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World J Diabetes. Jun 15, 2019; 10(6): 333-340
Published online Jun 15, 2019. doi: 10.4239/wjd.v10.i6.333
Exploration of the shared pathophysiological mechanisms of gestational diabetes and large for gestational age offspring
Sofia Nahavandi, The Royal Children’s Hospital Melbourne, Parkville, VIC 3052, Australia
Sarah Price, Priya Sumithran, Elif Ilhan Ekinci, Department of Endocrinology, Austin Health, Repatriation Campus Heidelberg West, Melbourne, VIC 3081, Australia
Sarah Price, Priya Sumithran, Elif Ilhan Ekinci, Department of Medicine, Austin Health and the University of Melbourne (Austin Campus), Parkville, Melbourne, VIC 3084, Australia
ORCID number: Sofia Nahavandi (0000-0001-6174-0158); Sarah Price (pending); Priya Sumithran (0000-0002-9576-1050); Elif Ilhan Ekinci (0000-0003-2372-395X).
Author contributions: Nahavandi S was the primary author. Price S, Sumithran P, and Ekinci EI provided subject matter expertise and edited the manuscript.
Conflict-of-interest statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Elif Ilhan Ekinci, FRACP, MBBS, PhD, Associate Professor, Sir Edward Dunlop Medical Research Foundation Principal Research Fellow in Metabolic Medicine, Department of Medicine, Austin Health and the University of Melbourne (Austin Campus), Level 1, Centaur Wing, Heidelberg Repatriation Hospital, 300 Waterdale Road, Melbourne, VIC 3084, Australia. elif.ekinci@unimelb.edu.au
Telephone: +61-03-94962250 Fax: +61-03-94974554
Received: March 30, 2019
Peer-review started: April 3, 2019
First decision: May 8, 2019
Revised: May 13, 2019
Accepted: May 23, 2019
Article in press: May 23, 2019
Published online: June 15, 2019
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Abstract

Gestational diabetes mellitus (GDM) and large for gestational age (LGA) offspring are two common pregnancy complications. Connections also exist between the two conditions, including mutual maternal risk factors for the conditions and an increased prevalence of LGA offspring amongst pregnancies affected by GDM. Thus, it is important to elucidate potential shared underlying mechanisms of both LGA and GDM. One potential mechanistic link relates to macronutrient metabolism. Indeed, derangement of carbohydrate and lipid metabolism is present in GDM, and maternal biomarkers of glucose and lipid control are associated with LGA neonates in such pregnancies. The aim of this paper is therefore to reflect on the existing nutritional guidelines for GDM in light of our understanding of the pathophysiological mechanisms of GDM and LGA offspring. Lifestyle modification is first line treatment for GDM, and while there is some promise that nutritional interventions may favourably impact outcomes, there is a lack of definitive evidence that changing the macronutrient composition of the diet reduces the incidence of either GDM or LGA offspring. The quality of the available evidence is a major issue, and rigorous trials are needed to inform evidence-based treatment guidelines.

Key Words: Gestational diabetes mellitus; Large for gestational age; Metabolism; Biomarkers; Glucose; Lipids

Core tip: The prevalence of gestational diabetes is on the rise, warranting attention on the consequences for mother and offspring, as well as management options. One consequence is an increased risk of large for gestational age (LGA) offspring. While deranged macronutrient metabolism of carbohydrate and lipids in gestational diabetes may play a role in fetal overgrowth, there is a lack of conclusive evidence that dietary interventions employed as first-line gestational diabetes management reduces this risk of LGA offspring.



INTRODUCTION

Gestational diabetes mellitus (GDM) is defined as glucose intolerance that develops after the first trimester of pregnancy and resolves post-delivery. Its prevalence has increased over recent years due to a variety of factors including a change in diagnostic criteria, increasing maternal obesity, and increasing maternal age. Although estimates vary according to the population and diagnostic tests used, in Australia the current prevalence is around 13% (reported in 2016)[1] compared to 3.6% 20 years earlier[2].

GDM increases the risk of a number of adverse outcomes for both mother and baby. A common concern is the increased risk of a large baby, referred to as “large for gestational age” or “LGA” - usually defined as birthweight above the 90th percentile for gestational age[3]. A related term is macrosomia - usually defined as absolute birthweight greater than 4000 g or 4500 g[4]. LGA and macrosomia in turn pose risks for delivery complications as well as potential longer-term metabolic complications.

While fetal growth is determined by the interaction of a number of factors, both genetic and environmental, the link between GDM and LGA suggests there may be shared pathogenic elements (Figure 1). Indeed, risk factors in common for both conditions include older maternal age, maternal obesity, gestational weight gain, and ethnicity[4]. The aim of this paper is to review the key elements of maternal meta-bolism that are both altered in the GDM state and linked to higher birthweight in such pregnancies, and to discuss how they relate to nutritional guidelines for women with GDM.

Figure 1
Figure 1 Gestational diabetes mellitus increases the risk of large for gestational age offspring, and both have potential long-term metabolic consequences. The two conditions also have shared maternal risk factors. Altered carbohydrate and lipid metabolism is present in pregnancies affected by gestational diabetes mellitus (GDM) and markers of this metabolism e.g., maternal blood glucose, triglycerides and high-density lipoprotein cholesterol (HDL-C), have been associated with large for gestational age offspring in GDM pregnancies. Therefore, these biomarkers may provide a link between the two conditions. HbA1c: Glycosylated haemoglobin; HDL-C: High-density lipoprotein cholesterol; GDM: Gestational diabetes mellitus.
GLYCAEMIA

Normal pregnancy involves a progressive increase in maternal insulin resistance from mid-pregnancy, promoting diversion of glucose to the fetus[4,5]. Maternal and placental hormones such as progesterone, oestrogen, prolactin, human placental lactogen, human placental growth hormone, and cortisol, are the main drivers for this insulin resistance[6,7]. Alterations in adipokines (proteins secreted by adipose tissue) such as tumour necrosis factor alpha, adiponectin, and leptin may also contribute[7].

In GDM, the insulin resistance of pregnancy is exaggerated, and/or maternal pancreatic beta cells can not sufficiently compensate[8]. GDM may therefore be the unmasking of underlying beta cell dysfunction. Other key elements of carbohydrate metabolism are also altered in GDM. For instance, compared to matched controls, women with GDM exhibit smaller increases in first-phase insulin response (the initial rapid insulin secretion in response to glucose ingestion that lasts only minutes) as pregnancy progresses[8]. Insulin suppression of gluconeogenesis is also impaired in women with GDM[9]. Overall, this leads to hyperglycaemia.

Maternal hyperglycaemia is believed to play a significant role in the development of LGA[9]. According to the hyperglycaemia-hyperinsulinaemia hypothesis (also called the Pedersen hypothesis), maternal hyperglycaemia leads to fetal hyperglycaemia as glucose is transferred down the placental concentration gradient[10]. This consequently stimulates the fetal pancreas to increase insulin production; the resulting hyperinsu-linaemia leads to fetal overgrowth as insulin is a prominent growth hormone for the fetus[11].

There is much data from human and animal studies indicating the importance of glycaemia management during pregnancy[10]. The Hyperglycemia and Adverse Pregnancy Outcomes study was the seminal paper demonstrating the continuous relationship between glucose levels at 24-28 wk’ gestation and pregnancy outcomes, including LGA offspring[12]. A similar linear relationship between maternal glucose and C-peptide levels in infant cord blood was also evident in this population, corro-borating the role of fetal hyperinsulinaemia. This study subsequently informed the development of GDM diagnostic criteria by demonstrating that hyperglycaemia below that of overt diabetes is associated with greater risk of adverse outcomes.

Moreover, other glycaemic markers have also been assessed for an association with LGA in GDM pregnancies. This includes glycosylated haemoglobin, 1,5-anhydrog-lucitol and fructosamine[13]; however, there is limited support for these markers. Overall, the association between glucose control and LGA offspring is incomplete, suggesting that other factors may be involved.

LIPIDS

Adaptive changes occur in lipid metabolism during normal pregnancy. The first two trimesters of gestation comprise an “anabolic phase”, involving enhanced maternal fat storage[14]. This occurs due to a combination of hormonal changes (e.g., progesterone, prolactin, cortisol) promoting lipid synthesis and storage, inhibition of lipid breakdown, as well as hyperphagia[15]. The final trimester is a “catabolic phase” where there is a net breakdown of fat stores. Insulin resistance plays an important role in this shift, by leading to enhanced lipolysis of adipose tissue and reduced lipoprotein lipase activity, thereby reducing overall lipid uptake[15]. These changes are associated with an initial decrease in maternal circulating lipid levels in the first trimester, with subsequent gradual increase across gestation, reaching peak levels prior to delivery[15]. The greatest increase is seen in triglyceride levels, which reach up to triple prepreg-nancy values[16].

Lipids are vitally important in fetal development, as they are involved in key processes such as synthesis of cell membranes and steroid hormones[17]. Fetal lipids are sourced through a combination of placental transfer and de novo synthesis. While maternal cholesterol is transferred across the placenta, particularly early on in pregnancy, endogenous fetal cholesterol synthesis becomes more prominent in late gestation[9,15]. On the other hand, triglycerides are the major lipid storage form in fetal adipocytes but maternal triglycerides do not cross the placenta intact. However, free fatty acids (FFAs) may be transferred across the placenta, with specific enzymes, receptors and binding proteins within the placenta thought to enable this process[15]. Fetal triglycerides are synthesised using FFAs[12,15].

In women with GDM, significantly higher triglyceride levels are present throu-ghout pregnancy, and lower high-density lipoprotein cholesterol (HDL-C) levels are present across the final two trimesters, compared to those without GDM[12]. The exaggerated insulin resistance in GDM again plays an important role, with one effect being reduced suppression of lipolysis[18].

The effect of these alterations in lipid metabolism on fetal adiposity in pregnancies with GDM is increasingly being recognised[12]. A meta-analysis involving GDM and non-GDM pregnancies indicated high maternal triglycerides and low HDL-C during pregnancy were associated with increased birthweight[19,20]. Furthermore, alterations in placental structure and function which are seen in GDM pregnancies, such as the expression of lipid-related genes and enzymes, as well as differences in placental phospholipid composition, raise the possibility of altered transplacental lipid pathways which may promote increased lipid transfer in GDM[21]. Indeed, the metabolic environment of GDM, involving hyperinsulinaemia, hyperlipidaemia, and hyperglycaemia, is proposed to contribute to enhanced transfer, synthesis and storage of lipids in fetal adipose tissue[15]. This has even led to revision of the Pedersen hypothesis, with lipids being proposed as a driver of LGA in pregnancies with dia-betes despite good glycaemic control[15,20].

Several studies have investigated associations between maternal lipids and birthweight in pregnancies affected by GDM. A study by Schaefer-Graf et al[22] showed third trimester maternal FFAs and triglycerides were associated with LGA newborns in GDM pregnancies, which remained significant after adjusting for confounding variables including glucose levels[23]. Of note, cord blood lipids were also sampled, with positive correlations evident between maternal and cord blood levels of triglycerides, FFAs, and glycerol. There was also indication of greater insulin resistance in LGA newborns, as cord blood insulin-to-glucose ratio was significantly positively correlated to birthweight.

Greater insight has come from a subsequent study from Schaefer-Graf et al[22], which found cord blood FFA levels were significantly lower in pregnancies without diabetes compared with those with GDM. This may be indicative of increased FFA trans-placental transport in GDM pregnancies. In addition, in a study of 104 Korean women with GDM, maternal hypertriglyceridaemia (defined as triglycerides > 75th percentile value, 3.33 mmol/L) at 24-32 wk’ gestation was significantly associated with LGA offspring, independent of maternal pre-pregnancy body mass index (BMI), gestational weight gain, maternal age or parity; although the model showed only a sensitivity of 48% and specificity of 83.5% for LGA prediction. This study found no significant association between total cholesterol or HDL-C levels and LGA newborns. In contrast, a European research group did find HDL-C was negatively associated with LGA newborns in GDM pregnancies[24]. Triglycerides, however, were not significantly associated in this study, which may be related to the earlier timing of the sample collection (booking visit compared to 24-32 wk’ gestation for the former study). Finally, a pilot study examining home monitoring of fasting and post-prandial triglyceride levels during late pregnancy has also been presented[25]. While the triglyceride levels were not correlated with birthweight, the study was limited by small sample size (twelve participants) and heterogeneous population (eight participants had GDM). It does however provide a new avenue to gather more comprehensive data on triglyceride profiles during pregnancy. In sum, there is increasing support for a role of lipids contributing to fetal overgrowth in GDM pregnancies.

Lipids are also being investigated as predictive biomarkers for GDM. Lipidomics, using techniques such as liquid-chromatography-mass spectrometry and nuclear magnetic resonance imaging, have been employed to identify potential lipid biomarkers of GDM in maternal blood[26]. However, limited data is available regarding optimal cut-off values[27,28]. One study of low risk pregnancies found triglycerides and LDL-C were independent predictors of GDM, although the sensitivity was low[5]. The ratio of triglycerides to HDL-C, proposed to be a clinical indicator of insulin resistance, may be superior than a single lipid biomarker[29], and has been shown to have a high negative predictive value, identifying women with low risk of GDM development in early gestation[30]. Ultimately, lipids may be most useful in a combined prediction model, including other biomarkers factors and clinical risk factors[31].

GDM NUTRITIONAL GUIDELINES

Given the aforementioned links between maternal glycaemia and lipids with GDM, it is unsurprising that dietary modification is central to GDM management. Indeed, medical nutrition therapy is considered first-line treatment, along with physical activity[32], aiming to achieve an appropriate balance between promoting normogly-caemia and adequate gestational weight gain, while allowing for optimal nutrition and fetal growth[33].

Despite being a foundation of management, a prominent issue is the paucity of specific dietary recommendations, reflecting the state of evidence. Indeed, there is substantial heterogeneity across studies including differences in experimental designs, macronutrient compositions, outcome measures, prescribed versus self-reported intakes (and lack of adherence monitoring), and lack of control conditions. Other issues include the small sample sizes, late timing of initiation of the dietary intervention and the short duration. Consequently, there is a lack of consensus, with differing guidelines available[34].

Carbohydrate intake has been the main focus of guidelines and research. Fasting and/or 2-h post-prandial glucose titres are key targets in the management of GDM[35,36]. The recommended dietary reference intake of carbohydrate during pregnancy is a minimum of 175 g per day[34], but the available evidence does not indicate the ideal carbohydrate intake for women with GDM. In part, this may be because the effect of carbohydrate intake may not only relate to the amount consumed (grams or percentage), but also to the type of carbohydrate [e.g., fibre, low/high glycaemic index (GI)], timing of consumption and the protein/fats consumed at the same time, thus elucidating the impact across studies can be difficult[35]. Indeed, recommendations on calorie intake vary, with studies examining a broad range from 1500 to 2800 kcal/d showing positive pregnancy outcomes[36]. Some guidelines do recommend moderate calorie restriction (1600-1800 kcal/d) for overweight or obese women with GDM to improve glycaemic control and limit gestational weight gain[29]. Currently, it is generally recommended that carbohydrate intake should be indivi-dualised with respect to amount and type of carbohydrate, according to ongoing assessment of nutrition and glycaemic management[37].

Different dietary interventions with varying carbohydrate compositions have been proposed for GDM management. GI is a relative ranking of food items (on a scale of 0-100), based on how quickly blood glucose levels increase after ingestion of a standard quantity of the particular food[38]. The GI is unchanged by pregnancy[39]. Low GI diets for women with GDM have been associated with reductions in the proportion of women requiring insulin and in neonatal birthweight in randomised control trials (RCTs)[37]. Meanwhile, a systematic review and meta-analysis of RCTs assessing different types of dietary interventions on maternal glycaemic control and birthweight in pregnancies with GDM concluded that on pooled analysis, dietary interventions demonstrated favourable effects compared with control diets[40]. This included improved maternal glycaemic control from baseline (fasting and post-prandial glucose levels), lower birthweight and less macrosomia (although similar LGA risk). While the quality of the evidence was graded as low, it does indicate nutritional guidance can play an important role in GDM management and there is potential for improvement in outcomes with firmer evidence to guide recommen-dations.

A concern about the attention on reducing carbohydrate intake is the possibility that it may lead to a proportional increase in dietary fat intake. The impact of this on pregnancy outcomes is unclear, although it may be associated with worsening of insulin resistance[34]. There has been limited specific investigation of maternal dietary lipid management during pregnancy[35]. A study involving women without GDM found a high fat maternal diet was associated with increased neonatal adiposity[41]. Meanwhile, a pilot study (n = 12) of women with diet-controlled GDM found a low fat/higher-complex carbohydrate diet was associated with lower insulin resistance of adipose tissue, compared with a higher fat/low-carbohydrate diet, although the birthweights of the two groups were not significantly different[42]. Furthermore, a high monounsaturated fatty acid diet compared with a high carbohydrate diet in GDM pregnancies showed there was better insulin sensitivity in the latter group, although the overall glucose control was similar between the groups[43]. There was no difference in birthweights, but the high monounsaturated fatty acid diet was associated with lower diastolic blood pressure. Moreover, a small study (n = 10) assessing the effect of the fat composition in a test meal on glycaemic parameters in women with GDM found that saturated fats were associated with significantly lower post-prandial glucose and insulin levels compared to monounsaturated fatty acids[44]. Hence, while there is a suggestion that dietary fats may influence metabolism in GDM, much more research is needed to properly assess this. Further evaluation of potential treatment options targeting maternal dyslipidaemia is also needed[45].

Furthermore, gestational weight gain is a related important consideration, with higher gestational weight gain associated with both GDM and LGA[41]. There are no specific guidelines for gestational weight gain in women with GDM, but since maternal overweight and obesity are also risk factors for adverse outcomes including GDM and LGA, the Institute of Medicine recommendations for appropriate gesta-tional weight gain are different according to pre-pregnancy BMI[46,47]. For women with obesity (BMI ≥ 30 kg/m2), 5-9 kg weight gain is recommended, compared to 11.5-16 kg for normal weight women (BMI 18.5-24.9 kg/m2). The importance of obesity in pregnancy is also highlighted by research demonstrating a synergistic relationship between obesity and GDM in increasing the risk of adverse pregnancy outcomes[48]. Meanwhile, although numerous diet and/or lifestyle interventions aiming to promote appropriate gestational weight gain have been reported, the results have overall been mixed, with only modest effectiveness demonstrated[49].

Finally, while many gaps remain in the current state of knowledge, techno-logical advancements are likely to be a key driver of developments in this space. Indeed, contributions from fields such as metabolomics are already shedding light on the mechanisms underlying GDM[50]. Analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy have been employed to investigate metabolic profiles associated with GDM and hence determine the pathways leading to insulin resistance[50]. Lipid and amino acid molecules have been most consistently identified by these processes thus far[51]. Importantly, such research is enabling identification of potential therapeutic targets, which in turn may involve dietary intervention. However, given the metabolic heterogeneity within pregnancy, personalisation of interventions will be important[52].

CONCLUSION

The relationships between GDM and LGA raise the possibility of shared mechanisms. Central components include abnormal carbohydrate and lipid metabolism, with insulin resistance recognised as a key instigating factor. While both glycaemic and lipid biomarkers have been associated with LGA, their utility for prediction in clinical practice is yet to be determined. Dietary modification is the cornerstone of GDM treatment, but there is insufficient data, particularly in the area of dietary lipids, to form definitive evidenced-based dietary recommendations. Hence there remains great need for rigorous studies investigating the impact of specific dietary interventions on pregnancy outcomes in women with GDM.

Footnotes

Manuscript source: Unsolicited manuscript

Specialty type: Endocrinology and metabolism

Country of origin: Australia

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References
1.  American Diabetes Association. Gestational diabetes mellitus. Diabetes Care. 2003;26 Suppl 1:S103-S105.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 275]  [Cited by in F6Publishing: 269]  [Article Influence: 12.8]  [Reference Citation Analysis (0)]
2.  Moses RG, Wong VC, Lambert K, Morris GJ, San Gil F. The prevalence of hyperglycaemia in pregnancy in Australia. Aust N Z J Obstet Gynaecol. 2016;56:341-345.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 33]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
3.  Stone CA, McLachlan KA, Halliday JL, Wein P, Tippett C. Gestational diabetes in Victoria in 1996: incidence, risk factors and outcomes. Med J Aust. 2002;177:486-491.  [PubMed]  [DOI]  [Cited in This Article: ]
4.  Walsh JM, McAuliffe FM. Prediction and prevention of the macrosomic fetus. Eur J Obstet Gynecol Reprod Biol. 2012;162:125-130.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 79]  [Cited by in F6Publishing: 70]  [Article Influence: 5.8]  [Reference Citation Analysis (0)]
5.  Rodrigo N, Glastras SJ. The Emerging Role of Biomarkers in the Diagnosis of Gestational Diabetes Mellitus. J Clin Med. 2018;7.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 42]  [Cited by in F6Publishing: 31]  [Article Influence: 5.2]  [Reference Citation Analysis (0)]
6.  Landon MB, Catalano PM, Gabbe SG, Obsterics: Normal and Problem Pregnancies. Diabetes Mellitus Complicating Pregnancy. Obsterics: Normal and Problem Pregnancies. 7th ed. Philadelphia, PA: Elsevier 2017; 862-898.  [PubMed]  [DOI]  [Cited in This Article: ]
7.  Knopp RH. Hormone-mediated changes in nutrient metabolism in pregnancy: a physiological basis for normal fetal development. Ann N Y Acad Sci. 1997;817:251-271.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 26]  [Cited by in F6Publishing: 26]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
8.  Fasshauer M, Blüher M, Stumvoll M. Adipokines in gestational diabetes. Lancet Diabetes Endocrinol. 2014;2:488-499.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 143]  [Cited by in F6Publishing: 153]  [Article Influence: 15.3]  [Reference Citation Analysis (0)]
9.  Butte NF. Carbohydrate and lipid metabolism in pregnancy: normal compared with gestational diabetes mellitus. Am J Clin Nutr. 2000;71:1256S-1261S.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 482]  [Cited by in F6Publishing: 476]  [Article Influence: 19.8]  [Reference Citation Analysis (0)]
10.  Langer O. Fetal macrosomia: etiologic factors. Clin Obstet Gynecol. 2000;43:283-297.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 110]  [Cited by in F6Publishing: 101]  [Article Influence: 4.2]  [Reference Citation Analysis (0)]
11.  Pedersen J. The pregnant diabetic and her newborn: problems and management. 2nd ed. Williams & Wilkins, 1977. .  [PubMed]  [DOI]  [Cited in This Article: ]
12.  Catalano PM, Hauguel-De Mouzon S. Is it time to revisit the Pedersen hypothesis in the face of the obesity epidemic? Am J Obstet Gynecol. 2011;204:479-487.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 236]  [Cited by in F6Publishing: 230]  [Article Influence: 17.7]  [Reference Citation Analysis (0)]
13.  HAPO Study Cooperative Research Group. Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, Coustan DR, Hadden DR, McCance DR, Hod M, McIntyre HD, Oats JJ, Persson B, Rogers MS, Sacks DA. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med. 2008;358:1991-2002.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3783]  [Cited by in F6Publishing: 3541]  [Article Influence: 221.3]  [Reference Citation Analysis (0)]
14.  Nahavandi S, Seah JM, Shub A, Houlihan C, Ekinci EI. Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes. Front Endocrinol (Lausanne). 2018;9:407.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 28]  [Cited by in F6Publishing: 32]  [Article Influence: 5.3]  [Reference Citation Analysis (0)]
15.  Herrera E, Ortega-Senovilla H. Disturbances in lipid metabolism in diabetic pregnancy - Are these the cause of the problem? Best Pract Res Clin Endocrinol Metab. 2010;24:515-525.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 163]  [Cited by in F6Publishing: 156]  [Article Influence: 11.1]  [Reference Citation Analysis (0)]
16.  Wiznitzer A, Mayer A, Novack V, Sheiner E, Gilutz H, Malhotra A, Novack L. Association of lipid levels during gestation with preeclampsia and gestational diabetes mellitus: a population-based study. Am J Obstet Gynecol. 2009;201:482.e1-482.e8.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 134]  [Cited by in F6Publishing: 160]  [Article Influence: 10.7]  [Reference Citation Analysis (0)]
17.  Barbour LA, Hernandez TL. Maternal Lipids and Fetal Overgrowth: Making Fat from Fat. Clin Ther. 2018;40:1638-1647.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 71]  [Cited by in F6Publishing: 78]  [Article Influence: 13.0]  [Reference Citation Analysis (0)]
18.  Ryckman KK, Spracklen CN, Smith CJ, Robinson JG, Saftlas AF. Maternal lipid levels during pregnancy and gestational diabetes: a systematic review and meta-analysis. BJOG. 2015;122:643-651.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 191]  [Cited by in F6Publishing: 244]  [Article Influence: 27.1]  [Reference Citation Analysis (0)]
19.  Barbour LA, Hernandez TL. Maternal Non-glycemic Contributors to Fetal Growth in Obesity and Gestational Diabetes: Spotlight on Lipids. Curr Diab Rep. 2018;18:37.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 44]  [Cited by in F6Publishing: 44]  [Article Influence: 7.3]  [Reference Citation Analysis (0)]
20.  Herrera E, Ortega-Senovilla H. Implications of Lipids in Neonatal Body Weight and Fat Mass in Gestational Diabetic Mothers and Non-Diabetic Controls. Curr Diab Rep. 2018;18:7.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 36]  [Cited by in F6Publishing: 38]  [Article Influence: 6.3]  [Reference Citation Analysis (0)]
21.  Wang J, Moore D, Subramanian A, Cheng KK, Toulis KA, Qiu X, Saravanan P, Price MJ, Nirantharakumar K. Gestational dyslipidaemia and adverse birthweight outcomes: a systematic review and meta-analysis. Obes Rev. 2018;19:1256-1268.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 53]  [Cited by in F6Publishing: 58]  [Article Influence: 9.7]  [Reference Citation Analysis (0)]
22.  Schaefer-Graf UM, Graf K, Kulbacka I, Kjos SL, Dudenhausen J, Vetter K, Herrera E. Maternal lipids as strong determinants of fetal environment and growth in pregnancies with gestational diabetes mellitus. Diabetes Care. 2008;31:1858-1863.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 317]  [Cited by in F6Publishing: 302]  [Article Influence: 18.9]  [Reference Citation Analysis (0)]
23.  Jin WY, Lin SL, Hou RL, Chen XY, Han T, Jin Y, Tang L, Zhu ZW, Zhao ZY. Associations between maternal lipid profile and pregnancy complications and perinatal outcomes: a population-based study from China. BMC Pregnancy Childbirth. 2016;16:60.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 132]  [Cited by in F6Publishing: 158]  [Article Influence: 19.8]  [Reference Citation Analysis (0)]
24.  Schaefer-Graf UM, Meitzner K, Ortega-Senovilla H, Graf K, Vetter K, Abou-Dakn M, Herrera E. Differences in the implications of maternal lipids on fetal metabolism and growth between gestational diabetes mellitus and control pregnancies. Diabet Med. 2011;28:1053-1059.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 82]  [Cited by in F6Publishing: 89]  [Article Influence: 6.8]  [Reference Citation Analysis (0)]
25.  Krstevska B, Velkoska Nakova V, Adamova G, Simeonova S, Dimitrovski Ch, Livrinova V, Serafimoski V. Association between foetal growth and different maternal metabolic characteristics in women with gestational diabetes mellitus. Prilozi. 2009;30:103-114.  [PubMed]  [DOI]  [Cited in This Article: ]
26.  Barrett HL, Dekker Nitert M, D'Emden M, McIntyre HD, Callaway LK. Validation of a triglyceride meter for use in pregnancy. BMC Res Notes. 2014;7:679.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 6]  [Article Influence: 0.6]  [Reference Citation Analysis (0)]
27.  Lu L, Koulman A, Petry CJ, Jenkins B, Matthews L, Hughes IA, Acerini CL, Ong KK, Dunger DB. An Unbiased Lipidomics Approach Identifies Early Second Trimester Lipids Predictive of Maternal Glycemic Traits and Gestational Diabetes Mellitus. Diabetes Care. 2016;39:2232-2239.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 53]  [Cited by in F6Publishing: 52]  [Article Influence: 6.5]  [Reference Citation Analysis (0)]
28.  Pinto J, Almeida LM, Martins AS, Duarte D, Barros AS, Galhano E, Pita C, Almeida Mdo C, Carreira IM, Gil AM. Prediction of Gestational Diabetes through NMR Metabolomics of Maternal Blood. J Proteome Res. 2015;14:2696-2706.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 53]  [Cited by in F6Publishing: 55]  [Article Influence: 6.1]  [Reference Citation Analysis (0)]
29.  Kumru P, Arisoy R, Erdogdu E, Demirci O, Kavrut M, Ardıc C, Aslaner N, Ozkoral A, Ertekin A. Prediction of gestational diabetes mellitus at first trimester in low-risk pregnancies. Taiwan J Obstet Gynecol. 2016;55:815-820.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 25]  [Cited by in F6Publishing: 24]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
30.  Wang D, Xu S, Chen H, Zhong L, Wang Z. The associations between triglyceride to high-density lipoprotein cholesterol ratios and the risks of gestational diabetes mellitus and large-for-gestational-age infant. Clin Endocrinol (Oxf). 2015;83:490-497.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 30]  [Cited by in F6Publishing: 38]  [Article Influence: 4.2]  [Reference Citation Analysis (0)]
31.  dos Santos-Weiss IC, Réa RR, Fadel-Picheth CM, Rego FG, Pedrosa Fde O, Gillery P, Souza EM, Picheth G. The plasma logarithm of the triglyceride/HDL-cholesterol ratio is a predictor of low risk gestational diabetes in early pregnancy. Clin Chim Acta. 2013;418:1-4.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 28]  [Cited by in F6Publishing: 31]  [Article Influence: 2.6]  [Reference Citation Analysis (0)]
32.  Savvidou M, Nelson SM, Makgoba M, Messow CM, Sattar N, Nicolaides K. First-trimester prediction of gestational diabetes mellitus: examining the potential of combining maternal characteristics and laboratory measures. Diabetes. 2010;59:3017-3022.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 120]  [Cited by in F6Publishing: 123]  [Article Influence: 8.8]  [Reference Citation Analysis (0)]
33.  Hod M, Kapur A, Sacks DA, Hadar E, Agarwal M, Di Renzo GC, Roura LC, McIntyre HD, Morris JL, Divakar H. The International Federation of Gynecology and Obstetrics (FIGO) Initiative on gestational diabetes mellitus: A pragmatic guide for diagnosis, management, and care<sup/>. Int J Gynaecol Obstet. 2015;131 Suppl 3:S173-S211.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 419]  [Cited by in F6Publishing: 520]  [Article Influence: 57.8]  [Reference Citation Analysis (0)]
34.  Duarte-Gardea MO, Gonzales-Pacheco DM, Reader DM, Thomas AM, Wang SR, Gregory RP, Piemonte TA, Thompson KL, Moloney L. Academy of Nutrition and Dietetics Gestational Diabetes Evidence-Based Nutrition Practice Guideline. J Acad Nutr Diet. 2018;118:1719-1742.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 40]  [Cited by in F6Publishing: 46]  [Article Influence: 7.7]  [Reference Citation Analysis (0)]
35.  Hernandez TL, Anderson MA, Chartier-Logan C, Friedman JE, Barbour LA. Strategies in the nutritional management of gestational diabetes. Clin Obstet Gynecol. 2013;56:803-815.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 34]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
36.  Gunderson EP. Gestational diabetes and nutritional recommendations. Curr Diab Rep. 2004;4:377-386.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 45]  [Cited by in F6Publishing: 26]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
37.  Viana LV, Gross JL, Azevedo MJ. Dietary intervention in patients with gestational diabetes mellitus: a systematic review and meta-analysis of randomized clinical trials on maternal and newborn outcomes. Diabetes Care. 2014;37:3345-3355.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 120]  [Cited by in F6Publishing: 110]  [Article Influence: 11.0]  [Reference Citation Analysis (0)]
38.  Blumer I, Hadar E, Hadden DR, Jovanovič L, Mestman JH, Murad MH, Yogev Y. Diabetes and pregnancy: an endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2013;98:4227-4249.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 398]  [Cited by in F6Publishing: 332]  [Article Influence: 30.2]  [Reference Citation Analysis (0)]
39.  Jenkins DJ, Wolever TM, Taylor RH, Barker H, Fielden H, Baldwin JM, Bowling AC, Newman HC, Jenkins AL, Goff DV. Glycemic index of foods: a physiological basis for carbohydrate exchange. Am J Clin Nutr. 1981;34:362-366.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2243]  [Cited by in F6Publishing: 1948]  [Article Influence: 45.3]  [Reference Citation Analysis (0)]
40.  Yamamoto JM, Kellett JE, Balsells M, García-Patterson A, Hadar E, Solà I, Gich I, van der Beek EM, Castañeda-Gutiérrez E, Heinonen S, Hod M, Laitinen K, Olsen SF, Poston L, Rueda R, Rust P, van Lieshout L, Schelkle B, Murphy HR, Corcoy R. Gestational Diabetes Mellitus and Diet: A Systematic Review and Meta-analysis of Randomized Controlled Trials Examining the Impact of Modified Dietary Interventions on Maternal Glucose Control and Neonatal Birth Weight. Diabetes Care. 2018;41:1346-1361.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 123]  [Cited by in F6Publishing: 143]  [Article Influence: 23.8]  [Reference Citation Analysis (0)]
41.  Barrett HL, Dekker Nitert M, McIntyre HD, Callaway LK. Normalizing metabolism in diabetic pregnancy: is it time to target lipids? Diabetes Care. 2014;37:1484-1493.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 97]  [Cited by in F6Publishing: 99]  [Article Influence: 9.9]  [Reference Citation Analysis (0)]
42.  Shapiro ALB, Ringham BM, Glueck DH, Norris JM, Barbour LA, Friedman JE, Dabelea D. Infant Adiposity is Independently Associated with a Maternal High Fat Diet but not Related to Niacin Intake: The Healthy Start Study. Matern Child Health J. 2017;21:1662-1668.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 9]  [Article Influence: 1.5]  [Reference Citation Analysis (0)]
43.  Hernandez TL, Van Pelt RE, Anderson MA, Reece MS, Reynolds RM, de la Houssaye BA, Heerwagen M, Donahoo WT, Daniels LJ, Chartier-Logan C, Janssen RC, Friedman JE, Barbour LA. Women With Gestational Diabetes Mellitus Randomized to a Higher-Complex Carbohydrate/Low-Fat Diet Manifest Lower Adipose Tissue Insulin Resistance, Inflammation, Glucose, and Free Fatty Acids: A Pilot Study. Diabetes Care. 2016;39:39-42.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 102]  [Cited by in F6Publishing: 105]  [Article Influence: 13.1]  [Reference Citation Analysis (0)]
44.  Lauszus FF, Rasmussen OW, Henriksen JE, Klebe JG, Jensen L, Lauszus KS, Hermansen K. Effect of a high monounsaturated fatty acid diet on blood pressure and glucose metabolism in women with gestational diabetes mellitus. Eur J Clin Nutr. 2001;55:436-443.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 34]  [Cited by in F6Publishing: 35]  [Article Influence: 1.5]  [Reference Citation Analysis (0)]
45.  Ilic S, Jovanovic L, Pettitt DJ. Comparison of the effect of saturated and monounsaturated fat on postprandial plasma glucose and insulin concentration in women with gestational diabetes mellitus. Am J Perinatol. 1999;16:489-495.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 21]  [Cited by in F6Publishing: 19]  [Article Influence: 0.8]  [Reference Citation Analysis (0)]
46.  Hedderson MM, Gunderson EP, Ferrara A. Gestational weight gain and risk of gestational diabetes mellitus. Obstet Gynecol. 2010;115:597-604.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 378]  [Cited by in F6Publishing: 384]  [Article Influence: 27.4]  [Reference Citation Analysis (0)]
47.  Siega-Riz AM, Viswanathan M, Moos MK, Deierlein A, Mumford S, Knaack J, Thieda P, Lux LJ, Lohr KN. A systematic review of outcomes of maternal weight gain according to the Institute of Medicine recommendations: birthweight, fetal growth, and postpartum weight retention. Am J Obstet Gynecol. 2009;201:339.e1-339.14.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 375]  [Cited by in F6Publishing: 402]  [Article Influence: 26.8]  [Reference Citation Analysis (0)]
48.  Institute of Medicine (US) and National Research Council (US) Committee to Reexamine IOM Pregnancy Weight Guidelines, Rasmussen KM, Yaktine AL.  2009.  [PubMed]  [DOI]  [Cited in This Article: ]
49.  Catalano PM, McIntyre HD, Cruickshank JK, McCance DR, Dyer AR, Metzger BE, Lowe LP, Trimble ER, Coustan DR, Hadden DR, Persson B, Hod M, Oats JJ; HAPO Study Cooperative Research Group. The hyperglycemia and adverse pregnancy outcome study: associations of GDM and obesity with pregnancy outcomes. Diabetes Care. 2012;35:780-786.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 701]  [Cited by in F6Publishing: 661]  [Article Influence: 55.1]  [Reference Citation Analysis (0)]
50.  Barbour LA. Metabolic Culprits in Obese Pregnancies and Gestational Diabetes Mellitus: Big Babies, Big Twists, Big Picture: The 2018 Norbert Freinkel Award Lecture. Diabetes Care. 2019;42:718-726.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 31]  [Article Influence: 6.2]  [Reference Citation Analysis (0)]
51.  Huynh J, Xiong G, Bentley-Lewis R. A systematic review of metabolite profiling in gestational diabetes mellitus. Diabetologia. 2014;57:2453-2464.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 72]  [Cited by in F6Publishing: 73]  [Article Influence: 7.3]  [Reference Citation Analysis (0)]
52.  Scholtens DM, Muehlbauer MJ, Daya NR, Stevens RD, Dyer AR, Lowe LP, Metzger BE, Newgard CB, Bain JR, Lowe WL; HAPO Study Cooperative Research Group. Metabolomics reveals broad-scale metabolic perturbations in hyperglycemic mothers during pregnancy. Diabetes Care. 2014;37:158-166.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 81]  [Cited by in F6Publishing: 84]  [Article Influence: 8.4]  [Reference Citation Analysis (0)]