NotionNext BLOG https://scholar.google.com/citations?user=d_VoC2MAAAAJ&hl/ 这是一个由NotionNext生成的站点 Thu, 05 Oct 2023 08:49:42 GMT https://validator.w3.org/feed/docs/rss2.html https://github.com/jpmonette/feed zh-CN All rights reserved 2023, Xueyi Shen <![CDATA[ENIGMA polygenic scores protocol]]> https://scholar.google.com/citations?user=d_VoC2MAAAAJ&hl/article/ENIGMA https://scholar.google.com/citations?user=d_VoC2MAAAAJ&hl/article/ENIGMA Sat, 30 Sep 2023 00:00:00 GMT
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Introduction of the project： Creating polygenic risk scores can be a daunting process for people without any genetic background. To simplify this process for the ENIGMA MDD working group, which includes many neuroscientists, I have developed a user-friendly pipeline for generating polygenic scores. This project is part of an international collaboration that I am leading.
 
#User-friendly #Comprehensive logs for project leaders #Comprehensive quality check and data harmonisation between datasets
 

📝 Main steps of the pipeline

  • Check genome build.
  • Create genomic relationship matrix and genetic principal components.
  • Determine reference panel for clumping.
  • Create polygenic scores based on site-specific and across-site SNP lists.
  • Generate a large number of polygenic risk scores for multiple traits using PRSice.
  • Check all the files generated and report any missing files.
 

📕 Manual

github.com
https://github.com/xshen796/ENIGMA_mdd_prs/blob/main/script/PREP_PRS/Calculate_PRS.md

📎 References

  • ENIGMA MDD working group:
ENIGMA-MDD « ENIGMA
ENIGMA-MDD « ENIGMA
https://enigma.ini.usc.edu/ongoing/enigma-mdd-working-group/
  • PRSice:
PRSice-2
None
PRSice-2
https://choishingwan.github.io/PRSice/
 
💡
Please email me if you have any questions.
 
]]> <![CDATA[About me]]> https://scholar.google.com/citations?user=d_VoC2MAAAAJ&hl/article/55bd93b0-b1bb-4e40-9d8a-461175670adf https://scholar.google.com/citations?user=d_VoC2MAAAAJ&hl/article/55bd93b0-b1bb-4e40-9d8a-461175670adf Wed, 04 Oct 2023 00:00:00 GMT 7 years experience of studying Major Depressive Disorder.]]>

A brief summary of myself

I am a researcher at the University of Edinburgh, where I utilize state-of-the-art statistical models to study Major Depressive Disorder. My expertise lies in the intersection of neuroscience and genomics, a field known as neuro-genomics. With a strong interest in mental health disorders, I believe it is crucial to combine these two disciplines to uncover the true mechanisms underlying depression.
In my research, I analyse large-scale clinical data to investigate the biological mechanisms of depression. This involves programming, data visualization, and writing research articles. I strongly believe in the power of data and figures, and I strive to conduct data-driven research.
 

Education

  • 2015-2019: PhD in Psychiatry, University of Edinburgh, UK
  • 2012-2015: MSc in Cognitive Neuroscience, Beijing Normal University, China
  • 2008-2012: BSc in Psychology, South China Normal University, China
 

Work

  • 2019-2023: Research Fellow, University of Edinburgh
  • 2010-2010: On-campus counsellor, Zhaoqing High School, China
 

Publication

💡
Number of first/corresponding author publications: 9 Total number of peer-reviewed publications: 63 (total citation = 3,910)
Research articles
  1. Shen, X.*, Caramaschi, D., Adams, M. J., Walker, R. M., et al. (2022). DNA methylome-wide association study of genetic risk for depression implicates antigen processing and immune responses. Genome Medicine, 14(1), 36.
  1. Thng, G., Shen, X.*, Stolicyn, A., Harris, et al. (2022). Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents. European Psychiatry, 65(1), E44.
  1. Shen, X.*, MacSweeney, N., Chan, S. W. Y., Barbu, M. C., Adams, M. J., Lawrie, S. M., Romaniuk, L., McIntosh, A. M., & Whalley, H. C. (2021). Brain structural associations with depression in a large early adolescent sample (The abcd study®). EClinicalMedicine, 42, 101204
  1. Shen, X.*, Howard, D.M., Adams, M.J. et al (2020). A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank. Nat Communications11, 2301.
  1. Shen, X.*, Ritakari, T.E., Adams, M.J., Cox, S.R., McIntosh, A.M., andWhalley, H.C (2019). White matter microstructure is related to the mean and within-subject variance of depressive symptoms. Biological Psychiatry 10, 15.
  1. Shen, X*, Cox, S.R., Adams, M.J., et al. Resting-state connectivity and its association with cognitive performance, educational attainment, and household income in UK Biobank (N= 3,950) (2018). Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2018: 164053.
  1. Shen, X.*, Reus, L. M., Cox, S. R., Adams, M. J., et al. (2017). Subcortical volume and white matter integrity abnormalities in major depressive disorder: findings from UK Biobank imaging data. Scientific Reports, 7(1), 5547.
  1. Shen, X.*, Mai, X., & Liu, C. (2015). Application of Internet-based big data in social cognitive science. Chinese Science Bulletin, 60(11), 986-993. (in Chinese)
  1. Shen, X.#, Zhu, R., Tang, H., Ye, P., Wang, H., Mai, X., & Liu, C. (2017). Self-punishment promotes forgiveness in the direct and indirect reciprocity contexts. Psychological reports, 120(3), 408-422.
  1. Davyson, E., Shen, X., Gadd, D. A., Bernabeu, E., et al. (2023). Metabolomic investigation of major depressive disorder identifies a potentially causal association with polyunsaturated fatty acids. Biological Psychiatry, S0006322323000550.
  1. Edmondson-Stait, A. J., Shen, X., et al. (2022). Early-life inflammatory markers and subsequent psychotic and depressive episodes between 10 to 28 years of age. Brain, Behavior, & Immunity - Health 26, 100528.
  1. Yeung, H. W., Shen, X., Stolicyn, A., et al. (2021). Spectral clustering based on structural magnetic resonance imaging and its relationship with major depressive disorder and cognitive ability. European Journal of Neuroscience, 54(6), 6281–6303.
  1. Green, C., Shen, X., Stevenson, A. J., et al. (2021). Structural brain correlates of serum and epigenetic markers of inflammation in major depressive disorder. Brain, Behavior, and Immunity, 92, 39–48.
  1. Barbu, M.C., Shen, X., Walker, R.M. et al (2020). Epigenetic prediction of major depressive disorder. Mol Psychiatry, 26, 5112–5123.
  1. Harris, M.A., Shen, X., Gibson, J., Cox, S.R., Adams, M.A., et al. (2019). Stratifying major depressive disorder by polygenic risk for schizophrenia: Differences in underlying neurobiology. Psychological Medicine. In press.
  1. Neilson, E., Shen, X., Cox, S.R., Clarke, T-K., et al. (2019). Impact of polygenic risk for Schizophrenia on cortical structure in UK Biobank (n = 2,864). Biological Psychiatry, 86(7), 536–544..
  1. Heinze, K., Shen, X., Hawkins, E., et al. (2019) Aberrant structural covariance networks in youth at high familial risk for mood disorder. Bipolar Disorder, 22(2):155-162.
  1. Barbu, M. C., Amador, C., Kwong, A. S. F., Shen, X., et al. (2022). Complex trait methylation scores in the prediction of major depressive disorder. EBioMedicine, 79, 104000.
  1. Barbu, M. C., Harris, M., Shen, X., Aleks, S., et al. (2022). Epigenome-wide association study of global cortical volumes in generation Scotland: Scottish family health study. Epigenetics, 17(10), 1143–1158.
  1. Sewell, M. D. E., Jiménez-Sánchez, L., Shen, X., Edmondson-Stait, A. J., et al. (2021). Associations between major psychiatric disorder polygenic risk scores and blood-based markers in UK biobank. Brain, Behavior, and Immunity, 97, 32–41.
  1. Schoorl, J., Barbu, M.C., Shen, X. et al (2021). Grey and white matter associations of psychotic-like experiences in a general population sample (UK Biobank). Transl Psychiatry 11, 21 (2021).
  1. Green, C., Stolicyn, A., Harris, M. A., Shen, X., et al. (2021). Hair glucocorticoids are associated with childhood adversity, depressive symptoms and reduced global and lobar grey matter in Generation Scotland. Translational Psychiatry, 11(1), 523.
  1. Stolicyn, A., Harris, M. A., Shen, X., et al. (2020). Automated classification of depression from structural brain measures across two independent community‐based cohorts. Human Brain Mapping, 41(14), 3922–3937.
  1. ENIGMA working group (2020). White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group. Molecular Psychiatry. 25, 1511–1525.
  1. Howard, D.M., Adams, M.J., Clarke, T.K., et al. (2019). Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nature Neuroscience, , 22(3), 343–352.
  1. Ritchie, S.J., Cox, S.R., Shen, X., et al. (2018) Sex differences in the adult human brain: Evidence from 5,216 UK Biobank participants. Cerebral Cortex, 28,8: 2959-2975.
  1. Howard, D. M., Adams, M. J., Shirali, M., Clarke, T. K., et al. (2018). Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways. Nature communications, 9(1), 1470.
  1. Romaniuk, L., Sandu A., Waiter G., McNeil C.J., Shen, X.,…Whalley, H. (2018). The neurobiology of personal control during reward learning and its relation to mood. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4(2):190–199.
  1. Barbu, M. C., Zeng, Y., Shen, X., Cox, S., Clarke, T., et al. (2018). 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. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4(1):91–100
  1. Reus, L. M., Shen, X., Gibson, J., Wigmore, E., Ligthart, L., Adams, M. J., et al. (2017). Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank. Scientific Reports, 7, 42140.
  1. Zhu, R., Jin, T., Shen, X., Zhang, S., Mai, X., & Liu, C. (2017). Relational utility affects self-punishment in direct and indirect reciprocity situations. Social Psychology. 44:19-27
  1. Zhu, R., Wu, H., Xu, Z., Tang, H., Shen, X., Mai, X., & Liu, C. (2017). Early distinction between shame and guilt processing in an interpersonal context. Social neuroscience, 1-14.
  1. Madden, R. A., Atkinson, K., Shen, X., Green, C., et al. (2022). Structural brain correlates of childhood trauma with replication across two large, independent community-based samples [Preprint]. medRxiv, Psychiatry and Clinical Psychology. https://doi.org/10.1101/2022.06.07.22276081
  1. Yeung, H. W., Stolicyn, A., Shen, X., Adams, M. J., et al. (2022). Classification accuracy of structural and functional connectomes across different depressive phenotypes [Preprint]. medRxiv, Psychiatry and Clinical Psychology. https://doi.org/10.1101/2022.11.22.22282621
  1. Gao, C., Amador, C., Walker, R. M., Campbell, A., Madden, R. A., Adams, M. J., Bai, X., Liu, Y., Li, M., Hayward, C., Porteous, D. J., Shen, X., et al. (2023). Phenome-wide analyses identify an association between the parent-of-origin effects dependent methylome and the rate of aging in humans. Genome Biology, 24(1), 117.
  1. MacSweeney, N., Allardyce, J., Edmondson-Stait, A., Shen, X., et al. (2023). The role of brain structure in the association between pubertal timing and depression risk in an early adolescent sample (The abcd study®): A registered report. Developmental Cognitive Neuroscience, 60, 101223.
  1. Cullen, B., Gameroff, M. J., Ward, J., Bailey, M. E. S., Lyall, D. M., Lyall, L. M., MacSweeney, N., Murphy, E., Sangha, N., Shen, X., et al. (2023). Cognitive function in people with familial risk of depression. JAMA Psychiatry, 80(6), 610.
Conference abstracts
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