Review

A compendium of single cell analysis in aging and disease

  • Received: 14 August 2019 Accepted: 25 March 2020 Published: 27 March 2020
  • Cell is the fundamental structural and functional unit of complex multicellular organisms. Conventional methods which involve average analysis of cells in bulk populations can undermine physiologically significant cell populations, whereas analysis of cells at a single cell level may reveal unique biomarkers and other mechanisms that govern the genotype and phenotype in various physiological processes in presumed homogenous cell populations. Cellular abnormalities such as irregularities in cellular mechanisms have been linked to human aging and other major diseases including neurodegenerative, vascular, autoimmune, and cancer. Aging is a functional decline associated with various diseases in an organism, majorly arising from cellular abnormalities. Single cell analysis (SCA) which involves isolation and study of single cell proteomics, genomics, transcriptomics and metabolomics which enables research of cellular abnormalities with a molecular resolution, is gaining recognition in the research of human aging and disease. The advances in SCA are producing breakthrough information about cellular heterogeneity, disease progression, cellular microenvironment and its interactions, early diagnostics, improving precision medicine through high throughput drug screening and discovery of novel biomarkers; combinedly, these advances exhibit the potential of SCA to study of human aging and disease. Primarily, we review the role of SCA in understanding cellular mechanisms involved in aging and other major diseases including neurological, vascular, autoimmunity and cancer. Secondly, we also include review of SCA role in studying cell adhesion mechanisms which are involved in tissue development and maintenance and disease progression. Finally, SCA potential to empower precision medicine and its overall challenges along with future directions are discussed.

    Citation: Uday Chintapula, Samir M Iqbal, Young-Tae Kim. A compendium of single cell analysis in aging and disease[J]. AIMS Molecular Science, 2020, 7(1): 49-69. doi: 10.3934/molsci.2020004

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  • Cell is the fundamental structural and functional unit of complex multicellular organisms. Conventional methods which involve average analysis of cells in bulk populations can undermine physiologically significant cell populations, whereas analysis of cells at a single cell level may reveal unique biomarkers and other mechanisms that govern the genotype and phenotype in various physiological processes in presumed homogenous cell populations. Cellular abnormalities such as irregularities in cellular mechanisms have been linked to human aging and other major diseases including neurodegenerative, vascular, autoimmune, and cancer. Aging is a functional decline associated with various diseases in an organism, majorly arising from cellular abnormalities. Single cell analysis (SCA) which involves isolation and study of single cell proteomics, genomics, transcriptomics and metabolomics which enables research of cellular abnormalities with a molecular resolution, is gaining recognition in the research of human aging and disease. The advances in SCA are producing breakthrough information about cellular heterogeneity, disease progression, cellular microenvironment and its interactions, early diagnostics, improving precision medicine through high throughput drug screening and discovery of novel biomarkers; combinedly, these advances exhibit the potential of SCA to study of human aging and disease. Primarily, we review the role of SCA in understanding cellular mechanisms involved in aging and other major diseases including neurological, vascular, autoimmunity and cancer. Secondly, we also include review of SCA role in studying cell adhesion mechanisms which are involved in tissue development and maintenance and disease progression. Finally, SCA potential to empower precision medicine and its overall challenges along with future directions are discussed.


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    The authors declare no conflict of interest for the contributions in this manuscript.

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