Bi-allelic variants in CELSR3 are implicated in central nervous system and urinary tract anomalies

CELSR3 codes for a planar cell polarity protein. We describe twelve affected individuals from eleven independent families with bi-allelic variants in CELSR3. Affected individuals presented with an overlapping phenotypic spectrum comprising central nervous system (CNS) anomalies (7/12), combined CNS anomalies and congenital anomalies of the kidneys and urinary tract (CAKUT) (3/12) and CAKUT only (2/12). Computational simulation of the 3D protein structure suggests the position of the identified variants to be implicated in penetrance and phenotype expression. CELSR3 immunolocalization in human embryonic urinary tract and transient suppression and rescue experiments of Celsr3 in fluorescent zebrafish reporter lines further support an embryonic role of CELSR3 in CNS and urinary tract formation.</p

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large‐scale studies. In response, we used cross‐sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to infer age‐related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta‐analysis and one‐way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to examine age‐related trajectories inferred from cross‐sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3–90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter‐individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age‐related morphometric patterns

Identifying multimodal signatures underlying the somatic comorbidity of psychosis: the COMMITMENT roadmap

Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40-60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p &amp;lt; 2.8 × 10?6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20-25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p = 8 × 10?13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10?43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10?22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10?12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10?4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10?7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10?29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence

X-linked variations in SHROOM4 are implicated in congenital anomalies of the urinary tract and the anorectal, cardiovascular and central nervous systems

BackgroundSHROOM4 is thought to play an important role in cytoskeletal modification and development of the early nervous system. Previously, single-nucleotide variants (SNVs) or copy number variations (CNVs) in SHROOM4 have been associated with the neurodevelopmental disorder Stocco dos Santos syndrome, but not with congenital anomalies of the urinary tract and the visceral or the cardiovascular system. MethodsHere, exome sequencing and CNV analyses besides expression studies in zebrafish and mouse and knockdown (KD) experiments using a splice blocking morpholino in zebrafish were performed to study the role of SHROOM4 during embryonic development. ResultsIn this study, we identified putative disease-causing SNVs and CNVs in SHROOM4 in six individuals from four families with congenital anomalies of the urinary tract and the anorectal, cardiovascular and central nervous systems (CNS). Embryonic mouse and zebrafish expression studies showed Shroom4 expression in the upper and lower urinary tract, the developing cloaca, the heart and the cerebral CNS. KD studies in zebrafish larvae revealed pronephric cysts, anomalies of the cloaca and the heart, decreased eye-to-head ratio and higher mortality compared with controls. These phenotypes could be rescued by co-injection of human wild-type SHROOM4 mRNA and morpholino. ConclusionThe identified SNVs and CNVs in affected individuals with congenital anomalies of the urinary tract, the anorectal, the cardiovascular and the central nervous systems, and subsequent embryonic mouse and zebrafish studies suggest SHROOM4 as a developmental gene for different organ systems

Brain Heterogeneity in Schizophrenia and Its Association With Polygenic Risk

Between-individual variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients with schizophrenia. However, group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature

Emotional Voice Processing: Investigating the Role of Genetic Variation in the Serotonin Transporter across Development

The ability to effectively respond to emotional information carried in the human voice plays a pivotal role for social interactions. We examined how genetic factors, especially the serotonin transporter genetic variation (5-HTTLPR), affect the neurodynamics of emotional voice processing in infants and adults by measuring event-related brain potentials (ERPs). The results revealed that infants distinguish between emotions during an early perceptual processing stage, whereas adults recognize and evaluate the meaning of emotions during later semantic processing stages. While infants do discriminate between emotions, only in adults was genetic variation associated with neurophysiological differences in how positive and negative emotions are processed in the brain. This suggests that genetic association with neurocognitive functions emerges during development, emphasizing the role that variation in serotonin plays in the maturation of brain systems involved in emotion recognition

Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder

Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients