Type 2 Diabetes Associated with Arrhythmic Daily Gut Microbe
By LabMedica International staff writers Posted on 16 Jul 2020 |

Image: Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes (Photo courtesy of Technical University of Munich).
Type 2 diabetes (T2D), formerly known as adult-onset diabetes, is a form of diabetes that is characterized by high blood sugar, insulin resistance, and relative lack of insulin. Common symptoms include increased thirst, frequent urination, and unexplained weight loss.
Several studies found that obesity-related changes in the gut microbiota are associated with low grade inflammation, which supports a close link between the immune and metabolic systems throughout the gut microbiota. There are several mechanisms that relate microbiota to the onset of insulin resistance and diabetes, including changes in bowel permeability, endotoxemia, interaction with bile acids, changes in the proportion of brown adipose tissue.
A large team of scientists collaborating with the Technical University of Munich (Freising, Germany) used high-throughput 16S ribosomal RNA gene sequencing to profile gut microbial community composition in fecal samples from 1,976 individuals from Germany enrolled in the prospective KORA population study, detecting distinct levels of specific pathogens across the day in individuals with available time of defecation data.
By analyzing the diurnal gut microbiome dynamics, the team noted that individuals that had T2D or were obese appeared to lose gut oscillations that involved changes in microbiome levels of dozens of gut bacteria. The authors noted that while both obesity and T2D coincided with altered gut microbiome oscillations during the span of a day, there were differences in the operational taxa units involved, hinting that weight contributes to T2D risk stratification independent of disrupted circadian rhythms in the microbiome. Shotgun metagenomic analysis functionally linked 26 metabolic pathways to the diurnal oscillation of gut bacteria.
The team went on to verify the 24-hour gut microbe rhythms in nearly 1,400 more German participants sampled at multiple time points. They also used an unsupervised machine learning method to focus in on a set of 13 oscillating gut bacteria with circadian patterns that are upset in individuals with T2D. The bacterial signature showed promise for finding and predicting T2D cases in a subset of 699 participants from the KORA cohort, while additional metagenomic sequence data for a subset of 50 study participants with or without T2D or pre-diabetes, each tested twice five years apart, provided a window into some of the gut microbe genes and pathways that are altered when metabolic disease-related microbe oscillations are upended.
Dirk Haller, PhD, holds the Chair of Nutrition and Immunology and is the senior author of the study, said, “We demonstrated that loss of circadian rhythmicity affects microbiome features related to the onset and progression of T2D and identified bacterial signatures for metabolic risk profiling in human populations.”
The authors concluded that it may be important to take circadian gut microbe oscillations into account to better understand the underlying mechanisms of disease-associated microbiome alterations and to validate risk profiles in prospective cohorts. The study was published on July 2, 2020 in the journal Cell Host & Microbe.
Related Links:
Technical University of Munich
Several studies found that obesity-related changes in the gut microbiota are associated with low grade inflammation, which supports a close link between the immune and metabolic systems throughout the gut microbiota. There are several mechanisms that relate microbiota to the onset of insulin resistance and diabetes, including changes in bowel permeability, endotoxemia, interaction with bile acids, changes in the proportion of brown adipose tissue.
A large team of scientists collaborating with the Technical University of Munich (Freising, Germany) used high-throughput 16S ribosomal RNA gene sequencing to profile gut microbial community composition in fecal samples from 1,976 individuals from Germany enrolled in the prospective KORA population study, detecting distinct levels of specific pathogens across the day in individuals with available time of defecation data.
By analyzing the diurnal gut microbiome dynamics, the team noted that individuals that had T2D or were obese appeared to lose gut oscillations that involved changes in microbiome levels of dozens of gut bacteria. The authors noted that while both obesity and T2D coincided with altered gut microbiome oscillations during the span of a day, there were differences in the operational taxa units involved, hinting that weight contributes to T2D risk stratification independent of disrupted circadian rhythms in the microbiome. Shotgun metagenomic analysis functionally linked 26 metabolic pathways to the diurnal oscillation of gut bacteria.
The team went on to verify the 24-hour gut microbe rhythms in nearly 1,400 more German participants sampled at multiple time points. They also used an unsupervised machine learning method to focus in on a set of 13 oscillating gut bacteria with circadian patterns that are upset in individuals with T2D. The bacterial signature showed promise for finding and predicting T2D cases in a subset of 699 participants from the KORA cohort, while additional metagenomic sequence data for a subset of 50 study participants with or without T2D or pre-diabetes, each tested twice five years apart, provided a window into some of the gut microbe genes and pathways that are altered when metabolic disease-related microbe oscillations are upended.
Dirk Haller, PhD, holds the Chair of Nutrition and Immunology and is the senior author of the study, said, “We demonstrated that loss of circadian rhythmicity affects microbiome features related to the onset and progression of T2D and identified bacterial signatures for metabolic risk profiling in human populations.”
The authors concluded that it may be important to take circadian gut microbe oscillations into account to better understand the underlying mechanisms of disease-associated microbiome alterations and to validate risk profiles in prospective cohorts. The study was published on July 2, 2020 in the journal Cell Host & Microbe.
Related Links:
Technical University of Munich
Latest Pathology News
- Spit Test More Accurate at Identifying Future Prostate Cancer Risk
- DNA Nanotechnology Boosts Sensitivity of Test Strips
- Novel UV and Machine Learning-Aided Method Detects Microbial Contamination in Cell Cultures
- New Error-Corrected Method to Help Detect Cancer from Blood Samples Alone
- "Metal Detector" Algorithm Hunts Down Vulnerable Tumors
- Novel Technique Uses ‘Sugar’ Signatures to Identify and Classify Pancreatic Cancer Cell Subtypes
- Advanced Imaging Reveals Mechanisms Causing Autoimmune Disease
- AI Model Effectively Predicts Patient Outcomes in Common Lung Cancer Type
- AI Model Predicts Patient Response to Bladder Cancer Treatment
- New Laser-Based Method to Accelerate Cancer Diagnosis
- New AI Model Predicts Gene Variants’ Effects on Specific Diseases
- Powerful AI Tool Diagnoses Coeliac Disease from Biopsy Images with Over 97% Accuracy
- Pre-Analytical Conditions Influence Cell-Free MicroRNA Stability in Blood Plasma Samples
- 3D Cell Culture System Could Revolutionize Cancer Diagnostics
- Painless Technique Measures Glucose Concentrations in Solution and Tissue Via Sound Waves
- Skin-Based Test to Improve Diagnosis of Rare, Debilitating Neurodegenerative Disease
Channels
Clinical Chemistry
view channel
‘Brilliantly Luminous’ Nanoscale Chemical Tool to Improve Disease Detection
Thousands of commercially available glowing molecules known as fluorophores are commonly used in medical imaging, disease detection, biomarker tagging, and chemical analysis. They are also integral in... Read more
Low-Cost Portable Screening Test to Transform Kidney Disease Detection
Millions of individuals suffer from kidney disease, which often remains undiagnosed until it has reached a critical stage. This silent epidemic not only diminishes the quality of life for those affected... Read more
New Method Uses Pulsed Infrared Light to Find Cancer's 'Fingerprints' In Blood Plasma
Cancer diagnoses have traditionally relied on invasive or time-consuming procedures like tissue biopsies. Now, new research published in ACS Central Science introduces a method that utilizes pulsed infrared... Read moreMolecular Diagnostics
view channel
Simple Blood Test Improves Heart Attack and Stroke Risk Prediction
Troponin is a protein found in heart muscle cells that is released into the bloodstream when the heart is damaged. High-sensitivity troponin blood tests are commonly used in hospitals to diagnose heart... Read more
Blood Biomarker Test Could Detect Genetic Predisposition to Alzheimer’s
New medications for Alzheimer’s disease, the most common form of dementia, are now becoming available. These treatments, known as “amyloid antibodies,” work by promoting the removal of small deposits from... Read more
Novel Autoantibody Against DAGLA Discovered in Cerebellitis
Autoimmune cerebellar ataxias are strongly disabling disorders characterized by an impaired ability to coordinate muscle movement. Cerebellar autoantibodies serve as useful biomarkers to support rapid... Read more
Gene-Based Blood Test Accurately Predicts Tumor Recurrence of Advanced Skin Cancer
Melanoma, an aggressive form of skin cancer, becomes extremely difficult to treat once it spreads to other parts of the body. For patients with metastatic melanoma tumors that cannot be surgically removed... Read moreHematology
view channel
New Scoring System Predicts Risk of Developing Cancer from Common Blood Disorder
Clonal cytopenia of undetermined significance (CCUS) is a blood disorder commonly found in older adults, characterized by mutations in blood cells and a low blood count, but without any obvious cause or... Read more
Non-Invasive Prenatal Test for Fetal RhD Status Demonstrates 100% Accuracy
In the United States, approximately 15% of pregnant individuals are RhD-negative. However, in about 40% of these cases, the fetus is also RhD-negative, making the administration of RhoGAM unnecessary.... Read moreImmunology
view channel
Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer
Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more
Machine Learning-Enabled Blood Test Predicts Immunotherapy Response in Lymphoma Patients
Chimeric antigen receptor (CAR) T-cell therapy has emerged as one of the most promising recent developments in the treatment of blood cancers. However, over half of non-Hodgkin lymphoma (NHL) patients... Read morePathology
view channel
Spit Test More Accurate at Identifying Future Prostate Cancer Risk
Currently, blood tests that measure the level of a protein called prostate-specific antigen (PSA) are commonly used to identify men at higher risk for prostate cancer. This test is typically used based... Read more
DNA Nanotechnology Boosts Sensitivity of Test Strips
Since the Covid-19 pandemic, most people have become familiar with paper-based rapid test strips, also known as lateral flow immunoassays (LFIAs). These tests are used to quickly detect biomarkers that... Read more
Novel UV and Machine Learning-Aided Method Detects Microbial Contamination in Cell Cultures
Cell therapy holds great potential in treating diseases such as cancers, inflammatory conditions, and chronic degenerative disorders by manipulating or replacing cells to restore function or combat disease.... Read moreTechnology
view channel
Disposable Microchip Technology Could Selectively Detect HIV in Whole Blood Samples
As of the end of 2023, approximately 40 million people globally were living with HIV, and around 630,000 individuals died from AIDS-related illnesses that same year. Despite a substantial decline in deaths... Read more
Pain-On-A-Chip Microfluidic Device Determines Types of Chronic Pain from Blood Samples
Chronic pain is a widespread condition that remains difficult to manage, and existing clinical methods for its treatment rely largely on self-reporting, which can be subjective and especially problematic... Read more
Innovative, Label-Free Ratiometric Fluorosensor Enables More Sensitive Viral RNA Detection
Viruses present a major global health risk, as demonstrated by recent pandemics, making early detection and identification essential for preventing new outbreaks. While traditional detection methods are... Read moreIndustry
view channel
Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions
Cepheid (Sunnyvale, CA, USA), a leading molecular diagnostics company, and Oxford Nanopore Technologies (Oxford, UK), the company behind a new generation of sequencing-based molecular analysis technologies,... Read more
Grifols and Tecan’s IBL Collaborate on Advanced Biomarker Panels
Grifols (Barcelona, Spain), one of the world’s leading producers of plasma-derived medicines and innovative diagnostic solutions, is expanding its offer in clinical diagnostics through a strategic partnership... Read more