Literature DB >> 23311345

Towards a gene expression biomarker set for human biological age.

Alice C Holly1, David Melzer, Luke C Pilling, William Henley, Dena G Hernandez, Andrew B Singleton, Stefania Bandinelli, Jack M Guralnik, Luigi Ferrucci, Lorna W Harries.   

Abstract

We have previously described a statistical model capable of distinguishing young (age <65 years) from old (age ≥75 years) individuals. Here we studied the performance of a modified model in three populations and determined whether individuals predicted to be biologically younger than their chronological age had biochemical and functional measures consistent with a younger biological age. Those with 'younger' gene expression patterns demonstrated higher muscle strength and serum albumin, and lower interleukin-6 and blood urea concentrations relative to 'biologically older' individuals (odds ratios 2.09, 1.64, 0.74, 0.74; P = 2.4 × 10(-2) , 3.5 × 10(-4) , 1.8 × 10(-2) , 1.5 × 10(-2) , respectively). We conclude that our expression signature of age is robust across three populations and may have utility for estimation of biological age.
© 2013 The Authors Aging Cell © 2013 Blackwell Publishing Ltd/Anatomical Society of Great Britain and Ireland.

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Year:  2013        PMID: 23311345      PMCID: PMC4623317          DOI: 10.1111/acel.12044

Source DB:  PubMed          Journal:  Aging Cell        ISSN: 1474-9718            Impact factor:   9.304


  15 in total

1.  Gene expression profiling of aging using DNA microarrays.

Authors:  Richard Weindruch; Tsuyoshi Kayo; Cheol Koo Lee; Tomas A Prolla
Journal:  Mech Ageing Dev       Date:  2002-01       Impact factor: 5.432

2.  A comparison of leg power and leg strength within the InCHIANTI study: which influences mobility more?

Authors:  Jonathan F Bean; Suzanne G Leveille; Dan K Kiely; Stephania Bandinelli; Jack M Guralnik; Luigi Ferrucci
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2003-08       Impact factor: 6.053

3.  Lower serum albumin concentration and change in muscle mass: the Health, Aging and Body Composition Study.

Authors:  Marjolein Visser; Stephen B Kritchevsky; Anne B Newman; Bret H Goodpaster; Frances A Tylavsky; Michael C Nevitt; Tamara B Harris
Journal:  Am J Clin Nutr       Date:  2005-09       Impact factor: 7.045

4.  A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission.

Authors:  J M Guralnik; E M Simonsick; L Ferrucci; R J Glynn; L F Berkman; D G Blazer; P A Scherr; R B Wallace
Journal:  J Gerontol       Date:  1994-03

5.  Physical performance measures in the clinical setting.

Authors:  Stephanie Studenski; Subashan Perera; Dennis Wallace; Julie M Chandler; Pamela W Duncan; Earl Rooney; Michael Fox; Jack M Guralnik
Journal:  J Am Geriatr Soc       Date:  2003-03       Impact factor: 5.562

6.  Subsystems contributing to the decline in ability to walk: bridging the gap between epidemiology and geriatric practice in the InCHIANTI study.

Authors:  L Ferrucci; S Bandinelli; E Benvenuti; A Di Iorio; C Macchi; T B Harris; J M Guralnik
Journal:  J Am Geriatr Soc       Date:  2000-12       Impact factor: 5.562

7.  Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes.

Authors:  Harald H H Göring; Joanne E Curran; Matthew P Johnson; Thomas D Dyer; Jac Charlesworth; Shelley A Cole; Jeremy B M Jowett; Lawrence J Abraham; David L Rainwater; Anthony G Comuzzie; Michael C Mahaney; Laura Almasy; Jean W MacCluer; Ahmed H Kissebah; Gregory R Collier; Eric K Moses; John Blangero
Journal:  Nat Genet       Date:  2007-09-16       Impact factor: 38.330

8.  [Normal ranges of blood urea nitrogen and serum creatinine levels in the community-dwelling elderly subjects aged 70 years or over--correlation between age and renal function].

Authors:  T Aono; K Matsubayashi; A Kawamoto; S Kimura; Y Doi; T Ozawa
Journal:  Nihon Ronen Igakkai Zasshi       Date:  1994-03

9.  Serum albumin is associated with skeletal muscle in elderly men and women.

Authors:  R N Baumgartner; K M Koehler; L Romero; P J Garry
Journal:  Am J Clin Nutr       Date:  1996-10       Impact factor: 7.045

10.  Inflammatory markers and physical performance in older persons: the InCHIANTI study.

Authors:  Matteo Cesari; Brenda W J H Penninx; Marco Pahor; Fulvio Lauretani; Anna Maria Corsi; G Rhys Williams; Jack M Guralnik; Luigi Ferrucci
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2004-03       Impact factor: 6.053

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  20 in total

1.  Shift work, DNA methylation and epigenetic age.

Authors:  Alexandra J White; Jacob K Kresovich; Zongli Xu; Dale P Sandler; Jack A Taylor
Journal:  Int J Epidemiol       Date:  2019-10-01       Impact factor: 7.196

2.  Age-associated telomere attrition of lymphocytes in vivo is co-ordinated with changes in telomerase activity, composition of lymphocyte subsets and health conditions.

Authors:  Yun Lin; Amanda Damjanovic; E Jeffrey Metter; Huy Nguyen; Thai Truong; Kevin Najarro; Christa Morris; Dan L Longo; Ming Zhan; Luigi Ferrucci; Richard J Hodes; Nan-ping Weng
Journal:  Clin Sci (Lond)       Date:  2015-03       Impact factor: 6.124

3.  Inflammaging: Age and Systemic, Cellular, and Nuclear Inflammatory Biology in Older Adults.

Authors:  Dominique Piber; Richard Olmstead; Joshua Hyong-Jin Cho; Tuff Witarama; Christian Perez; Nicholas Dietz; Teresa E Seeman; Elizabeth C Breen; Steve W Cole; Michael R Irwin
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2019-10-04       Impact factor: 6.053

4.  Trends in DNA Methylation with Age Replicate Across Diverse Human Populations.

Authors:  Shyamalika Gopalan; Oana Carja; Maud Fagny; Etienne Patin; Justin W Myrick; Lisa M McEwen; Sarah M Mah; Michael S Kobor; Alain Froment; Marcus W Feldman; Lluis Quintana-Murci; Brenna M Henn
Journal:  Genetics       Date:  2017-05-22       Impact factor: 4.562

5.  Methylation-Based Biological Age and Breast Cancer Risk.

Authors:  Jacob K Kresovich; Zongli Xu; Katie M O'Brien; Clarice R Weinberg; Dale P Sandler; Jack A Taylor
Journal:  J Natl Cancer Inst       Date:  2019-10-01       Impact factor: 13.506

6.  An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging.

Authors:  Nazish Sayed; Yingxiang Huang; Khiem Nguyen; Zuzana Krejciova-Rajaniemi; Anissa P Grawe; Tianxiang Gao; Robert Tibshirani; Trevor Hastie; Ayelet Alpert; Lu Cui; Tatiana Kuznetsova; Yael Rosenberg-Hasson; Rita Ostan; Daniela Monti; Benoit Lehallier; Shai S Shen-Orr; Holden T Maecker; Cornelia L Dekker; Tony Wyss-Coray; Claudio Franceschi; Vladimir Jojic; François Haddad; José G Montoya; Joseph C Wu; Mark M Davis; David Furman
Journal:  Nat Aging       Date:  2021-07-12

Review 7.  Biological Age Predictors.

Authors:  Juulia Jylhävä; Nancy L Pedersen; Sara Hägg
Journal:  EBioMedicine       Date:  2017-04-01       Impact factor: 8.143

8.  Modeling transcriptomic age using knowledge-primed artificial neural networks.

Authors:  Nicholas Holzscheck; Cassandra Falckenhayn; Jörn Söhle; Boris Kristof; Ralf Siegner; André Werner; Janka Schössow; Clemens Jürgens; Henry Völzke; Horst Wenck; Marc Winnefeld; Elke Grönniger; Lars Kaderali
Journal:  NPJ Aging Mech Dis       Date:  2021-06-01

9.  Aging on a different scale--chronological versus pathology-related aging.

Authors:  Joost P M Melis; Martijs J Jonker; Jan Vijg; Jan H J Hoeijmakers; Timo M Breit; Harry van Steeg
Journal:  Aging (Albany NY)       Date:  2013-10       Impact factor: 5.682

10.  The effects of aging on molecular modulators of human embryo implantation.

Authors:  Panagiotis Ntostis; Grace Swanson; Georgia Kokkali; David Iles; John Huntriss; Agni Pantou; Maria Tzetis; Konstantinos Pantos; Helen M Picton; Stephen A Krawetz; David Miller
Journal:  iScience       Date:  2021-06-19
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