201
|
Al-Mamun HA, Kwan P, Clark SA, Ferdosi MH, Tellam R, Gondro C. Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight. Genet Sel Evol 2015; 47:66. [PMID: 26272623 PMCID: PMC4536601 DOI: 10.1186/s12711-015-0142-4] [Citation(s) in RCA: 96] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2014] [Accepted: 07/23/2015] [Indexed: 12/27/2022] Open
Abstract
Background Body weight (BW) is an important trait for meat production in sheep. Although over the past few years, numerous quantitative trait loci (QTL) have been detected for production traits in cattle, few QTL studies have been reported for sheep, with even fewer on meat production traits. Our objective was to perform a genome-wide association study (GWAS) with the medium-density Illumina Ovine SNP50 BeadChip to identify genomic regions and corresponding haplotypes associated with BW in Australian Merino sheep. Methods A total of 1781 Australian Merino sheep were genotyped using the medium-density Illumina Ovine SNP50 BeadChip. Among the 53 862 single nucleotide polymorphisms (SNPs) on this array, 48 640 were used to perform a GWAS using a linear mixed model approach. Genotypes were phased with hsphase; to estimate SNP haplotype effects, linkage disequilibrium blocks were identified in the detected QTL region. Results Thirty-nine SNPs were associated with BW at a Bonferroni-corrected genome-wide significance threshold of 1 %. One region on sheep (Ovis aries) chromosome 6 (OAR6) between 36.15 and 38.56 Mb, included 13 significant SNPs that were associated with BW; the most significant SNP was OAR6_41936490.1 (P = 2.37 × 10−16) at 37.69 Mb with an allele substitution effect of 2.12 kg, which corresponds to 0.248 phenotypic standard deviations for BW. The region that surrounds this association signal on OAR6 contains three genes: leucine aminopeptidase 3 (LAP3), which is involved in the processing of the oxytocin precursor; NCAPG non-SMC condensin I complex, subunit G (NCAPG), which is associated with foetal growth and carcass size in cattle; and ligand dependent nuclear receptor corepressor-like (LCORL), which is associated with height in humans and cattle. Conclusions The GWAS analysis detected 39 SNPs associated with BW in sheep and a major QTL region was identified on OAR6. In several other mammalian species, regions that are syntenic with this region have been found to be associated with body size traits, which may reflect that the underlying biological mechanisms share a common ancestry. These findings should facilitate the discovery of causative variants for BW and contribute to marker-assisted selection. Electronic supplementary material The online version of this article (doi:10.1186/s12711-015-0142-4) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Hawlader A Al-Mamun
- School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia. .,School of Science and Technology, University of New England, Armidale, NSW, 2351, Australia.
| | - Paul Kwan
- School of Science and Technology, University of New England, Armidale, NSW, 2351, Australia.
| | - Samuel A Clark
- School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia.
| | - Mohammad H Ferdosi
- School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia.
| | - Ross Tellam
- CSIRO Animal, Food and Health Sciences, Queensland Bioscience Precinct, St. Lucia, QLD, 4067, Australia.
| | - Cedric Gondro
- School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia.
| |
Collapse
|
202
|
Abstract
A recent progress on stature genetics has revealed simple genetic architecture in livestock animals in contrast to that in humans. PLAG1 and/or NCAPG‐LCORL, both of which are known as a locus for adult human height, have been detected for association with body weight/height in cattle and horses, and for selective sweep in dogs and pigs. The findings indicate a significant impact of these loci on mammalian growth or body size and usefulness of the natural variants for selective breeding. However, association with an unfavorable trait, such as late puberty or risk for a neuropathic disease, was also reported for the respective loci, indicating an importance to discriminate between causality and association. Here I review the recent findings on quantitative trait loci (QTL) for stature in livestock animals, mainly focusing on the PLAG1 and NCAPG‐LCORL loci. I also describe our recent efforts to identify the causative variation for the third major locus for carcass weight in Japanese Black cattle.
Collapse
|
203
|
Punwasi RV, Monnereau C, Hofman A, Jaddoe VW, Felix JF. The Influence of Known Genetic Variants on Subclinical Cardiovascular Outcomes in Childhood. ACTA ACUST UNITED AC 2015; 8:596-602. [DOI: 10.1161/circgenetics.114.000915] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Accepted: 04/15/2015] [Indexed: 11/16/2022]
Abstract
Background—
Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) for subclinical cardiovascular outcomes in adults. We examined the influence of these variants on the same outcomes in childhood.
Methods and Results—
In a population-based prospective cohort study among 4137 children, we examined the associations of SNPs, individually and incorporated in genetic risk scores, which were identified in adults for cardiac (2 SNPs for left ventricular end-diastolic diameter and 5 SNPs for aortic root diameter) and blood pressure outcomes (29 SNPs for systolic and diastolic blood pressure, 22 SNPs for mean arterial pressure, and 10 SNPs for pulse pressure) with the same outcomes in children (median age of 6.0 years [95% range, 4.5–8.7]). Weighted and unweighted risk scores for aortic root diameter were associated with childhood aortic root diameter (difference per additional average risk allele 0.09 mm [95% CI: 0.05, 0.13]). Weighted and unweighted risk scores for pulse pressure were associated with childhood pulse pressure (difference per additional average risk allele 0.22 mm Hg [95% CI: 0.08, 0.35] and 0.18 mm Hg [95% CI: 0.05, 0.31], respectively), but not with childhood systolic or diastolic blood pressure or mean arterial pressure. The risk scores for blood pressure and mean arterial pressure were not associated with any of the childhood blood pressure outcomes.
Conclusions—
Genetic risk scores based on SNPs for aortic root diameter and pulse pressure in adults are associated with the same outcomes in children. SNPs related to cardiovascular outcomes in adulthood at least partly influence cardiovascular development from early life onwards.
Collapse
Affiliation(s)
- Rani V.G. Punwasi
- From the The Generation R Study Group (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), Department of Epidemiology (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), and Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands (R.V.G.P., C.M., V.W.V.J., J.F.F.)
| | - Claire Monnereau
- From the The Generation R Study Group (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), Department of Epidemiology (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), and Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands (R.V.G.P., C.M., V.W.V.J., J.F.F.)
| | - Albert Hofman
- From the The Generation R Study Group (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), Department of Epidemiology (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), and Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands (R.V.G.P., C.M., V.W.V.J., J.F.F.)
| | - Vincent W.V. Jaddoe
- From the The Generation R Study Group (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), Department of Epidemiology (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), and Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands (R.V.G.P., C.M., V.W.V.J., J.F.F.)
| | - Janine F. Felix
- From the The Generation R Study Group (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), Department of Epidemiology (R.V.G.P., C.M., A.H., V.W.V.J., J.F.F.), and Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands (R.V.G.P., C.M., V.W.V.J., J.F.F.)
| |
Collapse
|
204
|
Li Y, Ley SH, VanderWeele TJ, Curhan GC, Rich-Edwards JW, Willett WC, Forman JP, Hu FB, Qi L. Joint association between birth weight at term and later life adherence to a healthy lifestyle with risk of hypertension: a prospective cohort study. BMC Med 2015; 13:175. [PMID: 26228391 PMCID: PMC4521367 DOI: 10.1186/s12916-015-0409-1] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Accepted: 06/25/2015] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Low birth weight and unhealthy lifestyles in adulthood have been independently associated with an elevated risk of hypertension. However, no study has examined the joint effects of these factors on incidence of hypertension. METHODS We followed 52,114 women from the Nurses' Health Study II without hypercholesterolemia, diabetes, cardiovascular disease, cancer, prehypertension, and hypertension at baseline (1991-2011). Women born preterm, of a multiple pregnancy, or who were missing birth weight data were excluded. Unhealthy adulthood lifestyle was defined by compiling status scores of body mass index, physical activity, alcohol consumption, the Dietary Approaches to Stop Hypertension diet, and the use of non-narcotic analgesics. RESULTS We documented 12,588 incident cases of hypertension during 20 years of follow-up. The risk of hypertension associated with a combination of low birth weight at term and unhealthy lifestyle factors (RR, 1.95; 95 % CI, 1.83-2.07) was more than the addition of the risk associated with each individual factor, indicating a significant interaction on an additive scale (P interaction <0.001). The proportions of the association attributable to lower term birth weight alone, unhealthy lifestyle alone, and their joint effect were 23.9 % (95 % CI, 16.6-31.2), 63.7 % (95 % CI, 60.4-66.9), and 12.5 % (95 % CI, 9.87-15.0), respectively. The population-attributable-risk for the combined adulthood unhealthy lifestyle and low birth weight at term was 66.3 % (95 % CI, 56.9-74.0). CONCLUSION The majority of cases of hypertension could be prevented by the adoption of a healthier lifestyle, though some cases may depend on simultaneous improvement of both prenatal and postnatal factors.
Collapse
Affiliation(s)
- Yanping Li
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA.
| | - Sylvia H Ley
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA.
| | - Tyler J VanderWeele
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. .,Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.
| | - Gary C Curhan
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. .,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 665 Huntington Ave, Boston, MA, 02115, USA. .,Renal Division, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| | - Janet W Rich-Edwards
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. .,The Connors Center for Women's Health and Gender Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Walter C Willett
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA. .,Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. .,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 665 Huntington Ave, Boston, MA, 02115, USA.
| | - John P Forman
- Renal Division, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| | - Frank B Hu
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA. .,Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. .,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 665 Huntington Ave, Boston, MA, 02115, USA.
| | - Lu Qi
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA. .,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 665 Huntington Ave, Boston, MA, 02115, USA.
| |
Collapse
|
205
|
Roderick PJ, Jeffrey RF, Yuen HM, Godfrey KM, West J, Wright J. Smaller kidney size at birth in South Asians: findings from the Born in Bradford birth cohort study. Nephrol Dial Transplant 2015. [PMID: 26209714 DOI: 10.1093/ndt/gfv274] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Rates of advanced chronic kidney disease and renal replacement therapy are higher in South Asian than in white British populations. Low birth weight is also more frequent in South Asian populations and has been associated with increased risks of kidney disease, perhaps due to a reduced nephron endowment. METHODS Using ultrasound scans at 34 weeks of gestation, we measured fetal kidney dimensions (transverse and anteroposterior diameters, length and circumference) and derived volume in a random sample of 872 white British and 715 South Asian participants in the Born in Bradford cohort study. Kidney measurements were compared between ethnic groups. RESULTS Birth weight for gestational age at 40 weeks was 200 g less in South Asian babies compared with white British babies. The mean kidney volume for gestational age was 16% lower in South Asian than in white British babies [8.79 versus 10.45 cm(3), difference 1.66 cm(3) (95% confidence interval 1.40-1.93, P < 0.001)]. The difference was robust after adjustment for maternal age, socio-economic factors, marital status, body mass index, smoking and alcohol use in pregnancy, parity, baby's gender and birth weight for gestational age [adjusted difference 1.38 cm(3) (0.97-1.84), P < 0.001]. There were smaller reductions in other fetal measures. CONCLUSION South Asian babies have smaller kidneys compared with white British babies, even after adjusting for potential confounders including birth weight. This finding may contribute to increased risks of adult kidney disease in South Asian populations.
Collapse
Affiliation(s)
- Paul J Roderick
- Primary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Robin F Jeffrey
- Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Ho M Yuen
- Primary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Keith M Godfrey
- MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Jane West
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| |
Collapse
|
206
|
Li Y, Ley SH, Tobias DK, Chiuve SE, VanderWeele TJ, Rich-Edwards JW, Curhan GC, Willett WC, Manson JE, Hu FB, Qi L. Birth weight and later life adherence to unhealthy lifestyles in predicting type 2 diabetes: prospective cohort study. BMJ 2015; 351:h3672. [PMID: 26199273 PMCID: PMC4510778 DOI: 10.1136/bmj.h3672] [Citation(s) in RCA: 94] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
OBJECTIVES To prospectively assess the joint association of birth weight and established lifestyle risk factors in adulthood with incident type 2 diabetes and to quantitatively decompose the attributing effects to birth weight only, to adulthood lifestyle only, and to their interaction. DESIGN Prospective cohort study. SETTING Health Professionals Follow-up Study (1986-2010), Nurses' Health Study (1980-2010), and Nurses' Health Study II (1991-2011). PARTICIPANTS 149,794 men and women without diabetes, cardiovascular disease, or cancer at baseline. MAIN OUTCOME MEASURE Incident cases of type 2 diabetes, identified through self report and validated by a supplementary questionnaire. Unhealthy lifestyle was defined on the basis of body mass index, smoking, physical activity, alcohol consumption, and the alternate healthy eating index. RESULTS During 20-30 years of follow-up, 11,709 new cases of type 2 diabetes were documented. The multivariate adjusted relative risk of type 2 diabetes was 1.45 (95% confidence interval 1.32 to 1.59) per kg lower birth weight and 2.10 (1.71 to 2.58) per unhealthy lifestyle factor. The relative risk of type 2 diabetes associated with a combination of per kg lower birth weight and per unhealthy lifestyle factor was 2.86 (2.26 to 3.63), which was more than the addition of the risk associated with each individual factor, indicating a significant interaction on an additive scale (P for interaction < 0.001). The attributable proportions of joint effect were 22% (95% confidence interval 18.3% to 26.4%) to lower birth weight alone, 59% (57.1% to 61.5%) to unhealthy lifestyle alone, and 18% (13.9% to 21.3%) to their interaction. CONCLUSION Most cases of type 2 diabetes could be prevented by the adoption of a healthier lifestyle, but simultaneous improvement of both prenatal and postnatal factors could further prevent additional cases.
Collapse
Affiliation(s)
- Yanping Li
- Department of Nutrition, Harvard T H Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115, USA
| | - Sylvia H Ley
- Department of Nutrition, Harvard T H Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115, USA
| | - Deirdre K Tobias
- Department of Nutrition, Harvard T H Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115, USA
| | - Stephanie E Chiuve
- Department of Nutrition, Harvard T H Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115, USA Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston
| | - Tyler J VanderWeele
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston Department of Biostatistics, Harvard T H Chan School of Public Health, Boston
| | - Janet W Rich-Edwards
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston Connors Center for Women's Health and Gender Biology, Brigham and Women's Hospital, Harvard Medical School, Boston
| | - Gary C Curhan
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston Renal Division, Department of Medicine, Brigham and Women's Hospital, Boston
| | - Walter C Willett
- Department of Nutrition, Harvard T H Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115, USA Department of Epidemiology, Harvard T H Chan School of Public Health, Boston Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston
| | - JoAnn E Manson
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston Department of Epidemiology, Harvard T H Chan School of Public Health, Boston
| | - Frank B Hu
- Department of Nutrition, Harvard T H Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115, USA Department of Epidemiology, Harvard T H Chan School of Public Health, Boston Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston
| | - Lu Qi
- Department of Nutrition, Harvard T H Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115, USA Department of Epidemiology, Harvard T H Chan School of Public Health, Boston Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston
| |
Collapse
|
207
|
Frost L, Baez MAM, Harrilal C, Garabedian A, Fernandez-Lima F, Leng F. The Dimerization State of the Mammalian High Mobility Group Protein AT-Hook 2 (HMGA2). PLoS One 2015; 10:e0130478. [PMID: 26114780 PMCID: PMC4482583 DOI: 10.1371/journal.pone.0130478] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Accepted: 05/20/2015] [Indexed: 01/06/2023] Open
Abstract
The mammalian high mobility group protein AT-hook 2 (HMGA2) is a chromosomal architectural transcription factor involved in cell transformation and oncogenesis. It consists of three positively charged “AT-hooks” and a negatively charged C-terminus. Sequence analyses, circular dichroism experiments, and gel-filtration studies showed that HMGA2, in the native state, does not have a defined secondary or tertiary structure. Surprisingly, using combined approaches of 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) chemical cross-linking, analytical ultracentrifugation, fluorescence resonance energy transfer (FRET), and mass spectrometry, we discovered that HMGA2 is capable of self-associating into homodimers in aqueous buffer solution. Our results showed that electrostatic interactions between the positively charged “AT-hooks” and the negatively charged C-terminus greatly contribute to the homodimer formation.
Collapse
Affiliation(s)
- Lorraine Frost
- Biomolecular Sciences Institute, Florida International University, Miami, Florida, United States of America
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, United States of America
| | - Maria A. M. Baez
- Biomolecular Sciences Institute, Florida International University, Miami, Florida, United States of America
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, United States of America
| | - Christopher Harrilal
- Biomolecular Sciences Institute, Florida International University, Miami, Florida, United States of America
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, United States of America
| | - Alyssa Garabedian
- Biomolecular Sciences Institute, Florida International University, Miami, Florida, United States of America
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, United States of America
| | - Francisco Fernandez-Lima
- Biomolecular Sciences Institute, Florida International University, Miami, Florida, United States of America
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, United States of America
| | - Fenfei Leng
- Biomolecular Sciences Institute, Florida International University, Miami, Florida, United States of America
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, United States of America
- * E-mail:
| |
Collapse
|
208
|
Greco M FD, Minelli C, Sheehan NA, Thompson JR. Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med 2015; 34:2926-40. [DOI: 10.1002/sim.6522] [Citation(s) in RCA: 297] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2014] [Revised: 04/10/2015] [Accepted: 04/15/2015] [Indexed: 12/19/2022]
Affiliation(s)
| | - Cosetta Minelli
- Respiratory Epidemiology, Occupational Medicine and Public Health, NHLI; Imperial College; London U.K
| | - Nuala A Sheehan
- Department of Health Sciences; University of Leicester; Leicester U.K
| | - John R Thompson
- Department of Health Sciences; University of Leicester; Leicester U.K
| |
Collapse
|
209
|
Gjesing AP, Ribel-Madsen R, Harder MN, Eiberg H, Grarup N, Jørgensen T, Ekstrøm CT, Pedersen O, Hansen T. Genetic and phenotypic correlations between surrogate measures of insulin release obtained from OGTT data. Diabetologia 2015; 58:1006-12. [PMID: 25660259 DOI: 10.1007/s00125-015-3516-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2014] [Accepted: 01/12/2015] [Indexed: 10/24/2022]
Abstract
AIMS/HYPOTHESIS We examined the extent to which surrogate measures of insulin release have shared genetic causes. METHODS Genetic and phenotypic correlations were calculated in a family cohort (n = 315) in which beta cell indices were estimated based on fasting and oral glucose-stimulated plasma glucose, serum C-peptide and serum insulin levels. Furthermore, we genotyped a large population-based cohort (n = 6,269) for common genetic variants known to associate with type 2 diabetes, fasting plasma glucose levels or fasting serum insulin levels to examine their association with various indices. RESULTS We found a notable difference between the phenotypic and genetic correlations for the traits, emphasising that the phenotypic correlation is an insufficient measure of the magnitude of shared genetic impact. In addition, we found that corrected insulin response, insulinogenic index and incAUC for insulin after an oral glucose challenge shared the majority of their genetic backgrounds, with genetic correlations of 0.80-0.99. The BIGTT index for acute insulin response differed slightly more from the latter with genetic correlations of 0.78-0.87. The HOMA for beta cell function was genetically closely related to fasting insulin with a genetic correlation of 0.85. The effects of 82 selected susceptibility single nucleotide polymorphisms on these insulin secretion indices supported our interpretation of the data and added insight into the biological differences between the examined traits. CONCLUSIONS/INTERPRETATION The level of shared genetic background varies between surrogate measures of insulin release, and this should be considered when designing a genetic association study to best obtain information on various mechanisms of insulin release.
Collapse
Affiliation(s)
- Anette P Gjesing
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1-3, DK-2100, Copenhagen, Denmark,
| | | | | | | | | | | | | | | | | |
Collapse
|
210
|
Große-Brinkhaus C, Storck LC, Frieden L, Neuhoff C, Schellander K, Looft C, Tholen E. Genome-wide association analyses for boar taint components and testicular traits revealed regions having pleiotropic effects. BMC Genet 2015; 16:36. [PMID: 25879925 PMCID: PMC4429935 DOI: 10.1186/s12863-015-0194-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2014] [Accepted: 03/30/2015] [Indexed: 11/25/2022] Open
Abstract
Background The aim of this study was to perform a genome-wide association analyses (GWAS) for androstenone, skatole and indole in different Pietrain sire lines and compare the results with previous findings in purebred populations. Furthermore, the genetic relationship of androstenone and skatole were investigated with respect to pleiotropy. In order to characterize the performance of intact boars, crossbred progenies of 136 Pietrain boars mated to crossbred sows from three different breeding companies were tested on four test stations. A total of 598 boars were performance tested according to the rules of stationary performance testing in Germany. Beside common fattening and carcass composition traits, the concentrations of the boar taint components and testicular size parameters were recorded. All boars were genotyped with the PorcineSNP60 Illumina BeadChip. The GWAS were performed using the whole data set as well as in sub groups according to the line of origin. Besides an univariate GWAS approach, principal component (PC) techniques were applied to identify common expression pattern affecting the biosynthesis and the metabolism of androstenone. Results In total, 33 SNPs were significantly associated with at least one of the boar taint components. Only one SNP was identified being significant in both subgroups. The analyses of the testes size parameters revealed 31 significant associations. The numbers of significant SNPs within the genetic groups evidenced the strong population specific effects. A multivariate approach using PC revealed 33 significant associations for five different PC. Conclusions Based on Pietrain sired cross bred boars, the mayor objective of our study was to identify QTL for boar taint components and to detect pleiotropy among boar taint and testes traits. The high number of identified QTL revealed that boar taint traits are influenced by a large number of loci. Analyzing pleiotropy allowed identifying a QTL affecting androstenone and the gonasomatic index. In this region, QTL for ovulation rate and age at puberty of sows have been described in literature. This supports the physiological findings that the androstenone level of boars and reproduction performance of sows might be linked by an antagonistic relationship. Electronic supplementary material The online version of this article (doi:10.1186/s12863-015-0194-z) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
| | - Leonie C Storck
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany.
| | - Luc Frieden
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany.
| | - Christiane Neuhoff
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany.
| | - Karl Schellander
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany.
| | - Christian Looft
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany.
| | - Ernst Tholen
- Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115, Bonn, Germany.
| |
Collapse
|
211
|
Mendy M, Caboux E, Sylla BS, Dillner J, Chinquee J, Wild C. Infrastructure and facilities for human biobanking in low- and middle-income countries: a situation analysis. Pathobiology 2015; 81:252-260. [PMID: 25792214 DOI: 10.1159/000362093] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE To collect information on biobanking facilities in low- and middle-income countries (LMICs) as a first step towards establishing an LMIC biobank and cohort building network (BCNet) to support research, with a focus on cancer control. METHOD Sixty centres were identified from sources including cancer centres, universities, hospitals, and public health facilities and invited to participate in a survey between December 2012 and March 2013. RESULTS Of the 27 centres (45%) that responded, most have existed for <10 years. They store between 1,000 and 1,000,000 research samples as well as samples remaining after clinical diagnosis. Sample storage is mostly in freezers, although 45% (9/20) of the centres do not have regular access to electricity. Biobank managers, sample management systems, and mechanisms for follow-up using linkages are uncommon. Many (80%; 21/26) of the centres have regulations to govern research, but regulations for the use of biobank resources (samples and data) are not well developed. CONCLUSIONS Biobanking facilities are being developed in LMICs. Shortcomings in international visibility, sample sharing regulations, standardization, quality assurance, and sample management systems could be alleviated by international networking. Stakeholders need to work together to increase access to high-quality biological resources for scientific research.
Collapse
Affiliation(s)
- Maimuna Mendy
- International Agency for Research on Cancer, Lyon, France
| | | | | | | | | | | | | |
Collapse
|
212
|
van Dongen J, Willemsen G, Heijmans BT, Neuteboom J, Kluft C, Jansen R, Penninx BWJ, Slagboom PE, de Geus EJC, Boomsma DI. Longitudinal weight differences, gene expression and blood biomarkers in BMI-discordant identical twins. Int J Obes (Lond) 2015; 39:899-909. [PMID: 25765203 PMCID: PMC4471109 DOI: 10.1038/ijo.2015.24] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2014] [Revised: 11/28/2014] [Accepted: 12/18/2014] [Indexed: 12/31/2022]
Abstract
Background BMI discordant monozygotic (MZ) twins allows an examination of the causes and consequences of adiposity in a genetically controlled design. Few studies have examined longitudinal BMI discordance in MZ pairs. Objectives To study the development over time of BMI discordance in adolescent and adult MZ twin pairs, and to examine lifestyle, metabolic, inflammatory, and gene expression differences associated with concurrent and long-term BMI discordance in MZ pairs. Subjects/Methods BMI data from 2775 MZ twin pairs, collected in eight longitudinal surveys and a biobank project between 1991 and 2011, were analyzed to characterize longitudinal discordance. Lifestyle characteristics were compared within discordant pairs (ΔBMI ≥ 3 kg/m2) and biomarkers (lipids, glucose, insulin, CRP, fibrinogen, IL-6, TNF-α and sIL-6R and liver enzymes AST, ALT and GGT) and gene expression were compared in peripheral blood from discordant pairs who participated in the NTR biobank project. Results The prevalence of discordance ranged from 3.2% in 1991 (mean age=17, SD=2.4) to 17.4% (N=202 pairs) in 2009 (mean age=35, SD=15), and was 16.5% (N=174) among pairs participating in the biobank project (mean age=35, SD=12). Of 699 MZ with BMI data from 3-5 time points, 17 pairs (2.4%) were long-term discordant (at all available time points; mean follow-up range=6.4 years). Concurrently discordant pairs showed significant differences in self-ratings of which twin eats most (p=2.3×10−13), but not in leisure time exercise activity (p=0.28) and smoking (p>0.05). Ten out of 14 biomarkers showed significantly more unfavorable levels in the heavier of twin of the discordant pairs (p-values < 0.001); most of these biomarker differences were largest in longitudinally discordant pairs. No significant gene expression differences were identified, although high ranking genes were enriched for Gene Ontology (GO) terms highlighting metabolic gene regulation and inflammation pathways. Conclusions BMI discordance is uncommon in adolescent identical pairs but increases with higher pair-mean of BMI at older ages, although long-term BMI discordance is rare. In discordant pairs, the heavier twin had a more unfavorable blood biomarker profile than the genetically matched leaner twin, in support of causal effects of obesity.
Collapse
Affiliation(s)
- J van Dongen
- 1] Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands [2] EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - G Willemsen
- 1] Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands [2] EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - B T Heijmans
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - J Neuteboom
- Good Biomarker Sciences, Leiden, The Netherlands
| | - C Kluft
- Good Biomarker Sciences, Leiden, The Netherlands
| | - R Jansen
- Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
| | - B W J Penninx
- 1] EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands [2] Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
| | - P E Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - E J C de Geus
- 1] Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands [2] EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - D I Boomsma
- 1] Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands [2] EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| |
Collapse
|
213
|
Sequence and analysis of a whole genome from Kuwaiti population subgroup of Persian ancestry. BMC Genomics 2015; 16:92. [PMID: 25765185 PMCID: PMC4336699 DOI: 10.1186/s12864-015-1233-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2014] [Accepted: 01/12/2015] [Indexed: 12/30/2022] Open
Abstract
Background The 1000 Genome project paved the way for sequencing diverse human populations. New genome projects are being established to sequence underrepresented populations helping in understanding human genetic diversity. The Kuwait Genome Project an initiative to sequence individual genomes from the three subgroups of Kuwaiti population namely, Saudi Arabian tribe; “tent-dwelling” Bedouin; and Persian, attributing their ancestry to different regions in Arabian Peninsula and to modern-day Iran (West Asia). These subgroups were in line with settlement history and are confirmed by genetic studies. In this work, we report whole genome sequence of a Kuwaiti native from Persian subgroup at >37X coverage. Results We document 3,573,824 SNPs, 404,090 insertions/deletions, and 11,138 structural variations. Out of the reported SNPs and indels, 85,939 are novel. We identify 295 ‘loss-of-function’ and 2,314 ’deleterious’ coding variants, some of which carry homozygous genotypes in the sequenced genome; the associated phenotypes include pharmacogenomic traits such as greater triglyceride lowering ability with fenofibrate treatment, and requirement of high warfarin dosage to elicit anticoagulation response. 6,328 non-coding SNPs associate with 811 phenotype traits: in congruence with medical history of the participant for Type 2 diabetes and β-Thalassemia, and of participant’s family for migraine, 72 (of 159 known) Type 2 diabetes, 3 (of 4) β-Thalassemia, and 76 (of 169) migraine variants are seen in the genome. Intergenome comparisons based on shared disease-causing variants, positions the sequenced genome between Asian and European genomes in congruence with geographical location of the region. On comparison, bead arrays perform better than sequencing platforms in correctly calling genotypes in low-coverage sequenced genome regions however in the event of novel SNP or indel near genotype calling position can lead to false calls using bead arrays. Conclusions We report, for the first time, reference genome resource for the population of Persian ancestry. The resource provides a starting point for designing large-scale genetic studies in Peninsula including Kuwait, and Persian population. Such efforts on populations under-represented in global genome variation surveys help augment current knowledge on human genome diversity. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1233-x) contains supplementary material, which is available to authorized users.
Collapse
|
214
|
van der Valk RJP, Kreiner-Møller E, Kooijman MN, Guxens M, Stergiakouli E, Sääf A, Bradfield JP, Geller F, Hayes MG, Cousminer DL, Körner A, Thiering E, Curtin JA, Myhre R, Huikari V, Joro R, Kerkhof M, Warrington NM, Pitkänen N, Ntalla I, Horikoshi M, Veijola R, Freathy RM, Teo YY, Barton SJ, Evans DM, Kemp JP, St Pourcain B, Ring SM, Davey Smith G, Bergström A, Kull I, Hakonarson H, Mentch FD, Bisgaard H, Chawes B, Stokholm J, Waage J, Eriksen P, Sevelsted A, Melbye M, van Duijn CM, Medina-Gomez C, Hofman A, de Jongste JC, Taal HR, Uitterlinden AG, Armstrong LL, Eriksson J, Palotie A, Bustamante M, Estivill X, Gonzalez JR, Llop S, Kiess W, Mahajan A, Flexeder C, Tiesler CMT, Murray CS, Simpson A, Magnus P, Sengpiel V, Hartikainen AL, Keinanen-Kiukaanniemi S, Lewin A, Da Silva Couto Alves A, Blakemore AI, Buxton JL, Kaakinen M, Rodriguez A, Sebert S, Vaarasmaki M, Lakka T, Lindi V, Gehring U, Postma DS, Ang W, Newnham JP, Lyytikäinen LP, Pahkala K, Raitakari OT, Panoutsopoulou K, Zeggini E, Boomsma DI, Groen-Blokhuis M, Ilonen J, Franke L, Hirschhorn JN, Pers TH, Liang L, Huang J, Hocher B, Knip M, Saw SM, Holloway JW, Melén E, Grant SFA, Feenstra B, Lowe WL, Widén E, et alvan der Valk RJP, Kreiner-Møller E, Kooijman MN, Guxens M, Stergiakouli E, Sääf A, Bradfield JP, Geller F, Hayes MG, Cousminer DL, Körner A, Thiering E, Curtin JA, Myhre R, Huikari V, Joro R, Kerkhof M, Warrington NM, Pitkänen N, Ntalla I, Horikoshi M, Veijola R, Freathy RM, Teo YY, Barton SJ, Evans DM, Kemp JP, St Pourcain B, Ring SM, Davey Smith G, Bergström A, Kull I, Hakonarson H, Mentch FD, Bisgaard H, Chawes B, Stokholm J, Waage J, Eriksen P, Sevelsted A, Melbye M, van Duijn CM, Medina-Gomez C, Hofman A, de Jongste JC, Taal HR, Uitterlinden AG, Armstrong LL, Eriksson J, Palotie A, Bustamante M, Estivill X, Gonzalez JR, Llop S, Kiess W, Mahajan A, Flexeder C, Tiesler CMT, Murray CS, Simpson A, Magnus P, Sengpiel V, Hartikainen AL, Keinanen-Kiukaanniemi S, Lewin A, Da Silva Couto Alves A, Blakemore AI, Buxton JL, Kaakinen M, Rodriguez A, Sebert S, Vaarasmaki M, Lakka T, Lindi V, Gehring U, Postma DS, Ang W, Newnham JP, Lyytikäinen LP, Pahkala K, Raitakari OT, Panoutsopoulou K, Zeggini E, Boomsma DI, Groen-Blokhuis M, Ilonen J, Franke L, Hirschhorn JN, Pers TH, Liang L, Huang J, Hocher B, Knip M, Saw SM, Holloway JW, Melén E, Grant SFA, Feenstra B, Lowe WL, Widén E, Sergeyev E, Grallert H, Custovic A, Jacobsson B, Jarvelin MR, Atalay M, Koppelman GH, Pennell CE, Niinikoski H, Dedoussis GV, Mccarthy MI, Frayling TM, Sunyer J, Timpson NJ, Rivadeneira F, Bønnelykke K, Jaddoe VWV. A novel common variant in DCST2 is associated with length in early life and height in adulthood. Hum Mol Genet 2015; 24:1155-68. [PMID: 25281659 PMCID: PMC4447786 DOI: 10.1093/hmg/ddu510] [Show More Authors] [Citation(s) in RCA: 85] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2014] [Accepted: 09/29/2014] [Indexed: 01/04/2023] Open
Abstract
Common genetic variants have been identified for adult height, but not much is known about the genetics of skeletal growth in early life. To identify common genetic variants that influence fetal skeletal growth, we meta-analyzed 22 genome-wide association studies (Stage 1; N = 28 459). We identified seven independent top single nucleotide polymorphisms (SNPs) (P < 1 × 10(-6)) for birth length, of which three were novel and four were in or near loci known to be associated with adult height (LCORL, PTCH1, GPR126 and HMGA2). The three novel SNPs were followed-up in nine replication studies (Stage 2; N = 11 995), with rs905938 in DC-STAMP domain containing 2 (DCST2) genome-wide significantly associated with birth length in a joint analysis (Stages 1 + 2; β = 0.046, SE = 0.008, P = 2.46 × 10(-8), explained variance = 0.05%). Rs905938 was also associated with infant length (N = 28 228; P = 5.54 × 10(-4)) and adult height (N = 127 513; P = 1.45 × 10(-5)). DCST2 is a DC-STAMP-like protein family member and DC-STAMP is an osteoclast cell-fusion regulator. Polygenic scores based on 180 SNPs previously associated with human adult stature explained 0.13% of variance in birth length. The same SNPs explained 2.95% of the variance of infant length. Of the 180 known adult height loci, 11 were genome-wide significantly associated with infant length (SF3B4, LCORL, SPAG17, C6orf173, PTCH1, GDF5, ZNFX1, HHIP, ACAN, HLA locus and HMGA2). This study highlights that common variation in DCST2 influences variation in early growth and adult height.
Collapse
Affiliation(s)
| | - Eskil Kreiner-Møller
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen & Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark
| | - Marjolein N Kooijman
- Department of Epidemiology, Department of Paediatrics, The Generation R Study Group
| | - Mònica Guxens
- Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain, CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
| | | | - Annika Sääf
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - M Geoffrey Hayes
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | | | - Antje Körner
- Center of Pediatric Research, University Hospital Center Leipzig, University of Leipzig, Leipzig, Germany
| | - Elisabeth Thiering
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany, Institute of Epidemiology I
| | - John A Curtin
- Centre for Respiratory Medicine and Allergy, Institute of Inflammation and Repair, University of Manchester and University Hospital of South Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Ronny Myhre
- Division Epidemiology, Department Genes and Environment
| | | | | | - Marjan Kerkhof
- Department of Epidemiology, Groningen Research Institute for Asthma and COPD
| | - Nicole M Warrington
- School of Women's and Infants' Health, The University of Western Australia, Perth, Australia, University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine
| | - Ioanna Ntalla
- Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK, Department of Nutrition and Dietetics, Harokopio University of Athens, Athens 11527, Greece
| | - Momoko Horikoshi
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK
| | | | - Rachel M Freathy
- University of Exeter Medical School, Royal Devon and Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, Life Science Institute, National University of Singapore, Singapore, Genome Institute of Singapore, Agency for Science, Technology and Research
| | | | - David M Evans
- MRC Integrative Epidemiology Unit , University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - John P Kemp
- MRC Integrative Epidemiology Unit , University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - Beate St Pourcain
- MRC Integrative Epidemiology Unit , Avon Longitudinal Study of Parents and Children (ALSPAC), School of Social and Community Medicine, School of Oral and Dental Sciences, University of Bristol, Bristol, UK
| | - Susan M Ring
- MRC Integrative Epidemiology Unit , Avon Longitudinal Study of Parents and Children (ALSPAC), School of Social and Community Medicine
| | | | - Anna Bergström
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Inger Kull
- Department of Clinical Science and Education, Södersjukhuset, Stockholm, Sweden, Sachs' Children's Hospital, Stockholm, Sweden
| | - Hakon Hakonarson
- Center for Applied Genomics, Abramson Research Center, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA, Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | | | - Hans Bisgaard
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen & Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark
| | - Bo Chawes
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen & Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark
| | - Jakob Stokholm
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen & Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark
| | - Johannes Waage
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen & Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark
| | - Patrick Eriksen
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen & Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark
| | - Astrid Sevelsted
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen & Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark
| | - Mads Melbye
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark, Department of Medicine, Stanford School of Medicine, Stanford, USA
| | | | - Carolina Medina-Gomez
- Department of Epidemiology, The Generation R Study Group, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, The Generation R Study Group
| | | | - H Rob Taal
- Department of Epidemiology, Department of Paediatrics
| | - André G Uitterlinden
- Department of Epidemiology, The Generation R Study Group, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Loren L Armstrong
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | | | - Aarno Palotie
- Institute for Molecular Medicine Finland, Analytic and Translational Genetics Unit, Department of Medicine, Program in Medical and Population Genetics, Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Mariona Bustamante
- Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain, CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain, Centre for Genomic Regulation (CRG), Barcelona, Spain
| | - Xavier Estivill
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain, Centre for Genomic Regulation (CRG), Barcelona, Spain, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Juan R Gonzalez
- Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain, CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
| | - Sabrina Llop
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, FISABIO-Public Health, Valencia, Spain
| | - Wieland Kiess
- Center of Pediatric Research, University Hospital Center Leipzig, University of Leipzig, Leipzig, Germany
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | | | - Carla M T Tiesler
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany, Institute of Epidemiology I
| | - Clare S Murray
- Centre for Respiratory Medicine and Allergy, Institute of Inflammation and Repair, University of Manchester and University Hospital of South Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Angela Simpson
- Centre for Respiratory Medicine and Allergy, Institute of Inflammation and Repair, University of Manchester and University Hospital of South Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Per Magnus
- Division Epidemiology, Norwegian Institute of Public Health, Oslo, Norway
| | - Verena Sengpiel
- Department Obstetrics and Gynecology, Sahlgrenska Academy, Sahlgrenska University Hospital, Gothenburg, Sweden
| | | | | | - Alexandra Lewin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, MRC Health Protection Agency (HPE) Centre for Environment and Health
| | - Alexessander Da Silva Couto Alves
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, MRC Health Protection Agency (HPE) Centre for Environment and Health
| | - Alexandra I Blakemore
- Section of Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Faculty of Medicine, Imperial College, London W12 0NN, UK
| | - Jessica L Buxton
- Section of Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Faculty of Medicine, Imperial College, London W12 0NN, UK
| | - Marika Kaakinen
- Institute of Health Sciences, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, MRC Health Protection Agency (HPE) Centre for Environment and Health, Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Alina Rodriguez
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, MRC Health Protection Agency (HPE) Centre for Environment and Health, Department of Psychology, Mid Sweden University, Östersund, Sweden
| | | | - Marja Vaarasmaki
- Department of Obstetrics and Gynecology and MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Timo Lakka
- Institute of Biomedicine, Physiology, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland, Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | | | - Ulrike Gehring
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Dirkje S Postma
- Groningen Research Institute for Asthma and COPD, Department of Pulmonology
| | - Wei Ang
- School of Women's and Infants' Health, The University of Western Australia, Perth, Australia
| | - John P Newnham
- School of Women's and Infants' Health, The University of Western Australia, Perth, Australia
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland, Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, Department of Clinical Physiology and Nuclear Medicine
| | - Kalliope Panoutsopoulou
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1HH, UK
| | - Eleftheria Zeggini
- Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1HH, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands, EMGO Institute for Health and Care Research, Amsterdam, The Netherlands, Neuroscience Campus Amsterdam, The Netherlands
| | - Maria Groen-Blokhuis
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands, EMGO Institute for Health and Care Research, Amsterdam, The Netherlands, Neuroscience Campus Amsterdam, The Netherlands
| | - Jorma Ilonen
- Immunogenetics Laboratory, University of Turku, Turku, Finland, Department of Clinical Microbiology, University of Eastern Finland, Kuopio, Finland
| | - Lude Franke
- Department of Genetics, University of Groningen, University Medical Centre Groningen, The Netherlands
| | - Joel N Hirschhorn
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, USA, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Genetics, Harvard Medical School, USA
| | - Tune H Pers
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, USA, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Denmark
| | - Liming Liang
- Department of Pediatrics, Tampere University Hospital, Tampere, Finland
| | - Jinyan Huang
- Department of Pediatrics, Tampere University Hospital, Tampere, Finland, Shanghai Institute of Hematology, Rui Jin Hospital Affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Berthold Hocher
- Institute of Nutritional Science, University of Potsdam, Germany, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China, Center for Cardiovascular Research/Institute of Pharmacology, Charité, Berlin, Germany
| | - Mikael Knip
- Diabetes and Obesity Research Program, University of Helsinki, Helsinki, Finland, Department of Pediatrics, Tampere University Hospital, Tampere, Finland, Children's Hospital, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Seang-Mei Saw
- Saw Swee Hock School of Public Health, Singapore Eye Research Institute, Singapore, Duke-NUS Graduate Medical School, Singapore
| | - John W Holloway
- Human Genetics and Genomic Medicine, Human Development & Health, Faculty of Medicine, University of Southampton, UK
| | - Erik Melén
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden, Sachs' Children's Hospital, Stockholm, Sweden
| | - Struan F A Grant
- Center for Applied Genomics, Abramson Research Center, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA, Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - William L Lowe
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | | | - Elena Sergeyev
- Center of Pediatric Research, University Hospital Center Leipzig, University of Leipzig, Leipzig, Germany
| | - Harald Grallert
- Institute of Epidemiology II, Research Unit for Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Adnan Custovic
- Centre for Respiratory Medicine and Allergy, Institute of Inflammation and Repair, University of Manchester and University Hospital of South Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Bo Jacobsson
- Division Epidemiology, Department Genes and Environment, Department Obstetrics and Gynecology, Sahlgrenska Academy, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Marjo-Riitta Jarvelin
- Institute of Health Sciences, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, MRC Health Protection Agency (HPE) Centre for Environment and Health, Biocenter Oulu, University of Oulu, Oulu, Finland, Unit of Primary Care, Oulu University Hospital, Kajaanintie 50, P.O.Box 20, FI-90220, Oulu 90029 OYS, Finland, Department of Children and Young People and Families, National Institute for Health and Welfare, Aapistie 1, Box 310, Oulu FI-90101, Finland and
| | | | - Gerard H Koppelman
- Groningen Research Institute for Asthma and COPD, Beatrix Children's Hospital, Pediatric Pulmonology and Pediatric Allergy, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Craig E Pennell
- School of Women's and Infants' Health, The University of Western Australia, Perth, Australia
| | - Harri Niinikoski
- Research Centre of Applied and Preventive Cardiovascular Medicine, Department of Pediatrics, Turku University Hospital, Turku, Finland
| | - George V Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens 11527, Greece
| | - Mark I Mccarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK, Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LJ, UK
| | - Timothy M Frayling
- University of Exeter Medical School, Royal Devon and Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK
| | - Jordi Sunyer
- Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain, CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | | | - Fernando Rivadeneira
- Department of Epidemiology, The Generation R Study Group, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Klaus Bønnelykke
- Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen & Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark
| | - Vincent W V Jaddoe
- Department of Epidemiology, Department of Paediatrics, The Generation R Study Group,
| |
Collapse
|
215
|
Alonso N, Guillen R, Chambers JW, Leng F. A rapid and sensitive high-throughput screening method to identify compounds targeting protein-nucleic acids interactions. Nucleic Acids Res 2015; 43:e52. [PMID: 25653160 PMCID: PMC4417145 DOI: 10.1093/nar/gkv069] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2015] [Accepted: 01/19/2015] [Indexed: 01/09/2023] Open
Abstract
DNA-binding and RNA-binding proteins are usually considered ‘undruggable’ partly due to the lack of an efficient method to identify inhibitors from existing small molecule repositories. Here we report a rapid and sensitive high-throughput screening approach to identify compounds targeting protein–nucleic acids interactions based on protein–DNA or protein–RNA interaction enzyme-linked immunosorbent assays (PDI-ELISA or PRI-ELISA). We validated the PDI-ELISA method using the mammalian high-mobility-group protein AT-hook 2 (HMGA2) as the protein of interest and netropsin as the inhibitor of HMGA2–DNA interactions. With this method we successfully identified several inhibitors and an activator for HMGA2–DNA interactions from a collection of 29 DNA-binding compounds. Guided by this screening excise, we showed that netropsin, the specific inhibitor of HMGA2–DNA interactions, strongly inhibited the differentiation of the mouse pre-adipocyte 3T3-L1 cells into adipocytes, most likely through a mechanism by which the inhibition is through preventing the binding of HMGA2 to the target DNA sequences. This method should be broadly applicable to identify compounds or proteins modulating many DNA-binding or RNA-binding proteins.
Collapse
Affiliation(s)
- Nicole Alonso
- Biomolecular Sciences Institute, Florida International University, 11200 SW 8th Street, Miami, FL 33199, USA Department of Chemistry & Biochemistry, Florida International University, 11200 SW 8th Street, FL 33199, USA
| | - Roboan Guillen
- Biomolecular Sciences Institute, Florida International University, 11200 SW 8th Street, Miami, FL 33199, USA Department of Chemistry & Biochemistry, Florida International University, 11200 SW 8th Street, FL 33199, USA
| | - Jeremy W Chambers
- Biomolecular Sciences Institute, Florida International University, 11200 SW 8th Street, Miami, FL 33199, USA Department of Cellular Biology and Pharmacology, Herbert Wertheim College of Medicine, Florida International University, Miami, FL 33199, USA
| | - Fenfei Leng
- Biomolecular Sciences Institute, Florida International University, 11200 SW 8th Street, Miami, FL 33199, USA Department of Chemistry & Biochemistry, Florida International University, 11200 SW 8th Street, FL 33199, USA
| |
Collapse
|
216
|
Tam CHT, Wang Y, Luan J, Lee HM, Luk AOY, Tutino GE, Tong PCY, Ko GTC, Ozaki R, Tam WH, Kong APS, So WY, Chan JCN, Ma RCW. Non-linear relationship between birthweight and cardiometabolic risk factors in Chinese adolescents and adults. Diabet Med 2015; 32:220-5. [PMID: 25388749 DOI: 10.1111/dme.12630] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/07/2014] [Indexed: 02/01/2023]
Abstract
AIM To investigate the relationship between birthweight and cardiometabolic traits in two cohorts: one of Chinese adolescents and one of Chinese adults. METHODS Birthweight and clinical data, including anthropometric traits, fasting plasma glucose and fasting plasma insulin levels, blood pressure and lipid profiles were collected from 2035 adolescents and 456 adults. A subset of 735 subjects underwent an oral glucose tolerance test to measure the glucose and insulin concentrations at 0, 15, 30, 60 and 120 min. RESULTS Among adolescents, birthweight showed U-shaped relationships with larger body size, obesity, abdominal obesity in girls, insulin resistance and worse lipid profiles (0.0013 < P(quadratic) < 0.0499), as well as an inverse association with fasting plasma glucose (P(linear) = 0.0368). After further adjustment for adiposity, decreasing birthweight was associated with elevated fasting plasma glucose levels, greater insulin resistance and worse lipid profiles (3.1 × 10⁻⁵ < P(linear) < 0.0058). Among adults, high birthweight was associated with larger body size and abdominal obesity in men, while low birthweight was associated with elevated glucose levels at 15, 30, 60 and 120 min and a greater area under the curve at 0-120 min, as well as with β-cell dysfunction (6.5 × 10⁻⁵ < P(linear) < 0.0437). Adjustment for adult adiposity did not substantially change the relationships. There was significant interaction between birthweight and abdominal obesity in elevating fasting plasma insulin and homeostasis model assessment of insulin resistance (P > 0.05), with abdominally obese adolescents in the lowest birthweight category (≤ 2.5 kg) having the highest risk of insulin resistance. CONCLUSIONS Both high and low birthweights are associated with an increased risk of cardiometabolic abnormalities including obesity, abdominal obesity, hyperglycaemia, dyslipidaemia and insulin resistance, as well as with β-cell dysfunction.
Collapse
Affiliation(s)
- C H T Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
217
|
Day FR, Perry JRB, Ong KK. Genetic Regulation of Puberty Timing in Humans. Neuroendocrinology 2015; 102:247-255. [PMID: 25968239 PMCID: PMC6309186 DOI: 10.1159/000431023] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2015] [Accepted: 04/28/2015] [Indexed: 12/11/2022]
Abstract
Understanding the regulation of puberty timing has relevance to developmental and human biology and to the pathogenesis of various diseases. Recent large-scale genome-wide association studies on puberty timing and adult height, body mass index (BMI) and central body shape provide evidence for shared biological mechanisms that regulate these traits. There is a substantial genetic overlap between age at menarche in women and BMI, with almost invariable directional consistency with the epidemiological associations between earlier menarche and higher BMI. By contrast, the genetic loci identified for age at menarche are largely distinct from those identified for central body shape, while alleles that confer earlier menarche can be associated with taller or shorter adult height. The findings of population-based studies on age at menarche show increasing relevance for other studies of rare monogenic disorders and enrich our understanding of the mechanisms that regulate the timing of puberty and reproductive function.
Collapse
Affiliation(s)
- Felix R Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | | | | |
Collapse
|
218
|
Larsson SC, Drca N, Jensen-Urstad M, Wolk A. Incidence of atrial fibrillation in relation to birth weight and preterm birth. Int J Cardiol 2015; 178:149-52. [DOI: 10.1016/j.ijcard.2014.10.138] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2014] [Revised: 08/27/2014] [Accepted: 10/21/2014] [Indexed: 01/19/2023]
|
219
|
The Generation R Study: Biobank update 2015. Eur J Epidemiol 2014; 29:911-27. [PMID: 25527369 DOI: 10.1007/s10654-014-9980-6] [Citation(s) in RCA: 182] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2014] [Accepted: 12/06/2014] [Indexed: 12/14/2022]
Abstract
The Generation R Study is a population-based prospective cohort study from fetal life until adulthood. The study is designed to identify early environmental and genetic causes and causal pathways leading to normal and abnormal growth, development and health from fetal life, childhood and young adulthood. In total, 9,778 mothers were enrolled in the study. Data collection in children and their parents include questionnaires, interviews, detailed physical and ultrasound examinations, behavioural observations, Magnetic Resonance Imaging and biological samples. Efforts have been conducted for collecting biological samples including blood, hair, faeces, nasal swabs, saliva and urine samples and generating genomics data on DNA, RNA and microbiome. In this paper, we give an update of the collection, processing and storage of these biological samples and available measures. Together with detailed phenotype measurements, these biological samples provide a unique resource for epidemiological studies focused on environmental exposures, genetic and genomic determinants and their interactions in relation to growth, health and development from fetal life onwards.
Collapse
|
220
|
Abstract
The fat mass and obesity-associated (FTO) gene was placed center stage when common intronic variants within the gene were robustly associated with human obesity. Murine models of perturbed Fto expression have shown effects on body weight and composition. However, a clear understanding of the link between FTO intronic variants and FTO activity has remained elusive. Two recent reports now indicate that obesity-associated SNPs appear functionally connected not with FTO but with two neighboring genes: IRX3 and RPGRIP1L. Here, we review these new findings and consider the implications for future analysis of GWAS hits.
Collapse
Affiliation(s)
- Y C Loraine Tung
- Medical Research Council Metabolic Diseases Unit, University of Cambridge Metabolic Research Laboratories, Level 4, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Giles S H Yeo
- Medical Research Council Metabolic Diseases Unit, University of Cambridge Metabolic Research Laboratories, Level 4, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Stephen O'Rahilly
- Medical Research Council Metabolic Diseases Unit, University of Cambridge Metabolic Research Laboratories, Level 4, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Anthony P Coll
- Medical Research Council Metabolic Diseases Unit, University of Cambridge Metabolic Research Laboratories, Level 4, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK.
| |
Collapse
|
221
|
Chawla R, Badon SE, Rangarajan J, Reisetter AC, Armstrong LL, Lowe LP, Urbanek M, Metzger BE, Hayes MG, Scholtens DM, Lowe WL. Genetic risk score for prediction of newborn adiposity and large-for-gestational-age birth. J Clin Endocrinol Metab 2014; 99:E2377-86. [PMID: 25137420 PMCID: PMC4223445 DOI: 10.1210/jc.2013-4221] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
CONTEXT Macrosomic infants are at increased risk for adverse metabolic outcomes. Improving prediction of large-for-gestational-age (LGA) birth may help prevent these outcomes. OBJECTIVE This study sought to determine whether genes associated with obesity-related traits in adults are associated with newborn size, and whether a genetic risk score (GRS) predicts LGA birth. SETTING AND DESIGN Single nucleotide polymorphisms (SNPs) in 40 regions associated with adult obesity-related traits were tested for association with newborn size. GRS's for birth weight and sum of skinfolds (SSF) specific to ancestry were calculated using the most highly associated SNP for each ancestry in genomic regions with one or more SNPs associated with birth weight and/or SSF in at least one ancestry group or meta-analyses. PARTICIPANTS Newborns from the Hyperglycemia Adverse Pregnancy Outcomes Study were studied (942 Afro-Caribbean, 1294 Northern European, 573 Mexican-American, and 1182 Thai). OUTCOME MEASURES Birth weight >90th percentile (LGA) and newborn SSF >90th percentile were primary outcomes. RESULTS After adjustment for ancestry, sex, gestational age at delivery, parity, maternal genotype, maternal smoking/alcohol intake, age, body mass index, height, blood pressure and glucose, 25 and 23 SNPs were associated (P < .001) with birth weight and newborn SSF, respectively. The GRS was highly associated with both phenotypes as continuous variables across all ancestries (P ≤ 1.6 × 10(-19)) and improved prediction of birth weight and SSF >90th percentile when added to a baseline model incorporating the covariates listed above. CONCLUSIONS A GRS comprised of SNPs associated with adult obesity-related traits may provide an approach for predicting LGA birth and newborn adiposity beyond established risk factors.
Collapse
|
222
|
Yeo GSH. The role of the FTO (Fat Mass and Obesity Related) locus in regulating body size and composition. Mol Cell Endocrinol 2014; 397:34-41. [PMID: 25224490 DOI: 10.1016/j.mce.2014.09.012] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2014] [Revised: 09/10/2014] [Accepted: 09/10/2014] [Indexed: 01/23/2023]
Abstract
Genomewide association studies (GWAS) have indicated that SNPs on a chromosome 16 locus encompassing FTO, as well as IRX3, 5, 6, FTM and FTL are robustly associated with human obesity. GWAS, however, are by nature gene agnostic, and SNPs reaching the appropriate statistical threshold for a given phenotype can appear anywhere in the genome, within, near or far away from any coding sequence. Thus a major challenge in the field has been to translate these statistical hits into real biological insight. The key question is which of these genes are responsible for the association with obesity, and what is the underlying mechanism? With loss of function FTO mutations in both mice and humans resulting in severe growth retardation and mice globally over-expressing FTO being obese, the initial attention was focussed on this gene. We and others have shown that in vitro, recombinant FTO is able to catalyse the Fe(II)- and 2OG-dependent demethylation of single stranded nucleic-acids, with a preference for RNA. We have shown that FTO expression is regulated by essential amino acids (AAs) and that it couples amino acid levels to mammalian Target of Rapamycin Complex 1 (mTORC1) signalling, through a mechanism dependent on its ability to demethylate. Thus FTO is an AA sensor and plays a key role regulating appropriate growth and translation. However, recent data focussing on obesity associated variants within FTO have implicated two neighbouring genes, RPGRIP1L and IRX3, as having a functional link between the SNP and the observed human phenotypes. As with Fto, perturbing the expression of these genes in mice results in a bodyweight phenotype, with homozygous deletion of Irx3 resulting in a smaller mouse and heterozygous deletion of Rpgrip1l leading to a mild obesity phenotype. Thus it may be that a number of genes in this region play an important role in determining body composition.
Collapse
Affiliation(s)
- Giles S H Yeo
- MRC Metabolic Diseases Unit, University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK.
| |
Collapse
|
223
|
Perry JRB, Day F, Elks CE, Sulem P, Thompson DJ, Ferreira T, He C, Chasman DI, Esko T, Thorleifsson G, Albrecht E, Ang WQ, Corre T, Cousminer DL, Feenstra B, Franceschini N, Ganna A, Johnson AD, Kjellqvist S, Lunetta KL, McMahon G, Nolte IM, Paternoster L, Porcu E, Smith AV, Stolk L, Teumer A, Tšernikova N, Tikkanen E, Ulivi S, Wagner EK, Amin N, Bierut LJ, Byrne EM, Hottenga JJ, Koller DL, Mangino M, Pers TH, Yerges-Armstrong LM, Zhao JH, Andrulis IL, Anton-Culver H, Atsma F, Bandinelli S, Beckmann MW, Benitez J, Blomqvist C, Bojesen SE, Bolla MK, Bonanni B, Brauch H, Brenner H, Buring JE, Chang-Claude J, Chanock S, Chen J, Chenevix-Trench G, Collée JM, Couch FJ, Couper D, Coveillo AD, Cox A, Czene K, D’adamo AP, Smith GD, De Vivo I, Demerath EW, Dennis J, Devilee P, Dieffenbach AK, Dunning AM, Eiriksdottir G, Eriksson JG, Fasching PA, Ferrucci L, Flesch-Janys D, Flyger H, Foroud T, Franke L, Garcia ME, García-Closas M, Geller F, de Geus EEJ, Giles GG, Gudbjartsson DF, Gudnason V, Guénel P, Guo S, Hall P, Hamann U, Haring R, Hartman CA, Heath AC, Hofman A, Hooning MJ, Hopper JL, Hu FB, Hunter DJ, Karasik D, Kiel DP, et alPerry JRB, Day F, Elks CE, Sulem P, Thompson DJ, Ferreira T, He C, Chasman DI, Esko T, Thorleifsson G, Albrecht E, Ang WQ, Corre T, Cousminer DL, Feenstra B, Franceschini N, Ganna A, Johnson AD, Kjellqvist S, Lunetta KL, McMahon G, Nolte IM, Paternoster L, Porcu E, Smith AV, Stolk L, Teumer A, Tšernikova N, Tikkanen E, Ulivi S, Wagner EK, Amin N, Bierut LJ, Byrne EM, Hottenga JJ, Koller DL, Mangino M, Pers TH, Yerges-Armstrong LM, Zhao JH, Andrulis IL, Anton-Culver H, Atsma F, Bandinelli S, Beckmann MW, Benitez J, Blomqvist C, Bojesen SE, Bolla MK, Bonanni B, Brauch H, Brenner H, Buring JE, Chang-Claude J, Chanock S, Chen J, Chenevix-Trench G, Collée JM, Couch FJ, Couper D, Coveillo AD, Cox A, Czene K, D’adamo AP, Smith GD, De Vivo I, Demerath EW, Dennis J, Devilee P, Dieffenbach AK, Dunning AM, Eiriksdottir G, Eriksson JG, Fasching PA, Ferrucci L, Flesch-Janys D, Flyger H, Foroud T, Franke L, Garcia ME, García-Closas M, Geller F, de Geus EEJ, Giles GG, Gudbjartsson DF, Gudnason V, Guénel P, Guo S, Hall P, Hamann U, Haring R, Hartman CA, Heath AC, Hofman A, Hooning MJ, Hopper JL, Hu FB, Hunter DJ, Karasik D, Kiel DP, Knight JA, Kosma VM, Kutalik Z, Lai S, Lambrechts D, Lindblom A, Mägi R, Magnusson PK, Mannermaa A, Martin NG, Masson G, McArdle PF, McArdle WL, Melbye M, Michailidou K, Mihailov E, Milani L, Milne RL, Nevanlinna H, Neven P, Nohr EA, Oldehinkel AJ, Oostra BA, Palotie A, Peacock M, Pedersen NL, Peterlongo P, Peto J, Pharoah PDP, Postma DS, Pouta A, Pylkäs K, Radice P, Ring S, Rivadeneira F, Robino A, Rose LM, Rudolph A, Salomaa V, Sanna S, Schlessinger D, Schmidt MK, Southey MC, Sovio U, Stampfer MJ, Stöckl D, Storniolo AM, Timpson NJ, Tyrer J, Visser JA, Vollenweider P, Völzke H, Waeber G, Waldenberger M, Wallaschofski H, Wang Q, Willemsen G, Winqvist R, Wolffenbuttel BHR, Wright MJ, Boomsma DI, Econs MJ, Khaw KT, Loos RJF, McCarthy MI, Montgomery GW, Rice JP, Streeten EA, Thorsteinsdottir U, van Duijn CM, Alizadeh BZ, Bergmann S, Boerwinkle E, Boyd HA, Crisponi L, Gasparini P, Gieger C, Harris TB, Ingelsson E, Järvelin MR, Kraft P, Lawlor D, Metspalu A, Pennell CE, Ridker PM, Snieder H, Sørensen TIA, Spector TD, Strachan DP, Uitterlinden AG, Wareham NJ, Widen E, Zygmunt M, Murray A, Easton DF, Stefansson K, Murabito JM, Ong KK. Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche. Nature 2014; 514:92-97. [PMID: 25231870 PMCID: PMC4185210 DOI: 10.1038/nature13545] [Show More Authors] [Citation(s) in RCA: 414] [Impact Index Per Article: 37.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2013] [Accepted: 05/30/2014] [Indexed: 02/02/2023]
Abstract
Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition.
Collapse
Affiliation(s)
- John RB Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
- University of Exeter Medical School, University of Exeter, Exeter, UK EX1 2LU
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Felix Day
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Cathy E Elks
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | | | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, UK
| | - Teresa Ferreira
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Chunyan He
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN 46202, USA
- Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN 46202, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA 02215
- Harvard Medical School, Boston, MA 02115
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, 51010, Estonia
- Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, MA 02115, USA
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, 140 Cambridge 02142, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | | | - Eva Albrecht
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Wei Q Ang
- School of Women’s and Infants’ Health, The University of Western Australia
| | - Tanguy Corre
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Diana L Cousminer
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, DK-2300 Copenhagen, Denmark
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC
| | - Andrea Ganna
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden
| | - Andrew D Johnson
- NHLBI’s and Boston University’s Framingham Heart Study, Framingham, MA
| | - Sanela Kjellqvist
- Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden
| | - Kathryn L Lunetta
- NHLBI’s and Boston University’s Framingham Heart Study, Framingham, MA
- Boston University School of Public Health, Department of Biostatistics. Boston, MA
| | - George McMahon
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | | | - Eleonora Porcu
- Institute of Genetics and Biomedical Research, National Research Council, Cagliari, Italy
- University of Sassari, Dept. Of Biomedical Sciences, Sassari, Italy
| | - Albert V Smith
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Lisette Stolk
- Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands
- Netherlands Consortium on Health Aging and National Genomics Initiative, Leiden, the Netherlands
| | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Natalia Tšernikova
- Estonian Genome Center, University of Tartu, Tartu, 51010, Estonia
- Department of Biotechnology, University of Tartu, Tartu, 51010, Estonia
| | - Emmi Tikkanen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland
- Hjelt Institute, University of Helsinki, Finland
| | - Sheila Ulivi
- Institute for Maternal and Child Health - IRCCS “Burlo Garofolo” – Trieste, Italy
| | - Erin K Wagner
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN 46202, USA
- Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN 46202, USA
| | - Najaf Amin
- Genetic Epidemiology Unit Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands
| | - Laura J Bierut
- Dept. of Psychiatry, Washington University, St. Louis, MO 63110
| | - Enda M Byrne
- The University of Queensland, Queensland Brain Institute, St.Lucia, QLD, Australia
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands
| | - Daniel L Koller
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana USA
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Tune H Pers
- Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, MA 02115, USA
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, 140 Cambridge 02142, MA, USA
- Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, US
- Center for Biological Sequence Analysis, Department of Systems Biology, Technical 142 University of Denmark, Lyngby 2800, Denmark
| | - Laura M Yerges-Armstrong
- Program in Personalized and Genomic Medicine, and Department of Medicine, Division of Endocrinology, Diabetes and Nutrition - University of Maryland School of Medicine, USA. Baltimore, MD 21201
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Irene L Andrulis
- Ontario Cancer Genetics Network, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Hoda Anton-Culver
- Department of Epidemiology, University of California Irvine, Irvine, California, USA
| | | | - Stefania Bandinelli
- Tuscany Regional Health Agency, Florence, Italy, I.O.T. and Department of Medical and Surgical Critical Care, University of Florence, Florence, Italy
- Geriatric Unit, Azienda Sanitaria di Firenze, Florence, Italy
| | - Matthias W Beckmann
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Javier Benitez
- Human Genetics Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Valencia, Spain
| | - Carl Blomqvist
- Department of Oncology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev Hospital, Copenhagen University Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, UK
| | - Bernardo Bonanni
- Division of Cancer Prevention and Genetics, Istituto Europeo di Oncologia (IEO), Milan, Italy
| | - Hiltrud Brauch
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart
- University of Tübingen, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA 02215
- Harvard Medical School, Boston, MA 02115
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stephen Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jinhui Chen
- Departments of Anatomy and Neurological Surgery, Indiana University school of Medicine, Indianapolis, IN 46202, USA
- Stark Neuroscience Research Center, Indiana University school of Medicine, Indianapolis, IN 46202, USA
| | | | - J. Margriet Collée
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - David Couper
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC
| | - Andrea D Coveillo
- Boston University School of Medicine, Department of Medicine, Sections of Preventive Medicine and Endocrinology, Boston, MA
| | - Angela Cox
- Sheffield Cancer Research Centre, Department of Oncology, University of Sheffield, Sheffield, UK
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden
| | - Adamo Pio D’adamo
- Institute for Maternal and Child Health - IRCCS “Burlo Garofolo” – Trieste, Italy
- Department of Clinical Medical Sciences, Surgical and Health, University of Trieste, Italy
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Immaculata De Vivo
- Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ellen W Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minn., USA
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, UK
| | - Peter Devilee
- Department of Human Genetics & Department of Pathology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands
| | - Aida K Dieffenbach
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, UK
| | | | - Johan G Eriksson
- National Institute for Health and Welfare, Finland
- Department of General Practice and Primary health Care, University of Helsinki, Finland
- Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland
- Folkhalsan Research Centre, Helsinki, Finland
| | - Peter A Fasching
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Luigi Ferrucci
- Longitudinal Studies Section, Clinical Research Branch, Gerontology Research Center, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Dieter Flesch-Janys
- Department of Cancer Epidemiology/Clinical Cancer Registry and Institute for Medical Biometrics and Epidemiology, University Clinic Hamburg-Eppendorf, Hamburg, Germany
| | - Henrik Flyger
- Department of Breast Surgery, Herlev Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana USA
| | - Lude Franke
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Melissa E Garcia
- National Insitute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Montserrat García-Closas
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, UK
- Breakthrough Breast Cancer Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, UK
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, DK-2300 Copenhagen, Denmark
| | - Eco EJ de Geus
- Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands
- EMGO + Institute for Health and Care Research, VU University Medical Centre, Van der Boechorststraat 7, 1081 Bt, Amsterdam, The Netherlands
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Daniel F Gudbjartsson
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Pascal Guénel
- Inserm (National Institute of Health and Medical Research), CESP (Center for Research in Epidemiology and Population Health), U1018, Environmental Epidemiology of Cancer, Villejuif, France
- University Paris-Sud, UMRS 1018, Villejuif, France
| | - Suiqun Guo
- Department of Obstetrics and Gynecology, Southern Medical University, Guangzhou, China
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
| | - Robin Haring
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Catharina A Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Andrew C Heath
- Washington University, Department of Psychiatry, St.Louis, Missouri, USA
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdan, the Netherlands
| | - Maartje J Hooning
- Department of Medical Oncology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Frank B Hu
- Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
- Department of Nutrition, Harvard School of Public Health, Boston, MA 02115, USA
| | - David J Hunter
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, 140 Cambridge 02142, MA, USA
- Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - David Karasik
- Harvard Medical School, Boston, MA 02115
- Hebrew SeniorLife Institute for Aging Research, Boston, MA
| | - Douglas P Kiel
- Hebrew SeniorLife Institute for Aging Research, Boston, MA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02115
| | - Julia A Knight
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Veli-Matti Kosma
- School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland
| | - Zoltan Kutalik
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Sandra Lai
- Institute of Genetics and Biomedical Research, National Research Council, Cagliari, Italy
| | - Diether Lambrechts
- Vesalius Research Center (VRC), VIB, Leuven, Belgium
- Laboratory for Translational Genetics, Department of Oncology, University of Leuven, Leuven, Belgium
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, 51010, Estonia
| | - Patrik K Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden
| | - Arto Mannermaa
- School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland
| | - Nicholas G Martin
- Department of Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | - Patrick F McArdle
- Program in Personalized and Genomic Medicine, and Department of Medicine, Division of Endocrinology, Diabetes and Nutrition - University of Maryland School of Medicine, USA. Baltimore, MD 21201
| | - Wendy L McArdle
- School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Mads Melbye
- Department of Epidemiology Research, Statens Serum Institut, DK-2300 Copenhagen, Denmark
- Department of Medicine, Stanford School of Medicine, Stanford, USA
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, UK
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu, 51010, Estonia
- Department of Biotechnology, University of Tartu, Tartu, 51010, Estonia
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu, 51010, Estonia
| | - Roger L Milne
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Patrick Neven
- KULeuven (University of Leuven), Department of Oncology, Multidisciplinary Breast Center, University Hospitals Leuven, Belgium
| | - Ellen A Nohr
- Research Unit of Obstetrics & Gynecology, Institute of Clinical Research, University of Southern denmark, DK
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ben A Oostra
- Genetic Epidemiology Unit Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Munro Peacock
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden
| | - Paolo Peterlongo
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy
| | - Julian Peto
- Non-communicable Disease Epidemiology Department, London School of Hygiene and Tropical Medicine, London, UK
| | - Paul DP Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, UK
| | - Dirkje S Postma
- University Groningen, University Medical Center Groningen, Department Pulmonary Medicine and Tuberculosis, GRIAC Research Institute, Groningen, The Netherlands
| | - Anneli Pouta
- National Institute for Health and Welfare, Finland
- Department of Obstetrics and Gynecology, Oulu University Hospital, Finland
| | - Katri Pylkäs
- Laboratory of Cancer Genetics and Tumor Biology, Department of Clinical Chemistry and Biocenter Oulu, University of Oulu, Oulu University Hospital/NordLab Oulu, Oulu, Finland
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Susan Ring
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands
- Netherlands Consortium on Health Aging and National Genomics Initiative, Leiden, the Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdan, the Netherlands
| | - Antonietta Robino
- Institute for Maternal and Child Health - IRCCS “Burlo Garofolo” – Trieste, Italy
- Department of Clinical Medical Sciences, Surgical and Health, University of Trieste, Italy
| | - Lynda M Rose
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA 02215
| | - Anja Rudolph
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Serena Sanna
- Institute of Genetics and Biomedical Research, National Research Council, Cagliari, Italy
| | - David Schlessinger
- National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Marjanka K Schmidt
- Netherlands Cancer Institute, Antoni van Leeuwenhoek hospital, Amsterdam, The Netherlands
| | - Mellissa C Southey
- Department of Pathology, The University of Melbourne, Melbourne, Australia
| | - Ulla Sovio
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College London, UK
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, United Kingdom
| | - Meir J Stampfer
- Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
- Department of Nutrition, Harvard School of Public Health, Boston, MA 02115, USA
| | - Doris Stöckl
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Department of Obstetrics and Gynaecology, Campus Grosshadern, Ludwig-Maximilians- University, Munich, Germany
| | - Anna M Storniolo
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana USA
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Jonathan Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, UK
| | - Jenny A Visser
- Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - Peter Vollenweider
- Department of Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, 17475 Greifswald, Germany
| | - Gerard Waeber
- Department of Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Henri Wallaschofski
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, 17475 Greifswald, Germany
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, UK
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Department of Clinical Chemistry and Biocenter Oulu, University of Oulu, Oulu University Hospital/NordLab Oulu, Oulu, Finland
| | - Bruce HR Wolffenbuttel
- Department of Endocrinology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Margaret J Wright
- Queensland Insitute of Medical Research, Brisbane, Queensland, Australia
| | - Australian Ovarian Cancer Study
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Peter MacCallum Cancer Centre, Melbourne, Australia
| | - The GENICA Network
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart
- University of Tübingen, Germany
- Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, Germany
- Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany
- Institute of Pathology, Medical Faculty of the University of Bonn, Bonn, Germany
- Institute of Occupational Medicine and Maritime Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - kConFab
- Peter MacCallum Cancer Centre, Melbourne, Australia
| | | | | | | | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands
| | - Michael J Econs
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana USA
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Ruth JF Loos
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
- Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1003, New York, NY 10029, USA
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, OX3 7LE Oxford, UK
- Oxford Centre for Diabetes, Endocrinology, & Metabolism, University of Oxford, Churchill Hospital, OX37LJ Oxford, UK
| | - Grant W Montgomery
- Queensland Insitute of Medical Research, Brisbane, Queensland, Australia
| | - John P Rice
- Dept. of Psychiatry, Washington University, St. Louis, MO 63110
| | - Elizabeth A Streeten
- Program in Personalized and Genomic Medicine, and Department of Medicine, Division of Endocrinology, Diabetes and Nutrition - University of Maryland School of Medicine, USA. Baltimore, MD 21201
- Geriatric Research and Education Clinical Center (GRECC) - Veterans Administration Medical Center, USA. Baltimore, MD 21201
| | - Unnur Thorsteinsdottir
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Cornelia M van Duijn
- Netherlands Consortium on Health Aging and National Genomics Initiative, Leiden, the Netherlands
- Genetic Epidemiology Unit Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands
- Centre of Medical Systems Biology, Leiden, the Netherlands
| | - Behrooz Z Alizadeh
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sven Bergmann
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Eric Boerwinkle
- Human Genetics Center and Div. of Epidemiology, University of Houston, TX
| | - Heather A Boyd
- Department of Epidemiology Research, Statens Serum Institut, DK-2300 Copenhagen, Denmark
| | - Laura Crisponi
- Institute of Genetics and Biomedical Research, National Research Council, Cagliari, Italy
| | - Paolo Gasparini
- Institute for Maternal and Child Health - IRCCS “Burlo Garofolo” – Trieste, Italy
- Department of Clinical Medical Sciences, Surgical and Health, University of Trieste, Italy
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Tamara B Harris
- National Insitute on Aging, National Institutes of Health, Baltimore, MD 20892, USA
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College London, UK
- Institute of Health Sciences, P.O.Box 5000, FI-90014 University of Oulu, Finland
- Biocenter Oulu, P.O.Box 5000, Aapistie 5A, FI-90014 University of Oulu, Finland
- Department of Children and Young People and Families, National Institute for Health and Welfare, Aapistie 1, Box 310, FI-90101 Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Kajaanintie 50, P.O.Box 20, FI-90220 Oulu, 90029 OYS, Finland
| | - Peter Kraft
- Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
- Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
| | - Debbie Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, 51010, Estonia
- Department of Biotechnology, University of Tartu, Tartu, 51010, Estonia
| | - Craig E Pennell
- School of Women’s and Infants’ Health, The University of Western Australia
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA 02215
- Harvard Medical School, Boston, MA 02115
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Thorkild IA Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
- Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, Denmark
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - David P Strachan
- Division of Population Health Sciences and Education, St George’s, University of London, Cranmer Terrace, London SW17 0RE, UK
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands
- Netherlands Consortium on Health Aging and National Genomics Initiative, Leiden, the Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdan, the Netherlands
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland
| | - Marek Zygmunt
- Department of Obstetrics and Gynecology, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Anna Murray
- University of Exeter Medical School, University of Exeter, Exeter, UK EX1 2LU
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, UK
| | - Kari Stefansson
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Joanne M Murabito
- NHLBI’s and Boston University’s Framingham Heart Study, Framingham, MA
- Boston University School of Medicine, Department of Medicine, Section of General Internal Medicine, Boston, MA
| | - Ken K Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
- Department of Paediatrics,University of Cambridge,Cambridge,UK
| |
Collapse
|
224
|
Vaag A, Brøns C, Gillberg L, Hansen NS, Hjort L, Arora GP, Thomas N, Broholm C, Ribel-Madsen R, Grunnet LG. Genetic, nongenetic and epigenetic risk determinants in developmental programming of type 2 diabetes. Acta Obstet Gynecol Scand 2014; 93:1099-108. [PMID: 25179736 DOI: 10.1111/aogs.12494] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2014] [Accepted: 08/27/2014] [Indexed: 12/23/2022]
Abstract
Low birthweight (LBW) individuals and offspring of women with gestational diabetes mellitus (GDM) exhibit increased risk of developing type 2 diabetes (T2D) and associated cardiometabolic traits in adulthood, which for both groups may be mediated by adverse events and developmental changes in fetal life. T2D is a multifactorial disease occurring as a result of complicated interplay between genetic and both prenatal and postnatal nongenetic factors, and it remains unknown to what extent the increased risk of T2D associated with LBW or GDM in the mother may be due to, or confounded by, genetic factors. Indeed, it has been shown that genetic changes influencing risk of diabetes may also be associated with reduced fetal growth as a result of reduced insulin secretion and/or action. Similarly, increased risk of T2D among offspring could be explained by T2D susceptibility genes shared between the mother and her offspring. Epigenetic mechanisms may explain the link between factors operating in fetal life and later risk of developing T2D, but so far convincing evidence is lacking for epigenetic changes as a prime and direct cause of T2D. This review addresses recent literature on the early origins of adult disease hypothesis, with a special emphasis on the role of genetic compared with nongenetic and epigenetic risk determinants and disease mechanisms.
Collapse
Affiliation(s)
- Allan Vaag
- Department of Endocrinology, Diabetes and Metabolism, Rigshospitalet University Hospital/Copenhagen University, Copenhagen, Denmark; Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | | | | | | | | | | | | | | | | |
Collapse
|
225
|
The chromosome 3q25 locus associated with fetal adiposity is not associated with childhood adiposity. Nutr Diabetes 2014; 4:e138. [PMID: 25244357 PMCID: PMC4183976 DOI: 10.1038/nutd.2014.35] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2014] [Accepted: 08/18/2014] [Indexed: 11/17/2022] Open
Abstract
Increased newborn adiposity is associated with later adverse metabolic outcomes. Previous genome-wide association studies (GWAS) demonstrated strong association of a locus on chromosome 3 (3q25.31) with newborn sum of skinfolds, a measure of overall adiposity. Whether this locus is associated with childhood adiposity is unknown. Genotype and sum of skinfolds data were available for 293 children at birth and age 2, and for 350 children at birth and age 6 from a European cohort (Belfast, UK) who participated in the Hyperglycemia and Adverse Pregnancy Outcome GWAS. We examined single nucleotide polymorphisms (SNPs) at the 3q25.31 locus associated with newborn adiposity. Linear regression analyses under an additive genetic model adjusting for maternal body mass index were performed. In both cohorts, a positive association was observed between all SNPs and sum of skinfolds at birth (P=2.3 × 10−4, β=0.026 and P=4.8 × 10−4, β=0.025). At the age of 2 years, a non-significant negative association was observed with sum of skinfolds (P=0.06; β =−0.015). At the age of 6 years, there was no evidence of association (P=0.86; β=0.002). The 3q25.31 locus strongly associated with newborn adiposity had no significant association with childhood adiposity suggesting that its impact may largely be limited to fetal fat accretion.
Collapse
|
226
|
Abstract
This thesis explores the contribution of twin studies, particularly those studies originating from the Danish Twin Registry, to the understanding of the aetiology of asthma. First, it is explored how twin studies have established the contribution of genetic and environmental factors to the variation in the susceptibility to asthma, and to the variation in several aspects of the clinical expression of the disease such as its age at onset, its symptomatology, its intermediate phenotypes, and its relationship with other atopic diseases. Next, it is explored how twin studies have corroborated theories explaining asthma's recent increase in prevalence, and last, how these fit with the explanations of the epidemiological trends in other common chronic diseases of modernity.
Collapse
|
227
|
Moreno LA, Gottrand F, Huybrechts I, Ruiz JR, González-Gross M, DeHenauw S. Nutrition and lifestyle in european adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study. Adv Nutr 2014; 5:615S-623S. [PMID: 25469407 PMCID: PMC4188245 DOI: 10.3945/an.113.005678] [Citation(s) in RCA: 124] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Adolescence is a critical period, because major physical and psychologic changes occur during a very short period of time. Changes in dietary habits may induce different types of nutritional disorders and are likely to track into adulthood. The aim of this review is to describe the key findings related to nutritional status in European adolescents participating in the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study. We performed a cross-sectional study in 3528 (1845 females) adolescents aged 12.5–17.5 y. Birth weight was negatively associated with abdominal fat mass in adolescents and serum leptin concentrations (in female adolescents), providing additional evidence for a programming effect of birth weight on energy homeostasis control. Breakfast consumption was associated with lower body fat content and healthier cardiovascular profile. Adolescents eat half of the recommended amount of fruit and vegetables and less than two-thirds of the recommended amount of milk and milk products but consume more meat and meat products, fats, and sweets than recommended. For beverage consumption, sugar-sweetened beverages, sweetened milk, low-fat milk, and fruit juice provided the highest amount of energy. Although the intakes of saturated fatty acids (FAs) and salt were high, the intake of polyunsaturated FAs was low. Adolescents spent, on average, 9 h/d of their waking time (66–71% and 70–73% of the registered time in boys and girls, respectively) in sedentary activities. Factors associated with adolescents’ sedentary behavior included the following: 1) age; 2) media availability in the bedroom; 3) sleeping time; 4) breakfast consumption; and 5) season. Sedentary time was also associated with cardiovascular risk factors and bone mineral content. In European adolescents, deficient concentrations were identified for plasma folate (15%), vitamin D (15%), pyridoxal 5′-phosphate (5%), β-carotene (25%), and vitamin E (5%). Scientists and public health authorities should raise awareness of the importance of a healthy and sustainable lifestyle as a foundation of the health of the European population, now and in the future.
Collapse
Affiliation(s)
- Luis A. Moreno
- GENUD (Growth, Exercise, Nutrition, and Development)
Research Group, Faculty of Health Sciences, University of Zaragoza, Zaragoza,
Spain
| | - Frédéric Gottrand
- National Institute of Health and Medical Research, Jeanne
de Flandre University Hospital, Lille, France
| | - Inge Huybrechts
- Department of Public Health, Ghent University, Ghent,
Belgium
- International Agency for Research on Cancer, Dietary
Exposure Assessment Group, Lyon, France
| | - Jonatan R. Ruiz
- PROFITH (Promoting Fitness and Health through Physical
Activity) Research Group, Department of Physical Education and Sport, Faculty of
Sport Sciences, University of Granada, Granada, Spain; and
| | - Marcela González-Gross
- ImFINE Research Group, Department of Health and Human
Performance, Faculty of Physical Activity and Sport Sciences, Technical University of
Madrid, Madrid, Spain
| | | | - on behalf of the HELENA Study Group
- GENUD (Growth, Exercise, Nutrition, and Development)
Research Group, Faculty of Health Sciences, University of Zaragoza, Zaragoza,
Spain
- National Institute of Health and Medical Research, Jeanne
de Flandre University Hospital, Lille, France
- Department of Public Health, Ghent University, Ghent,
Belgium
- International Agency for Research on Cancer, Dietary
Exposure Assessment Group, Lyon, France
- PROFITH (Promoting Fitness and Health through Physical
Activity) Research Group, Department of Physical Education and Sport, Faculty of
Sport Sciences, University of Granada, Granada, Spain; and
- ImFINE Research Group, Department of Health and Human
Performance, Faculty of Physical Activity and Sport Sciences, Technical University of
Madrid, Madrid, Spain
| |
Collapse
|
228
|
Ruiz-Narváez EA, Palmer JR, Gerlovin H, Wise LA, Vimalananda VG, Rosenzweig JL, Rosenberg L. Birth weight and risk of type 2 diabetes in the black women's health study: does adult BMI play a mediating role? Diabetes Care 2014; 37:2572-8. [PMID: 25147255 PMCID: PMC4140161 DOI: 10.2337/dc14-0731] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To assess the association of birth weight with incident type 2 diabetes, and the possible mediating influence of obesity, in a large cohort of U.S. black women. RESEARCH DESIGN AND METHODS The Black Women's Health Study is an ongoing prospective study. We used Cox proportional hazards models to estimate incidence rate ratios (IRRs) and 95% CI for categories of birth weight (very low birth weight [<1,500 g], low birth weight [1,500-2,499 g], and high birth weight [≥4,000 g]) in reference to normal birth weight (2,500-3,999 g). Models were adjusted for age, questionnaire cycle, family history of diabetes, caloric intake, preterm birth, physical activity, years of education, and neighborhood socioeconomic status with and without inclusion of terms for adult BMI. RESULTS We followed 21,624 women over 16 years of follow-up. There were 2,388 cases of incident diabetes. Women with very low birth weight had a 40% higher risk of disease (IRR 1.40 [95% CI 1.08-1.82]) than women with normal birth weight; women with low birth weight had a 13% higher risk (IRR 1.13 [95% CI 1.02-1.25]). Adjustment for BMI did not appreciably change the estimates. CONCLUSIONS Very low birth weight and low birth weight appear to be associated with increased risk of type 2 diabetes in African American women, and the association does not seem to be mediated through BMI. The prevalence of low birth weight is especially high in African American populations, and this may explain in part the higher occurrence of type 2 diabetes.
Collapse
Affiliation(s)
- Edward A Ruiz-Narváez
- Slone Epidemiology Center at Boston University, Boston, MA Department of Epidemiology, Boston University School of Public Health, Boston, MA
| | - Julie R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA Department of Epidemiology, Boston University School of Public Health, Boston, MA
| | - Hanna Gerlovin
- Slone Epidemiology Center at Boston University, Boston, MA Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Lauren A Wise
- Slone Epidemiology Center at Boston University, Boston, MA Department of Epidemiology, Boston University School of Public Health, Boston, MA
| | - Varsha G Vimalananda
- Section of Endocrinology, Diabetes, and Nutrition, Boston University School of Medicine, Boston, MA
| | - James L Rosenzweig
- Section of Endocrinology, Diabetes, and Nutrition, Boston University School of Medicine, Boston, MA
| | - Lynn Rosenberg
- Slone Epidemiology Center at Boston University, Boston, MA Department of Epidemiology, Boston University School of Public Health, Boston, MA
| |
Collapse
|
229
|
Ahles A, Engelhardt S. Polymorphic variants of adrenoceptors: pharmacology, physiology, and role in disease. Pharmacol Rev 2014; 66:598-637. [PMID: 24928328 DOI: 10.1124/pr.113.008219] [Citation(s) in RCA: 86] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2025] Open
Abstract
The human genome encodes nine different adrenoceptor genes. These are grouped into three families, namely, the α1-, α2-, and β-adrenoceptors, with three family members each. Adrenoceptors are expressed by most cell types of the human body and are primary targets of the catecholamines epinephrine and norepinephrine that are released from the sympathetic nervous system during its activation. Upon catecholamine binding, adrenoceptors change conformation, couple to and activate G proteins, and thereby initiate various intracellular signaling cascades. As the primary receivers and transducers of sympathetic activation, adrenoceptors have a central role in human physiology and disease and are important targets for widely used drugs. All nine adrenoceptor subtypes display substantial genetic variation, both in their coding sequence as well as in adjacent regions. Despite the fact that some of the adrenoceptor variants range among the most frequently studied genetic variants assessed in pharmacogenetics to date, their functional relevance remains ill defined in many cases. A substantial fraction of the associations reported from early candidate gene approaches have not subsequently been confirmed in different cohorts or in genome-wide association studies, which have increasingly been conducted in recent years. This review aims to provide a comprehensive overview of all adrenoceptor variants that have reproducibly been detected in the larger genome sequencing efforts. We evaluate these variants with respect to the modulation of receptor function and expression and discuss their role in physiology and disease.
Collapse
Affiliation(s)
- Andrea Ahles
- Institut für Pharmakologie und Toxikologie, Technische Universität München, Munich, Germany (A.A., S.E.); and DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany (S.E.)
| | - Stefan Engelhardt
- Institut für Pharmakologie und Toxikologie, Technische Universität München, Munich, Germany (A.A., S.E.); and DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany (S.E.)
| |
Collapse
|
230
|
Kato N. Insights into the genetic basis of type 2 diabetes. J Diabetes Investig 2014; 4:233-44. [PMID: 24843659 PMCID: PMC4015657 DOI: 10.1111/jdi.12067] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2013] [Revised: 01/25/2013] [Accepted: 01/28/2013] [Indexed: 02/06/2023] Open
Abstract
Type 2 diabetes is one of the most common complex diseases, of which considerable efforts have been made to unravel the pathophysiological mechanisms. Recently, large‐scale genome‐wide association (GWA) studies have successfully identified genetic loci robustly associated with type 2 diabetes by searching susceptibility variants across the entire genome in an unbiased, hypothesis‐free manner. The number of loci has climbed from just three in 2006 to approximately 70 today. For the common type 2 diabetes‐associated variants, three features have been noted. First, genetic impacts of individual variants are generally modest; mostly, allelic odds ratios range between 1.06 and 1.20. Second, most of the loci identified to date are not in or near obvious candidate genes, but some are often located in the intergenic regions. Third, although the number of loci is limited, there might be some population specificity in type 2 diabetes association. Although we can estimate a single or a few target genes for individual loci detected in GWA studies by referring to the data for experiments in vitro, biological function remains largely unknown for a substantial part of such target genes. Nevertheless, new biology is arising from GWA study discoveries; for example, genes implicated in β‐cell dysfunction are over‐represented within type 2 diabetes‐associated regions. Toward translational advances, we have just begun to face new challenges – elucidation of multifaceted (i.e., molecular, cellular and physiological) mechanistic insights into disease biology by considering interaction with the environment. The present review summarizes recent advances in the genetics of type 2 diabetes, together with its realistic potential.
Collapse
Affiliation(s)
- Norihiro Kato
- Department of Gene Diagnostics and Therapeutics Research Institute National Center for Global Health and Medicine Tokyo Japan
| |
Collapse
|
231
|
Variants Close to NTRK2 Gene Are Associated With Birth Weight in Female Twins. Twin Res Hum Genet 2014; 17:254-61. [DOI: 10.1017/thg.2014.34] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Low weight at birth has previously been shown to be associated with a number of adult diseases such as type 2 diabetes, cardiovascular disease, high blood pressure, and obesity later in life. Genome-wide association studies (GWAS) have been published for singleton-born individuals, but the role of genetic variation in birth weight (BW) in twins has not yet been fully investigated. A GWAS was performed in 4,593 female study participants with BW data available from the TwinsUK cohort. A genome-wide significant signal was found in chromosome 9, close to the NTRK2 gene (OMIM: 600456). QIMR, an Australian twin cohort (n = 3,003), and UK-based singleton-birth individuals from the Hertfordshire cohort (n = 2,997) were used as replication for the top two single nucleotide polymorphism (SNPs) underpinning this signal, rs12340987 and rs7849941. The top SNP, rs12340987, was found to be in the same direction in the Australian twins and in the singleton-born females (fixed effects meta-analysis beta = -0.13, SE = 0.02, and p = 1.48 × 10−8) but not in the singleton-born males tested. These findings provide an important insight into the genetic component of BW in twins who are normally excluded due to their lower BW when compared with singleton births, as well as the difference in BW between twins. The NTRK2 gene identified in this study has previously been associated with obesity.
Collapse
|
232
|
Hiby SE, Apps R, Chazara O, Farrell LE, Magnus P, Trogstad L, Gjessing HK, Carrington M, Moffett A. Maternal KIR in combination with paternal HLA-C2 regulate human birth weight. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2014; 192:5069-73. [PMID: 24778445 PMCID: PMC4028203 DOI: 10.4049/jimmunol.1400577] [Citation(s) in RCA: 109] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Human birth weight is subject to stabilizing selection; babies born too small or too large are less likely to survive. Particular combinations of maternal/fetal immune system genes are associated with pregnancies where the babies are ≤ 5th birth weight centile, specifically an inhibitory maternal KIR AA genotype with a paternally derived fetal HLA-C2 ligand. We have now analyzed maternal KIR and fetal HLA-C combinations at the opposite end of the birth weight spectrum. Mother/baby pairs (n = 1316) were genotyped for maternal KIR as well as fetal and maternal HLA-C. Presence of a maternal-activating KIR2DS1 gene was associated with increased birth weight in linear or logistic regression analyses of all pregnancies >5th centile (p = 0.005, n = 1316). Effect of KIR2DS1 was most significant in pregnancies where its ligand, HLA-C2, was paternally but not maternally inherited by a fetus (p = 0.005, odds ratio = 2.65). Thus, maternal KIR are more frequently inhibitory with small babies but activating with big babies. At both extremes of birth weight, the KIR associations occur when their HLA-C2 ligand is paternally inherited by a fetus. We conclude that the two polymorphic immune gene systems, KIR and HLA-C, contribute to successful reproduction by maintaining birth weight between two extremes with a clear role for paternal HLA.
Collapse
Affiliation(s)
- Susan E Hiby
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, United Kingdom; Centre for Trophoblast Research, University of Cambridge, Cambridge CB2 1QP, United Kingdom
| | - Richard Apps
- Cancer and Inflammation Program, Laboratory of Experimental Immunology, Leidos Biomedical Research, Inc., Frederick National Laboratory, Frederick, MD 21702; Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02139
| | - Olympe Chazara
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, United Kingdom; Centre for Trophoblast Research, University of Cambridge, Cambridge CB2 1QP, United Kingdom
| | - Lydia E Farrell
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, United Kingdom; Centre for Trophoblast Research, University of Cambridge, Cambridge CB2 1QP, United Kingdom
| | - Per Magnus
- Division of Epidemiology, Norwegian Institute of Public Health, 0403 Oslo, Norway; and
| | - Lill Trogstad
- Division of Infectious Disease Control, Norwegian Institute of Public Health, 0403 Oslo, Norway
| | - Håkon K Gjessing
- Division of Epidemiology, Norwegian Institute of Public Health, 0403 Oslo, Norway; and
| | - Mary Carrington
- Cancer and Inflammation Program, Laboratory of Experimental Immunology, Leidos Biomedical Research, Inc., Frederick National Laboratory, Frederick, MD 21702; Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02139
| | - Ashley Moffett
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, United Kingdom; Centre for Trophoblast Research, University of Cambridge, Cambridge CB2 1QP, United Kingdom;
| |
Collapse
|
233
|
Cole J, Waurich B, Wensch-Dorendorf M, Bickhart D, Swalve H. A genome-wide association study of calf birth weight in Holstein cattle using single nucleotide polymorphisms and phenotypes predicted from auxiliary traits. J Dairy Sci 2014; 97:3156-72. [DOI: 10.3168/jds.2013-7409] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2013] [Accepted: 01/28/2014] [Indexed: 02/04/2023]
|
234
|
Abstract
Knowledge of the genetics of type 2 diabetes mellitus (T2DM) has evolved tremendously over the past few years. Following advances in technology and analytical approaches, collaborative case-control genome-wide association studies have revealed up to 65 loci credibly associated with T2DM. Prospective population studies have demonstrated that aggregated genetic risk scores, so-called because they sum the genetic risk attributed to each locus, can predict incident T2DM among individuals of various age ranges and diverse ethnic backgrounds. With each set of T2DM loci discovered, increasing the number of loci in these scores has improved their predictive ability, although a prediction plateau may already have been reached. The current literature shows that intensive lifestyle interventions are effective for preventing T2DM at any level of genetic risk and might be particularly efficacious among individuals with high genetic susceptibility. By contrast, counselling to inform patients about their personal T2DM genetic risk profiles does not seem to improve motivation or attitudes that lead to positive lifestyle behaviour changes. Future studies should investigate the role of genetics for both T2DM prediction and prevention in young populations in the hope of reducing disease burden for future generations.
Collapse
Affiliation(s)
- Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, 50 Staniford Street, 9th floor, Boston, MA 02114, USA
| | - Jason L Vassy
- Section of General Internal Medicine, VA Boston Healthcare System, Harvard Medical School, 50 Staniford Street, 9th floor, Boston, MA 02114, USA
| | - James B Meigs
- General Medicine Division, Massachusetts General Hospital, Harvard Medical School, 50 Staniford Street, 9th floor, Boston, MA 02114, USA
| |
Collapse
|
235
|
Schenk ER, Ridgeway ME, Park MA, Leng F, Fernandez-Lima F. Isomerization kinetics of AT hook decapeptide solution structures. Anal Chem 2014; 86:1210-4. [PMID: 24364733 PMCID: PMC3935383 DOI: 10.1021/ac403386q] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
The mammalian high mobility group protein HMGA2 contains three DNA binding motifs associated with many physiological functions including oncogenesis, obesity, stem cell youth, human height, and human intelligence. In the present paper, trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) has been utilized to study the conformational dynamics of the third DNA binding motif using the "AT hook" decapeptide unit (Lys(1)-Arg(2)-Prol(3)-Arg(4)-Gly(5)-Arg(6)-Prol(7)-Arg(8)-Lys(9)-Trp(10), ATHP) as a function of the solvent state. Solvent state distributions were preserved during electrospray ion formation, and multiple IMS bands were identified for the [M + 2H](2+) and for the [M + 3H](3+) charge states. Conformational isomer interconversion rates were measured as a function of the trapping time for the [M + 2H](2+) and [M + 3H](3+) charge states. Candidate structures were proposed for all IMS bands observed. Protonation site, proline residue conformation, and side chain orientations were identified as the main motifs governing the conformational interconversion processes. Conformational dynamics from the solvent state distribution to the gas-phase "de-solvated" state distribution demonstrated that ATHP is "structured", and relative abundances are associated with the relative stability between the proposed conformers. The most stable ATHP [M + 2H](2+) conformation at the "de-solvated" state corresponds to the AT hook motif observed in AT-rich DNA regions.
Collapse
Affiliation(s)
- Emily R. Schenk
- Department of Chemistry and Biochemistry, Florida International University, Miami, FL 33199, USA
| | | | - Melvin A. Park
- Bruker Daltonics, Inc., Billerica, Massachusetts 01821, USA
| | - Fenfei Leng
- Department of Chemistry and Biochemistry, Florida International University, Miami, FL 33199, USA
| | - Francisco Fernandez-Lima
- Department of Chemistry and Biochemistry, Florida International University, Miami, FL 33199, USA
| |
Collapse
|
236
|
Sebert S, Salonurmi T, Keinänen-Kiukaanniemi S, Savolainen M, Herzig KH, Symonds ME, Järvelin MR. Programming effects of FTO in the development of obesity. Acta Physiol (Oxf) 2014; 210:58-69. [PMID: 24219661 DOI: 10.1111/apha.12196] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2013] [Revised: 09/10/2013] [Accepted: 11/07/2013] [Indexed: 12/18/2022]
Abstract
It is becoming increasingly recognized that early-life nutritional, metabolic and environmental factors can have a long-term impact on the early onset of obesity, type 2 diabetes and cardiovascular diseases. Numerous experimental and epidemiological observations support the concept that an individual's response to their adult lifestyle and nutritional environment depends not only on their genetic susceptibility but also on their previous early-life experiences. The current research challenge is to determine the primary pathways contributing to 'non- or epi-genetic' causes of excess adult weight gain and adiposity. Evidence from the fields of genetic epidemiology, life course modelling and diet-induced foetal programming all support a role for the FTO gene in this complex biological interaction. It may provide a missing link in the developmental regulation of energy metabolism. Our review therefore considers the role of the FTO gene in the early-life determination of body weight, body composition and energy balance. We will summarize current knowledge on FTO biology combining human genetic epidemiology, molecular models and findings from animal studies. Notably, we will focus on the role of FTO in energy balance in humans, the importance of FTO polymorphisms in childhood growth and the impact of foetal nutrition. Ultimately, we propose a new hypothesis for future research designed to understand the role of FTO in setting gene expression in metabolically active tissues.
Collapse
Affiliation(s)
- S. Sebert
- Faculty of Medicine; Institute of Health Sciences; Centre For Life-Course Epidemiology; University of Oulu; Oulu Finland
- Biocenter Oulu; University of Oulu; Oulu Finland
| | - T. Salonurmi
- Biocenter Oulu; University of Oulu; Oulu Finland
- Institute of Clinical Medicine; Department of Internal Medicine, and Medical Research Centre; University of Oulu; Oulu Finland
| | - S. Keinänen-Kiukaanniemi
- Faculty of Medicine; Institute of Health Sciences; Centre For Life-Course Epidemiology; University of Oulu; Oulu Finland
| | - M. Savolainen
- Biocenter Oulu; University of Oulu; Oulu Finland
- Institute of Clinical Medicine; Department of Internal Medicine, and Medical Research Centre; University of Oulu; Oulu Finland
| | - K.-H. Herzig
- Biocenter Oulu; University of Oulu; Oulu Finland
- Institute of Biomedicine; Department of Physiology; University of Oulu; Oulu Finland
| | - M. E. Symonds
- Early Life Nutrition Research Unit; Academic Division of Child Health, Obstetrics & Gynaecology; School of Medicine; Queen's Medical Centre; University Hospital; The University of Nottingham; Nottingham UK
| | - M.-R. Järvelin
- Faculty of Medicine; Institute of Health Sciences; Centre For Life-Course Epidemiology; University of Oulu; Oulu Finland
- Biocenter Oulu; University of Oulu; Oulu Finland
- Department of Epidemiology and Biostatistics; MRC Health Protection Agency (HPA) Centre for Environment and Health; School of Public Health; Imperial College; London UK
- Unit of Primary Care; Oulu University Hospital; Oulu Finland
- Department of Children and Young People and Families; National Institute for Health and Welfare; Oulu Finland
| |
Collapse
|
237
|
Estampador AC, Franks PW. Genetic and epigenetic catalysts in early-life programming of adult cardiometabolic disorders. Diabetes Metab Syndr Obes 2014; 7:575-86. [PMID: 25489250 PMCID: PMC4257022 DOI: 10.2147/dmso.s51433] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Evidence has emerged across the past few decades that the lifetime risk of developing morbidities like type 2 diabetes, obesity, and cardiovascular disease may be influenced by exposures that occur in utero and in childhood. Developmental abnormalities are known to occur at various stages in fetal growth. Epidemiological and mechanistic studies have sought to delineate developmental processes and plausible risk factors influencing pregnancy outcomes and later health. Whether these observations reflect causal processes or are confounded by genetic and social factors remains unclear, although animal (and some human) studies suggest that epigenetic programming events may be involved. Regardless of the causal basis to observations of early-life risk factors and later disease risk, the fact that such associations exist and that they are of a fairly large magnitude justifies further research around this topic. Furthermore, additional information is needed to substantiate public health guidelines on lifestyle behaviors during pregnancy to improve infant health outcomes. Indeed, lifestyle intervention clinical trials in pregnancy are now coming online, where materials and data are being collected that should facilitate understanding of the causal nature of intrauterine exposures related with gestational weight gain, such as elevated maternal blood glucose concentrations. In this review, we provide an overview of these concepts.
Collapse
Affiliation(s)
- Angela C Estampador
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö, Sweden
- Department of Endocrinology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Paul W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö, Sweden
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA
- Correspondence: Paul W Franks, Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, CRC, Building 91, Level 10, Jan Waldenströms Gata 35, Skåne University Hospital Malmö, SE-205 02, Malmö, Sweden, Tel +46 40 391 149, Fax +46 40 391 222, Email
| |
Collapse
|
238
|
Marullo L, El-Sayed Moustafa JS, Prokopenko I. Insights into the genetic susceptibility to type 2 diabetes from genome-wide association studies of glycaemic traits. Curr Diab Rep 2014; 14:551. [PMID: 25344220 DOI: 10.1007/s11892-014-0551-8] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Over the past 8 years, the genetics of complex traits have benefited from an unprecedented advancement in the identification of common variant loci for diseases such as type 2 diabetes (T2D). The ability to undertake genome-wide association studies in large population-based samples for quantitative glycaemic traits has permitted us to explore the hypothesis that models arising from studies in non-diabetic individuals may reflect mechanisms involved in the pathogenesis of diabetes. Amongst 88 T2D risk and 72 glycaemic trait loci, only 29 are shared and show disproportionate magnitudes of phenotypic effects. Important mechanistic insights have been gained regarding the physiological role of T2D loci in disease predisposition through the elucidation of their contribution to glycaemic trait variability. Further investigation is warranted to define causal variants within these loci, including functional characterisation of associated variants, to dissect their role in disease mechanisms and to enable clinical translation.
Collapse
Affiliation(s)
- Letizia Marullo
- Department of Life Sciences and Biotechnology, Genetic Section, University of Ferrara, Via L. Borsari 46, 44121, Ferrara, Italy
| | | | | |
Collapse
|
239
|
Abstract
Single nucleotide polymorphisms (SNPs) that cluster in the first intron of fat mass and obesity associated (FTO) gene are associated obesity traits in genome-wide association studies. The minor allele increases BMI by 0.39 kg/m(2) (or 1,130 g in body weight) and risk of obesity by 1.20-fold. This association has been confirmed across age groups and populations of diverse ancestry; the largest effect is seen in young adulthood. The effect of FTO SNPs on obesity traits in populations of African and Asian ancestry is similar or somewhat smaller than in European ancestry populations. However, the BMI-increasing allele in FTO is substantially less prevalent in populations with non-European ancestry. FTO SNPs do not influence physical activity levels; yet, in physically active individuals, FTO's effect on obesity susceptibility is attenuated by approximately 30%. Evidence from epidemiological and functional studies suggests that FTO confers an increased risk of obesity by subtly changing food intake and preference. Moreover, emerging data suggest a role for FTO in nutrient sensing, regulation of mRNA translation and general growth. In this Review, we discuss the genetic epidemiology of FTO and discuss how its complex biology might link to the regulation of body weight.
Collapse
Affiliation(s)
- Ruth J F Loos
- The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1003, New York, NY 10029-6574, USA
| | - Giles S H Yeo
- MRC Metabolic Diseases Unit, University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| |
Collapse
|
240
|
Tyrrell JS, Yaghootkar H, Freathy RM, Hattersley AT, Frayling TM. Parental diabetes and birthweight in 236 030 individuals in the UK biobank study. Int J Epidemiol 2013; 42:1714-23. [PMID: 24336895 PMCID: PMC3887570 DOI: 10.1093/ije/dyt220] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background The UK Biobank study provides a unique opportunity to study the causes and consequences of disease. We aimed to use the UK Biobank data to study the well-established, but poorly understood, association between low birthweight and type 2 diabetes. Methods We used logistic regression to calculate the odds ratio for participants’ risk of type 2 diabetes given a one standard deviation increase in birthweight. To test for an association between parental diabetes and birthweight, we performed linear regression of self-reported parental diabetes status against birthweight. We performed path and mediation analyses to test the hypothesis that birthweight partly mediates the association between parental diabetes and participant type 2 diabetes status. Results Of the UK Biobank participants, 277 261 reported their birthweight. Of 257 715 individuals of White ethnicity and singleton pregnancies, 6576 had type 2 diabetes, 19 478 reported maternal diabetes (but not paternal), 20 057 reported paternal diabetes (but not maternal) and 2754 participants reported both parents as having diabetes. Lower birthweight was associated with type 2 diabetes in the UK Biobank participants. A one kilogram increase in birthweight was associated with a lower risk of type 2 diabetes (odds ratio: 0.74; 95% CI: 0.71, 0.76; P = 2 × 10−57). Paternal diabetes was associated with lower birthweight (45 g lower; 95% CI: 36, 54; P = 2 × 10−23) relative to individuals with no parental diabetes. Maternal diabetes was associated with higher birthweight (59 g increase; 95% CI: 50, 68; P = 3 × 10−37). Participants’ lower birthweight was a mediator of the association between reported paternal diabetes and participants’ type 2 diabetes status, explaining 1.1% of the association, and participants’ higher birthweight was a mediator of the association between reported maternal diabetes and participants’ type 2 diabetes status, explaining 1.2% of the association. Conclusions Data from the UK Biobank provides the strongest evidence by far that paternal diabetes is associated with lower birthweight, whereas maternal diabetes is associated with increased birthweight. Our findings with paternal diabetes are consistent with a role for the same genetic factors influencing foetal growth and type 2 diabetes.
Collapse
Affiliation(s)
- Jessica S Tyrrell
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, UK, Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK and Molecular Genetics, Wonford Building, University of Exeter Medical School, Exeter, UK
| | | | | | | | | |
Collapse
|
241
|
Longitudinal follow-up of the relationship between dietary intake and growth and development in the Lifeways cross-generation cohort study 2001-2013. Proc Nutr Soc 2013; 73:118-31. [PMID: 24300176 DOI: 10.1017/s002966511300373x] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
In this paper we will review evidence on the early life and familial influences on childhood growth and development, with particular reference to the Lifeways cross-generation cohort study in the Republic of Ireland. The Lifeways cross-generation cohort study was established in 2001-2013 through two maternity hospitals in the Republic of Ireland and was one of many new cohort studies established worldwide in the millennium period. Mothers were recruited at first booking visit, completing a self-administered questionnaire, which included a 147 item semi-quantitative FFQ. Longitudinal follow-up is ongoing in 2013, with linkage data to hospital and general practice records and examination of children when aged 5 and 9 years. The study is one of very few containing data on grandparents of both lineages with at least one grandparent recruited at baseline. There have been consistent associations between parental and grandparental health status characteristics and children's outcomes, including infant birth-weight, BMI when child was aged 5 years and childhood wheeze or asthma when child was aged 3 and aged 5 years. In conclusion, empirical evidence to date shows consistent familial and cross-generational patterns, particularly in the maternal line.
Collapse
|
242
|
Fatemifar G, Hoggart CJ, Paternoster L, Kemp JP, Prokopenko I, Horikoshi M, Wright VJ, Tobias JH, Richmond S, Zhurov AI, Toma AM, Pouta A, Taanila A, Sipila K, Lähdesmäki R, Pillas D, Geller F, Feenstra B, Melbye M, Nohr EA, Ring SM, St Pourcain B, Timpson NJ, Davey Smith G, Jarvelin MR, Evans DM. Genome-wide association study of primary tooth eruption identifies pleiotropic loci associated with height and craniofacial distances. Hum Mol Genet 2013; 22:3807-17. [PMID: 23704328 PMCID: PMC3749866 DOI: 10.1093/hmg/ddt231] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2013] [Revised: 05/01/2013] [Accepted: 05/17/2013] [Indexed: 01/11/2023] Open
Abstract
Twin and family studies indicate that the timing of primary tooth eruption is highly heritable, with estimates typically exceeding 80%. To identify variants involved in primary tooth eruption, we performed a population-based genome-wide association study of 'age at first tooth' and 'number of teeth' using 5998 and 6609 individuals, respectively, from the Avon Longitudinal Study of Parents and Children (ALSPAC) and 5403 individuals from the 1966 Northern Finland Birth Cohort (NFBC1966). We tested 2 446 724 SNPs imputed in both studies. Analyses were controlled for the effect of gestational age, sex and age of measurement. Results from the two studies were combined using fixed effects inverse variance meta-analysis. We identified a total of 15 independent loci, with 10 loci reaching genome-wide significance (P < 5 × 10(-8)) for 'age at first tooth' and 11 loci for 'number of teeth'. Together, these associations explain 6.06% of the variation in 'age of first tooth' and 4.76% of the variation in 'number of teeth'. The identified loci included eight previously unidentified loci, some containing genes known to play a role in tooth and other developmental pathways, including an SNP in the protein-coding region of BMP4 (rs17563, P = 9.080 × 10(-17)). Three of these loci, containing the genes HMGA2, AJUBA and ADK, also showed evidence of association with craniofacial distances, particularly those indexing facial width. Our results suggest that the genome-wide association approach is a powerful strategy for detecting variants involved in tooth eruption, and potentially craniofacial growth and more generally organ development.
Collapse
Affiliation(s)
- Ghazaleh Fatemifar
- MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, Lower Maudlin Street, Bristol, UK.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
243
|
Urbanek M, Hayes MG, Armstrong LL, Morrison J, Lowe LP, Badon SE, Scheftner D, Pluzhnikov A, Levine D, Laurie CC, McHugh C, Ackerman CM, Mirel DB, Doheny KF, Guo C, Scholtens DM, Dyer AR, Metzger BE, Reddy TE, Cox NJ, Lowe WL. The chromosome 3q25 genomic region is associated with measures of adiposity in newborns in a multi-ethnic genome-wide association study. Hum Mol Genet 2013; 22:3583-96. [PMID: 23575227 PMCID: PMC3736865 DOI: 10.1093/hmg/ddt168] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2012] [Accepted: 04/05/2013] [Indexed: 02/04/2023] Open
Abstract
Newborns characterized as large and small for gestational age are at risk for increased mortality and morbidity during the first year of life as well as for obesity and dysglycemia as children and adults. The intrauterine environment and fetal genes contribute to the fetal size at birth. To define the genetic architecture underlying the newborn size, we performed a genome-wide association study (GWAS) in 4281 newborns in four ethnic groups from the Hyperglycemia and Adverse Pregnancy Outcome Study. We tested for association with newborn anthropometric traits (birth length, head circumference, birth weight, percent fat mass and sum of skinfolds) and newborn metabolic traits (cord glucose and C-peptide) under three models. Model 1 adjusted for field center, ancestry, neonatal gender, gestational age at delivery, parity, maternal age at oral glucose tolerance test (OGTT); Model 2 adjusted for Model 1 covariates, maternal body mass index (BMI) at OGTT, maternal height at OGTT, maternal mean arterial pressure at OGTT, maternal smoking and drinking; Model 3 adjusted for Model 2 covariates, maternal glucose and C-peptide at OGTT. Strong evidence for association was observed with measures of newborn adiposity (sum of skinfolds model 3 Z-score 7.356, P = 1.90×10⁻¹³, and to a lesser degree fat mass and birth weight) and a region on Chr3q25.31 mapping between CCNL and LEKR1. These findings were replicated in an independent cohort of 2296 newborns. This region has previously been shown to be associated with birth weight in Europeans. The current study suggests that association of this locus with birth weight is secondary to an effect on fat as opposed to lean body mass.
Collapse
Affiliation(s)
- Margrit Urbanek
- Division on Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
244
|
Hollegaard MV, Grauholm J, Nielsen R, Grove J, Mandrup S, Hougaard DM. Archived neonatal dried blood spot samples can be used for accurate whole genome and exome-targeted next-generation sequencing. Mol Genet Metab 2013; 110:65-72. [PMID: 23830478 DOI: 10.1016/j.ymgme.2013.06.004] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2013] [Revised: 06/03/2013] [Accepted: 06/04/2013] [Indexed: 11/23/2022]
Abstract
Dried blood spot samples (DBSS) have been collected and stored for decades as part of newborn screening programmes worldwide. Representing almost an entire population under a certain age and collected with virtually no bias, the Newborn Screening Biobanks are of immense value in medical studies, for example, to examine the genetics of various disorders. We have previously demonstrated that DNA extracted from a fraction (2×3.2mm discs) of an archived DBSS can be whole genome amplified (wgaDNA) and used for accurate array genotyping. However, until now, it has been uncertain whether wgaDNA from DBSS can be used for accurate whole genome sequencing (WGS) and exome sequencing (WES). This study examined two individuals represented by three different types of samples each: whole-blood (reference samples), 3-year-old DBSS spotted with reference material (refDBSS), and 27- to 29-year-old archived neonatal DBSS (neoDBSS) stored at -20°C in the Danish Newborn Screening Biobank. The reference samples were genotyped using an Illumina Omni2.5M array, and all samples were sequenced on a HighSeq2000 Paired-End flow cell. First, we compared the array single nucleotide polymorphism (SNP) genotype data to the single nucleotide variation (SNV) calls from the WGS and WES SNV calls. We also compared the WGS and WES reference sample SNV calls to the DBSS SNV calls. The overall performance of the archived DBSS was similar to the whole blood reference sample. Plotting the error rates relative to coverage revealed that the error rates of DBSS were similar to that of their reference samples. SNVs called with a coverage<×8 had error rates between 1.5 and 35%, whereas the error rates of SNVs called with a coverage≥8 were <1.5%. In conclusion, the wgaDNA amplified from both new and old neonatal DBSS perform as well as their whole-blood reference samples with regards to error rates, strongly indicating that neonatal DBSS collected shortly after birth and stored for decades comprise an excellent resource for NGS studies of disease.
Collapse
Affiliation(s)
- Mads Vilhelm Hollegaard
- Department of Clinical Biochemistry, Immunology and Genetics, Statens Serum Institut, Artillerivej, Copenhagen, Denmark.
| | | | | | | | | | | |
Collapse
|
245
|
Yaghootkar H, Frayling TM. Recent progress in the use of genetics to understand links between type 2 diabetes and related metabolic traits. Genome Biol 2013; 14:203. [PMID: 23548046 PMCID: PMC3663087 DOI: 10.1186/gb-2013-14-3-203] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Genome-wide association studies have identified genetic variants associated with increased risk of type 2 diabetes. The aim of this review is to highlight some of the insights into the mechanism underlying type 2 diabetes provided by genetic association studies.
Collapse
|
246
|
Gurtan AM, Sharp PA. The role of miRNAs in regulating gene expression networks. J Mol Biol 2013; 425:3582-600. [PMID: 23500488 DOI: 10.1016/j.jmb.2013.03.007] [Citation(s) in RCA: 318] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2013] [Revised: 02/28/2013] [Accepted: 03/04/2013] [Indexed: 01/03/2023]
Abstract
MicroRNAs (miRNAs) are key regulators of gene expression. They are conserved across species, expressed across cell types, and active against a large proportion of the transcriptome. The sequence-complementary mechanism of miRNA activity exploits combinatorial diversity, a property conducive to network-wide regulation of gene expression, and functional evidence supporting this hypothesized systems-level role has steadily begun to accumulate. The emerging models are exciting and will yield deep insight into the regulatory architecture of biology. However, because of the technical challenges facing the network-based study of miRNAs, many gaps remain. Here, we review mammalian miRNAs by describing recent advances in understanding their molecular activity and network-wide function.
Collapse
Affiliation(s)
- Allan M Gurtan
- David H. Koch Institute for Integrative Cancer Research at MIT, Cambridge, MA 02139, USA.
| | | |
Collapse
|