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Background and aimsCannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes, including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identified associations with genetic variants.MethodsA twin-based heritability analysis using 8055 twins from three cohorts was performed. We then carried out a genome-wide association meta-analysis of age at first cannabis use in a discovery sample of 24 953 individuals from nine European, North American and Australian cohorts, and a replication sample of 3735 individuals.ResultsThe twin-based heritability for age at first cannabis use was 38% [95% confidence interval (CI) = 19-60%]. Shared and unique environmental factors explained 39% (95% CI = 20-56%) and 22% (95% CI = 16-29%). The genome-wide association meta-analysis identified five single nucleotide polymorphisms (SNPs) on chromosome 16 within the calcium-transporting ATPase gene (ATP2C2) at P  0.8), with the strongest association at the intronic variant rs1574587 (P = 4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P = 1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been associated previously with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant.ConclusionAge at cannabis initiation appears to be moderately heritable in western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

Background: Subjective cognitive complaints (SCCs) may be a precursor to mild cognitive impairment (MCI) and dementia. Objective: This study aimed to examine the heritability of SCCs, correlations between SCCs and memory ability, and the influence of personality and mood on these relationships. Methods: Participants were 306 twin pairs. The heritability of SCCs and the genetic correlations between SCCs and memory performance, personality, and mood scores were determined using structural equation modelling. Results: SCCs were low to moderately heritable. Memory performance, personality and mood were genetically, environmentally, and phenotypically correlated with SCCs in bivariate analysis. However, in multivariate analysis, only mood and memory performance had significant correlations with SCCs. Mood appeared to be related to SCCs by an environmental correlation, whereas memory performance was related to SCCs by a genetic correlation. The link between personality and SCCs was mediated by mood. SCCs had a significant amount of both genetic and environmental variances not explained by memory performance, personality, or mood. Conclusion: Our results suggest that SCCs are influenced both by a person's mood and their memory performance, and that these determinants are not mutually exclusive. While SCCs had genetic overlap with memory performance and environmental association with mood, much of the genetic and environmental components that comprised SCCs were specific to SCCs, though these specific factors are yet to be determined. [ABSTRACT FROM AUTHOR]

Study Objectives: To investigate the influence of genetic and environmental factors on sleep-wake behaviors across adolescence. Methods: Four hundred and ninety-five participants (aged 9-17; 55% females), including 93 monozygotic and 117 dizygotic twin pairs, and 75 unmatched twins, wore an accelerometry device and completed a sleep diary for 2 weeks. Results: Individual differences in sleep onset, wake time, and sleep midpoint were influenced by both additive genetic (44%-50% of total variance) and shared environmental (31%-42%) factors, with a predominant genetic influence for sleep duration (62%) and restorative sleep (43%). When stratified into younger (aged 9-14) and older (aged 16-17) subsamples, genetic sources were more prominent in older adolescents. The moderate correlation between sleep duration and midpoint (rP = -.43, rG = .54) was attributable to a common genetic source. Sleep-wake behaviors on school and nonschool nights were correlated (rP = .44-.72) and influenced by the same genetic and unique environmental factors. Genetic sources specific to night-type were also identified, for all behaviors except restorative sleep. Conclusions: There were strong genetic influences on sleep-wake phenotypes, particularly on sleep timing, in adolescence. Moreover, there may be common genetic influences underlying both sleep and circadian rhythms. The differences in sleep-wake behaviors on school and nonschool nights could be attributable to genetic factors involved in reactivity to environmental context. [ABSTRACT FROM AUTHOR]

There are a wealth of tools for fitting linear models at each location in the brain in neuroimaging analysis, and a wealth of genetic tools for estimating heritability for a small number of phenotypes. But there remains a need for computationally efficient neuroimaging genetic tools that can conduct analyses at the brain‐wide scale. Here we present a simple method for heritability estimation on twins that replaces a variance component model‐which requires iterative optimisation‐with a (noniterative) linear regression model, by transforming data to squared twin‐pair differences. We demonstrate that the method has comparable bias, mean squared error, false positive risk, and power to best practice maximum‐likelihood‐based methods, while requiring a small fraction of the computation time. Combined with permutation, we call this approach "Accelerated Permutation Inference for the ACE Model (APACE)" where ACE refers to the additive genetic (A) effects, and common (C), and unique (E) environmental influences on the trait. We show how the use of spatial statistics like cluster size can dramatically improve power, and illustrate the method on a heritability analysis of an fMRI working memory dataset. [ABSTRACT FROM AUTHOR]

Adequate cerebral blood flow (CBF) is necessary to maintain brain metabolism and function. Arterial spin labeling (ASL) is an emerging MRI technique offering a non-invasive and reliable quantification of CBF. The genetic basis of CBF has not been well documented, and one approach to investigate this is to examine its heritability. The current study aimed to examine the heritability of CBF using ASL data from a cohort of community-dwelling older twins (41 monozygotic (MZ) and 25 dizygotic (DZ) twin pairs; age range, 65–93 years; 56.4% female). The results showed that the cortex had higher CBF than subcortical gray matter (GM) regions, and CBF in the GM regions of the anterior cerebral artery (ACA) territory was lower than that of the middle (MCA) and posterior (PCA) cerebral arteries. After accounting for the effects of age, sex and scanner, moderate heritability was identified for global CBF (h 2 = 0.611; 95% CI = 0.380–0.761), as well as for cortical and subcortical GM and the GM in the major arterial territories (h 2 = 0.500–0.612). Strong genetic correlations (GCs) were found between CBF in subcortical and cortical GM regions, as well as among the three arterial territories (ACA, MCA, PCA), suggesting a largely convergent genetic control for the CBF in brain GM. The moderate heritability of CBF warrants future investigations to uncover the genetic variants and genes that regulate CBF. [ABSTRACT FROM AUTHOR]

Imaging genetic analyses use heritability calculations to measure the fraction of phenotypic variance attributable to additive genetic factors. We tested the agreement between heritability estimates provided by four methods that are used for heritability estimates in neuroimaging traits. SOLAR-Eclipse and OpenMx use iterative maximum likelihood estimation (MLE) methods. Accelerated Permutation inference for ACE (APACE) and fast permutation heritability inference (FPHI), employ fast, non-iterative approximation-based methods. We performed this evaluation in a simulated twin-sibling pedigree and phenotypes and in diffusion tensor imaging (DTI) data from three twin-sibling cohorts, the human connectome project (HCP), netherlands twin register (NTR) and BrainSCALE projects provided as a part of the enhancing neuro imaging genetics analysis (ENIGMA) consortium. We observed that heritability estimate may differ depending on the underlying method and dataset. The heritability estimates from the two MLE approaches provided excellent agreement in both simulated and imaging data. The heritability estimates for two approximation approaches showed reduced heritability estimates in datasets with deviations from data normality. We propose a data homogenization approach (implemented in solar-eclipse; www.solar-eclipse-genetics.org) to improve the convergence of heritability estimates across different methods. The homogenization steps include consistent regression of any nuisance covariates and enforcing normality on the trait data using inverse Gaussian transformation. Under these conditions, the heritability estimates for simulated and DTI phenotypes produced converging heritability estimates regardless of the method. Thus, using these simple suggestions may help new heritability studies to provide outcomes that are comparable regardless of software package. [ABSTRACT FROM AUTHOR]

Background: The Somatic and Psychological HEalth REport (SPHERE) is a 34-item self-report questionnaire that assesses symptoms of mental distress and persistent fatigue. As it was developed as a screening instrument for use mainly in primary care-based clinical settings, its validity and psychometric properties have not been studied extensively in population-based samples. Methods: We used non-parametric Item Response Theory to assess scale validity and item properties of the SPHERE-34 scales, collected through four waves of the Brisbane Longitudinal Twin Study (N = 1707, mean age = 12, 51% females; N = 1273, mean age = 14, 50% females; N = 1513, mean age = 16, 54% females, N = 1263, mean age = 18, 56% females). We estimated the heritability of the new scores, their genetic correlation, and their predictive ability in a sub-sample (N = 1993) who completed the Composite International Diagnostic Interview. Results: After excluding items most responsible for noise, sex or wave bias, the SPHERE-34 questionnaire was reduced to 21 items (SPHERE-21), comprising a 14-item scale for anxiety-depression and a 10-item scale for chronic fatigue (3 items overlapping). These new scores showed high internal consistency (alpha > 0.78), moderate three months reliability (ICC = 0.47-0.58) and item scalability (Hi > 0.23), and were positively correlated (phenotypic correlations r = 0.57-0.70; rG = 0.77-1.00). Heritability estimates ranged from 0.27 to 0.51. In addition, both scores were associated with later DSM-IV diagnoses of MDD, social anxiety and alcohol dependence (OR in 1.23-1.47). Finally, a post-hoc comparison showed that several psychometric properties of the SPHERE-21 were similar to those of the Beck Depression Inventory. Conclusions: The scales of SPHERE-21 measure valid and comparable constructs across sex and age groups (from 9 to 28 years). SPHERE-21 scores are heritable, genetically correlated and show good predictive ability of mental health in an Australian-based population sample of young people. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the genetic influence on the cerebral cortex, based on the analyses of heritability and genetic correlation between grey matter (GM) thickness, derived from structural MR images (sMRI), and associated white matter (WM) connections obtained from diffusion MRI (dMRI). We measured on sMRI the cortical thickness (CT) from a large twin imaging cohort using a surface-based approach ( N = 308, average age 22.8 ± 2.3 SD). An ACE model was employed to compute the heritability of CT. WM connections were estimated based on probabilistic tractography using fiber orientation distributions (FOD) from dMRI. We then fitted the ACE model to estimate the heritability of CT and FOD peak measures along WM fiber tracts. The WM fiber tracts where genetic influence was detected were mapped onto the cortical surface. Bivariate genetic modeling was performed to estimate the cross-trait genetic correlation between the CT and the FOD-based connectivity of the tracts associated with the cortical regions. We found some cortical regions displaying heritable and genetically correlated GM thickness and WM connectivity, forming networks under stronger genetic influence. Significant heritability and genetic correlations between the CT and WM connectivity were found in regions including the right postcentral gyrus, left posterior cingulate gyrus, right middle temporal gyri, suggesting common genetic factors influencing both GM and WM. Hum Brain Mapp 37:2331-2347, 2016. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Popular theory suggests that facial averageness is preferred in a partner for genetic benefits to offspring. However, whether facial averageness is associated with genetic quality is yet to be established. Here, we computed an objective measure of facial averageness for a large sample ( N = 1,823) of identical and nonidentical twins and their siblings to test two predictions from the theory that facial averageness reflects genetic quality. First, we use biometrical modelling to estimate the heritability of facial averageness, which is necessary if it reflects genetic quality. We also test for a genetic association between facial averageness and facial attractiveness. Second, we assess whether paternal age at conception (a proxy of mutation load) is associated with facial averageness and facial attractiveness. Our findings are mixed with respect to our hypotheses. While we found that facial averageness does have a genetic component, and a significant phenotypic correlation exists between facial averageness and attractiveness, we did not find a genetic correlation between facial averageness and attractiveness (therefore, we cannot say that the genes that affect facial averageness also affect facial attractiveness) and paternal age at conception was not negatively associated with facial averageness. These findings support some of the previously untested assumptions of the ‘genetic benefits’ account of facial averageness, but cast doubt on others. [ABSTRACT FROM AUTHOR]

The perception of sweetness varies among individuals but the sources of this variation are not fully understood. Here, in a sample of 1,901 adolescent and young adults (53.8% female; 243 MZ and 452 DZ twin pairs, 511 unpaired individuals; mean age 16.2 ± 2.8, range 12–26 years), we studied the variation in the perception of sweetness intensity of two monosaccharides and two high-potency sweeteners: glucose, fructose, neohesperidine dihydrochalcone (NHDC), and aspartame. Perceived intensity for all sweeteners decreased with age (2–5% per year) and increased with the history of otitis media (6–9%). Males rated aspartame slightly stronger than females (7%). We found similar heritabilities for sugars (glucose: h2 = 0.31, fructose: h2 = 0.34) and high-potency sweeteners (NHDC: h2 = 0.31, aspartame: h2 = 0.30); all were in the modest range. Multivariate modeling showed that a common genetic factor accounted for >75% of the genetic variance in the four sweeteners, suggesting that individual differences in perceived sweet intensity, which are partly due to genetic factors, may be attributed to a single set of genes. This study provided evidence of the shared genetic pathways between the perception of sugars and high-potency sweeteners. [ABSTRACT FROM PUBLISHER]

A wealth of empirical evidence is accumulating on the genetic mediation of brain structure phenotypes. This comes from twin studies that assess heritability and genetic covariance between traits, candidate gene associations, and genome-wide association studies (GWAS) that can identify specific genetic variants. Here we review the major findings from each of these approaches and consider how they inform on the genetic architecture of brain structure. The findings from twin studies show there is a strong genetic influence (heritability) on brain structure, and overlap of genetic effects (pleiotropy) between structures, and between structure and cognition. However, there is also evidence for genetic specificity, with distinct genetic effects across some brain regions. Candidate gene associations show little convergence; most have been under powered to detect effect sizes of the magnitude now expected. GWAS have identified 19 genetic variants for brain structure, though no replicated associations account for more than 1 % of the variance. Together these studies are revealing new insights into the genetic architecture of brain morphology. As the scope of inquiry broadens, including measures that capture the complexity of the brain, along with larger samples and new analyses, such as genome-wide common trait analysis (GCTA) and polygenic scores, which combine variant effects for a phenotype, as well as whole-genome sequencing, more genetic variants for brain structure will be identified. Increasingly, large-scale multi-site studies will facilitate this next wave of studies, and promise to enhance our understanding of the etiology of variation in brain morphology, as well as brain disorders. [ABSTRACT FROM AUTHOR]

The current study sought to examine the relative influence of genetic and environmental factors on corpus callosum (CC) microstructure in a community sample of older adult twins. Analyses were undertaken in 284 healthy older twins (66% female; 79 MZ and 63 DZ pairs) from the Older Australian Twins Study. The average age of the sample was 69.82 (SD = 4.76) years. Brain imaging scans were collected and DTI measures were estimated for the whole CC as well as its five subregions. Parcellation of the CC was performed using Analyze. In addition, white matter lesion (WMLs) burden was estimated. Heritability and genetic correlation analyses were undertaken using the SOLAR software package. Age, sex, scanner, handedness and blood pressure were considered as covariates. Heritability (h2) analysis for the DTI metrics of whole CC, indicated significant h2 for fractional anisotropy (FA) (h2 = 0.56; p = 2.89×10−10), mean diffusivity (MD) (h2 = 0.52; p = 0.30×10−6), radial diffusivity (RD) (h2 = 0.49; p = 0.2×10−6) and axial diffusivity (AD) (h2 = 0.37; p = 8.15×10−5). We also performed bivariate genetic correlation analyses between (i) whole CC DTI measures and (ii) whole CC DTI measures with total brain WML burden. Across the DTI measures for the whole CC, MD and RD shared 84% of the common genetic variance, followed by MD- AD (77%), FA - RD (52%), RD - AD (37%) and FA – MD (11%). For total WMLs, significant genetic correlations indicated that there was 19% shared common genetic variance with whole CC MD, followed by CC RD (17%), CC AD (16%) and CC FA (5%). Our findings suggest that the CC microstructure is under moderate genetic control. There was also evidence of shared genetic factors between the CC DTI measures. In contrast, there was less shared genetic variance between WMLs and the CC DTI metrics, suggesting fewer common genetic variants. [ABSTRACT FROM AUTHOR]

We examined the genetic architecture of functional brain connectivity measures in resting state electroencephalographic (EEG) recordings. Previous studies in Dutch twins have suggested that genetic factors are a main source of variance in functional brain connectivity derived from EEG recordings. In addition, qualitative descriptors of the brain network derived from graph analysis — network clustering and average path length — are also heritable traits. Here we replicated previous findings for connectivity, quantified by the synchronization likelihood, and the graph theoretical parameters cluster coefficient and path length in an Australian sample of 16-year-old twins (879) and their siblings (93). Modeling of monozygotic and dizygotic twins and sibling resemblance indicated heritability estimates of the synchronization likelihood (27–74%) and cluster coefficient and path length in the alpha and theta band (40–44% and 23–40% respectively) and path length in the beta band frequency (41%). This corroborates synchronization likelihood and its graph theoretical derivatives cluster coefficient and path length as potential endophenotypes for behavioral traits and neurological disorders. [ABSTRACT FROM PUBLISHER]

The article discusses a genome-wide study on the perception of odorants Androstenone and Galaxolide. It examines genome-wide association analysis using 2.3 million single nucleotide polymorphisms. It adds that perceived intensity of odorant is a heritable trait, use of a current genome-wide marker panel not detecting a known olfactory genotypeâ€"phenotype association, and differences in Androstenone perception are influenced by OR7D4 genotype and variants of other genes.

Objective/Hypothesis: Self-ratings of olfactory function often correlates poorly with results of objective smell tests. We explored these ratings relative to self-rating of odor annoyance, to odor identification ability, and to mean perceived intensity of odors, and estimated relative genetic and environmental contributions to these traits. Participants and Methods: A total of 1,311 individual twins from the general population (62% females and 38% males, aged 10-83 years, mean age 29 years) including 191 monozygous and 343 dizygous complete twin pairs from Australia, Denmark, Finland, and the United Kingdom rated their sense of smell and annoyance caused by ambient smells (e.g., smells of foods) using seven categories, and performed odor identification and evaluation task for six scratch-and-sniff odor stimuli. Results: The self-rating of olfactory function correlated with the self-rating of odor annoyance ( r = 0.30) but neither correlated with the odor identification score. Quantitative genetic modeling revealed no unambiguously significant genetic contribution to variation in any of the studied traits. Conclusion: The results suggest that environmental rather than genetic factors modify the self-rating of olfactory function and support earlier findings of discrepancy between subjective and objective measures of olfactory function. In addition, the results imply that the self-rating of olfactory function arises from experienced odor annoyance rather than from actual olfactory acuity. [ABSTRACT FROM AUTHOR]

As research encompassing neuroimaging and genetics gains momentum, extraordinary information will be uncovered on the genetic architecture of the human brain. However, there are significant challenges to be addressed first. Not the least of these challenges is to accomplish the sample size necessary to detect subtle genetic influences on the morphometry and function of the healthy brain. Aside from sample size, image acquisition and analysis methods need to be refined in order to ensure optimum sensitivity to genetic and complementary environmental influences. Then there is the vexing issue of interpreting the resulting data. We describe how researchers from the east coast of Australia and the west coast of America have embarked upon a collaboration to meet these challenges using data currently being collected from a large-scale twin study, and offer some opinions about future directions in the field. [ABSTRACT FROM AUTHOR]

Abstract: There is considerable evidence that human sexual orientation is genetically influenced, so it is not known how homosexuality, which tends to lower reproductive success, is maintained in the population at a relatively high frequency. One hypothesis proposes that while genes predisposing to homosexuality reduce homosexuals'' reproductive success, they may confer some advantage in heterosexuals who carry them. However, it is not clear what such an advantage may be. To investigate this, we examine a data set where a large community-based twin sample (N=4904) anonymously completed a detailed questionnaire examining sexual behaviors and attitudes. We show that psychologically masculine females and feminine men are (a) more likely to be nonheterosexual but (b), when heterosexual, have more opposite-sex sexual partners. With statistical modelling of the twin data, we show that both these relationships are partly due to pleiotropic genetic influences common to each trait. We also find a trend for heterosexuals with a nonheterosexual twin to have more opposite-sex partners than do heterosexual twin pairs. Taken together, these results suggest that genes predisposing to homosexuality may confer a mating advantage in heterosexuals, which could help explain the evolution and maintenance of homosexuality in the population. [Copyright &y& Elsevier]

Abstract: To further clarify the mode of genetic transmission on individual alpha frequency (IAF) and alpha power, the extent to which individual differences in these alpha indices are influenced by genetic factors were examined in a large sample of adolescent twins (237 MZ, 282 DZ pairs; aged 16). EEG was measured at rest (eyes closed) from the right occipital site, and a second EEG recording for 50 twin pairs obtained approximately 3 months after the initial collection, enabled an estimation of measurement error. Analyses confirmed a strong genetic influence on both IAF (h 2 =0.81) and alpha power (h 2 =0.82), and there was little support for non-additive genetic (dominance) variance. A small but significant negative correlation (−0.18) was found between IAF and alpha power, but genetic influences on IAF and alpha power were largely independent. All non-genetic variance was due to unreliability, with no significant variance attributed to unique environmental factors. Relationships between the alpha and IQ indices were also explored but were generally either non-significant or very low. The findings confirm the high heritability for both IAF and alpha power, they further suggest that the mode of genetic transmission is due to additive genetic factors, that genetic influences on the underlying neural mechanisms of alpha frequency and power are largely specific, and that individual differences in alpha activity are influenced little by developmental plasticity and individual experiences. [Copyright &y& Elsevier]

Cortical folds help drive the parcellation of the human cortex into functionally specific regions. Variations in the length, depth, width, and surface area of these sulcal landmarks have been associated with disease, and may be genetically mediated. Before estimating the heritability of sulcal variation, the extent to which these metrics can be reliably extracted from in-vivo MRI must be established. Using four independent test-retest datasets, we found high reliability across the brain (intraclass correlation interquartile range: 0.65–0.85). Heritability estimates were derived for three family-based cohorts using variance components analysis and pooled (total N > 3000); the overall sulcal heritability pattern was correlated to that derived for a large population cohort (N > 9000) calculated using genomic complex trait analysis. Overall, sulcal width was the most heritable metric, and earlier forming sulci showed higher heritability. The inter-hemispheric genetic correlations were high, yet select sulci showed incomplete pleiotropy, suggesting hemisphere-specific genetic influences. Fabrizio Pizzagalli et al. study the genetics factors that regulate cortical folding patterning in the brain. They use in vivo brain MRI datasets from around the world and report the reliability and heritability of sulcal morphometric characteristics for 61 sulci per hemisphere of the human brain. They uncover hemisphere-specific genetic influences on the cerebral cortex. [ABSTRACT FROM AUTHOR]

In a population-based genome-wide association (GWA) study of n -back working memory task-related brain activation, we extracted the average percent BOLD signal change (2-back minus 0-back) from 46 regions-of-interest (ROIs) in functional MRI scans from 863 healthy twins and siblings. ROIs were obtained by creating spheres around group random effects analysis local maxima, and by thresholding a voxel-based heritability map of working memory brain activation at 50%. Quality control for test-retest reliability and heritability of ROI measures yielded 20 reliable ( r > 0.7) and heritable ( h 2 > 20%) ROIs. For GWA analysis, the cohort was divided into a discovery ( n = 679) and replication ( n = 97) sample. No variants survived the stringent multiple-testing-corrected genome-wide significance threshold ( p < 4.5 × 10 −9 ), or were replicated ( p < 0.0016), but several genes were identified that are worthy of further investigation. A search of 529,379 genomic markers resulted in discovery of 31 independent single nucleotide polymorphisms (SNPs) associated with BOLD signal change at a discovery level of p < 1 × 10 −5 . Two SNPs (rs7917410 and rs7672408) were associated at a significance level of p < 1 × 10 −7 . Only one, most strongly affecting BOLD signal change in the left supramarginal gyrus ( R 2 = 5.5%), had multiple SNPs associated at p < 1 × 10 −5 in linkage disequilibrium with it, all located in and around the BANK1 gene. BANK1 encodes a B-cell-specific scaffold protein and has been shown to negatively regulate CD40-mediated AKT activation. AKT is part of the dopamine-signaling pathway, suggesting a mechanism for the involvement of BANK1 in the BOLD response to working memory. Variants identified here may be relevant to (the susceptibility to) common disorders affecting brain function. [ABSTRACT FROM AUTHOR]

The human hippocampal formation can be divided into a set of cytoarchitecturally and functionally distinct subregions, involved in different aspects of memory formation. Neuroanatomical disruptions within these subregions are associated with several debilitating brain disorders including Alzheimer's disease, major depression, schizophrenia, and bipolar disorder. Multi-center brain imaging consortia, such as the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) consortium, are interested in studying disease effects on these subregions, and in the genetic factors that affect them. For large-scale studies, automated extraction and subsequent genomic association studies of these hippocampal subregion measures may provide additional insight. Here, we evaluated the test–retest reliability and transplatform reliability (1.5 T versus 3 T) of the subregion segmentation module in the FreeSurfer software package using three independent cohorts of healthy adults, one young (Queensland Twins Imaging Study, N = 39), another elderly (Alzheimer's Disease Neuroimaging Initiative, ADNI-2, N = 163) and another mixed cohort of healthy and depressed participants (Max Planck Institute, MPIP, N = 598). We also investigated agreement between the most recent version of this algorithm (v6.0) and an older version (v5.3), again using the ADNI-2 and MPIP cohorts in addition to a sample from the Netherlands Study for Depression and Anxiety (NESDA) (N = 221). Finally, we estimated the heritability ( h 2 ) of the segmented subregion volumes using the full sample of young, healthy QTIM twins (N = 728). Test–retest reliability was high for all twelve subregions in the 3 T ADNI-2 sample (intraclass correlation coefficient (ICC) = 0.70–0.97) and moderate-to-high in the 4 T QTIM sample (ICC = 0.5–0.89). Transplatform reliability was strong for eleven of the twelve subregions (ICC = 0.66–0.96); however, the hippocampal fissure was not consistently reconstructed across 1.5 T and 3 T field strengths (ICC = 0.47–0.57). Between-version agreement was moderate for the hippocampal tail, subiculum and presubiculum (ICC = 0.78–0.84; Dice Similarity Coefficient (DSC) = 0.55–0.70), and poor for all other subregions (ICC = 0.34–0.81; DSC = 0.28–0.51). All hippocampal subregion volumes were highly heritable ( h 2 = 0.67–0.91). Our findings indicate that eleven of the twelve human hippocampal subregions segmented using FreeSurfer version 6.0 may serve as reliable and informative quantitative phenotypes for future multi-site imaging genetics initiatives such as those of the ENIGMA consortium. [ABSTRACT FROM AUTHOR]

In functional magnetic resonance imaging (fMRI), the hemodynamic response function (HRF) reflects regulation of regional cerebral blood flow in response to neuronal activation. The HRF varies significantly between individuals. This study investigated the genetic contribution to individual variation in HRF using fMRI data from 125 monozygotic (MZ) and 149 dizygotic (DZ) twin pairs. The resemblance in amplitude, latency, and duration of the HRF in six regions in the frontal and parietal lobes was compared between MZ and DZ twin pairs. Heritability was estimated using an ACE (Additive genetic, Common environmental, and unique Environmental factors) model. The genetic influence on the temporal profile and amplitude of HRF was moderate to strong (24%–51%). The HRF may be used in the genetic analysis of diseases with a cerebrovascular etiology. [ABSTRACT FROM AUTHOR]

The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and “rich-club” properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕ norm ), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k = 5–25%) in a large cohort of twins (N = 592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23 ± 2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h 2 (γ = 47–59%, Q = 38–59%, ϕ norm = 0–29%, λ = 52–64%, σ = 51–59%) at lower connection densities (≤ 15%), and when global signal regression was implemented, heritability estimates decreased substantially h 2 (γ = 0–26%, Q = 0–28%, ϕ norm = 0%, λ = 23–30%, σ = 0–27%). Distinct network features were phenotypically correlated (|r| = 0.15–0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices. [ABSTRACT FROM AUTHOR]

Head motion (HM) is a critical confounding factor in functional MRI. Here we investigate whether HM during resting state functional MRI (RS-fMRI) is influenced by genetic factors in a sample of 462 twins (65% female; 101 MZ (monozygotic) and 130 DZ (dizygotic) twin pairs; mean age: 21 (SD = 3.16), range 16–29). Heritability estimates for three HM components—mean translation (MT), maximum translation (MAXT) and mean rotation (MR)—ranged from 37 to 51%. We detected a significant common genetic influence on HM variability, with about two-thirds (genetic correlations range 0.76–1.00) of the variance shared between MR, MT and MAXT. A composite metric (HM-PC1), which aggregated these three, was also moderately heritable (h 2 = 42%). Using a sub-sample (N = 35) of the twins we confirmed that mean and maximum translational and rotational motions were consistent “traits” over repeated scans (r = 0.53–0.59); reliability was even higher for the composite metric (r = 0.66). In addition, phenotypic and cross-trait cross-twin correlations between HM and resting state functional connectivities (RS-FCs) with Brodmann areas (BA) 44 and 45, in which RS-FCs were found to be moderately heritable (BA44: h 2 ¯ = 0.23 (sd = 0.041), BA45: h 2 ¯ = 0.26 (sd = 0.061)), indicated that HM might not represent a major bias in genetic studies using FCs. Even so, the HM effect on FC was not completely eliminated after regression. HM may be a valuable endophenotype whose relationship with brain disorders remains to be elucidated. [ABSTRACT FROM AUTHOR]

Abstract: Over the past several years, evidence has accumulated showing that the cerebellum plays a significant role in cognitive function. Here we show, in a large genetically informative twin sample (n =430; aged 16–30years), that the cerebellum is strongly, and reliably (n =30 rescans), activated during an n-back working memory task, particularly lobules I–IV, VIIa Crus I and II, IX and the vermis. Monozygotic twin correlations for cerebellar activation were generally much larger than dizygotic twin correlations, consistent with genetic influences. Structural equation models showed that up to 65% of the variance in cerebellar activation during working memory is genetic (averaging 34% across significant voxels), most prominently in the lobules VI, and VIIa Crus I, with the remaining variance explained by unique/unshared environmental factors. Heritability estimates for brain activation in the cerebellum agree with those found for working memory activation in the cerebral cortex, even though cerebellar cyto-architecture differs substantially. Phenotypic correlations between BOLD percent signal change in cerebrum and cerebellum were low, and bivariate modeling indicated that genetic influences on the cerebellum are at least partly specific to the cerebellum. Activation on the voxel-level correlated very weakly with cerebellar gray matter volume, suggesting specific genetic influences on the BOLD signal. Heritable signals identified here should facilitate discovery of genetic polymorphisms influencing cerebellar function through genome-wide association studies, to elucidate the genetic liability to brain disorders affecting the cerebellum. [Copyright &y& Elsevier]

Abstract: Twin studies have shown that many aspects of brain structure are heritable, suggesting a strong genetic contribution to brain structure. Less is known about functional aspects of the brain, in particular biologically relevant metabolites in the brain such as those measured by proton magnetic resonance spectroscopy ( 1 H MRS), N-acetyl-aspartate (NAA), creatine (Cr), choline (Cho) and myoinositol (ml), which have been suggested as possible markers of brain aging and early dementia. We examined 296 (56 male/108 female monozygotic and 43 male/89 female dizygotic) older twins (mean age 72.2±5.5years, range 65–88), for the levels of these metabolites relative to the H2O signal in the posterior cingulate cortex using 1 H MRS. All metabolites showed substantial heritability, which was greatest for the neuronal integrity marker NAA (72%), and less so for the others — Cr (51%), Cho (33%) and ml (55%). The heritability of these markers did not change significantly with age or sex. The genetic determination of NAA, along with the evidence that NAA levels change in aging and neurodegenerative diseases suggest that it is a potential endophenotype of brain aging and dementia. [Copyright &y& Elsevier]

Abstract: Working memory-related brain activation has been widely studied, and impaired activation patterns have been reported for several psychiatric disorders. We investigated whether variation in N-back working memory brain activation is genetically influenced in 60 pairs of twins, (29 monozygotic (MZ), 31 dizygotic (DZ); mean age 24.4±1.7S.D.). Task-related brain response (BOLD percent signal difference of 2 minus 0-back) was measured in three regions of interest. Although statistical power was low due to the small sample size, for middle frontal gyrus, angular gyrus, and supramarginal gyrus, the MZ correlations were, in general, approximately twice those of the DZ pairs, with non-significant heritability estimates (14–30%) in the low-moderate range. Task performance was strongly influenced by genes (57–73%) and highly correlated with cognitive ability (0.44–0.55). This study, which will be expanded over the next 3 years, provides the first support that individual variation in working memory-related brain activation is to some extent influenced by genes. [Copyright &y& Elsevier]

Abstract: The relative contributions of genetic and environmental factors to brain structure change throughout the lifespan. Brain structures have been reported to be highly heritable in middle-aged individuals and younger; however, the influence of genes on brain structure is less studied in older adults. We performed a magnetic resonance imaging study of 236 older twins, with a mean age of 71.4 ± 5.7 years, to examine the heritability of 53 brain global and lobar volumetric measures. Total brain volume (63%) and other volumetric measures were moderately to highly heritable in late life, and these genetic influences tended to decrease with age, suggesting a greater influence of environmental factors as age advanced. Genetic influences were higher in men and on the left hemisphere compared with the right. In multivariate models, common genetic factors were observed for global and lobar total and gray matter volumes. This study examined the genetic contribution to 53 brain global and lobar volumetric measures in older twins for the first time, and the influence of age, sex, and laterality on these genetic contributions, which are useful information for a better understanding of the process of brain aging and helping individuals to have a healthy aging. [Copyright &y& Elsevier]