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Gestational diabetes mellitus (GDM) is a common complication of pregnancy, which has significant adverse effects on both the mother and fetus. The incidence of GDM is increasing globally, and early diagnosis is critical for timely treatment and reducing the risk of poor pregnancy outcomes. GDM is usually diagnosed and detected after 24 weeks of gestation, while complications due to GDM can occur much earlier. Copy number variations (CNVs) can be a possible biomarker for GDM diagnosis and screening in the early gestation stage. In this study, we proposed a machine-learning method to screen GDM in the early stage of gestation using cell-free DNA (cfDNA) sequencing data from maternal plasma. Five thousand and eighty-five patients from north regions of Mainland China, including 1942 GDM, were recruited. A non-overlapping sliding window method was applied for CNV coverage screening on low-coverage (~0.2×) sequencing data. The CNV coverage was fed to a convolutional neural network with attention architecture for the binary classification. The model achieved a classification accuracy of 88.14%, precision of 84.07%, recall of 93.04%, F1-score of 88.33% and AUC of 96.49%. The model identified 2190 genes associated with GDM, including DEFA1, DEFA3 and DEFB1. The enriched gene ontology (GO) terms and KEGG pathways showed that many identified genes are associated with diabetes-related pathways. Our study demonstrates the feasibility of using cfDNA sequencing data and machine-learning methods for early diagnosis of GDM, which may aid in early intervention and prevention of adverse pregnancy outcomes.
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Ácidos Nucleicos Libres de Células , Aprendizaje Profundo , Diabetes Gestacional , beta-Defensinas , Femenino , Embarazo , Humanos , Diabetes Gestacional/diagnóstico , Diabetes Gestacional/genética , Variaciones en el Número de Copia de ADN , Resultado del Embarazo , Ácidos Nucleicos Libres de Células/genéticaRESUMEN
BACKGROUND AND AIMS: Persons with rheumatoid arthritis (RA) have an increased risk of obstetric-associated complications, as well as long-term cardiovascular (CV) risk. Hence, the aim was to evaluate the association of RA with acute CV complications during delivery admissions. METHODS: Data from the National Inpatient Sample (2004-2019) were queried utilizing ICD-9 or ICD-10 codes to identify delivery hospitalizations and a diagnosis of RA. RESULTS: A total of 12 789 722 delivery hospitalizations were identified, of which 0.1% were among persons with RA (n = 11 979). Individuals with RA, vs. those without, were older (median 31 vs. 28 years, P < .01) and had a higher prevalence of chronic hypertension, chronic diabetes, gestational diabetes mellitus, obesity, and dyslipidaemia (P < .01). After adjustment for age, race/ethnicity, comorbidities, insurance, and income, RA remained an independent risk factor for peripartum CV complications including preeclampsia [adjusted odds ratio (aOR) 1.37 (95% confidence interval 1.27-1.47)], peripartum cardiomyopathy [aOR 2.10 (1.11-3.99)], and arrhythmias [aOR 2.00 (1.68-2.38)] compared with no RA. Likewise, the risk of acute kidney injury and venous thromboembolism was higher with RA. An overall increasing trend of obesity, gestational diabetes mellitus, and acute CV complications was also observed among individuals with RA from 2004-2019. For resource utilization, length of stay and cost of hospitalization were higher for deliveries among persons with RA. CONCLUSIONS: Pregnant persons with RA had higher risk of preeclampsia, peripartum cardiomyopathy, arrhythmias, acute kidney injury, and venous thromboembolism during delivery hospitalizations. Furthermore, cardiometabolic risk factors among pregnant individuals with RA rose over this 15-year period.
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Artritis Reumatoide , Humanos , Femenino , Embarazo , Estados Unidos/epidemiología , Adulto , Artritis Reumatoide/epidemiología , Artritis Reumatoide/complicaciones , Hospitalización/estadística & datos numéricos , Complicaciones Cardiovasculares del Embarazo/epidemiología , Enfermedades Cardiovasculares/epidemiología , Factores de Riesgo , Parto Obstétrico/efectos adversos , Parto Obstétrico/estadística & datos numéricos , Complicaciones del Embarazo/epidemiologíaRESUMEN
Gestational diabetes mellitus (GDM) with intrauterine hyperglycemia induces a series of changes in the placenta, which have adverse effects on both the mother and the fetus. The aim of this study was to investigate the changes in the placenta in GDM and its gender differences. In this study, we established an intrauterine hyperglycemia model using ICR mice. We collected placental specimens from mice before birth for histological observation, along with tandem mass tag (TMT)-labeled proteomic analysis, which was stratified by sex. When the analysis was not segregated by sex, the GDM group showed 208 upregulated and 225 downregulated proteins in the placenta, primarily within the extracellular matrix and mitochondria. Altered biological processes included cholesterol metabolism and oxidative stress responses. After stratification by sex, the male subgroup showed a heightened tendency for immune-related pathway alterations, whereas the female subgroup manifested changes in branched-chain amino acid metabolism. Our study suggests that the observed sex differences in placental protein expression may explain the differential impact of GDM on offspring.
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Diabetes Gestacional , Hiperglucemia , Humanos , Embarazo , Femenino , Masculino , Ratones , Animales , Placenta/metabolismo , Proteómica , Ratones Endogámicos ICR , Diabetes Gestacional/genética , Diabetes Gestacional/metabolismo , Hiperglucemia/genéticaRESUMEN
Lactylation is a novel post-translational modification of proteins. Although the histone lactylation modification has been reported to be involved in glucose metabolism, its role and molecular pathways in gestational diabetes mellitus (GDM) are still unclear. This study aims to elucidate the histone lactylation modification landscapes of GDM patients and explore lactylation-modification-related genes involved in GDM. We employed a combination of RNA-seq analysis and chromatin immunoprecipitation sequencing (ChIP-seq) analysis to identify upregulated differentially expressed genes (DEGs) with hyperhistone lactylation modification in GDM. We demonstrated that the levels of lactate and histone lactylation were significantly elevated in GDM patients. DEGs were involved in diabetes-related pathways, such as the PI3K-Akt signaling pathway, Jak-STAT signaling pathway, and mTOR signaling pathway. ChIP-seq analysis indicated that histone lactylation modification in the promoter regions of the GDM group was significantly changed. By integrating the results of RNA-seq and ChIP-seq analysis, we found that CACNA2D1 is a key gene for histone lactylation modification and is involved in the progression of GDM by promoting cell vitality and proliferation. In conclusion, we identified the key gene CACNA2D1, which upregulated and exhibited hypermodification of histone lactylation in GDM. These findings establish a theoretical groundwork for the targeted therapy of GDM.
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Secuenciación de Inmunoprecipitación de Cromatina , Diabetes Gestacional , Histonas , Procesamiento Proteico-Postraduccional , Diabetes Gestacional/genética , Diabetes Gestacional/metabolismo , Humanos , Femenino , Embarazo , Histonas/metabolismo , Histonas/genética , Transducción de Señal/genética , RNA-Seq , AdultoRESUMEN
AIMS/HYPOTHESIS: Pregnant women are advised to consume a minimum of 175 g per day of carbohydrate to meet maternal and fetal brain glucose requirements. This recommendation comes from a theoretical calculation of carbohydrate requirements in pregnancy, rather than from clinical data. This study aimed to determine whether fasting maternal ketone levels are associated with habitual carbohydrate intake in a subset of participants of the Study of PRobiotics IN Gestational diabetes (SPRING) randomised controlled trial. METHODS: Food frequency questionnaires on dietary intake during pregnancy were completed by pregnant women with overweight or obesity at 28 weeks' gestation (considering their intake from the beginning of pregnancy). Dietary intake from early pregnancy through to 28 weeks was analysed for macronutrient intake. At the same time, overnight fasting serum samples were obtained and analysed for metabolic parameters including serum ß-hydroxybutyrate, OGTTs, insulin and C-peptide. RESULTS: Fasting serum ß-hydroxybutyrate levels amongst 108 women (mean BMI 34.7 ± 6.3 kg/m2) ranged from 22.2 to 296.5 µmol/l. Median fasting ß-hydroxybutyrate levels were not different between women with high (median [IQR] 68.4 [49.1-109.2 µmol/l]) and low (65.4 [43.6-138.0 µmol/l]) carbohydrate intake in pregnancy. Fasting ß-hydroxybutyrate levels were not correlated with habitual carbohydrate intake (median 155 [126-189] g/day). The only metabolic parameter with which fasting ß-hydroxybutyrate levels were correlated was 1 h venous plasma glucose (ρ=0.23, p=0.03) during a 75 g OGTT. CONCLUSIONS/INTERPRETATION: Fasting serum ß-hydroxybutyrate levels are not associated with habitual carbohydrate intake at 28 weeks' gestation in pregnant women with overweight and obesity.
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Diabetes Gestacional , Sobrepeso , Embarazo , Femenino , Humanos , Ácido 3-Hidroxibutírico , Mujeres Embarazadas , Obesidad , Glucosa , Carbohidratos , Glucemia/metabolismoRESUMEN
AIMS/HYPOTHESIS: We aimed to assess maternal-fetal outcomes according to various subtypes of hyperglycaemia in pregnancy. METHODS: We used data from the French National Health Data System (Système National des Données de Santé), which links individual data from the hospital discharge database and the French National Health Insurance information system. We included all deliveries after 22 gestational weeks (GW) in women without pre-existing diabetes recorded in 2018. Women with hyperglycaemia were classified as having overt diabetes in pregnancy or gestational diabetes mellitus (GDM), then categorised into three subgroups according to their gestational age at the time of GDM diagnosis: before 22 GW (GDM<22); between 22 and 30 GW (GDM22-30); and after 30 GW (GDM>30). Adjusted prevalence ratios (95% CI) for the outcomes were estimated after adjusting for maternal age, gestational age and socioeconomic status. Due to the multiple tests, we considered an association to be statistically significant according to the Holm-Bonferroni procedure. To take into account the potential immortal time bias, we performed analyses on deliveries at ≥31 GW and deliveries at ≥37 GW. RESULTS: The study population of 695,912 women who gave birth in 2018 included 84,705 women (12.2%) with hyperglycaemia in pregnancy: overt diabetes in pregnancy, 0.4%; GDM<22, 36.8%; GDM22-30, 52.4%; and GDM>30, 10.4%. The following outcomes were statistically significant after Holm-Bonferroni adjustment for deliveries at ≥31 GW using GDM22-30 as the reference. Caesarean sections (1.54 [1.39, 1.72]), large-for-gestational-age (LGA) infants (2.00 [1.72, 2.32]), Erb's palsy or clavicle fracture (6.38 [2.42, 16.8]), preterm birth (1.84 [1.41, 2.40]) and neonatal hypoglycaemia (1.98 [1.39, 2.83]) were more frequent in women with overt diabetes. Similarly, LGA infants (1.10 [1.06, 1.14]) and Erb's palsy or clavicle fracture (1.55 [1.22, 1.99]) were more frequent in GDM<22. LGA infants (1.44 [1.37, 1.52]) were more frequent in GDM>30. Finally, women without hyperglycaemia in pregnancy were less likely to have preeclampsia or eclampsia (0.74 [0.69, 0.79]), Caesarean section (0.80 [0.79, 0.82]), pregnancy and postpartum haemorrhage (0.93 [0.89, 0.96]), LGA neonate (0.67 [0.65, 0.69]), premature neonate (0.80 [0.77, 0.83]) and neonate with neonatal hypoglycaemia (0.73 [0.66, 0.82]). Overall, the results were similar for deliveries at ≥37 GW. Although the estimation of the adjusted prevalence ratio of perinatal death was five times higher (5.06 [1.87, 13.7]) for women with overt diabetes, this result was non-significant after Holm-Bonferroni adjustment. CONCLUSIONS/INTERPRETATION: Compared with GDM22-30, overt diabetes, GDM<22 and, to a lesser extent, GDM>30 were associated with poorer maternal-fetal outcomes.
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Neuropatías del Plexo Braquial , Diabetes Gestacional , Hiperglucemia , Hipoglucemia , Nacimiento Prematuro , Embarazo , Recién Nacido , Humanos , Femenino , Estudios Transversales , Hiperglucemia/diagnóstico , Hiperglucemia/epidemiología , Cesárea , Nacimiento Prematuro/epidemiología , Diabetes Gestacional/diagnóstico , Diabetes Gestacional/epidemiología , Peso al Nacer , Resultado del EmbarazoRESUMEN
AIMS/HYPOTHESIS: Gestational diabetes mellitus (GDM) is a heterogeneous condition. Given such variability among patients, the ability to recognise distinct GDM subgroups using routine clinical variables may guide more personalised treatments. Our main aim was to identify distinct GDM subtypes through cluster analysis using routine clinical variables, and analyse treatment needs and pregnancy outcomes across these subgroups. METHODS: In this cohort study, we analysed datasets from a total of 2682 women with GDM treated at two central European hospitals (1865 participants from Charité University Hospital in Berlin and 817 participants from the Medical University of Vienna), collected between 2015 and 2022. We evaluated various clustering models, including k-means, k-medoids and agglomerative hierarchical clustering. Internal validation techniques were used to guide best model selection, while external validation on independent test sets was used to assess model generalisability. Clinical outcomes such as specific treatment needs and maternal and fetal complications were analysed across the identified clusters. RESULTS: Our optimal model identified three clusters from routinely available variables, i.e. maternal age, pre-pregnancy BMI (BMIPG) and glucose levels at fasting and 60 and 120 min after the diagnostic OGTT (OGTT0, OGTT60 and OGTT120, respectively). Cluster 1 was characterised by the highest OGTT values and obesity prevalence. Cluster 2 displayed intermediate BMIPG and elevated OGTT0, while cluster 3 consisted mainly of participants with normal BMIPG and high values for OGTT60 and OGTT120. Treatment modalities and clinical outcomes varied among clusters. In particular, cluster 1 participants showed a much higher need for glucose-lowering medications (39.6% of participants, compared with 12.9% and 10.0% in clusters 2 and 3, respectively, p<0.0001). Cluster 1 participants were also at higher risk of delivering large-for-gestational-age infants. Differences in the type of insulin-based treatment between cluster 2 and cluster 3 were observed in the external validation cohort. CONCLUSIONS/INTERPRETATION: Our findings confirm the heterogeneity of GDM. The identification of subgroups (clusters) has the potential to help clinicians define more tailored treatment approaches for improved maternal and neonatal outcomes.
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Diabetes Gestacional , Humanos , Diabetes Gestacional/epidemiología , Diabetes Gestacional/diagnóstico , Femenino , Embarazo , Adulto , Análisis por Conglomerados , Índice de Masa Corporal , Resultado del Embarazo/epidemiología , Prueba de Tolerancia a la Glucosa , Glucemia/metabolismo , Estudios de Cohortes , Edad MaternaRESUMEN
INTRODUCTION: Coronavirus disease 2019 (COVID-19) may be associated with gestational diabetes mellitus (GDM); however, evidence is limited by sample sizes and lack of control groups. METHODS: To assess the GDM risk after COVID-19 in pregnancy, we constructed a retrospective cohort of pregnancies ending March 2020-October 2022 using medical claims. People with COVID-19 diagnosis claims from conception to 21 gestational weeks (n = 57,675) were matched 1:2 to those without COVID-19 during pregnancy (n =115,350) by age-range, pregnancy start month, and encounter year-month. GDM (claim ≥23 gestational weeks) relative risk and risk difference overall, by race and ethnicity, and variant period were estimated using log-binomial models. RESULTS: GDM risk was higher among those with COVID-19 during pregnancy compared to those without (adjusted risk ratio, aRR = 1.12, 95% CI: 1.08-1.15). GDM risk was significantly associated with COVID-19 in non-Hispanic (NH) White (aRR = 1.08, 95% CI: 1.04-1.14), NH Black (aRR=1.15, 95% CI: 1.07-1.24), and Hispanic (aRR = 1.17, 95% CI: 1.10-1.24) groups. GDM risk was significantly higher during pre-Delta (aRR = 1.17, 95% CI: 1.11-1.24) as compared to Omicron (aRR = 1.07, 95% CI: 1.02-1.13) periods, but neither differed from the Delta period (aRR = 1.10, 95% CI: 1.04-1.17). The adjusted risk difference was 0-2% for all models. CONCLUSIONS: COVID-19 during pregnancy was modestly associated with GDM in claims-based data, especially during earlier SARS-CoV-2 variant periods. As these associations are based on COVID-19 in claims data, studies employing systematic testing are warranted.
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OBJECTIVE: We aimed to investigate the effects and mechanisms of the ghrelin-regulated endoplasmic reticulum stress (ERS) signalling pathway in gestational diabetes mellitus (GDM). METHODS: Pregnant female C57BL/6 mice were randomly divided into a normal group, GDM group (high-fat diet + STZ), GDM + ghrelin group (acyl ghrelin), and GDM + ghrelin + ghrelin inhibitor group ([D-lys3]-GHRP-6). We measured body weight, the intake of water and food, glucose, cholesterol, triglyceride and fasting insulin levels in each group. HE staining was used to observe the morphological changes in the pancreas. The TUNEL method was used to detect the apoptosis rate of islet cells. qPCR and Western boltting were performed to detect the relative expression levels of PERK, ATF6, IREIα, GRP78, CHOP and caspase-12, which are related to the ERS signalling pathway in the pancreas. Then, NIT-1 cells were cultured to verify whether ghrelin regulates ERS under high-glucose or tunicamycin conditions. RESULTS: Compared with the GDM group, the GDM + ghrelin group showed improved physical conditions and significantly decreased the fasting blood glucose, glucose tolerance, cholesterol, triglyceride and fasting insulin levels. Damaged islet areas were inhibited by ghrelin in the GDM group. The GDM + ghrelin group showed reduced ß-cell apoptosis compared to the GDM and GDM + ghrelin + ghrelin inhibitor groups. ERS-associated factors (PERK, ATF6, IREIα, GRP78, CHOP and caspase-12) mRNA and protein levels were obviously lower in the GDM + ghrelin group than in the GDM group, while expression levels were restored in the inhibitor group. Ghrelin treatment improved the high-glucose or tunicamycin-induced apoptosis, increased insulin levels and upregulation of GRP78, CHOP and caspase-12 in NIT-1 cells. CONCLUSION: Ghrelin suppressed ERS signalling and apoptosis in GDM mice and in NIT-1 cells. This study established a link between ghrelin and GDM, and the targeting of ERS with ghrelin represents a promising therapeutic strategy for GDM.
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Diabetes Gestacional , Estrés del Retículo Endoplásmico , Ghrelina , Animales , Femenino , Humanos , Ratones , Embarazo , Apoptosis/efectos de los fármacos , Caspasa 12 , Colesterol , Chaperón BiP del Retículo Endoplásmico , Estrés del Retículo Endoplásmico/efectos de los fármacos , Ghrelina/metabolismo , Ghrelina/farmacología , Glucosa , Insulinas , Ratones Endogámicos C57BL , Triglicéridos , Tunicamicina/farmacologíaRESUMEN
Gestational diabetes mellitus (GDM) presents a substantial population health concern. Previous studies have revealed that GDM can ultimately influence nephron endowment. In this study, we established a GDM mouse model to investigate the embryological alterations and molecular mechanisms underlying the development of congenital anomalies of the kidney and urinary tract (CAKUT) affected by GDM. Our study highlights that GDM could contribute to the manifestation of CAKUT, with prevalent phenotypes characterized by isolated hydronephrosis and duplex kidney complicated with hydronephrosis in mice. Ectopic ureteric buds (UBs) and extended length of common nephric ducts (CNDs) were noted in the metanephric development stage. The expression of Ret and downstream p-ERK activity were enhanced in UBs, which indicated the alteration of RET/MAPK/ERK pathway may be one of the mechanisms contributing to the increased occurrence of CAKUT associated with GDM.
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Diabetes Gestacional , Sistema de Señalización de MAP Quinasas , Proteínas Proto-Oncogénicas c-ret , Anomalías Urogenitales , Reflujo Vesicoureteral , Animales , Femenino , Ratones , Embarazo , Diabetes Gestacional/metabolismo , Riñón/anomalías , Riñón/metabolismo , Riñón/embriología , Proteínas Proto-Oncogénicas c-ret/metabolismo , Proteínas Proto-Oncogénicas c-ret/genética , Sistema Urinario/anomalías , Sistema Urinario/embriología , Anomalías Urogenitales/etiología , Anomalías Urogenitales/genética , Anomalías Urogenitales/patologíaRESUMEN
BACKGROUND: The increasing prevalence of gestational diabetes mellitus (GDM) is a major challenge, particularly in rural areas of China where control rates are suboptimal. This study aimed to evaluate the effectiveness of a GDM subsidy program in promoting GDM screening and management in these underserved regions. METHODS: This multicenter, randomized controlled trial (RCT) was conducted in obstetric clinics of six rural hospitals located in three provinces in China. Eligible participants were pregnant women in 24-28 weeks' gestation, without overt diabetes, with a singleton pregnancy, access to a telephone, and provided informed consent. Participants were randomly assigned in a 1:1 ratio to either the intervention or control groups using an internet-based, computer-generated randomization system. The intervention group received subsidized care for GDM, which included screening, blood glucose retesting, and lifestyle management, with financial assistance provided to health care providers. In contrast, the control group received usual care. The primary outcomes of this study were the combined maternal and neonatal complications associated with GDM, as defined by the occurrence of at least one pre-defined complication in either the mother or newborn. The secondary outcomes included the GDM screening rate, rates of glucose retesting for pregnant women diagnosed with GDM, dietary patterns, physical activity levels, gestational weight gain, and antenatal visit frequency for exploratory purposes. Primary and secondary outcomes were obtained for all participants with and without GDM. Binary outcomes were analyzed by the generalized linear model with a link of logistic, and odds ratios (OR) with 95% confidence intervals (CIs) were reported. Count outcomes were analyzed by Poisson regression, and incidence rate ratios with 95% CIs were reported. RESULTS: A total of 3294 pregnant women were randomly assigned to either the intervention group (n = 1649) or the control group (n = 1645) between 15 September 2018 and 30 September 2019. The proportion of pregnant women in the intervention group who suffered from combined maternal and/or neonatal complications was lower than in the control group with adjusted OR = 0.86 (0.80 to 0.94, P = 0.001), and a more significant difference was observed in the GDM subgroup (adjusted OR = 0.66, 95% CI 0.47 to 0.95, P = 0.025). No predefined safety or adverse events of ketosis or ketoacidosis associated with GDM management were detected in this study. Both the intervention and control groups had high GDM screening rates (intervention: 97.2% [1602/1649]; control: 94.5% [1555/1645], P < 0.001). Moreover, The intervention group showed a healthier lifestyle, with lower energy intake and more walking minutes (P values < 0.05), and more frequent blood glucose testing (1.5 vs. 0.4 visits; P = 0.001) compared to the control group. CONCLUSION: In rural China, a GDM care program that provided incentives for both pregnant women and healthcare providers resulted in improved maternal and neonatal health outcomes. Public health subsidy programs in China should consider incorporating GDM screening and management to further enhance reproductive health. TRIAL REGISTRATION: China Clinical Trials Registry ChiCTR1800017488. https://www.chictr.org.cn/.
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Diabetes Gestacional , Femenino , Humanos , Recién Nacido , Embarazo , Glucemia , China/epidemiología , Diabetes Gestacional/diagnóstico , Diabetes Gestacional/epidemiología , Diabetes Gestacional/terapia , Patrones Dietéticos , FamiliaRESUMEN
BACKGROUND: The impact of gestational diabetes mellitus (GDM) on incident dementia is unknown. Our aim was to evaluate the relationship between GDM and all-cause dementia and the mediating effects of chronic diseases on this relationship. METHODS: This prospective cohort study included women from the UK Biobank who were grouped based on GDM history. Multivariate Cox proportional hazard models were used to explore the associations between GDM and dementia. We further analysed the mediating effects of chronic diseases on this relationship and the interactions of covariates. RESULTS: A total of 1292 women with and 204,171 women without a history of GDM were included. During a median follow-up period of 45 years after first birth, 2921 women were diagnosed with dementia. Women with a GDM history had a 67% increased risk of incident dementia (hazard ratio 1.67, 95% confidence interval: 1.03-2.69) compared with those without a GDM history. According to mediation analyses, type 2 diabetes, coronary heart disease, chronic kidney disease and comorbidities (diagnosed with any two of the three diseases) explained 34.5%, 8.4%, 5.2% and 18.8% of the mediating effect on the relationship. Subgroup analyses revealed that physical activity modified the association between GDM history and dementia (p for interaction = 0.030). Among physically inactive women, GDM was significantly associated with incident dementia; however, this association was not observed among physically active women. CONCLUSIONS: A history of GDM was associated with a greater risk of incident dementia. Type 2 diabetes partially mediated this relationship. Strategies for dementia prevention might be considered for women with a history of GDM.
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Demencia , Diabetes Gestacional , Humanos , Femenino , Diabetes Gestacional/epidemiología , Demencia/epidemiología , Demencia/etiología , Embarazo , Incidencia , Estudios Prospectivos , Estudios de Seguimiento , Persona de Mediana Edad , Factores de Riesgo , Adulto , Modelos de Riesgos Proporcionales , Periodo Posparto , Diabetes Mellitus Tipo 2/epidemiología , Diabetes Mellitus Tipo 2/complicaciones , Reino Unido/epidemiologíaRESUMEN
The morbidity of gestational diabetes mellitus (GDM) is increasing and is associated with adverse perinatal outcomes and long-term maternal and infant health. The exact mechanism underlying changes in plasma free fatty acid (FFA) profiles in patients with GDM is unknown. However, it is believed that changes in diet and lipid metabolism may play a role. Fatty acids contain many specific FFAs, and the type of FFA has different impacts on physiological processes; hence, determining changes in FFAs in individual plasma is essential. Alterations in FFA concentration or profile may facilitate insulin resistance. Additionally, some FFAs show potential to predict GDM in early pregnancy and are strongly associated with the growth and development of the fetus and occurrence of macrosomia. Here, we aimed to review changes in FFAs in women with GDM and discuss the relationship of FFAs with GDM incidence and adverse outcomes.
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Diabetes Gestacional , Resistencia a la Insulina , Embarazo , Humanos , Femenino , Ácidos Grasos no Esterificados , Feto , Metabolismo de los LípidosRESUMEN
Gestational diabetes (GDM) is one of the most common complications occurring during pregnancy. Diagnosis is performed by oral glucose tolerance test, but harmonized testing methods and thresholds are still lacking worldwide. Short-term and long-term effects include obesity, type 2 diabetes, and increased risk of cardiovascular disease. The identification and validation of sensitidve, selective, and robust biomarkers for early diagnosis during the first trimester of pregnancy are required, as well as for the prediction of possible adverse outcomes after birth. Mass spectrometry (MS)-based omics technologies are nowadays the method of choice to characterize various pathologies at a molecular level. Proteomics and metabolomics of GDM were widely investigated in the last 10 years, and various proteins and metabolites were proposed as possible biomarkers. Metallomics of GDM was also reported, but studies are limited in number. The present review focuses on the description of the different analytical methods and MS-based instrumental platforms applied to GDM-related omics studies. Preparation procedures for various biological specimens are described and results are briefly summarized. Generally, only preliminary findings are reported by current studies and further efforts are required to determine definitive GDM biomarkers.
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Diabetes Mellitus Tipo 2 , Diabetes Gestacional , Embarazo , Femenino , Humanos , Diabetes Gestacional/diagnóstico , Diabetes Mellitus Tipo 2/diagnóstico , Biomarcadores , Prueba de Tolerancia a la Glucosa , Espectrometría de MasasRESUMEN
The nonenzymatic protein glycation and the subsequent formation of advanced glycation end products is a process involved in the long-term complications of diabetes. In this context the collaboration, in the last 30 years, between my research group, operating in the DPT of Medicine of Padua University, and the mass spectrometric group, operating in CNR of Padua, are described and discussed. The development of new mass spectrometric techniques has allowed investigation more indepth, starting from the applications on small molecules responsible for the browning observed in the interactions between sugars and proteins, and growing up to intact proteins as albumin, immunoglobulin, hemoglobin, and so forth, with the determination of their glycation levels as well as their glycation sites. This study has helped to clarify the role of advanced glycation end products in the pathogenesis of the chronic complications of diabetes. In particular the results obtained in diabetic nephropathy, diabetic cardiovascular disease and in placenta samples of patients affected by gestational diabetes are described in this review.
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Complicaciones de la Diabetes , Diabetes Mellitus , Médicos , Humanos , Diabetes Mellitus/metabolismo , Productos Finales de Glicación Avanzada/análisis , Espectrometría de Masas/métodosRESUMEN
Gestational diabetes mellitus (GDM) is characterized by insulin resistance and low-grade inflammation, and most studies have demonstrated gut dysbiosis in GDM pregnancies. Overall, they were manifested as a reduction in microbiome diversity and richness, depleted short chain fatty acid (SCFA)-producing genera and a dominant of Gram-negative pathogens releasing lipopolysaccharide (LPS). The SCFAs functioned as energy substance or signaling molecules to interact with host locally and beyond the gut. LPS contributed to pathophysiology of diseases through activating Toll-like receptor 4 (TLR4) and involved in inflammatory responses. The gut microbiome dysbiosis was not only closely related with GDM, it was also vital to fetal health through vertical transmission. In this review, we summarized gut microbiota signature in GDM pregnancies of each trimester, and presented a brief introduction of microbiome derived SCFAs. We then discussed mechanisms of microbiome-host interactions in the physiopathology of GDM and associated metabolic disorders. Finally, we compared offspring microbiota composition from GDM with that from normal pregnancies, and described the possible mechanism.
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Diabetes Gestacional , Disbiosis , Ácidos Grasos Volátiles , Microbioma Gastrointestinal , Diabetes Gestacional/microbiología , Diabetes Gestacional/metabolismo , Humanos , Embarazo , Femenino , Disbiosis/microbiología , Ácidos Grasos Volátiles/metabolismo , Bacterias/clasificación , Bacterias/genética , Bacterias/metabolismo , Bacterias/aislamiento & purificación , Interacciones Microbiota-Huesped , Lipopolisacáridos/metabolismoRESUMEN
OBJECTIVES: This study aims to develop and validate a prediction model for preterm birth in women with gestational diabetes mellitus (GDM). DESIGN: We conducted a retrospective study on women with GDM who gave birth at the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, between November 2017 and July 2021. We divided 1879 patients into a development set (n = 1346) and a validation set (n = 533). The development set was used to construct the prediction model for preterm birth using the stepwise logistic regression model. A nomogram and a web calculator were established based on the model. Discrimination and calibration were assessed in both sets. PATIENTS AND MEASUREMENTS: Patients were women with GDM. Data were collected from medical records. GDM was diagnosed with 75-g oral glucose tolerance test during 24-28 gestational weeks. Preterm birth was definied as gestational age at birth <37 weeks. RESULTS: The incidence of preterm birth was 9.4%. The predictive model included age, assisted reproductive technology, hypertensive disorders of pregnancy, reproductive system inflammation, intrahepatic cholestasis of pregnancy, high-density lipoprotein, homocysteine, and fasting blood glucose of 75-g oral glucose tolerance test. The area under the receiver operating characteristic curve for the development and validation sets was 0.722 and 0.632, respectively. The model has been adequately calibrated using a calibration curve and the Hosmer-Lemeshow test, demonstrating a correlation between the predicted and observed risk. CONCLUSION: This study presents a novel, validated risk model for preterm birth in pregnant women with GDM, providing an individualized risk estimation using clinical risk factors in the third trimester of pregnancy.
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Diabetes Gestacional , Nacimiento Prematuro , Humanos , Diabetes Gestacional/diagnóstico , Diabetes Gestacional/sangre , Diabetes Gestacional/epidemiología , Femenino , Embarazo , Nacimiento Prematuro/epidemiología , Adulto , Estudios Retrospectivos , China/epidemiología , Prueba de Tolerancia a la Glucosa , Factores de Riesgo , Medición de Riesgo/métodos , Modelos LogísticosRESUMEN
BACKGROUND: Gestational diabetes mellitus (GDM) significantly impacts maternal and infant health both immediately and over the long term, yet effective early diagnostic biomarkers are currently lacking. Thus, it is essential to identify early diagnostic biomarkers for GDM risk screening. Extrachromosomal circular DNA (eccDNA), being more stable than linear DNA and involved in disease pathologies, is a viable biomarker candidate for diverse conditions. In this study, eccDNA biomarkers identified for early diagnosis and assessment of GDM risk were explored. METHODS: Using Circle-seq, we identified plasma eccDNA profiles in five pregnant women who later developed GDM and five matched healthy controls at 11-13 weeks of gestation. These profiles were subsequently analyzed through bioinformatics and validated through outward PCR combined with Sanger sequencing. Furthermore, candidate eccDNA was validated by quantitative PCR (qPCR) in a larger cohort of 70 women who developed GDM and 70 normal glucose-tolerant (NGT) subjects. A ROC curve assessed the eccDNA's diagnostic potential for GDM. RESULTS: 2217 eccDNAs were differentially detected between future GDM patients and controls, with 1289 increased and 928 decreased in abundance. KEGG analysis linked eccDNA genes mainly to GDM-related pathways such as Rap1, MAPK, and PI3K-Akt, and Insulin resistance, among others. Validation confirmed a significant decrease in eccDNA PRDM16circle in the plasma of 70 women who developed GDM compared to 70 NGT women, consistent with the eccDNA-seq results. PRDM16circle showed significant diagnostic value in 11-13 weeks of gestation (AUC = 0.941, p < 0.001). CONCLUSIONS: Our study first demonstrats that eccDNAs are aberrantly produced in women who develop GDM, including PRDM16circle, which can predict GDM at an early stage of pregnancy, indicating its potential as a biomarker. TRIAL REGISTRATION: ChiCTR2300075971, http://www.chictr.org.cn . Registered 20 September 2023.
Asunto(s)
ADN Circular , Diabetes Gestacional , Edad Gestacional , Valor Predictivo de las Pruebas , Humanos , Diabetes Gestacional/diagnóstico , Diabetes Gestacional/sangre , Diabetes Gestacional/genética , Femenino , Embarazo , Adulto , Estudios de Casos y Controles , Medición de Riesgo , Factores de Riesgo , ADN Circular/sangre , ADN Circular/genética , Primer Trimestre del Embarazo/sangre , Ácidos Nucleicos Libres de Células/sangre , Ácidos Nucleicos Libres de Células/genética , Biomarcadores/sangre , Reproducibilidad de los Resultados , Diagnóstico PrecozRESUMEN
BACKGROUND: To investigate the association between gestational diabetes mellitus (GDM) without subsequent overt diabetes and long-term all-cause and cardiac mortality. METHODS: This prospective cohort study included 10,327 women (weighted population: 132,332,187) with a pregnancy history from the National Health and Nutrition Examination Survey (2007 to 2018). Participants were divided into three groups (GDM alone, overt diabetes, and no diabetes). Mortality data was linked from the National Death Index up to December 31, 2019. Multivariable Cox regression analysis was performed to examine the association between GDM alone and overt diabetes with all-cause mortality and cardiac mortality. Data analysis was performed from October 2022 to April 2023. RESULTS: Among the participants, 510 (weighted 5.3%) had GDM alone and 1862 (weighted 14.1%) had overt diabetes. Over a median follow-up period of 6.7 years (69,063 person-years), there were 758 deaths. The GDM group did not show an increased risk of all-cause mortality (hazard ratio [HR] 0.67; 95% CI, 0.25-1.84), while the overt diabetes group had a significantly higher risk (HR 1.95; 95% CI, 1.62-2.35). Similarly, the GDM group did not exhibit an elevated risk of cardiac mortality (HR 1.48; 95% CI, 0.50-4.39), whereas the overt diabetes group had a significantly higher risk (HR 2.37; 95% CI, 1.69-3.32). Furthermore, sensitivity analysis focusing on women aged 50 or above showed that the HR of GDM history for all-cause mortality was 1.14 (95% CI, 0.33-3.95) and the HR for cardiac mortality was 1.74 (95% CI, 0.49-6.20). CONCLUSIONS: GDM alone was not associated with an increased risk of all-cause and cardiac mortality, while overt diabetes was significantly associated with both types of mortality.
Asunto(s)
Diabetes Mellitus Tipo 2 , Diabetes Gestacional , Embarazo , Humanos , Femenino , Diabetes Gestacional/diagnóstico , Estudios Prospectivos , Encuestas Nutricionales , Factores de Riesgo , CorazónRESUMEN
BACKGROUND: Atherogenic index of plasma (AIP) is a non-traditional lipid parameter that can reflect the burden of atherosclerosis. A lipid profile resembling atherosclerosis emerged during pregnancy. Although lipid metabolism is pivotal in diabetes pathogenesis, there is no evidence linking AIP to gestational diabetes mellitus (GDM). Therefore, our objective was to explore the relationship between AIP and GDM and assess AIP's predictive capability for GDM. METHODS: This was a secondary analysis based on data from a prospective cohort study in Korea involving 585 single pregnant women. AIP was calculated as log10 (TG/HDL). We examined the relationship between AIP and GDM using logistic regression models, curve fitting, sensitivity analyses, and subgroup analyses. Receiver operating characteristic (ROC) analysis was also used to determine the ability of AIP to predict GDM. RESULTS: The average age of the participants was 32.06 ± 3.76 years. The AIP was 0.24 ± 0.20 on average. The GDM incidence was 6.15%. After adjustment for potentially confounding variables, AIP showed a positive linear relationship with GDM (P for non-linearity: 0.801, OR 1.58, 95% CI 1.27-1.97). The robustness of the connection between AIP and GDM was demonstrated by sensitivity analyses and subgroup analyses. An area under the ROC curve of 0.7879 (95% CI 0.7087-0.8671) indicates that AIP is an excellent predictor of GDM. With a specificity of 75.41% and sensitivity of 72.22%, the ideal AIP cut-off value for identifying GDM was 0.3557. CONCLUSIONS: This study revealed that the AIP at 10-14 weeks of gestation was independently and positively correlated with GDM risk. AIP could serve as an early screening and monitoring tool for pregnant women at high risk of GDM, thereby optimizing GDM prevention strategies. TRIAL REGISTRATION: ClinicalTrials.gov registration no. NCT02276144.