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Jasper E, Hellwege J, Greene C, Edwards TL, Edwards DV. Genomic Insights into Gestational Weight Gain: Uncovering Tissue-Specific Mechanisms and Pathways. RESEARCH SQUARE 2024:rs.3.rs-4427250. [PMID: 38854080 PMCID: PMC11160900 DOI: 10.21203/rs.3.rs-4427250/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Increasing gestational weight gain (GWG) is linked to adverse outcomes in pregnant persons and their children. The Early Growth Genetics (EGG) Consortium identified previously genetic variants that could contribute to early, late, and total GWG from fetal and maternal genomes. However, the biologic mechanisms and tissue-Specificity of these variants in GWG is unknown. We evaluated the association between genetically predicted gene expression in five relevant maternal (subcutaneous and visceral adipose, breast, uterus, and whole blood) from GTEx (v7) and fetal (placenta) tissues and early, late, and total GWG using S-PrediXcan. We tested enrichment of pre-defined biological pathways for nominally (P < 0.05) significant associations using the GENE2FUNC module from Functional Mapping and Annotation of Genome-Wide Association Studies. After multiple testing correction, we did not find significant associations between maternal and fetal gene expression and early, late, or total GWG. There was significant enrichment of several biological pathways, including metabolic processes, secretion, and intracellular transport, among nominally significant genes from the maternal analyses (false discovery rate p-values: 0.016 to 9.37×10). Enriched biological pathways varied across pregnancy. Though additional research is necessary, these results indicate that diverse biological pathways are likely to impact GWG, with their influence varying by tissue and weeks of gestation.
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Affiliation(s)
| | | | | | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center
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Sámano R, Martínez-Rojano H, Chico-Barba G, Gamboa R, Mendoza-Flores ME, Robles-Alarcón FJ, Pérez-Martínez I, Monroy-Muñoz IE. Gestational Weight Gain: Is the Role of Genetic Variants a Determinant? A Review. Int J Mol Sci 2024; 25:3039. [PMID: 38474283 DOI: 10.3390/ijms25053039] [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: 12/25/2023] [Revised: 03/01/2024] [Accepted: 03/03/2024] [Indexed: 03/14/2024] Open
Abstract
Excessive or insufficient gestational weight gain (GWG) leads to diverse adverse maternal and neonatal outcomes. There is evidence that pregestational body mass index (pBMI) plays a role in GWG, but no genetic cause has been identified. In this review, we aim to analyze genotype variants associated with GWG. Results: We identified seven genotype variants that may be involved in GWG regulation that were analyzed in studies carried out in Brazil, Romania, the USA, Turkey, Ukraine, and Canada. Some genetic variants were only associated with GWG in certain races or depending on the pBMI. In women who were obese or overweight before gestation, some genetic variants were associated with GWG. Environmental and genetic factors together showed a greater association with GWG than genetic factors alone; for example, type of diet was observed to have a significant influence. Conclusions: We found little scientific evidence of an association between genotype variants in countries with a high prevalence of women of reproductive age who are overweight and obese, such as in Latin America. GWG may be more dependent on environmental factors than genetic variants. We suggest a deeper study of genetic variants, cytokines, and their possible association with GWG, always with the respective control of potential cofounding factors, such as pBMI, diet, and race.
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Affiliation(s)
- Reyna Sámano
- Coordinación de Nutrición y Bioprogramación, Instituto Nacional de Perinatología, Secretaría de Salud, Mexico City 11000, Mexico
- Programa de Posgrado Doctorado en Ciencias Biológicas y de la Salud, División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana, Mexico City 04960, Mexico
| | - Hugo Martínez-Rojano
- Sección de Posgrado e Investigación de la Escuela Superior de Medicina del Instituto Politécnico Nacional, Mexico City 11340, Mexico
| | - Gabriela Chico-Barba
- Coordinación de Nutrición y Bioprogramación, Instituto Nacional de Perinatología, Secretaría de Salud, Mexico City 11000, Mexico
| | - Ricardo Gamboa
- Departamento de Fisiología, Instituto Nacional de Cardiología "Ignacio Chávez", Mexico City 14080, Mexico
| | - María Eugenia Mendoza-Flores
- Coordinación de Nutrición y Bioprogramación, Instituto Nacional de Perinatología, Secretaría de Salud, Mexico City 11000, Mexico
| | | | - Itzel Pérez-Martínez
- Facultad de Nutrición, Universidad Autónoma del Estado de Morelos, Cuernavaca 62350, Mexico
| | - Irma Eloisa Monroy-Muñoz
- Departamento de Investigación Clínica en Salud Reproductiva y Perinatal, Instituto Nacional de Perinatología, Secretaría de Salud, Mexico City 11000, Mexico
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Mikołajczyk-Stecyna J, Zuk E, Seremak-Mrozikiewicz A, Kurzawińska G, Wolski H, Drews K, Chmurzynska A. Genetic risk score for gestational weight gain. Eur J Obstet Gynecol Reprod Biol 2024; 294:20-27. [PMID: 38184896 DOI: 10.1016/j.ejogrb.2023.12.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 12/15/2023] [Accepted: 12/20/2023] [Indexed: 01/09/2024]
Abstract
Gestational weight gain (GWG) involves health consequences for both mother and offspring. Genetic factors seem to play a role in the GWG trait. For small effect sizes of a single genetic polymorphism (SNP), a genetic risk score (GRS) summarizing risk-associated variation from multiple SNPs can serve as an effective approach to genetic association analysis. The aim of the study was to analyze the association between genetic risk score (GRS) and gestational weight gain (GWG). GWG was calculated for a total of 342 healthy Polish women of Caucasian origin, aged 19 to 45 years. The SNPs rs9939609 (FTO), rs6548238 (TMEM18), rs17782313 (MC4R), rs10938397 (GNPDA2), rs10913469 (SEC16B), rs1137101 (LEPR), rs7799039 (LEP), and rs5443 (GNB3) were genotyped using commercial TaqMan SNP assays. A simple genetic risk score was calculated into two ways: GRS1 based on the sum of risk alleles from each of the SNPs, while GRS2 based on the sum of risk alleles of FTO, LEPR, LEP, and GNB3. Positive association between GRS2 and GWG (β = 0.12, p = 0.029) was observed. Genetic risk variants of TMEM18 (p = 0.006, OR = 2.6) and GNB3 (p < 0.001, OR = 3.3) are more frequent in women with increased GWG, but a risk variant of GNPDA2 (p < 0.001, OR = 2.7) is more frequent in women with adequate GWG, and a risk variant of LEPR (p = 0.011, OR = 3.1) in women with decreased GWG. GRS2 and genetic variants of TMEM18, GNB3, GNPDA2, and LEPR are associated with weight gain during pregnancy.
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Affiliation(s)
- Joanna Mikołajczyk-Stecyna
- Department of Human Nutrition and Dietetics, Poznań University of Life Sciences, Wojska Polskiego 31, 60-624 Poznań, Poland
| | - Ewelina Zuk
- Department of Human Nutrition and Dietetics, Poznań University of Life Sciences, Wojska Polskiego 31, 60-624 Poznań, Poland
| | - Agnieszka Seremak-Mrozikiewicz
- Division of Perinatology and Women's Diseases, Poznań University of Medical Sciences, Polna 33, 60-535 Poznań, Poland; Laboratory of Molecular Biology, Division of Perinatology and Women's Diseases, Poznań University of Medical Sciences, Polna 33, 60-535 Poznań, Poland
| | - Grażyna Kurzawińska
- Division of Perinatology and Women's Diseases, Poznań University of Medical Sciences, Polna 33, 60-535 Poznań, Poland; Laboratory of Molecular Biology, Division of Perinatology and Women's Diseases, Poznań University of Medical Sciences, Polna 33, 60-535 Poznań, Poland
| | - Hubert Wolski
- Division of Perinatology and Women's Diseases, Poznań University of Medical Sciences, Polna 33, 60-535 Poznań, Poland; Podhale State College of Applied Sciences in Nowy Targ, Kokoszków 71, 34-400 Nowy Targ, Poland
| | - Krzysztof Drews
- Division of Perinatology and Women's Diseases, Poznań University of Medical Sciences, Polna 33, 60-535 Poznań, Poland; Laboratory of Molecular Biology, Division of Perinatology and Women's Diseases, Poznań University of Medical Sciences, Polna 33, 60-535 Poznań, Poland
| | - Agata Chmurzynska
- Department of Human Nutrition and Dietetics, Poznań University of Life Sciences, Wojska Polskiego 31, 60-624 Poznań, Poland.
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Apicella C, Ruano CSM, Thilaganathan B, Khalil A, Giorgione V, Gascoin G, Marcellin L, Gaspar C, Jacques S, Murdoch CE, Miralles F, Méhats C, Vaiman D. Pan-Genomic Regulation of Gene Expression in Normal and Pathological Human Placentas. Cells 2023; 12:cells12040578. [PMID: 36831244 PMCID: PMC9954093 DOI: 10.3390/cells12040578] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 01/17/2023] [Accepted: 01/28/2023] [Indexed: 02/17/2023] Open
Abstract
In this study, we attempted to find genetic variants affecting gene expression (eQTL = expression Quantitative Trait Loci) in the human placenta in normal and pathological situations. The analysis of gene expression in placental diseases (Pre-eclampsia and Intra-Uterine Growth Restriction) is hindered by the fact that diseased placental tissue samples are generally taken at earlier gestations compared to control samples. The difference in gestational age is considered a major confounding factor in the transcriptome regulation of the placenta. To alleviate this significant problem, we propose here a novel approach to pinpoint disease-specific cis-eQTLs. By statistical correction for gestational age at sampling as well as other confounding/surrogate variables systematically searched and identified, we found 43 e-genes for which proximal SNPs influence expression level. Then, we performed the analysis again, removing the disease status from the covariates, and we identified 54 e-genes, 16 of which are identified de novo and, thus, possibly related to placental disease. We found a highly significant overlap with previous studies for the list of 43 e-genes, validating our methodology and findings. Among the 16 disease-specific e-genes, several are intrinsic to trophoblast biology and, therefore, constitute novel targets of interest to better characterize placental pathology and its varied clinical consequences. The approach that we used may also be applied to the study of other human diseases where confounding factors have hampered a better understanding of the pathology.
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Affiliation(s)
- Clara Apicella
- Team ‘From Gametes to Birth’, Institut Cochin, U1016 INSERM, UMR 8104 CNRS, Paris-Descartes University, 75014 Paris, France
| | - Camino S. M. Ruano
- Team ‘From Gametes to Birth’, Institut Cochin, U1016 INSERM, UMR 8104 CNRS, Paris-Descartes University, 75014 Paris, France
| | - Basky Thilaganathan
- Fetal Medicine Unit, St George’s University Hospitals NHS Foundation Trust, London SW17 0RE, UK
- Vascular Biology Research Centre, Molecular and Clinical Sciences Research Institute, St George’s University of London, London SW17 0RE, UK
| | - Asma Khalil
- Fetal Medicine Unit, St George’s University Hospitals NHS Foundation Trust, London SW17 0RE, UK
- Vascular Biology Research Centre, Molecular and Clinical Sciences Research Institute, St George’s University of London, London SW17 0RE, UK
| | - Veronica Giorgione
- Fetal Medicine Unit, St George’s University Hospitals NHS Foundation Trust, London SW17 0RE, UK
- Vascular Biology Research Centre, Molecular and Clinical Sciences Research Institute, St George’s University of London, London SW17 0RE, UK
| | - Géraldine Gascoin
- Department of Neonatology, Angers University Hospital, F-49000 Angers, France
| | - Louis Marcellin
- Department of Gynaecology, Obstetrics and Reproductive Medicine, Centre Hospitalier Universitaire (CHU) Cochin Faculté de Médecine, Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpitaux Universitaires Paris Centre (HUPC), Université de Paris, 138 Boulevard de Port-Royal, 75014 Paris, France
| | - Cassandra Gaspar
- Sorbonne Université, Inserm, UMS Production et Analyse des données en Sciences de la vie et en Santé, PASS, Plateforme Post-génomique de la Pitié-Salpêtrière, 75013 Paris, France
| | - Sébastien Jacques
- Team ‘From Gametes to Birth’, Institut Cochin, U1016 INSERM, UMR 8104 CNRS, Paris-Descartes University, 75014 Paris, France
| | - Colin E. Murdoch
- Systems Medicine, School of Medicine, University of Dundee, Dundee DD1 9SY, UK
| | - Francisco Miralles
- Team ‘From Gametes to Birth’, Institut Cochin, U1016 INSERM, UMR 8104 CNRS, Paris-Descartes University, 75014 Paris, France
| | - Céline Méhats
- Team ‘From Gametes to Birth’, Institut Cochin, U1016 INSERM, UMR 8104 CNRS, Paris-Descartes University, 75014 Paris, France
| | - Daniel Vaiman
- Team ‘From Gametes to Birth’, Institut Cochin, U1016 INSERM, UMR 8104 CNRS, Paris-Descartes University, 75014 Paris, France
- Correspondence: ; Tel.: +33-1-44412301; Fax: +33-1-44412302
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Ustianowski P, Malinowski D, Czerewaty M, Safranow K, Tarnowski M, Dziedziejko V, Pawlik A. THADA, SDHAF4, and MACF1 Gene Polymorphisms and Placental Expression in Women with Gestational Diabetes. Genes (Basel) 2022; 14:genes14010083. [PMID: 36672824 PMCID: PMC9859259 DOI: 10.3390/genes14010083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 12/13/2022] [Accepted: 12/22/2022] [Indexed: 12/29/2022] Open
Abstract
Gestational diabetes mellitus (GDM) is a metabolic disorder in pregnant women leading to various complications. Consequently, factors predisposing its development are being sought. Previous studies have shown that the pathogenesis of GDM is similar to that of type 2 diabetes, and it is therefore thought that the two diseases may have a common genetic basis. The aim of this study was to examine the associations between thyroid adenoma-associated (THADA) rs7578597 T>C, succinate dehydrogenase complex assembly factor 4 (SDHAF4) rs1048886 A>G, and microtubule-actin crosslinking factor 1 (MACF1) rs2296172 A>G gene polymorphisms and the risk of GDM development as well as selected clinical parameters in women with GDM. We also examined the expression of these genes in the placenta of women with and without GDM in association with clinical parameters. This case-control study included 272 pregnant women with GDM and 348 pregnant women with normal glucose tolerance. There were no statistically significant differences in the distribution of the THADA rs7578597 T>C, SDHAF4 rs1048886 A>G, and MACF1 rs2296172 A>G gene polymorphisms between pregnant control women and women with GDM. The associations between clinical parameters such as body mass before pregnancy, body mass at birth, body mass increase during pregnancy, BMI before pregnancy, BMI at birth, BMI increase during pregnancy, glycated hemoglobin (HbA1c), daily insulin requirement, childbirth time, and newborn body mass and APGAR score, and the THADA rs7578597 T>C, SDHAF4 rs1048886 A>G, and MACF1 rs2296172 A>G genotypes were statistically non-significant. We only observed lower values of body mass before pregnancy and body mass at birth in women with the SDHAF4 rs1048886 AG genotype in comparison with AA genotype carriers. There was no statistically significant difference in the expression of THADA, SDHAF4, and MACF1 genes in the placenta between women with GDM and healthy women. There were also no statistically significant correlations between THADA, SDHAF4, and MACF1 gene expression in the placenta and clinical parameters. The results of our study suggest that THADA rs7578597 T>C, SDHAF4 rs1048886 A>G, and MACF1 rs2296172 A>G gene polymorphisms are not significant factors associated with GDM onset. In addition, SDHAF4 rs1048886 A>G may be associated with body mass before pregnancy and body mass at birth in pregnant women.
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Affiliation(s)
| | - Damian Malinowski
- Department of Experimental and Clinical Pharmacology, Pomeranian Medical University, 70-111 Szczecin, Poland
| | - Michał Czerewaty
- Department of Physiology, Pomeranian Medical University, 70-111 Szczecin, Poland
| | - Krzysztof Safranow
- Department of Biochemistry and Medical Chemistry, Pomeranian Medical University, 70-111 Szczecin, Poland
| | - Maciej Tarnowski
- Department of Physiology in Health Sciences, Pomeranian Medical University, 70-210 Szczecin, Poland
| | - Violetta Dziedziejko
- Department of Biochemistry and Medical Chemistry, Pomeranian Medical University, 70-111 Szczecin, Poland
| | - Andrzej Pawlik
- Department of Physiology, Pomeranian Medical University, 70-111 Szczecin, Poland
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KCNJ11 and KCNQ1 Gene Polymorphisms and Placental Expression in Women with Gestational Diabetes Mellitus. Genes (Basel) 2022; 13:genes13081315. [PMID: 35893051 PMCID: PMC9331982 DOI: 10.3390/genes13081315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/19/2022] [Accepted: 07/21/2022] [Indexed: 11/17/2022] Open
Abstract
Gestational diabetes mellitus (GDM) represents carbohydrate intolerance in pregnant women. The pathogenesis of GDM is very complex, but abnormalities in insulin production and secretion underlie the disease. Potassium channels play an important role in insulin production and secretion. The family of potassium channels includes (among others) the potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) and voltage-gated K+ channel (KCNQ1). The aim of the study was to examine the distribution of the KCNJ11 rs5219 and KCNQ1 rs151290 and rs2237892 gene polymorphisms in women with GDM and pregnant women with normal carbohydrate tolerance, to verify whether these polymorphisms are risk factors for GDM. This study included 204 Caucasian pregnant women with GDM and 207 pregnant women with normal glucose tolerance (NGT) from the West Pomeranian region of Poland. The diagnosis of GDM was based on a 75 g oral glucose tolerance test (OGTT) at 24–28 weeks gestation. There were no statistically significant differences in distribution of the KCNJ11 rs5219 and KCNQ1 rs151290 and rs2237892 gene polymorphisms between women with GDM and pregnant women with normal carbohydrate tolerance. Moreover, there were no statistically significant associations between the studied genotypes and the selected clinical parameters in women with GDM. The results of our study suggest that the KCNJ11 rs5219 and KCNQ1 rs2237892 and rs151290 gene polymorphisms are not significant risk factors associated with the development of GDM in our population. There were also no differences in the expression of KCNJ11 and KCNQ1 genes in the placenta of women with GDM and normal carbohydrate tolerance. However, an association between KCNJ11 gene expression in placenta and APGAR score in newborns was found.
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Ouidir M, Zeng X, Chatterjee S, Zhang C, Tekola-Ayele F. Ancestry-Matched and Cross-Ancestry Genetic Risk Scores of Type 2 Diabetes in Pregnant Women and Fetal Growth: A Study in an Ancestrally Diverse Cohort. Diabetes 2022; 71:340-349. [PMID: 34789498 PMCID: PMC8914278 DOI: 10.2337/db21-0655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 11/11/2021] [Indexed: 02/03/2023]
Abstract
Maternal genetic variants associated with offspring birth weight and adult type 2 diabetes (T2D) risk loci show some overlap. Whether T2D genetic risk influences longitudinal fetal weight and the gestational timing when these relationships begin is unknown. We investigated the associations of T2D genetic risk scores (GRS) with longitudinal fetal weight and birth weight among 1,513 pregnant women from four ancestral groups. Women had up to five ultrasonography examinations. Ancestry-matched GRS were constructed separately using 380 European- (GRSeur), 104 African- (GRSafr), and 189 East Asian- (GRSeas) related T2D loci discovered in different population groups. Among European Americans, the highest quartile GRSeur was significantly associated with 53.8 g higher fetal weight (95% CI 19.2-88.5) over the pregnancy. The associations began at gestational week 24 and continued through week 40, with a 106.8 g (95% CI 6.5-207.1) increase in birth weight. The findings were similar in analysis further adjusted for maternal glucose challenge test results. No consistent association was found using ancestry-matched or cross-ancestry GRS in non-Europeans. In conclusion, T2D genetic susceptibility may influence fetal growth starting at midsecond trimester among Europeans. Absence of similar associations in non-Europeans urges the need for further genetic T2D studies in diverse ancestries.
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Si C, Wang N, Wang M, Liu Y, Niu Z, Ding Z. TMT-based proteomic and bioinformatic analyses of human granulosa cells from obese and normal-weight female subjects. Reprod Biol Endocrinol 2021; 19:75. [PMID: 34016141 PMCID: PMC8135161 DOI: 10.1186/s12958-021-00760-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 05/10/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Increasing evidence supports a relationship between obesity and either infertility or subfertility in women. Most previous omics studies were focused on determining if the serum and follicular fluid expression profiles of subjects afflicted with both obesity-related infertility and polycystic ovary syndrome (PCOS) are different than those in normal healthy controls. As granulosa cells (GCs) are essential for oocyte development and fertility, we determined here if the protein expression profiles in the GCs from obese subjects are different than those in their normal-weight counterpart. METHODS GC samples were collected from obese female subjects (n = 14) and normal-weight female subjects (n = 12) who were infertile and underwent in vitro fertilization (IVF) treatment due to tubal pathology. A quantitative approach including tandem mass tag labeling and liquid chromatography tandem mass spectrometry (TMT) was employed to identify differentially expressed proteins. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were then conducted to interrogate the functions and pathways of identified proteins. Clinical, hormonal, and biochemical parameters were also analyzed in both groups. RESULTS A total of 228 differentially expressed proteins were noted, including 138 that were upregulated whereas 90 others were downregulated. Significant pathways and GO terms associated with protein expression changes were also identified, especially within the mitochondrial electron transport chain. The levels of free fatty acids in both the serum and follicular fluid of obese subjects were significantly higher than those in matched normal-weight subjects. CONCLUSIONS In GCs obtained from obese subjects, their mitochondria were damaged and the endoplasmic reticulum stress response was accompanied by dysregulated hormonal synthesis whereas none of these changes occurred in normal-weight subjects. These alterations may be related to the high FFA and TG levels detected in human follicular fluid.
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Affiliation(s)
- Chenchen Si
- Department of Histology, Embryology, Genetics and Developmental Biology, Shanghai Key Laboratory for Reproductive Medicine, School of Medicine, Shanghai Jiao Tong University, 200025, Shanghai, China
- Department of Gynecology and Obstetrics, Reproductive Medical Center, School of Medicine, Ruijin Hospital, Shanghai Jiao Tong University, 197 Ruijin 2nd Road, 200025, Shanghai, China
| | - Nan Wang
- Department of Histology, Embryology, Genetics and Developmental Biology, Shanghai Key Laboratory for Reproductive Medicine, School of Medicine, Shanghai Jiao Tong University, 200025, Shanghai, China
| | - Mingjie Wang
- Department of Gynecology and Obstetrics, Reproductive Medical Center, School of Medicine, Ruijin Hospital, Shanghai Jiao Tong University, 197 Ruijin 2nd Road, 200025, Shanghai, China
| | - Yue Liu
- Department of Histology, Embryology, Genetics and Developmental Biology, Shanghai Key Laboratory for Reproductive Medicine, School of Medicine, Shanghai Jiao Tong University, 200025, Shanghai, China
| | - Zhihong Niu
- Department of Gynecology and Obstetrics, Reproductive Medical Center, School of Medicine, Ruijin Hospital, Shanghai Jiao Tong University, 197 Ruijin 2nd Road, 200025, Shanghai, China.
| | - Zhide Ding
- Department of Histology, Embryology, Genetics and Developmental Biology, Shanghai Key Laboratory for Reproductive Medicine, School of Medicine, Shanghai Jiao Tong University, 200025, Shanghai, China.
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Castillo-Higuera T, Alarcón-Granados MC, Marin-Suarez J, Moreno-Ortiz H, Esteban-Pérez CI, Ferrebuz-Cardozo AJ, Forero-Castro M, Camargo-Vill Alba G. A Comprehensive Overview of Common Polymorphic Variants in Genes Related to Polycystic Ovary Syndrome. Reprod Sci 2020; 28:2399-2412. [PMID: 33174186 DOI: 10.1007/s43032-020-00375-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 10/21/2020] [Indexed: 01/07/2023]
Abstract
Polycystic ovary syndrome (PCOS) is one of the most common endocrine-metabolic disorders in women of reproductive age. It is characterized by an increase in the biosynthesis of androgens, anovulation, and infertility. PCOS has been reported as a polygenic entity in which multiple single nucleotide polymorphisms (SNPs) are associated with the clinical features of the pathology. Herein, we describe the common polymorphic variants in genes related to PCOS, their role in its pathogenesis, and etiology. Whole-genome association studies have been focused on women from Asian and European populations. The most common genes associated with PCOS are DENND1A, THADA, FSHR, and LHCGR. However, other genes have been associated with PCOS such as AMH, AMHR2, ADIPOQ, FTO, HNF1A, CYP19, YAP1, HMGA2, RAB5B, SUOX, INSR, and TOX3. Nevertheless, the relationship between the biological functions of these genes and the development of the pathology is unclear. Studies in each gene in different populations do not always comply with a general pattern, so researching these variants is essential for better understanding of this polygenic syndrome. Future population studies should be carried out to evaluate biological processes, incidence rates, allelic and genotypic frequencies, and genetic susceptibility factors that predispose PCOS.
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Affiliation(s)
- Tatiana Castillo-Higuera
- Maestría en Ciencias Biológicas, Universidad Pedagógica y Tecnológica de Colombia, Tunja, 150003, Colombia.,Escuela de Ciencias Biológicas. Grupo de investigación en Ciencias Biomédicas (GICBUPTC), Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39-115, Tunja, 150003, Colombia
| | - María Camila Alarcón-Granados
- Escuela de Ciencias Biológicas. Grupo de investigación en Ciencias Biomédicas (GICBUPTC), Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39-115, Tunja, 150003, Colombia
| | - Johana Marin-Suarez
- Maestría en Ciencias Biológicas, Universidad Pedagógica y Tecnológica de Colombia, Tunja, 150003, Colombia.,Escuela de Ciencias Biológicas. Grupo de investigación en Ciencias Biomédicas (GICBUPTC), Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39-115, Tunja, 150003, Colombia
| | | | | | | | - Maribel Forero-Castro
- Escuela de Ciencias Biológicas. Grupo de investigación en Ciencias Biomédicas (GICBUPTC), Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39-115, Tunja, 150003, Colombia.
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Rahman ML, Shrestha D, Workalemahu T, Wu J, Zhu C, Zhang C, Tekola-Ayele F. Maternal and Offspring Genetic Risk of Type 2 Diabetes and Offspring Birthweight Among African Ancestry Populations. J Clin Endocrinol Metab 2019; 104:5032-5042. [PMID: 31120516 PMCID: PMC6753636 DOI: 10.1210/jc.2018-02756] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 05/17/2019] [Indexed: 12/14/2022]
Abstract
OBJECTIVES Maternal genetic risk of type 2 diabetes (T2D) can influence offspring birthweight through shared offspring genetic risk and by altering intrauterine glycemic status. The aim of this study was to estimate the independent effects of maternal and offspring genetic risk scores (GRSs) of T2D on offspring birthweight and the extent to which intrauterine glycemic traits mediate the effect of maternal GRSs on offspring birthweight. DESIGN The study involved 949 mother-offspring pairs of African ancestry from the Hyperglycemia Adverse Pregnancy Outcome study. GRSs of T2D were calculated separately for mothers and offspring as the weighted sum of 91 T2D risk alleles identified in a genome-wide association study meta-analysis in African Americans. Linear regression models were fit to estimate changes in birthweight by quartiles of GRSs. Mediation analysis was implemented to estimate the direct and indirect effects of maternal GRS on offspring birthweight through cord blood C-peptide and maternal fasting and postchallenge glucose levels. RESULTS Maternal and offspring GRSs were independently and differentially associated with offspring birthweight. Changes (95% CI) in birthweight across increasing quartiles of maternal GRSs were 0 g (reference), 83.1 g (6.5, 159.6), 103.1 g (26.0, 180.2), and 92.7 g (12.6, 172.8) (P trend = 0.041) and those of offspring GRSs were 0 (reference), -92.0 g (-169.2, -14.9), -64.9 g (-142.4, 12.6), and 2.0 g (-77.8, 81.7) (P trend = 0.032). Cord blood C-peptide mediated the effect of maternal GRS on offspring birthweight, whereas maternal postchallenge glucose levels showed additive effects with maternal GRS on birthweight. CONCLUSIONS Maternal and offspring GRSs of T2D were independently and differentially associated with offspring birthweight.
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Affiliation(s)
- Mohammad L Rahman
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
- Current Affiliation: M.L.R.’s current affiliation is Harvard Medical School Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts 02215
| | - Deepika Shrestha
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Jing Wu
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Chunming Zhu
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Cuilin Zhang
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
- Correspondence and Reprint Requests: Fasil Tekola-Ayele, PhD, Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, 6710B-3204, Bethesda, Maryland 20892. E-mail:
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11
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Kawai VK, Nwosu SK, Kurnik D, Harrell FE, Stein CM. Variants in BMI-Associated Genes and Adrenergic Genes are not Associated with Gestational Weight Trajectory. Obesity (Silver Spring) 2019; 27:1184-1189. [PMID: 31116007 PMCID: PMC6591076 DOI: 10.1002/oby.22505] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 03/19/2019] [Indexed: 12/25/2022]
Abstract
OBJECTIVE The aim of this study is to define the association between a genetic risk score (GRS) that combined the effect of multiple BMI-associated variants and gestational weight trajectory. Because pregnancy is a state of sympathetic activation, the association between gestational weight trajectory and variants in adrenergic pathways previously associated with weight was examined. METHODS In a previously defined cohort of pregnant women with (n = 1,504) and without gestational diabetes (GDM) (n = 435), weight trajectory was calculated using all weights during pregnancy. A GRS for BMI (GRSBMI ) was calculated using 31 common variants associated with BMI, and 10 variants in the adrenergic pathways were genotyped. Clinical and genetic factors were studied using generalized linear models. RESULTS Prepregnancy BMI was associated with the GRSBMI (P = 9.3 × 10-11 ) and parity (P = 4.54 × 10-17 ). The GRSBMI was associated with gestational weight trajectory in women with and without GDM (P = 0.041 and P < 0.0001, respectively); however, when prepregnancy BMI was included in the models, the associations disappeared (P > 0.05). Variants in adrenergic genes were not associated with gestational weight trajectory. CONCLUSIONS A GRS for BMI was associated with prepregnancy BMI but was not independently associated with gestational weight trajectory in women with and without GDM. Selected variants in adrenergic genes were not associated with gestational weight trajectory.
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Affiliation(s)
- Vivian K. Kawai
- Division of Clinical Pharmacology, Department of Medicine Vanderbilt University Medical Center, Nashville, TN, USA
| | - Samuel K. Nwosu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel Kurnik
- Division of Clinical Pharmacology, Department of Medicine Vanderbilt University Medical Center, Nashville, TN, USA
- Clinical Pharmacology Unit, Rambam Health Care Campus, Haifa, Israel
- Rappaport Faculty of Medicine, Technion – Israel Institute of Technology, Haifa, Israel
| | - Frank E. Harrell
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - C. Michael Stein
- Division of Clinical Pharmacology, Department of Medicine Vanderbilt University Medical Center, Nashville, TN, USA
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12
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Mărginean C, Mărginean CO, Bănescu C, Meliţ LE, Tripon F, Iancu M. The relationship among GNB3 rs5443, PNPLA3 rs738409, GCKR rs780094 gene polymorphisms, type of maternal gestational weight gain and neonatal outcomes (STROBE-compliant article). Medicine (Baltimore) 2019; 98:e16414. [PMID: 31305457 PMCID: PMC6641780 DOI: 10.1097/md.0000000000016414] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
The gestational weight gain is determined by food habits, environmental and genetic factors.The aims of this paper were to establish relationships between maternal gene polymorphisms (patatin-like phospholipase domain-containing protein 3 rs738409 [PNPLA3 rs738409], glucokinase regulatory protein rs780094 [GCKR rs780094], and guanine nucleotide-binding protein rs5443 [GNB3 rs5443]) and mothers' gestational weight gain, but also neonatal outcomes (birth weight, length, and ponderal index [PI]).We performed a cross-sectional study in a sample of 158 mothers and their product of conception' in an Obstetrics-Gynecology Clinic from Romania. We divided the pregnant women according to the Institute of Medicine recommendations into 3 subgroups: (1) insufficient gestational weight gain; (2) normal gestational weight gain; and (3) excessive gestational weight gain.The gestational weight gain among pregnant women included in this study was classified as insufficient (10.1%), normal (31%), and excessive (58.9%). We found a tendency towards statistical significance for mothers that were overweight or obese before pregnancy to present an excessive gestational weight gain as compared to the normal weight ones. Similarly, we identified a tendency for statistical significance regarding the association between the variant genotype of GNB3 rs5443 and excessive gestational weight gain. We noticed differences that tended to be statistical significant concerning aspartate aminotransferase values between the 3 subgroups, mothers with excessive gestational weight gain having higher values than mothers with normal gestational weight gain (median, IQR: 22.89[17.53; 31.59] for mothers with excessive gestational weight gain versus 22.71[18.58; 27.37] for mothers with normal gestational weight gain). In mothers with excessive gestational weight gain, we found a significant association between the variant genotype of PNPLA3 rs738409 polymorphism and neonatal PI noticing a decrease of this index in case of newborns from mothers carrying the variant genotype.Excessive gestational weight gain was noticed in pregnant women that were obese and overweight before pregnancy. We found a positive association between the variant genotype of GNB3 rs5443 polymorphism and excessive gestational weight gain. Similarly, the presence of variant genotype of PNPLA3 rs738409 in mothers was associated with a lower PI in their newborns. Our study pointed out the most important factors that influence gestational weight gain and related birth outcomes.
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Affiliation(s)
| | - Cristina Oana Mărginean
- Department of Pediatrics, University of Medicine, Pharmacy, Sciences and Technology Târgu Mureş
| | - Claudia Bănescu
- Genetics Laboratory, Center for Advanced Medical and Pharmaceutical Research, University of Medicine, Pharmacy, Sciences and Technology Târgu Mureş
| | - Lorena Elena Meliţ
- Department of Pediatrics, University of Medicine, Pharmacy, Sciences and Technology Târgu Mureş
| | - Florin Tripon
- Genetics Laboratory, Center for Advanced Medical and Pharmaceutical Research, University of Medicine, Pharmacy, Sciences and Technology Târgu Mureş
| | - Mihaela Iancu
- Department of Medical Informatics and Biostatistics, Iuliu Haţieganu University of Medicine and Pharmacy Cluj Napoca, Romania
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13
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Liu S, Liu Y, Liao S. Heterogeneous impact of type 2 diabetes mellitus-related genetic variants on gestational glycemic traits: review and future research needs. Mol Genet Genomics 2019; 294:811-847. [PMID: 30945019 DOI: 10.1007/s00438-019-01552-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 03/25/2019] [Indexed: 02/07/2023]
Abstract
Gestational glucose homeostasis influences mother's metabolic health, pregnancy outcomes, fetal development and offspring growth. To understand the genetic roles in pregnant glucose metabolism and genetic predisposition for gestational diabetes (GDM), we reviewed the recent literature up to Jan, 2018 and evaluated the influence of T2DM-related genetic variants on gestational glycemic traits and glucose tolerance. A total of 140 variants of 89 genes were integrated. Their associations with glycemic traits in and outside pregnancy were compared. The genetic circumstances underlying glucose metabolism exhibit a similarity between pregnant and non-pregnant populations. While, not all of the T2DM-associated genetic variants are related to pregnant glucose tolerance, such as genes involved in fasting insulin/C-peptide regulation. Some genetic variants may have distinct effects on gestational glucose homeostasis. And certain genes may be particularly involved in this process via specific mechanisms, such as HKDC1, MTNR1B, BACE2, genes encoding cell cycle regulators, adipocyte regulators, inflammatory factors and hepatic factors related to gestational glucose sensing and insulin signaling. However, it is currently difficult to evaluate these associations with quantitative synthesis due to inadequate data, different analytical methods, varied measurements for glycemic traits, controversies in diagnosis of GDM, and unknown ethnicity- and/or sex-related influences on pregnant maternal metabolism. In conclusion, different genetic associations with glycemic traits may exist between pregnant and non-pregnant conditions. Comprehensive research on specific genetic regulation in gestation is necessary.
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Affiliation(s)
- Shasha Liu
- Diabetes Center and Transplantation Translational Medicine, Key Laboratory of Sichuan Province, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Yihuanlu Xierduan 32#, Chengdu, 610072, China
| | - Yunqiang Liu
- Department of Medical Genetics and Division of Morbid Genomics, State Key Laboratory of Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, China
| | - Shunyao Liao
- Diabetes Center and Transplantation Translational Medicine, Key Laboratory of Sichuan Province, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Yihuanlu Xierduan 32#, Chengdu, 610072, China.
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14
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Khan IA, Jahan P, Hasan Q, Rao P. Genetic confirmation of T2DM meta-analysis variants studied in gestational diabetes mellitus in an Indian population. Diabetes Metab Syndr 2019; 13:688-694. [PMID: 30641791 DOI: 10.1016/j.dsx.2018.11.035] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 11/11/2018] [Indexed: 01/25/2023]
Abstract
BACKGROUND Meta-analysis is useful for combining the results of different studies statistically to confirm genuine associations in genetics. Based on earlier reports, we aimed to investigate the association between type 2 diabetes mellitus (T2DM) genetic variants identified in a previous meta-analysis in gestational diabetes mellitus (GDM) in an Indian woman. MATERIAL AND METHODS In this study, 137 pregnant women with GDM and 150 pregnant women were selected on the basis of their serum glucose levels. The six single nucleotide polymorphisms (SNPs) of different genes studied had known involvement in pancreatic β-cell function, particular pathways linked to T2DM, and other biological functions. Genomic DNA was isolated from the 287 women for polymerase chain reaction and restriction fragment length polymorphism analyses. RESULTS The rs7903146, rs13266634, rs2283228, rs5210 and rs179881 SNPs were found to be positively associated with GDM when calculated for genotype and allele frequencies (p < 0.05), but rs680 (ApaI) variant did not show statistically significant association (p = 0.31). The rs7903146, rs2283228, rs5210 and rs680 variants showed a strong association with oral glucose tolerance test values. CONCLUSION The SNPs studied in this GDM had the same role as those identified in a previous T2DM meta-analysis, and showed positive association in the Indian women. Meta-analyses should be implemented to assess the IGF2 gene in GDM subjects.
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Affiliation(s)
- Imran Ali Khan
- Department of Genetics and Molecular Medicine, Kamineni Hospitals, LB Nagar, Hyderabad, India; Department of Genetics, Vasavi Medical and Research Centre, Khairathabad, Hyderabad, India; Department of Genetics and Biotechnology, Osmania University, Tarnaka, Hyderabad, India
| | - Parveen Jahan
- Department of Genetics and Biotechnology, Osmania University, Tarnaka, Hyderabad, India
| | - Qurratulain Hasan
- Department of Genetics and Molecular Medicine, Kamineni Hospitals, LB Nagar, Hyderabad, India; Department of Genetics, Vasavi Medical and Research Centre, Khairathabad, Hyderabad, India
| | - Pragna Rao
- Department of Biochemistry, Kasturba Medical College, Manipal University, Manipal, Karnataka, India.
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15
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Dong Y, Teleman AA, Jedmowski C, Wirtz M, Hell R. The Arabidopsis THADA homologue modulates TOR activity and cold acclimation. PLANT BIOLOGY (STUTTGART, GERMANY) 2019; 21 Suppl 1:77-83. [PMID: 30098100 DOI: 10.1111/plb.12893] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 08/02/2018] [Indexed: 05/21/2023]
Abstract
Low temperature is one of the most important environmental factors that affect global survival of humans and animals and equally importantly the distribution of plants and crop productivity. Survival of metazoan cells under cold stress requires regulation of the sensor-kinase Target Of Rapamycin (TOR). TOR controls growth of eukaryotic cells by adjusting anabolic and catabolic metabolism. Previous studies identified the Thyroid Adenoma Associated (THADA) gene as the major effect locus by positive selection in the evolution of modern human adapted to cold. Here we investigate the role of THADA in TOR signaling and cold acclimation of plants. We applied BLAST searches and homology modeling to identify the AtTHADA (AT3G55160) in Arabidopsis thaliana as the highly probable orthologue protein. Reverse genetics approaches were combined with immunological detection of TOR activity and metabolite profiling to address the role of the TOR and THADA for growth regulation and cold acclimation. Depletion of the AtTHADA gene caused complete or partial loss of full-length mRNA, respectively, and significant retardation of growth under non-stressed conditions. Furthermore, depletion of AtTHADA caused hypersensitivity towards low-temperatures. Atthada displayed a lowered energy charge. This went along with decreased TOR activity, which offers a molecular explanation for the slow growth phenotype of Atthada. Finally, we used TOR RNAi lines to identify the de-regulation of TOR activity as one determinant for sensitivity towards low-temperatures. Taken together our results provide evidence for a conserved function of THADA in cold acclimation of eukaryotes and suggest that cold acclimation in plants requires regulation of TOR.
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Affiliation(s)
- Y Dong
- Centre for Organismal Studies (COS), University of Heidelberg, Heidelberg, Germany
| | - A A Teleman
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - M Wirtz
- Centre for Organismal Studies (COS), University of Heidelberg, Heidelberg, Germany
| | - R Hell
- Centre for Organismal Studies (COS), University of Heidelberg, Heidelberg, Germany
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16
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Beysel S, Eyerci N, Ulubay M, Caliskan M, Kizilgul M, Hafızoğlu M, Cakal E. Maternal genetic contribution to pre-pregnancy obesity, gestational weight gain, and gestational diabetes mellitus. Diabetol Metab Syndr 2019; 11:37. [PMID: 31114636 PMCID: PMC6518700 DOI: 10.1186/s13098-019-0434-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Accepted: 05/08/2019] [Indexed: 12/16/2022] Open
Abstract
INTRODUCTION Pre-pregnancy obesity, gestational diabetes mellitus (GDM), and gestational weight gain (GWG) are associated with each other. This is the first study to investigate whether genetic variants were associated with having GDM, and whether genetic variants-related GDM were associated with adiposity including pre-pregnancy obesity and excessive GWG in Turkish women. PATIENTS AND METHODS Women with GDM (n = 160) and without GDM (n = 145) were included in case-controlled study. Genotyping of the HNF1A gene (p.I27L rs1169288, p.98V rs1800574, p.S487N rs2464196), the VDR gene (p.BsmI rs1544410, p.ApaI rs7975232, p.TaqI rs731236, p.FokI rs2228570), and FTO gene (rs9939609) SNPs were performed by using RT-PCR. RESULTS The FTO AA genotype was associated with an increased risk of having GDM (AA vs. AT + TT, 24.4% vs. 12.4%, OR = 2.27, 95% CI [1.23-4.19], p = 0.007). The HNF1A p.I27L GT/TT genotype was associated with increased GDM risk (GT + TT vs. GG-wild, 79.4% vs. 65.5%, OR = 2.02, 95% CI 1.21-3.38], p = 0.007). However, all VDR gene SNPs and the HNF1A p.A98V, p.S487N were not associated with having GDM (p > 0.05). The FTO AA genotype was associated with an increased risk for pre-pregnancy overweight/obesity (OR = 1.43, 95% CI [1.25-3.4], p = 0.035), but not associated with excessive GWG after adjusting for pre-pregnancy weight (p > 0.05). Pre-pregnancy weight, weight at delivery, and GWG did not differ in both VDR and HNF1A gene carriers (p > 0.05). HOMA-IR and HbA1c were increased in both p.I27L TT and FTO AA genotype carriers (p < 0.05). CONCLUSION The adiposity-related gene FTO is associated with GDM by the effect of FTO on pre-pregnancy obesity. The diabetes-related p.I27L gene is associated with GDM by increasing insulin resistance.
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Affiliation(s)
- Selvihan Beysel
- Department of Endocrinology and Metabolism, Ankara Diskapi Yildirim Beyazit Teaching and Training Research Hospital, Ankara, Turkey
- Department of Medical Biology, Baskent University, Ankara, Turkey
- Department of Endocrinology and Metabolism, Afyonkarahisar Saglik Bilimleri University, Afyon, Turkey
| | - Nilnur Eyerci
- Department of Genetic Research, Ankara Diskapi Yildirim Beyazit Teaching and Training Research Hospital, Ankara, Turkey
| | - Mustafa Ulubay
- Department of Obstetrics and Gynecology, Gulhane School of Medicine, Ankara, Turkey
| | - Mustafa Caliskan
- Department of Endocrinology and Metabolism, Ankara Diskapi Yildirim Beyazit Teaching and Training Research Hospital, Ankara, Turkey
| | - Muhammed Kizilgul
- Department of Endocrinology and Metabolism, Ankara Diskapi Yildirim Beyazit Teaching and Training Research Hospital, Ankara, Turkey
| | - Merve Hafızoğlu
- Department of İnternal Medicine, Afyonkarahisar Saglik Bilimleri University, Afyon, Turkey
| | - Erman Cakal
- Department of Endocrinology and Metabolism, Ankara Diskapi Yildirim Beyazit Teaching and Training Research Hospital, Ankara, Turkey
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Zhang YJ, Li L, Wang ZJ, Zhang XJ, Zhao H, Zhao Y, Wang XT, Li CZ, Wan JP. Association study between variants in LHCGR DENND1A and THADA with preeclampsia risk in Han Chinese populations. J Matern Fetal Neonatal Med 2018; 32:3801-3805. [PMID: 29727258 DOI: 10.1080/14767058.2018.1472228] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Objective: To evaluate the association between preeclampsia and three single nucleotide polymorphisms (rs13405728 in LHCGR gene; rs13429458 in THADA gene, and rs2479106 in DENND1A gene) which were identified to be genetic variants of polycystic ovary syndrome (PCOS) by genome-wide association study in Han Chinese populations. Methods: A total of 784 northern Han Chinese women (378 controls and 406 cases) were genotyped for the three genetic variants by polymerase chain reaction and direct sequencing. Unconditional logistic regression analysis was used to adjust the impact of prepregnancy body mass index, primiparas, and maternal age. Results: No significant difference was found in the allele frequencies of the three genetic variants between cases and controls (p > .05), but genotype frequency of the SNP rs2479106 was significantly differ between cases and controls when analyzed under recessive models (p = .02). There was also a substantial difference in the genotype frequencies of the SNP rs13429458 between cases and controls under additive models (p = .01). Conclusions: Genetic variants of PCOS (rs13405728 in LHCGR gene; rs13429458 in THADA gene and rs2479106 in DENND1A gene) may not be involved in the development of preeclampsia in Han Chinese women.
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Affiliation(s)
- Ya-Jie Zhang
- a Center for Reproductive Medicine , Jinan Maternity and Child Care Hospital , Jinan , China
| | - Lei Li
- b Department of Obstetrics and Gynecology , Shandong Provincial Hospital Affiliated to Shandong University , Jinan , China
| | - Zhen-Jing Wang
- c Center for Reproductive Medicine , Shandong Provincial Hospital Affiliated to Shandong University , Jinan , China
| | - Xiao-Jing Zhang
- b Department of Obstetrics and Gynecology , Shandong Provincial Hospital Affiliated to Shandong University , Jinan , China
| | - Han Zhao
- c Center for Reproductive Medicine , Shandong Provincial Hospital Affiliated to Shandong University , Jinan , China
| | - Yan Zhao
- b Department of Obstetrics and Gynecology , Shandong Provincial Hospital Affiliated to Shandong University , Jinan , China
| | - Xie-Tong Wang
- b Department of Obstetrics and Gynecology , Shandong Provincial Hospital Affiliated to Shandong University , Jinan , China
| | - Chang-Zhong Li
- b Department of Obstetrics and Gynecology , Shandong Provincial Hospital Affiliated to Shandong University , Jinan , China
| | - Ji-Peng Wan
- b Department of Obstetrics and Gynecology , Shandong Provincial Hospital Affiliated to Shandong University , Jinan , China
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18
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Warrington NM, Richmond R, Fenstra B, Myhre R, Gaillard R, Paternoster L, Wang CA, Beaumont RN, Das S, Murcia M, Barton SJ, Espinosa A, Thiering E, Atalay M, Pitkänen N, Ntalla I, Jonsson AE, Freathy R, Karhunen V, Tiesler CMT, Allard C, Crawford A, Ring SM, Melbye M, Magnus P, Rivadeneira F, Skotte L, Hansen T, Marsh J, Guxens M, Holloway JW, Grallert H, Jaddoe VWV, Lowe Jr WL, Roumeliotaki T, Hattersley AT, Lindi V, Pahkala K, Panoutsopoulou K, Standl M, Flexeder C, Bouchard L, Aagaard Nohr E, Marina LS, Kogevinas M, Niinikoski H, Dedoussis G, Heinrich J, Reynolds RM, Lakka T, Zeggini E, Raitakari OT, Chatzi L, Inskip HM, Bustamante M, Hivert MF, Jarvelin MR, Sørensen TIA, Pennell C, Felix JF, Jacobsson B, Geller F, Evans DM, Lawlor DA. Maternal and fetal genetic contribution to gestational weight gain. Int J Obes (Lond) 2018; 42:775-784. [PMID: 28990592 PMCID: PMC5784805 DOI: 10.1038/ijo.2017.248] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 08/27/2017] [Accepted: 09/03/2017] [Indexed: 12/25/2022]
Abstract
BACKGROUND Clinical recommendations to limit gestational weight gain (GWG) imply high GWG is causally related to adverse outcomes in mother or offspring, but GWG is the sum of several inter-related complex phenotypes (maternal fat deposition and vascular expansion, placenta, amniotic fluid and fetal growth). Understanding the genetic contribution to GWG could help clarify the potential effect of its different components on maternal and offspring health. Here we explore the genetic contribution to total, early and late GWG. PARTICIPANTS AND METHODS A genome-wide association study was used to identify maternal and fetal variants contributing to GWG in up to 10 543 mothers and 16 317 offspring of European origin, with replication in 10 660 mothers and 7561 offspring. Additional analyses determined the proportion of variability in GWG from maternal and fetal common genetic variants and the overlap of established genome-wide significant variants for phenotypes relevant to GWG (for example, maternal body mass index (BMI) and glucose, birth weight). RESULTS Approximately 20% of the variability in GWG was tagged by common maternal genetic variants, and the fetal genome made a surprisingly minor contribution to explain variation in GWG. Variants near the pregnancy-specific beta-1 glycoprotein 5 (PSG5) gene reached genome-wide significance (P=1.71 × 10-8) for total GWG in the offspring genome, but did not replicate. Some established variants associated with increased BMI, fasting glucose and type 2 diabetes were associated with lower early, and higher later GWG. Maternal variants related to higher systolic blood pressure were related to lower late GWG. Established maternal and fetal birth weight variants were largely unrelated to GWG. CONCLUSIONS We found a modest contribution of maternal common variants to GWG and some overlap of maternal BMI, glucose and type 2 diabetes variants with GWG. These findings suggest that associations between GWG and later offspring/maternal outcomes may be due to the relationship of maternal BMI and diabetes with GWG.
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Affiliation(s)
- N M Warrington
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
| | - R Richmond
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - B Fenstra
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
| | - R Myhre
- Norwegian Institute of Public Health, Oslo, Norway
| | - R Gaillard
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - L Paternoster
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - C A Wang
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
| | - R N Beaumont
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - S Das
- Department of Public Health and Primary Care, School of Public Health, Imperial College London, London, UK
| | - M Murcia
- Epidemiology and Environmental Health Joint Research Unit, FISABIO–Universitat Jaume I–Universitat de València, Valencia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Spain
| | - S J Barton
- MRC Lifecourse Epidemiology Unit, Faulty of Medicine, University of Southampton, Southampton, UK
| | - A Espinosa
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Spain
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - E Thiering
- Institute of Epidemiology I, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany
| | - M Atalay
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - N Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - I Ntalla
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - A E Jonsson
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, and Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - R Freathy
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - V Karhunen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - C M T Tiesler
- Institute of Epidemiology I, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany
| | - C Allard
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Canada
| | - A Crawford
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- British Heart Foundation Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - S M Ring
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- ALSPAC (Children of the 90s), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - M Melbye
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
- Department of Clinical Medicine, Copenhagen University, Copenhagen, Denmark
- Department of Medicine, Stanford School of Medicine, Stanford, CA, USA
| | - P Magnus
- Norwegian Institute of Public Health, Oslo, Norway
| | - F Rivadeneira
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - L Skotte
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
| | - T Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, and Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - J Marsh
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
| | - M Guxens
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Spain
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre–Sophia Children’s Hospital, Rotterdam, The Netherlands
| | - J W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
| | - H Grallert
- Institute of Epidemiology II, Research Unit of Molecular Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Clinical Cooperation Group Type 2 Diabetes, Helmholtz Zentrum München, Neuherberg, Germany
- Clinical Cooperation Group Nutrigenomics and Type 2 Diabetes, Helmholtz Zentrum München, Neuherberg, Germany
- Technische Universität München, Freising, Germany
| | - V W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - W L Lowe Jr
- Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - T Roumeliotaki
- Department of Social Medicine, University of Crete, Crete, Greece
| | - A T Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - V Lindi
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - K Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Paavo Nurmi Centre, Sports and Exercise Medicine Unit, Department of Health and Physical Activity, Turku, Finland
| | - K Panoutsopoulou
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - M Standl
- Institute of Epidemiology I, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
| | - C Flexeder
- Institute of Epidemiology I, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
| | - L Bouchard
- Department of Biochemistry, Faculty of medicine and life sciences, Université de Sherbrooke, Sherbrooke, Canada
| | - E Aagaard Nohr
- Public Health Division of Gipuzkoa, Basque Government, Vitoria-Gasteiz, Spain
| | - L Santa Marina
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Spain
- Health Research Institute, Biodonostia, San Sebastián, Gipuzkoa, Spain
- Health Research Institute, Biodonostia, San Sebastián, Spain
| | - M Kogevinas
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Spain
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - H Niinikoski
- Department of Pediatrics, Turku University Hospital, Turku, Finland
| | - G Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece
| | - J Heinrich
- Institute of Epidemiology I, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Inner City Clinic, University Hospital Munich, Ludwig Maximilian University of Munich, Munich, Germany
| | - R M Reynolds
- British Heart Foundation Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - T Lakka
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - E Zeggini
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - O T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - L Chatzi
- Department of Social Medicine, University of Crete, Crete, Greece
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Social Medicine, University of Crete, Crete, Greece
- Department of Genetics and Cell Biology, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - H M Inskip
- MRC Lifecourse Epidemiology Unit, Faulty of Medicine, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - M Bustamante
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Spain
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - M-F Hivert
- Department of Population Medicine at Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - M-R Jarvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, MRC–PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - T I A Sørensen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, and Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Epidemiology (formally the Institute of Preventive Medicine), Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark
| | - C Pennell
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
| | - J F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - B Jacobsson
- Department of Obstetrics and Gynecology, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden
- Department of Genetics and Bioinformatics, Domain of Health Data and Digitalization, Institute of Public Health, Oslo, Norway
| | - F Geller
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
| | - D M Evans
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - D A Lawlor
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
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Franzago M, Fraticelli F, Marchetti D, Celentano C, Liberati M, Stuppia L, Vitacolonna E. Nutrigenetic variants and cardio-metabolic risk in women with or without gestational diabetes. Diabetes Res Clin Pract 2018; 137:64-71. [PMID: 29325775 DOI: 10.1016/j.diabres.2018.01.001] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2017] [Revised: 12/07/2017] [Accepted: 01/02/2018] [Indexed: 01/15/2023]
Abstract
AIM Gestational diabetes mellitus (GDM) is the most frequent metabolic disorder in pregnancy and it can be considered a silent risk associated to T2DM and CVD later in life. The aim of this study was to investigate the association of clinical parameters with nine single nucleotide polymorphisms (SNPs) involved with nutrients and metabolism in women with or without GDM in order to identify potential routine clinical markers for early prevention. METHODS Nine gene variants associated with nutrients and metabolism, namely PPARG2 rs1801282 (C > G); PPARGC1A rs8192678 (C > T); TCF7L2 rs7903146 (C > T); LDLR rs2228671 (C > T); MTHFR rs1801133 (C > T); APOA5 rs662799 (T > C); GCKR rs1260326 (C > T); FTO rs9939609 (T > A); MC4R rs17782313 (T > C) were genotyped in 104 GDM cases and 124 controls using High Resolution Melting (HRM) analysis. RESULTS The genetic variant rs7903146 (C > T) in TCF7L2 gene showed a strong association with GDM risk (OR: 2.56; 95% CI: [1.24-5.29]). Moreover, a significant correlation was observed between lipid parameters and polymorphisms in other genes, namely PPARG2 [p = 0,03], APOA5 [p = 0,02], MC4R [p = 0,03], LDLR [p = 0,04] and FTO [p = 0,03]. In addition, rs17782313 variant, mapped close to MC4R gene, was associated to BMI in pre-pregnancy [p = 0,02] and at the end of pregnancy [p = 0,03] in GDM group. CONCLUSION In our study, we found significant associations between routine clinical parameters and some gene variants connected with nutrients and metabolism in women with GDM. These results can provide useful information to develop effective tools and possible personalized intervention strategies in a timely manner.
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Affiliation(s)
- Marica Franzago
- Department of Psychological, Health and Territorial Sciences, School of Medicine and Health Sciences, "G. d'Annunzio" University, Chieti-Pescara, Chieti, Italy
| | - Federica Fraticelli
- Department of Medicine and Aging, School of Medicine and Health Sciences, "G. d'Annunzio" University, Chieti-Pescara, Chieti, Italy
| | - Daniela Marchetti
- Department of Psychological, Health and Territorial Sciences, School of Medicine and Health Sciences, "G. d'Annunzio" University, Chieti-Pescara, Chieti, Italy; Department of Medicine and Aging, School of Medicine and Health Sciences, "G. d'Annunzio" University, Chieti-Pescara, Chieti, Italy
| | - Claudio Celentano
- Department of Medicine and Aging, School of Medicine and Health Sciences, "G. d'Annunzio" University, Chieti-Pescara, Chieti, Italy
| | - Marco Liberati
- Department of Medicine and Aging, School of Medicine and Health Sciences, "G. d'Annunzio" University, Chieti-Pescara, Chieti, Italy
| | - Liborio Stuppia
- Department of Psychological, Health and Territorial Sciences, School of Medicine and Health Sciences, "G. d'Annunzio" University, Chieti-Pescara, Chieti, Italy
| | - Ester Vitacolonna
- Department of Medicine and Aging, School of Medicine and Health Sciences, "G. d'Annunzio" University, Chieti-Pescara, Chieti, Italy.
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The Association between Obesity-Risk Genes and Gestational Weight Gain Is Modified by Dietary Intake in African American Women. J Nutr Metab 2018; 2018:5080492. [PMID: 29686896 PMCID: PMC5852892 DOI: 10.1155/2018/5080492] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Accepted: 01/09/2018] [Indexed: 12/20/2022] Open
Abstract
Obesity-risk genes have been associated with dietary intake, appetite regulation, and gestational weight gain (GWG). The purpose of this study was to examine whether dietary intake including total energy intake and macronutrients modify or mediate the association between obesity-risk genes and GWG. An observational study was conducted with 85 African American pregnant women. Sociodemographic, medical, and lifestyle factors and dietary recalls were collected during pregnancy. Seven obesity-risk genetic variants were genotyped. Regression analyses with bootstrapping methods were used to examine the moderation and mediation effects of dietary intake. The mean GWG was 14.2 kg, and 55.3% of the women gained above the Institute of Medicine GWG guidelines. A nominally significant association was found between rs17782313 (close to MC4R) and percentage of energy intake from fat (P=0.043). A variant downstream of KCTD15 (rs11084753) was nominally significantly related to GWG (P=0.023). There was a significant interaction between the KCTD15 polymorphism and dietary fat intake (P=0.048). Women with the AG genotype gained more weight during pregnancy with more dietary fat consumption. In conclusion, our results indicate that dietary macronutrients, especially fat intake, may modify the effect of the KCTD15 gene on GWG. Improved knowledge of gene-diet interactions can facilitate the development of personalized interventions.
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Groth SW, LaLonde A, Wu T, Fernandez ID. Obesity candidate genes, gestational weight gain, and body weight changes in pregnant women. Nutrition 2017; 48:61-66. [PMID: 29469022 DOI: 10.1016/j.nut.2017.11.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2017] [Revised: 10/17/2017] [Accepted: 11/01/2017] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To examine the associations of two obesity-associated genes, FTO (rs9939609) and GNB3 (rs5443) single nucleotide polymorphisms (SNPs), with early pregnancy body mass index, gestational weight gain, and postpartum weight retention. METHODS Secondary data analysis of self-identified white (n = 580) and black (n = 194) women who participated in a randomized controlled trial (2009-2014) and provided a saliva sample of DNA. Bivariate relationships were assessed using analysis of variance. Multiple regression models assessed the relationship between outcomes and gene SNPs, controlling for income, parity, and smoking status. RESULTS FTO and GNB3 gene associations with pregnancy weight were different by racial group and early pregnancy body mass index. Obese black women homozygote for the FTO risk allele (AA) had a higher gestational weight gain compared with non-risk homozygotes (TT) (P = 0.006). GNB3 non-risk CC homozygotes tended to have a lower gestational weight gain compared with heterozygotes (P = 0.05). White GNB3 C carriers tended to be heavier in early pregnancy (P <0.1) and GNB3 homozygote (TT) overweight women tended to have lower postpartum weight retention than C carriers. CONCLUSIONS The FTO gene and possibly the GNB3 gene are associated with high gestational weight gain in obese black women. Obese carriers of the FTO risk allele gained 4.1 kg (AT) and 7.6 kg (TT) more than those without risk alleles. Overweight GNB3 heterozygotes (CT) gained 6.6 kg less than homozygotes (CC). Overweight or obese black women who have either risk variant are at risk for high gestational weight gain.
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Affiliation(s)
- Susan W Groth
- University of Rochester School of Nursing, Rochester, NY, USA; Department of Public Health Sciences, University of Rochester, Rochester, NY, USA.
| | - Amy LaLonde
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA
| | - Tongtong Wu
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA
| | - I Diana Fernandez
- Department of Public Health Sciences, University of Rochester, Rochester, NY, USA
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22
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Meng Y, Groth SW, Stewart P, Smith JA. An Exploration of the Determinants of Gestational Weight Gain in African American Women: Genetic Factors and Energy Expenditure. Biol Res Nurs 2017; 20:118-125. [PMID: 29161908 DOI: 10.1177/1099800417743326] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND Excessive gestational weight gain (GWG) has a long-term impact on women's body weight and contributes to the development of obesity in the mother and her child. Many risk factors for GWG have been identified, but to date, only 6-33.8% of the variance in GWG has been explained. The purpose of this study was to evaluate the overall variance of GWG that can be explained by including weight-adjusted resting metabolic rate (aRMR) and a genetic risk score constructed on obesity-related genes in addition to sociodemographic and lifestyle factors. METHODS In this observational study involving 55 African American women, data collected/measured during pregnancy included sociodemographic factors, medical information, lifestyle factors, aRMR, and seven obesity-related genes. Multivariable linear regression was performed to evaluate the variance in GWG explained by the potential risk factors listed above. RESULTS The mean GWG was 15 kg (±7.5 kg), and 63.6% of women gained more than the Institute of Medicine's GWG recommendations. The final regression model explained 53.3% of the variance in GWG. Higher genetic risk score, lower aRMR, and higher dietary intake of total energy and percentage of fat were significantly associated with increased GWG ( p < .05). These factors explained 18% additional variance in GWG over that explained by significant sociodemographic and lifestyle factors in the analysis (i.e., maternal age, prepregnancy body mass index, parity, illegal drug use, and education). CONCLUSION Overall, our results indicate that the genetic risk score, aRMR, and dietary intake have a substantial impact on GWG in African American women.
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Affiliation(s)
- Ying Meng
- 1 Clinical and Translational Science Institute, University of Rochester, Rochester, NY, USA.,2 School of Nursing, University of Rochester, Rochester, NY, USA
| | - Susan W Groth
- 2 School of Nursing, University of Rochester, Rochester, NY, USA
| | - Patricia Stewart
- 3 Department of Pediatrics, University of Rochester Medical Center, Rochester, NY, USA
| | - Joyce A Smith
- 2 School of Nursing, University of Rochester, Rochester, NY, USA
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23
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Li A, Teo KK, Morrison KM, McDonald SD, Atkinson SA, Anand SS, Meyre D. A genetic link between prepregnancy body mass index, postpartum weight retention, and offspring weight in early childhood. Obesity (Silver Spring) 2017; 25:236-243. [PMID: 27883278 DOI: 10.1002/oby.21707] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Revised: 08/22/2016] [Accepted: 09/09/2016] [Indexed: 02/04/2023]
Abstract
OBJECTIVE The effects of maternal prepregnancy body mass index (BMI) and gestational weight gain (GWG) on maternal and offspring obesity traits, as well as the maternal and offspring genetic contribution to GWG and postpartum weight retention, were examined. METHODS Blood samples from mothers (n = 608) and offspring (n = 541) were genotyped for 83 BMI-associated SNPs and 47 waist-to-hip ratio (WHR)-associated SNPs. Linear regression and mixed-effects regression models were performed to examine clinical epidemiological and genetic associations with unweighted and weighted BMI and WHR genetic risk scores (GRS). RESULTS Prepregnancy BMI was positively associated with offspring weight and BMI Z-score from birth to 5 years. GWG was positively associated with maternal postpartum weight retention at 1 and 5 years and with offspring weight Z-score from birth to 5 years old. The maternal unweighted BMI GRS was associated with prepregnancy BMI, postpartum weight retention at 5 years, and offspring weight Z-score from birth to 5 years old, but not associated with GWG. Both maternal and offspring unweighted WHR GRSs were negatively associated with GWG. CONCLUSIONS Maternal BMI-associated SNPs may contribute to the genetic link between prepregnancy BMI variation, long-term postpartum weight retention, and offspring birth weight and longitudinal weight. Maternal and offspring WHR-associated SNPs may contribute to GWG variation.
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Affiliation(s)
- Aihua Li
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
| | - Koon K Teo
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Katherine M Morrison
- Department of Pediatrics, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
| | - Sarah D McDonald
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
- Department of Obstetrics and Gynecology, McMaster University, Hamilton, Ontario, Canada
| | - Stephanie A Atkinson
- Department of Pediatrics, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
| | - Sonia S Anand
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - David Meyre
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
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24
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Association of the FTO (rs9939609) and MC4R (rs17782313) gene polymorphisms with maternal body weight during pregnancy. Nutrition 2016; 32:1223-30. [DOI: 10.1016/j.nut.2016.04.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Revised: 04/15/2016] [Accepted: 04/27/2016] [Indexed: 12/19/2022]
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Abstract
OBJECTIVES Excessive gestational weight gain (GWG) is associated with higher body mass index (BMI) later in life. Increased BMI is associated with health problems, but there is limited evidence linking GWG directly to later health in black women. We examined the association between GWG and health conditions 18 years after a first birth. METHODS This study was a secondary data analysis of 467 urban black women, enrolled during pregnancy (1990-1991). GWG was the difference between self-reported pre-pregnancy weight and measured weight at delivery. Hypertension, diabetes, obesity, and self-reported health were assessed with self-report and measurements of blood pressure, height, and weight, approximately 18 years after first childbirth. RESULTS Higher pre-pregnancy BMI was associated with increased probability of each health condition. Higher GWG was associated with hypertension for women with a pre-pregnancy BMI under 21.3 kg/m(2) (P < .05) and obesity for women with a pre-pregnancy BMI under 25.9 kg/m(2) (P < .05). Diabetes and poor health were not associated with GWG. CONCLUSIONS GWG may impact a mother's hypertension and obesity status 18 years after childbirth for underweight and normal weight women.
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26
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Chang T, Verma BA, Shull T, Moniz MH, Kohatsu L, Plegue MA, Collins-Thompson K. Crowdsourcing and the Accuracy of Online Information Regarding Weight Gain in Pregnancy: A Descriptive Study. J Med Internet Res 2016; 18:e81. [PMID: 27056465 PMCID: PMC4840255 DOI: 10.2196/jmir.5138] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Revised: 12/02/2015] [Accepted: 01/23/2016] [Indexed: 11/25/2022] Open
Abstract
Background Excess weight gain affects nearly half of all pregnancies in the United States and is a strong risk factor for adverse maternal and fetal outcomes, including long-term obesity. The Internet is a prominent source of information during pregnancy; however, the accuracy of this online information is unknown. Objective To identify, characterize, and assess the accuracy of frequently accessed webpages containing information about weight gain during pregnancy. Methods A descriptive study was used to identify and search frequently used phrases related to weight gain during pregnancy on the Google search engine. The first 10 webpages of each query were characterized by type and then assessed for accuracy and completeness, as compared to Institute of Medicine guidelines, using crowdsourcing. Results A total of 114 queries were searched, yielding 305 unique webpages. Of these webpages, 181 (59.3%) included information regarding weight gain during pregnancy. Out of 181 webpages, 62 (34.3%) contained no specific recommendations, 48 (26.5%) contained accurate but incomplete recommendations, 41 (22.7%) contained complete and accurate recommendations, and 22 (12.2%) were inaccurate. Webpages were most commonly from for-profit websites (112/181, 61.9%), followed by government (19/181, 10.5%), medical organizations or associations (13/181, 7.2%), and news sites (12/181, 6.6%). The largest proportion of for-profit sites contained no specific recommendations (44/112, 39.3%). Among pages that provided inaccurate information (22/181, 12.2%), 68% (15/22) were from for-profit sites. Conclusions For-profit websites dominate the online space with regard to weight gain during pregnancy and largely contain incomplete, inaccurate, or no specific recommendations. This represents a significant information gap regarding an important risk factor for obesity among mothers and infants. Our findings suggest that greater clinical and public health efforts to disseminate accurate information regarding healthy weight gain during pregnancy may help prevent significant morbidity and may support healthier pregnancies among at-risk women and children.
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Affiliation(s)
- Tammy Chang
- Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States.
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Larsen SC, Ängquist L, Laurin C, Morgen CS, Jakobsen MU, Paternoster L, Smith GD, Olsen SF, Sørensen TIA, Nohr EA. Association between Maternal Fish Consumption and Gestational Weight Gain: Influence of Molecular Genetic Predisposition to Obesity. PLoS One 2016; 11:e0150105. [PMID: 26930408 PMCID: PMC4773113 DOI: 10.1371/journal.pone.0150105] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 02/09/2016] [Indexed: 01/08/2023] Open
Abstract
Background Studies suggest that fish consumption can restrict weight gain. However, little is known about how fish consumption affects gestational weight gain (GWG), and whether this relationship depends on genetic makeup. Objective To examine the association between fish consumption and GWG, and whether this relationship is dependent on molecular genetic predisposition to obesity. Design A nested case-cohort study based on the Danish National Birth Cohort (DNBC) sampling the most obese women (n = 990) and a random sample of the remaining participants (n = 1,128). Replication of statistically significant findings was attempted in the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 4,841). We included 32 body mass index (BMI) associated single nucleotide polymorphisms (SNPs) and 5 SNPs found associated with GWG. BMI associated SNPs were combined in a genetic risk score (GRS). Associations between consumption of fish, GRS or individual variants and GWG were analysed, and interactions between fish and the GRS or individual variants were examined. Results In the DNBC, each portion/week (150 g) of fatty fish was associated with a higher GWG of 0.58 kg (95% CI: 0.16, 0.99, P<0.01). For total fish and lean fish, similar patterns were observed, but these associations were not statistically significant. We found no association between GRS and GWG, and no interactions between GRS and dietary fish on GWG. However, we found an interaction between the PPARG Pro12Ala variant and dietary fish. Each additional Pro12Ala G-allele was associated with a GWG of -0.83 kg (95% CI: -1.29, -0.37, P<0.01) per portion/week of dietary fish, with the same pattern for both lean and fatty fish. In ALSPAC, we were unable to replicate these findings. Conclusion We found no consistent evidence of association between fish consumption and GWG, and our results indicate that the association between dietary fish and GWG has little or no dependency on GRS or individual SNPs.
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Affiliation(s)
- Sofus C. Larsen
- Research Unit for Dietary Studies at the Parker Institute, Bispebjerg and Frederiksberg Hospitals, the Capital Region, Copenhagen, Denmark
- Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, Denmark
- * E-mail:
| | - Lars Ängquist
- Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, Denmark
| | - Charles Laurin
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Camilla S. Morgen
- Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, Denmark
| | - Marianne U. Jakobsen
- Department of Public Health, Section for Epidemiology, Aarhus University, Denmark
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Sjurdur F. Olsen
- Department of Epidemiology Research, Centre for Fetal Programming, Statens Serum Institut, 2300 Copenhagen S, Denmark
- Department of Nutrition, Harvard T. H. Chan School of Public Health, 655 Huntington Avenue, Boston, Massachusetts, United States of America
| | - Thorkild I. A. Sørensen
- Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, Denmark
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
- Novo Nordisk Foundation Center for Basic Metabolic Research and Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ellen A. Nohr
- Research Unit of Gynaecology and Obstetrics, Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
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Heritability of gestational weight gain--a Swedish register-based twin study. Twin Res Hum Genet 2015; 18:410-8. [PMID: 26111621 DOI: 10.1017/thg.2015.38] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Gestational weight gain (GWG) is a complex trait involving intrauterine environmental, maternal environmental, and genetic factors. However, the extent to which these factors contribute to the total variation in GWG is unclear. We therefore examined the genetic and environmental influences on the variation in GWG in the first and second pregnancy in monozygotic (MZ) and dizygotic (DZ) twin mother-pairs. Further, we explored if any co-variance existed between factors influencing the variation in GWG of the mothers’ first and second pregnancies. By using Swedish nationwide record-linkage data, we identified 694 twin mother-pairs with complete data on their first pregnancy and 465 twin mother-pairs with complete data on their second pregnancy during 1982–2010. For a subanalysis, 143 twin mother-pairs had complete data on two consecutive pregnancies during the study period. We used structural equation modeling (SEM) to assess the contribution of genetic, shared, and unique environmental factors to the variation in GWG. A bivariate Cholesky decomposition model was used for the subanalysis. We found that genetic factors explained 43% (95% CI: 36–51%) of the variation in GWG in the first pregnancy and 26% (95% CI: 16–36%) in the second pregnancy. The remaining variance was explained by unique environmental factors. Both overlapping and distinct genetic and unique environmental factors influenced GWG in the first and the second pregnancy. This study showed that GWG has a moderate heritability, suggesting that a large part of the variation in the trait can be explained by unique environmental factors.
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Lin X, Aris IM, Tint MT, Soh SE, Godfrey KM, Yeo GSH, Kwek K, Chan JKY, Gluckman PD, Chong YS, Yap F, Holbrook JD, Lee YS. Ethnic Differences in Effects of Maternal Pre-Pregnancy and Pregnancy Adiposity on Offspring Size and Adiposity. J Clin Endocrinol Metab 2015; 100. [PMID: 26200236 PMCID: PMC4628100 DOI: 10.1210/jc.2015-1728] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
CONTEXT Maternal adiposity and overnutrition, both before and during pregnancy, plays a key role in the subsequent development of obesity and metabolic outcomes in offspring. OBJECTIVE We explored the hypothesis that maternal adiposity (pre-pregnancy and at 26-28 weeks' gestation) and mid-pregnancy gestational weight gain (GWG) are independently associated with offspring size and adiposity in early childhood, and determined whether these effects are ethnicity dependent. DESIGN In a prospective mother-offspring cohort study (N = 976, 56% Chinese, 26% Malay, and 18% Indian), we assessed the associations of offspring size (weight, length) and adiposity (subscapular and triceps skinfolds), measured at birth and age 6, 12, 18, and 24 mo, with maternal pre-pregnancy body mass index (ppBMI), mid-pregnancy GWG, and mid-pregnancy four-site skinfold thicknesses (triceps, biceps, subscapular, suprailiac). RESULTS ppBMI and mid-pregnancy GWG were independently associated with postnatal weight up to 2 y and skinfold thickness at birth. Weight and subscapular and triceps skinfolds at birth increased by 2.56% (95% confidence interval, 1.68-3.45%), 3.85% (2.16-5.57%), and 2.14% (0.54-3.75%), respectively for every SD increase in ppBMI. Similarly, a one-SD increase in GWG increased weight and subscapular and triceps skinfolds at birth by 2.44% (1.66-3.23%), 3.28% (1.75-4.84%), and 3.23% (1.65-4.84%), respectively. ppBMI and mid-pregnancy suprailiac skinfold independently predicted postnatal skinfold adiposity up to 2 years of age, whereas only GWG predicted postnatal length. The associations of GWG with postnatal weight and length were present only among Chinese and Indians, but not Malays (P < .05 for interaction). CONCLUSIONS ppBMI and GWG are independent modifiable factors for child size and adiposity up to 2 years of age. The associations are ethnic-dependent, and underscore the importance of ethnic specific studies before generalizing the applicability of risk factors reported in other populations.
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Affiliation(s)
- Xinyi Lin
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Izzuddin M Aris
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Mya Thway Tint
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Shu E Soh
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Keith M Godfrey
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - George Seow-Heong Yeo
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Kenneth Kwek
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Jerry Kok-Yen Chan
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Peter D Gluckman
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Fabian Yap
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Joanna D Holbrook
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
| | - Yung Seng Lee
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (X.L., P.D.G., Y.S.C., J.D.H., Y.S.L.), 117609 Singapore; Department of Paediatrics (I.M.A., S.E.S., Y.S.L.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Department of Obstetrics and Gynaecology (M.T.T., Y.S.C.), Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; Saw Swee Hock School of Public Health (S.E.S.), National University of Singapore, 117597 Singapore; MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre (K.M.G.), University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD United Kingdom; Department of Maternal Fetal Medicine (G.S.-H.Y., K.K.), KK Women's and Children's Hospital, 229899 Singapore; Department of Reproductive Medicine (J.K.-Y.C.), KK Women's and Children's Hospital, 229899 Singapore; Centre for Human Evolution, Adaptation and Disease (P.D.G.), Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Paediatrics (F.Y.), KK Women's and Children's Hospital, 229899 Singapore; Department of Biochemistry (J.D.H.), National University of Singapore, 117596 Singapore; and Division of Paediatric Endocrinology and Diabetes (Y.S.L.), Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, 119228 Singapore
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Liang SS, Ouyang HJ, Liu J, Chen B, Nie QH, Zhang XQ. Expression of variant transcripts of the potassium channel tetramerization domain-containing 15 (KCTD15) gene and their association with fatness traits in chickens. Domest Anim Endocrinol 2015; 50:65-71. [PMID: 25447881 DOI: 10.1016/j.domaniend.2014.09.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2014] [Revised: 09/19/2014] [Accepted: 09/22/2014] [Indexed: 12/17/2022]
Abstract
The aim of this study was to characterize the structure, expression, and biological functions of potassium channel tetramerization domain containing 15 (KCTD15) in chickens. We compared the KCTD15 expression level in samples of hypothalamic, adipose, and liver tissue of Xinghua chickens that were maintained on different dietary status. An association analysis of KCTD15 gene variant transcripts with fatness traits in a F2 resource population of chickens was performed. Three KCTD15 transcripts were identified in which the complete transcript was predominantly expressed in adipose tissue and the hypothalamus. The chicken KCTD15 gene was regulated by both feeding and fasting and consumption of a high-fat diet. The expression level of KCTD15 gene was markedly decreased in hypothalamus and liver of fasted and refed chickens (P < 0.05) and significantly downregulated in adipose tissue by the high-fat diet (P < 0.05). Three single-nucleotide polymorphisms of the KCTD15 gene were significantly associated with a number of fatness traits in chicken (P < 0.05). These results suggest that KCTD15 have a potential role regulation of obesity and fat metabolism in chickens.
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Affiliation(s)
- S S Liang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China
| | - H J Ouyang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China
| | - J Liu
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China
| | - B Chen
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China
| | - Q H Nie
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China.
| | - X Q Zhang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou 510642, Guangdong, China
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Groth SW, Morrison-Beedy D. GNB3 and FTO Polymorphisms and Pregnancy Weight Gain in Black Women. Biol Res Nurs 2014; 17:405-12. [PMID: 25510251 DOI: 10.1177/1099800414561118] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Gestational weight gain (GWG) is a modifiable risk factor for obesity in women. Black women have the greatest prevalence of high body mass, which predisposes them to excessive GWG. Increased understanding of genetic influences on GWG has implications for the health of women. The purpose of this study was to explore the associations of GNB3 and FTO risk alleles in pregnant women with prepregnancy body mass index (BMI), GWG, and postpartum and infant birth weights. RESEARCH DESIGN AND METHODS This was an observational, prospective candidate gene association study. Pregnant, low-income Black women (N = 97) were enrolled in early pregnancy and followed until 6 months postpartum. RESULTS GWG differed depending on number of FTO risk alleles. The mean 6-month postpartum BMI differed, although not significantly, by 4 kg/m(2) between homozygous women. There was an interaction between the FTO risk allele and prepregnancy BMI (p = .022), with obese homozygote AA women having significantly higher mean GWG than obese TT women. When controlling for age and smoking, the FTO gene and physical activity predicted GWG (p = .032). Although not statistically significant, women who carried the GNB3 T risk allele gained 6 pounds more than noncarriers, and mean 6-month postpartum BMI differed by 2.2 kg/m(2) between homozygous women. Neither the GNB3 nor FTO gene predicted prepregnancy BMI, infant birth weight, or postpartum weight. CONCLUSION Obese women homozygous for the FTO risk allele were at greater risk of excessive GWG compared to nonrisk allele homozygous obese women or nonobese women. This study provides evidence of the FTO gene's effect on GWG in Black women.
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Widen EM, Gallagher D. Body composition changes in pregnancy: measurement, predictors and outcomes. Eur J Clin Nutr 2014; 68:643-52. [PMID: 24667754 PMCID: PMC4078736 DOI: 10.1038/ejcn.2014.40] [Citation(s) in RCA: 98] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2013] [Revised: 02/06/2014] [Accepted: 02/09/2014] [Indexed: 11/08/2022]
Abstract
Prevalence of overweight and obesity has risen in the United States over the past few decades. Concurrent with this rise in obesity has been an increase in pregravid body mass index and gestational weight gain affecting maternal body composition changes in pregnancy. During pregnancy, many of the assumptions inherent in body composition estimation are violated, particularly the hydration of fat-free mass, and available methods are unable to disentangle maternal composition from fetus and supporting tissues; therefore, estimates of maternal body composition during pregnancy are prone to error. Here we review commonly used and available methods for assessing body composition changes in pregnancy, including: (1) anthropometry, (2) total body water, (3) densitometry, (4) imaging, (5) dual-energy X-ray absorptiometry, (6) bioelectrical impedance and (7) ultrasound. Several of these methods can measure regional changes in adipose tissue; however, most of these methods provide only whole-body estimates of fat and fat-free mass. Consideration is given to factors that may influence changes in maternal body composition, as well as long-term maternal and offspring outcomes. Finally, we provide recommendations for future research in this area.
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Affiliation(s)
- EM Widen
- New York Obesity Nutrition Research Center, St. Luke’s-Roosevelt Hospital, New York, NY, USA
- Institute of Human Nutrition and Department of Medicine, College of Physicians and Surgeons, Columbia University Medical Center, New York, NY, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
| | - D Gallagher
- New York Obesity Nutrition Research Center, St. Luke’s-Roosevelt Hospital, New York, NY, USA
- Institute of Human Nutrition and Department of Medicine, College of Physicians and Surgeons, Columbia University Medical Center, New York, NY, USA
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Wander PL, Hochner H, Sitlani CM, Enquobahrie DA, Lumley T, Lawrence GM, Burger A, Savitsky B, Manor O, Meiner V, Hesselson S, Kwok PY, Siscovick DS, Friedlander Y. Maternal genetic variation accounts in part for the associations of maternal size during pregnancy with offspring cardiometabolic risk in adulthood. PLoS One 2014; 9:e91835. [PMID: 24670385 PMCID: PMC3966761 DOI: 10.1371/journal.pone.0091835] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2013] [Accepted: 02/12/2014] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Maternal pre-pregnancy body-mass index (ppBMI) and gestational weight gain (GWG) are associated with cardiometabolic risk (CMR) traits in the offspring. The extent to which maternal genetic variation accounts for these associations is unknown. METHODS/RESULTS In 1249 mother-offspring pairs recruited from the Jerusalem Perinatal Study, we used archival data to characterize ppBMI and GWG and follow-up data from offspring to assess CMR, including body mass index (BMI), waist circumference, glucose, insulin, blood pressure, and lipid levels, at an average age of 32. Maternal genetic risk scores (GRS) were created using a subset of SNPs most predictive of ppBMI, GWG, and each CMR trait, selected among 1384 single-nucleotide polymorphisms (SNPs) characterizing variation in 170 candidate genes potentially related to fetal development and/or metabolic risk. We fit linear regression models to examine the associations of ppBMI and GWG with CMR traits with and without adjustment for GRS. Compared to unadjusted models, the coefficient for the association of a one-standard-deviation (SD) difference in GWG and offspring BMI decreased by 41% (95%CI -81%, -11%) from 0.847 to 0.503 and the coefficient for a 1SD difference in GWG and WC decreased by 63% (95%CI -318%, -11%) from 1.196 to 0.443. For other traits, there were no statistically significant changes in the coefficients for GWG with adjustment for GRS. None of the associations of ppBMI with CMR traits were significantly altered by adjustment for GRS. CONCLUSIONS Maternal genetic variation may account in part for associations of GWG with offspring BMI and WC in young adults.
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Affiliation(s)
- Pandora L. Wander
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Hagit Hochner
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Colleen M. Sitlani
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
| | - Daniel A. Enquobahrie
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
| | - Thomas Lumley
- Department of Statistics, University of Auckland, Auckland, New Zealand
| | - Gabriela M. Lawrence
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Ayala Burger
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Bella Savitsky
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Orly Manor
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Vardiella Meiner
- Department of Human Genetics, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Stephanie Hesselson
- Institute of Human Genetics, University of California San Francisco, San Francisco, California, United States of America
| | - Pui Y. Kwok
- Institute of Human Genetics, University of California San Francisco, San Francisco, California, United States of America
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, California, United States of America
- Department of Dermatology, University of California San Francisco, San Francisco, California, United States of America
| | - David S. Siscovick
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
| | - Yechiel Friedlander
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
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Boitard S, Rocha D. Detection of signatures of selective sweeps in the Blonde d'Aquitaine cattle breed. Anim Genet 2013; 44:579-83. [PMID: 23647053 DOI: 10.1111/age.12042] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/25/2013] [Indexed: 01/03/2023]
Abstract
Identifying recent positive selection signatures in domesticated animals could provide information on genome response to strong directional selection from domestication and artificial selection and therefore could help in identifying mutations responsible for improved traits. We used genotyping data generated using Illumina's BovineSNP50 Genotyping BeadChips to identify selection signatures in the Blonde d'Aquitaine breed, a well-muscled French beef breed. For this purpose, we employed a hidden Markov model-based test, which detects selection by studying local variations in the allele frequency spectrum along the genome, within a single population. Three regions containing selective sweeps were identified. Annotation of genes located within these regions revealed interesting candidate genes. For example, myostatin (also known as GDF8), a known muscle growth factor inhibitor, is located within the selection signature region found on chromosome 2. In addition, we have identified chromosomal regions that show some evidence of selection within QTL regions for economically important traits. The results of this study could help to better understand the mechanisms related to the selection of the Blonde d'Aquitaine breed.
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Affiliation(s)
- S Boitard
- Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique/ENVT, UMR444, Castanet Tolosan, France
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35
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Hinkle SN, Sharma AJ, Swan DW, Schieve LA, Ramakrishnan U, Stein AD. Excess gestational weight gain is associated with child adiposity among mothers with normal and overweight prepregnancy weight status. J Nutr 2012; 142:1851-8. [PMID: 22955516 PMCID: PMC6498456 DOI: 10.3945/jn.112.161158] [Citation(s) in RCA: 68] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
There are inconsistencies in the literature regarding the association between gestational weight gain (GWG) and child adiposity. GWG is hypothesized to act on child adiposity directly through intrauterine programming and indirectly through birth weight. It is unclear if the relative importance of these pathways differs by prepregnancy BMI status. We analyzed data from 3600 participants of the nationally representative Early Childhood Longitudinal Study-Birth Cohort. Child BMI Z-score was calculated from height and weight measured at 5 y. Using linear regression, controlling for sociodemographics and family lifestyle, we examined prepregnancy BMI-specific associations between GWG and child BMI Z-score. There was a nonlinear association among normal (P < 0.001) and overweight mothers only (P = 0.013), such that GWG beyond the midpoint of the 2009 Institute of Medicine recommendations was associated with a significant increase in child BMI Z-score. After the addition of birth-weight-for-gestational-age and breastfeeding to the model, the association remained among normal-weight mothers (P = 0.005) and was slightly attenuated among overweight mothers (P = 0.09). No significant association was observed between GWG and child BMI Z-score among underweight or obese mothers. We used path analysis to decompose the total effect into direct and indirect effects. This indicated the presence of a stronger direct than indirect effect. In conclusion, low GWG is not associated with BMI Z-score among any prepregnancy BMI group. Excess GWG is associated with an increase in child BMI Z-score among normal and overweight mothers only. Prevention of excess GWG may be a strategy to prevent childhood obesity.
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Affiliation(s)
- Stefanie N. Hinkle
- Nutrition and Health Sciences, Division of Biological and Biomedical Sciences, Emory University, Atlanta, GA,National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Andrea J. Sharma
- Nutrition and Health Sciences, Division of Biological and Biomedical Sciences, Emory University, Atlanta, GA,National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA,United States Public Health Service Commissioned Corps, Atlanta, GA,To whom correspondence should be addressed. E-mail:
| | - Deanne W. Swan
- Rollins School of Public Health, Emory University, Atlanta, GA
| | - Laura A. Schieve
- National Center for Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, GA
| | - Usha Ramakrishnan
- Nutrition and Health Sciences, Division of Biological and Biomedical Sciences, Emory University, Atlanta, GA,Rollins School of Public Health, Emory University, Atlanta, GA
| | - Aryeh D. Stein
- Nutrition and Health Sciences, Division of Biological and Biomedical Sciences, Emory University, Atlanta, GA,Rollins School of Public Health, Emory University, Atlanta, GA
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36
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Deierlein AL, Siega-Riz AM, Herring AH, Adair LS, Daniels JL. Gestational weight gain and predicted changes in offspring anthropometrics between early infancy and 3 years. Pediatr Obes 2012; 7:134-42. [PMID: 22434753 PMCID: PMC3313077 DOI: 10.1111/j.2047-6310.2011.00025.x] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2011] [Revised: 11/02/2011] [Accepted: 11/22/2011] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To determine how gestational weight gain (GWG), categorized using the 2009 Institute of Medicine recommendations, relates to changes in offspring weight-for-age (WAZ), length-for-age (LAZ) and weight-for-length z-scores (WLZ) between early infancy and 3 years. METHODS Women with singleton infants were recruited from the third cohort of the Pregnancy, Infection, and Nutrition Study (2001-2005). Term infants with at least one weight or length measurement during the study period were included (n = 476). Multivariable linear mixed effects regression models estimated longitudinal changes in WAZ, LAZ and WLZ associated with GWG. RESULTS In early infancy, compared with infants of women with adequate weight gain, those of women with excessive weight gains had higher WAZ, LAZ and WLZ. Excessive GWG ≥ 200% of the recommended amount was associated with faster rates of change in WAZ and LAZ and noticeably higher predicted mean WAZ and WLZ that persisted across the study period. CONCLUSIONS GWG is associated with significant differences in offspring anthropometrics in early infancy that persisted to 3 years of age. More longitudinal studies that utilize maternal and paediatric body composition measures are necessary to understand the nature of this association.
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Affiliation(s)
- Andrea L. Deierlein
- Andrea Deierlein is now at Mount Sinai School of Medicine, Department of Preventive Medicine, NY, NY
| | | | - Amy H. Herring
- University of North Carolina Gillings School of Global Public Health
| | - Linda S. Adair
- University of North Carolina Gillings School of Global Public Health
| | - Julie L. Daniels
- University of North Carolina Gillings School of Global Public Health
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37
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Boraska V, Day-Williams A, Franklin CS, Elliott KS, Panoutsopoulou K, Tachmazidou I, Albrecht E, Bandinelli S, Beilin LJ, Bochud M, Cadby G, Ernst F, Evans DM, Hayward C, Hicks AA, Huffman J, Huth C, James AL, Klopp N, Kolcic I, Kutalik Z, Lawlor DA, Musk AW, Pehlic M, Pennell CE, Perry JRB, Peters A, Polasek O, Pourcain BS, Ring SM, Salvi E, Schipf S, Staessen JA, Teumer A, Timpson N, Vitart V, Warrington NM, Yaghootkar H, Zemunik T, Zgaga L, An P, Anttila V, Borecki IB, Holmen J, Ntalla I, Palotie A, Pietiläinen KH, Wedenoja J, Winsvold BS, Dedoussis GV, Kaprio J, Province MA, Zwart JA, Burnier M, Campbell H, Cusi D, Davey Smith G, Frayling TM, Gieger C, Palmer LJ, Pramstaller PP, Rudan I, Völzke H, Wichmann HE, Wright AF, Zeggini E. Genome-wide association study to identify common variants associated with brachial circumference: a meta-analysis of 14 cohorts. PLoS One 2012; 7:e31369. [PMID: 22479309 PMCID: PMC3315559 DOI: 10.1371/journal.pone.0031369] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2011] [Accepted: 01/09/2012] [Indexed: 01/06/2023] Open
Abstract
Brachial circumference (BC), also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS) meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men) of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05) in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC.
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Affiliation(s)
- Vesna Boraska
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
- Department of Medical Biology, University of Split School of Medicine, Split, Croatia
- * E-mail: (VB); (EZ)
| | - Aaron Day-Williams
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Christopher S. Franklin
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Katherine S. Elliott
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Kalliope Panoutsopoulou
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Ioanna Tachmazidou
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Eva Albrecht
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | | | - Lawrence J. Beilin
- School of Medicine and Pharmacology, The University of Western Australia, Perth, Australia
| | - Murielle Bochud
- Institute of Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | - Gemma Cadby
- Genetic Epidemiology and Biostatistics Platform, Ontario Institute for Cancer Research, Toronto, Canada
| | - Florian Ernst
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - David M. Evans
- MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, United Kingdom
| | - Andrew A. Hicks
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy, Affiliated Institute of the University of Lübeck, Lübeck, Germany
| | - Jennifer Huffman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, United Kingdom
| | - Cornelia Huth
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Alan L. James
- School of Medicine and Pharmacology, The University of Western Australia, Perth, Australia
- Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- Department of Pulmonary Physiology/West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
| | - Norman Klopp
- Unit for Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Ivana Kolcic
- Croatian Centre for Global Health, University of Split School of Medicine, Split, Croatia
| | - Zoltán Kutalik
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - Debbie A. Lawlor
- MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Arthur W. Musk
- Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- Schools of Population Health and Medicine and Pharmacology, University of Western Australia, Perth, Western Australia, Australia
| | - Marina Pehlic
- Department of Medical Biology, University of Split School of Medicine, Split, Croatia
| | - Craig E. Pennell
- School of Women's and Infants' Health, The University of Western Australia, Perth, Western Australia, Australia
| | - John R. B. Perry
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, United Kingdom
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Ozren Polasek
- Croatian Centre for Global Health, University of Split School of Medicine, Split, Croatia
| | - Beate St Pourcain
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Susan M. Ring
- MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Erika Salvi
- Department of Medicine, Surgery and Dentistry, University of Milano, Milano, Italy
- Genomics and Bioinformatics Platform, Fondazione Filarete, University of Milano, Milano, Italy
| | - Sabine Schipf
- Institute for Community Medicine/SHIP-Clinical Epidemiological Research, University of Greifswald, Greifswald, Germany
| | - Jan A. Staessen
- Studies Coordinating Centre, Division of Hypertension and Cardiovascular Rehabilitation, Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium
- Department of Epidemiology, Maastricht University, Maastricht, The Netherlands
| | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Nicholas Timpson
- MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, United Kingdom
| | - Nicole M. Warrington
- School of Women's and Infants' Health, The University of Western Australia, Perth, Western Australia, Australia
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, United Kingdom
| | - Tatijana Zemunik
- Department of Medical Biology, University of Split School of Medicine, Split, Croatia
| | - Lina Zgaga
- Centre for Population Health Sciences and Institute of Genetics and Molecular Medicine, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Andrija Štampar School of Public Health, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ping An
- Division of Statistical Genomics and Department of Genetics Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Verneri Anttila
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Ingrid B. Borecki
- Division of Statistical Genomics and Department of Genetics Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Jostein Holmen
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Ioanna Ntalla
- Harokopio University of Athens, Department of Dietetics and Nutrition, Athens, Greece
| | - Aarno Palotie
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Medical Genetics, University and University Central Hospital of Helsinki, Helsinki, Finland
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Kirsi H. Pietiläinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Obesity Research Unit, Department of Medicine, Division of Internal Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
| | - Juho Wedenoja
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
| | - Bendik S. Winsvold
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
- Department of Neurology, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - George V. Dedoussis
- Harokopio University of Athens, Department of Dietetics and Nutrition, Athens, Greece
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Dept of Mental Health and Substance Abuse Services, Helsinki, Finland
| | - Michael A. Province
- Division of Statistical Genomics and Department of Genetics Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - John-Anker Zwart
- Department of Neurology, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Michel Burnier
- Service of Nephrology, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
| | - Harry Campbell
- Centre for Population Health Sciences and Institute of Genetics and Molecular Medicine, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Daniele Cusi
- Genomics and Bioinformatics Platform, Fondazione Filarete, University of Milano, Milano, Italy
- Division of Nephrology, San Paolo Hospital, Milano, Italy
| | - George Davey Smith
- MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Timothy M. Frayling
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, United Kingdom
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Lyle J. Palmer
- Genetic Epidemiology and Biostatistics Platform, Ontario Institute for Cancer Research, Toronto, Canada
- Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Toronto, Canada
| | - Peter P. Pramstaller
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy, Affiliated Institute of the University of Lübeck, Lübeck, Germany
- Department of Neurology, General Central Hospital, Bolzano, Italy
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | - Igor Rudan
- Croatian Centre for Global Health, University of Split School of Medicine, Split, Croatia
- Centre for Population Health Sciences and Institute of Genetics and Molecular Medicine, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Henry Völzke
- Institute for Community Medicine/SHIP-Clinical Epidemiological Research, University of Greifswald, Greifswald, Germany
| | - H. -Erich Wichmann
- Institute of Epidemiology I, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- Klinikum Grosshadern, Munich, Germany
| | - Alan F. Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, United Kingdom
| | - Eleftheria Zeggini
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
- * E-mail: (VB); (EZ)
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Kwak SH, Park BL, Kim H, German MS, Go MJ, Jung HS, Koo BK, Cho YM, Choi SH, Cho YS, Shin HD, Jang HC, Park KS. Association of variations in TPH1 and HTR2B with gestational weight gain and measures of obesity. Obesity (Silver Spring) 2012; 20:233-8. [PMID: 21836641 DOI: 10.1038/oby.2011.253] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Serotonin is involved in appetite regulation and energy homeostasis. Recently, it has been reported that 5-hydroxytryptamine receptor 2B (Htr2b) and tryptophan hydroxylase 1 (Tph1) play major role in β-cell proliferation in mouse during pregnancy. We investigated the genetic association of HTR2B and TPH1 with risk of gestational diabetes mellitus (GDM) and measures of obesity, in 869 Korean GDM women and carefully selected 632 nondiabetic control subjects. Six single-nucleotide polymorphisms (SNPs) in HTR2B and ten SNPs in TPH1 were selected for genotyping according to their tagging status. Genetic variants in HTR2B and TPH1 were not associated with the risk of GDM. In GDM women, SNPs of TPH1 were significantly associated with weight gain during pregnancy. In nondiabetic controls, SNPs of TPH1 were associated with waist circumference and BMI. We also found that a variant of TPH1 (rs623580) was associated with BMI in a genome-wide association study comprised of 8,842 subjects. Although genetic variants in HTR2B and TPH1 were not associated with risk of GDM, we found significant association of these variants with measures of obesity. However, further replication studies in a different population are required to confirm our findings.
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Affiliation(s)
- Soo Heon Kwak
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
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Kloth L, Belge G, Burchardt K, Loeschke S, Wosniok W, Fu X, Nimzyk R, Mohamed SA, Drieschner N, Rippe V, Bullerdiek J. Decrease in thyroid adenoma associated (THADA) expression is a marker of dedifferentiation of thyroid tissue. BMC Clin Pathol 2011; 11:13. [PMID: 22050638 PMCID: PMC3229435 DOI: 10.1186/1472-6890-11-13] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2011] [Accepted: 11/04/2011] [Indexed: 12/17/2022] Open
Abstract
Background Thyroid adenoma associated (THADA) has been identified as the target gene affected by chromosome 2p21 translocations in thyroid adenomas, but the role of THADA in the thyroid is still elusive. The aim of this study was to quantify THADA gene expression in normal tissues and in thyroid hyper- and neoplasias, using real-time PCR. Methods For the analysis THADA and 18S rRNA gene expression assays were performed on 34 normal tissue samples, including thyroid, salivary gland, heart, endometrium, myometrium, lung, blood, and adipose tissue as well as on 85 thyroid hyper- and neoplasias, including three adenomas with a 2p21 translocation. In addition, NIS (sodium-iodide symporter) gene expression was measured on 34 of the pathological thyroid samples. Results Results illustrated that THADA expression in normal thyroid tissue was significantly higher (p < 0.0001, exact Wilcoxon test) than in the other tissues. Significant differences were also found between non-malignant pathological thyroid samples (goiters and adenomas) and malignant tumors (p < 0.001, Wilcoxon test, t approximation), anaplastic carcinomas (ATCs) and all other samples and also between ATCs and all other malignant tumors (p < 0.05, Wilcoxon test, t approximation). Furthermore, in thyroid tumors THADA mRNA expression was found to be inversely correlated with HMGA2 mRNA. HMGA2 expression was recently identified as a marker revealing malignant transformation of thyroid follicular tumors. A correlation between THADA and NIS has also been found in thyroid normal tissue and malignant tumors. Conclusions The results suggest THADA being a marker of dedifferentiation of thyroid tissue.
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Affiliation(s)
- Lars Kloth
- Center for Human Genetics, University of Bremen, Leobener Str, ZHG, 28359 Bremen, Germany.
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Lawlor DA, Fraser A, Macdonald-Wallis C, Nelson SM, Palmer TM, Davey Smith G, Tilling K. Maternal and offspring adiposity-related genetic variants and gestational weight gain. Am J Clin Nutr 2011; 94:149-55. [PMID: 21593506 PMCID: PMC3127507 DOI: 10.3945/ajcn.110.010751] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Gestational weight gain (GWG) is associated with a range of health outcomes, but little is known about the factors that influence it. OBJECTIVE The objective was to test the hypothesis that maternal and fetal genetic variants that are reliably associated with adiposity are associated with GWG. DESIGN We examined the association of a risk allele score by using 4 adiposity-related single nucleotide polymorphisms (SNPs; rs9939609 in FTO, rs17782313 near MC4R, rs6548238 near TMEM18, and rs10938397 near GNPDA2) with GWG in a pregnancy cohort in which women had detailed repeated assessment of GWG (median number of weight measurements: 10; interquartile range: 8, 11). The numbers included in our analyses varied between 2324 and 7563 for different variant-outcome analyses. A linear spline random-effects model was used to model weight change with gestational age and to relate genetic variants to this. This modeling confirmed 3 distinct periods of GWG: 0-18, 19-28, and ≥29 wk of gestation. RESULTS Maternal risk allele score and SNPs in FTO, MC4R, and TMEM18 were positively associated with prepregnancy weight. Maternal allele score was inversely associated with GWG in the first 18 wk of pregnancy (-14.46 g/wk per allele; 95% CI: -24.75, -4.17 g/wk per allele) but was not associated with other periods of GWG. Offspring allele score and maternal and offspring individual SNPs were not associated with GWG in any period or with birth weight or postnatal weight retention. CONCLUSIONS Our findings suggest that neither maternal nor fetal adiposity-related genetic variants are associated with greater GWG. The inverse association of maternal allele score with GWG in the first 18 wk requires replication.
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Affiliation(s)
- Debbie A Lawlor
- MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, United Kingdom.
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