The microbial diversity of newly diagnosed diabetics is different from that of healthy non-diabetics, although there is no major difference in prediabetics.

– By Kranti Karande

Type 2 diabetes (T2D) is the most common type of diabetes. People who have T2D are said to have insulin resistance. T2D is a chronic condition that affects blood sugar (glucose) absorption and lipid metabolism.

Recently the gut microbiome was identified as an important factor for T2D development. Disruption of the balance between gut microbes has been linked to the development of metabolic diseases, in particular T2D, obesity and cardiovascular disorders. Some of the earlier studies observed dissimialrity between the gut microbiome of diabetics, prediabetics, and healthy nondiabetic individuals, although very few investigated the gut microbiome of treatment-naive individuals with T2D.

In this study, scientists have analyzed ND, PreDMs, NewDMs, and KnownDMs gut microbiome to understand and identify differences in the T2D, and prediabetes-associated microbial community. The scientists also looked at the community changes in microbial association networks and identified genera which are contributing for the transition from healthy (control) to diabetic state here called as driver taxa. They also analyzed the association of a wide array of serum biomarkers with genera, which were differentially abundant and were also found to be contributing for the major changes in the gut microbiome of T2D individuals .

In this study, a total of 102 subjects were studied, and they looked at the gut microbiota of prediabetics (PreDMs) (n= 17), newly diagnosed diabetics (NewDMs) (n = 11), and diabetics on antidiabetic treatment (KnownDMs) (n = 39) and compared them with healthy nondiabetics (ND) (n= 35). Twenty-five different serum biomarkers were measured to assess the status of diabetes and their association with gut microbiota.

The research identified nine separate genera in four sample groups as having differential abundance. Among them, Akkermansia, Blautia, and Ruminococcus were found to be significantly decreased, while Lactobacillus was increased in NewDMs compared to ND and recovered in KnownDMs. Akkermansia was inversely correlated with HbA1c and positively correlated with total antioxidants. Compared to ND, there was increased abundance of Megasphaera, Escherichia, and Acidaminococcus and decreased abundance of Sutterella in KnownDMs.

Among many taxa known to act as community drivers during disease progression, it was observed that genus Sutterella is a common driver taxon among all diabetic groups. On the basis of the results of random forest analysis (methodology) , they discovered that the serum metabolites fasting glucose, HbA1c, methionine, and total antioxidants were highly discriminating factors among studied groups. The compiled data showed that the gut microbial diversity of NewDMs is substantially different from that of ND but not of PreDMs. Interestingly, after anti-diabetic treatment, the microbial diversity of KnownDMs tends to recover toward that of ND.

Gut microbiota is thought to play a role in the development of the disease, and previous studies have documented a microbiome dysbiosis association with T2D. In this study, scientists have attempted to investigate gut microbiota of ND, PreDMs, NewDMs, and KnownDMs. They found that the genera Akkermansia and Blautia decreased significantly in treatment-naive diabetics and were restored in KnownDMs on antidiabetic treatment. Understanding the transition of microbiota and its association with serum biomarkers in diabetics with different disease states may pave the way for new therapeutic approaches for T2D.

Twenty-five different serum biomarkers were checked and compared with the gut microbiota to assess the different states of diabetes. Targeted 16S rRNA amplicon sequencing was used to assess the microbial diversity, community shuffling, and identification of driver taxa for the disease state. They have investigated relationships between a wide array of serum biomarkers responsible for progression of T2D with significantly diverged and differentially abundant taxa in each study group. Significantly different patterns were observed in the gut microbiota of PreDMs, NewDMs, and KnownDMs compared to ND. In KnownDMs, abundance of some microbial taxa was found to be similar to that of ND group.

Since oxidative stress is known to be involved in the establishment of insulin resistance and diabetic complications , they also measured total antioxidant capacity and lipid peroxides, a marker of oxidative damage to lipids in the blood. Interstingly, they found a significant decrease in total antioxidant capacity and increase in lipid peroxidation in treatment-naive NewDMs but not in PreDMs. In KnownDMs on treatment with metformin, an increase in total antioxidant capacity and decrease in lipid peroxidation were observed.

These findings show differences in the gut microbiome in PreDMs, NewDMs, and KnownDMs compared to ND. In PreDMs, the gut microbiota doesn’t show a significant difference when compared with ND, while in NewDMs, both abundance and diversity have changed significantly, which seems to be restored to some degree in KnownDMs on antidiabetic care.

Reference: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112960/pdf/mSystems.00578-19.pdf

Microbiome of indian patrilineal families reveal association with age

-By Kranti Karande

The human microbiome plays an important role in maintaining stable health conditions. It is influenced by age, geography, diet and other factors. This study was aimed at understanding the association of composition of the human microbiome with age in Indian joint families formed through paternal descendants. Oral, skin and stool microbiome of a total of 54 healthy individuals from 6 joint families with three generations were studied and characterized using 16S rRNA gene based methodology. The study population had matching dietary, social habits, hygiene and sanitation habits, economic status and geographic position.  This study highlights that precise and perceptible association of age with microbiome can be drawn when other causal factors are kept constant. 

Human microbiome has evolved with the host and its ancestors for millions of years and it plays an important role in maintaining a good health by performing various functions such as digestion, protection against pathogen colonization to host immunity and regulation of central nervous system. The human microbiome is affected by various factors such as ethnicity, age, diet etc. Hence, it is important to study the same population for the exploration of a precise association of age and microbiome. This study of genetically linked individuals of different generations having similar diet, ethnicity and location will help to understand the ability of microbiome to persevere with increasing age and how they progress with the age. 

Approximately 99% of the gut microbiome was constituted of 5 bacterial phyla. Total of 174 bacterial genera were noted to be present out of which 5 contributed to 77% of the gut microbiome. The oral microbiome showed comparatively higher abundance of some specific bacterial phyla.  Bacterial genera prevalent in 95% of the study population with more than 0.1% abundance were considered as a part of the core microbiome. Gut, Oral and skin microbiome had 3, 13 and 2 core microbiome genera present in the samples respectively. 

Microbiome community structure of gut, oral and skin samples was investigated across three generations (age groups). Gut microbiome of each generation had a unique set of bacterial genera present in abundance out of the prevalent genera for the specific age group. High abundance of few bacterial taxa was recorded in particular age groups in the skin microbiome samples also. Comparative microbiome analysis in three age groups did not show significant difference in abundance of bacterial genera in the gut and skin microbiome. However, the oral microbiome showed significant variations in the abundance of genera Dialister, Fusobacterium, Streptococcus, Selenomonas, Filifactor and Treponema. 

Age-associated changes in the microbiome were further analyzed based on differentially abundant OTUs (a methodology). After performing a correlation analysis it was revealed that phylum Proteobacteria in gut microbiome and phylum Fusobacteria in oral microbiome showed higher abundance with increasing age. However, in the skin microbiome, no such statistically significant correlations were noted. Amongst the total 171 bacterial genera in the gut microbiome, only genus Bacteroides showed age-associated changes. Decreased abundance of Bacteroides was noted with increasing age.

Dietary information of the study population was collected using the food frequency questionnaire (FFQ) and this information is subsequently translated into the daily intake of carbohydrates, proteins, fats, lipids, fibers and calories with the help of a nutritionist. Detailed analysis showed that carbohydrates provide about 74%, 81% and 80% calories in the first, second and third generation members, respectively. Further analysis showed no significant correlation across generations suggesting similar microbiome structure and dietary pattern. This emphasizes the fact that overall homogeneity in the diet helps in maintaining the microbial state.

Bacteria with high fiber degrading potential were found highly abundant in first generation members while the second generation members showed an abundance of metabolism boosting gut microbiome. Early gut colonizers and Bacteroides were higher in the third generation members. The skin microbiome also showed age related changes in abundance of bacterial taxa present. With the increasing age, physiological changes occur in the skin structure which explains the association of key bacterial taxa in the members of the respective age groups. Similarly, in the oral microbiome, Fusobacteria was found to increase with increasing age. It was observed that a negative correlation in the abundance of Bacteroides with age; this is in contrast to previous studies demonstrating the higher abundance of genus Bacteroides with increasing age. Age related changes in oral microbiome could be associated with physiological changes occurring with increasing age in the oral cavity. 

In conclusion, this study particularly highlights the precise and perceptible association of age with the microbiome. The findings suggest that core taxa constitute more than 75% of the gut and oral microbiome, while only 67% of the skin microbiome, indicating a larger variability of the microbiome present on the skin. The baseline data presented from a healthy Indian sub-population can be used as reference for further studies including diabetes, obesity and inflammatory diseases. 

Reference: https://www.nature.com/articles/s41598-020-62195-5