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Talaat RM, Elsharnoby S, Abdelkhalek MS, El-Shenawy SZ, Elmasry S. The Impact of Interferon-γ (IFN-γ) and IFN-γ-Inducible Protein 10 (IP-10) Genes' Polymorphism on Risk of Hepatitis C Virus-Related Liver Cirrhosis. Immunol Invest 2021; 51:688-704. [PMID: 33445993 DOI: 10.1080/08820139.2020.1869251] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background: Today there is increasing evidence concerning the association between individual genetic polymorphisms within proinflammatory cytokines and chronic hepatitis C (CHC) severity. It has been demonstrated that polymorphisms in some genes may significantly predict HCV infected patients' susceptibility to developing liver cirrhosis or their responsiveness to the treatment.Aim: We investigated the influence of single nucleotide polymorphisms (SNPs) in Interferon (IFN-γ) and Interferon Gamma-Inducible Protein 10 (IP-10) genes on cirrhosis risk in HCV-infected patients and their association with response to various direct-acting antiviral drugs (DAAs).Methods: IFN-γ (+874T/A, +2109A/G) and IP-10 (-135G/A, -1447A/G) genotypes were determined in 175 CHC Egyptian HCV patients (69 liver cirrhotic and 106 non-cirrhotic patients) using either single-stranded polymorphism polymerase chain reaction (SSP-PCR) or Restriction fragment length-PCR (RFLP-PCR) methods.Results: IFN-γ + 874 TA, IP-10 - 135AA, and IP-10 - 1447AA and IP-10 - 1447GG genotypes are increased in patients developing liver cirrhosis compared to non-cirrhotic ones. Although, no statistical significance in their distribution was demonstrated, indicating the lack of association between these SNPs and liver cirrhosis susceptibility in HCV-infected patients. Haplotypes analysis between different loci on all selected genes showed a significant increase in AGGA and TAGA and a significant decrease in TGGA haplotypes in cirrhotic patients. Genotype frequencies at loci -135 and -1447 of IP-10 appeared to be in complete Linkage disequilibrium (LD) (D' = 0.999, r2 = 0.689).Conclusion: Our data support the concept that IFN-γ and IP-10 gene polymorphisms are not predictors of disease progression among Egyptian patients with HCV infection.
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Affiliation(s)
- Roba M Talaat
- Molecular Biology Department, Genetic Engineering and Biotechnology Research Institute (GEBRI), University of Sadat City (USC), Sadat City, Egypt
| | - Shimaa Elsharnoby
- Molecular Biology Department, Genetic Engineering and Biotechnology Research Institute (GEBRI), University of Sadat City (USC), Sadat City, Egypt
| | - Mohamed S Abdelkhalek
- Molecular Biology Department, Genetic Engineering and Biotechnology Research Institute (GEBRI), University of Sadat City (USC), Sadat City, Egypt
| | - Soha Z El-Shenawy
- Biochemistry Department, National Liver Institute (NLI), Menoufiya University, Sadat City, Egypt
| | - Samir Elmasry
- Molecular Biology Department, Genetic Engineering and Biotechnology Research Institute (GEBRI), University of Sadat City (USC), Sadat City, Egypt
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Ruuskanen MO, Åberg F, Männistö V, Havulinna AS, Méric G, Liu Y, Loomba R, Vázquez-Baeza Y, Tripathi A, Valsta LM, Inouye M, Jousilahti P, Salomaa V, Jain M, Knight R, Lahti L, Niiranen TJ. Links between gut microbiome composition and fatty liver disease in a large population sample. Gut Microbes 2021; 13:1-22. [PMID: 33651661 PMCID: PMC7928040 DOI: 10.1080/19490976.2021.1888673] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 01/14/2021] [Accepted: 01/28/2021] [Indexed: 02/08/2023] Open
Abstract
Fatty liver disease is the most common liver disease in the world. Its connection with the gut microbiome has been known for at least 80 y, but this association remains mostly unstudied in the general population because of underdiagnosis and small sample sizes. To address this knowledge gap, we studied the link between the Fatty Liver Index (FLI), a well-established proxy for fatty liver disease, and gut microbiome composition in a representative, ethnically homogeneous population sample of 6,269 Finnish participants. We based our models on biometric covariates and gut microbiome compositions from shallow metagenome sequencing. Our classification models could discriminate between individuals with a high FLI (≥60, indicates likely liver steatosis) and low FLI (<60) in internal cross-region validation, consisting of 30% of the data not used in model training, with an average AUC of 0.75 and AUPRC of 0.56 (baseline at 0.30). In addition to age and sex, our models included differences in 11 microbial groups from class Clostridia, mostly belonging to orders Lachnospirales and Oscillospirales. Our models were also predictive of the high FLI group in a different Finnish cohort, consisting of 258 participants, with an average AUC of 0.77 and AUPRC of 0.51 (baseline at 0.21). Pathway analysis of representative genomes of the positively FLI-associated taxa in (NCBI) Clostridium subclusters IV and XIVa indicated the presence of, e.g., ethanol fermentation pathways. These results support several findings from smaller case-control studies, such as the role of endogenous ethanol producers in the development of the fatty liver.
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Affiliation(s)
- Matti O. Ruuskanen
- Department of Internal Medicine, University of Turku, Turku, Finland
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Fredrik Åberg
- Transplantation and Liver Surgery Clinic, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
- Transplant Institute, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Ville Männistö
- Department of Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
- Department of Experimental Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Aki S. Havulinna
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, FIMM - HiLIFE, Helsinki, Finland
| | - Guillaume Méric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Yang Liu
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Rohit Loomba
- Department of Medicine, NAFLD Research Center, La Jolla, CA, USA
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Yoshiki Vázquez-Baeza
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
| | - Anupriya Tripathi
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - Liisa M. Valsta
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Public Health and Primary Care, Cambridge University, Cambridge, UK
| | - Pekka Jousilahti
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Mohit Jain
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Pharmacology, University of California San Diego, La Jolla, California, USA
| | - Rob Knight
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Department of Computer Science & Engineering, University of California San Diego, La Jolla, California, USA
| | - Leo Lahti
- Deparment of Computing, University of Turku, Turku, Finland
| | - Teemu J. Niiranen
- Department of Internal Medicine, University of Turku, Turku, Finland
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
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