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Gestational diabetes mellitus (GDM) is a common condition that affects approximately one out of every six pregnancies. It is defined by elevated levels of blood glucose during pregnancy, usually detected through a glucose challenge test conducted at approximately 24-28 weeks of gestation. Gestational diabetes, by nature of the elevated glucose levels during pregnancy, is known to be linked to an increased risk of some conditions in the mother. Furthermore, the elevated glucose, if not well controlled, can be linked to a higher birth weight in the baby, as well as other effects. Although it is known that women with gestational diabetes have higher risks of diabetes later in life, exactly why gestational diabetes increases the risk of diabetes is not entirely known. It is known that some of the genetic factors that are linked to gestational diabetes are also linked to diabetes risk. Furthermore, how elevated glucose during pregnancy may affect later generations is not entirely clear.
This is a research study that aims to improve the postnatal follow-up of women with gestational diabetes. Currently, there are no standard recommendations on how women with gestational diabetes should be followed up after they have given birth. Furthermore, despite being at increased risk of other metabolic problems including high blood pressure, abnormal lipids, and obesity, these are not routinely being monitored after gestational diabetes.
The study aims to enroll women with gestational diabetes into a multi-center registry, where they will be provided with information about the long-term risks of metabolic diseases and be reminded to undergo regular assessments to monitor their health status, including assessment of glucose status, monitoring of blood pressure, as well as other parameters. Regular assessments will be provided for the initial 3 years. A subgroup of participants will also be invited to participate in a separate study of a lifestyle intervention program to reduce their risk of developing diabetes. It is hoped that results from this study will help guide the development of care programs to better monitor the health of women after pregnancies complicated by gestational diabetes, which will help improve the overall health of the population. In addition, the study aims to identify clinical factors, genetic and other biological biomarkers, as well as algorithms to predict different clinical outcomes and categorize participants into different subtypes of gestational diabetes, in order to optimize future treatments according to the characteristics of each individual.
Full description
Women with gestational diabetes are known to be at increased risk of type 2 diabetes, cardiovascular disease, renal dysfunction, metabolic-associated fatty liver disease (MAFLD), and other adverse outcomes. Furthermore, offspring of mothers with pre-existing diabetes or gestational DM (GDM) have an increased risk of obesity in childhood and may have an increased risk of metabolic disease tracking into adulthood. Whilst there has been much debate about the diagnostic criteria of gestational diabetes, results from the Hyperglycaemia and Adverse Pregnancy Outcome (HAPO) Study have provided important insights into the effects of maternal hyperglycemia and its links with pregnancy complications. The results from the HAPO study guided the development of diagnostic criteria proposed by the International Association of the Diabetes and Pregnancy Study Groups (IADPSG), and these were subsequently adopted by the World Health Organization (WHO), the International Diabetes Federation (IDF), and the International Federation of Gynecology and Obstetrics (FIGO). This diagnostic criterion, adopted by the WHO, is the most widely accepted, though there is also recent discussion about the value of moving the diagnostic timeline earlier to detect "early GDM." In HAPO, higher levels of maternal glucose were independently associated with an increased frequency of birthweight, cord serum C-peptide, and infant adiposity (infant body fat or sum of skinfolds) above the 90th percentile. In previous studies in offspring of mothers with pre-existing diabetes, these neonatal outcomes have been identified as risk factors for obesity and metabolic disorders in childhood and later life. The implications of a diagnosis of GDM according to the WHO 2013 criteria have been examined in the multi-center HAPO Follow-Up Study, which provided a unique opportunity to examine the association of GDM with obesity and metabolic disorders in childhood, unconfounded by treatment of GDM. The results of the HAPO Follow-up Study highlighted a persistent association between maternal glucose levels during pregnancy with glycemia and adiposity in offspring up to adolescence. Furthermore, the HAPO Follow-up Study highlighted that mothers with GDM, diagnosed according to the IADPSG/WHO criteria, have an approximately 7-fold higher risk of diabetes at the follow-up visit, approximately 10-14 years after the index pregnancy.
Although GDM is considered one entity, there is increasing interest in the heterogeneity of gestational diabetes, whereby further sub-phenotyping according to insulin sensitivity and beta-cell function, or according to underlying genetic profile, might identify subgroups with differential risk. This has been highlighted by work that showed that GDM cases with less insulin resistance appear to have lower rates of pregnancy complications compared to the other subtypes. There is also emerging interest in using pathophysiological traits such as maternal glucose, insulin sensitivity, and beta-cell function in predicting short-term pregnancy outcomes, suggesting this might be superior for predicting pregnancy outcomes compared to the categorical variable of the presence vs. absence of a diagnosis of GDM. These studies highlight the need to incorporate a more detailed phenotype to fully appreciate the impact of GDM on an individual level for precision medicine.
Genetic factors also play an important role in influencing an individual's phenotype and long-term outcome. Using recent advances in the understanding of the genetics of type 2 diabetes, which has significant overlap with the genetics of GDM, it has been possible to generate polygenic risk scores that capture the contribution from different pathophysiological pathways and demonstrate the additive effect on reducing the age of onset of diabetes. Recent analysis among women with or without GDM highlights that using these pathway-specific polygenic risk scores can identify the contribution of maternal genetics towards increased birthweight or adiposity in the offspring, again highlighting the utility of using genetics or other biomarkers to unravel the heterogeneity in GDM.
In addition, gestational diabetes due to glucokinase mutation has significant implications for management, depending on fetal genotype. This highlights the importance of identifying mothers diagnosed with GDM who in fact have monogenic diabetes due to glucokinase mutation.
Despite the well-known increased risk of diabetes, cardiovascular disease, and other co-morbidities among women with gestational diabetes, a significant proportion of mothers with GDM worldwide default on postnatal evaluation with an oral glucose tolerance test. Furthermore, there are no structured follow-ups for this high-risk population. Establishing a strategy for structured follow-up of this high-risk population of women may help to reduce the long-term burden of diabetes and related co-morbidities. Indeed, in the Lancet Report on Diabetes, focusing diabetes prevention efforts on high-risk populations such as women with gestational diabetes is considered a strategy for addressing the "low-hanging fruits." The Hong Kong Gestational Diabetes Register (HKGDR) Study will aim to establish a unique resource, through assembling a large cohort of women who have been diagnosed with GDM, together with their offspring, to address these questions. Furthermore, the register and its follow-up data on maternal and offspring outcomes will provide a unique opportunity to address the heterogeneity of GDM in the local population to identify sub-phenotypes to guide the understanding of the prognosis of different GDM subtypes. The aim is to utilize this resource to identify biomarkers in the early postpartum period that can predict progression towards abnormal glucose tolerance after GDM. Finally, the HKGDR will help identify a pool of women with GDM who may be suitable for enrollment into a randomized controlled trial of a postnatal intervention program to reduce progression towards glucose intolerance and diabetes post-GDM.
The hypotheses to be tested in the Hong Kong Gestational Diabetes Register are as follows:
Through establishing a GDM register, the attendance rates of postnatal OGTT can be improved.
Hyperglycemia in pregnancy (HIP), as defined by GDM according to the IADPSG/WHO criteria, is associated with a significant risk of glucose abnormalities and cardiometabolic traits in the mother.
Women with GDM may be suitable for recruitment into a randomized controlled trial for postnatal lifestyle intervention.
There is significant heterogeneity in GDM pathophysiology, with differential effects on pregnancy outcomes and short-term metabolic outcomes.
Biomarkers, including those measured at the first postnatal visit, can help predict subsequent maternal progression to abnormal glucose tolerance during follow-up.
The General Aim is to establish a cohort and register of 2,000 local women who have been diagnosed with GDM. All women recruited will undergo assessment with an oral glucose tolerance test 6-12 weeks post-delivery as per current recommendations and undergo the collection of basic medical and dietary information, assessment of anthropometric measurements, adiposity measures, as well as blood pressure, and biochemical investigations to evaluate lipid levels, insulin sensitivity, and secretion. Additional phenotyping will be done through genome-wide genotyping or sequencing to examine genetic predisposition to type 2 diabetes and underlying pathophysiological pathways using polygenic risk scores or partitioned polygenic risk scores. Additional biospecimens will be saved for future biomarker work for identifying biomarkers to predict future risk of dysglycemia and cardiovascular risk. In addition, the mother-offspring pairs will be invited to participate in follow-up for assessment of cardiometabolic risk and risk of other non-communicable diseases (NCDs) in the mother and offspring.
The primary aims and hypotheses of the Hong Kong Gestational Diabetes Register are as follows:
Primary Aim 1: To establish a multi-center register of women with gestational diabetes to improve engagement towards postnatal glycemic assessment.
Hypothesis 1: Through establishing a GDM register, the attendance rates of postnatal OGTT can be improved compared to routine care.
Primary Aim 2: To recruit women with a history of GDM for invitation to participate in a randomized controlled trial for a postnatal lifestyle intervention program to reduce progression towards glucose intolerance and diabetes.
Hypothesis 2: The GDM register can identify women with GDM who can be engaged in lifestyle intervention to reduce the risk of progression towards diabetes.
Secondary Aim 1: To examine the relationship between Gestational Diabetes Mellitus (GDM) and glucose, lipids, and blood pressure in the mother during follow-up.
Hypothesis 1: Hyperglycemia in pregnancy (HIP), as defined by GDM according to the IADPSG/WHO criteria, is associated with a significant risk of abnormalities in glycemia and cardiometabolic traits in the mother during follow-up.
Secondary Aim 2: To investigate the relationship between GDM subtypes and pregnancy outcomes and metabolic outcomes.
Secondary Hypothesis 2: There is significant heterogeneity in GDM pathophysiology, with differential effects on pregnancy outcomes and short-term metabolic outcomes.
Secondary Aim 3: To identify biomarkers for predicting the progression to abnormal glucose tolerance during follow-up.
Secondary Hypothesis 3: Clinical +/- genetic biomarkers postpartum can help stratify women at increased risk of glucose intolerance post-pregnancy.
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Data sourced from clinicaltrials.gov
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