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• Journal article
  Powles STR, Gallagher KI, Chong LWL, Alexander JL, Mullish BH, Hicks LC, McDonald JAK, Marchesi JR, Williams HRT, Orchard TRet al., 2022,
  , BMC Gastroenterology, Vol: 22

  <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>Urinary and faecal metabolic profiling have been extensively studied in gastrointestinal diseases as potential diagnostic markers, and to enhance our understanding of the intestinal microbiome in the pathogenesis these conditions. The impact of bowel cleansing on the microbiome has been investigated in several studies, but limited to just one study on the faecal metabolome.</jats:p> </jats:sec><jats:sec> <jats:title>Aim</jats:title> <jats:p>To compare the effects of bowel cleansing on the composition of the faecal microbiome, and the urine and faecal metabolome.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>Urine and faecal samples were obtained from eleven patients undergoing colonoscopy at baseline, and then at day 3 and week 6 after colonoscopy. 16S rRNA gene sequencing was used to analyse changes in the microbiome, and metabonomic analysis was performed using proton nuclear magnetic resonance (<jats:sup>1</jats:sup>H NMR) spectroscopy.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>Microbiomic analysis demonstrated a reduction in alpha diversity (Shannon index) between samples taken at baseline and three days following bowel cleansing (<jats:italic>p</jats:italic> = 0.002), and there was no significant difference between samples at baseline and six weeks post colonoscopy. Targeted and non-targeted analysis of urinary and faecal bacterial associated metabolites showed no significant impact following bowel cleansing.</jats:p> </jats:sec><jats:sec>

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• Conference paper
  Routy B, Lenehan J, Daisley B, Messaoudene M, Al K, Richard C, Miller W, Jamal R, Ernst S, Logan D, Belanger K, Martinez-Gili L, Mullish B, Takis P, Samayoa CH, Ninkov M, Parvathy SN, Lambert C, Elkrief A, Lapointe R, Haeryfar M, Burton J, Silverman M, Maleki Set al., 2022,
  , SITC 37th Annual Meeting (SITC 2022) Abstracts, Publisher: BMJ Publishing Group Ltd, Pages: A646-A646
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• Conference paper
  Lythgoe M, Mullish B, Frampton A, Dama P, Pickford E, Tookman L, Cunnea P, Fotopoulou C, Jeffery I, Fyvie G, Stevenson A, Krell Jet al., 2022,
  , Publisher: BMJ PUBLISHING GROUP, Pages: A659-A659
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• Journal article
  Ianiro G, Mullish BH, Iqbal TH, Terveer EM, Baunwall SMD, Link A, Sokol H, Kupcinskas J, Masucci L, Sanguinetti M, Vehreschild MJGT, Hvas CL, Keller JJ, Gasbarrini A, Kujiper EJ, Cammarota Get al., 2022,
  , The Lancet Gastroenterology &amp; Hepatology, Vol: 7, Pages: 979-980, ISSN: 2468-1253
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• Conference paper
  Mullish BH, Paizs P, Alexander J, Verigos E, McDonald JAK, Ford L, Maneta-Stavrakaki S, Sani M, Roberts LA, Chrysostomou D, Kinross J, Monaghan T, Marchesi JR, Kao D, Takats Zet al., 2022,
  , UEG Week 2022, Pages: 823-823
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• Journal article
  Forlano R, Sivakumar M, Mullish BH, Manousou Pet al., 2022,
  , International Journal of Molecular Sciences, Vol: 23, Pages: 1-13, ISSN: 1422-0067

  Non-alcoholic fatty liver disease (NAFLD) represents an increasing cause of liver disease, affecting one-third of the population worldwide. Despite many medications being in the pipeline to treat the condition, there is still no pharmaceutical agent licensed to treat the disease. As intestinal bacteria play a crucial role in the pathogenesis and progression of liver damage in patients with NAFLD, it has been suggested that manipulating the microbiome may represent a therapeutical option. In this review, we summarise the latest evidence supporting the manipulation of the intestinal microbiome as a potential therapy for treating liver disease in patients with NAFLD.

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• Journal article
  Mullish BH, McDonald JAK, Marchesi JR, 2022,
  , The Lancet Gastroenterology & Hepatology, Vol: 7, Pages: 594-594, ISSN: 2468-1253
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• Journal article
  Ghani R, Mullish BH, Davies FJ, Marchesi JRet al., 2022,
  , Clinical Microbiology and Infection, Vol: 28, Pages: 502-512, ISSN: 1198-743X
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• Journal article
  Fromentin S, Forslund SK, Chechi K, Aron-Wisnewsky J, Chakaroun R, Nielsen T, Tremaroli V, Ji B, Prifti E, Myridakis A, Chilloux J, Andrikopoulos P, Fan Y, Olanipekun MT, Alves R, Adiouch S, Bar N, Talmor-Barkan Y, Belda E, Caesar R, Coelho LP, Falony G, Fellahi S, Galan P, Galleron N, Helft G, Hoyles L, Isnard R, Le Chatelier E, Julienne H, Olsson L, Pedersen HK, Pons N, Quinquis B, Rouault C, Roume H, Salem J-E, Schmidt TSB, Vieira-Silva S, Li P, Zimmermann-Kogadeeva M, Lewinter C, Sondertoft NB, Hansen TH, Gauguier D, Gotze JP, Kober L, Kornowski R, Vestergaard H, Hansen T, Zucker J-D, Hercberg S, Letunic I, Backhed F, Oppert J-M, Nielsen J, Raes J, Bork P, Stumvoll M, Segal E, Clement K, Dumas M-E, Ehrlich SD, Pedersen Oet al., 2022,
  , Nature Medicine, Vol: 28, Pages: 303-+, ISSN: 1078-8956

  Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages—acute coronary syndrome, chronic IHD and IHD with heart failure—and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.

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• Journal article
  Talmor-Barkan Y, Bar N, Shaul AA, Shahaf N, Godneva A, Bussi Y, Lotan-Pompan M, Weinberger A, Shechter A, Chezar-Azerrad C, Arow Z, Hammer Y, Chechi K, Forslund SK, Fromentin S, Dumas M-E, Ehrlich SD, Pedersen O, Kornowski R, Segal Eet al., 2022,
  , NATURE MEDICINE, Vol: 28, Pages: 295-+, ISSN: 1078-8956
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  • Citations: 131

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