Risk factor patterns in type 2 diabetes and cardiovascular disease : exploring methods for precision medicine in public health

Non-communicable diseases, including type 2 diabetes and cardiovascular disease, are leading contributors to the global burden of disease and an important public health challenge. At an individual level, there is important variability in the risk of these conditions. However, public health interventions often adopt a generalized one-size-fits-all approach.

The overall aim of this thesis was to explore the utility of a precision medicine approach to public health and epidemiology, by applying different analytical methods to classify individuals into similar sub-populations based on their individual level characteristics.

In study I, I investigated the patterns of weight changes from childhood to early adulthood and how they relate to the occurrence of type 2 diabetes later in life. The results indicate that exposure to overweight/obesity during early adulthood explains a large proportion of the cases of type 2 diabetes, highlighting the importance of public health interventions during this period.

In study II, I used different methods for mediation analysis to study the importance of different mechanisms linking low socioeconomic status and type 2 diabetes. The findings show that around 50% of the association between socioeconomic status and type 2 diabetes could be reduced if unhealthy behaviors and metabolic exposures were removed. Interestingly, the results were similar across the different mediation methods.

Finally, in studies III and IV, I used data-driven methods to identify sub-groups of healthy adults based on simple clinical characteristics and laboratory values. The findings show that this method was equally effective, or even better, than those commonly used in clinical practice, and could improve the way we define who is at high risk of type 2 diabetes or cardiovascular disease.

In conclusion, these studies provide evidence that precision medicine can be a useful approach to guide development and implementation of public health interventions.

List of scientific papers

I. Yacamán-Méndez D, Trolle-Lagerros Y, Zhou M, Ponce de Leon A, Gudjonsdottir H, Tynelius P, Lager A. Life-course trajectories of weight and their impact on the incidence of type 2 diabetes. Sci Rep. 2021 Jun 14;11(1):12494.
https://doi.org/10.1038/s41598-021-91910-z

II. Yacamán Mendez D, Trolle Lagerros Y, Ponce de Leon A, Tynelius P, Fors S, Lager A. Behavioral and metabolic mediators of socioeconomic inequalities in type 2 diabetes: comparing counterfactual and traditional mediation analysis. [Submitted]

III. Yacamán Méndez D, Zhou M, Trolle Lagerros Y, Gómez Velasco DV, Tynelius P, Gudjonsdottir H, Ponce de Leon A, Eeg-Olofsson K, Östenson CG, Brynedal B, Aguilar Salinas CA, Ebbevi D, Lager A. Characterization of data-driven clusters in diabetes-free adults and their utility for risk stratification of type 2 diabetes. BMC Med. 2022 Oct 18;20(1):356.
https://doi.org/10.1186/s12916-022-02551-6

IV. Yacamán Méndez D, Zhou M, Trolle Lagerros Y, Lager A. Cluster analysis for cardiovascular risk stratification. [Submitted]