title: Human aging is characterized by focused changes in gene expression and deregulation of alternative splicing.
abstract: Aging is a major risk factor for chronic disease in the human population, but there are little human data on gene expression alterations that accompany the process. We examined human peripheral blood leukocyte in-vivo RNA in a large-scale transcriptomic microarray study (subjects aged 30-104 years). We tested associations between probe expression intensity and advancing age (adjusting for confounding factors), initially in a discovery set (n= 58), following-up findings in a replication set (n=240). We confirmed expression of key results by real-time PCR. Of 16,571 expressed probes, only 295 (2%) were robustly associated with age. Just six probes were required for a highly efficient model for distinguishing between young and old (area under the curve in replication set; 95%). The focused nature of age-related gene expression may therefore provide potential biomarkers of aging. Similarly, only 7 of 1065 biological or metabolic pathways were age-associated, in gene set enrichment analysis, notably including the processing of messenger RNAs (mRNAs); [P<0.002, false discovery rate (FDR) q<0.05]. This is supported by our observation of age-associated disruption to the balance of alternatively expressed isoforms for selected genes, suggesting that modification of mRNA processing may be a feature of human aging.
authors.affiliation: Institute of Biomedical and Clinical Sciences, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK. Lorna.Harries@pms.ac.uk
authors.forename: Lorna W
authors.initials: LW
authors.lastname: Harries
authors.forename: Dena
authors.initials: D
authors.lastname: Hernandez
authors.forename: William
authors.initials: W
authors.lastname: Henley
authors.forename: Andrew R
authors.initials: AR
authors.lastname: Wood
authors.forename: Alice C
authors.initials: AC
authors.lastname: Holly
authors.forename: Rachel M
authors.initials: RM
authors.lastname: Bradley-Smith
authors.forename: Hanieh
authors.initials: H
authors.lastname: Yaghootkar
authors.forename: Ambarish
authors.initials: A
authors.lastname: Dutta
authors.forename: Anna
authors.initials: A
authors.lastname: Murray
authors.forename: Timothy M
authors.initials: TM
authors.lastname: Frayling
authors.forename: Jack M
authors.initials: JM
authors.lastname: Guralnik
authors.forename: Stefania
authors.initials: S
authors.lastname: Bandinelli
authors.forename: Andrew
authors.initials: A
authors.lastname: Singleton
authors.forename: Luigi
authors.initials: L
authors.lastname: Ferrucci
authors.forename: David
authors.initials: D
authors.lastname: Melzer
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D017398:Alternative Splicing; D015415:Biomarkers; D015331:Cohort Studies; D005260:Female; D020869:Gene Expression Profiling; D018507:Gene Expression Regulation, Developmental; D015894:Genome, Human; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D020033:Protein Isoforms / Q000235:genetics / Q000378:metabolism; D012333:RNA, Messenger / Q000097:blood / Q000235:genetics / Q000378:metabolism
chemical_list: D015415:Biomarkers; D020033:Protein Isoforms; D012333:RNA, Messenger