MULTIOMICS PREDICTION OF GESTATIONAL DIABETES

Gestional Daibetes (GD) is a common complication of pregnancy associated with adverse perinatal outcomes, and identifying women at risk of future type 2 diabetes. We have previously shown in BiB that fetal growth (assessed by repeat unltasound) is greater in those whose mothers were diagnosed with GD compared to those not, indicating that earlier diagnosis (and hence treatment) is important.1 We have also previously shown, in BiB, that NM (externally validated in the UPBEAT cohort) and MS (externally validated in the POPs cohort) metabolites increase the accuracy of GD beyond current clinical predictors by a modest amount.2,3. With the recently aquired Olink Explore398-Cardiovascular and Target96-Cardiovascular-II system proteomics in BiB, and funds for aquiring the Olink Explore 5300 system proteomics we are now in a strong position to determine the extent to which combining genome-wide (GW), and whole genome sequence (WGS) benomic, proteomic and metabolomic data increases the accuracy of GD prediction.