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Warrier, V.

Publications and source records attributed to Warrier, V..

At least 19 recordsLinked to original sources

Polygenic hierarchies of macroscale brain structural organisation

Different Magnetic Resonance Imaging-derived cortical, subcortical, and white matter measures are presumed to reflect different developmental and cellular processes, but how their genetic architecture is organised and the underlying cellular and developmental processes is unclear. We conducted genome-wide association studies of 2,326 imaging-derived phenotypes (IDPs) spanning twelve structural measures across the cortex, subcortex, ventricles, and white matter tracts in the UK Biobank (Nmax = 53,751), replicated in ABCD (Nmax = 5,119), identifying 14,176 experiment-wide significant loci and prioritizing 848 genes. We found that IDPs primarily cluster by measure into six families: brain size, cortical thickness, curvature, microstructural coherence, microstructural diffusivity, and orientation dispersion. This structure was preserved across prioritized genes, cell types, and developmental timing; brain size implicates first-trimester radial glia programs, while white matter coherence implicates adolescent astrocyte and oligodendrocyte lineages. Within individual measures, genetic effects were further organised along broad spatial gradients, with a principal gradient reflecting allometric scaling for most measures and secondary gradients showing correspondence with the sensory-association topographic axis across several measures. We identified 79 genes with spatially restricted effects along the cortex, with many aligning with these dominant gradients while a substantial subset showed additional spatial patterns. Together, these findings reveal a hierarchical organisation of the genetic architecture of macroscale human brain structure, spanning phenotype families, broad spatial gradients, and regionally restricted developmental programmes.

genomics↗

Partitioning the roots of interactions between microbes (PRISM): environment-supplied resources versus species-produced mediators

Microbial species in a community can interact through competition for resources present in the environment, as well as inhibition or facilitation by metabolites produced by other species. Understanding the relative contribution of these two types of interaction will help us modulate bacterial interactions more effectively. Our work focuses on partitioning the impact of metabolites that mediate the interactions between bacteria into the contribution of resources present in the environment versus that of mediators released as by-products of cellular activities. For this, we create a range of conditions in which the ratio of environmentally supplied resources (R) and the species-produced metabolites (M) is modulated to infer the contribution of each to the overall interaction. We performed this assay with six different nasal bacterial strains and saw an array of outcomes in terms of how secreted metabolites by one strain affected other nasal strains. Metabolites produced by Staphylococcus suppressed the growth of most strains tested. In contrast, metabolites produced by commensal strains such as Corynebacterium accolens and Corynebacterium tuberculostearicum could aid the growth of Staphylococcus aureus and Staphylococcus epidermidis strains. Interestingly, the growth of Staphylococcus epidermidis benefited from metabolites produced by four out of the five strains tested. Our proposed assay offers additional insights into the roots of bacterial interactions, enabling applications such as engrafting helpful probiotics and knocking out harmful bacteria.

microbiology↗

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↗

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↗

The genetic architecture of cortical similarity networks

The genetic architecture of human brain networks is central to understanding the organization and evolution of the cortex, the causal relationships between brain structure and function, and the pathogenesis of heritable neuropsychiatric disorders. However, the current understanding of the genetics of brain networks remains fragmented. Here, we investigated common genetic effects on Morphometric INverse Divergence (MIND), a biologically-validated, heritable, and multimodal MRI metric of inter-areal similarity and connectivity. Using a discovery dataset (N>30,000 adults), we estimated subject-specific MIND networks from the multivariate distributions of four MRI features at each of 23 cortical areas and performed genome-wide association studies (GWAS) at each of the 276 inter-areal edges. These edge-level genetic effects were highly replicated by parallel GWAS of an independent validation dataset (N>18,000 adults). We found that strong genetic correlations between multiple edges were largely reducible to two gradients of genetically-determined cortical similarity, each of which was aligned with geodesic distance from one of the two phylogenetically primitive areas (paleocortex and archicortex) predicted by the dual origin theory of cortical evolution. Genetic MIND gradients were more heritable than comparable gradients derived from GWAS of functional MRI connectivity networks; and the paleocortical trend was genetically correlated with, and causally predictive of, functional connectivity. Finally, we identified multiple global and local genetic correlations between both MIND gradients and nine clinical diagnoses or biomedical traits, indicating that the normative genetic architecture of human brain networks is pleiotropically associated with inherited risk of neuropsychiatric disorders and systemic metabolic and immune traits. These results provide fresh insight into the dual origins of the human cortex and their implications for brain function and health.

neuroscience↗

A protective role for the cerebellum in cognitive aging

BackgroundBrain reserve -- the brains resilience to age-related change or damage -- provides protection against cognitive decline. The cerebellum is relatively unstudied as a contributor to brain reserve. This study investigates cerebellar brain reserve in the largest cohort to date. MethodsWe used data from the Human Connectome Project (n=708, 36-100yrs), UK Biobank (n=45,013, 44-81yrs), and ADNI (n=1,423, 56-95yrs). ADNI participants were cognitively normal or had a diagnosis of mild cognitive impairment or Alzheimers disease (AD) dementia. We examined associations between cerebellar tissue volume, age, Montreal Cognitive Assessment (MoCA) scores, global PET amyloid burden, and APOE genotype. FindingsHCP-Aging data revealed heterogenous aging-associated changes in cerebellar volume, with the greatest effects in posterior hemispheric regions (crus I) (Bonferroni-corrected, p<0{middle dot}05). MoCA scores were associated with higher tissue density in the cerebellum (p<0{middle dot}0001) to the same extent as neocortex, and MoCA scores coupled most strongly with posterior cerebellar cortex. Strikingly, greater volume in MoCA visuospatial-related cerebellar cortex protected against aging-related cognitive decline (p=0{middle dot}0001). We replicated tissue aging results in the UK Biobank with the greatest aging-related effects in posterior cerebellum (p<0{middle dot}0001), and an association of greater cerebellar volumes with less cognitive decline (Trails Making-B: p<0{middle dot}00001; Digit Symbol Substitution: p=0{middle dot}034). AD patients with low amyloid-beta burden (A{beta}-) exhibited the strongest cerebellar association with MoCA (volume x group, A{beta}- AD: p=0{middle dot}0001). In A{beta}- individuals, APOE {varepsilon}4/{varepsilon}4 carriers showed the greatest effect with MoCA (volume x APOE, {varepsilon}4/{varepsilon}4: p=0{middle dot}017). InterpretationOur large-scale study demonstrates a potentially strong role for the cerebellum in mitigating cognitive decline. The persistence of this protection in APOE {varepsilon}4/{varepsilon}4 carriers reshapes our understanding of reserve and AD risk. Our findings open the cerebellum as a novel target for future clinical research on brain reserve in aging populations. FundingNational Science Foundation, National Academies of Sciences, Engineering and Medicine, National Institutes of Health. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and GoogleScholar between August 12, 2023, and September 25, 2024 for articles irrespective of language or date of publication, relating to measures of cortical and cerebellar aging. Search terms included "cerebellum", "cognitive aging", "cerebellar reserve", "Alzheimers disease", "covariance", "retrogenesis", and "connectivity". Prior research demonstrated that the cerebellum may play a role in cognitive function. Studies have shown that cerebellar development is spatially heterogenous, with posterior regions undergoing the most protracted change in structure and function. Brain reserve has been predominantly studied in the neocortex, with some studies suggesting the cerebellum may contribute to cognitive changes in diseases like Alzheimers disease (AD) dementia. Cerebellar volume differences between young and older adults have been noted, as well as between healthy adults and neurodegenerative conditions like Parkinsons disease. However, the cerebellums contribution to cognitive reserve, particularly in healthy aging and individuals with a clinical diagnosis of mild cognitive impairment or AD dementia, had not been explored especially in large population-based datasets. Added value of this studyTo our knowledge, this study is the largest to date looking into how cerebellar structures contribute to cognitive outcomes in both healthy older adults, and those with mild cognitive impairment or AD dementia. We leverage three large neuroimaging datasets -- HCP-Aging, UK Biobank, and ADNI -- and demonstrate that cerebellar aging is spatially heterogeneous, with posterior regions showing the greatest age-related decline. We further establish a significant link between larger cerebellar volumes and better cognitive outcomes, suggesting that the cerebellum plays a role in cognitive resilience. Additionally, we identify how cerebellar structures predict cognitive performance and interact with amyloid-beta brain pathology and APOE genotype, particularly in those with low amyloid brain burden and those at greatest risk of AD such as in homozygous APOE e4 allele carriers. Implications of all the available evidenceThe aging of the global population raises the challenge of maintaining cognitive health in older age. Our research focuses on the cerebellum as a novel mediator of preserved cognitive function in old age and clinical dementia. Our findings have profound implications, given that individuals with robust cerebellar structures may be missed during cognitive and clinical screenings. Greater cerebellum volume seems to be most advantageous in those at higher risk for Alzheimers disease based on APOE4 status and those who have yet to accumulate substantial amyloid-beta brain pathology. Our study underscores the importance of the cerebellum as a novel brain reserve mechanism in aging populations.

neuroscience↗

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↗

A common neural signature between genetic and environmental risk

Not everyone is equally likely to experience mental illness. What is the contribution of an individuals genetic background, or experiences of childhood adversity, to that likelihood? And how do these dimensions of risk interact at the level of the brain? We investigated the relationship between genetic liability for mental illness, childhood adversity, and cortico-limbic connectivity in a large developmental sample drawn from the ABCD cohort. First, we used Canonical Correlation Analysis to uncover two genetic dimensions of mental health using polygenic risk scores for ADHD, Anxiety, Depression, and Psychosis. The first dimension represented liability for broad psychopathology which positively correlated with adversity, while the second represented neurodevelopmental-specific risk which negatively interacted with adversity. Next, we investigated the cortico-limbic signature of adversity and genetic liability using Partial Least Squares. We found that the neural correlates of adversity broadly mirrored those of genetic liability, with adversity capturing most of the shared variance. These novel findings suggest that genetic and environmental risk overlap in the neural connections that underlie behavioural symptomatology.

neuroscience↗

The overlapping genetic architecture of psychiatric disorders and cortical brain structure

Both psychiatric vulnerability and cortical structure are shaped by the cumulative effect of common genetic variants across the genome. However, the shared genetic underpinnings between psychiatric disorders and brain structural phenotypes, such as thickness and surface area of the cerebral cortex, remains elusive. In this study, we employed pleiotropy-informed conjunctional false discovery rate analysis to investigate shared loci across genome-wide association scans of regional cortical thickness, surface area, and seven psychiatric disorders in approximately 700,000 individuals of European ancestry. Aggregating regional measures, we identified 50 genetic loci shared between psychiatric disorders and surface area, as well as 26 genetic loci shared with cortical thickness. Risk alleles exhibited bidirectional effects on both cortical thickness and surface area, such that some risk alleles for each disorder increased regional brain size while other risk alleles decreased regional brain size. Due to bidirectional effects, in many cases we observed extensive pleiotropy between an imaging phenotype and a psychiatric disorder even in the absence of a significant genetic correlation between them. The impact of genetic risk for psychiatric disorders on regional brain structure did exhibit a consistent pattern across highly comorbid psychiatric disorders, with 80% of the genetic loci shared across multiple disorders displaying consistent directions of effect. Cortical patterning of genetic overlap revealed a hierarchical genetic architecture, with the association cortex and sensorimotor cortex representing two extremes of shared genetic influence on psychiatric disorders and brain structural variation. Integrating multi-scale functional annotations and transcriptomic profiles, we observed that shared genetic loci were enriched in active genomic regions, converged on neurobiological and metabolic pathways, and showed differential expression in postmortem brain tissue from individuals with psychiatric disorders. Cumulatively, these findings provide a significant advance in our understanding of the overlapping polygenic architecture between psychopathology and cortical brain structure.

genetics↗

Two differentiated brain systems micro-structurally associated with obesity

The relationship between obesity and brain structure is incompletely understood. Using diffusion-weighted MRI from [~]30,000 UK Biobank participants we test the hypothesis that obesity (waist-to-hip ratio, WHR) is associated with regional differences in two micro-structural MRI metrics: isotropic volume fraction (ISOVF), an index of free water, and intra-cellular volume fraction (ICVF), an index of neurite density. We observed significant associations with obesity in two coupled but distinct brain systems: a prefrontal-temporal-striatal system associated with ISOVF and a medial temporal-occipital-striatal system associated with ICVF. The ISOVF[~]WHR system colocated with expression of genes enriched for innate immune functions, decreased glial density, and high mu opioid (MOR) and other neurotransmitter receptor density. Conversely, the ICVF[~]WHR system co-located with expression of genes enriched for G-protein coupled receptors and decreased density of MOR and other receptors. To test whether these distinct brain phenotypes might differ in terms of their underlying shared genetics or relationship to maps of the inflammatory marker C-reactive Protein (CRP), we estimated the genetic correlations between WHR and ISOVF (rg = 0.026, P = 0.36) and ICVF (rg = 0.112, P < 9 x 10-4) as well as comparing correlations between WHR maps and equivalent CRP maps for ISOVF and ICVF (p<0.05). These correlational results are consistent with a two-way mechanistic model whereby genetically determined differences in neurite density in the medial temporal system may contribute to obesity, whereas water content in the prefrontal system could reflect a consequence of obesity mediated by innate immune system activation.

neuroscience↗

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↗

MIND Networks: Robust Estimation of Structural Similarity from Brain MRI

Structural similarity networks are a central focus of magnetic resonance imaging (MRI) research into human brain connectomes in health and disease. We present Morphometric INverse Divergence (MIND), a robust method to estimate within-subject structural similarity between cortical areas based on the Kullback-Leibler divergence between the multivariate distributions of their structural features. Compared to the prior approach of morphometric similarity networks (MSNs) on N>10,000 data from the ABCD cohort, MIND networks were more consistent with known cortical symmetry, cytoarchitecture, and (in N=19 macaques) gold-standard tract-tracing connectivity, and were more invariant to cortical parcellation. Importantly, MIND networks were remarkably coupled with cortical gene co-expression, providing fresh evidence for the unified architecture of brain structure and transcription. Using kinship (N=1282) and genetic data (N=4085), we characterized the heritability of MIND phenotypes, identifying stronger genetic influence on the relationship between structurally divergent regions compared to structurally similar regions. Overall, MIND presents a biologically-validated lens for analyzing the structural organization of the cortex using readily-available MRI measurements.

neuroscience↗

The genetics of cortical organisation and development: a study of 2,347 neuroimaging phenotypes

Our understanding of the genetic architecture of the human cerebral cortex is limited both in terms of the diversity of brain structural phenotypes and the anatomical granularity of their associations with genetic variants. Here, we conducted genome-wide association meta-analysis of 13 structural and diffusion magnetic resonance imaging derived cortical phenotypes, measured globally and at 180 bilaterally averaged regions in 36,843 individuals from the UK Biobank and the ABCD cohorts. These phenotypes include cortical thickness, surface area, grey matter volume, and measures of folding, neurite density, and water diffusion. We identified 4,349 experiment-wide significant loci associated with global and regional phenotypes. Multiple lines of analyses identified four genetic latent structures and causal relationships between surface area and some measures of cortical folding. These latent structures partly relate to different underlying gene expression trajectories during development and are enriched for different cell types. We also identified differential enrichment for neurodevelopmental and constrained genes and demonstrate that common genetic variants associated with surface area and volume specifically are associated with cephalic disorders. Finally, we identified complex inter-phenotype and inter-regional genetic relationships among the 13 phenotypes which reflect developmental differences among them. These analyses help refine the role of common genetic variants in human cortical development and organisation. One sentence summaryGWAS of 2,347 neuroimaging phenotypes shed light on the global and regional genetic organisation of the cortex, underlying cellular and developmental processes, and links to neurodevelopmental and cephalic disorders.

neuroscience↗

When does a Lotka-Volterra model represent microbial interactions? Insights from in-vitro nasal bacterial communities

To alter microbial community composition for therapeutic purposes, an accurate and reliable modeling framework capable of predicting microbial community outcomes is required. Lotka-Volterra (LV) equations have been utilized to describe a breadth of microbial communities, yet, the conditions in which this modeling framework is successful remain unclear. Here, we propose that a set of simple in vitro experiments--growing each member in cell-free filtrates obtained from other members--can be used as a test to decide whether a LV model is appropriate for describing microbial interactions of interest. We show that for LV to be a good candidate, the ratio of growth rate to carrying capacity of each isolate when grown in the cell-free spent medium of other isolates should remain constant. Using an in vitro community of human nasal bacteria as a tractable system, we find that LV can be a good approximation when the environment is low-nutrient (i.e., when growth is limited by the availability of nutrients) and complex (i.e., when multiple resources, rather than a few, determine growth). These findings can help clarify the range of applicability of LV models and reveal when a more complex model may be necessary for predictive modeling of microbial communities.

microbiology↗

Assortative mating, autistic traits, empathizing, and systemizing

It has been suggested that the children of parents with particular interests and aptitude for understanding systems via input-operation-output rules (i.e. systemizing) are at increased likelihood of developing autism. Furthermore, assortative mating (i.e. a non-random pattern in which individuals are more likely to pair with others who are similar to themselves) is hypothesised to occur in relation to systemizing, and so romantic couples may be more similar on this variable than chance would dictate. However, no published study has yet tested this hypothesis. We therefore examined intra-couple correlations for a measure of autistic traits (Autism Spectrum Quotient [AQ]), self-report measures of empathizing (Empathy Quotient [EQ]), and systemizing (Systemizing Quotient-Revised [SQ-R]), as well as the Reading the Mind in the Eyes Test (RMET) and Embedded Figures Task (EFT). We observed positive intra-couple correlations of small-to-medium magnitude for all measures except EQ. Further analyses suggest that these effects are attributable to people pairing with those who are more similar to themselves than chance (initial assortment) rather than becoming more alike over the course of a relationship (convergence), and to seeking out self-resembling partners (active assortment) rather than pairing in this manner due to social stratification increasing the likelihood of similar people meeting in the first place (social homogamy). Additionally, we found that the difference in scores for the AQ, SQ-R, RMET and EFT of actual couples were smaller (i.e. more similar) than the average difference scores calculated from all other possible male-female pairings within the dataset. The current findings therefore provide clear evidence in support of the assortative mating theory of autism.

evolutionary biology↗

Rule-governed Dynamic Stochastic Equilibration of Multicellular Motion In Vivo During Olfactory Neurogenesis

The complexity of patterning during organ-wide stem cell migration and differentiation can be challenging to interpret quantitatively. Here, we track neural crest (NC) and ectodermal placode-derived progenitor movements in vivo, for hundreds of cells, implement unbiased algorithmic approaches to extract biologically meaningful information, and discover cell-cell and lineage-lineage coordination between progenitors that form olfactory sensory neurons (OSNs) during zebrafish embryogenesis. Our approach discriminates between NC- and placode-derived contributions and segregates ingressing NC cells into two previously unidentified subtypes termed trend and dispersed lineages. Our analyses indicate that NC and placodal progenitor migration and intercalation are coordinated by at least two types of collective behavior: spatiotemporal exclusion and elastic tethering, akin to a push-pull mechanism. A stochastic equilibrium model accurately represents the interactions of NC and placode-derived lineages. Our approach provides insights into the coordination of dual-origin lineages during vertebrate olfactory neurogenesis and offers an algorithmic toolkit for probing multicellular coordination in vivo.\n\nO_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY Graphical Abstract C_FIG_DISPLAY

systems biology↗

Integrated genetic and methylomic analyses identify shared biology between autism and autistic traits

Previous studies have identified differences in DNA methylation in autistic individuals compared to neurotypical individuals. Yet, it is unclear if this extends to autistic traits - subclinical manifestation of autism features in the general population. Here, we investigate the association between DNA methylation at birth (cord blood), and scores on the Social and Communication Disorders Checklist (SCDC), a measure of autistic traits, in 701 8-year olds, by conducting a methylome-wide association study (MWAS) using DNA methylation data from cord-blood. Whilst did not identify significant loci demonstrating differential methylation, we observe a degree of overlap between the SCDC MWAS and post-mortem brain methylation signature in autism. Validating this, we observe an enrichment for genes that are dysregulated in the post-mortem autism brain. Finally, integrating genome-wide data from more than 40,000 individuals and mQTL maps from cord-blood, we demonstrate that mQTLs of CpGs associated with SCDC scores at different P-value thresholds are significantly shifted towards lower P-values in a GWAS for autism. We validate this using a GWAS of SCDC, and demonstrate a lack of enrichment in a GWAS of Alzheimers disease. Our results highlight the shared cross-tissue epigenetic architecture of autism and autistic traits, and demonstrate that mQTLs associated with methylation changes in childhood autistic traits are enriched for common genetic variants associated with autism and autistic traits.

genetics↗

Genetic contribution to theory of mind in adolescence

Difficulties in theory of mind (the ability to attribute mental states to oneself or others, and to make predictions about anothers behaviour based on these attributions) have been observed in several psychiatric conditions. We investigate the genetic architecture of theory of mind in 4,577 13-year-olds who completed the Emotional Triangles Task (Triangles Task), a first-order test of theory of mind. We observe a small but significant female-advantage on the Triangles Task (Cohens d = 0.19, P < 0.01), in keeping with previous work using other tests of theory of mind. Genome-wide association analyses did not identify any significant loci, and SNP heritability was small and non-significant. Polygenic scores for six psychiatric conditions (ADHD, anorexia, autism, bipolar disorder, depression, and schizophrenia), and empathy were not associated with scores on the Triangles Task. However, polygenic scores of cognitive aptitude, and cognitive empathy, a term synonymous with theory of mind and measured using the \"Reading the Mind in the Eyes\" Test, were significantly associated with scores on the Triangles Task at multiple P-value thresholds, suggesting shared genetics between different measures of theory of mind and cognition.

genetics↗