Use of a genealogical database demonstrates heritability of pulmonary fibrosis.

BACKGROUND

Pulmonary fibrosis (PF) is a progressive fatal disease of unknown etiology. Identification of risk genes and pathways will enhance our understanding of this disease. Analysis of Utah genealogical resources has shown previously strong evidence for a genetic contribution to other disease, such as cancer. This approach has led to gene discovery in diseases, such as breast cancer and colon cancer and is used here for PF to quantify the heritability.

HYPOTHESIS

We hypothesize that there is a heritable contribution to death from PF and use existing genealogic and death certificate data to examine patterns of relatedness amongst individuals who have died of PF.

METHODS

We analyzed familial clustering of individuals who died from PF using the Utah Population Database, a unique population-based genealogical resource that has been linked to death certificates dating from 1904. We identified 1,000 individuals with at least three generations of genealogy data and a cause of death documented as PF (cases). We estimated the relative risk (RR) of death from PF among the first-, second-, and third-degree relatives of cases. We also tested the hypothesis of excess relatedness among the cases by comparing the average pairwise relatedness of all cases to the average pair-wise relatedness of 1,000 sets of matched controls.

RESULTS

We observed significantly increased risk for death from PF among the first- (RR = 4.69), second- (RR = 1.92), and third-degree relatives (RR = 1.14) of cases. The average relatedness of the 1,000 cases was significantly higher than the expected average relatedness of matched control sets (p < 0.001). When close (first- and second-degree) relationships were ignored, significantly increased relatedness remained (p = 0.002).

CONCLUSIONS

Our results demonstrate significant clustering among both close and distant relatives, providing strong support for genetic contributions to death from PF. High-risk pedigrees derived from this unique resource may help identify new risk genes and gene pathways.