Erik van den Akker | 28-02-2015 | Computational Biology in Human Aging. An omics data integration approach
Throughout this thesis, human aging and its relation to health are studied in the context of two parallel though complementary lines of research: biomarkers and genetics. The search for informative biomarkers of aging focuses on easy accessible and quantifiable substances of the body that can be used to predict the early signs of deteriorating health, prior to the development of overt age-related disease. The challenge in this field is to translate the molecular changes captured by omics platforms to the age-associated deterioration observed at the whole body-level. In this thesis, new integrative methodology was developed that lead to the identification of gene expression networks that serve as biomarkers for aging and mortality. The second part of this thesis is aimed at identifying genetic determinants that predispose to a decelerated rate of aging and an extension of life span. Using whole genome sequencing data created in 218 nonagenarians of the Leiden Longevity Study we observed that a long life is not necessarily hampered by potentially premalignant somatic mutations in either TET2 or DNMT3A. In addition, genetic variation at chr13q34 attenuating the thyroid function, may be beneficial at middle age, but seems to contribute causally to increased mortality above 90 years.