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Zhang H, Liu J. Lifestyle factors, glycemic traits, and lipoprotein traits and risk of liver cancer: a Mendelian randomization analysis. Sci Rep 2024; 14:8502. [PMID: 38605235 PMCID: PMC11009263 DOI: 10.1038/s41598-024-59211-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 04/08/2024] [Indexed: 04/13/2024] Open
Abstract
The current state of knowledge on the relationship between lifestyle factors, glycemic traits, lipoprotein traits with liver cancer risk is still uncertain despite some attempts made by observational studies. This study aims to investigate the causal genetic relationship between factors highly associated with liver cancer incidence by using Mendelian randomization (MR) analysis. Employing MR analysis, this study utilized previously published GWAS datasets to investigate whether lifestyle factors, glycemic traits, and lipoprotein traits would affect the risk of liver cancer. The study utilized three MR methods, including inverse variance-weighted model (IVW), MR Egger, and weighted median. Furthermore, MR-Egger analyses were performed to detect heterogeneity in the MR results. The study also conducted a leave-one-out analysis to assess the potential influence of individual SNPs on the MR analysis results. MR-PRESSO was used to identify and remove SNP outliers associated with liver cancer. MR analyses revealed that 2-h glucose (odds ratio, OR 2.33, 95% confidence interval, CI 1.28-4.21), type 2 diabetes mellitus (T2DM, OR 1.67, 95% CI 1.18-2.37), body mass index (BMI, OR 1.67, 95% CI 1.18-2.37), waist circumference (OR 1.78, 95% CI 1.18-2.37) were associated with increased risk of liver cancer. On the contrary, apolipoproteins B (APOB, OR 0.67, 95% CI 0.47-0.97), and low-density lipoprotein (LDL, OR 0.62, 95% CI 0.42-0.92) were negatively related to liver cancer risk. Additionally, after adjusting for BMI, apolipoproteins A-I (APOA-I, OR 0.56, 95% CI, 0.38-0.81), total cholesterol (TC, OR 0.72, 95% CI, 0.54-0.94), and total triglycerides (TG, OR 0.57, 95% CI, 0.40-0.78) exhibited a significant inverse correlation with the risk of liver cancer. This study supports a causal relationship between 2-h glucose, T2DM, BMI, and waist circumference with the increased risk of liver cancer. Conversely, the study reveals a cause-effect relationship between TC, TG, LDL, APOA-I, and APOB with a decreased risk of liver cancer.
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Affiliation(s)
- Honglu Zhang
- Department of Pharmacy, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Jiyong Liu
- Department of Pharmacy, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China.
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Yang M, Wan X, Su Y, Xu K, Wen P, Zhang B, Liu L, Yang Z, Xu P. The genetic causal relationship between type 2 diabetes, glycemic traits and venous thromboembolism, deep vein thrombosis, pulmonary embolism: a two-sample Mendelian randomization study. Thromb J 2024; 22:33. [PMID: 38553747 PMCID: PMC10979561 DOI: 10.1186/s12959-024-00600-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/20/2024] [Indexed: 04/02/2024] Open
Abstract
OBJECTIVE To investigate the genetic underpinnings of the association between type 2 diabetes (T2D), glycemic indicators such as fasting glucose (FG), fasting insulin (FI), and glycated hemoglobin (GH), and venous thromboembolism (VTE), encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), thereby contributing novel insights to the scholarly discourse within this domain. METHODS Genome-wide association study (GWAS) summary data pertaining to exposures (T2D, FG, FI, GH) and outcomes (VTE, DVT, PE) were acquired from the IEU Open GWAS database, encompassing participants of European descent, including both male and female individuals. Two-sample Mendelian randomization (MR) analyses were conducted utilizing the TwoSampleMR and MRPRESSO packages within the R programming environment. The primary analytical approach employed was the random-effects inverse variance weighted (IVW) method. Heterogeneity was assessed via Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger. Horizontal pleiotropy was evaluated using the intercept test of MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, with the latter also employed for outlier detection. Additionally, a "Leave one out" analysis was conducted to ascertain the influence of individual single nucleotide polymorphisms (SNPs) on MR results. RESULTS The random-effects IVW analysis revealed a negative genetic causal association between T2D) and VTE (P = 0.008, Odds Ratio [OR] 95% confidence interval [CI] = 0.896 [0.827-0.972]), as well as between FG and VTE (P = 0.002, OR 95% CI = 0.655 [0.503-0.853]), GH and VTE (P = 0.010, OR 95% CI = 0.604 [0.412-0.884]), and GH and DVT (P = 0.002, OR 95% CI = 0.413 [0.235-0.725]). Conversely, the random-effects IVW analysis did not detect a genetic causal relationship between FI and VTE (P > 0.05), nor between T2D, FG, or FI and DVT (P > 0.05), or between T2D, FG, FI, or GH and PE (P > 0.05). Both the Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger indicated no significant heterogeneity (P > 0.05). Moreover, the intercept tests of MR Egger and MR-PRESSO suggested the absence of horizontal pleiotropy (P > 0.05). MR-PRESSO analysis identified no outliers, while the "Leave one out" analysis underscored that the MR analysis was not influenced by any single SNP. CONCLUSION Our investigation revealed that T2D, FG, and GH exhibit negative genetic causal relationships with VTE at the genetic level, while GH demonstrates a negative genetic causal relationship with DVT at the genetic level. These findings furnish genetic-level evidence warranting further examination of VTE, DVT, and PE, thereby making a contribution to the advancement of related research domains.
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Affiliation(s)
- Mingyi Yang
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Xianjie Wan
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Yani Su
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Ke Xu
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Pengfei Wen
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Binfei Zhang
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Lin Liu
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Zhi Yang
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China
| | - Peng Xu
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China.
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Liu XJ, Sultan MT, Li GS. Obesity, Glycemic Traits, Lifestyle Factors, and Risk of Facial Aging: A Mendelian Randomization Study in 423,999 Participants. Aesthetic Plast Surg 2024; 48:1005-1015. [PMID: 37605021 DOI: 10.1007/s00266-023-03551-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Accepted: 07/23/2023] [Indexed: 08/23/2023]
Abstract
BACKGROUND Several recent observational studies have associated obesity, lifestyle factors (smoking, sleep duration, and alcohol drinking), and glycemic traits with facial aging. However, whether this relationship is causal due to confounding and reverse causation is yet to be substantiated. AIMS We aimed to assess these relationships using Mendelian randomization (MR). METHODS For the instrumental variables, this paper selected independent single nucleotide polymorphisms (SNPs) linked to the exposures at a genome-wide state (P < 5 × 10-8) in equivalent genome-wide association studies (GWAS). Using the UK Biobank, we obtained summary-level data for facial aging on 423,999 individuals. The primary assessments were performed through the combination of complementing techniques (simple method approaches, weighted model, MR-Egger, and weighted median) and the inverse-variance-weighted method. Along with that, we examined the heterogeneity and horizontal pleiotropy through different types of sensitivity analyses. RESULTS The correlations were (a) facial aging for body mass index (BMI, OR = 1.054, 95% CI 1.044-1.64), (b) waist/hip ratio (OR = 1.056, 95% CI 1.023-1.091), and (c) smoking (OR = 1.023, 95% CI 1.007-1.039). Equally important, the correlations for waist/hip ratio remained robust after adjusting for the genetically predicted BMI (OR = 1.028, 95% CI 1.003-1.054). However, no causal effects of alcoholic drinking, glycemic traits, and sleep duration on facial aging were observed. CONCLUSIONS The outcomes shed light on the potential correlation of obesity and cigarette smoking with facial aging while putting forward a more comprehensive and credible foundation for the optimization of facial aging strategies. NO LEVEL ASSIGNED This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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Affiliation(s)
- Xuan-Jun Liu
- Department of Plastic and Reconstructive Surgery, the First Affiliated Hospital of Zhengzhou University, #1 Jianshe East Road, Zhengzhou, 450052, China
| | - Muhammad Tipu Sultan
- Department of Plastic and Reconstructive Surgery, the First Affiliated Hospital of Zhengzhou University, #1 Jianshe East Road, Zhengzhou, 450052, China
| | - Guang-Shuai Li
- Department of Plastic and Reconstructive Surgery, the First Affiliated Hospital of Zhengzhou University, #1 Jianshe East Road, Zhengzhou, 450052, China.
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Xu Z, Shi Y, Wei C, Li T, Wen J, Du W, Yu Y, Zhu T. Causal relationship between glycemic traits and bone mineral density in different age groups and skeletal sites: a Mendelian randomization analysis. J Bone Miner Metab 2024; 42:90-98. [PMID: 38157037 DOI: 10.1007/s00774-023-01480-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/25/2023] [Indexed: 01/03/2024]
Abstract
INTRODUCTION Previous research has confirmed that patients with type 2 diabetes mellitus tend to have higher bone mineral density (BMD), but it is unknown whether this pattern holds true for individuals without diabetes. This Mendelian randomization (MR) study aims to investigate the potential causal relationship between various glycemic trait (including fasting glucose, fasting insulin, 2-h postprandial glucose, and glycated hemoglobin) and BMD in non-diabetic individuals. The investigation focuses on different age groups (15-30, 30-45, 45-60, and 60 + years) and various skeletal sites (forearm, lumbar spine, and hip). MATERIALS AND METHODS We utilized genome-wide association study data from large population-based cohorts to identify robust instrumental variables for each glycemic traits parameter. Our primary analysis employed the inverse-variance weighted method, with sensitivity analyses conducted using MR-Egger, weighted median, MR-PRESSO, and multivariable MR methods to assess the robustness and potential horizontal pleiotropy of the study results. RESULTS Fasting insulin showed a negative modulating relationship on both lumbar spine and forearm. However, these associations were only nominally significant. No significant causal association was observed between blood glucose traits and BMD across the different age groups. The direction of fasting insulin's causal effects on BMD showed inconsistency between genders, with potentially decreased BMD in women with high fasting insulin levels and an increasing trend in BMD in men. CONCLUSIONS In the non-diabetic population, currently available evidence does not support a causal relationship between glycemic traits and BMD. However, further investigation is warranted considering the observed gender differences.
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Affiliation(s)
- Zhangmeng Xu
- Department of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, No. 37 Shi-er-qiao Road, Chengdu, Sichuan, China
- Department-2 of Neck Shoulder Back and Leg Pain, Department of Preventive Treatment, Sichuan Province Orthopaedic Hospital, Chengdu, Sichuan, China
| | - Yushan Shi
- Department of Medical Laboratory, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Changhong Wei
- Department of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, No. 37 Shi-er-qiao Road, Chengdu, Sichuan, China
| | - Tao Li
- Department-2 of Neck Shoulder Back and Leg Pain, Department of Preventive Treatment, Sichuan Province Orthopaedic Hospital, Chengdu, Sichuan, China
| | - Jiang Wen
- Department-2 of Neck Shoulder Back and Leg Pain, Department of Preventive Treatment, Sichuan Province Orthopaedic Hospital, Chengdu, Sichuan, China
| | - Wanli Du
- Department-2 of Neck Shoulder Back and Leg Pain, Department of Preventive Treatment, Sichuan Province Orthopaedic Hospital, Chengdu, Sichuan, China
| | - Yaming Yu
- Department-2 of Neck Shoulder Back and Leg Pain, Department of Preventive Treatment, Sichuan Province Orthopaedic Hospital, Chengdu, Sichuan, China.
- Department of preventive treatment, Sichuan Province Orthopaedic Hospital, No. 132 West 1st Section, 1st Ring Road in Chengdu, Chengdu, Sichuan, China.
| | - Tianmin Zhu
- Department of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, No. 37 Shi-er-qiao Road, Chengdu, Sichuan, China.
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Li Z, Xiong J, Guo Y, Tang H, Guo B, Wang B, Gao D, Dong Z, Tu Y. Effects of diabetes mellitus and glycemic traits on cardiovascular morpho-functional phenotypes. Cardiovasc Diabetol 2023; 22:336. [PMID: 38066511 PMCID: PMC10709859 DOI: 10.1186/s12933-023-02079-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND The effects of diabetes on the cardiac and aortic structure and function remain unclear. Detecting and intervening these variations early is crucial for the prevention and management of complications. Cardiovascular magnetic resonance imaging-derived traits are established endophenotypes and serve as precise, early-detection, noninvasive clinical risk biomarkers. We conducted a Mendelian randomization (MR) study to examine the association between two types of diabetes, four glycemic traits, and preclinical endophenotypes of cardiac and aortic structure and function. METHODS Independent genetic variants significantly associated with type 1 diabetes, type 2 diabetes, fasting insulin (FIns), fasting glucose (FGlu), 2 h-glucose post-challenge (2hGlu), and glycated hemoglobin (HbA1c) were selected as instrumental variables. The 96 cardiovascular magnetic resonance imaging traits came from six independent genome-wide association studies. These traits serve as preclinical endophenotypes and offer an early indication of the structure and function of the four cardiac chambers and two aortic sections. The primary analysis was performed using MR with the inverse-variance weighted method. Confirmation was achieved through Steiger filtering and testing to determine the causal direction. Sensitivity analyses were conducted using the weighted median, MR-Egger, and MR-PRESSO methods. Additionally, multivariable MR was used to adjust for potential effects associated with body mass index. RESULTS Genetic susceptibility to type 1 diabetes was associated with increased ascending aortic distensibility. Conversely, type 2 diabetes showed a correlation with a reduced diameter and areas of the ascending aorta, as well as decreased distensibility of the descending aorta. Genetically predicted higher levels of FGlu and HbA1c were correlated with a decrease in diameter and areas of the ascending aorta. Furthermore, higher 2hGlu levels predominantly showed association with a reduced diameter of both the ascending and descending aorta. Higher FIns levels corresponded to increased regional myocardial-wall thicknesses at end-diastole, global myocardial-wall thickness at end-diastole, and regional peak circumferential strain of the left ventricle. CONCLUSIONS This study provides evidence that diabetes and glycemic traits have a causal relationship with cardiac and aortic structural and functional remodeling, highlighting the importance of intensive glucose-lowering for primary prevention of cardiovascular diseases.
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Affiliation(s)
- Zhaoyue Li
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Jie Xiong
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Yutong Guo
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Hao Tang
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Bingchen Guo
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Bo Wang
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Dianyu Gao
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Zengxiang Dong
- Harbin Medical University, Harbin, China.
- The Key Laboratory of Cardiovascular Disease Acousto-Optic Electromagnetic Diagnosis and Treatment in Heilongjiang Province, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
- NHC Key Laboratory of Cell Transplantation, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Yingfeng Tu
- Harbin Medical University, Harbin, China.
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China.
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Ai S, Wang X, Wang S, Zhao Y, Guo S, Li G, Chen Z, Lin F, Guo S, Li Y, Zhang J, Zhao G. Effects of glycemic traits on left ventricular structure and function: a mendelian randomization study. Cardiovasc Diabetol 2022; 21:109. [PMID: 35715813 PMCID: PMC9206364 DOI: 10.1186/s12933-022-01540-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 06/01/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Adverse ventricular structure and function is a key pathogenic mechanism of heart failure. Observational studies have shown that both insulin resistance (IR) and glycemic level are associated with adverse ventricular structure and function. However, whether IR and glycemic level are causally associated with cardiac structure and function remains unclear. METHODS Genetic variants for IR, fasting insulin, HbA1c, and fasting glucose were selected based on published genome-wide association studies, which included 188,577, 108,557, 123,665, and 133,010 individuals of European ancestry, respectively. Outcome datasets for left ventricular (LV) parameters were obtained from UK Biobank Cardiovascular Magnetic Resonance sub-study (n = 16,923). Mendelian randomization (MR) analyses with the inverse-variance weighted (IVW) method were used for the primary analyses, while weighted median, MR-Egger, and MR-PRESSO were used for sensitivity analyses. Multivariable MR analyses were also conducted to examine the independent effects of glycemic traits on LV parameters. RESULTS In the primary IVW MR analyses, per 1-standard deviation (SD) higher IR was significantly associated with lower LV end-diastolic volume (β = - 0.31 ml, 95% confidence interval [CI] - 0.48 to - 0.14 ml; P = 4.20 × 10-4), lower LV end-systolic volume (β = - 0.34 ml, 95% CI - 0.51 to - 0.16 ml; P = 1.43 × 10-4), and higher LV mass to end-diastolic volume ratio (β = 0.50 g/ml, 95% CI 0.32 to 0.67 g/ml; P = 6.24 × 10-8) after Bonferroni adjustment. However, no associations of HbA1c and fasting glucose were observed with any LV parameters. Results from sensitivity analyses were consistent with the main findings, but with a slightly attenuated estimate. Multivariable MR analyses provided further evidence for an independent effect of IR on the adverse changes in LV parameters after controlling for HbA1c. CONCLUSIONS Our study suggests that genetic liability to IR rather than those of glycemic levels are associated with adverse changes in LV structure and function, which may strengthen our understanding of IR as a risk factor for heart failure by providing evidence of direct impact on cardiac morphology.
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Affiliation(s)
- Sizhi Ai
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Xiaoyu Wang
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Shanshan Wang
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Yilin Zhao
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Shuxun Guo
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Guohua Li
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Zhigang Chen
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Fei Lin
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Sheng Guo
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Yan Li
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Jihui Zhang
- Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China. .,Guangdong Mental Health Center, Guangdong Provincial People's Hospital Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China. .,Li Chiu Kong Family Sleep assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
| | - Guoan Zhao
- Department of Cardiology, Life Science Research Center, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China.
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Jia X, Xuan L, Dai H, Zhu W, Deng C, Wang T, Li M, Zhao Z, Xu Y, Lu J, Bi Y, Wang W, Chen Y, Xu M, Ning G. Fruit intake, genetic risk and type 2 diabetes: a population-based gene-diet interaction analysis. Eur J Nutr 2021; 60:2769-2779. [PMID: 33399975 PMCID: PMC8275558 DOI: 10.1007/s00394-020-02449-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 11/24/2020] [Indexed: 12/11/2022]
Abstract
PURPOSE Whether the association between fruit and type 2 diabetes (T2D) is modified by the genetic predisposition of T2D was yet elucidated. The current study is meant to examine the gene-dietary fruit intake interactions in the risk of T2D and related glycemic traits. METHODS We performed a cross-sectional study in 11,657 participants aged ≥ 40 years from a community-based population in Shanghai, China. Fruit intake information was collected by a validated food frequency questionnaire by asking the frequency of consumption of typical food items over the previous 12 months. T2D-genetic risk score (GRS) was constructed by 34 well established T2D common variants in East Asians. The risk of T2D, fasting, 2 h-postprandial plasma glucose, and glycated hemoglobin A1c associated with T2D-GRS and each individual single nucleotide polymorphisms (SNPs) were tested. RESULTS The risk of T2D associated with each 1-point of T2D-GRS was gradually decreased from the lower fruit intake level (< 1 times/week) [the odds ratio (OR) and 95% confidence interval (CI) was 1.10 (1.07-1.13)], to higher levels (1-3 and > 3 times/week) [the corresponding ORs and 95% CIs were 1.08 (1.05-1.10) and 1.07 (1.05-1.08); P for interaction = 0.04]. Analyses for associations with fasting, 2 h-postprandial plasma glucose and glycated hemoglobin A1c demonstrated consistent tendencies (all P for interaction ≤ 0.03). The inverse associations of fruit intake with risk of T2D and glucose traits were more prominent in the higher T2D-GRS tertile. CONCLUSIONS Fruit intakes interact with the genetic predisposition of T2D on the risk of diabetes and related glucose metabolic traits. Fruit intake alleviates the association between genetic predisposition of T2D and the risk of diabetes; the association of fruit intake with a lower risk of diabetes was more prominent in population with a stronger genetic predisposition of T2D.
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Affiliation(s)
- Xu Jia
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Liping Xuan
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huajie Dai
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wen Zhu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chanjuan Deng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Chen Y, Zhou T, Sun D, Li X, Ma H, Liang Z, Heianza Y, Pei X, Bray GA, Sacks FM, Qi L. Distinct genetic subtypes of adiposity and glycemic changes in response to weight-loss diet intervention: the POUNDS Lost trial. Eur J Nutr 2021; 60:249-58. [PMID: 32274554 DOI: 10.1007/s00394-020-02244-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 04/01/2020] [Indexed: 01/09/2023]
Abstract
PURPOSE Obesity is a heterogeneous condition and distinct adiposity subtypes may differentially affect type 2 diabetes risk. We assessed relations between genetically determined subtypes of adiposity and changes in glycemic traits in a dietary intervention trial. METHODS The four genetic subtypes of adiposity including waist-hip ratio-increase only (WHRonly+), body mass index-increase only (BMIonly+), WHR-increase and BMI-increase (BMI+WHR+), and WHR-decrease and BMI-increase (BMI+WHR-) were assessed by polygenetic scores (PGSs), calculated based on 159 single nucleotide polymorphisms related to BMI and/or WHR. We examined the associations between the four PGSs and changes in fasting glucose, insulin, β-cell function (HOMA-B) and insulin resistance (HOMA-IR) in 692 overweight participants (84% white Americans) who were randomly assigned to one of four weight-loss diets in a 2-year intervention trial. RESULTS Higher BMI+WHR-PGS was associated with a greater decrease in 2-year changes in waist circumference in white participants (P = 0.002). We also found significant interactions between WHRonly+PGS and dietary protein in 2-year changes in fasting glucose and HOMA-B (P = 0.0007 and < 0.0001, respectively). When consuming an average-protein diet, participants with higher WHRonly+PGS showed less increased fasting glucose (β = - 0.46, P = 0.006) and less reduction in HOMA-B (β = 0.02, P = 0.005) compared with lower WHRonly+PGS. Conversely, eating high-protein diet was associated with less decreased HOMA-B among individuals with lower than higher WHRonly+PGS (β = - 0.02, P = 0.006). CONCLUSIONS Distinct genetically determined adiposity subtypes may differentially modify the effects of weight-loss diets on improving glucose metabolism in white Americans. This trial was registered at clinicaltrials.gov as NCT00072995.
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