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Updated: Oct 26, 2025

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
Association of Insulin Resistance and Type 2 Diabetes With Gut Microbial Diversity: A Microbiome-Wide Analysis From
Zhangling Chen1,2, Djawad Radjabzadeh3, Lianmin Chen4,5,6
1Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands.
Importance:
Previous studies have indicated that gut microbiome may be associated with development of type 2 diabetes. However, these studies are limited by small sample size and insufficient for confounding. Furthermore, which specific taxa play a role in the development of type 2 diabetes remains unclear.
Objective:
To examine associations of gut microbiome composition with insulin resistance and type 2 diabetes in a large population-based setting controlling for various sociodemographic and lifestyle factors.
Design, Setting, And Participants:
This cross-sectional analysis included 2166 participants from 2 Dutch population-based prospective cohorts: the Rotterdam Study and the LifeLines-DEEP study.
Exposures:
The 16S ribosomal RNA method was used to measure microbiome composition in stool samples collected between January 1, 2012, and December 31, 2013. The α diversity (Shannon, richness, and Inverse Simpson indexes), β diversity (Bray-Curtis dissimilarity matrix), and taxa (from domain to genus level) were identified to reflect gut microbiome composition.
Main Outcomes And Measures:
Associations among α diversity, β diversity, and taxa with the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and with type 2 diabetes were examined. Glucose and insulin were measured to calculate the HOMA-IR. Type 2 diabetes cases were identified based on glucose levels and medical records from January 2012 to December 2013. Analyses were adjusted for technical covariates, lifestyle, sociodemographic, and medical factors. Data analysis was performed from January 1, 2018, to December 31, 2020.
Results:
There were 2166 participants in this study: 1418 from the Rotterdam Study (mean [SD] age, 62.4 [5.9] years; 815 [57.5%] male) and 748 from the LifeLines-DEEP study (mean [SD] age, 44.7 [13.4] years; 431 [57.6%] male); from this total, 193 type 2 diabetes cases were identified. Lower microbiome Shannon index and richness were associated with higher HOMA-IR (eg, Shannon index, -0.06; 95% CI, -0.10 to -0.02), and patients with type 2 diabetes had a lower richness than participants without diabetes (odds ratio [OR], 0.93; 95% CI, 0.88-0.99). The β diversity (Bray-Curtis dissimilarity matrix) was associated with insulin resistance (R2 = 0.004, P = .001 in the Rotterdam Study and R2 = 0.005, P = .002 in the LifeLines-DEEP study). A total of 12 groups of bacteria were associated with HOMA-IR or type 2 diabetes. Specifically, a higher abundance of Christensenellaceae (β = -0.08; 95% CI, -0.12 to -0.03: P < .001), Christensenellaceae R7 group (β = -0.07; 95% CI, -0.12 to -0.03; P < .001), Marvinbryantia (β = -0.07; 95% CI, -0.11 to -0.03; P < .001), Ruminococcaceae UCG005 (β = -0.09; 95% CI, -0.13 to -0.05; P < .001), Ruminococcaceae UCG008 (β = -0.07; 95% CI, -0.11 to -0.03; P < .001), Ruminococcaceae UCG010 (β = -0.08; 95% CI, -0.12 to -0.04; P < .001), or Ruminococcaceae NK4A214 group (β = -0.09; 95% CI, -0.13 to -0.05; P < .001) was associated with lower HOMA-IR. A higher abundance of Clostridiaceae 1 (OR, 0.51; 95% CI, 0.41-0.65; P < .001), Peptostreptococcaceae (OR, 0.56; 95% CI, 0.45-0.70; P < .001), C sensu stricto 1 (OR, 0.51; 95% CI, 0.40-0.65; P < .001), Intestinibacter (OR, 0.60; 95% CI, 0.48-0.76; P < .001), or Romboutsia (OR, 0.55; 95% CI, 0.44-0.70; P < .001) was associated with less type 2 diabetes. These bacteria are all known to produce butyrate.
Conclusions And Relevance:
In this cross-sectional study, higher microbiome α diversity, along with more butyrate-producing gut bacteria, was associated with less type 2 diabetes and with lower insulin resistance among individuals without diabetes. These findings could help provide insight into the etiology, pathogenesis, and treatment of type 2 diabetes.
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