title: Imbalance of bacteriome profiles within the Finnish Diabetes Prediction and Prevention study: Parallel use of 16S profiling and virome sequencing in stool samples from children with islet autoimmunity and matched controls.
abstract: BACKGROUND
  We set out to explore associations between the stool bacteriome profiles and early-onset islet autoimmunity, taking into account the interactions with the virus component of the microbiome.
  
  
  METHODS
  Serial stool samples were longitudinally collected from 18 infants and toddlers with early-onset islet autoimmunity (median age 17.4 months) followed by type 1 diabetes, and 18 tightly matched controls from the Finnish Diabetes Prediction and Prevention (DIPP) cohort. Three stool samples were analyzed, taken 3, 6, and 9 months before the first detection of serum autoantibodies in the case child. The risk of islet autoimmunity was evaluated in relation to the composition of the bacteriome 16S rDNA profiles assessed by mass sequencing, and to the composition of DNA and RNA viromes.
  
  
  RESULTS
  Four operational taxonomic units were significantly less abundant in children who later on developed islet autoimmunity as compared to controls-most markedly the species of Bacteroides vulgatus and Bifidobacterium bifidum. The alpha or beta diversity, or the taxonomic levels of bacterial phyla, classes or genera, showed no differences between cases and controls. A correlation analysis suggested a possible relation between CrAssphage signals and quantities of Bacteroides dorei. No apparent associations were seen between development of islet autoimmunity and sequences of yet unknown origin.
  
  
  CONCLUSIONS
  The results confirm previous findings that an imbalance within the prevalent Bacteroides genus is associated with islet autoimmunity. The detected quantitative relation of the novel "orphan" bacteriophage CrAssphage with a prevalent species of the Bacteroides genus may exemplify possible modifiers of the bacteriome.
authors.affiliation: Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic.
authors.forename: Ondrej
authors.initials: O
authors.lastname: Cinek
authors.affiliation: Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic.
authors.forename: Lenka
authors.initials: L
authors.lastname: Kramna
authors.affiliation: BioMediTech, Computational Biology, University of Tampere, Tampere, Finland.
authors.forename: Jake
authors.initials: J
authors.lastname: Lin
authors.affiliation: School of Medicine, Department of Virology, University of Tampere, Tampere, Finland.
authors.forename: Sami
authors.initials: S
authors.lastname: Oikarinen
authors.affiliation: Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic.
authors.forename: Katerina
authors.initials: K
authors.lastname: Kolarova
authors.affiliation: Immunogenetics Laboratory, University of Turku and Turku University Hospital, Turku, Finland.
authors.forename: Jorma
authors.initials: J
authors.lastname: Ilonen
authors.affiliation: Department of Pediatrics and Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.|Department of Pediatrics and Adolescent Medicine, Turku University Hospital, Turku, Finland.
authors.forename: Olli
authors.initials: O
authors.lastname: Simell
authors.affiliation: Department of Pediatrics, University of Oulu and Oulu University Hospital, Oulu, Finland.
authors.forename: Riitta
authors.initials: R
authors.lastname: Veijola
authors.affiliation: School of Health Sciences, University of Tampere, Tampere, Finland.
authors.forename: Reija
authors.initials: R
authors.lastname: Autio
authors.affiliation: School of Medicine, Department of Virology, University of Tampere, Tampere, Finland.|Fimlab Laboratories, Pirkanmaa Hospital District, Tampere, Finland.
authors.forename: Heikki
authors.initials: H
authors.lastname: Hyöty
mesh_terms: D001327:Autoimmune Diseases / Q000097:blood / Q000453:epidemiology / Q000209:etiology* / Q000276:immunology; D015551:Autoimmunity; D001435:Bacteriophages / Q000145:classification / Q000276:immunology* / Q000302:isolation & purification; D001439:Bacteroides / Q000145:classification / Q000276:immunology* / Q000302:isolation & purification / Q000821:virology; D016022:Case-Control Studies; D002648:Child; D015331:Cohort Studies; D019295:Computational Biology; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000453:epidemiology / Q000209:etiology* / Q000276:immunology; D064806:Dysbiosis / Q000276:immunology / Q000382:microbiology / Q000503:physiopathology* / Q000821:virology; D005243:Feces / Q000382:microbiology / Q000821:virology; D005260:Female; D005387:Finland / Q000453:epidemiology; D000069196:Gastrointestinal Microbiome / Q000276:immunology*; D006785:Hospitals, University; D006801:Humans; D007515:Islets of Langerhans / Q000276:immunology; D008137:Longitudinal Studies; D008297:Male; D058889:Molecular Typing; D010802:Phylogeny; D011446:Prospective Studies; D012329:RNA, Bacterial / Q000737:chemistry / Q000378:metabolism; D012336:RNA, Ribosomal, 16S / Q000737:chemistry / Q000378:metabolism; D012367:RNA, Viral / Q000737:chemistry / Q000378:metabolism; D012306:Risk
chemical_list: D012329:RNA, Bacterial; D012336:RNA, Ribosomal, 16S; D012367:RNA, Viral
keywords: CrAssphage; association; microbiome; virome