Alterations in Intestinal Microbiota Correlate With Susceptibility to Type 1 Diabetes Original paper

Researched by:

  • Dr. Umar ID
    Dr. Umar

    User avatarClinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.

    Read More

January 16, 2026

Researched by:

  • Dr. Umar ID
    Dr. Umar

    User avatarClinical Pharmacist and Clinical Pharmacy Master’s candidate focused on antibiotic stewardship, AI-driven pharmacy practice, and research that strengthens safe and effective medication use. Experience spans digital health research with Bloomsbury Health (London), pharmacovigilance in patient support programs, and behavioral approaches to mental health care. Published work includes studies on antibiotic use and awareness, AI applications in medicine, postpartum depression management, and patient safety reporting. Developer of an AI-based clinical decision support system designed to enhance antimicrobial stewardship and optimize therapeutic outcomes.

    Read More

Last Updated: 2015-01-01

Microbiome Signatures identifies and validates condition-specific microbiome shifts and interventions to accelerate clinical translation. Our multidisciplinary team supports clinicians, researchers, and innovators in turning microbiome science into actionable medicine.

Karen Pendergrass

Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease—four years before the first published case study.

Location
United States of America
Sample Site
Feces
Species
Homo sapiens

What was studied?

Gut microbiome in type 1 diabetes risk was examined in a U.S. cross-sectional cohort study testing whether intestinal bacterial community differences track with islet autoimmunity and early type 1 diabetes (T1D). Investigators profiled stool microbiota using high-throughput 16S rRNA (V4) sequencing, then compared relative abundances across four clinically defined groups while adjusting for age, sex, HLA-DR3/DR4 status, and autoantibody status. The primary goal was not to “predict diabetes” from a single organism, but to identify reproducible taxonomic shifts—candidate microbiome signatures—that align with stages from genetic/familial susceptibility through seroconversion (islet autoantibodies) to new-onset T1D.

Who was studied?

Participants lived in the Denver metro area and spanned children through adults, enabling stage-based comparisons rather than a single case-control snapshot. The study included 21 islet autoantibody–positive individuals (1–4 autoantibodies), 32 autoantibody-negative first-degree relatives (FDRs) of people with islet autoimmunity, 35 individuals with new-onset T1D (≤6 months from diagnosis), and 23 unrelated healthy controls with no family history of autoimmunity. Recent antibiotic exposure (within 4 weeks), known infections, or gastrointestinal disorders were exclusionary to reduce confounding, and HLA risk alleles were common in the at-risk groups, as expected for a susceptibility-enriched design.

Most important findings

Across groups, overall community structure looked broadly similar and alpha diversity did not differ between seropositive and seronegative FDRs, suggesting that stage-associated signals were driven by specific taxa rather than a global loss of diversity. After covariate adjustment, seropositive individuals differed from seronegative FDRs in four taxa: higher Catenibacterium (Firmicutes), higher Prevotellaceae and RC9-gut-group (Bacteroidetes), and lower “Bacteroidetes other” (unclassified within the phylum). When extending comparisons to unrelated healthy controls, two genera stood out as relatively enriched in controls but reduced in genetically susceptible and/or autoimmune states: Lactobacillus and Staphylococcus (both Firmicutes-associated in the paper’s analyses). Multivariate canonical discriminant analysis further suggested clustering of seropositive subjects with seronegative FDRs (a “familial/genetic-risk-like” microbiome pattern) distinct from both new-onset T1D and unrelated controls. In an exploratory subanalysis (limited power), multiple-autoantibody seropositive subjects trended toward markedly higher Bacteroides and Akkermansia and much lower Prevotella, plus reductions in several short-chain–fatty-acid–linked genera (e.g., Butyricimonas, Coprococcus, Butyrivibrio), consistent with a shift away from fiber-fermenting ecology in higher-risk seropositivity.

Microbe/taxonAssociation with T1D risk stage
LactobacillusLower in seropositive/new-onset vs unrelated healthy controls
StaphylococcusLower in seropositive/new-onset vs unrelated healthy controls
CatenibacteriumHigher in seropositive vs seronegative FDRs

Key implications

Clinically, the work argues for “stage-aware” microbiome signatures: modest, taxon-level shifts (not sweeping dysbiosis) may accompany susceptibility and seroconversion, while new-onset T1D may show a different profile—potentially influenced by inflammation and post-diagnosis diet changes. For a microbiome signatures database, the most actionable candidates are the directionality of Catenibacterium/Prevotellaceae/RC9-gut-group in seropositivity and the relative depletion of Lactobacillus and Staphylococcus in at-risk/new-onset states, plus the higher-risk (multiple autoantibody) pattern of increased Bacteroides/Akkermansia with decreased Prevotella and putative SCFA producers. The study’s cross-sectional design limits causality; longitudinal sampling, dietary metadata, and strain-/function-level profiling will be needed before translating these signals into preventive counseling or microbiome-targeted interventions.

Citation

Aimon K. Alkanani, Naoko Hara, Peter A. Gottlieb, Diana Ir, Charles E. Robertson, Brandie D. Wagner, Daniel N. Frank, Danny Zipris; Alterations in Intestinal Microbiota Correlate With Susceptibility to Type 1 Diabetes. Diabetes 1 October 2015

Diabetes Type I

Type 1 diabetes is an autoimmune condition in which pancreatic β-cells are destroyed, causing insulin deficiency and hyperglycemia. It typically arises in youth and requires lifelong insulin therapy. This article provides a clinician-focused review of T1D’s causes, mechanisms, complications, diagnosis, and management, including emerging multi-omics insights.

Short-chain Fatty Acids (SCFAs)

Short-chain fatty acids are microbially derived metabolites that regulate epithelial integrity, immune signaling, and microbial ecology. Their production patterns and mechanistic roles provide essential functional markers within microbiome signatures and support the interpretation of MBTIs, MMAs, and systems-level microbial shifts across clinical conditions.

Short-chain Fatty Acids (SCFAs)

Short-chain fatty acids are microbially derived metabolites that regulate epithelial integrity, immune signaling, and microbial ecology. Their production patterns and mechanistic roles provide essential functional markers within microbiome signatures and support the interpretation of MBTIs, MMAs, and systems-level microbial shifts across clinical conditions.

Join the Roundtable

Contribute to published consensus reports, connect with top clinicians and researchers, and receive exclusive invitations to roundtable conferences.