Refining the diagnosis of Gestational Diabetes Mellitus: A systematic review to inform efforts in precision medicine

BackgroundAmong people with gestational diabetes mellitus (GDM), there is inter-individual variability in clinical outcomes that appears to be related to factors beyond glycemia. However, the precise factors (information on the unique pathophysiology within a person, environment, and/or context) that may help refine the diagnosis of GDM remain unclear. To determine if a precision medicine approach could refine the diagnosis of GDM, we conducted a systematic review of a variety of potential precision markers analyzed in studies among individuals with GDM. MethodsSystematic literature searches were performed in PubMed (https://pubmed.ncbi.nlm.nih.gov/) and EMBASE (https://www.embase.com) databases from inception to March 2022 for observational studies and controlled trials. Studies were included if they reported data on, and compared outcomes between, individuals with GDM. The following categories of precision markers were included in the current search: non-glycemic biochemical markers (cholesterol, insulin profiles); genetics/genomics or other -omics (proteomics, lipidomics, metabolomics, metagenomics); maternal/fetal anthropometric (eg., maternal BMI, gestational weight gain, fetal biometry ultra-sound measures); clinical risk factors (medical/familial history, prior delivery complicated by macrosomia or a large for gestational age [LGA] neonate); sociocultural or environmental modifiers (diet, smoking, race/ethnicity, socioeconomic status). ResultsWe focused on synthesizing the literature on genetics, -omics, non-glycemic biomarkers, maternal anthropometry/fetal biometry, and clinical/sociocultural risk factors. A total of 5,905 titles and abstracts were screened, 775 underwent full-text review, and 137 studies that included a total of 432,156 GDM cases were synthesized. Of the studies on non-glycemic biomarkers (n=33), lipids and insulin sensitivity/secretion indices were the two most common precision markers, with elevated maternal triglycerides and insulin resistance generally associated with greater risk of LGA and macrosomia. Studies of genetics or other -omics were scarce (n=5); however, differences in genetic variants in adiponectin or adiponutrient genes and non-coding RNAs accounted for variability in perinatal outcomes. The majority of studies (n=77) evaluated maternal anthropometry or fetal biometry as a precision marker, and these studies demonstrate that individuals with adiposity who develop GDM are at a substantially higher risk of LGA or macrosomia than those with GDM and lower adiposity. There were 49 studies evaluating GDM risk factors or sociocultural markers, with only six studies examining multiple risk factors as a composite marker. There were inconsistent findings that GDM risk factors, such as older maternal age, accounted for variation in adverse outcomes. ConclusionsOur review demonstrates that a major gap exists in studies examining non-glycemic biochemical, genetic, or other omic precision markers among individuals with GDM. Given that people meeting current diagnostic criteria for GDM may have different risk profiles, our review identifies several factors (including obesity, insulin resistance, hypertriglyceridemia) that may be useful in risk stratification of GDM, setting the stage for a precision approach to its diagnosis.