Genetic Influences on Longitudinal Trajectories of Cortical Thickness and Surface Area during the First 2 Years of Life.
ABSTRACT: Genetic influences on cortical thickness (CT) and surface area (SA) are known to vary across the life span. Little is known about the extent to which genetic factors influence CT and SA in infancy and toddlerhood. We performed the first longitudinal assessment of genetic influences on variation in CT and SA in 501 twins who were aged 0-2 years. We observed substantial additive genetic influences on both average CT (0.48 in neonates, 0.37 in 1-year-olds, and 0.44 in 2-year-olds) and total SA (0.59 in neonates, 0.74 in 1-year-olds, and 0.73 in 2-year-olds). In addition, we found strong heritability of the change in average CT (0.49) from neonates to 1-year-olds, but not from 1- to 2-year-olds. Moreover, we found strong genetic correlations for average CT (rG = 0.92) between 1- and 2-year-olds and strong genetic correlations for total SA across all timepoints (rG = 0.96 between neonates and 1-year-olds, rG = 1 between 1- and 2-year-olds). In addition, we found CT and SA are strongly genetic correlated at birth, but weaken over time. Overall, results suggest a dynamic genetic relationship between CT and SA during first 2 years of life and provide novel insights into how genetic influences shape the cortical structure during early brain development.
Project description:Genetic and environmental influences on cortical thickness (CT) and surface area (SA) are thought to vary in a complex and dynamic way across the lifespan. It has been established that CT and SA are genetically distinct in older children, adolescents, and adults, and that heritability varies across cortical regions. Very little, however, is known about how genetic and environmental factors influence infant CT and SA. Using structural MRI, we performed the first assessment of genetic and environmental influences on normal variation of SA and CT in 360 twin neonates. We observed strong and significant additive genetic influences on total SA (a<sup>2</sup> = 0.78) and small and nonsignificant genetic influences on average CT (a<sup>2</sup> = 0.29). Moreover, we found significant genetic overlap (genetic correlation = 0.65) between these global cortical measures. Regionally, there were minimal genetic influences across the cortex for both CT and SA measures and no distinct patterns of genetic regionalization. Overall, outcomes from this study suggest a dynamic relationship between CT and SA during the neonatal period and provide novel insights into how genetic influences shape cortical structure during early development.
Project description:Cortical structure has been consistently related to cognitive abilities in children and adults, yet we know little about how the cortex develops to support emergent cognition in infancy and toddlerhood when cortical thickness (CT) and surface area (SA) are maturing rapidly. In this report, we assessed how regional and global measures of CT and SA in a sample (N?=?487) of healthy neonates, 1-year-olds, and 2-year-olds related to motor, language, visual reception, and general cognitive ability. We report novel findings that thicker cortices at ages 1 and 2 and larger SA at birth, age 1, and age 2 confer a cognitive advantage in infancy and toddlerhood. While several expected brain-cognition relationships were observed, overlapping cortical regions were also implicated across cognitive domains, suggesting that infancy marks a period of plasticity and refinement in cortical structure to support burgeoning motor, language, and cognitive abilities. CT may be a particularly important morphological indicator of ability, but its impact on cognition is relatively weak when compared with gestational age and maternal education. Findings suggest that prenatal and early postnatal cortical developments are important for cognition in infants and toddlers but should be considered in relation to other child and demographic factors.
Project description:Cortical thickness (CT) and surface area (SA) vary widely between individuals and are associated with intellectual ability and risk for various psychiatric and neurodevelopmental conditions. Factors influencing this variability remain poorly understood, but the radial unit hypothesis, as well as the more recent supragranular cortex expansion hypothesis, suggests that prenatal and perinatal influences may be particularly important. In this report, we examine the impact of 17 major demographic and obstetric history variables on interindividual variation in CT and SA in a unique sample of 805 neonates who received MRI scans of the brain around 2 weeks of age. Birth weight, postnatal age at MRI, gestational age at birth, and sex emerged as important predictors of SA. Postnatal age at MRI, paternal education, and maternal ethnicity emerged as important predictors of CT. These findings suggest that individual variation in infant CT and SA is explained by different sets of environmental factors with neonatal SA more strongly influenced by sex and obstetric history and CT more strongly influenced by socioeconomic and ethnic disparities. Findings raise the possibility that interventions aimed at reducing disparities and improving obstetric outcomes may alter prenatal/perinatal cortical development.
Project description:We examined network properties of genetic covariance between average cortical thickness (CT) and surface area (SA) within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniques-biometrical genetic modeling, cluster analysis, and graph theory-to examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function.
Project description:BACKGROUND:Prior research has documented shared heritable contributions to non-suicidal self-injury (NSSI) and suicidal ideation (SI) as well as NSSI and suicide attempt (SA). In addition, trauma exposure has been implicated in risk for NSSI and suicide. Genetically informative studies are needed to determine common sources of liability to all three self-injurious thoughts and behaviors, and to clarify the nature of their associations with traumatic experiences. METHODS:Multivariate biometric modeling was conducted using data from 9526 twins [59% female, mean age = 31.7 years (range 24-42)] from two cohorts of the Australian Twin Registry, some of whom also participated in the Childhood Trauma Study and the Nicotine Addiction Genetics Project. RESULTS:The prevalences of high-risk trauma exposure (HRT), NSSI, SI, and SA were 24.4, 5.6, 27.1, and 4.6%, respectively. All phenotypes were moderately to highly correlated. Genetic influences on self-injurious thoughts and behaviors and HRT were significant and highly correlated among men [rG = 0.59, 95% confidence interval (CI) (0.37-0.81)] and women [rG = 0.56 (0.49-0.63)]. Unique environmental influences were modestly correlated in women [rE = 0.23 (0.01-0.45)], suggesting that high-risk trauma may confer some direct risk for self-injurious thoughts and behaviors among females. CONCLUSIONS:Individuals engaging in NSSI are at increased risk for suicide, and common heritable factors contribute to these associations. Preventing trauma exposure may help to mitigate risk for self-harm and suicide, either directly or indirectly via reductions in liability to psychopathology more broadly. In addition, targeting pre-existing vulnerability factors could significantly reduce risk for life-threatening behaviors among those who have experienced trauma.
Project description:The mitochondrial DNA (mtDNA) D-loop of endangered and critically endangered breeds has been studied to identify maternal lineages, characterize genetic inheritance, reconstruct phylogenetic relations among breeds, and develop biodiversity conservation and breeding programs. The aim of the study was to determine the variability remaining and the phylogenetic relationship of Martina Franca (MF, with total population of 160 females and 36 males), Ragusano (RG, 344 females and 30 males), Pantesco (PT, 47 females and 15 males), and Catalonian (CT) donkeys by collecting genetic data from maternal lineages. Genetic material was collected from saliva, and a 350 bp fragment of D-loop mtDNA was amplified and sequenced. Sequences were aligned and evaluated using standard bioinformatics software. A total of 56 haplotypes including 33 polymorphic sites were found in 77 samples (27 MF, 22 RG, 8 PT, 19 CT, 1 crossbred). The breed nucleotide diversity value (π) for all the breeds was 0.128 (MF: 0.162, RG: 0.132, PT: 0.025, CT: 0.038). Principal components analysis grouped most of the haplogroups into two different clusters, I (including all haplotypes from PT and CT, together with haplotypes from MF and RG) and II (including haplotypes from MF and RG only). In conclusion, we found that the primeval haplotypes, haplogroup variability, and a large number of maternal lineages were preserved in MF and RG; thus, these breeds play putative pivotal roles in the phyletic relationships of donkey breeds. Maternal inheritance is indispensable genetic information required to evaluate inheritance, variability, and breeding programs.
Project description:Cortical thickness (CT) and surface area (SA) are altered in many neuropsychiatric disorders and are correlated with cognitive functioning. Little is known about how these components of cortical gray matter develop in the first years of life. We studied the longitudinal development of regional CT and SA expansion in healthy infants from birth to 2 years. CT and SA have distinct and heterogeneous patterns of development that are exceptionally dynamic; overall CT increases by an average of 36.1%, while cortical SA increases 114.6%. By age 2, CT is on average 97% of adult values, compared with SA, which is 69%. This suggests that early identification, prevention, and intervention strategies for neuropsychiatric illness need to be targeted to this period of rapid postnatal brain development, and that SA expansion is the principal driving factor in cortical volume after 2 years of age.
Project description:<h4>Background</h4>Empirical evidence supporting the distinction between suicide attempt (SA) and non-suicidal self-harm (NSSH) is lacking. Although NSSH is a risk factor for SA, we do not currently know whether these behaviours lie on a continuum of severity, or whether they are discrete outcomes with different aetiologies. We conducted this exploratory genetic epidemiology study to investigate this issue further.<h4>Methods</h4>We explored the extent of genetic overlap between NSSH and SA in a large, richly-phenotyped cohort (the Avon Longitudinal Study of Parents and Children; N = 4959), utilising individual-level genetic and phenotypic data to conduct analyses of genome-wide complex traits and polygenic risk scores (PRS).<h4>Results</h4>The single nucleotide polymorphism heritability of NSSH was estimated to be 13% (SE 0.07) and that of SA to be 0% (SE 0.07). Of the traits investigated, NSSH was most strongly correlated with higher IQ (rG = 0.31, SE = 0.22), there was little evidence of high genetic correlation between NSSH and SA (rG = - 0.1, SE = 0.54), likely due to the low heritability estimate for SA. The PRS for depression differentiated between those with NSSH and SA in multinomial regression. The optimal PRS prediction model for SA (Nagelkerke R<sup>2</sup> 0.022, p < 0.001) included ADHD, depression, income, anorexia and neuroticism and explained more variance than the optimal prediction model for NSSH (Nagelkerke R<sup>2</sup> 0.010, p < 0.001) which included ADHD, alcohol consumption, autism spectrum conditions, depression, IQ, neuroticism and suicide attempt.<h4>Conclusions</h4>Our findings suggest that SA does not have a large genetic component, and that although NSSH and SA are not discrete outcomes there appears to be little genetic overlap between the two. The relatively small sample size and resulting low heritability estimate for SA was a limitation of the study. Combined with low heritability estimates, this implies that family or population structures in SA GWASs may contribute to signals detected.
Project description:Executive functions (EFs) and intelligence (IQ) are phenotypically correlated. In twin studies, latent variables for EFs and IQ display moderate to high heritability estimates; however, they show variable genetic correlations in twin studies spanning childhood to middle age. We analyzed data from over 11,000 children (9- to 10-year-olds, including 749 twin pairs) in the Adolescent Brain Cognitive Development (ABCD) Study to examine the phenotypic and genetic relations between EFs and IQ in childhood. We identified two EF factors-Common EF and Updating-Specific-which were both related to IQ (rs = 0.64-0.81). Common EF and IQ were heritable (53%-67%), and their genetic correlation (rG = 0.86) was not significantly different than 1. These results suggest that EFs and IQ are phenotypically but not genetically separable in middle childhood, meaning that this phenotypic separability may be influenced by environmental factors.
Project description:The mosaic model of brain evolution postulates that different brain regions are relatively free to evolve independently from each other. Such independent evolution is possible only if genetic correlations among the different brain regions are less than unity. We estimated heritabilities, evolvabilities and genetic correlations of relative size of the brain, and its different regions in the three-spined stickleback (Gasterosteus aculeatus). We found that heritabilities were low (average h(2) = 0.24), suggesting a large plastic component to brain architecture. However, evolvabilities of different brain parts were moderate, suggesting the presence of additive genetic variance to sustain a response to selection in the long term. Genetic correlations among different brain regions were low (average rG = 0.40) and significantly less than unity. These results, along with those from analyses of phenotypic and genetic integration, indicate a high degree of independence between different brain regions, suggesting that responses to selection are unlikely to be severely constrained by genetic and phenotypic correlations. Hence, the results give strong support for the mosaic model of brain evolution. However, the genetic correlation between brain and body size was high (rG = 0.89), suggesting a constraint for independent evolution of brain and body size in sticklebacks.