A P4 Medicine Perspective of Gut Microbiota and Prediabetes: Systems Analysis and Personalized Intervention

Associations of Dietary Live Microbes Intake and Prevalence of Prediabetes in US Adults: A Cross-Sectional Analysis

Objective

A higher dietary intake of live microbes has been shown to be associated with a range of health benefits. We aimed to elucidate the associations between dietary intake of live microbes and the risk of prediabetes.

Methods

Adult participants from the 1999-2018 US National Health and Nutrition Examination Survey were included and categorized into the low, medium, and high live microbe intake groups based on the Sanders classification system. Associations between dietary consumption of live microbes and prevalence of prediabetes were explored using univariate and multivariate logistic regression, stratified analysis, and sensitivity analysis.

Results

Among the 28201 participants (mean age 45.83 years, 48.40% men, 32.78% with prediabetes) included, 9761 (31.80%), 12,076 (41.42%) and 6364 (26.78%) were classified into the low, medium, and high dietary live microbe intake groups, respectively. After adjusting for all potential covariates, the odds ratios and 95% confidence intervals for the medium and high dietary live microbe intake groups were 0.868 (0.803-0.937) and 0.891 (0.807-0.983), respectively (P for trend = 0.017), with the low dietary live microbes intake group as the reference. This association is robust and not affected by participant's age, sex, race, poverty-income ratio, education level, hypertension status and estimated glomerular filtration rate.

Conclusion

A higher consumption of dietary live microbes was found to be cross-sectionally linked to a lower prevalence of prediabetes in US adults.

Causal relationship between gut microbiota and risk of gastroesophageal reflux disease: a genetic correlation and bidirectional Mendelian randomization study

Background

Numerous observational studies have identified a linkage between the gut microbiota and gastroesophageal reflux disease (GERD). However, a clear causative association between the gut microbiota and GERD has yet to be definitively ascertained, given the presence of confounding variables.

Methods

The genome-wide association study (GWAS) pertaining to the microbiome, conducted by the MiBioGen consortium and comprising 18,340 samples from 24 population-based cohorts, served as the exposure dataset. Summary-level data for GERD were obtained from a recent publicly available genome-wide association involving 78 707 GERD cases and 288 734 controls of European descent. The inverse variance-weighted (IVW) method was performed as a primary analysis, the other four methods were used as supporting analyses. Furthermore, sensitivity analyses encompassing Cochran's Q statistics, MR-Egger intercept, MR-PRESSO global test, and leave-one-out methodology were carried out to identify potential heterogeneity and horizontal pleiotropy. Ultimately, a reverse MR assessment was conducted to investigate the potential for reverse causation.

Results

The IVW method's findings suggested protective roles against GERD for the Family Clostridiales Vadin BB60 group (P = 0.027), Genus Lachnospiraceae UCG004 (P = 0.026), Genus Methanobrevibacter (P = 0.026), and Phylum Actinobacteria (P = 0.019). In contrast, Class Mollicutes (P = 0.037), Genus Anaerostipes (P = 0.049), and Phylum Tenericutes (P = 0.024) emerged as potential GERD risk factors. In assessing reverse causation with GERD as the exposure and gut microbiota as the outcome, the findings indicate that GERD leads to dysbiosis in 13 distinct gut microbiota classes. The MR results' reliability was confirmed by thorough assessments of heterogeneity and pleiotropy.

Conclusions

For the first time, the MR analysis indicates a genetic link between gut microbiota abundance changes and GERD risk. This not only substantiates the potential of intestinal microecological therapy for GERD, but also establishes a basis for advanced research into the role of intestinal microbiota in the etiology of GERD.

Short-term duration of diabetic retinopathy as a predictor for development of diabetic kidney disease

Background

Diabetic retinopathy (DR) is a risk factor for diabetic kidney disease (DKD). Whether the duration, especially the short-term duration, of DR is associated with the development and progression of DKD remains unclear.

Materials and Methods

A retrospective study and two-sample Mendelian randomization (MR) analysis were conducted. Kidney disease was defined by the urinary albumin-to-creatinine ratio (ACR) and the estimated glomerular filtration rate (eGFR). DR was diagnosed by an expert ophthalmologist by using a digital fundus camera. Binary and ordinal logistic regression analyses were performed. A restricted cubic spline was utilized to detect nonlinear associations. Summary statistics for DR- and DKD-associated single-nuclear polymorphisms (SNPs) were extracted from the FinnGen and the UK Biobank consortia.

Results

A total of 2674 patients with type 2 diabetes mellitus (T2DM) and type 2 diabetic kidney disease (T2DKD) were included. The prevalence and mean duration of DR increased with elevation of ACR and decline in eGFR. Renal function was significantly reduced in patients with DR in the fifth year of life. Binary and ordinal logistic regression showed that each 1-year increase in DR duration was associated with a 19% risk increase in the development of DKD, 16% in the elevation of ACR, and 21% in the decline of renal function. MR estimates indicated that DR was causally associated with DKD development, with an odds ratio of 2.89.

Conclusions

DR and the duration of DR were independent risk factors for the development and progression of DKD. The short-term duration of DR may be associated with DKD development. DR had a statistically significant effect on DKD.

Influence of group B streptococcus and vaginal cleanliness on the vaginal microbiome of pregnant women

BACKGROUND

The vaginal microbiome plays a critical role in the health of pregnant women and their newborns. Group B Streptococcus (GBS) and vaginal cleanliness significantly affect the vaginal microecosystem and are closely associated with vaginal diseases.

AIM

To explore the effects of GBS status and vaginal cleanliness on vaginal microecosystems.

METHODS

We collected 160 vaginal swabs from pregnant women and divided them into the following four groups based on GBS status and vaginal cleanliness: GBS-positive + vaginal cleanliness I–II degree, GBS-negative + vaginal cleanliness I–II degree, GBS-positive + vaginal cleanliness III–IV degree, and GBS-negative + vaginal cleanliness III–IV degree. Samples were subjected to 16S rRNA gene amplicon sequencing.

RESULTS

Alpha diversity analysis showed that the Shannon index did not significantly differ between the four groups. We identified significant variation in taxa abundance between the GBS-positive and GBS-negative groups and between the vaginal cleanliness I–II degree and III–IV degree groups. Principal coordinate analysis and non-metric multidimensional scaling analysis further confirmed the microbial diversity of the four groups. Moreover, the linear discriminant analysis demonstrated that Lactobacillus jensenii and Actinobacteria were strongly associated with GBS-positive status, and Lactobacillus iners, Lactobacillaceae, Lactobacillus, Lactobacillales, Bacilli and Firmicutes were closely correlated with GBS-negative status.

CONCLUSION

GBS status and vaginal cleanliness significantly affect vaginal microbiome differences in pregnant women. Our findings provide instructional information for clinical antibiotic treatment in pregnant women with different GBS statuses and vaginal cleanliness degrees.

A Comprehensive Weighted Gene Co-expression Network Analysis Uncovers Potential Targets in Diabetic Kidney Disease

Background and Objectives

Diabetic kidney disease (DKD) is one of the most common microvascular complications of diabetes. It has always been difficult to explore novel biomarkers and therapeutic targets of DKD. We aimed to identify new biomarkers and further explore their functions in DKD.

Methods

The weighted gene co-expression network analysis (WGCNA) method was used to analyze the expression profile data of DKD, obtain key modules related to the clinical traits of DKD, and perform gene enrichment analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the mRNA expression of the hub genes in DKD. Spearman's correlation coefficients were used to determine the relationship between gene expression and clinical indicators.

Results

Fifteen gene modules were obtained via WGCNA analysis, among which the green module had the most significant correlation with DKD. Gene enrichment analysis revealed that the genes in this module were mainly involved in sugar and lipid metabolism, regulation of small guanosine triphosphatase (GTPase) mediated signal transduction, G protein-coupled receptor signaling pathway, peroxisome proliferator-activated receptor (PPAR) molecular signaling pathway, Rho protein signal transduction, and oxidoreductase activity. The qRT-PCR results showed that the relative expression of nuclear pore complex-interacting protein family member A2 (NPIPA2) and ankyrin repeat domain 36 (ANKRD36) was notably increased in DKD compared to the control. NPIPA2 was positively correlated with the urine albumin/creatinine ratio (ACR) and serum creatinine (Scr) but negatively correlated with albumin (ALB) and hemoglobin (Hb) levels. ANKRD36 was positively correlated with the triglyceride (TG) level and white blood cell (WBC) count.

Conclusion

NPIPA2 expression is closely related to the disease condition of DKD, whereas ANKRD36 may be involved in the progression of DKD through lipid metabolism and inflammation, providing an experimental basis to further explore the pathogenesis of DKD.

A comprehensive weighted gene co-expression network analysis uncovers potential targets in diabetic kidney disease

Background and Objectives

Diabetic kidney disease (DKD) is one of the most common microvascular complications of diabetes. It has always been difficult to explore novel biomarkers and therapeutic targets of DKD. We aimed to identify new biomarkers and further explore their functions in DKD.

Methods

The weighted gene co-expression network analysis (WGCNA) method was used to analyze the expression profile data of DKD, obtain key modules related to the clinical traits of DKD, and perform gene enrichment analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the mRNA expression of the hub genes in DKD. Spearman’s correlation coefficients were used to determine the relationship between gene expression and clinical indicators.

Results

Fifteen gene modules were obtained via WGCNA analysis, among which the green module had the most significant correlation with DKD. Gene enrichment analysis revealed that the genes in this module were mainly involved in sugar and lipid metabolism, regulation of small guanosine triphosphatase (GTPase) mediated signal transduction, G protein-coupled receptor signaling pathway, peroxisome proliferator-activated receptor (PPAR) molecular signaling pathway, Rho protein signal transduction, and oxidoreductase activity. The qRT-PCR results showed that the relative expression of nuclear pore complex-interacting protein family member A2 (NPIPA2) and ankyrin repeat domain 36 (ANKRD36) was notably increased in DKD compared to the control. NPIPA2 was positively correlated with the urine albumin/creatinine ratio (ACR) and serum creatinine (Scr) but negatively correlated with albumin (ALB) and hemoglobin (Hb) levels. ANKRD36 was positively correlated with the triglyceride (TG) level and white blood cell (WBC) count.

Conclusion

NPIPA2 expression is closely related to the disease condition of DKD, whereas ANKRD36 may be involved in the progression of DKD through lipid metabolism and inflammation, providing an experimental basis to further explore the pathogenesis of DKD.

lncRNA ZFAS1 Positively Facilitates Endothelial Ferroptosis via miR-7-5p/ACSL4 Axis in Diabetic Retinopathy

Accumulating evidence has suggested the significant role of long noncoding RNAs (lncRNA) in regulating ferroptosis, while its regulatory mechanism in diabetic retinopathy (DR) remains unelucidated. In this work, we first demonstrated that lncRNA zinc finger antisense 1 (ZFAS1) is upregulated in high glucose-cultured human retinal endothelial cells (hRECs) and ZFAS1 inhibition attenuated high glucose- (HG-) induced ferroptosis, which was evidenced by cell viability, total iron and ferrous iron levels, reactive oxygen species (ROS) level, and Glutathione Peroxidase 4 (GP_X4) expression detection. Mechanistically, we validated that ZFAS1 may act as a competing endogenous RNA by competitively binding with microRNA-7-5p (miR-7-5p) and modulating the expression of its downstream molecule acyl-CoA synthetase long-chain family member 4 (ACSL4), which is now identified as a classic driver gene of ferroptosis process. In conclusion, our results demonstrate that HG-induced ZFAS1 elevation activates ferroptosis in hRECs and the ZFAS1/miR-7-5p/ACSL4 axis may serve as a therapeutic target for endothelial dysfunction in DR.

Indole-3-Propionic Acid as a Potential Therapeutic Agent for Sepsis-Induced Gut Microbiota Disturbance

The effects of using gut microbiota metabolites instead of live microorganisms to modulate sepsis-induced gut dysbiosis remain largely unknown. We assessed the effects of microbiota metabolite indole-3-propionic acid (IPA) on gut microbiota in mice during sepsis. Sepsis models were constructed by cecal ligation and puncture (CLP) methods. Fecal microbiota composition analysis was performed to characterize the gut microbiota composition. Fecal microbiota transplantation was performed to validate the roles of gut microbiota on sepsis progression. IPA-treated mice exhibited lower serum inflammatory mediator levels and a higher survival rate than those of saline-treated mice after modeling of sepsis, which were negated in the presence of antibiotics. Compared with saline-treated mice after modeling, IPA-treated mice showed a markedly different intestinal microbiota composition, with an enrichment of Bifidobacteriaceae family and a depletion of Enterobacteriaceae family. Mice gavaged with postoperative feces from IPA-treated animals displayed better survival than mice gavaged with feces from saline-treated animals. Overall, these data suggest that IPA offers a microbe-modulated survival advantage in septic mice, indicating that some microbiota metabolites could replace live microorganisms as potential options for regulation of sepsis-induced gut dysbiosis. IMPORTANCE The role of gut microbiota in the pathophysiology of sepsis is gaining increasing attention and developing effective and safe sepsis therapies targeting intestinal microorganisms is promising. Given the safety of probiotic supplementation or fecal microbiota transplantation in critically ill patients, identifying an abiotic agent to regulate the intestinal microbiota of septic patients is of clinical significance. This study revealed that IPA, a microbiota-generated tryptophan metabolite, ameliorated sepsis-induced mortality and decreased the serum levels of proinflammatory cytokines by modulating intestinal microbiota. Although IPA did not increase the abundance and diversity of the microbiota of septic mice, it significantly decreased the number of Enterobacteriaceae family. These findings indicate that a specific microbiota metabolite (e.g., IPA) can mediate the intestinal microbiota apart from FMT or probiotics.

Therapeutic Dilemma in personalized medicine

The practice of medicine depends over a long time on identifying therapies that target an entire population. The increase in scientific knowledge over the years has led to the gradual change towards individualization and personalization of drug therapy. The hope of this change is to achieve a better clinical response to given medications and reduction of their adverse effects. Tailoring of medicine on the road of personalized medicine considers molecular and genetic mapping of the individual. However, many factors still impede the smooth application of personalized medicine and represent challenges or limitations in its achievement. In this article, we put some clinical examples that show dilemmas in the application of personalized medicine such as opioids in pain control, fluoropyrimidines in malignancy, clopidogrel as antiplatelet therapy and oral hypoglycemic drugs in Type2 diabetes in adults. Shaping the future of medicine through the application of personalized medicine for a particular patient needs to put into consideration many factors such as patient's genetic makeup and life style, pathology of the disease and dynamic changes in its course as well as interactions between administered drugs and their effects on metabolizing enzymes. We hope in the coming years, the personalized medicine will foster changes in health care system in the way not only to treat patients but also to prevent diseases.