Biology subjects

Gardner, M.

Publications and source records attributed to Gardner, M..

17 recordsLinked to original sources

bioRxiv2026

Charting neuroimaging-based head circumference and cranial shape across development

Quantitative assessment of head growth supports early detection of neurological disease, yet current clinical practice relies on manual measurements that are variable, anatomically limited, and difficult to scale. Here we introduce a fully automated imaging-native framework (CranioTrace) that transforms routine neuroimaging into standardized, population-referenced markers of cranial development. By integrating topology-constrained segmentation, contour regularization, and geometry-based quality control for automated slice selection, CranioTrace robustly extracts head circumference and cranial morphology from heterogeneous MRI and CT data without manual intervention. The framework enabled construction of sex-specific population growth models across pediatric development in a dataset comprising 9,685 scans spanning birth to early adulthood across 25 cohorts. Imaging-derived head circumference shows strong agreement with tape measurements across independent datasets, high reproducibility (intraclass correlation up to 0.99), and consistent performance across modalities. Beyond conventional head circumference, CranioTrace quantifies cranial shape and asymmetry, capturing developmental dynamics that are not accessible through conventional measurements. Population modeling reveals rapid early-life expansion followed by nonlinear deceleration and stable sex differences. Application to neurogenetic cohorts identifies disease-consistent shifts in growth trajectories: head circumference was higher in neurofibromatosis type 1 and 16p11.2 deletion and lower in 22q11.2 deletion and 16p11.2 duplication. By converting clinical imaging archives into scalable cranial phenotypes linked to probabilistic reference models, CranioTrace provides a foundation for imaging-based growth charting, integrated skull-brain phenotyping, and precise assessment of neurodevelopment.

neuroscience↗

bioRxiv2026

Brain charts for neuroanatomical sex differences across the human lifespan

Population-level sex differences in human neuroanatomy have been highly debated, with prior literature limited by narrow age windows and assumptions about regions scaling with total brain size. Building on recent work charting brain structures across the lifespan, we use magnetic resonance imaging data from over 100,000 individuals (51.7% F) to model normative reference trajectories of 241 structural features capturing age-varying sex effects. Results show replicable age-varying sex differences in nearly all features, and sexs effects survive nonlinear correction for total brain size, with sex biases tending to increase across the lifespan. Notably, models are sensitive to atypicalities in six neuropsychiatric disorders. This work establishes and quantifies population-level sex biases in the largest-to-date study of sex differences in the human brain.

neuroscience↗

bioRxiv2025

Conditional-longitudinal brain growth charts detect MRI changes with birth weight and psychopathology

ImportanceBrain maturation varies between individuals, particularly during dynamic developmental periods like adolescence. Directly assessing differences in longitudinal trajectories can reveal deviations from normative patterns. ObjectiveWe present novel conditional-longitudinal normative models that characterize variability in brain maturation. We utilize these models to examine whether differences in longitudinal trajectories are associated with birth weight (BW), gestational age (GA), and longitudinal psychopathology derived from behavioral assessments. DesignCross-sectional and conditional-longitudinal normative models were developed for brain volumes derived from the first two neuroimaging timepoints from the Adolescent Brain Cognitive Development (ABCD) Study. Conditional-longitudinal models index an individuals expected brain volume at follow-up conditioned on their baseline measurement. Models were fit with split-half cross-validation on demographically matched samples. SettingThe ABCD Study is a multi-site, population-based study ParticipantsParticipants were excluded based on imaging quality flags and missing data, leaving 10,830 at baseline and 7,262 at follow-up. ExposuresBW and GA were derived from parent-report questionnaires. General psychopathology scores were calculated using a bifactor model. Main Outcomes and MeasuresWe calculated cross-sectional and conditional-longitudinal centiles, respectively quantifying individual deviations in size and change between timepoints. Sensitivity analyses included covariates for parental income and education as well as current weight and height. ResultsThe sample was 10,830 at baseline (48.2% F,age 9-10y) and 7,262 at follow-up (46.6% F,age 11-13y). Conditional-longitudinal centiles were sensitive to individual differences in brain change between timepoints. Lower BW was associated with lower conditional-longitudinal centiles, suggesting larger decreases in brain volumes over time (27 regions pfdr<0.05, {beta}max=0.08). Lower conditional-longitudinal centiles were associated with greater increases in psychopathology scores, suggesting with increased psychopathology brain volumes show greater decrease (37 regions pfdr<0.05, {beta}max=0.06). Notably, changes in psychopathology were not related to brain size at either timepoint, indexed by cross-sectional centiles. Conclusions and RelevanceModels that capture individual-level deviations from expected growth trajectories, rather than static positions on a growth curve, are particularly informative for assessing developmental change. Novel conditional-longitudinal models address this gap in lifespan brain imaging. Using this framework, we demonstrate robust associations between individual trajectory deviations, perinatal adversity, and longitudinally assessed mental health symptoms. Condition-longitudinal models hold promise for applications across psychiatric neuroscience, from development to aging. Key Points QuestionHow do differences in brain maturation trajectories, quantified by novel conditional-longitudinal models, relate to perinatal factors and mental health in adolescence? FindingsIn this longitudinal analysis of neuroimaging data from the Adolescent Brain Cognitive Development (ABCD) Study, conditional-longitudinal normative models revealed that trajectories of brain maturation in adolescence are associated with birth weight, and with longitudinal changes in mental health. MeaningConditional longitudinal models detect inter-individual variability in brain maturation, which is related to both perinatal factors and concurrent changes in psychopathology.

neuroscience↗

bioRxiv2025

Calibration of MRI-based reference intervals to new samples

Reference intervals, defined as intervals containing a new observation with a specified probability relative to reference data, would be clinically useful in assessing brain magnetic resonance imaging (MRI). Brain charts, which are estimates of MRI phenotypes across covariates such as age and sex, can be used to construct reference intervals. However, the reference data used to fit intervals often differs from a new sample in terms of study design, MRI acquisition, and image preprocessing. Application of MRI reference intervals to new samples remains a challenging problem. Here, we propose a new method called Reference interval calibration via conFormal prediction (ReForm) that adjusts reference intervals for a new sample. Our method builds on recent work in conformal prediction, which yields intervals with guaranteed coverage for new observations. Through resampling experiments in Lifespan Brain Chart Consortium cortical thickness data, we compare ReFormed reference intervals to refitting intervals, statistical harmonization methods, and model-based adjustment of intervals. Notably for patient privacy concerns, ReForm does not require sharing of reference data. Yet, our empirical results demonstrate that ReForm controls FPR similarly or better than alternative methods which require sharing reference data. Finally, we provide recommendations for practical applications of ReForm and an R package (https://github.com/andy1764/ReForm) for calibrating reference intervals using ReForm.

neuroscience↗

bioRxiv2025

ComBat-Predict enhances generalizability of neuroimaging models to new sites

Neuroimaging is vital in quantifying brain atrophy due to typical aging and due to neurodegenerative diseases. To collect large samples necessary to model lifespan brain development, research consortiums aggregate images acquired across multiple study sites. Previous studies have demonstrated that this multi-site study design can lead to site-related bias, necessitating harmonization of these "site effects". However, current methodologies are unable to generalize to new sites outside the original harmonized sample, limiting translation to new sites or clinical practice. Here, we propose a method called ComBat-Predict (CB-Predict) building upon the ComBat method for site effect adjustment, which extends to data from a new site with smaller sample sizes and unknown site effects. In data from the Alzheimers Disease Neuroimaging Initiative (ADNI), our proposed method mitigates bias and yields high accuracy in predicting cortical thickness measures when generalizing the model to new data. Furthermore, we demonstrate that our proposed harmonization method can reduce site-related variance in centile scores estimated using data from the Lifespan Brain Chart Consortium (LBCC). Altogether, our results demonstrate that CB-Predict effectively harmonizes new sites and thereby enables effective translation of neuroimaging models to additional samples.

neuroscience↗

bioRxiv2025

Charting structural brain asymmetry across the human lifespan

Lateralization is a fundamental principle of structural brain organization. In vivo imaging of brain asymmetry is essential for deciphering lateralized brain functions and their disruption in neurodevelopmental and neurodegenerative disorders. Here, we present a normative framework for benchmarking brain asymmetry across the lifespan, developed from an aggregated sample of 128 primary neuroimaging studies, including 177,701 scans from 138,231 individuals, jointly spanning the age range from 20 post menstrual weeks to 102 years. This resource includes comprehensive, hemisphere-specific brain growth charts for multiple neuroimaging phenotypes: regional cortical grey matter volume, thickness, surface area, and subcortical volumes. Our findings reveal distinct spatial patterns of asymmetry, with early leftward asymmetry observed in association cortices and late rightward asymmetry in sensory regions. These trajectories support theories of the neuroplasticity of asymmetry and the role of both genetic and environmental factors in shaping brain lateralization. Additionally, we provide tools to generate asymmetry centile scores, which allow the quantification of individual deviations from typical asymmetry throughout the lifespan and can be applied to unseen data or clinical populations. We demonstrate the utility of these models by highlighting group-level differences in asymmetry in autism spectrum disorder, schizophrenia, and Alzheimers disease, and exploring genetic correlations with hemispheric specialization. To facilitate further research, we have made this normative framework freely available as an interactive open-access resource (upon publication), offering an essential tool to advance both basic and clinical neuroscience.

neuroscience↗

bioRxiv2025

Two stages of substrate discrimination dictate selectivity in the E. coli MetNI-Q ABC transporter system

The Escherichia coli MetNI-Q importer, an ATP-binding cassette (ABC) transporter, mediates the uptake of both L- and D-enantiomers of methionine. Original in vivo uptake studies show a strong preference for L-Met over D-Met, but the molecular basis of this selectivity is unclear. In this work, we systematically examine substrate discrimination by the MetNI transporter and MetQ substrate binding protein using an array of biophysical and biochemical techniques. Based on the kinetic and thermodynamic parameters of individual intermediates in the transport cycle, we uncover multiple steps in the transport cycle that confer substrate specificity. As in many other ABC importer systems, selectivity is applied at the level of binding to the substrate binding protein: MetQ dictates a 1,000-fold preference for L-Met over D-Met. However, beyond this initial level of selectivity, MetQ displays distinct binding preferences for the MetNI transporter depending on the substrate. We propose that the differences in binding affinities reflect the more favored release of L-Met into the permeation pathway when compared to D-Met. In support of this model, under saturating conditions, MetNI transports L-Met across the lipid bilayer at a faster rate than D-Met. Interestingly, the ATPase activity of the MetNI-Q complex is not modulated by the presence of substrate. Our studies reveal that the MetNI-Q system incorporates two separate steps in tuning methionine uptake to substrate chirality and availability. This method of discrimination ensures the import of the most biologically preferred substrate while also allowing for adaptability to more limiting nutrient conditions.

biochemistry↗

bioRxiv2024

dGAMLSS: An exact, distributed algorithm to fit Generalized Additive Models for Location, Scale, and Shape for privacy-preserving population reference charts

There is growing interest in estimating population reference ranges across age and sex to better identify atypical clinically-relevant measurements throughout the lifespan. For this task, the World Health Organization recommends using Generalized Additive Models for Location, Scale, and Shape (GAMLSS) which can model non-linear growth trajectories under complex distributions that address the heterogeneity in human populations. Fitting GAMLSS models requires large, generalizable sample sizes, especially for accurate estimation of extreme quantiles, but obtaining such multi-site data can be challenging due to privacy concerns and practical considerations. In settings where patient data cannot be shared, privacy-preserving distributed algorithms for federated learning can be used, but no such algorithm exists for GAMLSS. We propose distributed GAMLSS (dGAMLSS), a distributed algorithm which can fit GAMLSS models across multiple sites without sharing patient-level data. We demonstrate the effectiveness of dGAMLSS in constructing population reference charts across clinical, genomics, and neuroimaging settings.

bioinformatics↗

bioRxiv2024

Reproducible Sex Differences in Personalized Functional Network Topography in Youth

BackgroundA key step towards understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organization at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organization of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex. AimsWe aimed to evaluate the impact of sex on the spatial organization of person-specific functional brain networks. MethodWe leveraged person-specific atlases of functional brain networks defined using non-negative matrix factorization in a sample of n = 6437 youths from the Adolescent Brain Cognitive Development Study. Across independent discovery and replication samples, we used generalized additive models to uncover associations between sex and the spatial layout ("topography") of personalized functional networks (PFNs). Next, we trained support vector machines to classify participants sex from multivariate patterns of PFN topography. Finally, we leveraged transcriptomic data from the Allen Human Brain Atlas to evaluate spatial correlations between sex differences in PFN topography and gene expression. ResultsSex differences in PFN topography were greatest in association networks including the fronto-parietal, ventral attention, and default mode networks. Machine learning models trained on participants PFNs were able to classify participant sex with high accuracy. Brain regions with the greatest sex differences in PFN topography were enriched in expression of X-linked genes as well as genes expressed in astrocytes and excitatory neurons. ConclusionsSex differences in PFN topography are robust, replicate across large-scale samples of youth, and are associated with expression patterns of X-linked genes. These results suggest a potential contributor to the female-biased risk in depressive and anxiety disorders that emerge at the transition from childhood to adolescence.

neuroscience↗

bioRxiv2024

ComBatLS: A location- and scale-preserving method for multi-site image harmonization

Recent work has leveraged massive datasets and advanced harmonization methods to construct normative models of neuroanatomical features and benchmark individuals morphology. However, current harmonization tools do not preserve the effects of biological covariates including sex and age on features variances; this failure may induce error in normative scores, particularly when such factors are distributed unequally across sites. Here, we introduce a new extension of the popular ComBat harmonization method, ComBatLS, that preserves biological variance in features locations and scales. We use UK Biobank data to show that ComBatLS robustly replicates individuals normative scores better than other ComBat methods when subjects are assigned to sex-imbalanced synthetic "sites". Additionally, we demonstrate that ComBatLS significantly reduces sex biases in normative scores compared to traditional methods. Finally, we show that ComBatLS successfully harmonizes consortium data collected across over 50 studies. R implementation of ComBatLS is available at https://github.com/andy1764/ComBatFamily.

neuroscience↗

bioRxiv2023

Development of an Engineered Mycobacterium tuberculosis Strain for a Safe and Effective Tuberculosis Human Challenge Model

Human challenge experiments could greatly accelerate the development of a tuberculosis (TB) vaccine. Human challenge for tuberculosis requires a strain that can both replicate in the host and be reliably cleared. To accomplish this, we designed Mycobacterium tuberculosis (Mtb) strains featuring up to three orthogonal kill switches, tightly regulated by exogenous tetracyclines and trimethoprim. The resultant strains displayed immunogenicity and antibiotic susceptibility similar to wild-type Mtb under permissive conditions. In the absence of supplementary exogenous compounds, the strains were rapidly killed in axenic culture, mice and nonhuman primates. Notably, the strain that contained three kill switches had an escape rate of less than 10-10 per genome per generation and displayed no relapse in a SCID mouse model. Collectively, these findings suggest that this engineered Mtb strain could be a safe and effective candidate for a human challenge model.

microbiology↗

bioRxiv2022

Rewarding Value or Prediction Error: Settling the debate over the role of dopamine in reward learning

The discovery that DA transients can be mapped onto the reward prediction errors in temporal difference models is a pinnacle achievement of neuroscience. Yet, there is abundant evidence that DA activity reinforces actions, suggesting it serves as an intrinsically rewarding event. These two possibilities are so conceptually intertwined that it is not surprising that they have been so far experimentally conflated. Here, using computational modeling, behavioural blocking and optogenetics, we show that stimulating VTA DA neurons promotes learning even when a natural reward and DA stimulation are held constant across the learning phases of blocking. These findings provide strong evidence in favour of the prediction error hypothesis rather than encoding the rewarding value of appetitive events.

neuroscience↗

bioRxiv2020

Mutations from bat ACE2 orthologs markedly enhance ACE2-Fc neutralization of SARS-CoV-2

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein mediates infection of cells expressing angiotensin-converting enzyme 2 (ACE2). ACE2 is also the viral receptor of SARS-CoV (SARS-CoV-1), a related coronavirus that emerged in 2002-2003. Horseshoe bats (genus Rhinolophus) are presumed to be the original reservoir of both viruses, and a SARS-like coronavirus, RaTG13, closely related SARS-CoV-2, has been isolated from one horseshoe-bat species. Here we characterize the ability of S-protein receptor-binding domains (RBDs) of SARS-CoV-1, SARS-CoV-2, and RaTG13 to bind a range of ACE2 orthologs. We observed that the SARS-CoV-2 RBD bound human, pangolin, and horseshoe bat (R. macrotis) ACE2 more efficiently than the SARS-CoV-1 or RaTG13 RBD. Only the RaTG13 RBD bound rodent ACE2 orthologs efficiently. Five mutations drawn from ACE2 orthologs of nine Rhinolophus species enhanced human ACE2 binding to the SARS-CoV-2 RBD and neutralization of SARS-CoV-2 by an immunoadhesin form of human ACE2 (ACE2-Fc). Two of these mutations impaired neutralization of SARS-CoV-1. An ACE2-Fc variant bearing all five mutations neutralized SARS-CoV-2 five-fold more efficiently than human ACE2-Fc. These data narrow the potential SARS-CoV-2 reservoir, suggest that SARS-CoV-1 and -2 originate from distinct bat species, and identify a more potently neutralizing form of ACE2-Fc.

microbiology↗

bioRxiv2020

Devaluation-sensitive responding to preconditioned cues requires orbitofrontal cortex during initial cue-cue learning

The orbitofrontal cortex (OFC) is necessary for value inference in tests of model-based reasoning. This ability could be accounted for by either representation of value or by representation of broader associative structure. Our lab recently reported correlates of both value and of valueless associative structure in OFC using single-unit recording (Sadacca et al., 2018). This incidental stimulus-stimulus representation was surprising since OFC was thought to be involved only when items of biological significance were driving responses. However, we did not assess whether this activity was necessary for encoding the associative information that would contribute to value inference during probe testing. Here, we used optogenetic OFC inhibition during sensory preconditioning to test this. We found that OFC inhibition during preconditioning impaired value inference during the probe test, demonstrating that the correlates we previously observed are not simply downstream readouts of sensory processing and instead contribute to encoding valueless sensory associative information.

neuroscience↗

bioRxiv2019

Tagging allows faithful tracing of expression and enhances biochemical detection of Ran Binding Protein 9 in vivo.

The lack of tools to reliably detect RanBP9 in vivo has significantly hampered progress in understanding the biological functions of this scaffold protein. We report here the generation of a novel mouse strain, RanBP9-TT, in which the endogenous protein is fused with a double (V5-HA) epitope tag at the C-terminus. We show that the double tag does not interfere with the essential functions of RanBP9. In contrast to RanBP9 constitutive knock-out animals, RanBP9-TT mice are viable, fertile and do not show any obvious phenotype. The V5-HA tag allows unequivocal detection of RanBP9 both by IHC and WB. Importantly, immunoprecipitation and mass spectrometry analyses reveal that the tagged protein pulls down known interactors of wild type RanBP9. Thanks to the increased detection power, we are also unveiling a novel interaction with Nucleolin, a prominent nucleolar protein. In summary, we report the generation of a new mouse line in which RanBP9 expression and interactions can be reliably studied by the use of commercially available tag antibodies. The use of this line will help to overcome some of the existing limitations in the study of RanBP9 and potentially reveal novel functions of this protein in vivo such as those linked to Nucleolin.

bioengineering↗

bioRxiv2018

New inhibitors of Mycobacterium tuberculosis identified using systems chemical biology

New antibiotics are needed to combat rising resistance, with new Mycobacterium tuberculosis (Mtb) drugs of highest priority. Conventional whole-cell and biochemical antibiotic screens have failed. We developed a novel strategy termed PROSPECT (PRimary screening Of Strains to Prioritize Expanded Chemistry and Targets) in which we screen compounds against pools of strains depleted for essential bacterial targets. We engineered strains targeting 474 Mtb essential genes and screened pools of 100-150 strains against activity-enriched and unbiased compounds libraries, measuring > 8.5-million chemical-genetic interactions. Primary screens identified >10-fold more hits than screening wild-type Mtb alone, with chemical-genetic interactions providing immediate, direct target insight. We identified > 40 novel compounds targeting DNA gyrase, cell wall, tryptophan, folate biosynthesis, and RNA polymerase, as well as inhibitors of a novel target EfpA. Chemical optimization yielded EfpA inhibitors with potent wild-type activity, thus demonstrating PROSPECTs ability to yield inhibitors against novel targets which would have eluded conventional drug discovery.

microbiology↗

bioRxiv2018

ATRAID, a genetic factor that regulates the clinical action of nitrogen-containing bisphosphonates on bone.

Nitrogen-containing bisphosphonates (N-BPs), such as alendronate, are the most widely prescribed medications for diseases involving bone, with nearly 200 million prescriptions written annually. Recently, widespread use of N-BPs has been challenged due to the risk of rare but traumatic side effects such as atypical femoral fracture (AFFs) and osteonecrosis of the jaw (ONJ). N-BPs bind to and inhibit farnesyl diphosphate synthase (FDPS), resulting in defects in protein prenylation. Yet it remains poorly understood what other cellular factors might allow N-BPs to exert their pharmacological effects. Here, we performed genome-wide studies in cells and patients to identify the poorly characterized gene, ATRAID. Loss of ATRAID function results in selective resistance to N-BP-mediated loss of cell viability and the prevention of alendronate-mediated inhibition of prenylation. ATRAID is required for alendronate inhibition of osteoclast function, and ATRAID-deficient mice have impaired therapeutic responses to alendronate in both postmenopausal and senile (old age) osteoporosis models. Lastly, we performed exome sequencing on patients taking N-BPs that suffered ONJ or an AFF. ATRAID is one of three genes that contain rare non-synonymous coding variants in patients with ONJ or AFF that is also differentially expressed in poor outcome groups of patients treated with N-BPs. We functionally validated this patient variation in ATRAID as conferring cellular hypersensitivity to N-BPs. Our work adds key insight into the mechanistic action of N-BPs and the processes that might underlie differential responsiveness to N-BPs in people. One Sentence SummaryATRAID is essential for responses to the commonly prescribed osteoporosis drugs nitrogen-containing bisphosphonates. OverlineBONE

genomics↗