Retinal screening contributes to early detection of diabetic retinopathy and timely treatment. To facilitate the screening process, we develop a deep learning system, named DeepDR, that can detect early-to-late stages of diabetic retinopathy. DeepDR is trained for real-time image quality assessment, lesion detection and grading using 466,247 fundus images from 121,342 patients with diabetes. Evaluation is performed on a local dataset with 200,136 fundus images from 52,004 patients and three external datasets with a total of 209,322 images. The area under the receiver operating characteristic curves for detecting microaneurysms, cotton-wool spots, hard exudates and hemorrhages are 0.901, 0.941, 0.954 and 0.967, respectively. The grading of diabetic retinopathy as mild, moderate, severe and proliferative achieves area under the curves of 0.943, 0.955, 0.960 and 0.972, respectively. In external validations, the area under the curves for grading range from 0.916 to 0.970, which further supports the system is efficient for diabetic retinopathy grading.

National Natural Science Foundation of China.

Objectives: Osteocalcin, a bone-derived protein, has recently been reported to affect energy metabolism. We investigated the relationship between serum osteocalcin and parameters of adiposity, glucose tolerance, and lipid profile in Chinese subjects. Methods: Serum osteocalcin was measured by electrochemiluminescence immunoassay in 254 men (128 with newly diagnosed type 2 diabetes mellitus (T2DM) and 126 with normal glucose tolerance (NGT)), 66 premenopausal women (33 with T2DM and 33 with NGT) as well as 180 postmenopausal women (92 with T2DM and 88 with NGT). Their associations with parameters of adiposity, glucose tolerance, and lipid profile were examined. Results: Serum osteocalcin concentrations in diabetic patients were significantly lower than those in NGT subjects after adjusted for age, gender, and body mass index (PZ0.003). Postmenopausal women had higher osteocalcin concentrations than premenopausal women and men (both P!0.001). Multiple stepwise regression analysis showed that age, %fat, high-density lipoprotein cholesterol, fasting plasma glucose, and fasting serum insulin were independently associated with osteocalcin in men (P!0.05). Age and HbA1c were independently correlated with osteocalcin in postmenopausal women. Besides age and HbA1c, serum triglyceride was also an independent factor influencing osteocalcin in premenopausal women. In addition, osteocalcin was also positively associated with homeostasis model assessment of b-cell function. Furthermore, multiple logistic regression analysis demonstrated that osteocalcin was independently associated with T2DM. Conclusions: Serum osteocalcin was closely associated with not only fat and glucose metabolism but also with lipid metabolism.

BackgroundRecent advance in genetic studies added the confirmed susceptible loci for type 2 diabetes to eighteen. In this study, we attempt to analyze the independent and joint effect of variants from these loci on type 2 diabetes and clinical phenotypes related to glucose metabolism.Methods/Principal FindingsTwenty-one single nucleotide polymorphisms (SNPs) from fourteen loci were successfully genotyped in 1,849 subjects with type 2 diabetes and 1,785 subjects with normal glucose regulation. We analyzed the allele and genotype distribution between the cases and controls of these SNPs as well as the joint effects of the susceptible loci on type 2 diabetes risk. The associations between SNPs and type 2 diabetes were examined by logistic regression. The associations between SNPs and quantitative traits were examined by linear regression. The discriminative accuracy of the prediction models was assessed by area under the receiver operating characteristic curves. We confirmed the effects of SNPs from PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8 on risk for type 2 diabetes, with odds ratios ranging from 1.114 to 1.406 (P value range from 0.0335 to 1.37E-12). But no significant association was detected between SNPs from WFS1, FTO, JAZF1, TSPAN8-LGR5, THADA, ADAMTS9, NOTCH2-ADAM30 and type 2 diabetes. Analyses on the quantitative traits in the control subjects showed that THADA SNP rs7578597 was association with 2-h insulin during oral glucose tolerance tests (P = 0.0005, empirical P = 0.0090). The joint effect analysis of SNPs from eleven loci showed the individual carrying more risk alleles had a significantly higher risk for type 2 diabetes. And the type 2 diabetes patients with more risk allele tended to have earlier diagnostic ages (P = 0.0006).Conclusions/SignificanceThe current study confirmed the association between PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8 and type 2 diabetes. These type 2 diabetes risk loci contributed to the disease additively.

BackgroundWe updated the prevalence of obesity and evaluated the clinical utility of separate and combined waist circumference (WC) or body mass index (BMI) category increments in identifying cardiometabolic disorder (CMD) and cardiovascular disease (CVD) risk in Chinese adults.Methods and Findings46,024 participants aged ≥20 years, a nationally representative sample surveyed in 2007–2008, were included in this analysis. Taking the cutoffs recommended by the Chinese Joint Committee for Developing Chinese Guidelines (JCDCG) and the Working Group on Obesity in China (WGOC) into account, the participants were divided into four WC and four BMI groups in 0.5-SD increments around the mean, and 16 cross-tabulated combination groups of WC and BMI. 27.1%, 31.4%, and 12.2% of Chinese adults are centrally obese, overweight, or obese according to JCDCG and WGOC criteria. After adjustment for confounders, after a 1-SD increment, WC is associated with a 1.7-fold or 2.2-fold greater risk of having DM or DM plus dyslipidemia than BMI, while BMI was associated with a 2.3-fold or 1.7-fold higher hypertension or hypertension plus dyslipidemia risk than WC. The combination of WC and BMI categories had stronger association with CMD risk, i.e., the adjusted ORs (95% CI) of having DM, hypertension, and dyslipidemia for the combined and separate highest WC and BMI categories were 2.19 (1.96–2.44) vs 1.88 (1.67–2.12) and 1.12 (0.99–1.26); 5.70 (5.24–6.19) vs 1.51 (1.39–1.65) and 1.69 (1.57–1.82); and 3.73 (3.42–4.07) vs 2.16 (1.98–2.35) and 1.33 (1.25–1.40), respectively. The combination of WC and BMI categories was more likely to identify individuals with lower WC and lower BMI at CVD risk, even after the effects of CMD were controlled (all P<0.05).ConclusionCentral obesity, overweight, and obesity are epidemic in Chinese adults. The combination of WC and BMI measures is superior to the separate indices in identifying CMD and CVD risk.

Results The area under the receiver operating characteristics curve for detecting undiagnosed diabetes was 0.856 (95% confidence interval 0.828 to 0.883) for HbA 1c alone and 0.920 (0.900 to 0.941) for fasting plasma glucose alone. Very high specificity (96.1%, 95% confidence interval 95.5% to 96.7%) was achieved at an HbA 1c threshold of 6.3% (2 SD above the normal mean). Moreover, the corresponding sensitivity was 62.8% (57.1% to 68.3%), which was equivalent to that of a fasting plasma glucose threshold of 7.0 mmol/l (57.5%, 51.7% to 63.1%) in detecting undiagnosed diabetes. In participants at high risk of diabetes, the HbA 1c threshold of 6.3% showed significantly higher sensitivity (66.9%, 61.0% to 72.5%) than both fasting plasma glucose ≥7.0 mmol/l (54.4%, 48.3% to 60.4%) and HbA 1c ≥6.5% (53.7%, 47.6% to 59.7%) (P<0.01). Conclusions An HbA 1c threshold of 6.3% was highly specific for detecting undiagnosed diabetes in Chinese adults and had sensitivity similar to that of using a fasting plasma glucose threshold of 7.0 mmol/l. This optimal HbA 1c threshold may be suitable as a diagnostic criterion for diabetes in Chinese adults when fasting plasma glucose and oral glucose tolerance tests are not available.

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets.

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