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PubMed2026

One brain, one mind: A joint EPA-EAN leadership perspective on brain health.

Neurology and psychiatry have operated as separate disciplines for over a century, yet this division reflects historical and institutional developments rather than the underlying biology of the brain. Contemporary neuroscience shows that brain and mental health disorders share genetic susceptibilities, inflammatory and metabolic pathways, environmental and social risk factors, and clinical features that cross diagnostic boundaries. Cognitive, emotional, sensory, and motor symptoms regularly appear across both neurological and psychiatric populations, and conditions such as seizures, psychosis, mood disorders, cognitive disorders, and sleep disorders are common to both. A brain health framework addresses this reality by treating the brain as a single biological organ whose function emerges from the interplay between genome and exposome - including stress, trauma, social context, existential meaning, pollution, and physical health - and which underlies perception, behaviour, cognition, emotion, resilience, and vulnerability. Translating this perspective into practice requires coordinated action across domains. Clinically, collaborative models such as joint neurology-psychiatry consultations and shared outpatient pathways can be implemented within existing resources to improve diagnostic clarity and continuity of care. In training, a more harmonised curriculum with shared foundations in neurobiology, joint seminars, and cross-rotations would equip clinicians with a common language while preserving specialist depth, and support the emerging fields of preventive neurology and preventive psychiatry. In research, organising studies around shared mechanisms and symptom dimensions, and launching joint funding calls, would enhance translational relevance and reduce duplication. To realise this vision, sustained leadership from European professional bodies is essential to establish collaboration as a shared professional standard.

Humans↗
PubMed2025

Exploring the transmission of cognitive task information through optimal brain pathways.

Understanding the large-scale information processing that underlies complex human cognition is the central goal of cognitive neuroscience. While emerging activity flow models demonstrate that cognitive task information is transferred by interregional functional or structural connectivity, graph-theory-based models typically assume that neural communication occurs via the shortest path of brain networks. However, whether the shortest path is the optimal route for empirical cognitive information transmission remains unclear. Based on a large-scale activity flow mapping framework, we found that the performance of activity flow prediction with the shortest path was significantly lower than that with the direct path. The shortest path routing was superior to other network communication strategies, including search information, path ensembles, and navigation. Intriguingly, the shortest path outperformed the direct path in activity flow prediction when the physical distance constraint and asymmetric routing contribution were simultaneously considered. This study not only challenges the shortest path assumption through empirical network models but also suggests that cognitive task information routing is constrained by the spatial and functional embedding of the brain network.

Humans↗
PubMed2025

A neural network model enables worm tracking in challenging conditions and increases signal-to-noise ratio in phenotypic screens.

High-resolution posture tracking of C. elegans has applications in genetics, neuroscience, and drug screening. While classic methods can reliably track isolated worms on uniform backgrounds, they fail when worms overlap, coil, or move in complex environments. Model-based tracking and deep learning approaches have addressed these issues to an extent, but there is still significant room for improvement in tracking crawling worms. Here we train a version of the DeepTangle algorithm developed for swimming worms using a combination of data derived from Tierpsy tracker and hand-annotated data for more difficult cases. DeepTangleCrawl (DTC) outperforms existing methods, reducing failure rates and producing more continuous, gap-free worm trajectories that are less likely to be interrupted by collisions between worms or self-intersecting postures (coils). We show that DTC enables the analysis of previously inaccessible behaviours and increases the signal-to-noise ratio in phenotypic screens, even for data that was specifically collected to be compatible with legacy trackers including low worm density and thin bacterial lawns. DTC broadens the applicability of high-throughput worm imaging to more complex behaviours that involve worm-worm interactions and more naturalistic environments including thicker bacterial lawns.

Caenorhabditis elegans↗
PubMed2025

Precision Genomics: A Reality Having Universal Impact in a New Era of Psychiatry - Lessons Learned, Past and Present.

Addiction neuroscience explores the complex interplay between genetic, neurobiological, environmental, and socio-spiritual factors underlying substance and behavioral addictions. Over the past three decades, research in this domain has identified critical molecular and epigenetic mechanisms-particularly those affecting dopaminergic signaling and reward pathways-that contribute to both vulnerability and resilience to addictive behaviors. Central to this understanding is the concept of reward deficiency syndrome (RDS), first introduced by Kenneth Blum, which posits that hypodopaminergic functioning predisposes individuals to seek maladaptive rewards. Advances in neurogenetics, including the identification of key polymorphisms such as the DRD2 A1 allele, have paved the way for precision tools like the genetic addiction risk severity (GARS®) test. This test, alongside pro-dopaminergic nutraceutical interventions like KB220, demonstrates the potential for early detection and individualized treatment of "pre-addiction" risk states. Despite ongoing reliance on opioids for opioid use disorder (OUD), emerging paradigms advocate for dopamine homeostasis through non-addictive, integrative approaches. Furthermore, the integration of whole genome sequencing data can be used for Genome-Wide Association Studies (GWAS), multi-omics, and machine learning into clinical practice holds promise for advancing personalized medicine in addiction treatment. As the field progresses, addressing health equity and improving genomic representation across populations remain critical goals. This evolving framework underscores the importance of leveraging genomic insights to prevent, predict, and personalize interventions for addiction and mental illness at scale.

Disorder↗
PubMed2026

Mitochondrial resilience: a convergent framework for pathogenesis and neuroprotection in Parkinson's disease.

Parkinson's disease (PD) is traditionally described as a dopaminergic neurodegenerative disorder driven by α-synuclein aggregation and selective neuronal loss in the substantia nigra pars compacta. While this characterization captures the core clinical and pathological features, it does not fully explain disease initiation and progression. Converging evidence from human genetics, cellular and structural biology, and systems neuroscience now supports a unified framework in which PD results from the progressive erosion of mitochondrial resilience. Here, mitochondrial resilience denotes the capacity of neuronal mitochondrial networks to withstand stress and recover bioenergetic and cellular homeostasis through coordinated quality control, metabolic adaptation, and organelle communication. Rare, high-impact monogenic mutations in PINK1, PRKN (encoding Parkin), PARK7 (DJ-1), LRRK2, and SNCA, along with common risk variants identified in genome-wide association studies, converge on interconnected pathways that govern mitochondrial quality control, bioenergetics, organelle dynamics, and cellular stress responses. These vulnerabilities are most pronounced in the highly energetic dopaminergic neurons of the substantia nigra, where sustained calcium cycling, high bioenergetic demand, and environmental stressors increase cellular susceptibility. Research has moved beyond early observations of respiratory chain impairment and oxidative stress to reveal context-specific disruptions in PINK1/Parkin-mediated mitophagy, lysosomal trafficking, mitochondrial-derived vesicle dynamics, and neuroimmune signaling. This integrated framework reframes PD as a disorder of impaired cellular maintenance rather than solely a consequence of late-stage degenerative processes. It provides a translational shift from mechanism-based biomarkers to early detection of mitochondrial failure and supports therapeutic strategies aimed at restoring mitochondrial function and resilience, offering a direct route to disease-modifying neuroprotection in PD and potentially other neurodegenerative disorders.

LRRK2↗
PubMed2026

Autism care: reimagining the spectrum.

Autism care policy is at a critical inflection point. Applied behavior analysis (ABA), long established as the "gold standard" through state insurance mandates in the US, has functioned as the default reimbursable intervention for autistic children. However, advances in genomics, neuroscience, developmental psychology, and scholarship on autistic lived experience have expanded understanding of autism as a heterogeneous neurotype characterized by meaningful differences in neural organization rather than a unitary disorder. Contemporary models emphasize neurodiversity, strengths-based perspectives, and the interaction between developmental processes and environmental contexts in shaping functional outcomes. Many autistic children also meet criteria for complex care needs, requiring coordinated, interdisciplinary services across health, educational, and community systems. This manuscript proposes reframing the "autism spectrum" from a hierarchy of symptom severity to a prevention-oriented "spectrum of care." Adapting a public health taxonomy, interventions are organized into universal, selective, and indicated levels, targeting the prevention of avoidable disability, distress, and participation barriers. This model aligns autism services with whole-child, neurodiversity-affirming, and developmentally informed care, emphasizing relational health, autonomy, and life-course participation.

applied behavior analysis↗
PubMed2025

Stem cell derived neural organoid approaches for neurological diseases.

Traditional two-dimensional cultures and animal models often fall short in capturing the complexities of neurodevelopmental and neurodegenerative diseases. However, recently developed neural organoid approaches, three-dimensional structures derived from human pluripotent stem cells, have become powerful tools for modeling human neuronal development and disease. Unlike traditional models, neural organoids provide significant insights and improved modeling capabilities. Here, we explore various types of neural organoids in disease modeling and outline distinct protocols for generating each type, including specific patterning methods, growth factors, and differentiation durations. The potential and advantages of co-culturing neural organoids with other cells and tissues are also discussed. While neural organoids have already made significant contributions to neuroscience research, future directions should focus on enhancing their maturation and functionality. The progression of neural organoids approaches will generate more accurate and comprehensive disease models, ultimately adding to our understanding of disease pathogenesis and paving the way for future precision therapies for neurological diseases.

neural differentiation↗
PubMed2025

Combined somatic mutation and transcriptome analysis reveals region-specific differences in clonal architecture in human cortex.

The human cerebral cortex is specialized into regions, but little is known about how human cellular lineages shape cortical regional variation and neuronal cell-type distribution during development. Here, we map single-cell lineages of human cortical regions and neuronal subtypes using >1,000 somatic single-nucleotide variants (sSNVs) identified from deep bulk whole-genome sequencing and analyzed over 25 regions and >72,000 single cells. In the fronto-parietal cortex, sSNVs are rarely restricted, marking neuron-generating clones that disperse into neighboring regions. In contrast, the primary visual cortex harbors 30%-70% more sSNVs than the neighboring secondary visual cortex. Clones at this border exhibit more restricted dispersion, suggesting late developmental lineage segregation. Single-nucleus sSNV and whole-transcriptome analysis reveal glutamatergic neuron clones with modest regional restrictions that share low-mosaic sSNVs with some GABAergic neurons, suggesting a recent dorsal cortical progenitor. Our analysis reveals human-specific cortical lineage patterns, regional differences in clonal patterns, and late divergence of some glutamatergic/GABAergic lineages.

Humans↗
PubMed2025

Phospho-proteome profiling in human neurons reveals targets of TBK1 in ALS/FTD-associated autophagy networks.

Loss-of-function variants in TBK1, encoding a protein kinase, are strongly associated with familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). However, how haploinsufficiency for TBK1 leads to age-related neurodegeneration remains unresolved. Here, we utilize sets of isogenic induced pluripotent stem cells (iPSCs) with loss of TBK1 or loss of optineurin (OPTN) for quantitative global proteomics and phospho-proteomics in both stem cells and excitatory neurons. We found that TBK1 sustains the abundance and phosphorylation of its interacting adapter proteins, AZI2/NAP1, TANK, and TBKBP1/SINTBAD. Moreover, TBK1 regulates the phosphorylation of endo-lysosomal proteins, such as GABARAPL2, the late-endosome GTPase RAB7A, and selective autophagy cargo receptor proteins-including novel phospho-sites in p62/SQSTM1-in neurons. Finally, we provide a census of the phospho-proteome in nascent human neurons for further studies. Overall, TBK1 serves as a point of convergence in ALS/FTD-linked endo-lysosomal networks that act in a cell-autonomous manner to maintain protein homeostasis in neurons.

Humans↗
PubMed2026

Ketogenic diet dampens excitatory neurotransmission by shrinking synaptic vesicle pools.

Ketogenic diet (KD) is used for the treatment of drug-resistant childhood epilepsy and has been proposed to improve outcomes in neurodegenerative diseases. However, the mechanisms by which KD alters brain circuitry remain unclear. Here, we investigated the impact of KD on hippocampal function through integrative analysis of gene expression and neurotransmission. We found that KD induces extensive transcriptional reprogramming, including altered expression of numerous synaptic genes. Proteomic and genomic profiling revealed significant changes in histone modifications, particularly at promoters of KD-regulated genes. Electrophysiological recordings showed that KD reduces excitatory synaptic gain and short-term plasticity at CA3-CA1 synapses, dampening the summation of excitatory inputs and enhancing the summation of inhibitory inputs. These functional changes were driven, in part, by a reduction in the readily releasable vesicle pool at excitatory synapses under KD. Together, our findings demonstrate that KD drives transcriptional remodeling of hippocampal circuits, leading to synaptic adaptations that may underlie its anti-epileptic and neuroprotective effects.

Animals↗
PubMed2026

Locus coeruleus activation transforms cortical taste representations.

Noradrenergic neurons in the locus coeruleus (LC) shape sensory processing, yet how LC activity influences population taste coding remains unclear. Using optogenetic LC activation with miniscope imaging in the gustatory cortex (GC), we examined LC modulation of multiple taste attributes. Phasic LC activation strengthens correlations between neuronal responses and palatability and expands the dynamic range of stimulus representations along a palatability axis. This expansion is driven by an aversive shift in the representations of all tastants except sucrose, the most palatable stimulus. For mixture ratio and concentration, phasic activation expands and rotates attribute axes, potentially reflecting dependencies between these attributes and palatability. These transformations likely arise from multiplicative gain modulation and more flexible tuning changes. Tonic LC activation affects fewer neurons and does not expand attribute axes. Together, the findings show that LC activation reorganizes GC population geometry in a pattern-dependent manner, linking neuromodulation with feeding behavior and affective processing.

CP: neuroscience↗
PubMed2024

SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.

Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Single-Cell Analysis↗
PubMed2026

Regulators of interferon-responsive microglia uncovered by Genome-wide CRISPRi screening.

Microglia dynamically support brain health through the induction of specialized activation states in response to injury or disease. Activation of the interferon-responsive microglia (IRM) state has been identified across neurodevelopmental windows, age-related cognitive decline, and neurodegenerative diseases. Functionally, IRM have been linked to synaptic pruning, dead cell removal, and neuroinflammation, making this state critical to brain homeostasis. While the functional importance of this state is becoming increasingly clear, our understanding of the regulatory networks that govern IRM induction remain incomplete. To systematically identify genetic regulators of the IRM state, we conducted a genome-wide CRISPR interference screen in human iPSC-derived microglia using IFIT1 as a representative IRM marker. We identified 772 genes that modulate IRM, including canonical type I interferon signaling genes (IFNAR2, TYK2, STAT1/2, USP18) and newly described regulators. We uncovered a non-canonical role for the CCR4-NOT transcription complex subunit 10, CNOT10, in IRM activation. This work provides a comprehensive resource that can be applied to dissect the functions of interferon-responsive microglia and highlights both established and novel targets for modulating microglial interferon signaling in health and disease.

Computational biology and bioinformatics↗
PubMed2026

Blood-based biomarkers of Alzheimer's disease and neurodegeneration in an indigenous African cohort using both Simoa and NULISA platforms.

In low- and middle-income countries, Alzheimer's disease (AD) constitutes a growing public health burden. However, AD biomarkers research remains underrepresented in African populations. This study assesses core biomarkers of AD and their relevance in the African context as potential aid in clinical diagnosis. Nigerian older adults from VALIANT cohort (n&#x2009;=&#x2009;967) underwent biomarker quantification in plasma (p-tau217, GFAP, NfL, A&#x3b2;42 and A&#x3b2;40) employing both the Single Molecule Assay (Simoa, Quanterix) and Nucleic acid-Linked Immuno-Sandwich Assay (NULISA, Alamar). Biomarkers were associated with disease severity in clinical-diagnostic and clinical-biological groups, with stepwise increases of p-tau217, NfL and GFAP from cognitively unimpaired to dementia (p&#x2009;<&#x2009;0.05). Results were consistent across platforms. Comparison between sexes showed higher biomarker levels in male participants across diagnostic groups. A significant effect of apoE-E4 proteotype on p-tau217 levels, after adjusting for age and sex was identified. These findings support the application of plasma AD biomarkers in the African context and the relevance of further AD biomarker research in diverse populations.

Biomarkers↗
PubMed2023

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis.

Large single-cell RNA datasets have contributed to unprecedented biological insight. Often, these take the form of cell atlases and serve as a reference for automating cell labeling of newly sequenced samples. Yet, classification algorithms have lacked the capacity to accurately annotate cells, particularly in complex datasets. Here we present SIMS (Scalable, Interpretable Machine Learning for Single-Cell), an end-to-end data-efficient machine learning pipeline for discrete classification of single-cell data that can be applied to new datasets with minimal coding. We benchmarked SIMS against common single-cell label transfer tools and demonstrated that it performs as well or better than state of the art algorithms. We then use SIMS to classify cells in one of the most complex tissues: the brain. We show that SIMS classifies cells of the adult cerebral cortex and hippocampus at a remarkably high accuracy. This accuracy is maintained in trans-sample label transfers of the adult human cerebral cortex. We then apply SIMS to classify cells in the developing brain and demonstrate a high level of accuracy at predicting neuronal subtypes, even in periods of fate refinement, shedding light on genetic changes affecting specific cell types across development. Finally, we apply SIMS to single cell datasets of cortical organoids to predict cell identities and unveil genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. When cell types are obscured by stress signals, label transfer from primary tissue improves the accuracy of cortical organoid annotations, serving as a reliable ground truth. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Brain organoids↗
PubMed2025

The cellular associates of late life changes in white matter microstructure.

The microstructural architecture of white matter supporting information flow across local circuits and large-scale networks changes throughout the lifespan. However, the genetic and cellular factors underlying age-related variations in white matter microstructure have yet to be established. Here, we examined the genetic associates of individual differences in diffusion-based measures of white matter in a population-based cohort (N=29,862) from the UK Biobank. Estimates of heritability from Genome-Wide Association Study (GWAS) data revealed that genetic factors are linked to population variability in 96.1% of 432 tract microstructural measures. The presence of shared genetic influences was observed to be greater within, relative to between, broad tract classes (commissural, association, projection, and complex cerebellar). Age associations with microstructural changes were estimated across diffusivity measures, with association class tracts showing the greatest vulnerability to age-related decline in older adults. Analyses of imputed cellular associates of age-related changes in white matter revealed a preferential relationship with cell gene markers of oligodendrocytes and other glial cell types, with sparse relationships observed for inhibitory and excitatory cells. These data indicate that white matter tract microstructure is shaped by genetic factors and suggest a role for glial cell-related transcripts in late-life changes in the structural wiring properties of the human brain.

Aging↗
PubMed2025

Transcriptional signature of induced neurons differentiates virologically suppressed people with HIV from people without HIV.

Neurocognitive impairment is a prevalent comorbidity in virologically suppressed people living with HIV (PLWH), yet the underlying mechanisms remain elusive and treatments lacking. We explored use of participant-derived directly induced neurons (iNs) to model neuronal biology and injury in PLWH. iNs retain age- and disease-related donor features, providing unique opportunities to reveal important aspects of neurological disorders. We obtained primary dermal fibroblasts from 6 virologically suppressed PLWH and 7 matched people without HIV (PWOH). iNs were generated using transcription factors NGN2 and ASCL1 and validated by immunocytochemistry, single-cell RNA-Seq, and electrophysiological recordings. Transcriptomic aging analyses confirmed retention of donor age-related signatures. Bulk RNA-Seq identified 29 significantly differentially expressed genes between PLWH and PWOH iNs. Of these, 16 were downregulated and 13 upregulated in PLWH iNs. Protein-protein interaction network mapping indicated iNs from PLWH exhibited differences in extracellular matrix organization and synaptic transmission. IFI27 was upregulated in PLWH iNs, complementing independent postmortem studies demonstrating elevated IFI27 expression in PLWH-derived brain tissue. FOXL2NB-FOXL2-LINC01391 expression was reduced in PLWH iNs and negatively correlated with neurocognitive impairment. Thus, we identified an iN gene signature of HIV revealing mechanisms of neurocognitive impairment in PLWH.

Humans↗
PubMed2026

Structural and functional gastrointestinal abnormalities in ACTA2 R179H mice modeling multisystemic smooth muscle dysfunction syndrome.

Multisystemic smooth muscle dysfunction syndrome (MSMDS) is a rare disorder caused by ACTA2 mutations, including the R179H variant, which alters actin filament stability and dynamics and smooth muscle contractility. Cardiovascular complications dominate its clinical presentation, but gastrointestinal (GI) dysfunction significantly affects quality of life. To investigate the structural, functional, and cellular basis of gut dysmotility in MSMDS, we reviewed clinical data from 24 patients with MSMDS and studied the ACTA2 R179H mouse model. Patients exhibited severe gut dysmotility, with 75% requiring medication for chronic constipation. ACTA2 mutant mice displayed cecal and colonic dilatation, reduced intestinal length, and disrupted colonic migrating motor complexes. Delayed whole-gut transit and impaired contractile responses to electrical and pharmacological stimulation were observed. Transcriptomic analysis revealed significant actin cytoskeleton-related gene changes in smooth muscle cells, and immune profiling identified increased lymphocytic infiltration. Despite functional abnormalities, there were no obvious changes in the enteric nervous system. These findings establish ACTA2 mice as a robust model for studying GI pathology in MSMDS, elucidating the role of smooth muscle dysfunction in gut dysmotility. This model provides a foundation for developing targeted therapies aimed at restoring intestinal motility by directly addressing actin cytoskeletal disruptions in smooth muscle cells.

Animals↗