There is widespread overlap across major psychiatric disorders, and this is the case at different levels of observations, from genetic variants to brain structures and function and to symptoms. However, it remains unknown to what extent these commonalities at different levels of observation map onto each other. Here, we systematically review and compare the degree of similarity between psychiatric disorders at all available levels of observation.
View Article and Find Full Text PDFAsymmetry between the left and right hemisphere 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 variants, which typically exert small effects on brain-related phenotypes.
View Article and Find Full Text PDFReciprocal Copy Number Variants (CNVs) at the 16p11.2 locus confer high risk for autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDDs). Morphometric MRI studies have revealed large and pervasive volumetric alterations in carriers of a 16p11.
View Article and Find Full Text PDFAsymmetry 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.
View Article and Find Full Text PDFCopy number variations (CNVs) are rare genomic deletions and duplications that can affect brain and behaviour. Previous reports of CNV pleiotropy imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, existing studies have primarily examined single CNV loci in small clinical cohorts.
View Article and Find Full Text PDFPleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks.
View Article and Find Full Text PDFMed Image Comput Comput Assist Interv
September 2022
Multi-site imaging studies can increase statistical power and improve the reproducibility and generalizability of findings, yet data often need to be harmonized. One alternative to data harmonization in the normative modeling setting is Hierarchical Bayesian Regression (HBR), which overcomes some of the weaknesses of data harmonization. Here, we test the utility of three model types, i.
View Article and Find Full Text PDFObjective: Copy number variants (CNVs) are strongly associated with neurodevelopmental and psychotic disorders. Early-onset psychosis (EOP), where symptoms appear before 18 years of age, is thought to be more strongly influenced by genetic factors than adult-onset psychotic disorders. However, the prevalence and effect of CNVs in EOP is unclear.
View Article and Find Full Text PDFPathogenic copy number variants (CNVs) and aneuploidies alter gene dosage and are associated with neurodevelopmental psychiatric disorders such as autism spectrum disorder and schizophrenia. Brain mechanisms mediating genetic risk for neurodevelopmental psychiatric disorders remain largely unknown, but there is a rapid increase in morphometry studies of CNVs using T1-weighted structural magnetic resonance imaging. Studies have been conducted one mutation at a time, leaving the field with a complex catalog of brain alterations linked to different genomic loci.
View Article and Find Full Text PDFCopy Number Variants (CNVs) are associated with elevated rates of neuropsychiatric disorders. A 'genetics-first' approach, involving the CNV effects on the brain, irrespective of clinical symptomatology, allows investigation of mechanisms underlying neuropsychiatric disorders in the general population. Recent years have seen an increasing number of larger multisite neuroimaging studies investigating the effect of CNVs on structural and functional brain endophenotypes.
View Article and Find Full Text PDFNeuroimaging genomic studies of autism spectrum disorder and schizophrenia have mainly adopted a 'top-down' approach, beginning with the behavioural diagnosis, and moving down to intermediate brain phenotypes and underlying genetic factors. Advances in imaging and genomics have been successfully applied to increasingly large case-control studies. As opposed to diagnostic-first approaches, the bottom-up strategy begins at the level of molecular factors enabling the study of mechanisms related to biological risk, irrespective of diagnoses or clinical manifestations.
View Article and Find Full Text PDFThe Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population.
View Article and Find Full Text PDF16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) remains unclear.
View Article and Find Full Text PDFMetadata are what makes databases searchable. Without them, researchers would have difficulty finding data with features they are interested in. Brain imaging genetics is at the intersection of two disciplines, each with dedicated dictionaries and ontologies facilitating data search and analysis.
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