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Merck & Co.

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BackgroundPolycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder accompanied with an increased risk of developing type 2 diabetes mellitus and cardiovascular disease; despite being a common condition, the pathogenesis of PCOS remains unclear. Our aim was to investigate the potential metabolic profiles for different phenotypes of PCOS, as well as for the early prognosis of complications.MethodsA total of 217 women with PCOS and 48 healthy women as normal controls were studied. Plasma samples of subjects were tested using two different analytical platforms of metabolomics: 1H nuclear magnetic resonance (NMR) and gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS).ResultsOur results showed that carbohydrate, lipid and amino acid metabolisms were influenced in PCOS. The levels of lactate, long-chain fatty acids, triglyceride and very low-density lipoprotein were elevated, while glucose, phosphatidylcholine and high-density lipoprotein (HDL) concentrations were reduced in PCOS patients as compared with controls. Additionally, the levels of alanine, valine, serine, threonine, ornithine, phenylalanine, tyrosine and tryptophan were generally increased, whereas the levels of glycine and proline were significantly reduced in PCOS samples compared to controls. Furthermore, the ratio of branched-chain amino acid to aromatic amino acid concentrations (BCAA/AAA) in PCOS plasma was significantly reduced in PCOS patients and was insusceptible to obesity and insulin sensitivity.ConclusionsOur results suggested that the enhanced glycolysis and inhibited tricarboxylic acid cycle (TAC) in women with PCOS. Decrease of BCAA/AAA ratio was directly correlated with the development of PCOS. Ovulatory dysfunction of PCOS patients was associated with raised production of serine, threonine, phenylalanine, tyrosine and ornithine. Elevated levels of valine and leucine, and decreased concentrations of glycine in PCOS plasma could contribute to insulin sensitivity and could be considered as the potential biomarkers for long-term risk assessment of diabetes mellitus.

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ObjectiveWe assessed the effectiveness and safety of daclatasvir (DCV) plus sofosbuvir (SOF), with or without ribavirin (RBV), in a large real-world cohort, including patients with advanced liver disease.DesignAdults with chronic HCV infection at high risk of decompensation or death within 12 months and with no available treatment options were treated in a European compassionate use programme. The recommended regimen was DCV 60 mg plus SOF 400 mg for 24 weeks; RBV addition or shorter duration was allowed at physicians' discretion. The primary endpoint was sustained virological response at post-treatment week 12 (SVR12).ResultsOf the 485 evaluable patients, 359 received DCV+SOF and 126 DCV+SOF+RBV. Most patients were men (66%), white (93%) and treatment-experienced (70%). The most frequent HCV genotypes were 1b (36%), 1a (33%) and 3 (21%), and 80% of patients had cirrhosis (42% Child–Pugh B/C; 46% Model for End-Stage Liver Disease score >10). SVR12 (modified intention-to-treat) was achieved by 91% of patients (419/460); 1 patient had virological breakthrough and 13 patients relapsed. Virological failure was not associated with treatment group (adjusted risk difference DCV+SOF minus DCV+SOF+RBV: 1.06%; 95% CI −2.22% to 4.35%). High SVR12 was observed regardless of HCV genotype or cirrhosis, liver transplant or HIV/HCV coinfection status. Twenty eight patients discontinued treatment due to adverse events (n=18) or death (n=10) and 18 died during follow-up. Deaths and most safety events were associated with advanced liver disease and not considered treatment related.ConclusionsDCV+SOF with or without RBV achieved high SVR12 and was well tolerated in a diverse cohort of patients with severe liver disease.Trial registration numberNCT0209966.

BackgroundThe gut microbiota plays important roles in modulating host metabolism. Previous studies have demonstrated differences in the gut microbiome of T2D and prediabetic individuals compared to healthy individuals, with distinct disease-related microbial profiles being reported in groups of different age and ethnicity. However, confounding factors such as anti-diabetic medication hamper identification of the gut microbial changes in disease development.MethodWe used a combination of in-depth metagenomics and metaproteomics analyses of faecal samples from treatment-naïve type 2 diabetic (TN-T2D, n = 77), pre-diabetic (Pre-DM, n = 80), and normal glucose tolerant (NGT, n = 97) individuals to investigate compositional and functional changes of the gut microbiota and the faecal content of microbial and host proteins in Pre-DM and treatment-naïve T2D individuals to elucidate possible host-microbial interplays characterizing different disease stages.FindingsWe observed distinct differences characterizing the gut microbiota of these three groups and validated several key features in an independent TN-T2D cohort. We also demonstrated that the content of several human antimicrobial peptides and pancreatic enzymes differed in faecal samples between three groups.InterpretationOur findings suggest a complex, disease stage-dependent interplay between the gut microbiota and the host and point to the value of metaproteomics to gain further insight into interplays between the gut microbiota and the host.FundThe study was supported by the National Natural Science Foundation of China (No. 31601073), the National Key Research and Development Program of China (No. 2017YFC0909703) and the Shenzhen Municipal Government of China (No. JCYJ20170817145809215). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Emerging evidence indicates an association between gut microbiome and arthritis diseases including gout. However, how and which gut bacteria affect host urate degradation and inflammation in gout remains unclear. Here we performed a metagenome analysis on 307 fecal samples from 102 gout patients and 86 healthy controls. Gout metagenomes significantly differed from those of healthy controls. The relative abundances of Prevotella, Fusobacterium, and Bacteroides were increased in gout, whereas those of Enterobacteriaceae and butyrate-producing species were decreased. Functionally, gout patients had greater abundances for genes in fructose, mannose metabolism and lipid A biosynthesis, and lower for genes in urate degradation and short chain fatty acid production. A three-pronged association between metagenomic species, functions and clinical parameters revealed that decreased abundances of species in Enterobacteriaceae were associated with reduced amino acid metabolism and environmental sensing, which together contribute to increased serum uric acid and C-reactive protein levels in gout. A random forest classifier based on three gut microbial genes showed high predictivity for gout in both discovery and validation cohorts (0.91 and 0.80 accuracy), with high specificity in the context of other chronic disorders. Longitudinal analysis showed that uric-acid-lowering and anti-inflammatory drugs partially restored gut microbiota after 24-week treatment. Comparative analysis with obesity, type 2 diabetes, ankylosing spondylitis and rheumatoid arthritis indicated that gout metagenomes were more similar to those of autoimmune than metabolic diseases. Our results suggest that gut dysbiosis was associated with dysregulated host urate degradation and systemic inflammation and may be used as non-invasive diagnostic markers for gout.