Abstract
The aim of this study was to measure the impact of genetic data in improving the prediction of type 2 diabetes (T2D) in the Malmö Diet and Cancer Study cohort. The current study was performed in 3,426 Swedish individuals and utilizes of a set of genetic and environmental risk data. We first validated our environmental risk model by comparing it to both the Finnish Diabetes Risk Score and the T2D risk model derived from the Framingham Offspring Study. The area under the curve (AUC) for our environmental model was 0.72 [95% CI, 0.69–0.74], which was significantly better than both the Finnish (0.64 [95% CI, 0.61–0.66], p-value < 1 x 10−4) and Framingham (0.69 [95% CI, 0.66–0.71], p-value = 0.0017) risk scores. We then verified that the genetic data has a statistically significant positive correlation with incidence of T2D in the studied population. We also verified that adding genetic data slightly but statistically increased the AUC of a model based only on environmental risk factors (RFs, AUC shift +1.0% from 0.72 to 0.73, p-value = 0.042). To study the dependence of the results on the environmental RFs, we divided the population into two equally sized risk groups based only on their environmental risk and repeated the same analysis within each subpopulation. While there is a statistically significant positive correlation between the genetic data and incidence of T2D in both environmental risk categories, the positive shift in the AUC remains statistically significant only in the category with the lower environmental risk. These results demonstrate that genetic data can be used to increase the accuracy of T2D prediction. Also, the data suggests that genetic data is more valuable in improving T2D prediction in populations with lower environmental risk. This suggests that the impact of genetic data depends on the environmental risk of the studied population and thus genetic association studies should be performed in light of the underlying environmental risk of the population.
Highlights
Type 2 diabetes, the most common form of diabetes, is a rising healthcare problem worldwide
Among the 21 environmental RFs and 154 genetic RFs that were utilized by the Risk assessment engine (RAE) for its type 2 diabetes (T2D) assessment, data for only 13 environmental and 139 genetic RFs was available from the Malmo Diet and Cancer study (MDC)-CC (Tables 3 and 4)
We found that 62% of the environmental factors that are used by the RAE were available in the data for the MDC-CC
Summary
Type 2 diabetes, the most common form of diabetes, is a rising healthcare problem worldwide. The number of people affected with type 2 diabetes has risen significantly over the past 30 years. The global prevalence of diabetes among adults over 18 years of age has increased from. Http://www.vr.se, Goran Gustafsson Foundation www.gustafssonsstiftelser.se and the Knut and Alice Wallenberg Foundation https://www. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funder, BaseHealth Inc., provided support in the form of salaries for authors HZ, HF and SL, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section
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