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Wang L, Cao Y, Li P, He P, Chen P. Relationship between pelvic floor muscle function and insulin resistance among non-diabetic females: a 3d ultrasound evaluation. J OBSTET GYNAECOL 2024; 44:2381569. [PMID: 39056468 DOI: 10.1080/01443615.2024.2381569] [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: 05/23/2024] [Accepted: 07/11/2024] [Indexed: 07/28/2024]
Abstract
BACKGROUND To use the three-dimensional (3D) ultrasound for assessment of pelvic floor muscle function in non-diabetic females with insulin resistance (IR), and to evaluate its functional relationship with insulin levels. METHODS From October 2022 to November 2023, 216 non-diabetic females with insulin-resistant (IR group) and 118 normal females (control group) were sequentially recruited from our hospital for our study. The 3D ultrasound was used to assess the levator hiatus in resting state for all females regarding diameter lines, perimeters and areas; as well as the Valsalva manoeuvre (VM). The t-test and linear regression model were used to analyse the collected data. RESULTS The analysis indicates that there were significant differences in the resting state of the levator hiatus between the IR and the control groups (14.8 ± 5.8 cm2 and 11.6 ± 2.7 cm2, p < 0.05); and in the VM (18.2 ± 6.3 cm2 and 13.4 ± 3. 4 cm2, p < 0.05). In addition, the anterior-posterior (AP) diameters of the hiatus on VM were significantly increased in the IR group (40.0 ± 4.7 mm and 33.0 ± 4.4 mm, p < 0.05). With insulin levels as the dependent variable, multivariate regression analysis shows that insulin levels were significantly correlated with the levator hiatus area on VM (p < 0.05) and waist circumference (p < 0.05). The pelvic organ descent on VM in the IR group was significant (p < 0.05). CONCLUSIONS The areas of resting state levator hiatus and on VM were significantly larger in the IR than that in the control groups. In addition, the position of the pelvic organ on VM in the IR group was significantly descended. The insulin levels were correlated with the pelvic floor muscle function.
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Affiliation(s)
- Lei Wang
- Departments of Ultrasound Diagnostics, the International Peace Maternity and Child Health Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yunyun Cao
- Departments of Ultrasound Diagnostics, the International Peace Maternity and Child Health Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ping Li
- Departments of Ultrasound Diagnostics, the International Peace Maternity and Child Health Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ping He
- Departments of Ultrasound Diagnostics, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China
| | - Ping Chen
- Departments of Ultrasound Diagnostics, the International Peace Maternity and Child Health Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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2
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Huang W, Gan Z, Gao Z, Lin Q, Li X, Xie W, Gao Z, Zhou Z, Qiu Z, Qiu W, Du S, Chen L, Hong H, Ye W. Discrepancies between general and central obesity in arterial stiffness: observational studies and Mendelian randomization study. BMC Med 2024; 22:325. [PMID: 39113079 PMCID: PMC11304581 DOI: 10.1186/s12916-024-03546-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 07/29/2024] [Indexed: 08/11/2024] Open
Abstract
BACKGROUND Obesity has been linked to arterial stiffness, while no consensus was reached on the association. We aimed to clarify the association of general and central obesity with arterial stiffness by combining observational studies and Mendelian randomization (MR) study. METHODS Two cross-sectional studies were performed in UK Biobank and Fuqing Cohort, respectively. Two-sample MR study was conducted using summary data of GWASs from GIANT consortium and UK Biobank. General obesity and central obesity were measured using body mass index (BMI) and waist circumference (WC), respectively. Arterial stiffness was measured by arterial stiffness index (ASI) in UK Biobank or branchial-ankle pulse wave velocity (baPWV) in Fuqing Cohort. RESULTS Two observational studies found a consistent positive association of BMI and WC with arterial stiffness when adjusting for age, sex, education, smoking, alcohol drinking, physical activity, and LDL cholesterol. However, when additionally adjusting for metabolic traits (i.e., systolic blood pressure, diastolic blood pressure, blood glucose, triglycerides, high-density lipoprotein cholesterol, and WC or BMI), the association with BMI changed to be inverse. As compared to the lowest quintile group, the adjusted ORs across groups of second to fifth quintile were 0.93, 0.90, 0.83, and 0.72 in UK Biobank and 0.88, 0.65, 0.63, and 0.50 in Fuqing Cohort. In contrast, the positive relationship with WC remained stable with the adjusted ORs of 1.23, 1.46, 1.60, and 1.56 in UK Biobank and 1.35, 1.44, 1.77, and 1.64 in Fuqing Cohort. MR analyses provided supportive evidence of the negative association with BMI (OR = 0.97, 95%CI = 0.94-1.00) and the positive association with WC (OR = 1.14, 95%CI = 1.08-1.20). CONCLUSIONS Observational and genetic analyses provide concordant results that central obesity is independently related to arterial stiffness, while the role of general obesity depends on metabolic status.
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Affiliation(s)
- Wuqing Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, University Town, No 1, Xue Yuan Road, Fujian, 350108, China
| | - Zhaojing Gan
- Department of Geriatrics, Fujian Key Laboratory of Vascular Aging, Fujian Institute of Geriatrics, Union Hospital, Fujian Medical University,, Fujian, 350001, China
| | - Ziting Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, University Town, No 1, Xue Yuan Road, Fujian, 350108, China
| | - Qiaofen Lin
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, University Town, No 1, Xue Yuan Road, Fujian, 350108, China
| | - Xiaojiang Li
- Department of Geriatrics, Fujian Key Laboratory of Vascular Aging, Fujian Institute of Geriatrics, Union Hospital, Fujian Medical University,, Fujian, 350001, China
| | - Wenhui Xie
- Department of Geriatrics, Fujian Key Laboratory of Vascular Aging, Fujian Institute of Geriatrics, Union Hospital, Fujian Medical University,, Fujian, 350001, China
| | - Zesen Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, University Town, No 1, Xue Yuan Road, Fujian, 350108, China
| | - Zhixian Zhou
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, University Town, No 1, Xue Yuan Road, Fujian, 350108, China
| | - Ziyi Qiu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, University Town, No 1, Xue Yuan Road, Fujian, 350108, China
| | - Weihong Qiu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, University Town, No 1, Xue Yuan Road, Fujian, 350108, China
| | - Shanshan Du
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, University Town, No 1, Xue Yuan Road, Fujian, 350108, China
| | - Liangwan Chen
- Department of Cardiovascular Surgery, Union Hospital, Fujian Medical University, No. 29 Xinquan Road, Fuzhou , Fujian, 350001, China.
- Key Laboratory of Cardio-Thoracic Surgery, Fujian Medical University, Fuzhou, Fujian, China.
| | - Huashan Hong
- Department of Geriatrics, Fujian Key Laboratory of Vascular Aging, Fujian Institute of Geriatrics, Union Hospital, Fujian Medical University,, Fujian, 350001, China.
| | - Weimin Ye
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, University Town, No 1, Xue Yuan Road, Fujian, 350108, China.
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
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3
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Huang Y, Cai Y, Chen Y, Zhu Q, Feng W, Jin L, Ma Y. Cholelithiasis and cholecystectomy increase the risk of gastroesophageal reflux disease and Barrett's esophagus. Front Med (Lausanne) 2024; 11:1420462. [PMID: 39091288 PMCID: PMC11292949 DOI: 10.3389/fmed.2024.1420462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Accepted: 06/20/2024] [Indexed: 08/04/2024] Open
Abstract
Background Cholelithiasis or cholecystectomy may contribute to the development of gastroesophageal reflux disease (GERD), Barrett's esophagus (BE), and esophageal adenocarcinoma (EAC) through bile reflux; however, current observational studies yield inconsistent findings. We utilized a novel approach combining meta-analysis and Mendelian randomization (MR) analysis, to assess the association between them. Methods The literature search was done using PubMed, Web of Science, and Embase databases, up to 3 November 2023. A meta-analysis of observational studies assessing the correlations between cholelithiasis or cholecystectomy, and the risk factors for GERD, BE, and EACwas conducted. In addition, the MR analysis was employed to assess the causative impact of genetic pre-disposition for cholelithiasis or cholecystectomy on these esophageal diseases. Results The results of the meta-analysis indicated that cholelithiasis was significantly linked to an elevated risk in the incidence of BE (RR, 1.77; 95% CI, 1.37-2.29; p < 0.001) and cholecystectomy was a risk factor for GERD (RR, 1.37; 95%CI, 1.09-1.72; p = 0.008). We observed significant genetic associations between cholelithiasis and both GERD (OR, 1.06; 95% CI, 1.02-1.10; p < 0.001) and BE (OR, 1.21; 95% CI, 1.11-1.32; p < 0.001), and a correlation between cholecystectomy and both GERD (OR, 1.04; 95% CI, 1.02-1.06; p < 0.001) and BE (OR, 1.13; 95% CI, 1.06-1.19; p < 0.001). After adjusting for common risk factors, such as smoking, alcohol consumption, and BMI in multivariate analysis, the risk of GERD and BE still persisted. Conclusion Our study revealed that both cholelithiasis and cholecystectomy elevate the risk of GERD and BE. However, there is no observed increase in the risk of EAC, despite GERD and BE being the primary pathophysiological pathways leading to EAC. Therefore, patients with cholelithiasis and cholecystectomy should be vigilant regarding esophageal symptoms; however, invasive EAC cytology may not be necessary.
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Affiliation(s)
- Yu Huang
- Department of Cardiothoracic Surgery, Third Xiangya Hospital of Central South University, Changsha, China
| | - Yicong Cai
- Department of Gastrointestinal Surgery, Third Xiangya Hospital of Central South University, Changsha, China
| | - Yingji Chen
- Department of Cardiothoracic Surgery, Third Xiangya Hospital of Central South University, Changsha, China
| | - Qianjun Zhu
- Department of Cardiothoracic Surgery, Third Xiangya Hospital of Central South University, Changsha, China
| | - Wei Feng
- Department of Cardiothoracic Surgery, Third Xiangya Hospital of Central South University, Changsha, China
| | - Longyu Jin
- Department of Cardiothoracic Surgery, Third Xiangya Hospital of Central South University, Changsha, China
| | - Yuchao Ma
- Department of Cardiothoracic Surgery, Third Xiangya Hospital of Central South University, Changsha, China
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Li CL, Liu YK, Lan YY, Wang ZS. Association of education with cholelithiasis and mediating effects of cardiometabolic factors: A Mendelian randomization study. World J Clin Cases 2024; 12:4272-4288. [PMID: 39015929 PMCID: PMC11235540 DOI: 10.12998/wjcc.v12.i20.4272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 05/10/2024] [Accepted: 06/03/2024] [Indexed: 06/30/2024] Open
Abstract
BACKGROUND Education, cognition, and intelligence are associated with cholelithiasis occurrence, yet which one has a prominent effect on cholelithiasis and which cardiometabolic risk factors mediate the causal relationship remain unelucidated. AIM To explore the causal associations between education, cognition, and intelligence and cholelithiasis, and the cardiometabolic risk factors that mediate the associations. METHODS Applying genome-wide association study summary statistics of primarily European individuals, we utilized two-sample multivariable Mendelian randomization to estimate the independent effects of education, intelligence, and cognition on cholelithiasis and cholecystitis (FinnGen study, 37041 and 11632 patients, respectively; n = 486484 participants) and performed two-step Mendelian randomization to evaluate 21 potential mediators and their mediating effects on the relationships between each exposure and cholelithiasis. RESULTS Inverse variance weighted Mendelian randomization results from the FinnGen consortium showed that genetically higher education, cognition, or intelligence were not independently associated with cholelithiasis and cholecystitis; when adjusted for cholelithiasis, higher education still presented an inverse effect on cholecystitis [odds ratio: 0.292 (95%CI: 0.171-0.501)], which could not be induced by cognition or intelligence. Five out of 21 cardiometabolic risk factors were perceived as mediators of the association between education and cholelithiasis, including body mass index (20.84%), body fat percentage (40.3%), waist circumference (44.4%), waist-to-hip ratio (32.9%), and time spent watching television (41.6%), while time spent watching television was also a mediator from cognition (20.4%) and intelligence to cholelithiasis (28.4%). All results were robust to sensitivity analyses. CONCLUSION Education, cognition, and intelligence all play crucial roles in the development of cholelithiasis, and several cardiometabolic mediators have been identified for prevention of cholelithiasis due to defects in each exposure.
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Affiliation(s)
- Chang-Lei Li
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Yu-Kun Liu
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Ying-Ying Lan
- Department of Oncology Medicine, The Affiliated Hospital of Qingdao University, Qingdao 266002, Shandong Province, China
| | - Zu-Sen Wang
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
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5
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Hong Y, Gao Z, Wei H, Wei Y, Qiu Z, Xiao J, Huang W. Bi-directional association of body size and composition with heart failure: A Mendelian randomization study. Int J Cardiol 2024; 407:132069. [PMID: 38642721 DOI: 10.1016/j.ijcard.2024.132069] [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: 11/18/2023] [Revised: 03/25/2024] [Accepted: 04/17/2024] [Indexed: 04/22/2024]
Abstract
PURPOSE The effect of obesity on the development of heart failure (HF) has received attention, and this study intends to further explore the bidirectional association between body size or composition and HF by using Mendelian Randomization (MR) approach. DESIGN We performed a two-sample bidirectional MR study to investigate the association between body size or composition and the risk of HF using aggregated data from genome-wide association studies. Univariable MR analysis was used to investigate the causal relationship, and multivariable MR analysis was used to explore the mediating role of general and central obesity in the relationship between body size or composition and HF. RESULTS This forward MR study found that body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), fat mass (FM) and fat-free mass (FFM) were risk factors for the development of HF with the strength of causal association BMI > FM > WC > FFM > WHR. After adjusting for BMI, the observed associations between the remaining indicators and heart failure attenuated to null. After adjusting for WC, only BMI (OR = 1.59, 95%CI: 1.32-1.92, P = 9.53E-07) and FM (OR = 1.39, 95%CI: 1.20-1.62, P = 1.35E-0.5) kept significantly related to the risk of HF. Reverse MR analysis showed no association of changes in body size or composition with the onset of HF. CONCLUSION The two-sample bidirectional MR study found that general obesity, measured by BMI, was an independent indicator of the development of HF, while other related indicators were associated with HF incidence dependent on BMI, besides, no association was observed between HF diagnosis and the body size or composites.
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Affiliation(s)
- Yuqi Hong
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China; Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Ziting Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Hongye Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Yajing Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Ziyi Qiu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Jun Xiao
- Department of Cardiovascular Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China; Fujian Provincial Clinical Research Center for Cardiovascular Diseases Heart Center of Fujian Medical University, Fuzhou, Fujian, China.
| | - Wuqing Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China.
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6
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Shi R, Xiang S, Jia T, Robbins TW, Kang J, Banaschewski T, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Orfanos DP, Paus T, Poustka L, Hohmann S, Millenet S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Lin X, Sahakian BJ, Feng J. Investigating grey matter volumetric trajectories through the lifespan at the individual level. Nat Commun 2024; 15:5954. [PMID: 39009591 PMCID: PMC11251262 DOI: 10.1038/s41467-024-50305-0] [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: 06/01/2023] [Accepted: 07/04/2024] [Indexed: 07/17/2024] Open
Abstract
Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to limited large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages, and the neurobiological basis underlying individual heterogeneity remains poorly understood. Here we identify, using the IMAGEN adolescent cohort followed up over 9 years (14-23 y), three groups of adolescents characterized by distinct developmental patterns of whole-brain gray matter volume (GMV). Group 1 show continuously decreasing GMV associated with higher neurocognitive performances than the other two groups during adolescence. Group 2 exhibit a slower rate of GMV decrease and lower neurocognitive performances compared with Group 1, which was associated with epigenetic differences and greater environmental burden. Group 3 show increasing GMV and lower baseline neurocognitive performances due to a genetic variation. Using the UK Biobank, we show these differences may be attenuated in mid-to-late adulthood. Our study reveals clusters of adolescent neurodevelopment based on GMV and the potential long-term impact.
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Grants
- R01 DA049238 NIDA NIH HHS
- R01 MH085772 NIMH NIH HHS
- R56 AG058854 NIA NIH HHS
- U54 EB020403 NIBIB NIH HHS
- National Key R&D Program of China (No.2023YFE0199700 [to X.L.])
- the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1 [to S.D.]), the National Institutes of Health (NIH) funded ENIGMA (grants 5U54EB020403-05 and 1R56AG058854-01 [to S.D.])
- NSFC grant 82150710554 and environMENTAL grant. Further support was provided by grants from: - the ANR (ANR-12-SAMA-0004, AAPG2019 - GeBra [to J.-L.M.]), the Eranet Neuron (AF12-NEUR0008-01 - WM2NA; and ANR-18-NEUR00002-01 - ADORe [to J.-L.M.]), the Fondation de France (00081242 [to J.-L.M.]), the Fondation pour la Recherche Médicale (DPA20140629802 [to J.-L.M.]), the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA [to J.-L.M.]), Paris Sud University IDEX 2012 [to J.-L.M.]
- the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant [to M.-L.P.M.]), the Fondation de l’Avenir (grant AP-RM-17-013 [to M.-L.P.M.])
- the Fédération pour la Recherche sur le Cerveau; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797 [to R.W.])
- the European Union-funded FP6 Integrated Project IMAGEN (Reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286 [to G.S.]), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313 [to G.S.]), Human Brain Project (HBP SGA 2, 785907, and HBP SGA 3, 945539 [to G.S.]), the Medical Research Council Grant 'c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1 [to G.S.]), the National Institute of Health (NIH) (R01DA049238 [to G.S.], A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers), the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152; 01EV0711 [to G.S.]; Forschungsnetz AERIAL 01EE1406A, 01EE1406B; Forschungsnetz IMAC-Mind 01GL1745B [to G.S.]), the Deutsche Forschungsgemeinschaft (DFG grants SM 80/7-2, SFB 940, TRR 265, NE 1383/14-1 [to G.S.])
- National Key R&D Program of China (No.2019YFA0709502 [to J.F.], No.2018YFC1312904 [to J.F.]),No.2019YFA0709502 [to J.F.], No.2018YFC1312904 [to J.F.]), Shanghai Municipal Science and Technology Major Project (No.2018SHZDZX01 [to J.F.], ZJ Lab [to J.F.], and Shanghai Center for Brain Science and Brain-Inspired Technology [to J.F.]), the 111 Project (No.B18015 [to J.F.])
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Affiliation(s)
- Runye Shi
- School of Data Science, Fudan University, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, China
- School of Psychology, University of Southampton, Southampton, UK
| | - Trevor W Robbins
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Department of Psychology and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- Department of Child and Adolescent Psychiatry, AP-HP, Sorbonne Université, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein Kiel University, Kiel, Germany
| | | | - Tomáš Paus
- Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, QC, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, ON, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, China
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Xiaolei Lin
- School of Data Science, Fudan University, Shanghai, China.
- Huashan Institute of Medicine, Huashan Hospital affiliated to Fudan University, Shanghai, China.
| | - Barbara J Sahakian
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Department of Psychology and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK.
| | - Jianfeng Feng
- School of Data Science, Fudan University, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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7
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Shen R, Pan C, Yi G, Li Z, Dong C, Yu J, Zhang J, Dong Q, Yu K, Zeng Q. Type 2 Diabetes, Circulating Metabolites, and Calcific Aortic Valve Stenosis: A Mendelian Randomization Study. Metabolites 2024; 14:385. [PMID: 39057708 PMCID: PMC11278608 DOI: 10.3390/metabo14070385] [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: 05/04/2024] [Revised: 06/26/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Epidemiological studies have shown an association between type 2 diabetes (T2D) and calcific aortic valve stenosis (CAVS), but the potential causal relationship and underlying mechanisms remain unclear. Therefore, we conducted a two-sample and two-step Mendelian randomization (MR) analysis to evaluate the association of T2D with CAVS and the mediating effects of circulating metabolites and blood pressure using genome-wide association study (GWAS) summary statistics. The inverse variance weighted (IVW) method was used for the primary MR analysis, and comprehensive sensitivity analyses were performed to validate the robustness of the results. Our results showed that genetically predicted T2D was associated with increased CAVS risk (OR 1.153, 95% CI 1.096-1.214, p < 0.001), and this association persisted even after adjusting for adiposity traits in multivariable MR analysis. Furthermore, the two-step MR analysis identified 69 of 251 candidate mediators that partially mediated the effect of T2D on CAVS, including total branched-chain amino acids (proportion mediated: 23.29%), valine (17.78%), tyrosine (9.68%), systolic blood pressure (8.72%), the triglyceride group (6.07-11.99%), the fatty acid group (4.78-12.82%), and the cholesterol group (3.64-11.56%). This MR study elucidated the causal impact of T2D on CAVS risk independently of adiposity and identified potential mediators in this association pathways. Our findings shed light on the pathogenesis of CAVS and suggest additional targets for the prevention and intervention of CAVS attributed to T2D.
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Affiliation(s)
- Rui Shen
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Chengliang Pan
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Guiwen Yi
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Zhiyang Li
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Chen Dong
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Jian Yu
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Jiangmei Zhang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Qian Dong
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Kunwu Yu
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Qiutang Zeng
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (R.S.); (C.P.); (G.Y.); (Z.L.); (C.D.); (J.Y.); (J.Z.); (Q.D.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
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8
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Pazokitoroudi A, Liu Z, Dahl A, Zaitlen N, Rosset S, Sankararaman S. A scalable and robust variance components method reveals insights into the architecture of gene-environment interactions underlying complex traits. Am J Hum Genet 2024; 111:1462-1480. [PMID: 38866020 PMCID: PMC11267529 DOI: 10.1016/j.ajhg.2024.05.015] [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: 09/20/2023] [Revised: 05/15/2024] [Accepted: 05/15/2024] [Indexed: 06/14/2024] Open
Abstract
Understanding the contribution of gene-environment interactions (GxE) to complex trait variation can provide insights into disease mechanisms, explain sources of heritability, and improve genetic risk prediction. While large biobanks with genetic and deep phenotypic data hold promise for obtaining novel insights into GxE, our understanding of GxE architecture in complex traits remains limited. We introduce a method to estimate the proportion of trait variance explained by GxE (GxE heritability) and additive genetic effects (additive heritability) across the genome and within specific genomic annotations. We show that our method is accurate in simulations and computationally efficient for biobank-scale datasets. We applied our method to common array SNPs (MAF ≥1%), fifty quantitative traits, and four environmental variables (smoking, sex, age, and statin usage) in unrelated white British individuals in the UK Biobank. We found 68 trait-E pairs with significant genome-wide GxE heritability (p<0.05/200) with a ratio of GxE to additive heritability of ≈6.8% on average. Analyzing ≈8 million imputed SNPs (MAF ≥0.1%), we documented an approximate 28% increase in genome-wide GxE heritability compared to array SNPs. We partitioned GxE heritability across minor allele frequency (MAF) and local linkage disequilibrium (LD) values, revealing that, like additive allelic effects, GxE allelic effects tend to increase with decreasing MAF and LD. Analyzing GxE heritability near genes highly expressed in specific tissues, we find significant brain-specific enrichment for body mass index (BMI) and basal metabolic rate in the context of smoking and adipose-specific enrichment for waist-hip ratio (WHR) in the context of sex.
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Affiliation(s)
- Ali Pazokitoroudi
- Department of Computer Science, UCLA, Los Angeles, CA, USA; Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Zhengtong Liu
- Department of Computer Science, UCLA, Los Angeles, CA, USA
| | - Andrew Dahl
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Noah Zaitlen
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA; Department of Neurology, UCLA, Los Angeles, CA, USA
| | - Saharon Rosset
- Department of Statistics, Tel-Aviv University, Tel-Aviv, Israel
| | - Sriram Sankararaman
- Department of Computer Science, UCLA, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
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9
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Yang LZ, Yang Y, Hong C, Wu QZ, Shi XJ, Liu YL, Chen GZ. Systematic Mendelian Randomization Exploring Druggable Genes for Hemorrhagic Strokes. Mol Neurobiol 2024:10.1007/s12035-024-04336-9. [PMID: 38977622 DOI: 10.1007/s12035-024-04336-9] [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: 12/30/2023] [Accepted: 06/26/2024] [Indexed: 07/10/2024]
Abstract
Patients with hemorrhagic stroke have high rates of morbidity and mortality, and drugs for prevention are very limited. Mendelian randomization (MR) analysis can increase the success rate of drug development by providing genetic evidence. Previous MR analyses only analyzed the role of individual drug target genes in hemorrhagic stroke; therefore, we used MR analysis to systematically explore the druggable genes for hemorrhagic stroke. We sequentially performed summary-data-based MR analysis and two-sample MR analysis to assess the associations of all genes within the database with intracranial aneurysm, intracerebral hemorrhage, and their subtypes. Validated genes were further analyzed by colocalization. Only genes that were positive in all three analyses and were druggable were considered desirable genes. We also explored the mediators of genes affecting hemorrhagic stroke incidence. Finally, the associations of druggable genes with other cardiovascular diseases were analyzed to assess potential side effects. We identified 56 genes that significantly affected hemorrhagic stroke incidence. Moreover, TNFSF12, SLC22A4, SPARC, KL, RELT, and ADORA3 were found to be druggable. The inhibition of TNFSF12, SLC22A4, and SPARC can reduce the risk of intracranial aneurysm, subarachnoid hemorrhage, and intracerebral hemorrhage. Gene-induced hypertension may be a potential mechanism by which these genes cause hemorrhagic stroke. We also found that blocking these genes may cause side effects, such as ischemic stroke and its subtypes. Our study revealed that six druggable genes were associated with hemorrhagic stroke, and the inhibition of TNFSF12, SLC22A4, and SPARC had preventive effects against hemorrhagic strokes.
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Affiliation(s)
- Lun-Zhe Yang
- Department of Neurosurgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yong Yang
- Department of Neurosurgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Chuan Hong
- Department of Neurosurgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Qi-Zhe Wu
- Department of Neurosurgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Xiong-Jie Shi
- Department of Neurosurgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yi-Lin Liu
- Department of Neurosurgery, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Guang-Zhong Chen
- Department of Neurosurgery, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
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10
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Hui D, Sanford E, Lorenz K, Damrauer SM, Assimes TL, Thom CS, Voight BF. Mendelian randomization analyses clarify the effects of height on cardiovascular diseases. PLoS One 2024; 19:e0298786. [PMID: 38959188 PMCID: PMC11221663 DOI: 10.1371/journal.pone.0298786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 01/30/2024] [Indexed: 07/05/2024] Open
Abstract
An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by cardiovascular, anthropometric, lung function, and lifestyle-related risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.
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Affiliation(s)
- Daniel Hui
- Graduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Eric Sanford
- Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Kimberly Lorenz
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Institute for Translational Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, United States of America
| | - Scott M. Damrauer
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, United States of America
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Themistocles L. Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, United States of America
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States of America
| | - Christopher S. Thom
- Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Institute for Translational Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, United States of America
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11
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Reed JN, Huang J, Li Y, Ma L, Banka D, Wabitsch M, Wang T, Ding W, Björkegren JL, Civelek M. Systems genetics analysis of human body fat distribution genes identifies adipocyte processes. Life Sci Alliance 2024; 7:e202402603. [PMID: 38702075 PMCID: PMC11068934 DOI: 10.26508/lsa.202402603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 05/06/2024] Open
Abstract
Excess abdominal fat is a sexually dimorphic risk factor for cardio-metabolic disease and is approximated by the waist-to-hip ratio adjusted for body mass index (WHRadjBMI). Whereas this trait is highly heritable, few causal genes are known. We aimed to identify novel drivers of WHRadjBMI using systems genetics. We used two independent cohorts of adipose tissue gene expression and constructed sex- and depot-specific Bayesian networks to model gene-gene interactions from 8,492 genes. Using key driver analysis, we identified genes that, in silico and putatively in vitro, regulate many others. 51-119 key drivers in each network were replicated in both cohorts. In other cell types, 23 of these genes are found in crucial adipocyte pathways: Wnt signaling or mitochondrial function. We overexpressed or down-regulated seven key driver genes in human subcutaneous pre-adipocytes. Key driver genes ANAPC2 and RSPO1 inhibited adipogenesis, whereas PSME3 increased adipogenesis. RSPO1 increased Wnt signaling activity. In differentiated adipocytes, MIGA1 and UBR1 down-regulation led to mitochondrial dysfunction. These five genes regulate adipocyte function, and we hypothesize that they regulate fat distribution.
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Affiliation(s)
- Jordan N Reed
- https://ror.org/0153tk833 Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- https://ror.org/0153tk833 Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jiansheng Huang
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Yong Li
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Lijiang Ma
- https://ror.org/04a9tmd77 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dhanush Banka
- https://ror.org/0153tk833 Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Martin Wabitsch
- Division of Paediatric Endocrinology and Diabetes, Department of Paediatrics and Adolescent Medicine, Ulm University Medical Centre, Ulm, Germany
| | - Tianfang Wang
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Wen Ding
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Johan Lm Björkegren
- https://ror.org/04a9tmd77 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Mete Civelek
- https://ror.org/0153tk833 Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- https://ror.org/0153tk833 Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
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12
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Agrawal S, Luan J, Cummings BB, Weiss EJ, Wareham NJ, Khera AV. Relationship of Fat Mass Ratio, a Biomarker for Lipodystrophy, With Cardiometabolic Traits. Diabetes 2024; 73:1099-1111. [PMID: 38345889 PMCID: PMC11189835 DOI: 10.2337/db23-0575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 02/06/2024] [Indexed: 06/22/2024]
Abstract
Familial partial lipodystrophy (FPLD) is a heterogenous group of syndromes associated with a high prevalence of cardiometabolic diseases. Prior work has proposed DEXA-derived fat mass ratio (FMR), defined as trunk fat percentage divided by leg fat percentage, as a biomarker of FPLD, but this metric has not previously been characterized in large cohort studies. We set out to 1) understand the cardiometabolic burden of individuals with high FMR in up to 40,796 participants in the UK Biobank and 9,408 participants in the Fenland study, 2) characterize the common variant genetic underpinnings of FMR, and 3) build and test a polygenic predictor for FMR. Participants with high FMR were at higher risk for type 2 diabetes (odds ratio [OR] 2.30, P = 3.5 × 10-41) and metabolic dysfunction-associated liver disease or steatohepatitis (OR 2.55, P = 4.9 × 10-7) in UK Biobank and had higher fasting insulin (difference 19.8 pmol/L, P = 5.7 × 10-36) and fasting triglycerides (difference 36.1 mg/dL, P = 2.5 × 10-28) in the Fenland study. Across FMR and its component traits, 61 conditionally independent variant-trait pairs were discovered, including 13 newly identified pairs. A polygenic score for FMR was associated with an increased risk of cardiometabolic diseases. This work establishes the cardiometabolic significance of high FMR, a biomarker for FPLD, in two large cohort studies and may prove useful in increasing diagnosis rates of patients with metabolically unhealthy fat distribution to enable treatment or a preventive therapy. ARTICLE HIGHLIGHTS
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Affiliation(s)
- Saaket Agrawal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Jian’an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge, U.K
| | | | | | - Nick J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge, U.K
| | - Amit V. Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of Cardiology, Department of Medicine, Brigham and Women’s Hospital, Boston, MA
- Verve Therapeutics, Boston, MA
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13
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Somasundaram A, Wu M, Reik A, Rupp S, Han J, Naebauer S, Junker D, Patzelt L, Wiechert M, Zhao Y, Rueckert D, Hauner H, Holzapfel C, Karampinos DC. Evaluating Sex-specific Differences in Abdominal Fat Volume and Proton Density Fat Fraction at MRI Using Automated nnU-Net-based Segmentation. Radiol Artif Intell 2024; 6:e230471. [PMID: 38809148 PMCID: PMC11294970 DOI: 10.1148/ryai.230471] [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: 10/27/2023] [Revised: 03/19/2024] [Accepted: 04/24/2024] [Indexed: 05/30/2024]
Abstract
Sex-specific abdominal organ volume and proton density fat fraction (PDFF) in people with obesity during a weight loss intervention was assessed with automated multiorgan segmentation of quantitative water-fat MRI. An nnU-Net architecture was employed for automatic segmentation of abdominal organs, including visceral and subcutaneous adipose tissue, liver, and psoas and erector spinae muscle, based on quantitative chemical shift-encoded MRI and using ground truth labels generated from participants of the Lifestyle Intervention (LION) study. Each organ's volume and fat content were examined in 127 participants (73 female and 54 male participants; body mass index, 30-39.9 kg/m2) and in 81 (54 female and 32 male participants) of these participants after an 8-week formula-based low-calorie diet. Dice scores ranging from 0.91 to 0.97 were achieved for the automatic segmentation. PDFF was found to be lower in visceral adipose tissue compared with subcutaneous adipose tissue in both male and female participants. Before intervention, female participants exhibited higher PDFF in subcutaneous adipose tissue (90.6% vs 89.7%; P < .001) and lower PDFF in liver (8.6% vs 13.3%; P < .001) and visceral adipose tissue (76.4% vs 81.3%; P < .001) compared with male participants. This relation persisted after intervention. As a response to caloric restriction, male participants lost significantly more visceral adipose tissue volume (1.76 L vs 0.91 L; P < .001) and showed a higher decrease in subcutaneous adipose tissue PDFF (2.7% vs 1.5%; P < .001) than female participants. Automated body composition analysis on quantitative water-fat MRI data provides new insights for understanding sex-specific metabolic response to caloric restriction and weight loss in people with obesity. Keywords: Obesity, Chemical Shift-encoded MRI, Abdominal Fat Volume, Proton Density Fat Fraction, nnU-Net ClinicalTrials.gov registration no. NCT04023942 Supplemental material is available for this article. Published under a CC BY 4.0 license.
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Affiliation(s)
| | | | - Anna Reik
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Selina Rupp
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Jessie Han
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Stella Naebauer
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Daniela Junker
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Lisa Patzelt
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Meike Wiechert
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Yu Zhao
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Daniel Rueckert
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Hans Hauner
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Christina Holzapfel
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
| | - Dimitrios C. Karampinos
- From the Department of Diagnostic and Interventional Radiology,
Klinikum rechts der Isar (A.S., M. Wu, S.R., J.H., S.N., D.J., L.P., D.C.K.),
Institute of Nutritional Medicine, School of Medicine (A.R., M. Wiechert, H.H.,
C.H.), TUM School of Computation, Information, and Technology (Y.Z., D.R.), TUM
School of Medicine and Health (D.R.), and Else Kröner Fresenius Center
for Nutritional Medicine, School of Medicine (H.H.), Technical University of
Munich, Ismaninger Str 22, 81675 Munich, Germany; Department of Computing,
Imperial College London, London, UK (D.R.); Department of Nutritional, Food and
Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany (C.H.);
and Munich Institute of Biomedical Engineering and Munich Data Science
Institute, Technical University of Munich, Garching, Germany (D.C.K.)
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14
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Rubin JB, Abou-Antoun T, Ippolito JE, Llaci L, Marquez CT, Wong JP, Yang L. Epigenetic developmental mechanisms underlying sex differences in cancer. J Clin Invest 2024; 134:e180071. [PMID: 38949020 PMCID: PMC11213507 DOI: 10.1172/jci180071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2024] Open
Abstract
Cancer risk is modulated by hereditary and somatic mutations, exposures, age, sex, and gender. The mechanisms by which sex and gender work alone and in combination with other cancer risk factors remain underexplored. In general, cancers that occur in both the male and female sexes occur more commonly in XY compared with XX individuals, regardless of genetic ancestry, geographic location, and age. Moreover, XY individuals are less frequently cured of their cancers, highlighting the need for a greater understanding of sex and gender effects in oncology. This will be necessary for optimal laboratory and clinical cancer investigations. To that end, we review the epigenetics of sexual differentiation and its effect on cancer hallmark pathways throughout life. Specifically, we will touch on how sex differences in metabolism, immunity, pluripotency, and tumor suppressor functions are patterned through the epigenetic effects of imprinting, sex chromosome complement, X inactivation, genes escaping X inactivation, sex hormones, and life history.
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Affiliation(s)
| | | | - Joseph E. Ippolito
- Department of Radiology
- Department of Biochemistry and Molecular Biophysics
| | - Lorida Llaci
- Deartment of Genetics Washington University School of Medicine, St. Louis, Missouri, USA
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15
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Chen W, Liu A, Jiang Y, Lin Y, Li X, Pan C, Wang Y, Yu H, Zhao Y, Li J, Liang H, Wang R, Wang W, Xu X, Huang Y. Association between strenuous sports or other exercises and lung cancer risk: a mendelian randomization study. Transl Lung Cancer Res 2024; 13:1210-1221. [PMID: 38973947 PMCID: PMC11225037 DOI: 10.21037/tlcr-23-810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 05/07/2024] [Indexed: 07/09/2024]
Abstract
Background Studying the relationship between strenuous sports or other exercises (SSOE) and lung cancer risk remains underexplored. Traditional observational studies face challenges like confounders and inverse causation. However, Mendelian randomization (MR) provides a promising approach in epidemiology and genetics, using genetic variants as instrumental variables to investigate causal relationships. By leveraging MR, we have scrutinized the causal link between SSOE and lung cancer development. Methods Twelve single-nucleotide polymorphisms (SNPs) associated with SSOE, as identified in previously published genome-wide association studies, were utilized as instrumental variables in our investigation. Summary genetic data at the individual level were obtained from relevant studies and cancer consortia. The study encompassed a total of 11,348 cases and 15,861 controls. The statistical technique of inverse variance-weighting (IVW), commonly employed in meta-analyses and MR studies, was employed to assess the causal relationship between SSOE and lung cancer risk. Results The MR risk analysis indicated a causal relationship between SSOE and the incidence of lung cancer, with evidence of a reduced risk for overall lung cancer [odds ratio (OR) =0.129; 95% confidence interval (CI): 0.021-0.779; P=0.03], lung adenocarcinoma (OR =0.161; 95% CI: 0.012-2.102; P=0.16) and squamous cell lung cancer (OR =0.045; 95% CI: 0.003-0.677; P=0.03). The combined OR for lung cancer from SSOE (controlling for waist circumference and smoking status) was 0.054 (95% CI: 0.010-0.302, P<0.001). Conclusions Our MR analysis findings indicate a potential correlation between SSOE and a protective effect against lung cancer development. Further investigation is imperative to uncover the precise mechanistic link between them.
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Affiliation(s)
- Wushu Chen
- Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Anlin Liu
- Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Yu Jiang
- Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Yuechun Lin
- Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Xingpei Li
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Chongde Pan
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Yixuan Wang
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Huiwen Yu
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Yulin Zhao
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Junxing Li
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Hengrui Liang
- Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
| | - Runchen Wang
- Nanshan School of Guangzhou Medical University Medical University, Guangzhou, China
| | - Wei Wang
- Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
| | - Xin Xu
- Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
| | - Ying Huang
- Department of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
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16
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Xia L, Yu XD, Wang L, Yang L, Bao EH, Wang B, Zhu PY. A Mendelian randomization study between metabolic syndrome and its components with prostate cancer. Sci Rep 2024; 14:14338. [PMID: 38906920 PMCID: PMC11192917 DOI: 10.1038/s41598-024-65310-y] [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: 02/24/2024] [Accepted: 06/19/2024] [Indexed: 06/23/2024] Open
Abstract
Previous research has produced inconsistent findings concerning the connection between metabolic syndrome and prostate cancer. It is challenging for observational studies to establish a conclusive causal relationship between the two. However, Mendelian randomization can provide stronger evidence of causality in this context. To examine the causal link between a metabolic composite and its components with prostate cancer, we performed a two-sample Mendelian randomization (MR) study utilizing aggregated data from genome-wide association studies, followed by meta-analyses. In our study, we employed inverse variance weighting as the primary method for MR analysis. Additionally, we assessed potential sources of heterogeneity and horizontal pleiotropy through the Cochran's Q test and MR-Egger regression. Moreover, we used multivariate MR to determine whether smoking versus alcohol consumption had an effect on the outcomes. We found no causal relationship between metabolic syndrome and its components and prostate cancer(MetS, odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.738-1.223, p = 0.691; TG, [OR] = 1.02, 95%[CI] = 0.96-1.08, p = 0.59); HDL, [OR] = 1.02, 95% [CI] = 0.97-1.07, p = 0.47; DBP, [OR] = 1.00, 95%[CI] = 0.99-1.01, p = 0.87; SBP, [OR] = 1.00, 95%[CI] = 0.99-1.00, p = 0.26; FBG [OR] = 0.92, 95%[CI] = 0.81-1.05, p = 0.23; WC, [OR] = 0.93, 95%[CI] = 0.84-1.03, p = 0.16). Finally, the MVMR confirms that the metabolic syndrome and its components are independent of smoking and alcohol consumption in prostate cancer. We didn't find significant evidence to determine a causal relationship between the metabolic syndrome and its components and prostate cancer through MR analysis. Further research is necessary to explore the potential pathogenesis between the two diseases.
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Affiliation(s)
- Long Xia
- Department of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Xiao-Dong Yu
- Department of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Li Wang
- Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, China
| | - Lin Yang
- Department of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Er-Hao Bao
- Department of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Ben Wang
- Department of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Ping-Yu Zhu
- Department of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China.
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17
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Cheng Z, Li J, Tong W, Liu T, Zhang C, Ma J, Lu G. Exploring the relationship between life course adiposity and sepsis: insights from a two-sample Mendelian randomization analysis. Front Endocrinol (Lausanne) 2024; 15:1413690. [PMID: 38948521 PMCID: PMC11211544 DOI: 10.3389/fendo.2024.1413690] [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: 04/07/2024] [Accepted: 06/03/2024] [Indexed: 07/02/2024] Open
Abstract
Objectives The relationship between adiposity and sepsis has received increasing attention. This study aims to explore the causal relationship between life course adiposity and the sepsis incidence. Methods Mendelian randomization (MR) method was employed in this study. Instrumental variants were obtained from genome-wide association studies for life course adiposity, including birth weight, childhood body mass index (BMI), childhood obesity, adult BMI, waist circumference, visceral adiposity, and body fat percentage. A meta-analysis of genome-wide association studies for sepsis including 10,154 cases and 454,764 controls was used in this study. MR analyses were performed using inverse variance weighted, MR Egger regression, weighted median, weighted mode, and simple mode. Instrumental variables were identified as significant single nucleotide polymorphisms at the genome-wide significance level (P < 5×10-8). The sensitivity analysis was conducted to assess the reliability of the MR estimates. Results Analysis using the MR analysis of inverse variance weighted method revealed that genetic predisposition to increased childhood BMI (OR = 1.29, P = 0.003), childhood obesity (OR = 1.07, P = 0.034), adult BMI (OR = 1.38, P < 0.001), adult waist circumference (OR = 1.01, P = 0.028), and adult visceral adiposity (OR = 1.53, P < 0.001) predicted a higher risk of sepsis. Sensitivity analysis did not identify any bias in the MR results. Conclusion The results demonstrated that adiposity in childhood and adults had causal effects on sepsis incidence. However, more well-designed studies are still needed to validate their association.
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Affiliation(s)
- Zimei Cheng
- Department of Pediatric Intensive Care Unit, Children’s Hospital of Fudan University, National Children’s Medical Center, Shanghai, China
| | - Jingjing Li
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
| | - Wenjia Tong
- Department of Pediatric Intensive Care Unit, Anhui Provincial Children's Hospital, Hefei, China
| | - Tingyan Liu
- Department of Pediatric Intensive Care Unit, Children’s Hospital of Fudan University, National Children’s Medical Center, Shanghai, China
| | - Caiyan Zhang
- Department of Pediatric Intensive Care Unit, Children’s Hospital of Fudan University, National Children’s Medical Center, Shanghai, China
| | - Jian Ma
- Department of Pediatric Intensive Care Unit, Children’s Hospital of Fudan University, National Children’s Medical Center, Shanghai, China
| | - Guoping Lu
- Department of Pediatric Intensive Care Unit, Children’s Hospital of Fudan University, National Children’s Medical Center, Shanghai, China
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
- Department of Pediatric Intensive Care Unit, Anhui Provincial Children's Hospital, Hefei, China
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18
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Xu H, Gupta S, Dinsmore I, Kollu A, Cawley AM, Anwar MY, Chen HH, Petty LE, Seshadri S, Graff M, Below P, Brody JA, Chittoor G, Fisher-Hoch SP, Heard-Costa NL, Levy D, Lin H, Loos RJF, Mccormick JB, Rotter JI, Mirshahi T, Still CD, Destefano A, Cupples LA, Mohlke KL, North KE, Justice AE, Liu CT. Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.11.24308730. [PMID: 38903089 PMCID: PMC11188121 DOI: 10.1101/2024.06.11.24308730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMI and PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA
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Affiliation(s)
- Hanfei Xu
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
| | - Shreyash Gupta
- Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Ian Dinsmore
- Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Abbey Kollu
- Department of Psychology and Neuroscience, University of North Carolina, 235 E. Cameron Avenue, Chapel Hill, NC, 27599, USA
| | - Anne Marie Cawley
- Marsico Lung Institute, University of North Carolina, 125 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Mohammad Y. Anwar
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
| | - Hung-Hsin Chen
- Institute of Biomedical Sciences, Academia Sinica, No. 128, Section 2, Academia Rd., Taipei, Nangang District, 115201, Taiwan
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
| | - Lauren E. Petty
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
| | - Sudha Seshadri
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
- Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, UT Health San Antonio, 8300 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Misa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
| | - Piper Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
| | - Jennifer A. Brody
- Department of Medicine, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Seattle, WA, 98101, USA
| | - Geetha Chittoor
- Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Susan P. Fisher-Hoch
- Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
| | - Nancy L. Heard-Costa
- Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA, 01702, USA
- Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, 72 E Concord St, Boston, MA, 02118, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, 6701 Rockledge Drive, Bethesda, MD, 20892, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, USA
| | - Ruth JF. Loos
- Charles Bronfman Institute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, 2200, Copenhagen, Denmark
| | - Joseph B. Mccormick
- Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
| | - Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90502, USA
| | - Tooraj Mirshahi
- Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Christopher D. Still
- Center for Obesity and Metabolic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Anita Destefano
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
- Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA
| | - L. Adrienne Cupples
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
| | - Karen L Mohlke
- Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
| | - Anne E. Justice
- Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Ching-Ti Liu
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
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19
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Zhang M, Ward J, Strawbridge RJ, Celis-Morales C, Pell JP, Lyall DM, Ho FK. How do lifestyle factors modify the association between genetic predisposition and obesity-related phenotypes? A 4-way decomposition analysis using UK Biobank. BMC Med 2024; 22:230. [PMID: 38853248 PMCID: PMC11163778 DOI: 10.1186/s12916-024-03436-6] [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: 12/14/2023] [Accepted: 05/22/2024] [Indexed: 06/11/2024] Open
Abstract
BACKGROUND Obesity and central obesity are multifactorial conditions with genetic and non-genetic (lifestyle and environmental) contributions. There is incomplete understanding of whether lifestyle modifies the translation from respective genetic risks into phenotypic obesity and central obesity, and to what extent genetic predisposition to obesity and central obesity is mediated via lifestyle factors. METHODS This is a cross-sectional study of 201,466 (out of approximately 502,000) European participants from UK Biobank and tested for interactions and mediation role of lifestyle factors (diet quality; physical activity levels; total energy intake; sleep duration, and smoking and alcohol intake) between genetic risk for obesity and central obesity. BMI-PRS and WHR-PRS are exposures and obesity and central obesity are outcomes. RESULTS Overall, 42.8% of the association between genetic predisposition to obesity and phenotypic obesity was explained by lifestyle: 0.9% by mediation and 41.9% by effect modification. A significant difference between men and women was found in central obesity; the figures were 42.1% (association explained by lifestyle), 1.4% (by mediation), and 40.7% (by modification) in women and 69.6% (association explained by lifestyle), 3.0% (by mediation), and 66.6% (by modification) in men. CONCLUSIONS A substantial proportion of the association between genetic predisposition to obesity/central obesity and phenotypic obesity/central obesity was explained by lifestyles. Future studies with repeated measures of obesity and lifestyle would be needed to clarify causation.
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Affiliation(s)
- Mengrong Zhang
- School of Health and Wellbeing, University of Glasgow, Clarice Pears Building, 90 Byers Road, Glasgow, G12 8TB, UK
| | - Joey Ward
- School of Health and Wellbeing, University of Glasgow, Clarice Pears Building, 90 Byers Road, Glasgow, G12 8TB, UK
| | - Rona J Strawbridge
- School of Health and Wellbeing, University of Glasgow, Clarice Pears Building, 90 Byers Road, Glasgow, G12 8TB, UK
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden
| | - Carlos Celis-Morales
- School of Cardiovascular and Metabolic Sciences, University of Glasgow, Glasgow, UK
- Human Performance Lab, Education, Physical Activity, and Health Research Unit, Universidad Católica del Maule, Talca, Chile
- Centro de Investigación en Medicina de Altura (CEIMA), Universidad Arturo Prat, Iquique, Chile
| | - Jill P Pell
- School of Health and Wellbeing, University of Glasgow, Clarice Pears Building, 90 Byers Road, Glasgow, G12 8TB, UK
| | - Donald M Lyall
- School of Health and Wellbeing, University of Glasgow, Clarice Pears Building, 90 Byers Road, Glasgow, G12 8TB, UK
| | - Frederick K Ho
- School of Health and Wellbeing, University of Glasgow, Clarice Pears Building, 90 Byers Road, Glasgow, G12 8TB, UK.
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20
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Hao RH, Zhang TP, Jiang F, Liu JH, Dong SS, Li M, Guo Y, Yang TL. Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression. Nat Commun 2024; 15:4890. [PMID: 38849352 PMCID: PMC11161590 DOI: 10.1038/s41467-024-49263-4] [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: 08/01/2023] [Accepted: 05/29/2024] [Indexed: 06/09/2024] Open
Abstract
The human brain has been implicated in the pathogenesis of several complex diseases. Taking advantage of single-cell techniques, genome-wide association studies (GWAS) have taken it a step further and revealed brain cell-type-specific functions for disease loci. However, genetic causal associations inferred by Mendelian randomization (MR) studies usually include all instrumental variables from GWAS, which hampers the understanding of cell-specific causality. Here, we developed an analytical framework, Cell-Stratified MR (csMR), to investigate cell-stratified causality through colocalizing GWAS signals with single-cell eQTL from different brain cells. By applying to obesity-related traits, our results demonstrate the cell-type-specific effects of GWAS variants on gene expression, and indicate the benefits of csMR to identify cell-type-specific causal effect that is often hidden from bulk analyses. We also found csMR valuable to reveal distinct causal pathways between different obesity indicators. These findings suggest the value of our approach to prioritize target cells for extending genetic causation studies.
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Affiliation(s)
- Ruo-Han Hao
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Tian-Pei Zhang
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Feng Jiang
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Jun-Hui Liu
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Shan-Shan Dong
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China
| | - Meng Li
- Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, P. R. China
| | - Yan Guo
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China.
| | - Tie-Lin Yang
- Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, P. R. China.
- Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, P. R. China.
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21
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Ghosh S, Bouchard C. Considerations on efforts needed to improve our understanding of the genetics of obesity. Int J Obes (Lond) 2024:10.1038/s41366-024-01528-0. [PMID: 38849463 DOI: 10.1038/s41366-024-01528-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 04/18/2024] [Accepted: 04/24/2024] [Indexed: 06/09/2024]
Affiliation(s)
- Sujoy Ghosh
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA.
| | - Claude Bouchard
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA.
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22
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Carrasquilla GD, García-Ureña M, Romero-Lado MJ, Kilpeläinen TO. Estimating causality between smoking and abdominal obesity by Mendelian randomization. Addiction 2024; 119:1024-1034. [PMID: 38509034 DOI: 10.1111/add.16454] [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: 06/09/2023] [Accepted: 01/12/2024] [Indexed: 03/22/2024]
Abstract
BACKGROUND AND AIMS Smokers tend to have a lower body weight than non-smokers, but also more abdominal fat. It remains unclear whether or not the relationship between smoking and abdominal obesity is causal. Previous Mendelian randomization (MR) studies have investigated this relationship by relying upon a single genetic variant for smoking heaviness. This approach is sensitive to pleiotropic effects and may produce imprecise causal estimates. We aimed to estimate causality between smoking and abdominal obesity using multiple genetic instruments. DESIGN MR study using causal analysis using summary effect estimates (CAUSE) and latent heritable confounder MR (LHC-MR) methods that instrument smoking using genome-wide data, and also two-sample MR (2SMR) methods. SETTING Genome-wide association studies (GWAS) summary statistics from participants of European ancestry, obtained from the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), Genetic Investigation of Anthropometric Traits (GIANT) Consortium and the UK Biobank. PARTICIPANTS We used GWAS results for smoking initiation (n = 1 232 091), life-time smoking (n = 462 690) and smoking heaviness (n = 337 334) as exposure traits, and waist-hip ratio (WHR) and waist and hip circumferences (WC and HC) (n up to 697 734), with and without adjustment for body mass index (adjBMI), as outcome traits. MEASUREMENTS Smoking initiation, life-time smoking, smoking heaviness, WHR, WC, HC, WHRadjBMI, WCadjBMI and HCadjBMI. FINDINGS Both CAUSE and LHC-MR indicated a positive causal effect of smoking initiation on WHR (0.13 [95% confidence interval (CI) = 0.10, 0.16 and 0.49 (0.41, 0.57), respectively] and WHRadjBMI (0.07 (0.03, 0.10) and 0.31 (0.26, 0.37). Similarly, they indicated a positive causal effect of life-time smoking on WHR [0.35 (0.29, 0.41) and 0.44 (0.38, 0.51)] and WHRadjBMI [0.18 (0.13, 0.24) and 0.26 (0.20, 0.31)]. In follow-up analyses, smoking particularly increased visceral fat. There was no evidence of a mediating role by cortisol or sex hormones. CONCLUSIONS Smoking initiation and higher life-time smoking may lead to increased abdominal fat distribution. The increase in abdominal fat due to smoking is characterized by an increase in visceral fat. Thus, efforts to prevent and cease smoking can have the added benefit of reducing abdominal fat.
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Affiliation(s)
- Germán D Carrasquilla
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mario García-Ureña
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - María J Romero-Lado
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Sobczyk MK, Faber BG, Southam L, Frysz M, Hartley A, Zeggini E, Tang H, Gaunt TR. Causal relationships between anthropometric traits, bone mineral density, osteoarthritis and spinal stenosis: A Mendelian randomisation investigation. Osteoarthritis Cartilage 2024; 32:719-729. [PMID: 38160745 DOI: 10.1016/j.joca.2023.12.003] [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: 10/31/2023] [Revised: 12/12/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVE Spinal stenosis is a common condition among older individuals, with significant morbidity attached. Little is known about its risk factors but degenerative conditions, such as osteoarthritis (OA) have been identified for their mechanistic role. This study aims to explore causal relationships between anthropometric risk factors, OA, and spinal stenosis using Mendelian randomisation (MR) techniques. DESIGN We applied two-sample MR to investigate the causal relationships between genetic liability for select risk factors and spinal stenosis. Next, we examined the genetic relationship between OA and spinal stenosis with linkage disequilibrium score regression and Causal Analysis Using Summary Effect estimates MR method. Finally, we used multivariable MR (MVMR) to explore whether OA and body mass index (BMI) mediate the causal pathways identified. RESULTS Our analysis revealed strong evidence for the effect of higher BMI (odds ratio [OR] = 1.54, 95%CI: 1.41-1.69, p-value = 2.7 × 10-21), waist (OR = 1.43, 95%CI: 1.15-1.79, p-value = 1.5 × 10-3) and hip (OR = 1.50, 95%CI: 1.27-1.78, p-value = 3.3 × 10-6) circumference on spinal stenosis. Strong evidence of causality was also observed for higher bone mineral density (BMD): total body (OR = 1.21, 95%CI: 1.12-1.29, p-value = 1.6 × 10-7), femoral neck (OR = 1.35, 95%CI: 1.09-1.37, p-value = 7.5×10-7), and lumbar spine (OR = 1.38, 95%CI: 1.25-1.52, p-value = 4.4 × 10-11). We detected high genetic correlations between spinal stenosis and OA (rg range: 0.47-0.66), with Causal Analysis Using Summary Effect estimates results supporting a causal effect of OA on spinal stenosis (ORallOA = 1.6, 95%CI: 1.41-1.79). Direct effects of BMI, BMD on spinal stenosis remained after adjusting for OA in the MVMR. CONCLUSIONS Genetic susceptibility to anthropometric risk factors, particularly higher BMI and BMD can increase the risk of spinal stenosis, independent of OA status. These results may inform preventative strategies and treatments.
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Affiliation(s)
- Maria K Sobczyk
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom.
| | - Benjamin G Faber
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom; Musculoskeletal Research Unit, University of Bristol, Bristol, UK.
| | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany.
| | - Monika Frysz
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom; Musculoskeletal Research Unit, University of Bristol, Bristol, UK.
| | - April Hartley
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom.
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, 85764 Neuherberg, Germany; Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, 81675 Munich, Germany.
| | - Haotian Tang
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom.
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom.
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24
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Yang Y, Wen L, Shi X, Yang C, Fan J, Zhang Y, Shen G, Zhou H, Jia X. Causal effects of sleep traits on metabolic syndrome and its components: a Mendelian randomization study. Sleep Breath 2024; 28:1423-1430. [PMID: 38507120 DOI: 10.1007/s11325-024-03020-5] [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: 11/28/2023] [Revised: 02/28/2024] [Accepted: 03/04/2024] [Indexed: 03/22/2024]
Abstract
PURPOSE Previous observational studies have suggested an association between sleep disturbance and metabolic syndrome (MetS). However, it remains unclear whether this association is causal. This study aims to investigate the causal effects of sleep-related traits on MetS using Mendelian randomization (MR). METHODS Single-nucleotide polymorphisms strongly associated with daytime napping, insomnia, chronotype, short sleep, and long sleep were selected as genetic instruments from the corresponding genome-wide association studies (GWAS). Summary-level data for MetS were obtained from two independent GWAS datasets. Univariable and multivariable MR analyses were conducted to investigate and verify the causal effects of sleep traits on MetS. RESULTS The univariable MR analysis demonstrated that genetically predicted daytime napping and insomnia were associated with increased risk of MetS in both discovery dataset (OR daytime napping = 1.630, 95% CI 1.273, 2.086; OR insomnia = 1.155, 95% CI 1.108, 1.204) and replication dataset (OR daytime napping = 1.325, 95% CI 1.131, 1.551; OR insomnia = 1.072, 95% CI 1.046, 1.099). For components, daytime napping was positively associated with triglycerides (beta = 0.383, 95% CI 0.160, 0.607) and waist circumference (beta = 0.383, 95% CI 0.184, 0.583). Insomnia was positively associated with hypertension (OR = 1.101, 95% CI 1.042, 1.162) and waist circumference (beta = 0.067, 95% CI 0.031, 0.104). The multivariable MR analysis indicated that the adverse effect of daytime napping and insomnia on MetS persisted after adjusting for BMI, smoking, drinking, and another sleep trait. CONCLUSION Our study supported daytime napping and insomnia were potential causal factors for MetS characterized by central obesity, hypertension, or elevated triglycerides.
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Affiliation(s)
- Yongli Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Long Wen
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xuezhong Shi
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Chaojun Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Jingwen Fan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Yi Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Guibin Shen
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Huiping Zhou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xiaocan Jia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
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25
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Yang S, Wang X, Li Y, Zhou L, Guo G, Wu M. The association between telomere length and blood lipids: a bidirectional two-sample Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1338698. [PMID: 38863926 PMCID: PMC11165217 DOI: 10.3389/fendo.2024.1338698] [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: 11/15/2023] [Accepted: 05/10/2024] [Indexed: 06/13/2024] Open
Abstract
Background Observational studies suggest an association between telomere length (TL) and blood lipid (BL) levels. Nevertheless, the causal connections between these two traits remain unclear. We aimed to elucidate whether genetically predicted TL is associated with BL levels via Mendelian randomization (MR) and vice versa. Methods We obtained genetic instruments associated with TL, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A-1 (ApoA-1) and apolipoprotein B (ApoB) from large-scale genome-wide association studies (GWASs). The causal relationships between TL and BL were investigated via bidirectional MR, multivariable MR and mediation analysis methods. The inverse variance weighted (IVW) method was employed as the principal methodology, complemented by several other estimators to enhance the robustness of the analysis. Results In the forward MR analyses, we identified significant positive correlation between genetically predicted TL and the levels of TG (β=0.04, 95% confidence interval [CI]: 0.01 to 0.06, p = 0.003). In the reverse MR analysis, TG (β=0.02, 95% CI: 0.01 to 0.03, p = 0.004), LDL-C (β=0.03, 95% CI: 0.01 to 0.04, p = 0.001) and ApoB (β=0.03, 95% CI: 0.01 to 0.04, p = 9.71×10-5) were significantly positively associated with TL, although this relationship was not observed in the multivariate MR analysis. The mediation analysis via two-step MR showed no significant mediation effects acting through obesity-related phenotypes in analysis of TL with TG, while the effect of LDL-C on TL was partially mediated by body mass index (BMI) in the reverse direction, with mediated proportion of 12.83% (95% CI: 0.62% to 25.04%). Conclusions Our study indicated that longer TL were associated with higher TG levels, while conversely, higher TG, LDL-C, and ApoB levels predicted longer TL, with BMI partially mediating these effects. Our findings present valuable insights into the development of preventive strategies and interventions that specifically target TL-related aging and age-related diseases.
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Affiliation(s)
- Shengjie Yang
- Guang’an men Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xinyue Wang
- Guang’an men Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yujuan Li
- Guang’an men Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Lijun Zhou
- Guang’an men Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Gang Guo
- Qilu Hospital of Shandong University, Jinan, China
| | - Min Wu
- Guang’an men Hospital, China Academy of Chinese Medical Sciences, Beijing, China
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26
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O'Reilly ME, Ho S, Coronel J, Zhu L, Liu W, Xue C, Kim E, Cynn E, Matias CV, Soni RK, Wang C, Ionita-Laza I, Bauer RC, Ross L, Zhang Y, Corvera S, Fried SK, Reilly MP. linc-ADAIN, a human adipose lincRNA, regulates adipogenesis by modulating KLF5 and IL-8 mRNA stability. Cell Rep 2024; 43:114240. [PMID: 38753486 PMCID: PMC11334222 DOI: 10.1016/j.celrep.2024.114240] [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: 07/07/2023] [Revised: 03/01/2024] [Accepted: 05/01/2024] [Indexed: 05/18/2024] Open
Abstract
Adipose tissue remodeling and dysfunction, characterized by elevated inflammation and insulin resistance, play a central role in obesity-related development of type 2 diabetes (T2D) and cardiovascular diseases. Long intergenic non-coding RNAs (lincRNAs) are important regulators of cellular functions. Here, we describe the functions of linc-ADAIN (adipose anti-inflammatory), an adipose lincRNA that is downregulated in white adipose tissue of obese humans. We demonstrate that linc-ADAIN knockdown (KD) increases KLF5 and interleukin-8 (IL-8) mRNA stability and translation by interacting with IGF2BP2. Upregulation of KLF5 and IL-8, via linc-ADAIN KD, leads to an enhanced adipogenic program and adipose tissue inflammation, mirroring the obese state, in vitro and in vivo. KD of linc-ADAIN in human adipose stromal cell (ASC) hTERT adipocytes implanted into mice increases adipocyte size and macrophage infiltration compared to implanted control adipocytes, mimicking hallmark features of obesity-induced adipose tissue remodeling. linc-ADAIN is an anti-inflammatory lincRNA that limits adipose tissue expansion and lipid storage.
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Affiliation(s)
- Marcella E O'Reilly
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Sebastian Ho
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Johana Coronel
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Lucie Zhu
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Wen Liu
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Chenyi Xue
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Eunyoung Kim
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Esther Cynn
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Caio V Matias
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Rajesh Kumar Soni
- Proteomics and Macromolecular Crystallography Shared Resource, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - Chen Wang
- Department of Statistics, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
| | - Iuliana Ionita-Laza
- Department of Statistics, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
| | - Robert C Bauer
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Leila Ross
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Yiying Zhang
- Division of Molecular Genetics, Department of Pediatrics, Columbia University Medical Center, New York, NY, USA
| | - Silvia Corvera
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Susan K Fried
- Diabetes, Obesity, and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Muredach P Reilly
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, USA; Irving Institute for Clinical and Translational Research, Columbia University, New York, NY 10032, USA.
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Pan Z, Khatry MA, Yu ML, Choudhury A, Sebastiani G, Alqahtani SA, Eslam M. MAFLD: an ideal framework for understanding disease phenotype in individuals of normal weight. Ther Adv Endocrinol Metab 2024; 15:20420188241252543. [PMID: 38808010 PMCID: PMC11131400 DOI: 10.1177/20420188241252543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/10/2024] [Indexed: 05/30/2024] Open
Abstract
The prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) is significant, impacting almost one-third of the global population. MAFLD constitutes a primary cause of end-stage liver disease, liver cancer and the need for liver transplantation. Moreover, it has a strong association with increased mortality rates due to various extrahepatic complications, notably cardiometabolic diseases. While MAFLD is typically correlated with obesity, not all individuals with obesity develop the disease and a significant percentage of MAFLD occurs in patients without obesity, termed lean MAFLD. The clinical features, progression and underlying physiological mechanisms of patients with lean MAFLD remain inadequately characterized. The present review aims to provide a comprehensive summary of current knowledge on lean MAFLD and offer a perspective on defining MAFLD in individuals with normal weight. Key to this process is the concept of metabolic health and flexibility, which links states of dysmetabolism to the development of lean MAFLD. This perspective offers a more nuanced understanding of MAFLD and its underlying mechanisms and highlights the importance of considering the broader metabolic context in which the disease occurs. It also bridges the knowledge gap and offers insights that can inform clinical practice.
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Affiliation(s)
- Ziyan Pan
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Sydney, NSW, Australia
| | - Maryam Al Khatry
- Department of Gastroenterology, Obaidullah Hospital, Emirates Health Services, Ministry of Health, Ras Al Khaimah, United Arab Emirates
| | - Ming-Lung Yu
- School of Medicine and Doctoral Program of Clinical and Experimental Medicine, College of Medicine and Center of Excellence for Metabolic Associated Fatty Liver Disease, National Sun Yat-sen University, Kaohsiung, Taiwan
- Hepatobiliary Division, Department of Internal Medicine, Kaohsiung Medical University Hospital, College of Medicine and Center for Liquid Biopsy and Cohort Research, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ashok Choudhury
- Department of Hepatology, Institute of Liver and Biliary Sciences, New Delhi, India
| | - Giada Sebastiani
- Division of Gastroenterology and Hepatology, McGill University Health Centre, Montreal, QC, Canada
| | - Saleh A. Alqahtani
- Organ Transplant Center of Excellence, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
- Division of Gastroenterology and Hepatology, Johns Hopkins University, Baltimore, MD, USA
| | - Mohammed Eslam
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, 176 Hawkesbury Road, Westmead 2145, NSW, Australia
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Hu M, Li X, Wu J, Li B, Xia J, Yang Y, Yin C. Phenome-Wide Investigation of the Causal Associations Between Pre-Pregnancy Obesity Traits and Gestational Diabetes: A Two-Sample Mendelian Randomization Analyses. Reprod Sci 2024:10.1007/s43032-024-01577-w. [PMID: 38789873 DOI: 10.1007/s43032-024-01577-w] [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: 02/08/2024] [Accepted: 04/19/2024] [Indexed: 05/26/2024]
Abstract
Pre-pregnancy obesity was associated with gestational diabetes in observational studies, but whether this relationship is causal remains to be determined. To evaluate whether pre-pregnancy obesity traits causally affect gestational diabetes risk, a two-sample Mendelian randomization (MR) analysis was performed utilizing summary-level statistics from published genome-wide association studies (GWAS). Obesity-related traits included body mass index (BMI), overweight, obesity, obesity class 1, obesity class 2, obesity class 3, childhood obesity, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), percent liver fat, visceral adipose tissue volume, abdominal subcutaneous adipose tissue volume. Effect estimates were evaluated using the inverse-variance weighting method. Weighted median, MR-Egger, simple mode, and weighted mode were performed as sensitivity analyses. Genetically predicted pre-pregnancy BMI [odds ratio (OR) = 1.68; 95% confidence interval (CI): 1.45-1.95; P = 9.13 × 10-12], overweight (OR = 1.49; 95% CI: 1.21-1.85; P = 2.06 × 10-4), obesity (OR = 1.25; 95% CI: 1.18-1.33; P = 8.01 × 10-13), obesity class 1 (OR = 1.31; 95% CI: 1.17-1.46; P = 1.49 × 10-6), obesity class 2 (OR = 1.26; 95% CI: 1.16-1.37; P = 5.23 × 10-8), childhood obesity (OR = 1.33; 95% CI: 1.23-1.44; P = 4.06 × 10-12), and WHR (OR = 2.35; 95% CI: 1.44-3.83; P = 5.89 × 10-4) were associated with increased risk of gestational diabetes. No significant association was observed with obesity class 3, WC, HC, percent liver fat, visceral adipose tissue volume, or abdominal subcutaneous adipose tissue volume. Similar results were observed in sensitivity analyses. Therefore, genetically predicted pre-pregnancy obesity traits may increase the risk of gestational diabetes. Weight control before pregnancy may be beneficial to prevent gestational diabetes.
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Affiliation(s)
- Mengjin Hu
- Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Xiaosong Li
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100037, China
| | - Jiangong Wu
- Fenyang Center for Disease Control and Prevention, Fenyang, 032200, Shanxi Province, China
| | - Boyu Li
- Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Jinggang Xia
- Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yuejin Yang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100037, China.
| | - Chunlin Yin
- Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
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Yoo L, Mendoza D, Richard AJ, Stephens JM. KAT8 beyond Acetylation: A Survey of Its Epigenetic Regulation, Genetic Variability, and Implications for Human Health. Genes (Basel) 2024; 15:639. [PMID: 38790268 PMCID: PMC11121512 DOI: 10.3390/genes15050639] [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: 04/20/2024] [Revised: 05/07/2024] [Accepted: 05/09/2024] [Indexed: 05/26/2024] Open
Abstract
Lysine acetyltransferase 8, also known as KAT8, is an enzyme involved in epigenetic regulation, primarily recognized for its ability to modulate histone acetylation. This review presents an overview of KAT8, emphasizing its biological functions, which impact many cellular processes and range from chromatin remodeling to genetic and epigenetic regulation. In many model systems, KAT8's acetylation of histone H4 lysine 16 (H4K16) is critical for chromatin structure modification, which influences gene expression, cell proliferation, differentiation, and apoptosis. Furthermore, this review summarizes the observed genetic variability within the KAT8 gene, underscoring the implications of various single nucleotide polymorphisms (SNPs) that affect its functional efficacy and are linked to diverse phenotypic outcomes, ranging from metabolic traits to neurological disorders. Advanced insights into the structural biology of KAT8 reveal its interaction with multiprotein assemblies, such as the male-specific lethal (MSL) and non-specific lethal (NSL) complexes, which regulate a wide range of transcriptional activities and developmental functions. Additionally, this review focuses on KAT8's roles in cellular homeostasis, stem cell identity, DNA damage repair, and immune response, highlighting its potential as a therapeutic target. The implications of KAT8 in health and disease, as evidenced by recent studies, affirm its importance in cellular physiology and human pathology.
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Affiliation(s)
- Lindsey Yoo
- Adipocyte Biology Laboratory, Pennington Biomedical, Baton Rouge, LA 70808, USA; (L.Y.); (D.M.); (A.J.R.)
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - David Mendoza
- Adipocyte Biology Laboratory, Pennington Biomedical, Baton Rouge, LA 70808, USA; (L.Y.); (D.M.); (A.J.R.)
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Allison J. Richard
- Adipocyte Biology Laboratory, Pennington Biomedical, Baton Rouge, LA 70808, USA; (L.Y.); (D.M.); (A.J.R.)
| | - Jacqueline M. Stephens
- Adipocyte Biology Laboratory, Pennington Biomedical, Baton Rouge, LA 70808, USA; (L.Y.); (D.M.); (A.J.R.)
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
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MacCarthy G, Pazoki R. Using Machine Learning to Evaluate the Value of Genetic Liabilities in the Classification of Hypertension within the UK Biobank. J Clin Med 2024; 13:2955. [PMID: 38792496 PMCID: PMC11122671 DOI: 10.3390/jcm13102955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 05/01/2024] [Accepted: 05/07/2024] [Indexed: 05/26/2024] Open
Abstract
Background and Objective: Hypertension increases the risk of cardiovascular diseases (CVD) such as stroke, heart attack, heart failure, and kidney disease, contributing to global disease burden and premature mortality. Previous studies have utilized statistical and machine learning techniques to develop hypertension prediction models. Only a few have included genetic liabilities and evaluated their predictive values. This study aimed to develop an effective hypertension classification model and investigate the potential influence of genetic liability for multiple risk factors linked to CVD on hypertension risk using the random forest and the neural network. Materials and Methods: The study involved 244,718 European participants, who were divided into training and testing sets. Genetic liabilities were constructed using genetic variants associated with CVD risk factors obtained from genome-wide association studies (GWAS). Various combinations of machine learning models before and after feature selection were tested to develop the best classification model. The models were evaluated using area under the curve (AUC), calibration, and net reclassification improvement in the testing set. Results: The models without genetic liabilities achieved AUCs of 0.70 and 0.72 using the random forest and the neural network methods, respectively. Adding genetic liabilities improved the AUC for the random forest but not for the neural network. The best classification model was achieved when feature selection and classification were performed using random forest (AUC = 0.71, Spiegelhalter z score = 0.10, p-value = 0.92, calibration slope = 0.99). This model included genetic liabilities for total cholesterol and low-density lipoprotein (LDL). Conclusions: The study highlighted that incorporating genetic liabilities for lipids in a machine learning model may provide incremental value for hypertension classification beyond baseline characteristics.
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Affiliation(s)
- Gideon MacCarthy
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London UB8 3PH, UK
| | - Raha Pazoki
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London UB8 3PH, UK
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary’s Campus, Norfolk Place, Imperial College London, London W2 1PG, UK
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31
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Zhao Y, Pang J, Fang X, Yan Z, Yang H, Deng Q, Ma T, Lv M, Li Y, Tu Z, Zou L. Causal relationships between modifiable risk factors and polycystic ovary syndrome: a comprehensive Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1348368. [PMID: 38779450 PMCID: PMC11109383 DOI: 10.3389/fendo.2024.1348368] [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: 12/02/2023] [Accepted: 04/15/2024] [Indexed: 05/25/2024] Open
Abstract
Background Polycystic Ovary Syndrome (PCOS) is a heritable condition with an as yet unclear etiology. Various factors, such as genetics, lifestyle, environment, inflammation, insulin resistance, hyperandrogenism, iron metabolism, and gut microbiota, have been proposed as potential contributors to PCOS. Nevertheless, a systematic assessment of modifiable risk factors and their causal effects on PCOS is lacking. This study aims to establish a comprehensive profile of modifiable risk factors for PCOS by utilizing a two-sample Mendelian Randomization (MR) framework. Methods After identifying over 400 modifiable risk factors, we employed a two-sample MR approach, including the Inverse Variance Weighted (IVW) method, Weighted Median method, and MR-Egger, to investigate their causal associations with PCOS. The reliability of our estimates underwent rigorous examination through sensitivity analyses, encompassing Cochran's Q test, MR-Egger intercept analysis, leave-one-out analysis, and funnel plots. Results We discovered that factors such as smoking per day, smoking initiation, body mass index, basal metabolic rate, waist-to-hip ratio, whole body fat mass, trunk fat mass, overall health rating, docosahexaenoic acid (DHA) (22:6n-3) in blood, monounsaturated fatty acids, other polyunsaturated fatty acids apart from 18:2 in blood, omega-3 fatty acids, ratio of bisallylic groups to double bonds, omega-9 and saturated fatty acids, total lipids in medium VLDL, phospholipids in medium VLDL, phospholipids in very large HDL, triglycerides in very large HDL, the genus Oscillibacter, the genus Alistipes, the genus Ruminiclostridium 9, the class Mollicutes, and the phylum Tenericutes, showed a significant effect on heightening genetic susceptibility of PCOS. In contrast, factors including fasting insulin interaction with body mass index, sex hormone-binding globulin, iron, ferritin, SDF1a, college or university degree, years of schooling, household income, the genus Enterorhabdus, the family Bifidobacteriaceae, the order Bifidobacteriales, the class Actinobacteria, and the phylum Actinobacteria were determined to reduce risk of PCOS. Conclusion This study innovatively employs the MR method to assess causal relationships between 400 modifiable risk factors and the susceptibility of PCOS risk. It supports causal links between factors like smoking, BMI, and various blood lipid levels and PCOS. These findings offer novel insights into potential strategies for the management and treatment of PCOS.
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Affiliation(s)
- Yuheng Zhao
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
- The First School of Clinical Medicine, Graduate School of Guangdong Medical University, Zhanjiang, China
| | - Jinglin Pang
- The First School of Clinical Medicine, Graduate School of Guangdong Medical University, Zhanjiang, China
- Department of Anorectal Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Xingyi Fang
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Zhaohua Yan
- Department of Obstetrics and Gynecology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Haili Yang
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Qinghua Deng
- Department of Gynecology, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Tianzhong Ma
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Mengqi Lv
- Department of Pathology, Southwest Hospital of Army Medical University, Chongqing, China
| | - Yingying Li
- The First School of Clinical Medicine, Graduate School of Guangdong Medical University, Zhanjiang, China
- Department of Obstetrics and Gynecology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Ziying Tu
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
- The First School of Clinical Medicine, Graduate School of Guangdong Medical University, Zhanjiang, China
| | - Lin Zou
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
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32
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Shi H, Wu Q, Guo N, Liu L, Widjaja J, Yang J, Gu Y. Causal relationship of obesity and adiposity distribution on risk of ventral hernia. World J Surg 2024; 48:1141-1148. [PMID: 38520680 DOI: 10.1002/wjs.12137] [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: 12/29/2023] [Accepted: 03/05/2024] [Indexed: 03/25/2024]
Abstract
PURPOSE Ventral hernia (VH) is a common surgical disease. Previous studies suggested that obesity is an important risk factor for VH. However, the causal relationship between fat distribution and the risk of VH is still unclear. This study used Mendelian randomization (MR) to evaluate their causal relationship. METHODS We used the body mass index (BMI), body fat percentage, and body fat mass to represent general obesity and utilized the volume of abdominal subcutaneous adiposity tissue, visceral adiposity tissue, waist circumference, hip circumference, and waist-to-hip ratio to represent abdominal adiposity. The data were extracted from the large-scale genome-wide association study of European ancestry. We used two-sample MR to infer causality, using multivariate MR to correct the effects of confounding factors. RESULTS Increased BMI, body fat percentage, body fat mass, visceral adiposity tissue, waist circumference, and hip circumference rather than subcutaneous adiposity tissue or waist-to-hip ratio, were causally associated with a higher risk of VH. The results of multivariate MR suggested that body fat percentage was causally associated with a higher risk of VH after adjusting for body mass index, diabetes, and smoking. CONCLUSION General obesity, increased visceral adiposity tissue, waist circumference, and hip circumference rather than subcutaneous adiposity tissue or the waist-to-hip ratio were causally associated with a higher risk of VH. These findings provided a deeper understanding of the role that the distribution of adiposity plays in the mechanism of VH.
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Affiliation(s)
- Hekai Shi
- Department of General Surgery, Fudan University Affiliated Huadong Hospital, Shanghai, China
| | - Qian Wu
- Department of General Surgery, Fudan University Affiliated Huadong Hospital, Shanghai, China
| | - Nuojin Guo
- Department of Endocrinology, Shanghai East Hospital, Tongji University, Shanghai, China
| | - Ligang Liu
- Institute of Therapeutic Innovations and Outcomes, College of Pharmacy, The Ohio State University, Columbus, Ohio, USA
| | - Jason Widjaja
- Department of General Surgery, Fudan University Affiliated Huadong Hospital, Shanghai, China
| | - Jianjun Yang
- Department of General Surgery, Fudan University Affiliated Huadong Hospital, Shanghai, China
| | - Yan Gu
- Department of General Surgery, Fudan University Affiliated Huadong Hospital, Shanghai, China
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33
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Rontogianni MO, Bouras E, Aglago EK, Freisling H, Murphy N, Cotterchio M, Hampe J, Lindblom A, Pai RK, Pharoah PDP, Phipps AI, van Duijnhoven FJB, Visvanathan K, van Guelpen B, Li CI, Brenner H, Pellatt AJ, Ogino S, Gunter MJ, Peters U, Christakoudi S, Tsilidis KK. Allometric versus traditional body-shape indices and risk of colorectal cancer: a Mendelian randomization analysis. Int J Obes (Lond) 2024; 48:709-716. [PMID: 38297030 PMCID: PMC11058311 DOI: 10.1038/s41366-024-01479-6] [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: 06/27/2023] [Revised: 01/12/2024] [Accepted: 01/18/2024] [Indexed: 02/02/2024]
Abstract
BACKGROUND Traditional body-shape indices such as Waist Circumference (WC), Hip Circumference (HC), and Waist-to-Hip Ratio (WHR) are associated with colorectal cancer (CRC) risk, but are correlated with Body Mass Index (BMI), and adjustment for BMI introduces a strong correlation with height. Thus, new allometric indices have been developed, namely A Body Shape Index (ABSI), Hip Index (HI), and Waist-to-Hip Index (WHI), which are uncorrelated with weight and height; these have also been associated with CRC risk in observational studies, but information from Mendelian randomization (MR) studies is missing. METHODS We used two-sample MR to examine potential causal cancer site- and sex-specific associations of the genetically-predicted allometric body-shape indices with CRC risk, and compared them with BMI-adjusted traditional body-shape indices, and BMI. Data were obtained from UK Biobank and the GIANT consortium, and from GECCO, CORECT and CCFR consortia. RESULTS WHI was positively associated with CRC in men (OR per SD: 1.20, 95% CI: 1.03-1.39) and in women (1.15, 1.06-1.24), and similarly for colon and rectal cancer. ABSI was positively associated with colon and rectal cancer in men (1.27, 1.03-1.57; and 1.40, 1.10-1.77, respectively), and with colon cancer in women (1.20, 1.07-1.35). There was little evidence for association between HI and colon or rectal cancer. The BMI-adjusted WHR and HC showed similar associations to WHI and HI, whereas WC showed similar associations to ABSI only in women. CONCLUSIONS This large MR study provides strong evidence for a potential causal positive association of the allometric indices ABSI and WHI with CRC in both sexes, thus establishing the association between abdominal fat and CRC without the limitations of the traditional waist size indices and independently of BMI. Among the BMI-adjusted traditional indices, WHR and HC provided equivalent associations with WHI and HI, while differences were observed between WC and ABSI.
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Affiliation(s)
- Marina O Rontogianni
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Emmanouil Bouras
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
- Department of Hygiene, Social-Preventive Medicine and Medical Statistics, Aristotle University of Thessaloniki School of Medicine, Thessaloniki, Greece
| | - Elom Kouassivi Aglago
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
| | - Heinz Freisling
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Neil Murphy
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Michelle Cotterchio
- Ontario Health (Cancer Care Ontario), Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Jochen Hampe
- Department of Medicine I, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Annika Lindblom
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Rish K Pai
- Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Paul D P Pharoah
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Amanda I Phipps
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, USA
| | | | - Kala Visvanathan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Bethany van Guelpen
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
- Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Christopher I Li
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, USA
- Translational Research Program and Epidemiology Program, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andrew J Pellatt
- Division of Cancer Medicine, University of Texas MD Anderson Cancer Center, Texas, TX, USA
| | - Shuji Ogino
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Cancer Immunology and Cancer Epidemiology Programs, Dana-Farber Harvard Cancer Center, Boston, MA, USA
| | - Marc J Gunter
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, USA
| | - Sofia Christakoudi
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- Department of Inflammation Biology, School of Immunology and Microbial Sciences, King's College London, London, UK
| | - Konstantinos K Tsilidis
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece.
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK.
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Hezekiah C, Blakemore AI, Bailey DP, Pazoki R. Physical activity alters the effect of genetic determinants of adiposity on hypertension among individuals of European ancestry in the UKB. Scand J Med Sci Sports 2024; 34:e14636. [PMID: 38671551 PMCID: PMC11135603 DOI: 10.1111/sms.14636] [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: 01/25/2024] [Revised: 03/30/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024]
Abstract
Hypertension is a leading risk factor for cardiovascular disease and is modulated by genetic variants. This study aimed to assess the effect of obesity genetic liability and physical activity on hypertension among European and African ancestry individuals within the UK Biobank (UKB). Participants were 230 115 individuals of European ancestry and 3239 individuals of African ancestry from UKB. Genetic liability for obesity were estimated using previously published data including genetic variants and effect sizes for body mass index (BMI), waist-hip ratio (WHR) and waist circumference (WC) using Plink software. The outcome was defined as stage 2 hypertension (systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥90 mmHg, or the use of anti-hypertensive medications). The association between obesity genetic liability and the outcome was assessed across categories of self-reported physical activity using logistic regression. Among European ancestry participants, there was up to a 1.2 greater odds of hypertension in individuals with high genetic liability and low physical activity compared to individuals with low genetic liability and high physical activity (p < 0.001). In individuals engaging in low levels of physical activity compared with moderate/high physical activity, the effect of BMI genetic liability on hypertension was greater (p interaction = 0.04). There was no evidence of an association between obesity genetic liability and hypertension in individuals of African ancestry in the whole sample or within separate physical activity groups (p > 0.05). This study suggests that higher physical activity levels are associated with lower odds of stage 2 hypertension among European ancestry individuals who carry high genetic liability for obesity. This cannot be inferred for individuals of African ancestry, possibly due to the low African ancestry sample size within the UKB.
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Affiliation(s)
- Chukwueloka Hezekiah
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life SciencesBrunel University LondonLondonUK
- Department of Mental Health, Faculty of Health, Science, Social Care and EducationKingston UniversitySurreyUK
| | - Alexandra I. Blakemore
- Department of Life Sciences, Centre for Cognitive Neuroscience, College of Health, Medicine and Life SciencesBrunel University LondonLondonUK
- Department of MetabolismDigestion and Reproduction, Imperial College LondonLondonUK
- School of MedicineUniversity of IrelandGalwayIreland
| | - Daniel P. Bailey
- Centre for Physical Activity in Health and Disease, College of Health, Medicine and Life SciencesBrunel University LondonUxbridgeUK
- Division of Sport, Health and Exercise Sciences, Department of Life SciencesBrunel University LondonUxbridgeUK
| | - Raha Pazoki
- Cardiovascular and Metabolic Research Group, Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life SciencesBrunel University LondonLondonUK
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUK
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35
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Liu BH, Mao YH, Li XY, Luo RX, Zhu WA, Su HB, Zeng HD, Chen CH, Zhao X, Zou C, Luo Y. Measurements of peri-prostatic adipose tissue by MRI predict bone metastasis in patients with newly diagnosed prostate cancer. Front Oncol 2024; 14:1393650. [PMID: 38737904 PMCID: PMC11082333 DOI: 10.3389/fonc.2024.1393650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 04/15/2024] [Indexed: 05/14/2024] Open
Abstract
Objectives To investigate the role of MRI measurements of peri-prostatic adipose tissue (PPAT) in predicting bone metastasis (BM) in patients with newly diagnosed prostate cancer (PCa). Methods We performed a retrospective study on 156 patients newly diagnosed with PCa by prostate biopsy between October 2010 and November 2022. Clinicopathologic characteristics were collected. Measurements including PPAT volume and prostate volume were calculated by MRI, and the normalized PPAT (PPAT volume/prostate volume) was computed. Independent predictors of BM were determined by univariate and multivariate logistic regression analysis, and a new nomogram was developed based on the predictors. Receiver operating characteristic (ROC) curves were used to estimate predictive performance. Results PPAT and normalized PPAT were associated with BM (P<0.001). Normalized PPAT positively correlated with clinical T stage(cT), clinical N stage(cN), and Grading Groups(P<0.05). The results of ROC curves indicated that PPAT and normalized PPAT had promising predictive value for BM with the AUC of 0.684 and 0.775 respectively. Univariate and multivariate analysis revealed that high normalized PPAT, cN, and alkaline phosphatase(ALP) were independently predictors of BM. The nomogram was developed and the concordance index(C-index) was 0.856. Conclusions Normalized PPAT is an independent predictor for BM among with cN, and ALP. Normalized PPAT may help predict BM in patients with newly diagnosed prostate cancer, thus providing adjunctive information for BM risk stratification and bone scan selection.
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Affiliation(s)
- Bo-Hao Liu
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yun-Hua Mao
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xiao-Yang Li
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Rui-Xiang Luo
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Wei-An Zhu
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Hua-Bin Su
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Heng-Da Zeng
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Chu-Hao Chen
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xiao Zhao
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Chen Zou
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yun Luo
- Department of Urology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- Department of Urology, Kashgar First People’s Hospital, Kashgar, Xinjiang, China
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Lingyu M, Hongguang L, Mingdong Z, Na L, Yahui L. Aminotransferases as causal factors for metabolic syndrome: A bidirectional Mendelian randomization study. PLoS One 2024; 19:e0302209. [PMID: 38662679 PMCID: PMC11045112 DOI: 10.1371/journal.pone.0302209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 03/30/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Circulating aminotransferases (ALT and AST) have been used as biomarkers for liver injury. The causal relationships between aminotransferases and metabolic syndrome remain ambiguous. METHODS We conducted bidirectional and multivariable Mendelian randomization (MR) analyses between aminotransferases and traits related to metabolic syndrome using genetic variants obtained from genome-wide association studies (GWASs). MR-PRESSO tests were adopted to remove outliers and eliminate pleiotropy. MR steiger tests were conducted to ensure the correct direction of the causal effects. RESULTS Both aminotransferases were risk factors for essential hypertension. ALT is a risk factor for type 2 diabetes. The bidirectional causal relationship between ALT and hyperglycemia, serum lipids, and obesity was demonstrated. The effect of fasting glucose on AST was demonstrated, while type 2 diabetes did not affect AST. The effect of HDL-C on ALT and the effect of triglycerides on AST were found in multivariable MR analyses. CONCLUSIONS Our bidirectional MR analyses suggest that ALT and AST are causally associated with several metabolic syndrome-related traits, especially hypertension and type 2 diabetes. These findings highlight the potential role of aminotransferases as biomarkers and therapeutic targets for metabolic syndrome.
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Affiliation(s)
- Meng Lingyu
- Hepatobiliary and Pancreatic Surgery Department, General Surgery Center, First Hospital of Jilin University, Changchun, Jilin, China
| | - Li Hongguang
- Office of Hospital Infection Control, The Third Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, Jilin, China
| | - Zhang Mingdong
- Faculty of Rehabilitation Medicine, Changchun University of Chinese Medicine, Changchun, Jilin, China
| | - Li Na
- Beihua University, Changchun, Jilin, China
| | - Liu Yahui
- Hepatobiliary and Pancreatic Surgery Department, General Surgery Center, First Hospital of Jilin University, Changchun, Jilin, China
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Kiseleva OI, Pyatnitskiy MA, Arzumanian VA, Kurbatov IY, Ilinsky VV, Ilgisonis EV, Plotnikova OA, Sharafetdinov KK, Tutelyan VA, Nikityuk DB, Ponomarenko EA, Poverennaya EV. Multiomics Picture of Obesity in Young Adults. BIOLOGY 2024; 13:272. [PMID: 38666884 PMCID: PMC11048234 DOI: 10.3390/biology13040272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/02/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024]
Abstract
Obesity is a socially significant disease that is characterized by a disproportionate accumulation of fat. It is also associated with chronic inflammation, cancer, diabetes, and other comorbidities. Investigating biomarkers and pathological processes linked to obesity is especially vital for young individuals, given their increased potential for lifestyle modifications. By comparing the genetic, proteomic, and metabolomic profiles of individuals categorized as underweight, normal, overweight, and obese, we aimed to determine which omics layer most accurately reflects the phenotypic changes in an organism that result from obesity. We profiled blood plasma samples by employing three omics methodologies. The untargeted GC×GC-MS metabolomics approach identified 313 metabolites. To augment the metabolomic dataset, we integrated a label-free HPLC-MS/MS proteomics method, leading to the identification of 708 proteins. The genomic layer encompassed the genotyping of 647,250 SNPs. Utilizing omics data, we trained sparse Partial Least Squares models to predict body mass index. Molecular features exhibiting frequently non-zero coefficients were selected as potential biomarkers, and we further explored enriched biological pathways. Proteomics was the most effective in single-omics analyses, with a median absolute error (MAE) of 5.44 ± 0.31 kg/m2, incorporating an average of 24 proteins per model. Metabolomics showed slightly lower performance (MAE = 6.06 ± 0.33 kg/m2), followed by genomics (MAE = 6.20 ± 0.34 kg/m2). As expected, multiomic models demonstrated better accuracy, particularly the combination of proteomics and metabolomics (MAE = 4.77 ± 0.33 kg/m2), while including genomics data did not enhance the results. This manuscript is the first multiomics study of obesity in a gender-balanced cohort of young adults profiled by genomic, proteomic, and metabolomic methods. The comprehensive approach provides novel insights into the molecular mechanisms of obesity, opening avenues for more targeted interventions.
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Affiliation(s)
- Olga I. Kiseleva
- Institute of Biomedical Chemistry, Moscow 119121, Russia; (O.I.K.)
| | - Mikhail A. Pyatnitskiy
- Institute of Biomedical Chemistry, Moscow 119121, Russia; (O.I.K.)
- Faculty of Computer Science, National Research University Higher School of Economics, Moscow 101000, Russia
| | | | - Ilya Y. Kurbatov
- Institute of Biomedical Chemistry, Moscow 119121, Russia; (O.I.K.)
| | | | | | - Oksana A. Plotnikova
- Federal Research Centre of Nutrition, Biotechnology and Food Safety, Russian Academy of Sciences, Moscow 109240, Russia
| | - Khaider K. Sharafetdinov
- Federal Research Centre of Nutrition, Biotechnology and Food Safety, Russian Academy of Sciences, Moscow 109240, Russia
- Russian Medical Academy of Continuing Professional Education, Ministry of Health of the Russian Federation, Moscow 125993, Russia
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of the Russian Federation, Moscow 119991, Russia
| | - Victor A. Tutelyan
- Federal Research Centre of Nutrition, Biotechnology and Food Safety, Russian Academy of Sciences, Moscow 109240, Russia
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of the Russian Federation, Moscow 119991, Russia
| | - Dmitry B. Nikityuk
- Federal Research Centre of Nutrition, Biotechnology and Food Safety, Russian Academy of Sciences, Moscow 109240, Russia
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of the Russian Federation, Moscow 119991, Russia
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Ning L, He C, Lu C, Huang W, Zeng T, Su Q. Association between basal metabolic rate and cardio-metabolic risk factors: Evidence from a Mendelian Randomization study. Heliyon 2024; 10:e28154. [PMID: 38590845 PMCID: PMC10999873 DOI: 10.1016/j.heliyon.2024.e28154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 03/12/2024] [Accepted: 03/13/2024] [Indexed: 04/10/2024] Open
Abstract
Background Cardio-metabolic risk factors play a crucial role in the development of cardiovascular and metabolic diseases. Basal metabolic rate (BMR) is a fundamental physiological parameter that affects energy expenditure and might contribute to variations in these risk factors. However, the exact relationship between BMR and cardio-metabolic risk factors has remained unclear. Methods We employed Mendelian Randomization (MR) analysis to explore the association between BMR (N: 534,045) and various cardio-metabolic risk factors, including body mass index (BMI, N: 681,275), fasting glucose (N: 200,622), high-density lipoprotein (HDL) cholesterol (N = 403,943), low-density lipoprotein (LDL) cholesterol (N = 431,167), total cholesterol (N: 344,278), and triglycerides (N: 441,016), C-reactive protein (N: 436,939), waist circumference (N: 232,101), systolic blood pressure (N: 810,865), diastolic blood pressure (N: 810,865), glycated haemoglobin (N: 389,889), and N-terminal prohormone brain natriuretic peptide (N: 21,758). We leveraged genetic variants strongly associated with BMR as instrumental variables to investigate potential causal relationships, with the primary analysis using the Inverse Variance Weighted (IVW) method. Results Our MR analysis revealed compelling evidence of a causal link between BMR and specific cardio-metabolic risk factors. Specifically, genetically determined higher BMR was associated with an increased BMI (β = 0.7538, 95% confidence interval [CI]: 0.6418 to 0.8659, p < 0.001), lower levels of HDL cholesterol (β = -0.3293, 95% CI: 0.4474 to -0.2111, p < 0.001), higher levels of triglycerides (β = 0.1472, 95% CI: 0.0370 to 0.2574, p = 0.0088), waist circumference (β = 0.4416, 95% CI: 0.2949 to 0.5883, p < 0.001), and glycated haemoglobin (β = 0.1037, 95% CI: 0.0080 to 0.1995, p = 0.0377). However, we did not observe any significant association between BMR and fasting glucose, LDL cholesterol, total cholesterol, C-reactive protein, systolic blood pressure, diastolic blood pressure, or N-terminal prohormone brain natriuretic peptide (all p-values>0.05). Conclusion This MR study provides valuable insights into the relationship between BMR and cardio-metabolic risk factors. Understanding the causal links between BMR and these factors could have important implications for the development of targeted interventions and therapies.
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Affiliation(s)
- Limeng Ning
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi, 530021, China
| | - Changjing He
- Pediatric surgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Youjiang Medical University for Nationalities, Baise, China
- Health Management Service Center, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No.85 Hedi Road, Nanning, Guangxi, 530021, China
- Guangxi Clinical Medical Research Center for Hepatobiliary Diseases, China
- Guangxi Zhuang Autonomous Region Engineering Research Center for Biomaterials in Bone and Joint Degenerative Diseases, China
- Guangxi Key Laboratory for Preclinica1 and Translational Research on Bone and Joint Degenerative Diseases, China
- Guangxi Key Laboratory of Molecular Pathology in Hepatobiliary Diseases, China
- Guangxi Key Laboratory of Clinical Cohort Research on Bone and Joint Degenerative Disease, China
- Guangxi Key Laboratory of Medical Research Basic Guarantee for Immune-Related Disease Research, China
- Guangxi Key Laboratory for Biomedical Material Research, China
- Key Laboratory of Research on Prevention and Control of High Incidence Diseases in Western Guangxi, China
- Key Laboratory of Molecular Pathology in Tumors of Guangxi, China
- Key Laboratory of Research on Clinical Molecular Diagnosis for High Incidence Diseases in Western Guangxi, China
- Baise Key Laboratory of Mo1ecular Pathology in Tumors, China
- Baise Key Laboratory for Metabolic Diseases, China
- Baise Key Laboratory for Research and Deve1opment on Clinical Mo1ecular Diagnosis for High-Incidence Diseases, China
- Key Laboratory of the Bone and Joint Degenerative Diseases, China
- Laboratory of the Atherosclerosis and Ischemic Cardiovascular Diseases, China
- Life Science and C1inical Medicine Research Center, China
- Key Laboratory of Clinical Diagnosis and Treatment Research of High Incidence Diseases in Guangxi, China
| | - Chunliu Lu
- Health Management Service Center, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No.85 Hedi Road, Nanning, Guangxi, 530021, China
| | - Wanzhong Huang
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi, 530021, China
| | - Ting Zeng
- Health Management Service Center, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi, 530021, China
| | - Qiang Su
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi, 530021, China
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Timasheva Y, Balkhiyarova Z, Avzaletdinova D, Morugova T, Korytina GF, Nouwen A, Prokopenko I, Kochetova O. Mendelian Randomization Analysis Identifies Inverse Causal Relationship between External Eating and Metabolic Phenotypes. Nutrients 2024; 16:1166. [PMID: 38674857 PMCID: PMC11054043 DOI: 10.3390/nu16081166] [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: 02/22/2024] [Revised: 04/10/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
Disordered eating contributes to weight gain, obesity, and type 2 diabetes (T2D), but the precise mechanisms underlying the development of different eating patterns and connecting them to specific metabolic phenotypes remain unclear. We aimed to identify genetic variants linked to eating behaviour and investigate its causal relationships with metabolic traits using Mendelian randomization (MR). We tested associations between 30 genetic variants and eating patterns in individuals with T2D from the Volga-Ural region and investigated causal relationships between variants associated with eating patterns and various metabolic and anthropometric traits using data from the Volga-Ural population and large international consortia. We detected associations between HTR1D and CDKAL1 and external eating; between HTR2A and emotional eating; between HTR2A, NPY2R, HTR1F, HTR3A, HTR2C, CXCR2, and T2D. Further analyses in a separate group revealed significant associations between metabolic syndrome (MetS) and the loci in CRP, ADCY3, GHRL, CDKAL1, BDNF, CHRM4, CHRM1, HTR3A, and AKT1 genes. MR results demonstrated an inverse causal relationship between external eating and glycated haemoglobin levels in the Volga-Ural sample. External eating influenced anthropometric traits such as body mass index, height, hip circumference, waist circumference, and weight in GWAS cohorts. Our findings suggest that eating patterns impact both anthropometric and metabolic traits.
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Affiliation(s)
- Yanina Timasheva
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of Russian Academy of Sciences, Ufa 450054, Russia; (G.F.K.); (O.K.)
- Department of Medical Genetics and Fundamental Medicine, Bashkir State Medical University, Ufa 450008, Russia;
| | - Zhanna Balkhiyarova
- Section of Statistical Multi-Omics, Department of Clinical & Experimental Medicine, School of Biosciences & Medicine, University of Surrey, Guildford GU2 7XH, UK; (Z.B.); (I.P.)
- Department of Endocrinology, Bashkir State Medical University, Ufa 450008, Russia;
| | - Diana Avzaletdinova
- Department of Medical Genetics and Fundamental Medicine, Bashkir State Medical University, Ufa 450008, Russia;
- Department of Endocrinology, Bashkir State Medical University, Ufa 450008, Russia;
| | - Tatyana Morugova
- Department of Endocrinology, Bashkir State Medical University, Ufa 450008, Russia;
| | - Gulnaz F. Korytina
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of Russian Academy of Sciences, Ufa 450054, Russia; (G.F.K.); (O.K.)
- Department of Biology, Bashkir State Medical University, Ufa 450008, Russia
| | - Arie Nouwen
- Department of Psychology, Middlesex University, London NW4 4BT, UK;
| | - Inga Prokopenko
- Section of Statistical Multi-Omics, Department of Clinical & Experimental Medicine, School of Biosciences & Medicine, University of Surrey, Guildford GU2 7XH, UK; (Z.B.); (I.P.)
| | - Olga Kochetova
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of Russian Academy of Sciences, Ufa 450054, Russia; (G.F.K.); (O.K.)
- Department of Biology, Bashkir State Medical University, Ufa 450008, Russia
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Zhao P, Sheng Z, Xu L, Li P, Xiao W, Yuan C, Xu Z, Yang M, Qian Y, Zhong J, Gu J, Karasik D, Zheng HF. Deciphering the complex relationship between type 2 diabetes and fracture risk with both genetic and observational evidence. eLife 2024; 12:RP89281. [PMID: 38591545 PMCID: PMC11003741 DOI: 10.7554/elife.89281] [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] [Indexed: 04/10/2024] Open
Abstract
The 'diabetic bone paradox' suggested that type 2 diabetes (T2D) patients would have higher areal bone mineral density (BMD) but higher fracture risk than individuals without T2D. In this study, we found that the genetically predicted T2D was associated with higher BMD and lower risk of fracture in both weighted genetic risk score (wGRS) and two-sample Mendelian randomization (MR) analyses. We also identified ten genomic loci shared between T2D and fracture, with the top signal at SNP rs4580892 in the intron of gene RSPO3. And the higher expression in adipose subcutaneous and higher protein level in plasma of RSPO3 were associated with increased risk of T2D, but decreased risk of fracture. In the prospective study, T2D was observed to be associated with higher risk of fracture, but BMI mediated 30.2% of the protective effect. However, when stratified by the T2D-related risk factors for fracture, we observed that the effect of T2D on the risk of fracture decreased when the number of T2D-related risk factors decreased, and the association became non-significant if the T2D patients carried none of the risk factors. In conclusion, the genetically determined T2D might not be associated with higher risk of fracture. And the shared genetic architecture between T2D and fracture suggested a top signal around RSPO3 gene. The observed effect size of T2D on fracture risk decreased if the T2D-related risk factors could be eliminated. Therefore, it is important to manage the complications of T2D to prevent the risk of fracture.
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Affiliation(s)
- Pianpian Zhao
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, ChinaHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - Zhifeng Sheng
- Health Management Center, The Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Lin Xu
- Department of Orthopedics, Yantai Affiliated Hospital of Binzhou Medical UniversityYantaiChina
| | - Peng Li
- Department of Geratology, The Third People's Hospital of HangzhouHangzhouChina
| | - Wenjin Xiao
- Department of Endocrinology, Second Affiliated Hospital of Soochow UniversitySuzhouChina
| | - Chengda Yuan
- Department of Dermatology, Hangzhou Hospital of Traditional Chinese MedicineHangzhouChina
| | - Zhanwei Xu
- Central Health Center of Mashenqiao TownTianjinChina
| | - Mengyuan Yang
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - Yu Qian
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - Jiadong Zhong
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - Jiaxuan Gu
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
| | - David Karasik
- Azrieli Faculty of Medicine, Bar-Ilan UniversitySafedIsrael
| | - Hou-Feng Zheng
- The affiliated Hangzhou first people’s hospital, School of Medicine, Westlake UniversityHangzhouChina
- Diseases & Population (DaP) Geninfo Lab, School of Life Sciences, Westlake University, Hangzhou, ChinaHangzhouChina
- Westlake Laboratory of Life Sciences and BiomedicineHangzhouChina
- Institute of Basic Medical Sciences, Westlake Institute for Advanced StudyHangzhouChina
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Zeng L, Li Y, Hong C, Wang J, Zhu H, Li Q, Cui H, Ma P, Li R, He J, Zhu H, Liu L, Xiao L. Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies. Osteoporos Int 2024; 35:679-689. [PMID: 38221591 DOI: 10.1007/s00198-023-06996-0] [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: 05/16/2023] [Accepted: 12/04/2023] [Indexed: 01/16/2024]
Abstract
Previously observational studies did not draw a clear conclusion on the association between fatty liver diseases and bone mineral density (BMD). Our large-scale studies revealed that MAFLD and hepatic steatosis had no causal effect on BMD, while some metabolic factors were correlated with BMD. The findings have important implications for the relationship between fatty liver diseases and BMD, and may help direct the clinical management of MAFLD patients who experience osteoporosis and osteopenia. PURPOSE Liver and bone are active endocrine organs with several metabolic functions. However, the link between metabolic dysfunction-associated fatty liver disease (MAFLD) and bone mineral density (BMD) is contradictory. METHODS Using the UK Biobank and National Health and Nutrition Examination Survey (NHANES) dataset, we investigated the association between MAFLD, steatosis, and BMD in the observational analysis. We performed genome-wide association analysis to identify single-nucleotide polymorphisms associated with MAFLD. Large-scale two-sample Mendelian randomization (TSMR) analyses examined the potential causal relationship between MAFLD, hepatic steatosis, or major comorbid metabolic factors, and BMD. RESULTS After adjusting for demographic factors and body mass index, logistic regression analysis demonstrated a significant association between MAFLD and reduced heel BMD. However, this association disappeared after adjusting for additional metabolic factors. MAFLD was not associated with total body, femur neck, and lumbar BMD in the NHANES dataset. Magnetic resonance imaging-measured steatosis did not show significant associations with reduced total body, femur neck, and lumbar BMD in multivariate analysis. TSMR analyses indicated that MAFLD and hepatic steatosis were not associated with BMD. Among all MAFLD-related comorbid factors, overweight and type 2 diabetes showed a causal relationship with increased BMD, while waist circumference and hyperlipidemia had the opposite effect. CONCLUSION No causal effect of MAFLD and hepatic steatosis on BMD was observed in this study, while some metabolic factors were correlated with BMD. This has important implications for understanding the relationship between fatty liver disease and BMD, which may help direct the clinical management of MAFLD patients with osteoporosis.
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Affiliation(s)
- Lin Zeng
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Yan Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Chang Hong
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Jiaren Wang
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Hongbo Zhu
- Department of Medical Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan Province, China
| | - Qimei Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Hao Cui
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Pengcheng Ma
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Ruining Li
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Jingzhe He
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Hong Zhu
- Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Li Liu
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
- Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Lushan Xiao
- Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
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Lin B, Paterson AD, Sun L. Better together against genetic heterogeneity: A sex-combined joint main and interaction analysis of 290 quantitative traits in the UK Biobank. PLoS Genet 2024; 20:e1011221. [PMID: 38656964 PMCID: PMC11073786 DOI: 10.1371/journal.pgen.1011221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 05/06/2024] [Accepted: 03/11/2024] [Indexed: 04/26/2024] Open
Abstract
Genetic effects can be sex-specific, particularly for traits such as testosterone, a sex hormone. While sex-stratified analysis provides easily interpretable sex-specific effect size estimates, the presence of sex-differences in SNP effect implies a SNP×sex interaction. This suggests the usage of the often overlooked joint test, testing for an SNP's main and SNP×sex interaction effects simultaneously. Notably, even without individual-level data, the joint test statistic can be derived from sex-stratified summary statistics through an omnibus meta-analysis. Utilizing the available sex-stratified summary statistics of the UK Biobank, we performed such omnibus meta-analyses for 290 quantitative traits. Results revealed that this approach is robust to genetic effect heterogeneity and can outperform the traditional sex-stratified or sex-combined main effect-only tests. Therefore, we advocate using the omnibus meta-analysis that captures both the main and interaction effects. Subsequent sex-stratified analysis should be conducted for sex-specific effect size estimation and interpretation.
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Affiliation(s)
- Boxi Lin
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Andrew D. Paterson
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Lei Sun
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada
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Liu Q, Wang L, Liao L, Cong H, Gao Y. Elucidating the causal landscape: Mendelian randomization analysis of lifestyle and physiological factors in stress urinary incontinence. Neurourol Urodyn 2024; 43:951-958. [PMID: 38374762 DOI: 10.1002/nau.25428] [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: 12/21/2023] [Accepted: 02/07/2024] [Indexed: 02/21/2024]
Abstract
PURPOSE To explore the potential causal links between obesity, type 2 diabetes (T2D), and lifestyle choices (such as smoking, alcohol and coffee consumption, and vigorous physical activity) on stress urinary incontinence (SUI), this study employs a Mendelian Randomization approach. This research aims to clarify these associations, which have been suggested but not conclusively established in prior observational studies. METHODS Genetic instruments associated with the exposures at the genome-wide significance (p < 5 × 10-8) were selected from corresponding genome-wide association studies. Summary-level data for SUI, was obtained from the UK Biobank. A two-sample MR analysis was employed to estimate causal effects, utilizing the inverse-variance weighted (IVW) method as the primary analytical approach. Complementary sensitivity analyses including MR-PRESSO, MR-Egger, and weighted median methods were performed. The horizontal pleiotropy was detected by using MR-Egger intercept and MR-PRESSO methods, and the heterogeneity was assessed using Cochran's Q statistics. RESULTS Our findings demonstrate a significant causal relationship between higher body mass index (BMI) and the risk of SUI, with increased abdominal adiposity (WHRadjBMI) similarly linked to SUI. Smoking initiation is also causally associated with an elevated risk. However, our analysis did not find definitive causal connections for other factors, including T2D, alcohol consumption, coffee intake, and vigorous physical activity. CONCLUSIONS These findings provide valuable insights for clinical strategies targeting SUI, suggesting a need for heightened awareness and potential intervention in individuals with higher BMI, WHR, and smoking habits. Further research is warranted to explore the complex interplay between genetic predisposition and lifestyle choices in the pathogenesis of SUI.
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Affiliation(s)
- Qinggang Liu
- Qilu Hospital of Shandong University, Jinan, Shandong, China
- Department of Urology, China Rehabilitation Research Center, Beijing, China
- University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
- China Rehabilitation Science Institute, Beijing, China
| | - Linna Wang
- Lanzhou Biotechnique Development Co., LTD, Lanzhou, Gansu, China
| | - Limin Liao
- Qilu Hospital of Shandong University, Jinan, Shandong, China
- Department of Urology, China Rehabilitation Research Center, Beijing, China
- University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
- Lanzhou Biotechnique Development Co., LTD, Lanzhou, Gansu, China
- School of Rehabilitation, Capital Medical University, Beijing, China
| | - Huiling Cong
- Department of Urology, China Rehabilitation Research Center, Beijing, China
- School of Rehabilitation, Capital Medical University, Beijing, China
| | - Yi Gao
- Department of Urology, China Rehabilitation Research Center, Beijing, China
- School of Rehabilitation, Capital Medical University, Beijing, China
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Hagberg CE, Spalding KL. White adipocyte dysfunction and obesity-associated pathologies in humans. Nat Rev Mol Cell Biol 2024; 25:270-289. [PMID: 38086922 DOI: 10.1038/s41580-023-00680-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/13/2023] [Indexed: 02/10/2024]
Abstract
The prevalence of obesity and associated chronic diseases continues to increase worldwide, negatively impacting on societies and economies. Whereas the association between excess body weight and increased risk for developing a multitude of diseases is well established, the initiating mechanisms by which weight gain impairs our metabolic health remain surprisingly contested. In order to better address the myriad of disease states associated with obesity, it is essential to understand adipose tissue dysfunction and develop strategies for reinforcing adipocyte health. In this Review we outline the diverse physiological functions and pathological roles of human white adipocytes, examining our current knowledge of why white adipocytes are vital for systemic metabolic control, yet poorly adapted to our current obesogenic environment.
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Affiliation(s)
- Carolina E Hagberg
- Division of Cardiovascular Medicine, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Kirsty L Spalding
- Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden.
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45
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Cai N, Luo W, Ding L, Chen L, Huang Y. Obesity-related indicators and tuberculosis: A Mendelian randomization study. PLoS One 2024; 19:e0297905. [PMID: 38557966 PMCID: PMC10984409 DOI: 10.1371/journal.pone.0297905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 01/15/2024] [Indexed: 04/04/2024] Open
Abstract
PURPOSE Obesity is a strong risk factor for many diseases, with controversy regarding the cause(s) of tuberculosis (TB) reflected by contradictory findings. Therefore, a larger sample population is required to determine the relationship between obesity and TB, which may further inform treatment. METHODS Obesity-related indicators and TB mutation data were obtained from a genome-wide association study database, while representative instrumental variables (IVs) were obtained by screening and merging. Causal relationships between exposure factors and outcomes were determined using two-sample Mendelian randomization (MR) analysis. Three tests were used to determine the representativeness and stability of the IVs, supported by sensitivity analysis. RESULTS Initially, 191 single nucleotide polymorphisms were designated as IVs by screening, followed by two-sample MR analysis, which revealed the causal relationship between waist circumference [odds ratio (OR): 2.13 (95% confidence interval (CI): 1.19-3.80); p = 0.011] and TB. Sensitivity analysis verified the credibility of the IVs, none of which were heterogeneous or horizontally pleiotropic. CONCLUSION The present study determined the causal effect between waist circumference and TB by two-sample MR analysis and found both to be likely to be potential risk factors.
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Affiliation(s)
- Nuannuan Cai
- Pulmonary and Critical Care Medicine, Hainan Provincial People’s Hospital, Haikou, Hainan, China
| | - Weiyan Luo
- Pulmonary and Critical Care Medicine, Hainan Provincial People’s Hospital, Haikou, Hainan, China
| | - Lili Ding
- Pulmonary and Critical Care Medicine, Hainan Provincial People’s Hospital, Haikou, Hainan, China
| | - Lijin Chen
- Pulmonary and Critical Care Medicine, Hainan Provincial People’s Hospital, Haikou, Hainan, China
| | - Yuanjiang Huang
- Infectious and Tropical Disease Dept (Tuberculosis), The Second Affiliated Hospital of Hainan Medical College, Haikou, Hainan, China
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Alser M, Naja K, Elrayess MA. Mechanisms of body fat distribution and gluteal-femoral fat protection against metabolic disorders. Front Nutr 2024; 11:1368966. [PMID: 38590830 PMCID: PMC10999599 DOI: 10.3389/fnut.2024.1368966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 03/07/2024] [Indexed: 04/10/2024] Open
Abstract
Obesity is a major health problem that affects millions of individuals, and it is associated with metabolic diseases including insulin resistance (IR), type 2 diabetes (T2D), and cardiovascular diseases (CVDs). However, Body fat distribution (BFD) rather than crude obesity is now considered as a more accurate factor associated with these diseases. The factors affecting BFD vary, from genetic background, epigenetic factors, ethnicity, aging, hormonal changes, to lifestyle and medication consumptions. The main goal of controlling BFD comes from the fact that fat accumulation in different depots has a different effect on the overall health and metabolic health of individuals. It is well established that fat storage in the abdominal visceral depot is associated with metabolic disorder occurrence, while gluteal-femoral subcutaneous fat depot seems to be protective against these diseases. In this paper, we will summarize the factors affecting fat distribution. Then, we will present evidence connecting gluteal-femoral fat depot with protection against metabolic disorders including IR, T2D, and CVDs. Finally, we will list the suggested mechanisms that lead to this protective effect. The abstract is visualized in Graphical Abstract.
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Affiliation(s)
- Maha Alser
- Biomedical Research Center, Qatar University, Doha, Qatar
| | - Khaled Naja
- Biomedical Research Center, Qatar University, Doha, Qatar
| | - Mohamed A. Elrayess
- Biomedical Research Center, Qatar University, Doha, Qatar
- QU Health, Qatar University, Doha, Qatar
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Zhang F, Yu Z. Mendelian randomization study on insulin resistance and risk of hypertension and cardiovascular disease. Sci Rep 2024; 14:6191. [PMID: 38485964 PMCID: PMC10940700 DOI: 10.1038/s41598-023-46983-3] [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] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 01/07/2022] [Indexed: 03/18/2024] Open
Abstract
Observational studies have suggested that insulin resistance (IR) is associated with hypertension and various cardiovascular diseases. However, the presence of a causal relationship between IR and cardiovascular disease remains unclear. Here, we applied Mendelian randomization (MR) approaches to address the causal association between genetically determined IR and the risk of cardiovascular diseases. Our primary genetic instruments comprised 53 SNPs associated with IR phenotype from a GWAS of up to 188,577 participants. Genetic association estimates for hypertension and venous thromboembolism (VTE) were extracted from UK Biobank, estimates for atrial fibrillation (AF) were extracted from the hitherto largest GWAS meta-analysis on AF, estimates for heart failure were extracted from HERMES Consortium, estimates for peripheral artery disease (PAD) and aortic aneurysm were extracted from the FinnGen Study. The main analyses were performed using the random-effects inverse-variance weighted approach, and complemented by sensitivity analyses and multivariable MR analyses. Corresponding to 55% higher fasting insulin adjusted for body mass index, 0.46 mmol/L lower high-density lipoprotein cholesterol and 0.89 mmol/L higher triglyceride, one standard deviation change in genetically predicted IR was associated with increased risk of hypertension (odds ratio (OR) 1.06, 95% CI 1.04-1.08; P = 1.91 × 10-11) and PAD (OR 1.90, 95% CI 1.43-2.54; P = 1.19 × 10-5). Suggestive evidence was obtained for an association between IR and heart failure (OR per SD change in IR: 1.19, 95% CI 1.01-1.41, P = 0.041). There was no MR evidence for an association between genetically predicted IR and atrial fibrillation, VTE, and aortic aneurysm. Results were widely consistent across all sensitivity analyses. In multivariable MR, the association between IR and PAD was attenuated after adjustment for lipids (P = 0.347) or BMI (P = 0.163). Our findings support that genetically determined IR increases the risk of hypertension and PAD.
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Affiliation(s)
- Fangfang Zhang
- Department of Outpatient, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, China
| | - Zhimin Yu
- Department of Geriatrics, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, China.
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Zhang M, Bai Y, Wang Y, Cui H, Zhang W, Zhang L, Yan P, Tang M, Liu Y, Jiang X, Zhang B. Independent association of general and central adiposity with risk of gallstone disease: observational and genetic analyses. Front Endocrinol (Lausanne) 2024; 15:1367229. [PMID: 38529389 PMCID: PMC10961427 DOI: 10.3389/fendo.2024.1367229] [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: 01/08/2024] [Accepted: 02/26/2024] [Indexed: 03/27/2024] Open
Abstract
Background General obesity is a well-established risk factor for gallstone disease (GSD), but whether central obesity contributes additional independent risk remains controversial. We aimed to comprehensively clarify the effect of body fat distribution on GSD. Methods We first investigated the observational association of central adiposity, characterized by waist-to-hip ratio (WHR), with GSD risk using data from UK Biobank (N=472,050). We then explored the genetic relationship using summary statistics from the largest genome-wide association study of GSD (ncase=43,639, ncontrol=506,798) as well as WHR, with and without adjusting for body mass index (BMI) (WHR: n=697,734; WHRadjBMI: n=694,649). Results Observational analysis demonstrated an increased risk of GSD with one unit increase in WHR (HR=1.18, 95%CI=1.14-1.21). A positive WHR-GSD genetic correlation (r g =0.41, P=1.42×10-52) was observed, driven by yet independent of BMI (WHRadjBMI: r g =0.19, P=6.89×10-16). Cross-trait meta-analysis identified four novel pleiotropic loci underlying WHR and GSD with biological mechanisms outside of BMI. Mendelian randomization confirmed a robust WHR-GSD causal relationship (OR=1.50, 95%CI=1.35-1.65) which attenuated yet remained significant after adjusting for BMI (OR=1.17, 95%CI=1.09-1.26). Furthermore, observational analysis confirmed a positive association between general obesity and GSD, corroborated by a shared genetic basis (r g =0.40, P=2.16×10-43), multiple novel pleiotropic loci (N=11) and a causal relationship (OR=1.67, 95%CI=1.56-1.78). Conclusion Both observational and genetic analyses consistently provide evidence on an association of central obesity with an increased risk of GSD, independent of general obesity. Our work highlights the need of considering both general and central obesity in the clinical management of GSD.
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Affiliation(s)
- Min Zhang
- Clinical and Public Health Research Center, Chongqing Research Center for Prevention & Control of Maternal and Child Diseases and Public Health, Chongqing Health Center for Women and Children, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Ye Bai
- Gene Diagnosis Center, the First Affiliated Hospital of Jilin University, Jilin, China
| | - Yutong Wang
- Department of Epidemiology and Health Statistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Huijie Cui
- Department of Epidemiology and Health Statistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Health Statistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Health Statistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Peijing Yan
- Department of Epidemiology and Health Statistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Mingshuang Tang
- Department of Epidemiology and Health Statistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Health Statistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xia Jiang
- Department of Epidemiology and Health Statistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ben Zhang
- Department of Epidemiology and Health Statistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
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Xiao XP, Dai YJ, Zhang Y, Yang M, Xie J, Chen G, Yang ZJ. Investigating the causal associations between five anthropometric indicators and nonalcoholic fatty liver disease: Mendelian randomization study. World J Clin Cases 2024; 12:1215-1226. [PMID: 38524522 PMCID: PMC10955530 DOI: 10.12998/wjcc.v12.i7.1215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 01/14/2024] [Accepted: 02/06/2024] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND Although the etiology of nonalcoholic fatty liver disease (NAFLD) has not been thoroughly understood, the emerging roles of anthropometric indicators in assessing and predicting the risk of NAFLD have been highlighted by accumulating evidence. AIM To evaluate the causal relationships between five anthropometric indicators and NAFLD employing Mendelian randomization (MR) design. METHODS The Anthropometric Consortium provided genetic exposure data for five anthropometric indicators, including hip circumference (HC), waist circumference (WC), waist-to-hip ratio (WHR), body mass index (BMI), and body fat percentage (BF). Genetic outcome data for NAFLD were obtained from the United Kingdom Biobank and FinnGen Consortium. Genome-wide significant single nucleotide polymorphisms were chosen as instrumental variables. Univariable MR (UVMR) and multivariable MR (MVMR) designs with analytical approaches, including inverse variance weighted (IVW), MR-Egger, weighted median (WM), and weighted mode methods, were used to assess the causal relationships between anthropometric indicators and NAFLD. RESULTS Causal relationships were revealed by UVMR, indicating that a higher risk of NAFLD was associated with a per-unit increase in WC [IVW: odds ratio (OR) = 2.67, 95%CI: 1.42-5.02, P = 2.25 × 10-3], and BF was causally associated with an increased risk of NAFLD (WM: OR = 2.23, 95%CI: 1.07-4.66, P = 0.033). The presence of causal effects of WC on the decreased risk of NAFLD was supported by MVMR after adjusting for BMI and smoking. However, no causal association between BF and NAFLD was observed. In addition, other causal relationships of HC, WHR (BMI adjusted), and BMI with the risk of NAFLD were not retained after FDR correction. CONCLUSION This study establishes a causal relationship, indicating that an increase in WC is associated with a higher risk of NAFLD. This demonstrates that a suitable decrease in WC is advantageous for preventing NAFLD.
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Affiliation(s)
- Xian-Pei Xiao
- Department of Oncology, Luojiang District People's Hospital of Deyang City, Deyang 618000, Sichuan Province, China
| | - Yong-Jun Dai
- Department of Orthopaedics, Luojiang District People's Hospital of Deyang City, Deyang 618000, Sichuan Province, China
| | - Yu Zhang
- Department of Oncology, Luojiang District People's Hospital of Deyang City, Deyang 618000, Sichuan Province, China
| | - Meng Yang
- Department of Oncology, Luojiang District People's Hospital of Deyang City, Deyang 618000, Sichuan Province, China
| | - Jian Xie
- Department of Oncology, Luojiang District People's Hospital of Deyang City, Deyang 618000, Sichuan Province, China
| | - Guo Chen
- Department of Infectious Diseases, Hospital of Chengdu University of Traditional Chinese Medical, Chengdu 610500, Sichuan Province, China
| | - Zheng-Jun Yang
- Department of Oncology, Luojiang District People's Hospital of Deyang City, Deyang 618000, Sichuan Province, China
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50
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Jiang Y, Zhang W, Wei M, Yin D, Tang Y, Jia W, Wang C, Guo J, Li A, Gong Y. Associations between type 1 diabetes and pulmonary tuberculosis: a bidirectional mendelian randomization study. Diabetol Metab Syndr 2024; 16:60. [PMID: 38443967 PMCID: PMC10913601 DOI: 10.1186/s13098-024-01296-x] [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: 11/23/2023] [Accepted: 02/20/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND Type 1 diabetes mellitus (T1DM) has been associated with higher pulmonary tuberculosis (PTB) risk in observational studies. However, the causal relationship between them remains unclear. This study aimed to assess the causal effect between T1DM and PTB using bidirectional Mendelian randomization (MR) analysis. METHODS Single nucleotide polymorphisms (SNPs) of T1DM and PTB were extracted from the public genetic variation summary database. In addition, GWAS data were collected to explore the causal relationship between PTB and relevant clinical traits of T1DM, including glycemic traits, lipids, and obesity. The inverse variance weighting method (IVW), weighted median method, and MR‒Egger regression were used to evaluate the causal relationship. To ensure the stability of the results, sensitivity analyses assess the robustness of the results by estimating heterogeneity and pleiotropy. RESULTS IVW showed that T1DM increased the risk of PTB (OR = 1.07, 95% CI: 1.03-1.12, P < 0.001), which was similar to the results of MR‒Egger and weighted median analyses. Moreover, we found that high-density lipoprotein cholesterol (HDL-C; OR = 1.28, 95% CI: 1.03-1.59, P = 0.026) was associated with PTB. There was no evidence of an effect of glycemic traits, remaining lipid markers, or obesity on the risk of PTB. In the reverse MR analysis, no causal relationships were detected for PTB on T1DM and its relevant clinical traits. CONCLUSION This study supported that T1DM and HDL-C were risk factors for PTB. This implies the effective role of treating T1DM and managing HDL-C in reducing the risk of PTB, which provides an essential basis for the prevention and comanagement of concurrent T1DM and PTB in clinical practice.
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Affiliation(s)
- Yijia Jiang
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China
| | - Wenhua Zhang
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China
| | - Maoying Wei
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China
| | - Dan Yin
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China
| | - Yiting Tang
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China
| | - Weiyu Jia
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China
| | - Churan Wang
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China
| | - Jingyi Guo
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China
| | - Aijing Li
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China
| | - Yanbing Gong
- Dongzhimen Hospital, Beijing University of Chinese Medicine, 100700, Beijing, China.
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