
Chronic low grade inflammation is a fundamental mechanism of aging. We estimated biologic age using nine biomarkers from diverse inflammatory pathways and we hypothesized that genes associated with inflammatory biological age would provide insights into human aging. In Framingham Offspring Study participants at examination 8 (2005 to 2008), we used the Klemera-Doubal method to estimate inflammatory biologic age and we computed the difference (∆Age) between biologic age and chronologic age. Gene expression in whole blood was measured using the Affymetrix Human Exon 1.0 ST Array. We used linear mixed effect models to test associations between inflammatory ∆Age and gene expression (dependent variable) adjusting for age, sex, imputed cell counts, and technical covariates. Our study sample included 2386 participants (mean age 67A±9 years, 55% women). There were 448 genes significantly were associated with inflammatory ∆Age (P<2.8x10-6), 302 genes were positively associated and 146 genes were negatively associated. Pathway analysis among the identified genes highlighted the NOD-like receptor signaling and ubiquitin mediated proteolysis pathways. In summary, we identified 448 genes that were significantly associated with inflammatory biologic age. Future functional characterization may identify molecular interventions to delay aging and prolong healthspan in older adults.
Male, Aging, Genotype, 610, 616, Humans, Gene Regulatory Networks, Protein Interaction Maps, Aged, Oligonucleotide Array Sequence Analysis, Inflammation, Gene Expression Profiling, aging, Age Factors, Middle Aged, Phenotype, Massachusetts, inflammation, gene expression, Linear Models, epidemiology, Female, Transcriptome, Research Paper, Genome-Wide Association Study, Signal Transduction
Male, Aging, Genotype, 610, 616, Humans, Gene Regulatory Networks, Protein Interaction Maps, Aged, Oligonucleotide Array Sequence Analysis, Inflammation, Gene Expression Profiling, aging, Age Factors, Middle Aged, Phenotype, Massachusetts, inflammation, gene expression, Linear Models, epidemiology, Female, Transcriptome, Research Paper, Genome-Wide Association Study, Signal Transduction
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
