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Jiang Y, Liu S, Liu G, Pan A, Peng M, Liao Y. Association between sex hormones and gout: An analysis of the UK Biobank cohort. Steroids 2024; 207:109422. [PMID: 38599307 DOI: 10.1016/j.steroids.2024.109422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 04/07/2024] [Accepted: 04/07/2024] [Indexed: 04/12/2024]
Abstract
OBJECTIVES To investigate the associations between sex hormones and gout. METHODS A total of 448,836 individuals free of gout at baseline were included from the UK Biobank. Cox regression models were used to estimate hazard ratios (HRs) for gout. Besides, we investigated the causal relationship between bioavailable testosterone (BAT) and gout using mendelian randomization (MR). RESULTS There were differential effects in different testosterone active states in gout. One-unit higher log-transformed total testosterone (TT) was associated with a 52 % [95 % CI, 0.39-0.58] lower risk of gout in males. In contrast, free testosterone (FT) and BAT were associated with a 74 % [95 % CI, 1.38-2.20] and a 78 % [95 % CI, 1.41-2.25] higher risk of gout in males respectively. For MR, the weighted median [OR, 1.70; 95 % CI, 1.14-2.56;] and inverse variance-weighted [OR, 1.25; 95 % CI, 0.96-1.62; P = 0.09] method revealed significant and approximately significant positive effect of genetic liability to BAT levels on the risk of gout respectively. CONCLUSIONS Sex hormones were potentially associated with gout. Notably, we were the first to explore different testosterone states on gout and found that FT and BAT may increase the risk of gout in males, which is opposite to TT. And the former are active states of androgens, may be more accurately reflect the association between androgens and gout.
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Affiliation(s)
- Yaoyao Jiang
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China
| | - Sen Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Gang Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - An Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Miaomiao Peng
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China.
| | - Yunfei Liao
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China.
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Pastika L, Sau A, Patlatzoglou K, Sieliwonczyk E, Ribeiro AH, McGurk KA, Khan S, Mandic D, Scott WR, Ware JS, Peters NS, Ribeiro ALP, Kramer DB, Waks JW, Ng FS. Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease. NPJ Digit Med 2024; 7:167. [PMID: 38918595 PMCID: PMC11199586 DOI: 10.1038/s41746-024-01170-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 06/14/2024] [Indexed: 06/27/2024] Open
Abstract
The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, and validated on UK Biobank (UKB) (n = 42,386), the model achieved a Pearson correlation coefficient (r) of 0.65 and 0.62, and an R2 of 0.43 and 0.39 in the BIDMC cohort and UK Biobank, respectively for AI-ECG BMI vs. measured BMI. We found delta-BMI, the difference between measured BMI and AI-ECG-predicted BMI (AI-ECG-BMI), to be a biomarker of cardiometabolic health. The top tertile of delta-BMI showed increased risk of future cardiometabolic disease (BIDMC: HR 1.15, p < 0.001; UKB: HR 1.58, p < 0.001) and diabetes mellitus (BIDMC: HR 1.25, p < 0.001; UKB: HR 2.28, p < 0.001) after adjusting for covariates including measured BMI. Significant enhancements in model fit, reclassification and improvements in discriminatory power were observed with the inclusion of delta-BMI in both cohorts. Phenotypic profiling highlighted associations between delta-BMI and cardiometabolic diseases, anthropometric measures of truncal obesity, and pericardial fat mass. Metabolic and proteomic profiling associates delta-BMI positively with valine, lipids in small HDL, syntaxin-3, and carnosine dipeptidase 1, and inversely with glutamine, glycine, colipase, and adiponectin. A genome-wide association study revealed associations with regulators of cardiovascular/metabolic traits, including SCN10A, SCN5A, EXOG and RXRG. In summary, our AI-ECG-BMI model accurately predicts BMI and introduces delta-BMI as a non-invasive biomarker for cardiometabolic risk stratification.
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Affiliation(s)
- Libor Pastika
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Arunashis Sau
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Department of Cardiology, Imperial College Healthcare NHS Trust, London, United Kingdom
| | | | - Ewa Sieliwonczyk
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- MRC Laboratory of Medical Sciences, Imperial College London, London, United Kingdom
| | - Antônio H Ribeiro
- Department of Information Technology, Uppsala University, Uppsala, Sweden
| | - Kathryn A McGurk
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- MRC Laboratory of Medical Sciences, Imperial College London, London, United Kingdom
| | - Sadia Khan
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Chelsea and Westminster NHS Foundation Trust, London, United Kingdom
| | - Danilo Mandic
- Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
| | - William R Scott
- MRC Laboratory of Medical Sciences, Imperial College London, London, United Kingdom
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - James S Ware
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- MRC Laboratory of Medical Sciences, Imperial College London, London, United Kingdom
| | - Nicholas S Peters
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Department of Cardiology, Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Antonio Luiz P Ribeiro
- Department of Internal Medicine, Faculdade de Medicina, and Telehealth Center and Cardiology Service, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Daniel B Kramer
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Jonathan W Waks
- Harvard-Thorndike Electrophysiology Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Fu Siong Ng
- National Heart and Lung Institute, Imperial College London, London, United Kingdom.
- Department of Cardiology, Imperial College Healthcare NHS Trust, London, United Kingdom.
- Chelsea and Westminster NHS Foundation Trust, London, United Kingdom.
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Ma H, Chen Y. Examining the causal relationship between sex hormone-binding globulin (SHBG) and infertility: A Mendelian randomization study. PLoS One 2024; 19:e0304216. [PMID: 38848344 PMCID: PMC11161117 DOI: 10.1371/journal.pone.0304216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 05/09/2024] [Indexed: 06/09/2024] Open
Abstract
BACKGROUND The causal relationship between sex hormone-binding globulin (SHBG) and infertility has remained unclear. Thus, we used Mendelian randomization (MR) to investigate this relationship. METHODS Risk factors for SHBG were extracted from European individuals within the UK Biobank using single-nucleotide polymorphism (SNP) data. Summary-level data for infertility outcomes were obtained from the FinnGen dataset. The causal relationship between SHBG and infertility was examined using inverse variance weighted, weighted model, weighted median, and MR-Egger regression analyses. Additionally, Cochran's Q test and Egger intercept tests were used to confirm the heterogeneity and pleiotropy of identified instrumental variables (IVs). RESULTS Our findings revealed a significant negative association between sex hormone-binding globulin (SHBG) levels and infertility, particularly with anovulation, a specific form of female infertility. However, SHBG did not exert a causal impact on male infertility or on female infertility of tubal origin. CONCLUSIONS SHBG expression offers protection against the development of certain types of female infertility, suggesting it is a potential therapeutic target for infertility.
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Affiliation(s)
- Hanghao Ma
- Department of Internal Medicine, Ningde People’s Hospital, Ningde, Fujian, China
| | - Yan Chen
- Department of Ultrasound, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China
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Cai M, Chen J. Association between life's essential 8 and testosterone deficiency in men: NHANES 2011-2016. Front Endocrinol (Lausanne) 2024; 15:1394383. [PMID: 38887271 PMCID: PMC11180778 DOI: 10.3389/fendo.2024.1394383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 05/22/2024] [Indexed: 06/20/2024] Open
Abstract
Background Serum testosterone is intrinsically associated to cardiovascular disease. Our aim is to explore the relationship between the recently updated cardiovascular health measurement, known as Life's Essential 8 (LE8), and the prevalence of testosterone deficiency (TD) in adult males in the United States. Methods Study data was obtained from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016. A weighted multivariate logistic regression model was applied to evaluate the correlation between LE8 and testosterone deficiency. Restricted Cubic Spline (RCS) was employed to explore its non-linear relationship. In addition, a stratified analysis was conducted. Results The final analysis included 2332 participants from NHANES from 2011 to 2016. After adjusting for confounding factors, the odds ratios (ORs) and 95% confidence intervals (CIs) for testosterone deficiency in participants with moderate and higher LE8 scores compared to the lowest LE8 scores were 0.59 (0.38-0.92) and 0.38 (0.19-0.76), respectively. The results of subgroup analysis showed that LE8 score was significantly associated with TD among young and middle-aged participants. Conclusion A lower LE8 score is related to a higher incidence of testosterone deficiency, especially in young and middle-aged men. Further research is necessary to explore the potential mechanisms between them.
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Affiliation(s)
| | - Jinzao Chen
- Department of Cardiology, The First Hospital of Putian City, Putian, Fujian, China
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Sun W, Wang Y, Li C, Yao X, Wu X, He A, Zhao B, Huang X, Song H. Genetically predicted high serum sex hormone-binding globulin levels are associated with lower ischemic stroke risk: A sex-stratified Mendelian randomization study. J Stroke Cerebrovasc Dis 2024; 33:107686. [PMID: 38522757 DOI: 10.1016/j.jstrokecerebrovasdis.2024.107686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 03/17/2024] [Accepted: 03/19/2024] [Indexed: 03/26/2024] Open
Abstract
OBJECTIVE Cross-sectional and cohort studies have found insufficient evidence of a causal relationship between sex hormone-binding globulin and ischemic stroke, only associations. Here, we performed a sex-stratified, bidirectional, two-sample Mendelian randomization analysis to evaluate whether a causal relationship exists between sex hormone-binding globulin and ischemic stroke. METHODS Single-nucleotide polymorphisms associated with sex hormone-binding globulin and ischemic stroke were screened from genome-wide association studies summary data as instrumental variables to enable a bidirectional, two-sample Mendelian randomization study design. Inverse-variance weighted analysis was used as the main method to evaluate potential causality, and additional methods, including the weighted median and MR-Egger tests, were used to validate the Mendelian randomization results. Cochran's Q statistic, MR-Egger intercept test, and Mendelian Randomization-Pleiotropy Residual Sum and Outlier global test were used as sensitivity analysis techniques to assure the reliability of the results. Multivariable analysis was used to show the robustness of the results with key theorized confounders. RESULTS Inverse-variance weighted analysis showed that genetically predicted higher serum sex hormone-binding globulin levels were associated with significantly decreased risk of ischemic stroke in males (odds radio = 0.934, 95 % confidence interval = 0.885-0.985, P = 0.012) and females (odds radio = 0.924, 95 % confidence interval = 0.868-0.983, P = 0.013). In an analysis of ischemic stroke subtypes, genetically predicted higher serum sex hormone-binding globulin levels were also associated with significantly decreased risk of small-vessel occlusion in both males (odds radio = 0.849, 95 % confidence interval = 0.759-0.949, P = 0.004) and females (odds radio = 0.829, 95 % confidence interval = 0.724-0.949, P = 0.006). The association remained in sensitivity analyses and multivariable analyses. The reverse analysis suggested an association between genetically predicted risk of cardioembolism and increased serum sex hormone-binding globulin in females (Beta = 0.029 nmol/L, Standard Error = 0.010, P = 0.003). CONCLUSION Our findings provide new insight into the etiology of ischemic stroke and suggest that modulating serum sex hormone-binding globulin may be a therapeutic strategy to protect against ischemic stroke.
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Affiliation(s)
- Wei Sun
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Yuan Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Cancan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Xuefan Yao
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Xiao Wu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Aini He
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Benke Zhao
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Xiaoqin Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Haiqing Song
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
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Weng C, Shao Z, Xiao M, Song M, Zhao Y, Li A, Pang Y, Huang T, Yu C, Lv J, Li L, Sun D. Association of sex hormones with non-alcoholic fatty liver disease: An observational and Mendelian randomization study. Liver Int 2024; 44:1154-1166. [PMID: 38345150 DOI: 10.1111/liv.15866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 01/20/2024] [Accepted: 01/28/2024] [Indexed: 04/19/2024]
Abstract
BACKGROUND AND AIMS Sex-specific associations of sex hormone-binding globulin (SHBG) and bioavailable testosterone (BAT) with NAFLD remain indeterminate. We aimed to explore observational and genetically determined relationships between each hormone and NAFLD. METHODS We included 187 395 men and 170 193 women from the UK Biobank. Linear and nonlinear Cox regression models and Mendelian randomization (MR) analysis were used to test the associations. RESULTS During 12.49 years of follow-up, 2209 male and 1886 female NAFLD cases were documented. Elevated SHBG levels were linearly associated with a lower risk of NAFLD in women (HR (95% CI), .71 (.63, .79)), but not in men (a "U" shape, pnon-linear < .001). Higher BAT levels were associated with a lower NAFLD risk in men (HR (95% CI), .81 (.71, .93)) but a higher risk in women (HR (95% CI): 1.25 (1.15, 1.36)). Genetically determined SHBG and BAT levels were linearly associated with NAFLD risk in women (OR (95% CI): .57 (.38, .87) and 2.21 (1.41, 3.26) respectively); in men, an "L-shaped" MR association between SHBG levels and NAFLD risk was found (pnon-linear = .016). The bidirectional MR analysis further revealed the effect of NAFLD on SHBG and BAT levels in both sexes. CONCLUSIONS Consistently, linear associations of lower SHBG and higher BAT levels with increased NAFLD risk were both conventionally and genetically found in women, while in men, SHBG acts in a nonlinear manner. In addition, NAFLD may affect SHBG and BAT levels.
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Affiliation(s)
- Chenghao Weng
- School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China
| | - Zilun Shao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Meng Xiao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Mingyu Song
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Yuxuan Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Aolin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
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Cao S, Hu Y. Creating machine learning models that interpretably link systemic inflammatory index, sex steroid hormones, and dietary antioxidants to identify gout using the SHAP (SHapley Additive exPlanations) method. Front Immunol 2024; 15:1367340. [PMID: 38751428 PMCID: PMC11094226 DOI: 10.3389/fimmu.2024.1367340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 04/22/2024] [Indexed: 05/18/2024] Open
Abstract
Background The relationship between systemic inflammatory index (SII), sex steroid hormones, dietary antioxidants (DA), and gout has not been determined. We aim to develop a reliable and interpretable machine learning (ML) model that links SII, sex steroid hormones, and DA to gout identification. Methods The dataset we used to study the relationship between SII, sex steroid hormones, DA, and gout was from the National Health and Nutrition Examination Survey (NHANES). Six ML models were developed to identify gout by SII, sex steroid hormones, and DA. The seven performance discriminative features of each model were summarized, and the eXtreme Gradient Boosting (XGBoost) model with the best overall performance was selected to identify gout. We used the SHapley Additive exPlanation (SHAP) method to explain the XGBoost model and its decision-making process. Results An initial survey of 20,146 participants resulted in 8,550 being included in the study. Selecting the best performing XGBoost model associated with SII, sex steroid hormones, and DA to identify gout (male: AUC: 0.795, 95% CI: 0.746- 0.843, accuracy: 98.7%; female: AUC: 0.822, 95% CI: 0.754- 0.883, accuracy: 99.2%). In the male group, The SHAP values showed that the lower feature values of lutein + zeaxanthin (LZ), vitamin C (VitC), lycopene, zinc, total testosterone (TT), vitamin E (VitE), and vitamin A (VitA), the greater the positive effect on the model output. In the female group, SHAP values showed that lower feature values of E2, zinc, lycopene, LZ, TT, and selenium had a greater positive effect on model output. Conclusion The interpretable XGBoost model demonstrated accuracy, efficiency, and robustness in identifying associations between SII, sex steroid hormones, DA, and gout in participants. Decreased TT in males and decreased E2 in females may be associated with gout, and increased DA intake and decreased SII may reduce the potential risk of gout.
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Affiliation(s)
- Shunshun Cao
- Pediatric Endocrinology, Genetics and Metabolism, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yangyang Hu
- Reproductive Medicine Center, Obstetrics and Gynecology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
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Qin T, Chu Y, Yao Y, Zhang C, Xu B, Song Q. Coffee intake reduced gout risk by decreasing urate and urea while increasing SHBG levels in plasma: a mediation Mendelian randomization study. Clin Rheumatol 2024; 43:1735-1743. [PMID: 38448745 DOI: 10.1007/s10067-024-06922-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 12/07/2023] [Accepted: 02/26/2024] [Indexed: 03/08/2024]
Abstract
OBJECTIVE This study aims to investigate the causal relationships between specific dietary habits and the risk of gout, while identifying the mediators involved in these associations. METHODS We initially assessed the causal effects of five dietary habits on gout by two-sample Mendelian randomization (MR). Subsequently, we identified mediators from five plasma metabolites by two-step MR, including urate, urea, sex hormone-binding globulin (SHBG), interleukin-18 (IL-18), and C-reactive protein (CRP). Next, we quantified the proportion of mediation effects by multivariable Mendelian randomization (MVMR). Last, we performed reverse MR analyses. Sensitivity analyses were conducted to enhance the robustness of our findings. RESULTS Only coffee intake demonstrated a significant negative casual effect on gout (inverse variance weighted: OR = 0.444, p = 0.049). In two-step MR, coffee intake decreased urate and urea while increased SHBG levels, but did not affect IL-18 and CRP levels. Besides, urate and urea showed positive causal effects while SHBG exhibited a negative impact on gout. In mediation analysis, urate, urea, and SHBG respectively mediated 53.60%, 16.43%, and 4.81% of the total causal effect of coffee intake on gout. The three mediators collectively mediated 27.45% of the total effect. Reverse MR analyses suggested no significant reverse causal effects. Sensitivity analyses supported the reliability of our causal inferences. CONCLUSION Coffee intake reduced gout risk by decreasing urate and urea while increasing SHBG levels in plasma. These findings accentuate the benefits of coffee intake for gout management. The mediators may provide a novel insight into potential therapeutic targets for gout prevention. Key Points • This study determines the causally protective effect of coffee intake on gout. • We reveal that coffee intake reduced the risk of gout by decreasing urate and urea while increasing SHBG levels in plasma. • Identifying specific mediators in the causal pathway from coffee intake to gout provides valuable information for clinical interventions of gout.
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Affiliation(s)
- Tingting Qin
- Cancer Center, Renmin Hospital of Wuhan University, Jiefang Road No. 238, Wuhan, 430060, China
| | - Yuxin Chu
- Cancer Center, Renmin Hospital of Wuhan University, Jiefang Road No. 238, Wuhan, 430060, China
| | - Yi Yao
- Cancer Center, Renmin Hospital of Wuhan University, Jiefang Road No. 238, Wuhan, 430060, China
| | - Cai Zhang
- Cancer Center, Renmin Hospital of Wuhan University, Jiefang Road No. 238, Wuhan, 430060, China
| | - Bin Xu
- Cancer Center, Renmin Hospital of Wuhan University, Jiefang Road No. 238, Wuhan, 430060, China
| | - Qibin Song
- Cancer Center, Renmin Hospital of Wuhan University, Jiefang Road No. 238, Wuhan, 430060, China.
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Yuan S, Jiang F, Chen J, Lebwohl B, Green PHR, Leffler D, Larsson SC, Li X, Ludvigsson JF. Phenome-wide Mendelian randomization analysis reveals multiple health comorbidities of coeliac disease. EBioMedicine 2024; 101:105033. [PMID: 38382313 PMCID: PMC10900254 DOI: 10.1016/j.ebiom.2024.105033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/28/2024] [Accepted: 02/09/2024] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Coeliac disease (CeD) has been associated with a broad range of diseases in observational data; however, whether these associations are causal remains undetermined. We conducted a phenome-wide Mendelian randomization analysis (MR-PheWAS) to investigate the comorbidities of CeD. METHODS Single nucleotide polymorphisms (SNPs) associated with CeD at the genome-wide significance threshold and without linkage disequilibrium (R2 <0.001) were selected from a genome-wide association study including 12,041 CeD cases as the instrumental variables. We first constructed a polygenic risk score for CeD and estimated its associations with 1060 unique clinical outcomes in the UK Biobank study (N = 385,917). We then used two-sample MR analysis to replicate the identified associations using data from the FinnGen study (N = 377,277). We performed a secondary analysis using a genetic instrument without extended MHC gene SNPs. FINDINGS Genetic liability to CeD was associated with 68 clinical outcomes in the UK Biobank, and 38 of the associations were replicated in the FinnGen study. Genetic liability to CeD was associated with a higher risk of several autoimmune diseases (type 1 diabetes and its complications, Graves' disease, Sjögren syndrome, chronic hepatitis, systemic and cutaneous lupus erythematosus, and sarcoidosis), non-Hodgkin's lymphoma, and osteoporosis and a lower risk of prostate diseases. The associations for type 1 diabetes and non-Hodgkin's lymphoma attenuated when excluding SNPs in the MHC region, indicating shared genetic aetiology. INTERPRETATION This study uncovers multiple clinical outcomes associated with genetic liability to CeD, which suggests the necessity of comorbidity monitoring among this population. FUNDING This project was funded by Karolinska Institutet and the Swedish Research Council.
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Affiliation(s)
- Shuai Yuan
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
| | - Fangyuan Jiang
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jie Chen
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Benjamin Lebwohl
- Department of Medicine, Celiac Disease Center at Columbia University Medical Center, New York, NY, USA
| | - Peter H R Green
- Departments of Medicine and Surgical Pathology, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Daniel Leffler
- The Celiac Center at Beth Israel Deaconess Medical Center, Harvard Medical School, USA
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Xue Li
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| | - Jonas F Ludvigsson
- Department of Medicine, Celiac Disease Center at Columbia University Medical Center, New York, NY, USA; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Pediatrics, Orebro University Hospital, Orebro, Sweden.
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Lai S, Jin Q, Wang D, Li T, Wang X. Effects of menstrual disorders and dysmenorrhea on cardiovascular disease: a Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1302312. [PMID: 38375191 PMCID: PMC10875084 DOI: 10.3389/fendo.2024.1302312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 01/19/2024] [Indexed: 02/21/2024] Open
Abstract
Background Observational studies have demonstrated associations between menstrual disorders, dysmenorrhea, and cardiovascular disease (CVD). However, it remains unclear whether these associations are causal. This study is to investigate whether menstrual disorders and dysmenorrhea causally affect the risk of CVD. Methods The summary data for menstrual disorders (excessive menstruation and irregular menses) and dysmenorrhea were obtained from FinnGen study, summary data for CVD were obtained from UK Biobank and meta-analysis. The inverse-variance-weighted method was mainly used in the Mendelian randomization for causality analysis. Sensitivity analyses were performed by several methods under different model assumptions. Results Genetic liability to excessive menstruation was associated with higher risk of atrial fibrillation (odds ratio (OR), 1.078 [95% confidence interval (CI), 1.015-1.145]; P=0.014), but a lower risk of hypertension (OR, 0.994 [95% CI: 0.989-0.999]; P=0.016). Irregular menses was associated with higher risk of atrial fibrillation (OR, 1.095 [95% CI: 1.015-1.182]; P=0.02), hypertension (OR, 1.007 [95% CI: 1.000-1.013]; P=0.047), myocardial infarction (OR, 1.172 [95% CI: 1.060-1.295]; P=0.02), ischemic heart disease, (OR, 1.005 [95% CI: 1.000-1.010]; P=0.037) and coronary heart disease (OR, 1.004 [95% CI: 1.001-1.008]; P=0.026). Dysmenorrhea was associated with higher risk of atrial fibrillation (OR, 1.052 [95% CI: 1.014-1.092]; P=0.008) and Ischemic stroke (cardioembolic) (OR, 1.122 [95% CI: 1.002-1.257]; P=0.046). After Benjamini-Hochberg correction, irregular menses was associated with higher risk of myocardial infarction. Conclusion We confirmed a causal relationship of excessive menstruation, irregular menses and dysmenorrhea on cardiovascular outcomes independent of sex hormone levels, with an emphasis on the link between irregular menses and myocardial infarction. These clinical features can be utilized as markers to identify women at higher risk of developing CVD in the future, recommending early clinical intervention of menstrual diseases.
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Affiliation(s)
- Sijia Lai
- Institute of Cardiovascular Disease, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Qiubai Jin
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Dayang Wang
- Institute of Cardiovascular Disease, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Tianli Li
- National Integrated Traditional and Western Medicine Center for Cardiovascular Disease, China-Japan Friendship Hospital, Beijing, China
| | - Xian Wang
- Institute of Cardiovascular Disease, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
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11
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Scholz M, Horn K, Pott J, Wuttke M, Kühnapfel A, Nasr MK, Kirsten H, Li Y, Hoppmann A, Gorski M, Ghasemi S, Li M, Tin A, Chai JF, Cocca M, Wang J, Nutile T, Akiyama M, Åsvold BO, Bansal N, Biggs ML, Boutin T, Brenner H, Brumpton B, Burkhardt R, Cai J, Campbell A, Campbell H, Chalmers J, Chasman DI, Chee ML, Chee ML, Chen X, Cheng CY, Cifkova R, Daviglus M, Delgado G, Dittrich K, Edwards TL, Endlich K, Michael Gaziano J, Giri A, Giulianini F, Gordon SD, Gudbjartsson DF, Hallan S, Hamet P, Hartman CA, Hayward C, Heid IM, Hellwege JN, Holleczek B, Holm H, Hutri-Kähönen N, Hveem K, Isermann B, Jonas JB, Joshi PK, Kamatani Y, Kanai M, Kastarinen M, Khor CC, Kiess W, Kleber ME, Körner A, Kovacs P, Krajcoviechova A, Kramer H, Krämer BK, Kuokkanen M, Kähönen M, Lange LA, Lash JP, Lehtimäki T, Li H, Lin BM, Liu J, Loeffler M, Lyytikäinen LP, Magnusson PKE, Martin NG, Matsuda K, Milaneschi Y, Mishra PP, Mononen N, Montgomery GW, Mook-Kanamori DO, Mychaleckyj JC, März W, Nauck M, Nikus K, Nolte IM, Noordam R, Okada Y, Olafsson I, Oldehinkel AJ, Penninx BWJH, Perola M, Pirastu N, Polasek O, Porteous DJ, Poulain T, Psaty BM, Rabelink TJ, Raffield LM, Raitakari OT, Rasheed H, Reilly DF, Rice KM, Richmond A, Ridker PM, Rotter JI, Rudan I, Sabanayagam C, Salomaa V, Schneiderman N, Schöttker B, Sims M, Snieder H, Stark KJ, Stefansson K, Stocker H, Stumvoll M, Sulem P, Sveinbjornsson G, Svensson PO, Tai ES, Taylor KD, Tayo BO, Teren A, Tham YC, Thiery J, Thio CHL, Thomas LF, Tremblay J, Tönjes A, van der Most PJ, Vitart V, Völker U, Wang YX, Wang C, Wei WB, Whitfield JB, Wild SH, Wilson JF, Winkler TW, Wong TY, Woodward M, Sim X, Chu AY, Feitosa MF, Thorsteinsdottir U, Hung AM, Teumer A, Franceschini N, Parsa A, Köttgen A, Schlosser P, Pattaro C. X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements. Nat Commun 2024; 15:586. [PMID: 38233393 PMCID: PMC10794254 DOI: 10.1038/s41467-024-44709-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 12/30/2023] [Indexed: 01/19/2024] Open
Abstract
X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.
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Affiliation(s)
- Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.
| | - Katrin Horn
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Janne Pott
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Andreas Kühnapfel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - M Kamal Nasr
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Holger Kirsten
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Anselm Hoppmann
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Mathias Gorski
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Sahar Ghasemi
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Man Li
- Division of Nephrology and Hypertension, Department of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Adrienne Tin
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA
- Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Massimiliano Cocca
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Judy Wang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Teresa Nutile
- Institute of Genetics and Biophysics 'Adriano Buzzati-Traverso'-CNR, Naples, Italy
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Bjørn Olav Åsvold
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Nisha Bansal
- Division of Nephrology, University of Washington, Seattle, WA, USA
- Kidney Research Institute, University of Washington, Seattle, WA, USA
| | - Mary L Biggs
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Thibaud Boutin
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Ben Brumpton
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Clinic of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Ralph Burkhardt
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Regensburg, Germany
| | - Jianwen Cai
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Harry Campbell
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - John Chalmers
- The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Miao Ling Chee
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Miao Li Chee
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Xu Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Renata Cifkova
- Center for Cardiovascular Prevention, Charles University in Prague, First Faculty of Medicine and Thomayer University Hospital, Prague, Czech Republic
- Department of Medicine II, Charles University in Prague, First Faculty of Medicine, Prague, Czech Republic
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Graciela Delgado
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Katalin Dittrich
- University Hospital for Children and Adolescents, Pediatric Research Unit, Medical Faculty, University Medical Center, University of Leipzig, Leipzig, Germany
| | - Todd L Edwards
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Karlhans Endlich
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Anatomy and Cell Biology, University Medicine Greifswald, Greifswald, Germany
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, USA
| | - Ayush Giri
- Division of Quantitative Sciences, Department of Obstetrics & Gynecology, Vanderbilt Genetics Institute, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Iceland School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Stein Hallan
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Nephrology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Pavel Hamet
- Montreal University Hospital Research Center, CHUM, Montréal, QC, Canada
- Medpharmgene, Montreal, QC, Canada
| | - Catharina A Hartman
- Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Jacklyn N Hellwege
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bernd Holleczek
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Nina Hutri-Kähönen
- Tampere Centre for Skills Training and Simulation, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Berend Isermann
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Institute for Laboratory Medicine, University of Leipzig, Leipzig, Germany
| | - Jost B Jonas
- Department of Ophthalmology, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany
- Beijing Institute of Ophthalmology, Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland
- Privatpraxis Prof Jonas und Dr Panda-Jonas, Heidelberg, Germany
| | - Peter K Joshi
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Masahiro Kanai
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | | | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Wieland Kiess
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- University Hospital for Children and Adolescents, Pediatric Research Unit, Medical Faculty, University Medical Center, University of Leipzig, Leipzig, Germany
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Antje Körner
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- University Hospital for Children and Adolescents, Pediatric Research Unit, Medical Faculty, University Medical Center, University of Leipzig, Leipzig, Germany
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
| | - Peter Kovacs
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Alena Krajcoviechova
- Center for Cardiovascular Prevention, Charles University in Prague, First Faculty of Medicine and Thomayer University Hospital, Prague, Czech Republic
| | - Holly Kramer
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
- Division of Nephrology and Hypertension, Loyola University Chicago, Chicago, IL, USA
| | - Bernhard K Krämer
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Mikko Kuokkanen
- Finnish Institute for Health and Welfare, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado Denver-Anschutz Medical Campus, Aurora, CO, USA
| | - James P Lash
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and The Wellbeing Services County of Pirkanmaa, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Hengtong Li
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Bridget M Lin
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, and The Wellbeing Services County of Pirkanmaa, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | | | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC/Vrije Universiteit and GGZ inGeest, Amsterdam, the Netherlands
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Fimlab Laboratories, and The Wellbeing Services County of Pirkanmaa, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, and The Wellbeing Services County of Pirkanmaa, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | | | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, Charlottesville, VA, USA
| | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University Graz, Graz, Austria
- Synlab Academy, Synlab Holding Deutschland GmbH, Augsburg, Germany
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, Finland
- Department of Cardiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Yukinori Okada
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali University Hospital, Reykjavik, Iceland
| | - Albertine J Oldehinkel
- Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC/Vrije Universiteit and GGZ inGeest, Amsterdam, the Netherlands
| | - Markus Perola
- Finnish Institute for Health and Welfare, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Nicola Pirastu
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
- Biostatistics Unit - Population and Medical Genomics Programme, Genomics Research Centre, Human Technopole Palazzo Italia, Viale Rita Levi‑Montalcini, 1, 20157, Milan, Italy
| | | | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Tanja Poulain
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- University Hospital for Children and Adolescents, Pediatric Research Unit, Medical Faculty, University Medical Center, University of Leipzig, Leipzig, Germany
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, Department of Epidemiology, Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ton J Rabelink
- Department of Internal Medicine, Section of Nephrology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory of Experimental Vascular Research, Leiden University Medical Center, Leiden, the Netherlands
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Center of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Humaira Rasheed
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Division of Medicine and Laboratory Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | | | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Anne Richmond
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Igor Rudan
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Veikko Salomaa
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Neil Schneiderman
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Mario Sims
- Department of Social Medicine, Population and Public Health, University of California at Riverside School of Medicine, Riverside, CA, USA
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Klaus J Stark
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Hannah Stocker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | | | | | | | - Per O Svensson
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- Department of Cardiology, Södersjukhuset, Stockholm, Sweden
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Bamidele O Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
| | - Andrej Teren
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Department of Cardiology and Intensive Care Medicine, University Hospital OWL of Bielefeld University, Campus Klinikum Bielefeld, Teutoburger Straße 50, 33604, Bielefeld, Germany
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Joachim Thiery
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Institute for Laboratory Medicine, University of Leipzig, Leipzig, Germany
| | - Chris H L Thio
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Laurent F Thomas
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Laboratory Medicine, St.Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Johanne Tremblay
- Montreal University Hospital Research Center, CHUM, Montréal, QC, Canada
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Uwe Völker
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Chaolong Wang
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wen Bin Wei
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - John B Whitfield
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sarah H Wild
- Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - James F Wilson
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Tsinghua Medicine, Tsinghua University, Beijing, China
| | - Mark Woodward
- The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
- The George Institute for Global Health, School of Public Health, Imperial College London, London, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | | | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Adriana M Hung
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Vanderbilt University Medical Center, Division of Nephrology & Hypertension, Nashville, TN, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Afshin Parsa
- Division of Kidney, Urologic and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Cristian Pattaro
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
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Xu B, Mo W, Tan X, Zhang P, Huang J, Huang C, Guo D, Wei X, Liu Y, Lei X, Dou W, Lin J, Liu D, Yang L, Huang Y, Zhang H, Liao Y. Associations of Serum Testosterone and Sex Hormone-binding Globulin With Incident Arrhythmias in Men From UK Biobank. J Clin Endocrinol Metab 2024; 109:e745-e756. [PMID: 37665960 DOI: 10.1210/clinem/dgad526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 08/29/2023] [Accepted: 08/31/2023] [Indexed: 09/06/2023]
Abstract
CONTEXT Sex hormones have been identified as cardiovascular risk factors, whereas the relationship between sex hormones and the risk of arrhythmias in men has not yet been well studied in the prospective cohort study. OBJECTIVE To analyze associations of serum testosterone and SHBG concentrations and calculate free testosterone (cFT) with arrhythmias in men. METHODS Sex hormones were measured at baseline from UK Biobank. Main outcomes were incidence of atrial fibrillation/flutter (AF), ventricular arrhythmia (VA), and bradyarrhythmia (BA). RESULTS Of 173 498 men (aged 37-73 years, followed for 11 years), 11 368 had incident AF, 1646 had incident VA, and 4788 had incident BA. Compared with the third quartiles, the lowest category of serum testosterone was associated with increased risks of AF (hazard ratio [HR], 1.06; 95% CI, 1.00-1.12) and BA (HR, 1.11; 95% CI, 1.02-1.20) after multivariable adjustment, but no VA. Likewise, similar associations were found between cFT values and AF and BA events. Furthermore, higher levels of cFT were associated with increased risks of AF (HR, 1.07; 95% CI, 1.02-1.13) and VA (HR, 1.18; 95% CI, 1.01-1.37). Higher SHBG concentrations were associated with increased risks of AF (HR, 1.44; 95% CI, 1.34-1.54), VA (HR, 1.27; 95% CI, 1.07-1.52), and BA (HR, 1.17; 95% CI ,1.05-1.29). CONCLUSIONS Lower levels of testosterone and cFT were associated with increased risk of AF and BA. Higher cFT levels were associated with increased risk of AF and VA. Higher SHBG levels were associated with increased risk of AF, VA, and BA.
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Affiliation(s)
- Bingyan Xu
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Wei Mo
- Department of Endocrinology & Metabolism, Guangdong Second Traditional Chinese Medicine Hospital, Guangzhou 510095, China
| | - Xiangliang Tan
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Peizhen Zhang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Junlin Huang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Chensihan Huang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Dan Guo
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Xueyun Wei
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Yating Liu
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Xuzhen Lei
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Weijuan Dou
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Jiayang Lin
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Deying Liu
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Linjie Yang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Yan Huang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Huijie Zhang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
- Guangdong Provincial Key Laboratory of Cardiac Function and Microcirculation, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Yunfei Liao
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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Xourafa G, Korbmacher M, Roden M. Inter-organ crosstalk during development and progression of type 2 diabetes mellitus. Nat Rev Endocrinol 2024; 20:27-49. [PMID: 37845351 DOI: 10.1038/s41574-023-00898-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/29/2023] [Indexed: 10/18/2023]
Abstract
Type 2 diabetes mellitus (T2DM) is characterized by tissue-specific insulin resistance and pancreatic β-cell dysfunction, which result from the interplay of local abnormalities within different tissues and systemic dysregulation of tissue crosstalk. The main local mechanisms comprise metabolic (lipid) signalling, altered mitochondrial metabolism with oxidative stress, endoplasmic reticulum stress and local inflammation. While the role of endocrine dysregulation in T2DM pathogenesis is well established, other forms of inter-organ crosstalk deserve closer investigation to better understand the multifactorial transition from normoglycaemia to hyperglycaemia. This narrative Review addresses the impact of certain tissue-specific messenger systems, such as metabolites, peptides and proteins and microRNAs, their secretion patterns and possible alternative transport mechanisms, such as extracellular vesicles (exosomes). The focus is on the effects of these messengers on distant organs during the development of T2DM and progression to its complications. Starting from the adipose tissue as a major organ relevant to T2DM pathophysiology, the discussion is expanded to other key tissues, such as skeletal muscle, liver, the endocrine pancreas and the intestine. Subsequently, this Review also sheds light on the potential of multimarker panels derived from these biomarkers and related multi-omics for the prediction of risk and progression of T2DM, novel diabetes mellitus subtypes and/or endotypes and T2DM-related complications.
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Affiliation(s)
- Georgia Xourafa
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research, Partner Düsseldorf, München-Neuherberg, Düsseldorf, Germany
| | - Melis Korbmacher
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research, Partner Düsseldorf, München-Neuherberg, Düsseldorf, Germany
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
- German Center for Diabetes Research, Partner Düsseldorf, München-Neuherberg, Düsseldorf, Germany.
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
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Fan Q, Meng Y, Nie Z, Xie S, Chen C. Sex hormone-binding globulin exerts sex-related causal effects on lower extremity varicose veins: evidence from gender-stratified Mendelian randomization. Front Endocrinol (Lausanne) 2023; 14:1230955. [PMID: 38152135 PMCID: PMC10752419 DOI: 10.3389/fendo.2023.1230955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 11/20/2023] [Indexed: 12/29/2023] Open
Abstract
Background The association between serum sex hormones and lower extremity varicose veins has been reported in observational studies. However, it is unclear whether the association reflects a causal relationship. Besides, serum sex hormone-binding globulin (SHBG) has been rarely studied in lower extremity varicose veins. Here, we aim to investigate the association between serum levels of SHBG, testosterone, and estradiol and the risk of lower extremity varicose veins using Mendelian randomization (MR). Methods We obtained genome-wide association study summary statistics for serum SHBG levels with 369,002 European participants, serum testosterone levels with 424,907 European participants, serum estradiol levels with 361,194 European participants, and lower extremity varicose veins with 207,055 European participants. First, a univariable MR was performed to identify the causality from SHBG and sex hormone levels to lower extremity varicose veins with several sensitivity analyses being performed. Then, a multivariable MR (MVMR) was performed to further assess whether the causal effects were independent. Finally, we performed a gender-stratified MR to understand the role of genders on lower extremity varicose veins. Results Genetically predicted higher serum SHBG levels significantly increased the risk of lower extremity varicose veins in the univariable MR analysis (OR=1.39; 95% CI: 1.13-1.70; P=1.58×10-3). Sensitivity analyses and MVMR (OR=1.50; 95% CI:1.13-1.99; P=5.61×10-3) verified the robustness of the causal relationships. Gender-stratified MR revealed that higher serum SHBG levels were associated with lower extremity varicose veins in both sexes. However, the OR of serum SHBG levels on lower extremity varicose veins risk in females (OR=1.51; 95% CI: 1.23-1.87; P=1.00×10-4) was greater than in males (OR=1.26; 95% CI: 1.04-1.54; P=1.86×10-2). Conclusions Serum SHBG levels are positively related to lower extremity varicose veins risk in both sexes, especially in females. This may partly explain the higher prevalence of varicose vines among females.
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Affiliation(s)
- Qinglu Fan
- Department of Thoracic Surgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yang Meng
- Department of Ophthalmology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhihao Nie
- Department of Thoracic Surgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Songping Xie
- Department of Thoracic Surgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Changzheng Chen
- Department of Ophthalmology, Renmin Hospital of Wuhan University, Wuhan, China
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Sun K, Ming Y, Xu J, Wu Y, Zeng Y, Wu L, Li M, Shen B. Assessing the Casual Association between Sex Hormone Levels and Fracture Risk: A Two-Sample Mendelian Randomization Study. Orthop Surg 2023; 15:3065-3074. [PMID: 37771125 PMCID: PMC10694015 DOI: 10.1111/os.13881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 08/06/2023] [Accepted: 08/08/2023] [Indexed: 09/30/2023] Open
Abstract
OBJECTIVE Prior observational studies have reported that levels of sex hormones constitute a risk factor for the fracture. The aim of this study was to ascertain whether there is a causal relationship between the levels of sex hormones and the risk of fracture through Mendelian randomization (MR). METHODS Single-nucleotide polymorphisms (SNPs) associated with two indicators of sex hormone levels, circulating sex hormone-binding globulin (SHBG) and bioavailable testosterone levels, as exposures were selected from a large genome-wide association study (GWAS) from UK Biobank. The summary statistics for 11 different types of fracture as outcomes from the FinnGen consortium. This study employed the two-sample MR approach. For the main analysis, the inverse-variance-weighted (IVW) method was utilized. To assess the heterogeneity of MR results, the IVW method and MR-Egger method were utilized. To evaluate potential pleiotropy, MR-Egger regression was conducted. Additionally, a leave-one-SNP-out test was performed to assess the robustness of MR results to the exclusion of any individual SNP. RESULTS The MR analyses demonstrated a conspicuous impact of SHBG on the risk of pathological fracture with osteoporosis (OP). We found that an increase of one standard deviation (SD) in SHBG correspondingly increased the risk of pathological fracture with OP [odds ratio (OR) 2.42, 95% confidence interval (CI), 1.52-3.85; p = 1.93 × 10-4 ]. The bioavailable testosterone showed the negative casual genetic associations with fractures of foot and forearm. An increase of one SD in the genetically predetermined bioavailable testosterone was associated with a reduction of 37% in the risk of fracture of foot (OR 0.63, 95% Cl 0.49 to 0.81; p = 3.37 × 10-4 ), as well as a 39% decrease in the risk of fracture of forearm (OR 0.61, 95% Cl 0.50 to 0.76; p = 5.40 × 10-6 ). CONCLUSIONS Our study confirms that individuals experiencing elevated SHBG concentrations showed a major causal effect on pathological fracture with OP. High bioavailable testosterone levels play an important role in preventing the fractures of foot and forearm. Although increasing bioavailable testosterone and decreasing SHBG levels had no casual effect on most fractures in the general population, they are likely to have the most clinically relevant effect on certain fracture risk reduction.
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Affiliation(s)
- Kaibo Sun
- Department of Orthopaedics SurgeryOrthopedic Research Institute, West China Hospital, Sichuan UniversityChengduChina
| | - Yue Ming
- Laboratory of Molecular Oncology, Frontiers Science Center for Disease‐related Molecular NetworksWest China Hospital, Sichuan UniversityChengduChina
| | - Jiawen Xu
- Department of Orthopaedics SurgeryOrthopedic Research Institute, West China Hospital, Sichuan UniversityChengduChina
| | - Yuangang Wu
- Department of Orthopaedics SurgeryOrthopedic Research Institute, West China Hospital, Sichuan UniversityChengduChina
| | - Yi Zeng
- Department of Orthopaedics SurgeryOrthopedic Research Institute, West China Hospital, Sichuan UniversityChengduChina
| | - Limin Wu
- Department of Orthopaedics SurgeryOrthopedic Research Institute, West China Hospital, Sichuan UniversityChengduChina
| | - Mingyang Li
- Department of Orthopaedics SurgeryOrthopedic Research Institute, West China Hospital, Sichuan UniversityChengduChina
| | - Bin Shen
- Department of Orthopaedics SurgeryOrthopedic Research Institute, West China Hospital, Sichuan UniversityChengduChina
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Cai X, Thorand B, Hohenester S, Prehn C, Cecil A, Adamski J, Zeller T, Dennis A, Banerjee R, Peters A, Yaghootkar H, Nano J. Association of sex hormones and sex hormone-binding globulin with liver fat in men and women: an observational and Mendelian randomization study. Front Endocrinol (Lausanne) 2023; 14:1223162. [PMID: 37900132 PMCID: PMC10611498 DOI: 10.3389/fendo.2023.1223162] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/11/2023] [Indexed: 10/31/2023] Open
Abstract
Background Sex hormones and sex hormone-binding globulin (SHBG) may play a role in fatty liver development. We sought to examine the association of various endogenous sex hormones, including testosterone (T), and SHBG with liver fat using complementary observational and Mendelian randomization (MR) analyses. Methods The observational analysis included a total of 2,239 participants (mean age 60 years; 35% postmenopausal women) from the population-based KORA study (average follow-up time: 6.5 years). We conducted linear regression analysis to investigate the sex-specific associations of sex hormones and SHBG with liver fat, estimated by fatty liver index (FLI). For MR analyses, we selected genetic variants associated with sex hormones and SHBG and extracted their associations with magnetic resonance imaging measured liver fat from the largest up to date European genome-wide associations studies. Results In the observational analysis, T, dihydrotestosterone (DHT), progesterone and 17α-hydroxyprogesterone (17-OHP) were inversely associated with FLI in men, with beta estimates ranging from -4.23 to -2.30 [p-value <0.001 to 0.003]. Whereas in women, a positive association of free T with FLI (β = 4.17, 95%CI: 1.35, 6.98) was observed. SHBG was inversely associated with FLI across sexes [men: -3.45 (-5.13, -1.78); women: -9.23 (-12.19, -6.28)]. No causal association was found between genetically determined sex hormones and liver fat, but higher genetically determined SHBG was associated with lower liver fat in women (β = -0.36, 95% CI: -0.61, -0.12). Conclusion Our results provide suggestive evidence for a causal association between SHBG and liver fat in women, implicating the protective role of SHBG against liver fat accumulation.
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Affiliation(s)
- Xinting Cai
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology – IBE, Faculty of Medicine, Ludwig-Maximilians University of Munich, Munich, Germany
- Pettenkofer School of Public Health, Ludwig-Maximilians University of Munich, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology – IBE, Faculty of Medicine, Ludwig-Maximilians University of Munich, Munich, Germany
- German Center for Diabetes Research (DZD), partner site Munich-Neuherberg, Neuherberg, Germany
| | - Simon Hohenester
- Department of Medicine II, University Hospital, Ludwig-Maximilians University of Munich, Munich, Germany
| | - Cornelia Prehn
- Core Facility Metabolomics and Proteomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Alexander Cecil
- Core Facility Metabolomics and Proteomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Queenstown, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tanja Zeller
- University Center of Cardiovascular Science, University Heart and Vascular Center Hamburg, Hamburg, Germany
- Clinic of Cardiology, University Heart and Vascular Center Hamburg, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck, Hamburg, Germany
| | | | | | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology – IBE, Faculty of Medicine, Ludwig-Maximilians University of Munich, Munich, Germany
- German Center for Diabetes Research (DZD), partner site Munich-Neuherberg, Neuherberg, Germany
- German Center for Cardiovascular Disease Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Hanieh Yaghootkar
- College of Health and Science, University of Lincoln, Joseph Banks Laboratories, Green Lane, Lincoln, Lincolnshire, United Kingdom
| | - Jana Nano
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology – IBE, Faculty of Medicine, Ludwig-Maximilians University of Munich, Munich, Germany
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Yuan S, Xu F, Li X, Chen J, Zheng J, Mantzoros CS, Larsson SC. Plasma proteins and onset of type 2 diabetes and diabetic complications: Proteome-wide Mendelian randomization and colocalization analyses. Cell Rep Med 2023; 4:101174. [PMID: 37652020 PMCID: PMC10518626 DOI: 10.1016/j.xcrm.2023.101174] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/16/2023] [Accepted: 08/06/2023] [Indexed: 09/02/2023]
Abstract
We conduct proteome-wide Mendelian randomization and colocalization analyses to decipher the associations of blood proteins with the risk of type 2 diabetes and diabetic complications. Genetic data on plasma proteome are obtained from 54,306 UK Biobank participants and 35,559 Icelanders. Summary-level data on type 2 diabetes are obtained from the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis consortium) consortium (74,124 cases) and FinnGen study (33,043 cases). Data on 10 diabetic complications are obtained from FinnGen and corresponding studies. Among 1,886 proteins, genetically predicted levels of 47 plasma proteins are associated with type 2 diabetes. Eleven of these proteins have strong support of colocalization. Seventeen proteins are associated with at least one diabetic complication, although a few have colocalization support. HLA-DRA, AGER, HSPA1A, and HSPA1B are associated with most microvascular complications. This study reveals causal proteins for the onset of type 2 diabetes and diabetic complications, which enhances the understanding of molecular etiology and development of therapeutics.
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Affiliation(s)
- Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Xue Li
- Department of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jie Chen
- Department of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Christos S Mantzoros
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Section of Endocrinology, VA Boston Healthcare System, Harvard Medical School, Boston, MA, USA
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
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Yuan S, Li Y, Wang L, Xu F, Chen J, Levin MG, Xiong Y, Voight BF, Damrauer SM, Gill D, Burgess S, Åkesson A, Michaëlsson K, Li X, Shen X, Larsson SC. Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.20.23292938. [PMID: 37546828 PMCID: PMC10402218 DOI: 10.1101/2023.07.20.23292938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Aims The study aimed to discover novel genetic loci for atrial fibrillation (AF), explore the shared genetic etiologies between AF and other cardiovascular and cardiometabolic traits, and uncover AF pathogenesis using Mendelian randomization analysis. Methods and results We conducted a genome-wide association study meta-analysis including 109,787 AF cases and 1,165,920 controls of European ancestry and identified 215 loci, among which 91 were novel. We performed Genomic Structural Equation Modeling analysis between AF and four cardiovascular comorbidities (coronary artery disease, ischemic stroke, heart failure, and vneous thromboembolism) and found 189 loci shared across these diseases as well as a universal genetic locus shared by atherosclerotic outcomes (i.e., rs1537373 near CDKN2B). Three genetic loci (rs10740129 near JMJD1C, rs2370982 near NRXN3, and rs9931494 near FTO) were associated with AF and cardiometabolic traits. A polygenic risk score derived from this genome-wide meta-analysis was associated with AF risk (odds ratio 2.36, 95% confidence interval 2.31-2.41 per standard deviation increase) in the UK biobank. This score, combined with age, sex, and basic clinical features, predicted AF risk (AUC 0.784, 95% CI 0.781-0.787) in Europeans. Phenome-wide association analysis of the polygenic risk score identified many AF-related comorbidities of the circulatory, endocrine, and respiratory systems. Phenome-wide and multi-omic Mendelian randomization analyses identified associations of blood lipids and pressure, diabetes, insomnia, obesity, short sleep, and smoking, 27 blood proteins, one gut microbe (genus.Catenibacterium), and 11 blood metabolites with risk to AF. Conclusions This genome-wide association study and trans-omic Mendelian randomization analysis provides insights into disease risk prediction, pathophysiology and downstream sequelae.
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Affiliation(s)
- Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Yuying Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Lijuan Wang
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Jie Chen
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Michael G Levin
- Division of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Ying Xiong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Scott M Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Agneta Åkesson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Karl Michaëlsson
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Xue Li
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xia Shen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Susanna C. Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
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19
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Yuan S, Merino J, Larsson SC. Causal factors underlying diabetes risk informed by Mendelian randomisation analysis: evidence, opportunities and challenges. Diabetologia 2023; 66:800-812. [PMID: 36786839 PMCID: PMC10036461 DOI: 10.1007/s00125-023-05879-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 01/04/2023] [Indexed: 02/15/2023]
Abstract
Diabetes and its complications cause a heavy disease burden globally. Identifying exposures, risk factors and molecular processes causally associated with the development of diabetes can provide important evidence bases for disease prevention and spur novel therapeutic strategies. Mendelian randomisation (MR), an epidemiological approach that uses genetic instruments to infer causal associations between an exposure and an outcome, can be leveraged to complement evidence from observational and clinical studies. This narrative review aims to summarise the evidence on potential causal risk factors for diabetes by integrating published MR studies on type 1 and 2 diabetes, and to reflect on future perspectives of MR studies on diabetes. Despite the genetic influence on type 1 diabetes, few MR studies have been conducted to identify causal exposures or molecular processes leading to increased disease risk. In type 2 diabetes, MR analyses support causal associations of somatic, mental and lifestyle factors with development of the disease. These studies have also identified biomarkers, some of them derived from the gut microbiota, and molecular processes leading to increased disease risk. These studies provide valuable data to better understand disease pathophysiology and explore potential therapeutic targets. Because genetic association studies have mostly been restricted to participants of European descent, multi-ancestry cohorts are needed to examine the role of different types of physical activity, dietary components, metabolites, protein biomarkers and gut microbiome in diabetes development.
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Affiliation(s)
- Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jordi Merino
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
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20
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Rooney MR, Chen J, Echouffo-Tcheugui JB, Walker KA, Schlosser P, Surapaneni A, Tang O, Chen J, Ballantyne CM, Boerwinkle E, Ndumele CE, Demmer RT, Pankow JS, Lutsey PL, Wagenknecht LE, Liang Y, Sim X, van Dam R, Tai ES, Grams ME, Selvin E, Coresh J. Proteomic Predictors of Incident Diabetes: Results From the Atherosclerosis Risk in Communities (ARIC) Study. Diabetes Care 2023; 46:733-741. [PMID: 36706097 PMCID: PMC10090896 DOI: 10.2337/dc22-1830] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 12/29/2022] [Indexed: 01/28/2023]
Abstract
OBJECTIVE The plasma proteome preceding diabetes can improve our understanding of diabetes pathogenesis. RESEARCH DESIGN AND METHODS In 8,923 Atherosclerosis Risk in Communities (ARIC) Study participants (aged 47-70 years, 57% women, 19% Black), we conducted discovery and internal validation for associations of 4,955 plasma proteins with incident diabetes. We externally validated results in the Singapore Multi-Ethnic Cohort (MEC) nested case-control (624 case subjects, 1,214 control subjects). We used Cox regression to discover and validate protein associations and risk-prediction models (elastic net regression with cardiometabolic risk factors and proteins) for incident diabetes. We conducted a pathway analysis and examined causality using genetic instruments. RESULTS There were 2,147 new diabetes cases over a median of 19 years. In the discovery sample (n = 6,010), 140 proteins were associated with incident diabetes after adjustment for 11 risk factors (P < 10-5). Internal validation (n = 2,913) showed 64 of the 140 proteins remained significant (P < 0.05/140). Of the 63 available proteins, 47 (75%) were validated in MEC. Novel associations with diabetes were found for 22 the 47 proteins. Prediction models (27 proteins selected by elastic net) developed in discovery had a C statistic of 0.731 in internal validation, with ΔC statistic of 0.011 (P = 0.04) beyond 13 risk factors, including fasting glucose and HbA1c. Inflammation and lipid metabolism pathways were overrepresented among the diabetes-associated proteins. Genetic instrument analyses suggested plasma SHBG, ATP1B2, and GSTA1 play causal roles in diabetes risk. CONCLUSIONS We identified 47 plasma proteins predictive of incident diabetes, established causal effects for 3 proteins, and identified diabetes-associated inflammation and lipid pathways with potential implications for diagnosis and therapy.
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Affiliation(s)
- Mary R. Rooney
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Jingsha Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Justin B. Echouffo-Tcheugui
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University, Baltimore, MD
| | - Keenan A. Walker
- Laboratory of Behavioral Neuroscience, Intramural Research Program, National Institute on Aging, Baltimore, MD
| | - Pascal Schlosser
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Aditya Surapaneni
- Division of Precision Medicine, New York University Grossman School of Medicine, New York, NY
| | - Olive Tang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Jinyu Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | | | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics and Environmental Science, University of Texas Health Science Center, Houston, TX
| | | | - Ryan T. Demmer
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - James S. Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Yujian Liang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Rob van Dam
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, George Washington University, Washington DC
| | - E. Shyong Tai
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Morgan E. Grams
- Division of Precision Medicine, New York University Grossman School of Medicine, New York, NY
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
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21
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Xing W, Gu W, Liang M, Wang Z, Fan D, Zhang B, Wang L. Association between aldehyde exposure and sex steroid hormones among adults. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:30444-30461. [PMID: 36434445 DOI: 10.1007/s11356-022-24362-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 11/17/2022] [Indexed: 06/16/2023]
Abstract
Exogenous and endogenous exposure to aldehydes is seen worldwide. Aldehydes are closely associated with human diseases, especially reproductive toxicity. However, the effect of aldehyde exposure on sex steroid hormones among adults remains uninvestigated. A total of 851 participants aged over 18 years were included in this cross-sectional analysis based on data from National Health and Nutrition Examination Survey (NHANES) 2013-2014. Serum aldehyde concentrations were quantified following an automated analytical method. Sex steroid hormones including total testosterone, estradiol, and sex hormone binding globulin (SHBG) were detected. Multivariate linear regression models, forest plots, generalized additive model (GAM), and smooth curve fitting analysis were used to assess the associations between quartiles of aldehydes and sex steroid hormones levels after adjusting for potential confounders. Butyraldehyde and propanaldehyde were found to be negatively associated with estradiol and SHBG in females and males, respectively. β values with 95% confidence intervals (95% CIs) were - 20.59 (- 38.30 to - 2.88) for Q2 vs. Q1 of butyraldehyde and - 8.13 (- 14.92 to - 1.33) and - 7.79 (- 14.91 to - 0.67) for Q2 vs. Q1 and Q4 vs. Q1 of propanaldehyde. No significant associations were observed between other aldehydes and sex hormones. In premenopausal women, isopentanaldehyde was inversely associated with serum total testosterone levels (Q4 vs. Q1: OR = - 7.95, 95% CI: - 15.62 to - 0.27), whereas propanaldehyde was positively associated with serum estradiol concentration (Q3 vs. Q1: β = 28.88, 95% CI: 0.83 to 56.94). Compared with Q1, Q3 of isopentanaldehyde was associated with 3.53 pg/mL higher concentration of estradiol in postmenopausal women (β = 3.53, 95% CI: 0.08 to 6.97). Moreover, in males under 40 years, butyraldehyde and heptanaldehyde were inversely proportional to total testosterone levels and heptanaldehyde and butyraldehyde were negatively associated with estradiol and SHBG. Decreased total testosterone, elevated estradiol, and decreased SHBG levels were found in higher quartiles of benzaldehyde, hexanaldehyde and isopentanaldehyde, and propanaldehyde, respectively, in males aged over 60 years. In male participants aged 40-60 years, only hexanaldehyde was observed to be correlated with higher serum estradiol levels. In conclusion, our current research presented the association between six serum aldehydes and sex hormones. Of note, stratification analyses were conducted in participants with different menopausal statuses and age among males and females. Sex- and age-specific effect of aldehyde exposure on alterations in sex hormone levels were observed. Further studies are warranted to confirm the causal relationship and explore the underlying mechanisms.
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Affiliation(s)
- Weilong Xing
- Laboratory of Pesticide Environmental Assessment and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment (MEE), Nanjing, 210042, People's Republic of China.
| | - Wen Gu
- Laboratory of Pesticide Environmental Assessment and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment (MEE), Nanjing, 210042, People's Republic of China
| | - Mengyuan Liang
- Laboratory of Pesticide Environmental Assessment and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment (MEE), Nanjing, 210042, People's Republic of China
| | - Zhen Wang
- Laboratory of Pesticide Environmental Assessment and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment (MEE), Nanjing, 210042, People's Republic of China
| | - Deling Fan
- Laboratory of Pesticide Environmental Assessment and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment (MEE), Nanjing, 210042, People's Republic of China
| | - Bing Zhang
- Laboratory of Pesticide Environmental Assessment and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment (MEE), Nanjing, 210042, People's Republic of China
| | - Lei Wang
- Laboratory of Pesticide Environmental Assessment and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment (MEE), Nanjing, 210042, People's Republic of China
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22
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Yuan S, Wang L, Zhang H, Xu F, Zhou X, Yu L, Sun J, Chen J, Ying H, Xu X, Yu Y, Spiliopoulou A, Shen X, Wilson J, Gill D, Theodoratou E, Larsson SC, Li X. Mendelian randomization and clinical trial evidence supports TYK2 inhibition as a therapeutic target for autoimmune diseases. EBioMedicine 2023; 89:104488. [PMID: 36842216 PMCID: PMC9988426 DOI: 10.1016/j.ebiom.2023.104488] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 02/05/2023] [Accepted: 02/07/2023] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND To explore the associations of genetically proxied TYK2 inhibition with a wide range of disease outcomes and biomarkers to identify therapeutic repurposing opportunities, adverse effects, and biomarkers of efficacy. METHODS The loss-of-function missense variant rs34536443 in TYK2 gene was used as a genetic instrument to proxy the effect of TYK2 inhibition. A phenome-wide Mendelian randomization (MR) study was conducted to explore the associations of genetically-proxied TYK2 inhibition with 1473 disease outcomes in UK Biobank (N = 339,197). Identified associations were examined for replication in FinnGen (N = 260,405). We further performed tissue-specific gene expression MR, colocalization analyses, and MR with 247 blood biomarkers. A systematic review of randomized controlled trials (RCTs) on TYK2 inhibitor was performed to complement the genetic evidence. FINDINGS PheWAS-MR found that genetically-proxied TYK2 inhibition was associated with lower risk of a wide range of autoimmune diseases. The associations with hypothyroidism and psoriasis were confirmed in MR analysis of tissue-specific TYK2 gene expression and the associations with systemic lupus erythematosus, psoriasis, and rheumatoid arthritis were observed in colocalization analysis. There were nominal associations of genetically-proxied TYK2 inhibition with increased risk of prostate and breast cancer but not in tissue-specific expression MR or colocalization analyses. Thirty-seven blood biomarkers were associated with the TYK2 loss-of-function mutation. Evidence from RCTs confirmed the effectiveness of TYK2 inhibitors on plaque psoriasis and reported several adverse effects. INTERPRETATION This study supports TYK2 inhibitor as a potential treatment for psoriasis and several other autoimmune diseases. Increased pharmacovigilance is warranted in relation to the potential adverse effects. FUNDING None.
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Affiliation(s)
- Shuai Yuan
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Lijuan Wang
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Han Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Xuan Zhou
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lili Yu
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Sun
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jie Chen
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Haochao Ying
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaolin Xu
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yongfu Yu
- Department of Biostatistics, School of Public Health, and The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China
| | - Athina Spiliopoulou
- Centre for Public Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Xia Shen
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK; Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China; State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Jim Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK
| | - Evropi Theodoratou
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK; Cancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
| | - Xue Li
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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23
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Larsson SC, Wang L, Li X, Jiang F, Chen X, Mantzoros CS. Circulating lipoprotein(a) levels and health outcomes: Phenome-wide Mendelian randomization and disease-trajectory analyses. Metabolism 2022; 137:155347. [PMID: 36396079 DOI: 10.1016/j.metabol.2022.155347] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/09/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Lipoprotein(a) [Lp(a)] is a risk factor for atherosclerotic and valvular diseases, but its possible role in other diseases has not yet been established. We conducted phenome-wide Mendelian randomization and disease-trajectory analyses to assess any associations of circulating Lp(a) levels with a broad range of diseases. METHODS A weighted polygenic risk score was constructed using independent genetic variants in the LPA gene and with an established effect on Lp(a) levels. The PheWAS analysis included 1081 phenotype outcomes ascertained among 385,917 White participants of the UK Biobank. Novel findings were investigated in MR analysis using data from the FinnGen consortium. Disease-trajectory and comorbidity analyses were further conducted to explore the sequential patterns of multiple morbidities related to high circulating Lp(a) levels. RESULTS PheWAS revealed statistically significant associations of higher circulating Lp(a) levels with increased risk of a large number of circulatory system diseases (including various cardiac diseases, peripheral vascular disease, hypertension, and valvular and cerebrovascular diseases) as well as some endocrine/metabolic diseases (including hyperlipidemia, hypercholesterolemia, disorders of lipoid metabolism, and type 2 diabetes), genitourinary system diseases (renal failure), and hematologic diseases (including different types of anemia). Two-sample MR analysis supported the association between Lp(a) and risk of anemia, showed a suggestive association with type 2 diabetes, but found no association with renal failure. Disease-trajectory and comorbidity analyses identified 3 major sequential patterns of multiple morbidities, mainly in the cardiovascular, metabolic, and mental disorders, related to high circulating Lp(a) levels. CONCLUSIONS Genetically predicted higher circulating Lp(a) levels were associated with increased risk of many circulatory system diseases and anemia. Additionally, this study identified three major sequential patterns of multiple morbidities related to high Lp(a).
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Affiliation(s)
- Susanna C Larsson
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Lijuan Wang
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Fangyuan Jiang
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiangjun Chen
- Eye Center of the Second Affiliated Hospital, Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Christos S Mantzoros
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Section of Endocrinology, Boston VA Healthcare System, Harvard Medical School, Boston, MA, USA
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24
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Yuan S, Sun J, Lu Y, Xu F, Li D, Jiang F, Wan Z, Li X, Qin LQ, Larsson SC. Health effects of milk consumption: phenome-wide Mendelian randomization study. BMC Med 2022; 20:455. [PMID: 36424608 PMCID: PMC9694907 DOI: 10.1186/s12916-022-02658-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 11/09/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND We performed phenome-wide Mendelian randomization analysis (MR-PheWAS), two-sample MR analysis, and systemic review to comprehensively explore the health effects of milk consumption in the European population. METHODS Rs4988235 located upstream of the LCT gene was used as the instrumental variable for milk consumption. MR-PheWAS analysis was conducted to map the association of genetically predicted milk consumption with 1081 phenotypes in the UK Biobank study (n=339,197). The associations identified in MR-PheWAS were examined by two-sample MR analysis using data from the FinnGen study (n=260,405) and international consortia. A systematic review of MR studies on milk consumption was further performed. RESULTS PheWAS and two-sample MR analyses found robust evidence in support of inverse associations of genetically predicted milk consumption with risk of cataract (odds ratio (OR) per 50 g/day increase in milk consumption, 0.89, 95% confidence interval (CI), 0.84-0.94; p=3.81×10-5), hypercholesterolemia (OR, 0.91, 95% CI 0.86-0.96; p=2.97×10-4), and anal and rectal polyps (OR, 0.85, 95% CI, 0.77-0.94; p=0.001). An inverse association for type 2 diabetes risk (OR, 0.92, 95% CI, 0.86-0.97; p=0.003) was observed in MR analysis based on genetic data with body mass index adjustment but not in the corresponding data without body mass index adjustment. The systematic review additionally found evidence that genetically predicted milk consumption was inversely associated with asthma, hay fever, multiple sclerosis, colorectal cancer, and Alzheimer's disease, and positively associated with Parkinson's disease, renal cell carcinoma, metabolic syndrome, overweight, and obesity. CONCLUSIONS This study suggests several health effects of milk consumption in the European population.
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Affiliation(s)
- Shuai Yuan
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jing Sun
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Lu
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Doudou Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fangyuan Jiang
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhongxiao Wan
- Department of Nutrition and Food Hygiene, School of Public Health, Soochow University, Suzhou, China
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Li-Qiang Qin
- Department of Nutrition and Food Hygiene, School of Public Health, Soochow University, Suzhou, China.
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. .,Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
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