Literature DB >> 28874057

Emerging Omics Approaches in Aging Research.

Jared S Lorusso1, Oleg A Sviderskiy2, Vyacheslav M Labunskyy1.   

Abstract

SIGNIFICANCE: Aging is a complex trait that is influenced by a combination of genetic and environmental factors. Although many cellular and physiological changes have been described to occur with aging, the precise molecular causes of aging remain unknown. Given the biological complexity and heterogeneity of the aging process, understanding the mechanisms that underlie aging requires integration of data about age-dependent changes that occur at the molecular, cellular, tissue, and organismal levels. Recent Advances: The development of high-throughput technologies such as next-generation sequencing, proteomics, metabolomics, and automated imaging techniques provides researchers with new opportunities to understand the mechanisms of aging. Using these methods, millions of biological molecules can be simultaneously monitored during the aging process with high accuracy and specificity. CRITICAL ISSUES: Although the ability to produce big data has drastically increased over the years, integration and interpreting of high-throughput data to infer regulatory relationships between biological factors and identify causes of aging remain the major challenges. In this review, we describe recent advances and survey emerging omics approaches in aging research. We then discuss their limitations and emphasize the need for the further development of methods for the integration of different types of data. FUTURE DIRECTIONS: Combining omics approaches and novel methods for single-cell analysis with systems biology tools would allow building interaction networks and investigate how these networks are perturbed with aging and disease states. Together, these studies are expected to provide a better understanding of the aging process and could provide insights into the pathophysiology of many age-associated human diseases. Antioxid. Redox Signal. 29, 985-1002.

Entities:  

Keywords:  aging; metabolomics; next-generation sequencing; proteomics; systems biology; translational regulation

Mesh:

Year:  2017        PMID: 28874057      PMCID: PMC6104250          DOI: 10.1089/ars.2017.7163

Source DB:  PubMed          Journal:  Antioxid Redox Signal        ISSN: 1523-0864            Impact factor:   7.468


  198 in total

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Journal:  Cell       Date:  2015-04-30       Impact factor: 41.582

3.  Small molecule activators of sirtuins extend Saccharomyces cerevisiae lifespan.

Authors:  Konrad T Howitz; Kevin J Bitterman; Haim Y Cohen; Dudley W Lamming; Siva Lavu; Jason G Wood; Robert E Zipkin; Phuong Chung; Anne Kisielewski; Li-Li Zhang; Brandy Scherer; David A Sinclair
Journal:  Nature       Date:  2003-08-24       Impact factor: 49.962

Review 4.  Next-generation analysis of gene expression regulation--comparing the roles of synthesis and degradation.

Authors:  Joel McManus; Zhe Cheng; Christine Vogel
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Authors:  Philipp Oberdoerffer; David A Sinclair
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6.  Regulation of lifespan in Drosophila by modulation of genes in the TOR signaling pathway.

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7.  Skeletal muscle gene expression profiles in 20-29 year old and 65-71 year old women.

Authors:  Stephen Welle; Andrew I Brooks; Joseph M Delehanty; Nancy Needler; Kirti Bhatt; Bharati Shah; Charles A Thornton
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8.  Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling.

Authors:  Nicholas T Ingolia; Sina Ghaemmaghami; John R S Newman; Jonathan S Weissman
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Authors:  Steve Horvath; Paolo Garagnani; Maria Giulia Bacalini; Chiara Pirazzini; Stefano Salvioli; Davide Gentilini; Anna Maria Di Blasio; Cristina Giuliani; Spencer Tung; Harry V Vinters; Claudio Franceschi
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2.  Circulating Metabolomic Analysis following Cecal Ligation and Puncture in Young and Aged Mice Reveals Age-Associated Temporal Shifts in Nicotinamide and Histidine/Histamine Metabolic Pathways.

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Review 3.  Structured Long-Chain Omega-3 Fatty Acids for Improvement of Cognitive Function during Aging.

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Journal:  Int J Mol Sci       Date:  2022-03-23       Impact factor: 5.923

Review 4.  Omics in a Digital World: The Role of Bioinformatics in Providing New Insights Into Human Aging.

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Journal:  Front Genet       Date:  2021-06-10       Impact factor: 4.599

5.  Lipid and metabolite correlation networks specific to clinical and biochemical covariate show differences associated with sexual dimorphism in a cohort of nonagenarians.

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Journal:  Geroscience       Date:  2021-07-29       Impact factor: 7.581

6.  MetaboAge DB: a repository of known ageing-related changes in the human metabolome.

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7.  A Deep-Learning Proteomic-Scale Approach for Drug Design.

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  7 in total

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