Environmental Influences on Infant Cortical Thickness and Surface Area.

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.

Disentangling the effects of early caregiving experience and heritable factors on brain white matter development in rhesus monkeys.

Early social experiences, particularly maternal care, shape behavioral and physiological development in primates. Thus, it is not surprising that adverse caregiving, such as child maltreatment leads to a vast array of poor developmental outcomes, including increased risk for psychopathology across the lifespan. Studies of the underlying neurobiology of this risk have identified structural and functional alterations in cortico-limbic brain circuits that seem particularly sensitive to these early adverse experiences and are associated with anxiety and affective disorders. However, it is not understood how these neurobiological alterations unfold during development as it is very difficult to study these early phases in humans, where the effects of maltreatment experience cannot be disentangled from heritable traits. The current study examined the specific effects of experience ("nurture") versus heritable factors ("nature") on the development of brain white matter (WM) tracts with putative roles in socioemotional behavior in primates from birth through the juvenile period. For this we used a randomized crossfostering experimental design in a naturalistic rhesus monkey model of infant maltreatment, where infant monkeys were randomly assigned at birth to either a mother with a history of maltreating her infants, or a competent mother. Using a longitudinal diffusion tensor imaging (DTI) atlas-based tract-profile approach we identified widespread, but also specific, maturational changes on major brain tracts, as well as alterations in a measure of WM integrity (fractional anisotropy, FA) in the middle longitudinal fasciculus (MdLF) and the inferior longitudinal fasciculus (ILF), of maltreated animals, suggesting decreased structural integrity in these tracts due to early adverse experience. Exploratory voxelwise analyses confirmed the tract-based approach, finding additional effects of early adversity, biological mother, social dominance rank, and sex in other WM tracts. These results suggest tract-specific effects of postnatal maternal care experience versus heritable or biological factors on primate WM microstructural development. Further studies are needed to determine the specific behavioral outcomes and biological mechanisms associated with these alterations in WM integrity.

Genetic influences on neonatal cortical thickness and surface area.

Genetic and environmental influences on cortical thickness (CT) and surface area (SA) are thought to vary in a complex and dynamic way across the lifespan. It has been established that CT and SA are genetically distinct in older children, adolescents, and adults, and that heritability varies across cortical regions. Very little, however, is known about how genetic and environmental factors influence infant CT and SA. Using structural MRI, we performed the first assessment of genetic and environmental influences on normal variation of SA and CT in 360 twin neonates. We observed strong and significant additive genetic influences on total SA (a2 = 0.78) and small and nonsignificant genetic influences on average CT (a2 = 0.29). Moreover, we found significant genetic overlap (genetic correlation = 0.65) between these global cortical measures. Regionally, there were minimal genetic influences across the cortex for both CT and SA measures and no distinct patterns of genetic regionalization. Overall, outcomes from this study suggest a dynamic relationship between CT and SA during the neonatal period and provide novel insights into how genetic influences shape cortical structure during early development.

Impact of Demographic and Obstetric Factors on Infant Brain Volumes: A Population Neuroscience Study.

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.

Differential reconstitution of T cell subsets following immunodepleting treatment with alemtuzumab (anti-CD52 monoclonal antibody) in patients with relapsing-remitting multiple sclerosis.

Alemtuzumab (anti-CD52 mAb) provides long-lasting disease activity suppression in relapsing-remitting multiple sclerosis (RRMS). The objective of this study was to characterize the immunological reconstitution of T cell subsets and its contribution to the prolonged RRMS suppression following alemtuzumab-induced lymphocyte depletion. The study was performed on blood samples from RRMS patients enrolled in the CARE-MS II clinical trial, which was recently completed and led to the submission of alemtuzumab for U.S. Food and Drug Administration approval as a treatment for RRMS. Alemtuzumab-treated patients exhibited a nearly complete depletion of circulating CD4(+) lymphocytes at day 7. During the immunological reconstitution, CD4(+)CD25(+)CD127(low) regulatory T cells preferentially expanded within the CD4(+) lymphocytes, reaching their peak expansion at month 1. The increase in the percentage of TGF-ß1-, IL-10-, and IL-4-producing CD4(+) cells reached a maximum at month 3, whereas a significant decrease in the percentages of Th1 and Th17 cells was detected at months 12 and 24 in comparison with the baseline. A gradual increase in serum IL-7 and IL-4 and a decrease in IL-17A, IL-17F, IL-21, IL-22, and IFN-γ levels were detected following treatment. In vitro studies have demonstrated that IL-7 induced an expansion of CD4(+)CD25(+)CD127(low) regulatory T cells and a decrease in the percentages of Th17 and Th1 cells. In conclusion, our results indicate that differential reconstitution of T cell subsets and selectively delayed CD4(+) T cell repopulation following alemtuzumab-induced lymphopenia may contribute to its long-lasting suppression of disease activity.

A SPARSE REDUCED RANK FRAMEWORK FOR GROUP ANALYSIS OF FUNCTIONAL NEUROIMAGING DATA.

In spatial-temporal neuroimaging studies, there is an evolving literature on the analysis of functional imaging data in order to learn the intrinsic functional connectivity patterns among different brain regions. However, there are only few efficient approaches for integrating functional connectivity pattern across subjects, while accounting for spatial-temporal functional variation across multiple groups of subjects. The objective of this paper is to develop a new sparse reduced rank (SRR) modeling framework for carrying out functional connectivity analysis across multiple groups of subjects in the frequency domain. Our new framework not only can extract both frequency and spatial factors across subjects, but also imposes sparse constraints on the frequency factors. It thus leads to the identification of important frequencies with high power spectra. In addition, we propose two novel adaptive criteria for automatic selection of sparsity level and model rank. Using simulated data, we demonstrate that SRR outperforms several existing methods. Finally, we apply SRR to detect group differences between controls and two subtypes of attention deficit hyperactivity disorder (ADHD) patients, through analyzing the ADHD-200 data.

Sleep apnoea and hypoventilation in patients with five major types of muscular dystrophy.

BACKGROUND: The characteristics of and relationship between sleep apnoea and hypoventilation in patients with muscular dystrophy (MD) remain to be fully understood. METHODS: We analysed 104 in-laboratory sleep studies of 73 patients with MD with five common types (DMD-Duchenne, Becker MD, CMD-congenital, LGMD-limb-girdle and DM-myotonic dystrophy). We used generalised estimating equations to examine differences among these types for outcomes. RESULTS: Patients in all five types had high risk of sleep apnoea with 53 of the 73 patients (73%) meeting the diagnostic criteria in at least one study. Patients with DM had higher risk of sleep apnoea compared with patients with LGMD (OR=5.15, 95% CI 1.47 to 18.0; p=0.003). Forty-three per cent of patients had hypoventilation with observed prevalence higher in CMD (67%), DMD (48%) and DM (44%). Hypoventilation and sleep apnoea were associated in those patients (unadjusted OR=2.75, 95% CI 1.15 to 6.60; p=0.03), but the association weakened after adjustment (OR=2.32, 95% CI 0.92 to 5.81; p=0.08). In-sleep average heart rate was about 10 beats/min higher in patients with CMD and DMD compared with patients with DM (p=0.0006 and p=0.02, respectively, adjusted for multiple testing). CONCLUSION: Sleep-disordered breathing is common in patients with MD but each type has its unique features. Hypoventilation was only weakly associated with sleep apnoea; thus, high clinical suspicion is needed for diagnosing hypoventilation. Identifying the window when respiratory muscle weakness begins to cause hypoventilation is important for patients with MD; it enables early intervention with non-invasive ventilation-a therapy that should both lengthen the expected life of these patients and improve its quality.Cite Now.

Assessment of systemic AAV-microdystrophin gene therapy in the GRMD model of Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD) is a progressive muscle wasting disease caused by the absence of dystrophin, a membrane-stabilizing protein encoded by the DMD gene. Although mouse models of DMD provide insight into the potential of a corrective therapy, data from genetically homologous large animals, such as the dystrophin-deficient golden retriever muscular dystrophy (GRMD) model, may more readily translate to humans. To evaluate the clinical translatability of an adeno-associated virus serotype 9 vector (AAV9)-microdystrophin (µDys5) construct, we performed a blinded, placebo-controlled study in which 12 GRMD dogs were divided among four dose groups [control, 1 × 1013 vector genomes per kilogram (vg/kg), 1 × 1014 vg/kg, and 2 × 1014 vg/kg; n = 3 each], treated intravenously at 3 months of age with a canine codon-optimized microdystrophin construct, rAAV9-CK8e-c-µDys5, and followed for 90 days after dosing. All dogs received prednisone (1 milligram/kilogram) for a total of 5 weeks from day -7 through day 28. We observed dose-dependent increases in tissue vector genome copy numbers; µDys5 protein in multiple appendicular muscles, the diaphragm, and heart; limb and respiratory muscle functional improvement; and reduction of histopathologic lesions. As expected, given that a truncated dystrophin protein was generated, phenotypic test results and histopathologic lesions did not fully normalize. All administrations were well tolerated, and adverse events were not seen. These data suggest that systemically administered AAV-microdystrophin may be dosed safely and could provide therapeutic benefit for patients with DMD.

MOMENT-BASED METHOD FOR RANDOM EFFECTS SELECTION IN LINEAR MIXED MODELS.

The selection of random effects in linear mixed models is an important yet challenging problem in practice. We propose a robust and unified framework for automatically selecting random effects and estimating covariance components in linear mixed models. A moment-based loss function is first constructed for estimating the covariance matrix of random effects. Two types of shrinkage penalties, a hard thresholding operator and a new sandwich-type soft-thresholding penalty, are then imposed for sparse estimation and random effects selection. Compared with existing approaches, the new procedure does not require any distributional assumption on the random effects and error terms. We establish the asymptotic properties of the resulting estimator in terms of its consistency in both random effects selection and variance component estimation. Optimization strategies are suggested to tackle the computational challenges involved in estimating the sparse variance-covariance matrix. Furthermore, we extend the procedure to incorporate the selection of fixed effects as well. Numerical results show promising performance of the new approach in selecting both random and fixed effects and, consequently, improving the efficiency of estimating model parameters. Finally, we apply the approach to a data set from the Amsterdam Growth and Health study.

Spike-and-slab type variable selection in the Cox proportional hazards model for high-dimensional features.

In this paper, we develop a variable selection framework with the spike-and-slab prior distribution via the hazard function of the Cox model. Specifically, we consider the transformation of the score and information functions for the partial likelihood function evaluated at the given data from the parameter space into the space generated by the logarithm of the hazard ratio. Thereby, we reduce the nonlinear complexity of the estimation equation for the Cox model and allow the utilization of a wider variety of stable variable selection methods. Then, we use a stochastic variable search Gibbs sampling approach via the spike-and-slab prior distribution to obtain the sparsity structure of the covariates associated with the survival outcome. Additionally, we conduct numerical simulations to evaluate the finite-sample performance of our proposed method. Finally, we apply this novel framework on lung adenocarcinoma data to find important genes associated with decreased survival in subjects with the disease.

Weighted functional linear Cox regression model.

The aim of this paper is to develop a weighted functional linear Cox regression model that accounts for the association between a failure time and a set of functional and scalar covariates. We formulate the weighted functional linear Cox regression by incorporating a comprehensive three-stage estimation procedure as a unified methodology. Specifically, the weighted functional linear Cox regression uses a functional principal component analysis to represent the functional covariates and a high-dimensional Cox regression model to capture the joint effects of both scalar and functional covariates on the failure time data. Then, we consider an uncensored probability for each subject by estimating the important parameter of a censoring distribution. Finally, we use such a weight to construct the pseudo-likelihood function and maximize it to acquire an estimator. We also show our estimation and testing procedures through simulations and an analysis of real data from the Alzheimer's Disease Neuroimaging Initiative.

Infant Gut Microbiome Associated With Cognitive Development.

BACKGROUND: Studies in rodents provide compelling evidence that microorganisms inhabiting the gut influence neurodevelopment. In particular, experimental manipulations that alter intestinal microbiota impact exploratory and communicative behaviors and cognitive performance. In humans, the first years of life are a dynamic time in gut colonization and brain development, but little is known about the relationship between these two processes. METHODS: We tested whether microbial composition at 1 year of age is associated with cognitive outcomes using the Mullen Scales of Early Learning and with global and regional brain volumes using structural magnetic resonance imaging at 1 and 2 years of age. Fecal samples were collected from 89 typically developing 1-year-olds. 16S ribosomal RNA amplicon sequencing was used for identification and relative quantification of bacterial taxa. RESULTS: Cluster analysis identified 3 groups of infants defined by their bacterial composition. Mullen scores at 2 years of age differed significantly between clusters. In addition, higher alpha diversity was associated with lower scores on the overall composite score, visual reception scale, and expressive language scale at 2 years of age. Exploratory analyses of neuroimaging data suggest the gut microbiome has minimal effects on regional brain volumes at 1 and 2 years of age. CONCLUSIONS: This is the first study to demonstrate associations between the gut microbiota and cognition in human infants. As such, it represents an essential first step in translating animal data into the clinic.

LCN: a random graph mixture model for community detection in functional brain networks.

The aim of this article is to develop a Bayesian random graph mixture model (RGMM) to detect the latent class network (LCN) structure of brain connectivity networks and estimate the parameters governing this structure. The use of conjugate priors for unknown parameters leads to efficient estimation, and a well-known nonidentifiability issue is avoided by a particular parameterization of the stochastic block model (SBM). Posterior computation proceeds via an efficient Markov Chain Monte Carlo algorithm. Simulations demonstrate that LCN outperforms several other competing methods for community detection in weighted networks, and we apply our RGMM to estimate the latent community structures in the functional resting brain networks of 185 subjects from the ADHD-200 sample. We find overlap in the estimated community structure across subjects, but also heterogeneity even within a given diagnosis group.

Sleep Apnea and Hypoventilation in Patients with Down Syndrome: Analysis of 144 Polysomnogram Studies.

Patients with Down syndrome (DS) are at risk for both obstructive sleep apnea (OSA) and central sleep apnea (CSA); however, it is unclear how these components evolve as patients age and whether patients are also at risk for hypoventilation. A retrospective review of 144 diagnostic polysomnograms (PSG) in a tertiary care facility over 10 years was conducted. Descriptive data and exploratory correlation analyses were performed. Sleep disordered breathing was common (seen in 78% of patients) with an average apnea-hypopnea index (AHI) = 10. The relative amount of obstructive apnea was positively correlated with age and body mass index (BMI). The relative amount of central sleep apnea was associated with younger age in the very youngest group (0-3 years). Hypoventilation was common occurring in more than 22% of patients and there was a positive correlation between the maximum CO2 and BMI. Sleep disordered breathing, including hypoventilation, was common in patients with DS. The obstructive component increased significantly with age and BMI, while the central component occurred most in the very young age group. Due to the high risk of hypoventilation, which has not been previously highlighted, it may be helpful to consider therapies to target both apnea and hypoventilation in this population.

Cortical thickness and surface area in neonates at high risk for schizophrenia.

Schizophrenia is a neurodevelopmental disorder associated with subtle abnormal cortical thickness and cortical surface area. However, it is unclear whether these abnormalities exist in neonates associated with genetic risk for schizophrenia. To this end, this preliminary study was conducted to identify possible abnormalities of cortical thickness and surface area in the high-genetic-risk neonates. Structural magnetic resonance images were acquired from offspring of mothers (N = 21) who had schizophrenia (N = 12) or schizoaffective disorder (N = 9), and also matched healthy neonates of mothers who were free of psychiatric illness (N = 26). Neonatal cortical surfaces were reconstructed and parcellated as regions of interest (ROIs), and cortical thickness for each vertex was computed as the shortest distance between the inner and outer surfaces. Comparisons were made for the average cortical thickness and total surface area in each of 68 cortical ROIs. After false discovery rate (FDR) correction, it was found that the female high-genetic-risk neonates had significantly thinner cortical thickness in the right lateral occipital cortex than the female control neonates. Before FDR correction, the high-genetic-risk neonates had significantly thinner cortex in the left transverse temporal gyrus, left banks of superior temporal sulcus, left lingual gyrus, right paracentral cortex, right posterior cingulate cortex, right temporal pole, and right lateral occipital cortex, compared with the control neonates. Before FDR correction, in comparison with control neonates, male high-risk neonates had significantly thicker cortex in the left frontal pole, left cuneus cortex, and left lateral occipital cortex; while female high-risk neonates had significantly thinner cortex in the bilateral paracentral, bilateral lateral occipital, left transverse temporal, left pars opercularis, right cuneus, and right posterior cingulate cortices. The high-risk neonates also had significantly smaller cortical surface area in the right pars triangularis (before FDR correction), compared with control neonates. This preliminary study provides the first evidence that early development of cortical thickness and surface area might be abnormal in the neonates at genetic risk for schizophrenia.

Antenatal depression, treatment with selective serotonin reuptake inhibitors, and neonatal brain structure: A propensity-matched cohort study.

The aim of this propensity-matched cohort study was to evaluate the impact of prenatal SSRI exposure and a history of maternal depression on neonatal brain volumes and white matter microstructure. SSRI-exposed neonates (n=27) were matched to children of mothers with no history of depression or SSRI use (n=54). Additionally, neonates of mothers with a history of depression, but no prenatal SSRI exposure (n=41), were matched to children of mothers with no history of depression or SSRI use (n=82). Structural magnetic resonance imaging and diffusion weighted imaging scans were acquired with a 3T Siemens Allegra scanner. Global tissue volumes were characterized using an automatic, atlas-moderated expectation maximization segmentation tool. Local differences in gray matter volumes were examined using deformation-based morphometry. Quantitative tractography was performed using an adaptation of the UNC-Utah NA-MIC DTI framework. SSRI-exposed neonates exhibited widespread changes in white matter microstructure compared to matched controls. Children exposed to a history of maternal depression but no SSRIs showed no significant differences in brain development compared to matched controls. No significant differences were found in global or regional tissue volumes. Additional research is needed to clarify whether SSRIs directly alter white matter development or whether this relationship is mediated by depressive symptoms during pregnancy.

Dystrophin-deficient dogs with reduced myostatin have unequal muscle growth and greater joint contractures.

BACKGROUND: Myostatin (Mstn) is a negative regulator of muscle growth whose inhibition promotes muscle growth and regeneration. Dystrophin-deficient mdx mice in which myostatin is knocked out or inhibited postnatally have a less severe phenotype with greater total mass and strength and less fibrosis and fatty replacement of muscles than mdx mice with wild-type myostatin expression. Dogs with golden retriever muscular dystrophy (GRMD) have previously been noted to have increased muscle mass and reduced fibrosis after systemic postnatal myostatin inhibition. Based partly on these results, myostatin inhibitors are in development for use in human muscular dystrophies. However, persisting concerns regarding the effects of long-term and profound myostatin inhibition will not be easily or imminently answered in clinical trials. METHODS: To address these concerns, we developed a canine (GRippet) model by crossbreeding dystrophin-deficient GRMD dogs with Mstn-heterozygous (Mstn (+/-)) whippets. A total of four GRippets (dystrophic and Mstn (+/-)), three GRMD (dystrophic and Mstn wild-type) dogs, and three non-dystrophic controls from two litters were evaluated. RESULTS: Myostatin messenger ribonucleic acid (mRNA) and protein levels were downregulated in both GRMD and GRippet dogs. GRippets had more severe postural changes and larger (more restricted) maximal joint flexion angles, apparently due to further exaggeration of disproportionate effects on muscle size. Flexors such as the cranial sartorius were more hypertrophied on magnetic resonance imaging (MRI) in the GRippets, while extensors, including the quadriceps femoris, underwent greater atrophy. Myostatin protein levels negatively correlated with relative cranial sartorius muscle cross-sectional area on MRI, supporting a role in disproportionate muscle size. Activin receptor type IIB (ActRIIB) expression was higher in dystrophic versus control dogs, consistent with physiologic feedback between myostatin and ActRIIB. However, there was no differential expression between GRMD and GRippet dogs. Satellite cell exhaustion was not observed in GRippets up to 3 years of age. CONCLUSIONS: Partial myostatin loss may exaggerate selective muscle hypertrophy or atrophy/hypoplasia in GRMD dogs and worsen contractures. While muscle imbalance is not a feature of myostatin inhibition in mdx mice, findings in a larger animal model could translate to human experience with myostatin inhibitors.

Spatially Weighted Principal Component Analysis for Imaging Classification.

The aim of this paper is to develop a supervised dimension reduction framework, called Spatially Weighted Principal Component Analysis (SWPCA), for high dimensional imaging classification. Two main challenges in imaging classification are the high dimensionality of the feature space and the complex spatial structure of imaging data. In SWPCA, we introduce two sets of novel weights including global and local spatial weights, which enable a selective treatment of individual features and incorporation of the spatial structure of imaging data and class label information. We develop an e cient two-stage iterative SWPCA algorithm and its penalized version along with the associated weight determination. We use both simulation studies and real data analysis to evaluate the finite-sample performance of our SWPCA. The results show that SWPCA outperforms several competing principal component analysis (PCA) methods, such as supervised PCA (SPCA), and other competing methods, such as sparse discriminant analysis (SDA).

Cook's Distance Measures for Varying Coefficient Models with Functional Responses.

The aim of this paper is to develop Cook's distance measures for assessing the influence of both atypical curves and observations under varying coefficient model for functional responses. Our Cook's distance measures include Cook's distances for deleting multiple curves and for deleting multiple grid points, and their scaled Cook's distances. We systematically investigate some theoretical properties of these diagnostic measures. Simulation studies are conducted to evaluate the finite sample properties of these Cook's distances under different scenarios. A real diffusion tensor tract data set is analyzed to illustrate the use of our diagnostic measures.

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.