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.

Background: The aim of this study was to evaluate associations between body-weight fluctuation and risk of mortality and cardiovascular diseases (CVD).Methods: PubMed, EMBASE databases and Cochrane Library were searched for cohort studies published up to May 20, 2019, reporting on associations of body-weight fluctuation and mortality from all causes, CVD and cancer, as well as morbidity of CVD and hypertension. Summary relative risks (RRs) were estimated using a random-effects model.Results: Twenty-five eligible publications from 23 studies with 441,199 participants were included. Body-weight fluctuation was associated with increased risk for all-cause mortality (RR, 1.41; 95% confidence interval (CI): 1.27–1.57), CVD mortality (RR, 1.36; 95% CI 1.22–1.52), and morbidity of CVD (RR, 1.49, 95% CI 1.26–1.76) and hypertension (RR, 1.35, 95% CI 1.14–1.61). However, there was no significant association between weight fluctuation and cancer mortality (RR, 1.01; 95% CI 0.90–1.13). No evidence of publication bias was observed (all P > 0.05) except for studies on all-cause mortality (Egger's test, P = 0.001; Begg's test, P = 0.014).Conclusions: Body-weight fluctuation was associated with higher mortality due to all causes and CVD and a higher morbidity of CVD and hypertension.

Highlights Our study documented three common types of PMIS clinical presentation: persistent fever and gastrointestinal symptoms, shocked with heart dysfunction and Kawasaki disease-like syndrome. PMIS patients proved with a marked inflammatory state are possibly associated with SARS-CoV-2 infection. we put forward several potential hypotheses in this discussion in hope of shedding light for future research.

Adequate calorie restriction (CR) as a healthy lifestyle is recommended not only for people with metabolic disorders but also for healthy adults. Previous studies have mainly focused on the beneficial metabolic effects of CR on obese subjects, while its effects on non-obese subjects are still scarce. Here, we conducted a three-week non-controlled CR intervention in 41 subjects, with approximately 40% fewer calories than the recommended daily energy intake. We measured BMI, and applied targeted metabolic profiling on fasting blood samples and shotgun metagenomic sequencing on fecal samples, before and after intervention. Subjects were stratified into two enterotypes according to their baseline microbial composition, including 28 enterotype Bacteroides (ETB) subjects and 13 enterotype Prevotella (ETP) subjects. CR decreased BMI in most subjects, and ETP subjects exhibited a significantly higher BMI loss ratio than the ETB subjects. Additionally, CR induced limited changes in gut microbial composition but substantial microbial-independent changes in blood AAs, including a significant increase in 3-methylhistidine, a biomarker of the skeletal muscle protein turnover. Finally, baseline abundances of seven microbial species, rather than baseline AA levels, could well predict CR-induced BMI loss. This non-controlled intervention study revealed associations between baseline gut microbiota and CR-induced BMI loss and provided evidence to accelerate the application of microbiome stratification in future personalized nutrition intervention.

The aim of the research was to investigate the factors contributing to cognitive dysfunction in type 2 diabetic patients, to distinguish the complex relationship between diabetic retinopathy (DR) and different cognitive status. Methods: Two hundred and ninety-seven type 2 diabetes mellitus (T2DM) patients were enrolled in our study. We adopted the Clinical Dementia Rating (CDR), Mini-mental State Examination (MMSE) and Montreal Cognitive Assessment (MOCA) to evaluate the cognitive function. Firstly, cognition status was classified into dementia and non-dementia according to MMSE and CDR. Patients with non-dementia were further classified into mild cognitive impairment (MCI) and normal cognition status based on MOCA. The factors contributing to cognitive dysfunction were analyzed.Results: Among the 297 T2DM subjects, 47 were enrolled in the dementia group and 174 in the MCI group according to a battery of cognitive function tests, presenting a prevalence of 15.8% and 58.6%

Aims/Introduction: In this meta-analysis, we aimed to explore the association between bodyweight cycling (weight fluctuation) and the risk of developing diabetes. Materials and Methods: We analyzed data from eligible cohort studies that assessed the association between weight cycling in adults and the risk of developing diabetes from online databases PubMed, Cochrane Library and EMBASE databases (1966 to April 2020). We pooled data using relative risks (RRs) with a random effects model. Results: A total of 14 studies involving 253,766 participants, including 8,904 diabetes events, were included. One study included eight independent reports, resulting in 21 reports in 14 studies. Summary analysis showed that individuals who suffered weight cycling had a higher risk of diabetes (RR 1.23. 95% confidence interval 1.07-1.41; P = 0.003). However, the association between weight cycling and the risk of developing diabetes was not observed in obese participants (body mass index ≥30 kg/m 2 ; P = 0.08). Conclusions: The present meta-analysis showed that weight cycling was a strong independent predictor of new-onset diabetes. Future studies are required to detect the causal links between weight cycling and the risk of developing diabetes.

ANGPTL8, an important regulator of glucose and lipid metabolism, is associated with diabetes, but the role of ANGPTL8 in the outcomes of novel subgroups of diabetes remains unclear. To assess the circulating ANGPTL8 levels in novel subgroups of diabetes and their association with health outcomes, we performed a data-driven cluster analysis (k-means) of patients with newly diagnosed diabetes (741 patients enrolled from 2011 through 2016) from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a longitudinal (REACTION) study. The primary outcomes were mortality from all causes and cardiovascular diseases (CVD), and the secondary outcome was any cardiovascular event. Comparisons among groups were performed using the Kruskal-Wallis test, and the correlations between variables were assessed using the Pearson correlation test. Logistic regression was used to detect associations between the risk of outcomes and the ANGPTL8 levels. We identified four replicable clusters of patients with diabetes that exhibited significantly different patient characteristics and risks of all-cause mortality. The serum ANGPTL8 levels in the cluster of mild age-related diabetes (MARD), severe insulin-resistant diabetes (SIRD), and severe insulin-deficient diabetes (SIDD) were significantly higher than those in the mild obesity-related diabetes (MOD) cluster (685.

Background: Angiopoietin-like protein 8 (ANGPTL8), an important regulator of lipid metabolism, is increased in diabetes and is associated with insulin resistance. However, the role of ANGPTL8 in the outcomes of diabetic patients remains unclear. This study aimed to investigate circulating levels of ANGPTL8 in participants with and without diabetes and its potential associations with clinical outcomes in a 5 year cohort study. Methods: Propensity-matched cohorts of subjects with and without diabetes from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: A longitudinal (REACTION) study were generated on the basis of age, sex and body mass index at baseline. The primary outcome was all-cause mortality. The secondary outcomes were a composite of new-onset major adverse cardiovascular events, hospitalization for heart failure, and renal dysfunction (eGFR < 60/ min/1.73 m 2). Results: We identified 769 matched pairs of diabetic patients and control subjects. Serum ANGPTL8 levels were elevated in patients with diabetes compared to control subjects (618.82 ± 318.08 vs 581.20 ± 299.54 pg/mL, p = 0.03). Binary logistic regression analysis showed that elevated ANGPTL8 levels were associated with greater risk ratios (RRs) of death (RR in quartile 4 vs. quartile 1, 3.54; 95% CI 1.32-9.50) and renal dysfunction (RR in quartile 4 vs. quartile 1, 12.43; 95% CI 1.48-104.81) only in diabetic patients. Multivariable-adjusted restricted cubic spline analyses revealed a significant, linear relationship between ANGPTL8 and all-cause mortality in diabetic patients (p for nonlinear trend = 0.99, p for linear trend = 0.01) but not in control subjects (p for nonlinear trend = 0.26, p for linear trend = 0.80). According to ROC curve analysis, the inclusion of ANGPTL8 in QFrailty score significantly improved its predictive performance for mortality in patients with diabetes. Conclusion: Serum ANGPTL8 levels were associated with an increased risk of all-cause mortality and could be used as a potential biomarker for the prediction of death in patients with diabetes.