Role of gut microbiota in type 2 diabetes pathophysiology.

Colorectal cancer (CRC) accounts for about 10% of all new cancer cases globally. Located at close proximity to the colorectal epithelium, the gut microbiota comprises a large population of microorganisms that interact with host cells to regulate many physiological processes, such as energy harvest, metabolism and immune response. Sequencing studies have revealed microbial compositional and ecological changes in patients with CRC, whereas functional studies in animal models have pinpointed the roles of several bacteria in colorectal carcinogenesis, including Fusobacterium nucleatum and certain strains of Escherichia coli and Bacteroides fragilis. These findings give new opportunities to take advantage of our knowledge on the gut microbiota for clinical applications, such as gut microbiota analysis as screening, prognostic or predictive biomarkers, or modulating microorganisms to prevent cancer, augment therapies and reduce adverse effects of treatment. This Review aims to provide an overview and discussion of the gut microbiota in colorectal neoplasia, including relevant mechanisms in microbiota-related carcinogenesis, the potential of utilizing the microbiota as CRC biomarkers, and the prospect for modulating the microbiota for CRC prevention or treatment. These scientific findings will pave the way to clinically translate the use of gut microbiota for CRC in the near future.

Gut microbiota in colorectal cancer: mechanisms of action and clinical applications

Vitamin D is responsible for regulation of calcium and phosphate metabolism and maintaining a healthy mineralized skeleton. It is also known as an immunomodulatory hormone. Experimental studies have shown that 1,25-dihydroxyvitamin D, the active form of vitamin D, exerts immunologic activities on multiple components of the innate and adaptive immune system as well as endothelial membrane stability. Association between low levels of serum 25-hydroxyvitamin D and increased risk of developing several immune-related diseases and disorders, including psoriasis, type 1 diabetes, multiple sclerosis, rheumatoid arthritis, tuberculosis, sepsis, respiratory infection, and COVID-19, has been observed. Accordingly, a number of clinical trials aiming to determine the efficacy of administration of vitamin D and its metabolites for treatment of these diseases have been conducted with variable outcomes. Interestingly, recent evidence suggests that some individuals might benefit from vitamin D more or less than others as high inter-individual difference in broad gene expression in human peripheral blood mononuclear cells in response to vitamin D supplementation has been observed. Although it is still debatable what level of serum 25-hydroxyvitamin D is optimal, it is advisable to increase vitamin D intake and have sensible sunlight exposure to maintain serum 25-hydroxyvitamin D at least 30 ng/mL (75 nmol/L), and preferably at 40–60 ng/mL (100–150 nmol/L) to achieve the optimal overall health benefits of vitamin D.

Immunologic Effects of Vitamin D on Human Health and Disease

Background Relationships between microbiota composition and clinical outcomes after allogeneic hematopoietic-cell transplantation have been described in single-center studies. Geographic v...

https://www.nejm.org/doi/suppl/10.1056/NEJMoa1900623/suppl_file/nejmoa1900623_appendix.pdf

Microbiota as Predictor of Mortality in Allogeneic Hematopoietic-Cell Transplantation

Background: Recently discovered relationships between the gastrointestinal microbiome and the brain have implications for psychiatric disorders, including major depressive disorder (MDD). Bacterial transplantation from MDD patients to rodents produces depression-like behaviors. In humans, case-control studies have examined the gut microbiome in healthy and affected individuals. We systematically reviewed existing studies comparing gut microbial composition in MDD and healthy volunteers. Methods: A PubMed literature search combined the terms “depression,” “depressive disorder,” “stool,” “fecal,” “gut,” and “microbiome” to identify human case-control studies that investigated relationships between MDD and microbiota quantified from stool. We evaluated the resulting studies, focusing on bacterial taxa that were different between MDD and healthy controls. Results: Six eligible studies were found in which 50 taxa exhibited differences (p<0.05) between patients with MDD and controls. Patient characteristics and methodologies varied widely between studies. Five phyla—Bacteroidetes, Firmicutes, Actinobacteria, Fusobacteria and Protobacteria—were represented; however, divergent results occurred across studies for all phyla. The largest number of differentiating taxa were within phylum Firmicutes, in which nine families and twelve genera differentiated the diagnostic groups. The majority of these families and genera were found to be statistically different between the two groups in two studies identified. Family Lachnospiraceae differentiated the diagnostic groups in four studies (with an even split in directionality). Across all five phyla, nine genera were higher in MDD (Anaerostipes, Blautia, Clostridium, Klebsiella, Lachnospiraceae incertae sedis, Parabacteroides, Parasuterella, Phascolarctobacterium, and Streptococcus), six were lower (Bifidobacterium, Dialister, Escherichia/Shigella, Faecalibacterium, and Ruminococcus), and six were divergent (Alistipes, Bacteroides, Megamonas, Oscillibacter, Prevotella, and Roseburia). We highlight mechanisms and products of bacterial metabolism as they may relate to the etiology of depression. Conclusions: No consensus has emerged from existing human studies of depression and gut microbiome concerning which bacterial taxa are most relevant to depression. This may in part be due to differences in study design. Given that bacterial functions are conserved across taxonomic groups, we propose that studying microbial functioning may be more productive than a purely taxonomic approach to understanding the gut microbiome in depression.

/pdf/systematic-review-of-gut-microbiota-and-major-depression-13owxslejt.pdf

Systematic Review of Gut Microbiota and Major Depression.

Dysbiosis, departure of the gut microbiome from a healthy state, has been suggested to be a powerful biomarker of disease incidence and progression1–3. Diagnostic applications have been proposed for inflammatory bowel disease diagnosis and prognosis4, colorectal cancer prescreening5 and therapeutic choices in melanoma6. Noninvasive sampling could facilitate large-scale public health applications, including early diagnosis and risk assessment in metabolic7 and cardiovascular diseases8. To understand the generalizability of microbiota-based diagnostic models of metabolic disease, we characterized the gut microbiota of 7,009 individuals from 14 districts within 1 province in China. Among phenotypes, host location showed the strongest associations with microbiota variations. Microbiota-based metabolic disease models developed in one location failed when used elsewhere, suggesting that such models cannot be extrapolated. Interpolated models performed much better, especially in diseases with obvious microbiota-related characteristics. Interpolation efficiency decreased as geographic scale increased, indicating a need to build localized baseline and disease models to predict metabolic risks. The definition of a 'healthy' microbiome is impacted by geographic regional variations.

Regional variation limits applications of healthy gut microbiome reference ranges and disease models.

The metabolic syndrome (MetS) epidemic is associated with economic development, lifestyle transition and dysbiosis of gut microbiota, but these associations are rarely studied at the population scale. Here, we utilised the Guangdong Gut Microbiome Project (GGMP), the largest Eastern population-based gut microbiome dataset covering individuals with different economic statuses, to investigate the relationships between the gut microbiome and host physiology, diet, geography, physical activity and socioeconomic status. At the population level, 529 OTUs were significantly associated with MetS. OTUs from Proteobacteria and Firmicutes (other than Ruminococcaceae) were mainly positively associated with MetS, whereas those from Bacteroidetes and Ruminococcaceae were negatively associated with MetS. Two hundred fourteen OTUs were significantly associated with host economic status (140 positive and 74 negative associations), and 157 of these OTUs were also MetS associated. A microbial MetS index was formulated to represent the overall gut dysbiosis of MetS. The values of this index were significantly higher in MetS subjects regardless of their economic status or geographical location. The index values did not increase with increasing personal economic status, although the prevalence of MetS was significantly higher in people of higher economic status. With increased economic status, the study population tended to consume more fruits and vegetables and fewer grains, whereas meat consumption was unchanged. Sedentary time was significantly and positively associated with higher economic status. The MetS index showed an additive effect with sedentary lifestyle, as the prevalence of MetS in individuals with high MetS index values and unhealthy lifestyles was significantly higher than that in the rest of the population. The gut microbiome is associated with MetS and economic status. A prolonged sedentary lifestyle, rather than Westernised dietary patterns, was the most notable lifestyle change in our Eastern population along with economic development. Moreover, gut dysbiosis and a Western lifestyle had an additive effect on increasing MetS prevalence.

/pdf/linking-gut-microbiota-metabolic-syndrome-and-economic-1ny8z6bv1c.pdf

Linking gut microbiota, metabolic syndrome and economic status based on a population-level analysis.

In the version of this article originally published, in the sentence “Applying the same approach to obesity (Fig 2b), MetS (Fig 2c) and fatty liver (Fig 2d) yielded similar results,” two figure panels were cited incorrectly The data for obesity are in Fig 2c, and the data for MetS are in Fig 2b The sentence has been updated with the correct citations in the print, PDF and HTML versions of the article

/pdf/author-correction-regional-variation-limits-applications-of-1r8pt620qa.pdf

Xian Wang

Papers

Regional variation limits applications of healthy gut microbiome reference ranges and disease models.

Linking gut microbiota, metabolic syndrome and economic status based on a population-level analysis.

Author Correction: Regional variation limits applications of healthy gut microbiome reference ranges and disease models.