Xueyi Shen

Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants

Abstract Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44–77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume, total surface area, mean cortical thickness, or height. There was generally greater male variance across the raw structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function.

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank

Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders.

Subcortical volume and white matter integrity abnormalities in major depressive disorder: Findings from UK Biobank imaging data

Previous reports of altered grey and white matter structure in Major Depressive Disorder (MDD) have been inconsistent. Recent meta-analyses have, however, reported reduced hippocampal grey matter volume in MDD and reduced white matter integrity in several brain regions. The use of different diagnostic criteria, scanners and imaging sequences may, however, obscure further anatomical differences. In this study, we tested for differences in subcortical grey matter volume (n = 1157) and white matter integrity (n = 1089) between depressed individuals and controls in the subset of 8590 UK Biobank Imaging study participants who had undergone depression assessments. Whilst we found no significant differences in subcortical volumes, significant reductions were found in depressed individuals versus controls in global white matter integrity, as measured by fractional anisotropy (FA) (β = −0.182, p = 0.005). We also found reductions in FA in association/commissural fibres (β = −0.184, pcorrected = 0.010) and thalamic radiations (β = −0.159, pcorrected = 0.020). Tract-specific FA reductions were also found in the left superior longitudinal fasciculus (β = −0.194, pcorrected = 0.025), superior thalamic radiation (β = −0.224, pcorrected = 0.009) and forceps major (β = −0.193, pcorrected = 0.025) in depression (all betas standardised). Our findings provide further evidence for disrupted white matter integrity in MDD.

Genome-wide association study of depression phenotypes in UK Biobank (n = 322,580) identifies the enrichment of variants in excitatory synaptic pathways

Depression is a polygenic trait that causes extensive periods of disability and increases the risk of suicide, a leading cause of death in young people. Previous genetic studies have identified a number of common risk variants which have increased in number in line with increasing sample sizes. We conducted a genome-wide association study (GWAS) in the largest single population-based cohort to date, UK Biobank. This allowed us to estimate the effects of ≈ 8 million genetic variants in 320,000 people for three depression phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. Each phenotype was found to be significantly genetically correlated with the results from a previous independent study of clinically defined MDD. We identified 14 independent loci that were significantly associated (P < 5 × 10−8) with broad depression, two independent variants for probable MDD, and one independent variant for ICD-coded MDD. Gene-based analysis of our GWAS results with MAGMA revealed 46 regions significantly associated (P < 2.77 × 10−6) with broad depression, two significant regions for probable MDD and one significant region for ICD-coded MDD. Gene region-based analysis of our GWAS results with MAGMA revealed 59 regions significantly associated (P < 6.02 × 10−6) with broad depression, of which 27 were also detected by gene-based analysis. Variants for broad depression were enriched in pathways for excitatory neurotransmission, mechanosensory behavior, postsynapse, neuron spine and dendrite. This study provides a number of novel genetic risk variants that can be leveraged to elucidate the mechanisms of MDD and low mood.

Association of whole-genome and NETRIN1 signaling pathway-derived polygenic risk scores for Major Depressive Disorder and thalamic radiation white matter microstructure in UK Biobank

Background Major Depressive Disorder (MDD) is a clinically heterogeneous psychiatric disorder with a polygenic architecture. Genome-wide association studies have identified a number of risk-associated variants across the genome, and growing evidence of NETRIN1 pathway involvement. Stratifying disease risk by genetic variation within the NETRIN1 pathway may provide an important route for identification of disease mechanisms by focusing on a specific process excluding heterogeneous risk-associated variation in other pathways. Here, we sought to investigate whether MDD polygenic risk scores derived from the NETRIN1 signaling pathway (NETRIN1-PRS) and the whole genome excluding NETRIN1 pathway genes (genomic-PRS) were associated with white matter integrity. Methods We used two diffusion tensor imaging measures, fractional anisotropy (FA) and mean diffusivity (MD), in the most up-to-date UK Biobank neuroimaging data release (FA: N = 6,401; MD: N = 6,390). Results We found significantly lower FA in the superior longitudinal fasciculus (β = -0.035, pcorrected = 0.029) and significantly higher MD in a global measure of thalamic radiations (β = 0.029, pcorrected = 0.021), as well as higher MD in the superior (β = 0.034, pcorrected = 0.039) and inferior (β = 0.029, pcorrected = 0.043) longitudinal fasciculus and in the anterior (β = 0.025, pcorrected = 0.046) and superior (β = 0.027, pcorrected = 0.043) thalamic radiation associated with NETRIN1-PRS. Genomic-PRS was also associated with lower FA and higher MD in several tracts. Conclusions Our findings indicate that variation in the NETRIN1 signaling pathway may confer risk for MDD through effects on thalamic radiation white matter microstructure.

Genome-wide meta-analysis of depression in 807,553 individuals identifies 102 independent variants with replication in a further 1,507,153 individuals

Abstract Major depression is a debilitating psychiatric illness that is typically associated with low mood, anhedonia and a range of comorbidities. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximise sample size, we meta-analysed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 gene-sets associated with depression, including both genes and gene-pathways associated with synaptic structure and neurotransmission. Further evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant following multiple testing correction. Based on the putative genes associated with depression this work also highlights several potential drug repositioning opportunities. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding aetiology and developing new treatment approaches.Major depression is a debilitating psychiatric illness that is typically associated with low mood, anhedonia and a range of comorbidities. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximise sample size, we meta-analysed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 gene-sets associated with depression, including both genes and gene-pathways associated with synaptic structure and neurotransmission. Further evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication sample of 1,507,153 individuals (474,574 cases and 1,032,579 controls), 87 of the 102 associated variants were significant following multiple testing correction. Based on the putative genes associated with depression this work also highlights several potential drug repositioning opportunities. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding aetiology and developing new treatment approaches.

Resting-State Connectivity and Its Association With Cognitive Performance, Educational Attainment, and Household Income in the UK Biobank

Background Cognitive ability is an important predictor of lifelong physical and mental well-being, and impairments are associated with many psychiatric disorders. Higher cognitive ability is also associated with greater educational attainment and increased household income. Understanding neural mechanisms underlying cognitive ability is of crucial importance for determining the nature of these associations. In the current study, we examined the spontaneous activity of the brain at rest to investigate its relationships with not only cognitive ability but also educational attainment and household income. Methods We used a large sample of resting-state neuroimaging data from the UK Biobank (n = 3950). Results First, analysis at the whole-brain level showed that connections involving the default mode network (DMN), frontoparietal network (FPN), and cingulo-opercular network (CON) were significantly positively associated with levels of cognitive performance assessed by a verbal-numerical reasoning test (standardized β cingulo-opercular values ranged from 0.054 to 0.097, pcorrected < .038). Connections associated with higher levels of cognitive performance were also significantly positively associated with educational attainment (r = .48, n = 4160) and household income (r = .38, n = 3793). Furthermore, analysis on the coupling of functional networks showed that better cognitive performance was associated with more positive DMN–CON connections, decreased cross-hemisphere connections between the homotopic network in the CON and FPN, and stronger CON–FPN connections (absolute βs ranged from 0.034 to 0.063, pcorrected < .045). Conclusions The current study found that variation in brain resting-state functional connectivity was associated with individual differences in cognitive ability, largely involving the DMN and lateral prefrontal network. In addition, we provide evidence of shared neural associations of cognitive ability, educational attainment, and household income.