A novel multi-tissue RNA diagnostic of healthy ageing relates to cognitive health status.
BACKGROUND
Diagnostics of the human ageing process may help predict future healthcare needs or guide preventative measures for tackling diseases of older age. We take a transcriptomics approach to build the first reproducible multi-tissue RNA expression signature by gene-chip profiling tissue from sedentary normal subjects who reached 65 years of age in good health.


RESULTS
One hundred and fifty probe-sets form an accurate classifier of young versus older muscle tissue and this healthy ageing RNA classifier performed consistently in independent cohorts of human muscle, skin and brain tissue (n = 594, AUC = 0.83-0.96) and thus represents a biomarker for biological age. Using the Uppsala Longitudinal Study of Adult Men birth-cohort (n = 108) we demonstrate that the RNA classifier is insensitive to confounding lifestyle biomarkers, while greater gene score at age 70 years is independently associated with better renal function at age 82 years and longevity. The gene score is 'up-regulated' in healthy human hippocampus with age, and when applied to blood RNA profiles from two large independent age-matched dementia case-control data sets (n = 717) the healthy controls have significantly greater gene scores than those with cognitive impairment. Alone, or when combined with our previously described prototype Alzheimer disease (AD) RNA 'disease signature', the healthy ageing RNA classifier is diagnostic for AD.


CONCLUSIONS
We identify a novel and statistically robust multi-tissue RNA signature of human healthy ageing that can act as a diagnostic of future health, using only a peripheral blood sample. This RNA signature has great potential to assist research aimed at finding treatments for and/or management of AD and other ageing-related conditions.
XRGenomics Ltd, London, UK.|Division of Genetics & Molecular Medicine, King's College London, 8th Floor, Tower Wing, Guy's Hospital, London, SE1 9RT, UK.
Sanjana
S
Sood
XRGenomics Ltd, London, UK.|School of Health, Stirling University, Stirling, Scotland, UK.
Iain J
IJ
Gallagher
Department of Old Age Psychiatry, King's College London, London, UK.|Present address: University of Exeter Medical School, Exeter, UK.
Katie
K
Lunnon
Division of Clinical Physiology, Karolinska University Hospital, Stockholm, Sweden.
Eric
E
Rullman
Department of Old Age Psychiatry, King's College London, London, UK.
Aoife
A
Keohane
Division of Genetics & Molecular Medicine, King's College London, 8th Floor, Tower Wing, Guy's Hospital, London, SE1 9RT, UK.|School of Medicine, Derby Royal Hospital, Derbyshire, UK.
Hannah
H
Crossland
School of Medicine, Derby Royal Hospital, Derbyshire, UK.
Bethan E
BE
Phillips
Department of Public Health, Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden.
Tommy
T
Cederholm
Medical Prognosis Institute A/S, Hørsholm, Denmark.
Thomas
T
Jensen
NUTRIM, Maastricht University, Maastricht, The Netherlands.
Luc J C
LJ
van Loon
Department of Public Health and Caring Sciences/Molecular Geriatrics, Uppsala University, Uppsala, Sweden.
Lars
L
Lannfelt
Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA.
William E
WE
Kraus
School of Medicine, Derby Royal Hospital, Derbyshire, UK.
Philip J
PJ
Atherton
Department of Old Age Psychiatry, King's College London, London, UK.
Robert
R
Howard
Division of Clinical Physiology, Karolinska University Hospital, Stockholm, Sweden.
Thomas
T
Gustafsson
Department of Old Age Psychiatry, King's College London, London, UK.
Angela
A
Hodges
XRGenomics Ltd, London, UK. james.timmons@kcl.ac.uk.|Division of Genetics & Molecular Medicine, King's College London, 8th Floor, Tower Wing, Guy's Hospital, London, SE1 9RT, UK. james.timmons@kcl.ac.uk.
James A
JA
Timmons
D000328:Adult; D000368:Aged; D000375:Aging / Q000235:genetics*; D015415:Biomarkers / Q000032:analysis; D001921:Brain / Q000378:metabolism; D003071:Cognition; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000378:metabolism; D010641:Phenotype; D012313:RNA / Q000097:blood; D015203:Reproducibility of Results; D012867:Skin / Q000378:metabolism; D055815:Young Adult
D015415:Biomarkers; D012313:RNA