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Tranidou A, Siargkas A, Magriplis E, Tsakiridis I, Apostolopoulou A, Chourdakis M, Dagklis T. Relationship Between Amino Acid Intake in Maternal Diet and Risk of Gestational Diabetes Mellitus: Results from the BORN 2020 Pregnant Cohort in Northern Greece. Nutrients 2025; 17:173. [PMID: 39796608 PMCID: PMC11723356 DOI: 10.3390/nu17010173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2024] [Revised: 12/30/2024] [Accepted: 12/31/2024] [Indexed: 01/13/2025] Open
Abstract
Background/Objectives: Maternal amino acid intake and its biological value may influence glucose regulation and insulin sensitivity, impacting the risk of developing gestational diabetes mellitus (GDM). This study aimed to evaluate the association between amino acid intake from maternal diet before and during pregnancy and the risk of GDM. Methods: This study is part of the ongoing BORN2020 epidemiological Greek cohort. A validated semi-quantitative Food Frequency Questionnaire (FFQ) was used. Amino acid intakes were quantified from the FFQ responses. A multinomial logistic regression model, with adjustments made for maternal characteristics, lifestyle habits, and pregnancy-specific factors, was used. Results: A total of 797 pregnant women were recruited, of which 14.7% developed GDM. Higher cysteine intake during pregnancy was associated with an increase in GDM risk (adjusted odds ratio [aOR]: 5.75; 95% confidence interval [CI]: 1.42-23.46), corresponding to a 476% increase in risk. Additionally, higher intakes of aspartic acid (aOR: 1.32; 95% CI: 1.05-1.66), isoleucine (aOR: 1.48; 95% CI: 1.03-2.14), phenylalanine (aOR: 1.6; 95% CI: 1.04-2.45), and threonine (aOR: 1.56; 95% CI: 1.0-2.43) during pregnancy were also associated with increased GDM risk. Furthermore, total essential amino acid (EAA) (aOR: 1.04; 95% CI: 1.0-1.09) and non-essential amino acid (NEAA) (aOR: 1.05; 95% CI: 1.0-1.1) intakes during pregnancy were also linked to an increased risk of GDM. A secondary dose-response analysis affected by timing of assessment revealed that higher intake levels of specific amino acids showed a more pronounced risk. Conclusions: Optimizing the balance of certain amino acids during pregnancy may guide personalized nutritional interventions to mitigate GDM risk.
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Affiliation(s)
- Antigoni Tranidou
- 3rd Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (A.T.); (A.S.); (I.T.); (A.A.)
- Laboratory of Hygiene, Social & Preventive Medicine and Medical Statistics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece;
| | - Antonios Siargkas
- 3rd Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (A.T.); (A.S.); (I.T.); (A.A.)
- Laboratory of Hygiene, Social & Preventive Medicine and Medical Statistics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece;
| | - Emmanuela Magriplis
- Department of Food Science and Human Nutrition, Agricultural University of Athens, Iera Oos 75, 118 55 Athens, Greece;
| | - Ioannis Tsakiridis
- 3rd Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (A.T.); (A.S.); (I.T.); (A.A.)
| | - Aikaterini Apostolopoulou
- 3rd Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (A.T.); (A.S.); (I.T.); (A.A.)
- Laboratory of Hygiene, Social & Preventive Medicine and Medical Statistics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece;
| | - Michail Chourdakis
- Laboratory of Hygiene, Social & Preventive Medicine and Medical Statistics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece;
| | - Themistoklis Dagklis
- 3rd Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (A.T.); (A.S.); (I.T.); (A.A.)
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Zhou J, Yu J, Ren J, Ren Y, Zeng Y, Wu Y, Zhang Q, Xiao X. Association of maternal blood metabolomics and gestational diabetes mellitus risk: a systematic review and meta-analysis. Rev Endocr Metab Disord 2024:10.1007/s11154-024-09934-5. [PMID: 39602052 DOI: 10.1007/s11154-024-09934-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/13/2024] [Indexed: 11/29/2024]
Abstract
Gestational diabetes mellitus (GDM) is a common complication of pregnancy that has short- and long-term adverse effects. Therefore, further exploration of the pathophysiology of GDM and related biomarkers is important. In this study, we performed a systematic review and meta-analysis to investigate the associations between metabolites in blood detected via metabolomics techniques and the risk of GDM and to identify possible biomarkers for predicting the occurrence of GDM. We retrieved case‒control and cohort studies of metabolomics and GDM published in PubMed, Embase, and Web of Science through March 29, 2024; extracted metabolite concentrations, odds ratios (ORs), or relative risks (RRs); and evaluated the integrated results with metabolites per-SD risk estimates and 95% CIs for GDM. We estimated the results via the random effects model and the inverse variance method. Our study is registered in PROSPERO (CRD42024539435). We included a total of 28 case‒control and cohort studies, including 17,370 subjects (4,372 GDM patients and 12,998 non-GDM subjects), and meta-analyzed 67 metabolites. Twenty-five of these metabolites were associated with GDM risk. Some amino acids (isoleucine, leucine, valine, alanine, aspartate, etc.), lipids (C16:0, C18:1n-9, C18:1n-7, lysophosphatidylcholine (LPC) (16:0), LPC (18:0), and palmitoylcarnitine), and carbohydrates and energy metabolites (glucose, pyruvate, lactate, 2-hydroxybutyrate, 3-hydroxybutyrate) were discovered to be associated with increased GDM risk (hazard ratio 1.06-2.77). Glutamine, histidine, C14:0, and sphingomyelin (SM) (34:1) were associated with lower GDM risk (hazard ratio 0.75-0.84). These findings suggest that these metabolites may play essential roles in GDM progression, and serve as biomarkers, contributing to the early diagnosis and prediction of GDM.
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Grants
- 81870545, 81870579, 82170854, 81570715, 81170736 National Natural Science Foundation of China
- 7202163 the Beijing Natural Science Foundation
- Z201100005520011 the Beijing Municipal Science and Technology Commission
- 2017YFC1309603, 2021YFC2501700, 2016YFA0101002, 2018YFC2001100 the National Key Research and Development Program of China
- 2019DCT-M-05 the Scientific Activities Foundation for Selected Returned Overseas Professionals of Human Resources and Social Security Ministry, Beijing Dongcheng District Outstanding Talent Funding Project
- 2017PT31036, 2018PT31021 the Medical Epigenetics Research Center, Chinese Academy of Medical Sciences
- 2023PT32010, 2017PT32020, 2018PT32001 the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences
- CIFMS2017-I2M-1-008, CIFMS2021-I2M-1-002 the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences
- 2022-PUMCH-C-019 National High Level Hospital Clinical Research Funding
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Affiliation(s)
- Jing Zhou
- Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Diabetes Research Center of Chinese Academy of Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Jie Yu
- Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Diabetes Research Center of Chinese Academy of Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Jing Ren
- Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Diabetes Research Center of Chinese Academy of Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yaolin Ren
- Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Diabetes Research Center of Chinese Academy of Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yuan Zeng
- Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Diabetes Research Center of Chinese Academy of Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yifan Wu
- Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Diabetes Research Center of Chinese Academy of Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Qian Zhang
- Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Diabetes Research Center of Chinese Academy of Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Xinhua Xiao
- Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Diabetes Research Center of Chinese Academy of Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100730, China.
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Masalin S, Klåvus A, Rönö K, Koistinen HA, Koistinen V, Kärkkäinen O, Jääskeläinen TJ, Klemetti MM. Analysis of early-pregnancy metabolome in early- and late-onset gestational diabetes reveals distinct associations with maternal overweight. Diabetologia 2024; 67:2539-2554. [PMID: 39083240 PMCID: PMC11519293 DOI: 10.1007/s00125-024-06237-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 05/10/2024] [Indexed: 10/29/2024]
Abstract
AIMS/HYPOTHESIS It is not known whether the early-pregnancy metabolome differs in patients with early- vs late-onset gestational diabetes mellitus (GDM) stratified by maternal overweight. The aims of this study were to analyse correlations between early-pregnancy metabolites and maternal glycaemic and anthropometric characteristics, and to identify early-pregnancy metabolomic alterations that characterise lean women (BMI <25 kg/m2) and women with overweight (BMI ≥25 kg/m2) with early-onset GDM (E-GDM) or late-onset GDM (L-GDM). METHODS We performed a nested case-control study within the population-based prospective Early Diagnosis of Diabetes in Pregnancy cohort, comprising 210 participants with GDM (126 early-onset, 84 late-onset) and 209 normoglycaemic control participants matched according to maternal age, BMI class and primiparity. Maternal weight, height and waist circumference were measured at 8-14 weeks' gestation. A 2 h 75 g OGTT was performed at 12-16 weeks' gestation (OGTT1), and women with normal results underwent repeat testing at 24-28 weeks' gestation (OGTT2). Comprehensive metabolomic profiling of fasting serum samples, collected at OGTT1, was performed by untargeted ultra-HPLC-MS. Linear models were applied to study correlations between early-pregnancy metabolites and maternal glucose concentrations during OGTT1, fasting insulin, HOMA-IR, BMI and waist circumference. Early-pregnancy metabolomic features for GDM subtypes (participants stratified by maternal overweight and gestational timepoint at GDM onset) were studied using linear and multivariate models. The false discovery rate was controlled using the Benjamini-Hochberg method. RESULTS In the total cohort (n=419), the clearest correlation patterns were observed between (1) maternal glucose concentrations and long-chain fatty acids and medium- and long-chain acylcarnitines; (2) maternal BMI and/or waist circumference and long-chain fatty acids, medium- and long-chain acylcarnitines, phospholipids, and aromatic and branched-chain amino acids; and (3) HOMA-IR and/or fasting insulin and L-tyrosine, certain long-chain fatty acids and phospholipids (q<0.001). Univariate analyses of GDM subtypes revealed significant differences (q<0.05) for seven non-glucose metabolites only in overweight women with E-GDM compared with control participants: linolenic acid, oleic acid, docosapentaenoic acid, docosatetraenoic acid and lysophosphatidylcholine 20:4/0:0 abundances were higher, whereas levels of specific phosphatidylcholines (P-16:0/18:2 and 15:0/18:2) were lower. However, multivariate analyses exploring the early-pregnancy metabolome of GDM subtypes showed differential clustering of acylcarnitines and long-chain fatty acids between normal-weight and overweight women with E- and L-GDM. CONCLUSIONS/INTERPRETATION GDM subtypes show distinct early-pregnancy metabolomic features that correlate with maternal glycaemic and anthropometric characteristics. The patterns identified suggest early-pregnancy disturbances of maternal lipid metabolism, with most alterations observed in overweight women with E-GDM. Our findings highlight the importance of maternal adiposity as the primary target for prevention and treatment.
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Affiliation(s)
- Senja Masalin
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Obstetrics and Gynecology, South Karelia Central Hospital, Lappeenranta, Finland.
- Department of General Practice and Primary Healthcare, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
| | | | - Kristiina Rönö
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Obstetrics and Gynecology, South Karelia Central Hospital, Lappeenranta, Finland
| | - Heikki A Koistinen
- Department of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | | | - Olli Kärkkäinen
- Afekta Technologies Ltd, Kuopio, Finland
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Tiina J Jääskeläinen
- Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland
- Department of Food and Nutrition, University of Helsinki, Helsinki, Finland
| | - Miira M Klemetti
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Obstetrics and Gynecology, South Karelia Central Hospital, Lappeenranta, Finland.
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Jiang Y, Sun T, Jiang Y, Wang X, Xi Q, Dou Y, Lv H, Peng Y, Xiao S, Xu X, Liu C, Xu B, Han X, Ma H, Hu Z, Shi Z, Du J, Lin Y. Titanium exposure and gestational diabetes mellitus: associations and potential mediation by perturbation of amino acids in early pregnancy. Environ Health 2024; 23:84. [PMID: 39394610 PMCID: PMC11470715 DOI: 10.1186/s12940-024-01128-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2024] [Accepted: 10/02/2024] [Indexed: 10/13/2024]
Abstract
BACKGROUND Several recent studies reported the potential adverse effects of titanium exposure on glucose homeostasis among the non-pregnant population, but the association of titanium exposure with gestational diabetes mellitus (GDM) is scarce. METHODS The present study of 1,449 pregnant women was conducted within the Jiangsu Birth Cohort (JBC) study in China. Urine samples were collected in the early pregnancy, and urinary titanium concentration and non-targeted metabolomics were measured. Poisson regression estimated the association of titanium exposure in the early pregnancy with subsequent risk of GDM. Multiple linear regression screened for titanium-related urine metabolites. Mediation analyses assessed the mediating effects of candidate metabolites and pathways. RESULTS As parameterized in tertiles, titanium showed positive dose-response relationship with GDM risk (P for trend = 0.008), with women at the highest tertile of titanium exposure having 30% increased risk of GDM [relative risk (RR) = 1.30 (95% CI: 1.06, 1.61)] when compared to those exposure at the first tertile level. Meanwhile, we identified the titanium-related metabolites involved in four amino acid metabolic pathways. Notably, the perturbation of the aminoacyl-tRNA biosynthesis and alanine, aspartate and glutamate metabolism mediated 27.1% and 31.0%, respectively, of the relative effect of titanium exposure on GDM. Specifically, three titanium-related metabolites, choline, creatine and L-alanine, demonstrated predominant mediation effects on the association between titanium exposure and GDM risk. CONCLUSIONS In this prospective study, we uniquely identified a correlation between early pregnancy titanium exposure and increased GDM risk. We unveiled novel insights into how perturbations in amino acid metabolism may mediate the link between titanium exposure and GDM. Notably, choline, creatine, and L-alanine emerged as key mediators influencing this association. Our findings imply that elevated titanium exposure in early pregnancy can lead to amino acid dysmetabolism, thereby elevating GDM risk.
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Affiliation(s)
- Yangqian Jiang
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Maternal, Child and Adolescent Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Tianyu Sun
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Yue Jiang
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Xiaoyan Wang
- Department of Obstetrics, Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Nanjing Medical University, Jiangsu, 215002, China
| | - Qi Xi
- Department of Obstetrics, Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Nanjing Medical University, Jiangsu, 215002, China
| | - Yuanyan Dou
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Hong Lv
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- State Key Laboratory of Reproductive Medicine and Offspring Health (Suzhou Centre), Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Nanjing Medical University, Suzhou, Jiangsu, 215002, China
| | - Yuting Peng
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Maternal, Child and Adolescent Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Shuxin Xiao
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Maternal, Child and Adolescent Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Xin Xu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Maternal, Child and Adolescent Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Cong Liu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Bo Xu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Xiumei Han
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Hongxia Ma
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- State Key Laboratory of Reproductive Medicine and Offspring Health (Suzhou Centre), Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Nanjing Medical University, Suzhou, Jiangsu, 215002, China
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
- State Key Laboratory of Reproductive Medicine and Offspring Health (Suzhou Centre), Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Nanjing Medical University, Suzhou, Jiangsu, 215002, China
| | - Zhonghua Shi
- Department of Obstetrics and Gynecology, Changzhou Maternity and Child Health Care Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, 213000, China.
| | - Jiangbo Du
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China.
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China.
- State Key Laboratory of Reproductive Medicine and Offspring Health (Suzhou Centre), Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Nanjing Medical University, Suzhou, Jiangsu, 215002, China.
| | - Yuan Lin
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China.
- Department of Maternal, Child and Adolescent Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China.
- State Key Laboratory of Reproductive Medicine and Offspring Health (Suzhou Centre), Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Nanjing Medical University, Suzhou, Jiangsu, 215002, China.
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Cui L, Li Z, Liu X, Li Z, Li J, Guo Y, Zhou H, Yang X, Zhang Z, Gao Y, Ren L, Hua L. Association between serum branched chain amino acids, mammalian target of rapamycin levels and the risk of gestational diabetes mellitus: a 1:1 matched case control study. BMC Pregnancy Childbirth 2024; 24:633. [PMID: 39358711 PMCID: PMC11446021 DOI: 10.1186/s12884-024-06815-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 09/10/2024] [Indexed: 10/04/2024] Open
Abstract
BACKGROUND To investigate the association between serum branched chain amino acids (BCAAs), mammalian target of rapamycin (mTOR) levels and the risk of gestational diabetes mellitus (GDM) in pregnant women. METHODS 1:1 matched case-control study was conducted including 66 GDM patients and 66 matched healthy pregnant women (± 3 years) in 2019, in China. Fasting bloods of pregnant women were collected in pregnancy at 24 ~ 28 weeks gestation. And the serum levels of valine (Val), leucine (Leu), isoleucine (Ile) and mTOR were determined. Conditional logistic regressions models were used to estimate the associations of BCAAs and mTOR concentrations with the risk of GDM. RESULTS Concentrations of serum Val and mTOR in cases were significantly higher than that in controls (P < 0.05). After adjusted for the confounded factors, both the second tertile and the third tertile of mTOR increased the risk of GDM (OR = 11.771, 95%CI: 3.949-35.083; OR = 4.869 95%CI: 1.742-13.611, respectively) compared to the first tertile of mTOR. However, the second tertile of serum Val (OR = 0.377, 95%CI:0.149-0.954) and the second tertile of serum Leu (OR = 0.322, 95%CI: 0.129-0.811) decreased the risk of GDM compared to the first tertile of serum Val and Leu, respectively. The restricted cubic spline indicated a significant nonlinear association between the serum levels of mTOR and the risk of GDM (P values for non-linearity = 0.0058). CONCLUSION We confirmed the association of higher mTOR with the increased risk of GDM in pregnant women. Pregnant women who were in the certain range level of Val and Leu were at lower risk of GDM. Our findings provided epidemiological evidence for the relation of serum BCAAs and mTOR with risk of GDM.
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Affiliation(s)
- Lingling Cui
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Zhiqian Li
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Xinxin Liu
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Zhonglei Li
- Department of Nutrition, Huaihe Hospital of Henan University, Kaifeng, Henan, 475000, China
| | - Jiaxin Li
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Yingying Guo
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Huijun Zhou
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Xiaoli Yang
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Zhengya Zhang
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Yuting Gao
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Lina Ren
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Linlin Hua
- Department of Advanced Medical Research, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450001, China.
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Wu H, Wang Q, Chen Y, Chen D. The association between circulating phenylalanine and the temporal risk of impaired insulin markers in gestational diabetes mellitus. Mol Genet Metab Rep 2024; 40:101090. [PMID: 38974841 PMCID: PMC11227027 DOI: 10.1016/j.ymgmr.2024.101090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 05/01/2024] [Accepted: 05/02/2024] [Indexed: 07/09/2024] Open
Abstract
Background We aimed to contrast plasma amino acid concentrations in pregnant women with Gestational Diabetes Mellitus (GDM) to those without, to analyze the link between plasma amino acid concentrations, GDM, insulin resistance, and insulin secretion at 24-28 weeks of gestation. Methods The research employed a retrospective case-control study design at a single center. Basic demographic and laboratory data were procured from the hospital's case system. The study encompassed seventy women without gestational diabetes mellitus (GDM) and thirty-five women with GDM matched in a 1-to-2 ratio for age and pre-pregnancy BMI. Utilizing high-performance liquid chromatography-mass spectrometry (HPLC-MS), peripheral fasting plasma amino acid concentrations in these women, during mid-pregnancy, were duly measured. We carefully evaluated the significant differences in the quantitative data between the two groups and developed linear regression models to assess the independent risk factors affecting insulin resistance and insulin secretion. Results Significant variations in insulin secretion and resistance levels distinguished GDM Group from the non-GDM group at three distinct time points, alongside relatively elevated serum Glycosylated Hemoglobin (HbA1c) levels. Triglycerides (TG) were also significantly increased in those with GDM during adipocytokine observations. Apart from glutamic acid and glutamine, the concentrations of the remaining 16 amino acids were notably increased in GDM patients, including all branched chain amino acids(BCAAs) and aromatic amino acids(AAAs). Ultimately, it was ascertained that fasting serum phenylalanine levels were independent risk factors affecting insulin resistance index and insulin secretion at various phases. Conclusions Various fasting serum amino acid levels are markedly increased in patients with GDM, specifically phenylalanine, which may play role in insulin resistance and secretion.
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Affiliation(s)
- Hao Wu
- Department of Obstetrics Central Laboratory, Women's Hospital School of Medicine Zhejiang University, China
| | - Qiong Wang
- Department of Maternity Inpatient, Women's Hospital School of Medicine Zhejiang University, China
| | - Yanmin Chen
- Department of Maternity Inpatient, Women's Hospital School of Medicine Zhejiang University, China
| | - Danqing Chen
- Department of Maternity Inpatient, Women's Hospital School of Medicine Zhejiang University, China
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Lai M, Li J, Yang J, Zhang Q, Gong Y, Ma Y, Fang F, Li N, Zhai Y, Shen T, Peng Y, Liu J, Wang Y. Metabolomic profiling reveals decreased serum cysteine levels during gestational diabetes mellitus progression. J Mol Cell Biol 2024; 16:mjae010. [PMID: 38429982 PMCID: PMC11418039 DOI: 10.1093/jmcb/mjae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 08/31/2023] [Accepted: 02/29/2024] [Indexed: 03/03/2024] Open
Abstract
Gestational diabetes mellitus (GDM) is a pregnancy-related metabolic disorder associated with short-term and long-term adverse health outcomes, but its pathogenesis has not been clearly elucidated. Investigations of the dynamic changes in metabolomic markers in different trimesters may reveal the underlying pathophysiology of GDM progression. Therefore, in the present study, we analysed the metabolic profiles of 75 women with GDM and 75 women with normal glucose tolerance throughout the three trimesters. We found that the variation trends of 38 metabolites were significantly changed during GDM development. Specifically, longitudinal analyses revealed that cysteine (Cys) levels significantly decreased over the course of GDM progression. Further study showed that Cys alleviated GDM in female mice at gestational day 14.5, possibly by inhibiting phosphoenolpyruvate carboxykinase to suppress hepatic gluconeogenesis. Taken together, these findings suggest that the Cys metabolism pathway might play a crucial role in GDM and Cys supplementation represents a potential new treatment strategy for GDM patients.
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Affiliation(s)
- Mengyu Lai
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Jiaomeng Li
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Jiaying Yang
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Qingli Zhang
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Yujia Gong
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Yuhang Ma
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Fang Fang
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Na Li
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Yingxiang Zhai
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
- School of Pharmacy, Henan University, Kaifeng 475004, China
| | - Tingting Shen
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Yongde Peng
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Jia Liu
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310058, China
| | - Yufan Wang
- Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
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Li N, Leng J, Zhang R, Wang H, Li W, Zhang S, Qiao Y, Li J, Yu Z, Hu G, Fang Z, Yang X. Maternal serum branched-chain amino acids in early pregnancy and offspring growth patterns from 1 year to 8 years of age. Chin Med J (Engl) 2024; 137:1876-1878. [PMID: 38404121 DOI: 10.1097/cm9.0000000000002967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Indexed: 02/27/2024] Open
Affiliation(s)
- Ninghua Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Junhong Leng
- Project Office, Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Rui Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Hui Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Weiqin Li
- Project Office, Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Shuang Zhang
- Project Office, Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Yijuan Qiao
- Project Office, Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Jing Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin 300070, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Zhijie Yu
- Population Cancer Research Program and Department of Pediatrics, Dalhousie University, 15000, Halifax, Canada
| | - Gang Hu
- Chronic Disease Epidemiology Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA
| | - Zhongze Fang
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin 300070, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Xilin Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin 300070, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
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Yu J, Ren J, Ren Y, Wu Y, Zeng Y, Zhang Q, Xiao X. Using metabolomics and proteomics to identify the potential urine biomarkers for prediction and diagnosis of gestational diabetes. EBioMedicine 2024; 101:105008. [PMID: 38368766 PMCID: PMC10882130 DOI: 10.1016/j.ebiom.2024.105008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/22/2024] [Accepted: 01/30/2024] [Indexed: 02/20/2024] Open
Abstract
Gestational diabetes mellitus (GDM) is one of the most common metabolic complications during pregnancy, threatening both maternal and fetal health. Prediction and diagnosis of GDM is not unified. Finding effective biomarkers for GDM is particularly important for achieving early prediction, accurate diagnosis and timely intervention. Urine, due to its accessibility in large quantities, noninvasive collection and easy preparation, has become a good sample for biomarker identification. In recent years, a number of studies using metabolomics and proteomics approaches have identified differential expressed urine metabolites and proteins in GDM patients. In this review, we summarized these potential urine biomarkers for GDM prediction and diagnosis and elucidated their role in development of GDM.
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Affiliation(s)
- Jie Yu
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Jing Ren
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yaolin Ren
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yifan Wu
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yuan Zeng
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Qian Zhang
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Xinhua Xiao
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China.
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Li N, Li J, Wang H, Qiao Y, Li W, Gao M, Liu E, Yu Z, Hu G, Fang Z, Leng J, Yang X. Serum Sulfur-Containing Amino Acids and Risk of Maternal Gestational Diabetes and Adverse Growth Patterns in Offspring. Nutrients 2023; 15:4089. [PMID: 37764871 PMCID: PMC10537007 DOI: 10.3390/nu15184089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/15/2023] [Accepted: 09/20/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND To estimate associations of sulfur-containing amino acids (SAAs) in the early trimester of pregnancy and gestational diabetes mellitus (GDM) and estimate associations of maternal SAAs with adverse growth patterns in offspring. METHODS We established a 1:1 matched case-control study (n = 486) from our cohort of pregnant women, and 401 children were followed up at ages 1 to 8 years. We conducted binary conditional logistic regression to estimate the risk associations of serum SAAs with GDM. Multinomial logistic regression was implemented to explore associations of maternal SAAs with adverse growth patterns in the offspring. RESULTS High serum methionine and cystine were independently associated with increased GDM risk (OR: 1.92, 95%CI: 1.18-3.13 and 2.69, 1.59-4.53). Conversely, a low level of serum taurine was independently associated with increased GDM risk (2.61, 1.64-4.16). Maternal high cystine and low taurine were also associated with an increased risk of persistent obesity growth pattern (POGP) in offspring (OR: 2.79, 95%CI: 1.09-7.17 and 3.92, 1.11-13.89) and the effect was largely independent of GDM. CONCLUSIONS High serum methionine, cystine and low serum taurine in the early trimester of pregnancy were associated with a greatly increased risk of GDM. Maternal high cystine and low taurine were associated with elevated risk of offspring POGP, largely independent of GDM.
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Affiliation(s)
- Ninghua Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China; (N.L.); (J.L.); (H.W.); (M.G.)
| | - Jing Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China; (N.L.); (J.L.); (H.W.); (M.G.)
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin 300070, China;
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Hui Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China; (N.L.); (J.L.); (H.W.); (M.G.)
| | - Yijuan Qiao
- Project Office, Tianjin Women and Children’s Health Center, Tianjin 300070, China; (Y.Q.); (W.L.); (E.L.)
| | - Weiqin Li
- Project Office, Tianjin Women and Children’s Health Center, Tianjin 300070, China; (Y.Q.); (W.L.); (E.L.)
| | - Ming Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China; (N.L.); (J.L.); (H.W.); (M.G.)
| | - Enqing Liu
- Project Office, Tianjin Women and Children’s Health Center, Tianjin 300070, China; (Y.Q.); (W.L.); (E.L.)
| | - Zhijie Yu
- Population Cancer Research Program and Department of Pediatrics, Dalhousie University, Halifax, NS 15000, Canada;
| | - Gang Hu
- Chronic Disease Epidemiology Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA;
| | - Zhongze Fang
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin 300070, China;
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Junhong Leng
- Project Office, Tianjin Women and Children’s Health Center, Tianjin 300070, China; (Y.Q.); (W.L.); (E.L.)
| | - Xilin Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China; (N.L.); (J.L.); (H.W.); (M.G.)
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin 300070, China;
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
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Li N, Li J, Wang H, Liu J, Li W, Yang K, Huo X, Leng J, Yu Z, Hu G, Fang Z, Yang X. Aromatic Amino Acids and Their Interactions with Gut Microbiota-Related Metabolites for Risk of Gestational Diabetes: A Prospective Nested Case-Control Study in a Chinese Cohort. ANNALS OF NUTRITION & METABOLISM 2023; 79:291-300. [PMID: 37339616 DOI: 10.1159/000531481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 06/05/2023] [Indexed: 06/22/2023]
Abstract
INTRODUCTION The aim of this study was to explore associations of aromatic amino acids (AAA) in early pregnancy with gestational diabetes mellitus (GDM), and whether high AAA and gut microbiota-related metabolites had interactive effects on GDM risk. METHODS We conducted a 1:1 case-control study (n = 486) nested in a prospective cohort of pregnant women from 2010 to 2012. According to the International Association of Diabetes and Pregnancy Study Group's criteria, 243 women were diagnosed with GDM. Binary conditional logistic regression was performed to examine associations of AAA with GDM risk. Interactions between AAA and gut microbiota-related metabolites for GDM were examined using additive interaction measures. RESULTS High phenylalanine and tryptophan were associated with increased GDM risk (OR: 1.72, 95% CI: 1.07-2.78 and 1.66, 1.02-2.71). The presence of high trimethylamine (TMA) markedly increased the OR of high phenylalanine alone up to 7.95 (2.79-22.71), while the presence of low glycoursodeoxycholic acid (GUDCA) markedly increased the OR of high tryptophan alone up to 22.88 (5.28-99.26), both with significant additive interactions. Furthermore, high lysophosphatidylcholines (LPC18:0) mediated both interactive effects. CONCLUSIONS High phenylalanine may have an additive interaction with high TMA, while high tryptophan may have an additive interaction with low GUDCA toward increased risk of GDM, both being mediated via LPC18:0.
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Affiliation(s)
- Ninghua Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Jing Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
| | - Hui Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Jinnan Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Weiqin Li
- Project Office, Tianjin Women and Children's Health Center, Tianjin, China
| | - Kai Yang
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xiaoxu Huo
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
| | - Junhong Leng
- Project Office, Tianjin Women and Children's Health Center, Tianjin, China
| | - Zhijie Yu
- Population Cancer Research Program and Department of Pediatrics, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Gang Hu
- Chronic Disease Epidemiology Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
| | - Zhongze Fang
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xilin Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
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Yang J, Wu J, Tekola-Ayele F, Li LJ, Bremer AA, Lu R, Rahman ML, Weir NL, Pang WW, Chen Z, Tsai MY, Zhang C. Plasma Amino Acids in Early Pregnancy and Midpregnancy and Their Interplay With Phospholipid Fatty Acids in Association With the Risk of Gestational Diabetes Mellitus: Results From a Longitudinal Prospective Cohort. Diabetes Care 2023; 46:722-732. [PMID: 36701229 PMCID: PMC10090921 DOI: 10.2337/dc22-1892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 12/29/2022] [Indexed: 01/27/2023]
Abstract
OBJECTIVE We prospectively evaluated plasma amino acids (AAs) in early pregnancy and midpregnancy and their interplay with phospholipid fatty acids (FAs) in association with gestational diabetes mellitus (GDM) risk. RESEARCH DESIGN AND METHODS From a longitudinal pregnancy cohort of 2,802 individuals, concentrations of 24 plasma AAs at 10-14 and 15-26 gestational weeks (GW) were assessed among 107 GDM case subjects and 214 non-GDM control subjects. We estimated adjusted odds ratios (OR) and 95% CI for the associations of plasma AAs and the joint associations of plasma AAs and phospholipid FAs with GDM risk, adjusting for risk factors including age, prepregnancy BMI, and family history of diabetes. RESULTS Glycine at 10-14 GW was inversely associated with GDM (adjusted OR [95% CI] per SD increment: 0.55 [0.39-0.79]). Alanine, aspartic acid, and glutamic acid at 10-14 GW were positively associated with GDM (1.43 [1.08-1.88], 1.41 [1.11-1.80], and 1.39 [0.98-1.98]). At 15-26 GW, findings for glycine, alanine, aspartic acid, and the glutamine-to-glutamic acid ratio were consistent with the directions observed at 10-14 GW. Isoleucine, phenylalanine, and tyrosine were positively associated with GDM (1.64 [1.19-2.27], 1.15 [0.87-1.53], and 1.56 [1.16-2.09]). All P values for linear trend were <0.05. Several AAs and phospholipid FAs were significantly and jointly associated with GDM. For instance, the lowest risk was observed among women with higher glycine and lower even-chain saturated FAs at 10-14 GW (adjusted OR [95% CI] 0.15 [0.06, 0.37]). CONCLUSIONS Plasma AAs may be implicated in GDM development starting in early pregnancy. Associations of AAs with GDM may be enhanced in the copresence of phospholipid FA profile.
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Affiliation(s)
- Jiaxi Yang
- Global Centre for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jing Wu
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Fasil Tekola-Ayele
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Ling-Jun Li
- Global Centre for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Andrew A. Bremer
- Division of Extramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Ruijin Lu
- Division of Biostatistics, School of Medicine, Washington University in St. Louis, St. Louis, MO
| | - Mohammad L. Rahman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD
| | - Natalie L. Weir
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Wei Wei Pang
- Global Centre for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Zhen Chen
- Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Cuilin Zhang
- Global Centre for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
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Ademolu AB. Branched Chain Amino Acids and Gestational Diabetes Mellitus. J Clin Endocrinol Metab 2022; 107:e4322-e4323. [PMID: 35994362 DOI: 10.1210/clinem/dgac481] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Indexed: 11/19/2022]
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Gadgil MD, Ingram KH, Appiah D, Rudd J, Whitaker KM, Bennett WL, Shikany JM, Jacobs DR, Lewis CE, Gunderson EP. Prepregnancy Protein Source and BCAA Intake Are Associated with Gestational Diabetes Mellitus in the CARDIA Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph192114142. [PMID: 36361016 PMCID: PMC9658365 DOI: 10.3390/ijerph192114142] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 10/22/2022] [Accepted: 10/26/2022] [Indexed: 06/03/2023]
Abstract
Diet quality and protein source are associated with type 2 diabetes, however relationships with GDM are less clear. This study aimed to determine whether prepregnancy diet quality and protein source are associated with gestational diabetes mellitus (GDM). Participants were 1314 Black and White women without diabetes, who had at least one birth during 25 years of follow-up in the Coronary Artery Risk Development in Young Adults (CARDIA) cohort study. The CARDIA A Priori Diet Quality Score (APDQS) was assessed in the overall cohort at enrollment and again at Year 7. Protein source and branched-chain amino acid (BCAA) intake were assessed only at the Year 7 exam (n = 565). Logistic regression analysis was used to determine associations between prepregnancy dietary factors and GDM. Women who developed GDM (n = 161) were more likely to have prepregnancy obesity and a family history of diabetes (p < 0.05). GDM was not associated with prepregnancy diet quality at enrollment (Year 0) (odds ratio [OR]: 1.01; 95% confidence interval [CI] 0.99, 1.02) or Year 7 (odds ratio [OR]: 0.97; 95% confidence interval [CI] 0.94, 1.00) in an adjusted model. Conversely, BCAA intake (OR:1.59, 95% CI 1.03, 2.43) and animal protein intake (OR: 1.06, 95% CI 1.02, 1.10) as a proportion of total protein intake, were associated with increased odds of GDM, while proportion of plant protein was associated with decreased odds of GDM (OR: 0.95, 95% CI 0.91, 0.99). In conclusion, GDM is strongly associated with source of prepregnancy dietary protein intake but not APDQS in the CARDIA study.
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Affiliation(s)
- Meghana D. Gadgil
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, CA 94143, USA
| | - Katherine H. Ingram
- Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA 30144, USA
| | - Duke Appiah
- Department of Public Health, Texas Tech University Health Sciences Center of Statistics and Analytical Sciences, Lubbock, TX 79409, USA
| | - Jessica Rudd
- Department of Statistics and Analytical Sciences, Kennesaw State University, Kennesaw, GA 30144, USA
| | - Kara M. Whitaker
- Department of Health and Human Physiology, Department of Epidemiology, University of Iowa, Iowa City, IA 52242, USA
| | - Wendy L. Bennett
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - James M. Shikany
- Division of Preventive Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - David R. Jacobs
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Cora E. Lewis
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Erica P. Gunderson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
- Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA 91101, USA
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