Literature DB >> 21538458

Applications of mass spectrometry to metabolomics and metabonomics: detection of biomarkers of aging and of age-related diseases.

Robert J Mishur1, Shane L Rea.   

Abstract

Every 5 years or so new technologies, or new combinations of old ones, seemingly burst onto the science scene and are then sought after until they reach the point of becoming commonplace. Advances in mass spectrometry instrumentation, coupled with the establishment of standardized chemical fragmentation libraries, increased computing power, novel data-analysis algorithms, new scientific applications, and commercial prospects have made mass spectrometry-based metabolomics the latest sought-after technology. This methodology affords the ability to dynamically catalogue and quantify, in parallel, femtomole quantities of cellular metabolites. The study of aging, and the diseases that accompany it, has accelerated significantly in the last decade. Mutant genes that alter the rate of aging have been found that increase lifespan by up to 10-fold in some model organisms, and substantial progress has been made in understanding fundamental alterations that occur at both the mRNA and protein level in tissues of aging organisms. The application of metabolomics to aging research is still relatively new, but has already added significant insight into the aging process. In this review we summarize these findings. We have targeted our manuscript to two audiences: mass spectrometrists interested in applying their technical knowledge to unanswered questions in the aging field, and gerontologists interested in expanding their knowledge of both mass spectrometry and the most recent advances in aging-related metabolomics.
Copyright © 2011 Wiley Periodicals, Inc.

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Year:  2011        PMID: 21538458     DOI: 10.1002/mas.20338

Source DB:  PubMed          Journal:  Mass Spectrom Rev        ISSN: 0277-7037            Impact factor:   10.946


  45 in total

1.  Chronic caloric restriction partially protects against age-related alteration in serum metabolome.

Authors:  Jennifer M De Guzman; Ginger Ku; Ryan Fahey; Yun-Hee Youm; Ignatius Kass; Donald K Ingram; Vishwa Deep Dixit; Indu Kheterpal
Journal:  Age (Dordr)       Date:  2012-06-04

Review 2.  Mass spectrometry strategies for clinical metabolomics and lipidomics in psychiatry, neurology, and neuro-oncology.

Authors:  Paul L Wood
Journal:  Neuropsychopharmacology       Date:  2013-07-11       Impact factor: 7.853

Review 3.  The impact of mass spectrometry application to screen new proteomics biomarkers in Ophthalmology.

Authors:  Bruno Nobre Lins Coronado; Felipe Bruno Santos da Cunha; Otávio de Toledo Nobrega; Aline Maria Araujo Martins
Journal:  Int Ophthalmol       Date:  2021-04-02       Impact factor: 2.031

4.  Automated deconvolution of overlapped ion mobility profiles.

Authors:  Matthew Brantley; Behrooz Zekavat; Brett Harper; Rachel Mason; Touradj Solouki
Journal:  J Am Soc Mass Spectrom       Date:  2014-08-06       Impact factor: 3.109

Review 5.  Toward a new philosophy of preventive nutrition: from a reductionist to a holistic paradigm to improve nutritional recommendations.

Authors:  Anthony Fardet; Edmond Rock
Journal:  Adv Nutr       Date:  2014-07-14       Impact factor: 8.701

Review 6.  Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems.

Authors:  Rahul Vijay Kapoore; Seetharaman Vaidyanathan
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2016-10-28       Impact factor: 4.226

7.  Metabolic Reprogramming by Folate Restriction Leads to a Less Aggressive Cancer Phenotype.

Authors:  Zahra Ashkavand; Ciara O'Flanagan; Mirko Hennig; Xiuxia Du; Stephen D Hursting; Sergey A Krupenko
Journal:  Mol Cancer Res       Date:  2017-02       Impact factor: 5.852

Review 8.  Photodissociation mass spectrometry: new tools for characterization of biological molecules.

Authors:  Jennifer S Brodbelt
Journal:  Chem Soc Rev       Date:  2014-01-30       Impact factor: 54.564

9.  Chip-based nLC-TOF-MS is a highly stable technology for large-scale high-throughput analyses.

Authors:  L Renee Ruhaak; Sandra L Taylor; Suzanne Miyamoto; Karen Kelly; Gary S Leiserowitz; David Gandara; Carlito B Lebrilla; Kyoungmi Kim
Journal:  Anal Bioanal Chem       Date:  2013-03-23       Impact factor: 4.142

10.  Microbial-mammalian cometabolites dominate the age-associated urinary metabolic phenotype in Taiwanese and American populations.

Authors:  Jonathan R Swann; Konstantina Spagou; Matthew Lewis; Jeremy K Nicholson; Dana A Glei; Teresa E Seeman; Christopher L Coe; Noreen Goldman; Carol D Ryff; Maxine Weinstein; Elaine Holmes
Journal:  J Proteome Res       Date:  2013-06-24       Impact factor: 4.466

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