Familial risk ratio of sarcoidosis in African-American sibs and parents

Am J Epidemiol. 2001 Jan 15;153(2):188-93. doi: 10.1093/aje/153.2.188.


While sarcoidosis is thought to aggregate in families, little is known about the risk to relatives of sarcoidosis patients. To estimate the familial risk ratio (lambda) of sarcoidosis in sibs and parents of cases, the authors studied 179 African-American families ascertained through an index sarcoidosis case diagnosed at Henry Ford Hospital in Detroit, Michigan. Among those relatives enrolled between 1997 and 1999, 12 of 327 (3.7%) sibs and 11 of 161 (6.8%) parents reported a history of sarcoidosis. The lambda in this sample of relatives, estimated by computing an age, sex, and race standardized incidence ratio, was 2.24 (95% confidence interval: 1.16, 3.92) for sibs and 2.82 (95% confidence interval: 1.41, 5.05) for parents. For sibs and parents combined, lambda was 2.49 (95% confidence interval: 1.58, 3.73). Results stratified by proband characteristics indicated that lambda was greater for relatives of younger (lambda = 2.93, 95% confidence interval: 1.52, 5.12) and male (lambda = 3.98, 95% confidence interval: 1.99, 7.12) probands. A higher lambda was also found for male family members and sibs born later in the birth order. A Monte Carlo method was also used to estimate lambda, with similar results obtained. Overall, these results indicate that, in African Americans, sibs and parents of sarcoidosis cases have about a 2.5-fold increased risk for sarcoidosis and that heterogeneity in disease risk may exist among family members.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • African Continental Ancestry Group / genetics*
  • Age Distribution
  • Aged
  • Birth Order
  • Female
  • Genetic Heterogeneity
  • Humans
  • Incidence
  • Male
  • Michigan / epidemiology
  • Middle Aged
  • Monte Carlo Method
  • Odds Ratio
  • Pedigree
  • Risk Factors
  • Sarcoidosis / epidemiology
  • Sarcoidosis / genetics*
  • Sex Distribution
  • Urban Health / statistics & numerical data