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Cao L, An Y, Liu H, Jiang J, Liu W, Zhou Y, Shi M, Dai W, Lv Y, Zhao Y, Lu Y, Chen L, Xia Y. Global epidemiology of type 2 diabetes in patients with NAFLD or MAFLD: a systematic review and meta-analysis. BMC Med 2024; 22:101. [PMID: 38448943 PMCID: PMC10919055 DOI: 10.1186/s12916-024-03315-0] [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: 08/01/2023] [Accepted: 02/23/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND Non-alcoholic fatty liver disease (NAFLD) and metabolic-associated fatty liver disease (MAFLD) shares common pathophysiological mechanisms with type 2 diabetes, making them significant risk factors for type 2 diabetes. The present study aimed to assess the epidemiological feature of type 2 diabetes in patients with NAFLD or MAFLD at global levels. METHODS Published studies were searched for terms that included type 2 diabetes, and NAFLD or MAFLD using PubMed, EMBASE, MEDLINE, and Web of Science databases from their inception to December 2022. The pooled global and regional prevalence and incidence density of type 2 diabetes in patients with NAFLD or MAFLD were evaluated using random-effects meta-analysis. Potential sources of heterogeneity were investigated using stratified meta-analysis and meta-regression. RESULTS A total of 395 studies (6,878,568 participants with NAFLD; 1,172,637 participants with MAFLD) from 40 countries or areas were included in the meta-analysis. The pooled prevalence of type 2 diabetes among NAFLD or MAFLD patients was 28.3% (95% confidence interval 25.2-31.6%) and 26.2% (23.9-28.6%) globally. The incidence density of type 2 diabetes in NAFLD or MAFLD patients was 24.6 per 1000-person year (20.7 to 29.2) and 26.9 per 1000-person year (7.3 to 44.4), respectively. CONCLUSIONS The present study describes the global prevalence and incidence of type 2 diabetes in patients with NAFLD or MAFLD. The study findings serve as a valuable resource to assess the global clinical and economic impact of type 2 diabetes in patients with NAFLD or MAFLD.
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Affiliation(s)
- Limin Cao
- The Third Central Hospital of Tianjin, Tianjin, China
| | - Yu An
- Department of Endocrinology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Huiyuan Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research On Major Chronic Disease, Liaoning Province, Shenyang, China
| | - Jinguo Jiang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research On Major Chronic Disease, Liaoning Province, Shenyang, China
| | - Wenqi Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research On Major Chronic Disease, Liaoning Province, Shenyang, China
| | - Yuhan Zhou
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research On Major Chronic Disease, Liaoning Province, Shenyang, China
| | - Mengyuan Shi
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research On Major Chronic Disease, Liaoning Province, Shenyang, China
| | - Wei Dai
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research On Major Chronic Disease, Liaoning Province, Shenyang, China
| | - Yanling Lv
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yuhong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research On Major Chronic Disease, Liaoning Province, Shenyang, China
| | - Yanhui Lu
- School of Nursing, Peking University, 38 Xueyuan Rd, Haidian District, Beijing, 100191, China.
| | - Liangkai Chen
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Yang Xia
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Liaoning Key Laboratory of Precision Medical Research On Major Chronic Disease, Liaoning Province, Shenyang, China.
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Zhu J, Min N, Gong W, Chen Y, Li X. Identification of Hub Genes and Biological Mechanisms Associated with Non-Alcoholic Fatty Liver Disease and Triple-Negative Breast Cancer. Life (Basel) 2023; 13:life13040998. [PMID: 37109526 PMCID: PMC10146727 DOI: 10.3390/life13040998] [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: 02/02/2023] [Revised: 03/20/2023] [Accepted: 04/06/2023] [Indexed: 04/29/2023] Open
Abstract
The relationship between non-alcoholic fatty liver disease (NAFLD) and triple-negative breast cancer (TNBC) has been widely recognized, but the underlying mechanisms are still unknown. The objective of this study was to identify the hub genes associated with NAFLD and TNBC, and to explore the potential co-pathogenesis and prognostic linkage of these two diseases. We used GEO, TCGA, STRING, ssGSEA, and Rstudio to investigate the common differentially expressed genes (DEGs), conduct functional and signaling pathway enrichment analyses, and determine prognostic value between TNBC and NAFLD. GO and KEGG enrichment analyses of the common DEGs showed that they were enriched in leukocyte aggregation, migration and adhesion, apoptosis regulation, and the PPAR signaling pathway. Fourteen candidate hub genes most likely to mediate NAFLD and TNBC occurrence were identified and validation results in a new cohort showed that ITGB2, RAC2, ITGAM, and CYBA were upregulated in both diseases. A univariate Cox analysis suggested that high expression levels of ITGB2, RAC2, ITGAM, and CXCL10 were associated with a good prognosis in TNBC. Immune infiltration analysis of TNBC samples showed that NCF2, ICAM1, and CXCL10 were significantly associated with activated CD8 T cells and activated CD4 T cells. NCF2, CXCL10, and CYBB were correlated with regulatory T cells and myeloid-derived suppressor cells. This study demonstrated that the redox reactions regulated by the NADPH oxidase (NOX) subunit genes and the transport and activation of immune cells regulated by integrins may play a central role in the co-occurrence trend of NAFLD and TNBC. Additionally, ITGB2, RAC2, and ITGAM were upregulated in both diseases and were prognostic protective factors of TNBC; they may be potential therapeutic targets for treatment of TNBC patients with NAFLD, but further experimental studies are still needed.
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Affiliation(s)
- Jingjin Zhu
- School of Medicine, Nankai University, Tianjin 300071, China
- Department of General Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
| | - Ningning Min
- School of Medicine, Nankai University, Tianjin 300071, China
- Department of General Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
| | - Wenye Gong
- Department of General Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
- Medical School of Chinese PLA, Beijing 100853, China
| | - Yizhu Chen
- Department of General Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
- Medical School of Chinese PLA, Beijing 100853, China
| | - Xiru Li
- Department of General Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
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Marti-Aguado D, Clemente-Sanchez A, Bataller R. Cigarette smoking and liver diseases. J Hepatol 2022; 77:191-205. [PMID: 35131406 DOI: 10.1016/j.jhep.2022.01.016] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 01/14/2022] [Accepted: 01/25/2022] [Indexed: 01/27/2023]
Abstract
Cigarette smoking is a preventable risk factor for premature morbidity and mortality. A history of smoking is observed in approximately 40% of patients with liver disease, while a growing number of studies are investigating the potential impact of smoking in chronic liver diseases. This review discusses the effects of smoking on liver diseases, at multiple levels, with a focus on its potential causal role. Clinical evidence indicates that cigarette smoking negatively impacts the incidence and severity of fatty liver disease, fibrosis progression, hepatocellular carcinoma development, and the outcomes of patients with advanced liver disease. The underlying mechanisms are complex and involve different pathophysiological pathways including oxidative stress and oncogenic signals. Importantly, smoking promotes cardiovascular disease and extrahepatic cancers in patients with steatohepatitis and in transplant recipients. We discuss how promoting smoking cessation could improve the rates of treatment response (in clinical trials) and fibrosis regression, while reducing the risk of hepatocellular carcinoma and improving liver transplant outcomes. Finally, we discuss current challenges such as the referral of smokers to specialised units for smoking cessation.
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Affiliation(s)
- David Marti-Aguado
- Digestive Disease Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain; Center for Liver Diseases, Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, Pittsburgh Liver Research Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Ana Clemente-Sanchez
- Center for Liver Diseases, Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, Pittsburgh Liver Research Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Liver Unit and Digestive Department, Hospital General Universitario Gregorio Marañon, CIBERehd, Instituto de Salud Carlos III, Madrid, Spain
| | - Ramon Bataller
- Center for Liver Diseases, Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, Pittsburgh Liver Research Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
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Gao Y, Liu L, Li T, Yuan D, Wang Y, Xu Z, Hou L, Zhang Y, Duan G, Sun C, Che L, Li S, Sun P, Li Y, Ren Z. A novel simple risk model to predict the prognosis of patients with paraquat poisoning. Sci Rep 2021; 11:237. [PMID: 33420265 PMCID: PMC7794476 DOI: 10.1038/s41598-020-80371-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Accepted: 12/21/2020] [Indexed: 12/22/2022] Open
Abstract
To identify risk factors and develop a simple model to predict early prognosis of acute paraquat (PQ) poisoning patients, we performed a retrospective cohort study of acute PQ poisoning patients (n = 1199). Patients (n = 913) with PQ poisoning from 2011 to 2018 were randomly divided into training (n = 609) and test (n = 304) samples. Another two independent cohorts were used as validation samples for a different time (n = 207) and site (n = 79). Risk factors were identified using a logistic model with Markov Chain Monte Carlo (MCMC) simulation and further evaluated using a latent class analysis. The prediction score was developed based on the training sample and was evaluated using the testing and validation samples. Eight factors, including age, ingestion volume, creatine kinase-MB [CK-MB], platelet [PLT], white blood cell [WBC], neutrophil counts [N], gamma-glutamyl transferase [GGT], and serum creatinine [Cr] were identified as independent risk indicators of in-hospital death events. The risk model had C statistics of 0.895 (95% CI 0.855-0.928), 0.891 (95% CI 0.848-0.932), and 0.829 (95% CI 0.455-1.000), and predictive ranges of 4.6-98.2%, 2.3-94.9%, and 0-12.5% for the test, validation_time, and validation_site samples, respectively. In the training sample, the risk model classified 18.4%, 59.9%, and 21.7% of patients into the high-, average-, and low-risk groups, with corresponding probabilities of 0.985, 0.365, and 0.03 for in-hospital death events. We developed and evaluated a simple risk model to predict the prognosis of patients with acute PQ poisoning. This risk scoring system could be helpful for identifying high-risk patients and reducing mortality due to PQ poisoning.
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Affiliation(s)
- Yanxia Gao
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Liwen Liu
- Department of Infectious Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.,Gene Hospital of Henan Province, Precision Medicine Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Tiegang Li
- Department of Emergency Medicine, Shengjing Hospital of China Medical University, Shenyang, 110001, China
| | - Ding Yuan
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yibo Wang
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhigao Xu
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Linlin Hou
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yan Zhang
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Guoyu Duan
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Changhua Sun
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Lu Che
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Sujuan Li
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Pei Sun
- Emergency Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yi Li
- Emergency Department, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, 100730, China.
| | - Zhigang Ren
- Department of Infectious Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China. .,Gene Hospital of Henan Province, Precision Medicine Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
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Wei Z, Ren Z, Hu S, Gao Y, Sun R, Lv S, Yang G, Yu Z, Kan Q. Development and validation of a simple risk model to predict major cancers for patients with nonalcoholic fatty liver disease. Cancer Med 2019; 9:1254-1262. [PMID: 31860170 PMCID: PMC6997093 DOI: 10.1002/cam4.2777] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 10/29/2019] [Accepted: 12/01/2019] [Indexed: 02/06/2023] Open
Abstract
Objective To recognize risk factors and build up and validate a simple risk model predicting 8‐year cancer events after nonalcoholic fatty liver disease (NAFLD). Methods This was a retrospective cohort study. Patients with NAFLD (n = 5561) were randomly divided into groups: training (n = 1254), test (n = 627), evaluation (n = 627), and validation (n = 3053). Risk factors were recognized by statistical method named as a Cox model with Markov chain Monte Carlo (MCMC) simulation. This prediction score was established based on the training group and was further validated based on the testing and evaluation group from January 1, 2007 to December 31, 2009 and another 3053 independent cases from January 1, 2010 to February 13, 2014. Results The main outcomes were NAFLD‐related cancer events, including those of the liver, breast, esophagus, stomach, pancreas, prostate and colon, within 8 years after hospitalization for NAFLD diagnosis. Seven risk factors (age (every 5 years),LDL, smoking, BMI, diabetes, OSAS, and aspartate aminotransferase (every 5 units)) were identified as independent indicators of cancer events. This risk model contained a predictive range of 0.4%‐37.7%, 0.3%‐39.6%, and 0.4%‐39.3% in the training, test, evaluation group, respectively, with a range 0.4%‐30.4% for validation groups. In the training group, 12.6%, 76.9%, and 10.5% of patients, which corresponded to the low ‐, moderate ‐, and high‐risk groups, had probabilities of, <0.01, <0.1, and 0.23 for 8‐year events. Conclusions Seven risk factors were recognized and a simple risk model were developed and validated to predict the risk of cancer events after NAFLD based on 8 years. This simple risk score system may recognize high‐risk patients and reduce cancer incidence.
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Affiliation(s)
- Zihan Wei
- Department of GeriatricsThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Department of Infectious DiseasesThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Gene Hospital of Henan ProvincePrecision Medicine CenterThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Department of PharmacyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Zhigang Ren
- Department of Infectious DiseasesThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Gene Hospital of Henan ProvincePrecision Medicine CenterThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Department of PharmacyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Shuang Hu
- National Clinical Research Center of Cardiovascular DiseasesState Key Laboratory of Cardiovascular DiseaseFuwai HospitalNational Center for Cardiovascular DiseasesBeijingChina
| | - Yan Gao
- National Clinical Research Center of Cardiovascular DiseasesState Key Laboratory of Cardiovascular DiseaseFuwai HospitalNational Center for Cardiovascular DiseasesBeijingChina
| | - Ranran Sun
- Department of Infectious DiseasesThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Gene Hospital of Henan ProvincePrecision Medicine CenterThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Department of PharmacyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Shuai Lv
- Department of gastroenterologyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Guojie Yang
- Department of GeriatricsThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Zujiang Yu
- Department of Infectious DiseasesThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Gene Hospital of Henan ProvincePrecision Medicine CenterThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Department of PharmacyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Quancheng Kan
- Department of Infectious DiseasesThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Gene Hospital of Henan ProvincePrecision Medicine CenterThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Department of PharmacyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
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