Sex differences in neocortical structure and cognitive performance: A surface-based morphometry study

Evaluating the Impact of Intracranial Volume Correction Approaches on the Quantification of Intracranial Structures in MRI: A Systematic Analysis

BACKGROUND

In neuroscience, accurately quantifying individual brain regions in large cohorts is a challenge. Differences in intracranial structures can suggest functional differences, but they also reflect the effects of other factors. However, there is currently no standardized method for the correction of intracranial structure measurements.

PURPOSE

To identify the optimal method to counteract the influence of total intracranial volume (TIV) and gender on the measurement of intracranial structures.

STUDY TYPE

Prospective.

POPULATION/SUBJECTS

One hundred forty-one healthy adult volunteers (70 male, mean age 21.8 ± 1.7 years).

FIELD STRENGTH/SEQUENCE

T1-weighted 3D gradient-echo sequence at 3.0 T.

ASSESSMENT

A radiologist with 5 years of work experience screened the raw images to exclude poor-quality images. Freesurfer then performed automated segmentation to obtain measurements of intracranial structures. Male-only, female-only, and TIV-matched sub-samples were created separately. Comparisons between the original data and these sub-samples were used to assess the effects of gender and TIV. Comparison the consistency between TIV-matched sample and corrected data that corrected by four methods: Proportion method, power-corrected proportion method, covariate regression method, and residual method.

STATISTICAL TESTS

Cohen's d for examining group distribution disparities, t-tests for probing mean differences, correlation coefficients to assess the relationships between intracranial substructure measurements and TIV. Multiple comparison corrections were applied to the results.

RESULTS

The correlation coefficients between TIV and the volumes of intracranial structures ranged from 0.033 to 0.883, with an average of 0.467. Thirty significant volume differences were found among 36 structures in the original sample, while no differences were observed in the TIV-matched sample. Among the four correction methods, the residual method had highest consistency (similarity 94.4%) with the TIV-matched group.

DATA CONCLUSION

The variation in intracranial structure sizes between genders was largely attributable to TIV. The residual method offers a more accurate and effective approach for correcting the effects of TIV on intracranial structures.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

A Potential Mechanism of Neurological Impairment in Children With Infantile Spasm: Based on Microanatomic Structure Analysis Employing Voxel-Based Morphometry and Surface-Based Morphometry

BACKGROUND

Infantile epileptic spasms syndrome (IESS) would accompany with severe neurological impairment. Our study aimed to explore the potential mechanism by employing voxel-based and surface-based morphometry to detect brain microwould accompany with severe neurological impairment. Our study aimed to explore the potential mechanism by employing voxel-based and surface-based morphometry to detect brain microanatomic structure alteration.

METHODS

The IESS group had 21 males and 13 females (mean age: 17.7 ± 15.6 months), whereas the healthy controls group had 22 males and 10 females (mean age: 29.4 ± 18.7 months). High-resolution 3D T1WI was performed. Computational Anatomy Toolbox implemented in Statistical Parametric Mapping 12 was used to measure the gray matter and white matter volume, and the cortical thickness separately. Independent sample t test was used to assess between-group differences. IESS group was assessed using the Bayley Scales of Infant Development.

RESULTS

The IESS group showed a significantly decreased volume of gray matter in right middle temporal gyrus, inferior temporal gyrus, superior temporal gyrus, right fusiform, and bilateral precuneus (P < 0.001). There were no significant between-group differences with respect to white matter volume or cortical thickness (P > 0.001). The results of Bayley Scales of Infant Development showed that the Mental Development Index (MDI) and Psychomotor Development Index scores of children with IESS were almost concentrated in the range of <70. MDI score showed a positive correlation with gray matter reduction area in IESS group.

CONCLUSION

Children with IESS had impaired cognitive and delayed motor development. And the decreased gray matter in the right temporal lobe, fusiform, and bilateral precuneus could be the potential anatomic basis for impaired function, such as hearing, visual, and language.

Biomechanics of Traumatic Head and Neck Injuries on Women: A State-of-the-Art Review and Future Directions

The biomechanics of traumatic injuries of the human body as a consequence of road crashes, falling, contact sports, and military environments have been studied for decades. In particular, traumatic brain injury (TBI), the so-called "silent epidemic", is the traumatic insult responsible for the greatest percentage of death and disability, justifying the relevance of this research topic. Despite its great importance, only recently have research groups started to seriously consider the sex differences regarding the morphology and physiology of women, which differs from men and may result in a specific outcome for a given traumatic event. This work aims to provide a summary of the contributions given in this field so far, from clinical reports to numerical models, covering not only the direct injuries from inertial loading scenarios but also the role sex plays in the conditions that precede an accident, and post-traumatic events, with an emphasis on neuroendocrine dysfunctions and chronic traumatic encephalopathy. A review on finite element head models and finite element neck models for the study of specific traumatic events is also performed, discussing whether sex was a factor in validating them. Based on the information collected, improvement perspectives and future directions are discussed.

Surface-based brain morphometry in schizophrenia vs. cannabis-induced psychosis: A controlled comparison

BACKGROUND & AIM

We examined group differences in cortical thickness and surface-parameters among age and handedness--matched persons with cannabis-induced psychosis (CIP), schizophrenia with heavy cannabis use (SZC), and healthy controls (HC).

METHODS

We recruited 31 men with SZC, 28 with CIP, and 30 with HC. We used the Psychiatric Research Interview for Substance and Mental Disorders to differentiate between CIP and SZC. We processed and analyzed T1 MR images using the Surface-based Brain Morphometry (SBM) pipeline of the CAT-12 toolbox within the statistical parametric mapping. After pre-processing, volumes were segmented using surface and thickness estimation for the analysis of the region of interest. We used the projection-based thickness method to assess the cortical thickness and Desikan-Killiany atlas for cortical parcellation.

RESULTS

We observed the lowest cortical thickness, depth, and gyrification in the SZC, followed by CIP and the control groups. The differences were predominantly seen in frontal cortices, with limited parietal and temporal regions involvement. After False Discovery Rate (FDR) corrections and post-hoc analysis, SZC had reduced cortical thickness than HC in the middle and inferior frontal, right entorhinal, and left postcentral regions. Cortical thickness of SZC was also significantly lower than CIP in bilateral postcentral and right middle frontal regions. We found negative correlations (after FDR corrections) between the duration of cannabis use and cortical thickness in loci of parietal and occipital cortices.

CONCLUSION

Our study suggested cortical structural abnormalities in schizophrenia, in reference to healthy controls and cannabis-induced psychosis, indicating different pathophysiology of SZC and CIP.

Sex and gender differences in mild traumatic brain injury/concussion

The high incidence of concussions/mild traumatic brain injury and the significant number of people with persisting concussion symptoms as well as the concern for delayed, neurodegenerative effects of concussions makes them a major public health concern. There is much to learn on concussions with respect to pathophysiology as well as vulnerability and resiliency factors. The heterogeneity in outcome after a concussion warrants a more personalized approach to better understand the biological and psychosocial factors that may affect outcome. In this chapter we address biological sex and gender as they impact different aspects of concussion including incidence, risk factors and outcome. As well, this chapter will provide a more fulsome overview of intimate partner violence, an often-overlooked cause of concussion in women. Applying the sex and gender lens to concussion/mild traumatic brain injury is imperative for discovery of its pathophysiology and moving closer to treatments.

Investigating sexual dimorphism in human brain structure by combining multiple indexes of brain morphology and source-based morphometry

Computational morphometry of magnetic resonance images represents a powerful tool for studying macroscopic differences in human brains. In the present study (N participants = 829), we combined different techniques and measures of brain morphology to investigate one of the most compelling topics in neuroscience: sexual dimorphism in human brain structure. When accounting for overall larger male brains, results showed limited sex differences in gray matter volume (GMV) and surface area. On the other hand, we found larger differences in cortical thickness, favoring both males and females, arguably as a result of region-specific differences. We also observed higher values of fractal dimension, a measure of cortical complexity, for males versus females across the four lobes. In addition, we applied source-based morphometry, an alternative method for measuring GMV based on the independent component analysis. Analyses on independent components revealed higher GMV in fronto-parietal regions, thalamus and caudate nucleus for females, and in cerebellar- temporal cortices and putamen for males, a pattern that is largely consistent with previous findings.

Neocortical Age and Fluid Ability: Greater Accelerated Brain Aging for Thickness, but Smaller for Surface Area, in High Cognitive Ability Individuals

Biological (BA) and chronological (CA) age may or may not fit. The available evidence reveals remarkable individual differences in the overlap/mismatch between BA and CA. Increased mismatch can be interpreted as delayed (BA/CA < 1) or accelerated biological aging (BA/CA > 1). Body and brain health are correlated and both predict aging outcomes associated with physical and mental fitness. Moreover, research has shown that older brain age at midlife correlates negatively with cognitive ability measured in early childhood, which suggests early life predisposition to accelerated aging in adulthood. Under this framework, here we test if increased cognitive ability is associated with delayed brain aging, analyzing structural MRI data of 188 individuals, sixty of whom were recruited from MENSA, an association comprising individuals who obtained cognitive ability scores in the top 2 percent of the population. These high ability individuals (HCA) showed an average advantage of 33 IQ points, on a fluid reasoning test they completed for this research, over those other recruited because of their average cognitive ability (ACA). Next, brain age was computed at the individual level for two distinguishable neocortical features (thickness and surface area) according to models trained in an independent large-scale sample of 2377 individuals. Results revealed a stronger pattern of accelerated brain aging in HCA compared to ACA individuals for thickness, while the opposite pattern was suggested for surface area. The findings align well with the greater relevance of individual differences in cortical surface area for enhancing our understanding of cognitive differences at the brain level.

Considering Biological Sex in Traumatic Brain Injury

Published epidemiological studies of traumatic brain injury (TBI) of all severities consistently report higher incidence in men. Recent increases in the participation of women in sports and active military service as well as increasing awareness of the very large number of women who sustain but do not report TBI as a result of intimate partner violence (IPV) suggest that the number of women with TBI is significantly larger than previously believed. Women are also grossly under-represented in clinical and natural history studies of TBI, most of which include relatively small numbers of women, ignore the role of sex- and age-related gonadal hormone levels, and report conflicting results. The emerging picture from recent studies powered to detect effects of biological sex as well as age (as a surrogate of hormonal status) suggest young (i.e., premenopausal) women are more likely to die from TBI relative to men of the same age group, but this is reversed in the 6th and 7th decades of life, coinciding with postmenopausal status in women. New data from concussion studies in young male and female athletes extend this finding to mild TBI, since female athletes who sustained mild TBI are significantly more likely to report more symptoms than males. Studies including information on gonadal hormone status at the time of injury are still too scarce and small to draw reliable conclusions, so there is an urgent need to include biological sex and gonadal hormone status in the design and analysis of future studies of TBI.

Structural differences between male and female brains

Research based on structural magnetic resonance imaging (MRI) has revealed a number of sex differences in the anatomy of the human brain. The first part of this chapter presents an excerpt of these findings discriminating among effects on a global, regional, and local level. While findings are far from consistent and conclusive, there is general consensus with respect to sex-specific brain size, with male brains being bigger on average than female brains. So, the question arises as to whether any of the observed sex differences are merely driven by brain size. The second part of this chapter thus sheds light on a unique scientific attempt to discriminate between brain size effects and sex effects. The overarching goal of this chapter is to exemplify the variety of findings and to demonstrate that the presence, magnitude, and direction of significant sex differences strongly depend on the measurement applied. The assumption that sex differences are simply a by-product of brain size, rather than pure (size independent) sex effects has proven to be true for some but certainly not all findings. Therefore, when examining the possible sexual dimorphism of the brain, it is imperative to avoid oversimplification and generalization.

Brain Morphological Dynamics of Procrastination: The Crucial Role of the Self-Control, Emotional, and Episodic Prospection Network

Globally, about 17% individuals are suffering from the maladaptive procrastination until now, which impacts individual's financial status, mental health, and even public policy. However, the comprehensive understanding of neuroanatomical understructure of procrastination still remains gap. 688 participants including 3 independent samples were recruited for this study. Brain morphological dynamics referred to the idiosyncrasies of both brain size and brain shape. Multilinear regression analysis was utilized to delineate brain morphological dynamics of procrastination in Sample 1. In the Sample 2, cross-validation was yielded. Finally, prediction models of machine learning were conducted in Sample 3. Procrastination had a significantly positive correlation with the gray matter volume (GMV) in the left insula, anterior cingulate gyrus (ACC), and parahippocampal gyrus (PHC) but was negatively correlated with GMV of dorsolateral prefrontal cortex (dlPFC) and gray matter density of ACC. Furthermore, procrastination was positively correlated to the cortical thickness and cortical complexity of bilateral orbital frontal cortex (OFC). In Sample 2, all the results were cross-validated highly. Predication analysis demonstrated that these brain morphological dynamic can predict procrastination with high accuracy. This study ascertained the brain morphological dynamics involving in self-control, emotion, and episodic prospection brain network for procrastination, which advanced promising aspects of the biomarkers for it.

Sex differences in gray matter volume: how many and how large are they really?

Background

Studies assessing volumetric sex differences have provided contradictory results. Total intracranial volume (TIV) is a major confounding factor when estimating local volumes of interest (VOIs). We investigated how the number, size, and direction of sex differences in gray matter volume (GMv) vary depending on how TIV variation is statistically handled.

Methods

Sex differences in the GMv of 116 VOIs were assessed in 356 participants (171 females) without correcting for TIV variation or after adjusting the data with 5 different methods (VBM8 non-linear-only modulation, proportions, power-corrected-proportions, covariation, and the residuals method). The outcomes obtained with these procedures were compared to each other and to those obtained in three criterial subsamples, one comparing female-male pairs matched on their TIV and two others comparing groups of either females or males with large/small TIVs. Linear regression was used to quantify TIV effects on raw GMv and the efficacy of each method in controlling for them.

Results

Males had larger raw GMv than females in all brain areas, but these differences were driven by direct TIV-VOIs relationships and more closely resembled the differences observed between individuals with large/small TIVs of sex-specific subsamples than the sex differences observed in the TIV-matched subsample. All TIV-adjustment methods reduced the number of sex differences but their results were very different. The VBM8- and the proportions-adjustment methods inverted TIV-VOIs relationships and resulted in larger adjusted volumes in females, promoting sex differences largely attributable to TIV variation and very distinct from those observed in the TIV-matched subsample. The other three methods provided results unrelated to TIV and very similar to those of the TIV-matched subsample. In these datasets, sex differences were bidirectional and achieved satisfactory replication rates in 19 VOIs, but they were “small” (d < ∣0.38∣) and most of them faded away after correcting for multiple comparisons.

Conclusions

There is not just one answer to the question of how many and how large the sex differences in GMv are, but not all the possible answers are equally valid. When TIV effects are ruled out using appropriate adjustment methods, few sex differences (if any) remain statistically significant, and their size is quite reduced.

Electronic supplementary material

The online version of this article (10.1186/s13293-019-0245-7) contains supplementary material, which is available to authorized users.

Genes, Cells and Brain Areas of Intelligence

What is the neurobiological basis of human intelligence? The brains of some people seem to be more efficient than those of others. Understanding the biological foundations of these differences is of great interest to basic and applied neuroscience. Somehow, the secret must lie in the cells in our brain with which we think. However, at present, research into the neurobiology of intelligence is divided between two main strategies: brain imaging studies investigate macroscopic brain structure and function to identify brain areas involved in intelligence, while genetic associations studies aim to pinpoint genes and genetic loci associated with intelligence. Nothing is known about how properties of brain cells relate to intelligence. The emergence of transcriptomics and cellular neuroscience of intelligence might, however, provide a third strategy and bridge the gap between identified genes for intelligence and brain function and structure. Here, we discuss the latest developments in the search for the biological basis of intelligence. In particular, the recent availability of very large cohorts with hundreds of thousands of individuals have propelled exciting developments in the genetics of intelligence. Furthermore, we discuss the first studies that show that specific populations of brain cells associate with intelligence. Finally, we highlight how specific genes that have been identified generate cellular properties associated with intelligence and may ultimately explain structure and function of the brain areas involved. Thereby, the road is paved for a cellular understanding of intelligence, which will provide a conceptual scaffold for understanding how the constellation of identified genes benefit cellular functions that support intelligence.

The macro-structural variability of the human neocortex

The human neocortex shows a considerable individual structural variability. While primary gyri and sulci are found in all normally developed brains and bear clear-cut gross structural descriptions, secondary structures are highly variable and not present in all brains. The blend of common and individual structures poses challenges when comparing structural and functional results from quantitative neuroimaging studies across individuals, and sets limits on the precision of location information much above the spatial resolution of current neuroimaging methods. This work aimed at quantifying structural variability on the neocortex, and at assessing the spatial relationship between regions common to all brains and their individual structural variants. Based on structural MRI data provided as the "900 Subjects Release" of the Human Connectome Project, a data-driven analytic approach was employed here from which the definition of seven cortical "communities" emerged. Apparently, these communities comprise common regions of structural features, while the individual variability is confined within a community. Similarities between the community structure and the state of the brain development at gestation week 32 lead suggest that communities are segregated early. Subdividing the neocortex into communities is suggested as anatomically more meaningful than the traditional lobar structure.

Association Between the Probability of Autism Spectrum Disorder and Normative Sex-Related Phenotypic Diversity in Brain Structure

Importance

Autism spectrum disorder (ASD) is 2 to 5 times more common in male individuals than in female individuals. While the male preponderant prevalence of ASD might partially be explained by sex differences in clinical symptoms, etiological models suggest that the biological male phenotype carries a higher intrinsic risk for ASD than the female phenotype. To our knowledge, this hypothesis has never been tested directly, and the neurobiological mechanisms that modulate ASD risk in male individuals and female individuals remain elusive.

Objectives

To examine the probability of ASD as a function of normative sex-related phenotypic diversity in brain structure and to identify the patterns of sex-related neuroanatomical variability associated with low or high probability of ASD.

Design, Setting, and Participants

This study examined a cross-sectional sample of 98 right-handed, high-functioning adults with ASD and 98 matched neurotypical control individuals aged 18 to 42 years. A multivariate probabilistic classification approach was used to develop a predictive model of biological sex based on cortical thickness measures assessed via magnetic resonance imaging in neurotypical controls. This normative model was subsequently applied to individuals with ASD. The study dates were June 2005 to October 2009, and this analysis was conducted between June 2015 and July 2016.

Main Outcomes and Measures

Sample and population ASD probability estimates as a function of normative sex-related diversity in brain structure, as well as neuroanatomical patterns associated with low or high ASD probability in male individuals and female individuals.

Results

Among the 98 individuals with ASD, 49 were male and 49 female, with a mean (SD) age of 26.88 (7.18) years. Among the 98 controls, 51 were male and 47 female, with a mean (SD) age of 27.39 (6.44) years. The sample probability of ASD increased significantly with predictive probabilities for the male neuroanatomical brain phenotype. For example, biological female individuals with a more male-typic pattern of brain anatomy were significantly (ie, 3 times) more likely to have ASD than biological female individuals with a characteristically female brain phenotype (P = .72 vs .24, respectively; χ21 = 20.26; P < .001; difference in P values, 0.48; 95% CI, 0.29-0.68). This finding translates to an estimated variability in population prevalence from 0.2% to 1.3%, respectively. Moreover, the patterns of neuroanatomical variability carrying low or high ASD probability were sex specific (eg, in inferior temporal regions, where ASD has different neurobiological underpinnings in male individuals and female individuals).

Conclusions and Relevance

These findings highlight the need for considering normative sex-related phenotypic diversity when determining an individual's risk for ASD and provide important novel insights into the neurobiological mechanisms mediating sex differences in ASD prevalence.

Advances in Intelligence Research: What Should be Expected in the XXI Century (Questions & Answers)

Here I briefly delineate my view about the main question of this International Seminar, namely, what should we expecting from the XXI Century regarding the advancements in intelligence research. This view can be summarized as 'The Brain Connection' (TBC), meaning that neuroscience will be of paramount relevance for increasing our current knowledge related to the key question: why are some people smarter than others? We need answers to the issue of what happens in our brains when the genotype and the environment are integrated. The scientific community has devoted great research efforts, ranging from observable behavior to hidden genetics, but we are still far from having a clear general picture of what it means to be more or less intelligent. After the discussion held with the panel of experts participating in the seminar, it is concluded that advancements will be more solid and safe increasing the collaboration of scientists with shared research interests worldwide. Paralleling current sophisticated analyses of how the brain computes, nowadays science may embrace a network approach.

Prefrontal Cortex Structure Predicts Training-Induced Improvements in Multitasking Performance

The ability to perform multiple, concurrent tasks efficiently is a much-desired cognitive skill, but one that remains elusive due to the brain's inherent information-processing limitations. Multitasking performance can, however, be greatly improved through cognitive training (Van Selst et al., 1999, Dux et al., 2009). Previous studies have examined how patterns of brain activity change following training (for review, see Kelly and Garavan, 2005). Here, in a large-scale human behavioral and imaging study of 100 healthy adults, we tested whether multitasking training benefits, assessed using a standard dual-task paradigm, are associated with variability in brain structure. We found that the volume of the rostral part of the left dorsolateral prefrontal cortex (DLPFC) predicted an individual's response to training. Critically, this association was observed exclusively in a task-specific training group, and not in an active-training control group. Our findings reveal a link between DLPFC structure and an individual's propensity to gain from training on a task that taps the limits of cognitive control.

SIGNIFICANCE STATEMENT

Cognitive "brain" training is a rapidly growing, multibillion dollar industry (Hayden, 2012) that has been touted as the panacea for a variety of disorders that result in cognitive decline. A key process targeted by such training is "cognitive control." Here, we combined an established cognitive control measure, multitasking ability, with structural brain imaging in a sample of 100 participants. Our goal was to determine whether individual differences in brain structure predict the extent to which people derive measurable benefits from a cognitive training regime. Ours is the first study to identify a structural brain marker-volume of left hemisphere dorsolateral prefrontal cortex-associated with the magnitude of multitasking performance benefits induced by training at an individual level.

An Allometric Analysis of Sex and Sex Chromosome Dosage Effects on Subcortical Anatomy in Humans

Structural neuroimaging of humans with typical and atypical sex-chromosome complements has established the marked influence of both Yand X-/Y-chromosome dosage on total brain volume (TBV) and identified potential cortical substrates for the psychiatric phenotypes associated with sex-chromosome aneuploidy (SCA). Here, in a cohort of 354 humans with varying karyotypes (XX, XY, XXX, XXY, XYY, XXYY, XXXXY), we investigate sex and SCA effects on subcortical size and shape; focusing on the striatum, pallidum and thalamus. We find large effect-size differences in the volume and shape of all three structures as a function of sex and SCA. We correct for TBV effects with a novel allometric method harnessing normative scaling rules for subcortical size and shape in humans, which we derive here for the first time. We show that all three subcortical volumes scale sublinearly with TBV among healthy humans, mirroring known relationships between subcortical volume and TBV among species. Traditional TBV correction methods assume linear scaling and can therefore invert or exaggerate sex and SCA effects on subcortical anatomy. Allometric analysis restricts sex-differences to: (1) greater pallidal volume (PV) in males, and (2) relative caudate head expansion and ventral striatum contraction in females. Allometric analysis of SCA reveals that supernumerary X- and Y-chromosomes both cause disproportionate reductions in PV, and coordinated deformations of striatopallidal shape. Our study provides a novel understanding of sex and sex-chromosome dosage effects on subcortical organization, using an allometric approach that can be generalized to other basic and clinical structural neuroimaging settings.

Age effects on cortical thickness in young Down's syndrome subjects: a cross-sectional gender study

INTRODUCTION

The aim of this study was to determine differences in the characteristic pattern of age-related cortical thinning in men and women with Down's syndrome (DS) by means of MRI and automatic cortical thickness measurements and a cross-sectional design, in a large cohort of young subjects.

METHODS

Eighty-four subjects with DS, 30 females (11-35 years, mean age ± SD = 22.8 ± 5.9) and 54 males (11-35 years, mean age ± SD = 21.5 ± 6.5), were examined using a 1.5-T scanner. MRI-based quantification of cortical thickness was performed using FreeSurfer software package. For all subjects participating in the study, the Pearson product-moment correlation coefficient between age and mean cortical thickness values has been evaluated.

RESULTS

A significant negative correlation between cortical thickness and age was found in female DS subjects, predominantly in frontal and parietal lobes, bilaterally. In male DS subjects, a significant negative correlation between cortical thickness and age was found in the right fronto-temporal lobes and cingulate regions. Whole brain mean cortical thickness values were significantly negative correlated with age only in female DS subjects.

CONCLUSIONS

Females with Down's syndrome showed a strong correlation between cortical thickness and age, already in early age. We suggest that the cognitive impairment due to hormonal deficit in the postmenopausal period could be emphasized by the early structural decline of gray matter in female DS subjects.