Research Paper Volume 9, Issue 11 pp 2288—2301
Transcriptome-wide association study of inflammatory biologic age
- 1 National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- 2 Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
- 3 Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- 4 Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- 5 Section of Cardiovascular Medicine and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
- 6 Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
- 7 Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
- 8 Department of Cardiology, Boston Children's(tm)s Hospital, Harvard Medical School, Boston, MA 02115, USA
- 9 Hebrew SeniorLife, Harvard Medical School, Boston, MA 02115, USA
- 10 Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
Received: August 11, 2017 Accepted: November 2, 2017 Published: November 11, 2017
https://doi.org/10.18632/aging.101321How to Cite
Copyright: Lin et al. This is an open‐access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
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.
Abbreviations
DMGs: Differentially methylated genes.