Literature DB >> 28645536

Imaging genetics of schizophrenia in the post-GWAS era.

Ayla Arslan1.   

Abstract

Imaging genetics is a research methodology studying the effect of genetic variation on brain structure, function, behavior, and risk for psychopathology. Since the early 2000s, imaging genetics has been increasingly used in the research of schizophrenia (SZ). SZ is a severe mental disorder with no precise knowledge of its underlying neurobiology, however, new genetic and neurobiological data generate a climate for new avenues. The accumulating data of genome wide association studies (GWAS) continuously decode SZ risk genes. Global neuroimaging consortia produce collections of brain phenotypes from tens of thousands of people. In this context, imaging genetics will be strategically important both for the validation and discovery of SZ related findings. Thus, the study of GWAS supported risk variants as candidate genes to validate by neuroimaging is one trend. The study of epigenetic differences in relation to variations of brain phenotypes and the study of large scale multivariate analysis of genome wide and brain wide associations are other trends. While these studies hold a big potential for understanding the neurobiology of SZ, the problem of reproducibility appears as a major challenge, which requires standardizations in study designs and compensations of methodological limitations such as sensitivity and specificity. On the other hand, advancements of neuroimaging, optical and electron microscopy along with the use of genetically encoded fluorescent probes and robust statistical approaches will not only catalyze integrative methodologies but also will help better design the imaging genetics studies. In this invited paper, I will discuss the current perspective of imaging genetics and emerging opportunities of SZ research.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 28645536     DOI: 10.1016/j.pnpbp.2017.06.018

Source DB:  PubMed          Journal:  Prog Neuropsychopharmacol Biol Psychiatry        ISSN: 0278-5846            Impact factor:   5.067


  7 in total

1.  Novel functional variants at the GWAS-implicated loci might confer risk to major depressive disorder, bipolar affective disorder and schizophrenia.

Authors:  Leonid O Bryzgalov; Elena E Korbolina; Ilja I Brusentsov; Elena Y Leberfarb; Natalia P Bondar; Tatiana I Merkulova
Journal:  BMC Neurosci       Date:  2018-04-19       Impact factor: 3.288

2.  Effects of the LHPP gene polymorphism on the functional and structural changes of gray matter in major depressive disorder.

Authors:  Lingling Cui; Fei Wang; Zhiyang Yin; Miao Chang; Yanzhuo Song; Yange Wei; Jing Lv; Yifan Zhang; Yanqing Tang; Xiaohong Gong; Ke Xu
Journal:  Quant Imaging Med Surg       Date:  2020-01

Review 3.  Mapping the Schizophrenia Genes by Neuroimaging: The Opportunities and the Challenges.

Authors:  Ayla Arslan
Journal:  Int J Mol Sci       Date:  2018-01-11       Impact factor: 5.923

4.  Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling.

Authors:  Anna A Igolkina; Chris Armoskus; Jeremy R B Newman; Oleg V Evgrafov; Lauren M McIntyre; Sergey V Nuzhdin; Maria G Samsonova
Journal:  Front Mol Neurosci       Date:  2018-06-11       Impact factor: 5.639

Review 5.  Research Progress in Biological Studies of Schizophrenia in China in 2017.

Authors:  Dengtang Liu; Haixin Cen; Kaida Jiang; Yifeng Xu
Journal:  Shanghai Arch Psychiatry       Date:  2018-06-25

6.  Effect Analysis of "Four-Step" Training and Assessment Tool in the Prevention and Control of COVID-19.

Authors:  Bin Han; Feng Zang; Juan Liu; Songqin Li; Weihong Zhang; Yongxiang Zhang; Zhanjie Li
Journal:  Infect Drug Resist       Date:  2022-03-24       Impact factor: 4.003

Review 7.  Early Senescence and Leukocyte Telomere Shortening in SCHIZOPHRENIA: A Role for Cytomegalovirus Infection?

Authors:  Corona Solana; Diana Pereira; Raquel Tarazona
Journal:  Brain Sci       Date:  2018-10-18
  7 in total

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