scholarly journals Localizing genomic regions contributing to the extremes of externalizing behavior: ADHD, aggressive and antisocial behaviors

2019 ◽  
Author(s):  
Mariana L. Rodríguez-López ◽  
Hilleke Hulshoff Pol ◽  
Barbara Franke ◽  
Marieke Klein
Keyword(s):  
Externalizing Behavior ◽  
Meta Analysis ◽  
Neurodevelopmental Disorder ◽  
Expression Patterns ◽  
Genetic Correlations ◽  
Brain Regions ◽  
Genetic Loci ◽  
Association Analyses ◽  
Meta Analyses ◽  
Genomic Regions

AbstractAttention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, which in some cases occurs comorbid with aggressive and antisocial behavior (AGG; ASB). The three externalizing behaviors are moderately to highly heritable and are genetically correlated. However, the genomic regions underlying this correlation are unknown. In this study, we aimed to localize genetic loci shared between ADHD, AGG, and ASB, using two complementary approaches.GWAS summary statistics for ADHD, AGG, and ASB were used for (1) cross-trait gene-based meta-analysis association analyses and (2) local genetic correlation analyses to identify shared genetic loci. Results of both complementary methods were combined to retrieve overlapping genes. Biological functionality of prioritized genes was assessed by exploring gene expression patterns in brain tissues and testing for gene-based association with (subcortical) brain regions.We confirmed previous findings that ADHD, AGG, and ASB were positively genetically correlated at a global level. We identified eleven significant genes in cross-trait gene-based meta-analyses, 31 loci shared between traits; 34 genes were identified when both approaches were combined.This study emphasizes the complex genetic architecture underlying global genetic correlations at the locus level. Converging evidence from these cross-trait analyses highlights novel candidate genes underlying biological mechanisms shared by ADHD, AGG, and ASB.

The Student Risk Screening Scale: A Reliability and Validity Generalization Meta-Analysis

2017 ◽  
Vol 26 (3) ◽  
pp. 143-155 ◽  
Author(s):  
Stephen P. Kilgus ◽  
Katie Eklund ◽  
Daniel M. Maggin ◽  
Crystal N. Taylor ◽  
Amanda N. Allen
Keyword(s):  
Internal Consistency ◽  
Externalizing Behavior ◽  
Meta Analysis ◽  
Reliability And Validity ◽  
Future Research ◽  
Risk Screening ◽  
Validity Generalization ◽  
Meta Analyses ◽  
Student Risk ◽  
Screening Scale

The purpose of this study was to conduct reliability and validity generalization meta-analyses of evidence regarding the Student Risk Screening Scale (SRSS), a universal screener for externalizing behavior problems. A systematic review of the literature resulted in the identification of 17 studies inclusive of evidence regarding SRSS score (a) internal consistency reliability (i.e., alpha coefficients), and/or (b) criterion-related validity (e.g., correlations between the SRSS and various outcomes). Multilevel meta-analyses indicated that across studies, SRSS scores were associated with adequate internal consistency (α = .83). Analyses further suggested the SRSS was a valid indicator of both social and behavioral outcomes ( r = .52) and academic outcomes ( r = .42). Follow-up analyses suggested that in accordance with theory-driven expectations, the SRSS was a stronger indicator of externalizing problems and broad behavior outcomes relative to alternative outcomes (e.g., internalizing problems). Limitations and directions for future research are discussed, including recommendations for the collection of additional SRSS diagnostic accuracy evidence.

scholarly journals GWAS of Depression Phenotypes in the Million Veteran Program and Meta-analysis in More than 1.2 Million Participants Yields 178 Independent Risk Loci

2020 ◽  
Author(s):  
Daniel F Levey ◽  
Murray B Stein ◽  
Frank R Wendt ◽  
Gita A Pathak ◽  
Hang Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Meta Analysis ◽  
African Ancestry ◽  
Genetic Correlations ◽  
Brain Regions ◽  
Self Report ◽  
European Ancestry ◽  
Causal Variants ◽  
Using Data ◽  
Genomic Risk

We report a large meta-analysis of depression using data from the Million Veteran Program (MVP), 23andMe Inc., UK Biobank, and FinnGen; including individuals of European ancestry (n=1,154,267; 340,591 cases) and African ancestry (n=59,600; 25,843 cases). We identified 223 and 233 independent SNPs associated with depression in European ancestry and transancestral analysis, respectively. Genetic correlations within the MVP cohort across electronic health records diagnosis, survey self-report of diagnosis, and a 2-item depression screen exceeded 0.81. Using transcriptome-wide association study (TWAS) we found significant associations for gene expression in several brain regions, including hypothalamus (NEGR1, p=3.19x10-25) and nucleus accumbens (DRD2, p=1.87x10-20). 178 genomic risk loci were fine-mapped to find likely causal variants. We identified likely pathogenicity in these variants and overlapping gene expression for 17 genes from our TWAS, including TRAF3. This study sheds light on the genetic architecture of depression and provides new insight into the interrelatedness of complex psychiatric traits.

scholarly journals A Meta-analysis of Functional Neuroimaging Studies of Self- and Other Judgments Reveals a Spatial Gradient for Mentalizing in Medial Prefrontal Cortex

2012 ◽  
Vol 24 (8) ◽  
pp. 1742-1752 ◽  
Author(s):  
Bryan T. Denny ◽  
Hedy Kober ◽  
Tor D. Wager ◽  
Kevin N. Ochsner
Keyword(s):  
Functional Organization ◽  
Functional Neuroimaging ◽  
Meta Analysis ◽  
Brain Regions ◽  
The Self ◽  
Spatial Gradient ◽  
Self And Other ◽  
Neuroimaging Data ◽  
Medial Pfc ◽  
Meta Analyses

The distinction between processes used to perceive and understand the self and others has received considerable attention in psychology and neuroscience. Brain findings highlight a role for various regions, in particular the medial PFC (mPFC), in supporting judgments about both the self and others. We performed a meta-analysis of 107 neuroimaging studies of self- and other-related judgments using multilevel kernel density analysis [Kober, H., & Wager, T. D. Meta-analyses of neuroimaging data. Wiley Interdisciplinary Reviews, 1, 293–300, 2010]. We sought to determine what brain regions are reliably involved in each judgment type and, in particular, what the spatial and functional organization of mPFC is with respect to them. Relative to nonmentalizing judgments, both self- and other judgments were associated with activity in mPFC, ranging from ventral to dorsal extents, as well as common activation of the left TPJ and posterior cingulate. A direct comparison between self- and other judgments revealed that ventral mPFC as well as left ventrolateral PFC and left insula were more frequently activated by self-related judgments, whereas dorsal mPFC, in addition to bilateral TPJ and cuneus, was more frequently activated by other-related judgments. Logistic regression analyses revealed that ventral and dorsal mPFC lay at opposite ends of a functional gradient: The z coordinates reported in individual studies predicted whether the study involved self- or other-related judgments, which were associated with increasingly ventral or dorsal portions of mPFC, respectively. These results argue for a distributed rather than localizationist account of mPFC organization and support an emerging view on the functional heterogeneity of mPFC.

scholarly journals Gene-based analysis of ADHD using PASCAL: a biological insight into the novel associated genes

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Aitana Alonso-Gonzalez ◽  
Manuel Calaza ◽  
Cristina Rodriguez-Fontenla ◽  
Angel Carracedo
Keyword(s):  
Gene Network ◽  
Association Studies ◽  
Meta Analysis ◽  
Neurodevelopmental Disorder ◽  
Differentially Expressed Gene ◽  
Brain Regions ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Biological Insight ◽  
Insight Into

Abstract Background Attention-Deficit Hyperactivity Disorder (ADHD) is a complex neurodevelopmental disorder (NDD) which may significantly impact on the affected individual’s life. ADHD is acknowledged to have a high heritability component (70–80%). Recently, a meta-analysis of GWAS (Genome Wide Association Studies) has demonstrated the association of several independent loci. Our main aim here, is to apply PASCAL (pathway scoring algorithm), a new gene-based analysis (GBA) method, to the summary statistics obtained in this meta-analysis. PASCAL will take into account the linkage disequilibrium (LD) across genomic regions in a different way than the most commonly employed GBA methods (MAGMA or VEGAS (Versatile Gene-based Association Study)). In addition to PASCAL analysis a gene network and an enrichment analysis for KEGG and GO terms were carried out. Moreover, GENE2FUNC tool was employed to create gene expression heatmaps and to carry out a (DEG) (Differentially Expressed Gene) analysis using GTEX v7 and BrainSpan data. Results PASCAL results have revealed the association of new loci with ADHD and it has also highlighted other genes previously reported by MAGMA analysis. PASCAL was able to discover new associations at a gene level for ADHD: FEZF1 (p-value: 2.2 × 10− 7) and FEZF1-AS1 (p-value: 4.58 × 10− 7). In addition, PASCAL has been able to highlight association of other genes that share the same LD block with some previously reported ADHD susceptibility genes. Gene network analysis has revealed several interactors with the associated ADHD genes and different GO and KEGG terms have been associated. In addition, GENE2FUNC has demonstrated the existence of several up and down regulated expression clusters when the associated genes and their interactors were considered. Conclusions PASCAL has been revealed as an efficient tool to extract additional information from previous GWAS using their summary statistics. This study has identified novel ADHD associated genes that were not previously reported when other GBA methods were employed. Moreover, a biological insight into the biological function of the ADHD associated genes across brain regions and neurodevelopmental stages is provided.

scholarly journals Meta-Analysis: MRI Volumetric Data of Children with ADHD Subtypes

2020 ◽  
Author(s):  
Amanda Hysell
Keyword(s):  
Brain Structure ◽  
Brain Volume ◽  
Meta Analysis ◽  
Neurodevelopmental Disorder ◽  
Brain Regions ◽  
Volume Reduction ◽  
Volumetric Data ◽  
Adhd Subtypes ◽  
Magnetic Resonance Imaging Mri ◽  
Inattentive Type

Attention-deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder consisting of inattentive and/or hyperactive behaviors that is typically prevalent in childhood. There are three recognized subtypes of this disorder—hyperactive, inattentive, and combined. The current study’s purpose is to examine how the subtypes differentiate based on brain structure volume size. There have been studies on ADHD subtypes and brain structure volumes in children, but there are a number of limitations in available research that make it difficult to generalize findings. A meta-analysis was done using 8 studies that included volumetric data of ADHD subtypes (inattentive and combined) in children that was acquired through magnetic resonance imaging (MRI) techniques. Analyses were done looking at combined and inattentive type in comparison to controls and between the two groups. Further subgroup analyses were done on gender and brain regions in the two subtypes. Results show that there is a significant brain volume reduction in combined type in comparison to controls and inattentive type. There is also a significant volume reduction observed in males. The other analyses done yielded insignificant findings, although the volume reduction in inattentive type was only slightly above the cutoff of alpha (0.05). These findings help in better understanding the relations between brain volume and ADHD subtypes, but further research is still needed in this area.

scholarly journals Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities

Stroke ◽  
2020 ◽  
Vol 51 (7) ◽  
pp. 2111-2121 ◽  
Author(s):  
Nicola J. Armstrong ◽  
Karen A. Mather ◽  
Muralidharan Sargurupremraj ◽  
Maria J. Knol ◽  
Rainer Malik ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Imaging Genetics ◽  
Genome Wide Association ◽  
Association Analyses ◽  
New Genes ◽  
Genome Wide

Background and Purpose: Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. Methods: Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. Results: In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 ( NBEAL ), 10q23.1 ( TSPAN14/FAM231A ), and 10q24.33 ( SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 ( NOS3 ) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. Conclusions: Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.

scholarly journals An fMRI Study Using a Combined Task of Interval Discrimination and Oddball Could Reveal Common Brain Circuits of Cognitive Change

2021 ◽  
Vol 12 ◽  
Author(s):  
María Sol Garcés ◽  
Irene Alústiza ◽  
Anton Albajes-Eizagirre ◽  
Javier Goena ◽  
Patricio Molero ◽  
...  
Keyword(s):  
Cognitive Processes ◽  
Healthy Subjects ◽  
Functional Neuroimaging ◽  
Meta Analysis ◽  
Brain Structures ◽  
Cognitive Change ◽  
Brain Regions ◽  
Task Type ◽  
Meta Analyses ◽  
The Brain

Recent functional neuroimaging studies suggest that the brain networks responsible for time processing are involved during other cognitive processes, leading to a hypothesis that time-related processing is needed to perform a range of tasks across various cognitive functions. To examine this hypothesis, we analyze whether, in healthy subjects, the brain structures activated or deactivated during performance of timing and oddball-detection type tasks coincide. To this end, we conducted two independent signed differential mapping (SDM) meta-analyses of functional magnetic resonance imaging (fMRI) studies assessing the cerebral generators of the responses elicited by tasks based on timing and oddball-detection paradigms. Finally, we undertook a multimodal meta-analysis to detect brain regions common to the findings of the two previous meta-analyses. We found that healthy subjects showed significant activation in cortical areas related to timing and salience networks. The patterns of activation and deactivation corresponding to each task type partially coincided. We hypothesize that there exists a time and change-detection network that serves as a common underlying resource used in a broad range of cognitive processes.

scholarly journals Genetic Architecture of 11 Major Psychiatric Disorders at Biobehavioral, Functional Genomic, and Molecular Genetic Levels of Analysis

2020 ◽  
Author(s):  
Andrew D. Grotzinger ◽  
Travis T. Mallard ◽  
Wonuola A. Akingbuwa ◽  
Hill F. Ip ◽  
Mark J. Adams ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Structural Equation ◽  
Genetic Architecture ◽  
Molecular Genetic ◽  
Genetic Correlations ◽  
Levels Of Analysis ◽  
Functional Genomic ◽  
Association Analyses ◽  
Psychotic Features ◽  
Genomic Regions

We systematically interrogate the joint genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic, and molecular genetic levels of analysis. We identify four broad factors (Neurodevelopmental, Compulsive, Psychotic, and Internalizing) that underlie genetic correlations among the disorders, and test whether these factors adequately explain their genetic correlations with biobehavioral traits. We introduce Stratified Genomic Structural Equation Modelling, which we use to identify gene sets and genomic regions that disproportionately contribute to pleiotropy, including protein-truncating variant intolerant genes expressed in excitatory and GABAergic brain cells that are enriched for pleiotropy between disorders with psychotic features. Multivariate association analyses detect a total of 152 (20 novel) independent loci which act on the four factors, and identify nine loci that act heterogeneously across disorders within a factor. Despite moderate to high genetic correlations across all 11 disorders, we find very little utility of, or evidence for, a single dimension of genetic risk across psychiatric disorders.

scholarly journals HASE: Framework for efficient high-dimensional association analyses

2016 ◽  
Author(s):  
G.V. Roshchupkin ◽  
H.H.H. Adams ◽  
M.W. Vernooij ◽  
A. Hofman ◽  
C.M. Van Duijn ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
High Dimensional ◽  
Total N ◽  
Association Analyses ◽  
Large Scale Data ◽  
Individual Participant ◽  
Intermediate Results ◽  
Meta Analyses

ABSTRACTLarge-scale data collection and processing have facilitated scientific discoveries in fields such as genomics and imaging, but cross-investigations between multiple big datasets remain impractical. Computational requirements of high-dimensional association studies are often too demanding for individual sites. Additionally, the sheer size of intermediate results is unfit for collaborative settings where summary statistics are exchanged for meta-analyses. Here we introduce the HASE framework to perform high-dimensional association studies with dramatic reduction in both computational burden and storage requirements of intermediate results. We implemented a novel meta-analytical method that yields identical power as pooled analyses without the need of sharing individual participant data. The efficiency of the framework is illustrated by associating 9 million genetic variants with 1.5 million brain imaging voxels in three cohorts (total N=4,034) followed by meta-analysis, on a standard computational infrastructure. These experiments indicate that HASE facilitates high-dimensional association studies enabling large multicenter association studies for future discoveries.

scholarly journals The genetic basis of natural antibody titers of young healthy pigs and relationships with disease resilience

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Yulu Chen ◽  
◽  
Laura E. Tibbs Cortes ◽  
Carolyn Ashley ◽  
Austin M. Putz ◽  
...  
Keyword(s):  
Genetic Correlations ◽  
Parenteral Antibiotic ◽  
Association Analyses ◽  
Breeding Populations ◽  
Young Pigs ◽  
Genome Wide ◽  
Antibody Titers ◽  
Polymicrobial Disease ◽  
Genomic Regions ◽  
Indicator Traits

Abstract Background Disease resilience is the ability to maintain performance under pathogen exposure but is difficult to select for because breeding populations are raised under high health. Selection for resilience requires a trait that is heritable, easy to measure on healthy animals, and genetically correlated with resilience. Natural antibodies (NAb) are important parts of the innate immune system and are found to be heritable and associated with disease susceptibility in dairy cattle and poultry. Our objective was to investigate NAb and total IgG in blood of healthy, young pigs as potential indicator traits for disease resilience. Results Data were from Yorkshire x Landrace pigs, with IgG and IgM NAb (four antigens) and total IgG measured by ELISA in blood plasma collected ~ 1 week after weaning, prior to their exposure to a natural polymicrobial challenge. Heritability estimates were lower for IgG NAb (0.12 to 0.24, + 0.05) and for total IgG (0.19 + 0.05) than for IgM NAb (0.33 to 0.53, + 0.07) but maternal effects were larger for IgG NAb (0.41 to 0.52, + 0.03) and for total IgG (0.19 + 0.05) than for IgM NAb (0.00 to 0.10, + 0.04). Phenotypically, IgM NAb titers were moderately correlated with each other (average 0.60), as were IgG NAb titers (average 0.42), but correlations between IgM and IgG NAb titers were weak (average 0.09). Phenotypic correlations of total IgG were moderate with NAb IgG (average 0.46) but weak with NAb IgM (average 0.01). Estimates of genetic correlations among NAb showed similar patterns but with small SE, with estimates averaging 0.76 among IgG NAb, 0.63 among IgM NAb, 0.17 between IgG and IgM NAb, 0.64 between total IgG and IgG NAb, and 0.13 between total IgG and IgM NAb. Phenotypically, pigs that survived had slightly higher levels of NAb and total IgG than pigs that died. Genetically, higher levels of NAb tended to be associated with greater disease resilience based on lower mortality and fewer parenteral antibiotic treatments. Genome-wide association analyses for NAb titers identified several genomic regions, with several candidate genes for immune response. Conclusions Levels of NAb in blood of healthy young piglets are heritable and potential genetic indicators of resilience to polymicrobial disease.

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