| Application: | 10279, The relationship of cognitive function and negative emotions with morbidity and mortality: an aetiological investigation |
| Title: | Genetic prediction of male pattern baldness |
| Size: | 872569 B |
| Archived: | 2 Aug 2018 |
| Stability: | Complete |
| Personal: | No individual-level data |
Return 1522
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Notes
Living with male pattern baldness can be stressful and embarrassing. Previous studies have shown baldness to have a complex genetic architecture, with particularly strong signals on the X chromosome. However, these studies have been limited by small sample sizes. Here, we present the largest genome-wide study of baldness to date, using data from over 52,000 male participants in the UK Biobank study. We identify over 200 novel findings. We also split our dataset in two to build and apply a genetic predictor of baldness. Of those with a polygenic score below the median, 14% had severe hair loss and 39% no hair loss. By contrast, of those with a polygenic score in the top 10%, 58% reported moderate-to-severe hair loss.Application 10279
The relationship of cognitive function and negative emotions with morbidity and mortality: an aetiological investigation
The proposed research aims to understand why it is that poorer cognitive function and negative emotional factors are typically associated with poorer health and increased mortality. We shall use health outcome data to examine how all-cause mortality and incident cancer and cardiovascular disease (CVD)vary according to prior cognitive function and negative emotions. We shall investigate the extent to which relationships we find between cognition, emotions and these health outcomes are explained or modified by physical, biological, genetic, behavioural, and socio-demographic factors. Genetic analyses will incorporate multivariate genome-wide complex trait analysis and polygenic prediction of these relationships. Poorer cognitive function and negative emotional states and traits have been shown to increase mortality but the reasons for this are unclear. We anticipate that the proposed research will: 1) show us how mortality and morbidity from common health conditions vary according to prior cognitive abilities and emotional factors; 2) reveal potential mechanisms whereby poorer cognition and negative emotion increase risk; and 3) identify whether other characteristics can increase or reduce the risk of ill health in those with poorer cognition and negative emotions. This information could help inform intervention strategies for preventing or treating common health conditions. Using data on cognitive function and negative emotions together with data collected on health outcomes, scientists at the Centre for Cognitive Ageing and Cognitive Epidemiology will examine whether cognitive performance and emotional states predict risk of all-cause mortality and the onset of cancer and CVD. They will investigate whether other characteristics, such as lifestyle, socio-demographic, physical, behavioural or biological factors, help to explain any links between cognitive function and emotions and these health outcomes. They will estimate degree of genetic sharing between: 1) cognitive function/emotions and these characteristics, and 2) cognitive function/emotions and health outcomes. The full cohort
| Lead investigator: | Dr Michelle Luciano |
| Lead institution: | University of Edinburgh |
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1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 1523 | Genetic prediction of male pattern baldness | Saskia P. Hagenaars (+9) | 2017 | PLOS Genetics |
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