Development and Application of Population-Based Dynamic Relative Relationship with Trans-Generation Pedigree Structure---An Illustation from Hypertension Based on Keelung Community-Based Integrated Screeing

Background Population and family-based data play an important role in genetic epidemiology, particularly studying familial aggregation. However, such data are hardly available. Health information management system based integrated screening which based on community family members offers an opportunity to develop fundaments of population-based and family-based associated researches. The dynamic algorithms for family construction and identification of relationship were developed for research and public health application from nuclear family to extended family. Aims The aim of this project is to develop the auto-, dynamic algorithm for family construction and relationship based on population-based and family-based database by using 10-year screening program in Keelung city. This development will be helpful for efficient work for large-scale study for disease-oriented family and genetic studies. Methods Based on Keelung community-based integrated screening program, we investigated to (1)develop dynamic, systematized and computerize algorithm to build up population-based and family-based data; (2)illustrate how population-based and family-based data from (1) can be applied to study whether and how familial aggregation in association with dynamic relationship with proband (disease) change was attributed to genetic factors, environmental factors, or both using family case-control proband study design; (3)illustrated how population-based and family-based from (2) can be applied to study population-based association and familial aggregation of hypertension. Based on the Keelung population-based registry database, at least, the three generation of family structure will be expected to represent in our research outcome. All participants were informed the data management for health care by Health Bureau of Keelung. We will perform this algorithm development on the computer server of Keelung office. All procedures are required on behave of statement of personal information security. The KCIS data was further linked with population registry by identical name of parents to construct trans-generation pedigree (at first stage) and to ascertain degrees of relationship at the second stage. This family-based data was applied to study familial aggregation of hypertension with family case-control proband sampling design and of hypertension with entire cohort. The random sample with proband research was conducted for demonstration of dynamic algorithm for relationship identification. For the familial aggregation approach of hypertension, our study will conducted generalized estimation equation (GEE) to analyze the effect of family aggregation on hypertension adjusted other factors, especially for effect on different relationship. Expected outcome Population-based and family-based data were further developed for studies on genetic epidemiology underpinning health information management system for KCIS with dynamic algorithm of family construction. This system not only integrated multiple diseases screening, but also make significant contribution to epidemiology profiles, including investigation of familial aggregation or advanced genetic researches. Based on applications of family-based database and different statistical methods, as far as familial aggregation is concerned, our results supported the early finding studies, both genetic and environmental contributed to hypertension. This program and dynamic algorithm development will be the basis for future analysis of gene-disease associations and gene-environment interactions, which will be applied for population- and family-based for many diseases discovery. It would be promising for application of public health and disease risk management.

Project ID:PC9907-2506
External Project ID:NSC99-2314-B182-026