Decreased Glycemic Difference Between Diabetes and Nondiabetes in the Elderly Leads to the Reduced Diagnostic Accuracy of Hemoglobin A1c for Diabetes Screening in an Aged Chinese Population

Differential effect of interventions in patients with prediabetes stratified by a machine learning-based diabetes progression prediction model

AIM

To investigate whether stratifying participants with prediabetes according to their diabetes progression risks (PR) could affect their responses to interventions.

METHODS

We developed a machine learning-based model to predict the 1-year diabetes PR (ML-PR) with the least predictors. The model was developed and internally validated in participants with prediabetes in the Pinggu Study (a prospective population-based survey in suburban Beijing; n = 622). Patients from the Beijing Prediabetes Reversion Program cohort (a multicentre randomized control trial to evaluate the efficacy of lifestyle and/or pioglitazone on prediabetes reversion; n = 1936) were stratified to low-, medium- and high-risk groups using ML-PR. Different effect of four interventions within subgroups on prediabetes reversal and diabetes progression was assessed.

RESULTS

Using least predictors including fasting plasma glucose, 2-h postprandial glucose after 75 g glucose administration, glycated haemoglobin, high-density lipoprotein cholesterol and triglycerides, and the ML algorithm XGBoost, ML-PR successfully predicted the 1-year progression of participants with prediabetes in the Pinggu study [internal area under the curve of the receiver operating characteristic curve 0.80 (0.72-0.89)] and Beijing Prediabetes Reversion Program [external area under the curve of the receiver operating characteristic curve 0.80 (0.74-0.86)]. In the high-risk group pioglitazone plus intensive lifestyle therapy significantly reduced diabetes progression by about 50% at year l and the end of the trial in the high-risk group compared with conventional lifestyle therapy with placebo. In the medium- or low-risk group, intensified lifestyle therapy, pioglitazone or their combination did not show any benefit on diabetes progression and prediabetes reversion.

CONCLUSIONS

This study suggests personalized treatment for prediabetes according to their PR is necessary. ML-PR model with simple clinical variables may facilitate personal treatment strategies in participants with prediabetes.

Rare Variant in Metallothionein 1E Increases the Risk of Type 2 Diabetes in a Chinese Population

OBJECTIVE

To uncover novel targets for the treatment of type 2 diabetes (T2D) by investigating rare variants with large effects in monogenic forms of the disease.

RESEARCH DESIGN AND METHODS

We performed whole-exome sequencing in a family with diabetes. We validated the identified gene using Sanger sequencing in additional families and diabetes- and community-based cohorts. Wild-type and variant gene transgenic mouse models were used to study the gene function.

RESULTS

Our analysis revealed a rare variant of the metallothionein 1E (MT1E) gene, p.C36Y, in a three-generation family with diabetes. This risk allele was associated with T2D or prediabetes in a community-based cohort. MT1E p.C36 carriers had higher HbA1c levels and greater BMI than those carrying the wild-type allele. Mice with forced expression of MT1E p.C36Y demonstrated increased weight gain, elevated postchallenge serum glucose and liver enzyme levels, and hepatic steatosis, similar to the phenotypes observed in human carriers of MT1E p.C36Y. In contrast, mice with forced expression of MT1E p.C36C displayed reduced weight and lower serum glucose and serum triglyceride levels. Forced expression of wild-type and variant MT1E demonstrated differential expression of genes related to lipid metabolism.

CONCLUSIONS

Our results suggest that MT1E could be a promising target for drug development, because forced expression of MT1E p.C36C stabilized glucose metabolism and reduced body weight, whereas MT1E p.C36Y expression had the opposite effect. These findings highlight the importance of considering the impact of rare variants in the development of new T2D treatments.

Gender-specific data-driven adiposity subtypes using deep-learning-based abdominal CT segmentation

OBJECTIVE

The aim of this study was to quantify abdominal adiposity and generate data-driven adiposity subtypes with different diabetes risks.

METHODS

A total of 3817 participants from the Pinggu Metabolic Disease Study were recruited. A deep-learning-based recognition model on abdominal computed tomography (CT) images (A-CT model) was developed and validated in 100 randomly selected cases. The volumes and proportions of subcutaneous fat, visceral fat, liver fat, and muscle fat were automatically recognized in all cases. K-means clustering was used to identify subgroups using the proportions of the four fat components.

RESULTS

The Dice indices among the measurements assessed by the A-CT model and manual evaluation to detect liver fat, muscle fat, and subcutaneous fat areas were 0.96, 0.95, and 0.92, respectively. Three subtypes were generated separately in men and women: visceral fat dominant type (VFD); subcutaneous fat dominant type (SFD); and intermuscular fat dominant type (MFD). Compared with the SFD group, the MFD group had similar diabetes risk, and the VFD group had a 60% higher diabetes risk when age and BMI were adjusted for in men. The adjusted odds ratio for diabetes was 1.92 (95% CI: 1.32-2.78) in the MFD group and 6.14 (95% CI: 4.18-9.03) in the VFD group in women.

CONCLUSIONS

This study identified gender-specific abdominal adiposity subgroups, which may help clinicians to distinguish diabetes risk quickly and automatically.

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.

Association of serum fibroblast growth factor 21 with kidney function in a population-based Chinese cohort

Fibroblast growth factor 21 (FGF21) plays a role in kidney disease. Circulating FGF21 levels are associated with kidney function and progression in patients with type 2 diabetes (T2D). However, the association between FGF21 and kidney function in the general population is still lacking. The aim of this study was to determine the association between FGF21 and kidney function and its progression in a Chinese cohort.A total of 2425 participants from a population-based survey of diabetes and metabolic syndrome in Pinggu, Beijing, were included in the baseline analysis. After a median follow-up of 12 months, 2402 participants with baseline estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 were analyzed in the longitudinal study. The progression of kidney function was defined as an eGFR decline exceeding 3.3% per year. Serum FGF21 levels were measured using an enzyme-linked immunosorbent assay at baseline.Male sex, body mass index (BMI), homeostasis model assessment of insulin resistance, higher levels of low-density lipoprotein cholesterol (LDL-c), uric acid, and FGF21 were associated with increased odds of a lower eGFR at baseline. The association of FGF21 with lower eGFR was independent of all the potential confounders in multivariable logistic regression (odds ratio, 1.005; 95% confidence interval 1.002-1.008). However, FGF21 was not associated with eGFR decline in the longitudinal analysis (odds ratio, 1.000; 95% confidence interval 0.998-1.001).Increased serum FGF21 levels were independently associated with lower eGFR in this nonmedicated general population. FGF21 could be a biomarker of kidney function in the general population.

The impact of ferritin on the disassociation of HbA1c and mean plasma glucose

OBJECTIVE

To explore the impact of ferritin level on the disassociation of glycated hemoglobin A1c (HbA1c) and mean plasma glucose (MPG).

RESEACH DESIGN AND METHODS

We used a 2012-2013 cross-sectional survey conducted in Pinggu district, Beijing including 3095 Chinese participants aged 25-75 years. We categorized their glycemic status by interviewing for diagnosed diabetes and by measuring HbA1c, fasting plasma glucose (FPG), and 2-hours post-load plasma glucose (2-hours PPG). We fitted a multivariable regression model to explore the impact of ferritin on the association of HbA1c or glycated albumin (GA) and mean plasma glucose.

RESULTS

A total of 5.65% of participants were diagnosed as diabetes using HbA1c criteria, and 9.79% using oral glucose tolerance test criteria. Compared with males, females had significantly lower hemoglobin levels (159.82 ± 11.56 vs 135.93 ± 12.62) and lower ferritin levels (113.00 [68.55, 185.50] vs 33.40 [12.40, 70.13]). Linear regression analysis performed in different groups classified by different diagnose criterion indicated that the correlation between MPG and HbA1c differs in different tertiles of ferritin (lowest vs middle vs highest: R² = 0.507 vs 0.645 vs 0.687 in female; R² = 0.415 vs 0.715 vs 0.615 in male), and the association between MPG and HbA1c diminished in the lowest tertile of ferritin.

CONCLUSIONS

Ferritin level might affect the association between glucose and HbA1c, which should be taken into account when using HbA1c as a diagnosis criterion for diabetes and prediabetes.

Diagnostic accuracy of tests for type 2 diabetes and prediabetes: A systematic review and meta-analysis

Aim

This systematic review aimed to ascertain the diagnostic accuracy (sensitivity and specificity) of screening tests for early detection of type 2 diabetes and prediabetes in previously undiagnosed adults.

Methods

This systematic review included published studies that included one or more index tests (random and fasting tests, HbA1c) for glucose detection, with 75-gram Oral Glucose Tolerance Test (or 2-hour post load glucose) as a reference standard (PROSPERO ID CRD42018102477). Seven databases were searched electronically (from their inception up to March 9, 2020) accompanied with bibliographic and website searches. Records were manually screened and full text were selected based on inclusion and exclusion criteria. Subsequently, data extraction was done using standardized form and quality assessment of studies using QUADAS-2 tool. Meta-analysis was done using bivariate model using Stata 14.0. Optimal cut offs in terms of sensitivity and specificity for the tests were analysed using R software.

Results

Of 7,151 records assessed by title and abstract, a total of 37 peer reviewed articles were included in this systematic review. The pooled sensitivity, specificity, positive (LR+) and negative likelihood ratio (LR-) for diagnosing diabetes with HbA1c (6.5%; venous sample; n = 17 studies) were 50% (95% CI: 42–59%), 97.3% (95% CI: 95.3–98.4), 18.32 (95% CI: 11.06–30.53) and 0.51 (95% CI: 0.43–0.60), respectively. However, the optimal cut-off for diagnosing diabetes in previously undiagnosed adults with HbA1c was estimated as 6.03% with pooled sensitivity of 73.9% (95% CI: 68–79.1%) and specificity of 87.2% (95% CI: 82–91%). The optimal cut-off for Fasting Plasma Glucose (FPG) was estimated as 104 milligram/dL (mg/dL) with a sensitivity of 82.3% (95% CI: 74.6–88.1%) and specificity of 89.4% (95% CI: 85.2–92.5%).

Conclusion

Our findings suggest that at present recommended threshold of 6.5%, HbA1c is more specific and less sensitive in diagnosing the newly detected diabetes in undiagnosed population from community settings. Lowering of thresholds for HbA1c and FPG to 6.03% and 104 mg/dL for early detection in previously undiagnosed persons for screening purposes may be considered.

Independent markers of nonalcoholic fatty liver disease in a gentrifying population-based Chinese cohort

BACKGROUND

Prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing in developing countries, but its causes are not known. We aimed to ascertain the prevalence and determinants of NAFLD in a new largely unmedicated population-based cohort from the rapidly gentrifying region of Pinggu, China.

METHODS

We randomized cluster sampled 4002 Pinggu residents aged 26 to 76 years. Data from 1238 men and 1928 women without significant alcohol drinking or hepatitis virus B or C infection were analysed. NAFLD was defined using a liver-spleen ratio (L/S ratio) ≤1.1 on unenhanced abdominal computed tomography (CT) scanning.

RESULTS

Of men and women, 26.5% and 20.1%, respectively, had NAFLD. NAFLD prevalence was highest in younger men and older women. In multivariate logistic regression models, higher body mass index, waist circumference, serum triglyceride, alanine transaminase, and haemoglobin A1c independently increased the odds of NAFLD in both men and women separately. Higher annual household income and systolic blood pressure for men and higher serum uric acid and red meat intake and lower physical activity levels for women also independently associated with higher odds of NAFLD. Individuals with L/S ratio ≤1.1 had linearly increasing rates of obesity, diabetes, and metabolic syndrome that paralleled fatty liver increase.

CONCLUSIONS

NAFLD is common in a gentrifying Chinese population particularly in younger men of high socioeconomic status and older women with sedentary behaviour who eat red meat. Demographic factors add independent risk of NAFLD above traditional metabolic risk factors. A CT L/S ratio of ≤1.1 identifies individuals at high risk of metabolic disease.

The Association of Retinopathy and Plasma Glucose and HbA1c: A Validation of Diabetes Diagnostic Criteria in a Chinese Population

Aims. This study aimed to evaluate the associations of diabetic retinopathy (DR) with fasting plasma glucose (FPG), 2-hour postload plasma glucose (2hPG), and glycated hemoglobin A1c (HbA1c) in a Chinese population. Materials and Methods. A total of 3124 participants, identified from a population-based survey in Pinggu district, were examined by retinal photography (45°). DR was classified according to the Early Treatment Diabetic Retinopathy Study scale. FPG, 2hPG, and HbA1c were tested and categorized by deciles, with the prevalence of DR calculated in each decile. Results. The prevalence of DR increased sharply in the 10th deciles, when FPG exceeded 7.03 mmol/L and HbA1c exceeded 6.4%. Analysis of the receiver operating characteristic curves showed that the optimal cutoffs for detecting DR were 6.52 mmol/L and 5.9% for FPG and HbA1c, respectively. The World Health Organization (WHO) criteria for diagnosing diabetes showed high specificity (90.5-99.5%) and low sensitivity (35.3-65.0%). Further, 6 individuals with retinopathy had normal plasma glucose; however, their characteristics did not differ from those without retinopathy. Conclusions. Thresholds of FPG and HbA1c for detecting DR were observed, and the WHO criteria of diagnosing diabetes were shown to have high specificity and low sensitivity in this population.