Sex continuum in the brain and body during adolescence and psychological traits

Modeling brain sex in the limbic system as phenotype for female-prevalent mental disorders

BACKGROUND

Sex differences exist in the prevalence and clinical manifestation of several mental disorders, suggesting that sex-specific brain phenotypes may play key roles. Previous research used machine learning models to classify sex from imaging data of the whole brain and studied the association of class probabilities with mental health, potentially overlooking regional specific characteristics.

METHODS

We here investigated if a regionally constrained model of brain volumetric imaging data may provide estimates that are more sensitive to mental health than whole brain-based estimates. Given its known role in emotional processing and mood disorders, we focused on the limbic system. Using two different cohorts of healthy subjects, the Human Connectome Project and the Queensland Twin IMaging, we investigated sex differences and heritability of brain volumes of limbic structures compared to non-limbic structures, and subsequently applied regionally constrained machine learning models trained solely on limbic or non-limbic features. To investigate the biological underpinnings of such models, we assessed the heritability of the obtained sex class probability estimates, and we investigated the association with major depression diagnosis in an independent clinical sample. All analyses were performed both with and without controlling for estimated total intracranial volume (eTIV).

RESULTS

Limbic structures show greater sex differences and are more heritable compared to non-limbic structures in both analyses, with and without eTIV control. Consequently, machine learning models performed well at classifying sex based solely on limbic structures and achieved performance as high as those on non-limbic or whole brain data, despite the much smaller number of features in the limbic system. The resulting class probabilities were heritable, suggesting potentially meaningful underlying biological information. Applied to an independent population with major depressive disorder, we found that depression is associated with male-female class probabilities, with largest effects obtained using the limbic model. This association was significant for models not controlling for eTIV whereas in those controlling for eTIV the associations did not pass significance correction.

CONCLUSIONS

Overall, our results highlight the potential utility of regionally constrained models of brain sex to better understand the link between sex differences in the brain and mental disorders.

Sex and Gender in Population Neuroscience

To understand psychiatric and neurological disorders and the structural and functional properties of the human brain, it is essential to consider the roles of sex and gender. In this chapter, I first define sex and gender and describe studies of sex differences in non-human animals. In humans, I describe the sex differences in behavioral and clinical phenotypes and neuroimaging-derived phenotypes, including whole-brain measures, regional subcortical and cortical measures, and structural and functional connectivity. Although structural whole-brain sex differences are large, regional effects (adjusting for whole-brain volumes) are typically much smaller and often fail to replicate. Nevertheless, while an individual neuroimaging feature may have a small effect size, aggregating them in a "maleness/femaleness" score or machine learning multivariate paradigm may prove to be predictive and informative of sex- and gender-related traits. Finally, I conclude by summarizing emerging investigations of gender norms and gender identity and provide methodological recommendations to incorporate sex and gender in population neuroscience research.

Self-reported emotional and behavioral problems among school-going adolescents in Nepal-A cross-sectional study

BACKGROUND

Studies on self-reported emotional and behavioral problems (EBPs) among adolescents are still sparse in many low- and middle-income countries. In Nepal, no such studies have been performed on a larger scale, and little is known about self-reported EBPs in the adolescent population.

METHODS

This cross-sectional, school-based study on EBPs included 1904 adolescents aged 11-18 years, enrolled in government and private schools located in 16 districts in Nepal. The Nepali version of the Youth Self Report form was used to assess self-reported EBPs, and the Teacher Report Form was used to assess academic performance. Analysis of variance (ANOVA) was used for gender comparisons on adolescents' EBPs and on academic competence. Multiple regression analysis was done to explore correlates of self-reported EBPs.

RESULTS

The overall prevalence of self-reported EBPs was 14.2%; 15.6% in boys and 12.9% in girls. The mean Total Problems score was 39.27 (standard deviation = 24.16); no gender differences were observed. Boys scored higher on Externalizing Problems and girls scored higher on Internalizing Problems. The effect sizes for gender comparisons were small with Hedges' g ranging from -0.29 to 0.28. Physical illness and negative/traumatic life events were positively correlated with self-reported EBPs, whereas academic performance was negatively correlated. However, the effect sizes were small (η2 < 0.02).

CONCLUSION

This study helps to narrow the knowledge gap on the prevalence, magnitude, and types of self-reported EBPs in Nepali adolescents. It demonstrated an association between self-reported EBPs and academic performance and linked self-reported EBPs to other factors such as negative/traumatic life events and physical illness. The findings might assist health authorities in the planning of mental health services and may also provide valuable background information to clinicians dealing with adolescent mental health problems.

The genetics of a "femaleness/maleness" score in cardiometabolic traits in the UK biobank

We recently devised continuous "sex-scores" that sum up multiple quantitative traits, weighted by their respective sex-difference effect sizes, as an approach to estimating polyphenotypic "maleness/femaleness" within each binary sex. To identify the genetic architecture underlying these sex-scores, we conducted sex-specific genome-wide association studies (GWASs) in the UK Biobank cohort (females: n = 161,906; males: n = 141,980). As a control, we also conducted GWASs of sex-specific "sum-scores", simply aggregating the same traits, without weighting by sex differences. Among GWAS-identified genes, while sum-score genes were enriched for genes differentially expressed in the liver in both sexes, sex-score genes were enriched for genes differentially expressed in the cervix and across brain tissues, particularly for females. We then considered single nucleotide polymorphisms with significantly different effects (sdSNPs) between the sexes for sex-scores and sum-scores, mapping to male-dominant and female-dominant genes. Here, we identified brain-related enrichment for sex-scores, especially for male-dominant genes; these findings were present but weaker for sum-scores. Genetic correlation analyses of sex-biased diseases indicated that both sex-scores and sum-scores were associated with cardiometabolic, immune, and psychiatric disorders.

Breaking the binary: Gender versus sex analysis in human brain imaging

Despite decades of pursuit, human brain imaging has yet to uncover clear neural correlates of male-female behavioral differences. Given that such behavior does not always align with sex categories, we argue that neuroimaging research may find more success by partitioning subjects along nonbinary gender attributes in addition to sex. We review the handful of studies that have done this, several of which find as good or better association between brain measures and "gender" as they do with "sex." Recent advances in operationalizing "gender" as a multidimensional variable should facilitate such studies, along with discovery-based approaches that mine brain imaging data for gender-associated attributes, independent of sex.

The sexual brain, genes, and cognition: A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children

Sex impacts the development of the brain and cognition differently across individuals. However, the literature on brain sex dimorphism in humans is mixed. We aim to investigate the biological underpinnings of the individual variability of sexual dimorphism in the brain and its impact on cognitive performance. To this end, we tested whether the individual difference in brain sex would be linked to that in cognitive performance that is influenced by genetic factors in prepubertal children (N = 9,658, ages 9-10 years old; the Adolescent Brain Cognitive Development study). To capture the interindividual variability of the brain, we estimated the probability of being male or female based on the brain morphometry and connectivity features using machine learning (herein called a brain sex score). The models accurately classified the biological sex with a test ROC-AUC of 93.32%. As a result, a greater brain sex score correlated significantly with greater intelligence (p_fdr  < .001, η p 2 $$ {\eta}_p^2 $$  = .011-.034; adjusted for covariates) and higher cognitive genome-wide polygenic scores (GPSs) (p_fdr  < .001, η p 2 $$ {\eta}_p^2 $$  < .005). Structural equation models revealed that the GPS-intelligence association was significantly modulated by the brain sex score, such that a brain with a higher maleness score (or a lower femaleness score) mediated a positive GPS effect on intelligence (indirect effects = .006-.009; p = .002-.022; sex-stratified analysis). The finding of the sex modulatory effect on the gene-brain-cognition relationship presents a likely biological pathway to the individual and sex differences in the brain and cognitive performance in preadolescence.

The genetics of testosterone contributes to "femaleness/maleness" of cardiometabolic traits and type 2 diabetes

The genetic architecture of testosterone is highly distinct between sexes. Moreover, obesity is associated with higher testosterone in females but lower testosterone in males. Here, we ask whether male-specific testosterone variants are associated with a male pattern of obesity and type 2 diabetes (T2D) in females, and vice versa. In the UK Biobank, we conducted sex-specific genome-wide association studies and computed polygenic scores for total (PGS_TT) and bioavailable testosterone (PGS_BT). We tested sex-congruent and sex-incongruent associations between sex-specific PGS_Ts and metabolic traits, as well as T2D diagnosis. Female-specific PGS_BT was associated with an elevated cardiometabolic risk and probability of T2D, in both sexes. Male-specific PGS_TT was associated with traits conferring a lower cardiometabolic risk and probability of T2D, in both sexes. We demonstrate the value in considering polygenic testosterone as sex-related continuous traits, in each sex.

Sex differences in schizophrenia relevant to clinical care

Introduction: Most medical diagnoses present somewhat differently in men and women, more so at specific periods of life. Treatment effects may also differ. This is true for schizophrenia, where premorbid effects are experienced earlier in life in boys than in girls, and where symptoms and outcomes differ.Areas covered: This review does not cover all the differences that have been reported between men and women but, instead, focuses on the ones that carry important implications for clinical care: effective antipsychotic doses, medication side effects, symptom fluctuation due to hormonal levels, comorbidities, and women's requirements for prenatal, obstetric, postpartum, and parenting support.Expert opinion: Of consequence to schizophrenia, sex-biased genes, epigenetic modifications, and sex steroids all impact the structure and function of the brain. Furthermore, life experiences and social roles exert major sex-specific influences. The co-morbidities that accompany schizophrenia also affect men and women to different degrees. This review offers several examples of sex-specific intervention and concludes that gold standard treatment must look beyond symptoms and address all the physiologic, psychologic, and social role needs of men and women suffering from this psychiatric disorder.