Longitudinal variance-components analysis of the Framingham Heart Study data
2003

Analysis of Genetic Factors in Heart Disease Over Time

Sample size: 4692 publication Evidence: moderate

Author Information

Author(s): Stuart Macgregor, Sara A Knott, Ian White, Peter M Visscher

Primary Institution: University of Wales College of Medicine

Hypothesis

How do inherited factors related to heart disease change over the life of an individual?

Conclusion

The study found that a QTL affecting BMI primarily acts at younger ages and that genetic correlations between traits remain high across different ages.

Supporting Evidence

  • A QTL affecting BMI was shown to act mainly at early ages.
  • The longitudinal method allowed the characterization of the change in QTL effects with aging.
  • High genetic correlations were observed between traits across large time periods.

Takeaway

Scientists looked at how genes related to heart disease change as people get older, finding that some genes are more important when you're younger.

Methodology

The study used mixed-model-based random-regression and univariate variance component techniques to analyze longitudinal phenotype data.

Potential Biases

There may be biased QTL effects for QTL acting at later ages due to correlations between trait value and survival.

Limitations

Time constraints prevented a full longitudinal genome scan for QTL.

Participant Demographics

The study included 4692 individuals, with phenotype data available for 2885 individuals and genotype data for 1702 individuals.

Digital Object Identifier (DOI)

10.1186/1471-2156-4-S1-S22

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