Xueyi Shen

Xueyi Shen

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Xueyi Shen

Institute of Neuroscience and Cardiovascular Research, University of Edinburgh, Edinburgh, UK

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 February 2019 in Nature Neuroscience
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Journal Article
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DHDavid M. Howard
David M. Howard
MAMark J. Adams
Mark J. Adams
TCToni-Kim Clarke
Toni-Kim Clarke
JHJonathan D. Hafferty
Jonathan D. Hafferty
JGJude Gibson
Jude Gibson
AMAndrew M. McIntosh
Andrew M. McIntosh
Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed 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 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. 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 after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.

16 May 2018 in Cerebral Cortex
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Journal Article
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SRStuart J Ritchie
Stuart J Ritchie
SCSimon R Cox
Simon R Cox
XSXueyi Shen
Xueyi Shen
MLMichael V Lombardo
Michael V Lombardo
LRLianne M Reus
Lianne M Reus
IDIan Deary
Ian Deary
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.

16 April 2018 in Nature Communications
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Journal Article
Open access
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DHDavid M. Howard
David M. Howard
MAMark J. Adams
Mark J. Adams
Masoud ShiraliMasoud Shirali
Masoud Shirali
TCToni-Kim Clarke
Toni-Kim Clarke
RMRiccardo E. Marioni
Riccardo E. Marioni
CWCatherine H. Wilson
Catherine H. Wilson
Depression is a polygenic trait that causes extensive periods of disability. Previous genetic studies have identified common risk variants which have progressively increased in number with increasing sample sizes of the respective studies. Here, we conduct a genome-wide association study in 322,580 UK Biobank participants for three depression-related phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. We identify 17 independent loci that are significantly associated (P < 5 × 10−8) across the three phenotypes. The direction of effect of these loci is consistently replicated in an independent sample, with 14 loci likely representing novel findings. Gene sets are enriched in excitatory neurotransmission, mechanosensory behaviour, post synapse, neuron spine and dendrite functions. Our findings suggest that broad depression is the most tractable UK Biobank phenotype for discovering genes and gene sets that further our understanding of the biological pathways underlying depression.

30 August 2019 in Molecular Psychiatry
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LVLaura S. van Velzen
Laura S. van Velzen
SKSinead Kelly
Sinead Kelly
DIDmitry Isaev
Dmitry Isaev
AAAndre Aleman
Andre Aleman
LALyubomir I. Aftanas
Lyubomir I. Aftanas
LSLianne Schmaal
Lianne Schmaal
Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12–88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen’s d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen’s d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.

11 March 2019 in European Heart Journal
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Journal Article
Open access
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SCSimon R Cox
Simon R Cox
DLDonald M Lyall
Donald M Lyall
SRStuart J Ritchie
Stuart J Ritchie
MBMark E Bastin
Mark E Bastin
MHMathew A Harris
Mathew A Harris
IDIan J Deary
Ian J Deary
Several factors are known to increase risk for cerebrovascular disease and dementia, but there is limited evidence on associations between multiple vascular risk factors (VRFs) and detailed aspects of brain macrostructure and microstructure in large community-dwelling populations across middle and older age. Associations between VRFs (smoking, hypertension, pulse pressure, diabetes, hypercholesterolaemia, body mass index, and waist–hip ratio) and brain structural and diffusion MRI markers were examined in UK Biobank (N = 9722, age range 44–79 years). A larger number of VRFs was associated with greater brain atrophy, lower grey matter volume, and poorer white matter health. Effect sizes were small (brain structural R2 ≤1.8%). Higher aggregate vascular risk was related to multiple regional MRI hallmarks associated with dementia risk: lower frontal and temporal cortical volumes, lower subcortical volumes, higher white matter hyperintensity volumes, and poorer white matter microstructure in association and thalamic pathways. Smoking pack years, hypertension and diabetes showed the most consistent associations across all brain measures. Hypercholesterolaemia was not uniquely associated with any MRI marker. Higher levels of VRFs were associated with poorer brain health across grey and white matter macrostructure and microstructure. Effects are mainly additive, converging upon frontal and temporal cortex, subcortical structures, and specific classes of white matter fibres. Though effect sizes were small, these results emphasize the vulnerability of brain health to vascular factors even in relatively healthy middle and older age, and the potential to partly ameliorate cognitive decline by addressing these malleable risk factors.

16 December 2019 in Nature Communications
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Journal Article
Open access
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WHWilliam Hill
William Hill
NDNeil M. Davies
Neil M. Davies
SRStuart J. Ritchie
Stuart J. Ritchie
NSNathan G. Skene
Nathan G. Skene
JBJulien Bryois
Julien Bryois
IDIan J. Deary
Ian J. Deary
Socioeconomic position (SEP) is a multi-dimensional construct reflecting (and influencing) multiple socio-cultural, physical, and environmental factors. In a sample of 286,301 participants from UK Biobank, we identify 30 (29 previously unreported) independent-loci associated with income. Using a method to meta-analyze data from genetically-correlated traits, we identify an additional 120 income-associated loci. These loci show clear evidence of functionality, with transcriptional differences identified across multiple cortical tissues, and links to GABAergic and serotonergic neurotransmission. By combining our genome wide association study on income with data from eQTL studies and chromatin interactions, 24 genes are prioritized for follow up, 18 of which were previously associated with intelligence. We identify intelligence as one of the likely causal, partly-heritable phenotypes that might bridge the gap between molecular genetic inheritance and phenotypic consequence in terms of income differences. These results indicate that, in modern era Great Britain, genetic effects contribute towards some of the observed socioeconomic inequalities.