Application of odds ratio regression models for assessing familial aggregation from case-control studies

Area of Science:

• Epidemiology
• Biostatistics
• Genetics

Background:

• Familial aggregation studies are crucial for understanding genetic and environmental influences on common diseases.
• Existing methods, like the Mantel-Haenszel estimator, often assume independence among relatives, which may not hold true.
• Chronic obstructive pulmonary disease (COPD) is a complex disease with suspected familial aggregation.

Purpose of the Study:

• To present a novel regression model for estimating covariate effects on odds ratios.
• To test for familial aggregation of common diseases in first-degree relatives.
• To develop a robust test statistic for covariate effects on odds ratios, without assuming independence among relatives.

Main Methods:

• Development of a regression model extending the Mantel-Haenszel estimator.
• Application of the model to family data from a chronic obstructive pulmonary disease (COPD) study.
• Inclusion of a robust test statistic for covariate effects on odds ratios.

Main Results:

• The proposed model estimates covariate effects on odds ratios, accounting for non-independence among relatives.
• Analysis of COPD family data suggested a difference in odds ratios between black and white case-control pairs.
• A potential difference in familial aggregation was observed across racial groups, though sample size limited definitive conclusions.

Conclusions:

• The developed regression model provides a flexible approach for analyzing familial aggregation of diseases.
• The findings suggest that race may be a significant covariate influencing familial aggregation of COPD.
• Further research with larger sample sizes is needed to confirm these preliminary observations regarding racial differences in COPD familial aggregation.