Abstract
Cortical thickness (CT) and surface area (SA) vary widely between individuals and are associated with intellectual ability and risk for various psychiatric and neurodevelopmental conditions. ...Factors influencing this variability remain poorly understood, but the radial unit hypothesis, as well as the more recent supragranular cortex expansion hypothesis, suggests that prenatal and perinatal influences may be particularly important. In this report, we examine the impact of 17 major demographic and obstetric history variables on interindividual variation in CT and SA in a unique sample of 805 neonates who received MRI scans of the brain around 2 weeks of age. Birth weight, postnatal age at MRI, gestational age at birth, and sex emerged as important predictors of SA. Postnatal age at MRI, paternal education, and maternal ethnicity emerged as important predictors of CT. These findings suggest that individual variation in infant CT and SA is explained by different sets of environmental factors with neonatal SA more strongly influenced by sex and obstetric history and CT more strongly influenced by socioeconomic and ethnic disparities. Findings raise the possibility that interventions aimed at reducing disparities and improving obstetric outcomes may alter prenatal/perinatal cortical development.
Recently, there has been a surge of interest in the possibility that microbial communities inhabiting the human gut could affect cognitive development and increase risk for mental illness via the ...“microbiome-gut-brain axis.” Infancy likely represents a critical period for the establishment of these relationships, as it is the most dynamic stage of postnatal brain development and a key period in the maturation of the microbiome. Indeed, recent reports indicate that characteristics of the infant gut microbiome are associated with both temperament and cognitive performance. The neural circuits underlying these relationships have not yet been delineated. To address this gap, resting-state fMRI scans were acquired from 39 1-year-old human infants who had provided fecal samples for identification and relative quantification of bacterial taxa. Measures of alpha diversity were generated and tested for associations with measures of functional connectivity. Primary analyses focused on the amygdala as manipulation of the gut microbiota in animal models alters the structure and neurochemistry of this brain region. Secondary analyses explored functional connectivity of nine canonical resting-state functional networks. Alpha diversity was significantly associated with functional connectivity between the amygdala and thalamus and between the anterior cingulate cortex and anterior insula. These regions play an important role in processing/responding to threat. Alpha diversity was also associated with functional connectivity between the supplementary motor area (SMA, representing the sensorimotor network) and the inferior parietal lobule (IPL). Importantly, SMA-IPL connectivity also related to cognitive outcomes at 2 years of age, suggesting a potential pathway linking gut microbiome diversity and cognitive outcomes during infancy. These results provide exciting new insights into the gut-brain axis during early human development and should stimulate further studies into whether microbiome-associated changes in brain circuitry influence later risk for psychopathology.
It becomes increasingly important in using genome-wide association studies (GWAS) to select important genetic information associated with qualitative or quantitative traits. Currently, the discovery ...of biological association among SNPs motivates various strategies to construct SNP-sets along the genome and to incorporate such set information into selection procedure for a higher selection power, while facilitating more biologically meaningful results. The aim of this paper is to propose a novel Bayesian framework for hierarchical variable selection at both SNP-set (group) level and SNP (within group) level. We overcome a key limitation of existing posterior updating scheme in most Bayesian variable selection methods by proposing a novel sampling scheme to explicitly accommodate the ultrahigh-dimensionality of genetic data. Specifically, by constructing an auxiliary variable selection model under SNP-set level, the new procedure utilizes the posterior samples of the auxiliary model to subsequently guide the posterior inference for the targeted hierarchical selection model. We apply the proposed method to a variety of simulation studies and show that our method is computationally efficient and achieves substantially better performance than competing approaches in both SNP-set and SNP selection. Applying the method to the Alzheimers Disease Neuroimaging Initiative (ADNI) data, we identify biologically meaningful genetic factors under several neuroimaging volumetric phenotypes. Our method is general and readily to be applied to a wide range of biomedical studies.
Individual differences in neuroanatomy are associated with intellectual ability and psychiatric risk. Factors responsible for this variability remain poorly understood. We tested whether 17 major ...demographic and obstetric variables were associated with individual differences in brain volumes in 756 neonates assessed with MRI. Gestational age at MRI, sex, gestational age at birth, and birthweight were the most significant predictors, explaining 31% to 59% of variance. Unexpectedly, earlier born babies had larger brains than later born babies after adjusting for other predictors. Our results suggest earlier born children experience accelerated brain growth, either as a consequence of the richer sensory environment they experience outside the womb or in response to other factors associated with delivery. In the full sample, maternal and paternal education, maternal ethnicity, maternal smoking, and maternal psychiatric history showed marginal associations with brain volumes, whereas maternal age, paternal age, paternal ethnicity, paternal psychiatric history, and income did not. Effects of parental education and maternal ethnicity are partially mediated by differences in birthweight. Remaining effects may reflect differences in genetic variation or cultural capital. In particular late initiation of prenatal care could negatively impact brain development. Findings could inform public health policy aimed at optimizing child development.
The relative lengths of the 2nd and 4th digits (2D:4D) may provide an easily measurable and stable anthropometric index of prenatal androgen exposure, but no study has examined the development of ...2D:4D in infancy and the potential impact of neonatal testosterone levels. We collected 2D:4D ratios from 364 children between 0 and 2years of age. Saliva samples were collected from 236 of these children 3months after birth and analyzed for testosterone. In addition, 259 children provided DNA samples which were genotyped for the CAG repeat polymorphism in the androgen receptor. There was substantial variability across age in 2D:4D. Sex differences were small compared to adults and did not consistently reach statistical significance. This suggests that 2D:4D may not function well as a proxy measure of prenatal testosterone exposure in infancy. In addition, the interaction of salivary T and CAG repeats predicted right hand digit ratio at 12months and left hand digit ratio at 12months and 24months in males. The interaction of salivary testosterone and CAG repeat length also predicted change in left hand 2D:4D from 2weeks to 12months in males. This suggests that 2D:4D in adults may reflect, in part, neonatal testosterone exposure. No significant relationships were observed within females. No significant relationships were observed when salivary testosterone and CAG repeats were examined independent of each other. Results have important implications for the design and interpretation of studies which use 2D:4D as a proxy measure of prenatal testosterone exposure.
► Ethnicity differences in 2D:4D apparent in first 2years of life. ► Sex differences in 2D:4D small and inconsistent in first 2years of life. ► Interaction of neonatal testosterone and receptor sensitivity predicts 2D:4D in males. ► Instability in 2D:4D across age. ► 2D:4D collected in early childhood may not be a reliable proxy for prenatal testosterone.
Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and ...neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs.
•The proposed method FGWAS jointly analyzes high-dimensional functional neuroimaging responses and genetic covariates.•FGWAS identifies genetic effects on the hippocampal surface data from the Alzheimer’s Disease Neuroimaging Initiative.•Outperforming existing GWAS methods for searching sparse signals in an extremely large space, while controlling the FWER.•A divide-and-conquer algorithm coupled with parallel computing.•The package for FGWAS, along with its documentation, is freely accessible from the website https://github.com/BIG-S2.
More and more large-scale imaging genetic studies are being widely conducted to collect a rich set of imaging, genetic, and clinical data to detect putative genes for complexly inherited ...neuropsychiatric and neurodegenerative disorders. Several major big-data challenges arise from testing genome-wide (NC>12 million known variants) associations with signals at millions of locations (NV~106) in the brain from thousands of subjects (n~103). The aim of this paper is to develop a Fast Voxelwise Genome Wide Association analysiS (FVGWAS) framework to efficiently carry out whole-genome analyses of whole-brain data. FVGWAS consists of three components including a heteroscedastic linear model, a global sure independence screening (GSIS) procedure, and a detection procedure based on wild bootstrap methods. Specifically, for standard linear association, the computational complexity is O (nNVNC) for voxelwise genome wide association analysis (VGWAS) method compared with O ((NC+NV)n2) for FVGWAS. Simulation studies show that FVGWAS is an efficient method of searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. Finally, we have successfully applied FVGWAS to a large-scale imaging genetic data analysis of ADNI data with 708 subjects, 193,275voxels in RAVENS maps, and 501,584 SNPs, and the total processing time was 203,645s for a single CPU. Our FVGWAS may be a valuable statistical toolbox for large-scale imaging genetic analysis as the field is rapidly advancing with ultra-high-resolution imaging and whole-genome sequencing.
•Develop a FVGAWS for adaptive analysis of large-scale imaging genetic data•An efficient global sure independence screening•Develop companion software for FVGWAS
•Infants show robust cortisol reactivity to heel stick at 1 month of age.•Diversity of gut microbiome associated with cortisol reactivity to heel stick.•Associations with specific genera and sample ...sizes for larger studies explored.
The Hypothalamic Pituitary Adrenal (HPA) axis regulates hormonal responses to stress in both humans and animals and is dysregulated in a wide range of psychiatric disorders. There is strong evidence from rodent studies that gut microbial composition influences HPA axis development. In humans, variation in the gut microbiome has been associated with several psychological domains including depression and cognitive development, but studies focused on HPA axis development are still lacking. We tested whether differences in microbial composition are associated with HPA axis reactivity in a pilot study of 34 healthy human infants. HPA axis reactivity was assessed by measuring salivary cortisol in samples taken both before and after a heel stick, and 16S rRNA amplicon sequencing was used for identification and relative quantification of bacterial taxa. Subjects’ alpha diversity levels showed a moderate positive association with their cortisol reactivity at one month of age. Exploratory genus-level analyses suggest that Staphylococcus, Prevotella, and genera in the order Lachnospiraceae may be related to cortisol reactivity at one month as well. The current study gives support for the endocrine pathway as a potential mediator in the microbiome-gut-brain axis during infancy, and as such provides motivation for future clinical work to support the development of stress-response systems through the manipulation of gut microbes.
Turner syndrome, which results from the complete or partial loss of a sex chromosome, is associated with a particular pattern of cognitive impairments and strengths and an increased risk for specific ...neurodevelopmental disorders. This review highlights recent progress in understanding brain structure and function in Turner syndrome and identifies several critical research needs.
Recent work on social cognition in Turner syndrome has identified a range of difficulties despite a maintained social appetite, a disconnect which could result in distress for affected individuals. Progress has been made in identifying foundational deficits in attention and executive function that could explain visual-spatial and arithmetical impairments. Neuroimaging studies have advanced our understanding of brain development and function through the application of cutting edge analysis techniques. Haploinsufficiency of genes, failure to express parentally imprinted genes, uncovering of X chromosome mutations, and gonadal steroid deficiency may all contribute to altered brain development, but additional work is required to link specific mechanisms to specific phenotypes. Also needed are studies of interventions to assist individuals with Turner syndrome in visual-spatial, mathematical, and social skills.
Ultimately a better understanding of brain structure and function in Turner syndrome will generate new therapeutic approaches for this population.
Individuals with Turner syndrome (TS) often exhibit specific deficits in visual-spatial functions, arithmetical abilities, social cognition, and executive functions with preserved general ...intelligence and preserved or enhanced verbal skills. This unique pattern of cognitive strengths and weaknesses is accompanied by a well-described neuroanatomical phenotype characterized by decreased gray matter volumes in premotor, somatosensory, and parietal-occipital cortex, and increased volumes of the amygdala and orbitofrontal cortex. Why the absence of the second sex chromosome should produce these effects remains poorly understood. In this article, we propose that the TS research community leverage recent advances in neuroimaging, large-scale data-rich biology (omics), and patient-powered research registries to build a comprehensive neurodevelopmental model of TS.
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