First-Trimester Plasmatic microRNAs Are Associated with Fasting Glucose Levels in Late Second Trimester of Pregnancy.

Maternal blood glucose regulation adaptation to pregnancy aims to support fetal growth but may also lead to the development of gestational diabetes mellitus, the most common pregnancy complication. MiRNAs are small RNA molecules secreted and stable in the blood, where they could have paracrine hormone-like functions (ribo-hormone) and regulate metabolic processes including fetal growth and glucose metabolism. The objective of this study was to identify plasmatic microRNA (miRNAs) measured during the first trimester of pregnancy that were associated with glucose levels during a 75 g oral glucose tolerance test (OGTT) at ~26 weeks of pregnancy. miRNAs were quantified using next-generation sequencing in 444 pregnant women and replicated in an independent cohort of 106 pregnant women. MiRNAs associated with glucose levels were identified with the DESeq2 package. We identified 24 miRNAs associated with fasting glycemia, of which 18 were common to both cohorts (q-value < 0.1). However, no association was found between miRNAs and 1 h or 2 h post OGTT glycemia. To conclude, we identified 18 miRNAs early in pregnancy that were associated with fasting blood glucose measured 3 months later. Our findings offer new insights into the mechanisms involved in fasting glucose homeostasis regulation in pregnancy, which is critical to understanding how gestational diabetes develops.

First Trimester Plasma MicroRNA Levels Predict Risk of Developing Gestational Diabetes Mellitus.

Aims: Our objective is to identify first-trimester plasmatic miRNAs associated with and predictive of GDM. Methods: We quantified miRNA using next-generation sequencing in discovery (Gen3G: n = 443/GDM = 56) and replication (3D: n = 139/GDM = 76) cohorts. We have diagnosed GDM using a 75-g oral glucose tolerance test and the IADPSG criteria. We applied stepwise logistic regression analysis among replicated miRNAs to build prediction models. Results: We identified 17 miRNAs associated with GDM development in both cohorts. The prediction performance of hsa-miR-517a-3p|hsa-miR-517b-3p, hsa-miR-218-5p, and hsa-let7a-3p was slightly better than GDM classic risk factors (age, BMI, familial history of type 2 diabetes, history of GDM or macrosomia, and HbA1c) (AUC 0.78 vs. 0.75). MiRNAs and GDM classic risk factors together further improved the prediction values [AUC 0.84 (95% CI 0.73-0.94)]. These results were replicated in 3D, although weaker predictive values were obtained. We suggest very low and higher risk GDM thresholds, which could be used to identify women who could do without a diagnostic test for GDM and women most likely to benefit from an early GDM prevention program. Conclusions: In summary, three miRNAs combined with classic GDM risk factors provide excellent prediction values, potentially strong enough to improve early detection and prevention of GDM.

Maternal Body Mass Index Is Associated with Profile Variation in Circulating MicroRNAs at First Trimester of Pregnancy.

Many women enter pregnancy with overweight and obesity, which are associated with complications for both the expectant mother and her child. MicroRNAs (miRNAs) are short non-coding RNAs that regulate many biological processes, including energy metabolism. Our study aimed to identify first trimester plasmatic miRNAs associated with maternal body mass index (BMI) in early pregnancy. We sequenced a total of 658 plasma samples collected between the 4th and 16th week of pregnancy from two independent prospective birth cohorts (Gen3G and 3D). In each cohort, we assessed associations between early pregnancy maternal BMI and plasmatic miRNAs using DESeq2 R package, adjusting for sequencing run and lane, gestational age, maternal age at the first trimester of pregnancy and parity. A total of 38 miRNAs were associated (FDR q < 0.05) with BMI in the Gen3G cohort and were replicated (direction and magnitude of the fold change) in the 3D cohort, including 22 with a nominal p-value < 0.05. Some of these miRNAs were enriched in fatty acid metabolism-related pathways. We identified first trimester plasmatic miRNAs associated with maternal BMI. These miRNAs potentially regulate fatty acid metabolism-related pathways, supporting the hypothesis of their potential contribution to energy metabolism regulation in early pregnancy.

Time-course full profiling of circulating miRNAs in neurologically deceased organ donors: a proof of concept study to understand the onset of the cytokine storm.

Neurologically deceased organ donors (NDDs) generally display an immune response involving an intense production of pro-inflammatory cytokines referred to as the cytokine storm. The sudden surge of inflammatory mediators in circulation promotes tissue and organ damages and ultimately leads to poor transplant outcome. As microRNAs (miRNAs) are frequently proposed as key regulators of inflammation and are relatively stable in circulation, changes in their profiles could play a role in the onset of the cytokine storm in NDDs. In this proof-of-concept study, we sought to investigate differentially abundant circulating miRNAs in a temporal manner between neurological death and organ recovery and to assess the association between specific miRNAs and levels of inflammatory cytokines in blood. Plasma samples from five NDDs were obtained at multiple time points between organ donation consent and organ recovery. Using a time-course analysis and miRNA sequencing, we identified 32 plasma miRNAs fluctuating between consent and organ recovery (false discovery rate; q-value < 0.1). Eleven miRNAs relatively abundant (>100 reads) and detected in all samples were selected for further biological pathway analysis (miR-486-3p, miR-103a-3p, miR-106b-3p, miR-182-5p, miR-101-3p, miR-10a-5p, miR-125a-5p, miR-146b-5p, miR-26a-5p, miR-423-5p, miR-92b-3p). These miRNAs targeted genes such as c-JUN (TNF signalling pathway) and eEF2 (AMPK pathway), suggesting a potential role in regulation of inflammation. Our results contribute to a better understanding of the miRNAs dynamic after neurological death in organ donors and could potentially be used to predict the related early cytokine storm.Trial registration: ClinicalTrials.gov ID NCT03786991. Registered December 2018.

Intra-abdominal adipose depot variation in adipogenesis, lipogenesis, angiogenesis, and fibrosis gene expression and relationships with insulin resistance and inflammation in premenopausal women with severe obesity

Although severe obesity is associated with insulin resistance (IR) and inflammation, secretory function of intra-abdominal adipose tissues and their relationships with IR and inflammation markers remain poorly understood. Aims were to measure gene expression of adipogenic (C/EBPα/β, PPARγ-1/2, SREBP-1c, LXRα), lipogenic (SCD1, DGAT-1/2), angiogenic (VEGFα, leptin), and fibrotic (LOX, COL6A3) factors in the round ligament (RL), omental (OM), and mesenteric (ME) fat depots and to evaluate their relationships with IR and inflammation markers in 48 women with severe obesity undergoing bariatric surgery. Gene expression was assessed by RT-qPCR, and plasma glucose and insulin (HOMA-IR calculated), PAI-1, IL-6, TNFα, adiponectin, and leptin levels were determined. C/EBPβ and PPARγ-1/2 mRNA levels were more expressed in the OM (0.001

First trimester plasma microRNAs levels predict Matsuda Index-estimated insulin sensitivity between 24th and 29th week of pregnancy.

INTRODUCTION: Gestational diabetes mellitus (GDM) is a consequence of an imbalance between insulin sensitivity (IS) and secretion during pregnancy. MicroRNAs (miRNAs) are small and secreted RNA molecules stable in blood and known to regulate physiological processes including glucose homeostasis. The aim of this study was to identify plasmatic miRNAs detectable in early pregnancy predicting IS at 24th-29th week of pregnancy. RESEARCH DESIGN AND METHODS: We quantified circulating miRNAs in 421 women in plasma collected at 9.6±2.2 weeks of pregnancy using next-generation sequencing. RESULTS: we detected 2170 miRNAs: 39 (35 positively and 4 negatively) were associated with IS as estimated by the Matsuda Index at 26.4±1.0 weeks of pregnancy. Lasso regression identified 18 miRNAs independently predicting Matsuda Index-estimated IS. Together with gestational age, maternal age and body mass index at first trimester, they explain 36% of IS variance in late second trimester of pregnancy. These miRNAs regulate fatty acid biosynthesis and metabolism among other pathways. CONCLUSIONS: In summary, we have identified first trimester plasmatic miRNAs predictive of Matsuda Index-estimated IS in late second trimester of pregnancy. These miRNAs could also contribute to initiate and support IS adaptation to pregnancy potentially through lipid metabolism regulation.

Intra-abdominal adipose depot variation in adipogenesis, lipogenesis, angiogenesis, and fibrosis gene expression and relationships with insulin resistance and inflammation in premenopausal women with severe obesity.

Although severe obesity is associated with insulin resistance (IR) and inflammation, secretory function of intra-abdominal adipose tissues and their relationships with IR and inflammation markers remain poorly understood. Aims were to measure gene expression of adipogenic (C/EBPα/ß, PPARγ-1/2, SREBP-1c, LXRα), lipogenic (SCD1, DGAT-1/2), angiogenic (VEGFα, leptin), and fibrotic (LOX, COL6A3) factors in the round ligament (RL), omental (OM), and mesenteric (ME) fat depots and to evaluate their relationships with IR and inflammation markers in 48 women with severe obesity undergoing bariatric surgery. Gene expression was assessed by RT-qPCR, and plasma glucose and insulin (HOMA-IR calculated), PAI-1, IL-6, TNFα, adiponectin, and leptin levels were determined. C/EBPß and PPARγ-1/2 mRNA levels were more expressed in the OM (0.001

Human plasma pregnancy-associated miRNAs and their temporal variation within the first trimester of pregnancy.

BACKGROUND: During pregnancy, maternal metabolism undergoes substantial changes to support the developing fetus. Such changes are finely regulated by different mechanisms carried out by effectors such as microRNAs (miRNAs). These small non-coding RNAs regulate numerous biological functions, mostly through post-transcriptional repression of gene expression. miRNAs are also secreted in circulation by numerous organs, such as the placenta. However, the complete plasmatic microtranscriptome of pregnant women has still not been fully described, although some miRNA clusters from the chromosome 14 (C14MC) and the chromosome 19 (C19MC and miR-371-3 cluster) have been proposed as being specific to pregnancy. Our aims were thus to describe the plasma microtranscriptome during the first trimester of pregnancy, by assessing the differences with non-pregnant women, and how it varies between the 4th and the 16th week of pregnancy. METHODS: Plasmatic miRNAs from 436 pregnant (gestational week 4 to 16) and 15 non-pregnant women were quantified using Illumina HiSeq next-generation sequencing platform. Differentially abundant miRNAs were identified using DESeq2 package (FDR q-value ≤ 0.05) and their targeted biological pathways were assessed with DIANA-miRpath. RESULTS: A total of 2101 miRNAs were detected, of which 191 were differentially abundant (fold change < 0.05 or > 2, FDR q-value ≤ 0.05) between pregnant and non-pregnant women. Of these, 100 miRNAs were less and 91 miRNAs were more abundant in pregnant women. Additionally, the abundance of 57 miRNAs varied according to gestational age at first trimester, of which 47 were positively and 10 were negatively associated with advancing gestational age. miRNAs from the C19MC were positively associated with both pregnancy and gestational age variation during the first trimester. Biological pathway analysis revealed that these 191 (pregnancy-specific) and 57 (gestational age markers) miRNAs targeted genes involved in fatty acid metabolism, ECM-receptor interaction and TGF-beta signaling pathways. CONCLUSION: We have identified circulating miRNAs specific to pregnancy and/or that varied with gestational age in first trimester. These miRNAs target biological pathways involved in lipid metabolism as well as placenta and embryo development, suggesting a contribution to the maternal metabolic adaptation to pregnancy and fetal growth.

HDL-enriched miR-30a-5p is associated with HDL-cholesterol levels and glucose metabolism in healthy men and women.

Aim: To investigate the associations between high-density lipoprotein (HDL)-enriched miRNAs and the cardiometabolic profile of healthy men and women. Patients & methods: miRNAs were quantified using next-generation sequencing of miRNAs extracted from purified HDL and plasma from 17 healthy men and women couples. Results: Among the HDL-enriched miRNAs, miR-30a-5p correlated positively with HDL-cholesterol levels, whereas miR-144-5p and miR-30a-5p were negatively associated with fasting insulin levels and Homeostasis model assessment of insulin resistance index. Overall, miR-30a-5p, miR-150-5p and sex contributed to 45% of HDL-cholesterol variance. A model containing only miR-30a-5p, age and sex explained 41% of fasting glucose variance. Conclusion: HDL-enriched miRNAs, notably miR-30a-5p, are associated with cardiometabolic markers. These miRNAs could play a role in HDL's protective functions, particularly regarding glucose-insulin homeostasis.

Comparing an adiposopathy approach with four popular classifications schemes to categorize the metabolic profile of postmenopausal women.

Numerous classifications are used to discern metabolically healthy obese (MHO) from metabolically abnormal obese (MAO) individuals. The goal of this study was to compare a single phenotype approach, adiposopathy (i.e., the plasma adiponectin/leptin ratio), with four commonly used classifications (International Diabetes Federation (IDF), Karelis, Lynch, Wildman), all based on obesity with other risk factors), for their ability to discern phenotypic differences between MAO and MHO postmenopausal women. Anthropometry, body composition, blood pressure, cardiorespiratory fitness (CRF), lipid-lipoprotein, hepatic, inflammatory, and adipokine profiles, as well as glucose-insulin homeostasis, were assessed in 79 obese sedentary postmenopausal women (60 ± 5 years; body mass index, BMI, 34.0 ± 3.7 kg/m2). Abdominal subcutaneous adipose tissue (SCAT) expression of selected genes involved in fatty acid metabolism and inflammation was used as markers of tissue state (n = 48). Beyond their intrinsic criteria, adiposopathy was almost as effective as the Karelis definition in discerning differences in MHO for adiposity (reduced body weight, BMI, waist circumference, and fat mass), lipid-lipoprotein (lower triacylglycerol and higher HDL-cholesterol levels, reduced atherogenic ratios) and adipokine (higher adiponectin and lower leptin levels) profiles, and glucose-insulin homeostasis (lower insulin resistance) as well as for some SCAT gene expression related to lipolysis and lipogenesis, but was the only one able to distinguish these subjects for greater CRF. The other classifications revealed fewer differences between MAO and MHO women. These data suggest that considering a marker of AT dysfunction such as adiposopathy either alone or in addition to other criteria could be potentially interesting in discerning the MHO phenotype.

The relationship between adiposopathy and glucose-insulin homeostasis is not affected by moderate-intensity aerobic training in healthy women with obesity

The contribution of adiposopathy to glucose-insulin homeostasis remains unclear. This longitudinal study examined the potential relationship between the adiponectin/leptin ratio (A/L, a marker of adiposopathy) and insulin resistance (IR: homeostasis model assessment (HOMA)), insulin sensitivity (IS: Matsuda), and insulin response to an oral glucose tolerance test before and after a 16-week walking program, in 29 physically inactive pre- and postmenopausal women with obesity (BMI, 29-35 kg/m2; age, 47-54 years). Anthropometry, body composition, VO2max, and fasting lipid-lipoprotein and inflammatory profiles were assessed. A/L was unchanged after training (p = 0.15), despite decreased leptin levels (p < 0.05). While the Matsuda index tended to increase (p = 0.07), HOMA decreased (p < 0.05) and fasting insulin was reduced (p < 0.01) but insulin area under the curve (AUC) remained unchanged (p = 0.18) after training. Body fatness and VO2max were improved (p < 0.05) while triacylglycerols increased and HDL-CHOL levels decreased after training (p < 0.05). At baseline, A/L was positively associated with VO2max, HDL-CHOL levels, and Matsuda (0.37 < ρ < 0.56; p < 0.05) but negatively with body fatness, HOMA, insulin AUC, IL-6, and hs-CRP levels (− 0.41 < ρ < − 0.66; p < 0.05). After training, associations with fitness, HOMA, and inflammation were lost. Multiple regression analysis revealed A/L as an independent predictor of IR and IS, before training (partial R2 = 0.10 and 0.22), although A/L did not predict the insulin AUC pre- or post-intervention. A significant correlation was found between training-induced changes to A/L and IS (r = 0.38; p < 0.05) but not with IR or insulin AUC. Although changes in the A/L ratio could not explain improvements to glucose-insulin homeostasis indices following training, a relationship with insulin sensitivity was revealed in healthy women with obesity

The relationship between adiposopathy and glucose-insulin homeostasis is not affected by moderate-intensity aerobic training in healthy women with obesity.

The contribution of adiposopathy to glucose-insulin homeostasis remains unclear. This longitudinal study examined the potential relationship between the adiponectin/leptin ratio (A/L, a marker of adiposopathy) and insulin resistance (IR: homeostasis model assessment (HOMA)), insulin sensitivity (IS: Matsuda), and insulin response to an oral glucose tolerance test before and after a 16-week walking program, in 29 physically inactive pre- and postmenopausal women with obesity (BMI, 29-35 kg/m2; age, 47-54 years). Anthropometry, body composition, VO2max, and fasting lipid-lipoprotein and inflammatory profiles were assessed. A/L was unchanged after training (p = 0.15), despite decreased leptin levels (p < 0.05). While the Matsuda index tended to increase (p = 0.07), HOMA decreased (p < 0.05) and fasting insulin was reduced (p < 0.01) but insulin area under the curve (AUC) remained unchanged (p = 0.18) after training. Body fatness and VO2max were improved (p < 0.05) while triacylglycerols increased and HDL-CHOL levels decreased after training (p < 0.05). At baseline, A/L was positively associated with VO2max, HDL-CHOL levels, and Matsuda (0.37 < ρ < 0.56; p < 0.05) but negatively with body fatness, HOMA, insulin AUC, IL-6, and hs-CRP levels (- 0.41 < ρ < - 0.66; p < 0.05). After training, associations with fitness, HOMA, and inflammation were lost. Multiple regression analysis revealed A/L as an independent predictor of IR and IS, before training (partial R2 = 0.10 and 0.22), although A/L did not predict the insulin AUC pre- or post-intervention. A significant correlation was found between training-induced changes to A/L and IS (r = 0.38; p < 0.05) but not with IR or insulin AUC. Although changes in the A/L ratio could not explain improvements to glucose-insulin homeostasis indices following training, a relationship with insulin sensitivity was revealed in healthy women with obesity.