Biology subjects

Bearden, C. E.

Publications and source records attributed to Bearden, C. E..

At least 19 recordsLinked to original sources

bioRxiv2026

Synaptic microRNA dysregulation orchestrates aberrant glutamatergic transmission in a human neuronal model of 22q11.2 deletion syndrome

22q11.2 Deletion Syndrome (22q11DS), the most prevalent chromosomal microdeletion disorder in humans (incidence ~1 in 4,000 live births), arises from hemizygous deletions of a 1.5-3.0 Mb region on chromosome 22. Notably, 20-30% of individuals with 22q11DS develop schizophrenia (SCZ) by early adulthood, making 22q11DS one of the strongest genetic risk factors for SCZ. However, the mechanisms by which the 22q11.2 deletion perturbs neuronal function and drive psychotic manifestations in 22q11DS remain poorly defined. In this study, we generated human 2D cortical neurons and 3D cortical organoids from induced pluripotent stem cells (iPSCs) derived from clinically well-characterized individuals with 22q11DS. Cellular and electrophysiological analyses revealed that 22q11DS neurons exhibit hyperexcitability, reduced glutamatergic synaptic transmission, and impaired homeostatic synaptic plasticity, which are pathophysiological hallmarks that may be relevant to the clinical, cognitive, and psychophysiological profiles of patients. Transcriptomic profiling of neurons and synaptosomes from 22q11DS cortical organoids uncovered dysregulated immune pathways and synaptic gene networks. Integrative mRNA-microRNA network analysis identified synergistic downregulation of hsa-miR-185-5p and hsa-miR-128-3p at synapses, driving aberrant regulation of immune and synaptic transcripts. Experimental knockdown of these microRNAs in control neurons recapitulated the molecular and functional phenotypes of 22q11DS neurons, thereby establishing a mechanistic link to synaptic dysfunction and impaired plasticity. Collectively, these findings delineate a multimodal mechanistic framework that bridges genetic vulnerability, synaptic pathology, and psychosis penetrance in 22q11DS, positioning dysregulated synaptic microRNAs as nodal regulators of neurodevelopmental networks and potential therapeutic targets.

neuroscience↗

bioRxiv2026

Analysis of Rare Coding Variation Identifies New Genetic Contributors to Schizophrenia

In this study, we present the largest rare coding variant association study of schizophrenia to date, with 87,959 schizophrenia cases and 150,587 controls. We identify 16 genes at exome-wide significance: SETD1A, ZMYM2, HERC1, RB1CC1, SCAF1, XPO7, SP4, FYN, PPP3CA, CUL1, HDAC9, JARID2, ATP9A, PTK2, STAG1, and SCN2A, and an additional 24 at a 5% false discovery rate. Cases carrying ultra-rare, damaging variants, primarily protein-truncating and deleterious missense mutations, show strong enrichment in constrained genes with consistent effects across ancestries. Half of the 40 identified genes overlap with those implicated in developmental delay, autism, or bipolar disorder, underscoring shared neurodevelopmental risk. All 40 genes identified are highly expressed in excitatory and inhibitory neurons, and their expression patterns span diverse developmental stages. Functionally, the identified genes implicate chromatin regulation, protein degradation, and synaptic function. Overall, our results advance understanding of the genetic architecture of schizophrenia, provide a foundation for modeling risk genes in cellular and animal systems, and offer a framework for future work toward biologically informed patient stratification.

genetics↗

bioRxiv2026

Symptom Dimension-Specific Neurotransmitter Correlates of Psychopathology and Cognition in Early Psychosis

Extended duration of under-treated psychosis (DUP) is among the strongest predictors of poor outcome, yet diagnostic heterogeneity impedes treatment matching, with approximately 50% of patients failing to respond to first-line antipsychotics. Negative symptoms and cognitive impairment are particularly refractory, lacking effective pharmacological treatments. Identifying neurotransmitter systems associated with specific symptom dimensions could accelerate targeted therapeutic development and reduce DUP. We applied Partial Least Squares correlation (PLSc) to derive whole-brain resting-state functional connectivity (RSFC) and anatomical (cortical thickness and subcortical volume) signatures associated with five psychopathology dimensions (positive symptoms, negative symptoms, general psychopathology, mania, and cognition) in a transdiagnostic sample from the Human Connectome Project-Early Psychosis (HCP-EP; n=124). We tested associations with potential confounds including antipsychotic medication dosage and substance use. Signatures were spatially correlated with 21 Positron Emission Tomography (PET)-derived receptor and transporter maps across 9 neurotransmitter systems using the neuromaps toolbox. Significant RSFC signatures emerged for positive symptoms, negative symptoms, general psychopathology, and cognition, but not mania. The negative symptom RSFC signature correlated with norepinephrine transporter (NET; {rho}=.40, q=.030) and vesicular acetylcholine transporter (VAChT; {rho}=.38, q=.048) distributions. The cognition signature similarly correlated with VAChT ({rho}=.48, q=.025). Anatomical signatures were associated with positive symptoms, general psychopathology, and cognition, but were more susceptible to confounding by medication and substance use. No significant receptor associations were detected for anatomical signatures. These findings implicate cholinergic and noradrenergic systems as molecular targets for negative symptoms and cognitive impairment, supporting prioritization of these systems in pharmacotherapy development in early psychosis.

neuroscience↗

bioRxiv2026

Spectral and non-spectral EEG measures in the prediction of working memory task performance and psychopathology

Working memory (WM) supports the temporary maintenance of goal-relevant information and is disrupted across many neuropsychiatric disorders. We examined whether scalp electroencephalography (EEG) data features beyond spectral power, including waveform shape, broadband spectral structure, and signal complexity, provide complementary information for predicting cognitive and clinical outcomes. EEG was recorded from 200 adults spanning a broad range of neuropsychiatric symptom severity while they completed three WM task paradigms: Sternberg spatial WM (SWM), delayed face recognition (DFR), and dot pattern expectancy (DPX). Separate machine learning models were trained on EEG features from the encoding, delay, and probe phase of each task to predict participants task accuracy, reaction time (RT) variability, WM capacity, and psychopathology scores (Brief Psychiatric Rating Scale). A split-half analytic framework was used, with cross-validated model development in an exploratory dataset (N=100) and evaluation of statistically significant models in a held-out validation dataset (N=100). In the exploratory dataset, SWM task data best predicted WM capacity, DPX task data predicted RT variability, and DFR task data predicted psychopathology, suggesting that these three WM paradigms engage distinct neural processes relevant to different outcomes. No models reliably predicted task accuracy. Models incorporating features beyond spectral power generally outperformed power-only models, and task-derived features outperformed resting-state-derived features. However, only those models predicting WM capacity and RT variability generalized to the validation dataset; models predicting psychopathology did not. These findings demonstrate functional heterogeneity across WM paradigms, show that complementary EEG features enhance predictive modeling, and highlight the importance of rigorous validation for identifying robust brain-behavior relationships.

neuroscience↗

bioRxiv2026

Genetic insights on the mechanisms of human cortical folding

The unique and intricate pattern of human cortical folding is rooted in fetal neurodevelopmental processes and can now be comprehensively quantified by new neuroimaging-derived measures of sulcal complexity. Here, we provide the first genetic maps of human sulcal complexity. Beginning with large effects of rare variants, we survey nine different neurogenetic syndromes (n=615), detecting visible changes in sulcal complexity on a shared axis of sulcal change coupled to the prenatal timing of sulcation. Turning to common genetic variants, we use genome-wide association studies of complexity scores for 40 sulci in the UK Biobank (n[~]29,000) to (i) resolve variable heritability across sulci, (ii) reveal both local and remote shared genetic effects with cortical morphology, and (iii) identify complexity-associated genes and their embedding in brain maps of prenatal gene expression. These reference genetic maps uncover multiple new mechanistic pathways for cortical morphogenesis in health and disease.

neuroscience↗

bioRxiv2025

Convergent and Divergent Cerebellar Alterations in 22q11.2 Copy Number Variants

BackgroundIndividuals with copy number variants (CNVs) at 22q11.2 are at elevated risk for neurodevelopmental and psychiatric disorders, including autism spectrum disorder and intellectual disability. For psychosis, effects diverge, with 22q11.2 deletion (22qDel) conferring one of the highest known risks for schizophrenia, while duplication (22qDup) may be protective. Prior investigations of neurobiological mechanisms in 22q11.2 CNVs have predominantly focused on the cerebrum, whereas the cerebellum--a region increasingly recognized for its contributions to cognitive, affective, and social processes--remains underexplored and represents a promising target for investigation. Although alterations in cerebellar structure have been reported in 22qDel, they remain largely unexplored in 22qDup. This study provides the first characterization of regional cerebellar volumes in 22qDup and the first direct comparison of cerebellar structure across 22q11.2 CNVs, offering a unique opportunity to identify shared and distinct neurobiological mechanisms with implications for understanding cerebellar contributions to brain-behavior relationships in CNV carriers. MethodsWe analyzed 514 longitudinally collected structural Magnetic Resonance Imaging (MRI) scans of 111 individuals with 22qDel, 37 individuals with 22qDup, and 167 typically developing (TD) controls. Total and regional cerebellar volumes were quantified using ACAPULCO, a deep-learning-based parcellation method that segments the cerebellum into 28 subregions. Group differences in cerebellar volumes, as well as their associations with cognition, autism-related traits, and psychosis-risk symptoms, were examined using linear mixed-effects models. False discovery rate (FDR) correction was applied to control for multiple comparisons where appropriate. ResultsIn relation to TD controls, cerebellar volumes were broadly reduced in 22qDel, whereas cerebellar alterations in 22qDup were more modest and variable. Regional analyses revealed both linear (22qDel < TD < 22qDup) and nonlinear (22qDel {approx} 22qDup < TD; 22qDel < 22qDup < TD) gene-dosage patterns, though not all reached significance. Vermis VII was significantly reduced in both CNVs but showed no relationship to behavioral differences. In contrast, reduction of Right Lobule VIIIA was associated with greater social impairment in 22qDup. Unlike TD controls, this region was not associated with IQ in 22qDup, suggesting CNV-specific alterations in cerebellar-behavior relationships. ConclusionThese findings indicate that reciprocal CNVs at the 22q11.2 locus both affect cerebellar structure, yet their functional consequences diverge, suggesting overlapping but distinct pathways to clinical risk. They underscore the cerebellums multifaceted role in neurodevelopment and highlight the need for studies examining broader cognitive and socio-affective domains, as well as cerebellar-cortical connectivity, to clarify links to clinical outcomes.

neuroscience↗

bioRxiv2025

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblast reveals shared allelic effects between Latin American and European ancestries

Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n=150) and Latin American (n=96) ancestries. Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R{superscript 2} [≥] 0.93 for eQTL effect sizes and R{superscript 2} [≥] 0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 high-confidence (posterior probability > 90 %) regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations.

genomics↗

bioRxiv2025

Multivariate Resting-State Functional Connectivity Features Linked to Transdiagnostic Psychopathology in Early Psychosis

BackgroundEarly psychosis (EP) is characterized by neurobiological changes, including alterations in resting-state functional connectivity (RSFC). We now understand that symptoms and neural changes may overlap across EP diagnostic categories. However, the relationship between RSFC patterns and transdiagnostic symptom dimensions remains poorly understood. MethodsWe employed Partial Least Squares correlation to examine multivariate relationships between whole-brain RSFC and clinical symptoms in 124 EP patients (aged 16-35 years) diagnosed with schizophrenia, schizoaffective disorder, or a psychotic mood disorder. RSFC was computed among 216 cortical and subcortical regions. Clinical assessment included 41 symptom measures spanning positive, negative, general psychopathology, and manic dimensions. ResultsAnalysis revealed one significant latent component (p<0.001) capturing 41.6% of the RSFC-symptom covariance. This component was characterized by increased between-network connectivity, particularly involving sensory-motor, default mode, and subcortical regions including the amygdala and thalamus. The associated symptom profile included cognitive rigidity and arousal dysregulation (stereotyped thinking, anxiety, and somatic concerns), rather than traditional positive or negative symptoms. This brain-behavior relationship was consistent across diagnoses and independent of medication and substance use. The clinical relevance was validated through significant correlations with standardized measures of hostility (r=0.23), negative affect (r=0.25), and perceived stress (r=0.22). ConclusionsOur findings reveal a distinct transdiagnostic phenotype in EP characterized by cognitive inflexibility and arousal dysregulation that is associated with altered integration between sensory, default mode, and subcortical networks. This work suggests that specific patterns of network-level functional connectivity may relate to symptom dimensions that cut across conventional diagnostic boundaries, potentially informing more targeted therapeutic approaches.

neuroscience↗

bioRxiv2025

Gene dosage effects of 22q11.2 copy number variants on in-vivo measures of white matter axonal density and dispersion

22q11.2 deletion (22qDel) and duplication (22qDup) carriers have an increased risk of neurodevelopmental disorders and exhibit altered brain structure, including white matter microstructure. However, the underlying cellular architecture and age-related changes contributing to these white matter alterations remain poorly understood. Neurite orientation dispersion and density imaging (NODDI) was used on mixed cross-sectional and longitudinal data to examine group differences and age-related trajectories in measures of axonal density (i.e., intracellular volume fraction; ICVF), axonal orientation (orientation dispersion index; ODI) and free water diffusion (isotropic volume fraction; ISO) in 50 22qDel (n scans = 69, mean age = 20.7, age range = 7.4-51.1, 64.0% female) and 24 22qDup (n scans = 34, mean age = 21.6, age range = 8.3-49.4, 54.2% female) carriers, and 890 controls (n scans = 901, mean age = 21.9, age range = 7.8-51.1, 54.5% female). The results showed widespread gene dosage effects, with higher ICVF in 22qDel and lower ICVF in 22qDup compared to controls, and region-specific effects of the 22qDel and 22qDup on ODI and ISO measures. However, 22qDel and 22qDup carriers did not exhibit altered age-related trajectories relative to controls. Observed differences in ICVF suggest higher white matter axonal density in 22qDel and lower axonal density in 22qDup compared to controls. Conversely, differences in ODI are highly localized, indicating region-specific effects on axonal dispersion in white matter. We do not find evidence for altered developmental trajectories of axonal density or dispersion among 22q11.2 CNV carriers, suggesting stable disruptions to neurodevelopmental events before childhood.

neuroscience↗

bioRxiv2024

Lifespan Normative Modeling of Brain Microstructure

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

neuroscience↗

bioRxiv2024

Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated with Psychopathology Across Independent Cohorts

BackgroundEarly Psychosis patients (EP, within 3 years after psychosis onset) show significant variability, making outcome predictions challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, limiting the development of early interventions. MethodsA data-driven approach, Partial Least Squares (PLS) correlation, was used across two independent datasets to examine multivariate relationships between white matter (WM) properties and symptomatology, to identify stable and generalizable signatures in EP. The primary cohort included EP patients from the Human Connectome Project-Early Psychosis (n=124). The replication cohort included EP patients from the Feinstein Institute for Medical Research (n=78). Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders. ResultsIn both cohorts, a significant latent component (LC) corresponded to a symptom profile combining negative symptoms, primarily diminished expression, with specific somatic symptoms. Both LCs captured comprehensive features of WM disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the PLS model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use. ConclusionsThis data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural WM alterations in EP, across diagnoses and datasets, showing a strong covariance of these alterations with a unique profile of negative and somatic symptoms. This finding suggests the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.

neuroscience↗

bioRxiv2024

Unique functional neuroimaging signatures of genetic versus clinical high risk for psychosis

Background22q11.2 Deletion Syndrome (22qDel) is a copy number variant (CNV) associated with psychosis and other neurodevelopmental disorders. Adolescents at clinical high risk for psychosis (CHR) have subthreshold psychosis symptoms without known genetic risk factors. Whether common neural substrates underlie these distinct high-risk populations is unknown. We compared functional brain measures in 22qDel and CHR cohorts and mapped results to biological pathways. MethodsWe analyzed two large multi-site cohorts with resting-state functional MRI (rs-fMRI): 1) 22qDel (n=164, 47% female) and typically developing (TD) controls (n=134, 56% female); 2) CHR individuals (n=244, 41% female) and TD controls (n=151, 46% female) from the North American Prodrome Longitudinal Study-2. We computed global brain connectivity (GBC), local connectivity (LC), and brain signal variability (BSV) across cortical regions, testing case-control differences for 22qDel and CHR separately. Group difference maps were related to published brain maps using autocorrelation-preserving permutation. ResultsBSV, LC, and GBC are significantly disrupted in 22qDel compared with TD controls (False Discovery Rate q<0.05). Spatial maps of BSV and LC differences are highly correlated with each other, unlike GBC. In CHR, only LC is significantly altered versus controls, with a different spatial pattern compared to 22qDel. Group differences map onto biological gradients, with 22qDel effects strongest in regions with high predicted blood flow and metabolism. Conclusion22qDel and CHR exhibit divergent effects on fMRI temporal variability and multi-scale functional connectivity. In 22qDel, strong and convergent disruptions in BSV and LC not seen in CHR individuals suggest distinct functional brain alterations.

neuroscience↗

bioRxiv2024

Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome

Chromosome 22q11.2 deletion is among the strongest known genetic risk factors for neuropsychiatric disorders, including autism and schizophrenia. Brain imaging studies have reported disrupted large-scale functional connectivity in people with 22q11 deletion syndrome (22q11DS). However, the significance and biological determinants of these functional alterations remain unclear. Here, we use a cross-species design to investigate the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. We find that LgDel mice, an established mouse model of 22q11DS, exhibit age-specific patterns of functional MRI (fMRI) dysconnectivity, with widespread fMRI hyper-connectivity in juvenile mice reverting to focal hippocampal hypoconnectivity over puberty. These fMRI connectivity alterations are mirrored by co-occurring developmental alterations in dendritic spine density, and are both transiently normalized by developmental GSK3{beta} inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous hyper-to hypoconnectivity reconfiguration occurs also in human 22q11DS, where it affects hippocampal and cortical regions spatially enriched for synaptic genes that interact with GSK3{beta}, and autism-relevant transcripts. Functional dysconnectivity in somatomotor components of this network is predictive of age-dependent social alterations in 22q11.2 deletion carriers. Taken together, these findings suggest that synaptic-related mechanisms underlie developmentally mediated functional dysconnectivity in 22q11DS.

neuroscience↗

bioRxiv2023

Effects of Gene Dosage and Development on Subcortical Nuclei Volumes in Individuals with 22q11.2 Copy Number Variations

The 22q11.2 locus contains genes critical for brain development. Reciprocal Copy Number Variations (CNVs) at this locus impact risk for neurodevelopmental and psychiatric disorders. Both 22q11.2 deletions (22qDel) and duplications (22qDup) are associated with autism, but 22qDel uniquely elevates schizophrenia risk. Understanding brain phenotypes associated with these highly penetrant CNVs can provide insights into genetic pathways underlying neuropsychiatric disorders. Human neuroimaging and animal models indicate subcortical brain alterations in 22qDel, yet little is known about developmental differences across specific nuclei between reciprocal 22q11.2 CNV carriers and typically developing (TD) controls. We conducted a longitudinal MRI study in 22qDel (n=96, 53.1% female), 22qDup (n=37, 45.9% female), and TD controls (n=80, 51.2% female), across a wide age range (5.5-49.5 years). Volumes of the thalamus, hippocampus, amygdala, and anatomical subregions were estimated using FreeSurfer, and the effect of 22q11.2 gene dosage was examined using linear mixed models. Age-related changes were characterized with general additive mixed models (GAMMs). Positive gene dosage effects (22qDel < TD < 22qDup) were observed for total intracranial and whole hippocampus volumes, but not whole thalamus or amygdala volumes. Several amygdala subregions exhibited similar positive effects, with bi-directional effects found across thalamic nuclei. Distinct age- related trajectories were observed across the three groups. Notably, both 22qDel and 22qDup carriers exhibited flattened development of hippocampal CA2/3 subfields relative to TD controls. This study provides novel insights into the impact of 22q11.2 CNVs on subcortical brain structures and their developmental trajectories.

neuroscience↗

bioRxiv2023

Longitudinal development of thalamocortical functional connectivity in 22q11.2 deletion syndrome

Background22q11.2 Deletion Syndrome (22qDel) is a genetic Copy Number Variant (CNV) that strongly increases risk for schizophrenia and other neurodevelopmental disorders. Disrupted functional connectivity between the thalamus and somatomotor/frontoparietal cortex has been implicated in cross-sectional studies of 22qDel, idiopathic schizophrenia, and youth at clinical high risk (CHR) for psychosis. Here, we use a novel functional atlas approach to investigate longitudinal age-related changes in network-specific thalamocortical functional connectivity (TCC) in 22qDel and typically developing (TD) controls. MethodsTCC was calculated for nine functional networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) scans collected from n=65 22qDel participants (63.1% female) and n=69 demographically matched TD controls (49.3% female), ages 6 to 23 years. Analyses included 86 longitudinal follow-up scans. Non-linear age trajectories were characterized with general additive mixed models (GAMMs). ResultsIn 22qDel, TCC in the frontoparietal network increases until approximately age 13, while somatomotor and cingulo-opercular TCC decrease from age 6 to 23. In contrast, no significant relationships between TCC and age were found in TD controls. Somatomotor connectivity in 22qDel is significantly higher than TD in childhood, but lower in late adolescence. Frontoparietal TCC shows the opposite pattern. Conclusions22qDel is associated with aberrant development of functional network connectivity between the thalamus and cortex. Younger individuals with 22qDel have lower frontoparietal connectivity and higher somatomotor connectivity than controls, but this phenotype may normalize or partially reverse by early adulthood. Altered maturation of this circuitry may underlie elevated neuropsychiatric disease risk in this syndrome.

neuroscience↗

bioRxiv2023

Using rare genetic mutations to revisit structural brain asymmetry

Asymmetry between the left and right brain is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variant studies, which typically exert small effects on brain phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We quantitatively dissected the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior mapping highlights the consequences of genetically controlled brain lateralization on human-defining cognitive traits.

neuroscience↗

bioRxiv2022

Linking Choroid Plexus Enlargement with Plasma Analyte and Structural Phenotypes in Clinical High Risk for Psychosis: A Multisite Neuroimaging Study

BackgroundChoroid plexus (ChP) enlargement exists in first-episode and chronic psychosis, but whether enlargement occurs before psychosis onset is unknown. This study investigated whether ChP volume is enlarged in individuals with clinical high-risk (CHR) for psychosis and whether these changes are related to clinical, neuroanatomical, and plasma analytes. MethodsClinical and neuroimaging data from the North American Prodrome Longitudinal Study 2 (NAPLS2) was used for analysis. 509 participants (169 controls, 340 CHR) were recruited. Conversion status was determined after 2-years of follow-up, with 36 psychosis converters. The lateral ventricle ChP was manually segmented from baseline scans. A subsample of 31 controls and 53 CHR had plasma analyte and neuroimaging data. ResultsCompared to controls, CHR (d=0.23, p=0.017) and non-converters (d=0.22, p=0.03) demonstrated higher ChP volumes, but not in converters. In CHR, greater ChP volume correlated with lower cortical (r=-0.22, p<0.001), subcortical gray matter (r=-0.21, p<0.001), and total white matter volume (r=-0.28,p<0.001), as well as larger lateral ventricle volume (r=0.63,p<0.001). Greater ChP volume correlated with makers functionally associated with the lateral ventricle ChP in CHR [CCL1 (r=-0.30, p=0.035), ICAM1 (r=0.33, p=0.02)], converters [IL1{beta} (r=0.66, p=0.004)], and non-converters [BMP6 (r=-0.96, p<0.001), CALB1 (r=-0.98, p<0.001), ICAM1 (r=0.80, p=0.003), SELE (r=0.59, p=0.026), SHBG (r=0.99, p<0.001), TNFRSF10C (r=0.78, p=0.001)]. ConclusionsCHR and non-converters demonstrated significantly larger ChP volumes compared to controls. Enlarged ChP was associated with neuroanatomical alterations and analyte markers functionally associated with the ChP. These findings suggest that the ChP may be a key explanatory biomarker in CHR for psychosis.

neuroscience↗

bioRxiv2022

Chromatin regulators in the TBX1 network confer risk for conotruncal heart defects in 22q11.2DS and sporadic congenital heart disease

BackgroundCongenital heart disease (CHD) affecting the conotruncal region of the heart, occur in half of patients with 22q11.2 deletion syndrome. This syndrome is a rare disorder with relative genetic homogeneity that can facilitate identification of genetic modifiers. Haploinsufficiency of TBX1, mapped to the 22q11.2 region, encoding a T-box transcription factor, is one of the main genes for the etiology of the syndrome. We suggest that genetic modifiers of CHD in patients with 22q11.2 deletion syndrome may be in the TBX1 gene network. MethodsTo identify genetic modifiers of 22q11.2 deletion syndrome, we analyzed whole genome sequence of subjects with 22q11.2DS, of which 456 were cases with conotruncal heart defects and 537 were controls with normal cardiac structures. We retained the most damaging rare coding variants and examined 19 functional gene sets for association that were weighted upon expression of genes in cardiac progenitor cells in mouse embryos identified by RNA-sequencing. ResultsWe identified rare damaging coding variants in chromatin regulatory genes as modifiers of conotruncal heart defects in 22q11.2DS. Chromatin genes with recurrent damaging variants include EP400, KAT6A, KMT2C, KMT2D, NSD1, CHD7 and PHF21A. In total, we identified 37 chromatin regulatory genes, that may increase risk for conotruncal heart defects in 8.5% of 22q11.2 deletion syndrome cases. Many of these genes were identified as risk factors for sporadic CHD in the general population increasing the likelihood that these genes are medically important contributors for CHD. These genes are co-expressed in cardiac progenitor cells with TBX1, suggesting that they may be in the same genetic network. Some of the genes identified, such as KAT6A, KMT2C, CHD7 and EZH2, have been previously shown to genetically interact with TBX1 in mouse models, providing mechanistic validation of these genes found. ConclusionsOur findings indicate that disturbance of chromatin regulatory genes impact a TBX1 gene network serving as genetic modifiers of 22q11.2 deletion syndrome. Since some of these chromatin regulatory genes were found in individuals with sporadic CHD, we suggest that there are shared mechanisms involving the TBX1 gene network in the etiology of CHD.

genetics↗