Biology subjects

Peyre, H.

Publications and source records attributed to Peyre, H..

4 recordsLinked to original sources

bioRxiv2022

Brain Volumes, Thicknesses, and Surface Areas as Mediators of Genetic Factors and Childhood Adversity on Intelligence

Although genetic and environmental factors influence general intelligence (g-factor), few studies examined the neuroanatomical measures mediating environmental and genetic effects on intelligence. Therefore, we investigate the brain volumes, cortical mean thicknesses, and cortical surface areas mediating the effects of the g-factor polygenic score (gPGS) and childhood adversity on the g-factor in the UK Biobank. We first identified the global and regional brain measures for the mediation models that contribute to the g-factor independently of global brain size and regional associations. Most regions contributed to the g-factor through global brain size. Parieto-Frontal Integration Theory (P-FIT) regions were not more associated with the g-factor than non-PFIT regions. Adjusting for global brain size and regional associations, only a few regions, such as the right olfactory sulcus and the right mediodorsal thalamic nuclei volumes, the right orbital inferior frontal gyrus surface area, and the anterior cingulate gyrus mean thicknesses, predicted intelligence and were included in the mediation analyses. We conducted mediation analyses on global measures, regional volumes, mean thicknesses, and surface areas, separately. Total brain volume mediated 7.04% of the gPGS effect on the g-factor and 2.50% of childhood adversitys effect on the g-factor. In comparison, the fraction of the gPGS and childhood adversitys effects mediated by individual regional volumes, surfaces, and mean thicknesses was 10-15 times smaller. Our findings suggest that genetic and environmental effects on general intelligence must be mediated to a larger extent by other structural brain properties. Significance StatementGenes and environmental factors, such as childhood adversity, influence our cognitive abilities via the brain. Our results show that genetic and environmental effects on intelligence are mediated to some extent by neuroanatomical properties. However, we find that global brain measures (e.g., total brain volume) are the largest mediators and that regional volumes, surfaces, and mean thicknesses only mediated a fraction of a persons genetic predisposition to intelligence and childhood adversitys effect on intelligence. This suggests that genetic and environmental effects on general intelligence are to a large extent mediated by other kinds of brain structural properties.

neuroscience↗

bioRxiv2021

Comparing Brain Asymmetries Independently of Brain Size

Studies examining cerebral asymmetries typically divide the L-R Measure (e.g., Left- Right Volume) by the L+R Measure to obtain an Asymmetry Index (AI). However, contrary to widespread belief, such a division fails to render the AI independent from the L+R Measure and/or from total brain size. As a result, variations in brain size may bias correlation estimates with the AI or group differences in AI. We investigated how to analyze brain asymmetries in to distinguish global from regional effects, and report unbiased group differences in cerebral asymmetries. We analyzed the extent to which the L+R Measure, Total Cerebral Measure (TCM, e.g., Total Brain Volume), and L-R TCM predict regional asymmetries. As a case study, we assessed the consequences of omitting each of these predictors on the magnitude and significance of sex differences in asymmetries. We found that the L+R Measure, the TCM, and the L-R TCM predicted the AI of more than 89% of regions and that their relationships were generally linear. Removing any of these predictors changed the significance of sex differences in 33% of regions and the magnitude of sex differences across 13-42% of regions. Although we generally report similar sex and age effects on cerebral asymmetries to those of previous large-scale studies, properly adjusting for regional and global brain size revealed additional sex and age effects on brain asymmetry. Highlights- The typical Asymmetry Index (AI) scales with the size of a region and brain size. - Omitting the Left+Right Measure influences reported sex differences in asymmetries. - Omitting brain size or asymmetry influences reported sex differences in asymmetries. - We report sex and age effects on AIs independent of regional and global brain size.

neuroscience↗

bioRxiv2020

Neuroanatomical Norms in the UK Biobank: The Impact of Allometric Scaling, Sex, and Age.

Few neuroimaging studies are sufficiently large to adequately describe population-wide variations. This studys primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40 028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry - the non-linear scaling relationship between a region and brain size (e.g., Total Brain Volume) across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |{beta}|= 0.13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. This large scale-study advances our understanding of age, sex, and brain allometrys impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/422684v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@405c3borg.highwire.dtl.DTLVardef@1673e3corg.highwire.dtl.DTLVardef@126fee4org.highwire.dtl.DTLVardef@128545b_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIWe created neuroanatomical norms and individual markers for the UK Biobank (N=40 028) C_LIO_LIAllometry was common across 83% of brain volumes, thicknesses, and surface areas C_LIO_LI67% of regions differed between sexes: 37% were larger in males and 30% in females C_LIO_LIOmitting brain allometry influenced reported sex differences in variance C_LIO_LI49% of regions declined with age, with variations across regions and sexes C_LI

neuroscience↗

bioRxiv2020

Combining multivariate genomic approaches to elucidate the comorbidity between ASD and ADHD

BackgroundSeveral lines of evidence point toward the presence of shared genetic factors underlying Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). However, Genome-Wide Association Studies (GWAS) have yet to identify risk variants (i.e. Single-Nucleotide Polymorphisms, SNPs) shared by ADHD and ASD. MethodsTwo complementary multivariate analyses - genomic structural equation modelling (SEM) and colocalization analysis - were exploited to identify the shared SNPs for ASD and ADHD, using summary data from two independent GWAS of ASD (N=46,350) and ADHD individuals (N=55,374). ResultsGenomic SEM identified 7 novel SNPs shared between ASD and ADHD (pgenome-wide<5e-8), including three SNPs that were not identified in any of the original univariate GWAS of ASD and ADHD (rs227378, rs2391769 and rs325506). We also mapped 4 novel genes (MANBA, DPYD, INSM1, and PAX1) to SNPs shared by ASD and ADHD, as well as 4 genes that had already been mapped to SNPs identified in either ASD or ADHD GWAS (SORCS3, XRN2, PTBP2 and NKX2-4). All the shared genes between ADHD and ASD were more prominently expressed in the brain than the genes mapped to SNPs specific to ASD or ADHD. Colocalization analyses revealed that 44% percent of the SNPs associated with ASD (p<1e-6) colocalized with ADHD SNPs and 26% of the SNPs associated with ADHD (p<1e-6) colocalized with ASD SNPs. ConclusionsUsing multivariate genomic analyses, the present study reveals the shared genetic pathways that underlie ASD and ADHD. Further investigation of these pathways may help identify new targets for treatment of these disorders.

genetics↗