Epigenome-wide association scans (EWAS) of human complex traits are a rapidly growing area of research, in part due to recent advances in technology that have allowed for a deeper coverage of the human methylome. One of the unique features of the human methylome is that it is dynamic and previous studies have shown that age can have a strong impact on DNA methylation patterns. The dynamic nature of DNA methylation also influences EWAS methodology, both from a statistical and biological perspective. In this thesis, I explored EWAS methods and applications to ageing and age-related phenotypes. Firstly, I estimated EWAS power under several simulation scenarios and study designs, and my results suggested that the majority of recent EWAS studies lack statistical power to detect small DNA methylation effect sizes. I then applied EWAS to identify differential methylation CpG sites associated with three phenotypes, including ageing, birth weight and smoking. One of the novel findings from this thesis was that hundreds of genome-wide significant ageing-related hypermethylated regions were identified across multiple tissues in twins. These findings confirm and extend previous work showing that ageing has a strong underlying effect on DNA methylation. Birth weight did not yield significant differential methylation sites, which may be partly explained by low power to detect modest methylation effects. Smoking is a well-known environmental risk factor for disease, and my analyses identified novel impacts of smoking on DNA methylation patterns in adipose tissue, which are of interest to cardiovascular and metabolic disease. I further explored the impacts of smoking by integrating DNA methylation and gene expression profiles in adipose tissue and in whole blood. In addition to identifying novel results, my findings also confirmed that the AHRR and F2RL3 genes showed stable and consistent changes related to smoking in both DNA methylation and gene expression profiles across tissues. My findings explored methodological issues in genome-wide methylation studies and showed that age and smoking have a strong and reproducible effect on DNA methylation across tissues in humans, which suggests that these factors should always be included as covariates in EWAS of human complex traits.