Genetic variants in epoxyeicosatrienoic acid processing and degradation pathways are associated with gestational diabetes mellitus.

AIM: To explore the genetic effects of CYP2C8, CYP2C9, CYP2J2, and EPHX2, the key genes involved in epoxyeicosatrienoic acid processing and degradation pathways in gestational diabetes mellitus (GDM) and metabolic traits in Chinese pregnant women. METHODS: A total of 2548 unrelated pregnant women were included, of which 938 had GDM and 1610 were considered as controls. Common variants were genotyped using the Infinium Asian Screening Array. Association studies of single nucleotide polymorphisms (SNPs) with GDM and related traits were performed using logistic regression and multivariable linear regression analyses. A genetic risk score (GRS) model based on 12 independent target SNPs associated with GDM was constructed. Logistic regression was used to estimate odds ratios and 95% confidence intervals, adjusting for potential confounders including age, pre-pregnancy body mass index, history of polycystic ovarian syndrome, history of GDM, and family history of diabetes, with GRS entered both as a continuous variable and categorized groups. The relationship between GRS and quantitative traits was also evaluated. RESULTS: The 12 SNPs in CYP2C8, CYP2C9, CYP2J2, and EPHX2 were significantly associated with GDM after adjusting for covariates (all P < 0.05). The GRS generated from these SNPs significantly correlated with GDM. Furthermore, a significant interaction between CYP2J2 and CYP2C8 in GDM (PInteraction = 0.014, ORInteraction= 0.61, 95%CI 0.41-0.90) was observed. CONCLUSION: We found significant associations between GDM susceptibility and 12 SNPs of the four genes involved in epoxyeicosatrienoic acid processing and degradation pathways in a Chinese population. Subjects with a higher GRS showed higher GDM susceptibility with higher fasting plasma glucose and area under the curve of glucose and poorer ß-cell function.

GPSM1 impairs metabolic homeostasis by controlling a pro-inflammatory pathway in macrophages.

G-protein-signaling modulator 1 (GPSM1) exhibits strong genetic association with Type 2 diabetes (T2D) and Body Mass Index in population studies. However, how GPSM1 carries out such control and in which types of cells are poorly understood. Here, we demonstrate that myeloid GPSM1 promotes metabolic inflammation to accelerate T2D and obesity development. Mice with myeloid-specific GPSM1 ablation are protected against high fat diet-induced insulin resistance, glucose dysregulation, and liver steatosis via repression of adipose tissue pro-inflammatory states. Mechanistically, GPSM1 deficiency mainly promotes TNFAIP3 transcription via the Gαi3/cAMP/PKA/CREB axis, thus inhibiting TLR4-induced NF-κB signaling in macrophages. In addition, we identify a small-molecule compound, AN-465/42243987, which suppresses the pro-inflammatory phenotype by inhibiting GPSM1 function, which could make it a candidate for metabolic therapy. Furthermore, GPSM1 expression is upregulated in visceral fat of individuals with obesity and is correlated with clinical metabolic traits. Overall, our findings identify macrophage GPSM1 as a link between metabolic inflammation and systemic homeostasis.

The mediating role of maternal metabolites between lipids and adverse pregnancy outcomes of gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy, and the demographics of pregnant women have changed in recent decades. GDM is a metabolic disease with short- and long-term adverse effects on both pregnant women and newborns. The metabolic changes and corresponding risk factors should be of great significance in understanding the pathological mechanism of GDM and reducing the incidence of adverse pregnancy outcomes in patients with GDM. The well-known GDM-associated lipids used in clinical tests, such as triglyceride (TG), are thought to play a major role in metabolic changes during GDM, which have a potential causal relationship with abnormal pregnancy outcomes of GDM. Therefore, this study analyzed the relationship between clinical lipid indicators, metabolic profiles, and abnormal pregnancy outcomes in GDM through mediation analysis. By constructing a metabolic atlas of 399 samples from GDM patients in different trimesters, we efficiently detected the key metabolites of adverse pregnancy outcomes and their mediating roles in bridging abnormal lipids and adverse pregnancy outcomes in patients with GDM. Our study confirmed that TG and total cholesterol were independent risk factors for adverse pregnancy outcomes in patients with GDM. Several key metabolites as mediators (e.g., gamma-linolenic acid, heptadecanoic acid, oleic acid, palmitic acid, and palmitoleic acid) have been identified as potential biomarkers for adverse pregnancy outcomes in patients with GDM. These metabolites mainly participate in the biosynthesis of unsaturated fatty acids, which may shed new light on the pathology of GDM and provide insights for further exploration of the molecular mechanisms underlying adverse pregnancy outcomes.

Pathology and ultrasound findings in diffuse sclerosing thyroid papillary carcinoma.

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Common single-nucleotide polymorphisms combined with a genetic risk score provide new insights regarding the etiology of gestational diabetes mellitus.

AIMS: Few studies have constructed a genetic risk score (GRS) to predict the risk of gestaional diabetes mellitus (GDM). We tested the hypothesis that single-nucleotide polymorphisms (SNPs) confirmed for diabetes and obesity and the GRS are associated with GDM. METHODS: We conducted a case-control study comprising 971 GDM cases and 1682 controls from the University of Hong Kong Shenzhen Hospital. A total of 1448 SNPs reported with type 2 diabetes (T2D), type 1 diabetes (T1D), and obesity were selected and the GRS based on SNPs associated with GDM was created. RESULTS: We confirmed that rs10830963 (OR = 1.41,95% CI = 1.25, 1.59) in MTNR1B and rs2206734 (OR = 1.38, 95% CI = 1.22, 1.55) in CDKAL1 were strongly associated with the risk of GDM. Compared with participants with GRS based on T2D SNPs in the low tertile, the ORs of GDM across increasing GRS tertiles were 1.63 (95% CI 1.29, 2.06) and 2.72 (95% CI 2.18, 3.38) in the middle and high tertile, respectively. The positive associations between the GRS and the risk of GDM were also observed in GRS based on obesity/waist-to-hip ratio (WHR)/body mass index (BMI) SNPs. The resulting GRS for each allele increase was significantly associated with higher glycemic indices and lower HOMA-B values for GRS based on T2D SNPs, but not for GRS based on T1D SNPs and GRS based on obesity/WHR/BMI SNPs. CONCLUSION: These findings indicate that GDM may share a common genetic background with T2D and obesity and that SNPs associated with insulin secretion defects have a vital role in the development of GDM.

Discovery of metabolic biomarkers for gestational diabetes mellitus in a Chinese population.

BACKGROUND: Gestational diabetes mellitus (GDM), one of the most common pregnancy complications, can lead to morbidity and mortality in both the mother and the infant. Metabolomics has provided new insights into the pathology of GDM and systemic analysis of GDM with metabolites is required for providing more clues for GDM diagnosis and mechanism research. This study aims to reveal metabolic differences between normal pregnant women and GDM patients in the second- and third-trimester stages and to confirm the clinical relevance of these new findings. METHODS: Metabolites were quantitated with the serum samples of 200 healthy pregnant women and 200 GDM women in the second trimester, 199 normal controls, and 199 GDM patients in the third trimester. Both function and pathway analyses were applied to explore biological roles involved in the two sets of metabolites. Then the trimester stage-specific GDM metabolite biomarkers were identified by combining machine learning approaches, and the logistic regression models were constructed to evaluate predictive efficiency. Finally, the weighted gene co-expression network analysis method was used to further capture the associations between metabolite modules with biomarkers and clinical indices. RESULTS: This study revealed that 57 differentially expressed metabolites (DEMs) were discovered in the second-trimester group, among which the most significant one was 3-methyl-2-oxovaleric acid. Similarly, 72 DEMs were found in the third-trimester group, and the most significant metabolites were ketoleucine and alpha-ketoisovaleric acid. These DEMs were mainly involved in the metabolism pathway of amino acids, fatty acids and bile acids. The logistic regression models for selected metabolite biomarkers achieved the area under the curve values of 0.807 and 0.81 for the second- and third-trimester groups. Furthermore, significant associations were found between DEMs/biomarkers and GDM-related indices. CONCLUSIONS: Metabolic differences between healthy pregnant women and GDM patients were found. Associations between biomarkers and clinical indices were also investigated, which may provide insights into pathology of GDM.

Association between circulating full-length angiopoietin-like protein 8 and non-high-density lipoprotein cholesterol levels in Chinese non-diabetic individuals: a cross-sectional study.

BACKGROUND: Angiopoietin-like protein 8 (ANGPTL8) is a novel hormone involved in the regulation of lipid metabolism and glucose homeostasis. There are inconsistent results regarding the association between ANGPTL8 and lipids in humans. We aimed to investigate the associations between ANGPTL8 and lipids in people without diabetes. METHODS: This was a cross-sectional study of 107 patients with dyslipidemia and 141 patients without. Dyslipidemia diagnosis was based on Chinese guidelines for the prevention and treatment of dyslipidemia in adults. Total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol (HDL-C) were examined. Non-HDL-C was calculated by subtracting HDL-C from TC. Circulating full-length ANGPTL8 concentrations were measured using enzyme-linked immunosorbent assay. Associations between log-transformed circulating full-length ANGPTL8 and serum lipids were examined using multivariate linear regression analysis. RESULTS: Circulating ANGPTL8 concentrations were significantly elevated in patients with dyslipidemia compared with patients without dyslipidemia. Circulating full-length ANGPTL8 concentrations were positively associated with non-HDL-C, TG and TC levels after adjusting for age, gender, body mass index, high-sensitivity C-reactive protein, alanine aminotransferase, and creatinine. CONCLUSION: In people without diabetes, circulating full-length ANGPTL8 concentrations in patients with dyslipidemia were significantly elevated compared with non-dyslipidemia, and ANGPTL8 was positively associated with serum non-HDL-C levels.

[Effect of estrogen on the expression of matrix GLA protein in ovariectomized SD rats].

OBJECTIVE: To investigate the effect of estrogen on expression of matrix GLA protein (MGP) in ovariectomized Sprague-Dawley (SD) rats and the role of estrogen in improving postmenopausal osteoporosis. METHODS: Thirty-six SD female rats were allocated into 3 groups randomly, every 12 rats in ovariectomized group (OVX group), estrogen group (E group) and control group (sham group). Rats in OVX and E group all underwent bilateral ovariectomy, those rats in E group were given by estradiol benzoate intramuscularly after 3 weeks of ovariectomy. Rats in sham group underwent bilateral lipectomy near the ovary. All rats were kept the urine and the serum every three weeks and were sacrificed after 15 weeks. The pathology changes of uterus, lumbar vertebral bones were observed by immunohistochemistry. Bone mineral density (BMD) of lumbar vertebra of rats was determined by dual energy X ray absorptiometry (DEXA). The content of MGP in serum and urine was determined by ELISA. Expression of undercarboxylated matrix GLA Protein (MGP) was detected by immunohistochemistry. Relative quantification of MGP mRNA expression in lumbar vertebra bone was detected by Fluorescent real-time quantitative polymerase chain reaction. RESULTS: (1) After 15 weeks of ovariectomized, the endometrium of uterus and lumbar vertebra exhibit remarkable pathologic changes in OVX group. The serum estrogen of (454 ± 66) pmol/L in OVX group were lower than in (527 ± 77) pmol/L in sham group and (556 ± 80) pmol/L in E group significantly (P < 0.05). The BMD of lumbar vertebra of (0.263 ± 0.030) g/cm(2) in OVX group were lower than (0.295 ± 0.024) g/cm(2) in sham group and (0.279 ± 0.024) g/cm(2) in E group significantly (P < 0.01). (2) The serum MPG protein in OVX group and E group showed decreased trends after ovariectomized, which were (104 ± 64) ng/L in OVX group and (134 ± 6) ng/L in E group at 9 weeks, which reached statistical difference (P < 0.05). However, MGP in urine in sham group did not exhibit significant difference after 15 weeks of surgery (P > 0.05). The MGP in urine of E group showed increased trends after 12 weeks of surgery, which reached (110.0 ± 3.4) ng/L at 15 weeks, in the mean time, it was found that (86.5 ± 2.5) ng/L of MGP in urine in OVX group, which showed significant difference (P < 0.05). (3) MGP could be observed in lumbar vertebra in OVX group by immunochemistry staining. In the other two groups, the expression of MGP was not dominant. (4) Relative quantification of MGP mRNA expression in lumbar vertebra was defined as 1 in OVX group, when compared with 0.289 ± 0.260 in E group and 0.103 ± 0.098 in sham group, the difference showed statistically significant (P < 0.01). CONCLUSION: Estrogen could increase the expression of MGP mRNA and protein in ovariectomized rats and might play an important role in improving postmenopausal osteoporosis.