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Gu Y, Chi VTQ, Zhang Q, Liu L, Meng G, Wu H, Bao X, Zhang S, Sun S, Wang X, Zhou M, Jia Q, Song K, Niu K. Low-Normal Thyroid Function Predicts Incident Anemia in the General Population With Euthyroid Status. J Clin Endocrinol Metab 2019; 104:5693-5702. [PMID: 31361306 DOI: 10.1210/jc.2019-00888] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 07/18/2019] [Indexed: 01/01/2023]
Abstract
CONTEXT Thyroid hormones (THs) have direct and indirect effects on hematopoiesis. However, few studies have directly evaluated the effect of THs on incident anemia among euthyroid subjects. This cohort study aimed to explore whether THs under physiological conditions can affect the development of anemia in the general population. DESIGN A total of 12,310 participants were enrolled in the cohort study (∼5-year follow-up period; mean, 3.1 years). A chemiluminescence immunoassay was used to measure free T3 (FT3), free T4 (FT4), and TSH, and anemia was defined according to the World Health Organization recommendation. THs, TSH, and Hb were assessed yearly during follow-up. Multivariable Cox proportional hazards regression models were used to assess the association between THs, TSH, and incident anemia. RESULTS The fully adjusted hazards ratios (95% CI) of anemia per 1-unit change in FT3, FT4, and TSH concentrations were 0.70 (0.56, 0.87), 0.93 (0.88, 0.98), and 1.19 (0.94, 1.50) (P < 0.01, P < 0.01, and P = 0.14, respectively). Moreover, a significant and positive association between FT3, FT4, and annual changes in Hb (standard regression coefficients of 0.056 and 0.028, respectively; both P < 0.01) was observed. Similar associations were observed when the participants who had thyroid dysfunction upon follow-up were excluded. CONCLUSIONS The current study demonstrated that THs significantly predict future anemia and annual changes in Hb, even in the euthyroid population.
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Affiliation(s)
- Yeqing Gu
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
| | - Vu Thi Quynh Chi
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
| | - Qing Zhang
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Li Liu
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Ge Meng
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Hongmei Wu
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xue Bao
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
| | - Shunming Zhang
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
| | - Shaomei Sun
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Xing Wang
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Ming Zhou
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Qiyu Jia
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Kun Song
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Kaijun Niu
- Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
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McLachlan S, Giambartolomei C, White J, Charoen P, Wong A, Finan C, Engmann J, Shah T, Hersch M, Podmore C, Cavadino A, Jefferis BJ, Dale CE, Hypponen E, Morris RW, Casas JP, Kumari M, Ben-Shlomo Y, Gaunt TR, Drenos F, Langenberg C, Kuh D, Kivimaki M, Rueedi R, Waeber G, Hingorani AD, Price JF, Walker AP. Replication and Characterization of Association between ABO SNPs and Red Blood Cell Traits by Meta-Analysis in Europeans. PLoS One 2016; 11:e0156914. [PMID: 27280446 PMCID: PMC4900668 DOI: 10.1371/journal.pone.0156914] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 05/20/2016] [Indexed: 01/07/2023] Open
Abstract
Red blood cell (RBC) traits are routinely measured in clinical practice as important markers of health. Deviations from the physiological ranges are usually a sign of disease, although variation between healthy individuals also occurs, at least partly due to genetic factors. Recent large scale genetic studies identified loci associated with one or more of these traits; further characterization of known loci and identification of new loci is necessary to better understand their role in health and disease and to identify potential molecular mechanisms. We performed meta-analysis of Metabochip association results for six RBC traits—hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV) and red blood cell count (RCC)—in 11 093 Europeans from seven studies of the UCL-LSHTM-Edinburgh-Bristol (UCLEB) Consortium. We identified 394 non-overlapping SNPs in five loci at genome-wide significance: 6p22.1-6p21.33 (with HFE among others), 6q23.2 (with HBS1L among others), 6q23.3 (contains no genes), 9q34.3 (only ABO gene) and 22q13.1 (with TMPRSS6 among others), replicating previous findings of association with RBC traits at these loci and extending them by imputation to 1000 Genomes. We further characterized associations between ABO SNPs and three traits: hemoglobin, hematocrit and red blood cell count, replicating them in an independent cohort. Conditional analyses indicated the independent association of each of these traits with ABO SNPs and a role for blood group O in mediating the association. The 15 most significant RBC-associated ABO SNPs were also associated with five cardiometabolic traits, with discordance in the direction of effect between groups of traits, suggesting that ABO may act through more than one mechanism to influence cardiometabolic risk.
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Affiliation(s)
- Stela McLachlan
- Centre for Population Health Sciences, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail:
| | - Claudia Giambartolomei
- Department of Psychiatry, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, The Leon and Norma Hess Center for Science and Medicine, New York, New York, United States of America
| | - Jon White
- University College London Genetics Institute, Department of Genetics, Environment and Evolution, London, United Kingdom
| | - Pimphen Charoen
- Department of Non-communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Chris Finan
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Jorgen Engmann
- Genetic Epidemiology Group, Institute of Cardiovascular Science, University College London, London, United Kingdom
- Farr Institute of Health Informatics Research, Department of Epidemiology & Public Health, University College London, London, United Kingdom
| | - Tina Shah
- Genetic Epidemiology Group, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Micha Hersch
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Clara Podmore
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Alana Cavadino
- Centre for Environmental and Preventive Medicine, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom
- Population, Policy and Practice, UCL Institute of Child Health, University College London, London, United Kingdom
| | - Barbara J. Jefferis
- Department of Primary Care & Population Health, UCL Institute of Epidemiology & Health Care, University College London, London, United Kingdom
| | - Caroline E. Dale
- Farr Institute of Health Informatics Research, Department of Epidemiology & Public Health, University College London, London, United Kingdom
| | - Elina Hypponen
- Population, Policy and Practice, UCL Institute of Child Health, University College London, London, United Kingdom
- Centre for Population Health Research, School of Health Sciences and Sansom Institute of Health Research, University of South Australia, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Richard W. Morris
- Department of Primary Care & Population Health, UCL Institute of Epidemiology & Health Care, University College London, London, United Kingdom
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Juan P. Casas
- Institute of Health Informatics, University College London, London, United Kingdom
| | - Meena Kumari
- Institute for Social and Economic Research, University of Essex, Colchester, United Kingdom
- Department of Epidemiology & Public Health, UCL Institute of Epidemiology & Health Care, University College London, London, United Kingdom
| | - Yoav Ben-Shlomo
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Tom R. Gaunt
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Fotios Drenos
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Institute of Health Informatics, University College London, London, United Kingdom
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Mika Kivimaki
- Department of Epidemiology & Public Health, UCL Institute of Epidemiology & Health Care, University College London, London, United Kingdom
| | - Rico Rueedi
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Gerard Waeber
- Department of Internal Medicine, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | - Aroon D. Hingorani
- Institute of Cardiovascular Science, University College London, London, United Kingdom
- Farr Institute of Health Informatics Research, Department of Epidemiology & Public Health, University College London, London, United Kingdom
| | - Jacqueline F. Price
- Centre for Population Health Sciences, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Ann P. Walker
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, United Kingdom
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Maggio M, De Vita F, Fisichella A, Lauretani F, Ticinesi A, Ceresini G, Cappola A, Ferrucci L, Ceda GP. The Role of the Multiple Hormonal Dysregulation in the Onset of "Anemia of Aging": Focus on Testosterone, IGF-1, and Thyroid Hormones. Int J Endocrinol 2015; 2015:292574. [PMID: 26779261 PMCID: PMC4686706 DOI: 10.1155/2015/292574] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Revised: 10/23/2015] [Accepted: 10/27/2015] [Indexed: 12/13/2022] Open
Abstract
Anemia is a multifactorial condition whose prevalence increases in both sexes after the fifth decade of life. It is a highly represented phenomenon in older adults and in one-third of cases is "unexplained." Ageing process is also characterized by a "multiple hormonal dysregulation" with disruption in gonadal, adrenal, and somatotropic axes. Experimental studies suggest that anabolic hormones such as testosterone, IGF-1, and thyroid hormones are able to increase erythroid mass, erythropoietin synthesis, and iron bioavailability, underlining a potential role of multiple hormonal changes in the anemia of aging. Epidemiological data more consistently support an association between lower testosterone and anemia in adult-older individuals. Low IGF-1 has been especially associated with anemia in the pediatric population and in a wide range of disorders. There is also evidence of an association between thyroid hormones and abnormalities in hematological parameters under overt thyroid and euthyroid conditions, with limited data on subclinical statuses. Although RCTs have shown beneficial effects, stronger for testosterone and the GH-IGF-1 axis and less evident for thyroid hormones, in improving different hematological parameters, there is no clear evidence for the usefulness of hormonal treatment in improving anemia in older subjects. Thus, more clinical and research efforts are needed to investigate the hormonal contribution to anemia in the older individuals.
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Affiliation(s)
- Marcello Maggio
- Department of Clinical and Experimental Medicine, Section of Geriatrics, University of Parma, 43126 Parma, Italy
- Geriatric Rehabilitation Department, University Hospital of Parma, 43126 Parma, Italy
- *Marcello Maggio:
| | - Francesca De Vita
- Department of Clinical and Experimental Medicine, Section of Geriatrics, University of Parma, 43126 Parma, Italy
| | - Alberto Fisichella
- Department of Clinical and Experimental Medicine, Section of Geriatrics, University of Parma, 43126 Parma, Italy
| | - Fulvio Lauretani
- Geriatric Rehabilitation Department, University Hospital of Parma, 43126 Parma, Italy
| | - Andrea Ticinesi
- Department of Clinical and Experimental Medicine, Section of Geriatrics, University of Parma, 43126 Parma, Italy
| | - Graziano Ceresini
- Department of Clinical and Experimental Medicine, Section of Geriatrics, University of Parma, 43126 Parma, Italy
- Geriatric Rehabilitation Department, University Hospital of Parma, 43126 Parma, Italy
| | - Anne Cappola
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Luigi Ferrucci
- National Institute on Aging, National Institutes of Health (NIH), Baltimore, MD 21201, USA
| | - Gian Paolo Ceda
- Department of Clinical and Experimental Medicine, Section of Geriatrics, University of Parma, 43126 Parma, Italy
- Geriatric Rehabilitation Department, University Hospital of Parma, 43126 Parma, Italy
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Schindhelm RK, ten Boekel E, Heima NE, van Schoor NM, Simsek S. Thyroid hormones and erythrocyte indices in a cohort of euthyroid older subjects. Eur J Intern Med 2013; 24:241-4. [PMID: 23276452 DOI: 10.1016/j.ejim.2012.12.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2012] [Revised: 12/03/2012] [Accepted: 12/05/2012] [Indexed: 11/22/2022]
Abstract
OBJECTIVES Hypothyroidism is associated with normocytic anaemia. Indeed, a limited number of studies have shown significant associations between free thyroxin (T4) and erythrocyte indices. These studies did not include vitamin B12, folic acid, iron and renal function in the analyses. We therefore studied the association between thyroid hormones and erythrocyte indices in a population-based cohort of older euthyroid subjects, with adjustment for major confounding parameters. DESIGN Data, including thyroid hormones and erythrocyte indices, are from the Longitudinal Aging Study Amsterdam (LASA), an ongoing cohort study on predictors and consequences of changes in health in the ageing population in the Netherlands. Multivariable linear regression analyses were applied to study the cross-sectional associations between free T4, thyroid stimulating hormone (TSH) and erythrocyte indices (haemoglobin content, haematocrit, mean cell volume (MCV) and erythrocyte count) in a euthyroid sub-sample. The final models were adjusted for vitamin B12, folic acid, iron levels and renal function. RESULTS In 708 euthyroid older subjects, an increase of 5pmol/L free T4 was associated with a mean increase of 0.12mmol/L or 0.19g/dL of haemoglobin, 0.068 10(12)/L erythrocytes and 0.006L/L haematocrit (P=0.007, P=0.005, P=0.001, respectively). Free T4 was not significantly associated with MCV (P>0.05). TSH appeared not to be associated with any of the erythrocyte indices (all P>0.05). CONCLUSIONS In a cohort of older subjects, free T4, but not TSH, was associated with erythrocyte indices, confirming the role of thyroid hormones in the regulation of erythropoiesis.
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Affiliation(s)
- Roger K Schindhelm
- Department of Clinical Chemistry, Haematology & Immunology, Medical Centre Alkmaar, Alkmaar, The Netherlands.
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