Disease and tissue aging are thought to be influenced by genetic changes, or mutations, acquired throughout life. These mutations provide clues regarding the genetic damage that occurred through the lifetime of the patient, and include mutations caused by environmental factors such as ultraviolet light from sunlight or tobacco smoke affecting the skin or internal tissues, respectively. Other mutations may occur due to errors in copying the genome as cells divide. Improvements in technologies that read the genetic code have made it possible for all or selected parts of the genetic code of a human being to be "sequenced", allowing mutations (changes in the genetic code) to be detected.
In this research, samples of blood, skin biopsies, plucked hairs, urine, surplus tissue removed during future planned surgery, and archived samples removed in the past will be used. The order of DNA bases in the genetic code (sequencing) in the samples will help to understand how the number and type of cells with changes in their DNA is different in tissues depending on a person's age, their exposure to environmental agents, or other factors such as disease history or treatments such as radiotherapy.
Study Type
OBSERVATIONAL
Enrollment
600
Samples could include blood, skin biopsy, urine, plucked hair.
Excess surgical tissue (diseased tissue or tissue being removed for a clinical reason).
Wellcome Sanger Institute
Cambridge, United Kingdom
The study will measure the burden of somatic mutations in tissues and how this varies between controls and patients.
Robust statistical methods developed at the Wellcome Trust Sanger Institute will be used to analyse and interpret human genome data. This study will use bespoke computer programmes to determine the prevalence of rare mutations in normal tissue by competing the ratio of synonymous and nonsynonymous mutations for each gene analysed.
Time frame: 10 years
The specific mutations in genes and their prevalence will be determined.
Robust statistical methods developed at the Wellcome Trust Sanger Institute will be used to analyse and interpret human genome data. This study will use bespoke computer programmes to determine the prevalence of rare mutations in normal tissue by competing the ratio of synonymous and nonsynonymous mutations for each gene analysed.
Time frame: 10 years
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.