Sex Differences in the Human Brain Transcriptome of Cases With Schizophrenia

Hoffman, Gabriel E.; Ma, Yixuan; Montgomery, Kelsey S.; Bendl, Jaroslav; Jaiswal, Manoj Kumar; Kozlenkov, Alex; Peters, Mette A.; Dracheva, Stella; Fullard, John F.; Chess, Andrew; Devlin, Bernie; Sieberts, Solveig K.; Roussos, Panos

doi:10.1016/j.biopsych.2021.03.020

Cited by 46 publications

(44 citation statements)

References 54 publications

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“…Alternatively, we speculate that the different expression patterns of autosomal variants across sex (Boraska et al, 2012; Wijchers & Festenstein, 2011; Zuo et al, 2015) may account for the modulatory effects of sex. Indeed, in line with this speculation, recent literature highlights sex differences in brain transcriptomes related to schizophrenia and alcohol effects (Hitzemann et al, 2021; Hoffman et al, 2022). Future research may test the association between sex differences in genetic expression in the brain and neurocognitive development.…”

Section: Discussionmentioning

confidence: 75%

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

Kim

Joo

Ahn

et al. 2022

Human Brain Mapping

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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 2 p = .011-.034; adjusted for covariates) and higher cognitive genome-wide polygenic scores (GPSs) (p fdr < .001, η 2 p < .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.

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Section: Discussionmentioning

confidence: 75%

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

Kim

Joo

Ahn

et al. 2022

Human Brain Mapping

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“…However, the cell-type- and synapse-specific roles Nrxns perform remain enigmatic. Furthermore, stunning sex differences in the prevalence and symptomology of neuropsychiatric disorders such as schizophrenia (SCZ) and SUDs ( Becker, 2016 ; Hoffman et al, 2021 ; Leung and Chue, 2000 ) raise the possibility that adhesion molecule usage in SCZ and SUD-relevant circuits is sexually dimorphic.…”

Section: Introductionmentioning

confidence: 99%

Neurexin-3 defines synapse- and sex-dependent diversity of GABAergic inhibition in ventral subiculum

et al. 2021

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“…We explored whether expression of the 10 highest risk genes was dysregulated in schizophrenia cases compared with controls using the CommonMind Consortium database (https://www.synapse.org/#!Synapse:syn2759792). A total of 778 individuals (including 437 controls and 341 schizophrenia patients) (Hoffman et al, 2022) were analyzed, and only CACNA1G was found to be differentially expressed in cases (Supplementary Table 4, Supplemental Digital Content 4, http://links.lww.com/PG/ A286).…”

Section: Discussionmentioning

confidence: 99%

Association analysis of risk genes identified by SCHEMA with schizophrenia in the Chinese Han population

Ai-guo

Lun

Chen

et al. 2022

Psychiatric Genetics

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Background Schizophrenia is a chronic brain disorder. Previously, the Schizophrenia Exome Sequencing Metaanalysis consortium identified 10 highest risk genes related to schizophrenia. This study aimed to analyze the relationship between the 10 highest risk genes identified by the SCHEMA and schizophrenia in a Chinese population.Methods A total of 225 variants in 10 genes were screened in a Chinese population of 6836 using a customized array. All variants were annotated through the Variant Effect Predictor tool, and the functional impacts of missense variants were assessed based on sorting intolerant from tolerant and PolyPhen-2 scores. The SHEsisPlus tool was used to analyze the association between risk genes and schizophrenia at the locus and gene levels.Results At the locus level, no missense variants significantly related to schizophrenia were found, but we detected three missense variants that appeared only in cases, including TRIO p. Arg1185Gln, RB1CC1 p. Arg1514Cys, and HERC1 p. Val4517Leu. At the gene level, five genes (TRIO, RB1CC1, HERC1, GRIN2A, and CACAN1G) with more than one variant analyzed were kept for the gene-level association analysis. Only the association between RB1CC1 and schizophrenia reached a significant level (OR = 1.634; 95% CI, 1.062-2.516; P = 0.025). ConclusionIn this study, we determined that RB1CC1 might be a risk gene for schizophrenia in the Chinese population. Our results provide new evidence for recognizing the correlation of these risk genes with the Chinese schizophrenia population.

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Sex Differences in the Human Brain Transcriptome of Cases With Schizophrenia

Cited by 46 publications

References 54 publications

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

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

Neurexin-3 defines synapse- and sex-dependent diversity of GABAergic inhibition in ventral subiculum

Association analysis of risk genes identified by SCHEMA with schizophrenia in the Chinese Han population

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