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Romero-Garcia, R.

Publications and source records attributed to Romero-Garcia, R..

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↗

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↗

Using gene complementation to identify a SulP-family bicarbonate transporter in an N2-fixing cyanobacterial endosymbiont of an open ocean diatom

Diatom-Diazotrophic Associations (DDAs) contribute significantly to new and primary production in the worlds oceans, yet the understanding of how production is sustained is poorly resolved. These symbioses involve diatoms and N2-fixing, heterocyst-forming cyanobacteria of the genus Richelia, both partners being photosynthetic. Richelia euintracellularis resides in the cytoplasm of Hemiaulus hauckii, whereas Richelia intracellularis is periplasmic in Rhizosolenia clevei. In the ocean, bicarbonate is taken up by phytoplankton to provide CO2 for photosynthesis. The genomes of both Richelia endobionts (ReuHH01 and RintRC01, respectively) contain genes encoding SulP-family proteins, which are oxyanion transporters. To study the possible involvement of these transporters in bicarbonate uptake, we used complementation of a Synechocystis sp. PCC 6803 mutant with its five CO2 uptake systems inactivated, which is unable to grow in air levels of CO2. Three genes from RintRC01 and one gene and a DNA fragment containing four partial gene sequences from ReuHH01 were chemically synthesized, cloned under the control of a strong gene promoter and incorporated in the chromosome of the Synechocystis mutant. One gene from RintRC01, RintRC_3892, complemented the Synechocystis mutant to grow with air levels of CO2 or with low bicarbonate concentrations. The complemented strain showed strong sodium-dependent, low affinity bicarbonate uptake, which, together with phylogenetic analyses, identified RintRC_3892 as a BicA protein. Additionally, RintRC_3892 transcripts were consistently detected in environmental samples from three ocean basins. No evidence for a bicarbonate transporter was found, however, for ReuHH01, suggesting different strategies for inorganic carbon uptake in the periplasmic and cytoplasmic endobionts.

microbiology↗

Resilient functioning after childhood adversity is associated with altered structural brain network topology in adolescence.

Childhood adversity is one of the strongest predictors of adolescent mental illness. Therefore, it is critical that the mechanisms that aid resilient functioning in individuals exposed to childhood adversity are better understood. Here, we examined whether resilient functioning was related to structural brain network topology. We quantified resilient functioning at the individual level as psychosocial functioning adjusted for the severity of childhood adversity in a large sample of adolescents (N=2406, aged 14-24). Next, we examined nodal degree (the number of connections that brain regions have in a network) using brain-wide cortical thickness measures in a representative subset (N=275) using a sliding window approach. We found that higher resilient functioning was associated with lower nodal degree of multiple regions including the dorsolateral prefrontal cortex, the medial prefrontal cortex, and the posterior superior temporal sulcus (z > 1.645). During adolescence, decreases in nodal degree are thought to reflect a normative developmental process that is part of the extensive remodelling of structural brain network topology. Prior findings in this sample showed that decreased nodal degree was associated with age, as such our findings of negative associations between nodal degree and resilient functioning may therefore potentially resemble a more mature structural network configuration in individuals with higher resilient functioning.

neuroscience↗

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 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↗

A Deep Graph Neural Network Architecture for Modelling Spatio-temporal Dynamics in resting-stating functional MRI Data

Resting-state functional magnetic resonance imaging (rs-fMRI) has been successfully employed to understand the organisation of the human brain. For rs-fMRI analysis, the brain is typically parcellated into regions of interest (ROIs) and modelled as a graph where each ROI is a node and pairwise correlation between ROI blood-oxygen-level-dependent (BOLD) time series are edges. Recently, graph neural networks (GNNs) have seen a surge in popularity due to their successes in modelling unstructured relational data. The latest developments with GNNs, however, have not yet been fully exploited for the analysis of rs-fMRI data, particularly with regards to its spatio-temporal dynamics. Herein we present a novel deep neural network architecture, combining both GNNs and temporal convolutional networks (TCNs), which is able to learn from the spatial and temporal components of rs-fMRI data in an end-to-end fashion. In particular, this corresponds to intra-feature learning (i.e., learning temporal dynamics with TCNs) as well as inter-feature learning (i.e., leveraging spatial interactions between ROIs with GNNs). We evaluate our model with an ablation study using 35,159 samples from the UK Biobank rs-fMRI database. We also demonstrate explainability features of our architecture which map to realistic neurobiological insights. We hope our model could lay the groundwork for future deep learning architectures focused on leveraging the inherently and inextricably spatio-temporal nature of rs-fMRI data.

neuroscience↗

Sexually dimorphic development of depression-related brain networks during healthy human adolescence

We hypothesized that there are sexual differences in human brain network development underlying the female > male divergence in adolescent depression. We tested for sex differences in parameters of brain network development (accelerated longitudinal fMRI, N=298 healthy adolescents, each scanned 1 to 3 times). Sexually divergent development of functional connectivity was located in default mode network (DMN), limbic cortex, and subcortical nuclei. Females had a more "disruptive" pattern of development, where weak functional connectivity at age 14 became stronger during adolescence. This fMRI-derived map of divergent adolescent development was co-located with (i) a map of functional dysconnectivity associated with adult major depressive disorder (MDD); and (ii) an adult brain gene expression pattern enriched for genes on the X chromosome, neurodevelopmental genes, and risk genes for MDD. Sexual divergence in disruptive development of DMN, limbic and subcortical functional networks is potentially relevant to the increased risk of depression in adolescent females.

neuroscience↗

A moment of change: shifts in myeloarchitecture characterise adolescent development of cortical gradients

The biological processes underpinning adolescent brain maturation remain elusive. Expanding on previous work showing age-related changes in cortical morphology, we studied an accelerated longitudinal cohort of adolescents and young adults (n=223, two time points) to investigate dynamic reconfigurations in myeloarchitecture. Intracortical profiles were generated using magnetization transfer (MT) data, a myelin-sensitive magnetic resonance imaging contrast. Mixed-effect models of depth specific intracortical profiles demonstrated two separate processes i) related to overall increases in MT, and ii) showing a flattening of the MT profile related to enhanced signal in mid-to-deeper layers, especially in heteromodal and unimodal association cortices. This development was independent of morphological changes, and enhanced MT in mid-to-deeper layers was found to spatially co-localise specifically with gene expression markers of oligodendrocytes. Covariance analysis between all pairs of intracortical profiles revealed that these intracortical changes contributed to a gradual and dynamic differentiation from higher-order to lower-order systems. Depth-dependent trajectories of intracortical myeloarchitectural development contribute to the maturation of structural hierarchies in the human neocortex, providing a model for adolescent development that bridges microstructural and macroscopic scales of brain organization.\n\neLife digestIntracortical myelin imposes a spatial structure on cortico-cortical connections, yet little is known about how myeloarchitecture develops throughout youth. We formulated a novel approach to study cortical myeloarchitecture in individual humans and leveraged an accelerated longitudinal design to track age-related changes from 14-27 years. We discovered two unique processes: one involving increasing mean myelin and another characterised by the preferential accumulation of myelin in mid-to-deeper cortical layers. Both processes contributed to an increasing segregation of lower-order from higher-order systems along the macroscale cortical hierarchy. These findings illustrate how layer specific microstructural changes contribute to the maturation of cortical organization and suggest adolescent fine tuning of hierarchical gradients of cortical networks.

neuroscience↗

Conservative and disruptive modes of adolescent change in brain functional connectivity

Adolescent changes in human brain function are not entirely understood. Here we used multi-echo functional magnetic resonance imaging (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in N=298 healthy adolescents. Participants were aged 14-26 years and were scanned on two or more occasions at least 6 months apart. We found two distinct modes of age-related change in FC: \"conservative\" and \"disruptive\". Conservative development was characteristic of primary cortex, which was strongly connected at 14 years and became even more connected in the period 14-26 years. Disruptive development was characteristic of association cortex, hippocampus and amygdala, which were not strongly connected at 14 years but became more strongly connected during adolescence. We defined the maturational index (MI) as the signed coefficient of the linear relationship between baseline FC (at 14 years, FC14) and adolescent change in FC ({triangleup}FC14-26). Disruptive systems (with negative MI) were functionally specialised for social cognition and autobiographical memory and were significantly co-located with prior maps of aerobic glycolysis (AG), AG-related gene expression, post-natal expansion of cortical surface area, and adolescent shrinkage of cortical depth. We conclude that human brain organization is disrupted during adolescence by the emergence of strong functional connectivity of subcortical nuclei and association cortical areas, representing metabolically expensive re-modelling of synaptic connectivity between brain regions that were not strongly connected in childhood. We suggest that this re-modelling process may support emergence of social skills and self-awareness during healthy human adolescence.

neuroscience↗

Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental Disorders

Neurodevelopmental disorders are highly heritable and associated with spatially-selective disruptions of brain anatomy. The logic that translates genetic risks into spatially patterned brain vulnerabilities remains unclear but is a fundamental question in disease pathogenesis. Here, we approach this question by integrating (i) in vivo neuroimaging data from patient subgroups with known causal genomic copy number variations (CNVs), and (ii) bulk and single-cell gene expression data from healthy cortex. First, for each of six different CNV disorders, we show that spatial patterns of cortical anatomy change in youth are correlated with spatial patterns of expression for CNV region genes in bulk cortical tissue from typically-developing adults. Next, by transforming normative bulk-tissue cortical expression data into cell-type expression maps, we further link each disorders anatomical change map to specific cell classes and specific CNV-region genes that these cells express. Finally, we establish convergent validity of this "transcriptional vulnerability model" by inter-relating patient neuroimaging data with measures of altered gene expression in both brain and blood-derived patient tissue. Our work clarifies general biological principles that govern the mapping of genetic risks onto regional brain disruption in neurodevelopmental disorders. We present new methods that can harness these principles to screen for potential cellular and molecular determinants of disease from readily available patient neuroimaging data.

neuroscience↗

Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia related genes

Schizophrenia has been conceived as a disorder of brain connectivity but it is unclear how this network phenotype is related to the emerging genetics. We used morphometric similarity analysis of magnetic resonance imaging (MRI) data as a marker of inter-areal cortical connectivity in three prior case-control studies of psychosis: in total, N=185 cases and N=227 controls. Psychosis was associated with globally reduced morphometric similarity (MS) in all 3 studies. There was also a replicable pattern of case-control differences in regional MS which was significantly reduced in patients in frontal and temporal cortical areas, but increased in parietal cortex. Using prior brain-wide gene expression data, we found that the cortical map of case-control differences in MS was spatially correlated with cortical expression of a weighted combination of genes enriched for neu-robiologically relevant ontology terms and pathways. In addition, genes that were normally over-expressed in cortical areas with reduced MS were significantly up-regulated in a prior post mortem study of schizophrenia. We propose that this combination of neuroimaging and transcriptional data provides new insight into how previously implicated genes and proteins, as well as a number of unreported proteins in their vicinity on the protein interaction network, may interact to drive structural brain network changes in schizophrenia.

neuroscience↗

Brain-behaviour modes of covariation in healthy and clinically depressed young people

Understanding how variations in dimensions of psychometrics, IQ and demographics relate to changes in brain connectivity during the critical developmental period of adolescence and early adulthood is a major challenge. This has particular relevance for mental health disorders where a failure to understand these links might hinder the development of better diagnostic approaches and therapeutics. Here, we investigated this question in 306 adolescents and young adults (14-24y, 25 clinically depressed) using a multivariate statistical framework, based on canonical correlation analysis (CCA). By linking individual functional brain connectivity profiles to self-report questionnaires, IQ and demographic data we identified two distinct modes of covariation. The first mode mapped onto an externalization/internalization axis and showed a strong association with sex. The second mode mapped onto a well-being/distress axis independent of sex. Interestingly, both modes showed an association with age. Crucially, the changes in functional brain connectivity associated with changes in these phenotypes showed marked developmental effects. The findings point to a role for the default mode, frontoparietal and limbic networks in psychopathology and depression.

neuroscience↗

Schizotypy-related magnetization of cortex in healthy adolescence is co-located with expression of schizophrenia risk genes

BackgroundGenetic risk is thought to drive clinical variation on a spectrum of schizophrenia-like traits but the underlying changes in brain structure that mechanistically link genomic variation to schizotypal experience and behaviour are unclear. MethodsWe assessed schizotypy using a self-reported questionnaire, and measured magnetization transfer (MT), as a putative micro-structural MRI marker of intra-cortical myelination, in 68 brain regions, in 248 healthy young people (aged 14-25 years). We used normative adult brain gene expression data, and partial least squares (PLS) analysis, to find the weighted gene expression pattern that was most co-located with the cortical map of schizotypy-related magnetization (SRM). ResultsMagnetization was significantly correlated with schizotypy in bilateral posterior cingulate cortex and precuneus (and for disorganized schizotypy also in medial prefrontal cortex; all FDR-corrected P < 0.05), which are regions of the default mode network specialized for social and memory functions. The genes most positively weighted on the whole genome expression map co-located with SRM were enriched for genes that were significantly down-regulated in two prior case-control histological studies of brain gene expression in schizophrenia. Conversely, the most negatively weighted genes were enriched for genes that were transcriptionally up-regulated in schizophrenia. Positively weighted (down-regulated) genes were enriched for neuronal, specifically inter-neuronal, affiliations and coded a network of proteins comprising a few highly interactive "hubs" such as parvalbumin and calmodulin. ConclusionsMicrostructural MRI maps of intracortical magnetization can be linked to both the behavioural traits of schizotypy and to prior histological data on dysregulated gene expression in schizophrenia.

neuroscience↗

Using normative age modelling to isolate subsets of individuals with autism expressing highly age-atypical cortical thickness features

Understanding heterogeneity in neural phenotypes is an important goal on the path to precision medicine for autism spectrum disorders (ASD). Age is a critically important variable in normal structural brain development and examining structural features with respect to age-related norms could help to explain ASD heterogeneity in neural phenotypes. Here we examined how cortical thickness (CT) in ASD can be parameterized as an individualized metric of deviance relative to typically-developing (TD) age-related norms. Across a large sample (n=870 per group) and wide age range (5-40 years), we applied a normative modelling approach that provides individualized whole-brain maps of age-related CT deviance in ASD. This approach isolates a subgroup of ASD individuals with highly age-deviant CT. The median prevalence of this ASD subgroup across all brain regions is 7.6%, and can reach as high as 10% for some brain regions. This work showcases an individualized approach for understanding ASD heterogeneity that could potentially further prioritize work on a subset of individuals with significant cortical pathophysiology represented in age-related CT deviance. Rather than cortical thickness pathology being a widespread characteristic of most ASD patients, only a small subset of ASD individuals are actually highly deviant relative to age-norms. These individuals drive small on-average effects from case-control comparisons. Rather than sticking to the diagnostic label of autism, future research should pivot to focus on isolating subsets of autism patients with highly deviant phenotypes and better understand the underlying mechanisms that drive those phenotypes.

neuroscience↗

Synaptic and transcriptionally downregulated genes are associated with cortical thickness differences in autism

Differences in cortical morphology - in particular, cortical volume, thickness and surface area - have been reported in individuals with autism. However, it is unclear what aspects of genetic and transcriptomic variation are associated with these differences. Here we investigate the genetic correlates of global cortical thickness differences ({Delta}CT) in children with autism. We used Partial Least Squares Regression (PLSR) on structural MRI data from 548 children (166 with autism, 295 neurotypical children and 87 children with ADHD) and cortical gene expression data from the Allen Institute for Brain Science to identify genetic correlates of {Delta}CT in autism.\n\nWe identify that these genes are enriched for synaptic transmission pathways and explain significant variation in {Delta}CT. These genes are also significantly enriched for genes dysregulated in the autism post-mortem cortex (Odd Ratio (OR) = 1.11, Pcorrected < 10-14), driven entirely by downregulated genes (OR = 1.87, Pcorrected < 10-15). We validated the enrichment for downregulated genes in two independent datasets: Validation 1 (OR = 1.44, Pcorrected = 0.004) and Validation 2 (OR = 1.30; Pcorrected = 0.001). We conclude that transcriptionally downregulated genes implicated in autism are robustly associated with global changes in cortical thickness variability in children with autism.

neuroscience↗