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Literature DB >> 27303027

Metabolomics of aging requires large-scale longitudinal studies with replication.

Ville-Petteri Mäkinen¹, Mika Ala-Korpela².

Abstract

Mesh：

Year: 2016 PMID： 27303027 PMCID： PMC4922179 DOI： 10.1073/pnas.1607062113

Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN： 0027-8424 Impact factor: 11.205

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5 in total

1. Individual variability in human blood metabolites identifies age-related differences.

Authors: Romanas Chaleckis; Itsuo Murakami; Junko Takada; Hiroshi Kondoh; Mitsuhiro Yanagida
Journal: Proc Natl Acad Sci U S A Date: 2016-03-28 Impact factor: 11.205

2. Quantification of biological aging in young adults.

Authors: Daniel W Belsky; Avshalom Caspi; Renate Houts; Harvey J Cohen; David L Corcoran; Andrea Danese; HonaLee Harrington; Salomon Israel; Morgan E Levine; Jonathan D Schaefer; Karen Sugden; Ben Williams; Anatoli I Yashin; Richie Poulton; Terrie E Moffitt
Journal: Proc Natl Acad Sci U S A Date: 2015-07-06 Impact factor: 11.205

3. Translational biomarker discovery in clinical metabolomics: an introductory tutorial.

Authors: Jianguo Xia; David I Broadhurst; Michael Wilson; David S Wishart
Journal: Metabolomics Date: 2012-12-04 Impact factor: 4.290

4. Human metabolic profiles are stably controlled by genetic and environmental variation.

Authors: George Nicholson; Mattias Rantalainen; Anthony D Maher; Jia V Li; Daniel Malmodin; Kourosh R Ahmadi; Johan H Faber; Ingileif B Hallgrímsdóttir; Amy Barrett; Henrik Toft; Maria Krestyaninova; Juris Viksna; Sudeshna Guha Neogi; Marc-Emmanuel Dumas; Ugis Sarkans; Bernard W Silverman; Peter Donnelly; Jeremy K Nicholson; Maxine Allen; Krina T Zondervan; John C Lindon; Tim D Spector; Mark I McCarthy; Elaine Holmes; Dorrit Baunsgaard; Chris C Holmes
Journal: Mol Syst Biol Date: 2011-08-30 Impact factor: 11.429

5. Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology.

Authors: George Davey Smith; Debbie A Lawlor; Roger Harbord; Nic Timpson; Ian Day; Shah Ebrahim
Journal: PLoS Med Date: 2007-12 Impact factor: 11.069

5 in total

8 in total

1. Reply to Mäkinen and Ala-Korpela: Small-scale but accurate metabolomics with high reproducibility for identifying age-related blood metabolites.

Authors: Hiroshi Kondoh; Mitsuhiro Yanagida
Journal: Proc Natl Acad Sci U S A Date: 2016-06-14 Impact factor: 11.205

Review 2. Proteomics and metabolomics in ageing research: from biomarkers to systems biology.

Authors: Jessica M Hoffman; Yang Lyu; Scott D Pletcher; Daniel E L Promislow
Journal: Essays Biochem Date: 2017-07-11 Impact factor: 7.258

3. Ageing Investigation Using Two-Time-Point Metabolomics Data from KORA and CARLA Studies.

Authors: Choiwai Maggie Chak; Maria Elena Lacruz; Jonathan Adam; Stefan Brandmaier; Marcela Covic; Jialing Huang; Christa Meisinger; Daniel Tiller; Cornelia Prehn; Jerzy Adamski; Ursula Berger; Christian Gieger; Annette Peters; Alexander Kluttig; Rui Wang-Sattler
Journal: Metabolites Date: 2019-03-05

Metabolomics of aging requires large-scale longitudinal studies with replication.

1. Individual variability in human blood metabolites identifies age-related differences.

2. Quantification of biological aging in young adults.

3. Translational biomarker discovery in clinical metabolomics: an introductory tutorial.

4. Human metabolic profiles are stably controlled by genetic and environmental variation.

5. Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology.

1. Reply to Mäkinen and Ala-Korpela: Small-scale but accurate metabolomics with high reproducibility for identifying age-related blood metabolites.

Review 2. Proteomics and metabolomics in ageing research: from biomarkers to systems biology.

3. Ageing Investigation Using Two-Time-Point Metabolomics Data from KORA and CARLA Studies.

4. Longitudinal plasma metabolomics of aging and sex.

Review 5. Emerging Insights into the Metabolic Alterations in Aging Using Metabolomics.

6. A procession of metabolic alterations accompanying muscle senescence in Manduca sexta.

Review 7. Beyond genomics: understanding exposotypes through metabolomics.

8. Cutaneous Thermal Injury Modulates Blood and Skin Metabolomes Differently in a Murine Model.