Dataset Information

Haplotype-based association analysis of general cognitive ability in Generation Scotland, the English Longitudinal Study of Ageing, and UK Biobank.

ABSTRACT: Background: Cognitive ability is a heritable trait with a polygenic architecture, for which several associated variants have been identified using genotype-based and candidate gene approaches. Haplotype-based analyses are a complementary technique that take phased genotype data into account, and potentially provide greater statistical power to detect lower frequency variants.

Methods: In the present analysis, three cohort studies (n _total = 48,002) were utilised: Generation Scotland: Scottish Family Health Study (GS:SFHS), the English Longitudinal Study of Ageing (ELSA), and the UK Biobank. A genome-wide haplotype-based meta-analysis of cognitive ability was performed, as well as a targeted meta-analysis of several gene coding regions.

Results: None of the assessed haplotypes provided evidence of a statistically significant association with cognitive ability in either the individual cohorts or the meta-analysis. Within the meta-analysis, the haplotype with the lowest observed P-value overlapped with the D-amino acid oxidase activator ( DAOA) gene coding region. This coding region has previously been associated with bipolar disorder, schizophrenia and Alzheimer's disease, which have all been shown to impact upon cognitive ability. Another potentially interesting region highlighted within the current genome-wide association analysis (GS:SFHS: P = 4.09 x 10 ^-7), was the butyrylcholinesterase ( BCHE) gene coding region. The protein encoded by BCHE has been shown to influence the progression of Alzheimer's disease and its role in cognitive ability merits further investigation.

Conclusions: Although no evidence was found for any haplotypes with a statistically significant association with cognitive ability, our results did provide further evidence that the genetic variants contributing to the variance of cognitive ability are likely to be of small effect.

SUBMITTER: Howard DM

PROVIDER: S-EPMC5605947 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Haplotype-based association analysis of general cognitive ability in Generation Scotland, the English Longitudinal Study of Ageing, and UK Biobank.

Howard David M DM Adams Mark J MJ Clarke Toni-Kim TK Wigmore Eleanor M EM Zeng Yanni Y Hagenaars Saskia P SP Lyall Donald M DM Thomson Pippa A PA Evans Kathryn L KL Porteous David J DJ Nagy Reka R Hayward Caroline C Haley Chris S CS Smith Blair H BH Murray Alison D AD Batty G David GD Deary Ian J IJ McIntosh Andrew M AM

Wellcome open research 20170810

<h4>Background</h4>Cognitive ability is a heritable trait with a polygenic architecture, for which several associated variants have been identified using genotype-based and candidate gene approaches. Haplotype-based analyses are a complementary technique that take phased genotype data into account, and potentially provide greater statistical power to detect lower frequency variants.<h4>Methods</h4>In the present analysis, three cohort studies (n <sub>total</sub> = 48,002) were utilised: Generati ...[more]

PMID: 28989979

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Project description:BackgroundThe number of people living with obesity or who are overweight presents a global challenge, and the development of effective interventions is hampered by a lack of research which takes a joined up, whole system, approach that considers multiple elements of the complex obesity system together. We need to better understand the collective characteristics and behaviours of those who are overweight or have obesity and how these differ from those who maintain a healthy weight.MethodsUsing the UK Biobank cohort we develop an obesity classification system using k-means clustering. Variable selection from the UK Biobank cohort is informed by the Foresight obesity system map across key domains (Societal Influences, Individual Psychology, Individual Physiology, Individual Physical Activity, Physical Activity Environment).ResultsOur classification identifies eight groups of people, similar in respect to their exposure to known drivers of obesity: 'Younger, urban hard-pressed', 'Comfortable, fit families', 'Healthy, active and retirees', 'Content, rural and retirees', 'Comfortable professionals', 'Stressed and not in work', 'Deprived with less healthy lifestyles' and 'Active manual workers'. Pen portraits are developed to describe the characteristics of these different groups. Multinomial logistic regression is used to demonstrate that the classification can effectively detect groups of individuals more likely to be living with overweight or obesity. The group identified as 'Comfortable, fit families' are observed to have a higher proportion of healthy weight, while three groups have increased relative risk of being overweight or having obesity: 'Active manual workers', 'Stressed and not in work' and 'Deprived with less healthy lifestyles'.ConclusionsThis paper presents the first study of UK Biobank participants to adopt this obesity system approach to characterising participants. It provides an innovative new approach to better understand the complex drivers of obesity which has the potential to produce meaningful tools for policy makers to better target interventions across the whole system to reduce overweight and obesity.

Dataset Information

Haplotype-based association analysis of general cognitive ability in Generation Scotland, the English Longitudinal Study of Ageing, and UK Biobank.

Publications

Haplotype-based association analysis of general cognitive ability in Generation Scotland, the English Longitudinal Study of Ageing, and UK Biobank.

Similar Datasets

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