocyte transcription factor (MITF) in safeguarding McSCs in embryonic development and their potential to pigment large clones in the adult. MITF is well known is for its role in the specification of melanoblasts from the neural crest (NC) and their differentiation into melanocytes, yet little is known about how this activity shapes the stem cell lineages. Here, we use live imaging coupled with single-cell transcriptomics and lineage tracing to show that MITF (mitfa in zebrafish) protects the melanocyte stem cell (McSC) fate in zebrafish. Utilizing a temperature sensitive mitfavc7 mutant, we show loss of Mitfa leads to a surprising premature and aberrant expansion of McSC progeny at the niche during embryogenesis, coupled with novel emergent transcriptional cell states. Linage tracing of McSCs from the embryonic to juvenile stages reveals Mitfa activity is subsequently required in regeneration by Schwann cell-like and melanocyte stem cell progenitors that serve as a reservoir for fast-responding pigment progenitors. Thus, the impact of Mitfa loss on the melanocyte lineage is cell-state and stage-specific. The emergent cell states upon mitfa loss may have important implications for our understanding the loss of MITF activity in human genetic disease and melanoma.

The shared genetic liability between cortical morphology and psychiatric disorders remains unclear. We aimed to identify whether the genetic loci shared between cortical morphology and six psychiatric disorders show regional or global effects. We identified substantial pairwise genetic overlaps of cortical surface area or thickness with psychiatric disorders; however, these loci lacked a uniform direction (~50% concordance). Cross-trait analyses revealed distinct architectures: internalizing disorders and schizophrenia/bipolar disorder shared more genetic loci with localized effects, whereas neurodevelopmental disorders shared fewer loci but more with widespread effects. We identified 17 genomic loci shared across all disorders, most of which had opposing directional effects across cortical regions. Only one locus (rs2431112) had region-specific and unidirectional effects (reduced primary visual and posterior cingulate surface area). This directional heterogeneity within and across pleiotropic loci reveals complex shared genetic architectures and likely limits the genetic predictive performance of brain morphology for psychiatric disorders.

Tourette Syndrome and other tic disorders (TD) are common, highly heritable neurodevelopmental conditions with complex genetic architectures. We conducted a genome-wide association study of 13,247 TD cases and 536,217 European ancestry controls and identified six independent genome-wide significant loci, including a pleiotropic signal at 3p21 shared with attention-deficit/hyperactivity disorder, among other traits. Gene prioritization highlighted 20 genes, including PCDH9, HCN1, NCKIPSD, WDR6, DALRD3, and CELSR3. Integrative analyses provide genetic support for the role of cortico-striato-thalamo-cortical circuits in TD pathophysiology and further localize TD genetic risk to specific cell types, including dopamine D1- and D2-receptor-positive medium spiny neurons, cortical pyramidal neurons, and oligodendrocyte-lineage cells. We further demonstrate extensive genetic correlations with neurodevelopmental and psychiatric traits, but not with neurological disorders. These findings advance our understanding of the genetic basis of TD, pinpointing specific genes and cell types that drive pathophysiology and providing a foundation for future mechanistic studies.

The APOE {varepsilon}4 allele is the strongest genetic risk factor for Alzheimers Disease. However, its distribution across Indian populations is poorly characterized. We analyze APOE allele frequencies in 9,524 individuals from 83 distinct populations in the GenomeIndia dataset. {varepsilon}4 frequencies show large variation across populations within India, ranging from 2.7% to 36.1%, with a median of 11%. Tribal populations have higher {varepsilon}4 frequencies compared to non-tribal groups, while Tibeto-Burman populations have significantly lower frequencies. One tribal population from the northern coastal highlands has {varepsilon}4 frequency of 0.36, with 59% of individuals being carriers. {varepsilon}4 carrier status correlates significantly with lipid phenotypes including LDL, HDL, total cholesterol, and triglycerides. Collectively, these findings reveal exceptional genetic diversity in Alzheimers Disease risk across India and have important implications for population-specific screening strategies, genetic counseling, and precision medicine approaches to dementia prevention.

De novo mutations (DNMs) arising in the parental germline are a major cause of severe developmental disorders. While most DNMs originate in the paternal germline, it remains unclear whether fathers of affected children carry a systematically altered burden of transmissible germline risk, or whether disease largely reflects stochastic outcomes of shared population-wide mutational processes. Here, we combined whole-genome sequencing of 168 parent-child trios with ultra-accurate duplex sequencing of paternal sperm to directly relate transmitted DNMs to the broader mutational and selective landscape of the male germline. In 127 fathers, sperm mutation burden and mutational spectra were indistinguishable from population reference cohorts. Positive selection metrics were likewise concordant, with a global dN/dS of 1.56 (95% CI 1.45-1.67) compared to 1.44 (95% CI 1.17-1.77) in controls and 28 of 32 significantly selected genes overlapping with prior findings. Six fathers harboured a pathogenic early mosaic variant detectable in sperm at allele fractions that ranged from 0.7% to 14.8%. Although these variants generated substantial individual-level risk outliers, they accounted for only [~]11% of the aggregated exome pathogenic burden across the cohort. The remaining burden was distributed across low-VAF mutations, including positively selected driver variants and other rare mutations accumulating with paternal age. Together, these results show that transmissible de novo disease risk is governed primarily by universal germline mutational and selective processes, while early developmental mosaicism produces uncommon but clinically meaningful deviations. This integrated view clarifies how mutation timing, age-associated accumulation and germline selection jointly shape inheritance risk.

Neural excitability fluctuates with sensory events, creating windows of opportunity to enhance brain stimulation. Repetitive transcranial magnetic stimulation (TMS), including intermittent theta burst stimulation (iTBS), is a promising treatment for neurological and psychiatric disorders, but does not account for fluctuations in neural excitability, likely contributing to variable outcomes. Sensory Entrained TMS (seTMS) leverages sensorimotor oscillations to enhance corticospinal responses, but the sustained effects as a repetitive protocol are unknown. We extend seTMS to iTBS, measuring motor-evoked potentials (MEPs) as a physiological readout. In a randomized crossover study comparing standard iTBS with sensory entrained iTBS (se-iTBS; n=20), we found that se-iTBS more than doubled the MEP effect (55% vs 26% MEP enhancement) and persisted for at least 30 minutes. Notably, at least 80% of participants showed larger responses with se-iTBS at all time points. se-iTBS may provide a robust and practical framework for optimizing TMS that bridges electrophysiological mechanisms and clinical applications.

Osteoarthritis (OA) is a prevalent musculoskeletal disorder and a leading cause of global disability. Although meniscal damage is a major risk factor of OA pathogenesis, genetic regulatory studies have remained largely confined to articular cartilage. Here, we establish the first comprehensive expression quantitative trait locus (eQTL) map integrating whole-genome sequencing and bulk transcriptomics from human meniscus (n=112) and cartilage (n=113). Supported by single-nucleus multiomics (cartilage: 56,549 nuclei; meniscus: 34,343 nuclei), we uncovered highly tissue-specific genetic risk architectures. Colocalization with OA GWAS identified 27 meniscus-specific, 28 shared, and 20 cartilage-specific causal genes. Chromatin-informed fine-mapping and deconvolution elucidated distinct pathogenic mechanisms; notably, meniscus-specific signals converged on VEGFA via rare promoter variants and an enhancer in fibrochondrocyte progenitors, alongside a shared eQTL for CLEC18A. Exploratory analysis suggested candidate compounds to reverse pathogenic gene expression. Our findings underscore the meniscus as a distinct genetic driver, molecularly reinforcing OA as an entire joint organ failure.

Genome-wide association studies (GWAS) have transformed our understanding of human biology, but are constrained by the need for predefined phenotypes. We introduce Vector2Variant (V2V), a general-purpose framework that transforms any set of high-dimensional measurements (such as machine learning embeddings) into a genome-wide scan for associations, without requiring rigid specification of a phenotype. Rather than testing genetic variants against single traits, V2V finds the axis in multivariate space along which carriers and non-carriers maximally differ, and produces a continuous "projection phenotype" that can be interpreted by association with disease labels. The projection phenotypes correlate with orthogonal clinical biomarkers never seen during training, suggesting the learned axes capture biologically meaningful variation. We applied V2V to imaging, timeseries, and omics modalities in the UK Biobank and recovered established biology (like the role of CASP9 in renal failure) without the need for targeted measurements, alongside novel associations including a frameshift variant in LRRIQ1 (potentially protective for cardiovascular disease). V2V is computationally efficient at genome-wide scale, producing summary statistics and disease associations that facilitate target prioritization without the need for phenotype engineering.

Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease with a heterogeneous clinical presentation, complicating early diagnosis and therapeutic monitoring. To identify disease-specific biomarkers, we performed an unbiased cerebrospinal fluid (CSF) proteomic analysis in 87 ALS patients, 89 healthy controls, and 61 neurological controls using mass spectrometry. Across all quantified proteins, 399 were significantly dysregulated in ALS, including established neurodegeneration (NEFL, NEFM, UCHL1) and neuroinflammatory (CHIT1, CHI3L1, CHI3L2) markers. Correlation and pathway analyses uncovered dysregulation of immune, synaptic, and metabolic processes, with aberrant complement activation emerging as a hallmark. Complement proteins increased progressively with declining ALS Functional Rating Scale-Revised and longer disease duration, whereas early-stage markers (CLSTN3, CHAD, RELN) indicated pre symptomatic neuronal and synaptic disruptions. Machine learning identified a minimal five protein CSF panel (MB, ITLN1, YWHAG, FCGR3A, PGAM1) that accurately distinguished ALS patients from healthy controls, capturing disease-specific pathophysiology beyond general neurodegeneration. Our findings define a robust ALS-specific CSF proteomic signature, reveal prognostic protein candidates across disease stages, and provide a framework for diagnostic biomarker development, enabling earlier intervention and monitoring.

Background: The apolipoprotein E (APOE) locus is the strongest genetic risk factor for late-onset Alzheimer's disease (AD). Variation in APOE isoforms is known to have diverse pleiotropic effects on circulating lipids and other metabolites, but effects on the circulating proteome across the life course are not well characterised. We investigated the specific effects of APOE {epsilon}4 and APOE {epsilon}2 carriage on the circulating proteome in middle-age and later life. Methods: In primary modelling, we analysed associations of APOE {epsilon}4 and {epsilon}2 carriage (reference {epsilon}3/{epsilon}3) with circulating proteins in UK Biobank participants (N = 42,642; age = 39.1 to 70.9 years). Using multivariable linear regression, we conducted ancestry-specific analyses of 2,922 assayed plasma proteins across individuals of European (EUR), African (AFR), and South Asian (SAS) ancestry. To identify age-dependent effects, stratified analyses were performed with the sample split into age groups. We then performed replication analyses of APOE-associated proteins in age-matched groups, using data from two independent UK-based cohorts. Results: We identified 351 proteins associated with {epsilon}2 carriage and 480 with {epsilon}4 carriage among individuals of European ancestry (n = 40,092); 130 of these were associated with both {epsilon}2 and {epsilon}4 carriage (with either consistent or inverse association directions). These included established biomarkers of neurodegeneration (GFAP and NEFL) and other proteins implicated by AD genetic risk loci (e.g., TREM2, CTSB, IDUA, SORT1, GRN). Many of these proteins are linked to other neurodegenerative diseases besides AD. In multiple age groups, {epsilon}4 carriage was strongly associated with consistent differences in circulating APOE, MENT, and PLA2G7 levels across ancestries and cohorts. Conclusion: APOE {epsilon}4 and {epsilon}2 exert broad, often age-dependent effects on the plasma proteome, detectable decades before typical ages of AD diagnoses, highlighting a potential early window for monitoring and intervention.

Dysarthric speech severity assessment typically requires either trained clinicians or supervised machine learning models built from labelled pathological speech data, limiting scalability across languages and clinical settings. We present a training-free method (no supervised severity model is trained; feature directions are estimated from healthy control speech using a pretrained forced aligner) that quantifies dysarthria severity by measuring the degradation of phonological feature subspaces within frozen HuBERT representations. For each speaker, we extract phone-level embeddings via Montreal Forced Aligner, compute d scores along phonological contrast directions (nasality, voicing, stridency, sonorance, manner, and four vowel features) derived exclusively from healthy control speech, and construct a 12-dimensional phonological profile. Evaluating 890 speakers across10corpora, 5 languages for the full MFA pipeline (English, Spanish, Dutch, Mandarin, French) and 3 primary aetiologies (Parkinsons disease, cerebral palsy, amyotrophic lateral sclerosis), we find that all five consonant d features correlate significantly with clinical severity (random-effects meta-analysis rho = -0.50 to -0.56, p < 2 x 10^-4; pooled Spearman rho = -0.47 to -0.55 with bootstrap 95% CIs not crossing zero), with the effect replicating within individual corpora, surviving FDR correction, and remaining robust to leave-one-corpus-out removal and alignment quality controls. Nasality d decreases monotonically from control to severe in 6 of 7 severity-graded corpora. Mann-Whitney U tests confirm that all 12 features distinguish controls from severely dysarthric speakers (p < 0.001).The method requires no dysarthric training data and applies to any language with an existing MFA acoustic model (currently 29 languages) or a model trained from healthy speech alone. It produces clinically interpretable per-feature profiles. We release the full pipeline and phone feature configurations for six languages to support replication and clinical adoption. Author SummaryOne of the authors has lived with ALS for sixteen years. Bernard Muller, who built this entire analytical pipeline using only eye-tracking technology, has experienced the progression of the disease firsthand, including the dysarthric speech that comes with advancing ALS and the tracheostomy that followed. The problem this paper addresses is not abstract to him, and that shapes how the method was designed. We developed a method to measure how well a person with dysarthria can produce distinct speech sounds, without needing any recordings of disordered speech for training. Our approach works by analysing how a widely available AI speech model organises different sound categories -- such as nasal versus oral consonants, or voiced versus voiceless sounds -- and measuring whether those categories become harder to tell apart. We tested this on 890 speakers across 10 datasets in five languages, covering Parkinsons disease, cerebral palsy, and ALS. Because the method only needs healthy speech recordings to set up, it applies to any language with an existing acoustic model, currently covering 29 languages. The resulting profiles show clinicians which specific aspects of speech production are degrading, rather than providing a single opaque severity score. This could support remote monitoring of speech decline in neurodegenerative disease and enable screening in languages and settings where specialist assessment is unavailable.

Pathogenic variants in TP53, the key tumour-suppressor gene underlying Li-Fraumeni syndrome (LFS), are among the best-established causes of inherited cancer predisposition. However, large-scale sequencing has revealed that many apparently pathogenic TP53 variants detected in blood are the result of somatic clonal expansions, complicating risk interpretation. Using blood-derived whole-exome data from 469,391 UK Biobank participants, we combined variant allele fraction (VAF) with haplotype-sharing analysis to distinguish germline and somatic TP53 variants. Germline variants were concentrated at sites linked to partial loss of p53 function and lower disease penetrance, whereas classic LFS alleles appeared almost entirely somatic. High-VAF carriers of classic LFS alleles conferred markedly increased risk of haematological malignancy but not solid tumours, consistent with large TP53-mutant clonal expansions. The prevalence of somatic clonal expansion also correlated with missense variant pathogenicity, suggesting that somatic activity provides an informative in vivo proxy for functional impact. These results provide new insights into TP53-associated cancer risk at the population level, demonstrate that somatic rather than germline risk predominates in middle-aged healthy adults and provide a scalable framework for variant classification in large-scale population genomics.

Patients who participate in intracranial neuroscience research make invaluable contributions to our understanding of the brain, accelerating the development of neurotechnological interventions. Engagement of patients as part of this research presents unique challenges, where study goals can be distant from immediate clinical applications and require specialized domain knowledge. Yet methods for meaningfully integrating patient communities as part of these research efforts is essential, as intracranial neuroscience guides the application of artificial intelligence for understanding and enhancing human cognition. In order to identify what patients consider meaningful research engagement we interviewed individuals who participated in a study during their Deep Brain Stimulation (DBS) surgery and attended a group event where they interacted with our research team. Analysis of semi-structured interviews identified four main themes: interest in science and the future of clinical care, contributing to science to improve lives, connecting with others, and accessibility considerations. Based on these insights, we propose strategies for transformational participation of patient communities in intracranial neuroscience research with respect to engagement objectives, communication and scope. This approach offers a foundation for sustaining relationships between scientists and communities rooted in trust and transparency, to ensure that impacts of neurotechnology on human health and cognition are aligned with patient needs as well as desired public values.

Obtaining novel antibodies against specific protein targets is a widely important yet experimentally laborious process. Meanwhile, computational methods for antibody design have been limited by low success rates that currently require resource-intensive screening. Here, we introduce Germinal, a broadly enabling generative pipeline that designs antibodies against specific epitopes with nanomolar binding affinities while requiring only low-n experimental testing. Our method co-optimizes antibody structure and sequence by integrating a structure predictor with an antibody-specific protein language model to perform de novo design of functional complementarity-determining regions (CDRs) onto a user-specified structural framework. When tested against four diverse protein targets, Germinal successfully designed functional antibodies across all targets and binder formats, testing only 43-101 designs for each antigen. Validated designs also exhibited robust expression in mammalian cells and high sequence and structural novelty. We provide open-source code and full computational and experimental protocols to facilitate wide adoption. Germinal represents a milestone in efficient, epitope-targeted de novo antibody design, with notable implications for the development of molecular tools and therapeutics.

A central question in psycholinguistics in visual word recognition is whether morphologically complex words are obligatorily decomposed into stems and affixes during visual word recognition or whether whole-word access can occur when forms are frequent and familiar. The present study investigated how morphological complexity and lexical frequency jointly shape neural responses by leveraging Korean nominal inflection, whose transparent stem-suffix structure permits a clean dissociation between base (stem) frequency and surface (whole-word) frequency. Twenty-five native Korean speakers completed a rapid event-related fMRI lexical decision task involving simple and inflected nouns that varied parametrically in both frequency measures. Representational similarity analysis (RSA) revealed robust encoding of surface frequency--but not base frequency--in the inferior frontal gyrus (IFG) pars opercularis and supramarginal gyrus (SMG), with significantly stronger correlations for inflected than simple nouns. Univariate analyses converged with this result: surface frequency selectively increased activation for inflected nouns in inferior parietal regions, whereas base frequency showed no reliable effects in any ROI. These findings challenge models positing obligatory pre-lexical decomposition, instead supporting accounts in which morphological processing is shaped by post-lexical, usage-driven lexical statistics. Taken together, our findings shed light on a distributed perspective on morphological processing, suggesting that structural and statistical factors jointly constrain access to morphologically complex forms.

Our understanding of human mucosal T cell clonotype distribution in health and disease has centered on immunodominant antigens. We performed single cell T cell receptor (TCR) and RNA sequencing as an untargeted approach to define distributions of T cell clonal groups in health and ulcerative colitis (UC) across 333,088 T cells in colon and peripheral blood. Healthy donor-specific TCR repertoires had limited blood-colon clonal sharing, which was highest in cytotoxic T effector memory (Tem) populations and lowest in regulatory T cells (Tregs), reflecting tissue-based compartmentalization. Within healthy colon, TCR repertoires showed high T cell clonal sharing independent of anatomic distance, associated with high intra-clonal phenotypic diversity. Colon cytotoxic and Th17 populations showed high dispersion across sites, while Tregs were compartmentalized. Clonal lineages dispersed across blood and colon upregulated trafficking markers, suggesting active movement between tissues, while those dispersed across colon sites upregulated residency markers, suggesting intra-colon repertoire sharing is mediated by long-term, slow moving clonal groups. In UC, Tregs were expanded across inflamed sites, and increased CD8 Tem clonal groups showed increased dispersion regardless of inflammation. These findings reveal principles of T cell clonal organization in the human colon during health and disease, identifying opposing patterns of clonal dispersion among Treg and Th17 clonal groups, high phenotypic diversity within dispersed clonal groups, and elevated cross-colon dispersion of CD8 Tem clonotypes in UC.

Drug-tolerant persisters (DTPs) represent a major obstacle to durable responses in targeted cancer therapy. DTPs are commonly described as distinct single-cell states that survive drug treatment via reversible, non-genetic mechanisms and drive tumor recurrence. Recent work demonstrates that multiple DTPs can coexist, reflecting diversity in lineage, signaling programs, or stress responses. However, each DTP is still generally viewed as a uniform cellular phenotype. Building on our prior work describing a population-level DTP termed "idling" [Paudel et al., Biophys. J. (2018) 114, 1499-1511], here we present evidence supporting a fundamentally different view: that DTPs are not single-cell states, but rather heterogeneous populations composed of multiple sub-states with distinct division and death rates that balance to produce near-zero net population growth. Using single-cell transcriptomics and lineage barcoding, we identify multiple phenotypic states within idling DTP populations, with reduced heterogeneity compared to untreated populations, and find that idling DTP cells emerge from nearly all lineages. Transcriptomic and functional analyses further reveal altered ion-channel activity in idling DTPs, which we confirm experimentally. Moreover, drug-response assays reveal increased susceptibility of idling DTPs to ferroptosis, a non-apoptotic form of regulated cell death, indicating the emergence of vulnerabilities associated with drug tolerance. Altogether, our results support a population-level view of tumor drug tolerance in which DTPs comprise stable collections of phenotypic states, shaped by treatment-defined phenotypic landscapes, which are potentially vulnerable to subsequent interventions. This perspective implies that eradicating DTPs will require a fundamental shift away from cell-type-centric strategies toward sequential treatments that progressively reduce phenotypic heterogeneity by modulating the molecular and cellular processes that establish the DTP landscape, an approach previously termed "targeted landscaping."