A structural MRI study of human brain development from birth to two years

pre-printBrain development in the first 2 years after birth is extremely dynamic and likely plays an important role in neurodevelopmental disorders, including autism and schizophrenia. Knowledge regarding this period is currently quite limited. We studied structural brain development in healthy subjects from birth to 2. Ninety-eight children received structural MRI scans on a Siemens head-only 3T scanner with magnetization prepared rapid gradient echo T1-weighted, and turbo spin echo, dual-echo (proton density and T2 weighted) sequences: 84 children at 2- 4 weeks, 35 at 1 year and 26 at 2 years of age. Tissue segmentation was accomplished using a novel automated approach. Lateral ventricle, caudate, and hippocampal volumes were also determined. Total brain volume increased 101% in the first year, with a 15% increase in the second. The majority of hemispheric growth was accounted for by gray matter, which increased 149% in the first year; hemispheric white matter volume increased by only 11%. Cerebellum volume increased 240% in the first year. Lateral ventricle volume increased 280% in the first year, with a small decrease in the second. The caudate increased 19% and the hippocampus 13% from age 1 to age 2. There was robust growth of the human brain in the first two years of life, driven mainly by gray matter growth. In contrast, white matter growth was much slower. Cerebellum volume also increased substantially in the first year of life. These results suggest the structural underpinnings of cognitive and motor development in early childhood, as well as the potential pathogenesis of neurodevelopmental disorders

Twin-singleton differences in neonatal brain structure

pre-printTwin studies suggest that global and regional brain volumes are highly heritable. However, estimates of heritability vary across development. Given that all twin studies are open to the potential criticism of non-generalizability due to differences in intrauterine environment between twins and singletons, these age effects may reflect the influence of perinatal environmental factors which are unique to twins and which may be especially evident early in life. To address this question, we compared brain volumes and the relationship of brain volumes to gestational age in 136 singletons (67 male, 69 female) and 154 twins (75 male, 79 female; 82 DZ, 72 MZ) who had received high resolution MRI scans of the brain in the first month of life. Intracranial volume, total white matter, and ventricle volumes did not differ between twins and singletons. However, cerebrospinal fluid and frontal white matter volume was greater in twins compared to singletons. While gray matter volumes at MRI did not differ between groups, the slope of the relationship between total and cortical gray matter and gestational age at the MRI scan was steeper in MZ twins compared to DZ twins. Post-hoc analyses suggested that gray matter development is delayed in MZ twins in utero and that they experience "catch-up" growth in the first month of life. These differences should be taken into account when interpreting and designing studies in the early postnatal period

SARS-CoV-2 (COVID-19) as a possible risk factor for neurodevelopmental disorders

Pregnant women constitute one of the most vulnerable populations to be affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the cause of coronavirus disease 2019. SARS-CoV-2 infection during pregnancy could negatively impact fetal brain development via multiple mechanisms. Accumulating evidence indicates that mother to fetus transmission of SARS-CoV-2 does occur, albeit rarely. When it does occur, there is a potential for neuroinvasion via immune cells, retrograde axonal transport, and olfactory bulb and lymphatic pathways. In the absence of maternal to fetal transmission, there is still the potential for negative neurodevelopmental outcomes as a consequence of disrupted placental development and function leading to preeclampsia, preterm birth, and intrauterine growth restriction. In addition, maternal immune activation may lead to hypomyelination, microglial activation, white matter damage, and reduced neurogenesis in the developing fetus. Moreover, maternal immune activation can disrupt the maternal or fetal hypothalamic-pituitary-adrenal (HPA) axis leading to altered neurodevelopment. Finally, pro-inflammatory cytokines can potentially alter epigenetic processes within the developing brain. In this review, we address each of these potential mechanisms. We propose that SARS-CoV-2 could lead to neurodevelopmental disorders in a subset of pregnant women and that long-term studies are warranted

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer’s Disease Neuroimag-ing Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme

2D:4D ratios in the first 2years of life: Stability and relation to testosterone exposure and sensitivity

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 2 years of age. Saliva samples were collected from 236 of these children 3 months 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 12 months and left hand digit ratio at 12 months and 24 months in males. The interaction of salivary testosterone and CAG repeat length also predicted change in left hand 2D:4D from 2 weeks to 12 months 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

Projection Regression Models for Multivariate Imaging Phenotype: Projection Regression Model

This paper presents a projection regression model (PRM) to assess the relationship between a multivariate phenotype and a set of covariates, such as a genetic marker, age and gender. In the existing literature, a standard statistical approach to this problem is to fit a multivariate linear model to the multivariate phenotype and then use Hotelling’s T2 to test hypotheses of interest. An alternative approach is to fit a simple linear model and test hypotheses for each individual phenotype and then correct for multiplicity. However, even when the dimension of the multivariate phenotype is relatively small, say 5, such standard approaches can suffer from the issue of low statistical power in detecting the association between the multivariate phenotype and the covariates. The PRM generalizes a statistical method based on the principal component of heritability for association analysis in genetic studies of complex multivariate phenotypes. The key components of the PRM include an estimation procedure for extracting several principal directions of multivariate phenotypes relating to covariates and a test procedure based on wild-bootstrap method for testing for the association between the weighted multivariate phenotype and explanatory variables. Simulation studies and an imaging genetic dataset are used to examine the finite sample performance of the PRM

Multiple SNP Set Analysis for Genome-Wide Association Studies Through Bayesian Latent Variable Selection

The power of genome-wide association studies (GWAS) for mapping complex traits with single SNP analysis may be undermined by modest SNP effect sizes, unobserved causal SNPs, correlation among adjacent SNPs, and SNP-SNP interactions. Alternative approaches for testing the association between a single SNP-set and individual phenotypes have been shown to be promising for improving the power of GWAS. We propose a Bayesian latent variable selection (BLVS) method to simultaneously model the joint association mapping between a large number of SNP-sets and complex traits. Compared to single SNP-set analysis, such joint association mapping not only accounts for the correlation among SNP-sets, but also is capable of detecting causal SNP-sets that are marginally uncorrelated with traits. The spike-slab prior assigned to the effects of SNP-sets can greatly reduce the dimension of effective SNP-sets, while speeding up computation. An efficient MCMC algorithm is developed. Simulations demonstrate that BLVS outperforms several competing variable selection methods in some important scenarios

Environmental and Genetic Contributors to Salivary Testosterone Levels in Infants

Transient activation of the hypothalamic–pituitary–gonadal axis in early infancy plays an important role in male genital development and sexual differentiation of the brain, but factors contributing to individual variation in testosterone levels during this period are poorly understood. We measured salivary testosterone levels in 222 infants (119 males, 103 females, 108 singletons, 114 twins) between 2.70 and 4.80 months of age. We tested 16 major demographic and medical history variables for effects on inter-individual variation in salivary testosterone. Using the subset of twins, we estimated genetic and environmental contributions to salivary testosterone levels. Finally, we tested single nucleotide polymorphisms (SNPs) within ±5 kb of genes involved in testosterone synthesis, transport, signaling, and metabolism for associations with salivary testosterone using univariate tests and random forest (RF) analysis. We report an association between 5 min APGAR scores and salivary testosterone levels in males. Twin modeling indicated that individual variability in testosterone levels was primarily explained by environmental factors. Regarding genetic variation, univariate tests did not reveal any variants significantly associated with salivary testosterone after adjusting for false discovery rate. The top hit in males was rs10923844, an SNP of unknown function located downstream of HSD3B1 and HSD3B2. The top hits in females were two SNPs located upstream of ESR1 (rs3407085 and rs2295190). RF analysis, which reflects joint and conditional effects of multiple variants, indicated that genes involved in regulation of reproductive function, particularly LHCGR, are related to salivary testosterone levels in male infants, as are genes involved in cholesterol production, transport, and removal, while genes involved in estrogen signaling are related to salivary testosterone levels in female infants

Environmental and Genetic Contributors to Salivary Testosterone Levels in Infants

Transient activation of the hypothalamic–pituitary–gonadal axis in early infancy plays an important role in male genital development and sexual differentiation of the brain, but factors contributing to individual variation in testosterone levels during this period are poorly understood. We measured salivary testosterone levels in 222 infants (119 males, 103 females, 108 singletons, 114 twins) between 2.70 and 4.80 months of age. We tested 16 major demographic and medical history variables for effects on inter-individual variation in salivary testosterone. Using the subset of twins, we estimated genetic and environmental contributions to salivary testosterone levels. Finally, we tested single nucleotide polymorphisms (SNPs) within ±5 kb of genes involved in testosterone synthesis, transport, signaling, and metabolism for associations with salivary testosterone using univariate tests and random forest (RF) analysis. We report an association between 5 min APGAR scores and salivary testosterone levels in males. Twin modeling indicated that individual variability in testosterone levels was primarily explained by environmental factors. Regarding genetic variation, univariate tests did not reveal any variants significantly associated with salivary testosterone after adjusting for false discovery rate. The top hit in males was rs10923844, an SNP of unknown function located downstream of HSD3B1 and HSD3B2. The top hits in females were two SNPs located upstream of ESR1 (rs3407085 and rs2295190). RF analysis, which reflects joint and conditional effects of multiple variants, indicated that genes involved in regulation of reproductive function, particularly LHCGR, are related to salivary testosterone levels in male infants, as are genes involved in cholesterol production, transport, and removal, while genes involved in estrogen signaling are related to salivary testosterone levels in female infants