A common MECP2 haplotype associates with reduced cortical surface area in humans in two independent populations

Spatiotemporal patterns in cortical development: Age, puberty, and individual variability from 9 to 13 years of age

Humans and nonhuman primate studies suggest that timing and tempo of cortical development varies neuroanatomically along a sensorimotor-to-association (S-A) axis. Prior human studies have reported a principal S-A axis across various modalities, but largely rely on cross-sectional samples with wide age-ranges. Here, we investigate developmental changes and individual variability in cortical organization along the S-A axis between the ages of 9-13 years using a large, longitudinal sample (N = 2487-3747, 46-50% female) from the Adolescent Brain Cognitive Development Study (ABCD Study®). This work assesses multiple aspects of neurodevelopment indexed by changes in cortical thickness, cortical microarchitecture, and resting-state functional fluctuations. First, we evaluated S-A organization in age-related changes and, then, computed individual-level S-A alignment in brain changes and assessing differences therein due to age, sex, and puberty. Varying degrees of linear and quadratic age-related brain changes were identified along the S-A axis. Yet, these patterns of cortical development were overshadowed by considerable individual variability in S-A alignment. Even within individuals, there was little correspondence between S-A patterning across the different aspects of neurodevelopment investigated (i.e., cortical morphology, microarchitecture, function). Some of the individual variation in developmental patterning of cortical morphology and microarchitecture was explained by age, sex, and pubertal development. Altogether, this work contextualizes prior findings that regional age differences do progress along an S-A axis at a group level, while highlighting broad variation in developmental change between individuals and between aspects of cortical development, in part due to sex and puberty.

Significance Statement

Understanding normative patterns of adolescent brain change, and individual variability therein, is crucial for disentangling healthy and abnormal development. We used longitudinal human neuroimaging data to study several aspects of neurodevelopment during early adolescence and assessed their organization along a sensorimotor-to-association (S-A) axis across the cerebral cortex. Age differences in brain changes were linear and curvilinear along this S-A axis. However, individual-level sensorimotor-association alignment varied considerably, driven in part by differences in age, sex, and pubertal development.

The structural basis of age-related decline in global motion perception at fast and slow speeds

A decrease in global motion perception (GMP) has been reported in older adults, and this age-related decline in GMP varies with the speed of global motion. However, no studies have investigated whether the asynchronous age-related decline in GMP is related to degenerative changes in brain structure. In this study, the random dot kinematogram paradigm and structural magnetic resonance imaging were used to investigate the asynchronous aging of GMP at fast and slow speeds (called fast GMP and slow GMP, respectively) and their relationships with brain structure. Ninety-four older adults (65.74 ± 4.50 yrs) and 90 younger adults (22.83 ± 4.84 yrs) participated in the experiment. The results showed that older adults had higher motion coherence thresholds (MCT) than younger adults at both fast and slow speeds. Brain-behavior correlation analyses of younger adults revealed that none of the correlations between morphological measures and MCTs survived correction for multiple comparisons. For older adults, slow MCT was correlated with cortical thickness in the bilateral V4v, V5/MT+, left V7, V8, LO, and surface area in the right V7. Fast MCT was significantly correlated with gray matter volume in the right V7 and thickness in the left V5/MT+. These results support the view that global motion extraction occurs within two speed-tuned systems that are at least partially independent in terms of their neural substrates, which deteriorate with age at different speeds. Aging of GMP is also associated with morphological changes in the visual cortex. Age-related cerebral atrophy in the dorsal stream may impair both fast and slow GMP, whereas aging of the ventral stream specifically impairs slow GMP.

Brain morphometry in 22q11.2 deletion syndrome: an exploration of differences in cortical thickness, surface area, and their contribution to cortical volume

22q11.2 Deletion Syndrome (22q11.2DS) is the most common microdeletion in humans, with a heterogenous clinical presentation including medical, behavioural and psychiatric conditions. Previous neuroimaging studies examining the neuroanatomical underpinnings of 22q11.2DS show alterations in cortical volume (CV), cortical thickness (CT) and surface area (SA). The aim of this study was to identify (1) the spatially distributed networks of differences in CT and SA in 22q11.2DS compared to controls, (2) their unique and spatial overlap, as well as (3) their relative contribution to observed differences in CV. Structural MRI scans were obtained from 62 individuals with 22q11.2DS and 57 age-and-gender-matched controls (aged 6-31). Using FreeSurfer, we examined differences in vertex-wise estimates of CV, CT and SA at each vertex, and compared the frequencies of vertices with a unique or overlapping difference for each morphometric feature. Our findings indicate that CT and SA make both common and unique contributions to volumetric differences in 22q11.2DS, and in some areas, their strong opposite effects mask differences in CV. By identifying the neuroanatomic variability in 22q11.2DS, and the separate contributions of CT and SA, we can start exploring the shared and distinct mechanisms that mediate neuropsychiatric symptoms across disorders, e.g. 22q11.2DS-related ASD and/or psychosis/schizophrenia.

Sex Differences in Variability of Brain Structure Across the Lifespan

Several brain disorders exhibit sex differences in onset, presentation, and prevalence. Increased understanding of the neurobiology of sex-based differences in variability across the lifespan can provide insight into both disease vulnerability and resilience. In n = 3069 participants, from 8 to 95 years of age, we found widespread greater variability in males compared with females in cortical surface area and global and subcortical volumes for discrete brain regions. In contrast, variance in cortical thickness was similar for males and females. These findings were supported by multivariate analysis accounting for structural covariance, and present and stable across the lifespan. Additionally, we examined variability among brain regions by sex. We found significant age-by-sex interactions across neuroimaging metrics, whereby in very early life males had reduced among-region variability compared with females, while in very late life this was reversed. Overall, our findings of greater regional variability, but less among-region variability in males in early life may aid our understanding of sex-based risk for neurodevelopmental disorders. In contrast, our findings in late life may provide a potential sex-based risk mechanism for dementia.

Large-scale mapping of cortical alterations in 22q11.2 deletion syndrome: Convergence with idiopathic psychosis and effects of deletion size

The 22q11.2 deletion (22q11DS) is a common chromosomal microdeletion and a potent risk factor for psychotic illness. Prior studies reported widespread cortical changes in 22q11DS, but were generally underpowered to characterize neuroanatomic abnormalities associated with psychosis in 22q11DS, and/or neuroanatomic effects of variability in deletion size. To address these issues, we developed the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta-Analysis) 22q11.2 Working Group, representing the largest analysis of brain structural alterations in 22q11DS to date. The imaging data were collected from 10 centers worldwide, including 474 subjects with 22q11DS (age = 18.2 ± 8.6; 46.9% female) and 315 typically developing, matched controls (age = 18.0 ± 9.2; 45.9% female). Compared to controls, 22q11DS individuals showed thicker cortical gray matter overall (left/right hemispheres: Cohen's d = 0.61/0.65), but focal thickness reduction in temporal and cingulate cortex. Cortical surface area (SA), however, showed pervasive reductions in 22q11DS (left/right hemispheres: d = -1.01/-1.02). 22q11DS cases vs. controls were classified with 93.8% accuracy based on these neuroanatomic patterns. Comparison of 22q11DS-psychosis to idiopathic schizophrenia (ENIGMA-Schizophrenia Working Group) revealed significant convergence of affected brain regions, particularly in fronto-temporal cortex. Finally, cortical SA was significantly greater in 22q11DS cases with smaller 1.5 Mb deletions, relative to those with typical 3 Mb deletions. We found a robust neuroanatomic signature of 22q11DS, and the first evidence that deletion size impacts brain structure. Psychotic illness in this highly penetrant deletion was associated with similar neuroanatomic abnormalities to idiopathic schizophrenia. These consistent cross-site findings highlight the homogeneity of this single genetic etiology, and support the suitability of 22q11DS as a biological model of schizophrenia.

The Role of MECP2 and CCR5 Polymorphisms on the Development and Course of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a chronic and systemic autoimmune disease. SLE is described by production of autoantibodies and causes damage of many organs. T-cells play a crucial role in SLE pathogenesis. T-cells intensify inflammation through a number of processes, which leads to autoimmunization. CCR5 and MECP2 genes are linked with T-cells and pathogenesis of SLE. Polymorphisms in these genes are related with the prognostic factors of risk of disease onset and disease severity. The aim of this study was to estimate the influence of polymorphisms in MECP2 and CCR5 genes on the development and course of systemic lupus erythematosus. We examined 137 SLE patients and 604 healthy controls. We studied polymorphisms for CCR5 gene: rs333 and for MECP2: rs2075596, rs1734787, rs17435, and rs2239464. We genotyped our MECP2 samples and we performed a restriction fragment length polymorphism (RFLP) analysis for CCR5 samples. We showed a risk factor for allele T in rs17435 and for allele A in rs2075596 in MECP2. We noticed that MECP2 rs2075596 G/A, rs1734787 C/A, rs17435 A/T, and rs2239464 G/A polymorphisms are more prevalent in SLE patients than in healthy controls. We believe that above-mentioned MECP2 polymorphisms can be considered as SLE susceptibility factor.

Image processing and analysis methods for the Adolescent Brain Cognitive Development Study

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

Associations of cortical thickness, surface area and subcortical volumes with insight in drug-naïve adults with obsessive-compulsive disorder

• We first used the SBM method to explore the neuroanatomical basis underlying insight in OCD.

• OCD-GI and OCD-PI displayed mostly shared, but partly distinct brain structural alterations.

• Decreased cortical thickness in the left dmPFC, the left ACC and the right lateral parietal cortex was associated with poorer insight.

• The potential effect of other clinical variables on the results has been ruled out.

Poor insight in obsessive-compulsive disorder (OCD) is associated with several adverse clinical outcomes. However, the neurobiological basis of this insight deficit is not clearly understood. The present study thus aimed to investigate associations of cortical thickness, cortical surface area and subcortical volumes with insight in a sample of drug-naïve adults with OCD. Forty-seven OCD patients and 42 healthy controls (HCs) underwent MRI scanning, depression and anxiety assessments. The Brown Assessment of Beliefs Scale (BABS) measured insight levels and patients were divided into two groups: poor insight (OCD-PI; n = 21), and good insight (OCD-GI; n = 26). Cortical thickness and surface area between groups were compared with whole-brain exploratory vertex-by-vertex analyses, while subcortical volumes were compared on a structure-by-structure basis. Partial correlation analyses were then performed to assess associations between regional cortical and subcortical measures and insight levels. OCD-GI and OCD-PI groups displayed partly shared, but also partly distinct brain structural alterations. Strikingly, OCD-PI showed decreased cortical thickness in the left superior frontal gyrus, left anterior cingulate cortex (ACC) and right inferior parietal gyrus, compared to both OCD-GI and HCs. Average cortical thickness extracted from these areas was further negatively correlated with BABS scores in the OCD-PI patients. Our findings suggest that poor insight in patients with OCD may have a neural substrate involving the left medial frontal and the right inferior parietal cortices.

High Functioning Autism with Missense Mutations in Synaptotagmin-Like Protein 4 (SYTL4) and Transmembrane Protein 187 (TMEM187) Genes: SYTL4- Protein Modeling, Protein-Protein Interaction, Expression Profiling and MicroRNA Studies

We describe a 7-year-old male with high functioning autism spectrum disorder (ASD) and maternally-inherited rare missense variant of Synaptotagmin-like protein 4 (SYTL4) gene (Xq22.1; c.835C>T; p.Arg279Cys) and an unknown missense variant of Transmembrane protein 187 (TMEM187) gene (Xq28; c.708G>T; p. Gln236His). Multiple in-silico predictions described in our study indicate a potentially damaging status for both X-linked genes. Analysis of predicted atomic threading models of the mutant and the native SYTL4 proteins suggest a potential structural change induced by the R279C variant which eliminates the stabilizing Arg279-Asp60 salt bridge in the N-terminal half of the SYTL4, affecting the functionality of the protein's critical RAB-Binding Domain. In the European (Non-Finnish) population, the allele frequency for this variant is 0.00042. The SYTL4 gene is known to directly interact with several members of the RAB family of genes, such as, RAB27A, RAB27B, RAB8A, and RAB3A which are known autism spectrum disorder genes. The SYTL4 gene also directly interacts with three known autism genes: STX1A, SNAP25 and STXBP1. Through a literature-based analytical approach, we identified three of five (60%) autism-associated serum microRNAs (miRs) with high predictive power among the total of 298 mouse Sytl4 associated/predicted microRNA interactions. Five of 13 (38%) miRs were differentially expressed in serum from ASD individuals which were predicted to interact with the mouse equivalent Sytl4 gene. TMEM187 gene, like SYTL4, is a protein-coding gene that belongs to a group of genes which host microRNA genes in their introns or exons. The novel Q236H amino acid variant in the TMEM187 in our patient is near the terminal end region of the protein which is represented by multiple sequence alignments and hidden Markov models, preventing comparative structural analysis of the variant harboring region. Like SYTL4, the TMEM187 gene is expressed in the brain and interacts with four known ASD genes, namely, HCFC1; TMLHE; MECP2; and GPHN. TMM187 is in linkage with MECP2, which is a well-known determinant of brain structure and size and is a well-known autism gene. Other members of the TMEM gene family, TMEM132E and TMEM132D genes are associated with bipolar and panic disorders, respectively, while TMEM231 is a known syndromic autism gene. Together, TMEM187 and SYTL4 genes directly interact with recognized important ASD genes, and their mRNAs are found in extracellular vesicles in the nervous system and stimulate target cells to translate into active protein. Our evidence shows that both these genes should be considered as candidate genes for autism. Additional biological testing is warranted to further determine the pathogenicity of these gene variants in the causation of autism.

Neonatal amygdalae and hippocampi are influenced by genotype and prenatal environment, and reflected in the neonatal DNA methylome

The amygdala and hippocampus undergo rapid development in early life. The relative contribution of genetic and environmental factors to the establishment of their developmental trajectories has yet to be examined. We performed imaging on neonates and examined how the observed variation in volume and microstructure of the amygdala and hippocampus varied by genotype, and compared with prenatal maternal mental health and socioeconomic status. Gene × Environment models outcompeted models containing genotype or environment only to best explain the majority of measures but some, especially of the amygdaloid microstructure, were best explained by genotype only. Models including DNA methylation measured in the neonate umbilical cords outcompeted the Gene and Gene × Environment models for the majority of amygdaloid measures and minority of hippocampal measures. This study identified brain region-specific gene networks associated with individual differences in fetal brain development. In particular, genetic and epigenetic variation within CUX1 was highlighted.

Joint Analysis of Cortical Area and Thickness as a Replacement for the Analysis of the Volume of the Cerebral Cortex

Cortical surface area is an increasingly used brain morphology metric that is ontogenetically and phylogenetically distinct from cortical thickness and offers a separate index of neurodevelopment and disease. However, the various existing methods for assessment of cortical surface area from magnetic resonance images have never been systematically compared. We show that the surface area method implemented in FreeSurfer corresponds closely to the exact, but computationally more demanding, mass-conservative (pycnophylactic) method, provided that images are smoothed. Thus, the data produced by this method can be interpreted as estimates of cortical surface area, as opposed to areal expansion. In addition, focusing on the joint analysis of thickness and area, we compare an improved, analytic method for measuring cortical volume to a permutation-based nonparametric combination (NPC) method. We use the methods to analyze area, thickness and volume in young adults born preterm with very low birth weight, and show that NPC analysis is a more sensitive option for studying joint effects on area and thickness, giving equal weight to variation in both of these 2 morphological features.

Group sparse reduced rank regression for neuroimaging genetic study

The neuroimaging genetic study usually needs to deal with high dimensionality of both brain imaging data and genetic data, so that often resulting in the issue of curse of dimensionality. In this paper, we propose a group sparse reduced rank regression model to take the relations of both the phenotypes and the genotypes for the neuroimaging genetic study. Specifically, we propose designing a graph sparsity constraint as well as a reduced rank constraint to simultaneously conduct subspace learning and feature selection. The group sparsity constraint conducts feature selection to identify genotypes highly related to neuroimaging data, while the reduced rank constraint considers the relations among neuroimaging data to conduct subspace learning in the feature selection model. Furthermore, an alternative optimization algorithm is proposed to solve the resulting objective function and is proved to achieve fast convergence. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset showed that the proposed method has superiority on predicting the phenotype data by the genotype data, than the alternative methods under comparison.

Hemispheric Module-Specific Influence of the X Chromosome on White Matter Connectivity: Evidence from Girls with Turner Syndrome

Turner syndrome (TS) is caused by the congenital absence of all or part of one of the X chromosomes in females, offering a valuable human “knockout model” to study the functioning patterns of the X chromosome in the human brain. Little is known about whether and how the loss of the X chromosome influences the brain structural wiring patterns in human. We acquired a multimodal MRI dataset and cognitive assessments from 22 girls with TS and 21 age-matched control girls to address these questions. Hemispheric white matter (WM) networks and modules were derived using refined diffusion MRI tractography. Statistical comparisons revealed a reduced topological efficiency of both hemispheric networks and bilateral parietal modules in TS girls. Specifically, the efficiency of right parietal module significantly mediated the effect of the X chromosome on working memory performance, indicating that X chromosome loss impairs working memory performance by disrupting this module. Additionally, TS girls showed structural and functional connectivity decoupling across specific within- and between-modular connections, predominantly in the right hemisphere. These findings provide novel insights into the functional pathways in the brain that are regulated by the X chromosome and highlight a module-specific genetic contribution to WM connectivity in the human brain.

The Physiology of Homeoprotein Transduction

The homeoprotein family comprises ~300 transcription factors and was long seen as primarily involved in developmental programs through cell autonomous regulation. However, recent evidence reveals that many of these factors are also expressed in the adult where they exert physiological functions not yet fully deciphered. Furthermore, the DNA-binding domain of most homeoproteins contains two signal sequences allowing their secretion and internalization, thus intercellular transfer. This review focuses on this new-found signaling in cell migration, axon guidance, and cerebral cortex physiological homeostasis and speculates on how it may play important roles in early arealization of the neuroepithelium. It also describes the use of homeoproteins as therapeutic proteins in mouse models of diseases affecting the central nervous system, in particular Parkinson disease and glaucoma.

The Sex Chromosome Hypothesis of Schizophrenia: Alive, Dead, or Forgotten? A Commentary and Review

The X chromosome has long been an intriguing site for harboring genes that have importance in brain development and function. It has received the most attention for having specific genes underlying the X-linked inherited intellectual disabilities, but has also been associated with schizophrenia in a number of early studies. An X chromosome hypothesis for a genetic predisposition for schizophrenia initially came from the X chromosome anomaly population data showing an excess of schizophrenia in Klinefelter's (XXY) males and triple X (XXX) females. Crow and colleagues later expanded the X chromosome hypothesis to include the possibility of a locus on the Y chromosome and, specifically, genes on X that escaped inactivation and are X-Y homologous loci. Some new information about possible risk loci on these chromosomes has come from the current large genetic consortia genome-wide association studies, suggesting that perhaps this hypothesis needs to be revisited for some schizophrenias. The following commentary reviews the early and more recent literature supporting or refuting this dormant hypothesis and emphasizes the possible candidate genes still of interest that could be explored in further studies.

Sex-specific Behavioral Features of Rodent Models of Autism Spectrum Disorder

Sex is an important factor in understanding the clinical presentation, management, and developmental trajectory of children with neuropsychiatric disorders. While much is known about the clinical and neurobehavioral profiles of males with neuropsychiatric disorders, surprisingly little is known about females in this respect. Animal models may provide detailed mechanistic information about sex differences in autism spectrum disorder (ASD) in terms of manifestation, disease progression, and development of therapeutic options. This review aims to widen our understanding of the role of sex in autism spectrum disorder, by summarizing and comparing behavioral characteristics of animal models. Our current understanding of how differences emerge in boys and girls with neuropsychiatric disorders is limited: Information derived from animal studies will stimulate future research on the role of biological maturation rates, sex hormones, sex-selective protective (or aggravating) factors and psychosocial factors, which are essential to devise sex precision medicine and to improve diagnostic accuracy. Moreover, there is a strong need of novel strategies to elucidate the major mechanisms leading to sex-specific autism features, as well as novel models or methods to examine these sex differences.

Longitudinal trajectories of cortical thickness as a biomarker for psychosis in individuals with 22q11.2 deletion syndrome

OBJECTIVE

22q11.2 deletion syndrome (DS) or velo-cardio-facial syndrome (VCFS) is a genetic condition that has been identified as the highest genetic risk factor for developing psychotic illnesses. This unique biological nature of 22q11DS provides a valuable opportunity to explore predictive biomarkers of psychosis. In this study, we examined the relationship of cortical thickness and surface area between various brain regions and prodromal symptoms of psychosis.

METHODS

75 probands with 22q11DS, 32 age-matched controls and 28 siblings underwent MRIs over 2 or 3 timepoints. Longitudinal mixed model regression analyses, with age as an interaction variable, were carried out to study the differences in longitudinal trajectories of change in average cortical thickness and surface area over 6-9years. Similar analyses were carried out to examine the relationship with positive prodromal symptoms of psychosis.

RESULTS

Significant differences were noted in the inferior and superior parietal regions in both the average thickness and longitudinal change in cortical thickness with age between the probands and controls. Significant associations were also noted between regions in the frontal cortex and positive prodromal symptoms among probands. No associations were noted with cortical surface area.

CONCLUSION

Our results indicate that individuals with 22q11DS who develop positive prodromal symptoms demonstrate differential longitudinal trajectories of cortical thickness in some regions of the frontal lobe. Our results suggest that the pruning stage associated with adolescent brain development may be disrupted.

Reduced cortical thickness, surface area in patients with chronic obstructive pulmonary disease: a surface-based morphometry and neuropsychological study

Neural impairments accompanying chronic obstructive pulmonary disease (COPD) have received growing research attention. Previous neuroimaging studies exclusively used volumetric methods to measure cortical volume as a whole rather than focusing on anatomical and neuropathological distinct indices. Here we decomposed the cortical architecture into cortical thickness (CTh), surface area (SA), and gyrification, for the first time, to provide a more integrative profile of brain damage in COPD. Clinical T1-weighted MRI scans were acquired in 25 stable COPD patients (mean age 69) and 25 age-matched controls. Images were processed using surface-based morphometry to obtain cortical parameters enabling more accurate measurement in deep sulci and localized regional mapping. Demographic, physiological, and cognitive assessments were made and correlated with cortical indices. Compared to controls, COPD patients showed significantly reduced CTh broadly distributed in motor, parietal, and prefrontal cortices, together with more circumscribed SA reduction in dorsomedial prefrontal cortex and Broca's area (cluster-level P < 0.05 corrected). No abnormal gyrification was detected. Decreased CTh in parietofrontal networks strongly correlated with visuospatial construction impairment in COPD patients. Furthermore, thinner dorsolateral prefrontal cortex (DLPFC) best predicted poorer performance (r (2)  = 0.315, P = 0.004), and was associated with lower arterial oxygen saturation. These data indicate that cortical thinning is a key morphologic feature associated with COPD that could be partly attributed to oxygen desaturation and contributes to COPD visual memory and drawing deficits. Surface-based morphometry provides valuable information concerning COPD, and could ultimately help us to characterize the neurodegenerative pattern and to clarify neurologic mechanisms underlying cognitive dysfunction in COPD patients.

Birth weight discordance, DNA methylation, and cortical morphology of adolescent monozygotic twins

BACKGROUND

Several studies have shown that the in utero environment, which can be indexed by birth weight (BW), is associated with cortical morphology in adolescence and adulthood. Work in monozygotic (MZ) twins suggests that this association is driven by non-shared environmental factors. This correlation could be the result of in utero impacts on DNA methylation. The aim of the present study with MZ twins is to replicate the association between discordance in BW and brain morphology and test whether discordance in DNA methylation mediates this relationship.

METHODS

One hundred and four adolescent MZ twins (52 pairs, of which 42% were male pairs) who have been followed regularly since birth underwent T1 weighted structural MRI, and epigenome-wide assessment of DNA methylation from saliva at age 15.

RESULTS

Co-twins had very similar measures of DNA methylation and cortical morphology. Higher BW members of a twin pair had increased total cortical surface area, and decreased cortical thickness compared to their lower BW sibling. BW Discordance was positively associated with both cortical surface area and cortical volume discordance. Genes involved in neurodevelopment were tentatively identified as mediators of both the BW - cortical volume, and BW- cortical surface area relationships.

CONCLUSIONS

The association between BW and cortical morphology in adolescence appears to be attributable to in utero environmental effects, and DNA methylation may play a role in mediating this relationship. Hum Brain Mapp 38:2037-2050, 2017. © 2017 Wiley Periodicals, Inc.

Whole Genome Expression Analysis in a Mouse Model of Tauopathy Identifies MECP2 as a Possible Regulator of Tau Pathology

Increasing evidence suggests that hyperphosphorylation and aggregation of microtubule-associated protein tau (MAPT or tau) correlates with the development of cognitive impairment in Alzheimer’s disease (AD) and related tauopathies. While numerous attempts have been made to model AD-relevant tau pathology in various animal models, there has been very limited success for these models to fully recapitulate the progression of disease as seen in human tauopathies. Here, we performed whole genome gene expression in a genomic mouse model of tauopathy that expressed human MAPT gene under the control of endogenous human MAPT promoter and also were complete knockout for endogenous mouse tau [referred to as ‘hTau^MaptKO(Duke)′ mice]. First, whole genome expression analysis revealed 64 genes, which were differentially expressed (32 up-regulated and 32 down-regulated) in the hippocampus of 6-month-old hTau^MaptKO(Duke) mice compared to age-matched non-transgenic controls. Genes relevant to neuronal function or neurological disease include up-regulated genes: PKC-alpha (Prkca), MECP2 (Mecp2), STRN4 (Strn4), SLC40a1 (Slc40a1), POLD2 (Pold2), PCSK2 (Pcsk2), and down-regulated genes: KRT12 (Krt12), LASS1 (Cers1), PLAT (Plat), and NRXN1 (Nrxn1). Second, network analysis suggested anatomical structure development, cellular metabolic process, cell death, signal transduction, and stress response were significantly altered biological processes in the hTau^MaptKO(Duke) mice as compared to age-matched non-transgenic controls. Further characterization of a sub-group of significantly altered genes revealed elevated phosphorylation of MECP2 (methyl-CpG-binding protein-2), which binds to methylated CpGs and associates with chromatin, in hTau^MaptKO(Duke) mice compared to age-matched controls. Third, phoshpho-MECP2 was elevated in autopsy brain samples from human AD compared to healthy controls. Finally, siRNA-mediated knockdown of MECP2 in human tau expressing N2a cells resulted in a significant decrease in total and phosphorylated tau. Together, these results suggest that MECP2 is a potential novel regulator of tau pathology relevant to AD and tauopathies.

Diagnostic model generated by MRI-derived brain features in toddlers with autism spectrum disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder mainly showed atypical social interaction, communication, and restricted, repetitive patterns of behavior, interests and activities. Now clinic diagnosis of ASD is mostly based on psychological evaluation, clinical observation and medical history. All these behavioral indexes could not avoid defects such as subjectivity and reporter-dependency. Therefore researchers devoted themselves to seek relatively stable biomarkers of ASD as supplementary diagnostic evidence. The goal of present study is to generate relatively stable predictive model based on anatomical brain features by using machine learning technique. Forty-six ASD children and thirty-nine development delay children aged from 18 to 37 months were evolved in. As a result, the predictive model generated by regional average cortical thickness of regions with top 20 highest importance of random forest classifier showed best diagnostic performance. And random forest was proved to be the optimal approach for neuroimaging data mining in small size set and thickness-based classification outperformed volume-based classification and surface area-based classification in ASD. The brain regions selected by the models might attract attention and the idea of considering biomarkers as a supplementary evidence of ASD diagnosis worth exploring. Autism Res 2017, 0: 000-000. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 620-630. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications

We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches.

Distinct Genetic Influences on Cortical and Subcortical Brain Structures

This study examined the heritability of brain grey matter structures in a subsample of older adult twins (93 MZ and 68 DZ twin pairs; mean age 70 years) from the Older Australian Twins Study. The heritability estimates of subcortical regions ranged from 0.41 (amygdala) to 0.73 (hippocampus), and of cortical regions, from 0.55 (parietal lobe) to 0.78 (frontal lobe). Corresponding structures in the two hemispheres were influenced by the same genetic factors and high genetic correlations were observed between the two hemispheric regions. There were three genetically correlated clusters, comprising (i) the cortical lobes (frontal, temporal, parietal and occipital lobes); (ii) the basal ganglia (caudate, putamen and pallidum) with weak genetic correlations with cortical lobes, and (iii) the amygdala, hippocampus, thalamus and nucleus accumbens grouped together, which genetically correlated with both basal ganglia and cortical lobes, albeit relatively weakly. Our study demonstrates a complex but patterned and clustered genetic architecture of the human brain, with divergent genetic determinants of cortical and subcortical structures, in particular the basal ganglia.

Is bigger always better? The importance of cortical configuration with respect to cognitive ability

General cognitive ability (GCA) has substantial explanatory power for behavioral and health outcomes, but its cortical substrate is still not fully established. GCA is highly polygenic and research to date strongly suggests that its cortical substrate is highly polyregional. We show in map-based and region-of-interest-based analyses of adult twins that a complex cortical configuration underlies GCA. Having relatively greater surface area in evolutionary and developmentally high-expanded prefrontal, lateral temporal, and inferior parietal regions is positively correlated with GCA, whereas relatively greater surface area in low-expanded occipital, medial temporal, and motor cortices is negatively correlated with GCA. Essentially the opposite pattern holds for relative cortical thickness. The phenotypic positive-to-negative gradients in our cortical-GCA association maps were largely driven by a similar pattern of genetic associations. The patterns are consistent with regional cortical stretching whereby relatively greater surface area is related to relatively thinner cortex in high-expanded regions. Thus, the typical "bigger is better" view does not adequately capture cortical-GCA associations. Rather, cognitive ability is influenced by complex configurations of cortical development patterns that are strongly influenced by genetic factors. Optimal cognitive ability appears to be driven both by the absolute size and the polyregional configuration of the entire cortex rather than by small, circumscribed regions.

Brain development during adolescence: A mixed-longitudinal investigation of cortical thickness, surface area, and volume

What we know about cortical development during adolescence largely stems from analyses of cross-sectional or cohort-sequential samples, with few studies investigating brain development using a longitudinal design. Further, cortical volume is a product of two evolutionarily and genetically distinct features of the cortex - thickness and surface area, and few studies have investigated development of these three characteristics within the same sample. The current study examined maturation of cortical thickness, surface area and volume during adolescence, as well as sex differences in development, using a mixed longitudinal design. 192 MRI scans were obtained from 90 healthy (i.e., free from lifetime psychopathology) adolescents (11-20 years) at three time points (with different MRI scanners used at time 1 compared to 2 and 3). Developmental trajectories were estimated using linear mixed models. Non-linear increases were present across most of the cortex for surface area. In comparison, thickness and volume were both characterised by a combination of non-linear decreasing and increasing trajectories. While sex differences in volume and surface area were observed across time, no differences in thickness were identified. Furthermore, few regions exhibited sex differences in the cortical development. Our findings clearly illustrate that volume is a product of surface area and thickness, with each exhibiting differential patterns of development during adolescence, particularly in regions known to contribute to the development of social-cognition and behavioral regulation. These findings suggest that thickness and surface area may be driven by different underlying mechanisms, with each measure potentially providing independent information about brain development. Hum Brain Mapp 37:2027-2038, 2016. © 2016 Wiley Periodicals, Inc.

Morphological abnormalities in prefrontal surface area and thalamic volume in attention deficit/hyperactivity disorder

Although previous morphological studies have demonstrated abnormalities in prefrontal cortical thickness in children with attention deficit/hyperactivity disorder (ADHD), studies investigating cortical surface area are lacking. As the development of cortical surface is closely linked to the establishment of thalam-ocortical connections, any abnormalities in the structure of the thalamus are likely to relate to altered cortical surface area. Using a clinically well-defined sample of children with ADHD (n = 25, 1 female) and typically developing controls (n = 24, 1 female), we studied surface area across the cortex to determine whether children with ADHD had reduced thalamic volume that related to prefrontal cortical surface area. Relative to controls, children with ADHD had a significant reduction in thalamic volume and dorsolateral prefrontal cortical area in both hemispheres. Furthermore, children with ADHD with smaller thalamic volumes were found to have greater reductions in surface area, a pattern not evident in the control children. Our results are further evidence of reduced lateral prefrontal cortical area in ADHD. Moreover, for the first time, we have also shown a direct association between thalamic anatomy and frontal anatomy in ADHD, suggesting the pathophysiological process that alters surface area maturation is likely to be linked to the development of the thalamus.

Reduced cortical surface area in adolescents with conduct disorder

Children with conduct disorder (CD) are at increased risk of developing antisocial personality disorder and psychopathy in adulthood. Neuroimaging research has identified abnormal cortical volume (CV) in CD. However, CV comprises two genetically and developmentally separable components: cortical thickness (CT) and surface area (SA). Aim of this study is to explore the relationship between the cortical constituents of CV in boys with CD. We applied FreeSurfer software to structural MRI data to derive measures of CV, CT, and SA in 21 boys with CD and 19 controls. Relationships between these cortical measures were investigated. Boys with CD had significantly reduced CV and SA compared to non-CD boys in ventromedial and dorsolateral prefrontal cortex. We found no significant between-group differences in CT. Reduced prefrontal CV in boys with CD is associated with significantly reduced SA in the same regions. This finding may help to identify specific neurodevelopmental mechanisms underlying cortical deficits observed in CD.

Neuroanatomical correlates of late-life depression and associated cognitive changes

We compared cortical thickness between patients with late-life depression (LLD) and healthy controls and between patients with early-onset (EOD) and late-onset (LOD) depression. We also tested age effects on cortical thickness in LLD and controls and if cortical thickness and hippocampal volumes were associated with cognitive performance in LLD. Three-dimensional T1-weighted magnetic resonance images were obtained in 49 LLD and 49 matched hospital controls and processed using FreeSurfer. General linear model analysis was used as a statistical approach. LLD group had thinning in the left parahippocampal, fusiform, and inferior-parietal cortex compared with controls. Age correlated with cortical thinning in controls but not in LLD. Women in the LOD groups had extensive cortical thinning in the lateral prefrontal cortex bilaterally compared with EOD women. Absence of statistically significant changes observed in men should however be treated with caution because of the low number of men in the study. Mini-Mental Status Examination score correlated with lateral prefrontal cortical thickness bilaterally and hippocampal volume in the total group of LLD and in LOD but not EOD. LLD is associated with cortical thinning, which is associated with age at depression onset, gender, and level of cognitive functioning.

Aberrant Cortical Morphometry in the 22q11.2 Deletion Syndrome

BACKGROUND

There is increased risk of developing psychosis in 22q11.2 deletion syndrome (22q11DS). Although this condition is associated with morphologic brain abnormalities, simultaneous examination of multiple high-resolution measures of cortical structure has not been performed.

METHODS

Fifty-three patients with 22q11DS, 30 with psychotic symptoms, were compared with demographically matched nondeleted youths: 53 typically developing and 53 with psychotic symptoms. High-resolution magnetic resonance imaging measures of cerebral volume, cortical thickness, surface area, and an index of local gyrification were obtained and compared between groups.

RESULTS

Patients with 22q11DS demonstrated global increases in cortical thickness associated with reductions in surface area, reduced index of local gyrification, and lower cerebral volumes relative to typically developing controls. Findings were principally in the frontal lobe, superior parietal lobes, and in the paramedian cerebral cortex. Focally decreased thickness was seen in the superior temporal gyrus and posterior cingulate cortex in 22q11DS relative to nondeleted groups. Patterns between nondeleted participants with psychotic symptoms and 22q11DS were similar but with important differences in several regions implicated in schizophrenia. Post hoc analysis suggested that like the 22q11DS group, cortical thickness in nondeleted individuals with psychotic symptoms differed from typically developing controls in the superior frontal gyrus and superior temporal gyrus, regions previously linked to schizophrenia.

CONCLUSIONS

Simultaneous examination of multiple measures of cerebral architecture demonstrates that differences in 22q11DS localize to regions of the frontal, superior parietal, superior temporal, and paramidline cerebral cortex. The overlapping patterns between nondeleted participants with psychotic symptoms and 22q11DS suggest partially shared neuroanatomic substrates.

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository

The main objective of the multi-site Pediatric Imaging, Neurocognition, and Genetics (PING) study was to create a large repository of standardized measurements of behavioral and imaging phenotypes accompanied by whole genome genotyping acquired from typically-developing children varying widely in age (3 to 20 years). This cross-sectional study produced sharable data from 1493 children, and these data have been described in several publications focusing on brain and cognitive development. Researchers may gain access to these data by applying for an account on the PING portal and filing a data use agreement. Here we describe the recruiting and screening of the children and give a brief overview of the assessments performed, the imaging methods applied, the genetic data produced, and the numbers of cases for whom different data types are available. We also cite sources of more detailed information about the methods and data. Finally we describe the procedures for accessing the data and for using the PING data exploration portal.

Neural population tuning links visual cortical anatomy to human visual perception

The anatomy of cerebral cortex is characterized by two genetically independent variables, cortical thickness and cortical surface area, that jointly determine cortical volume. It remains unclear how cortical anatomy might influence neural response properties and whether such influences would have behavioral consequences. Here, we report that thickness and surface area of human early visual cortices exert opposite influences on neural population tuning with behavioral consequences for perceptual acuity. We found that visual cortical thickness correlated negatively with the sharpness of neural population tuning and the accuracy of perceptual discrimination at different visual field positions. In contrast, visual cortical surface area correlated positively with neural population tuning sharpness and perceptual discrimination accuracy. Our findings reveal a central role for neural population tuning in linking visual cortical anatomy to visual perception and suggest that a perceptually advantageous visual cortex is a thinned one with an enlarged surface area.

Mild expression differences of MECP2 influencing aggressive social behavior

The X-chromosomal MECP2/Mecp2 gene encodes methyl-CpG-binding protein 2, a transcriptional activator and repressor regulating many other genes. We discovered in male FVB/N mice that mild (∼50%) transgenic overexpression of Mecp2 enhances aggression. Surprisingly, when the same transgene was expressed in C57BL/6N mice, transgenics showed reduced aggression and social interaction. This suggests that Mecp2 modulates aggressive social behavior. To test this hypothesis in humans, we performed a phenotype-based genetic association study (PGAS) in >1000 schizophrenic individuals. We found MECP2 SNPs rs2239464 (G/A) and rs2734647 (C/T; 3′UTR) associated with aggression, with the G and C carriers, respectively, being more aggressive. This finding was replicated in an independent schizophrenia cohort. Allele-specific MECP2mRNA expression differs in peripheral blood mononuclear cells by ∼50% (rs2734647: C > T). Notably, the brain-expressed, species-conserved miR-511 binds to MECP2 3′UTR only in T carriers, thereby suppressing gene expression. To conclude, subtle MECP2/Mecp2 expression alterations impact aggression. While the mouse data provides evidence of an interaction between genetic background and mild Mecp2 overexpression, the human data convey means by which genetic variation affects MECP2 expression and behavior.

The rise of large-scale imaging studies in psychiatry

From the initial arguments over whether 12 to 20 subjects were sufficient for an fMRI study, sample sizes in psychiatric neuroimaging studies have expanded into the tens of thousands. These large-scale imaging studies fall into several categories, each of which has specific advantages and challenges. The different study types can be grouped based on their level of control: meta-analyses, at one extreme of the spectrum, control nothing about the imaging protocol or subject selection criteria in the datasets they include, On the other hand, planned multi-site mega studies pour intense efforts into strictly having the same protocols. However, there are several other combinations possible, each of which is best used to address certain questions. The growing investment of all these studies is delivering on the promises of neuroimaging for psychiatry, and holds incredible potential for impact at the level of the individual patient. However, to realize this potential requires both standardized data-sharing efforts, so that there is more staying power in the datasets for re-use and new applications, as well as training the next generation of neuropsychiatric researchers in "Big Data" techniques in addition to traditional experimental methods. The increased access to thousands of datasets along with the needed informatics demands a new emphasis on integrative scientific methods.

DNA modifications: function and applications in normal and disease States

Epigenetics refers to a variety of processes that have heritable effects on gene expression programs without changes in DNA sequence. Key players in epigenetic control are chemical modifications to DNA, histone, and non-histone chromosomal proteins, which establish a complex regulatory network that controls genome function. Methylation of DNA at the fifth position of cytosine in CpG dinucleotides (5-methylcytosine, 5mC), which is carried out by DNA methyltransferases, is commonly associated with gene silencing. However, high resolution mapping of DNA methylation has revealed that 5mC is enriched in exonic nucleosomes and at intron-exon junctions, suggesting a role of DNA methylation in the relationship between elongation and RNA splicing. Recent studies have increased our knowledge of another modification of DNA, 5-hydroxymethylcytosine (5hmC), which is a product of the ten-eleven translocation (TET) proteins converting 5mC to 5hmC. In this review, we will highlight current studies on the role of 5mC and 5hmC in regulating gene expression (using some aspects of brain development as examples). Further the roles of these modifications in detection of pathological states (type 2 diabetes, Rett syndrome, fetal alcohol spectrum disorders and teratogen exposure) will be discussed.

Cortical thickness and surface area relate to specific symptoms in early relapsing–remitting multiple sclerosis

Background:

Cortical atrophy is common in early relapsing–remitting multiple sclerosis (RRMS). Whether this atrophy is caused by changes in cortical thickness or cortical surface area is not known, nor is their separate contributions to clinical symptoms.

Objectives:

To investigate the difference in cortical surface area, thickness and volume between early RRMS patients and healthy controls; and the relationship between these measures and neurological disability, cognitive decline, fatigue and depression.

Methods:

RRMS patients ( n = 61) underwent magnetic resonance imaging (MRI), neurological and neuropsychological examinations. We estimated cortical surface area, thickness and volume and compared them with matched healthy controls ( n = 61). We estimated the correlations between clinical symptoms and cortical measures within the patient group.

Results:

We found no differences in cortical surface area, but widespread differences in cortical thickness and volume between the groups. Neurological disability was related to regionally smaller cortical thickness and volume. Better verbal memory was related to regionally larger surface area; and better visuo-spatial memory, to regionally larger cortical volume. Higher depression scores and fatigue were associated with regionally smaller cortical surface area and volume.

Conclusions:

We found that cortical thickness, but not cortical surface area, is affected in early RRMS. We identified specific structural correlates to the main clinical symptoms in early RRMS.

Common variants on Xq28 conferring risk of schizophrenia in Han Chinese

Schizophrenia is a highly heritable, severe psychiatric disorder affecting approximately 1% of the world population. A substantial portion of heritability is still unexplained and the pathophysiology of schizophrenia remains to be elucidated. To identify more schizophrenia susceptibility loci, we performed a genome-wide association study (GWAS) on 498 patients with schizophrenia and 2025 controls from the Han Chinese population, and a follow-up study on 1027 cases and 1005 controls. In the follow-up study, we included 384 single nucleotide polymorphisms (SNPs) which were selected from the top hits in our GWAS (130 SNPs) and from previously implicated loci for schizophrenia based on the SZGene database, NHGRI GWAS Catalog, copy number variation studies, GWAS meta-analysis results from the international Psychiatric Genomics Consortium (PGC) and candidate genes from plausible biological pathways (254 SNPs). Within the chromosomal region Xq28, SNP rs2269372 in RENBP achieved genome-wide significance with a combined P value of 3.98 × 10(-8) (OR of allele A = 1.31). SNPs with suggestive P values were identified within 2 genes that have been previously implicated in schizophrenia, MECP2 (rs2734647, P combined = 8.78 × 10(-7), OR = 1.28; rs2239464, P combined = 6.71 × 10(-6), OR = 1.26) and ARHGAP4 (rs2269368, P combined = 4.74 × 10(-7), OR = 1.25). In addition, the patient sample in our follow-up study showed a significantly greater burden for pre-defined risk alleles based on the SNPs selected than the controls. This indicates the existence of schizophrenia susceptibility loci among the SNPs we selected. This also further supports multigenic inheritance in schizophrenia. Our findings identified a new schizophrenia susceptibility locus on Xq28, which harbor the genes RENBP, MECP2, and ARHGAP4.

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Dynamic Development of Regional Cortical Thickness and Surface Area in Early Childhood

Cortical thickness (CT) and surface area (SA) are altered in many neuropsychiatric disorders and are correlated with cognitive functioning. Little is known about how these components of cortical gray matter develop in the first years of life. We studied the longitudinal development of regional CT and SA expansion in healthy infants from birth to 2 years. CT and SA have distinct and heterogeneous patterns of development that are exceptionally dynamic; overall CT increases by an average of 36.1%, while cortical SA increases 114.6%. By age 2, CT is on average 97% of adult values, compared with SA, which is 69%. This suggests that early identification, prevention, and intervention strategies for neuropsychiatric illness need to be targeted to this period of rapid postnatal brain development, and that SA expansion is the principal driving factor in cortical volume after 2 years of age.

Adolescent brain maturation and cortical folding: evidence for reductions in gyrification

Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development.

Neuroimaging in autism--from basic science to translational research

Over the past decade, human neuroimaging studies have provided invaluable insights into the neural substrates that underlie autism spectrum disorder (ASD). Although observations from multiple neuroimaging approaches converge in suggesting that changes in brain structure, functioning and connectivity are associated with ASD, the neurobiology of this disorder is complex, and considerable aetiological and phenotypic heterogeneity exists among individuals on the autism spectrum. Characterization of the neurobiological alterations that underlie ASD and development of novel pharmacotherapies for ASD, therefore, requires multidisciplinary collaboration. Consequently, pressure is growing to combine neuroimaging data with information provided by other disciplines to translate research findings into clinically useful biomarkers. So far, however, neuroimaging studies in patients with ASD have mainly been conducted in isolation, and the low specificity of neuroimaging measures has hindered the development of biomarkers that could aid clinical trials and/or facilitate patient identification. Novel approaches to acquiring and analysing data on brain characteristics are currently being developed to overcome these inherent limitations, and to integrate neuroimaging into translational research. Here, we discuss promising new studies of cortical pathology in patients with ASD, and outline how the novel insights thereby obtained could inform diagnosis and treatment of ASD in the future.

Boosting the power of schizophrenia genetics by leveraging new statistical tools

Genome-wide association studies (GWAS) have identified a large number of gene variants associated with schizophrenia, but these variants explain only a small portion of the heritability. It is becoming increasingly clear that schizophrenia is influenced by many genes, most of which have effects too small to be identified using traditional GWAS statistical methods. By applying recently developed Empirical Bayes statistical approaches, we have demonstrated that functional genic elements show differential contribution to phenotypic variance, with some elements (regulatory regions and exons) showing strong enrichment for association with schizophrenia. Applying related methods, we also showed abundant genetic overlap (pleiotropy) between schizophrenia and other phenotypes, including bipolar disorder, cardiovascular disease risk factors, and multiple sclerosis. We estimated the number of gene variants with effects in schizophrenia and bipolar disorder to be approximately 1.2%. By applying our novel statistical framework, we dramatically improved gene discovery and detected a large number of new gene loci associated with schizophrenia that have not yet been identified with standard GWAS methods. Utilizing independent schizophrenia substudies, we showed that these new loci have high replication rates in de novo samples, indicating that they likely represent true schizophrenia risk genes. The new statistical tools provide a powerful approach for uncovering more of the missing heritability of schizophrenia and other complex disorders. In conclusion, the highly polygenic architecture of schizophrenia strongly suggests the utility of research approaches that recognize schizophrenia neuropathology as a complex dynamic system, with many small gene effects integrated in functional networks.

Bipolar II disorder is associated with thinning of prefrontal and temporal cortices involved in affect regulation

OBJECTIVES

The neurobiological substrate of bipolar II disorder (BD-II) remains largely unknown. A few previous studies have found evidence for cerebral cortical thinning in mixed samples of BD-II and bipolar I disorder patients; however, no study of cortical thickness or surface area has been limited to BD-II. In the present study, we compared magnetic resonance imaging (MRI)-based indices of cortical thickness and surface area between individuals with BD-II and healthy controls.

METHODS

Thirty-six individuals with a DSM-IV diagnosis of BD-II and 42 controls underwent 3T MRI. Comparisons of thickness and relative surface areal expansion across the cerebral cortical mantle were performed using Freesurfer.

RESULTS

Individuals with BD-II showed significant thinning in two prefrontal clusters primarily comprising the left subgenual anterior cingulate cortex, left perigenual ventromedial prefrontal cortex (PFC), bilateral dorsomedial PFC, and bilateral dorsolateral PFC (p < 0.0002 for both clusters, cluster size corrected) and in a left temporal cluster involving the superior, middle, and inferior temporal gyrus (p = 0.006, cluster size corrected). No group differences in cortical surface area were found. No significant effect of medication, mood state, illness duration, or family history of bipolar disorders on cortical thinning was observed.

CONCLUSIONS

These results indicate that BD-II is associated with thinning of prefrontal and temporal cortices implicated in the expression and regulation of negative and positive affect. Longitudinal studies are needed to clarify whether cortical thinning is a stable trait of BD-II, an illness effect that might progress during the course of the disease, or a combination of the two.