Gut Microbial Signatures for Glycemic Responses of GLP-1 Receptor Agonists in Type 2 Diabetic Patients: A Pilot Study

BackgroundsGlucagon-like peptide-1 receptor agonist (GLP-1 RA) is probably one of more effective antidiabetic agents in treatment of type 2 diabetes mellitus (T2D). However, the heterogenicity in responses to GLP-1 RA may be potentially related to gut microbiota, although no human evidence has been published. This pilot study aims to identify microbial signatures associated with glycemic responses to GLP-1 RA.Materials and MethodsMicrobial compositions of 52 patients with T2D receiving GLP-1 RA were determined by 16S rRNA amplicon sequencing. Bacterial biodiversity was compared between responders versus non-responders. Pearson’s correlation and random forest tree algorithm were used to identify microbial features of glycemic responses in T2D patients and multivariable linear regression models were used to validate clinical relevance.ResultsBeta diversity significantly differed between GLP-1 RA responders (n = 34) and non-responders (n = 18) (ADONIS, P = 0.004). The top 17 features associated with glycohemoglobin reduction had a 0.96 diagnostic ability, based on area under the ROC curve: Bacteroides dorei and Roseburia inulinivorans, the two microbes having immunomodulation effects, along with Lachnoclostridium sp. and Butyricicoccus sp., were positively correlated with glycemic reduction; Prevotella copri, the microbe related to insulin resistance, together with Ruminococcaceae sp., Bacteroidales sp., Eubacterium coprostanoligenes sp., Dialister succinatiphilus, Alistipes obesi, Mitsuokella spp., Butyricimonas virosa, Moryella sp., and Lactobacillus mucosae had negative correlation. Furthermore, Bacteroides dorei, Lachnoclostridium sp. and Mitsuokella multacida were significant after adjusting for baseline glycohemoglobin and C-peptide concentrations, two clinical confounders.ConclusionsUnique gut microbial signatures are associated with glycemic responses to GLP-RA treatment and reflect degrees of dysbiosis in T2D patients.

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A pilot study to detect oxidative stress in type 2 diabetic patients

Free Radical Biology and Medicine ◽

10.1016/j.freeradbiomed.2016.04.133 ◽

2016 ◽

Vol 96 ◽

pp. S62

Author(s):

Ayse C. Hamamcioglu ◽

Zehra Safi-Oz ◽

Yasin Hazer ◽

Dilek Arpaci ◽

Furuzan Kokturk

Keyword(s):

Oxidative Stress ◽

Pilot Study ◽

Diabetic Patients ◽

Type 2 Diabetic Patients ◽

Type 2 Diabetic

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Pilot study: Hypoglycemic and antiglycation activities of bitter melon (Momordica charantia L.) in type 2 diabetic patients

Journal of Pharmacy Research ◽

10.1016/j.jopr.2013.08.007 ◽

2013 ◽

Vol 6 (8) ◽

pp. 859-864 ◽

Cited By ~ 8

Author(s):

Wilai Trakoon-osot ◽

Uthai Sotanaphun ◽

Pariya Phanachet ◽

Supatra Porasuphatana ◽

Umaporn Udomsubpayakul ◽

...

Keyword(s):

Pilot Study ◽

Momordica Charantia ◽

Diabetic Patients ◽

Bitter Melon ◽

Type 2 Diabetic Patients ◽

Type 2 Diabetic

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Comparing postprandial efficacy in type 2 diabetic patients receiving mitiglinide and sitagliptin by using continuous glucose monitoring: a pilot study

Expert Opinion on Pharmacotherapy ◽

10.1517/14656566.2014.970531 ◽

2014 ◽

Vol 15 (17) ◽

pp. 2479-2485 ◽

Cited By ~ 4

Author(s):

Kiyotaka Ando ◽

Rimei Nishimura ◽

Chiaki Seo ◽

Daisuke Tsujino ◽

Masaya Sakamoto ◽

...

Keyword(s):

Pilot Study ◽

Continuous Glucose Monitoring ◽

Glucose Monitoring ◽

Diabetic Patients ◽

Type 2 Diabetic Patients ◽

Type 2 Diabetic

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Assessing Quality of Life Related to Oral Health and Glycemic Control in Type 2 Diabetic Patients - A Pilot Study Using GOHAI Test

Clinical Medicine Research ◽

10.11648/j.cmr.20200901.12 ◽

2020 ◽

Vol 9 (1) ◽

pp. 6

Author(s):

Andreea Wagner ◽

Elena Preoteasa ◽

Cristina Teodora Preoteasa

Keyword(s):

Quality Of Life ◽

Oral Health ◽

Pilot Study ◽

Glycemic Control ◽

Diabetic Patients ◽

Type 2 Diabetic Patients ◽

Type 2 Diabetic

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A pilot study on genetic variation in purine-rich elements in the nephrin gene promoter in type 2 diabetic patients

Biological Research ◽

10.4067/s0716-97602007000400010 ◽

2007 ◽

Vol 40 (3) ◽

Author(s):

RODRIGO GONZÁLEZ ◽

ARES TIRADO ◽

MONSERRAT BALANDA ◽

MIRIAM ALVO ◽

INÉS BARQUÍN ◽

...

Keyword(s):

Genetic Variation ◽

Pilot Study ◽

Gene Promoter ◽

Diabetic Patients ◽

Type 2 Diabetic Patients ◽

Type 2 Diabetic

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Distinct Gut Microbiota Induced by Different Fat-to-Sugar-Ratio High-Energy Diets Share Similar Pro-obesity Genetic and Metabolite Profiles in Prediabetic Mice

mSystems ◽

10.1128/msystems.00219-19 ◽

2019 ◽

Vol 4 (5) ◽

Cited By ~ 3

Author(s):

Kai Shan ◽

Hongyan Qu ◽

Keru Zhou ◽

Liangfang Wang ◽

Congmin Zhu ◽

...

Keyword(s):

Metabolic Syndrome ◽

Gut Microbiota ◽

Early Stage ◽

Amplicon Sequencing ◽

High Energy ◽

Diabetic Patients ◽

Type 2 Diabetic Patients

ABSTRACT Gut microbiota play important roles in host metabolism, especially in diabetes. However, why different diets lead to similar diabetic states despite being associated with different microbiota is not clear. Mice were fed two high-energy diets (HED) with the same energy density but different fat-to-sugar ratios to determine the associations between the microbiota and early-stage metabolic syndrome. The two diets resulted in different microbiota but similar diabetic states. Interestingly, the microbial gene profiles were not significantly different, and many common metabolites were identified, including l-aspartic acid, cholestan-3-ol (5β, 3α), and campesterol, which have been associated with lipogenesis and inflammation. Our study suggests that different metabolic-syndrome-inducing diets may result in different microbiota but similar microbiomes and metabolomes. This suggests that the metagenome and metabolome are crucial for the prognosis and pathogenesis of obesity and metabolic syndrome. IMPORTANCE Various types of diet can lead to type 2 diabetes. The gut microbiota in type 2 diabetic patients are also different. So, two questions arise: whether there are any commonalities between gut microbiota induced by different pro-obese diets and whether these commonalities lead to disease. Here we found that high-energy diets with two different fat-to-sugar ratios can both cause obesity and prediabetes but enrich different gut microbiota. Still, these different gut microbiota have similar genetic and metabolite compositions. The microbial metabolites in common between the diets modulate lipid accumulation and macrophage inflammation in vivo and in vitro. This work suggests that studies that only use 16S rRNA amplicon sequencing to determine how the microbes respond to diet and associate with diabetic state are missing vital information.

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