The Academia Sinica said its Taiwan Biobank project — a large-scale population-based genetic database — has identified a predictive model for diabetes with a precision rate of about 88 percent.
In three years of operations the database has gathered information from more than 53,000 people, including biospecimens, blood, urine, DNA, dietary patterns, lifestyle and family health history.
Since September last year it has initiated more than 20 research projects investigating causes for common diseases.
Institute of Biomedical Sciences Academia Sinica research fellow and Taiwan Biobank chief executive Shen Chen-Yang (沈志陽) said the team screened approximately 650,000 loci (the specific location or position of a gene or DNA sequence on a chromosome) and identified 41 loci significantly associated with genetic susceptibility to type II diabetes.
Using the 41 loci as preceptor of diabetes, the precision rate is only about 72 percent, but researchers developed a predictive model for type II diabetes based on these loci, as well as other risk factors, such as obesity and smoking, and the precision rate increased to about 88 percent, Shen said.
Although genetics play a role in determining the occurrence of diabetes, environmental factors, including smoking, drinking alcohol, obesity and other lifestyle choices also play a part in the occurrence of type II diabetes, he said.
It is hoped the prediction model can help doctors assess the risk of diabetes in individuals at a lower cost, he said.
Other than the diabetes prediction model, Shen said the database has completed whole-genome sequencing of 1,000 individuals and whole-genome typing for 12,000 individuals this year, and it hopes to collect information from over 200,000 people by 2024, allowing the nation to have a database for genetic research.
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