Biology subjects

Lawrence, K. E.

Publications and source records attributed to Lawrence, K. E..

14 recordsLinked to original sources

bioRxiv2026

Structural brain alterations in autism: A large-scale voxel-based morphometry mega-analysis

BackgroundPrevious large-scale structural MRI analyses of the brain in autism have identified gray matter (GM) differences when using region-of-interest analyses based on gross anatomical regions. However, such analyses have limited spatial specificity and may obscure subtle focal differences. Whole brain voxel-based morphometry (VBM) analyses enable greater spatial precision to identify and localize previously undetected neuroanatomical alterations. PurposeTo rigorously identify voxel-wise GM and white matter (WM) volume differences in autism in the largest VBM mega-analysis to date. Materials and MethodsThis retrospective mega-analysis included structural 3D volumetric T1-weighted MRI brain scans from 3,051 participants (15.0 {+/-} 8.2 yrs; 76.8% male; 1,519 autism; 1,532 neurotypicals) collected across 51 sites/scanners. Voxel-wise GM and WM volumes were quantified using the ENIGMA CAT12 VBM pipeline. Linear mixed-effects regression was performed at each voxel to evaluate the association between diagnostic group and voxel-wise volume while adjusting for standard nuisance covariates ResultsAutism was associated with widespread lower GM volume involving cortical, subcortical, and cerebellar regions (peak t=7.39, peak {beta}=0.13); such GM differences were most notably detected in the bilateral orbitofrontal cortex, amygdala, thalamus, and posterior lobes of the cerebellum. WM volume was lower in autism across major projection, commissural, association, and cerebellar/brainstem tracts (peak t=6.74, peak {beta}=0.08), including the corona radiata, internal capsule, corpus callosum, and cerebellar peduncles. These findings remained consistent in sensitivity analyses, including covarying for full-scale IQ and the application of increasingly strict motion exclusion criteria. ConclusionAutism is associated with smaller voxel-wise GM and WM volume involving widespread cortical, subcortical, and cerebellar regions. This high-resolution identification and localization of structural brain differences support the involvement of distributed neural systems in autism that underlie reward processing, sensory integration, and motor functioning in autism. Summary statementIn the largest voxel-based morphometry study of autism to date, widespread smaller gray and white matter volumes were identified across distributed brain regions implicated in reward and sensorimotor function. Key ResultsO_LIOur largest voxel-based morphometry mega-analysis to date in autism (N=3,051), identified widespread gray and white matter alterations (peak t=7.39, peak {beta}=0.13). C_LIO_LIWe reveal novel associations within thalamic mediodorsal nuclei by leveraging finer voxel-wise volumetric analyses. C_LIO_LIAdditional associations in orbitofrontal cortex, amygdala, and cerebellum, along with extensive white matter alterations across projection, commissural, association fibers, reinforce reward-processing, sensory and motor development theories in autism. C_LI

neuroscience↗

bioRxiv2026

The Regional Vulnerability Index (RVI) as a Neuroimaging-Based Biomarker for Autism: Associations with Likelihood, Cognition, and Longitudinal Social Outcomes

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with symptoms spanning cognitive, social and behavioral domains and leading to lifelong challenges. Autism is heritable but specific genetic and environmental factors that shape its early neurodevelopmental trajectory remain unknown. Despite the clinical variability, neuroimaging findings from Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA)-ASD consortium identified stable and replicable patterns of cortical and subcortical differences that were consistent with those reported by an independent consortium, the Cognitive Genetics Collaborative Research Organization (COCORO) in Japan. Here we developed and evaluated a regional vulnerability index (RVI), a similarity metric that quantifies how closely a persons brain resembles the specific pattern of an individual with autism. RVI-ASD is based on combining the regional effect sizes for regional brain measurements published by the ENIGMA-ASD group with microstructural white matter integrity differences reported by COCORO. RVI-ASD showed significantly higher effect size for case-control differences relative to any individual brain measure (d=0.30 vs. d=0.01-0.21) in individuals with autism, particularly in the adolescent-to-adult sample (N=2,577; Mean age = 16.1; SD=5.0). We next calculated RVI-ASD in the baseline and follow-up (ages 10 and 12) data from normally developing participants of the ABCD study (N=4,201). We tested the longitudinal stability, heritability, genotype-by-age interaction and sensitivity of RVI-ASD to known factors and cognitive measurements. RVI-ASD were stable on the 2-year follow up (ICC=0.76-0.92); showed significant heritability (h{superscript 2}=0.55-0.83, p<10-16) but was not affected by gene-by-age interaction. RVI-ASD showed significant positive correlation with paternal age, while correlation with maternal age was non-significant. Baseline and follow-up RVI-ASD were negatively correlated with cognitive measures including total, fluid and crystallized intelligence (r=-0.09 to -0.11, p<10-6). RVI-ASD scores tracked with core autism phenotypes including poor eye contact and rigid routines (p < .01). In a sub-sample of children with symptoms of autism (N=20), we found that earlier age of symptom onset was strongly correlated with higher White Matter RVI (r = -0.61), linking early behavioral emergence to the neuroanatomical signature. Longitudinal changes in subcortical RVI-ASD are significantly correlated with change in social functioning. The RVI-ASD is a neuroimaging-based biomarker linked to stable and reproducible brain patterns in autism. RVI-ASD allows researchers to study associations with factors associated with the likelihood for autism and cognition across large and inclusive non-clinical samples, thus moving beyond simple case-control models to understand the biological pathways of autism.

neuroscience↗

bioRxiv2026

Distributional and Centile Calibration of Diffusion Tensor Imaging Normative Models as Training Sample Sizes Increase to 40,000 Subjects

Normative modeling (NM) is a powerful framework for quantifying individual deviations in brain structure and function relative to a population reference. However, its clinical utility depends on well-calibrated models trained on heterogeneous datasets such as those found in neuroimaging. Here, we systematically examine the effect of training sample size on the distributional and centile calibration of hierarchical Bayesian regression (HBR)-based NMs. Using multisite 3D diffusion MRI scans of the brain from 54,583 subjects, spanning almost the entire lifespan (age: 4-91 years), we trained NMs of white matter fractional anisotropy, a key microstructural metric, on subsamples ranging from 5,000 to 40,000 subjects. HBR was modeled with a Sinh-Arcsinh likelihood. Model calibration was evaluated using Kernelized Stein Discrepancy (KSD) to assess distributional agreement of Z-scores with the standard normal distribution; we also used Mean Absolute Centile Error (MACE) to quantify centile accuracy. Both metrics showed consistent and substantial improvements as the training sample size increased, indicating reduced posterior uncertainty and improved estimation of distributional parameters, particularly at the centile extremes. These results demonstrate that large training cohorts are essential for well-calibrated NMs derived from heterogeneous neuroimaging data and highlight the importance of large-scale data aggregation for reliable individual-level inference.

bioinformatics↗

bioRxiv2025

Mapping Along-Tract White Matter Microstructural Differences in Autism

Previous diffusion magnetic resonance imaging (dMRI) research has indicated altered white matter microstructure in autism, but the implicated regions are highly inconsistent across studies. Such prior work has largely used conventional dMRI analysis methods, including the traditional microstructure model, based on diffusion tensor imaging (DTI). However, these methods are limited in their ability to precisely map microstructural differences and accurately resolve complex fiber configurations. In our study, we investigated white matter microstructure alterations in autism using the refined along-tract analytic approach, BUndle ANalytics (BUAN), and an advanced microstructure model, the tensor distribution function (TDF). We analyzed dMRI data from 365 autistic and neurotypical participants (5-24 years; 34% female) from 10 cohorts to examine commissural and association tracts. Autism was associated with lower fractional anisotropy and higher diffusivity in localized portions of nearly every commissural and association tract examined; these tracts inter-connected a wide range of brain regions, including frontal, temporal, parietal, and occipital. Taken together, BUAN and TDF allow robust and spatially precise mapping of microstructural properties in autism. Our findings rigorously demonstrate that white matter microstructure alterations in autism may be greater within specific regions of individual tracts, and that the implicated tracts are distributed across the brain.

neuroscience↗

bioRxiv2024

Oral and faecal viromes of New Zealand calves on pasture with an idiopathic ill-thrift syndrome

Since 2015, an idiopathic ill-thrift syndrome featuring diarrhoea and, in some cases, gastrointestinal ulceration has been reported in weaned New Zealand dairy calves. Similar syndromes have been described in the British Isles and Australia, but investigations in New Zealand have yet to identify a specific cause. Notably, the viromes of affected calves remain understudied. We conducted metatranscriptomic analyses of oral and faecal viromes in 11 calves from a dairy farm in Taranaki, New Zealand experiencing an outbreak of this syndrome. This included nine symptomatic calves. Our analysis identified 18 bovine-associated viruses across two DNA and three RNA viral families, including five novel species. Oral viromes were dominated by Pseudocowpox virus, detected in all calves with oral lesions. Faecal viromes were more diverse, featuring adenoviruses, caliciviruses, astroviruses, and picornaviruses. Bovine bopivirus, from the Picornaviridae family and previously unreported in New Zealand, was significantly associated with calves showing oral lesions and diarrhoea, indicating a possible link to disease, though its role remains unclear. The diverse viral communities in the calves complicates identifying a single causative agent. Importantly, no novel viruses were significantly associated with the syndrome, and the viromes closely resembled those found in cattle globally. These findings suggest the syndrome likely has a multifactorial origin involving nutritional, management, and environmental factors rather than being driven primarily by known or novel viruses. Further research across regions and seasons is recommended to clarify the role of viruses in idiopathic ill-thrift among New Zealand calves.

microbiology↗

bioRxiv2024

Lifespan Normative Modeling of Brain Microstructure

Normative models of brain metrics based on large populations could be extremely valuable for detecting brain abnormalities in patients with a variety of disorders, including degenerative, psychiatric and neurodevelopmental conditions, but no such models exist for the brains white matter (WM) microstructure. Here we present a large-scale normative model of brain WM microstructure - based on 19 international diffusion MRI datasets covering almost the entire lifespan (totaling N=54,583 individuals; age: 4-91 years). We extracted regional diffusion tensor imaging (DTI) metrics using a standardized analysis and quality control protocol and used hierarchical Bayesian regression (HBR) to model the statistical distribution of derived WM metrics as a function of age and sex. We extracted the average lifespan trajectories and corresponding centile curves for each WM region. We illustrate the utility of the method by applying it to detect and visualize profiles of WM microstructural deviations in a variety of contexts: in mild cognitive impairment, Alzheimers disease, and 22q11.2 deletion syndrome - a neurogenetic condition that markedly increases risk for schizophrenia. The resulting large-scale model provides a common reference to identify disease effects on the brains microstructure in individuals or groups, and to compare disorders, and discover factors affecting WM abnormalities. The derived normative models are a valuable resource publicly available to the community, adaptable and extendable to future datasets as the available data expands.

neuroscience↗

bioRxiv2024

White Matter Microstructural Alterations in Autism Localized with Bundle Analytics

Previous diffusion magnetic resonance imaging research in autism has reported altered microstructure in the corpus callosum (CC), the major commissure connecting the two brain hemispheres. However, the CC consists of many fibers connecting various brain regions, and the precise localization of these differences in autism remains unclear. Additionally, the conventional diffusion tensor imaging (DTI) model cannot resolve complex fiber configurations and may miss subtle alterations. In this study, we investigated CC microstructure in 365 participants (5-25 years; 34.0% female; 195 with autism) from 10 sites/scanners by using a novel along-tract mapping method, BUndle ANalytics (BUAN), and advanced microstructure model, the tensor distribution function (TDF). Autism was associated with regionally specific reductions in white matter integrity and elevations in diffusivity. The TDF model detected CC microstructure differences more sensitively than DTI. Taken together, BUAN and TDF allow for precise and rigorous white matter analyses, enhancing the detection of subtle neural differences.

neuroscience↗

bioRxiv2024

The neuroendocrine transition in prostate cancer is dynamic and dependent on ASCL1

Lineage plasticity is a recognized hallmark of cancer progression that can shape therapy outcomes. The underlying cellular and molecular mechanisms mediating lineage plasticity remain poorly understood. Here, we describe a versatile in vivo platform to identify and interrogate the molecular determinants of neuroendocrine lineage transformation at different stages of prostate cancer progression. Adenocarcinomas reliably develop following orthotopic transplantation of primary mouse prostate organoids acutely engineered with human-relevant driver alterations (e.g., Rb1-/-; Trp53-/-; cMyc+ or Pten-/-; Trp53-/-; cMyc+), but only those with Rb1 deletion progress to ASCL1+ neuroendocrine prostate cancer (NEPC), a highly aggressive, androgen receptor signaling inhibitor (ARSI)-resistant tumor. Importantly, we show this lineage transition requires a native in vivo microenvironment not replicated by conventional organoid culture. By integrating multiplexed immunofluorescence, spatial transcriptomics and PrismSpot to identify cell type-specific spatial gene modules, we reveal that ASCL1+ cells arise from KRT8+ luminal epithelial cells that progressively acquire transcriptional heterogeneity, producing large ASCL1+;KRT8- NEPC clusters. Ascl1 loss in established NEPC results in transient tumor regression followed by recurrence; however, Ascl1 deletion prior to transplantation completely abrogates lineage plasticity, yielding adenocarcinomas with elevated AR expression and marked sensitivity to castration. The dynamic feature of this model reveals the importance of timing of therapies focused on lineage plasticity and offers a platform for identification of additional lineage plasticity drivers.

cell biology↗

bioRxiv2024

Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models

Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical individuals across a wide developmental age (N=239, aged 5-22 years). We used the conventional diffusion-weighted MRI (dMRI) model, diffusion tensor imaging (DTI), and two advanced dMRI models, the tensor distribution function (TDF) and neurite orientation dispersion density imaging (NODDI) to assess WM microstructure. WM microstructure exhibited significant, regionally consistent sex differences across the brain during typical development. Additionally, the TDF model was most sensitive in detecting sex differences. These findings highlight the importance of considering sex in neurodevelopmental research and underscore the value of the advanced TDF model.

neuroscience↗

bioRxiv2022

Allosteric interactions prime androgen receptor dimerization and activation

The androgen receptor (AR) is a steroid receptor and master transcription factor that governs gene expression programs required for luminal development of prostate epithelium, formation of muscle tissue and maintenance of the male phenotype. AR misregulation is a hallmark of multiple malignancies, including prostate cancer, where AR hyperactivation and expansion of its transcriptome occur in part through AR gene amplification and interaction with oncoprotein cofactors. Despite its biological importance, how ARs individual domains and its protein cofactors cooperate to bind DNA have remained elusive. Using a combination of reconstitution biochemistry and single particle cryo-electron microscopy (EM), we have isolated three conformational states of AR bound to DNA. We observe that AR forms a non-obligate dimer, with the buried dimer interface utilized by related ancestral nuclear receptors repurposed to facilitate cooperative DNA binding. We identify surfaces bridging ARs domains responsible for allosteric communication, that are compromised in partial androgen insensitivity syndrome (PAIS), and are reinforced by ARs oncoprotein cofactor, ERG, and DNA binding site motifs. Finally, we present evidence that this plastic dimer interface for transcriptional activation may have been adopted by AR at the expense of DNA binding. Our work highlights how fine-tuning of ARs cooperative interactions translate to consequences in development and disease.

biochemistry↗

bioRxiv2022

A new immunocompetent rectal cancer model to study radiation therapy

We describe a new mouse model of rectal cancer (RC) involving rapid tumor organoid engraftment via orthotopic transplantation; the resulting RC tumors invaded inward from the mucosal surface and metastasized to distant organs. Histologically the tumors closely resemble human RC and mirror remodeling of the tumor microenvirnoment (TME) in response to radiation. This murine RC model thus recapitulates the pathogenesis of human RC, thereby fulfilling the need for a physiologically accurate model for preclinical efficacy studies.

cancer biology↗

bioRxiv2021

White matter microstructure shows sex differences in late childhood: Evidence from 6,797 children

Sex differences in white matter microstructure have been robustly demonstrated in the adult brain using both conventional and advanced diffusion-weighted magnetic resonance imaging (dMRI) approaches. However, sex differences in white matter microstructure prior to adulthood remain poorly understood; previous developmental work focused on conventional microstructure metrics and yielded mixed results. Here we rigorously characterized sex differences in white matter microstructure among over 6,000 children from the Adolescent Brain Cognitive Development (ABCD) Study who were between 9 and 10 years old. Microstructure was quantified using both the conventional model - diffusion tensor imaging (DTI) - and an advanced model, restriction spectrum imaging (RSI). DTI metrics included fractional anisotropy (FA) and mean, axial, and radial diffusivity (MD, AD, RD). RSI metrics included normalized isotropic, directional, and total intracellular diffusion (N0, ND, NT). We found significant and replicable sex differences in DTI or RSI microstructure metrics in every white matter region examined across the brain. Sex differences in FA were regionally specific. Across white matter regions, boys exhibited greater MD, AD, and RD than girls, on average. Girls displayed increased N0, ND, and NT compared to boys, on average, suggesting greater cell and neurite density in girls. Together, these robust and replicable findings provide an important foundation for understanding sex differences in health and disease.

neuroscience↗

bioRxiv2020

Exogenous sex hormone effects on brain microstructure in women: a diffusion MRI study in the UK Biobank

Changes in estrogen levels in women have been associated with increased risk for age-related neurodegenerative diseases, including Alzheimers disease, but the impact of exogenous estrogen exposure on the brain is poorly understood. Oral contraceptives (OC) and hormone therapy (HT) and are both common sources of exogenous estrogen for women in reproductive and post-menopausal years, respectively. Here we examined the association of exogenous sex hormone exposure with the brains white matter (WM) aging trajectories in postmenopausal women using and not using OC and HT (HT users: n=3,033, non-users n=5,093; OC users: n=6,964; non-users n=1,156), while also investigating multiple dMRI models. Cross-sectional brain dMRI data was analyzed from the UK Biobank using conventional diffusion tensor imaging (DTI), the tensor distribution function (TDF), and neurite orientation dispersion and density imaging (NODDI). Mean skeletonized diffusivity measures were extracted across the whole brain, and fractional polynomial regressions were used to characterize age-related trajectories for WM microstructural measures. Advanced dMRI model NODDI revealed a steeper WM aging trajectory in HT users relative to non-users, and for those using unopposed estrogens relative to combined estrogens treatment. By contrast, no interaction was detected between OC status and age effects on the diffusivity measures we examined. Exogenous sex hormone exposure may negatively impact WM microstructure aging in postmenopausal women. We also present normative reference curves for white matter microarchitectural parameters in women, to help identify individuals with microstructural anomalies.

neuroscience↗

bioRxiv2020

Advanced diffusion-weighted MRI metrics detect sex differences in aging among 15,000 adults in the UK Biobank

A comprehensive characterization of the brains white matter is critical for improving our understanding of healthy and diseased aging. Here we used diffusion-weighted magnetic resonance imaging (dMRI) to estimate age and sex effects on white matter microstructure in a cross-sectional sample of 15,628 adults aged 45-80 years old (47.6% male, 52.4% female). Microstructure was assessed using the following four models: a conventional single-shell model, diffusion tensor imaging (DTI); a more advanced single-shell model, the tensor distribution function (TDF); an advanced multi-shell model, neurite orientation dispersion and density imaging (NODDI); and another advanced multi-shell model, mean apparent propagator MRI (MAPMRI). Age was modeled using a data-driven statistical approach, and normative centile curves were created to provide sex-stratified white matter reference charts. Participant age and sex substantially impacted many aspects of white matter microstructure across the brain, with the advanced dMRI models TDF and NODDI detecting such effects the most sensitively. These findings and the normative reference curves provide an important foundation for the study of healthy and diseased brain aging.

neuroscience↗