Diabetes polygenic risk scores and maternal characteristics in Hoosier Moms Cohort participants

Gestational diabetes mellitus (GDM) increases the risk of adverse perinatal outcomes. Understanding genetic-based risk for GDM is important for clinical risk prediction. The objective of this study was to examine participant and pregnancy characteristics in different polygenic risk score (PRS) quartiles in a study cohort of people at high risk for GDM.

This was a secondary analysis of a prospective observational pregnancy cohort study. A total of 411 participants with a singleton gestation were recruited with samples obtained for DNA analysis. Ancestry-adjusted PRS for diabetes was calculated for the cohort via PLINK v1.9. Continuous variables were analyzed via ANOVA, and categorical variables were analyzed via Chi-square to examine participant differences by PRS risk quartile, with quartile 1 (Q1) at lowest genetic risk and quartile 4 (Q4) at highest genetic risk.

PRS values were calculated for 391 participants. Distributions of maternal characteristics were similar among the four PRS quartile groups. Participants in Q4 demonstrated a higher rate of positive family history of diabetes (61.9%, p = 0.06) and a higher rate of personal history of past GDM (8.2%, p = 0.08). Compared to individuals only in Q1 (46.4%), the rate of diabetes family history was significantly higher in Q4 (61.9%, p = 0.03). Dichotomizing PRS by combining Q1 and Q2 compared to Q3 and Q4 showed that rates of GDM may be higher in the higher risk group (12.8% vs. 7.1%, p = 0.06).

Pregnant individuals in the highest diabetes PRS risk group tended to be more likely to have a positive family history of diabetes and personal history of GDM. Higher risk quartiles tended to have higher rates of GDM. Ancestry-adjusted PRS calculations facilitated our ability to account for differences in baseline demographic characteristics such as race and ethnicity and thus are likely preferred to isolate the PRS effects on outcomes. These preliminary findings exploring PRS risk group characteristics, if replicated, may help clinicians understand how to stratify genetic-based GDM risk using only clinical characteristics.