Association between equol producers and type 2 diabetes mellitus among Japanese older adults.

AIMS/INTRODUCTION: Equol, which is produced by enteric bacteria from soybean isoflavones, has a chemical structure similar to estrogen. Both in vivo and in vitro studies have shown the beneficial metabolic effects of equol. However, its effects on type 2 diabetes remain unclear. We investigated the association between the equol producers/non-producers and type 2 diabetes. MATERIALS AND METHODS: The participants included 147 patients with type diabetes mellitus aged 70-89 years, and 147 age- and sex-matched controls. To ascertain the equol producers or non-producers, we used the comparative logarithm between the urinary equol and daidzein concentrations (cut-off value -1.75). RESULTS: The urinary equol concentration was significantly lower in the diabetes group compared with the non-diabetes group (P = 0.01). A significant difference in the proportion of equol producers was observed among all participants (38.8% in the diabetes group and 53.1% in the non-diabetes group; P = 0.01). The proportion of equol producers among women was significantly lower in the diabetes group (31.4%) than in the non-diabetes group (52.8%; P < 0.01). Additionally, the frequency of dyslipidemia in female equol producers was significantly lower than that in female non-equol producers (P < 0.01). Among men, no such differences were observed. We found a significant positive correlation between the urinary equol and daidzein concentrations among equol producers (r = 0.55, P < 0.01). CONCLUSIONS: Our study findings showed that postmenopausal women had a low proportion of equol producers with diabetes and dyslipidemia.

Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables.

Recent attempts to classify adult-onset diabetes using only six diabetes-related variables (GAD antibody, age at diagnosis, BMI, HbA1c, and homeostatic model assessment 2 estimates of b-cell function and insulin resistance (HOMA2-B and HOMA2-IR)) showed that diabetes can be classified into five clusters, of which four correspond to type 2 diabetes (T2DM). Here, we classified nondiabetic individuals to identify risk clusters for incident T2DM to facilitate the refinement of prevention strategies. Of the 1167 participants in the population-based Iwaki Health Promotion Project in 2014 (baseline), 868 nondiabetic individuals who attended at least once during 2015-2019 were included in a prospective study. A hierarchical cluster analysis was performed using four variables (BMI, HbA1c, and HOMA2 indices). Of the four clusters identified, cluster 1 (n = 103), labeled as "obese insulin resistant with sufficient compensatory insulin secretion", and cluster 2 (n = 136), labeled as "low insulin secretion", were found to be at risk of diabetes during the 5-year follow-up period: the multiple factor-adjusted HRs for clusters 1 and 2 were 14.7 and 53.1, respectively. Further, individuals in clusters 1and 2 could be accurately identified: the area under the ROC curves for clusters 1and 2 were 0.997 and 0.983, respectively. The risk of diabetes could be better assessed on the basis of the cluster that an individual belongs to.

The Relationship between Serum Adiponectin, Urinary Albumin/Creatinine Ratio and Type 2 Diabetes: A Population-Based Cross-Sectional Study.

The relationship between serum adiponectin concentration (S-Adipo) and various diseases, such as type 2 diabetes (T2D) is conflicting. We hypothesized that the extent of kidney damage in patients with T2D may be responsible for this inconsistency and, thus, examined association between S-Adipo and T2D after consideration for the extent of kidney damage present. Of the 1816 participants in the population-based Iwaki study of Japanese people, 1751 participants with a complete dataset were included. Multivariate logistic regression analyses revealed that low S-Adipo was independently associated with T2D (<0.001), as was high urinary albumin to creatinine ratio (uACR) (<0.001). Principal components analysis showed that the relative value of S-Adipo to uACR (adiponectin relative excess) was significantly associated with T2D (odds ratio: 0.49, p < 0.001). Receiver operating curve analyses revealed that an index of adiponectin relative excess the ratio of S-Adipo to uACR was superior to S-Adipo per se as a marker of T2D (area under the curve: 0.746 vs. 0.579, p < 0.001). This finding indicates that the relationship between S-Adipo and T2D should be evaluated according to the extent of kidney damage present and may warrant similar analyses of the relationships between S-Adipo and other medicalconditions, such as cardiovascular disease.

Interrelations between Gut Microbiota Composition, Nutrient Intake and Diabetes Status in an Adult Japanese Population.

Upon food digestion, the gut microbiota plays a pivotal role in energy metabolism, thus affecting the development of type 2 diabetes (DM). We aimed to examine the influence of the composition of selected nutrients consumed on the association between the gut microbiota and DM. This cross-sectional study of a general population was conducted on 1019 Japanese volunteers. Compared with non-diabetic subjects, diabetic subjects had larger proportions of the genera Bifidobacterium and Streptococcus but smaller proportions of the genera Roseburia and Blautia in their gut microbiotas. The genera Streptococcus and Roseburia were positively correlated with the amounts of energy (p = 0.027) and carbohydrate and fiber (p = 0.007 and p = 0.010, respectively) consumed, respectively. In contrast, the genera Bifidobacterium and Blautia were not correlated with any of the selected nutrients consumed. Cluster analyses of these four genera revealed that the Blautia-dominant cluster was most negatively associated with DM, whereas the Bifidobacterium-dominant cluster was positively associated with DM (vs. the Blautia-dominant cluster; odds ratio 3.97, 95% confidence interval 1.68-9.35). These results indicate the possible involvement of nutrient factors in the association between the gut microbiota and DM. Furthermore, independent of nutrient factors, having a Bifidobacterium-dominant gut microbiota may be a risk factor for DM compared to having a Blautia-dominant gut microbiota in a general Japanese population.

Correction: Tamura et al. Interrelations between Gut Microbiota Composition, Nutrient Intake and Diabetes Status in an Adult Japanese Population. J. Clin. Med. 2022, 11, 3216.

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