Tan, G.C.-Y.; (2011) Genetic dissection of sex differences in human brain and behaviour. Doctoral thesis , UCL (University College London).

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Abstract

The importance of sex differences in the brain and behaviour is indisputable. It forms the basis for differences in risk across a range of neurological and psychiatric disorders, as well as gender roles within society. The classical approach to investigating sex differences primarily involves comparisons between males and females. While informative for characterizing the wide array of sexually dimorphic traits, straight comparisons are insufficient to elucidate specific molecular contributions due to the multiplicity of confounding factors. Discrete genetic polymorphisms can be used to investigate variance in these traits due to sex-related molecular factors independent of confounds of sex. This thesis applies candidate genetics to understand the specific contributions of molecular components of the sex hormone pathways to sexual dimorphism in brain structure, personality and cognition. A cohort of 384 individuals were recruited to undergo MRI brain scans, cognitive and personality testing. They also provided blood samples for candidate genotyping in polymorphisms in genes for the androgen receptor, oestrogen receptors, progesterone receptor and aromatase enzyme that converts testosterone to oestrogen. Voxel-based morphometry was used to characterise regional differences in brain volume accounted for by these polymorphisms and the relationship to sex differences in brain volume. Diffusion tensor imaging was then used to determine variation in white matter integrity and structural connectivity due to these polymorphisms. Sex differences in personality and cognition are further investigated in terms of correlations with the polymorphisms and brain structure. Finally an endophenotype approach was used to investigate differential risk for conditions such as Alzheimer’s disease and depression between sexes through related brain and personality-based traits. The neural and molecular genetic mechanisms underlying this risk are inferred from correlations with brain-based measures and genotype. The strengths and weaknesses of this approach and the scientific implications of this work to gender research are discussed.

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