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Millership SJ, Van de Pette M, Withers DJ. Genomic imprinting and its effects on postnatal growth and adult metabolism. Cell Mol Life Sci 2019; 76:4009-4021. [PMID: 31270580 PMCID: PMC6785587 DOI: 10.1007/s00018-019-03197-z] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 06/10/2019] [Accepted: 06/17/2019] [Indexed: 12/25/2022]
Abstract
Imprinted genes display parent-of-origin-specific expression with this epigenetic system of regulation found exclusively in therian mammals. Historically, defined imprinted gene functions were almost solely focused on pregnancy and the influence on the growth parameters of the developing embryo and placenta. More recently, a number of postnatal functions have been identified which converge on resource allocation, both for animals in the nest and in adults. While many of the prenatal functions of imprinted genes that have so far been described adhere to the "parental conflict" hypothesis, no clear picture has yet emerged on the functional role of imprints on postnatal metabolism. As these roles are uncovered, interest in the potential for these genes to influence postnatal metabolism and associated adult-onset disease outcomes when dysregulated has gathered pace. Here, we review the published data on imprinted genes and their influence on postnatal metabolism, starting in the nest, and then progressing through to adulthood. When observing the functional effects of these genes on adult metabolism, we must always be careful to acknowledge the influence both of direct expression in the relevant metabolic tissue, but also indirect metabolic programming effects caused by their modulation of both in utero and postnatal growth trajectories.
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Affiliation(s)
- Steven J Millership
- MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK.
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK.
| | - Mathew Van de Pette
- MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Dominic J Withers
- MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK.
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK.
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Millership SJ, Tunster SJ, Van de Pette M, Choudhury AI, Irvine EE, Christian M, Fisher AG, John RM, Scott J, Withers DJ. Neuronatin deletion causes postnatal growth restriction and adult obesity in 129S2/Sv mice. Mol Metab 2018; 18:97-106. [PMID: 30279096 PMCID: PMC6308027 DOI: 10.1016/j.molmet.2018.09.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 09/10/2018] [Indexed: 01/31/2023] Open
Abstract
OBJECTIVE Imprinted genes are crucial for the growth and development of fetal and juvenile mammals. Altered imprinted gene dosage causes a variety of human disorders, with growth and development during these crucial early stages strongly linked with future metabolic health in adulthood. Neuronatin (Nnat) is a paternally expressed imprinted gene found in neuroendocrine systems and white adipose tissue and is regulated by the diet and leptin. Neuronatin expression is downregulated in obese children and has been associated with stochastic obesity in C57BL/6 mice. However, our recent studies of Nnat null mice on this genetic background failed to display any body weight or feeding phenotypes but revealed a defect in glucose-stimulated insulin secretion due to the ability of neuronatin to potentiate signal peptidase cleavage of preproinsulin. Nnat deficiency in beta cells therefore caused a lack of appropriate storage and secretion of mature insulin. METHODS To further explore the potential role of Nnat in the regulation of body weight and adiposity, we studied classical imprinting-related phenotypes such as placental, fetal, and postnatal growth trajectory patterns that may impact upon subsequent adult metabolic phenotypes. RESULTS Here we find that, in contrast to the lack of any body weight or feeding phenotypes on the C57BL/6J background, deletion of Nnat in mice on 129S2/Sv background causes a postnatal growth restriction with reduced adipose tissue accumulation, followed by catch up growth after weaning. This was in the absence of any effect on fetal growth or placental development. In adult 129S2/Sv mice, Nnat deletion was associated with hyperphagia, reduced energy expenditure, and partial leptin resistance. Lack of neuronatin also potentiated obesity caused by either aging or high fat diet feeding. CONCLUSIONS The imprinted gene Nnat plays a key role in postnatal growth, adult energy homeostasis, and the pathogenesis of obesity via catch up growth effects, but this role is dependent upon genetic background.
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Affiliation(s)
- Steven J Millership
- MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK; Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Simon J Tunster
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff, CF10 3AX, UK
| | | | | | - Elaine E Irvine
- MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Mark Christian
- Institute of Reproductive and Developmental Biology, Department of Surgery and Cancer, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Amanda G Fisher
- MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Rosalind M John
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff, CF10 3AX, UK
| | - James Scott
- National Heart and Lung Institute, Department of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Dominic J Withers
- MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK; Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK.
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Dechamethakun S, Muramatsu M. Long noncoding RNA variations in cardiometabolic diseases. J Hum Genet 2016; 62:97-104. [PMID: 27305986 DOI: 10.1038/jhg.2016.70] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Revised: 04/27/2016] [Accepted: 05/06/2016] [Indexed: 12/18/2022]
Abstract
Cardiometabolic diseases are characterized as a combination of multiple risk factors for cardiovascular disease (CVD) and metabolic diseases including diabetes mellitus, dyslipidemia, hypertension and abdominal obesity. This cluster of abnormalities individually and interdependently leads to atherosclerosis and CVD morbidity and mortality. In the past decade, genome-wide association studies (GWASs) have identified a series of cardiometabolic disease-associated variants that can collectively explain a small proportion of the variability. Intriguingly, the susceptibility variants imputed from GWASs usually do not reside in the coding regions, suggesting a crucial role of the noncoding elements of the genome. In recent years, emerging evidence suggests that noncoding RNA (ncRNA) is functional for physiology and pathophysiology of human diseases. These include microRNAs and long noncoding RNAs (lncRNAs) that are now implicated in human diseases. The ncRNAs can interact with each other and with proteins, to interfere gene expressions, leading to the development of many human disorders. Although evidence suggests the functional role of lncRNAs in cardiometabolic traits, the molecular mechanisms of gene regulation underlying cardiometabolic diseases remain to be better defined. Here, we summarize the recent discoveries of lncRNA variations in the context of cardiometabolic diseases.
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Affiliation(s)
- Sariya Dechamethakun
- Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
| | - Masaaki Muramatsu
- Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
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Hu Y, Rosa GJM, Gianola D. Incorporating parent-of-origin effects in whole-genome prediction of complex traits. Genet Sel Evol 2016; 48:34. [PMID: 27091137 PMCID: PMC4834899 DOI: 10.1186/s12711-016-0213-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Accepted: 04/04/2016] [Indexed: 12/24/2022] Open
Abstract
Background Parent-of-origin effects are due to differential contributions of paternal and maternal lineages to offspring phenotypes. Such effects include, for example, maternal effects in several species. However, epigenetically induced parent-of-origin effects have recently attracted attention due to their potential impact on variation of complex traits. Given that prediction of genetic merit or phenotypic performance is of interest in the study of complex traits, it is relevant to consider parent-of-origin effects in such predictions. We built a whole-genome prediction model that incorporates parent-of-origin effects by considering parental allele substitution effects of single nucleotide polymorphisms and gametic relationships derived from a pedigree (the POE model). We used this model to predict body mass index in a mouse population, a trait that is presumably affected by parent-of-origin effects, and also compared the prediction performance to that of a standard additive model that ignores parent-of-origin effects (the ADD model). We also used simulated data to assess the predictive performance of the POE model under various circumstances, in which parent-of-origin effects were generated by mimicking an imprinting mechanism. Results The POE model did not predict better than the ADD model in the real data analysis, probably due to overfitting, since the POE model had far more parameters than the ADD model. However, when applied to simulated data, the POE model outperformed the ADD model when the contribution of parent-of-origin effects to phenotypic variation increased. The superiority of the POE model over the ADD model was up to 8 % on predictive correlation and 5 % on predictive mean squared error. Conclusions The simulation and the negative result obtained in the real data analysis indicated that, in order to gain benefit from the POE model in terms of prediction, a sizable contribution of parent-of-origin effects to variation is needed and such variation must be captured by the genetic markers fitted. Recent studies, however, suggest that most parent-of-origin effects stem from epigenetic regulation but not from a change in DNA sequence. Therefore, integrating epigenetic information with genetic markers may help to account for parent-of-origin effects in whole-genome prediction.
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Affiliation(s)
- Yaodong Hu
- Department of Animal Sciences, University of Wisconsin-Madison, 1675 Observatory Dr., Madison, WI, 53706, USA.
| | - Guilherme J M Rosa
- Department of Animal Sciences, University of Wisconsin-Madison, 1675 Observatory Dr., Madison, WI, 53706, USA.,Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI, 53792, USA
| | - Daniel Gianola
- Department of Animal Sciences, University of Wisconsin-Madison, 1675 Observatory Dr., Madison, WI, 53706, USA.,Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI, 53792, USA.,Department of Dairy Science, University of Wisconsin-Madison, 1675 Observatory Dr., Madison, WI, 53706, USA
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Morita S, Nakabayashi K, Kawai T, Hayashi K, Horii T, Kimura M, Kamei Y, Ogawa Y, Hata K, Hatada I. Gene expression profiling of white adipose tissue reveals paternal transmission of proneness to obesity. Sci Rep 2016; 6:21693. [PMID: 26868178 PMCID: PMC4751506 DOI: 10.1038/srep21693] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Accepted: 01/29/2016] [Indexed: 11/21/2022] Open
Abstract
Previously, we found that C57BL/6J (B6) mice are more prone to develop obesity than PWK mice. In addition, we analyzed reciprocal crosses between these mice and found that (PWK × B6) F1 mice, which have B6 fathers, are more likely to develop dietary obesity than (B6 × PWK) F1 mice, which have B6 mothers. These results suggested that diet-induced obesity is paternally transmitted. In this study, we performed transcriptome analysis of adipose tissues of B6, PWK, (PWK × B6) F1, and (B6 × PWK) F1 mice using next-generation sequencing. We found that paternal transmission of diet-induced obesity was correlated with genes involved in adipose tissue inflammation, metal ion transport, and cilia. Furthermore, we analyzed the imprinted genes expressed in white adipose tissue (WAT) and obesity. Expression of paternally expressed imprinted genes (PEGs) was negatively correlated with body weight, whereas expression of maternally expressed imprinted genes (MEGs) was positively correlated. In the obesity-prone B6 mice, expression of PEGs was down-regulated by a high-fat diet, suggesting that abnormally low expression of PEGs contributes to high-fat diet-induced obesity in B6 mice. In addition, using single-nucleotide polymorphisms that differ between B6 and PWK, we identified candidate imprinted genes in WAT.
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Affiliation(s)
- Sumiyo Morita
- Laboratory of Genome Science, Biosignal Genome Resource Center, Institute for Molecular and Cellular Regulation, Gunma University, 3-39-15 Showa-machi Maebashi, 371-8512, Japan
| | - Kazuhiko Nakabayashi
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, 2-10-1 Okura Setagaya-ku Tokyo, 157-8535, Japan
| | - Tomoko Kawai
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, 2-10-1 Okura Setagaya-ku Tokyo, 157-8535, Japan
| | - Keiko Hayashi
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, 2-10-1 Okura Setagaya-ku Tokyo, 157-8535, Japan
| | - Takuro Horii
- Laboratory of Genome Science, Biosignal Genome Resource Center, Institute for Molecular and Cellular Regulation, Gunma University, 3-39-15 Showa-machi Maebashi, 371-8512, Japan
| | - Mika Kimura
- Laboratory of Genome Science, Biosignal Genome Resource Center, Institute for Molecular and Cellular Regulation, Gunma University, 3-39-15 Showa-machi Maebashi, 371-8512, Japan
| | - Yasutomi Kamei
- Laboratory of Molecular Nutrition, Graduate School of Environmental and Life Science, Kyoto Prefectural University, 1-5 Hangi-cho, Shimogamo, Sakyo-ku, Kyoto, 606-8522, Japan
| | - Yoshihiro Ogawa
- Department of Molecular Endocrinology and Metabolism, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Bunkyo-ku, Yushima, Tokyo, 113-8510, Japan
| | - Kenichiro Hata
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, 2-10-1 Okura Setagaya-ku Tokyo, 157-8535, Japan
| | - Izuho Hatada
- Laboratory of Genome Science, Biosignal Genome Resource Center, Institute for Molecular and Cellular Regulation, Gunma University, 3-39-15 Showa-machi Maebashi, 371-8512, Japan
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Hochner H, Allard C, Granot-Hershkovitz E, Chen J, Sitlani CM, Sazdovska S, Lumley T, McKnight B, Rice K, Enquobahrie DA, Meigs JB, Kwok P, Hivert MF, Borecki IB, Gomez F, Wang T, van Duijn C, Amin N, Rotter JI, Stamatoyannopoulos J, Meiner V, Manor O, Dupuis J, Friedlander Y, Siscovick DS. Parent-of-Origin Effects of the APOB Gene on Adiposity in Young Adults. PLoS Genet 2015; 11:e1005573. [PMID: 26451733 PMCID: PMC4599806 DOI: 10.1371/journal.pgen.1005573] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2015] [Accepted: 09/15/2015] [Indexed: 01/23/2023] Open
Abstract
Loci identified in genome-wide association studies (GWAS) of cardio-metabolic traits account for a small proportion of the traits' heritability. To date, most association studies have not considered parent-of-origin effects (POEs). Here we report investigation of POEs on adiposity and glycemic traits in young adults. The Jerusalem Perinatal Family Follow-Up Study (JPS), comprising 1250 young adults and their mothers was used for discovery. Focusing on 18 genes identified by previous GWAS as associated with cardio-metabolic traits, we used linear regression to examine the associations of maternally- and paternally-derived offspring minor alleles with body mass index (BMI), waist circumference (WC), fasting glucose and insulin. We replicated and meta-analyzed JPS findings in individuals of European ancestry aged ≤50 belonging to pedigrees from the Framingham Heart Study, Family Heart Study and Erasmus Rucphen Family study (total N≅4800). We considered p<2.7x10-4 statistically significant to account for multiple testing. We identified a common coding variant in the 4th exon of APOB (rs1367117) with a significant maternally-derived effect on BMI (β = 0.8; 95%CI:0.4,1.1; p = 3.1x10-5) and WC (β = 2.7; 95%CI:1.7,3.7; p = 2.1x10-7). The corresponding paternally-derived effects were non-significant (p>0.6). Suggestive maternally-derived associations of rs1367117 were observed with fasting glucose (β = 0.9; 95%CI:0.3,1.5; p = 4.0x10-3) and insulin (ln-transformed, β = 0.06; 95%CI:0.03,0.1; p = 7.4x10-4). Bioinformatic annotation for rs1367117 revealed a variety of regulatory functions in this region in liver and adipose tissues and a 50% methylation pattern in liver only, consistent with allelic-specific methylation, which may indicate tissue-specific POE. Our findings demonstrate a maternal-specific association between a common APOB variant and adiposity, an association that was not previously detected in GWAS. These results provide evidence for the role of regulatory mechanisms, POEs specifically, in adiposity. In addition this study highlights the benefit of utilizing family studies for deciphering the genetic architecture of complex traits. To date, genetic variants identified in large-scale genetic studies using recent technical and methodological advances explain only a small proportion of the genetic basis of obesity, diabetes and other cardiovascular risk factors. These studies were typically conducted in samples of unrelated individuals. Here we utilize a family-based approach to identify genetic variants associated with obesity-related traits. Specifically, we examined the separate contribution of maternally- vs. paternally-inherited common genetic variants to these traits. By examining 1250 young adults and their mothers from Jerusalem, we show that a specific genetic variant, rs1367117, located in the APOB gene on chromosome 2 is related to body mass index and waist circumference when inherited from mother and not from father. This maternal effect is not restricted to Jerusalemites, but is also seen in a large sample of individuals of European descent from independent family studies worldwide. Our findings provide support of the role of complex genetic mechanisms in obesity, and highlight the benefit of utilizing family studies for uncovering genetic pathways underlying common risk factors and diseases.
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Affiliation(s)
- Hagit Hochner
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
- * E-mail:
| | - Catherine Allard
- Département de Mathématiques, Université de Sherbrooke and Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec, Canada
| | | | - Jinbo Chen
- Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - 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
| | - Sandra Sazdovska
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Thomas Lumley
- Department of Statistics, University of Auckland, Auckland, New Zealand
| | - Barbara McKnight
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Daniel A. Enquobahrie
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
| | - James B. Meigs
- Harvard Medical School and General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Pui Kwok
- Institute of Human Genetics, University of California, San Francisco, California, United States of America
- Cardiovascular Research Institute, University of California, San Francisco, California, United States of America
- Department of Dermatology, University of California, San Francisco, California, United States of America
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States of America
| | - Ingrid B. Borecki
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Felicia Gomez
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Ting Wang
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Cornelia van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - John Stamatoyannopoulos
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Vardiella Meiner
- Department of Genetics and Metabolism, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Orly Manor
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Yechiel Friedlander
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - David S. Siscovick
- New York Academy of Medicine, New York, New York, United States of America
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Hu Y, Rosa GJ, Gianola D. A GWAS assessment of the contribution of genomic imprinting to the variation of body mass index in mice. BMC Genomics 2015; 16:576. [PMID: 26238105 PMCID: PMC4523993 DOI: 10.1186/s12864-015-1721-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Accepted: 06/25/2015] [Indexed: 11/10/2022] Open
Abstract
Background Genomic imprinting is an epigenetic mechanism that can lead to differential gene expression depending on the parent-of-origin of a received allele. While most studies on imprinting address its underlying molecular mechanisms or attempt at discovering genomic regions that might be subject to imprinting, few have focused on the amount of phenotypic variation contributed by such epigenetic process. In this report, we give a brief review of a one-locus imprinting model in a quantitative genetics framework, and provide a decomposition of the genetic variance according to this model. Analytical deductions from the proposed imprinting model indicated a non-negligible contribution of imprinting to genetic variation of complex traits. Also, we performed a whole-genome scan analysis on mouse body mass index (BMI) aiming at revealing potential consequences when existing imprinting effects are ignored in genetic analysis. Results 10,021 SNP markers were used to perform a whole-genome single marker regression on mouse BMI using an additive and an imprinting model. Markers significant for imprinting indicated that BMI is subject to imprinting. Marked variance changed from 1.218 ×10−4 to 1.842 ×10−4 when imprinting was considered in the analysis, implying that one third of marked variance would be lost if existing imprinting effects were not accounted for. When both marker and pedigree information were used, estimated heritability increased from 0.176 to 0.195 when imprinting was considered. Conclusions When a complex trait is subject to imprinting, using an additive model that ignores this phenomenon may result in an underestimate of additive variability, potentially leading to wrong inferences about the underlying genetic architecture of that trait. This could be a possible factor explaining part of the missing heritability commonly observed in genome-wide association studies (GWAS).
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Affiliation(s)
- Yaodong Hu
- Department of Animal Sciences, University of Wisconsin - Madison, 1675 Observatory Dr., Madison, 53706, WI, USA.
| | - Guilherme Jm Rosa
- Department of Animal Sciences, University of Wisconsin - Madison, 1675 Observatory Dr., Madison, 53706, WI, USA. .,Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, 600 Highland Avenue, Madison, 53792, WI, USA.
| | - Daniel Gianola
- Department of Animal Sciences, University of Wisconsin - Madison, 1675 Observatory Dr., Madison, 53706, WI, USA. .,Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, 600 Highland Avenue, Madison, 53792, WI, USA. .,Department of Dairy Science, University of Wisconsin - Madison, 1675 Observatory Dr., Madison, 53706, WI, USA.
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Li J, Wang Z, Li R, Wu R. BAYESIAN GROUP LASSO FOR NONPARAMETRIC VARYING-COEFFICIENT MODELS WITH APPLICATION TO FUNCTIONAL GENOME-WIDE ASSOCIATION STUDIES. Ann Appl Stat 2015; 9:640-664. [PMID: 26478762 DOI: 10.1214/15-aoas808] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Although genome-wide association studies (GWAS) have proven powerful for comprehending the genetic architecture of complex traits, they are challenged by a high dimension of single-nucleotide polymorphisms (SNPs) as predictors, the presence of complex environmental factors, and longitudinal or functional natures of many complex traits or diseases. To address these challenges, we propose a high-dimensional varying-coefficient model for incorporating functional aspects of phenotypic traits into GWAS to formulate a so-called functional GWAS or fGWAS. Bayesian group lasso and the associated MCMC algorithms are developed to identify significant SNPs and estimate how they affect longitudinal traits through time-varying genetic actions. The model is generalized to analyze the genetic control of complex traits using subject-specific sparse longitudinal data. The statistical properties of the new model are investigated through simulation studies. We use the new model to analyze a real GWAS data set from the Framingham Heart Study, leading to the identification of several significant SNPs associated with age-specific changes of body mass index. The fGWAS model, equipped with Bayesian group lassso, will provide a useful tool for genetic and developmental analysis of complex traits or diseases.
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Affiliation(s)
- Jiahan Li
- Department of Applied and Computational, Mathematics and Statistics, The University of Notre Dame, Notre Dame, IN 46556.
| | - Zhong Wang
- Center for Computational Biology, Beijing Forestry University, Beijing, China 100083.
| | - Runze Li
- Department of Statistics, The Methodology Center, The Pennsylvania State University, University Park, PA 16802.
| | - Rongling Wu
- Center for Statistical Genetics, The Pennsylvania State University, Hershey, PA 17033.
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Interplay between polymorphisms and methylation in the H19/IGF2 gene region may contribute to obesity in Mexican-American children. J Dev Orig Health Dis 2014; 4:499-506. [PMID: 24575294 DOI: 10.1017/s204017441300041x] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Imprinted genes often affect body size-related traits such as weight. However, the association of imprinting with obesity, especially childhood obesity, has not been well studied. Mexican-American children have a high prevalence, approaching 50%, of obesity and/or overweight. In a pilot study of 75 Mexican-American children, we analyzed the relationships among obese/overweight status, methylation status and single-nucleotide polymorphism (SNP) status at a CpG site in a differentially methylated region (DMR) of the imprinted H19/IGF2 locus. We observed a significant difference in SNP rs10732516 frequency between boys and girls among the overweight and obese children but not among the lean children. We also found that children with lower methylation of the polymorphic CpG site (CpG4) in the H19 DMR had higher birth weights than did children with higher methylation (P = 0.04). Our results suggest that CpG4 methylation status may be associated with childhood obesity in Mexican-American children in a sex-specific manner.
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Effects of Italian Mediterranean organic diet vs. low-protein diet in nephropathic patients according to MTHFR genotypes. J Nephrol 2014; 27:529-36. [DOI: 10.1007/s40620-014-0067-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2013] [Accepted: 12/14/2013] [Indexed: 01/28/2023]
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Abstract
Obesity is a disorder characterized by an excess accumulation of body fat resulting from a mismatch between energy intake and expenditure. Incidence of obesity has increased dramatically in the past few years, almost certainly fuelled by a shift in dietary habits owing to the widespread availability of low-cost, hypercaloric foods. However, clear differences exist in obesity susceptibility among individuals exposed to the same obesogenic environment, implicating genetic risk factors. Numerous genes have been shown to be involved in the development of monofactorial forms of obesity. In genome-wide association studies, a large number of common variants have been associated with adiposity levels, each accounting for only a small proportion of the predicted heritability. Although the small effect sizes of obesity variants identified in genome-wide association studies currently preclude their utility in clinical settings, screening for a number of monogenic obesity variants is now possible. Such regular screening will provide more informed prognoses and help in the identification of at-risk individuals who could benefit from early intervention, in evaluation of the outcomes of current obesity treatments, and in personalization of the clinical management of obesity. This Review summarizes current advances in obesity genetics and discusses the future of research in this field and the potential relevance to personalized obesity therapy.
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TaqIA polymorphism in dopamine D2 receptor gene complicates weight maintenance in younger obese patients. Nutrition 2012; 28:996-1001. [DOI: 10.1016/j.nut.2011.12.018] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2011] [Revised: 11/28/2011] [Accepted: 12/27/2011] [Indexed: 01/03/2023]
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Snyder EE, Walts B, Pérusse L, Chagnon YC, Weisnagel SJ, Rankinen T, Bouchard C. The Human Obesity Gene Map: The 2003 Update. ACTA ACUST UNITED AC 2012; 12:369-439. [PMID: 15044658 DOI: 10.1038/oby.2004.47] [Citation(s) in RCA: 207] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
This is the tenth update of the human obesity gene map, incorporating published results up to the end of October 2003 and continuing the previous format. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, quantitative trait loci (QTLs) from human genome-wide scans and animal crossbreeding experiments, and association and linkage studies with candidate genes and other markers is reviewed. Transgenic and knockout murine models relevant to obesity are also incorporated (N = 55). As of October 2003, 41 Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. QTLs reported from animal models currently number 183. There are 208 human QTLs for obesity phenotypes from genome-wide scans and candidate regions in targeted studies. A total of 35 genomic regions harbor QTLs replicated among two to five studies. Attempts to relate DNA sequence variation in specific genes to obesity phenotypes continue to grow, with 272 studies reporting positive associations with 90 candidate genes. Fifteen such candidate genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, more than 430 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful sites can be found at http://obesitygene.pbrc.edu.
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Affiliation(s)
- Eric E Snyder
- Human Genomics Laboratory, Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana 70808-4124, USA
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Pérusse L, Rankinen T, Zuberi A, Chagnon YC, Weisnagel SJ, Argyropoulos G, Walts B, Snyder EE, Bouchard C. The Human Obesity Gene Map: The 2004 Update. ACTA ACUST UNITED AC 2012; 13:381-490. [PMID: 15833932 DOI: 10.1038/oby.2005.50] [Citation(s) in RCA: 212] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
This paper presents the eleventh update of the human obesity gene map, which incorporates published results up to the end of October 2004. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTLs) from animal cross-breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2004, 173 human obesity cases due to single-gene mutations in 10 different genes have been reported, and 49 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 166 genes which, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 221. The number of human obesity QTLs derived from genome scans continues to grow, and we have now 204 QTLs for obesity-related phenotypes from 50 genome-wide scans. A total of 38 genomic regions harbor QTLs replicated among two to four studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably with 358 findings of positive associations with 113 candidate genes. Among them, 18 genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, >600 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful publications and genomic and other relevant sites can be found at http://obesitygene.pbrc.edu.
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Affiliation(s)
- Louis Pérusse
- Division of Kinesiology, Department of Social and Preventive Medicine, Faculty of Medicine, Laval University, Sainte-Foy, Québec, Canada
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Cornes BK, Medland SE, Ferreira MAR, Morley KI, Duffy DL, Heijmans BT, Montgomery GW, Martin NG. Sex-Limited Genome-Wide Linkage Scan for Body Mass Index in an Unselected Sample of 933 Australian Twin Families. Twin Res Hum Genet 2012. [DOI: 10.1375/twin.8.6.616] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
AbstractGenes involved in pathways regulating body weight may operate differently in men and women. To determine whether sex-limited genes influence the obesity-related phenotype body mass index (BMI), we have conducted a general non- scalar sex-limited genome-wide linkage scan using variance components analysis in Mx (Neale, 2002). BMI measurements and genotypic data were available for 2053 Australian female and male adult twins and their siblings from 933 families. Clinical measures of BMI were available for 64.4% of these individuals, while only self-reported measures were available for the remaining participants. The mean age of participants was 39.0 years of age (SD 12.1 years). The use of a sex-limited linkage model identified areas on the genome where quantitative trait loci (QTL) effects differ between the sexes, particularly on chromosome 8 and 20, providing us with evidence that some of the genes responsible for BMI may have different effects in men and women. Our highest linkage peak was observed at 12q24 (–log10p = 3.02), which was near the recommended threshold for suggestive linkage (–log10p = 3.13). Previous studies have found evidence for a quantitative trait locus on 12q24 affecting BMI in a wide range of populations, and candidate genes for non- insulin-dependent diabetes mellitus, a consequence of obesity, have also been mapped to this region. We also identified many peaks near a –log10p of 2 (threshold for replicating an existing finding) in many areas across the genome that are within regions previously identified by other studies, as well as in locations that harbor genes known to influence weight regulation.
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Imumorin IG, Kim EH, Lee YM, De Koning DJ, van Arendonk JA, De Donato M, Taylor JF, Kim JJ. Genome Scan for Parent-of-Origin QTL Effects on Bovine Growth and Carcass Traits. Front Genet 2011; 2:44. [PMID: 22303340 PMCID: PMC3268597 DOI: 10.3389/fgene.2011.00044] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2011] [Accepted: 06/25/2011] [Indexed: 11/13/2022] Open
Abstract
Parent-of-origin effects (POE) such as genomic imprinting influence growth and body composition in livestock, rodents, and humans. Here, we report the results of a genome scan to detect quantitative trait loci (QTL) with POE on growth and carcass traits in Angus × Brahman cattle crossbreds. We identified 24 POE–QTL on 15 Bos taurus autosomes (BTAs) of which six were significant at 5% genome-wide (GW) level and 18 at the 5% chromosome-wide (CW) significance level. Six QTL were paternally expressed while 15 were maternally expressed. Three QTL influencing post-weaning growth map to the proximal end of BTA2 (linkage region of 0–9 cM; genomic region of 5.0–10.8 Mb), for which only one imprinted ortholog is known so far in the human and mouse genomes, and therefore may potentially represent a novel imprinted region. The detected QTL individually explained 1.4 ∼ 5.1% of each trait’s phenotypic variance. Comparative in silico analysis of bovine genomic locations show that 32 out of 1,442 known mammalian imprinted genes from human and mouse homologs map to the identified QTL regions. Although several of the 32 genes have been associated with quantitative traits in cattle, only two (GNAS and PEG3) have experimental proof of being imprinted in cattle. These results lend additional support to recent reports that POE on quantitative traits in mammals may be more common than previously thought, and strengthen the need to identify and experimentally validate cattle orthologs of imprinted genes so as to investigate their effects on quantitative traits.
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Effects of deficiency of the G protein Gsα on energy and glucose homeostasis. Eur J Pharmacol 2011; 660:119-24. [PMID: 21208600 DOI: 10.1016/j.ejphar.2010.10.105] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2010] [Revised: 09/24/2010] [Accepted: 10/12/2010] [Indexed: 02/07/2023]
Abstract
G(s)α is a ubiquitously expressed G protein α-subunit that couples receptors to the generation of intracellular cyclic AMP. The G(s)α gene GNAS is a complex gene that undergoes genomic imprinting, an epigenetic phenomenon that leads to differential expression from the two parental alleles. G(s)α is imprinted in a tissue-specific manner, being expressed primarily from the maternal allele in a small number of tissues. Albright hereditary osteodystrophy is a monogenic obesity disorder caused by heterozygous G(s)α mutations but only when the mutations are maternally inherited. Studies in mice indicate a similar parent-of-origin effect on energy and glucose metabolism, with maternal but not paternal mutations leading to obesity, reduced sympathetic nerve activity and energy expenditure, glucose intolerance and insulin resistance, with no primary effect on food intake. These effects result from G(s)α imprinting leading to severe G(s)α deficiency in one or more regions of the central nervous system, and are associated with a specific defect in melanocortins to stimulate sympathetic nerve activity and energy expenditure.
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Cheverud JM, Lawson HA, Fawcett GL, Wang B, Pletscher LS, R Fox A, Maxwell TJ, Ehrich TH, Kenney-Hunt JP, Wolf JB, Semenkovich CF. Diet-dependent genetic and genomic imprinting effects on obesity in mice. Obesity (Silver Spring) 2011; 19:160-70. [PMID: 20539295 PMCID: PMC3677968 DOI: 10.1038/oby.2010.141] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Although the current obesity epidemic is of environmental origin, there is substantial genetic variation in individual response to an obesogenic environment. In this study, we perform a genome-wide scan for quantitative trait loci (QTLs) affecting obesity per se, or an obese response to a high-fat diet in mice from the LG/J by SM/J Advanced Intercross (AI) Line (Wustl:LG,SM-G16). A total of 1,002 animals from 78 F₁₆ full sibships were weaned at 3 weeks of age and half of each litter placed on high- and low-fat diets. Animals remained on the diet until 20 weeks of age when they were necropsied and the weights of the reproductive, kidney, mesenteric, and inguinal fat depots were recorded. Effects on these phenotypes, along with total fat depot weight and carcass weight at necropsy, were mapped across the genome using 1,402 autosomal single-nucleotide polymorphism (SNP) markers. Haplotypes were reconstructed and additive, dominance, and imprinting genotype scores were derived every 1 cM along the F₁₆ map. Analysis was performed using a mixed model with additive, dominance, and imprinting genotype scores, their interactions with sex, diet, and with sex-by-diet as fixed effects and with family and its interaction with sex, diet, and sex-by-diet as random effects. We discovered 95 trait-specific QTLs mapping to 40 locations. Most QTLs had additive effects with dominance and imprinting effects occurring at two-thirds of the loci. Nearly every locus interacted with sex and/or diet in important ways demonstrating that gene effects are primarily context dependent, changing depending on sex and/or diet.
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Affiliation(s)
- James M Cheverud
- Department of Anatomy & Neurobiology, Washington University School of Medicine, St. Louis, Missouri, USA.
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19
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Kier C, Forde SA. Childhood Overweight and Obesity and Their Association With Asthma. ACTA ACUST UNITED AC 2010. [DOI: 10.1177/2150129710384503] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Catherine Kier
- Stony Brook University Medical Center, Stony Brook, New York (CK)
- Boston University School of Medicine, Boston, Massachusetts (SAF)
| | - Simone A. Forde
- Stony Brook University Medical Center, Stony Brook, New York (CK)
- Boston University School of Medicine, Boston, Massachusetts (SAF)
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20
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Abstract
Patterns and risks of human disease have evolved. In this article, I review evidence regarding the importance of recent adaptive evolution, positive selection, and genomic conflicts in shaping the genetic and phenotypic architectures of polygenic human diseases. Strong recent selection in human populations can create and maintain genetically based disease risk primarily through three processes: increased scope for dysregulation from recent human adaptations, divergent optima generated by intraspecific genomic conflicts, and transient or stable deleterious by-products of positive selection caused by antagonistic pleiotropy, ultimately due to trade-offs at the levels of molecular genetics, development, and physiology. Human disease due to these processes appears to be concentrated in three sets of phenotypes: cognition and emotion, reproductive traits, and life-history traits related to long life-span. Diverse, convergent lines of evidence suggest that a small set of tissues whose pleiotropic patterns of gene function and expression are under especially strong selection-brain, placenta, testis, prostate, breast, and ovary-has mediated a considerable proportion of disease risk in modern humans.
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Affiliation(s)
- Bernard J Crespi
- Department of Biosciences, Simon Fraser University, Burnaby, B. C., Canada V5A 1S6.
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21
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Abstract
Genomic imprinting refers to a class of transmissible genetic effects in which the expression of the phenotype in the offspring depends on the parental origin of the transmitted allele. The DNA from one parent may be epigenetically modified so that only a single allele of the imprinted gene is expressed in the offspring. Although imprinting has an important role in the regulation of growth and development through its role in regulating gene expression, its contribution to susceptibility to common complex disorders is not well understood. We summarize current views on the role of imprinting in diabetes and in particular chromosome 6q24-related transient neonatal diabetes mellitus, the best known example of an imprinted genetic disorder that leads to diabetes.
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Affiliation(s)
- Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland, 6601 West Redwood Street, Baltimore, MD 21201, USA.
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22
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Chiu YF, Chuang LM, Kao HY, Shih KC, Lin MW, Lee WJ, Quertermous T, Curb JD, Chen I, Rodriguez BL, Hsiung CA. Sex-specific genetic architecture of human fatness in Chinese: the SAPPHIRe Study. Hum Genet 2010; 128:501-13. [PMID: 20725740 DOI: 10.1007/s00439-010-0877-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2010] [Accepted: 08/11/2010] [Indexed: 01/02/2023]
Abstract
To dissect the genetic architecture of sexual dimorphism in obesity-related traits, we evaluated the sex-genotype interaction, sex-specific heritability and genome-wide linkages for seven measurements related to obesity. A total of 1,365 non-diabetic Chinese subjects from the family study of the Stanford Asia-Pacific Program of Hypertension and Insulin Resistance were used to search for quantitative trait loci (QTLs) responsible for the obesity-related traits. Pleiotropy and co-incidence effects from the QTLs were also examined using the bivariate linkage approach. We found that sex-specific differences in heritability and the genotype-sex interaction effects were substantially significant for most of these traits. Several QTLs with strong linkage evidence were identified after incorporating genotype by sex (G × S) interactions into the linkage mapping, including one QTL for hip circumference [maximum LOD score (MLS) = 4.22, empirical p = 0.000033] and two QTLs: for BMI on chromosome 12q with MLS 3.37 (empirical p = 0.0043) and 3.10 (empirical p = 0.0054). Sex-specific analyses demonstrated that these linkage signals all resulted from females rather than males. Most of these QTLs for obesity-related traits replicated the findings in other ethnic groups. Bivariate linkage analyses showed several obesity traits were influenced by a common set of QTLs. All regions with linkage signals were observed in one gender, but not in the whole sample, suggesting the genetic architecture of obesity-related traits does differ by gender. These findings are useful for further identification of the liability genes for these phenotypes through candidate genes or genome-wide association analysis.
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Affiliation(s)
- Y-F Chiu
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, 35 Keyan Rd, Zhunan, Miaoli 350, Taiwan, ROC
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23
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Yazbek SN, Spiezio SH, Nadeau JH, Buchner DA. Ancestral paternal genotype controls body weight and food intake for multiple generations. Hum Mol Genet 2010; 19:4134-44. [PMID: 20696673 DOI: 10.1093/hmg/ddq332] [Citation(s) in RCA: 61] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Current treatments have largely failed to slow the rapidly increasing world-wide prevalence of obesity and its co-morbidities. Despite a strong genetic contribution to obesity (40-70%), only a small percentage of heritability is explained with current knowledge of monogenic abnormalities, common sequence variants and conventional modes of inheritance. Epigenetic effects are rarely tested in humans because of difficulties arranging studies that distinguish conventional and transgenerational inheritance while simultaneously controlling environmental factors and learned behaviors. However, growing evidence from model organisms implicates genetic and environmental factors in one generation that affect phenotypes in subsequent generations. In this report, we provide the first evidence for paternal transgenerational genetic effects on body weight and food intake. This test focused on the obesity-resistant 6C2d congenic strain, which carries the Obrq2a(A/J) allele on an otherwise C57BL/6J background. Various crosses between 6C2d and the control C57BL/6J strain showed that the Obrq2a(A/J) allele in the paternal or grandpaternal generation was sufficient to inhibit diet-induced obesity and reduce food intake in the normally obesity-susceptible, high food intake C57BL/6J strain. These obesity-resistant and reduced food intake phenotypes were transmitted through the paternal lineage but not the maternal lineage with equal strength for at least two generations. Eliminating social interaction between the father and both his offspring and the pregnant dam did not significantly affect food intake levels, demonstrating that the phenotype is transmitted through the male germline rather than through social interactions. Persistence of these phenotypes across multiple generations raises the possibility that transgenerational genetic effects contribute to current metabolic conditions.
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Affiliation(s)
- Soha N Yazbek
- Department of Genetics, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
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24
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Weinstein LS, Xie T, Qasem A, Wang J, Chen M. The role of GNAS and other imprinted genes in the development of obesity. Int J Obes (Lond) 2009; 34:6-17. [PMID: 19844212 DOI: 10.1038/ijo.2009.222] [Citation(s) in RCA: 61] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Genomic imprinting is an epigenetic phenomenon affecting a small number of genes, which leads to differential expression from the two parental alleles. Imprinted genes are known to regulate fetal growth and a 'kinship' or 'parental conflict' model predicts that paternally and maternally expressed imprinted genes promote and inhibit fetal growth, respectively. In this review we examine the role of imprinted genes in postnatal growth and metabolism, with an emphasis on the GNAS/Gnas locus. GNAS is a complex imprinted locus with multiple oppositely imprinted gene products, including the G-protein alpha-subunit G(s)alpha that is expressed primarily from the maternal allele in some tissues and the G(s)alpha isoform XLalphas that is expressed only from the paternal allele. Maternal, but not paternal, G(s)alpha mutations lead to obesity in Albright hereditary osteodystrophy. Mouse studies show that this phenomenon is due to G(s)alpha imprinting in the central nervous system leading to a specific defect in the ability of central melanocortins to stimulate sympathetic nervous system activity and energy expenditure. In contrast mutation of paternally expressed XLalphas leads to opposite metabolic effects in mice. Although these findings conform to the 'kinship' model, the effects of other imprinted genes on body weight regulation do not conform to this model.
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Affiliation(s)
- L S Weinstein
- Signal Transduction Section, National Institute of Diabetes, Digestive, and Kidney Disease, National Institutes of Health, Building 10 Rm 8C101, Bethesda, MD 20892-1752, USA.
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A novel locus for arterial hypertension on chromosome 1p36 maps to a metabolic syndrome trait cluster in the Sorbs, a Slavic population isolate in Germany. J Hypertens 2009; 27:983-90. [PMID: 19373111 DOI: 10.1097/hjh.0b013e328328123d] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
OBJECTIVE Genome-wide linkage studies and genome-wide association studies have not as yet identified major genes contributing to primary hypertension in the general population. This state-of-affairs suggests considerable heterogeneity with small contributing effects for primary hypertension, or other complex genetic traits, in outbred populations. Isolated populations, as recent data from Iceland and French Canada suggest, could offer a solution to this problem. METHODS We studied a Slavic isolate in Germany, the Sorbs, and genotyped 1040 polymorphic microsatellite markers in 87 multigeneration families. RESULTS Our genome-wide linkage scan revealed a locus on chromosome 1p36.13 at D1S3669-D1S2826 (40.95 cM Marshfield coordinates; logarithm of the odds = 3.45, nominal P = 0.00003) that reached genome-wide significance (P = 0.004), indicating the increased power in isolated populations. The chromosome 1 locus maps to a region in which traits such as diabetes, hyperlipidemia, obesity and BMI cluster. CONCLUSION Our results suggest that this locus contributes to the metabolic syndrome, and that further attention in this and other populations is warranted.
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Basu A, Tang H, Arnett D, Gu CC, Mosley T, Kardia S, Luke A, Tayo B, Cooper R, Zhu X, Risch N. Admixture mapping of quantitative trait loci for BMI in African Americans: evidence for loci on chromosomes 3q, 5q, and 15q. Obesity (Silver Spring) 2009; 17:1226-31. [PMID: 19584881 PMCID: PMC2929755 DOI: 10.1038/oby.2009.24] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Obesity is a heritable trait and a major risk factor for highly prevalent common diseases such as hypertension and type 2 diabetes. Previously we showed that BMI was positively correlated with African ancestry among the African Americans (AAs) in the US National Heart, Lung, and Blood Institute's Family Blood Pressure Program (FBPP). In a set of 1,344 unrelated AAs, using Individual Ancestry (IA) estimates at 284 marker locations across the genome, we now present a quantitative admixture mapping analysis of BMI. We used a set of unrelated individuals from Nigeria to represent the African ancestral population and the European American (EA) in the FBPP as the European ancestral population. The analysis was based on a common set of 284 microsatellite markers genotyped in all three groups. We considered the quantitative trait, BMI, as the response variable in a regression analysis with the marker location specific excess European ancestry as the explanatory variable. After suitably adjusting for different covariates such as sex, age, and network, we found strong evidence for a positive association with European ancestry at chromosome locations 3q29 and 5q14 and a negative association on chromosome 15q26. To our knowledge, this is the largest quantitative admixture mapping effort in terms of sample size and marker locus involvement for the trait. These results suggest that these regions may harbor genes influencing BMI in the AA population.
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Affiliation(s)
- Analabha Basu
- Institute for Human Genetics, Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
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Abstract
Common DNA sequence variants inadequately explain variability in fat mass among individuals. Abnormal body weights are characteristic of specific imprinted-gene disorders. However, the relevance of imprinted genes to our understanding of obesity among the general population is uncertain. Hitherto unidentified imprinted genes and epigenetic mosaicism are two of the challenges for this emerging field of epigenetics. Subtle epigenetic differences in imprinted genes and gene networks are likely to be present among cells, tissues and individuals. In order to advance obesity research it will be necessary to use genome-wide, next-generation sequencing approaches that allow the detection of such epigenetic differences.
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Affiliation(s)
- Reinhard Stöger
- Department of Biology, University of Washington, 156 Kincaid Hall, Box 351800, Seattle, WA, 98195-1800, USA.
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28
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Rampersaud E, Mitchell BD, Naj AC, Pollin TI. Investigating parent of origin effects in studies of type 2 diabetes and obesity. Curr Diabetes Rev 2008; 4:329-39. [PMID: 18991601 PMCID: PMC2896493 DOI: 10.2174/157339908786241179] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
The role of parent-of-origin effects (POE) in the etiology of complex diseases such as type 2 diabetes (T2DM) and obesity is currently of intense interest, but still largely unclear. POE are transmittable genetic effects whereby the expression of the phenotype in the offspring depends upon whether the transmission originated from the mother or father. In mammals, POE can be caused by genetic imprinting, intrauterine effects, or maternally inherited mitochondrial genes. In this paper, we describe the different mechanisms underlying POE, characterize known examples of POE in rare forms of diabetes, and review the evidence from linkage and association studies for POE in T2DM and obesity. Finally, we summarize some of the new and established statistical and experimental approaches commonly used to detect POE. Through this paper, we hope emphasizes the potentially significant importance of POE in the etiology of T2DM and obesity.
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Affiliation(s)
- Evadnie Rampersaud
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland, Baltimore, MD, USA.
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29
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Crespi B. Genomic imprinting in the development and evolution of psychotic spectrum conditions. Biol Rev Camb Philos Soc 2008; 83:441-93. [PMID: 18783362 DOI: 10.1111/j.1469-185x.2008.00050.x] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
I review and evaluate genetic and genomic evidence salient to the hypothesis that the development and evolution of psychotic spectrum conditions have been mediated in part by alterations of imprinted genes expressed in the brain. Evidence from the genetics and genomics of schizophrenia, bipolar disorder, major depression, Prader-Willi syndrome, Klinefelter syndrome, and other neurogenetic conditions support the hypothesis that the etiologies of psychotic spectrum conditions commonly involve genetic and epigenetic imbalances in the effects of imprinted genes, with a bias towards increased relative effects from imprinted genes with maternal expression or other genes favouring maternal interests. By contrast, autistic spectrum conditions, including Kanner autism, Asperger syndrome, Rett syndrome, Turner syndrome, Angelman syndrome, and Beckwith-Wiedemann syndrome, commonly engender increased relative effects from paternally expressed imprinted genes, or reduced effects from genes favouring maternal interests. Imprinted-gene effects on the etiologies of autistic and psychotic spectrum conditions parallel the diametric effects of imprinted genes in placental and foetal development, in that psychotic spectrum conditions tend to be associated with undergrowth and relatively-slow brain development, whereas some autistic spectrum conditions involve brain and body overgrowth, especially in foetal development and early childhood. An important role for imprinted genes in the etiologies of psychotic and autistic spectrum conditions is consistent with neurodevelopmental models of these disorders, and with predictions from the conflict theory of genomic imprinting.
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Affiliation(s)
- Bernard Crespi
- Department of Biosciences, Simon Fraser University, Burnaby BCV5A1S6, Canada.
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30
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Sung YJ, Rao D. Model-based linkage analysis with imprinting for quantitative traits: ignoring imprinting effects can severely jeopardize detection of linkage. Genet Epidemiol 2008; 32:487-96. [DOI: 10.1002/gepi.20321] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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31
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Psychosis and autism as diametrical disorders of the social brain. Behav Brain Sci 2008; 31:241-61; discussion 261-320. [DOI: 10.1017/s0140525x08004214] [Citation(s) in RCA: 379] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
AbstractAutistic-spectrum conditions and psychotic-spectrum conditions (mainly schizophrenia, bipolar disorder, and major depression) represent two major suites of disorders of human cognition, affect, and behavior that involve altered development and function of the social brain. We describe evidence that a large set of phenotypic traits exhibit diametrically opposite phenotypes in autistic-spectrum versus psychotic-spectrum conditions, with a focus on schizophrenia. This suite of traits is inter-correlated, in that autism involves a general pattern of constrained overgrowth, whereas schizophrenia involves undergrowth. These disorders also exhibit diametric patterns for traits related to social brain development, including aspects of gaze, agency, social cognition, local versus global processing, language, and behavior. Social cognition is thus underdeveloped in autistic-spectrum conditions and hyper-developed on the psychotic spectrum.;>We propose and evaluate a novel hypothesis that may help to explain these diametric phenotypes: that the development of these two sets of conditions is mediated in part by alterations of genomic imprinting. Evidence regarding the genetic, physiological, neurological, and psychological underpinnings of psychotic-spectrum conditions supports the hypothesis that the etiologies of these conditions involve biases towards increased relative effects from imprinted genes with maternal expression, which engender a general pattern of undergrowth. By contrast, autistic-spectrum conditions appear to involve increased relative bias towards effects of paternally expressed genes, which mediate overgrowth. This hypothesis provides a simple yet comprehensive theory, grounded in evolutionary biology and genetics, for understanding the causes and phenotypes of autistic-spectrum and psychotic-spectrum conditions.
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He LN, Liu YJ, Xiao P, Zhang L, Guo Y, Yang TL, Zhao LJ, Drees B, Hamilton J, Deng HY, Recker RR, Deng HW. Genomewide Linkage Scan for Combined Obesity Phenotypes using Principal Component Analysis. Ann Hum Genet 2008; 72:319-26. [DOI: 10.1111/j.1469-1809.2007.00423.x] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Lasky-Su J, Lyon HN, Emilsson V, Heid IM, Molony C, Raby BA, Lazarus R, Klanderman B, Soto-Quiros ME, Avila L, Silverman EK, Thorleifsson G, Thorsteinsdottir U, Kronenberg F, Vollmert C, Illig T, Fox CS, Levy D, Laird N, Ding X, McQueen MB, Butler J, Ardlie K, Papoutsakis C, Dedoussis G, O'Donnell CJ, Wichmann HE, Celedón JC, Schadt E, Hirschhorn J, Weiss ST, Stefansson K, Lange C. On the replication of genetic associations: timing can be everything! Am J Hum Genet 2008; 82:849-58. [PMID: 18387595 PMCID: PMC2427263 DOI: 10.1016/j.ajhg.2008.01.018] [Citation(s) in RCA: 107] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2007] [Revised: 12/10/2007] [Accepted: 01/11/2008] [Indexed: 01/22/2023] Open
Abstract
The failure of researchers to replicate genetic-association findings is most commonly attributed to insufficient statistical power, population stratification, or various forms of between-study heterogeneity or environmental influences.(1) Here, we illustrate another potential cause for nonreplications that has so far not received much attention in the literature. We illustrate that the strength of a genetic effect can vary by age, causing "age-varying associations." If not taken into account during the design and the analysis of a study, age-varying genetic associations can cause nonreplication. By using the 100K SNP scan of the Framingham Heart Study, we identified an age-varying association between a SNP in ROBO1 and obesity and hypothesized an age-gene interaction. This finding was followed up in eight independent samples comprising 13,584 individuals. The association was replicated in five of the eight studies, showing an age-dependent relationship (one-sided combined p = 3.92 x 10(-9), combined p value from pediatric cohorts = 2.21 x 10(-8), combined p value from adult cohorts = 0.00422). Furthermore, this study illustrates that it is difficult for cross-sectional study designs to detect age-varying associations. If the specifics of age- or time-varying genetic effects are not considered in the selection of both the follow-up samples and in the statistical analysis, important genetic associations may be missed.
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Affiliation(s)
- Jessica Lasky-Su
- SUNY Upstate Medical University, Syracuse, NY 13210, USA
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Helen N. Lyon
- Divisions of Genetics and Endocrinology, Program in Genomics, Children's Hospital, Boston, MA 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Valur Emilsson
- deCode Genetics, IS-101 Reykjavik, Iceland
- Rosetta Inpharmatics, Seattle, WA 98109, USA
| | - Iris M. Heid
- GSF National Research Centre for Environment and Health, Institute of Epidemiology, 85764 Neuherberg, Germany
- Institute of Medical Informatics, Biometry, and Epidemiology, Ludwig-Maximilians-University, 80539 Munich, Germany
| | | | - Benjamin A. Raby
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Ross Lazarus
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Barbara Klanderman
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Manuel E. Soto-Quiros
- Division of Pediatric Pulmonology, Hospital Nacional de Niños, PO Box 1654-1000, San José, Costa Rica
| | - Lydiana Avila
- Division of Pediatric Pulmonology, Hospital Nacional de Niños, PO Box 1654-1000, San José, Costa Rica
| | - Edwin K. Silverman
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | | | - Florian Kronenberg
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, 6020 Innsbruck, Austria
| | - Caren Vollmert
- GSF National Research Centre for Environment and Health, Institute of Epidemiology, 85764 Neuherberg, Germany
| | - Thomas Illig
- GSF National Research Centre for Environment and Health, Institute of Epidemiology, 85764 Neuherberg, Germany
| | - Caroline S. Fox
- National Heart, Lung, and Blood Institute and its Framingham Heart Study, Framingham, MA 01702, USA
| | - Daniel Levy
- National Heart, Lung, and Blood Institute and its Framingham Heart Study, Framingham, MA 01702, USA
| | - Nan Laird
- Harvard School of Public Health, Boston, MA 02115, USA
| | - Xiao Ding
- Harvard School of Public Health, Boston, MA 02115, USA
| | - Matt B. McQueen
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO 80309, USA
| | - Johannah Butler
- Divisions of Genetics and Endocrinology, Program in Genomics, Children's Hospital, Boston, MA 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Kristin Ardlie
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | | | - George Dedoussis
- Department of Nutrition and Dietetics, Harokopio University, Athens 17671, Greece
| | - Christopher J. O'Donnell
- National Heart, Lung, and Blood Institute and its Framingham Heart Study, Framingham, MA 01702, USA
| | - H.-Erich Wichmann
- GSF National Research Centre for Environment and Health, Institute of Epidemiology, 85764 Neuherberg, Germany
- Institute of Medical Informatics, Biometry, and Epidemiology, Ludwig-Maximilians-University, 80539 Munich, Germany
| | - Juan C. Celedón
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Eric Schadt
- Rosetta Inpharmatics, Seattle, WA 98109, USA
| | - Joel Hirschhorn
- Divisions of Genetics and Endocrinology, Program in Genomics, Children's Hospital, Boston, MA 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Scott T. Weiss
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Christoph Lange
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
- Harvard School of Public Health, Boston, MA 02115, USA
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Cheverud JM, Hager R, Roseman C, Fawcett G, Wang B, Wolf JB. Genomic imprinting effects on adult body composition in mice. Proc Natl Acad Sci U S A 2008; 105:4253-8. [PMID: 18337500 PMCID: PMC2393747 DOI: 10.1073/pnas.0706562105] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2007] [Indexed: 11/18/2022] Open
Abstract
Genomic imprinting results in the differential expression of genes, depending on which allele is inherited from the mother and which from the father. The effects of such differential gene expression are reflected in phenotypic differences between the reciprocal heterozygotes (Aa vs. aA). Although many imprinted genes have been identified and play a key role in development, little is known about the contribution of imprinting to quantitative variation in trait expression. Here, we examine this problem by mapping imprinting effects on adult body composition traits in the F(3) generation of an intercross between the Large (LG/J) and Small (SM/J) inbred mouse strains. We identified eight pleiotropic imprinted quantitative trait loci (iQTL) located throughout the genome. Most iQTL are in novel locations that have not previously been associated with imprinting effects, but those on chromosomes 7, 12, and centromeric 18 lie in regions previously identified as containing imprinted genes. Our results show that the effects of genomic imprinting are relatively small, with reciprocal heterozygotes differing by approximately 0.25 standard deviation units and the effects at each locus accounting for 1% to 4% of the phenotypic variance. We detected a variety of imprinting patterns, with paternal expression being the most common. These results indicate that genomic imprinting has small, but detectable, effects on the normal variation of complex traits in adults and is likely to be more common than usually thought.
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Affiliation(s)
- James M. Cheverud
- *Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Reinmar Hager
- Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, United Kingdom; and
| | - Charles Roseman
- Department of Anthropology, University of Illinois at Urbana–Champaign, Urbana, IL 61801
| | - Gloria Fawcett
- *Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Bing Wang
- *Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Jason B. Wolf
- Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, United Kingdom; and
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The MTHFR gene polymorphism is associated with lean body mass but not fat body mass. Hum Genet 2008; 123:189-96. [DOI: 10.1007/s00439-007-0463-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2007] [Accepted: 12/23/2007] [Indexed: 01/25/2023]
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Abstract
Thanks to the recent revolutionary genomic advances such as the International HapMap consortium, resolution of the genetic architecture of common complex traits is beginning to look hopeful. While demonstrating the feasibility of genome-wide association (GWA) studies, the pathbreaking Wellcome Trust Case Control Consortium (WTCCC) study also serves to underscore the critical importance of very large sample sizes and draws attention to potential problems, which need to be addressed as part of the study design. Even the large WTCCC study had vastly inadequate power for several of the associations reported (and confirmed) and, therefore, most of the regions harboring relevant associations may not be identified anytime soon. This chapter provides an overview of some of the key developments in the methodological approaches to genetic dissection of common complex traits. Constrained Bayesian networks are suggested as especially useful for analysis of pathway-based SNPs. Likewise, composite likelihood is suggested as a promising method for modeling complex systems. It discusses the key steps in a study design, with an emphasis on GWA studies. Potential limitations highlighted by the WTCCC GWA study are discussed, including problems associated with massive genotype imputation, analysis of pooled national samples, shared controls, and the critical role of interactions. GWA studies clearly need massive sample sizes that are only possible through genuine collaborations. After all, for common complex traits, the question is not whether we can find some pieces of the puzzle, but how large and what kind of a sample we need to (nearly) solve the genetic puzzle.
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Affiliation(s)
- D C Rao
- Division of Biostatistics and Departments of Genetics, Psychiatry, and Mathematics, School of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA
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Imprinted Genes, Postnatal Adaptations and Enduring Effects on Energy Homeostasis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2008; 626:41-61. [DOI: 10.1007/978-0-387-77576-0_4] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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Voruganti VS, Göring HHH, Diego VP, Cai G, Mehta NR, Haack K, Cole SA, Butte NF, Comuzzie AG. Genome-wide scan for serum ghrelin detects linkage on chromosome 1p36 in Hispanic children: results from the Viva La Familia study. Pediatr Res 2007; 62:445-50. [PMID: 17667848 DOI: 10.1203/pdr.0b013e31813cbf02] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
This study was conducted to investigate genetic influence on serum ghrelin and its relationship with adiposity-related phenotypes in Hispanic children (n=1030) from the Viva La Familia study (VFS). Anthropometric measurements and levels of serum ghrelin were estimated and genetic analyses conducted according to standard procedures. Mean age, body mass index (BMI), and serum ghrelin were 11+/-0.13 y, 25+/-0.24 kg/m2 and 38+/-0.5 ng/mL, respectively. Significant heritabilities (p<0.001) were obtained for BMI, weight, fat mass, percent fat, waist circumference, waist-to-height ratio, and ghrelin. Bivariate analyses of ghrelin with adiposity traits showed significant negative genetic correlations (p<0.0001) with weight, BMI, fat mass, percent fat, waist circumference, and waist-to-height ratio. A genome-wide scan for ghrelin detected significant linkage on chromosome 1p36.2 between STR markers D1S2697 and D1S199 (LOD=3.2). The same region on chromosome 1 was the site of linkage for insulin (LOD=3.3), insulinlike growth factor binding protein 1 (IGFBP1) (LOD=3.4), homeostatic model assessment method (HOMA) (LOD=2.9), and C-peptide (LOD=2.0). Several family-based studies have reported linkages for obesity-related phenotypes in the region of 1p36. These results indicate the importance of this region in relation to adiposity in children from the VFS.
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Affiliation(s)
- V Saroja Voruganti
- Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas 78227, USA.
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Voruganti VS, Tejero ME, Proffitt JM, Cole SA, Freeland-Graves JH, Comuzzie AG. Genome-wide scan of plasma cholecystokinin in baboons shows linkage to human chromosome 17. Obesity (Silver Spring) 2007; 15:2043-50. [PMID: 17712122 DOI: 10.1038/oby.2007.243] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVE Cholecystokinin (CCK) is known to inhibit food intake and is an important signal for controlling meal volume, indicating a possible role in weight regulation. Our objective was to investigate genetic influences on plasma CCK in baboons. RESEARCH METHODS AND PROCEDURES Subjects were 376 baboons (males = 113, females = 263) from the Southwest National Primate Research Center, housed at the Southwest Foundation for Biomedical Research, San Antonio, Texas. Anthropometric and biochemical parameters were analyzed. Genetic effects on plasma CCK were estimated by the maximum likelihood-based variance components method implemented in the software program SOLAR (Sequential Oligogenic Linkage Analysis Routines). RESULTS Male baboons (32.7 +/- 6 kg) were much heavier than females (20.2 +/- 4 kg). Similarly, mean (+/- standard deviation) plasma CCK values were also higher in male baboons (13.8 +/- 6 pM) than female baboons (12.5 +/- 4 pM). Significant heritabilities were observed for plasma CCK (0.14 +/- 0.1, p < 0.05), body weight (h2 = 0.62 +/- 0.15, p < 10(-8)), and glucose (h2 = 0.68 +/- 0.17, p < 10(-7)). A genome-wide scan of plasma CCK detected a strong signal for a quantitative trait locus (QTL) on chromosome 17p12-13 [logarithm of the odds (LOD) = 3.1] near marker D17S804. Suggestive evidence of a second QTL was observed on chromosome 4q34-35 (LOD = 2.3) near marker D4S2374. DISCUSSION A substantial contribution of additive genetic effects to the variation in plasma levels of CCK was demonstrated in baboons. The identification of a QTL for plasma CCK on chromosome 17p is significant, as several obesity-related traits such as BMI, leptin, adiponectin, and acylation stimulating protein have already been mapped to this region.
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Affiliation(s)
- V Saroja Voruganti
- Department of Genetics, Southwest Foundation for Biomedical Research, P.O. Box 760549, San Antonio, TX 78245-0549, USA.
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Boesgaard TW, Castella SI, Andersen G, Albrechtsen A, Sparsø T, Borch-Johnsen K, Jørgensen T, Hansen T, Pedersen O. A -243A-->G polymorphism upstream of the gene encoding GAD65 associates with lower levels of body mass index and glycaemia in a population-based sample of 5857 middle-aged White subjects. Diabet Med 2007; 24:702-6. [PMID: 17459095 DOI: 10.1111/j.1464-5491.2007.02110.x] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
AIMS The glutamate decarboxylase gene (GAD2) encodes GAD65, an enzyme catalysing the production of the gamma-aminobutyric acid (GABA) which interacts with neuropeptide Y to stimulate food intake. It has been suggested that in pancreatic islets, GABA serves as a functional regulator of pancreatic hormone release. Conflicting results have been reported concerning the potential impact of GAD2 variation on estimates of energy metabolism. The aim of this study was to elucidate potential associations between the GAD2-243A-->G polymorphism and levels of body mass index (BMI) and estimates of glycaemia. METHODS Using high-throughput chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, the GAD2-243A-->G (rs2236418) polymorphism was genotyped in a population-based sample (Inter99) of 5857 middle-aged, unrelated Danish White subjects. RESULTS The G-allele was associated with modestly lower BMI (P = 0.01). In a case-control study of obesity, the G-allele frequency in 2582 participants with BMI < 25 kg/m2 was 19.5% (18.4-20.6) compared with 17.1% (15.5-18.8) in 968 participants having BMI > or = 30 kg/m2 (P = 0.03), odds ratio 0.9 (0.7-1.0). Of the 5857 subjects, GG carriers had lower fasting plasma glucose levels (mmol/l) [AA (n = 3859) 5.6 +/- 0.8; AG (n = 1792) 5.5 +/- 0.8; GG (n = 206) 5.5 +/- 0.8, P = 0.008] and lower 30-min oral glucose tolerance test (OGTT)-related plasma glucose levels (AA 8.7 +/- 1.9; AG 8.6 +/- 1.9; GG 8.6 +/- 2.0, P = 0.04), adjusted for sex, age and BMI. Analysing subjects who were both normoglycaemic and glucose tolerant (n = 4431) GG carriers still had lower fasting plasma glucose concentrations: AA (n = 2895) 5.3 +/- 0.4; AG (n = 1383) 5.3 +/- 0.4; GG (n = 153) 5.2 +/- 0.4 (P = 9.10(-5)). CONCLUSION The present study suggests that the GAD2-243A-->G polymorphism in a population of middle-aged White people associates with a modest reduction in BMI and fasting and OGTT-related plasma glucose levels.
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Almasy L, Göring HHH, Diego V, Cole S, Laston S, Dyke B, Howard BV, Lee ET, Best LG, Devereux R, Fabsitz RR, MacCluer JW. A novel obesity locus on chromosome 4q: the Strong Heart Family Study. Obesity (Silver Spring) 2007; 15:1741-8. [PMID: 17636092 DOI: 10.1038/oby.2007.207] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVE Obesity is a growing and important public health problem in Western countries and worldwide. There is ample evidence that both environmental and genetic factors influence the risk of developing obesity. Although a number of genes influencing obesity and obesity-related measures have been localized, it is clear that others remain to be identified. The rate of obesity is particularly high in American Indian populations. This study reports the results of a genome-wide scan for loci influencing BMI and weight in 963 individuals in 58 families from three American Indian populations in Arizona, Oklahoma, and North and South Dakota participating in the Strong Heart Family Study. RESEARCH METHODS AND PROCEDURES Short tandem repeat markers were genotyped, resulting in a marker map with an average spacing of 10 centimorgans. Standard multipoint variance component linkage methods were used. RESULTS Significant evidence of linkage was observed in the overall sample, including all three study sites, for a locus on chromosome 4q35 [logarithm of the odds (LOD)=5.17 for weight, 5.08 for BMI]. Analyses of the three study sites individually showed that the greatest linkage support for the chromosome 4 locus came from Arizona (LOD=2.6 for BMI), but that LOD scores for weight were >1 in all three samples. Suggestive linkage signals (LOD>2) were also observed on chromosomes 5, 7, 8, and 10. DISCUSSION The chromosome 4 locus detected in this scan is in a region lacking any obvious positional candidate genes with known functions related to obesity. This locus may represent a novel obesity gene.
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Affiliation(s)
- Laura Almasy
- Department of Genetics, Southwest Foundation for Biomedical Research, P.O. Box 760549, San Antonio TX 78245-0549, USA.
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Gorlova OY, Lei L, Zhu D, Weng SF, Shete S, Zhang Y, Li WD, Price RA, Amos CI. Imprinting detection by extending a regression-based QTL analysis method. Hum Genet 2007; 122:159-74. [PMID: 17562082 DOI: 10.1007/s00439-007-0387-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2007] [Accepted: 05/25/2007] [Indexed: 12/30/2022]
Abstract
We present an extension of a regression-based quantitative-trait linkage analysis method to incorporate parent-of-origin effects. We separately regressed total, paternal, and maternal IBD sharing on traits' squared sums and differences. We also developed a test for imprinting that indicates whether there is any difference between the paternal and maternal regression coefficients. Since this method treats the identity-by-descent information as the dependent variable that is conditioned on the trait, it can be readily applied to data from complex ascertainment processes. We performed a simulation study to examine the performance of the method. We found that when using empirical critical values, the method shows identical or higher power compared to existing methods for evaluation of parent-of-origin effect in linkage analysis of quantitative traits. Missing parental genotypes increase the type I error rate of the linkage test and decrease the power of the imprinting test. When the major gene has a low heritability, the power of the method decreases considerably, but the statistical tests still perform well. We also applied a permutation algorithm, which ensures the appropriate type I error rate for the test for imprinting. The method was applied to a data from a study of 6 body size related measures and 23 loci on chromosome 7 for 255 nuclear families. Multipoint identities-by-descent (IBD) were obtained using a modification of the SIMWALK 2 program. A parent-of-origin effect consistent with maternal imprinting was suggested at 99.67-111.26 Mb for body mass index, bioelectrical impedance analysis, waist circumference, and leptin concentration.
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Affiliation(s)
- Olga Y Gorlova
- Department of Epidemiology, MD Anderson Cancer Center, University of Texas, Unit 1340, 1155 Pressler Street, Houston, TX 77030, USA.
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Fradin D, Heath S, Lathrop M, Bougnères P. Quantitative trait loci for fasting glucose in young Europeans replicate previous findings for type 2 diabetes in 2q23-24 and other locations. Diabetes 2007; 56:1742-5. [PMID: 17416800 DOI: 10.2337/db06-1329] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Long before reaching diagnostic cutoff levels for type 2 diabetes, fasting glucose can be a powerful risk marker for this disease. We conducted a genome-wide search for fasting glucose as a quantitative trait in 412 young European sib-pairs including obese children, with adjustment for sex, age, and BMI. We identified more quantitative trait loci specific to fasting glucose and more significant than would be found by simple chance estimated by permutation tests. The strongest linkage was on chromosome 2q (logarithm of odds [LOD] = 3.00) in a region previously linked to type 2 diabetes as a disease. We also found linkage signals of fasting glucose with 7q (LOD = 2.03), 8q (1.28), 17p (2.12), 17q (1.4), and 11p (1.33). These findings suggest that the quantitative genetics of fasting glucose could contribute to the search for type 2 diabetes genes.
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Affiliation(s)
- Delphine Fradin
- Department of Pediatric Endocrinology, Hôpital Saint-Vincent de Paul and U561 Institut National de la Santé et de la Recherche Médicale, Paris, France.
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Farber CR, Medrano JF. Fine mapping reveals sex bias in quantitative trait loci affecting growth, skeletal size and obesity-related traits on mouse chromosomes 2 and 11. Genetics 2007; 175:349-60. [PMID: 17110492 PMCID: PMC1775020 DOI: 10.1534/genetics.106.063693] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2006] [Accepted: 10/16/2006] [Indexed: 01/30/2023] Open
Abstract
Previous speed congenic analysis has suggested that the expression of growth and obesity quantitative trait loci (QTL) on distal mouse chromosomes (MMU) 2 and 11, segregating between the CAST/EiJ (CAST) and C57BL/6J-hg/hg (HG) strains, is dependent on sex. To confirm, fine map, and further evaluate QTL x sex interactions, we constructed congenic by recipient F2 crosses for the HG.CAST-(D2Mit329-D2Mit457)N(6) (HG2D) and HG.CAST-(D11Mit260-D11Mit255)N(6) (HG11) congenic strains. Over 700 F2 mice were densely genotyped and phenotyped for a panel of 40 body and organ weight, skeletal length, and obesity-related traits at 9 weeks of age. Linkage analysis revealed 20 QTL affecting a representative subset of phenotypes in HG2DF2 and HG11F2 mice. The effect of sex was quantified by comparing two linear models: the first model included sex as an additive covariate and the second incorporated sex as an additive and an interactive covariate. Of the 20 QTL, 8 were sex biased, sex specific, or sex antagonistic. Most traits were regulated by single QTL; however, two closely linked loci were identified for five traits in HG2DF2 mice. Additionally, the confidence intervals for most QTL were significantly reduced relative to the original mapping results, setting the stage for quantitative trait gene (QTG) discovery. These results highlight the importance of assessing the contribution of sex in complex trait analyses.
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Affiliation(s)
- Charles R Farber
- Department of Animal Science, University of California, Davis, California 95016-8521, USA
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Zhao LJ, Xiao P, Liu YJ, Xiong DH, Shen H, Recker RR, Deng HW. A genome-wide linkage scan for quantitative trait loci underlying obesity related phenotypes in 434 Caucasian families. Hum Genet 2006; 121:145-8. [PMID: 17115187 DOI: 10.1007/s00439-006-0286-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2006] [Accepted: 10/18/2006] [Indexed: 01/09/2023]
Abstract
To identify quantitative trait loci (QTLs) that contribute to obesity, we performed a large-scale whole genome linkage scan (WGS) involving 4,102 individuals from 434 Caucasian families. The most pronounced linkage evidence was found at the genomic region 20p11-12 for fat mass (LOD = 3.31) and percentage fat mass (PFM) (LOD = 2.92). We also identified several regions showing suggestive linkage signals (threshold LOD = 1.9) for obesity phenotypes, including 5q35, 8q13, 10p12, and 17q11.
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Affiliation(s)
- Lan-Juan Zhao
- Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University, Omaha, NE 68131, USA
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Wuschke S, Dahm S, Schmidt C, Joost HG, Al-Hasani H. A meta-analysis of quantitative trait loci associated with body weight and adiposity in mice. Int J Obes (Lond) 2006; 31:829-41. [PMID: 17060928 DOI: 10.1038/sj.ijo.0803473] [Citation(s) in RCA: 74] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
OBJECTIVE Cross-breeding experiments with different mouse strains have successfully been used by many groups to identify genetic loci that predispose for obesity. In order to provide a statistical assessment of these quantitative trait loci (QTL) as a basis for a systematic investigation of candidate genes, we have performed a meta-analysis of genome-wide linkage scans for body weight and body fat. DATA From a total of 34 published mouse cross-breeding experiments, we compiled a list of 162 non-redundant QTL for body weight and 117 QTL for fat weight and body fat percentage. Collectively, these studies include data from 42 different parental mouse strains and >14,500 individual mice. METHODS The results of the studies were analyzed using the truncated product method (TPM). RESULTS The analysis revealed significant evidence (logarithm of odds (LOD) score >4.3) for linkage of body weight and adiposity to 49 different segments of the mouse genome. The most prominent regions with linkage for body weight and body fat (LOD scores 14.8-21.8) on chromosomes 1, 2, 7, 11, 15, and 17 contain a total of 58 QTL for body weight and body fat. At least 34 candidate genes and genetic loci, which have been implicated in regulation of body weight and body composition in rodents and/or humans, are found in these regions, including CCAAT/enhancer-binding protein alpha (C/EBPA), sterol regulatory element-binding transcription factor 1 (SREBP-1), peroxisome proliferator activator receptor delta (PPARD), and hydroxysteroid 11-beta dehydrogenase 1 (HSD11B1). Our results demonstrate the presence of numerous distinct consensus QTL regions with highly significant LOD scores that control body weight and body composition. An interactive physical map of the QTL is available online at (http://www.obesitygenes.org).
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Affiliation(s)
- S Wuschke
- Department of Pharmacology, German Institute for Human Nutrition, Potsdam-Rehbrücke, Nuthetal, Germany
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Cai G, Cole SA, Butte N, Bacino C, Diego V, Tan K, Göring HH, O'Rahilly S, Farooqi IS, Comuzzie AG. A quantitative trait locus on chromosome 18q for physical activity and dietary intake in Hispanic children. Obesity (Silver Spring) 2006; 14:1596-604. [PMID: 17030971 DOI: 10.1038/oby.2006.184] [Citation(s) in RCA: 92] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Genetic components of energy homeostasis contributing to childhood obesity are poorly understood. Genome scans were performed to identify chromosomal regions contributing to physical activity and dietary intake traits in Hispanic children participating in the VIVA LA FAMILIA Study. RESEARCH METHODS AND PROCEDURES We report linkage findings on chromosome 18 for physical activity and dietary intake in 1030 siblings from 319 Hispanic families. Measurements entailed physical activity by accelerometry, dietary intake by two 24-hour recalls, and genetic linkage analyses using SOLAR software. RESULTS Significant heritabilities were seen for physical activity and dietary intake, ranging from 0.46 to 0.69, except for vigorous activity (h2 = 0.18). Percentage time in sedentary activity mapped to markers D18S1102-D18S64 on chromosome 18 [logarithm of the odds (LOD) score = 4.07], where melanocortin 4 receptor gene (MC4R) resides. Quantitative trait loci (QTLs) for total activity counts, percentage time in light or in moderate activity, and carbohydrate intake and percentage of energy intake from carbohydrates were detected in the same region (LOD = 2.28, 2.79, 2.2, 1.84, and 1.51, respectively). A novel loss of function mutation in MC4R (G55V) was detected in six obese relatives, but not in the rest of the cohort. Removal of these MC4R-deficient subjects from the analysis reduced the LOD score for sedentary activity to 3.94. DISCUSSION Given its role in the regulation of food intake and energy expenditure, MC4R is a strong positional candidate gene for the QTL on chromosome 18 detected for physical activity and dietary intake in Hispanic children.
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Affiliation(s)
- Guowen Cai
- U.S. Department of Agriculture/Agricultural Research Service, Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas 77030, USA.
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Tejero ME, Cai G, Göring HHH, Diego V, Cole SA, Bacino CA, Butte NF, Comuzzie AG. Linkage analysis of circulating levels of adiponectin in Hispanic children. Int J Obes (Lond) 2006; 31:535-42. [PMID: 16894363 DOI: 10.1038/sj.ijo.0803436] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Adiponectin, a hormone produced exclusively by adipose tissue, is inversely associated with insulin resistance and proinflammatory conditions. The aim of this study was to find quantitative trait loci (QTLs) that affect circulating levels of adiponectin in Hispanic children participating in the VIVA LA FAMILIA Study by use of a systematic genome scan. METHODS The present study included extended families with at least one overweight child between 4 and 19 years old. Overweight was defined as body mass index (BMI) 95th percentile. Fasting blood was collected from 466 children from 127 families. Adiponectin was assayed by radioimmunoassay (RIA) technique in fasting serum. A genome-wide scan on circulating levels of adiponectin as a quantitative phenotype was conducted using the variance decomposition approach. RESULTS The highest logarithm of odds (LOD) score (4.2) was found on chromosome 11q23.2-11q24.2, and a second significant signal (LOD score=3.0) was found on chromosome 8q12.1-8q21.3. In addition, a signal suggestive of linkage (LOD score=2.5) was found between 18q21.3 and 18q22.3. After adjustment for BMI-Z score, the LOD score on chromosome 11 remained unchanged, but the signals on chromosomes 8 and 18 dropped to 1.6 and 1.7, respectively. Two other signals suggestive of linkage were found on chromosome 3 (LOD score=2.1) and 10 (LOD score=2.5). Although the region on chromosome 11 has been associated with obesity and diabetes-related traits in adult populations, this is the first observation of linkage in this region for adiponectin levels. Our suggestive linkages on chromosomes 10 and 3 replicate results for adiponectin seen in other populations. The influence of loci on chromosomes 18 and 8 on circulating adiponectin seemed to be mediated by BMI in the present study. CONCLUSION Our genome scan in children has identified a novel QTL and replicated QTLs in chromosomal regions previously shown to be linked with obesity and type 2 diabetes (T2D)-related phenotypes in adults. The genetic contribution of loci to adiponectin levels may vary across different populations and age groups. The strong linkage signal on chromosome 11 is most likely underlain by a gene(s) that may contribute to the high susceptibility of these Hispanic children to obesity and T2D.
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Affiliation(s)
- M E Tejero
- Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX 78245-0549, USA
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Groves CJ, Zeggini E, Walker M, Hitman GA, Levy JC, O'Rahilly S, Hattersley AT, McCarthy MI, Wiltshire S. Significant linkage of BMI to chromosome 10p in the U.K. population and evaluation of GAD2 as a positional candidate. Diabetes 2006; 55:1884-9. [PMID: 16731858 DOI: 10.2337/db05-1674] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Obesity is a major health problem, and many family-based studies have suggested that it has a strong genetic basis. We performed a genome-wide quantitative trait linkage scan for loci influencing BMI in 573 pedigrees from the U.K. We identified genome-wide significant linkage (logarithm of odds = 3.74, between D10S208 and D10S196, genome-wide P=0.0186) on chromosome 10p. The size of our study population and the statistical significance of our findings provide substantial contributions to the body of evidence for a locus on chromosome 10p. We examined eight single nucleotide polymorphisms (SNPs) in GAD2, which maps to this linkage region, tagging the majority of variation in the gene, and observed marginally significant (0.01<P<0.05) associations between four common variants and BMI. However, these SNPs did not account for our evidence of linkage to BMI, and they did not replicate (in direction of effect) the previous associations. We therefore conclude that these SNPs are not the etiological variants underlying this locus. We cannot rule out the possibility that other untagged variations in GAD2 may, in part, be involved, but it is most likely that alternative gene(s) within the broad gene-rich region of linkage on 10p are responsible for variation in body mass and susceptibility to obesity.
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Affiliation(s)
- Christopher J Groves
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
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Wilson SG, Adam G, Langdown M, Reneland R, Braun A, Andrew T, Surdulescu GL, Norberg M, Dudbridge F, Reed PW, Sambrook PN, Kleyn PW, Spector TD. Linkage and potential association of obesity-related phenotypes with two genes on chromosome 12q24 in a female dizygous twin cohort. Eur J Hum Genet 2006; 14:340-8. [PMID: 16391564 DOI: 10.1038/sj.ejhg.5201551] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Obesity is a multifactorial disorder with a complex phenotype. It is a significant risk factor for diabetes and hypertension. We assessed obesity-related traits in a large cohort of twins and performed a genome-wide linkage scan and positional candidate analysis to identify genes that play a role in regulating fat mass and distribution in women. Dizygous female twin pairs from 1,094 pedigrees were studied (mean age 47.0+/-11.5 years (range 18-79 years)). Nonparametric multipoint linkage analyses showed linkage for central fat mass to 12q24 (141 cM) with LOD 2.2 and body mass index to 8q11 (67 cM) with LOD 1.3, supporting previously established linkage data. Novel areas of suggestive linkage were for total fat percentage at 6q12 (LOD 2.4) and for total lean mass at 2q37 (LOD 2.4). Data from follow-up fine mapping in an expanded cohort of 1243 twin pairs reinforced the linkage for central fat mass to 12q24 (LOD 2.6; 143 cM) and narrowed the -1 LOD support interval to 22 cM. In all, 45 single-nucleotide polymorphisms (SNPs) from 26 positional candidate genes within the 12q24 interval were then tested for association in a cohort of 1102 twins. Single-point Monks-Kaplan analysis provided evidence of association between central fat mass and SNPs in two genes - PLA2G1B (P = 0.0067) and P2RX4 (P = 0.017). These data provide replication and refinement of the 12q24 obesity locus and suggest that genes involved in phospholipase and purinoreceptor pathways may regulate fat accumulation and distribution.
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Affiliation(s)
- Scott G Wilson
- Department of Endocrinology & Diabetes, Sir Charles Gairdner Hospital, Nedlands, Australia
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