Genetic and environmental influences on neuroimaging phenotypes: a meta-analytical perspective on twin imaging studies

Quantitative MRI Measures and Cognitive Function in People With Drug-Resistant Juvenile Myoclonic Epilepsy

BACKGROUND AND OBJECTIVES

Neuroimaging studies have so far identified structural changes in individuals with juvenile myoclonic epilepsy (JME) when compared with controls. However, the underlying mechanisms of drug-resistant JME remain unknown. In this study, we aimed at characterizing the structural underpinnings of drug-resistant JME using MRI-derived cortical morphologic markers.

METHODS

In this prospective cross-sectional 2-center study, T1-weighted MRI and neuropsychological measures of verbal memory and executive function were obtained in individuals with drug-resistant and drug-responsive JME recruited from epilepsy outpatient clinics and healthy controls. We performed vertexwise measurements of cortical thickness, surface area, and local gyrification index (LGI). Vertexwise group comparisons were corrected for multiple comparisons at a familywise error (FWE) of 0.05. The neuropsychological profile of disease subgroups was analyzed through principal component analysis.

RESULTS

We studied 42 individuals with drug-resistant JME (mean age 29 ± 11 years, 50% female), 37 with drug-responsive JME (mean age 34 ± 10, years, 59% female), and 71 healthy controls (mean age 21 ± 9 years, 61% female). Surface area was increased in participants with drug-resistant JME in the left temporal lobe (Cohen d = 0.82 [-0.52 to -1.12], pFWE < 0.05) when compared with the drug-responsive group. Although no cortical thickness changes were observed between disease subgroups, drug-resistant and drug-sensitive participants showed discrete cortical thinning against controls (Cohen d = -0.42 [-0.83 to -0.01], pFWE < 0.05; Cohen d = -0.57 [-1.03 to -0.11], pFWE < 0.05, respectively). LGI was increased in the left temporal and occipital lobes in drug-resistant participants (Cohen d = 0.60 [0.34-0.86], pFWE < 0.05) when contrasting against drug-sensitive participants, but not controls. The composite executive function score was reduced in drug-resistant individuals compared with controls and drug-sensitive individuals (-1.74 [-2.58 to -0.90], p < 0.001 and -1.29 [-2.25 to -0.33], p < 0.01, respectively). Significant correlations were observed between executive function impairment and increased surface area in the precuneus and medial prefrontal regions (r = -0.79, pFWE < 0.05) in participants with drug-resistant JME.

DISCUSSION

We identified a developmental phenotype in individuals with drug-resistant JME characterized by changes in cortical surface area and folding complexity, the extent of which correlates with executive dysfunction. No association was observed between cortical thickness and disease severity. Our findings support a neurodevelopmental basis for drug resistance and cognitive impairment in JME.

The interplay of genetic and environmental factors on the morphology of the limbic cortex and hippocampal subfields: Insights from an MRI twin study

INTRODUCTION

The limbic system and the hippocampus are complex brain structures with key roles in memory, emotions, sexual stimulation and learning, with subregion abnormalities associated with a range of disorders and psychopathologies. Our study aimed to explore the heritability of specific subfield structures within the limbic system and hippocampus first in a Caucasian twin sample with volBrain pipeline.

MATERIALS AND METHODS

59 healthy adult Caucasian twin pairs from the Hungarian Twin Registry without any history of previous neurodegenerative or cerebrovascular diseases underwent brain MRI on a 3.0 T scanner (43 monozygotic, MZ and 16 dizygotic, DZ pairs, with a median age of 50±+27 years). The volBrain automated volumetry pipeline was used to calculate the subcortical and general brain volumes from three-dimensional T1-weighted images. Based on age- and sex-adjusted MZ and DZ intra-pair correlations, the univariate ACE model was applied to calculate additive genetic, shared and unshared environmental influences.

RESULTS

Adjusting for age and sex, moderate to strong heritability (A: 59.7 to 73.1 %) was found for most limbic cortex volumes, except for the volumes of entorhinal area and posterior cingulate gyrus where common environmental contribution was detected (C: 56.6 % and 65.0 %, respectively). A substantial heritability (A: 67.0 to 79.4 %) was estimated for the overall hippocampus and most subfield volumes, except for the CA2-CA3 region which was determinated by common environmental factors (C: 45.7 %). Unique environmental variance was a minor to moderate contributor across all variables (E: 20.6 to 54.3 %).

CONCLUSIONS

Albeit most limbic cortex, overall hippocampus and most subfield volumes are under substantial genetic influence in healthy adult twins, the volumes of entorhinal area, posterior cingulate gyrus and the CA2-CA3 region of the hippocampus are influenced common environmental factors. The findings underline the importance of unique environmental factors which may play a role in the prevention of disorders related to limbic cortex and hippocampus.

Brain structures with stronger genetic associations are not less associated with family- and state-level economic contexts

We investigate whether neural, cognitive, and psychopathology phenotypes that are more strongly related to genetic differences are less strongly associated with family- and state-level economic contexts (N = 5374 individuals with 1KG-EUR-like genotypes with 870 twins, from the Adolescent Behavior and Cognitive Development study). We estimated the twin- and SNP-based heritability of each phenotype, as well as its association with an educational attainment polygenic index (EA PGI). We further examined associations with family socioeconomic status (SES) and tested whether SES-related differences were moderated by state cost of living and social safety net programs (Medicaid expansion and cash assistance). SES was broadly associated with cognition, psychopathology, brain volumes, and cortical surface areas, even after controlling for the EA PGI. Brain phenotypes that were more heritable or more strongly associated with the EA PGI were not, overall, less related to SES, nor were SES-related differences in these phenotypes less moderated by macroeconomic context and policy. Informing a long-running theoretical debate, and contra to widespread lay beliefs, results suggest that aspects of child brain development that are more strongly related to genetic differences are not, in general, less associated with socioeconomic contexts and policies.

Heritability of white matter in twins: A diffusion neuroimaging review

Diffusion neuroimaging has emerged as an essential non-invasive technique to explore in vivo microstructural characteristics of white matter (WM), whose integrity allows complex behaviors and cognitive abilities. Studying the factors contributing to inter-individual variability in WM microstructure can provide valuable insight into structural and functional differences of brain among individuals. Genetic influence on this variation has been largely investigated in twin studies employing different measures derived from diffusion neuroimaging. In this context, we performed a comprehensive literature search across PubMed, Scopus and Web of Science of original twin studies focused on the heritability of WM. Overall, our results highlighted a consistent heritability of diffusion indices (i.e., fractional anisotropy, mean, axial and radial diffusivity), and network topology among twins. The genetic influence resulted prominent in frontal and occipital regions, in the limbic system, and in commissural fibers. To enhance the understanding of genetic influence on WM microstructure further studies in less heterogeneous experimental settings, encompassing all diffusion indices, are warranted.

Identifying the genetic association between the cerebral cortex and fibromyalgia

Fibromyalgia (FM) is a central sensitization syndrome that is strongly associated with the cerebral cortex. This study used bidirectional two-sample Mendelian randomization (MR) analysis to investigate the bidirectional causality between FM and the cortical surface area and cortical thickness of 34 brain regions. Inverse variance weighted (IVW) was used as the primary method for this study, and sensitivity analyses further supported the results. The forward MR analysis revealed that genetically determined thinner cortical thickness in the parstriangularis (OR = 0.0567 mm, PIVW = 0.0463), caudal middle frontal (OR = 0.0346 mm, PIVW = 0.0433), and rostral middle frontal (OR = 0.0285 mm, PIVW = 0.0463) was associated with FM. Additionally, a reduced genetically determined cortical surface area in the pericalcarine (OR = 0.9988 mm2, PIVW = 0.0085) was associated with an increased risk of FM. Conversely, reverse MR indicated that FM was associated with cortical thickness in the caudal middle frontal region (β = -0.0035 mm, PIVW = 0.0265), fusiform region (β = 0.0024 mm, SE = 0.0012, PIVW = 0.0440), the cortical surface area in the supramarginal (β = -9.3938 mm2, PIVW = 0.0132), and postcentral regions (β = -6.3137 mm2, PIVW = 0.0360). Reduced cortical thickness in the caudal middle frontal gyrus is shown to have a significant relationship with FM prevalence in a bidirectional causal analysis.

Genetic influences on brain and cognitive health and their interactions with cardiovascular conditions and depression

Approximately 40% of dementia cases could be prevented or delayed by modifiable risk factors related to lifestyle and environment. These risk factors, such as depression and vascular disease, do not affect all individuals in the same way, likely due to inter-individual differences in genetics. However, the precise nature of how genetic risk profiles interact with modifiable risk factors to affect brain health is poorly understood. Here we combine multiple data resources, including genotyping and postmortem gene expression, to map the genetic landscape of brain structure and identify 367 loci associated with cortical thickness and 13 loci associated with white matter hyperintensities (P < 5×10-8), with several loci also showing a significant association with cognitive function. We show that among 220 unique genetic loci associated with cortical thickness in our genome-wide association studies (GWAS), 95 also showed evidence of interaction with depression or cardiovascular conditions. Polygenic risk scores based on our GWAS of inferior frontal thickness also interacted with hypertension in predicting executive function in the Canadian Longitudinal Study on Aging. These findings advance our understanding of the genetic underpinning of brain structure and show that genetic risk for brain and cognitive health is in part moderated by treatable mid-life factors.

Structural deviations of the posterior fossa and the cerebellum and their cognitive links in a neurodevelopmental deletion syndrome

High-impact genetic variants associated with neurodevelopmental disorders provide biologically-defined entry points for mechanistic investigation. The 3q29 deletion (3q29Del) is one such variant, conferring a 40-100-fold increased risk for schizophrenia, as well as high risk for autism and intellectual disability. However, the mechanisms leading to neurodevelopmental disability remain largely unknown. Here, we report the first in vivo quantitative neuroimaging study in individuals with 3q29Del (N = 24) and neurotypical controls (N = 1608) using structural MRI. Given prior radiology reports of posterior fossa abnormalities in 3q29Del, we focused our investigation on the cerebellum and its tissue-types and lobules. Additionally, we compared the prevalence of cystic/cyst-like malformations of the posterior fossa between 3q29Del and controls and examined the association between neuroanatomical findings and quantitative traits to probe gene-brain-behavior relationships. 3q29Del participants had smaller cerebellar cortex volumes than controls, before and after correction for intracranial volume (ICV). An anterior-posterior gradient emerged in finer grained lobule-based and voxel-wise analyses. 3q29Del participants also had larger cerebellar white matter volumes than controls following ICV-correction and displayed elevated rates of posterior fossa arachnoid cysts and mega cisterna magna findings independent of cerebellar volume. Cerebellar white matter and subregional gray matter volumes were associated with visual-perception and visual-motor integration skills as well as IQ, while cystic/cyst-like malformations yielded no behavioral link. In summary, we find that abnormal development of cerebellar structures may represent neuroimaging-based biomarkers of cognitive and sensorimotor function in 3q29Del, adding to the growing evidence identifying cerebellar pathology as an intersection point between syndromic and idiopathic forms of neurodevelopmental disabilities.

Are human connectomes heritable?

A complete understanding of human behavior and disease depends upon our ability to parse genetic and environmental influences in the human brain. The heritability of a trait quantifies the degree of its variability due to genetic influences. Classical approach for quantifying heritability operate on simple traits, and sometimes do not properly model and control for other potential sources of variation, such as age or sex. We therefore develop Causal Heritability of Networks (CHaiN) to rigorously quantify heritability of human brain networks (i.e., connectomes). We applied CHaiN to 1024 anatomical connectomes derived from the Human Connectome Project. Connectomes appeared to be heritable, but heritability was insignificant once we addressed variability within networks. These results suggest that previous conclusions on connectome heritability may be driven by the shared network structures, and highlights the importance of modeling networks and other sources of variability when studying heritability of connectomes.

Dissociation of Reliability, Heritability, and Predictivity in Coarse- and Fine-Scale Functional Connectomes during Development

The functional connectome supports information transmission through the brain at various spatial scales, from exchange between broad cortical regions to finer-scale, vertex-wise connections that underlie specific information processing mechanisms. In adults, while both the coarse- and fine-scale functional connectomes predict cognition, the fine scale can predict up to twice the variance as the coarse-scale functional connectome. Yet, past brain-wide association studies, particularly using large developmental samples, focus on the coarse connectome to understand the neural underpinnings of individual differences in cognition. Using a large cohort of children (age 9-10 years; n = 1,115 individuals; both sexes; 50% female, including 170 monozygotic and 219 dizygotic twin pairs and 337 unrelated individuals), we examine the reliability, heritability, and behavioral relevance of resting-state functional connectivity computed at different spatial scales. We use connectivity hyperalignment to improve access to reliable fine-scale (vertex-wise) connectivity information and compare the fine-scale connectome with the traditional parcel-wise (coarse scale) functional connectomes. Though individual differences in the fine-scale connectome are more reliable than those in the coarse-scale, they are less heritable. Further, the alignment and scale of connectomes influence their ability to predict behavior, whereby some cognitive traits are equally well predicted by both connectome scales, but other, less heritable cognitive traits are better predicted by the fine-scale connectome. Together, our findings suggest there are dissociable individual differences in information processing represented at different scales of the functional connectome which, in turn, have distinct implications for heritability and cognition.

Heritability of cognitive and emotion processing during functional MRI in a twin sample

Despite compelling evidence that brain structure is heritable, the evidence for the heritability of task-evoked brain function is less robust. Findings from previous studies are inconsistent possibly reflecting small samples and methodological variations. In a large national twin sample, we systematically evaluated heritability of task-evoked brain activity derived from functional magnetic resonance imaging. We used established standardised tasks to engage brain regions involved in cognitive and emotional functions. Heritability was evaluated across a conscious and nonconscious Facial Expressions of Emotion Task (FEET), selective attention Oddball Task, N-back task of working memory maintenance, and a Go-NoGo cognitive control task in a sample of Australian adult twins (N ranged from 136 to 226 participants depending on the task and pairs). Two methods for quantifying associations of heritability and brain activity were utilised; a multivariate independent component analysis (ICA) approach and a univariate brain region-of-interest (ROI) approach. Using ICA, we observed that a significant proportion of task-evoked brain activity was heritable, with estimates ranging from 23% to 26% for activity elicited by nonconscious facial emotion stimuli, 27% to 34% for N-back working memory maintenance and sustained attention, and 32% to 33% for selective attention in the Oddball task. Using the ROI approach, we found that activity of regions specifically implicated in emotion processing and selective attention showed significant heritability for three ROIs, including estimates of 33%-34% for the left and right amygdala in the nonconscious processing of sad faces and 29% in the medial superior prefrontal cortex for the Oddball task. Although both approaches show similar levels of heritability for the Nonconscious Faces and Oddball tasks, ICA results displayed a more extensive network of heritable brain function, including additional regions beyond the ROI analysis. Furthermore, multivariate twin modelling of both ICA networks and ROI activation suggested a mix of common genetic and unique environmental factors that contribute to the associations between networks/regions. Together, the results indicate a complex relationship between genetic factors and environmental interactions that ultimately give rise to neural activation underlying cognition and emotion.

Structural and functional network analysis of twins using fMRI data

Similarities between twins have been widely demonstrated, underscoring the remarkable influence of genetics across numerous traits. In this study, we explore the genetic underpinnings of the human brain by examining MRI data from the Queensland Twin Imaging study. Specifically, this study seeks to compare brain structure and function between twins and unrelated subjects, with an emphasis on describing the effects of genetic factors. To achieve these goals, we employed the source-based morphometry method to extract intrinsic components and elucidate recognizable patterns. Our results show that twins exhibit a higher degree of similarity in gray and white matter density compared with unrelated individuals. In addition, four distinct states of brain activity were identified using coactivation patterns analysis. Furthermore, twins demonstrated a greater degree of similarity in the temporal and spatial features of each state compared with unrelated subjects. Taken together, these results support the hypothesis that twins show greater similarity in both brain structure and dynamic functional brain activity. Further exploration of these methods may advance our understanding of the complex interplay between genes, environment, and brain networks.

Neural correlates of aggression in personality disorders from the perspective of DSM-5 maladaptive traits: a systematic review

The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), published in 2013, includes an alternative model of personality disorders (AMPD) focusing on a maladaptive trait model utilized to diagnose several personality disorders. Borderline personality disorder (BPD) and antisocial personality disorder (ASPD) are two conditions categorized by AMPD that exhibit high rates of violence and aggression. Several of the traits outlined in the AMPD, including hostility, impulsivity, risk-taking, and callousness, have been previously linked to aggression in BPD and ASPD. However, to the best of our knowledge, there has never been a synthesis of neuroimaging studies that have investigated links between these traits and aggression in BPD and ASPD. To overcome this gap, we conducted a systematic review under the PRISMA framework to locate neuroimaging articles published since the release of AMPD linking trait anger/hostility, impulsivity, risk-taking, and callousness to aggression in BPD and ASPD. Key findings included the following: i) anger/hostility, associated with alterations in the interplay between prefrontal and subcortical regions (primarily the amygdala), may be a common factor explaining aggressive reactions to response to interpersonal threat or provocation; ii) alterations of fronto-temporal-limbic regions and serotonergic and endocannabinoid signaling systems may link impulsivity to aggression in BPD and ASPD; iii) weaker cortico-striatal connectivity could relate to greater risk taking and greater proclivity for violence. Insufficient evidence from neuroimaging articles was discerned to describe a relationship between callousness and aggression. Overall, results of this review reveal a relative paucity of neuroimaging studies examining AMPD traits relevant to aggression in BPD and ASPD. In addition to encouraging further investigation of neuroimaging markers of AMPD traits linked to aggression, we recommend multi-methodological designs, including the incorporation of other biomarkers, such as hormones and indices of physiological arousal, to fully expand our understanding of aggression in BPD and ASPD.

Brain-wide genome-wide colocalization study for integrating genetics, transcriptomics and brain morphometry in Alzheimer's disease

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. However, the AD mechanism has not yet been fully elucidated to date, hindering the development of effective therapies. In our work, we perform a brain imaging genomics study to link genetics, single-cell gene expression data, tissue-specific gene expression data, brain imaging-derived volumetric endophenotypes, and disease diagnosis to discover potential underlying neurobiological pathways for AD. To do so, we perform brain-wide genome-wide colocalization analyses to integrate multidimensional imaging genomic biobank data. Specifically, we use (1) the individual-level imputed genotyping data and magnetic resonance imaging (MRI) data from the UK Biobank, (2) the summary statistics of the genome-wide association study (GWAS) from multiple European ancestry cohorts, and (3) the tissue-specific cis-expression quantitative trait loci (cis-eQTL) summary statistics from the GTEx project. We apply a Bayes factor colocalization framework and mediation analysis to these multi-modal imaging genomic data. As a result, we derive the brain regional level GWAS summary statistics for 145 brain regions with 482,831 single nucleotide polymorphisms (SNPs) followed by posthoc functional annotations. Our analysis yields the discovery of a potential AD causal pathway from a systems biology perspective: the SNP chr10:124165615:G>A (rs6585827) mutation upregulates the expression of BTBD16 gene in oligodendrocytes, a specialized glial cells, in the brain cortex, leading to a reduced risk of volumetric loss in the entorhinal cortex, resulting in the protective effect on AD. We substantiate our findings with multiple evidence from existing imaging, genetic and genomic studies in AD literature. Our study connects genetics, molecular and cellular signatures, regional brain morphologic endophenotypes, and AD diagnosis, providing new insights into the mechanistic understanding of the disease. Our findings can provide valuable guidance for subsequent therapeutic target identification and drug discovery in AD.

Profiling intra- and inter-individual differences in brain development across early adolescence

As we move toward population-level developmental neuroscience, understanding intra- and inter-individual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and inter-individual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment across early adolescence (ages 8.92 to 13.83 years) in the Adolescent Brain Cognitive Development (ABCD) Study and examine inter-individual variability as a function of age, sex, and puberty. Our results provide novel insight into differences in annualized percent change in macrostructure, microstructure, and functional brain development from ages 9-13 years old. These findings reveal moderate age-related intra-individual change, but age-related differences in inter-individual variability only in a few measures of cortical macro- and microstructure development. Greater inter-individual variability in brain development were seen in mid-pubertal individuals, except for a few aspects of white matter development that were more variable between prepubertal individuals in some tracts. Although both sexes contributed to inter-individual differences in macrostructure and functional development in a few regions of the brain, we found limited support for hypotheses regarding greater male-than-female variability. This work highlights pockets of individual variability across facets of early adolescent brain development, while also highlighting regional differences in heterogeneity to facilitate future investigations in quantifying and probing nuances in normative development, and deviations therefrom.

Genetic and Environmental Influences on Structural and Diffusion-Based Alzheimer's Disease Neuroimaging Signatures Across Midlife and Early Old Age

BACKGROUND

Composite scores of magnetic resonance imaging-derived metrics in brain regions associated with Alzheimer's disease (AD), commonly termed AD signatures, have been developed to distinguish early AD-related atrophy from normal age-associated changes. Diffusion-based gray matter signatures may be more sensitive to early AD-related changes compared with thickness/volume-based signatures, demonstrating their potential clinical utility. The timing of early (i.e., midlife) changes in AD signatures from different modalities and whether diffusion- and thickness/volume-based signatures each capture unique AD-related phenotypic or genetic information remains unknown.

METHODS

Our validated thickness/volume signature, our novel mean diffusivity (MD) signature, and a magnetic resonance imaging-derived measure of brain age were used in biometrical analyses to examine genetic and environmental influences on the measures as well as phenotypic and genetic relationships between measures over 12 years. Participants were 736 men from 3 waves of the Vietnam Era Twin Study of Aging (VETSA) (baseline/wave 1: mean age [years] = 56.1, SD = 2.6, range = 51.1-60.2). Subsequent waves occurred at approximately 5.7-year intervals.

RESULTS

MD and thickness/volume signatures were highly heritable (56%-72%). Baseline MD signatures predicted thickness/volume signatures over a decade later, but baseline thickness/volume signatures showed a significantly weaker relationship with future MD signatures. AD signatures and brain age were correlated, but each measure captured unique phenotypic and genetic variance.

CONCLUSIONS

Cortical MD and thickness/volume AD signatures are heritable, and each signature captures unique variance that is also not explained by brain age. Moreover, results are in line with changes in MD emerging before changes in cortical thickness, underscoring the utility of MD as a very early predictor of AD risk.

Reduced brain connectivity along the autism spectrum controlled for familial confounding by co-twin design

Previous studies on brain connectivity correlates of autism have often focused on selective connections and yielded inconsistent results. By applying global fiber tracking and utilizing a within-twin pair design, we aimed to contribute to a more unbiased picture of white matter connectivity in association with clinical autism and autistic traits. Eighty-seven twin pairs (n = 174; 55% monozygotic; 24 with clinical autism) underwent diffusion tensor imaging. Linear regressions assessed within-twin pair associations between structural brain connectivity of anatomically defined brain regions and both clinical autism and autistic traits. These were explicitly adjusted for IQ, other neurodevelopmental/psychiatric conditions and multiple testing, and implicitly for biological sex, age, and all genetic and environmental factors shared by twins. Both clinical autism and autistic traits were associated with reductions in structural connectivity. Twins fulfilling diagnostic criteria for clinical autism had decreased brainstem-cuneus connectivity compared to their co-twins without clinical autism. Further, twins with higher autistic traits had decreased connectivity of the left hippocampus with the left fusiform and parahippocampal areas. These associations were also significant in dizygotic twins alone. Reduced brainstem-cuneus connectivity might point towards alterations in low-level visual processing in clinical autism while higher autistic traits seemed to be more associated with reduced connectivity in networks involving the hippocampus and the fusiform gyrus, crucial especially for processing of faces and other (higher order) visual processing. The observed associations were likely influenced by both genes and environment.

Statistical Learning Methods for Neuroimaging Data Analysis with Applications

The aim of this review is to provide a comprehensive survey of statistical challenges in neuroimaging data analysis, from neuroimaging techniques to large-scale neuroimaging studies and statistical learning methods. We briefly review eight popular neuroimaging techniques and their potential applications in neuroscience research and clinical translation. We delineate four themes of neuroimaging data and review major image processing analysis methods for processing neuroimaging data at the individual level. We briefly review four large-scale neuroimaging-related studies and a consortium on imaging genomics and discuss four themes of neuroimaging data analysis at the population level. We review nine major population-based statistical analysis methods and their associated statistical challenges and present recent progress in statistical methodology to address these challenges.

Genetic and Environmental Contributions to Subcortical Gray Matter Microstructure and Volume in the Developing Brain

Using baseline (ages 9-10) and two-year follow-up (ages 11-12) data from monozygotic and dizygotic twins enrolled in the longitudinal Adolescent Brain Cognitive DevelopmentSM Study, we investigated the genetic and environmental contributions to microstructure and volume of nine subcortical gray matter regions. Microstructure was assessed using diffusion MRI data analyzed using restriction spectrum imaging (RSI) and diffusion tensor imaging (DTI) models. The highest heritability estimates (estimate [95% confidence interval]) for microstructure were found using the RSI model in the pallidum (baseline: 0.859 [0.818, 0.889], follow-up: 0.835 [0.787, 0.871]), putamen (baseline: 0.859 [0.819, 0.889], follow-up: 0.874 [0.838, 0.902]), and thalamus (baseline: 0.855 [0.814, 0.887], follow-up: 0.819 [0.769, 0.857]). For volumes the corresponding regions were the caudate (baseline: 0.831 [0.688, 0.992], follow-up: 0.848 [0.701, 1.011]) and putamen (baseline: 0.906 [0.875, 0.914], follow-up: 0.906 [0.885, 0.923]). The subcortical regions displayed high genetic stability (rA = 0.743-1.000) across time and exhibited unique environmental correlations (rE = 0.194-0.610). Individual differences in both gray matter microstructure and volumes can be largely explained by additive genetic effects in this sample.

Predominant polarity as a neurobiological specifier in bipolar disorder: Evidence from a multimodal neuroimaging study

BACKGROUND

While predominant (PP) and onset polarity (OP) have considerable clinical and treatment implications in bipolar disorder (BD), the neurobiological underpinnings of PP and OP from a radiological perspective remain largely unknown. The main objective of this study is to investigate the neuroanatomical profile of polarity subphenotypes (PP and OP) in euthymic BD patients, using a standardized multimodal neuroimaging protocol to evaluate regional gray matter (GM) volumes, cortical thickness, as well as white matter (WM) integrity of major projection, commissural and association tracts.

METHODS

Forty-two euthymic BD patients stratified for PP and OP and 42 healthy controls (HC) were included in this computational neuroimaging study to comprehensively characterize gray and white matter alterations. Univariate analyses of covariance (ANCOVAs) were conducted with Bonferroni corrections for each MRI modality and Cohen's d effect sizes were calculated for group comparisons.

RESULTS

Phenotype-associated cortical thickness abnormalities and volumetric alterations were identified, but no WM changes ascertained. Specifically, we found a main effect of OP on GM volume of left middle frontal gyrus and of OP and PP (either or both) on cortical thickness of various regions previously implicated in BD, i.e. inferior frontal gyrus-pars opercularis (left) and pars orbitalis (bilateral), left lateral orbitofrontal gyrus, bilateral medial segment of the superior frontal gyrus, left planum polare, right anterior cingulate gyrus, left anterior and posterior insula, bilateral frontal operculum (both OP and PP); left anterior and posterior orbitofrontal gyrus, left transverse temporal gyrus, right posterior insula (only OP); and right medial frontal cortex (only PP). Based on the magnitude of differences on pairwise comparisons, we found a large effect of OP on cortical thickness in a single region (left anterior orbitofrontal gyrus) (OP-M > OP-D), while PP subgroups showed large or medium effect size differences in cortical thickness (PP-M > PP-D) in a wider array of regions (right medial frontal cortex, left frontal operculum, left inferior frontal gyrus-pars opercularis, bilateral medial segment of the superior frontal gyrus). For most regions, PP-D patients showed the greatest decreases in cortical thickness compared to HC while PP-M showed the smallest, with PP-U showing an "unspecified" pattern mostly lying in-between PP-D and PP-M.

CONCLUSIONS

Our multimodal imaging findings suggest specific polarity BD subgroups with compromised cortical thickness; we recorded a greater impact of PP on brain structure compared to OP, which provides additional evidence that PP can be considered as a neurobiological specifier in BD.

Transcriptional substrates of brain structural and functional impairments in drug-naive first-episode patients with major depressive disorder

BACKGROUND

Despite remarkable success in identifying genetic risk factors for depression, there are still open questions about the exact genetic mechanisms underlying certain disease phenotypes, such as brain structural and functional impairments.

METHODS

Comprehensive multi-modal neuroimaging meta-analyses were conducted to examine changes in brain structure and function in drug-naive first-episode patients with major depressive disorder (DF-MDD). Combined with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were performed to identify genes whose expression related to these brain structural and functional changes, followed by a range of gene functional signature analyses.

RESULTS

Meta-analyses revealed gray matter atrophy in the insula, temporal pole, cerebellum and postcentral gyrus, and a complex pattern of hyper-function in the temporal pole and hypo-function in the cuneus/precuneus, angular gyrus and lingual gyrus in DF-MDD. Moreover, these brain structural and functional changes were spatially associated with the expression of 1194 and 1733 genes, respectively. Importantly, there were commonalities and differences in the two gene sets and their functional signatures including functional enrichment, specific expression, behavioral relevance, and constructed protein-protein interaction networks.

LIMITATIONS

The results merit further verification using a large sample of DF-MDD.

CONCLUSIONS

Our findings not only corroborate the polygenic nature of depression, but also suggest common and distinct genetic modulations of brain structural and functional impairments in this disorder.

Network evolution of regional brain volumes in young children reflects neurocognitive scores and mother's education

The maturation of regional brain volumes from birth to preadolescence is a critical developmental process that underlies emerging brain structural connectivity and function. Regulated by genes and environment, the coordinated growth of different brain regions plays an important role in cognitive development. Current knowledge about structural network evolution is limited, partly due to the sparse and irregular nature of most longitudinal neuroimaging data. In particular, it is unknown how factors such as mother's education or sex of the child impact the structural network evolution. To address this issue, we propose a method to construct evolving structural networks and study how the evolving connections among brain regions as reflected at the network level are related to maternal education and biological sex of the child and also how they are associated with cognitive development. Our methodology is based on applying local Fréchet regression to longitudinal neuroimaging data acquired from the RESONANCE cohort, a cohort of healthy children (245 females and 309 males) ranging in age from 9 weeks to 10 years. Our findings reveal that sustained highly coordinated volume growth across brain regions is associated with lower maternal education and lower cognitive development. This suggests that higher neurocognitive performance levels in children are associated with increased variability of regional growth patterns as children age.

Genetic and Environmental Variation in Continuous Phenotypes in the ABCD Study®

Twin studies yield valuable insights into the sources of variation, covariation and causation in human traits. The ABCD Study® (abcdstudy.org) was designed to take advantage of four universities known for their twin research, neuroimaging, population-based sampling, and expertise in genetic epidemiology so that representative twin studies could be performed. In this paper we use the twin data to: (i) provide initial estimates of heritability for the wide range of phenotypes assessed in the ABCD Study using a consistent direct variance estimation approach, assuring that both data and methodology are sound; and (ii) provide an online resource for researchers that can serve as a reference point for future behavior genetic studies of this publicly available dataset. Data were analyzed from 772 pairs of twins aged 9-10 years at study inception, with zygosity determined using genotypic data, recruited and assessed at four twin hub sites. The online tool provides twin correlations and both standardized and unstandardized estimates of additive genetic, and environmental variation for 14,500 continuously distributed phenotypic features, including: structural and functional neuroimaging, neurocognition, personality, psychopathology, substance use propensity, physical, and environmental trait variables. The estimates were obtained using an unconstrained variance approach, so they can be incorporated directly into meta-analyses without upwardly biasing aggregate estimates. The results indicated broad consistency with prior literature where available and provided novel estimates for phenotypes without prior twin studies or those assessed at different ages. Effects of site, self-identified race/ethnicity, age and sex were statistically controlled. Results from genetic modeling of all 53,172 continuous variables, including 38,672 functional MRI variables, will be accessible via the user-friendly open-access web interface we have established, and will be updated as new data are released from the ABCD Study. This paper provides an overview of the initial results from the twin study embedded within the ABCD Study, an introduction to the primary research domains in the ABCD study and twin methodology, and an evaluation of the initial findings with a focus on data quality and suitability for future behavior genetic studies using the ABCD dataset. The broad introductory material is provided in recognition of the multidisciplinary appeal of the ABCD Study. While this paper focuses on univariate analyses, we emphasize the opportunities for multivariate, developmental and causal analyses, as well as those evaluating heterogeneity by key moderators such as sex, demographic factors and genetic background.

Neuroimaging Genetics and Network Analysis in Alzheimer's Disease

The issue of the genetics in brain imaging phenotypes serves as a crucial link between two distinct scientific fields: neuroimaging genetics (NG). The articles included here provide solid proof that this NG link has considerable synergy. There is a suitable collection of articles that offer a wide range of viewpoints on how genetic variations affect brain structure and function. They serve as illustrations of several study approaches used in contemporary genetics and neuroscience. Genome-wide association studies and candidate-gene association are two examples of genetic techniques. Cortical gray matter structural/volumetric measures from magnetic resonance imaging (MRI) are sources of information on brain phenotypes. Together, they show how various scientific disciplines have benefited from significant technological advances, such as the single-nucleotide polymorphism array in genetics and the development of increasingly higher-resolution MRI imaging. Moreover, we discuss NG's contribution to expanding our knowledge about the heterogeneity within Alzheimer's disease as well as the benefits of different network analyses.

Longitudinal Effects of Asymptomatic C9orf72 Carriership on Brain Morphology

OBJECTIVE

We investigated effects of C9orf72 repeat expansion and gene expression on longitudinal cerebral changes before symptom onset.

METHODS

We enrolled 79 asymptomatic family members (AFMs) from 9 families with C9orf72 repeat expansion. Twenty-eight AFMs carried the mutation (C9+). Participants had up to 3 magnetic resonance imaging (MRI) scans, after which we compared motor cortex and motor tracts between C9+ and C9- AFMs using mixed effects models, incorporating kinship to correct for familial relations and lessen effects of other genetic factors. We also compared cortical, subcortical, cerebellar, and connectome structural measurements in a hypothesis-free analysis. We correlated regional C9orf72 expression in donor brains with the pattern of cortical thinning in C9+ AFMs using meta-regression. For comparison, we included 42 C9+ and 439 C9- patients with amyotrophic lateral sclerosis (ALS) in this analysis.

RESULTS

C9+ AFM motor cortex had less gyrification and was thinner than in C9- AFMs, without differences in motor tracts. Whole brain analysis revealed thinner cortex and less gyrification in parietal, occipital, and temporal regions, smaller thalami and right hippocampus, and affected frontotemporal connections. Thinning of bilateral precentral, precuneus, and left superior parietal cortex was faster in C9+ than in C9- AFMs. Higher C9orf72 expression correlated with thinner cortex in both C9+ AFMs and C9+ ALS patients.

INTERPRETATION

In asymptomatic C9orf72 repeat expansion carriers, brain MRI reveals widespread features suggestive of impaired neurodevelopment, along with faster decline of motor and parietal cortex than found in normal aging. C9orf72 expression might play a role in cortical development, and consequently explain the specific brain abnormalities of mutation carriers. ANN NEUROL 2022.

Heritability of Subcortical Grey Matter Structures

Background and Objectives: Subcortical grey matter structures play essential roles in cognitive, affective, social, and motoric functions in humans. Their volume changes with age, and decreased volumes have been linked with many neuropsychiatric disorders. The aim of our study was to examine the heritability of six subcortical brain volumes (the amygdala, caudate nucleus, pallidum, putamen, thalamus, and nucleus accumbens) and four general brain volumes (the total intra-cranial volume and the grey matter, white matter, and cerebrospinal fluid (CSF) volume) in twins. Materials and Methods: A total of 118 healthy adult twins from the Hungarian Twin Registry (86 monozygotic and 32 dizygotic; median age 50 ± 27 years) underwent brain magnetic resonance imaging. Two automated volumetry pipelines, Computational Anatomy Toolbox 12 (CAT12) and volBrain, were used to calculate the subcortical and general brain volumes from three-dimensional T1-weighted images. Age- and sex-adjusted monozygotic and dizygotic intra-pair correlations were calculated, and the univariate ACE model was applied. Pearson's correlation test was used to compare the results obtained by the two pipelines. Results: The age- and sex-adjusted heritability estimates, using CAT12 for the amygdala, caudate nucleus, pallidum, putamen, and nucleus accumbens, were between 0.75 and 0.95. The thalamus volume was more strongly influenced by common environmental factors (C = 0.45-0.73). The heritability estimates, using volBrain, were between 0.69 and 0.92 for the nucleus accumbens, pallidum, putamen, right amygdala, and caudate nucleus. The left amygdala and thalamus were more strongly influenced by common environmental factors (C = 0.72-0.85). A strong correlation between CAT12 and volBrain (r = 0.74-0.94) was obtained for all volumes. Conclusions: The majority of examined subcortical volumes appeared to be strongly heritable. The thalamus was more strongly influenced by common environmental factors when investigated with both segmentation methods. Our results underline the importance of identifying the relevant genes responsible for variations in the subcortical structure volume and associated diseases.

Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives

Cortical morphology is a key determinant of cognitive ability and mental health. Its development is a highly intricate process spanning decades, involving the coordinated, localized expression of thousands of genes. We are now beginning to unravel the genetic architecture of cortical morphology, thanks to the recent availability of large-scale neuroimaging and genomic data and the development of powerful biostatistical tools. Here, we review the progress made in this field, providing an overview of the lessons learned from genetic studies of cortical volume, thickness, surface area, and folding as captured by neuroimaging. It is now clear that morphology is shaped by thousands of genetic variants, with effects that are region- and time-dependent, thereby challenging conventional study approaches. The most recent genome-wide association studies have started discovering common genetic variants influencing cortical thickness and surface area, yet together these explain only a fraction of the high heritability of these measures. Further, the impact of rare variants and non-additive effects remains elusive. There are indications that the quickly increasing availability of data from whole-genome sequencing and large, deeply phenotyped population cohorts across the lifespan will enable us to uncover much of the missing heritability in the upcoming years. Novel approaches leveraging shared information across measures will accelerate this process by providing substantial increases in statistical power, together with more accurate mapping of genetic relationships. Important challenges remain, including better representation of understudied demographic groups, integration of other 'omics data, and mapping of effects from gene to brain to behavior across the lifespan.

Identifying genes associated with brain volumetric differences through tissue specific transcriptomic inference from GWAS summary data

BACKGROUND

Brain volume has been widely studied in the neuroimaging field, since it is an important and heritable trait associated with brain development, aging and various neurological and psychiatric disorders. Genome-wide association studies (GWAS) have successfully identified numerous associations between genetic variants such as single nucleotide polymorphisms and complex traits like brain volume. However, it is unclear how these genetic variations influence regional gene expression levels, which may subsequently lead to phenotypic changes. S-PrediXcan is a tissue-specific transcriptomic data analysis method that can be applied to bridge this gap. In this work, we perform an S-PrediXcan analysis on GWAS summary data from two large imaging genetics initiatives, the UK Biobank and Enhancing Neuroimaging Genetics through Meta Analysis, to identify tissue-specific transcriptomic effects on two closely related brain volume measures: total brain volume (TBV) and intracranial volume (ICV).

RESULTS

As a result of the analysis, we identified 10 genes that are highly associated with both TBV and ICV. Nine out of 10 genes were found to be associated with TBV in another study using a different gene-based association analysis. Moreover, most of our discovered genes were also found to be correlated with multiple cognitive and behavioral traits. Further analyses revealed the protein-protein interactions, associated molecular pathways and biological functions that offer insight into how these genes function and interact with others.

CONCLUSIONS

These results confirm that S-PrediXcan can identify genes with tissue-specific transcriptomic effects on complex traits. The analysis also suggested novel genes whose expression levels are related to brain volumetric traits. This provides important insights into the genetic mechanisms of the human brain.

Cognitive control inhibition networks in adulthood are impaired by early iron deficiency in infancy

Iron deficiency, a common form of micronutrient deficiency, primarily affects children and women. The principal cause of iron deficiency is undernutrition in low-income countries and malnutrition in middle to upper income regions. Iron is a key element for myelin production, neuronal metabolism, and dopamine functions. Iron deficiency in early life can alter brain development and exert long-lasting effects. Control inhibition is an executive function that involves several brain regions, including the prefrontal cortex and caudate and sub-thalamic nuclei. Dopamine is the prevalent neurotransmitter underlying cognitive inhibition. We followed cohort study participants who had iron deficiency anemia in infancy as well non-anemic controls. At 22 years of age, the participants were subjected to functional magnetic resonance imaging (fMRI) to evaluate the correlation between functional connectivity and performance on an inhibitory cognitive task (Go/No-Go). We hypothesized that former iron deficient anemic (FIDA) participants demonstrate less strength in functional connectivity compared with controls (C). There were not significant group differences in the behavioral results in terms of accuracy and response time. A continuous covariate interaction analysis of functional connectivity and the Go/No-Go scores demonstrated significant differences between the FIDA and C groups. The FIDA participants demonstrated less strength in connectivity in brain regions related to control inhibition, including the medial temporal lobe, impairment in the integration of the default mode network (indicating decreased attention and alertness), and an increase in connectivity in posterior brain areas, all of which suggest slower circuitry maturation. The results support the hypothesis that FIDA young adults show differences in the connectivity of networks related to executive functions. These differences could increase their vulnerability to develop cognitive dysfunctions or mental disorders in adulthood.

Orbitofrontal cortex volume links polygenic risk for smoking with tobacco use in healthy adolescents

BACKGROUND

Tobacco smoking remains one of the leading causes of preventable illness and death and is heritable with complex underpinnings. Converging evidence suggests a contribution of the polygenic risk for smoking to the use of tobacco and other substances. Yet, the underlying brain mechanisms between the genetic risk and tobacco smoking remain poorly understood.

METHODS

Genomic, neuroimaging, and self-report data were acquired from a large cohort of adolescents from the IMAGEN study (a European multicenter study). Polygenic risk scores (PGRS) for smoking were calculated based on a genome-wide association study meta-analysis conducted by the Tobacco and Genetics Consortium. We examined the interrelationships among the genetic risk for smoking initiation, brain structure, and the number of occasions of tobacco use.

RESULTS

A higher smoking PGRS was significantly associated with both an increased number of occasions of tobacco use and smaller cortical volume of the right orbitofrontal cortex (OFC). Furthermore, reduced cortical volume within this cluster correlated with greater tobacco use. A subsequent path analysis suggested that the cortical volume within this cluster partially mediated the association between the genetic risk for smoking and the number of occasions of tobacco use.

CONCLUSIONS

Our data provide the first evidence for the involvement of the OFC in the relationship between smoking PGRS and tobacco use. Future studies of the molecular mechanisms underlying tobacco smoking should consider the mediation effect of the related neural structure.

Efficacy of transcranial Direct Current Stimulation (tDCS) combined with intensive speech therapy for language production in monozygotic twins with corpus callosum dysgenesis (CCD): A sham-controlled single subject study

The purpose of this single subject study was to investigate whether transcranial direct current stimulation (tDCS) applied to both hemispheres combined with speech therapy can improve language learning in a pair of 5-year-old twins with corpus callosum dysgenesis (CCD). The treatment protocol included anodal tDCS with simultaneous speech therapy in one of the participants (T.D.), and sham-tDCS with the same montage, and stimulation regime concomitant with speech therapy for the other twin (A.D.). Our findings show that T.D. improved in language production when treated with speech therapy in combination with tDCS. A.D. showed evidence for a relatively minor behavioral benefit from speech therapy.

Genetic common variants associated with cerebellar volume and their overlap with mental disorders: a study on 33,265 individuals from the UK-Biobank

Interest in the cerebellum is expanding given evidence of its contributions to cognition and emotion, and dysfunction in various psychopathologies. However, research into its genetic architecture and shared influences with liability for mental disorders is lacking. We conducted a genome-wide association study (GWAS) of total cerebellar volume and underlying cerebellar lobe volumes in 33,265 UK-Biobank participants. Total cerebellar volume was heritable (h2SNP = 50.6%), showing moderate genetic homogeneity across lobes (h2SNP from 35.4% to 57.1%; mean genetic correlation between lobes rg ≈ 0.44). We identified 33 GWAS signals associated with total cerebellar volume, of which 6 are known to alter protein-coding gene structure, while a further five mapped to genomic regions known to alter cerebellar tissue gene expression. Use of summary data-based Mendelian randomisation further prioritised genes whose change in expression appears to mediate the SNP-trait association. In total, we highlight 21 unique genes of greatest interest for follow-up analyses. Using LD-regression, we report significant genetic correlations between total cerebellar volume and brainstem, pallidum and thalamus volumes. While the same approach did not result in significant correlations with psychiatric phenotypes, we report enrichment of schizophrenia, bipolar disorder and autism spectrum disorder associated signals within total cerebellar GWAS results via conditional and conjunctional-FDR analysis. Via these methods and GWAS catalogue, we identify which of our cerebellar genomic regions also associate with psychiatric traits. Our results provide important insights into the common allele architecture of cerebellar volume and its overlap with other brain volumes and psychiatric phenotypes.

Multivariate Genetic Structure of Externalizing Behavior and Structural Brain Development in a Longitudinal Adolescent Twin Sample

Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers, and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and the brain volumes and white matter integrity (fractional anisotropy [FA] and mean diffusivity [MD]) with magnetic resonance imaging in the BrainSCALE cohort, which consisted of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years for the twins. Genetic covariance modeling based on the classical twin design, extended to also include siblings of twins, showed that genes influence externalizing behavior and changes therein (h² up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation r_ph up to +0.20) and lower MD (r_ph up to −0.20), with sizeable genetic correlations (FA r_a up to +0.42; MD r_a up to −0.33). The cortical gray matter (CGM; r_ph up to −0.20) and cerebral white matter (CWM; r_ph up to +0.20) volume were phenotypically but not genetically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence of the same genetic factor.

What Has Been Learned from Using EEG Methods in Research of ADHD?

Electrophysiological recording methods, including electroencephalography (EEG) and magnetoencephalography (MEG), have an unparalleled capacity to provide insights into the timing and frequency (spectral) composition of rapidly changing neural activity associated with various cognitive processes. The current chapter provides an overview of EEG studies examining alterations in brain activity in ADHD, measured both at rest and during cognitive tasks. While EEG resting state studies of ADHD indicate no universal alterations in the disorder, event-related studies reveal consistent deficits in attentional and inhibitory control and consequently inform the proposed cognitive models of ADHD. Similar to other neuroimaging measures, EEG research indicates alterations in multiple neural circuits and cognitive functions. EEG methods - supported by the constant refinement of analytic strategies - have the potential to contribute to improved diagnostics and interventions for ADHD, underlining their clinical utility.

Association of subcortical gray-matter volumes with life-course-persistent antisocial behavior in a population-representative longitudinal birth cohort

Neuropsychological evidence supports the developmental taxonomy theory of antisocial behavior, suggesting that abnormal brain development distinguishes life-course-persistent from adolescence-limited antisocial behavior. Recent neuroimaging work confirmed that prospectively-measured life-course-persistent antisocial behavior is associated with differences in cortical brain structure. Whether this extends to subcortical brain structures remains uninvestigated. This study compared subcortical gray-matter volumes between 672 members of the Dunedin Study previously defined as exhibiting life-course-persistent, adolescence-limited or low-level antisocial behavior based on repeated assessments at ages 7-26 years. Gray-matter volumes of 10 subcortical structures were compared across groups. The life-course-persistent group had lower volumes of amygdala, brain stem, cerebellum, hippocampus, pallidum, thalamus, and ventral diencephalon compared to the low-antisocial group. Differences between life-course-persistent and adolescence-limited individuals were comparable in effect size to differences between life-course-persistent and low-antisocial individuals, but were not statistically significant due to less statistical power. Gray-matter volumes in adolescence-limited individuals were near the norm in this population-representative cohort and similar to volumes in low-antisocial individuals. Although this study could not establish causal links between brain volume and antisocial behavior, it constitutes new biological evidence that all people with antisocial behavior are not the same, supporting a need for greater developmental and diagnostic precision in clinical, forensic, and policy-based interventions.

Polygenic Architecture of Human Neuroanatomical Diversity

We analyzed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26 000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r ~ 0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes (~51%) captured ~1.5 times more genetic variance than the rest, and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF <5% captured <one fourth of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG ~ 0.45. Genetic correlations were similar to phenotypic and environmental correlations; however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available athttps://github.com/neuroanatomy/genomic-architecture.

Intergenerational transmission of the patterns of functional and structural brain networks

There is clear evidence of intergenerational transmission of life values, cognitive traits, psychiatric disorders, and even aspects of daily decision making. To investigate biological substrates of this phenomenon, the brain has received increasing attention as a measurable biomarker and potential target for intervention. However, no previous study has quantitatively and comprehensively investigated the effects of intergenerational transmission on functional and structural brain networks. Here, by employing an unusually large cohort dataset (N = 84 parent-child dyads; 45 sons, 39 daughters, 81 mothers, and 3 fathers), we show that patterns of functional and structural brain networks are preserved over a generation. We also demonstrate that several demographic factors and behavioral/physiological phenotypes have a relationship with brain similarity. Collectively, our results provide a comprehensive picture of neurobiological substrates of intergenerational transmission and demonstrate the usability of our dataset for investigating the neurobiological substrates of intergenerational transmission.

Diffusion MRI derived free-water imaging measures in patients with schizophrenia and their non-psychotic siblings

Free-water imaging is a diffusion MRI technique that separately models water diffusion hindered by fiber tissue and water that disperses freely in the extracellular space. Studies using this technique have shown that schizophrenia is characterized by a lower level of fractional anisotropy of the tissue compartment (FA_t) and higher free-water fractional volume (FW). It is unknown, however, whether such abnormalities are an expression of pre-existing (genetic) risk for schizophrenia or a manifestation of the illness. To investigate the contribution of familial risk factors to white matter abnormalities, we used the free-water imaging technique to assess FA_t and FW in a large cohort of 471 participants including 161 patients with schizophrenia, 182 non-psychotic siblings, and 128 healthy controls. In this sample, patients did not show significant differences in FA_t as compared to controls, but did exhibit a higher level of FW relative to both controls and siblings in the left uncinate fasciculus, superior corona radiata and fornix / stria terminalis. This increase in FW was found to be related to, though not solely explained by, ventricular enlargement. Siblings did not show significant FW abnormalities. However, siblings did show a higher level of FA_t as compared to controls and patients, in line with results of a previous study on the same data using conventional DTI. Taken together, our findings suggest that extracellular free-water accumulation in patients is likely a manifestation of established disease rather than an expression of familial risk for schizophrenia and that super-normal levels of FA_t in unaffected siblings may reflect a compensatory process.

Smaller total brain volume but not subcortical structure volume related to common genetic risk for ADHD

BACKGROUND

Mechanistic endophenotypes can inform process models of psychopathology and aid interpretation of genetic risk factors. Smaller total brain and subcortical volumes are associated with attention-deficit hyperactivity disorder (ADHD) and provide clues to its development. This study evaluates whether common genetic risk for ADHD is associated with total brain volume (TBV) and hypothesized subcortical structures in children.

METHODS

Children 7-15 years old were recruited for a case-control study (N = 312, N = 199 ADHD). Children were assessed with a multi-informant, best-estimate diagnostic procedure and motion-corrected MRI measured brain volumes. Polygenic scores were computed based on discovery data from the Psychiatric Genomics Consortium (N = 19 099 ADHD, N = 34 194 controls) and the ENIGMA + CHARGE consortium (N = 26 577).

RESULTS

ADHD was associated with smaller TBV, and altered volumes of caudate, cerebellum, putamen, and thalamus after adjustment for TBV; however, effects were larger and statistically reliable only in boys. TBV was associated with an ADHD polygenic score [β = -0.147 (-0.27 to -0.03)], and mediated a small proportion of the effect of polygenic risk on ADHD diagnosis (average ACME = 0.0087, p = 0.012). This finding was stronger in boys (average ACME = 0.019, p = 0.008). In addition, we confirm genetic variation associated with whole brain volume, via an intracranial volume polygenic score.

CONCLUSION

Common genetic risk for ADHD is not expressed primarily as developmental alterations in subcortical brain volumes, but appears to alter brain development in other ways, as evidenced by TBV differences. This is among the first demonstrations of this effect using molecular genetic data. Potential sex differences in these effects warrant further examination.

Evaluating endophenotypes for bipolar disorder

BACKGROUND

Phenotypic heterogeneity is a major impediment to the elucidation of the neurobiology and genetics of bipolar disorder. Endophenotype could help in reducing heterogeneity by defining biological traits that are more direct expressions of gene effects. The aim of this review is to examine the recent literature on clinical, epidemiological, neurobiological, and genetic findings and to select and evaluate candidate endophenotypes for bipolar disorder. Evaluating putative endophenotype could be helpful in better understanding the neurobiology of bipolar disorder by improving the definition of bipolar-related phenotypes in genetic studies. In this manner, research on endophenotypes could be useful to improve psychopathological diagnostics in the long-run by dissecting psychiatric macro phenotypes into biologically valid components.

MAIN BODY

The associations among the psychopathological and biological endophenotypes are discussed with respect to specificity, temporal stability, heritability, familiarity, and clinical and biological plausibility. Numerous findings regarding brain function, brain structure, neuropsychology and altered neurochemical pathways in patients with bipolar disorder and their relatives deserve further investigation. Overall, major findings suggest a developmental origin of this disorder as all the candidate endophenotypes that we have been able to select are present both in the early stages of the disorder as well as in subjects at risk.

CONCLUSIONS

Among the stronger candidate endophenotypes, we suggest circadian rhythm instability, dysmodulation of emotion and reward, altered neuroimmune state, attention and executive dysfunctions, anterior cingulate cortex thickness and early white matter abnormalities. In particular, early white matter abnormalities could be the result of a vulnerable brain on which new stressors are added in young adulthood which favours the onset of the disorder. Possible pathways that lead to a vulnerable brain are discussed starting from the data about molecular and imaging endophenotypes of bipolar disorder.

Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits

Structural variations of the human brain are heritable and highly polygenic traits, with hundreds of associated genes identified in recent genome-wide association studies (GWAS). Transcriptome-wide association studies (TWAS) can both prioritize these GWAS findings and also identify additional gene-trait associations. Here we perform cross-tissue TWAS analysis of 211 structural neuroimaging and discover 278 associated genes exceeding Bonferroni significance threshold of 1.04 × 10-8. The TWAS-significant genes for brain structures have been linked to a wide range of complex traits in different domains. Through TWAS gene-based polygenic risk scores (PRS) prediction, we find that TWAS PRS gains substantial power in association analysis compared to conventional variant-based GWAS PRS, and up to 6.97% of phenotypic variance (p-value = 7.56 × 10-31) can be explained in independent testing data sets. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction.

Gray Matter Volume in Elderly adults With ADHD: Associations of Symptoms and Comorbidities With Brain Structures

Objective: To investigate total and selected region-of-interest-based gray matter volume (GMV) in older adults with ADHD. Method: Twenty-five elderly (≥65 years old) patients with ADHD and 34 healthy controls underwent 1.5-T magnetic resonance imaging (MRI). We used voxel-based morphometry to compare GMV between groups and performed a correlation analysis with ADHD symptoms and comorbidities. Results: Findings revealed a smaller total GMV in males with ADHD and a smaller GMV in the right medial frontal orbital area extending toward the medial frontal superior, the frontal superior, and the subgenual anterior cingulate cortex (ACC) besides correlations between inattentiveness and ACC (bilaterally) and left cerebellum, hyperactivity/impulsivity and the left frontal inferior orbital, depression and caudate (bilaterally), and the right inferior parietal lobule. Conclusion: Neural correlates in regions related to attention, executive control, and affective processing suggest that impairments in frontostriatal and frontoparietal-cerebellar areas observed in adults with ADHD persist into old age.

Overlap in genetic risk for cross-disorder vulnerability to mental disorders and genetic risk for altered subcortical brain volumes

BACKGROUND

There have been considerable recent advances in understanding the genetic architecture of psychiatric disorders as well as the underlying neurocircuitry. However, there is little work on the concordance of genetic variations that increase risk for cross-disorder vulnerability, and those that influence subcortical brain structures. We undertook a genome-wide investigation of the genetic overlap between cross-disorder vulnerability to psychiatric disorders (p-factor) and subcortical brain structures.

METHODS

Summary statistics were obtained from the PGC cross-disorder genome-wide association study (GWAS) (N_case= 232,964, N_control= 494,162) and the CHARGE-ENIGMA subcortical brain volumes GWAS (N=38,851). SNP effect concordance analysis (SECA) was used to assess pleiotropy and concordance. Linkage Disequilibrium (LD) Score Regression and ρ-HESS were used to assess genetic correlation and conditional false discovery (cFDR) was used to identify variants associated with p-factor, conditional on the variants association with subcortical brain volumes.

RESULTS

Evidence of global pleiotropy between p-factor and all subcortical brain regions was observed. Risk variants for p-factor correlated negatively with brainstem. A total of 787 LD-independent variants were significantly associated with p-factor when conditioned on the subcortical GWAS results. Gene set enrichment analysis of these variants implicated actin binding and neuronal regulation.

LIMITATIONS

SECA could be biased due to the potential presence of overlapping study participants in the p-factor and subcortical GWASs.

CONCLUSION

Findings of genome-wide pleiotropy and possible concordance between genetic variants that contribute to p-factor and smaller brainstem volumes, are consistent with previous work. cFDR results highlight actin binding and neuron regulation as key underlying mechanisms. Further fine-grained delineation of these mechanisms is needed to advance the field.

MRI-assessed locus coeruleus integrity is heritable and associated with multiple cognitive domains, mild cognitive impairment, and daytime dysfunction

Introduction

The locus coeruleus (LC) undergoes extensive neurodegeneration in early Alzheimer's disease (AD). The LC is implicated in regulating the sleep–wake cycle, modulating cognitive function, and AD progression.

Methods

Participants were 481 men (ages 62 to 71.7) from the Vietnam Era Twin Study of Aging. LC structural integrity was indexed by neuromelanin‐sensitive magnetic resonance imaging (MRI) contrast‐to‐noise ratio (LC_CNR). We examined LC_CNR, cognition, amnestic mild cognitive impairment (aMCI), and daytime dysfunction.

Results

Heritability of LC_CNR was .48. Participants with aMCI showed greater daytime dysfunction. Lower LC_CNR was associated with poorer episodic memory, general verbal fluency, semantic fluency, and processing speed, as well as increased odds of aMCI and greater daytime dysfunction.

Discussion

Reduced LC integrity is associated with widespread differences across cognitive domains, daytime sleep‐related dysfunction, and risk for aMCI. These findings in late‐middle‐aged adults highlight the potential of MRI‐based measures of LC integrity in early identification of AD risk.

Psychiatric neuroimaging research in Brazil: historical overview, current challenges, and future opportunities

The last four decades have witnessed tremendous growth in research studies applying neuroimaging methods to evaluate pathophysiological and treatment aspects of psychiatric disorders around the world. This article provides a brief history of psychiatric neuroimaging research in Brazil, including quantitative information about the growth of this field in the country over the past 20 years. Also described are the various methodologies used, the wealth of scientific questions investigated, and the strength of international collaborations established. Finally, examples of the many methodological advances that have emerged in the field of in vivo neuroimaging are provided, with discussion of the challenges faced by psychiatric research groups in Brazil, a country of limited resources, to continue incorporating such innovations to generate novel scientific data of local and global relevance.

Effects of the dopamine transporter gene on neuroimaging findings in different attention deficit hyperactivity disorder presentations

Attention-Deficit/Hyperactivity Disorder (ADHD) is a phenotipically and neurobiologically heterogeneous disorder. Deficiencies at different levels in response inhibition, differences in dopamine transporter genotype (DAT1) and various symptomatic presentations contribute to ADHD heterogeneity. Integrating these three aspects into a functional neuroimaging research could help unreval specific neurobiological components of more phenotipically homogeneous groups of patients with ADHD. During the Go-NoGo trial, we investigated the effect of the DAT1 gene using 3 T MRI in 72 ADHD cases and 24 (TD) controls that typically developed between the ages 8 and 15 years. In the total ADHD group, DAT1 predicted homozygosity for the 10R allele and hypoactivation in the anterior cingulate cortex and paracingulate cortex. There were no significant activation differences between DAT1 10R/10R homozygotes and 9R carriers in TD controls. Subjects with predominantly inattentive ADHD (ADHD-I) presentation with DAT1 10R/10R homozygous reduced neuronal activation during Go trial particularly in the frontal regions and insular cortex, and in the parietal regions during NoGo trial (brain regions reported as part of Default Mode Network- DMN). Additionally, DAT1 10R/10R homozygousness was associated with increased occipital zone activation during only the Go trial in the ADHD combined presentation (ADHD-C) group. Our results point the three main findings: 1) The DAT1 gene is 10R homozygous for differentiated brain activation in ADHD cases but not in the TD controls, supporting the DAT1 gene as a potential marker for ADHD, 2) The relationship between the DAT1 gene and the occipital regions in ADHD-C group which may reflect compensatory mechanisms, 3) The relationship between DAT1 gene and the reduced DMN suppression for 9R carriers probabaly stems from the ADHD-I group.

Heritability of Structural Patterning in the Human Cerebral Cortex

Genetic influences that govern the spatial patterning of the human cortex and its structural variability are still incompletely known. We analyzed structural MR images in twins, siblings, and pairs of unrelated subjects. A comprehensive set of methods was employed to quantify properties of cortical features at different spatial scales. Measures were used to assess the influence of genetic similarity on structural patterning. Results indicated that: (1) Genetic effects significantly influence all structural features assessed here at all spatial resolutions, albeit at different strengths. (2) While strong genetic effects were found at the whole-brain and hemisphere level, effects were weaker at the regional and vertex level, depending on the measure under study. (3) Besides cortical thickness, sulcal (geodesic) depth was found to be under strong genetic control. The local pattern indicated that two axes along (a) the anterior-posterior direction (insula to parieto-occipital sulcus), and (b) superior-inferior direction (central sulcus to callosal sulcus) presumably determine the segregation of four quadrants in each hemisphere early in development. (4) While strong structural asymmetries were found at the regional level, genetic influences on laterality were relatively minor.

Genetic and environmental influences on structural brain measures in twins with autism spectrum disorder

Atypical growth patterns of the brain have been previously reported in autism spectrum disorder (ASD) but these alterations are heterogeneous across individuals, which may be associated with the variable effects of genetic and environmental influences on brain development. Monozygotic (MZ) and dizygotic (DZ) twin pairs with and without ASD (aged 6-15 years) were recruited to participate in this study. T1-weighted MRIs (n = 164) were processed with FreeSurfer to evaluate structural brain measures. Intra-class correlations were examined within twin pairs and compared across diagnostic groups. ACE modeling was also completed. Structural brain measures, including cerebral and cerebellar gray matter (GM) and white matter (WM) volume, surface area, and cortical thickness, were primarily influenced by genetic factors in TD twins; however, mean curvature appeared to be primarily influenced by environmental factors. Similarly, genetic factors accounted for the majority of variation in brain size in twins with ASD, potentially to a larger extent regarding curvature and subcortical GM; however, there were also more environmental contributions in twins with ASD on some structural brain measures, such that cortical thickness and cerebellar WM volume were primarily influenced by environmental factors. These findings indicate potential neurobiological outcomes of the genetic and environmental risk factors that have been previously associated with ASD and, although preliminary, may help account for some of the previously outlined neurobiological heterogeneity across affected individuals. This is especially relevant regarding the role of genetic and environmental factors in the development of ASD, in which certain brain structures may be more sensitive to specific influences.

Sex-specific association between infant caudate volumes and a polygenic risk score for major depressive disorder

Polygenic risk scores for major depressive disorder (PRS-MDD) have been identified in large genome-wide association studies, and recent findings suggest that PRS-MDD might interact with environmental risk factors to shape human limbic brain development as early as in the prenatal period. Striatal structures are crucially involved in depression; however, the association of PRS-MDD with infant striatal volumes is yet unknown. In this study, 105 Finnish mother-infant dyads (44 female, 11-54 days old) were investigated to reveal how infant PRS-MDD is associated with infant dorsal striatal volumes (caudate, putamen) and whether PRS-MDD interacts with prenatal maternal depressive symptoms (Edinburgh Postnatal Depression Scale, gestational weeks 14, 24, 34) on infant striatal volumes. A robust sex-specific main effect of PRS-MDD on bilateral infant caudate volumes was observed. PRS-MDD were more positively associated with caudate volumes in boys compared to girls. No significant interaction effects of genotype PRS-MDD with the environmental risk factor "prenatal maternal depressive symptoms" (genotype-by-environment interaction) nor significant interaction effects of genotype with prenatal maternal depressive symptoms and sex (genotype-by-environment-by-sex interaction) were found for infant dorsal striatal volumes. Our study showed that a higher PRS-MDD irrespective of prenatal exposure to maternal depressive symptoms is associated with smaller bilateral caudate volumes, an indicator of greater susceptibility to major depressive disorder, in female compared to male infants. This sex-specific polygenic effect might lay the ground for the higher prevalence of depression in women compared to men.

Interhemispheric Relationship of Genetic Influence on Human Brain Connectivity

To understand the origins of interhemispheric differences and commonalities/coupling in human brain wiring, it is crucial to determine how homologous interregional connectivities of the left and right hemispheres are genetically determined and related. To address this, in the present study, we analyzed human twin and pedigree samples with high-quality diffusion magnetic resonance imaging tractography and estimated the heritability and genetic correlation of homologous left and right white matter (WM) connections. The results showed that the heritability of WM connectivity was similar and coupled between the 2 hemispheres and that the degree of overlap in genetic factors underlying homologous WM connectivity (i.e., interhemispheric genetic correlation) varied substantially across the human brain: from complete overlap to complete nonoverlap. Particularly, the heritability was significantly stronger and the chance of interhemispheric complete overlap in genetic factors was higher in subcortical WM connections than in cortical WM connections. In addition, the heritability and interhemispheric genetic correlations were stronger for long-range connections than for short-range connections. These findings highlight the determinants of the genetics underlying WM connectivity and its interhemispheric relationships, and provide insight into genetic basis of WM connectivity asymmetries in both healthy and disease states.

Biological aging in childhood and adolescence following experiences of threat and deprivation: A systematic review and meta-analysis

Life history theory argues that exposure to early life adversity (ELA) accelerates development, although existing evidence for this varies. We present a meta-analysis and systematic review testing the hypothesis that ELA involving threat (e.g., violence exposure) will be associated with accelerated biological aging across multiple metrics, whereas exposure to deprivation (e.g., neglect, institutional rearing) and low-socioeconomic status (SES) will not. We meta-analyze 54 studies (n = 116,010) examining associations of ELA with pubertal timing and cellular aging (telomere length and DNA methylation age), systematically review 25 studies (n = 3,253) examining ELA and neural markers of accelerated development (cortical thickness and amygdala-prefrontal cortex functional connectivity) and evaluate whether associations of ELA with biological aging vary according to the nature of adversity experienced. ELA overall was associated with accelerated pubertal timing (d = -0.10) and cellular aging (d = -0.21), but these associations varied by adversity type. Moderator analysis revealed that ELA characterized by threat was associated with accelerated pubertal development (d = -0.26) and accelerated cellular aging (d = -0.43), but deprivation and SES were unrelated to accelerated development. Systematic review revealed associations between ELA and accelerated cortical thinning, with threat-related ELA consistently associated with thinning in ventromedial prefrontal cortex, and deprivation and SES associated with thinning in frontoparietal, default, and visual networks. There was no consistent association of ELA with amygdala-PFC connectivity. These findings suggest specificity in the types of early environmental experiences associated with accelerated biological aging and highlight the importance of evaluating how accelerated aging contributes to health disparities and whether this process can be mitigated through early intervention. (PsycInfo Database Record (c) 2020 APA, all rights reserved).