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ObjectiveThe impact of faecal microbiota transplantation (FMT) on microbiota engraftment in patients with metabolic syndrome is uncertain. We aimed to study whether combining FMT with lifestyle modification could enhance the engraftment of favourable microbiota in obese patients with type 2 diabetes mellitus (T2DM).DesignIn this double-blind, randomised, placebo-controlled trial, 61 obese subjects with T2DM were randomly assigned to three parallel groups: FMT plus lifestyle intervention (LSI), FMT alone, or sham transplantation plus LSI every 4 weeks for up to week 12. FMT solution was prepared from six healthy lean donors. Faecal metagenomic sequencing was performed at baseline, weeks 4, 16 and 24. The primary outcome was the proportion of subjects acquiring ≥20% of microbiota from lean donors at week 24.ResultsProportions of subjects acquiring ≥20% of lean-associated microbiota at week 24 were 100%, 88.2% and 22% in the FMT plus LSI, FMT alone, and sham plus LSI groups, respectively (p<0.0001). Repeated FMTs significantly increased the engraftment of lean-associated microbiota (p<0.05). FMT with or without LSI increased butyrate-producing bacteria. Combining LSI and FMT led to increase in Bifidobacterium and Lactobacillus compared with FMT alone (p<0.05). FMT plus LSI group had reduced total and low-density lipoprotein cholesterol and liver stiffness at week 24 compared with baseline (p<0.05).ConclusionRepeated FMTs enhance the level and duration of microbiota engraftment in obese patients with T2DM. Combining lifestyle intervention with FMT led to more favourable changes in recipients’ microbiota and improvement in lipid profile and liver stiffness.Trial registration number NCT03127696.

Cinnamyl alcohol dehydrogenase (CAD) catalyzes the last step in monolignol biosynthesis and genetic evidence indicates CAD deficiency in grasses both decreases overall lignin, alters lignin structure and increases enzymatic recovery of sugars. To ascertain the effect of CAD downregulation in switchgrass, RNA mediated silencing of CAD was induced through Agrobacterium mediated transformation of cv. “Alamo” with an inverted repeat construct containing a fragment derived from the coding sequence of PviCAD2 . The resulting primary transformants accumulated less CAD RNA transcript and protein than control transformants and were demonstrated to be stably transformed with between 1 and 5 copies of the T-DNA. CAD activity against coniferaldehyde, and sinapaldehyde in stems of silenced lines was significantly reduced as was overall lignin and cutin. Glucose release from ground samples pretreated with ammonium hydroxide and digested with cellulases was greater than in control transformants. When stained with the lignin and cutin specific stain phloroglucinol-HCl the staining intensity of one line indicated greater incorporation of hydroxycinnamyl aldehydes in the lignin.

Type 2 diabetes (T2D) is a progressive disease whereby there is often deterioration in glucose control despite escalation in treatment. There is significant heterogeneity to this progression of glycemia after onset of diabetes, yet the factors that influence glycemic progression are not well understood. Given the tremendous burden of diabetes in the Chinese population, and limited knowledge on factors that influence glycemia, we aim to identify the clinical and genetic predictors for glycemic progression in Chinese patients with T2D. In 1995-2007, 7,091 insulin-naïve Chinese patients (mean age 56.8 ± 13.3 [SD] years; mean age of T2D onset 51.1 ± 12.7 years; 47% men; 28.4% current or ex-smokers; median duration of diabetes 4 [IQR: 1-9] years; mean HbA1c 7.4% ± 1.7%; mean body mass index [BMI] 25.3 ± 4.0 kg/m2) were followed prospectively in the Hong Kong Diabetes Register. We examined associations of BMI and other clinical and genetic factors with glycemic progression defined as requirement of continuous insulin treatment, or 2 consecutive HbA1c ≥8.5% while on ≥2 oral glucose-lowering drugs (OGLDs), with validation in another multicenter cohort of Hong Kong Diabetes Biobank. During a median follow-up period of 8.8 (IQR: 4.8-13.3) years, incidence of glycemic progression was 48.0 (95% confidence interval [CI] 46.3-49.8) per 1,000 person-years with 2,519 patients started on insulin. Among the latter, 33.2% had a lag period of 1.3 years before insulin was initiated. Risk of progression was associated with extremes of BMI and high HbA1c. On multivariate Cox analysis, early age at diagnosis, microvascular complications, high triglyceride levels, and tobacco use were additional independent predictors for glycemic progression. A polygenic risk score (PRS) including 123 known risk variants for T2D also predicted rapid progression to insulin therapy (hazard ratio [HR]: 1.07 [95% CI 1.03-1.12] per SD; P = 0.001), with validation in the replication cohort (HR: 1.24 [95% CI 1.06-1.46] per SD; P = 0.008). A PRS using 63 BMI-related variants predicted BMI (beta [SE] = 0.312 [0.057] per SD; P = 5.84 × 10-8) but not glycemic progression (HR: 1.01 [95% CI 0.96-1.05] per SD; P = 0.747). Limitations of this study include potential misdiagnosis of T2D and lack of detailed data of drug use during follow-up in the replication cohort. Our results show that approximately 5% of patients with T2D failed OGLDs annually in this clinic-based cohort. The independent associations of modifiable and genetic risk factors allow more precise identification of high-risk patients for early intensive control of multiple risk factors to prevent glycemic progression.

Objective High-density lipoproteins (HDL) comprise particles of different size, density and composition and their vasoprotective functions may differ. Diabetes modifies the composition and function of HDL. We assessed associations of HDL size-based subclasses with incident cardiovascular disease (CVD) and mortality and their prognostic utility. Research design and methods HDL subclasses by nuclear magnetic resonance spectroscopy were determined in sera from 1991 fasted adults with type 2 diabetes (T2D) consecutively recruited from March 2014 to February 2015 in Hong Kong. HDL was divided into small, medium, large and very large subclasses. Associations (per SD increment) with outcomes were evaluated using multivariate Cox proportional hazards models. C-statistic, integrated discrimination index (IDI), and categorial and continuous net reclassification improvement (NRI) were used to assess predictive value. Results Over median (IQR) 5.2 (5.0–5.4) years, 125 participants developed incident CVD and 90 participants died. Small HDL particles (HDL-P) were inversely associated with incident CVD [hazard ratio (HR) 0.65 (95% CI 0.52, 0.81)] and all-cause mortality [0.47 (0.38, 0.59)] (false discovery rate < 0.05). Very large HDL-P were positively associated with all-cause mortality [1.75 (1.19, 2.58)]. Small HDL-P improved prediction of mortality [C-statistic 0.034 (0.013, 0.055), IDI 0.052 (0.014, 0.103), categorical NRI 0.156 (0.006, 0.252), and continuous NRI 0.571 (0.246, 0.851)] and CVD [IDI 0.017 (0.003, 0.038) and continuous NRI 0.282 (0.088, 0.486)] over the RECODe model. Conclusion Small HDL-P were inversely associated with incident CVD and all-cause mortality and improved risk stratification for adverse outcomes in people with T2D. HDL-P may be used as markers for residual risk in people with T2D.

To investigate association between skin autofluorescence (SAF) and cardiovascular events (CVE) and assess its predictive value in Chinese adults with type 2 diabetes (T2D). SAF was measured non-invasively in 3806 Chinese adults with T2D between 2016 and 2019 with CVE as primary endpoint and individual components as secondary endpoints. Cox proportional hazard models were used to examine associations between SAF and endpoints with adjustment for conventional risk factors. C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were performed to evaluate SAF's predictive value. During a median 1.8 (interquartile range, 1.2–3.1) years of follow-up, 172 individuals experienced CVE. Multivariate Cox model showed that SAF was independently associated with CVE (HR 1.18 per SD, 95% CI [1.02, 1.37]), coronary heart disease (HR 1.29 per SD, 95% CI [1.02, 1.63]), and congestive heart failure (HR 1.53 per SD, 95% CI [1.14, 2.05]). SAF yielded additional value on CVE risk stratification with enhanced IDI (95% CI) (0.023 [0.001, 0.057]) and continuous NRI (0.377 [0.002, 0.558]) over traditional risk factors. Higher SAF was independently associated with CVE in Chinese adults with T2D and yielded incremental predictive information for CVE. SAF has potential as a prognostic maker for CVE.

There is very limited data on the time trend of diabetes incidence in Asia. Using population-level data, we report the secular trend of the incidence of type 1 and type 2 diabetes in Hong Kong between 2002 and 2015. The Hong Kong Diabetes Surveillance Database hosts clinical information on people with diabetes receiving care under the Hong Kong Hospital Authority, a statutory body that governs all public hospitals and clinics. Sex-specific incidence rates were standardised to the age structure of the World Health Organization population. Joinpoint regression analysis was used to describe incidence trends. A total of 562,022 cases of incident diabetes (type 1 diabetes [n = 2,426]: mean age at diagnosis is 32.5 years, 48.4% men; type 2 diabetes [n = 559,596]: mean age at diagnosis is 61.8 years, 51.9% men) were included. Among people aged <20 years, incidence of both type 1 and type 2 diabetes increased. For type 1 diabetes, the incidence increased from 3.5 (95% CI 2.2-4.9) to 5.3 (95% CI 3.4-7.1) per 100,000 person-years (average annual percentage change [AAPC] 3.6% [95% CI 0.2-7.1], p < 0.05) in boys and from 4.3 (95% CI 2.7-5.8) to 6.4 (95% CI 4.3-8.4) per 100,000 person-years (AAPC 4.7% [95% CI 1.7-7.7], p < 0.05] in girls; for type 2 diabetes, the incidence increased from 4.6 (95% CI 3.2-6.0) to 7.5 (95% CI 5.5-9.6) per 100,000 person-years (AAPC 5.9% [95% CI 3.4-8.5], p < 0.05) in boys and from 5.9 (95% CI 4.3-7.6) to 8.5 (95% CI 6.2-10.8) per 100,000 person-years (AAPC 4.8% [95% CI 2.7-7.0], p < 0.05) in girls. In people aged 20 to <40 years, incidence of type 1 diabetes remained stable, but incidence of type 2 diabetes increased over time from 75.4 (95% CI 70.1-80.7) to 110.8 (95% CI 104.1-117.5) per 100,000 person-years (AAPC 4.2% [95% CI 3.1-5.3], p < 0.05) in men and from 45.0 (95% CI 41.4-48.6) to 62.1 (95% CI 57.8-66.3) per 100,000 person-years (AAPC 3.3% [95% CI 2.3-4.2], p < 0.05) in women. In people aged 40 to <60 years, incidence of type 2 diabetes increased until 2011/2012 and then flattened. In people aged ≥60 years, incidence was stable in men and declined in women after 2011. No trend was identified in the incidence of type 1 diabetes in people aged ≥20 years. The present study is limited by its reliance on electronic medical records for identification of people with diabetes, which may result in incomplete capture of diabetes cases. The differentiation of type 1 and type 2 diabetes was based on an algorithm subject to potential misclassification. There was an increase in incidence of type 2 diabetes in people aged <40 years and stabilisation in people aged ≥40 years. Incidence of type 1 diabetes continued to climb in people aged <20 years but remained constant in other age groups.

People with type 2 diabetes (T2D) have increased cancer risk. Liver cancer (LC) has a high prevalence in East Asia and is one of the leading causes of cancer death globally. Diagnosis of LC at early stage carries good prognosis. We used stored serum from patients of Hong Kong Diabetes Register before cancer diagnosis to extract RNA to screen for microRNA markers for early detection of LC in T2D. After screening with Affymetrix GeneChip microarray with serum RNA from 19 incident T2D LC (T2D-LC), 20 T2D cancer free (T2D-CF) and 20 non-T2D non-cancer patients, top signals were validated in a 3-group comparison including 1888 T2D-CF, 127 T2D-LC, and 487 T2D patients with non-liver cancer patients using qPCR. We detected 2.55-fold increase in miR-122-5p and 9.21-fold increase in miR-455-3p in the T2D-LC group. Using ROC analysis, miR-122-5p and miR-455-3p jointly predicted LC with an area under the curve of 0.770. After adjustment for confounders, each unit increase of miR-455-3p increased the odds ratio for liver cancer by 1.022. Increased serum levels of miR-122-5p and miR-455-3p were independently associated with increased risk of incident LC in T2D and may serve as potential biomarkers for early detection of LC in T2D.

Background Patients with type 2 diabetes (T2D) are at high risk of developing multiple complications, affecting their health‐related quality of life (HRQoL). Existing studies only considered impact of complication on HRQoL in the year of occurrence but not its residual impacts in subsequent years. We investigated temporal impacts of diabetes‐related complications on HRQoL in a 12‐year prospective cohort of ambulatory Chinese patients with T2D enrolled in the clinic‐based Joint Asia Diabetes Evaluation (JADE) Register. Methods HRQoL utility measures were derived from EuroQol five‐dimensional three‐level questionnaire (EQ‐5D‐3L) questionnaires completed by 19 322 patients with T2D in Hong Kong (2007–2018). Temporal EQ‐5D utility decrements associated with subtypes of cardiovascular‐renal events were estimated using generalized linear regression model after stepwise selection of covariates with p < .01 as cutoff. Results In this cohort (mean ± SD age:61.2 ± 11.5 years, 55.3% men, median [interquartile range] duration of diabetes:10.1 [3.0–15.0] years, glycated hemoglobin [HbA1C] 7.5 ± 1.5%), EQ‐5D utility was 0.860 ± 0.163. The largest HRQoL decrements were observed in year of occurrence of hemorrhagic stroke (−0.230), followed by ischemic stroke (−0.165), peripheral vascular disease (−0.117), lower extremity amputation (−0.093), chronic kidney disease (CKD) G5 without renal replacement therapy (RRT) (−0.079), congestive heart failure (CHF) (−0.061), and CKD G3–G4 without RRT (−0.042). Residual impacts on HRQoL persisted for 2 years after occurrence of CHF or ischemic stroke and 1 year after hemorrhagic stroke or CKD G3–G4 without RRT. Conclusion This is the first comprehensive report on temporal associations of HRQoL decrements with subtypes of diabetes‐related complications in ambulatory Asian patients with T2D. These data will improve the accuracy of cost‐effectiveness analysis of diabetes interventions at an individual level in an Asian setting. Highlights This is the first report on health‐related quality‐of‐life (HRQoL) decrements associated with subtypes of diabetes‐related cardiovascular‐renal complications in the year of occurrence and their residual impacts in subsequent years amongst 19 322 ambulatory Asian patients with type 2 diabetes (T2D) enrolled in the clinic‐based Joint Asia Diabetes Evaluation (JADE) Register (2007–2018) The largest HRQoL decrements expressed as EuroQol five‐dimensional questionnaire utility scores were observed in the year of occurrence of hemorrhagic stroke (−0.230), followed by ischemic stroke (−0.165), peripheral vascular disease (−0.117), lower extremity amputation (−0.093), chronic kidney disease (CKD) G5 without renal replacement therapy (RRT) (−0.079), congestive heart failure (−0.061) and CKD G3–G4 without RRT (−0.042) Residual impacts on HRQoL persisted for 2 years after occurrence of CHF or ischemic stroke, and 1 year after hemorrhagic stroke or CKD G3–G4 without RRT HRQoL estimates considering residual impacts of diabetes complications would improve accuracy of evaluation of cost‐effectiveness of novel diabetes interventions at an individual level in an Asian setting

Aims/hypothesis The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers. Methods From a prospective cohort of individuals with type 2 diabetes, baseline sera ( N =1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m 2 ) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts. Results At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p =0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p =0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts. Conclusions/interpretation Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification. Graphical Abstract

To address these knowledge gaps, we conducted a large register- and population-based cohort study to measure how age at diagnosis affects (1) glycemic exposure, (2) glycemic deterioration, and (3) responses to oral glucose-lowering drugs (OGLDs) during the first decade after diagnosis among adults with T2D. The Hong Kong Hospital Authority (HA) provides universal public healthcare modeled after the British National Health Service. Because of the high out-of-pocket cost of private healthcare, 95% of people with diabetes in Hong Kong receive care in HA clinics [20]. All participants undergo structured assessment (eyes, feet, blood, urine) by trained nurses every 2–3 years to collect data not routinely captured in the HA EHR, including diabetes type, age at diagnosis, family history, and lifestyle habits. According to HA regulations, these drugs are only indicated for diabetes [24].