Gestational diabetes mellitus (GDM) occurs when insulin production or utilization is impaired during pregnancy, resulting in hyperglycemia. It typically resolves after delivery. GDM is a prevalent condition, affecting 14.0% of live births worldwide in 2021 [1]. Unmanaged GDM can lead to adverse perinatal outcomes [2] and increased long-term metabolic risks for both mothers and children. A recent meta-analysis assessing over 1.3 million individuals reported that women with GDM have a nearly 10-fold increased risk of developing type 2 diabetes mellitus (T2DM) compared with healthy controls [3]. Moreover, offspring exposed to hyperglycemia in utero are more likely to be obese and insulin resistant in childhood and early adulthood than offspring of mothers with normoglycemia [4-6]. These observations indicate that (1) GDM shares a common pathology with T2DM; and (2) GDM can provide insights into the predisposition of T2DM, with pregnancy serving as a stressor that unmask hyperglycemia during pregnancy among those who are at risk of future diabetes because of impaired β-cell function.

Given the increased lifetime risk of T2DM associated with GDM, many genetic studies have focused on the assumption that the genetic architecture of both conditions shared similarities. A number of T2DM susceptibility loci have been examined for their association with GDM in modest sample sizes [7]. In a recent meta-analysis of 23 studies, eight T2DM loci (insulin like growth factor 2 mRNA binding protein 2 [IGF2BP2], CDK5 regulatory subunit-associated protein 1-like 1 [CDKAL1], GLIS family zinc finger 3 [GLIS3], cyclin dependent kinase inhibitor 2A/2B [CDKN2A/2B], hematopoietically expressed homeobox [HHEX]/insulin degrading enzyme [IDE] transcription factor 7 like 2 [TCF7L2], melatonin receptor 1B [MTNR1B], and HNF1 homeobox A [HNF1A]) showed association with GDM after correcting for multiple comparisons [7]. Notably, these loci demonstrated a consistent direction of association with T2DM, supporting a shared genetic background between the two conditions. More recently, the GENetics of Diabetes In Pregnancy (GenDIP) Consortium conducted a multi-ancestry genomewide association studies (GWAS) meta-analysis for GDM, involving over 300K women [8]. Among the five genome-wide significant loci identified, four were previously reported to be associated with T2DM: MTNR1B, TCF7L2, CDKAL1, and CDKN2A/B. Interestingly, the novel locus at hexokinase domain containing 1 (HKDC1) did not show a strong association with T2DM, highlighting the presence of genetic determinants specific to glucose regulation in pregnancy. The FinnGen Study further explored genetic features distinct from T2DM and identified eight loci with effects on GDM that were three times stronger compared to T2DM [9].

There is growing interest in utilizing a polygenic risk score (PRS) to assess the individual’s risks of developing GDM and T2DM postpartum. Prior efforts to construct PRSs for GDM typically involved variants associated with T2DM, and suffered from a small number of variants and participants. As a result, these scores had limited success in enhancing predictive capability compared to models that included only clinical variables [10]. For instance, in a study of Caucasian women involving 458 GDM cases and 1,538 controls, a PRS consisting of 34 variants related to T2DM and/or fasting glucose was associated with increased risk of GDM. However, its utility in identifying GDM cases was limited, with only a modest improvement in GDM prediction when added to clinical factors (increase in c-statistic=0.03) [11].

This study aimed to (1) identify novel GDM susceptibility loci by performing a meta-analysis of three GWASs in Chinese women, followed by replication studies in independent Chinese, European, and multi-ethnic cohorts; and (2) explore the clinical utility of the identified variants by deriving a PRS for GDM, and evaluating its predictive value for GDM and abnormal glucose tolerance (AGT) at 7-year postpartum.

This study reported a meta-analysis of three GWASs for GDM in Chinese women, with subsequent replication studies in Chinese and multi-ethnic populations. We identified four susceptibility loci at TBR1-SLC4A10, MTNR1B, CDKAL1, and INSIGF2-KCNQ1, using both genome-wide scan and candidate gene approaches. Moreover, the PRS derived from these loci showed improved risk stratification for Chinese women who are at risk of developing GDM or AGT postpartum.

Three out of the four GDM-associated loci identified in this study have also been implicated in glycemic traits and the development of T2DM in non-gravid populations. Aligning with previous GWASs in Korean [18], Finnish [9], and multi-ethnic populations [8], as well as candidate gene studies across different populations [21,22], our findings further support the associations of CDKAL1, MTNR1B, and KCNQ1 loci with GDM risk, with comparable effect sizes estimated in Chinese pregnant women. To the best of our knowledge, this is the first study showing a genome-wide significant association between the KCNQ1 variant and GDM risk. These three genes have been found to impact insulin secretion and glucose homeostasis, contributing to the development of diabetes [23-25]. Although the role of CDKAL1 in pancreatic β-cell function remains incompletely understood, it is known to be expressed in human adult pancreatic islets [26]. In mice, CDKAL1 gene deletion has been observed to cause a modest impairment in insulin secretion during high-fat feeding [27]. Moreover, emerging evidence indicates that functional loss of CDKAL1 affects the accuracy of protein translation, resulting in abnormal insulin synthesis and subsequently triggering endoplasmic reticulum stress in β-cells [28]. These findings provide evidence linking the molecular function of CDKAL1 with GDM. MTNR1B plays a crucial role in regulating circadian rhythm. Disruptions in circadian rhythms have been observed to promote systemic metabolic dysfunction, including obesity or diabetes, in both humans and rodents [29]. Consequently, altered MTNR1B function may influence circadian rhythm regulation, potentially affecting glucose metabolism during pregnancy. The KCNQ1 gene encodes for a voltage-gated potassium channel (Kv7.1) that is expressed in multiple organs/tissues, including pancreas [30]. In the pancreas, this channel drives an electrical signal in the β-cells that facilitates glucose-stimulated insulin secretion [30]. Changes of KCNQ1 function may impact the proper functioning of pancreatic β-cells, leading to impaired insulin secretion and glucose regulation in GDM women. Overall, our findings suggest shared genetic determinants between GDM and T2DM. The lack of association observed between other known T2DM-related loci and GDM may indicate partial differences in the genetic architecture of glucose metabolism between the pregnant and non-pregnant states, and/or limited power in the current study.

While many previous studies have identified susceptibility loci associated with both GDM and T2DM, two recent large-scale GWASs involving 143K–353K participants, predominantly of European descent, have uncovered a total of nine novel loci (i.e., HKDC1, glucokinase regulator [GCKR], SPC25 component of NDC80 kinetochore complex [SPC25], adenylate cyclase 5 [ADCY5], proprotein convertase subtilisin/kexin type 1 [PCSK1], estrogen receptor 1 [ESR1], cyclin D2 [CCND2], NEDD1 gamma-tubulin ring complex targeting factor [NEDD1], c-Maf inducing protein [CMIP], and mitogen-activated protein kinase kinase kinase 15 [MAP3K15]) specifically linked to glucose regulation during pregnancy [8,9]. These findings motivate further investigation into the distinct genetic mechanisms underlying GDM compared to T2DM, particularly within non-European populations. In this study, we have discovered a novel common variant rs117781972 located between the TBR1 and SLC4A10 gene regions in Chinese population. This variant has not been reported in GWASs for T2DM or glycemic traits. We found that the GDM-associated risk allele of rs117781972 was also associated with higher postprandial glucose levels (i.e., 1-hour glucose and 2-hour glucose) during pregnancy. Interestingly, inconsistent associations have been observed among replication studies, which may be due to differences in genetic background. For instance, the allele frequency of rs117781972 is significantly higher in East Asian populations (minor allele frequency [MAF]=0.227) compared to European (MAF=0.002 to 0.014), South Asian (MAF=0.01), and African (MAF=0.003) populations (https://gnomad.broadinstitute.org/). This genetic heterogeneity can be further modified by differences in phenotypes, lifestyles, and treatments. Our study, along with other research, suggests that while metabolic changes during pregnancy may resemble those observed in the progression of T2DM, and despite the shared genetic risk factors between T2DM and GDM, the underlying mechanisms driving the development of hyperglycemia during pregnancy may have some important differences.

The product of TBR1 is vital for the development and functioning of brain regions, including cerebral cortex, hippocampus, and amygdala [31,32]. SLC4A10, a member of the sodium-coupled bicarbonate transporters (NCBTs) family, regulates neuronal pH and excitability, and the secretion of cerebrospinal fluid [33]. Both genes are primarily expressed in the brain (data source: GTEx Analysis Release V8). TBR1 protein and multiple variants at SLC4A10 (rs4500960, rs7604885, and rs7580486) have demonstrated associations with major neurological disorders such as autism spectrum disorder (ASD) [32], cognitive ability [34], schizophrenia [35], and intelligence [36]. In line with the observational data linking exposure to maternal diabetes in utero with ASD risk [37], the effects of TRB1-SLC4A10 locus on GDM may also influence the fetal brain development, potentially leading to ASD after birth. However, little is known about the GDM-associated locus at these genes. A few recent GWASs have linked common variants at the TBR1-SLC4A10 locus (rs55732192, rs62189012, rs2053865, rs77882688, and rs1449631) to cardiometabolic traits, including BMI, mean arterial pressure, and systolic blood pressure [38-41]. Our identified variant rs117781972, strongly associated with GDM, appears to be independent of these reported variants (r²<0.1 in East Asian population). Furthermore, our data did not show any association between rs117781972 and blood pressure or BMI during pregnancy (Supplementary Table 13). To pinpoint the relevant gene and functional variant(s), further fine-mapping in larger multi-ancestry cohorts may be required.

Similar to T2DM, the risk of GDM may arise from variants in multiple loci, each conferring modest individual effects. Therefore, we computed a PRS using variants identified in this study to evaluate their cumulative impact on predicting an individual’s risk of developing hyperglycemia during and after pregnancy. Previous studies in Caucasian, Chinese and Indian populations have examined the association between PRS and GDM risk, using PRSs involving six to 14,971,357 variants [11,42-45]. However, there is limited data available for evaluating the performance of PRS in risk prediction [11,42,46]. Most of these studies derived PRSs using common variants associated with T2DM or glycemic traits, and tested associations in small sample sizes (n=296 to 8,722) [10]. Consistent with previous observations [11,42,46], our PRS, consisting of four variants, showed a significant association with GDM in Chinese and Hispanic populations. Our analysis further demonstrated that this PRS modestly contributed to GDM prediction when combined with well-recognized risk factors, although its overall value in identifying GDM cases at the population level was limited. It is worth noting that this PRS effectively stratified the risk of GDM in Chinese women, independent of clinical risk factors such as age and BMI. We found that women with a high PRS (top 20% of the distribution) had over a three-fold increased GDM risk compared to their counterparts with a lower PRS (remaining 80% of the distribution). More importantly, our PRS improved risk prediction for post-pregnancy hyperglycemia, showing a 71% higher risk among women with a high PRS compared to those with a lower PRS. This relationship was attenuated when adjusting for GDM history, further supporting the causal link between GDM and future T2DM progression. Overall, our findings underscore the importance of the polygenic contributions to GDM, and demonstrated the potential utility of genetic information in clinical practice, such as early genomic screening and personalized risk assessment for pregnant women.

This study has several limitations. First, the sample size for our genome-wide scan analysis was relatively modest, limiting our ability to discover new loci and detect variants with small genetic effects. Additionally, the HAPO Study have excluded women with severe GDM, further reducing the study’s power. Nevertheless, we were able to identify a novel locus associated with GDM within our cohorts. Second, our discovery study was exclusively conducted among Han Chinese women only, with limited generalizability. Third, the glucose tolerance status of controls in the TGDM-NDM Study was not assessed during pregnancy, potentially leading to the inclusion of some women with GDM as controls. Fourth, the predictive value of our PRS may be significantly diminished due to the inclusion of only a small number of genetic variants. Fifth, there is a possibility of over-fitting when evaluating the PRS in the discovery cohort used in the GWAS; however, it has been validated in independent cohorts. Furthermore, the impact of genetic variants may vary between GDM and AGT, and certain loci may be unique to each disease. We anticipate that constructing our PRS using weights from larger GWASs will enhance its predictive accuracy.

In summary, this study identified associations of four genetic loci with GDM among Chinese women. The MTNR1B, CDKAL1, and KCNQ1 loci, known for their role in hyperglycemia in non-pregnant populations, also have a significant impact during pregnancy, suggesting shared underlying pathology between T2DM and GDM. The TBR1-SLC4A10 locus, on the other hand, showed no association with hyperglycemia in non-pregnant populations, highlighting its specific importance in glucose metabolism during pregnancy. Finally, incorporating GDM-related PRS with clinical risk factors enhanced the prediction of GDM and post-pregnancy AGT. This demonstrates the clinical potential of integrating genetic information into risk assessment tools for identifying pregnant women at risk of developing these diseases, thereby providing opportunities to delaying disease onset.