The circulating microbiome signature and inferred functional metagenomics in alcoholic hepatitis
Intestinal dysbiosis is implicated in alcoholic hepatitis (AH). However, changes in the circulating microbiome, its association with the presence and severity of AH, and its functional relevance in AH is unknown. Qualitative and quantitative assessment of changes in the circulating microbiome were p...
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| Published in | Hepatology (Baltimore, Md.) Vol. 67; no. 4; pp. 1284 - 1302 |
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| Main Authors | , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Wolters Kluwer Health, Inc
01.04.2018
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| Subjects | |
| Online Access | Get full text |
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| Abstract | Intestinal dysbiosis is implicated in alcoholic hepatitis (AH). However, changes in the circulating microbiome, its association with the presence and severity of AH, and its functional relevance in AH is unknown. Qualitative and quantitative assessment of changes in the circulating microbiome were performed by sequencing bacterial DNA in subjects with moderate AH (MAH) (n = 18) or severe AH (SAH) (n = 19). These data were compared with heavy drinking controls (HDCs) without obvious liver disease (n = 19) and non–alcohol‐consuming controls (NACs, n = 20). The data were related to endotoxin levels and markers of monocyte activation. Linear discriminant analysis effect size (LEfSe) analysis, inferred metagenomics, and predictive functional analysis using PICRUSt were performed. There was a significant increase in 16S copies/ng DNA both in MAH (P < 0.01) and SAH (P < 0.001) subjects. Compared with NACs, the relative abundance of phylum Bacteroidetes was significantly decreased in HDCs, MAH, and SAH (P < 0.001). In contrast, all alcohol‐consuming groups had enrichment with Fusobacteria; this was greatest for HDCs and decreased progressively in MAH and SAH. Subjects with SAH had significantly higher endotoxemia (P = 0.01). Compared with alcohol‐consuming groups, predictive functional metagenomics indicated an enrichment of bacteria with genes related to methanogenesis and denitrification. Furthermore, both HDCs and SAH showed activation of a type III secretion system that has been linked to gram‐negative bacterial virulence. Metagenomics in SAH versus NACs predicted increased isoprenoid synthesis via mevalonate and anthranilate degradation, known modulators of gram‐positive bacterial growth and biofilm production, respectively. Conclusion: Heavy alcohol consumption appears to be the primary driver of changes in the circulating microbiome associated with a shift in its inferred metabolic functions. (Hepatology 2018;67:1284‐1302). |
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| AbstractList | Intestinal dysbiosis is implicated in alcoholic hepatitis (AH). However, changes in the circulating microbiome, its association with the presence and severity of AH, and its functional relevance in AH is unknown. Qualitative and quantitative assessment of changes in the circulating microbiome were performed by sequencing bacterial DNA in subjects with moderate AH (MAH) (n = 18) or severe AH (SAH) (n = 19). These data were compared with heavy drinking controls (HDCs) without obvious liver disease (n = 19) and non–alcohol‐consuming controls (NACs, n = 20). The data were related to endotoxin levels and markers of monocyte activation. Linear discriminant analysis effect size (LEfSe) analysis, inferred metagenomics, and predictive functional analysis using PICRUSt were performed. There was a significant increase in 16S copies/ng DNA both in MAH (P < 0.01) and SAH (P < 0.001) subjects. Compared with NACs, the relative abundance of phylum Bacteroidetes was significantly decreased in HDCs, MAH, and SAH (P < 0.001). In contrast, all alcohol‐consuming groups had enrichment with Fusobacteria; this was greatest for HDCs and decreased progressively in MAH and SAH. Subjects with SAH had significantly higher endotoxemia (P = 0.01). Compared with alcohol‐consuming groups, predictive functional metagenomics indicated an enrichment of bacteria with genes related to methanogenesis and denitrification. Furthermore, both HDCs and SAH showed activation of a type III secretion system that has been linked to gram‐negative bacterial virulence. Metagenomics in SAH versus NACs predicted increased isoprenoid synthesis via mevalonate and anthranilate degradation, known modulators of gram‐positive bacterial growth and biofilm production, respectively. Conclusion: Heavy alcohol consumption appears to be the primary driver of changes in the circulating microbiome associated with a shift in its inferred metabolic functions. (Hepatology 2018;67:1284‐1302). Intestinal dysbiosis is implicated in alcoholic hepatitis (AH). However, changes in the circulating microbiome, its association with the presence and severity of AH, and its functional relevance in AH is unknown. Qualitative and quantitative assessment of changes in the circulating microbiome were performed by sequencing bacterial DNA in subjects with moderate AH (MAH) (n = 18) or severe AH (SAH) (n = 19). These data were compared with heavy drinking controls (HDCs) without obvious liver disease (n = 19) and non-alcohol-consuming controls (NACs, n = 20). The data were related to endotoxin levels and markers of monocyte activation. Linear discriminant analysis effect size (LEfSe) analysis, inferred metagenomics, and predictive functional analysis using PICRUSt were performed. There was a significant increase in 16S copies/ng DNA both in MAH (P < 0.01) and SAH (P < 0.001) subjects. Compared with NACs, the relative abundance of phylum Bacteroidetes was significantly decreased in HDCs, MAH, and SAH (P < 0.001). In contrast, all alcohol-consuming groups had enrichment with Fusobacteria; this was greatest for HDCs and decreased progressively in MAH and SAH. Subjects with SAH had significantly higher endotoxemia (P = 0.01). Compared with alcohol-consuming groups, predictive functional metagenomics indicated an enrichment of bacteria with genes related to methanogenesis and denitrification. Furthermore, both HDCs and SAH showed activation of a type III secretion system that has been linked to gram-negative bacterial virulence. Metagenomics in SAH versus NACs predicted increased isoprenoid synthesis via mevalonate and anthranilate degradation, known modulators of gram-positive bacterial growth and biofilm production, respectively. Heavy alcohol consumption appears to be the primary driver of changes in the circulating microbiome associated with a shift in its inferred metabolic functions. (Hepatology 2018;67:1284-1302). Intestinal dysbiosis is implicated in alcoholic hepatitis (AH). However, changes in the circulating microbiome, its association with the presence and severity of AH and its functional relevance in AH is unknown. Qualitative and quantitative assessment of changes in the circulating microbiome were performed by sequencing bacterial DNA in subjects with moderate (n=18) or severe AH (n=19). These data were compared to heavy drinking controls (HDC) without obvious liver disease (n=19) and non-alcohol consuming controls (NAC, n=20). The data were related to endotoxin levels and markers of monocyte activation. Linear Discriminant Analysis (LDA) Effect Size (LEfSe) analysis, inferred metagenomics and predictive functional analysis using PICRUSt were performed. There was a significant increase in 16S copies/ng DNA both in MAH (p<0.01) and SAH (p<0.001) subjects. Compared to NAC, the relative abundance of phylum Bacteroidetes was significantly decreased in HDC, MAH, and SAH (p<0.001). In contrast, all alcohol consuming groups had enrichment with Fusobacteria ; this was greatest for HDC and decreased progressively in MAH and SAH. Subjects with SAH had significantly higher endotoxemia (p=0.01). Compared to alcohol consuming groups, predictive functional metagenomics indicated an enrichment of bacteria with genes related to methanogenesis and denitrification. Also, both HDC and SAH showed activation of type III secretion system which has been linked to gram negative bacterial virulence. Metagenomics in SAH vs NAC predicted increased isoprenoid synthesis via mevalonate and anthranilate degradation, known modulators of gram positive bacterial growth and biofilm production respectively. In conclusion, heavy alcohol consumption appears to be the primary driver of changes in the circulating microbiome associated with a shift in its inferred metabolic functions. Intestinal dysbiosis is implicated in alcoholic hepatitis (AH). However, changes in the circulating microbiome, its association with the presence and severity of AH, and its functional relevance in AH is unknown. Qualitative and quantitative assessment of changes in the circulating microbiome were performed by sequencing bacterial DNA in subjects with moderate AH (MAH) (n = 18) or severe AH (SAH) (n = 19). These data were compared with heavy drinking controls (HDCs) without obvious liver disease (n = 19) and non-alcohol-consuming controls (NACs, n = 20). The data were related to endotoxin levels and markers of monocyte activation. Linear discriminant analysis effect size (LEfSe) analysis, inferred metagenomics, and predictive functional analysis using PICRUSt were performed. There was a significant increase in 16S copies/ng DNA both in MAH (P < 0.01) and SAH (P < 0.001) subjects. Compared with NACs, the relative abundance of phylum Bacteroidetes was significantly decreased in HDCs, MAH, and SAH (P < 0.001). In contrast, all alcohol-consuming groups had enrichment with Fusobacteria; this was greatest for HDCs and decreased progressively in MAH and SAH. Subjects with SAH had significantly higher endotoxemia (P = 0.01). Compared with alcohol-consuming groups, predictive functional metagenomics indicated an enrichment of bacteria with genes related to methanogenesis and denitrification. Furthermore, both HDCs and SAH showed activation of a type III secretion system that has been linked to gram-negative bacterial virulence. Metagenomics in SAH versus NACs predicted increased isoprenoid synthesis via mevalonate and anthranilate degradation, known modulators of gram-positive bacterial growth and biofilm production, respectively.Intestinal dysbiosis is implicated in alcoholic hepatitis (AH). However, changes in the circulating microbiome, its association with the presence and severity of AH, and its functional relevance in AH is unknown. Qualitative and quantitative assessment of changes in the circulating microbiome were performed by sequencing bacterial DNA in subjects with moderate AH (MAH) (n = 18) or severe AH (SAH) (n = 19). These data were compared with heavy drinking controls (HDCs) without obvious liver disease (n = 19) and non-alcohol-consuming controls (NACs, n = 20). The data were related to endotoxin levels and markers of monocyte activation. Linear discriminant analysis effect size (LEfSe) analysis, inferred metagenomics, and predictive functional analysis using PICRUSt were performed. There was a significant increase in 16S copies/ng DNA both in MAH (P < 0.01) and SAH (P < 0.001) subjects. Compared with NACs, the relative abundance of phylum Bacteroidetes was significantly decreased in HDCs, MAH, and SAH (P < 0.001). In contrast, all alcohol-consuming groups had enrichment with Fusobacteria; this was greatest for HDCs and decreased progressively in MAH and SAH. Subjects with SAH had significantly higher endotoxemia (P = 0.01). Compared with alcohol-consuming groups, predictive functional metagenomics indicated an enrichment of bacteria with genes related to methanogenesis and denitrification. Furthermore, both HDCs and SAH showed activation of a type III secretion system that has been linked to gram-negative bacterial virulence. Metagenomics in SAH versus NACs predicted increased isoprenoid synthesis via mevalonate and anthranilate degradation, known modulators of gram-positive bacterial growth and biofilm production, respectively.Heavy alcohol consumption appears to be the primary driver of changes in the circulating microbiome associated with a shift in its inferred metabolic functions. (Hepatology 2018;67:1284-1302).CONCLUSIONHeavy alcohol consumption appears to be the primary driver of changes in the circulating microbiome associated with a shift in its inferred metabolic functions. (Hepatology 2018;67:1284-1302). |
| Author | Gores, Gregory J. Crabb, David W. Puri, Puneet Katz, Barry Shah, Vijay H. Borst, Andrew Chalasani, Naga P. Comerford, Megan Walker, Susan Christensen, Jeffrey E. Radaeva, Svetlana Kamath, Patrick S. Mirshahi, Faridoddin Yu, Qigui Liangpunsakul, Suthat Kumar, Divya P. Sanyal, Arun J. |
| AuthorAffiliation | 7 National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Rockville, MD 5 Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN 2 Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 4 Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 8 Institut National de la Santé et de la Recherche Médicale (INSERM), Toulouse, France; Institut des Maladies Métaboliques et Cardiovasculaires (I2MC), F-31432 Toulouse Cedex 4, France 6 Eskenazi Health, Indianapolis, IN 3 Roudebush Veterans Administration Medical Center, Indianapolis, IN 1 Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Virginia Commonwealth University, Richmond, VA |
| AuthorAffiliation_xml | – name: 4 Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN – name: 7 National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Rockville, MD – name: 2 Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN – name: 1 Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Virginia Commonwealth University, Richmond, VA – name: 3 Roudebush Veterans Administration Medical Center, Indianapolis, IN – name: 6 Eskenazi Health, Indianapolis, IN – name: 8 Institut National de la Santé et de la Recherche Médicale (INSERM), Toulouse, France; Institut des Maladies Métaboliques et Cardiovasculaires (I2MC), F-31432 Toulouse Cedex 4, France – name: 5 Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN |
| Author_xml | – sequence: 1 givenname: Puneet surname: Puri fullname: Puri, Puneet email: puneet.puri@vcuhealth.org organization: Virginia Commonwealth University – sequence: 2 givenname: Suthat surname: Liangpunsakul fullname: Liangpunsakul, Suthat organization: Roudebush Veterans Administration Medical Center – sequence: 3 givenname: Jeffrey E. surname: Christensen fullname: Christensen, Jeffrey E. organization: Institut des Maladies Métaboliques et Cardiovasculaires (I2MC) – sequence: 4 givenname: Vijay H. orcidid: 0000-0001-7620-573X surname: Shah fullname: Shah, Vijay H. organization: Mayo Clinic – sequence: 5 givenname: Patrick S. surname: Kamath fullname: Kamath, Patrick S. organization: Mayo Clinic – sequence: 6 givenname: Gregory J. surname: Gores fullname: Gores, Gregory J. organization: Mayo Clinic – sequence: 7 givenname: Susan surname: Walker fullname: Walker, Susan organization: Virginia Commonwealth University – sequence: 8 givenname: Megan surname: Comerford fullname: Comerford, Megan organization: Indiana University School of Medicine – sequence: 9 givenname: Barry surname: Katz fullname: Katz, Barry organization: Indiana University School of Medicine – sequence: 10 givenname: Andrew surname: Borst fullname: Borst, Andrew organization: Indiana University School of Medicine – sequence: 11 givenname: Qigui surname: Yu fullname: Yu, Qigui organization: Indiana University School of Medicine – sequence: 12 givenname: Divya P. surname: Kumar fullname: Kumar, Divya P. organization: Virginia Commonwealth University – sequence: 13 givenname: Faridoddin surname: Mirshahi fullname: Mirshahi, Faridoddin organization: Virginia Commonwealth University – sequence: 14 givenname: Svetlana surname: Radaeva fullname: Radaeva, Svetlana organization: National Institutes of Health – sequence: 15 givenname: Naga P. surname: Chalasani fullname: Chalasani, Naga P. organization: Roudebush Veterans Administration Medical Center – sequence: 16 givenname: David W. surname: Crabb fullname: Crabb, David W. organization: Eskenazi Health – sequence: 17 givenname: Arun J. surname: Sanyal fullname: Sanyal, Arun J. organization: Virginia Commonwealth University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29083504$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | 2017 by the American Association for the Study of Liver Diseases. 2018 by the American Association for the Study of Liver Diseases. |
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| Language | English |
| License | 2017 by the American Association for the Study of Liver Diseases. |
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| Notes | Potential conflicts of interest: Arun J. Sanyal consults for Gilead, Malinckrodt, Salix, Pfizer, Numbus, Nitto Denko, Hemosheat and Lilly. VCU has received grants from Conatus, Novartis, Galectin, Bristol‐Myers Squibb, Merck and Sequana. Sanyal has received royalties from Elseveir and uptodate owns stocks in Akarna, GenFit and Sanyal Bio. The Translational Research and Evolving Alcoholic Hepatitis Treatment (TREAT) Consortium is supported by the National Institute on Alcohol Abuse and Alcoholism (grants 5U01AA021883‐05, 5U01AA021891‐05, 5U01AA021788‐05, 5U01AA021840‐05, and K23AA021179 [to P.P.]). See Editorial on Page 1207 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Senior author |
| ORCID | 0000-0001-7620-573X |
| OpenAccessLink | https://aasldpubs.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hep.29623 |
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| PublicationDate | April 2018 |
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| PublicationDecade | 2010 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States – name: Hoboken |
| PublicationTitle | Hepatology (Baltimore, Md.) |
| PublicationTitleAlternate | Hepatology |
| PublicationYear | 2018 |
| Publisher | Wolters Kluwer Health, Inc |
| Publisher_xml | – name: Wolters Kluwer Health, Inc |
| References | 2010; 10 2002; 15 2015; 148 1978; 75 1987; 4 2002; 277 2011; 55 2011; 54 2014; 68 2011; 12 2013; 8 2016; 39 1983; 18 2014; 21 2013; 59 2009; 50 2013; 57 2015; 373 2013; 310 2014; 15 2017; 161 2009; 360 2017; 127 2016; 150 1948; 27 2015; 12 2017; 25 1998; 339 2005; 41 2016; 51 2012; 302 1998; 62 2016; 14 2016; 56 2014; 306 2016; 6 2012; 1 2000; 37 2000; 32 2015; 112 2013; 31 2016; 65 2016; 64 2013; 452 2016; 63 1995; 346 2012; 6 1998; 101 2012; 40 Kryger (R49-20-20241017) 1983; 18 Galan (R41-20-20241017) 2014; 68 Bardou (R23-20-20241017) 2014; 15 Costaglioli (R46-20-20241017) 2012; 1 Werner (R24-20-20241017) 2012; 6 Lucey (R9-20-20241017) 2009; 360 Martin (R37-20-20241017) 1998; 339 Kakiyama (R28-20-20241017) 2014; 306 Mathurin (R8-20-20241017) 2013; 310 Lelouvier (R20-20-20241017) 2016; 64 Zhu (R32-20-20241017) 2013; 57 Chen (R15-20-20241017) 2015; 148 Mutlu (R18-20-20241017) 2012; 302 Parlesak (R16-20-20241017) 2000; 32 Wang (R30-20-20241017) 2016; 6 Bajaj (R34-20-20241017) 2012; 302 Meszaros (R35-20-20241017) 2017; 161 Boucher (R44-20-20241017) 2000; 37 Paisse (R14-20-20241017) 2016; 56 Llopis (R13-20-20241017) 2016; 65 Pannen (R38-20-20241017) 1998; 62 Goda (R39-20-20241017) 1998; 101 Kanehisa (R26-20-20241017) 2012; 40 Maddrey (R7-20-20241017) 1978; 75 Jewell (R1-20-20241017) 2010; 10 Shannon (R27-20-20241017) 1948; 27 Bode (R48-20-20241017) 1987; 4 Louvet (R11-20-20241017) 2015; 12 Liangpunsakul (R5-20-20241017) 2016; 14 Yang (R17-20-20241017) 2017; 127 Mookerjee (R50-20-20241017) 2011; 55 Bull‐Otterson (R31-20-20241017) 2013; 8 Teli (R4-20-20241017) 1995; 346 Boursier (R29-20-20241017) 2016; 63 Segata (R22-20-20241017) 2011; 12 Thursz (R10-20-20241017) 2015; 373 Perez‐Gil (R43-20-20241017) 2013; 452 Nagy (R12-20-20241017) 2016; 150 Zhao (R36-20-20241017) 2016; 39 Radics (R42-20-20241017) 2014; 21 Rehm (R2-20-20241017) 2013; 59 Beisel (R45-20-20241017) 2016; 51 Keshavarzian (R19-20-20241017) 2009; 50 Case (R3-20-20241017) 2015; 112 Loomba (R21-20-20241017) 2017; 25 Donlan (R47-20-20241017) 2002; 15 Dunn (R6-20-20241017) 2005; 41 Chen (R33-20-20241017) 2011; 54 Brouard (R40-20-20241017) 2002; 277 Langille (R25-20-20241017) 2013; 31 29083499 - Hepatology. 2018 Apr;67(4):1207-1209 |
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| SubjectTerms | Adult Alcohol Alcohol Drinking - adverse effects Alcohol use Bacteria Biodegradation Biofilms Cell activation Denitrification Deoxyribonucleic acid Discriminant analysis DNA DNA sequencing DNA, Bacterial - blood DNA, Bacterial - genetics Drinking behavior Dysbacteriosis Endotoxemia Endotoxins - blood Female Gram-negative bacteria Hepatitis Hepatitis, Alcoholic - microbiology Hepatology Humans Intestine Liver - microbiology Liver - pathology Liver diseases Liver Diseases, Alcoholic - microbiology Male Metagenomics - methods Methanogenesis Mevalonic acid Microbiomes Microbiota - genetics Middle Aged Monocytes Monocytes - pathology Secretion Virulence |
| Title | The circulating microbiome signature and inferred functional metagenomics in alcoholic hepatitis |
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