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van der Spoel E, Roelfsema F, Akintola AA, Jansen SW, Slagboom PE, Westendorp RGJ, Blauw GJ, Pijl H, van Heemst D. Interrelationships Between Pituitary Hormones as Assessed From 24-hour Serum Concentrations in Healthy Older Subjects. J Clin Endocrinol Metab 2020; 105:5680671. [PMID: 31853555 PMCID: PMC7065845 DOI: 10.1210/clinem/dgz253] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Accepted: 12/17/2019] [Indexed: 12/17/2022]
Abstract
CONTEXT Hormones of the hypothalamic-pituitary-target gland axes are mostly investigated separately, whereas the interplay between hormones might be as important as each separate hormonal axis. OBJECTIVE Our aim is to determine the interrelationships between GH, TSH, ACTH, and cortisol in healthy older individuals. DESIGN We made use of 24-hour hormone serum concentrations assessed with intervals of 10 minutes from 38 healthy older individuals with a mean age (SD) of 65.1 (5.1) years from the Leiden Longevity Study. Cross-correlation analyses were performed to assess the relative strength between 2 24-hour hormone serum concentration series for all possible time shifts. Cross-approximate entropy was used to assess pattern synchronicity between 2 24-hour hormone serum concentration series. RESULTS Within an interlinked hormonal axis, ACTH and cortisol were positively correlated with a mean (95% confidence interval) correlation coefficient of 0.78 (0.74-0.81) with cortisol following ACTH concentrations with a delay of 10 minutes. Between different hormonal axes, we observed a negative correlation coefficient between cortisol and TSH of -0.30 (-0.36 to -0.25) with TSH following cortisol concentrations with a delay of 170 minutes. Furthermore, a positive mean (95% confidence interval) correlation coefficient of 0.29 (0.22-0.37) was found between TSH and GH concentrations without any delay. Moreover, cross-approximate entropy analyses showed that GH and cortisol exhibit synchronous serum concentration patterns. CONCLUSIONS This study demonstrates that interrelations between hormones from interlinked as well as different hypothalamic-pituitary-target gland axes are observed in healthy older individuals. More research is needed to determine the biological meaning and clinical consequences of these observations.
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Affiliation(s)
- Evie van der Spoel
- Section Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
- Correspondence and Reprint Requests: Evie van der Spoel, Section Gerontology and Geriatrics, Department of Internal, Medicine, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands. E-mail:
| | - Ferdinand Roelfsema
- Section Endocrinology, Department of Internal Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
| | - Abimbola A Akintola
- Section Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
| | - Steffy W Jansen
- Section Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
| | - P Eline Slagboom
- Section Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, RC Leiden The Netherlands
| | - Rudi G J Westendorp
- Section Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
- Department of Public Health, Center of Healthy Aging, University of Copenhagen, Copenhagen, Denmark
| | - Gerard J Blauw
- Section Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
| | - Hanno Pijl
- Section Endocrinology, Department of Internal Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
| | - Diana van Heemst
- Section Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
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Tikk K, Sookthai D, Johnson T, Dossus L, Clavel-Chapelon F, Tjønneland A, Olsen A, Overvad K, Baglietto L, Rinaldi S, Romieu I, Boeing H, Trichopoulou A, Lagiou P, Trichopoulos D, Masala G, Agnoli C, Tumino R, Sacerdote C, Mattiello A, Buckland G, Sánchez S, Molina-Montes E, Amiano P, Castaño JMH, Barricarte A, Bueno-de-Mesquita HB, Monninkhof EM, Onland-Moret NC, Idahl A, Lundin E, Weiderpass E, Lund E, Waaseth M, Khaw KT, Key TJ, Travis RC, Gunter MJ, Riboli E, Kaaks R. Prolactin determinants in healthy women: A large cross-sectional study within the EPIC cohort. Cancer Epidemiol Biomarkers Prev 2014; 23:2532-42. [PMID: 25143360 DOI: 10.1158/1055-9965.epi-14-0613] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Experimental and epidemiologic data suggest that higher circulating prolactin is associated with breast cancer risk; however, how various risk factors for breast cancer influence prolactin levels in healthy women is not clear. METHODS We analyzed cross-sectional associations between several suggested reproductive and lifestyle risk factors for breast cancer and circulating prolactin among pre- and postmenopausal women, taking into account the use of current postmenopausal hormone therapy, among 2,560 controls from a breast cancer nested case-control study within the EPIC cohort. RESULTS Adjusted geometric mean prolactin levels were significantly higher among premenopausal women, and among postmenopausal women using hormone therapy compared with nonusers (8.2, 7.0, and 6.3 ng/mL, respectively; Pcat = <0.0001). Furthermore, prolactin levels were significantly higher among users of combined estrogen-progestin hormone therapy compared with users of estrogen-alone hormone therapy (6.66 vs. 5.90 ng/mL; Pcat = 0.001). Prolactin levels were lower among parous women compared with nulliparous women (8.61 vs. 10.95 ng/mL; Pcat = 0.0002, premenopausal women); the magnitude of this difference depended on the number of full-term pregnancies (22.1% lower, ≥3 vs. 1 pregnancy, Ptrend = 0.01). Results for parity were similar but lower in magnitude among postmenopausal women. Prolactin did not vary by other studied factors, with the exception of lower levels among postmenopausal smokers compared with never smokers. CONCLUSIONS Our study shows that current hormone therapy use, especially the use of combined hormone therapy, is associated with higher circulating prolactin levels in postmenopausal women, and confirms prior findings of lower circulating prolactin in parous women. IMPACT Our study extends the knowledge linking various breast cancer risk factors with circulating prolactin.
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Affiliation(s)
- Kaja Tikk
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Disorn Sookthai
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Theron Johnson
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Laure Dossus
- Nutrition, Hormones, and Women's Health Team, Centre for Research in Epidemiology and Population Health (CESP), INSERM U1018, Villejuif, France. Univ Paris Sud, UMRS 1018, Villejuif, France. IGR, Villejuif, France
| | - Françoise Clavel-Chapelon
- Nutrition, Hormones, and Women's Health Team, Centre for Research in Epidemiology and Population Health (CESP), INSERM U1018, Villejuif, France. Univ Paris Sud, UMRS 1018, Villejuif, France. IGR, Villejuif, France
| | | | - Anja Olsen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Laura Baglietto
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia. Centre for Molecular, Environmental, Genetic, and Analytic Epidemiology, The University of Melbourne, Melbourne, Australia
| | - Sabina Rinaldi
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC), Lyon, France
| | - Isabelle Romieu
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC), Lyon, France
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition (DIfE), Nuthetal, Germany
| | - Antonia Trichopoulou
- Department of Hygiene, Epidemiology, and Medical Statistics, University of Athens Medical School, Athens, Greece. Hellenic Health Foundation, Athens, Greece
| | - Pagona Lagiou
- Department of Hygiene, Epidemiology, and Medical Statistics, University of Athens Medical School, Athens, Greece. Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts. Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece
| | - Dimitrios Trichopoulos
- Hellenic Health Foundation, Athens, Greece. Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts. Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece
| | - Giovanna Masala
- Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute-ISPO, Florence, Italy
| | - Claudia Agnoli
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Unit, "Civic-M.P.Arezzo" Hospital ASP, Ragusa, Italy
| | - Carlotta Sacerdote
- Center for Cancer Prevention (CPO-Piemonte), Torino, Italy. Human Genetic Foundation (HuGeF), Torino, Italy
| | - Amalia Mattiello
- Department of Clinical and Experimental Medicine, Federico II University, Naples, Italy
| | - Genevieve Buckland
- Unit of Nutrition, Environment, and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain
| | | | - Esther Molina-Montes
- Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitario de Granada, Granada, Spain. Consortium for Biomedical Research in Epidemiology and Public Health (CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Pilar Amiano
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain. Basque Regional Health Department, Public Health Division of Gipuzkoa, San Sebastian, Spain
| | - José María Huerta Castaño
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain. Department of Epidemiology, Murcia Regional Health Authority, Murcia, Spain
| | - Aurelio Barricarte
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain. Navarre Public Health Institute, Pamplona, Spain
| | - H Bas Bueno-de-Mesquita
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands. Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, the Netherlands. School of Public Health, Imperial College, London, United Kingdom
| | - Evelyn M Monninkhof
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, the Netherlands
| | - N Charlotte Onland-Moret
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, the Netherlands
| | - Annika Idahl
- Department of Clinical Sciences, Obstetrics and Gynaecology, Faculty of Medicine, Umeå University, Umeå, Sweden
| | - Eva Lundin
- Department of Medical Biosciences, Pathology, Faculty of Medicine, Umeå University, Umeå, Sweden
| | - Elisabete Weiderpass
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway. Department of Research, Cancer Registry of Norway, Oslo, Norway. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. Samfundet Folkhälsan, Helsinki, Finland
| | - Eiliv Lund
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
| | - Marit Waaseth
- Department of Pharmacy, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
| | - Kay-Tee Khaw
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Timothy J Key
- Cancer Epidemiology Unit, University of Oxford, Oxford, United Kingdom
| | - Ruth C Travis
- Cancer Epidemiology Unit, University of Oxford, Oxford, United Kingdom
| | - Marc J Gunter
- School of Public Health, Imperial College, London, United Kingdom
| | - Elio Riboli
- School of Public Health, Imperial College, London, United Kingdom
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Takiguchi S, Nakamura Y, Yamagata Y, Takayama H, Harada A, Sugino N, Kato H. Role of transient hyperprolactinemia in the late follicular phase of the gonadotropin-stimulated cycle. Reprod Med Biol 2002; 1:69-74. [PMID: 29662350 PMCID: PMC5891783 DOI: 10.1046/j.1445-5781.2002.00012.x] [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: 11/20/2022] Open
Abstract
Background: Serum prolactin (PRL) concentration is known to transiently increase in rats; however, its change is obscure and the role of it is also unclear in women. We studied the relationship between estradiol (E2) and PRL production and the role of transient hyperprolactinemia in the late follicular phase of the gonadotropin-stimulated cycle. Methods: (1) Serum E2 and PRL concentrations were measured on an early follicular day and immediately before a human chorionic gonadotropin (hCG) injection in 60 patients with normoprolactinemia. Twelve of the 60 patients also received a gonadotropin injection with bromocriptine, and serum hormone levels were compared with those without bromocriptine. (2) Preovulatory serum E2 and PRL concentrations were compared between the natural and clomiphene treatment cycles in 14 hormonally normal women. (3) Changes of serum PRL concentrations were measured before and after E2 loading in five premature ovarian failure (POF) patients. (4) The E2 production by granulosa cells in the presence of PRL was measured. Results and Conclusion: Serum E2 and PRL concentrations were significantly increased by the gonadotropin injection. Bromocriptine treatment completely inhibited the PRL increase, but further increased serum E2 concentration on the late follicular day. The E2 loading increased serum PRL levels in POF patients. The clomiphene treatment increased serum E2 but decreased PRL concentrations. Prolactin significantly decreased E2 production by granulosa cells. A feedback loop may exist between E2 and PRL to control the excess E2 production induced by gonadotropin injection. (Reprod Med Biol 2002; 1: 69-74).
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Affiliation(s)
- Shuji Takiguchi
- Reproductive, Pediatric and Infectious Science, Yamaguchi University School of Medicine, Ube, Japan
| | - Yasuhiko Nakamura
- Reproductive, Pediatric and Infectious Science, Yamaguchi University School of Medicine, Ube, Japan
| | - Yoshiaki Yamagata
- Reproductive, Pediatric and Infectious Science, Yamaguchi University School of Medicine, Ube, Japan
| | - Hisako Takayama
- Reproductive, Pediatric and Infectious Science, Yamaguchi University School of Medicine, Ube, Japan
| | - Ayako Harada
- Reproductive, Pediatric and Infectious Science, Yamaguchi University School of Medicine, Ube, Japan
| | - Norihiro Sugino
- Reproductive, Pediatric and Infectious Science, Yamaguchi University School of Medicine, Ube, Japan
| | - Hiroshi Kato
- Reproductive, Pediatric and Infectious Science, Yamaguchi University School of Medicine, Ube, Japan
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