Biology subjects

Vogel, J. W.

Publications and source records attributed to Vogel, J. W..

At least 19 recordsLinked to original sources

bioRxiv2026

A coordinated and reproducible multicellular response to AD pathology

While single-cell measurements of the Alzheimer's disease (AD) brain allow investigation of vulnerable cells in unprecedented depth, reported findings are heterogeneous, mostly descriptive and often ignore interdependence of cellular responses. Operationalization of these findings requires a multi-cellular model of AD that is robust and reproducible. Here, we utilize a coordinated multicellular community approach across 2.3 million nuclei from 427 ROSMAP donors to identify robust multicellular axes associated with AD pathology and sex. The AD signature comprised profound alteration to RORB-GABRG excitatory neurons and disrupted oligodendrocyte precursor cell signaling. A separate set of AD-related cell-type specific molecular processes with strong sexual dimorphism also emerged. Importantly, these signatures developed and ROSMAP predicted neuropathology and sex, respectively, in a completely independent dataset (SEA-AD). These findings altogether summarize a highly consistent multi-cellular response to AD pathology in the human brain, creating a baseline cellular model to which perturbation and treatment experiments can be compared.

neuroscience↗

bioRxiv2026

HippoGenes: A robust workflow for subregional transcriptomic profiling of the human hippocampus

The human hippocampus is a unique cortical structure central to brain function, plasticity, and disease. Unravelling its complex organization requires the integration of multiscale data, linking molecular features to mesoscale anatomy and macroscale functional patterns. Gene expression is a fundamental microscale phenotype, and its profiling can provide a reference description of how molecular features are distributed across the brain. Capitalizing on recent imaging-transcriptomic analyses, we introduce HippoGenes, a repository of fine-grained gene expression patterns across human hippocampal subregions. We leveraged spatial statistical models and hippocampal surface mapping to reconstruct dense transcriptomic maps from sparse post-mortem tissue samples of the Allen Human Brain Atlas, generating continuous expression estimates for thousands of genes aligned to a common surface-based coordinate system. We illustrate the utility of HippoGenes to (i) map medial-lateral and anterior-posterior transcriptomic gradients that align with subfield and tripartite subdivisions of the hippocampal formation, (ii) examine associations between gene expression and canonical microstructural and functional features of the hippocampus, and (iii) perform a molecular decoding of subregional alterations in neurological patients with hippocampal pathology. HippoGenes provides a framework for exploring the molecular organization of the hippocampus, opening avenues for multiscale integration in health and disease, and is openly available on https://hippogenes.readthedocs.io/.

neuroscience↗

bioRxiv2026

Dynamical Aβ-Tau-Neurodegeneration Model Predicts Alzheimer's Disease Mechanisms and Biomarker Progression

Alzheimers disease is characterised by the pathological interaction of two proteins, amyloid-beta (A{beta}) and tau, which collectively drive neurodegeneration and cognitive decline. The progression of A{beta}, tau, and neurodegeneration biomarkers is captured by the ATN framework, which is a powerful tool for disease classification. However, since the ATN framework is mainly descriptive, it cannot quantify or predict relationships between biomarkers over time. We address this limitation by introducing a dynamical ATN (dATN) model that mechanistically simulates the spatiotemporal progression of A{beta}, tau, and neurodegeneration. The dATN model integrates mechanisms of prion-like protein aggregation of A{beta} and tau, network-based tau propagation, A{beta}-driven catalysis of tau progression, and tau-driven neurodegeneration. We calibrated the model using multimodal longitudinal imaging data from both the ADNI and BioFINDER-2 cohorts and show that it accurately fits longitudinal regional A{beta}, tau, and neurodegeneration data. Using the dATN model, we show that A{beta}-induced effects predict Braak-like cortical tau progression, that the spatial colocalisation of A{beta} and tau is a crucial biomarker of disease acceleration, and that tau-driven atrophy strongly correlates with observed neurodegeneration. Furthermore, by integrating the disease progression model with pharmacokinetic-pharmacodynamic simulations, we present a powerful tool that facilitates regional evaluation of therapeutic strategies targeting A{beta}, identification of critical intervention windows, and prediction of heterogeneous treatment effects across brain regions. This framework unifies mechanistic understanding with clinical imaging biomarkers, offering a quantitative approach for forecasting disease progression, testing mechanistic hypotheses, and optimising personalised treatment strategies in AD. One Sentence SummaryColocalisation of A{beta} and tau predicts regional tau progression and optimal A{beta}-targeted intervention windows, while tau predicts neurodegeneration.

neuroscience↗

bioRxiv2025

Patient-specific functional brain architecture explains cortical patterns of tau PET in Alzheimer's disease

The spatial distribution of tau pathology, a key correlate of neurodegeneration and cognitive decline in Alzheimer's disease (AD), varies markedly across individuals. While tau is thought to spread along brain networks, the role of inter-individual variability in accounting for these patterns remains underexplored. Using resting-state fMRI and tau-PET from 805 BioFINDER participants across the AD continuum, with replication in ADNI (n=361) and A4 (n=336), we studied whether subject-specific functional connectivity (FC) profiles enhance the characterization of tau deposition patterns. A hybrid approach integrating individual and group-average FC explained individual tau-PET topographies better than either FC representation alone, particularly in symptomatic individuals and at finer spatial resolutions. Hybrid FC also better captured individual tau topographies than canonical tau-PET maps derived from cohort-level data. These effects were specific to tau and not similarly observed for {beta}-amyloid, and the explanatory advantage of FC-based models increased with spatial granularity. Furthermore, baseline hybrid FC explained follow-up tau-PET topography better than template FC, suggesting that individualized baseline connectivity contains information about future tau-PET progression. The main FC model-comparison findings replicated in ADNI and A4. Collectively, these findings show that individual functional brain architecture is associated with heterogeneity in tau-PET topography. While not establishing a causal propagation mechanism, our findings are consistent with network-spread models. This work advances the methodological characterization of tau-PET heterogeneity in AD and highlights functional connectivity as a potentially informative marker of individual tau-PET trajectories.

neuroscience↗

bioRxiv2025

Age and Alzheimer's disease affect functional connectivity along separate axes of functional brain organization

Aging and Alzheimers disease (AD) are accompanied by alterations to large-scale communication patterns in the brain, which can be tracked in vivo using functional connectivity (FC). The location, direction and relevance of these changes remain widely debated, though they are rarely studied in the context of whole-cortex communication dynamics. In two independent cohorts (BioFINDER-2, N=973; ADNI, N=129), we show that FC changes associated with aging and AD are strongly aligned with separate fundamental axes of hierarchical brain communication. Early accumulation of AD pathology and subsequent cognitive decline are both linked to functional change along the sensory-association axis. Meanwhile, age-related functional changes occur along the representation-executive axis consistently throughout the adult lifespan. These findings together suggest AD and aging both alter major but orthogonal functional pathways in the brain. More broadly, our findings position whole-brain connectivity dynamics as a unifying framework for interpreting functional changes across the adult lifespan.

neuroscience↗

bioRxiv2025

Brain network dynamics determine tau presence while regional vulnerability governs tau load in Alzheimer's disease

In Alzheimers disease (AD), tau pathology accumulates gradually throughout the brain, with clinical decline reflecting tau progression. A comprehensive understanding of, first, whether tau propagation is predominantly governed by connectome-based diffusion, regional vulnerability, or an interplay of both, and second, which types of brain connectivity or regional factors best explain tau propagation, remains crucial for advancing our understanding of AD progression. Here, we apply multi-scale, biologically informed disease progression simulations to human data, to disentangle the influence of local mechanisms on global tau progression patterns in AD. We find that whether tau reaches a brain region (presence) and how much tau accumulates there (load) are governed by different mechanisms. Tau presence patterns are highly consistent across the population, and can be largely explained through synaptic spread through white-matter networks and excitatory-inhibitory dynamics. Meanwhile tau load differs across people, and is driven by a combination of synaptic spread and intrinsic or extrinsic regional properties, including regional {beta}-amyloid load, MAPT gene expression and regional blood flow. Finally, while distinct tau patterns in the population could each be explained by established AD mechanisms, our models highlight a role of distinct brain networks (parietal networks in MTL-sparing AD tau subtype) and neurotransmitter systems (cholinergic system in posterior subtype). Together, this work suggests that network dynamics likely determine the sequence of regional tau progression, while individual-specific tissue-vulnerability factors influence regional tau load.

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bioRxiv2025

Hemispheric Asymmetry of Tau Pathology is Related to Asymmetric Amyloid Deposition in Alzheimer's Disease

The distribution of tau pathology in Alzheimers disease (AD) shows remarkable inter-individual heterogeneity, including hemispheric asymmetry. However, the factors driving this asymmetry remain poorly understood. We explored whether tau asymmetry is linked to i) reduced inter-hemispheric brain connectivity (potentially restricting tau spread), or ii) asymmetry in amyloid-beta (A{beta}) distribution (indicating greater hemisphere-specific vulnerability to AD pathology). 452 participants from the Swedish BioFINDER-2 cohort with evidence of both A{beta} pathology (CSF A{beta}42/40 or neocortical A{beta}-PET) and tau pathology (temporal tau-PET), were categorised as left asymmetric (n=102), symmetric (n=306), or right asymmetric (n=44) based on temporal lobe tau-PET uptake distribution. Edge-wise inter-hemispheric functional (RSfMRI; n=318) and structural connectivity (dMRI; n=352) patterns were examined but no differences in inter-hemispheric functional or structural connectivity were found between groups. However, a strong association was observed between tau and A{beta} laterality patterns based on PET uptake (n=233; {beta}=0.632, p<0.001), which was replicated in three independent cohorts (n=234; {beta}=0.535, p<0.001). In a longitudinal A{beta}-positive sample, baseline A{beta} asymmetry predicted the progression of tau laterality over time (n=289; {beta}=0.025, p=0.028). These findings suggest that tau asymmetry is not associated with a weaker inter-hemispheric connectivity but might reflect hemispheric differences in vulnerability to A{beta} pathology, underscoring the role of regional vulnerability in determining the distribution of AD pathology.

neuroscience↗

bioRxiv2024

Lesions that Cause Psychosis Map to a Common Brain Circuit in the Hippocampus

ImportanceIdentifying anatomy causally involved in psychosis could inform therapeutic neuromodulation targets for schizophrenia. ObjectiveTo assess whether lesions that cause secondary psychosis have functional connections to a common brain circuit. DesignThis case-control study mapped functional connections of published cases of lesions causing secondary psychosis compared with control lesions unassociated with psychosis. SettingThis study was conducted in a computational laboratory. ParticipantsPublished cases of lesion-induced psychosis were analyzed. Included subjects had documented brain lesions associated with new-onset psychotic symptoms without prior history of psychosis. Control cases included 1156 patients with lesions not associated with psychosis. Generalizability across lesional datasets was assessed using an independent cohort of 181 patients with brain lesions who subsequently underwent neurobehavioral testing. ExposuresLesions causing secondary psychosis. Main Outcomes and MeasuresPsychosis or no psychosis. Results153 lesions from published cases were determined to be causal of psychosis (65 [42%] male; mean [SD] age, 50.0 [20.8] years), 42 of which were described as "schizophrenia" or "schizophrenia-like". Lesions that caused secondary psychosis mapped to a common brain circuit defined by functional connectivity to the posterior subiculum of the hippocampus (84% functional overlap, pFWE<5 x 10-5). At a lower statistical threshold (75%> overlap, pFWE<5 x 10-4), this circuit included the ventral tegmental area, retrosplenial cortex, lobule IX and dentate nucleus of the cerebellum, and the mediodorsal and midline nuclei of the thalamus. This circuit was consistent when derived from "schizophrenia-like" cases (spatial r=0.98). We repeated these analyses after excluding lesions intersecting the hippocampus (n=47) and found a consistent functional connectivity profile (spatial r=0.98) with the posterior subiculum remaining the center of connectivity (>75% overlap, pFWE<5x10-5), demonstrating a circuit-level effect. In an independent observational cohort of patients with penetrating head trauma (n=181), lesions associated with symptoms of psychosis exhibited significantly similar connectivity profiles to the lesion-derived psychosis circuit (suspiciousness, p=0.025; unusual thought content, p=0.046). Voxels in the rostromedial prefrontal cortex (rmPFC) are highly correlated with this psychosis circuit (spatial r=0.82), suggesting the rmPFC as a promising TMS target for psychosis. Conclusions and RelevanceLesions that cause secondary psychosis affect a common brain circuit in the hippocampus. These results can help inform therapeutic neuromodulation targeting. Key PointsO_ST_ABSQuestionC_ST_ABSDo lesions that cause psychosis affect a common brain circuit? FindingsThis case-control study found that lesions causing psychosis specifically affected a common functional circuit aligning with the posterior subiculum of the hippocampus. This functional circuit was consistent across different psychotic symptoms, suggesting a shared neural substrate for psychosis. A similar circuit was derived when excluding lesions directly intersecting the hippocampus, indicating a circuit-level effect. MeaningIdentifying a common brain circuit causally involved in psychotic symptoms suggests that the hippocampus may be pivotal in the pathophysiology and treatment targeting of psychotic disorders.

neuroscience↗

bioRxiv2024

Translational control of microglial inflammatory and neurodegenerative responses

In Alzheimers Disease (AD), activation of the mechanistic target of rapamycin (mTOR) pathway is essential for microglia neuroprotective roles, but it is unclear which mTOR effectors promote these neuroprotective functions. The mTOR complex 1 (mTORC1) inactivates the translation suppressors eukaryotic translation Initiation Factor 4E (eIF4E)-Binding Proteins (4E-BP) to promote mRNA translation. We show that 4E-BP1 inactivation is impaired in microglia under AD-relevant conditions. Depleting 4E-BPs in microglia increases mitochondrial metabolism, suppresses the pro-inflammatory profile, and mitigates amyloid-induced apoptosis. Furthermore, in the cerebrospinal fluid of patients with amyloid pathology, there was a positive association between microglia activation and neurodegeneration, which increases along 4E-BP1 levels. Thus, we propose the engagement mTORC1-4E-BP1 axis as a neuroprotective mechanism and a therapeutic target or biomarker for microglia modulation in AD.

neuroscience↗

bioRxiv2023

Disease progression modelling reveals heterogeneity in trajectories of Lewy-type alpha-synuclein pathology

Lewy body (LB) disorders, characterized by the aggregation of misfolded -synuclein proteins, exhibit notable clinical heterogeneity. This may be due to variations in accumulation patterns of LB neuropathology. By applying data-driven disease progression modelling to regional neuropathological LB density scores from 814 brain donors, we describe three inferred trajectories of LB pathology that were characterized by differing clinicopathological presentation and longitudinal antemortem clinical progression. Most donors (81.9%) showed earliest pathology in the olfactory bulb, followed by accumulation in either limbic (60.8%) or brainstem (21.1%) regions. The remaining donors (18.1%) exhibited the first abnormalities in brainstem regions. Early limbic pathology was associated with Alzheimers disease-associated characteristics. Meanwhile, brainstem-first pathology was associated with progressive motor impairment and substantial LB pathology outside of the brain. Our data provides evidence for heterogeneity in the temporal spread of LB pathology, possibly explaining some of the clinical disparities observed in LBDs.

pathology↗

bioRxiv2023

Personalised Regional Modelling Predicts Tau Progression in the Human Brain

Aggregation of the hyperphosphorylated tau protein is a central driver of Alzheimers disease, and its accumulation exhibits a rich spatio-temporal pattern that unfolds during the course of the disease, sequentially progressing through the brain across axonal connections. It is unclear how this spatio-temporal process is orchestrated - namely, to what extent the spread of pathologic tau is governed by transport between brain regions, local production or both. To address this, we develop a mechanistic model from tau PET data to describe tau dynamics along the Alzheimers disease timeline. Our analysis reveals longitudinal changes in production and transport dynamics on two independent cohorts, with subjects in early stage of the disease exhibiting transport-dominated spread, consistent with an initial spread of pathologic tau seeds, and subjects in late stage disease (Braak stage 3/4 onwards) characterised primarily by local production of tau. Furthermore, we demonstrate that the model can accurately predict subject-specific longitudinal tau accumulation at a regional level, potentially providing a new clinical tool to monitor and classify patient disease progression. TeaserA mechanistic model reveals tau protein dynamics in Alzheimers, showing stage-specific shifts in transport and local production.

neuroscience↗

bioRxiv2022

The molecular genetic landscape of human brain size variation

Human brain size increases dynamically through early development, peaks in adolescence, and varies up to two-fold among adults. Although previous studies have elucidated changes in brain size across evolution, development, traits, and diseases, the molecular underpinnings of interindividual variation in brain size remain unknown. Here, we leverage postmortem brain RNA sequencing and estimates of brain weight (BW) in 2,531 individuals across three independent datasets, to identify 928 genes that show genome-wide significant associations with either higher or lower BW (BW+, BW-, respectively). These BW gene sets showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto developmental, functional and cellular axes of brain organization. Expression differences among evolutionarily conserved BW genes were predictive of interspecies differences in brain size, and functional annotation of BW genes revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses of in vivo neuroimaging phenotypes confirmed that the genetic regulation of BW-transcripts influences cortical surface area and volume, as well as behavioral traits related to brain function and disease. Cumulatively, our study represents a major step towards the goal of delineating the causal mechanisms of human brain size variation in health and disease.

neuroscience↗

bioRxiv2022

Conserved whole-brain spatiomolecular gradients shape adult brain functional organization

Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression of morphogens and transcription factors. However, how these gradients relate to adult brain function, and whether they are maintained in the adult brain, remains unknown. Here we uncover three axes of topographic variation in gene expression in the adult human brain that specifically capture previously identified rostral-caudal, dorsal-ventral and medial-lateral axes of early developmental patterning. The interaction of these spatiomolecular gradients i) accurately predicts the location of unseen brain tissue samples, ii) delineates known functional territories, and iii) explains the topographical variation of diverse cortical features. The spatiomolecular gradients are distinct from canonical cortical functional hierarchies differentiating primary sensory cortex from association cortex, but radiate in parallel with the axes traversed by local field potentials along the cortex. We replicate all three molecular gradients in three independent human datasets as well as two non-human primate datasets, and find that each gradient shows a distinct developmental trajectory across the lifespan. The gradients are composed of several well known morphogens (e.g., PAX6 and SIX3), and a small set of genes shared across gradients are strongly enriched for multiple diseases. Together, these results provide insight into the developmental sculpting of functionally distinct brain regions, governed by three robust transcriptomic axes embedded within brain parenchyma.

neuroscience↗

bioRxiv2022

Curation of BIDS (CuBIDS): a workflow and software package for streamlining reproducible curation of large BIDS datasets

The Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled "Curation of BIDS" (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad--a version control software package for data--to ensure reproducibility and provenance tracking throughout the entire curation process. CuBIDS provides tools to help users perform quality control on their images metadata and identify unique combinations of imaging parameters. Users can then execute BIDS Apps on a subset of participants that represent the full range of acquisition parameters that are present, accelerating pipeline testing on large datasets. HIGHLIGHTSO_LICuBIDS is a workflow and software package for curating BIDS data. C_LIO_LICuBIDS summarizes the heterogeneity in a BIDS dataset. C_LIO_LICuBIDS prepares BIDS data for successful preprocessing pipeline runs. C_LIO_LICuBIDS helps users perform metadata-based quality control. C_LI

neuroscience↗

bioRxiv2022

Molecular and connectomic vulnerability shape cross-disorder cortical abnormalities

Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21 000 patients and N = 26 000 controls, collected using a harmonized processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find that regional molecular vulnerability and macroscale brain network architecture interact to drive the spatial patterning of cortical abnormalities in multiple disorders. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, medial temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local biological attributes and global connectivity jointly shape cross-disorder cortical abnormalities.

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bioRxiv2021

Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth

The spatial layout of large-scale functional brain networks differs between individuals and is particularly variable in association cortex that has been implicated in a broad range of psychiatric disorders. However, it remains unknown whether this variation in functional topography is related to major dimensions of psychopathology in youth. Capitalizing on a large sample with 27-minutes of high-quality functional MRI data (n=790, ages 8-23 years) and advances in machine learning, we examined associations between functional topography and four correlated dimensions of psychopathology (fear, psychosis, externalizing, anxious-misery) as well as an overall psychopathology factor. We found that functional topography significantly predicted individual differences in dimensions of psychopathology, driven mainly by robust associations between topography and overall psychopathology. Reduced cortical representations of association networks were among the most important features of the model. Our results emphasize the value of considering systematic differences in functional neuroanatomy for personalized diagnostics and therapeutics in psychiatry.

neuroscience↗

bioRxiv2021

Differentiating amyloid beta spread in autosomal dominant and sporadic Alzheimer's disease

Amyloid-beta (A{beta}) deposition is one of the hallmark pathologies in both sporadic Alzheimers disease (sAD) and autosomal dominant Alzheimers disease (ADAD), the latter of which is caused by mutations in genes involved in A{beta} processing. Despite A{beta} deposition being a centerpiece to both sAD and ADAD, some differences between these AD subtypes have been observed with respect to the spatial pattern of A{beta}. Previous work has shown that the spatial pattern of A{beta} in individuals spanning the sAD spectrum can be reproduced with high accuracy using an epidemic spreading model (ESM), which simulates the diffusion of A{beta} across neuronal connections and is constrained by individual rates of A{beta} production and clearance. However, it has not been investigated whether A{beta} deposition in the rarer ADAD can be modeled in the same way, and if so, how congruent the spreading patterns of A{beta} across sAD and ADAD are. We leverage the ESM as a data-driven approach to probe individual-level variation in the spreading patterns of A{beta} across three different large-scale imaging datasets (2 SAD, 1 ADAD). We applied the ESM separately to the Alzheimers Disease Neuroimaging initiative (N=737), the Open Access Series of Imaging Studies (N=510), and the Dominantly Inherited Alzheimers Network (N=249), the latter two of which were processed using an identical pipeline. We assessed inter- and intra-individual model performance in each dataset separately, and further identified the most likely epicenter of A{beta} spread for each individual. Using epicenters defined in previous work in sAD, the ESM provided moderate prediction of the regional pattern of A{beta} deposition across all three datasets. We further find that, while the most likely epicenter for most A{beta}-positive subjects overlaps with the default mode network, 13% of ADAD individuals were best characterized by a striatal origin of A{beta} spread. These subjects were also distinguished by being younger than ADAD subjects with a DMN A{beta} origin, despite having a similar estimated age of symptom onset. Together, our results suggest that most ADAD patients express A{beta} spreading patters similar to those of sAD, but that there may be a subset of ADAD patients with a separate, striatal phenotype.

neuroscience↗

bioRxiv2021

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure. Furthermore, we provide open resources to support future advances towards adoption of brain charts as standards for quantitative benchmarking of typical or atypical brain MRI scans.

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