Biology subjects

Bralten, J.

Publications and source records attributed to Bralten, J..

14 recordsLinked to original sources

bioRxiv2021

Missing genetic links between general factors of brain resting-state functional magnetic resonance imaging, cognition and psychopathology

General factors capturing the shared genetics in psychiatric (genomic p-factor) and cognitive traits (genomic g-factor), and more recently in resting-state functional magnetic resonance imaging-derived brain networks, have contributed to our increased understanding of the etiologies in their respective domains. Yet it remains unclear whether general factors can capture the three-way genetic overlap of psychopathology, cognition and brain function. Here we tested for the presence of this genetic overlap via genetic correlation analyses using summary statistics of genome-wide association studies of the p-factor (N = 162,151 cases and 276,846 controls), the g-factor (N = 269,867), and the two genomic factors estimated from the amplitude in resting-state functional magnetic resonance imaging-derived brain networks (N = 31,688). Unlike hypothesized, only the genetic correlation between the p-factor and the g-factor was significant. We conclude that specific functional brain network constructs may have more potential than their derived general dimensions to capture relevant genetic variation for cognition and psychopathology.

neuroscience↗

bioRxiv2021

Shared genetic influences on resting-state functional networks of the brain

The amplitude of activation in brain resting state networks (RSNs), measured with resting-state functional MRI, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome-wide association studies (GWAS) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study we used a novel multivariate method called genomic SEM to model latent factors that capture the shared genomic influence on RSNs and to identify SNPs and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modelling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function.

neuroscience↗

bioRxiv2020

Examining sex-differentiated genetic effects across neuropsychiatric and behavioral traits

BackgroundThe origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations across these traits, we tested for a sex-differentiated genetic architecture within and between traits. MethodsUsing genome-wide association study (GWAS) summary statistics for 20 neuropsychiatric and behavioral traits, we tested for differences in SNP-based heritability (h2) and genetic correlation (rg<1) between sexes. For each trait, we computed z-scores from sex-stratified GWAS regression coefficients and identified genes with sex-differentiated effects. We calculated Pearson correlation coefficients between z-scores for each trait pair, to assess whether specific pairs share variants with sex-differentiated effects. Finally, we tested for sex differences in between-trait genetic correlations. ResultsWith current sample sizes (and power), we found no significant, consistent sex differences in SNP-based h2. Between-sex, within-trait genetic correlations were consistently high, although significantly less than 1 for educational attainment and risk-taking behavior. We identified genome-wide significant genes with sex-differentiated effects for eight traits. Several trait pairs shared sex-differentiated effects. The top 0.1% of genes with sex-differentiated effects across traits overlapped with neuron- and synapse-related gene sets. Most between-trait genetic correlation estimates were similar across sex, with several exceptions (e.g. educational attainment & risk-taking behavior). ConclusionsSex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic, requiring large sample sizes. Genes with sex-differentiated effects are enriched for neuron-related gene sets. This work motivates further investigation of genetic, as well as environmental, influences on sex differences.

genetics↗

bioRxiv2019

Genome-wide Association Study of Pediatric Obsessive-Compulsive Traits: Shared Genetic Risk between Traits and Disorder

ObjectiveTo identify genetic variants associated with obsessive-compulsive (OC) traits and test for sharing of genetic risks between OC traits and obsessive-compulsive disorder (OCD). MethodsWe conducted a genome-wide association analysis of OC traits using the Toronto Obsessive-Compulsive Scale (TOCS) in 5018 unrelated Caucasian children and adolescents from the community (Spit for Science sample). We tested the hypothesis that genetic variants associated with OC traits from the community would be associated with clinical OCD using a meta-analysis of three OCD case-controls samples (cases=3384, controls=8363). Shared genetic risk was examined between OC traits and OCD in the respective samples using polygenic risk score and genetic correlation analyses. ResultsA locus tagged by rs7856850 in an intron of PTPRD (protein tyrosine phosphatase {delta}) was significantly associated with OC traits at the genome-wide significance level (p=2.48x10-8). The rs7856850 locus was also associated with OCD in a meta-analysis of three independent OCD case/control genome-wide datasets (p=0.0069). Polygenic risk scores derived from OC traits were significantly associated with OCD in a sample of childhood-onset OCD and vice versa (ps<0.01). OC traits were highly but not significantly genetically correlated with OCD (rg=0.83, p=0.07). ConclusionsWe report the first validated genome-wide significant variant for OC traits. OC traits measured in the community sample shared genetic risk with OCD case/control status. Our results demonstrate the importance of the type of measure used to measure traits as well as the feasibility and power of using trait-based approaches in community samples for genetic discovery.

genomics↗

bioRxiv2019

The Role of Gene Encoding Variation of DRD4 in the Relationship between Inattention and Seasonal Daylight

Daylight is the strongest synchronizer of human circadian rhythms. The circadian pathway hypothesis posits that synchrony between daylight and the circadian system relates to (in)attention. The dopamine neurotransmitter system is implicated in regulating the circadian system as well as in (attention)-deficit hyperactivity disorder [ADHD]. We studied the role of functional genetic variation in the gene encoding of dopamine-receptor-D4 (DRD4) in the relationship between inattention and seasonal daylight (changes). Gene-by-environment (GxE) mega-analyses were performed across eight studies including 3757 adult participants (with and without ADHD). We tested 1) the Spring-focus hypothesis, in which attention in 7R-carriers normalizes with increasing daylight levels preceding measurement, 2) the Summer-born ADHD hypothesis, in which 7R-carriers report more inattention when born in spring/summer than in autumn/winter, 3) the Winter-born ADHD hypothesis, opposing the second hypothesis. The Spring-focus hypothesis was upheld (1386 ADHD, 760 controls; d=-0.16 between periods); 7R-carriers reported even less inattention than 7R-non-carriers after winter solstice (d=0.27 between genotype-groups). Results were diagnosis-independent. Sensitivity analyses at individual study level confirmed the circannual patterns for 7R-carriers. Incorporating geographic changes into the independent measure, we also calculated changes in sunlight levels. This approach likewise showed that inattention correlated negatively with increasing light levels in 7R-carriers (r=-.135). Results emphasize peripheral effects of dopamine and the effects of (seasonal) daylight changes on cognition.

genetics↗

bioRxiv2019

Genetic underpinnings of sociability in the UK Biobank

Difficulties with sociability include a tendency to avoid social contacts and activities, and to prefer being alone rather than being with others. While sociability is a continuously distributed trait in the population, decreased sociability represent a common early manifestation of multiple neuropsychiatric disorders such as Schizophrenia (SCZ), Bipolar Disorder (BP), Major Depressive Disorder (MDD), Autism Spectrum Disorders (ASDs), and Alzheimers disease (AD). We aimed to investigate the genetic underpinnings of sociability as a continuous trait in the general population. In this respect, we performed a genome-wide association study (GWAS) using a sociability score based on 4 social functioning-related self-report questions in the UK Biobank sample (n=342,461) to test the effect of individual genetic variants. This was followed by LD score analyses to investigate the genetic correlation with psychiatric disorders (SCZ, BP, MDD, ASDs) and a neurological disorder (AD) as well as related phenotypes (Loneliness and Social Anxiety). The phenotypic data indeed showed that the sociability score was decreased in individuals with ASD, (probable) MDD, BP and SCZ, but not in individuals with AD. Our GWAS showed 604 genome-wide significant SNPs, coming from 18 independent loci (SNP-based h2=0.06). Genetic correlation analyses showed significant correlations with SCZ (rg=0.15, p=9.8e-23), MDD (rg=0.68, p=6.6e-248) and ASDs (rg=0.27, p=4.5e-28), but no correlation with BP (rg=0.01, p=0.45) or AD (rg=0.04, p=0.55). Our sociability trait was also genetically correlated with Loneliness (rg=0.45, p=2.4e-8) and Social Anxiety (rg=0.48, p=0.002). Our study shows that there is a significant genetic component to variation in population levels of sociability, which is relevant to some psychiatric disorders (SCZ, MDD, ASDs), but not to BP and AD.

genetics↗

bioRxiv2019

Discovering the shared biology of cognitive traits determined by genetic overlap

Investigating the contribution of biology to human cognition has assumed a bottom-up causal cascade where genes influence brain systems that activate, communicate, and ultimately drive behavior. Yet few studies have directly tested whether cognitive traits with overlapping genetic underpinnings also rely on overlapping brain systems. Here, we report a step-wise exploratory analysis of genetic and functional imaging overlaps among cognitive traits. We used twin-based genetic analyses in the human connectome project (HCP) dataset (N=486), in which we quantified the heritability of measures of cognitive functions, and tested whether they were driven by common genetic factors using pairwise genetic correlations. Subsequently, we derived activation maps associated with cognitive tasks via functional imaging meta-analysis in BrainMap (N=4484), and tested whether cognitive traits that shared genetic variation also exhibited overlapping brain activation. Our genetic analysis determined that six cognitive measures (card sorting, no-go continuous performance, fluid intelligence, processing speed, reading decoding and vocabulary comprehension) were heritable (0.3<h2<0.5), and genetically correlated with at least one other heritable cognitive measure (0.2<{rho}g<0.35). The meta-analysis showed that two genetically-correlated traits, card sorting and fluid intelligence ({rho}g=0.24), also had a significant brain activation overlap ({rho}perm=0.29). These findings indicate that fluid intelligence and executive functioning rely on overlapping biological features, both at the neural systems level and at the molecular level. The cross-disciplinary approach we introduce provides a concrete framework for data-driven quantification of biological convergence between genetics, brain function, and behavior in health and disease.

neuroscience↗

bioRxiv2019

The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area

Structural brain changes along the lineage that led to modern Homo sapiens have contributed to our unique cognitive and social abilities. However, the evolutionarily relevant molecular variants impacting key aspects of neuroanatomy are largely unknown. Here, we integrate evolutionary annotations of the genome at diverse timescales with common variant associations from large-scale neuroimaging genetic screens in living humans, to reveal how selective pressures have shaped neocortical surface area. We show that variation within human gained enhancers active in the developing brain is associated with global surface area as well as that of specific regions. Moreover, we find evidence of recent polygenic selection over the past 2,000 years influencing surface area of multiple cortical regions, including those involved in spoken language and visual processing.

neuroscience↗

bioRxiv2019

Genetic overlap between obsessive-compulsive disorder, related symptoms in the population and insulin signaling: etiological implications

ObjectiveObsessive-compulsive symptoms (OCS) in the population have been linked to obsessive-compulsive disorder (OCD) in genetic and epidemiological studies. Insulin signaling has been implicated in OCD. We extend previous work by assessing genetic overlap between OCD, population-based OCS, and central nervous system (CNS) and peripheral insulin signaling.\n\nMethodsWe conducted genome-wide association studies (GWASs) in the population-based Philadelphia Neurodevelopmental Cohort (PNC, 650 children and adolescents) of the total OCS score and six OCS factors from an exploratory factor analysis of 22 questions. Subsequently, we performed polygenic risk score (PRS) analysis to assess shared genetic etiologies between clinical OCD (using GWAS data from the Psychiatric Genomics Consortium), the total OCS score and OCS factors. We then performed gene-set analyses with a set of OCD-linked genes centered around CNS insulin-regulated synaptic function and PRS analyses for five peripheral insulin signaling-related traits. For validation purposes, we explored data from the independent Spit for Science population cohort (5047 children and adolescents).\n\nResultsIn the PNC, we found a shared genetic etiology between OCD and impairment, contamination/cleaning and guilty taboo thoughts. In the Spit for Science cohort, we were able to validate the finding for contamination/cleaning, and additionally observed genetic sharing between OCD and symmetry/counting/ordering. The CNS insulin-linked gene-set associated with symmetry/counting/ordering. We also identified genetic sharing between peripheral insulin signaling-related traits (type 2 diabetes and the blood levels of HbA1C, fasting insulin and 2 hour glucose) and OCD as well as certain OCS.\n\nConclusionsOCD, OCS in the population and insulin-related traits share genetic risk factors, indicating a common etiological mechanism underlying somatic and psychiatric disorders.

genetics↗

bioRxiv2018

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet we know little about the specific genetic loci influencing human cortical structure. To identify genetic variants, including structural variants, impacting cortical structure, we conducted a genome-wide association meta-analysis of brain MRI data from 51,662 individuals. We analysed the surface area and average thickness of the whole cortex and 34 regions with known functional specialisations. We identified 255 nominally significant loci (P [≤] 5 x 10-8); 199 survived multiple testing correction (P [≤] 8.3 x 10-10; 187 surface area; 12 thickness). We found significant enrichment for loci influencing total surface area within regulatory elements active during prenatal cortical development, supporting the radial unit hypothesis. Loci impacting regional surface area cluster near genes in Wnt signalling pathways, known to influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinsons disease, insomnia, depression and ADHD.\n\nOne Sentence SummaryCommon genetic variation is associated with inter-individual variation in the structure of the human cortex, both globally and within specific regions, and is shared with genetic risk factors for some neuropsychiatric disorders.

genetics↗

bioRxiv2018

Brain scans from 21297 individuals reveal the genetic architecture of hippocampal subfield volumes

The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimers disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields genetic architecture. T1-weighted brain scans (n=21297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, covarying for total hippocampal volume. We further calculated the single nucleotide polymorphism (SNP)-based heritability of twelve subfields, as well as their genetic correlation with each other, with other structural brain features, and with AD and schizophrenia. All outcome measures were corrected for age, sex, and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from .14 to .27, all p< 1x10-16) and clustered together based on their genetic correlations compared to other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.

genetics↗

bioRxiv2017

Mapping Cortical Brain Asymmetry in 17,141 Healthy Individuals Worldwide via the ENIGMA Consortium

Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here the ENIGMA consortium presents the largest ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and brain size (indexed by intracranial volume). Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (N = 1,443 and 1,113, respectively), we found several asymmetries showing modest but highly reliable heritability. The structural asymmetries identified, and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.\n\nSignificance StatementLeft-right asymmetry is a key feature of the human brain's structure and function. It remains unclear which cortical regions are asymmetrical on average in the population, and how biological factors such as age, sex and genetic variation affect these asymmetries. Here we describe by far the largest ever study of cerebral cortical brain asymmetry, based on data from 17,141 participants. We found a global anterior-posterior 'torque' pattern in cortical thickness, together with various regional asymmetries at the population level, which have not been previously described, as well as effects of age, sex, and heritability estimates. From these data, we have created an on-line resource that will serve future studies of human brain anatomy in health and disease.

neuroscience↗

bioRxiv2017

Genetic markers of ADHD-related variations in intracranial volume

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common and highly heritable neurodevelopmental disorder with a complex pathophysiology, where genetic risk is hypothesized to be mediated by alterations in structure and function of diverse brain networks. We tested one aspect of this hypothesis by investigating the genetic overlap between ADHD (n=55,374) and (mainly subcortical) brain volumes (n=11,221-24,704), using the largest publicly available studies. At the level of common variant genetic architecture, we discovered a significant negative genetic correlation between ADHD and intracranial volume (ICV). Meta-analysis of individual variants found significant loci associated with both ADHD risk and ICV; additional loci were identified for ADHD and amygdala, caudate nucleus, and putamen volumes. Gene-set analysis in the ADHD-ICV meta-analytic data showed significant association with variation in neurite outgrowth-related genes. In summary, our results suggest new hypotheses about biological mechanisms involved in ADHD etiology and highlight the need to study additional brain parameters.

genetics↗

bioRxiv2017

Do Candidate Genes Affect the Brain’s White Matter Microstructure? Large-Scale Evaluation of 6,165 Diffusion MRI Scans

AbstractSusceptibility genes for psychiatric and neurological disorders - including APOE, BDNF, CLU,CNTNAP2, COMT, DISC1, DTNBP1, ErbB4, HFE, NRG1, NTKR3, and ZNF804A - have been reported to affect white matter (WM) microstructure in the healthy human brain, as assessed through diffusion tensor imaging (DTI). However, effects of single nucleotide polymorphisms (SNPs) in these genes explain only a small fraction of the overall variance and are challenging to detect reliably in single cohort studies. To date, few studies have evaluated the reproducibility of these results. As part of the ENIGMA-DTI consortium, we pooled regional fractional anisotropy (FA) measures for 6,165 subjects (CEU ancestry N=4,458) from 11 cohorts worldwide to evaluate effects of 15 candidate SNPs by examining their associations with WM microstructure. Additive association tests were conducted for each SNP. We used several meta-analytic and mega-analytic designs, and we evaluated regions of interest at multiple granularity levels. The ENIGMA-DTI protocol was able to detect single-cohort findings as originally reported. Even so, in this very large sample, no significant associations remained after multiple-testing correction for the 15 SNPs investigated. Suggestive associations (1.3x10-4 < p < 0.05, uncorrected) were found for BDNF, COMT, and ZNF804A in specific tracts. Meta-and mega-analyses revealed similar findings. Regardless of the approach, the previously reported candidate SNPs did not show significant associations with WM microstructure in this largest genetic study of DTI to date; the negative findings are likely not due to insufficient power. Genome-wide studies, involving large-scale meta-analyses, may help to discover SNPs robustly influencing WM microstructure.

neuroscience↗