Nienke Z Borren1,2, Damian Plichta3, Amit D Joshi1, Gracia Bonilla4, Ruslan Sadreyev4, Hera Vlamakis3,4, Ramnik J Xavier1,3,4, Ashwin N Ananthakrishnan1. 1. Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. 2. Department of Gastroenterology & Hepatology, Erasmus University Medical Center, Rotterdam, the Netherlands. 3. Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. 4. Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Abstract
BACKGROUND: Inflammatory bowel diseases (IBD) are characterized by intermittent relapses, and their course is heterogeneous and unpredictable. Our aim was to determine the ability of protein, metabolite, or microbial biomarkers to predict relapse in patients with quiescent disease. METHODS: This prospective study enrolled patients with quiescent Crohn disease and ulcerative colitis, defined as the absence of clinical symptoms (Harvey-Bradshaw Index ≤ 4, Simple Clinical Colitis Activity Index ≤ 2) and endoscopic remission within the prior year. The primary outcome was relapse within 2 years, defined as symptomatic worsening accompanied by elevated inflammatory markers resulting in a change in therapy or IBD-related hospitalization or surgery. Biomarkers were tested in a derivation cohort, and their performance was examined in an independent validation cohort. RESULTS: Our prospective cohort study included 164 patients with IBD (108 with Crohn disease, 56 with ulcerative colitis). Upon follow-up for a median of 1 year, 22 patients (13.4%) experienced a relapse. Three protein biomarkers (interleukin-10, glial cell line-derived neurotrophic factor, and T-cell surface glycoprotein CD8 alpha chain) and 4 metabolomic markers (propionyl-L-carnitine, carnitine, sarcosine, and sorbitol) were associated with relapse in multivariable models. Proteomic and metabolomic risk scores independently predicted relapse with a combined area under the curve of 0.83. A high proteomic risk score (odds ratio = 9.11; 95% confidence interval, 1.90-43.61) or metabolomic risk score (odds ratio = 5.79; 95% confidence interval, 1.24-27.11) independently predicted a higher risk of relapse over 2 years. Fecal metagenomics showed an increased abundance of Proteobacteria (P = 0.0019, q = 0.019) and Fusobacteria (P = 0.0040, q = 0.020) and at the species level Lachnospiraceae_bacterium_2_1_58FAA (P = 0.000008, q = 0.0009) among the relapses. CONCLUSIONS: Proteomic, metabolomic, and microbial biomarkers identify a proinflammatory state in quiescent IBD that predisposes to clinical relapse.
BACKGROUND: Inflammatory bowel diseases (IBD) are characterized by intermittent relapses, and their course is heterogeneous and unpredictable. Our aim was to determine the ability of protein, metabolite, or microbial biomarkers to predict relapse in patients with quiescent disease. METHODS: This prospective study enrolled patients with quiescent Crohn disease and ulcerative colitis, defined as the absence of clinical symptoms (Harvey-Bradshaw Index ≤ 4, Simple Clinical Colitis Activity Index ≤ 2) and endoscopic remission within the prior year. The primary outcome was relapse within 2 years, defined as symptomatic worsening accompanied by elevated inflammatory markers resulting in a change in therapy or IBD-related hospitalization or surgery. Biomarkers were tested in a derivation cohort, and their performance was examined in an independent validation cohort. RESULTS: Our prospective cohort study included 164 patients with IBD (108 with Crohn disease, 56 with ulcerative colitis). Upon follow-up for a median of 1 year, 22 patients (13.4%) experienced a relapse. Three protein biomarkers (interleukin-10, glial cell line-derived neurotrophic factor, and T-cell surface glycoprotein CD8 alpha chain) and 4 metabolomic markers (propionyl-L-carnitine, carnitine, sarcosine, and sorbitol) were associated with relapse in multivariable models. Proteomic and metabolomic risk scores independently predicted relapse with a combined area under the curve of 0.83. A high proteomic risk score (odds ratio = 9.11; 95% confidence interval, 1.90-43.61) or metabolomic risk score (odds ratio = 5.79; 95% confidence interval, 1.24-27.11) independently predicted a higher risk of relapse over 2 years. Fecal metagenomics showed an increased abundance of Proteobacteria (P = 0.0019, q = 0.019) and Fusobacteria (P = 0.0040, q = 0.020) and at the species level Lachnospiraceae_bacterium_2_1_58FAA (P = 0.000008, q = 0.0009) among the relapses. CONCLUSIONS: Proteomic, metabolomic, and microbial biomarkers identify a proinflammatory state in quiescent IBD that predisposes to clinical relapse.
Authors: Katherine A Dunn; Jessica Moore-Connors; Brad MacIntyre; Andrew W Stadnyk; Nikhil A Thomas; Angela Noble; Gamal Mahdi; Mohsin Rashid; Anthony R Otley; Joseph P Bielawski; Johan Van Limbergen Journal: Inflamm Bowel Dis Date: 2016-12 Impact factor: 5.325
Authors: Maria Laura Santoru; Cristina Piras; Antonio Murgia; Vanessa Palmas; Tania Camboni; Sonia Liggi; Ivan Ibba; Maria Antonia Lai; Sandro Orrù; Sylvain Blois; Anna Lisa Loizedda; Julian Leether Griffin; Paolo Usai; Pierluigi Caboni; Luigi Atzori; Aldo Manzin Journal: Sci Rep Date: 2017-08-25 Impact factor: 4.379
Authors: Raina Shivashankar; William J Tremaine; W Scott Harmsen; Edward V Loftus Journal: Clin Gastroenterol Hepatol Date: 2016-11-14 Impact factor: 11.382
Authors: Giuseppe Merra; Giovanni Gasbarrini; Lucrezia Laterza; Marco Pizzoferrato; Andrea Poscia; Franco Scaldaferri; Vincenzo Arena; Francesca Fiore; Achille Cittadini; Alessandro Sgambato; Francesco Franceschi; Antonio Gasbarrini Journal: World J Gastroenterol Date: 2012-09-28 Impact factor: 5.742
Authors: Jordan C Langston; Michael T Rossi; Qingliang Yang; William Ohley; Edwin Perez; Laurie E Kilpatrick; Balabhaskar Prabhakarpandian; Mohammad F Kiani Journal: Vasc Biol Date: 2022-04-07
Authors: Alexandra J Noble; Rachel V Purcell; Alex T Adams; Ying K Lam; Paulina M Ring; Jessica R Anderson; Amy J Osborne Journal: Front Genet Date: 2022-02-08 Impact factor: 4.599
Authors: Carlos G Gonzalez; Robert H Mills; Qiyun Zhu; Consuelo Sauceda; Rob Knight; Parambir S Dulai; David J Gonzalez Journal: Microbiome Date: 2022-08-24 Impact factor: 16.837