Investigation into the inter-relationship between paternal age, traits and the incidence of diseases
Principal Investigator:
Dr Pin Tong
Approved Research ID:
4364
Approval date:
January 20th 2014
Lay summary
The average age of fathers has dramatically increased in industrialized countries over the past 40 years, with the average age of fathers in England and Wales increasing from 29 to 33 between 1974 and 2011. The aim of this study is to characterize the population health consequences of this trend, by investigating the relationship between a father?s age and each of the diseases and also quantitative traits (weight, height etc) recorded in the UK Biobank cohort. Previous studies have shown that the incidence of certain diseases, including, schizophrenia, autism spectrum disorders and major depressive disorder, is higher in individuals born to older fathers. This has been attributed to the higher number of mutations in the sperm of older men. Consequently children of older fathers have an increased risk that a disease or trait-associated gene has been mutated. Despite the importance of these novel mutations to population disease incidence, their contribution to the majority of disorders and traits remains poorly characterised. We propose to investigate the inter-relationship between paternal age, traits and the incidence of diseases using the cohort of 114,687 individuals for whom the father's age is known. For this, we will use the data on diseases and traits in these individuals as reported at recruitment, in hospital admissions records as well as corresponding information from cancer/death registries. Using these data (no samples being required) we will characterize which disorders and traits are most strongly associated with paternal age (having controlled for potential confounding factors), and which are therefore most likely to be affected by the average increase in the age of fathers. The co-association of participants father?s age with their baseline traits and risk of disease will also be considered. 17,673 Generation Scotland individuals will be used as a replication dataset in this study.