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Analytic options for asthma genetics

S S Rich1

  • 1Department of Public Health Sciences, Bowman Gray School of Medicine, Winston-Salem, North Carolina, USA.

Clinical and Experimental Allergy : Journal of the British Society for Allergy and Clinical Immunology
|June 26, 1998
PubMed
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Analyzing asthma genetics is complex. New quantitative trait scores, like the Framingham Risk Score, may improve genetic mapping power but require further development for family-based studies.

Area of Science:

  • Genetics
  • Pulmonology
  • Biostatistics

Background:

  • Current asthma genetics studies predominantly use non-parametric linkage analysis on genome screen data from affected sibling pairs.
  • Analyzing asthma genetics is complicated by phenotypic definitions and joint analysis with related traits.

Purpose of the Study:

  • To explore alternative analytical approaches for asthma genetics research.
  • To evaluate the potential of treating asthma as a quantitative trait rather than a binary one.

Main Methods:

  • Review of current non-parametric methods for asthma genetics.
  • Discussion of alternative quantitative trait approaches, including risk scores, selection indices, and propensity scores.
  • Consideration of challenges in estimation and family structure incorporation for new methods.

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Main Results:

  • Existing methods focus on sibling pair linkage analysis.
  • Quantitative trait approaches offer potential but face unresolved estimation and family structure issues.
  • Standardized clinical data collection across studies could enhance genetic mapping power.

Conclusions:

  • Developing quantitative trait scores for asthma presents challenges but holds promise.
  • Further research is needed to resolve estimation and family incorporation issues for these novel scores.
  • Collaborative data collection can significantly boost the power of genetic mapping studies for asthma.