Although a few studies have investigated the intestinal microbiota of women with polycystic ovary syndrome (PCOS), the functional and metabolic mechanisms of the microbes associated with PCOS, as well as potential microbial biomarkers, have not yet been identified. To address this gap, we designed a two-phase experiment in which we performed shotgun metagenomic sequencing and monitored the metabolic parameters, gut-brain mediators, and sex hormones of PCOS patients. In the first stage, we identified an imbalance in the intestinal microbiota of the PCOS patients, observing that Faecalibacterium, Bifidobacterium, and Blautia were significantly more abundant in the control group, whereas Parabacteroides and Clostridium were enriched in the PCOS group. In the second stage, we monitored the impact of the probiotic Bifidobacterium lactis V9 on the intestinal microbiome, gut-brain mediators, and sex hormones of 14 PCOS patients. Notably, we observed that the levels of luteinizing hormone (LH) and LH/follicle-stimulating hormone (LH/FSH) decreased significantly in 9 volunteers, whereas the levels of sex hormones and intestinal short-chain fatty acids (SCFAs) increased markedly. In contrast, the changes in the indices mentioned above were indistinct in the remaining 5 volunteers. The results of an analysis of the number of viable Bifidobacterium lactis V9 cells in the two groups were highly consistent with the clinical and SCFA results. Therefore, effective host gut colonization of the probiotic Bifidobacterium lactis V9 was crucial for its ability to function as a probiotic. Finally, we propose a potential mechanism describing how probiotics regulate the levels of sex hormones by manipulating the intestinal microbiome in PCOS patients. IMPORTANCE Polycystic ovary syndrome (PCOS) is a common metabolic disorder among women of reproductive age worldwide. Through a two-phase clinical experiment, we first revealed an imbalance in the intestinal microbiome of PCOS patients. By binning and annotating shotgun metagenomic sequences into metagenomic species (MGS), 61 MGSs were identified as potential PCOS-related microbial biomarkers. In the second stage, we monitored the impact of the probiotic Bifidobacterium lactis V9 on the intestinal microbiota, metabolic parameters, gut-brain mediators, and sex hormones of PCOS patients. Notably, we observed that the PCOS-related clinical indices and the intestinal microbiotas of the participating patients exhibited an inconsistent response to the intake of the B. lactis V9 probiotic. Therefore, effective host gut colonization of the probiotic was crucial for its ability to function as a probiotic. Finally, we propose a potential mechanism by which B. lactis V9 regulates the levels of sex hormones by manipulating the intestinal microbiome in PCOS patients.

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BackgroundType A insulin resistance syndrome, one type of the hereditary insulin resistance syndromes, is a rare disorder. Patients with type A insulin resistance syndrome are nonobese and demonstrate severe hyperinsulinemia, hyperandrogenism, and acanthosis nigricans. The clinical features are more severe in affected females than in males, and they mostly become apparent at the age of puberty. In many cases, when severe insulin resistance is covered up by other signs or symptoms of type A insulin resistance syndrome, patients are often easily misdiagnosed with other diseases, such as polycystic ovary syndrome.Case presentationOur patient was a 27-year-old Han Chinese woman who sought treatment because of a menstrual disorder and hirsutism. Tests showed that her levels of insulin and testosterone were elevated, and gynecological color Doppler ultrasound suggested multiple cystic changes in the bilateral ovaries. After a diagnosis of polycystic ovary syndrome was made, pulsatile gonadotropin-releasing hormone therapy and metformin were administered, but the patient’s symptoms did not improve in 1 year of follow-up. Considering that the previous diagnosis might have been incorrect, venous blood samples were collected from the patient and her relatives for genetic analysis. Subsequently, using Illumina sequencing, it was found that the proband, her father, and two brothers all had the c.3601C>T heterozygous missense mutation in exon 20 of the insulin receptor gene. The diagnosis was corrected to type A insulin resistance syndrome, and the patient’s treatment was modified.ConclusionWe report a case of a young woman with type A insulin resistance syndrome that was misdiagnosed as polycystic ovary syndrome. We discuss the causes, clinical features, diagnosis, and treatment of type A insulin resistance syndrome to improve the recognition of the disease and reduce its misdiagnosis. Female patients with high androgen levels and severe hyperinsulinemia should be considered for the possibility of hereditary insulin resistance syndromes (such as type A insulin resistance syndrome). Gene sequencing helps in making an early diagnosis and developing a targeted treatment strategy.

Maturity-onset diabetes mellitus of the young (MODY) is a monogenic diabetes characterized by autosomal dominant inheritance. Its atypical clinical features make diagnosis difficult and it can be misdiagnosed as type 1 or type 2 diabetes. Fourteen subtypes of MODY have been diagnosed so far, of which MODY12 is caused by mutation of the ABCC8 (ATP Binding Cassette Subfamily C Member 8) gene, which is rarely reported in China. This paper reports a Chinese family of MODY12 caused by a rare missense mutation on the ABCC8 gene, which has not been reported to be associated with MODY in China or in other countries, with the aim of increasing clinicians' awareness and attention to the disease.

Abstract. The aim of the present study was to explore the effects of various combinations of exenatide, metformin (MET) and biphasic insulin aspart 30 (BIA30) on type 2 diabetes mellitus (T2DM). Two hundred overweight or obese patients newly diagnosed with T2DM were evenly randomized into two groups: A (twice daily for all: Phase I, 5 µg exenatide + 0.5 g MET for 4 weeks, then 10 µg exenatide + 0.5 g MET for 8 weeks; Phase II, 0.5 g MET for 12 weeks; Phase III, 0.3-0.4 U/kg/day BIA30 + 0.5 g MET for 12 weeks) and B (Phases I, II, III matched the phases III, II and I in group A). In groups A and B a significant decrease and increase, respectively, in glycated hemoglobin (HbAlc) and body mass index (BMI) was noted during Phase I. A 3.2±0.4-kg decrease in body weight in group A and a 2.6±0.3-kg increase in group B was observed. In Phase II, HbAlc was significantly increased in both groups (P<0.05). In Phase III, the BMI was increased in group A and reduced in group B (P<0.05). There was a 3.8±0.4-kg weight decrease in group B and 4.2±0.5-kg increase in group A (P<0.05). The combination of exenatide and MET promoted weight loss, glycemic control, β-cell function index, C peptide and adiponectin levels. These results suggested that the combination of exenatide and MET is better than the combination of BIA and MET for the therapy of overweight or obese patients newly diagnosed with T2DM.

Diabetes mellitus (DM) is a chronic disease that seriously threatens human health. Prediabetes is a stage in the progression of DM. The level of clinical indicators including fasting plasma glucose (FPG), 2-h postprandial glucose (2hPG), and glycosylated hemoglobin (HbA1C) are the diagnostic markers of diabetes. In this genome-wide association study (GWAS), we aimed to investigate the association of genetic variants with these phenotypes in Hainan prediabetes. In this study, we recruited 451 prediabetes patients from the residents aged ≥18 years who participated in the National Diabetes Prevalence Survey of the Chinese Medical Association in 2017. The GWAS of FPG, 2hPG, HbA1C, and body mass index (BMI) in prediabetes was analyzed with a linear model using an additive genetic model with adjustment for age and sex. We identified that rs13052524 in MRPS6 and rs62212118 in SLC5A3 were associated with 2hPG in Hainan prediabetes (p = 4.35 × 10-6, p = 4.05 × 10-6, respectively). Another six variants in the four genes (LINC01648, MATN1, CRAT37, and SLCO3A1) were related to HbA1C. Moreover, rs11142842, rs1891298, rs1891299, and rs11142843 in TRPM3/TMEM2 and rs78432036 in MLYCD/OSGIN1 were correlated to BMI (all p &lt; 5 × 10-6). This study is the first to determine the genome-wide association of FPG, 2hPG, and HbA1C, which emphasizes the importance of in-depth understanding of the phenotypes of high-value susceptibility gene markers in the diagnosis of prediabetes.

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Diabetes mellitus is a kind of highly prevalent chronic disease in the world. The intervention measures on the risk factors of prediabetes contribute to control and reduce the occurrence of diabetes. This study aimed to investigate the correlation between proinsulin (PI), true insulin (TI), PI/TI, 25(OH) D3, waist circumference (WC), and risk of prediabetes. Methods In this cross-sectional study, 1662 subjects including 615 prediabetes and 1047 non-prediabetes were recruited. Spearman's correlation analysis was used to explore the association of PI, TI, PI/TI, 25(OH) D3, and waist circumference with prediabetes. Odds ratios (OR) and 95% confidence intervals (CI) were calculated by logistic regression. Receiver-Operator Characteristic (ROC) curve was used to evaluate the risk of prediabetes. Results Our study showed that FPI, 2hPI, FTI, 2hTI, FPI/FTI, and WC could enhance the risk of prediabetes (OR 1.034; OR 1.007; OR 1.005; OR 1.002; OR 3.577, OR 1.053, respectively; all p< 0.001). Stratified analyses indicated that FPI/FTI associated with an increased risk of prediabetes in men (OR 2.080, p = 0.042). FTI have a weak association with prediabetes risk in men and women (OR 0.987, p = 0.001; OR 0.994, p = 0.004, respectively). 2hPI could decrease prediabetes in women (OR 0.995, p = 0.037). Interesting, the sensitivity (86.0%) and AUC (0.942, p< 0.001) of combination (FPI+FTI+2hPI+2hTI+25(OH) D3+WC) were higher than the diagnostic value of these alone diagnoses. The optimal cutoff point of FPI, FTI, 2hPI, 2hTI, 25(OH) D3, and WC for indicating prediabetes were 15.