Leveraging sex-genetic interactions to understand brain disorders: recent advances and current gaps

Abstract

It is established that there are sex differences in terms of prevalence, age of onset, clinical manifestations, and response to treatment for a variety of brain disorders, including neurodevelopmental, psychiatric, and neurodegenerative disorders. Cohorts of increasing sample sizes with diverse data types collected, including genetic, transcriptomic and/or phenotypic data, are providing the building blocks to permit analytical designs to test for sex-biased genetic variant-trait associations, and for sex-biased transcriptional regulation. Such molecular assessments can contribute to our understanding of the manifested phenotypic differences between the sexes for brain disorders, offering the future possibility of delivering personalized therapy for females and males. With the intention of raising the profile of this field as a research priority, this review aims to shed light on the importance of investigating sex-genetic interactions for brain disorders, focusing on two areas: (i) variant-trait associations and (ii) transcriptomics (i.e. gene expression, transcript usage and regulation). We specifically discuss recent advances in the field, current gaps and provide considerations for future studies.

Keywords: brain; gene expression; genetic association; sex-bias.

Graphical abstract

Figure 1

Visual representation of the aim of this review. Here we summarise sex-biased variant-trait associations and gene expression to better understand phenotypic sex differences in brain disorders.

Figure 2

Power curves at varying sample sizes. Power curves corresponding to three genetic variants each with an odds ratio (OR) of 1.1 with different minor allele frequency (MAF) for a binary trait.

Figure 3

Number of reported variants (unique base pair positions) present in the EBI-NHLBI GWAS catalog (last updated 2023-06-22) split by chromosome base pair length (A) or coding sequence length of canonical transcripts of protein-coding genes (B). The coding sequence length is based on data from Gencode version 44. The line is the regression line for autosomal data, and the shaded area around it represents the 95% confidence interval. The autosomes are represented by circles. The X chromosome is represented by a triangle and the Y is represented by a square.