Biology subjects

Beck, D.

Publications and source records attributed to Beck, D..

At least 19 recordsLinked to original sources

bioRxiv2026

FBXW11 Activity Regulates Radial Glial Expansion in Human Cerebral Organoids

Human brain development depends on tightly coordinated gene-regulatory programs and the emergence of complex tissue architecture, making large scale functional interrogation difficult using conventional screen models. To overcome this challenge, we used a pooled CRISPR screening approach. Guided by neuro-specific whole-genome screens in Drosophila, we tested 129 poorly characterised human orthologs and found 8 that modify cerebral organoid development. Candidates were validated using individual CRISPR knockouts and mosaic competition assays. Among these candidates we describe FBXW11, a substrate-recognition component of the SCF E3 ubiquitin ligase complex, as a potent negative regulator of cerebral organoid expansion. FBXW11 loss increases radial glial abundance, expands ventricular-like domains, and impairs neuronal maturation. Mechanistically, FBXW11 associates with {beta}-catenin and alters WNT signalling. FBXW11 mutations cause the autosomal-dominant Mendelian syndrome Neurodevelopmental, Jaw, Eye and Digital syndrome (NEDJED), and we found that disease-associated variants mapped preferentially to WD40 substrate-binding repeats and {beta}-catenin contact regions, linking impaired substrate recognition to neurodevelopmental disease. Together, these findings identify FBXW11 as a conserved negative regulator of {beta}-catenin-dependent radial glial expansion and neuronal maturation during human cerebral brain development.

neuroscience↗

bioRxiv2026

A Quartet of Native Orai Channel Isoforms Orchestrates Graded NFAT Activation and Transcription

The Ca{superscript 2} release-activated Ca{superscript 2} (CRAC) channel mediates store-operated calcium entry (SOCE), a ubiquitous pathway essential for many cell types, including immune cells. Three Orai (Orai1/2/3) proteins constitute the plasma membrane pore-forming units of CRAC channels that are activated by the endoplasmic reticulum (ER) Ca2+-sensing STIM1/2 proteins when ER Ca2+ stores are depleted. Orai1/2/3 are differentially expressed across primary cells with discernible differences in their structures and biophysical properties. Further, Orai1 has two alternatively translated isoforms: long mammalian-specific Orai1 and the 63-residue shorter Orai1{beta}, which is evolutionarily older and conserved across vertebrates. Whether Orai1/1{beta}/2/3 produce unique cytosolic Ca{superscript 2} signatures that bias transcriptional responses through effectors like NFAT is unclear. Here, we used HEK293 cells engineered to express one native Orai isoform and show that all Orai isoforms couple to NFAT1/4 induction. The magnitude of NFAT1/4 induction for each Orai isoform matches that of SOCE, with the following profile: Orai1{beta}>Orai1>>Orai2>Orai3. Near-native re-expression of either Orai1 or Orai1{beta} in primary murine Orai1-/- CD4 T cells restored SOCE, NFAT activation, cytokine production and promoted near identical transcriptional responses enriched for immune activation pathways. An analysis of genetic and clinical data of human individuals showed that homozygous null mutations selectively abolishing Orai1 are not associated with disease resembling CRAC channelopathy. Primary T cells from individuals homozygous or heterozygous for an Orai1 null mutation showed enhanced, rather than impaired, SOCE and NFAT induction. Our data indicate that NFAT activation and transcriptional outputs are primarily driven by the graded strength of SOCE mediated by each isoform of the Orai quartet.

cell biology↗

bioRxiv2026

Semi-quantitative Classification of HIV-1 Nucleic Acids Using ResNet Image Analysis of Discretized Isothermal Amplification Reactions in a Microfluidic Chip

Isothermal nucleic acid amplification tests enable rapid and decentralized molecular diagnostics but often lack robust quantitative readouts compared to quantitative PCR. Here, we present a semi-quantitative nucleic acid measurement approach using machine learning to extract spatiotemporal features from real-time fluorescence imaging of rapid isothermal amplification reactions in microfluidic chips. A convolutional neural network was trained on multiple images sampled throughout a chip-based recombinase polymerase amplification reaction to classify samples into clinically relevant or logarithmically spaced concentration ranges spanning five orders of magnitude. The clinical classification model achieved 94.6% accuracy, and the logarithmic model achieved 92.7% accuracy, with most errors occurring between adjacent concentration categories. By learning spatiotemporal patterns of fluorescence development rather than relying on explicit feature extraction, the model remained accurate at both high and low nucleic acid concentration regimes where other quantitative isothermal molecular tests struggle. This approach enables automated interpretation of amplification reactions and extends the usable dynamic range of the assay. These results demonstrate that integrating machine learning with image-based amplification methods can support rapid semi-quantitative molecular testing and may facilitate broader deployment of nucleic acid diagnostics outside centralized laboratory settings. Author summaryMany rapid nucleic acid testing methods for infectious diseases are simple to run but struggle to measure how much genetic material is present, which limits their usefulness in clinical decision-making. In our work, we study a technique that produces visible fluorescent patterns during nucleic acid amplification reactions. Traditionally, the amount of nucleic acids present are measured by counting individual bright spots, but this becomes difficult when the target nucleic acid concentration is high and the spots merge together. We developed a machine learning approach that models how the fluorescence pattern changes over time. By analyzing a sequence of images from each reaction, our model can assign samples to concentration ranges across a wide span. This allows us to extract meaningful information even when traditional analysis methods break down. Because this approach works with simple imaging systems and does not require complex equipment, it could help support more informative and accessible diagnostic testing in point-of-care and low-resource settings.

bioengineering↗

bioRxiv2026

Cell autonomous inflammation in VEXAS is mediated by cGAS-STING

VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is a severe adult-onset inflammatory disease caused by somatic mutations that reduce cytoplasmic activity of UBA1, the primary initiating enzyme for ubiquitylation. How this hypomorphic state drives cell-intrinsic immune activation in mature myeloid cells is unknown. Using unbiased multi-omic, biochemical, and cell biological analyses of model systems and patient-derived cells, we show that loss of cytoplasmic UBA1 activity convergently disrupts endoplasmic reticulum- associated degradation (ERAD) and mitochondrial homeostasis. ERAD failure arises from preferential under-charging of ERAD E2 enzymes, explaining hallmark VEXAS features, including ER-derived vacuoles and unfolded protein response activation, and promotes accumulation of the ERAD substrate STING. Simultaneously, mitochondrial dysfunction drives cytosolic leakage of mitochondrial DNA, inducing cGAS-dependent STING signaling and inflammatory cytokine production. STING inhibition or reversal of mitochondrial DNA leakage resolves multi-cytokine inflammation in VEXAS models and patient myeloid cells, establishing the cGAS-STING pathway as a therapeutically actionable vulnerability.

genetics↗

bioRxiv2025

Humans can learn bimodal priors in complex sensorimotor behaviour

Extensive research suggests that humans integrate sensory information and prior expectations in a Bayesian manner to reduce uncertainty in perception and action. However, while Bayesian integration provides a powerful explanatory framework, the question remains as to what extent it explains human behaviour in naturalistic situations, including more complex movements and distributions. Here, we examine whether humans can learn bimodal priors in a complex sensorimotor task: returning tennis serves. Participants returned serves in an immersive virtual reality setup with realistic movements and spatiotemporal task demands matching those in real tennis. The location of the opponents serves followed a bimodal distribution. We manipulated visual uncertainty through three levels of ball speeds: slow, moderate, and fast. After extensive exposure to the opponents serves, participants movements were biased by the bimodal prior distribution. As predicted by Bayesian theory, the magnitude of the bias depends on visual uncertainty. Additionally, our data indicate that participants movements in this complex task were not only biased by prior expectations but also by biomechanical constraints and associated motor costs. Intriguingly, an explicit knowledge test after the experiment revealed that, despite incorporating prior knowledge of the opponents serve distribution into their behaviour, participants were not explicitly aware of the pattern. Our results show that humans can implicitly learn and utilise bimodal priors in complex sensorimotor behaviour.

neuroscience↗

bioRxiv2024

Risk optimization during ongoing movement: Insights from movement and gaze behavior in throwing

Handling motor noise is fundamental to successful sensorimotor behavior, especially in high-risk situations. Research using finger-pointing tasks shows that humans account for motor noise and costs of potential outcomes in movement planning. However, does this mechanism generalize to more complex movement tasks? Here, we investigate sensorimotor behavior under risk in throwing across three experiments with 20 participants each. Their task was to throw balls at a target circle, partially overlapped by a penalty circle. This task challenged participants to find strategies that trade off potential penalties and rewards. In the experiments, penalty magnitude and the distance between the circles were manipulated. We measured the location of their final gaze fixation before movement--as an indicator of their planned aiming point--and the balls impact location. Without penalty, the final gaze fixation and the balls impact location were both centered on the target. In the penalty condition, the location of the participants final gaze fixations and the balls impact shifted away from the penalty circle, with larger shifts for higher penalties and smaller distances. Interestingly, the shifts in the balls impact locations were not only larger ("more conservative") but also closer to the statistically optimal (expected gain-maximizing) location compared to the fixated aim points. Movement trajectory analyses show that, in penalty conditions, the shifts away from the penalty zone increased until the final phases of the movement. These results suggest that risk evaluation is not completed in a pre-movement planning phase but is further optimized during movement execution. NEW & NOTEWORTHYWe extend the study of sensorimotor behavior under risk from simple finger-pointing movements (Trommershauser et al., 2008) to a complex throwing task in virtual reality. Our results suggest that, in complex sensorimotor behavior, risk evaluation of potential movements is not confined to a cognitive planning phase before movement but is optimized in action, with the motor system continuously biasing competing action options toward regions of higher expected rewards.

neuroscience↗

bioRxiv2024

Linking Pre- and Perinatal Risk Factors to a Multivariate Fusion of Child Cortical Structure

Pregnancy- and birth-related factors affect offspring brain development, emphasizing the importance of early life exposures. While most previous studies have focused on a few variables in isolation, here we investigated associations between a broad range of pregnancy- and birth-related variables and multivariate cortical brain MRI features. Our sample consisted of 8,396 children aged 8.9 to 11.1 years from the ABCD Study. Through multiple correspondence analysis and factor analysis of mixed data, we distilled numerous pregnancy and birth variables into four overarching dimensions; maternal pregnancy complications, maternal substance use, low birth weight and prematurity, and newborn birth complications. Vertex-wise measures of cortical thickness, surface area, and curvature were fused using linked independent component analysis. Linear mixed effects models showed that maternal pregnancy complications and low birth weight and prematurity were associated with smaller global surface area. Additionally, low birth weight and prematurity was associated with complex regional cortical patterns reflecting bidirectional variations in both surface area and cortical thickness. Newborn birth complications showed multivariate patterns reflecting smaller occipital- and larger temporal area, bi-directional frontal area variations, and reduced cortical thickness across the cortex. Maternal substance use showed no associations with child cortical structure. By employing a multifactorial and multivariate morphometric fusion approach, we connected complications during pregnancy and fetal size and prematurity to global surface area and specific regional signatures across child cortical MRI features. Significance StatementEarly life stages, including pregnancy and birth circumstances, are critically important for a wide range of real-life outcomes for the child. In this study, we linked maternal complications during pregnancy and low birth weight and prematurity to globally reduced cortical surface area, and low birth weight and prematurity, in addition to pregnancy and birth complications, to complex cortical structural patterns later in late childhood. Our findings underscore the importance of providing support to mothers and children during these crucial phases, helping to ensure optimal conditions for healthy child development.

neuroscience↗

bioRxiv2024

Dimensions of early life adversity are differentially associated with patterns of delayed and accelerated brain maturation

BackgroundDifferent types of early-life adversity have been associated with childrens brain structure and function. However, understanding the disparate influence of distinct adversity exposures on the developing brain remains a major challenge. MethodsThis study investigates the neural correlates of 10 robust dimensions of early-life adversity identified through exploratory factor analysis in a large community sample of youth from the Adolescent Brain Cognitive Development (ABCD) Study. Brain age models were trained, validated, and tested separately on T1-weighted (T1; N = 9524), diffusion tensor (DTI; N = 8834), and resting-state functional (rs-fMRI; N = 8233) magnetic resonance imaging (MRI) data from two time points (mean age = 10.7 years, SD = 1.2, range = 8.9-13.8 years). ResultsBayesian multilevel modelling supported distinct associations between different types of early-life adversity exposures and younger- and older-looking brains. Dimensions generally related to emotional neglect, such as lack of primary and secondary caregiver support, and lack of caregiver supervision, were associated with lower brain age gaps (BAGs), i.e., younger-looking brains. In contrast, dimensions generally related to caregiver psychopathology, trauma exposure, family aggression, substance use and separation from biological parent, and socio-economic disadvantage and neighbourhood safety were associated with higher BAGs, i.e., older-looking brains. ConclusionsThe findings suggest that dimensions of early-life adversity are differentially associated with distinct neurodevelopmental patterns, indicative of dimension-specific delayed and accelerated brain maturation.

neuroscience↗

bioRxiv2023

Brain asymmetries from midlife to old adulthood and hemispheric brain age

The human brain demonstrates structural and functional asymmetries which have implications for ageing and mental and neurological disease development. We used a set of magnetic resonance imaging (MRI) metrics derived from structural and diffusion MRI data in N =48,040 UK Biobank participants to evaluate age-related differences in brain asymmetry. Most regional grey and white matter metrics presented asymmetry, which were higher later in life. Informed by these results, we conducted hemispheric brain age (HBA) predictions from left/right multimodal MRI metrics. HBA was concordant to conventional brain age predictions, using metrics from both hemispheres, but offers a supplemental general marker of brain asymmetry when setting left/right HBA into relationship with each other. In contrast to WM brain asymmetries, left/right discrepancies in HBA are lower at higher ages. Our findings outline various sex-specific differences, particularly important for brain age estimates, and the value of further investigating the role of brain asymmetries in brain ageing and disease development.

neuroscience↗

bioRxiv2023

Cell Type-Specific Regulation by a Heptad of Transcription Factors in Human Hematopoietic Stem and Progenitor Cells

Hematopoietic stem and progenitor cells (HSPCs) rely on a complex interplay of transcription factors (TFs) to regulate differentiation into mature blood cells. A heptad of TFs - FLI1, ERG, GATA2, RUNX1, TAL1, LYL1, LMO2 - bind regulatory elements in bulk CD34+ HSPCs. However, whether specific heptad-TF combinations have distinct roles in regulating hematopoietic differentiation remained unknown. We mapped genome-wide chromatin contacts and TF binding profiles in HSPC subsets (HSC, CMP, GMP, MEP) and found that heptad occupancy and enhancer-promoter interactions varied significantly across cell types and were associated with cell-type-specific gene expression. Distinct regulatory elements were enriched with specific heptad-TF combinations, including stem-cell-specific elements with ERG, and myeloid- and erythroid-specific elements with combinations of FLI1, RUNX1, GATA2, TAL1, LYL1, and LMO2. These findings suggest that specific heptad-TF combinations play critical roles in regulating hematopoietic differentiation and provide a valuable resource for development of targeted therapies to manipulate specific HSPC subsets.

developmental biology↗

bioRxiv2022

Free-water volume fraction increases non-linearly with age in the white matter of the healthy human brain

The term free-water volume fraction (FWVF) refers to the cerebrospinal and interstitial fluids in the extracellular space of the white matter (WM) of the brain, which has been demonstrated as a sensitive biomarker that correlates with the cognitive performance and the neuropathological processes modifying the interstitial extracellular spaces. It can be quantified by properly fitting the isotropic compartment of the magnetic resonance (MR) signal in diffusion-sensitized sequences. Using N = 287 healthy subjects aged 25-94, this study examines in detail the evolution of the FWVF in the human brain WM across the adult lifespan, which has been previously reported to exhibit a positive trend. We found evidence of a noticeably non-linear gain after the sixth decade of life, with a region-specific variate and varying change rate of the FWVF parameter with age, at the same time a heteroskedastic pattern across the adult lifespan is suggested. On the other hand, the FW-compensated MR signal leads to a region-dependent flattened age-related evolution of the mean diffusivity (MD) and fractional anisotropy (FA), along with a considerable reduction in their variability, as compared to standard studies conducted over the raw MR signal. This way, our study provides a new perspective on the trajectory-based assessment of the brain and explains the source of the variations observed in FA and MD parameters across the lifespan with previous studies with the standard diffusion tensor imaging.

neuroscience↗

bioRxiv2022

Brain-wide associations between white matter and agehighlight the role of fornix microstructure in brain age

Unveiling the details of white matter (WM) maturation throughout ageing is a fundamental question for understanding the ageing brain. In an extensive comparison of brain age predictions and age- associations of WM features from different diffusion approaches, we analysed UK Biobank diffusion Magnetic Resonance Imaging (dMRI) data across midlife and older age (N = 35,749, 44.6 to 82.8 years of age). Conventional and advanced dMRI approaches were consistent in predicting brain age. WM-age associations indicate a steady microstructure degeneration with increasing age from midlife to older ages. Brain age was estimated best when combining diffusion approaches, showing different aspects of WM contributing to brain age. Fornix was found as the central region for brain age predictions across diffusion approaches in complement to forceps minor as another important region. These regions exhibited a general pattern of positive associations with age for intra axonal water fractions, axial, radial diffusivities and negative relationships with age for mean diffusivities, fractional anisotropy, kurtosis. We encourage the application of multiple dMRI approaches for detailed insights into WM, and the further investigation of fornix and forceps as potential biomarkers of brain age and ageing.

neuroscience↗

bioRxiv2022

Rhometa: Population recombination rate estimation from metagenomic read datasets

Bacterial evolution is influenced by the exchange of genetic information between species through a process referred to as recombination. The rate of recombination is a useful measure for the adaptive capacity of a bacterial population. We introduce Rhometa (https://github.com/sid-krish/Rhometa), a new software package to determine recombination rates from shotgun sequencing reads of metagenomes.It extends the composite likelihood approach for population recombination rate estimation and enables the analysis of modern short-read datasets. We evaluated Rhometa over a broad range of sequencing depths and complexities, using simulated and real experimental short-read data aligned to external reference genomes. In simulated datasets, the deviation from the expected value decreased as the number of genomes increased and we show that 80 genomes are sufficient to reduce these variations below 30%. Testing on an S. pneumoniae transformation experiment dataset we show that Rhometa accurately estimate the expected levels of recombination in a real world dataset.

bioinformatics↗

bioRxiv2022

A comparison of intracranial volume estimation methods and their cross-sectional and longitudinal associations with age

Intracranial volume (ICV) is frequently used in volumetric brain magnetic resonance imaging (MRI) studies, both as an adjustment factor for head size and as a variable of interest. Associations with age have been reported in both longitudinal and cross-sectional studies, but results have varied, potentially due to differences in ICV estimation methods. Here, we compared five commonly used ICV estimation methods and their cross-sectional and longitudinal associations with age. T1-weighted cross-sectional MRI data was included for 651 healthy individuals recruited through the NORMENT Centre (mean age = 46.1 years, range = 12.0-85.8 years) and 2,410 healthy individuals recruited through the UK Biobank study (UKB, mean age = 63.2 years, range = 47.0-80.3 years), where follow-up data was also available with a mean follow-up interval of 2.3 years. ICV was estimated with FreeSurfer (eTIV and sbTIV), SPM12, CAT12, and FSL. We assessed Pearson correlations, performed Bland-Altman analysis, and tested the explained variance of sex, height, body weight, and age on pairwise differences between ICV estimation methods. We fitted regression models to test linear and non-linear cross-sectional associations between age and ICV. For the UKB dataset, we further assessed longitudinal ICV change using linear mixed-effects (LME) models. We found overall high correlations across ICV estimation method, with the lowest correlations between FSL and eTIV (r=0.87) and between FSL and CAT12 (r=0.89). Widespread proportional bias was found in the Bland-Altman analyses, i.e., agreement between methods varying as a function of head size. Body weight, age, and sex explained the most variance in the differences between ICV estimation methods, indicating possible confounding by these variables for some estimation methods. In the NORMENT dataset, cross-sectional associations with age were found only for FSL and SPM12, indicating a positive association. For the UKB dataset, we observed negative cross-sectional associations with age for all ICV estimation methods. Longitudinal associations with age were found for all ICV estimation methods, with estimated annual percentage change ranging from -0.291 % to -0.416 % across the sampled age range. This convergence of longitudinal results across ICV estimation methods, in the largest dataset to date, offers strong evidence for age-related ICV reductions in mid- to late adulthood. HighlightsO_LICorrelations between the five assessed estimation methods were very high (r>0.90) with the exception of FSL and eTIV (r=0.87), and FSL and CAT12 (r=0.89). C_LIO_LIExplained variance of estimated ICV differences by body weight, age, and sex indicate possible confounding for some ICV estimation methods. C_LIO_LIPositive cross-sectional associations with age, from adolescence to old age, were observed for the SPM12 and FSL estimation methods in one dataset. C_LIO_LIIn the other dataset, negative cross-sectional associations with age, from mid- to late adulthood, were found for all estimation methods. C_LIO_LILongitudinal ICV changes were observed for all estimation methods, indicating an annual percentage ICV reduction of -0.29 % to -0.42 % in mid- to late adulthood. C_LI

neuroscience↗

bioRxiv2021

Mesoderm-Derived PDGFRA+ Cells Regulate the Emergence of Hematopoietic Stem Cells in the Dorsal Aorta

Mouse hematopoietic stem cells (HSCs) first emerge at embryonic day 10.5 (E10.5) on the ventral surface of the dorsal aorta, by endothelial-to-hematopoietic transition (EHT). We investigated whether cells with mesenchymal stem cell-like activity, which provide an essential niche for long-term HSCs (LT-HSCs) in the bone marrow, reside in the aorta- gonad-mesonephros (AGM) and contribute to the structural development of the dorsal aorta and EHT. Using transgenic mice, we demonstrate a lineage hierarchy for AGM stromal cells and traced the E10.5/E11.5 aortic endothelium and HSCs to mesoderm derived (Mesp1) PDGFRA+ stromal cells (Mesp1der PSCs). Mesp1der PSCs dominate the sub-endothelial and ventral stroma in the E10.5-E11.5 AGM but by E13.5 were replaced by neural crest (Wnt1) derived PDGFRA+ stromal cells (Wnt1der PSCs). Co-aggregating non-hemogenic embryonic and adult endothelial cells with Mesp1der PSCs but not with Wnt1der PSCs resulted in activation of a hematopoietic transcriptional program in endothelial cells accompanied by EHT and generation of LT-HSCs. Dose-dependent inhibition of PDGFRA signalling or BMP, WNT, NOTCH signalling interrupted this reprogramming event. This partnership between endothelial cells and AGM Mesp1der PSCs could potentially be harnessed to manufacture LT-HSCs from endothelium.

developmental biology↗

bioRxiv2021

Effects of High-Volume versus High-Load Resistance Training on Skeletal Muscle Growth and Molecular Adaptations

AimWe evaluated the effects of higher-load (HL) versus (lower-load) higher-volume (HV) resistance training on skeletal muscle hypertrophy, strength, and muscle-level molecular markers. MethodsTrained men (n=15, age: 23{+/-}3 y; training experience: 7{+/-}3 y) performed unilateral lower body training for 6 weeks (3x weekly), where single legs were assigned to HV and HL paradigms. Vastus lateralis (VL) biopsies were obtained prior to study initiation (PRE) as well as 3 days (POST) and 10 days following the last bout (POSTPR). Body composition and strength tests were performed at each testing session, and biochemical assays were performed on muscle tissue after study completion. Two-way within subjects repeated measures ANOVAs were performed on all dependent variables except tracer data, which was compared using dependent samples t-tests. ResultsA significant (p<0.05) interaction existed for unilateral leg extension 1RM (HV<HL at POST and POSTPR). Six-week integrated sarcoplasmic protein synthesis (iSarcoPS) rates were higher in the HV versus HL leg, while no difference between legs existed for integrated myofibrillar protein synthesis rates. Main time effects existed for unilateral leg press strength (PRE<POST and POSTPR), knee extensor peak torque (PRE and POST<POSTPR), dual-energy x-ray absorptiometry (DXA)-derived upper leg lean mass (PRE<POST and POSTPR), ultrasound-derived VL thickness (PRE and POSTPR<POST), sarcoplasmic protein concentrations (POST and POSTPR<PRE), and tropomyosin and troponin protein abundances (POST and POSTPR<PRE). ConclusionsWith the exception of differences in leg extensor strength and iSarcoPS between legs, our data suggest that short-term (6 weeks) HV and HL training elicit similar hypertrophic, strength, and molecular-level adaptations.

physiology↗

bioRxiv2020

Women with a history of previous childbirths show less evident white matter brain ageing

Maternal brain adaptations occur in response to pregnancy, but little is known about how parity impacts white matter (WM) and WM ageing trajectories later in life. Utilising global and regional brain-age prediction based on multi-shell diffusion MRI data, we investigated the association between previous childbirths and WM brain age in 8,895 women in the UK Biobank cohort (age range = 54 - 81 years). The results showed that number of previous childbirths was negatively associated with WM brain age, potentially indicating a protective effect of parity on brain WM later in life. Both global WM and grey matter brain age estimates showed unique contributions to the association with previous childbirths, suggesting partly independent processes. Corpus callosum contributed uniquely to the global WM association with previous childbirths, and showed a stronger relationship relative to several other tracts. While our findings demonstrate a link between reproductive history and brain WM characteristics later in life, longitudinal studies are required to establish causality and determine how parity may influence womens WM trajectories across the lifespan.

neuroscience↗

bioRxiv2020

Disruption of a GATA2, TAL1, ERG regulatory circuit promotes erythroid transition in healthy and leukemic stem cells

Changes in gene regulation and expression govern orderly transitions from hematopoietic stem cells to terminally differentiated blood cell types. These transitions are disrupted during leukemic transformation but knowledge of the gene regulatory changes underpinning this process is elusive. We hypothesised that identifying core gene regulatory networks in healthy hematopoietic and leukemic cells could provide insights into network alterations that perturb cell state transitions. A heptad of transcription factors (LYL1, TAL1, LMO2, FLI1, ERG, GATA2, RUNX1) bind key hematopoietic genes in human CD34+ haematopoietic stem and progenitor cells (HSPCs) and have prognostic significance in acute myeloid leukemia (AML). These factors also form a densely interconnected circuit by binding combinatorially at their own, and each others, regulatory elements. However, their mutual regulation during normal haematopoiesis and in AML cells, and how perturbation of their expression levels influences cell fate decisions remains unclear. Here, we integrated bulk and single cell data and found that the fully connected heptad circuit identified in healthy HSPCs persists with only minor alterations in AML, and that chromatin accessibility at key heptad regulatory elements was predictive of cell identity in both healthy progenitors and in leukemic cells. The heptad factors GATA2, TAL1 and ERG formed an integrated sub-circuit that regulates stem cell to erythroid transition in both healthy and leukemic cells. Components of this triad could be manipulated to facilitate erythroid transition providing a proof of concept that such regulatory circuits could be harnessed to promote specific cell type transitions and overcome dysregulated haematopoiesis.

cancer biology↗