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Lee K, Kuang A, Bain JR, Hayes MG, Muehlbauer MJ, Ilkayeva OR, Newgard CB, Powe CE, Hivert MF, Scholtens DM, Lowe WL. Metabolomic and genetic architecture of gestational diabetes subtypes. Diabetologia 2024; 67:895-907. [PMID: 38367033 DOI: 10.1007/s00125-024-06110-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: 08/14/2023] [Accepted: 01/12/2024] [Indexed: 02/19/2024]
Abstract
AIMS/HYPOTHESIS Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes. METHODS This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM). RESULTS Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM. CONCLUSIONS/INTERPRETATION This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.
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Affiliation(s)
- Kristen Lee
- Department of Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Alan Kuang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - James R Bain
- Duke Molecular Physiology Institute, Durham, NC, USA
- Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC, USA
| | - M Geoffrey Hayes
- Department of Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - Olga R Ilkayeva
- Duke Molecular Physiology Institute, Durham, NC, USA
- Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC, USA
| | - Christopher B Newgard
- Duke Molecular Physiology Institute, Durham, NC, USA
- Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC, USA
| | - Camille E Powe
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Marie-France Hivert
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Denise M Scholtens
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - William L Lowe
- Department of Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
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Elliott A, Walters RK, Pirinen M, Kurki M, Junna N, Goldstein JI, Reeve MP, Siirtola H, Lemmelä SM, Turley P, Lahtela E, Mehtonen J, Reis K, Elnahas AG, Reigo A, Palta P, Esko T, Mägi R, Palotie A, Daly MJ, Widén E. Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes. Nat Genet 2024; 56:377-382. [PMID: 38182742 PMCID: PMC10937370 DOI: 10.1038/s41588-023-01607-4] [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: 03/04/2023] [Accepted: 11/07/2023] [Indexed: 01/07/2024]
Abstract
Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting more than 16 million pregnancies annually worldwide1,2. GDM is related to an increased lifetime risk of type 2 diabetes (T2D)1-3, with over a third of women developing T2D within 15 years of their GDM diagnosis. The diseases are hypothesized to share a genetic predisposition1-7, but few studies have sought to uncover the genetic underpinnings of GDM. Most studies have evaluated the impact of T2D loci only8-10, and the three prior genome-wide association studies of GDM11-13 have identified only five loci, limiting the power to assess to what extent variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen study and identified 13 GDM-associated loci, including nine new loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into the following two distinct categories: one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis and placental expression.
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Grants
- R00 AG062787 NIA NIH HHS
- R01 MH101244 NIMH NIH HHS
- A.E. was a research Scholar supported by Sarnoff Cardiovascular Research Foundation
- U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- Academy of Finland (Suomen Akatemia)
- U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
- The FinnGen project is funded by two grants from Business Finland (HUS 4685/31/2016 and UH 4386/31/2016) and by eleven industry partners (AbbVie Inc, AstraZeneca UK Ltd, Biogen MA Inc, Celgene Corporation, Celgene International II Sàrl, Genentech Inc, Merck Sharp & Dohme Corp, Pfizer Inc., GlaxoSmithKline, Sanofi, Maze Therapeutics Inc., Janssen Biotech Inc).
- EstBB GWAS analysis is supported by research funding from the Estonian Research Council: Team grant PRG1291 and PRG1911.
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Affiliation(s)
- Amanda Elliott
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Raymond K Walters
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Mitja Kurki
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Nella Junna
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Jacqueline I Goldstein
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Mary Pat Reeve
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Harri Siirtola
- TAUCHI Research Center, Faculty of Information Technology and Communication Sciences (ITC), Tampere University, Tampere, Finland
| | - Susanna M Lemmelä
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Patrick Turley
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
- Department of Economics, University of Southern California, Los Angeles, CA, USA
| | - Elisa Lahtela
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Juha Mehtonen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Kadri Reis
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Anu Reigo
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Priit Palta
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Reedik Mägi
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Aarno Palotie
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland.
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland.
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 175] [Impact Index Per Article: 175.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Hughes ZH, Hughes LM, Khan SS. Genetic contributions to risk of adverse pregnancy outcomes. CURRENT CARDIOVASCULAR RISK REPORTS 2023; 17:185-193. [PMID: 38186860 PMCID: PMC10768680 DOI: 10.1007/s12170-023-00729-y] [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] [Accepted: 09/01/2023] [Indexed: 01/09/2024]
Abstract
Purpose of Review Adverse pregnancy outcomes (APOs), including hypertensive disorders of pregnancy (HDP), low birthweight (LBW), and preterm birth (PTB), along with peripartum cardiomyopathy (PPCM) are associated with short- and long-term maternal and fetal cardiovascular risks. This review focuses on the genetic contributions to the risk of APOs and PPCM. Recent Findings The expansion of genome-wide association studies (GWAS) has led to better understanding of the biologic mechanisms underpinning APO, PPCM, and the predisposition to cardiovascular disease across the life course. Genetic loci known to be involved with the risk of hypertension (FTO, ZNF831) have been associated with the development of overall HDP and preeclampsia. Additionally, four loci significantly associated with type 2 diabetes have been associated with GDM (CDKAL1, MTNR1B, TCF7L2, CDK2NA-CDKN2B). Variants in loci known to affect genes coding for proteins involved in immune cell function and placental health (EBF1, EEFSEC, AGTR2, 2q13) have been implicated in the development of PTB and future cardiovascular risks for both the mother and the offspring. Genetic similarities in rare variants between PPCM and dilated cardiomyopathy have been described suggesting shared pathophysiologic origins as well as predisposition for future risk of heart failure, highlighting the need for the development PPCM genetic counseling guidelines. Summary Genetics may inform mechanisms, risk, and counseling for individuals after an APO or PPCM. Through recent advances in genetic techniques and analytic approaches, new insights into the underlying biologic mechanisms and genetic variants leading to these risks have been discovered.
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Affiliation(s)
- Zachary H. Hughes
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, UA
| | - Lydia M. Hughes
- Department of Obstetrics & Gynecology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, UA
| | - Sadiya S. Khan
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
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5
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Lai S, Yan D, Xu J, Yu X, Guo J, Fang X, Tang M, Zhang R, Zhang H, Jia W, Luo M, Hu C. Genetic variants in epoxyeicosatrienoic acid processing and degradation pathways are associated with gestational diabetes mellitus. Nutr J 2023; 22:31. [PMID: 37370090 DOI: 10.1186/s12937-023-00862-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 06/24/2023] [Indexed: 06/29/2023] Open
Abstract
AIM To explore the genetic effects of CYP2C8, CYP2C9, CYP2J2, and EPHX2, the key genes involved in epoxyeicosatrienoic acid processing and degradation pathways in gestational diabetes mellitus (GDM) and metabolic traits in Chinese pregnant women. METHODS A total of 2548 unrelated pregnant women were included, of which 938 had GDM and 1610 were considered as controls. Common variants were genotyped using the Infinium Asian Screening Array. Association studies of single nucleotide polymorphisms (SNPs) with GDM and related traits were performed using logistic regression and multivariable linear regression analyses. A genetic risk score (GRS) model based on 12 independent target SNPs associated with GDM was constructed. Logistic regression was used to estimate odds ratios and 95% confidence intervals, adjusting for potential confounders including age, pre-pregnancy body mass index, history of polycystic ovarian syndrome, history of GDM, and family history of diabetes, with GRS entered both as a continuous variable and categorized groups. The relationship between GRS and quantitative traits was also evaluated. RESULTS The 12 SNPs in CYP2C8, CYP2C9, CYP2J2, and EPHX2 were significantly associated with GDM after adjusting for covariates (all P < 0.05). The GRS generated from these SNPs significantly correlated with GDM. Furthermore, a significant interaction between CYP2J2 and CYP2C8 in GDM (PInteraction = 0.014, ORInteraction= 0.61, 95%CI 0.41-0.90) was observed. CONCLUSION We found significant associations between GDM susceptibility and 12 SNPs of the four genes involved in epoxyeicosatrienoic acid processing and degradation pathways in a Chinese population. Subjects with a higher GRS showed higher GDM susceptibility with higher fasting plasma glucose and area under the curve of glucose and poorer β-cell function.
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Affiliation(s)
- Siyu Lai
- The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Endocrinology and Metabolism, Southern Medical University Affiliated Fengxian Hospital, Shanghai, China
| | - Dandan Yan
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Xu
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiangtian Yu
- Clinical Research Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingyi Guo
- Clinical Research Center, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiangnan Fang
- The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Endocrinology and Metabolism, Southern Medical University Affiliated Fengxian Hospital, Shanghai, China
- Department of Endocrinology, First Affiliated Hospital of Gannan Medical University, Ganzhou, China
| | - Mengyang Tang
- The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Endocrinology and Metabolism, Southern Medical University Affiliated Fengxian Hospital, Shanghai, China
| | - Rong Zhang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hong Zhang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiping Jia
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Mingjuan Luo
- Department of Endocrinology and Metabolism, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China.
| | - Cheng Hu
- The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China.
- Department of Endocrinology and Metabolism, Southern Medical University Affiliated Fengxian Hospital, Shanghai, China.
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Lowe WL. Genetics and Epigenetics: Implications for the Life Course of Gestational Diabetes. Int J Mol Sci 2023; 24:6047. [PMID: 37047019 PMCID: PMC10094577 DOI: 10.3390/ijms24076047] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/19/2023] [Accepted: 03/21/2023] [Indexed: 04/14/2023] Open
Abstract
Gestational diabetes (GDM) is one of the most common complications of pregnancy, affecting as many as one in six pregnancies. It is associated with both short- and long-term adverse outcomes for the mother and fetus and has important implications for the life course of affected women. Advances in genetics and epigenetics have not only provided new insight into the pathophysiology of GDM but have also provided new approaches to identify women at high risk for progression to postpartum cardiometabolic disease. GDM and type 2 diabetes share similarities in their pathophysiology, suggesting that they also share similarities in their genetic architecture. Candidate gene and genome-wide association studies have identified susceptibility genes that are shared between GDM and type 2 diabetes. Despite these similarities, a much greater effect size for MTNR1B in GDM compared to type 2 diabetes and association of HKDC1, which encodes a hexokinase, with GDM but not type 2 diabetes suggest some differences in the genetic architecture of GDM. Genetic risk scores have shown some efficacy in identifying women with a history of GDM who will progress to type 2 diabetes. The association of epigenetic changes, including DNA methylation and circulating microRNAs, with GDM has also been examined. Targeted and epigenome-wide approaches have been used to identify DNA methylation in circulating blood cells collected during early, mid-, and late pregnancy that is associated with GDM. DNA methylation in early pregnancy had some ability to identify women who progressed to GDM, while DNA methylation in blood collected at 26-30 weeks gestation improved upon the ability of clinical factors alone to identify women at risk for progression to abnormal glucose tolerance post-partum. Finally, circulating microRNAs and long non-coding RNAs that are present in early or mid-pregnancy and associated with GDM have been identified. MicroRNAs have also proven efficacious in predicting both the development of GDM as well as its long-term cardiometabolic complications. Studies performed to date have demonstrated the potential for genetic and epigenetic technologies to impact clinical care, although much remains to be done.
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Affiliation(s)
- William L Lowe
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Rubloff 12, 420 E. Superior Street, Chicago, IL 60611, USA
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Grupe K, Scherneck S. Mouse Models of Gestational Diabetes Mellitus and Its Subtypes: Recent Insights and Pitfalls. Int J Mol Sci 2023; 24:ijms24065982. [PMID: 36983056 PMCID: PMC10058162 DOI: 10.3390/ijms24065982] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 03/30/2023] Open
Abstract
Gestational diabetes mellitus (GDM) is currently the most common complication of pregnancy and is defined as a glucose intolerance disorder with recognition during pregnancy. GDM is considered a uniform group of patients in conventional guidelines. In recent years, evidence of the disease's heterogeneity has led to a growing understanding of the value of dividing patients into different subpopulations. Furthermore, in view of the increasing incidence of hyperglycemia outside pregnancy, it is likely that many cases diagnosed as GDM are in fact patients with undiagnosed pre-pregnancy impaired glucose tolerance (IGT). Experimental models contribute significantly to the understanding of the pathogenesis of GDM and numerous animal models have been described in the literature. The aim of this review is to provide an overview of the existing mouse models of GDM, in particular those that have been obtained by genetic manipulation. However, these commonly used models have certain limitations in the study of the pathogenesis of GDM and cannot fully describe the heterogeneous spectrum of this polygenic disease. The polygenic New Zealand obese (NZO) mouse is introduced as a recently emerged model of a subpopulation of GDM. Although this strain lacks conventional GDM, it exhibits prediabetes and an IGT both preconceptionally and during gestation. In addition, it should be emphasized that the choice of an appropriate control strain is of great importance in metabolic studies. The commonly used control strain C57BL/6N, which exhibits IGT during gestation, is discussed in this review as a potential model of GDM.
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Affiliation(s)
- Katharina Grupe
- Institute of Pharmacology, Toxicology and Clinical Pharmacy, Technische Universität Braunschweig, Mendelssohnstraße 1, D-38106 Braunschweig, Germany
| | - Stephan Scherneck
- Institute of Pharmacology, Toxicology and Clinical Pharmacy, Technische Universität Braunschweig, Mendelssohnstraße 1, D-38106 Braunschweig, Germany
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8
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Elliott A, Walters RK, Pirinen M, Kurki M, Junna N, Goldstein J, Reeve M, Siirtola H, Lemmelä S, Turley P, Palotie A, Daly M, Widén E. Distinct and shared genetic architectures of Gestational diabetes mellitus and Type 2 Diabetes Mellitus. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.16.23286014. [PMID: 36865330 PMCID: PMC9980250 DOI: 10.1101/2023.02.16.23286014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
Gestational diabetes mellitus (GDM) affects more than 16 million pregnancies annually worldwide and is related to an increased lifetime risk of Type 2 diabetes (T2D). The diseases are hypothesized to share a genetic predisposition, but there are few GWAS studies of GDM and none of them is sufficiently powered to assess whether any variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen Study and identified 13 GDM-associated loci including 8 novel loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into two distinct categories - one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis, and placental expression. These results pave the way for an improved biological understanding of GDM pathophysiology and its role in the development and course of T2D.
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Affiliation(s)
- A. Elliott
- Analytic and Translational Genetics Unit, Massachusetts Gen. Hosp., Boston, MA
- Stanley Ctr. for Psychiatric Res., Broad Inst. of Harvard and MIT, Cambridge, MA
- Harvard Med. Sch., Boston, MA
| | - R. K. Walters
- Analytic and Translational Genetics Unit, Massachusetts Gen. Hosp., Boston, MA
- Stanley Ctr. for Psychiatric Res., Broad Inst. of Harvard and MIT, Cambridge, MA
- Harvard Med. Sch., Boston, MA
| | - M. Pirinen
- Institute for Molecular Med. Finland, Helsinki Institute of Life Sciences., University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - M. Kurki
- Analytic and Translational Genetics Unit, Massachusetts Gen. Hosp., Boston, MA
- Stanley Ctr. for Psychiatric Res., Broad Inst. of Harvard and MIT, Cambridge, MA
| | - N. Junna
- Institute for Molecular Med. Finland, Helsinki Institute of Life Sciences., University of Helsinki, Helsinki, Finland
| | - J. Goldstein
- Stanley Ctr. for Psychiatric Res., Broad Inst. of Harvard and MIT, Cambridge, MA
| | - M.P. Reeve
- Institute for Molecular Med. Finland, Helsinki Institute of Life Sciences., University of Helsinki, Helsinki, Finland
| | - H. Siirtola
- TAUCHI Research Center, Faculty of Information Technology and Communication Sciences (ITC), Tampere University, Tampere, Finland
| | - S. Lemmelä
- Institute for Molecular Med. Finland, Helsinki Institute of Life Sciences., University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - P. Turley
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
- Department of Economics, University of Southern California, Los Angeles, CA, USA
| | | | - A. Palotie
- Analytic and Translational Genetics Unit, Massachusetts Gen. Hosp., Boston, MA
- Stanley Ctr. for Psychiatric Res., Broad Inst. of Harvard and MIT, Cambridge, MA
- Harvard Med. Sch., Boston, MA
- Institute for Molecular Med. Finland, Helsinki Institute of Life Sciences., University of Helsinki, Helsinki, Finland
| | - M. Daly
- Analytic and Translational Genetics Unit, Massachusetts Gen. Hosp., Boston, MA
- Stanley Ctr. for Psychiatric Res., Broad Inst. of Harvard and MIT, Cambridge, MA
- Harvard Med. Sch., Boston, MA
- Institute for Molecular Med. Finland, Helsinki Institute of Life Sciences., University of Helsinki, Helsinki, Finland
| | - E. Widén
- Institute for Molecular Med. Finland, Helsinki Institute of Life Sciences., University of Helsinki, Helsinki, Finland
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 1399] [Impact Index Per Article: 1399.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Zhang D, Sheng J, Chen L, Cheng D, Cao Y, Su Y, Jiang Y, Liu W, Yu Y, Jia H, He P, Wang L, Xu X. Effects of Dietary Fiber on the Risk of Gestational Diabetes Mellitus in Advanced Maternal Age Women: Study Protocol for a Randomized Controlled Trial. Mol Nutr Food Res 2023; 67:e2200437. [PMID: 36267027 DOI: 10.1002/mnfr.202200437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 10/09/2022] [Indexed: 11/09/2022]
Abstract
SCOPE To investigate whether dietary fiber supplementation may reduce the risk of gestational diabetes mellitus (GDM) in advanced maternal age Chinese women (≥35 years). Secondary outcomes include glucose metabolism, diet change, weight gain, and maternal and neonatal outcomes. METHODS AND RESULTS In a randomized controlled trial, a dietary fiber group (19.56 g day-1 ) or control group (standard prenatal care) was conducted from 20 to 24+6 gestational weeks in advanced maternal age women. Dietary intakes were assessed using a validated 39-item Food Frequency Questionnaire (FFQ). GDM was diagnosed by a 75 g oral glucose tolerance test (OGTT) at 25-28 weeks. After intervention, the incidence of GDM was not significantly different between groups (21.6% vs 12.9%, p = 0.165). The mean increased in carbohydrate intake in the dietary fiber group is significantly lower than in the control group (-0.94 ± 92.12 g vs 32.27 ± 91.81 g, p = 0.032). In addition, the glucose tolerance, weight gain between 20 and 25 weeks, and preterm birth in the intervention group have improved compared to the control group. CONCLUSION Supplementation with dietary fiber during pregnancy among advanced maternal age Chinese women do not lower the incidence of GDM, but improve glucose metabolism, gestational weight gain, and preterm birth.
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Affiliation(s)
- Dongyao Zhang
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Jing Sheng
- Department of Radiology, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China
| | - Li Chen
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Decui Cheng
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Yannan Cao
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Yao Su
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Ying Jiang
- Nursing Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Wenyu Liu
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Yuexin Yu
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Haoyi Jia
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Pengyuan He
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Li Wang
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Xianming Xu
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
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11
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Zhang M, Li Q, Wang KL, Dong Y, Mu YT, Cao YM, Liu J, Li ZH, Cui HL, Liu HY, Hu AQ, Zheng YJ. Lipolysis and gestational diabetes mellitus onset: a case-cohort genome-wide association study in Chinese. J Transl Med 2023; 21:47. [PMID: 36698149 PMCID: PMC9875546 DOI: 10.1186/s12967-023-03902-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 01/17/2023] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Genetic knowledge of gestational diabetes mellitus (GDM) in Chinese women is quite limited. This study aimed to identify the risk factors and mechanism of GDM at the genetic level in a Chinese population. METHODS We conducted a genome-wide association study (GWAS) based on single nucleotide polymorphism (SNP) array genotyping (ASA-CHIA Bead chip, Illumina) and a case-cohort study design. Variants including SNPs, copy number variants (CNVs), and insertions-deletions (InDels) were called from genotyping data. A total of 2232 pregnant women were enrolled in their first/second trimester between February 2018 and December 2020 from Anqing Municipal Hospital in Anhui Province, China. The GWAS included 193 GDM patients and 819 subjects without a diabetes diagnosis, and risk ratios (RRs) and their 95% confidence intervals (CIs) were estimated by a regression-based method conditional on the population structure. The calling and quality control of genotyping data were performed following published guidelines. CNVs were merged into CNV regions (CNVR) to simplify analyses. To interpret the GWAS results, gene mapping and overexpression analyses (ORAs) were further performed to prioritize the candidate genes and related biological mechanisms. RESULTS We identified 14 CNVRs (false discovery rate corrected P values < 0.05) and two suggestively significant SNPs (P value < 0.00001) associated with GDM, and a total of 19 candidate genes were mapped. Ten genes were significantly enriched in gene sets related to lipase (triglyceride lipase and lipoprotein lipase) activity (LIPF, LIPK, LIPN, and LIPJ genes), oxidoreductase activity (TPH1 and TPH2 genes), and cellular components beta-catenin destruction complex (APC and GSK3B genes), Wnt signalosome (APC and GSK3B genes), and lateral element in the Gene Ontology resource (BRCA1 and SYCP2 genes) by two ORA methods (adjusted P values < 0.05). CONCLUSIONS Genes related to lipolysis, redox reaction, and proliferation of islet β-cells are associated with GDM in Chinese women. Energy metabolism, particularly lipolysis, may play an important role in GDM aetiology and pathology, which needs further molecular studies to verify.
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Affiliation(s)
- Miao Zhang
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Qing Li
- Department of Obstetrics and Gynecology, Anqing Municipal Hospital, Anqing, 246003, China
| | - Kai-Lin Wang
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Yao Dong
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Yu-Tong Mu
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Yan-Min Cao
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Jin Liu
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Zi-Heng Li
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Hui-Lu Cui
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Hai-Yan Liu
- Department of Clinical Laboratory, Anqing Municipal Hospital, Anqing, 246003, China.
| | - An-Qun Hu
- Department of Clinical Laboratory, Anqing Municipal Hospital, Anqing, 246003, China.
| | - Ying-Jie Zheng
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China.
- Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University, Shanghai, 200032, China.
- Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China.
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12
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Magkos F, Reeds DN, Mittendorfer B. Evolution of the diagnostic value of "the sugar of the blood": hitting the sweet spot to identify alterations in glucose dynamics. Physiol Rev 2023; 103:7-30. [PMID: 35635320 PMCID: PMC9576168 DOI: 10.1152/physrev.00015.2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 05/23/2022] [Accepted: 05/24/2022] [Indexed: 11/22/2022] Open
Abstract
In this paper, we provide an overview of the evolution of the definition of hyperglycemia during the past century and the alterations in glucose dynamics that cause fasting and postprandial hyperglycemia. We discuss how extensive mechanistic, physiological research into the factors and pathways that regulate the appearance of glucose in the circulation and its uptake and metabolism by tissues and organs has contributed knowledge that has advanced our understanding of different types of hyperglycemia, namely prediabetes and diabetes and their subtypes (impaired fasting plasma glucose, impaired glucose tolerance, combined impaired fasting plasma glucose, impaired glucose tolerance, type 1 diabetes, type 2 diabetes, gestational diabetes mellitus), their relationships with medical complications, and how to prevent and treat hyperglycemia.
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Affiliation(s)
- Faidon Magkos
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg, Denmark
| | - Dominic N Reeds
- Center for Human Nutrition, Washington University School of Medicine, St. Louis, Missouri
| | - Bettina Mittendorfer
- Center for Human Nutrition, Washington University School of Medicine, St. Louis, Missouri
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13
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Lamri A, De Paoli M, De Souza R, Werstuck G, Anand S, Pigeyre M. Insight into genetic, biological, and environmental determinants of sexual-dimorphism in type 2 diabetes and glucose-related traits. Front Cardiovasc Med 2022; 9:964743. [PMID: 36505380 PMCID: PMC9729955 DOI: 10.3389/fcvm.2022.964743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 10/21/2022] [Indexed: 11/25/2022] Open
Abstract
There is growing evidence that sex and gender differences play an important role in risk and pathophysiology of type 2 diabetes (T2D). Men develop T2D earlier than women, even though there is more obesity in young women than men. This difference in T2D prevalence is attenuated after the menopause. However, not all women are equally protected against T2D before the menopause, and gestational diabetes represents an important risk factor for future T2D. Biological mechanisms underlying sex and gender differences on T2D physiopathology are not yet fully understood. Sex hormones affect behavior and biological changes, and can have implications on lifestyle; thus, both sex-specific environmental and biological risk factors interact within a complex network to explain the differences in T2D risk and physiopathology in men and women. In addition, lifetime hormone fluctuations and body changes due to reproductive factors are generally more dramatic in women than men (ovarian cycle, pregnancy, and menopause). Progress in genetic studies and rodent models have significantly advanced our understanding of the biological pathways involved in the physiopathology of T2D. However, evidence of the sex-specific effects on genetic factors involved in T2D is still limited, and this gap of knowledge is even more important when investigating sex-specific differences during the life course. In this narrative review, we will focus on the current state of knowledge on the sex-specific effects of genetic factors associated with T2D over a lifetime, as well as the biological effects of these different hormonal stages on T2D risk. We will also discuss how biological insights from rodent models complement the genetic insights into the sex-dimorphism effects on T2D. Finally, we will suggest future directions to cover the knowledge gaps.
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Affiliation(s)
- Amel Lamri
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Population Health Research Institute (PHRI), Hamilton, ON, Canada
| | - Monica De Paoli
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Thrombosis and Atherosclerosis Research Institute (TaARI), Hamilton, ON, Canada
| | - Russell De Souza
- Population Health Research Institute (PHRI), Hamilton, ON, Canada,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Geoff Werstuck
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Thrombosis and Atherosclerosis Research Institute (TaARI), Hamilton, ON, Canada
| | - Sonia Anand
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Population Health Research Institute (PHRI), Hamilton, ON, Canada,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Marie Pigeyre
- Department of Medicine, McMaster University, Hamilton, ON, Canada,Population Health Research Institute (PHRI), Hamilton, ON, Canada,*Correspondence: Marie Pigeyre
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14
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Jääskeläinen T, Klemetti MM. Genetic Risk Factors and Gene-Lifestyle Interactions in Gestational Diabetes. Nutrients 2022; 14:nu14224799. [PMID: 36432486 PMCID: PMC9694797 DOI: 10.3390/nu14224799] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 11/08/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022] Open
Abstract
Paralleling the increasing trends of maternal obesity, gestational diabetes (GDM) has become a global health challenge with significant public health repercussions. In addition to short-term adverse outcomes, such as hypertensive pregnancy disorders and fetal macrosomia, in the long term, GDM results in excess cardiometabolic morbidity in both the mother and child. Recent data suggest that women with GDM are characterized by notable phenotypic and genotypic heterogeneity and that frequencies of adverse obstetric and perinatal outcomes are different between physiologic GDM subtypes. However, as of yet, GDM treatment protocols do not differentiate between these subtypes. Mapping the genetic architecture of GDM, as well as accurate phenotypic and genotypic definitions of GDM, could potentially help in the individualization of GDM treatment and assessment of long-term prognoses. In this narrative review, we outline recent studies exploring genetic risk factors of GDM and later type 2 diabetes (T2D) in women with prior GDM. Further, we discuss the current evidence on gene-lifestyle interactions in the development of these diseases. In addition, we point out specific research gaps that still need to be addressed to better understand the complex genetic and metabolic crosstalk within the mother-placenta-fetus triad that contributes to hyperglycemia in pregnancy.
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Affiliation(s)
- Tiina Jääskeläinen
- Department of Food and Nutrition, University of Helsinki, P.O. Box 66, 00014 Helsinki, Finland
- Department of Medical and Clinical Genetics, University of Helsinki, P.O. Box 63, 00014 Helsinki, Finland
- Correspondence:
| | - Miira M. Klemetti
- Department of Medical and Clinical Genetics, University of Helsinki, P.O. Box 63, 00014 Helsinki, Finland
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, P.O. Box 140, 00029 Helsinki, Finland
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15
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Sparks JR, Ghildayal N, Hivert MF, Redman LM. Lifestyle interventions in pregnancy targeting GDM prevention: looking ahead to precision medicine. Diabetologia 2022; 65:1814-1824. [PMID: 35150287 PMCID: PMC10994387 DOI: 10.1007/s00125-022-05658-w] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/05/2021] [Indexed: 12/12/2022]
Abstract
Gestational diabetes mellitus (GDM) is the most prevalent pregnancy-related endocrinopathy, affecting up to 25% of pregnancies worldwide. Pregnant individuals who develop GDM have an increased risk of complications during pregnancy and birth, as well as future development of type 2 diabetes mellitus and CVD. This increased risk is subsequently passed along to the offspring, perpetuating a cycle of metabolic dysfunction across generations. GDM prevention strategies have had mixed results for many years, but more recent systematic reviews and meta-analyses have suggested potential new avenues of prevention. The objective of this review is to summarise the literature examining the efficacy of lifestyle interventions for the prevention of GDM and to uncover if specific individual-level characteristics influence this outcome. Based on the present literature, we determined that future trials should be designed to understand if initiation of lifestyle intervention in the preconception period is more effective to reduce GDM. Furthermore, trials initiated during pregnancy should be developed through the lens of precision prevention. That is, trials should tailor intervention approaches based on individual-level risk defined by the presence of modifiable and non-modifiable risk factors. Finally, future interventions might also benefit from just-in-time adaptive intervention designs, which allow for interventions to be modified in real-time based on objective assessments of an individual's response.
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Affiliation(s)
- Joshua R Sparks
- Reproductive Endocrinology and Women's Health Laboratory, Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA
| | - Nidhi Ghildayal
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Harvard University, Boston, MA, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Harvard University, Boston, MA, USA.
| | - Leanne M Redman
- Reproductive Endocrinology and Women's Health Laboratory, Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA.
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16
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Wagner A, Schosserer M. The epitranscriptome in ageing and stress resistance: A systematic review. Ageing Res Rev 2022; 81:101700. [PMID: 35908668 DOI: 10.1016/j.arr.2022.101700] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/15/2022] [Accepted: 07/25/2022] [Indexed: 01/31/2023]
Abstract
Modifications of RNA, collectively called the "epitranscriptome", might provide novel biomarkers and innovative targets for interventions in geroscience but are just beginning to be studied in the context of ageing and stress resistance. RNA modifications modulate gene expression by affecting translation initiation and speed, miRNA binding, RNA stability, and RNA degradation. Nonetheless, the precise underlying molecular mechanisms and physiological consequences of most alterations of the epitranscriptome are still only poorly understood. We here systematically review different types of modifications of rRNA, tRNA and mRNA, the methodology to analyze them, current challenges in the field, and human disease associations. Furthermore, we compiled evidence for a connection between individual enzymes, which install RNA modifications, and lifespan in yeast, worm and fly. We also included resistance to different stressors and competitive fitness as search criteria for genes potentially relevant to ageing. Promising candidates identified by this approach include RCM1/NSUN5, RRP8, and F33A8.4/ZCCHC4 that introduce base methylations in rRNA, the methyltransferases DNMT2 and TRM9/ALKBH8, as well as factors involved in the thiolation or A to I editing in tRNA, and finally the m6A machinery for mRNA.
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Affiliation(s)
- Anja Wagner
- Institute of Molecular Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria
| | - Markus Schosserer
- Institute of Molecular Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria; Institute of Medical Genetics, Center for Pathobiochemistry and Genetics, Medical University of Vienna, Vienna, Austria; Austrian Cluster for Tissue Regeneration, Vienna, Austria.
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17
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Wang H, Li J, Liu J, Leng J, Li W, Yu Z, Tam CHT, Hu G, Ma RCW, Fang Z, Wang Y, Yang X. Interactions of CDKAL1 rs7747752 polymorphism and serum levels of L-carnitine and choline are related to increased risk of gestational diabetes mellitus. GENES & NUTRITION 2022; 17:14. [PMID: 36183068 PMCID: PMC9526259 DOI: 10.1186/s12263-022-00716-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 09/20/2022] [Indexed: 11/10/2022]
Abstract
BACKGROUND Interactions between genetic, metabolic, and environmental factors lead to gestational diabetes mellitus (GDM). We aimed to examine interactive effects of cyclin-dependent kinase 5 regulatory subunit-associated protein1-like 1(CDKAL1) rs7747752 polymorphism with low serum levels of L-carnitine, choline, and betaine for GDM. METHODS A nested case-control study of 207 GDM women and their one-to-one, age-matched controls was organized from a prospective cohort of pregnant women in Tianjin, China. Conditional logistic regressions were used to test associations between CDKAL1 rs7747752 and serum levels of L-carnitine, choline, and betaine, and the risk of GDM. Additive interactions were performed to examine interactive effects of rs7747752 and low serum levels of L-carnitine, choline, and betaine on the risk of GDM. RESULTS The CDKAL1 rs7747752 G > C was associated with GDM in additive, dominant, and recessive model (P <0.05). The rs7747752 CC genotype enhanced the OR of L-carnitine ≤ vs. > 150 nmol/mL for GDM from 6.14 (2.61-14.4) to 19.6 (5.65-68.1) and the OR of choline ≤ vs. > 110 nmol/mL from 2.37 (1.07-5.28) to 12.1 (3.22-45.6), with significant additive interactions. Similarly, CG genotype also enhanced the OR of L-carnitine ≤ vs. > 150 nmol/mL for GDM from 4.70 (2.01-11.0) to 11.4 (3.98-32.9), with a significant additive interaction. However, the additive interaction between rs7747752 and betaine ≤ 200 nmol/mL on the risk of GDM was not significant. CONCLUSIONS The CC or CG genotype carriers in rs7747752 of CDKAL1 who have a low serum level of L-carnitine or choline are at a particular high risk of GDM. Randomized controlled trials are warranted to test the effect of supplement of L-carnitine or choline on the risk of GDM in the high-risk group.
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Affiliation(s)
- Hui Wang
- grid.265021.20000 0000 9792 1228Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, 300070 China
| | - Jing Li
- grid.265021.20000 0000 9792 1228Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, 300070 China ,grid.265021.20000 0000 9792 1228Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, 300070 China ,grid.265021.20000 0000 9792 1228Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, 300070 China
| | - Jinnan Liu
- grid.265021.20000 0000 9792 1228Department 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, 300041 China
| | - Weiqin Li
- Project Office, Tianjin Women and Children’s Health Center, Tianjin, 300041 China
| | - Zhijie Yu
- grid.55602.340000 0004 1936 8200Population Cancer Research Program and Department of Pediatrics, Dalhousie University, Halifax, B3H 4R2 Canada
| | - Claudia H. T. Tam
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics and Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, 999077 China
| | - Gang Hu
- grid.250514.70000 0001 2159 6024Chronic Disease Epidemiology Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808 USA
| | - Ronald C. W. Ma
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics and Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, 999077 China
| | - Zhongze Fang
- grid.265021.20000 0000 9792 1228Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, 300070 China ,grid.265021.20000 0000 9792 1228Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, 300070 China ,grid.265021.20000 0000 9792 1228Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin, 300070 China
| | - Ying Wang
- grid.410560.60000 0004 1760 3078Scientific Research Platform of the Second School of Clinical Medicine & Key Laboratory of 3D Printing Technology in Stomatology, Guangdong Medical University, Dongguan, 523808 Guangdong China
| | - Xilin Yang
- grid.265021.20000 0000 9792 1228Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, 300070 China ,grid.265021.20000 0000 9792 1228Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, 300070 China ,grid.265021.20000 0000 9792 1228Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, 300070 China
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18
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Perišić MM, Vladimir K, Karpov S, Štorga M, Mostashari A, Khanin R. Polygenic Risk Score and Risk Factors for Gestational Diabetes. J Pers Med 2022; 12:1381. [PMID: 36143166 PMCID: PMC9505112 DOI: 10.3390/jpm12091381] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/09/2022] [Accepted: 08/18/2022] [Indexed: 02/07/2023] Open
Abstract
Gestational diabetes mellitus (GDM) is a common complication of pregnancy that adversely affects maternal and offspring health. A variety of risk factors, such as BMI and age, have been associated with increased risks of gestational diabetes. However, in many cases, gestational diabetes occurs in healthy nulliparous women with no obvious risk factors. Emerging data suggest that the tendency to develop gestational diabetes has genetic and environmental components. Here we develop a polygenic risk score for GDM and investigate relationships between its genetic architecture and genetically constructed risk factors and biomarkers. Our results demonstrate that the polygenic risk score can be used as an early screening tool that identifies women at higher risk of GDM before its onset allowing comprehensive monitoring and preventative programs to mitigate the risks.
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Affiliation(s)
- Marija Majda Perišić
- Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000 Zagreb, Croatia
- LifeNome Inc., New York, NY 10018, USA
| | - Klemo Vladimir
- LifeNome Inc., New York, NY 10018, USA
- Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia
| | | | - Mario Štorga
- Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000 Zagreb, Croatia
- LifeNome Inc., New York, NY 10018, USA
| | | | - Raya Khanin
- LifeNome Inc., New York, NY 10018, USA
- Bioinformatics Core, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA
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19
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Pagel KA, Chu H, Ramola R, Guerrero RF, Chung JH, Parry S, Reddy UM, Silver RM, Steller JG, Yee LM, Wapner RJ, Hahn MW, Natarajan S, Haas DM, Radivojac P. Association of Genetic Predisposition and Physical Activity With Risk of Gestational Diabetes in Nulliparous Women. JAMA Netw Open 2022; 5:e2229158. [PMID: 36040739 PMCID: PMC9428742 DOI: 10.1001/jamanetworkopen.2022.29158] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 07/11/2022] [Indexed: 11/17/2022] Open
Abstract
Importance Polygenic risk scores (PRS) for type 2 diabetes (T2D) can improve risk prediction for gestational diabetes (GD), yet the strength of the association between genetic and lifestyle risk factors has not been quantified. Objective To assess the association of PRS and physical activity in existing GD risk models and identify patient subgroups who may receive the most benefits from a PRS or physical activity intervention. Design, Settings, and Participants The Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be cohort was established to study individuals without previous pregnancy lasting at least 20 weeks (nulliparous) and to elucidate factors associated with adverse pregnancy outcomes. A subcohort of 3533 participants with European ancestry was used for risk assessment and performance evaluation. Participants were enrolled from October 5, 2010, to December 3, 2013, and underwent genotyping between February 19, 2019, and February 28, 2020. Data were analyzed from September 15, 2020, to November 10, 2021. Exposures Self-reported total physical activity in early pregnancy was quantified as metabolic equivalents of task (METs). Polygenic risk scores were calculated for T2D using contributions of 84 single nucleotide variants, weighted by their association in the Diabetes Genetics Replication and Meta-analysis Consortium data. Main Outcomes and Measures Estimation of the development of GD from clinical, genetic, and environmental variables collected in early pregnancy, assessed using measures of model discrimination. Odds ratios and positive likelihood ratios were used to evaluate the association of PRS and physical activity with GD risk. Results A total of 3533 women were included in this analysis (mean [SD] age, 28.6 [4.9] years). In high-risk population subgroups (body mass index ≥25 or aged ≥35 years), individuals with high PRS (top 25th percentile) or low activity levels (METs <450) had increased odds of a GD diagnosis of 25% to 75%. Compared with the general population, participants with both high PRS and low activity levels had higher odds of a GD diagnosis (odds ratio, 3.4 [95% CI, 2.3-5.3]), whereas participants with low PRS and high METs had significantly reduced risk of a GD diagnosis (odds ratio, 0.5 [95% CI, 0.3-0.9]; P = .01). Conclusions and Relevance In this cohort study, the addition of PRS was associated with the stratified risk of GD diagnosis among high-risk patient subgroups, suggesting the benefits of targeted PRS ascertainment to encourage early intervention.
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Affiliation(s)
- Kymberleigh A. Pagel
- Department of Computer Science, Indiana University, Bloomington
- Institute of Computational Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Hoyin Chu
- Khoury College of Computer Sciences, Northeastern University, Boston, Massachusetts
- Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Rashika Ramola
- Khoury College of Computer Sciences, Northeastern University, Boston, Massachusetts
| | - Rafael F. Guerrero
- Department of Biological Sciences, North Carolina State University, Raleigh
| | - Judith H. Chung
- Department of Obstetrics and Gynecology, University of California, Irvine
| | - Samuel Parry
- Department of Obstetrics and Gynecology, University of Pennsylvania School of Medicine, Philadelphia
| | - Uma M. Reddy
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Robert M. Silver
- Department of Obstetrics and Gynecology, University of Utah School of Medicine, Salt Lake City
| | | | - Lynn M. Yee
- Department of Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Ronald J. Wapner
- College of Physicians and Surgeons, Columbia University, New York, New York
| | - Matthew W. Hahn
- Department of Computer Science, Indiana University, Bloomington
- Department of Biology, Indiana University, Bloomington
| | | | - David M. Haas
- Department of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis
| | - Predrag Radivojac
- Khoury College of Computer Sciences, Northeastern University, Boston, Massachusetts
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20
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Huvinen E, Lahti J, Klemetti MM, Bergman PH, Räikkönen K, Orho-Melander M, Laivuori H, Koivusalo SB. Genetic risk of type 2 diabetes modifies the effects of a lifestyle intervention aimed at the prevention of gestational and postpartum diabetes. Diabetologia 2022; 65:1291-1301. [PMID: 35501401 PMCID: PMC9283155 DOI: 10.1007/s00125-022-05712-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 02/23/2022] [Indexed: 11/29/2022]
Abstract
AIMS/HYPOTHESIS The aim of this study was to assess the interaction between genetic risk and lifestyle intervention on the occurrence of gestational diabetes mellitus (GDM) and postpartum diabetes. METHODS The RADIEL study is an RCT aimed at prevention of GDM and postpartum diabetes through lifestyle intervention. Participants with a BMI ≥30 kg/m2 and/or prior GDM were allocated to intervention and control groups before pregnancy or in early pregnancy. The study visits took place every 3 months before pregnancy, once in each trimester, and at 6 weeks and 6 and 12 months postpartum. We calculated a polygenic risk score (PRS) based on 50 risk variants for type 2 diabetes. RESULTS Altogether, 516 participants provided genetic and GDM data. The PRS was associated with higher glycaemic levels (fasting glucose and/or HbA1c) and a lower insulin secretion index in the second and third trimesters and at 12 months postpartum, as well as with a higher occurrence of GDM and glycaemic abnormalities at 12 months postpartum (n = 356). There was an interaction between the PRS and lifestyle intervention (p=0.016 during pregnancy and p=0.024 postpartum) when analysing participants who did not have GDM at the first study visit during pregnancy (n = 386). When analysing women in tertiles according to the PRS, the intervention was effective in reducing the age-adjusted occurrence of GDM only among those with the highest genetic risk (OR 0.37; 95% CI 0.17, 0.82). The risk of glycaemic abnormalities at 12 months postpartum was reduced in the same group after adjusting additionally for BMI, parity, smoking and education (OR 0.35; 95% CI 0.13, 0.97). CONCLUSIONS/INTERPRETATION Genetic predisposition to diabetes modifies the response to a lifestyle intervention aimed at prevention of GDM and postpartum diabetes. This suggests that lifestyle intervention may benefit from being tailored according to genetic risk. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT01698385.
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Affiliation(s)
- Emilia Huvinen
- Teratology Information Service, Department of Emergency Medicine and Services, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Miira M Klemetti
- Department of Obstetrics and Gynecology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Paula H Bergman
- Biostatistics Consulting, Department of Public Health, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | | | - Hannele Laivuori
- Department of Obstetrics and Gynecology, Tampere University Hospital, Tampere, Finland
- Center for Child, Adolescent, and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Saila B Koivusalo
- Department of Obstetrics and Gynecology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
- Department of Obstetrics and Gynecology, Turku University Hospital and University of Turku, Turku, Finland
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21
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Genomics and Epigenomics of Gestational Diabetes Mellitus: Understanding the Molecular Pathways of the Disease Pathogenesis. Int J Mol Sci 2022; 23:ijms23073514. [PMID: 35408874 PMCID: PMC8998752 DOI: 10.3390/ijms23073514] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/01/2022] [Accepted: 03/04/2022] [Indexed: 11/16/2022] Open
Abstract
One of the most common complications during pregnancy is gestational diabetes mellitus (GDM), hyperglycemia that occurs for the first time during pregnancy. The condition is multifactorial, caused by an interaction between genetic, epigenetic, and environmental factors. However, the underlying mechanisms responsible for its pathogenesis remain elusive. Moreover, in contrast to several common metabolic disorders, molecular research in GDM is lagging. It is important to recognize that GDM is still commonly diagnosed during the second trimester of pregnancy using the oral glucose tolerance test (OGGT), at a time when both a fetal and maternal pathophysiology is already present, demonstrating the increased blood glucose levels associated with exacerbated insulin resistance. Therefore, early detection of metabolic changes and associated epigenetic and genetic factors that can lead to an improved prediction of adverse pregnancy outcomes and future cardio-metabolic pathologies in GDM women and their children is imperative. Several genomic and epigenetic approaches have been used to identify the genes, genetic variants, metabolic pathways, and epigenetic modifications involved in GDM to determine its etiology. In this article, we explore these factors as well as how their functional effects may contribute to immediate and future pathologies in women with GDM and their offspring from birth to adulthood. We also discuss how these approaches contribute to the changes in different molecular pathways that contribute to the GDM pathogenesis, with a special focus on the development of insulin resistance.
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22
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Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation 2022; 145:e153-e639. [PMID: 35078371 DOI: 10.1161/cir.0000000000001052] [Citation(s) in RCA: 2562] [Impact Index Per Article: 1281.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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23
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van Poppel MNM, Corcoy R, Hill D, Simmons D, Mendizabal L, Zulueta M, Simon L, Desoye G. Interaction between rs10830962 polymorphism in MTNR1B and lifestyle intervention on maternal and neonatal outcomes: secondary analyses of the DALI lifestyle randomized controlled trial. Am J Clin Nutr 2022; 115:388-396. [PMID: 34669935 DOI: 10.1093/ajcn/nqab347] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 10/12/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Interactions between polymorphisms of the melatonin receptor 1B (MTNR1B) gene and lifestyle intervention for gestational diabetes have been described. Whether these are specific for physical activity or the healthy eating intervention is unknown. OBJECTIVES The aim was to assess the interaction between MTNR1B rs10830962 and rs10830963 polymorphisms and lifestyle interventions during pregnancy. METHODS Women with a BMI (in kg/m2) of ≥29 (n = 436) received counseling on healthy eating (HE), physical activity (PA), or both. The control group received usual care. This secondary analysis had a factorial design with comparison of HE compared with no HE and PA compared with no PA. Maternal outcomes at 24-28 wk were gestational weight gain (GWG), maternal fasting glucose, insulin, insulin resistance (HOMA-IR), disposition index, and development of GDM. Neonatal outcomes were cord blood leptin and C-peptide and estimated neonatal fat percentage. The interaction between receiving either the HE or PA intervention and genotypes of both rs10830962 and rs10830963 was assessed using multilevel regression analysis. RESULTS GDM risk was increased in women homozygous for the G allele of rs10830962 (OR: 2.60; 95% CI: 1.34, 5.06) or rs10830963 (OR: 2.83; 95% CI: 1.24, 6.47). Significant interactions between rs10830962 and interventions were found: in women homozygous for the G allele but not in the other genotypes, the PA intervention reduced maternal fasting insulin (β: -0.16; 95% CI: -0.33, 0.02; P = 0.08) and HOMA-IR (β: -0.17; 95% CI: -0.35, 0.01; P = 0.06), and reduced cord blood leptin (β: -0.84; 95% CI: -1.42, -0.25; P = 0.01) and C-peptide (β: -0.62; 95% CI: -1.07, -0.17; P = 0.01). In heterozygous women, the HE intervention had no effect, whereas in women homozygous for the C allele, HE intervention reduced GWG (β: -1.6 kg; 95% CI: -2.4, -0.8 kg). No interactions were found. CONCLUSIONS In women homozygous for the risk allele of MTNR1B rs10830962, GDM risk was increased and PA intervention might be more beneficial than HE intervention for reducing maternal insulin resistance, cord blood C-peptide, and cord blood leptin.
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Affiliation(s)
| | - Rosa Corcoy
- Institut de Recerca de l´Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.,CIBER Bioengineering, Biomaterials and Nanotechnology, Instituto de Salud Carlos III, Madrid, Spain
| | - David Hill
- Recherche en Santé Lawson SA, Bronschhofen, Switzerland.,Lawson Health Research Institute, London, Ontario, Canada
| | - David Simmons
- Western Sydney University, Campbelltown, New South Wales, Australia.,Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | | | | | - Laureano Simon
- Department of Obstetrics and Gynecology, Medical University Graz, Graz, Austria
| | - Gernot Desoye
- Department of Obstetrics and Gynecology, Medical University Graz, Graz, Austria
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24
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Wang H, Li J, Leng J, Li W, Liu J, Yan X, Yu Z, Hu G, Ma RCW, Fang Z, Wang Y, Yang X. The CDKAL1 rs7747752-Bile Acids Interaction Increased Risk of Gestational Diabetes Mellitus: A Nested Case-Control Study. Front Endocrinol (Lausanne) 2022; 13:808956. [PMID: 35360068 PMCID: PMC8960111 DOI: 10.3389/fendo.2022.808956] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 02/16/2022] [Indexed: 11/19/2022] Open
Abstract
AIMS The study aimed to explore additive interactions of CDKAL1 rs7747752 and GUDCA/DCA for GDM risk and whether the interactive effects on the risk of GDM was mediated via increasing lysophosphatidylcholines (LPC) 18:0 and/or saturated fatty acid (SFA) 16:0. METHODS A 1:1 age-matched study nested in a prospective cohort of pregnant women (207 pairs) was organized in Tianjin, China. Additive interactions were used to test interaction effects while mediation analyses and Sobel tests were used to test mediation effects of LPC18:0 and SFA16:0 between copresence of rs7747752 and low GUDCA/DCA, and GDM risk. RESULTS The CDKAL1 rs7747752 was associated with GDM (P<0.05). The rs7747752 C polymorphism markedly enhanced ORs of low GUDCA from 4.04 (0.72-22.8) to 9.02 (1.63-49.7) and low DCA from 1.67 (0.68-4.11) to 4.24 (1.84-9.76), both with significant additive interactions. Further adjustment for LPC18:0 attenuated the interactive effects of rs7747752 and low DCA, with a significant mediation effect (P=0.003). High SFA16:0 did not mediate the interactive effects of rs7747752 and low DCA/GUDCA on GDM risk. CONCLUSIONS The CDKAL1 rs7747752 C carrier status and low GUDCA/DCA had significant additive interactions on the risk of GDM with the effect from interaction with DCA being partially mediated via increasing LPC18:0.
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Affiliation(s)
- Hui Wang
- 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 Medical University, Tianjin, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, China
| | - Junhong Leng
- Project Office, Tianjin Women and Children’s Health Center, Tianjin, China
| | - Weiqin Li
- Project Office, Tianjin Women and Children’s Health Center, Tianjin, China
| | - Jinnan Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xiaoyan Yan
- School of Public Health, Shanxi Medical University, Shanxi, China
| | - Zhijie Yu
- Population Cancer Research Program and Department of Pediatrics, Dalhousie University, Halifax, NS, Canada
| | - Gang Hu
- Chronic Disease Epidemiology Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Ronald C. W. Ma
- Department of Medicine and Therapeutics and Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Zhongze Fang
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, China
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin, China
- *Correspondence: Xilin Yang, ; ; Ying Wang, ; Zhongze Fang,
| | - Ying Wang
- Scientific Research Platform of the Second School of Clinical Medicine & Key Laboratory of 3D Printing Technology in Stomatology, Guangdong Medical University, Dongguan, China
- *Correspondence: Xilin Yang, ; ; Ying Wang, ; Zhongze Fang,
| | - 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 Medical University, Tianjin, China
- Tianjin Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, China
- *Correspondence: Xilin Yang, ; ; Ying Wang, ; Zhongze Fang,
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25
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Alharbi KK, Alsaikhan AS, Alshammary AF, Al-Hakeem MM, Ali Khan I. Screening of mitochondrial mutations in Saudi women diagnosed with gestational diabetes mellitus: A non-replicative case-control study. Saudi J Biol Sci 2022; 29:360-365. [PMID: 35002430 PMCID: PMC8716902 DOI: 10.1016/j.sjbs.2021.08.102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/29/2021] [Accepted: 08/30/2021] [Indexed: 12/15/2022] Open
Abstract
Introduction Among metabolic disorders, gestational diabetes mellitus (GDM) is specified as hyperglycemia caused by glucose or carbohydrate intolerance defects. GDM is distinguished by oxidative stress, and has been connected to mitochondrial dysfunction. Previous studies have documented the relation between A12026G, A8344G and A3243G mutations in ND4, tRNALeu(UUR), and tRNALys genes in different modes of diabetes. Aim The purpose of this study was to investigate into the relationship between GDM women and common mitochondrial mutations including A12026, A8344G, and A3243G in Saudi women. Methods In this case-control study, we have opted 96 GDM and 102 non-GDM pregnant women and DNA was extracted using EDTA blood and based on specific primers, Polymerase Chain Reaction was followed and then Restriction Fragment Length Polymorphism (RFLP) analysis was performed. Restriction enzymes was cross-checked with Lambda DNA and 10% of the purified PCR products were performed the Sanger sequencing analysis to reconfirm the RFLP analysis of the studied results. Results None of the heterozygous and homozygous mutations were not observed in our study. All the subjects were turned to be homozygous normal genotypes. Conclusion This study confirms that A12026, A8344G, and A3243G mutations have no role in the Saudi women with GDM.
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Affiliation(s)
- Khalid Khalaf Alharbi
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
| | - Abdullah Sulaiman Alsaikhan
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
| | - Amal F Alshammary
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
| | - Malak Mohammed Al-Hakeem
- Department of Obstetrics and Gynecology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Imran Ali Khan
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
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26
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Jowell AR, Sarma AA, Gulati M, Michos ED, Vaught AJ, Natarajan P, Powe CE, Honigberg MC. Interventions to Mitigate Risk of Cardiovascular Disease After Adverse Pregnancy Outcomes: A Review. JAMA Cardiol 2021; 7:346-355. [PMID: 34705020 DOI: 10.1001/jamacardio.2021.4391] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Importance A growing body of evidence suggests that adverse pregnancy outcomes (APOs), including hypertensive disorders of pregnancy, gestational diabetes (GD), preterm birth, and intrauterine growth restriction, are associated with increased risk of cardiometabolic disease and cardiovascular disease (CVD) later in life. Adverse pregnancy outcomes may therefore represent an opportunity to intervene to prevent or delay onset of CVD. The objective of this review was to summarize the current evidence for targeted postpartum interventions and strategies to reduce CVD risk in women with a history of APOs. Observations A search of PubMed and Ovid for English-language randomized clinical trials, cohort studies, descriptive studies, and guidelines published from January 1, 2000, to April 30, 2021, was performed. Four broad categories of interventions were identified: transitional clinics, lifestyle interventions, pharmacotherapy, and patient and clinician education. Observational studies suggest that postpartum transitional clinics identify women who are at elevated risk for CVD and may aid in the transition to longitudinal primary care. Lifestyle interventions to increase physical activity and improve diet quality may help reduce the incidence of type 2 diabetes in women with prior GD; less is known about women with other prior APOs. Metformin hydrochloride may prevent development of type 2 diabetes in women with prior GD. Evidence is lacking in regard to specific pharmacotherapies after other APOs. Cardiovascular guidelines endorse using a history of APOs to refine CVD risk assessment and guide statin prescription for primary prevention in women with intermediate calculated 10-year CVD risk. Research suggests a low level of awareness of the link between APOs and CVD among both patients and clinicians. Conclusions and Relevance These findings suggest that transitional clinics, lifestyle intervention, targeted pharmacotherapy, and clinician and patient education represent promising strategies for improving postpartum maternal cardiometabolic health in women with APOs; further research is needed to develop and rigorously evaluate these interventions. Future efforts should focus on strategies to increase maternal postpartum follow-up, improve accessibility to interventions across diverse racial and cultural groups, expand awareness of sex-specific CVD risk factors, and define evidence-based precision prevention strategies for this high-risk population.
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Affiliation(s)
- Amanda R Jowell
- Currently a medical student at Harvard Medical School, Boston, Massachusetts
| | - Amy A Sarma
- Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston.,Corrigan Women's Heart Health Program, Massachusetts General Hospital, Boston
| | - Martha Gulati
- Division of Cardiology, University of Arizona, Phoenix
| | - Erin D Michos
- Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland.,Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Arthur J Vaught
- Division of Maternal-Fetal Medicine, Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, Maryland.,Division of Surgical Critical Care, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Pradeep Natarajan
- Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston.,Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Cardiovascular Research Center, Massachusetts General Hospital, Boston
| | - Camille E Powe
- Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston
| | - Michael C Honigberg
- Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston.,Corrigan Women's Heart Health Program, Massachusetts General Hospital, Boston.,Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Cardiovascular Research Center, Massachusetts General Hospital, Boston
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27
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Desoye G, Wells JCK. Pregnancies in Diabetes and Obesity: The Capacity-Load Model of Placental Adaptation. Diabetes 2021; 70:823-830. [PMID: 33741605 PMCID: PMC7980199 DOI: 10.2337/db20-1111] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/19/2021] [Indexed: 12/19/2022]
Abstract
Excess nutritional supply to the growing fetus, resulting from maternal diabetes and obesity, is associated with increased risks of fetal maldevelopment and adverse metabolic conditions in postnatal life. The placenta, interposed between mother and fetus, serves as the gateway between the two circulations and is usually considered to mediate maternal exposures to the fetus through a direct supply line. In this Perspective, however, we argue that the placenta is not an innocent bystander and mounts responses to fetal "signals of distress" to sustain its own adequate function and protect the fetus. We describe several types of protection that the placenta can offer the fetus against maternal metabolic perturbations and offer a theoretical model of how the placenta responds to the intrauterine environment in maternal diabetes and obesity to stabilize the fetal environment. Our approach supports growing calls for early screening and control of pregnancy metabolism to minimize harmful fetal outcomes.
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