Unraveling Psychiatric Disorders through Neural Single-Cell Transcriptomics Approaches

被引:8
作者
Chehimi, Samar N. [1 ]
Crist, Richard C. [1 ]
Reiner, Benjamin C. [1 ]
机构
[1] Univ Penn, Perelman Sch Med, Dept Psychiat, Philadelphia, PA 19104 USA
关键词
single-nuclei RNA-seq; transcriptome; psychiatric disorders; cellular characterization; ANALYSIS REVEALS; BRAIN; EXPRESSION; MOUSE; DIFFERENTIATION; DEPRESSION; DIVERSITY; DOPAMINE; NICOTINE; MORPHINE;
D O I
10.3390/genes14030771
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
The development of single-cell and single-nucleus transcriptome technologies is enabling the unraveling of the molecular and cellular heterogeneity of psychiatric disorders. The complexity of the brain and the relationships between different brain regions can be better understood through the classification of individual cell populations based on their molecular markers and transcriptomic features. Analysis of these unique cell types can explain their involvement in the pathology of psychiatric disorders. Recent studies in both human and animal models have emphasized the importance of transcriptome analysis of neuronal cells in psychiatric disorders but also revealed critical roles for non-neuronal cells, such as oligodendrocytes and microglia. In this review, we update current findings on the brain transcriptome and explore molecular studies addressing transcriptomic alterations identified in human and animal models in depression and stress, neurodegenerative disorders (Parkinson's and Alzheimer's disease), schizophrenia, opioid use disorder, and alcohol and psychostimulant abuse. We also comment on potential future directions in single-cell and single-nucleus studies.
引用
收藏
页数:16
相关论文
共 50 条
  • [31] Single-cell transcriptomics for the assessment of cardiac disease
    Miranda, Antonio M. A.
    Janbandhu, Vaibhao
    Maatz, Henrike
    Kanemaru, Kazumasa
    Cranley, James
    Teichmann, Sarah A.
    Huebner, Norbert
    Schneider, Michael D.
    Harvey, Richard P.
    Noseda, Michela
    NATURE REVIEWS CARDIOLOGY, 2023, 20 (05) : 289 - 308
  • [32] Lymphoma Heterogeneity Unraveled by Single-Cell Transcriptomics
    Ysebaert, Loic
    Quillet-Mary, Anne
    Tosolini, Marie
    Pont, Frederic
    Laurent, Camille
    Fournie, Jean-Jacques
    FRONTIERS IN IMMUNOLOGY, 2021, 12
  • [33] Single-Cell Transcriptomics of the Human Endocrine Pancreas
    Wang, Yue J.
    Schug, Jonathan
    Won, Kyoung-Jae
    Liu, Chengyang
    Naji, Ali
    Avrahami, Dana
    Golson, Maria L.
    Kaestner, Klaus H.
    DIABETES, 2016, 65 (10) : 3028 - 3038
  • [34] Validation of noise models for single-cell transcriptomics
    Grun, Dominic
    Kester, Lennart
    van Oudenaarden, Alexander
    NATURE METHODS, 2014, 11 (06) : 637 - +
  • [35] Single-cell and spatial transcriptomics in endocrine research
    Matsumoto, Ryusaku
    Yamamoto, Takuya
    ENDOCRINE JOURNAL, 2024, 71 (02) : 101 - 118
  • [36] Transcriptomics and single-cell RNA-sequencing
    Chambers, Daniel C.
    Carew, Alan M.
    Lukowski, Samuel W.
    Powell, Joseph E.
    RESPIROLOGY, 2019, 24 (01) : 29 - 36
  • [37] Application of single-cell transcriptomics to kinetoplastid research
    Briggs, Emma M.
    Warren, Felix S. L.
    Matthews, Keith R.
    McCulloch, Richard
    Otto, Thomas D.
    PARASITOLOGY, 2021, 148 (10) : 1223 - 1236
  • [38] Profiling mouse cochlear cell maturation using 10x Genomics single-cell transcriptomics
    Xu, Zhenhang
    Tu, Shu
    Pass, Caroline
    Zhang, Yan
    Liu, Huizhan
    Diers, Jack
    Fu, Yusi
    He, David Z. Z.
    Zuo, Jian
    FRONTIERS IN CELLULAR NEUROSCIENCE, 2022, 16
  • [39] Single-cell transcriptomics of human organoid-derived enteroendocrine cell populations from the small intestine
    Smith, Christopher A.
    Lu, Van B.
    Bakar, Rula Bany
    Miedzybrodzka, Emily
    Davison, Adam
    Goldspink, Deborah
    Reimann, Frank
    Gribble, Fiona M.
    JOURNAL OF PHYSIOLOGY-LONDON, 2024,
  • [40] New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
    Shao, Xin
    Lu, Xiaoyan
    Liao, Jie
    Chen, Huajun
    Fan, Xiaohui
    PROTEIN & CELL, 2020, 11 (12) : 866 - 880