title: Significance of genetic information in risk assessment and individual classification using silicosis as a case model.
abstract: Over the last decade the role of genetic data in epidemiological research has expanded considerably. We recently published a case-control study that evaluated the interaction between silica exposure and minor variants in the genes coding for interleukin-1alpha (IL-1alpha), interleukin-1 receptor antagonist (IL-1RA) and tumor necrosis factor alpha (TNFalpha) as risk factors associated with silicosis, a fibrotic lung disease. In contrast, this report uses data generated from these studies to illustrate the utility of genetic information for the purposes of risk assessment and clinical prediction. Specifically, this study will address how, given a known exposure, genetic information affects the characterization of risk groups. Relative operating characteristic (ROC) curves were then used to determine the impact of genetic information on individual classification. Logistic regression modeling procedures were used to estimate the predicted probability of developing silicosis. This probability was then used to construct predicted risk deciles, first for a model with occupational exposure only and then for a model containing occupational exposure and genetic main effects and interactions. Results indicate that the exposure-only model effectively captures an increasing relationship between predicted risk deciles and prevalence of observed silicosis cases. Individuals comprising the highest risk decile were almost four times as likely to have silicosis as opposed to the lowest risk decile. The addition of genetic data, however, substantially improved characterization of risk categories; the proportion of cases in the highest risk decile was almost eight times that in the lowest risk decile. However, the ROC curve and classification analysis demonstrated that the addition of genetic main effects and interactions did not significantly impact on prediction of the individual's case status. These results indicate that genetic information plays a valuable role in effectively characterizing risk groups and mechanisms of disease operating in a substantial proportion of the population. However, in the case of fibrotic lung disease caused by silica exposure, information about the presence or absence of the minor variants of IL-1alpha, IL-1RA and TNFalpha is unlikely to be a useful tool for individual classification.
authors.affiliation: Biostatistics Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505, USA. eim4@cdc.gov
authors.forename: Erin
authors.initials: E
authors.lastname: McCanlies
authors.forename: Douglas P
authors.initials: DP
authors.lastname: Landsittel
authors.forename: Berran
authors.initials: B
authors.lastname: Yucesoy
authors.forename: Val
authors.initials: V
authors.lastname: Vallyathan
authors.forename: Michael L
authors.initials: ML
authors.lastname: Luster
authors.forename: Dan S
authors.initials: DS
authors.lastname: Sharp
mesh_terms: D000368:Aged; D003032:Coal Mining; D020022:Genetic Predisposition to Disease / Q000453:epidemiology*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012829:Silicosis / Q000453:epidemiology* / Q000235:genetics*