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Yang ML, Xu C, Gupte T, Hoffmann TJ, Iribarren C, Zhou X, Ganesh SK. Sex-specific genetic architecture of blood pressure. Nat Med 2024; 30:818-828. [PMID: 38459180 DOI: 10.1038/s41591-024-02858-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 02/05/2024] [Indexed: 03/10/2024]
Abstract
The genetic and genomic basis of sex differences in blood pressure (BP) traits remain unstudied at scale. Here, we conducted sex-stratified and combined-sex genome-wide association studies of BP traits using the UK Biobank resource, identifying 1,346 previously reported and 29 new BP trait-associated loci. Among associated loci, 412 were female-specific (Pfemale ≤ 5 × 10-8; Pmale > 5 × 10-8) and 142 were male-specific (Pmale ≤ 5 × 10-8; Pfemale > 5 × 10-8); these sex-specific loci were enriched for hormone-related transcription factors, in particular, estrogen receptor 1. Analyses of gene-by-sex interactions and sexually dimorphic effects identified four genomic regions, showing female-specific associations with diastolic BP or pulse pressure, including the chromosome 13q34-COL4A1/COL4A2 locus. Notably, female-specific pulse pressure-associated loci exhibited enriched acetylated histone H3 Lys27 modifications in arterial tissues and a female-specific association with fibromuscular dysplasia, a female-biased vascular disease; colocalization signals included Chr13q34: COL4A1/COL4A2, Chr9p21: CDKN2B-AS1 and Chr4q32.1: MAP9 regions. Sex-specific and sex-biased polygenic associations of BP traits were associated with multiple cardiovascular traits. These findings suggest potentially clinically significant and BP sex-specific pleiotropic effects on cardiovascular diseases.
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Affiliation(s)
- Min-Lee Yang
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chang Xu
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Trisha Gupte
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Thomas J Hoffmann
- Department of Epidemiology & Biostatistics, and Institute for Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Xiang Zhou
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Santhi K Ganesh
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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Douma Z, Dallel M, Bahia W, Ben Salem A, Hachani Ben Ali F, Almawi WY, Lautier C, Haydar S, Grigorescu F, Mahjoub T. Association of estrogen receptor gene variants (ESR1 and ESR2) with polycystic ovary syndrome in Tunisia. Gene 2020; 741:144560. [PMID: 32169631 DOI: 10.1016/j.gene.2020.144560] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 03/08/2020] [Indexed: 02/07/2023]
Abstract
SNV (single nucleotide variation) in estrogen receptor (ESR1 and ESR2) genes are susceptibility markers for complex diseases, such as cancer, metabolic disorders and women infertility. We explored six widely used SNVs in ESR1 (rs2234693, rs9340799, rs3798577, rs3020314) and ESR2 (rs1256049, rs4986938) in polycystic ovary syndrome (PCOS) in women from Tunisia (n = 254) compared to controls (n = 170). Genotyping was performed by RFLP-PCR or real-time PCR and analyzed in GoldenHelix statistical package. Logistic regression revealed association of rs2234693, rs3798577 and rs3020314 (ESR1) and rs1256049 (ESR2), the association of rs2234693 (C/T) being the strongest with P < 4.81 × 10-6, 2.88 × 10-5 after Bonferroni correction, OR 0.31, 95%CI (0.18-0.53)). Correlations were found with LH, LH/FSH or hyperandrogenism and even more significant with metabolic syndrome (rs9340799) and hyperglycemia (rs3798577). Among 14 haplotypes reconstructed in ESR1gene, four haplotypes (H1 to H4) were associated with PCOS the strongest being that of H1 (P < 0.002) supported by Bonferroni (P < 0.033) and permutation tests (P < 4 x10-4). In haplotype trend regression, concordant correlations were found with insulin resistance (P < 0.033) for H2 and with high blood pressure for H3 (P < 0.048). While these data revealed influential role on metabolic rather and hormonal features of PCOS, the association of rs2234693 was the strongest among all ethnic populations studied thus far giving a new insight on estrogen receptor gene variation in distant North African populations and their role in metabolic alteration of PCOS.
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Affiliation(s)
- Zeineb Douma
- Laboratory of Human Genome and Multifactorial Diseases (LR12ES07), Faculty of Pharmacy, University of Monastir, Monastir, Tunisia
| | - Meriem Dallel
- Laboratory of Human Genome and Multifactorial Diseases (LR12ES07), Faculty of Pharmacy, University of Monastir, Monastir, Tunisia
| | - Weal Bahia
- Laboratory of Human Genome and Multifactorial Diseases (LR12ES07), Faculty of Pharmacy, University of Monastir, Monastir, Tunisia
| | - Assila Ben Salem
- Laboratory of Human Genome and Multifactorial Diseases (LR12ES07), Faculty of Pharmacy, University of Monastir, Monastir, Tunisia
| | | | - Wassim Y Almawi
- School of Medicine, Nazarbayev University, Astana, Kazakhstan and Faculty of Sciences, El-Manar University, Tunis, Tunisia
| | - Corinne Lautier
- University of Montpellier, UMR204 NUTRIPASS (IRD, UM, SupAgro), Montpellier, France
| | - Sara Haydar
- University of Montpellier, UMR204 NUTRIPASS (IRD, UM, SupAgro), Montpellier, France
| | - Florin Grigorescu
- University of Montpellier, UMR204 NUTRIPASS (IRD, UM, SupAgro), Montpellier, France; Institut Convergences Migrations, Collège de France, Paris, France.
| | - Touhemi Mahjoub
- Laboratory of Human Genome and Multifactorial Diseases (LR12ES07), Faculty of Pharmacy, University of Monastir, Monastir, Tunisia
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Abstract
The past decade has witnessed an exponential increase in our ability to search the genome for genetic factors predisposing to cardiovascular disease (CVD) and in particular coronary heart disease (CHD). Identifying these genes could lead to the development of innovative strategies to prevent the cardiovascular complications of diabetes by allowing us to 1) create predictive algorithms for the identification of patients at especially high risk of CVD so that these individuals can undergo preventive interventions early in the natural history of the disease; 2) discover as yet unknown disease pathways linking diabetes to atherosclerosis, which can be used as targets for the development of new CVD-preventing drugs specifically directed at subjects with diabetes; and 3) devise personalized programs increasing the cost-effectiveness of preventive interventions by tailoring them to the genetic background of each patient. Substantial progress has been made in each of these three areas as exemplified by the recent development of a CHD genetic risk score improving CHD prediction among subjects with type 2 diabetes, the discovery of a diabetes-specific CHD locus on 1q25 pointing to glutamine synthase (GLUL) and the γ-glutamyl cycle as key regulators of CHD risk in diabetes, and the identification of two genetic loci allowing the selection of patients with type 2 diabetes who may especially benefit from intensive glycemic control. Translating these discoveries into clinical practice will not be without challenges, but the potential rewards, from the perspective of public health as well as that of persons with diabetes, make this goal worth pursuing.
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Affiliation(s)
- Alessandro Doria
- Research Division, Joslin Diabetes Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
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Mahmoodzadeh S, Dworatzek E. The Role of 17β-Estradiol and Estrogen Receptors in Regulation of Ca 2+ Channels and Mitochondrial Function in Cardiomyocytes. Front Endocrinol (Lausanne) 2019; 10:310. [PMID: 31156557 PMCID: PMC6529529 DOI: 10.3389/fendo.2019.00310] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Accepted: 04/30/2019] [Indexed: 11/13/2022] Open
Abstract
Numerous epidemiological, clinical, and animal studies showed that cardiac function and manifestation of cardiovascular diseases (CVDs) are different between males and females. The underlying reasons for these sex differences are definitely multifactorial, but major evidence points to a causal role of the sex steroid hormone 17β-estradiol (E2) and its receptors (ER) in the physiology and pathophysiology of the heart. Interestingly, it has been shown that cardiac calcium (Ca2+) ion channels and mitochondrial function are regulated in a sex-specific manner. Accurate mitochondrial function and Ca2+ signaling are of utmost importance for adequate heart function and crucial to maintaining the cardiovascular health. Due to the highly sensitive nature of these processes in the heart, this review article highlights the current knowledge regarding sex dimorphisms in the heart implicating the importance of E2 and ERs in the regulation of cardiac mitochondrial function and Ca2+ ion channels, thus the contractility. In particular, we provide an overview of in-vitro and in-vivo studies using either E2 deficiency; ER deficiency or selective ER activation, which suggest that E2 and ERs are strongly involved in these processes. In this context, this review also discusses the divergent E2-responses resulting from the activation of different ER subtypes in these processes. Detailed understanding of the E2 and ER-mediated molecular and cellular mechanisms in the heart under physiological and pathological conditions may help to design more specifically targeted drugs for the management of CVDs in men and women.
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Affiliation(s)
- Shokoufeh Mahmoodzadeh
- Department of Molecular Muscle Physiology, Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
- *Correspondence: Shokoufeh Mahmoodzadeh
| | - Elke Dworatzek
- Department of Molecular Muscle Physiology, Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
- Institute of Gender in Medicine, Charité Universitaetsmedizin, Berlin, Germany
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Shah HS, Gao H, Morieri ML, Skupien J, Marvel S, Paré G, Mannino GC, Buranasupkajorn P, Mendonca C, Hastings T, Marcovina SM, Sigal RJ, Gerstein HC, Wagner MJ, Motsinger-Reif AA, Buse JB, Kraft P, Mychaleckyj JC, Doria A. Genetic Predictors of Cardiovascular Mortality During Intensive Glycemic Control in Type 2 Diabetes: Findings From the ACCORD Clinical Trial. Diabetes Care 2016; 39:1915-1924. [PMID: 27527847 PMCID: PMC5079609 DOI: 10.2337/dc16-0285] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2016] [Accepted: 07/20/2016] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To identify genetic determinants of increased cardiovascular mortality among subjects with type 2 diabetes who underwent intensive glycemic therapy in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. RESEARCH DESIGN AND METHODS A total of 6.8 million common variants were analyzed for genome-wide association with cardiovascular mortality among 2,667 self-reported white subjects in the ACCORD intensive treatment arm. Significant loci were examined in the entire ACCORD white genetic dataset (n = 5,360) for their modulation of cardiovascular responses to glycemic treatment assignment and in a Joslin Clinic cohort (n = 422) for their interaction with long-term glycemic control on cardiovascular mortality. RESULTS Two loci, at 10q26 and 5q13, attained genome-wide significance as determinants of cardiovascular mortality in the ACCORD intensive arm (P = 9.8 × 10-9 and P = 2 × 10-8, respectively). A genetic risk score (GRS) defined by the two variants was a significant modulator of cardiovascular mortality response to treatment assignment in the entire ACCORD white genetic dataset. Participants with GRS = 0 experienced a fourfold reduction in cardiovascular mortality in response to intensive treatment (hazard ratio [HR] 0.24 [95% CI 0.07-0.86]), those with GRS = 1 experienced no difference (HR 0.92 [95% CI 0.54-1.56]), and those with GRS ≥2 experienced a threefold increase (HR 3.08 [95% CI 1.82-5.21]). The modulatory effect of the GRS on the association between glycemic control and cardiovascular mortality was confirmed in the Joslin cohort (P = 0.029). CONCLUSIONS Two genetic variants predict the cardiovascular effects of intensive glycemic control in ACCORD. Further studies are warranted to determine whether these findings can be translated into new strategies to prevent cardiovascular complications of diabetes.
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Affiliation(s)
- Hetal S Shah
- Research Division, Joslin Diabetes Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - He Gao
- Research Division, Joslin Diabetes Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Mario Luca Morieri
- Research Division, Joslin Diabetes Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Jan Skupien
- Research Division, Joslin Diabetes Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Department of Metabolic Diseases, Jagiellonian University Medical College, Krakow, Poland
| | - Skylar Marvel
- Bioinformatics Research Center and Department of Statistics, North Carolina State University, Raleigh, NC
| | - Guillaume Paré
- Department of Medicine and the Population Health Research Institute, McMaster University and Hamilton Health Sciences, Ontario, Canada
| | - Gaia C Mannino
- Research Division, Joslin Diabetes Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Patinut Buranasupkajorn
- Research Division, Joslin Diabetes Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | | | | | - Santica M Marcovina
- Department of Medicine, University of Washington, and Northwest Lipid Metabolism and Diabetes Research Laboratories, Seattle, WA
| | - Ronald J Sigal
- Departments of Medicine, Cardiac Sciences, and Community Health Sciences, Cumming School of Medicine, Faculties of Medicine and Kinesiology, University of Calgary, Alberta, Canada
| | - Hertzel C Gerstein
- Department of Medicine and the Population Health Research Institute, McMaster University and Hamilton Health Sciences, Ontario, Canada
| | - Michael J Wagner
- Center for Pharmacogenomics and Individualized Therapy, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Alison A Motsinger-Reif
- Bioinformatics Research Center and Department of Statistics, North Carolina State University, Raleigh, NC
| | - John B Buse
- Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Peter Kraft
- Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA
| | - Alessandro Doria
- Research Division, Joslin Diabetes Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
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