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Abstract
Menopause nomenclature varies in the scholarly literature making synthesis and interpretation of research findings difficult. Therefore, the present study aimed to review and discuss critical developments in menopause nomenclature; determine the level of heterogeneity amongst menopause definitions and compare them with the Stages of Reproductive Aging Workshop criteria. Definitions/criteria used to characterise premenopausal and postmenopausal status were extracted from 210 studies and 128 of these studies were included in the final analyses. The main findings were that 39.84% of included studies were consistent with STRAW classification of premenopause, whereas 70.31% were consistent with STRAW classification of postmenopause. Surprisingly, major inconsistencies relating to premenopause definition were due to a total lack of reporting of any definitions/criteria for premenopause (39.84% of studies). In contrast, only 20.31% did not report definitions/criteria for postmenopause. The present findings indicate that there is a significant amount of heterogeneity associated with the definition of premenopause, compared with postmenopause. We propose three key suggestions/recommendations, which can be distilled from these findings. Firstly, premenopause should be transparently operationalised and reported. Secondly, as a minimum requirement, regular menstruation should be defined as the number of menstrual cycles in a period of at least 3 months. Finally, the utility of introducing normative age-ranges as supplementary criterion for defining stages of reproductive ageing should be considered. The use of consistent terminology in research will enhance our capacity to compare results from different studies and more effectively investigate issues related to women's health and ageing.
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Affiliation(s)
- Ananthan Ambikairajah
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, ACT, 2601, Australia.
- Discipline of Psychology, Faculty of Health, University of Canberra, Building 12, 11 Kirinari Street, Canberra, ACT, 2617, Australia.
| | - Erin Walsh
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, ACT, 2601, Australia
| | - Nicolas Cherbuin
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, ACT, 2601, Australia
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Dvornyk V, Churnosov M, Deng HW. Polymorphisms of the TNF, LTA, and TNFRSF1B genes are associated with onsets of menarche and menopause in US women of European ancestry. Ann Hum Biol 2021; 48:400-405. [PMID: 34595982 DOI: 10.1080/03014460.2021.1987519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
BACKGROUND The TNF, LTA and TNFRSF1B genes have been implicated in various traits related to menarche and menopause. AIM To analyse the TNF, LTA and TNFRSF1B genes for their association with ages at menarche (AM) and natural menopause (ANM). SUBJECTS AND METHODS The study sample consisted of 314 unrelated females of European ancestry. Twenty SNPs located in and near the genes were analysed using various statistical methods. In addition, the functional significance of the loci associated with AM and ANM was analysed in silico. RESULTS Locus rs2229094 of the LTA gene was associated with AM according to the additive (β = -0.295, pperm = 0.016) and recessive (β = -0.940, pperm = 0.016) genetic models. Haplotype GG rs1148459-rs590368 of the TNFRSF1B gene was associated with AM (β = 0.307, pperm = 0.023). Haplotype GCA rs2844484-rs2229094-rs1799964 was associated with ANM after adjustment for covariates (β = -1.020, pperm = 0.035). All studied loci were associated with ANM after adjustment for breastfeeding (raw p < 0.05). In addition, eight of the most significant models of interlocus interactions were associated with AM and five with ANM. CONCLUSION The results of the present study suggest that the TNF, LTA and TNFRSF1B genes are associated with AM and ANM.
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Affiliation(s)
- Volodymyr Dvornyk
- Department of Life Sciences, College of Science and General Studies, Alfaisal University, Riyadh, Kingdom of Saudi Arabia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State University, Belgorod, Russia
| | - Hong-Wen Deng
- Deming Department of Medicine, School of Medicine, Tulane Centre of Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, USA
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Adolescent Sport Participation and Age at Menarche in Relation to Midlife Body Composition, Bone Mineral Density, Fitness, and Physical Activity. J Clin Med 2020; 9:jcm9123797. [PMID: 33255351 PMCID: PMC7760316 DOI: 10.3390/jcm9123797] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/19/2020] [Accepted: 11/21/2020] [Indexed: 12/23/2022] Open
Abstract
This study aimed to investigate the associations of competitive sport participation in adolescence and age at menarche (AAM) with body composition, femoral neck bone mineral density (BMD), physical performance, and physical activity (PA) in middle-aged women. 1098 women aged 47–55 years formed the sample of this retrospective study. Participants self-reported their PA level at age 13–16 years and AAM. The protocol also included dual-energy X-ray absorptiometry, physical performance tests, and accelerometer-measured PA. Participants were divided into three groups according to their PA level at the age of 13–16 (no exercise, regular PA, and competitive sport) and according to their AAM (≤12, 13, and ≥14 years). After adjusting for potential confounding factors, participation in competitive sport at age 13–16 was associated with higher midlife lean mass and BMD, and better physical performance compared to groups with no exercise or regular PA. Individuals with AAM ≥ 14 years had lower midlife BMI and fat mass than participants in the other AAM groups and pre- and perimenopausal women with AAM ≥ 14 years had lower BMD than those with AAM ≤ 12. The findings indicate that participation in competitive sport in adolescence is associated with healthier body composition, higher BMD, and better physical performance in midlife, but BMD might be impaired if menarche occurs late.
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Ambikairajah A, Walsh E, Tabatabaei-Jafari H, Cherbuin N. Fat mass changes during menopause: a metaanalysis. Am J Obstet Gynecol 2019; 221:393-409.e50. [PMID: 31034807 DOI: 10.1016/j.ajog.2019.04.023] [Citation(s) in RCA: 134] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 03/15/2019] [Accepted: 04/19/2019] [Indexed: 02/08/2023]
Abstract
OBJECTIVE Data: Fat mass has been shown to increase in aging women; however, the extent to which menopausal status mediates these changes remains unclear. The purpose of this review was to determine (1) how fat mass differs in quantity and distribution between premenopausal and postmenopausal women, (2) whether and how age and/or menopausal status moderates any observed differences, and (3) which type of fat mass measure is best suited to the detection of differences in fat mass between groups. STUDY This review with metaanalyses is reported according to Metaanalysis of Observational Studies in Epidemiology guidelines. STUDY APPRAISAL AND SYNTHESIS METHODS Studies (published up to May 2018) were identified via PubMed to provide fat mass measures in premenopausal and postmenopausal women. We included 201 cross-sectional studies in the metaanalysis, which provided a combined sample size of 1,049,919 individuals and consisted of 478,734 premenopausal women and 571,185 postmenopausal women. Eleven longitudinal studies were included in the metaanalyses, which provided a combined sample size of 2472 women who were premenopausal at baseline and postmenopausal at follow up. RESULTS The main findings of this review were that fat mass significantly increased between premenopausal and postmenopausal women across most measures, which included body mass index (1.14 kg/m2; 95% confidence interval, 0.95-1.32 kg/m2), bodyweight (1 kg; 95% confidence interval, 0.44-1.57 kg), body fat percentage (2.88%; 95% confidence interval, 2.13-3.63%), waist circumference (4.63 cm; 95% confidence interval, 3.90-5.35 cm), hip circumference (2.01 cm; 95% confidence interval, 1.36-2.65 cm), waist-hip ratio (0.04; 95% confidence interval, 0.03-0.05), visceral fat (26.90 cm2; 95% confidence interval, 13.12-40.68), and trunk fat percentage (5.49%; 95% confidence interval, 3.91-7.06 cm2). The exception was total leg fat percentage, which significantly decreased (-3.19%; 95% confidence interval, -5.98 to -0.41%). No interactive effects were observed between menopausal status and age across all fat mass measures. CONCLUSION The change in fat mass quantity between premenopausal and postmenopausal women was attributable predominantly to increasing age; menopause had no significant additional influence. However, the decrease in total leg fat percentage and increase in measures of central fat are indicative of a possible change in fat mass distribution after menopause. These changes are likely to, at least in part, be due to hormonal shifts that occur during midlife when women have a higher androgen (ie, testosterone) to estradiol ratio after menopause, which has been linked to enhanced central adiposity deposition. Evidently, these findings suggest attention should be paid to the accumulation of central fat after menopause, whereas increases in total fat mass should be monitored consistently across the lifespan.
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Fernández-Rhodes L, Malinowski JR, Wang Y, Tao R, Pankratz N, Jeff JM, Yoneyama S, Carty CL, Setiawan VW, Le Marchand L, Haiman C, Corbett S, Demerath E, Heiss G, Gross M, Buzkova P, Crawford DC, Hunt SC, Rao DC, Schwander K, Chakravarti A, Gottesman O, Abul-Husn NS, Bottinger EP, Loos RJF, Raffel LJ, Yao J, Guo X, Bielinski SJ, Rotter JI, Vaidya D, Chen YDI, Castañeda SF, Daviglus M, Kaplan R, Talavera GA, Ryckman KK, Peters U, Ambite JL, Buyske S, Hindorff L, Kooperberg C, Matise T, Franceschini N, North KE. The genetic underpinnings of variation in ages at menarche and natural menopause among women from the multi-ethnic Population Architecture using Genomics and Epidemiology (PAGE) Study: A trans-ethnic meta-analysis. PLoS One 2018; 13:e0200486. [PMID: 30044860 PMCID: PMC6059436 DOI: 10.1371/journal.pone.0200486] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Accepted: 06/27/2018] [Indexed: 11/18/2022] Open
Abstract
Current knowledge of the genetic architecture of key reproductive events across the female life course is largely based on association studies of European descent women. The relevance of known loci for age at menarche (AAM) and age at natural menopause (ANM) in diverse populations remains unclear. We investigated 32 AAM and 14 ANM previously-identified loci and sought to identify novel loci in a trans-ethnic array-wide study of 196,483 SNPs on the MetaboChip (Illumina, Inc.). A total of 45,364 women of diverse ancestries (African, Hispanic/Latina, Asian American and American Indian/Alaskan Native) in the Population Architecture using Genomics and Epidemiology (PAGE) Study were included in cross-sectional analyses of AAM and ANM. Within each study we conducted a linear regression of SNP associations with self-reported or medical record-derived AAM or ANM (in years), adjusting for birth year, population stratification, and center/region, as appropriate, and meta-analyzed results across studies using multiple meta-analytic techniques. For both AAM and ANM, we observed more directionally consistent associations with the previously reported risk alleles than expected by chance (p-valuesbinomial≤0.01). Eight densely genotyped reproductive loci generalized significantly to at least one non-European population. We identified one trans-ethnic array-wide SNP association with AAM and two significant associations with ANM, which have not been described previously. Additionally, we observed evidence of independent secondary signals at three of six AAM trans-ethnic loci. Our findings support the transferability of reproductive trait loci discovered in European women to women of other race/ethnicities and indicate the presence of additional trans-ethnic associations both at both novel and established loci. These findings suggest the benefit of including diverse populations in future studies of the genetic architecture of female growth and development.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- * E-mail:
| | | | - Yujie Wang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Janina M. Jeff
- Genotyping Arrays Division, Illumina, Inc., San Diego, California, United States of America
| | - Sachiko Yoneyama
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Cara L. Carty
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - V. Wendy Setiawan
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Christopher Haiman
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Steven Corbett
- Kansas Health Institute, Topeka, Kansas, United States of America
| | - Ellen Demerath
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Gerardo Heiss
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Petra Buzkova
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington, United States of America
| | - Dana C. Crawford
- Institute for Computational Biology, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Steven C. Hunt
- Department of Genetic Medicine, Weill Cornell Medical College in Qatar, Doha, Qatar
| | - D. C. Rao
- Division of Biostatistics, Washington University in St. Louis, St. Louis, Michigan, United States of America
| | - Karen Schwander
- Division of Biostatistics, Washington University in St. Louis, St. Louis, Michigan, United States of America
| | - Aravinda Chakravarti
- Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Omri Gottesman
- Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Noura S. Abul-Husn
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Erwin P. Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Leslie J. Raffel
- Division of Genetic and Genomic Medicine, University of California—Irvine, Irvine, California, United States of America
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Suzette J. Bielinski
- College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Dhananjay Vaidya
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Sheila F. Castañeda
- South Bay Latino Research Center, Graduate School of Public Health, San Diego State University, San Diego, California, United States of America
| | - Martha Daviglus
- Institute of Minority Health Research, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Gregory A. Talavera
- South Bay Latino Research Center, Graduate School of Public Health, San Diego State University, San Diego, California, United States of America
| | - Kelli K. Ryckman
- Departments of Epidemiology and Pediatrics, University of Iowa, Iowa City, Iowa, United States of America
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Jose Luis Ambite
- Information Sciences Institute, University of Southern California, Marina del Rey, California, United States of America
| | - Steven Buyske
- Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Lucia Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Tara Matise
- Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kari E. North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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Dall GV, Britt KL. Estrogen Effects on the Mammary Gland in Early and Late Life and Breast Cancer Risk. Front Oncol 2017; 7:110. [PMID: 28603694 PMCID: PMC5445118 DOI: 10.3389/fonc.2017.00110] [Citation(s) in RCA: 87] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 05/10/2017] [Indexed: 12/16/2022] Open
Abstract
A woman has an increased risk of breast cancer if her lifelong estrogen exposure is increased due to an early menarche, a late menopause, and/or an absence of childbearing. For decades, it was presumed that the number of years of exposure drove the increased risk, however, recent epidemiological data have shown that early life exposure (young menarche) has a more significant effect on cancer risk than late menopause. Thus, rather than the overall exposure it seems that the timing of hormone exposure plays a major role in defining breast cancer risk. In support of this, it is also known that aberrant hormonal exposure prior to puberty can also increase breast cancer risk, yet the elevated estrogen levels during pregnancy decrease breast cancer risk. This suggests that the effects of estrogen on the mammary gland/breast are age-dependent. In this review article, we will discuss the existing epidemiological data linking hormone exposure and estrogen receptor-positive breast cancer risk including menarche, menopause, parity, and aberrant environmental hormone exposure. We will discuss the predominantly rodent generated experimental data that confirm the association with hormone exposure and breast cancer risk, confirming its use as a model system. We will review the work that has been done attempting to define the direct effects of estrogen on the breast, which are beginning to reveal the mechanism of increased cancer risk. We will then conclude with our views on the most pertinent questions to be addressed experimentally in order to explore the relationship between age, estrogen exposure, and breast cancer risk.
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Affiliation(s)
| | - Kara Louise Britt
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- The Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
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Wang L, Oehlers SH, Espenschied ST, Rawls JF, Tobin DM, Ko DC. CPAG: software for leveraging pleiotropy in GWAS to reveal similarity between human traits links plasma fatty acids and intestinal inflammation. Genome Biol 2015; 16:190. [PMID: 26374098 PMCID: PMC4570686 DOI: 10.1186/s13059-015-0722-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Accepted: 07/09/2015] [Indexed: 12/31/2022] Open
Abstract
Meta-analyses of genome-wide association studies (GWAS) have demonstrated that the same genetic variants can be associated with multiple diseases and other complex traits. We present software called CPAG (Cross-Phenotype Analysis of GWAS) to look for similarities between 700 traits, build trees with informative clusters, and highlight underlying pathways. Clusters are consistent with pre-defined groups and literature-based validation but also reveal novel connections. We report similarity between plasma palmitoleic acid and Crohn's disease and find that specific fatty acids exacerbate enterocolitis in zebrafish. CPAG will become increasingly powerful as more genetic variants are uncovered, leading to a deeper understanding of complex traits. CPAG is freely available at www.sourceforge.net/projects/CPAG/.
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Affiliation(s)
- Liuyang Wang
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC, 27710, USA.
| | - Stefan H Oehlers
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC, 27710, USA.
| | - Scott T Espenschied
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC, 27710, USA.
| | - John F Rawls
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC, 27710, USA.
| | - David M Tobin
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC, 27710, USA.
| | - Dennis C Ko
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC, 27710, USA. .,Department of Medicine and the Center for Human Genome Variation, School of Medicine, Duke University, Durham, NC, 27710, USA.
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Jelenkovic A, Rebato E. Association of maternal menarcheal age with anthropometric dimensions and blood pressure in children from Greater Bilbao. Ann Hum Biol 2015; 43:430-7. [PMID: 26243478 DOI: 10.3109/03014460.2015.1069892] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND Earlier menarche has been related to shorter height and greater obesity-related anthropometric dimensions and blood pressure in women. Boys and girls with earlier maternal menarcheal age (MMA) have shown greater height and body mass index (BMI) in childhood. AIM To analyse associations of menarcheal age with their own and their children's anthropometric dimensions and blood pressure. SUBJECTS AND METHODS The sample consisted of 493 women and their children (aged 2-19 years) from Greater Bilbao (Basque Country, Spain). For both generations there is information on 19 anthropometric dimensions, blood pressure and socio-demographic characteristics. Linear regressions adjusted for different covariates were used to analyse the associations. RESULTS Menarcheal age in women showed the greatest positive associations with iliospinal height and ectomorphy and negative associations with BMI, sum of six skin-folds, endomorphy and mesomorphy. Boys with earlier MMA had greater body heights and breadths, particularly iliospinal height and biacromial breadth (0.10 z-score/year; p < 0.05). In girls, earlier MMA predicted greater sitting height, biepicondylar humerus breadth, weight and sum of four circumferences (0.07-0.09 z-score/year; p < 0.05). However, there was some evidence that MMA was positively associated with body heights, ectomorphy and blood pressure in girls aged ≥12. CONCLUSION Children with earlier MMA tend to have greater anthropometric dimensions. Adolescent growth spurt might affect these relationships, at least in girls.
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Affiliation(s)
- Aline Jelenkovic
- a Department of Genetics, Physical Anthropology and Animal Physiology , University of the Basque Country UPV/EHU , Spain .,b IKERBASQUE, Basque Foundation for Science , Spain , and.,c Department of Public Health , Hjelt Institute, University of Helsinki , Finland
| | - Esther Rebato
- a Department of Genetics, Physical Anthropology and Animal Physiology , University of the Basque Country UPV/EHU , Spain
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Perry JR, Hsu YH, Chasman DI, Johnson AD, Elks C, Albrecht E, Andrulis IL, Beesley J, Berenson GS, Bergmann S, Bojesen SE, Bolla MK, Brown J, Buring JE, Campbell H, Chang-Claude J, Chenevix-Trench G, Corre T, Couch FJ, Cox A, Czene K, D'adamo AP, Davies G, Deary IJ, Dennis J, Easton DF, Engelhardt EG, Eriksson JG, Esko T, Fasching PA, Figueroa JD, Flyger H, Fraser A, Garcia-Closas M, Gasparini P, Gieger C, Giles G, Guenel P, Hägg S, Hall P, Hayward C, Hopper J, Ingelsson E, Kardia SL, Kasiman K, Knight JA, Lahti J, Lawlor DA, Magnusson PK, Margolin S, Marsh JA, Metspalu A, Olson JE, Pennell CE, Polasek O, Rahman I, Ridker PM, Robino A, Rudan I, Rudolph A, Salumets A, Schmidt MK, Schoemaker MJ, Smith EN, Smith JA, Southey M, Stöckl D, Swerdlow AJ, Thompson DJ, Truong T, Ulivi S, Waldenberger M, Wang Q, Wild S, Wilson JF, Wright AF, Zgaga L, Ong KK, Murabito JM, Karasik D, Murray A. DNA mismatch repair gene MSH6 implicated in determining age at natural menopause. Hum Mol Genet 2014; 23:2490-7. [PMID: 24357391 PMCID: PMC3976329 DOI: 10.1093/hmg/ddt620] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2013] [Revised: 11/19/2013] [Accepted: 12/06/2013] [Indexed: 12/17/2022] Open
Abstract
The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10(-9)), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.
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Affiliation(s)
- John R.B. Perry
- University of Exeter Medical School, Exeter, UK,
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK,
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK,
- Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK,
| | - Yi-Hsiang Hsu
- Hebrew SeniorLife Institute for Aging Research and Harvard Medical School, Boston, MA, USA,
- Molecular and Integrative Physiological Sciences Program, Harvard School of Public Health, Boston, MA, USA,
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, 900 Commonwealth Avenue East, Boston MA 02215, USA,
- Harvard Medical School, Boston, MA, USA,
| | - Andrew D. Johnson
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA,
- NHLBI Cardiovascular Epidemiology & Human Genomics Branch, Bethesda, MD, USA,
| | - Cathy Elks
- Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK,
| | | | - Irene L. Andrulis
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada,
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada,
| | - Jonathan Beesley
- Department of Genetics, Queensland Institute of Medical Research, Brisbane, QLD, Australia,
| | | | - Sven Bergmann
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland,
- Swiss Institute of Bioinformatics, Lausanne, Switzerland,
| | - Stig E. Bojesen
- Department of Clinical Biochemistry and the Copenhagen General Population Study, Herlev Hospital, Copenhagen University Hospital, Copenhagen, Denmark,
| | - Manjeet K. Bolla
- Centre for Cancer Genetic Epidemiology and Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,
| | - Judith Brown
- Centre for Cancer Genetic Epidemiology and Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,
| | - Julie E. Buring
- Division of Preventive Medicine, Brigham and Women's Hospital, 900 Commonwealth Avenue East, Boston MA 02215, USA,
- Harvard Medical School, Boston, MA, USA,
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, EdinburghEH8 9AG, UK,
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany,
| | | | - Tanguy Corre
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland,
- Swiss Institute of Bioinformatics, Lausanne, Switzerland,
| | - Fergus J. Couch
- Departments of Laboratory Medicine and Pathology, and Health Science Research
| | - Angela Cox
- CR-UK/YCR Sheffield Cancer Research Centre, Department of Oncology, University of Sheffield, UK,
| | - Kamila Czene
- Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,
| | - Adamo Pio D'adamo
- Institute for Maternal and Child Health, IRCCS ‘Burlo Garofolo’, University of Trieste, Trieste, Italy,
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology
- Department of Psychology and
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology
- Department of Psychology and
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology and Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology and Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,
| | | | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland,
- National Institute for Health and Welfare, Helsinki, Finland,
- Folkhälsan Research Centre, Helsinki, Finland,
- University Central Hospital, Unit of General Practice, Helsinki, Finland,
- Vasa Central Hospital, Vasa, Finland,
| | - Tõnu Esko
- Divisions of Endocrinology, Children's Hospital, Boston, MA, USA,
- Broad Institute, Cambridge, MA, USA,
- Estonian Genome Center, University of Tartu, 51010Tartu, Estonia,
| | - Peter A. Fasching
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany,
| | - Jonine D. Figueroa
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, Maryland, USA,
| | - Henrik Flyger
- Department of Breast Surgery, Herlev Hospital, Copenhagen University Hospital, Copenhagen, Denmark,
| | - Abigail Fraser
- School of Social and Community Medicine, MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK,
| | - Montse Garcia-Closas
- Divisions of Breast Cancer Research and of Genetics and Epidemiology, and the Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK,
| | - Paolo Gasparini
- Institute for Maternal and Child Health, IRCCS ‘Burlo Garofolo’, University of Trieste, Trieste, Italy,
| | | | - Graham Giles
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, Melbourne School of Population Health, The University of Melbourne, Melbourne, VIC, Australia,
- Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, VIC, Australia,
| | - Pascal Guenel
- Environmental Epidemiology of Cancer, Inserm U1018, Villejuif, France,
| | - Sara Hägg
- Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden,
| | - Per Hall
- Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,
| | - Caroline Hayward
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, EdinburghEH4 2XU, UK,
| | - John Hopper
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, Melbourne School of Population Health, The University of Melbourne, Melbourne, VIC, Australia,
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden,
| | | | | | - Katherine Kasiman
- Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,
| | - Julia A. Knight
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada,
| | - Jari Lahti
- Folkhälsan Research Centre, Helsinki, Finland,
- Institute of Behavioural Science, University of Helsinki, Helsinki, Finland,
| | - Debbie A. Lawlor
- School of Social and Community Medicine, MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol, UK,
| | | | - Sara Margolin
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden,
| | - Julie A. Marsh
- School of Women's and Infants’ Health, University of Western Australia, Australia,
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, 51010Tartu, Estonia,
| | - Janet E. Olson
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA,
| | - Craig E. Pennell
- School of Women's and Infants’ Health, University of Western Australia, Australia,
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Croatia,
| | - Iffat Rahman
- Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, 900 Commonwealth Avenue East, Boston MA 02215, USA,
- Harvard Medical School, Boston, MA, USA,
| | - Antonietta Robino
- Institute for Maternal and Child Health, IRCCS ‘Burlo Garofolo’, University of Trieste, Trieste, Italy,
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, EdinburghEH8 9AG, UK,
| | - Anja Rudolph
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany,
| | - Andres Salumets
- Department of Obstetrics and Gynecology, University of Tartu, 51014 Tartu, Estonia,
- Competence Centre on Reproductive Medicine and Biology, 50410 Tartu, Estonia,
| | - Marjanka K. Schmidt
- Division of Psychosocial Research and Epidemiology and
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands,
| | - Minouk J. Schoemaker
- Divisions of Breast Cancer Research and of Genetics and Epidemiology, and the Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK,
| | - Erin N. Smith
- Department of Pediatrics and Rady Children's Hospital, University of California San Diego, La Jolla, CA 92093, USA,
| | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA,
| | - Melissa Southey
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne, VIC, Australia,
| | - Doris Stöckl
- Institute of Epidemiology II and
- Department of Obstetrics and Gynaecology, Campus Grosshadern, Ludwig-Maximilians-University, Munich, Germany,
| | - Anthony J. Swerdlow
- Divisions of Breast Cancer Research and of Genetics and Epidemiology, and the Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK,
| | - Deborah J. Thompson
- Centre for Cancer Genetic Epidemiology and Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,
| | - Therese Truong
- Environmental Epidemiology of Cancer, Inserm U1018, Villejuif, France,
| | - Sheila Ulivi
- Institute for Maternal and Child Health, IRCCS ‘Burlo Garofolo’, Trieste, Italy,
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany,
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology and Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK,
| | - Sarah Wild
- Centre for Population Health Sciences, University of Edinburgh, EdinburghEH8 9AG, UK,
| | - James F Wilson
- Centre for Population Health Sciences, University of Edinburgh, EdinburghEH8 9AG, UK,
| | - Alan F. Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK,
| | - Lina Zgaga
- Centre for Population Health Sciences, University of Edinburgh, EdinburghEH8 9AG, UK,
| | | | - Ken K. Ong
- Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK,
- Department of Paediatrics, University of Cambridge, Cambridge, UK,
| | - Joanne M. Murabito
- The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA,
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - David Karasik
- Hebrew SeniorLife Institute for Aging Research and Harvard Medical School, Boston, MA, USA,
| | - Anna Murray
- University of Exeter Medical School, Exeter, UK,
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10
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Fernández-Rhodes L, Demerath EW, Cousminer DL, Tao R, Dreyfus JG, Esko T, Smith AV, Gudnason V, Harris TB, Launer L, McArdle PF, Yerges-Armstrong LM, Elks CE, Strachan DP, Kutalik Z, Vollenweider P, Feenstra B, Boyd HA, Metspalu A, Mihailov E, Broer L, Zillikens MC, Oostra B, van Duijn CM, Lunetta KL, Perry JRB, Murray A, Koller DL, Lai D, Corre T, Toniolo D, Albrecht E, Stöckl D, Grallert H, Gieger C, Hayward C, Polasek O, Rudan I, Wilson JF, He C, Kraft P, Hu FB, Hunter DJ, Hottenga JJ, Willemsen G, Boomsma DI, Byrne EM, Martin NG, Montgomery GW, Warrington NM, Pennell CE, Stolk L, Visser JA, Hofman A, Uitterlinden AG, Rivadeneira F, Lin P, Fisher SL, Bierut LJ, Crisponi L, Porcu E, Mangino M, Zhai G, Spector TD, Buring JE, Rose LM, Ridker PM, Poole C, Hirschhorn JN, Murabito JM, Chasman DI, Widen E, North KE, Ong KK, Franceschini N. Association of adiposity genetic variants with menarche timing in 92,105 women of European descent. Am J Epidemiol 2013; 178:451-60. [PMID: 23558354 DOI: 10.1093/aje/kws473] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Obesity is of global health concern. There are well-described inverse relationships between female pubertal timing and obesity. Recent genome-wide association studies of age at menarche identified several obesity-related variants. Using data from the ReproGen Consortium, we employed meta-analytical techniques to estimate the associations of 95 a priori and recently identified obesity-related (body mass index (weight (kg)/height (m)(2)), waist circumference, and waist:hip ratio) single-nucleotide polymorphisms (SNPs) with age at menarche in 92,116 women of European descent from 38 studies (1970-2010), in order to estimate associations between genetic variants associated with central or overall adiposity and pubertal timing in girls. Investigators in each study performed a separate analysis of associations between the selected SNPs and age at menarche (ages 9-17 years) using linear regression models and adjusting for birth year, site (as appropriate), and population stratification. Heterogeneity of effect-measure estimates was investigated using meta-regression. Six novel associations of body mass index loci with age at menarche were identified, and 11 adiposity loci previously reported to be associated with age at menarche were confirmed, but none of the central adiposity variants individually showed significant associations. These findings suggest complex genetic relationships between menarche and overall obesity, and to a lesser extent central obesity, in normal processes of growth and development.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, 137 East Franklin Street, Suite 306, Campus Box 8050, Chapel Hill, NC 27514-8050, USA.
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11
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Grandone A, Cirillo G, Messa F, Coppola R, Festa A, Perrone L, del Giudice EM. LIN28B polymorphism could modulate the relationship between childhood obesity and age at menarche. J Adolesc Health 2013; 52:375. [PMID: 23427786 DOI: 10.1016/j.jadohealth.2012.10.273] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2012] [Accepted: 10/30/2012] [Indexed: 11/25/2022]
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12
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Currie C, Ahluwalia N, Godeau E, Nic Gabhainn S, Due P, Currie DB. Is obesity at individual and national level associated with lower age at menarche? Evidence from 34 countries in the Health Behaviour in School-aged Children Study. J Adolesc Health 2012; 50:621-6. [PMID: 22626490 DOI: 10.1016/j.jadohealth.2011.10.254] [Citation(s) in RCA: 76] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2010] [Revised: 10/27/2011] [Accepted: 10/27/2011] [Indexed: 11/26/2022]
Abstract
PURPOSE A unique standardized international data set from adolescent girls in 34 countries in Europe and North America participating in the Health Behaviour in School-aged Children Study (HBSC) is used to investigate the contribution of body mass index (BMI) at individual and country level to cross-national differences in age at menarche. METHODS Two independent nationally representative survey data sets from 15-year-olds (n = 27,878, in 34 countries, year = 2005/2006) and 11-year-olds (n = 18,101, in 29 countries, year = 2001/2002) were analyzed. The survey instrument is a self-report questionnaire. Median age at menarche and 95% confidence intervals (CIs) were estimated using Kaplan-Meier analysis. Hierarchical models were used to assess the relationship between BMI and age at menarche (months). "Country-level obesity" was measured by prevalence of overweight/obesity (%) in each country. RESULTS Country-level median age at menarche ranged between 12 years and 5 months and 13 years and 5 months. Country-level prevalence of overweight among 15-year-old girls ranged from 4% to 28%. Age at menarche was inversely associated with individual BMI (unstandardized regression coefficient beta = -1.01; 95% CI, -1.09 to -.94) and country-level aggregate overweight at age 11 (unstandardized regression coefficient beta = -.25; 95% CI, -.43 to -.08). Individual- and country-level measures of BMI account for 40% of the country-level variance in age at menarche. CONCLUSIONS The findings add to the evidence that obesity in childhood is a risk factor for early puberty in girls and accounts for much of the cross-national variation in age at menarche. Future HBSC surveys can track this relationship in the wake of the obesity "epidemic."
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Affiliation(s)
- Candace Currie
- Child and Adolescent Health Research Unit, School of Medicine, University of St Andrews, Scotland.
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Dvornyk V, Waqar-ul-Haq. Genetics of age at menarche: a systematic review. Hum Reprod Update 2012; 18:198-210. [PMID: 22258758 DOI: 10.1093/humupd/dmr050] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Menarche is the first menstrual period of a girl at puberty. The timing of menarche is important for health in later life. Age at menarche is a complex trait and has a strong genetic component. This review summarizes the results of the genetic studies of age at menarche conducted to date, highlights existing problems in this area and outlines prospects of future studies on genetic factors for the trait. METHODS PubMed and Google Scholar were searched until May 2011 using the keywords: 'menarche', 'puberty' and 'age at menarche' in combination with the keywords 'polymorphism', 'candidate gene', 'genome-wide association study' and 'linkage'. RESULTS Our search yielded 170 papers, 35 of which were selected for further analysis. Several large-scale genome-wide association studies along with a powerful meta-analysis of their aggregated data identified about 50 candidate genes for the trait. Some genes were replicated in different studies of Caucasians (e.g. LIN28B, TMEM38B) or in different ethnicities (e.g. SPOCK, RANK and RANKL). However, despite the large volume of results obtained, there is a huge gap in relevant data on ethnic groups other than Caucasians. CONCLUSIONS The reviewed studies laid a solid basis for future research on genetics of age at menarche. However, as yet specific genes for this trait have not been identified consistently in all ethnicities and types of studies. We suggest expanding the research to different ethnicities and propose several methodologies to increase the efficiency of studies in this area, including a systems approach, which combines existing high-throughput methods in a single pipeline.
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Affiliation(s)
- Volodymyr Dvornyk
- School of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong SAR, PR China.
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Pan R, Liu YZ, Deng HW, Dvornyk V. Association analyses suggest the effects of RANK and RANKL on age at menarche in Chinese women. Climacteric 2011; 15:75-81. [PMID: 22023082 DOI: 10.3109/13697137.2011.587556] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
OBJECTIVES Age at menarche (AAM), the time of the first menstrual bleeding, is an important developmental milestone in the female life. It marks the beginning of the reproductive period. AAM is implicated in the risk of many health complications in later life. In this study, we conducted an analysis for association of single nucleotide polymorphisms (SNPs) and common haplotypes of two candidate genes, RANK (receptor activator of the NF-κB) and RANKL (receptor activator of the NF-κB ligand), with AAM in 825 unrelated Chinese women. METHODS In total, 73 SNPs of RANKL and 23 SNPs of RANK were genotyped. The SNPs and common haplotypes were then analyzed for their association with AAM. Age and age( 2 ) were used as covariates. RESULTS We found five individual SNPs (rs7239261, rs8094884, rs3826620, rs8089829, and rs9956850) of RANK significantly associated with AAM (p < 0.05). Although no significant association was identified for the RANKL gene, three polymorphisms showed nearly significant (0.05 < p < 0.08) association with AAM. Seven haplotypes of RANK were significantly associated with AAM (p < 0.05); the most significant association of the AT haplotype composed by rs1805034 and rs4524034 (p = 9.4 × 10(-4)) remained significant (p = 0.0235) after the Bonferroni correction for multiple testing. Three haplotypes of RANKL were significantly associated with AAM (p < 0.05). Importantly, the association of rs3826620 replicated our previous findings for Caucasian females. CONCLUSIONS The results of the present study suggest that the RANK and RANKL are two candidate genes for AAM in Chinese women.
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Affiliation(s)
- R Pan
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, PR China
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15
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Zhang YX, Wang SR. Changes in nutritional status of children and adolescents in Shandong, China from 1995 to 2005. Ann Hum Biol 2011; 38:485-91. [PMID: 21338249 DOI: 10.3109/03014460.2011.555415] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Nutritional status of children and adolescents has long been known to be a determinant of health and disease; both obesity and underweight are associated with health consequences. However, no studies have been reported on changes in nutritional status of children and adolescents in Shandong, China. AIM The present study assessed the changes in nutritional status of children and adolescents in Shandong Province from 1995 to 2005. SUBJECTS AND METHODS Data used derived from two national surveys on students' constitution and health carried out by the government in 1995 and 2005 in Shandong Province, China. Increments of stature, body weight, body mass index (BMI) and haemoglobin (Hb) for children and adolescents aged 7, 9, 12, 14 and 17 years were reported. Prevalence of underweight, overweight and obesity were obtained according to the screening criteria of underweight, overweight and obesity for Chinese students using BMI and prevalence of anaemia was obtained according to the WHO criteria. RESULTS Means of stature, body weight, BMI and Hb for both boys and girls surveyed in 2005 were significantly higher than 1995 values. The range of increments of stature and body weight for adolescents aged 7, 9, 12, 14 and 17 years were 1.95-3.66 cm and 2.21-6.25 kg for boys and 1.40-2.91 cm and 1.48-3.10 kg for girls. In the past 10 years, rates of overweight and obesity increased, while underweight was not as evident: for overweight from 7.95% (boys) and 5.21% (girls) in 1995 to 13.62% (boys) and 8.25% (girls) in 2005; and for obesity from 3.48% (boys) and 2.07% (girls) in 1995 to 11.17% (boys) and 5.64% (girls) in 2005. The rate of anaemia decreased, from 19.99% (boys) and 23.43% (girls) in 1995 to 10.28% (boys) and 13.07% (girls) in 2005. CONCLUSION The nutritional status of children and adolescents has shown some improvement, although prevalence of overweight and obesity increased significantly during the 10-year period. Concerted efforts should be made to appropriately control the prevalence of overweight and obesity.
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Affiliation(s)
- Ying-Xiu Zhang
- Shandong Center for Disease Control and Prevention, Jinan, 250014, PR China.
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16
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Lu Y, Liu P, Recker RR, Deng HW, Dvornyk V. TNFRSF11A and TNFSF11 are associated with age at menarche and natural menopause in white women. Menopause 2010; 17:1048-54. [PMID: 20531232 PMCID: PMC2939156 DOI: 10.1097/gme.0b013e3181d5d523] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Menarche and menopause mark the lower and upper limits of the female reproductive period. The timing of these events influences women's health in later life. The onsets of menarche and menopause have a strong genetic basis. We tested two genes, TNFRSF11A (RANK) and TNFSF11 (RANKL), for their association with age at menarche (AM) and age at natural menopause (ANM). METHODS Nineteen single nucleotide polymorphisms (SNPs) of TNFRSF11A and 12 SNPs of TNFSF11 were genotyped in a random sample of 306 unrelated white women. This sample was analyzed for the association of the SNPs and common haplotypes with AM. Then, a subsample of 211 women with natural menopause was analyzed for the association of both genes with ANM. Smoking, alcohol intake, and duration of lactation were applied as covariates in the association analyses. RESULTS Three polymorphisms of TNFSF11 were associated with AM: rs2200287 (P = 0.005), rs9525641 (P = 0.039), and rs1054016 (P = 0.047). Two SNPs of this gene, rs346578 and rs9525641, showed an association with ANM (P = 0.007 and P = 0.011, respectively). Two SNPs of TNFRSF11A were associated with AM (rs3826620; P = 0.022) and ANM (rs8086340; P = 0.015). Multiple SNP-SNP and SNP-environment interaction effects on AM and ANM were detected for both genes. One polymorphism of TNFRSF11A, rs4436867, was not directly associated with either trait but indicated significant interactions with four TNFSF11 polymorphisms on ANM. Two other TNFRSF11A polymorphisms, rs4941125 and rs7235803, showed interaction effects with several TNFSF11 polymorphisms on AM. Both genes manifested significant interaction with the duration of breast-feeding in their effect on ANM. CONCLUSIONS The TNFRSF11A and TNFSF11 genes are associated with the onset of AM and ANM in white women.
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Affiliation(s)
- Yan Lu
- Department of Surgery, Washington University in St. Louis, Campus Box 8109, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Pengyuan Liu
- Department of Surgery, Washington University in St. Louis, Campus Box 8109, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Robert R. Recker
- Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University, Omaha, NE 68131, USA
| | - Hong-Wen Deng
- School of Medicine, University of Missouri-Kansas City, Kansas City, MO 64108, USA
| | - Volodymyr Dvornyk
- School of Biological Sciences, University of Hong Kong, Pokfulam Road, Hong Kong SAR, PR China
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17
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Abstract
Objective An individual’s growth trajectory is, at least in part, inherited. Mother’s early age at menarche has been associated with taller offspring height and greater body mass index (BMI) at age 9 years, suggesting that mother’s age at menarche may be an intergenerational marker of growth. We examined the association between mother’s age at menarche and childhood size at birth, and at the ages 1, 3, 4, 7, and 8 years in the Collaborative Perinatal Project (CPP). Subjects We examined 128,636 measurements from 31,474 Black and White children. We transformed the original measurements into z-scores. Child size was examined in mixed models, adjusted for center, child sex, race, socioeconomic index, child’s exact age at measurement (in months), mother's age at recruitment and, depending on which measure was the outcome in the specific model, mother's height, pre-pregnancy weight, or BMI. Results Compared with children whose mother had menarche at age 15 or later, children whose mothers had age at menarche before age 12 were taller from age 1 and had higher BMI at ages 7 and 8 (0.17 and 0.19 z, respecively). Conclusions Mother’s age at menarche is a modest predictor of their children’s growth trajectory. The mechanism is likely to be heritable, although other explanations are possible.
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Affiliation(s)
- O Basso
- Epidemiology Branch, National Institute of Environmental Health Sciences NIH, DHHS, Durham, NC, USA.
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18
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Rigon F, Bianchin L, Bernasconi S, Bona G, Bozzola M, Buzi F, Cicognani A, De Sanctis C, De Sanctis V, Radetti G, Tatò L, Tonini G, Perissinotto E. Update on age at menarche in Italy: toward the leveling off of the secular trend. J Adolesc Health 2010; 46:238-44. [PMID: 20159500 DOI: 10.1016/j.jadohealth.2009.07.009] [Citation(s) in RCA: 72] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2009] [Revised: 07/30/2009] [Accepted: 08/04/2009] [Indexed: 10/20/2022]
Abstract
PURPOSE To update the information on age at menarche in the Italian population and to verify the influence of genetic, nutritional, and socioeconomic factors on menarcheal age. Recent studies suggest that the magnitude of the secular trend toward an earlier age at menarche is slackening in industrialized countries. METHODS This multicenter study was conducted on a large, population-based sample of Italian high school girls (n = 3,783), using a self-administered questionnaire. The questionnaire was used to gather information on the girls, including demography, anthropometry, menarcheal date, regularity of menses, behavioral habits, and physical activity. The questionnaire was also used to gather information on parents, including demography and mothers' and sisters' menarcheal ages. The median age at menarche and its 95% confidence interval were estimated by means of Kaplan-Meier survival analysis. To identify the independent predictive factors of age at menarche, multivariate mixed-effects models were applied. RESULTS The median age at menarche of the subjects was 12.4 years (95% confidence interval: 12.34-12.46). The girls had their first menses approximately one-quarter of a year (median-0.13) earlier than did their mothers (p < .0001). Among all variables, parents' birth area, body mass index, family size, and the mother's menarcheal age were significantly and independently associated with age at menarche. CONCLUSIONS This study confirmed the reduction in the trend toward earlier menarche in Italy. The results also confirmed that genetic and nutritional factors are strong markers for early menarche. Currently, socioeconomic factors do not seem to play as significant a role as in the past.
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Affiliation(s)
- Franco Rigon
- Department of Pediatrics, University of Padua, Padua, Italy
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19
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Liu P, Lu Y, Recker RR, Deng HW, Dvornyk V. Association analyses suggest multiple interaction effects of the methylenetetrahydrofolate reductase polymorphisms on timing of menarche and natural menopause in white women. Menopause 2010; 17:185-90. [PMID: 19593234 PMCID: PMC2806497 DOI: 10.1097/gme.0b013e3181aa2597] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE This study aimed to investigate whether polymorphisms of the methylenetetrahydrofolate reductase (MTHFR) gene are associated with age at menarche and age at natural menopause in white women. METHODS In a cross-sectional study, a total of 305 randomly selected unrelated white women were genotyped for six single nucleotide polymorphisms (SNPs) of the MTHFR gene (including one common replacement, rs1801133). This sample was comprehensively analyzed for the association of the SNPs with age at menarche. Then a subsample of 210 women who experienced natural menopause was analyzed for the association of the MTHFR gene with age at natural menopause. RESULTS Duration of breast-feeding was a significant predictor of earlier natural menopause (P < 0.05). No individual SNPs were associated with either age at menarche or age at natural menopause. However, three significant (P < 0.05) SNP-SNP interaction effects (rs2066470/rs1476413, rs2066470/rs4846049, and rs17037390/rs4846049) on the onset of menarche were determined. Three haplotypes were significantly associated with age at menopause (P < 0.05). Four SNPs (rs2066470, rs17037390, rs1801133, and rs4846048) indicated significant interaction effects with various lifestyle factors on age at natural menopause. CONCLUSIONS The results of our study suggest that the MTHFR gene may influence the onset of menarche and natural menopause. This effect is probably due to the multiple SNP-SNP and SNP-environment interactions. More independent studies are needed to further clarify the possible contribution of this gene to the timing of menarche and menopause.
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Affiliation(s)
- Pengyuan Liu
- Department of Surgery, Washington University in St. Louis, Campus Box 8109, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Yan Lu
- Department of Surgery, Washington University in St. Louis, Campus Box 8109, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Robert R. Recker
- Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University, Omaha, NE 68131, USA
| | - Hong-Wen Deng
- School of Medicine, University of Missouri-Kansas City, Kansas City, MO 64108, USA
| | - Volodymyr Dvornyk
- School of Biological Sciences, University of Hong Kong, Pokfulam Road, Hong Kong SAR, PR China
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Perry JRB, Stolk L, Franceschini N, Lunetta KL, Zhai G, McArdle PF, Smith AV, Aspelund T, Bandinelli S, Boerwinkle E, Cherkas L, Eiriksdottir G, Estrada K, Ferrucci L, Folsom AR, Garcia M, Gudnason V, Hofman A, Karasik D, Kiel DP, Launer LJ, van Meurs J, Nalls MA, Rivadeneira F, Shuldiner AR, Singleton A, Soranzo N, Tanaka T, Visser JA, Weedon MN, Wilson SG, Zhuang V, Streeten EA, Harris TB, Murray A, Spector TD, Demerath EW, Uitterlinden AG, Murabito JM. Meta-analysis of genome-wide association data identifies two loci influencing age at menarche. Nat Genet 2009; 41:648-50. [PMID: 19448620 PMCID: PMC2942986 DOI: 10.1038/ng.386] [Citation(s) in RCA: 211] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2009] [Accepted: 04/21/2009] [Indexed: 11/09/2022]
Abstract
We conducted a meta-analysis of genome-wide association data to detect genes influencing age at menarche in 17,510 women. The strongest signal was at 9q31.2 (P = 1.7 × 10(-9)), where the nearest genes include TMEM38B, FKTN, FSD1L, TAL2 and ZNF462. The next best signal was near the LIN28B gene (rs7759938; P = 7.0 × 10(-9)), which also influences adult height. We provide the first evidence for common genetic variants influencing female sexual maturation.
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Affiliation(s)
- John R B Perry
- Institute of Biomedical and Clinical Science, Peninsula Medical School, Exeter, UK
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21
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Age at menarche in the Canadian population: secular trends and relationship to adulthood BMI. J Adolesc Health 2008; 43:548-54. [PMID: 19027642 DOI: 10.1016/j.jadohealth.2008.07.017] [Citation(s) in RCA: 73] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2008] [Revised: 07/23/2008] [Accepted: 07/23/2008] [Indexed: 11/23/2022]
Abstract
PURPOSE Studies from around the world indicate a trend toward younger ages of menarche. The extent of this trend in the Canadian population is unknown, and the relationship to later-life health indicators has not yet been fully elucidated. The objective of this study is to estimate the trend in age at menarche (AAM) in the Canadian population and evaluate the relationship between AAM and adult body mass index (BMI). METHODS Our data source was a nationally representative survey (the Canadian Community Health Survey, 2.2), and analyses included 8080 women, aged 15 and older, who self-reported AAM. Height and weight were measured by the interviewers for the calculation of current BMI. We modeled the secular trend in AAM over time, and the relationship between current BMI and AAM. RESULTS We found a statistically significant decline in AAM in successive age cohorts, indicating a 0.73-year (8.8-month) decrease in AAM between the oldest and youngest age cohorts in the sample. A 1-year increase in AAM was associated with a decrease in mean BMI of approximately 0.5 kg/m(2), after adjustment for covariates. A current age-AAM interaction term was nonsignificant, indicating that the relationship was stable throughout increasing temporal separation from puberty. CONCLUSION The observed trend toward earlier menarche could be an indicator of a change in insulin-related metabolism, possibly mediated by behavioral and environmental variables. This study suggests that AAM may be an important clinical and public health indicator of susceptibility to overweight and obesity and attendant morbidity.
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22
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Douglas JA, Roy-Gagnon MH, Zhou C, Mitchell BD, Shuldiner AR, Chan HP, Helvie MA. Mammographic breast density--evidence for genetic correlations with established breast cancer risk factors. Cancer Epidemiol Biomarkers Prev 2008; 17:3509-16. [PMID: 19029399 DOI: 10.1158/1055-9965.epi-08-0480] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Previous twin and family studies indicate that the familial aggregation of breast density is due (in part) to genetic factors. Whether these genetic influences are shared with other breast cancer risk factors, however, is not known. Using standard film-screen mammography, we screened 550 women, including 611 pairs of sisters, from the Old Order Amish population of Lancaster County, Pennsylvania. We digitized mammograms and quantified the dense and nondense areas of the breast using a computer-assisted method. Information about other breast cancer risk factors was collected via questionnaires and a physical exam. Using pedigree-based variance component methods, we estimated the genetic contributions to several breast cancer risk factors, including breast density, and evaluated the evidence for shared genetic influences between them. After adjusting for covariates, genetic effects accounted for >33% of the total variance of each risk factor (P < 0.001), including breast density, and the dense and nondense areas of the breast were significantly genetically correlated with parity [genetic correlation (rho(G)) = -0.47; P = 0.013] and age at menarche (rho(G) = -0.38; P = 0.008), respectively. The nondense area of the breast and, in turn, breast density, expressed as a ratio of dense area to total area, were also genetically correlated with most measures of adiposity but in opposite directions (rho(G) > or = 0.75; P < 10(-7) for nondense area). We conclude that the genetic components that influence breast density are not independent of the genetic components that influence other breast cancer risk factors. This shared genetic architecture should be considered in future genetic studies of breast density.
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Affiliation(s)
- Julie A Douglas
- Department of Human Genetics, University of Michigan Medical School, Room 5912, Buhl Building, 1241 E. Catherine Street, Ann Arbor, MI 48109-5618, USA.
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23
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Skrzypczak M, Szwed A, Pawlińska-Chmara R, Skrzypulec V. Body mass index, waist to hip ratio and waist/height in adult Polish women in relation to their education, place of residence, smoking and alcohol consumption. HOMO-JOURNAL OF COMPARATIVE HUMAN BIOLOGY 2008; 59:329-42. [PMID: 18675976 DOI: 10.1016/j.jchb.2008.06.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2007] [Accepted: 03/17/2008] [Indexed: 10/21/2022]
Abstract
Obesity is a complex, multifactorial disorder that develops from genotype and environmental interactions. The aim of this study is to describe the variability of body mass index (BMI), waist to hip ratio (WHR) and waist to height (W/Ht) in adult Polish women, and to determine relationships between these variables and factors such as education, place of residence, smoking and alcohol drinking. The tested group consisted of 10,254 women aged 25-95 years, who voluntarily filled in questionnaires and participated in anthropometric measurements (body height and mass, waist and hip circumferences). The BMI, WHR and W/Ht values were calculated based on these measurements. The participants were differentiated in terms of education, residence and lifestyle (smoking, alcohol drinking). Chi-squared test, product-moment correlations, ANOVA, multiple correspondence analysis (MCA) and logistic regression with backward elimination were used to evaluate associations between social and lifestyle factors and BMI, WHR and W/Ht. The results confirm (1) the relationship between low social status and the risk of overweight and obesity as observed in developed countries; (2) higher susceptibility to environmental factors such as education, place of residence, smoking and alcohol drinking in younger (premenopausal) women; (3) the usefulness of simple and practical anthropometric indicators such as WHR and W/Ht for the identification of the higher risk of future metabolic diseases in obese people and those with a normal body mass.
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Affiliation(s)
- M Skrzypczak
- Department of Human Biological Development, Institute of Anthropology, Faculty of Biology, Adam Mickiewicz University, Umultowska 89, 61-614 Poznań, Poland.
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Abstract
Assessment of the BMI, WHR and W/Ht in pre- and postmenopausal womenThe main goal of this study was to determine whether and how values of the BMI, WHR and W/Ht indicators change in pre- and postmenopausal women. The tested group consisted of 10,216 women aged 25-95 years. Data were collected during the national campaign "Fighting Obesity", organized by Hand-Prod Company between 2000-2002 across Poland, when adult women voluntarily filled in a questionnaire and participated in anthropometric measurements. The BMI, WHR and W/Ht values were calculated based on these measurements. The values of the BMI, WHR and W/Ht change with age. However, in each age group postmenopausal women have higher BMI, WHR and W/Ht than premenopausal women. Thus, the results obtained indicate that hormonal changes occurring in the climacterium period cause an increase in the analyzed index values. The BMI used herein is characterized by high accuracy in indicating obesity. Moreover, the WHR and W/Ht are also used as adiposity indicators, which may be useful in assessment of the risk of disease or death caused by hypertension, cardiac diseases, diabetes, or even cancers. However, they should not be used only in relation to obese women, because even a slight increase in visceral obesity, with body mass within normal limits, may contribute to unfavorable changes in the woman's metabolic profile, which in turn, may present a risk of illness.
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Abstract
Puberty is a complex, coordinated biological process with multiple levels of regulation. Epidemiological observations suggest that the timing of pubertal events is a heritable trait, although environmental factors can modulate such genetic influence. The study of pathological states of early and late puberty has provided valuable insight into those genes that regulate gonadotrophin-releasing hormone (GnRH) activity. The development of pulsatile release of GnRH secretion mediated through kisspeptin-1 activation of G-protein coupled receptor-54 appears to be a central event at the onset and during progression of puberty. Stimulating and restraining influences (e.g. in the form of glutamatergic and GABAergic neuronal inputs) are likely to influence the timing of this process. The study of extreme variants of 'normality', such as constitutional delay of growth and puberty and early puberty, may lead to the recognition of additional genes and pathways that can modulate both the timing of pubertal onset and its tempo.
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Affiliation(s)
- I Banerjee
- Paediatric Endocrinology, Royal Manchester Children's Hospital, Manchester, UK
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