Phenotypic features, prevalence of KCNJ11-MODY in Chinese patients with early-onset diabetes and a literature review.

OBJECTIVE: Gain-of-function (GOF) variants of KCNJ11 cause neonate diabetes and maturity-onset diabetes of the young (KCNJ11-MODY), while loss-of-function (LOF) variants lead to hyperinsulinemia hypoglycemia and subsequent diabetes. Given the limited research of KCNJ11-MODY, we aimed to analyse its phenotypic features and prevalence in Chinese patients with early-onset type 2 diabetes (EOD). DESIGN, PATIENTS AND MEASUREMENTS: We performed next-generation sequencing on 679 Chinese EOD patients to screen for KCNJ11 exons variants. Bioinformatics prediction and the American College of Medical Genetics and Genomics guidelines was used to determine the pathogenicity and diagnosed KCNJ11-MODY. A literature review was conducted to investigate the phenotypic features of KCNJ11-MODY. RESULTS: We identified six predicted deleterious rare variants in six EOD patients (0.88%). They were classified as uncertain significance (variant of uncertain significance [VUS]), but more common in this EOD cohort than a general Chinese population database, however, without significant difference (53/10,588, 0.50%) (p = .268). Among 80 previously reported patients with KCNJ11-MODY, 23.8% (19/80) carried 9 (32.1%) LOF variants, who had significantly older age at diagnosis, higher birthweight and higher fasting C-peptide compared to patients with GOF variants. Many patients carrying VUS were not correctly diagnosed. CONCLUSIONS: Some rare variants of KCNJ11 might contribute to the development of Chinese EOD, although available evidence has not enough power to support them as cause of KCNJ11-MODY. The clinical features of LOF variants were different from GOF variants in KCNJ11-MODY patients. It is necessary to evaluate the pathogenicity of VUS through function experiments.

Overburden of rare ALMS1 deleterious variants in Chinese early-onset type 2 diabetes with severe insulin resistance.

AIMS: Alström syndrome (AS) is a rare recessive disorder characterised by diabetes, obesity, insulin resistance (IR), and visual and hearing impairments. Mutations in the ALMS1 gene have been identified as the causative agents of AS. This study aimed to explore the relationship between rare ALMS1 variants and clinical features in Chinese patients with early-onset type 2 diabetes (age at diagnosis ≤40 years; EOD). MATERIALS AND METHODS: ALMS1 gene sequencing was performed in 611 Chinese individuals with EOD, 36 with postprandial hyperinsulinemia, and 47 with pre-diabetes and fasting IR. In-silico prediction algorithm and the American College of Medical Genetics Guidelines (ACMG) were used to evaluate the deleteriousness and pathogenicity of the variants. RESULTS: Sixty-two rare ALMS1 variants (frequency <0.005) were identified in 82 patients with EOD. Nineteen variants were predicted to be deleterious (pD). Patients with EOD carrying pD variants had higher fasting C-peptide, postprandial C-peptide, and HOMA2-IR levels than those without variants. The frequency of ALMS1 pD variants in the subgroup with more insulin-resistant EOD was higher than that in other EOD subgroups. Two patients with EOD, obesity, and IR who carried one heterozygous pathogenic/likely pathogenic rare variant of ALMS1 according to ACMG were identified. Moreover, rare heterozygous pD variants of ALMS1 were found in participants from cohorts of postprandial hyperinsulinemia as well as in pre-diabetes with fasting IR. CONCLUSIONS: ALMS1 rare pD variants are enriched in the populations with significant IR, which is a major hallmark of diabetes pathogenesis. Accordingly, our exploratory study provides insights and hypotheses for further studies of gene function.

Baseline Urine Albumin-to-Creatinine Ratio is Associated With Decline of Estimated Glomerular Filtration Rate in Patients Newly Diagnosed With Type 2 Diabetes Mellitus: An Observational 5-year Cohort Study.

OBJECTIVE: This study aimed to investigate the association between baseline albuminuria and the progression of diabetic kidney disease (DKD) in patients newly diagnosed with type 2 diabetes mellitus (DM). METHODS: A retrospective cohort study was conducted among 604 patients aged ≥18 years who were newly diagnosed with type 2 DM between January 2014 and 31 December 2017 at an outpatient clinic in a tertiary hospital in China. The incidence of albuminuria was determined and the associations between albuminuria at baseline and the progression of DKD estimated by estimated glomerular filtration rate slope were evaluated using binary logistic regression analysis. RESULTS: At diagnosis of type 2 DM, 18.8% of patients had albuminuria, with 17.4% having microalbuminuria and the other 1.4% having macroalbuminuria. During the 5-year follow-up period, patients with albuminuria at the baseline experienced a more rapid decline of estimated glomerular filtration rate over time than patients with normoalbuminuria at baseline (-2.6 vs -1.5 mL/min/1.73 m2 per year, P =.01). Albuminuria at baseline is independently associated with the progression of DKD. CONCLUSIONS: The prevalence of albuminuria is 18.8% in patients newly diagnosed with type 2 diabetes and the occurrence of albuminuria can predict steeper annual decline in kidney function.

The efficacy of canagliflozin in diabetes subgroups stratified by data-driven clustering or a supervised machine learning method: a post hoc analysis of canagliflozin clinical trial data.

AIMS/HYPOTHESIS: Data-driven diabetes subgroups have shown distinct clinical characteristics and disease progression, although there is a lack of evidence that this information can guide clinical decisions. We aimed to investigate whether diabetes subgroups, identified by data-driven clustering or supervised machine learning methods, respond differently to canagliflozin. METHODS: We pooled data from five randomised, double-blinded clinical trials of canagliflozin at an individual level. We applied the coordinates from the All New Diabetics in Scania (ANDIS) study to form four subgroups: mild age-related diabetes (MARD); severe insulin-deficient diabetes (SIDD); mild obesity-related diabetes (MOD) and severe insulin-resistant diabetes (SIRD). Machine learning models for HbA1c lowering (ML-A1C) and albuminuria progression (ML-ACR) were developed. The primary efficacy endpoint was reduction in HbA1c at 52 weeks. Concordance of a model was defined as the difference between predicted HbA1c and actual HbA1c decline less than 3.28 mmol/mol (0.3%). RESULTS: The decline in HbA1c resulting from treatment was different among the four diabetes clusters (pinteraction=0.004). In MOD, canagliflozin showed a robust glucose-lowering effect at week 52, compared with other drugs, with least-squares mean of HbA1c decline [95% CI] being 6.6 mmol/mol (4.1, 9.2) (0.61% [0.38, 0.84]) for sitagliptin, 7.1 mmol/mol (4.7, 9.5) (0.65% [0.43, 0.87]) for glimepiride, and 9.8 mmol/mol (9.0, 10.5) (0.90% [0.83, 0.96]) for canagliflozin. This superiority persisted until 104 weeks. The proportion of individuals who achieved HbA1c <53 mmol/mol (<7.0%) was highest in sitagliptin-treated individuals with MARD but was similar among drugs in individuals with MOD. The ML-A1C model and the cluster algorithm showed a similar concordance rate in predicting HbA1c lowering (31.5% vs 31.4%, p=0.996). Individuals were divided into high-risk and low-risk groups using ML-ACR model according to their predicted progression risk for albuminuria. The effect of canagliflozin vs placebo on albuminuria progression differed significantly between the high-risk (HR 0.67 [95% CI 0.57, 0.80]) and low-risk groups (HR 0.91 [0.75, 1.11]) (pinteraction=0.016). CONCLUSIONS/INTERPRETATION: Data-driven clusters of individuals with diabetes showed different responses to canagliflozin in glucose lowering but not renal outcome prevention. Canagliflozin reduced the risk of albumin progression in high-risk individuals identified by supervised machine learning. Further studies with larger sample sizes for external replication and subtype-specific clinical trials are necessary to determine the clinical utility of these stratification strategies in sodium-glucose cotransporter 2 inhibitor treatment. DATA AVAILABILITY: The application for the clinical trial data source is available on the YODA website ( http://yoda.yale.edu/ ).

Metagenomic analysis reveals crosstalk between gut microbiota and glucose-lowering drugs targeting the gastrointestinal tract in Chinese patients with type 2 diabetes: a 6 month, two-arm randomised trial.

AIMS/HYPOTHESIS: The use of oral glucose-lowering drugs, particularly those designed to target the gut ecosystem, is often observed in association with altered gut microbial composition or functional capacity in individuals with type 2 diabetes. The gut microbiota, in turn, plays crucial roles in the modulation of drug efficacy. We aimed to assess the impacts of acarbose and vildagliptin on human gut microbiota and the relationships between pre-treatment gut microbiota and therapeutic responses. METHODS: This was a randomised, open-labelled, two-arm trial in treatment-naive type 2 diabetes patients conducted in Beijing between December 2016 and December 2017. One hundred participants with overweight/obesity and newly diagnosed type 2 diabetes were recruited from the Pinggu Hospital and randomly assigned to the acarbose (n=50) or vildagliptin (n=50) group using sealed envelopes. The treatment period was 6 months. Blood, faecal samples and visceral fat data from computed tomography images were collected before and after treatments to measure therapeutic outcomes and gut microbiota. Metagenomic datasets from a previous type 2 diabetes cohort receiving acarbose or glipizide for 3 months were downloaded and processed. Statistical analyses were applied to identify the treatment-related changes in clinical variables, gut microbiota and associations. RESULTS: Ninety-two participants were analysed. After 6 months of acarbose (n=44) or vildagliptin (n=48) monotherapy, both groups achieved significant reductions in HbA1c (from 60 to 46 mmol/mol [from 7.65% to 6.40%] in the acarbose group and from 59 to 44 mmol/mol [from 7.55% to 6.20%] in the vildagliptin group) and visceral fat areas (all adjusted p values for pre-post comparisons <0.05). Both arms showed drug-specific and shared changes in relative abundances of multiple gut microbial species and pathways, especially the common reductions in Bacteroidetes species. Three months and 6 months of acarbose-induced changes in microbial composition were highly similar in type 2 diabetes patients from the two independent studies. Vildagliptin treatment significantly enhanced fasting active glucagon-like peptide-1 (GLP-1) levels. Baseline gut microbiota, rather than baseline GLP-1 levels, were strongly associated with GLP-1 response to vildagliptin, and to a lesser extent with GLP-1 response to acarbose. CONCLUSIONS/INTERPRETATION: This study reveals common microbial responses in type 2 diabetes patients treated with two glucose-lowering drugs targeting the gut differently and acceptable performance of baseline gut microbiota in classifying individuals with different GLP-1 responses to vildagliptin. Our findings highlight bidirectional interactions between gut microbiota and glucose-lowering drugs. TRIAL REGISTRATION: ClinicalTrials.gov NCT02999841 FUNDING: National Key Research and Development Project: 2016YFC1304901.

A variation in SORBS1 is associated with type 2 diabetes and high-density lipoprotein cholesterol in Chinese population.

AIM: Sorbin and SH3-domain-containing-1 (SORBS1) play important roles in insulin signalling and cytoskeleton regulation. Variants of the SORBS1 gene have been inconsistently reported to be associated with type 2 diabetes or diabetic kidney disease (DKD). METHODS: Two independent case-control studies based on two randomized sampling cohorts (cohort 1, n = 3345; cohort 2, n = 2282) were used to confirm the association between rs2281939 of SORBS1 and impaired glucose regulation (IGR). An additional hospital-based cohort (cohort 3, n = 2135) and cohort 1 were used to investigate the association between rs2281939 and DKD. The phenotype of rare variants of SORBS1 was explored in 453 patients with early onset type 2 diabetes (diagnosed before 40 years of age, EOD). RESULTS: The G allele was associated with type 2 diabetes (additive model: OR = 1.25, 95% CI [1.03-1.52], p = 0.022) in cohort 1, and IGR in cohort 2 (additive model: OR = 1.22, 95% CI [1.05-1.43], p = 0.01). We found that the G allele was also associated with HDL-c levels in women in both cohort 1 (p = 0.03) and 2 (p = 0.029) in the dominant model. The rare variant carriers also had lower HDL-c and LDL-c levels than non-carriers in patients with EOD. No association between rs2281939 or rare variants and DKD was observed. CONCLUSIONS: The variants in the SORBS1 gene were associated with IGR and HDL-c levels but not with DKD in the Chinese Han population.

Clinical evaluation of an automated TSI bridge immunoassay in the diagnosis of Graves' disease and its relationship to the degree of hyperthyroidism.

BACKGROUND: The rapid and accurate detection of thyroid-stimulating hormone (TSH) receptor antibodies has always been an urgent need for the clinical diagnosis and management of Graves' disease (GD). We aimed to evaluate the use of an automated thyroid-stimulating immunoglobulin (TSI) bridge immunoassay in the diagnosis of GD and to analyze the relationship between TSI and the degree of hyperthyroidism. METHODS: A total of 227 new-onset GD patients, 29 Hashimoto thyroiditis, 43 non-autoimmune thyroid diseases and 37 euthyroid controls were consecutively recruited. All participants accepted the measurement of their serum thyroid function and thyroid-associated antibodies, including TSI being measured by an Immulite 2000 bridge immunoassay and TSH receptor autoantibodies (TRAb) being measured by a third-generation Roche electrochemiluminescence immunoassay. The quantitative consistency between the TSI and TRAb detection methods was analyzed by using Passing-Bablok regression and Bland-Altman plots. The diagnostic performance for GD was assessed by receiver operating characteristic (ROC) curve analysis. RESULTS: Among 227 GD patients (174 females and 53 males, with a mean age of 39 years), the quantitative TSI was positively correlated with TRAb (r = 0.8099). According to the cut-off values proposed by the manufacturers (TSI: 0.55 IU/L, TRAb: 1.75 IU/L), the positive rates of TSI and TRAb in new-onset GD patients were 96.92% and 95.15%, respectively. Both TSI and TRAb levels positively correlated with FT4 levels (TSI: r = 0.243, TRAb: r = 0.317; all P < 0.001) and FT3 levels (TSI: r = 0.288, TRAb: r = 0.360; all P < 0.001) in new-onset GD patients. The ROC analysis showed that the optimal TSI cut-off value was 0.577 IU/L for GD diagnosis in this Chinese population, with a sensitivity of 96.92% and a specificity of 97.25%, respectively. The optimal TRAb cut-off value of was 1.38 IU/L, with a sensitivity of 96.92% and a specificity of 99.08%. There were no significant differences between the cut-off values obtained through the ROC analysis and those provided by the manufacturer for both TSI and TRAb when calculating their sensitivity and specificity in diagnosing GD. Among the 8 newly diagnosed GD cases with discordant qualitative antibody results, TSI was more likely than TRAb to match the clinical diagnosis of GD (6 TSI-positive vs. 2 TRAb-positive patients). CONCLUSION: The automated TSI bridge immunoassay was positively correlated with thyroxine levels in new-onset GD patients and was more likely to be consistent with the clinical diagnosis of GD than with that of TRAb. The positive Immulite 2000 TSI cut-off value of 0.577 IU/L for GD diagnosis in the Chinese population were close to the value recommended by the manufacturer.

Dipeptidyl peptidase-4 inhibitor treatment and the risk of bullous pemphigoid and skin-related adverse events: A systematic review and meta-analysis of randomized controlled trials.

AIMS: This meta-analysis aimed to evaluate the risk of developing bullous pemphigoid (BP) and other skin-related adverse events (AEs) in patients with type 2 diabetes (T2DM) undergoing dipeptidyl peptidase-4 inhibitor (DPP-4i) treatment in randomized controlled trials (RCTs). METHODS: In this meta-analysis, the MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases were searched for RCTs, which involve patients with T2DM reporting skin-related AEs. RCTs that comparatively evaluated the effects of DPP-4i treatment and placebo on patients with T2DM and reported skin-related AEs were included in the analysis. The odds ratio (OR) and 95% confidence interval (CI) were calculated using the Peto's methods. The GRADE approach was used to rate the quality of evidence. RESULTS: A total of 46 randomized placebo-controlled trials, including 3 trials with reports of BP (n = 38 011), that reported skin-related AEs were included (n = 59 332). Compared to the placebo group, the risk of developing BP was significantly higher in the DPP-4i treatment group (OR = 7.38, 95% CI 2.00-27.25, I2 = 0%, P = .003; quality rating: very low). Additionally, DPP-4i treatment was associated with an increased overall risk of developing skin-related AEs (OR = 1.22, 95% CI 1.02-1.46, I2 = 32%, P = .03; quality rating: moderate). CONCLUSIONS: This meta-analysis suggested that treatment with DPP-4is, including sitagliptin, saxagliptin, and linagliptin, was associated with an increased risk of developing BP. Additionally, the risk of developing skin-related AEs increased when all DPP-4is were combined. Skin lesion, especially BP, should be monitored in patients with diabetes undergoing DPP-4i treatment. Future studies should evaluate the susceptible population and develop strategies for early detection of skin-related AEs.

Flash glucose monitoring data analysed by detrended fluctuation function on beta-cell function and diabetes classification.

AIM: We aimed to use data-driven glucose pattern analysis to unveil the correlation between the metrics reflecting glucose fluctuation and beta-cell function, and to identify the possible role of this metric in diabetes classification. MATERIALS AND METHODS: In total, 78 participants with type 1 diabetes and 59 with type 2 diabetes were enrolled in this study. All participants wore a flash glucose monitoring system, and glucose data were collected. A detrended fluctuation function (DFF) was utilized to extract glucose fluctuation information from flash glucose monitoring data and a DFF-based glucose fluctuation metric was proposed. RESULTS: For the entire study population, a significant negative correlation between the DFF-based glucose fluctuation metric and fasting C-peptide was observed (r = -0.667; P <.001), which was larger than the correlation coefficient between the fasting C-peptide and mean amplitude of plasma glucose excursions (r = -0.639; P < .001), standard deviation (r = -0.649; P <.001), mean blood glucose (r = -0.519; P < .001) and time in range (r = 0.593; P < .001). As glucose data analysed by DFF revealed a clear bimodal distribution among the total participants, we randomly assigned the 137 participants into discovery cohorts (n = 100) and validation cohorts (n = 37) for 10 times to evaluate the consistency and effectiveness of the proposed metric for diabetes classification. The confidence interval for area under the curve according to the receiver operating characteristic analysis in the 10 discovery cohorts achieved (0.846, 0.868) and that for the 10 validation cohorts was (0.799, 0.862). In addition, the confidence intervals for sensitivity and specificity in the discovery cohorts were (75.5%, 83.0%), (81.3%, 88.5%) and (71.8%, 88.3%), (76.5%, 90.3%) in the validation cohorts, indicating the potential capacity of DFF in distinguishing type 1 and type 2 diabetes. CONCLUSIONS: Our study first proposed the possible role of data-driven analysis acquired glucose metric in predicting beta-cell function and diabetes classification, and a large-scale, multicentre study will be needed in the future.

A case report of pseudohypoaldosteronism type II with a homozygous KLHL3 variant accompanied by hyperthyroidism.

BACKGROUND: Pseudohypoaldosteronism type II (PHAII), also called Gordon syndrome, is a rare hereditary disease caused by variants in the WNK1, WNK4, KLHL3 and CUL3 genes. The combination of PHAII with hyperthyroidism and secondary hyperparathyroidism has not been reported previously. CASE PRESENTATION: A 54-year-old female with recently diagnosed Graves' disease presented hyperkalemia, hypertension, hypercalciuria, elevated levels of parathyroid hormone (PTH) and normal renal function. PHAII was established based on the finding of a homozygous variant (c.328 A > G, T110A) in the KLHL3 gene. Low-dose thiazide diuretics normalized her potassium, calcium and PTH. CONCLUSIONS: PHAII caused by a KLHL3 variant can affect adults later in life. This diagnosis should be considered in patients with hypertension, consistent hyperkalemia, and normal eGFR and can be corrected by thiazides. The patient also had hyperthyroidism and secondary hyperparathyroidism. The latter was also corrected by thiazide treatment. The hyperthyroidism was assumed to be unrelated to PHAII.