Edinburgh Research Explorer

A genome wide association study of non pathological cognitive ageing

Project: Research

StatusFinished
Effective start/end date1/09/0831/08/10
Total award£844,183.00
Funding organisationBBSRC
Funder project referenceBB/F019394/1
Total award£28,375.00
Funding organisationBBSRC
Funder project referenceBB/F019394/1
Period1/09/0831/08/10

Key findings

This project combines two of the largest and most informative elderly cognitive ageing cohorts in the world. A whole genome screen of their DNA was performed using the most up to date genetic testing platform to allow the most detailed screening of an elderly cohort for genes that influence cognitive ability and decline. This project has created a resource which combines detailed genetic information with an individual's cognitive ability and its age-related change, for approximately 3,500 individuals. This is an unusual resource as very few studies have detailed cognitive decline data over extended periods of time.
One aspect of this project found that intelligence in old age is influenced by many genes each of which has a very small effect. We found that it is possible to predict intelligence, although with limited accuracy, from purely genetic information. We were also able to estimate the proportion of intelligence which is attributable to common variation observed in the genome. Using a similar method we were able to investigate genetic contributions to stability and change in intelligence from childhood to old age.
We identified an association of the TOMM40/APOE region of chromosome 19 with cognitive decline. This region is known to be associated with Alzheimer's disease (AD). As part of this study we performed a detailed genetic analysis of this region of the genome which has long been associated with AD. The results of this analysis suggest that APOE has an effect on cognitive decline in healthy older individuals.
We were the first group in the world to discover and publish that three genetic differences explain a lot of what makes people's blood clot in different times. Three genetic variants were found to explain ~18% of the variation in activated partial thromboplastin (aPTT) time, a measure of blood clotting time, in the Lothian Birth Cohorts. aPTT is associated with risk of thrombosis and coagulation disorders.
This study has also made huge contributions to our knowledge of the genetic bases of bodily physiology and biochemistry through participation in more than 50 large genetic consortia. This has already led to many publications, summarized below, with many more in preparation.
Summaries of consortia publications:
Measures of lung function indicate respiratory health and are used in the diagnosis of respiratory disease. The effects of 2.5 million genetic variants on lung function measures were analysed in 48,000 individuals. Regions of the genome in or close to 16 genes were found to have an effect on lung function. These genes could be used to develop new drug targets for the treatment of respiratory diseases.
Platelets are an essential part of the blood’s clotting mechanism. The effects of 2.5 million genetic variants on platelet measures were analysed in 66,000 individuals. Sixty eight regions of the genome were found to be linked to these platelet measures. Animal models, zebra fish and fruit flies, were used for further investigation of these regions and 11 genes were found to play a role in blood cell formation.
Previous studies have identified genetic variants which have an effect on blood pressure. In this study the effect of genetic variants on two further blood pressure measures, mean arterial pressure (MAP) and pulse pressure (PP). MAP is used to describe an average blood pressure in an individual and PP is defined as the amount of pressure required to create the feeling of a pulse. Seven new regions, in or close to genes, were found to have an effect on MAP (4), PP (2) or both of the measures (1). These results identified new biological pathways which influence variation in blood pressure.
Variation in personality is predictive of many outcomes in life, including mental health. 2.5 million genetic variants were analysed for association with personality measures in approximately 17000 individuals. Personality measures used were Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness. One gene, KATNAL2, was found to found to have an effect on conscientiousness, however a follow up analysis in a further 3000 individuals did not confirm this finding.
Four genes previously reported to have an effect on early onset Alzheimer’s disease and other neurodegenerative diseases were analysed for associations with risk of late onset Alzheimer’s disease. Three of the genes studied were not found to contribute to the risk of developing late onset Alzheimer’s disease. One gene, MAPT, was found to confer a possible risk, this finding requires further study.
Genetic factors that influence success in bodily ageing are thought to also contribute to the successful ageing of mental abilities. Genes found to be linked to longevity in model organisms, yeast and nematodes, were investigated for association with mental ability in around 3500 older individuals and decline in this ability. One gene, SYNJ2, was found to be associated with mental ability in older individuals.
Genetic influences on age at natural menopause were investigated in around 44,000 women. Four previously reported genomic regions and 13 new regions were found to be associated with age at menopause. Functions of the genes found in these regions include DNA repair and immune function. A pathway analysis method, used to identify groups of genes linked by function, identified new biological processes linked to timing of menopause.
The white matter of the brain forms connections between the nerve cells. White matter integrity is a measure of the health of those connections. Variation at approximately 550,000 genetic markers was investigated for association with white matter integrity in around 500 older individuals. Suggestive links were reported with two genes (ADAMTS18 and LOC388630) however further work is required to confirm these findings. A pathway analysis method, used to identify groups of genes linked by function, identified biological processes - involving transmission of information and cell signaling - linked to white matter integrity measures.

Press/Media

Research outputs