Genome-wide linkage analysis of systolic blood pressure slope using the Genetic Analysis Workshop 13 data sets
2003

Genome-wide analysis of blood pressure changes over time

Sample size: 1672 publication Evidence: moderate

Author Information

Author(s): Pinnaduwage Dushanthi, Beyene Joseph, Fallah Shafagh

Primary Institution: Mount Sinai Hospital, Toronto, Ontario, Canada

Hypothesis

Can multiple imputation improve the analysis of systolic blood pressure changes in genetic studies?

Conclusion

Multiple imputation is effective in recovering missing data in longitudinal genetic studies, enhancing linkage analysis results.

Supporting Evidence

  • Multiple imputation improved linkage results for treated subjects.
  • Heritability estimates for SBP slopes were higher for females than males.
  • Significant differences in SBP slopes were found between genders in the Framingham data.

Takeaway

This study looked at how blood pressure changes over time and found that using a special method to fill in missing data helps researchers get better results.

Methodology

A variance-component model and multiple imputation were used to analyze the rate of change in systolic blood pressure over time.

Potential Biases

Exclusion of treated subjects in one method may reduce power to detect genetic links.

Limitations

The study excluded deceased individuals, which may have led to loss of important genetic information.

Participant Demographics

Cohort 2 of the Framingham Heart Study, including both males and females.

Statistical Information

P-Value

0.00004

Statistical Significance

p<0.0001

Digital Object Identifier (DOI)

10.1186/1471-2156-4-S1-S86

Want to read the original?

Access the complete publication on the publisher's website

View Original Publication