Chinese newborn screening for the incidence of G6PD deficiency and variant of G6PD gene from 2013 to 2017.

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is one of the most common X-linked enzymopathies caused by G6PD gene variant. We aimed to provide the characteristics of G6PD deficiency and G6PD gene variant distribution in a large Chinese newborn screening population. We investigated the prevalence of G6PD in China from 2013 to 2017. Then, we examined G6PD activity and G6PD gene in representative Chinese birth cohort to explore the distribution of G6PD gene variant in 2016. We then performed multicolor melting curve analysis to classify G6PD gene variants in 10,357 neonates with activity-confirmed G6PD deficiency, and DNA Sanger sequencing for G6PD coding exons if hot site variants were not found. The screened population, organizations, and provinces of G6PD deficiency were increased from 2013 to 2017 in China. The top five frequency of G6PD gene variants were c.1376G>T, c.1388G>A, c.95A>G, c.1024C>T, and c.871G>A and varied in different provinces, with regional and ethnic features, and four pathogenic variant sites (c.152C>T, c.290A>T, c.697G>C, and c.1285A>G) were first reported. G6PD deficiency mainly occurs in South China, and the frequency of G6PD gene variant varies in different regions and ethnicities.

Effect of potassium ions at the different concentration on the interaction between AmB and the lipid monolayer containing cholesterol or ergosterol.

AmB is an antifungal drug of polyene. Although it is prone to nephrotoxicity, it is still the gold standard in the clinical treatment of fungal infection. Sterol plays a decisive role in the drug activity of AmB. The antifungal activity of AmB depends on ergosterol in fungal membranes, and its toxicity is related to cholesterol in mammalian membranes. At the same time, AmB interacts with biofilms, leading to a significant loss of potassium ions and affecting the transport of potassium ions across membranes. Meanwhile, metal cation may also affect AmB molecules' aggregation on the membrane. This paper mainly studied the effects of different concentrations of potassium ions on the interactions between AmB and lipid monolayers containing cholesterol or ergosterol and explored the differences in the impact of varying potassium ions on the drug activity of AmB on monolayers rich in these two kinds of sterols. The results show that potassium ions caused the collapse of lipid monolayer and lipid-AmB monolayer to disappear. The limiting molecular area of these monolayers also increased due to potassium ions. The limiting molecular area of the monolayer in the presence of ergosterol has a great difference in the different concentration of potassium ions, which is different from that in the presence of cholesterol. The presence of potassium ions, regardless of the intensity of K+ ions, increased the maximum elastic modulus of the lipid/sterol monolayer with and without AmB. The presence of potassium ions reduced the influence of AmB on the stability of the lipid monolayer containing cholesterol. The impact of AmB on the stability of the lipid monolayer containing ergosterol was related to the concentration of potassium ions. The potassium ions increased the area of the ordered "island" region on the lipid-AmB monolayer containing cholesterol, and the boundary of the microregion produced different degrees of curvature. However, on the lipid/ergosterol monolayer, 5 mM and 10 mM potassium ions made the holes caused by AmB more denser, and the diameter of holes become larger. These results can help to improve the effect of potassium ions on the transmembrane transport of substances affected by AmB. The results will provide a basis for further exploration of the effect mechanism of metal ions on the antifungal activity of polyene drugs.

Prediction of Protein-Protein Interactions from Amino Acid Sequences Based on Continuous and Discrete Wavelet Transform Features.

Protein-protein interactions (PPIs) play important roles in various aspects of the structural and functional organization of cells; thus, detecting PPIs is one of the most important issues in current molecular biology. Although much effort has been devoted to using high-throughput techniques to identify protein-protein interactions, the experimental methods are both time-consuming and costly. In addition, they yield high rates of false positive and false negative results. In addition, most of the proposed computational methods are limited in information about protein homology or the interaction marks of the protein partners. In this paper, we report a computational method only using the information from protein sequences. The main improvements come from novel protein sequence representation by combing the continuous and discrete wavelet transforms and from adopting weighted sparse representation-based classifier (WSRC). The proposed method was used to predict PPIs from three different datasets: yeast, human and H. pylori. In addition, we employed the prediction model trained on the PPIs dataset of yeast to predict the PPIs of six datasets of other species. To further evaluate the performance of the prediction model, we compared WSRC with the state-of-the-art support vector machine classifier. When predicting PPIs of yeast, humans and H. pylori dataset, we obtained high average prediction accuracies of 97.38%, 98.92% and 93.93% respectively. In the cross-species experiments, most of the prediction accuracies are over 94%. These promising results show that the proposed method is indeed capable of obtaining higher performance in PPIs detection.

Effects of electromagnetic pulse exposure on gelatinase of blood-brain barrier in vitro.

The biological effects of electromagnetic pulse (EMP) on the brain have been focused on for years. It was reported that gelatinase played an important role in maintaining brain function through regulating permeability in the blood-brain barrier (BBB). To investigate the effects of EMP on gelatinase of BBB, an in vitro BBB model was established using primary cultured rat brain microvascular endothelial cells (BMVEC), astrocytes and half-contact culture of these cells in a transwell chamber. Cultured supernatant and cells were collected at different time points after exposure to EMP (peak intensity 400 kV/m, rise time 10 ns, pulse width 350 ns, 0.5 pps and 200 pulses). Protein levels of cellular gelatinase MMP-2 and MMP-9, and endogenous inhibitor TIMP-1 and TIMP-2 were detected by Western blot. The activity of gelatinase in culture supernatant was detected by gelatin zymography. It was found that compared with the sham-exposed group, the protein level of MMP-2 was significantly increased at 6 h (p < 0.05), and the protein level of its endogenous inhibitor TIMP-2 did not change after EMP exposure. In addition, the protein levels of MMP-9 and its endogenous inhibitor TIMP-1 did not change after EMP exposure. Gelatin zymography results showed that the activity of MMP-2 in the inner pool and the outer pool of the transwell chamber was significantly increased at 6 h after EMP exposure compared with that of the sham group. These results suggested that EMP exposure could affect the expression and activity of MMP-2 in the BBB model.

A fast vanishing point detection method based on row space features suitable for real driving scenarios.

The vanishing point (VP) is particularly important road information, which provides an important judgment criterion for the autonomous driving system. Existing vanishing point detection methods lack speed and accuracy when dealing with real road environments. This paper proposes a fast vanishing point detection method based on row space features. By analyzing the row space features, clustering candidates for similar vanishing points in the row space are performed, and then motion vectors are screened for the vanishing points in the candidate lines. The experimental results show that the average error of the normalized Euclidean distance is 0.0023716 in driving scenes under various lighting conditions. The unique candidate row space greatly reduces the amount of calculation, making the real-time FPS up to 86. It can be concluded that the fast vanishing point detection proposed in this paper would be suitable for high-speed driving scenarios.

CDBA: a novel multi-branch feature fusion model for EEG-based emotion recognition.

EEG-based emotion recognition through artificial intelligence is one of the major areas of biomedical and machine learning, which plays a key role in understanding brain activity and developing decision-making systems. However, the traditional EEG-based emotion recognition is a single feature input mode, which cannot obtain multiple feature information, and cannot meet the requirements of intelligent and high real-time brain computer interface. And because the EEG signal is nonlinear, the traditional methods of time domain or frequency domain are not suitable. In this paper, a CNN-DSC-Bi-LSTM-Attention (CDBA) model based on EEG signals for automatic emotion recognition is presented, which contains three feature-extracted channels. The normalized EEG signals are used as an input, the feature of which is extracted by multi-branching and then concatenated, and each channel feature weight is assigned through the attention mechanism layer. Finally, Softmax was used to classify EEG signals. To evaluate the performance of the proposed CDBA model, experiments were performed on SEED and DREAMER datasets, separately. The validation experimental results show that the proposed CDBA model is effective in classifying EEG emotions. For triple-category (positive, neutral and negative) and four-category (happiness, sadness, fear and neutrality), the classification accuracies were respectively 99.44% and 99.99% on SEED datasets. For five classification (Valence 1-Valence 5) on DREAMER datasets, the accuracy is 84.49%. To further verify and evaluate the model accuracy and credibility, the multi-classification experiments based on ten-fold cross-validation were conducted, the elevation indexes of which are all higher than other models. The results show that the multi-branch feature fusion deep learning model based on attention mechanism has strong fitting and generalization ability and can solve nonlinear modeling problems, so it is an effective emotion recognition method. Therefore, it is helpful to the diagnosis and treatment of nervous system diseases, and it is expected to be applied to emotion-based brain computer interface systems.

Identifying obesity indicators which best correlate with type 2 diabetes in a Chinese population.

BACKGROUND: Obesity has been shown to be a prognostic indicator of type 2 diabetes (T2D); however, the power of different obesity indicators in the detection of T2D remains controversial. This study evaluates the detecting power of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHTR) for the presence of T2D in undiagnosed diabetics among the Chinese population. METHODS: Individuals were selected from an ongoing large-scale population-based Beijing Community Pre-Diabetes (BCPD) study cohort. The oral glucose tolerance tests (OGTT) were performed to diagnose diabetes. A total of 220 new cases of T2D and 1,868 normal blood glucose subjects were analyzed. ROC curve analyses were used to compare the association of different obesity indicators with T2D and determine the optimal cut-off points of the best predictor for identifying T2D in men and women. RESULTS: All indicators positively correlated with presence of T2D in both men and women. In women, WC, WHR and WHTR were similar, but were better in identifying T2D when compared to BMI (P < 0.0001, P=0.0016 and P=0.0001, respectively). In men, WC, WHTR and BMI were similar, but WC and WHTR were better than WHR (P=0.0234, P=0.0101, respectively). For women, 86 cm was the optimal WC cut-off point, and its sensitivity and specificity were 0.714 and 0.616; for men, the optimal cut-off point was 90 cm, and its sensitivity and specificity were 0.722 and 0.571. CONCLUSION: Compared with BMI, WHR and WHTR, WC is a simple and accurate measure for predicting T2D in the Chinese population.

DSCNN-LSTMs: A Lightweight and Efficient Model for Epilepsy Recognition.

Epilepsy is the second most common disease of the nervous system. Because of its high disability rate and the long course of the disease, it is a worldwide medical problem and social public health problem. Therefore, the timely detection and treatment of epilepsy are very important. Currently, medical professionals use their own diagnostic experience to identify seizures by visual inspection of the electroencephalogram (EEG). Not only does it require a lot of time and effort, but the process is also very cumbersome. Machine learning-based methods have recently been proposed for epilepsy detection, which can help clinicians make rapid and correct diagnoses. However, these methods often require extracting the features of EEG signals before using the data. In addition, the selection of features often requires domain knowledge, and feature types also have a significant impact on the performance of the classifier. In this paper, a one-dimensional depthwise separable convolutional neural network and long short-term memory networks (1D DSCNN-LSTMs) model is proposed to identify epileptic seizures by autonomously extracting the features of raw EEG. On the UCI dataset, the performance of the proposed 1D DSCNN-LSTMs model is verified by cross-validation and time complexity comparison. Compared with other previous models, the experimental results show that the highest recognition rates of binary and quintuple classification are 99.57% and 81.30%, respectively. It can be concluded that the 1D DSCNN-LSTMs model proposed in this paper is an effective method to identify seizures based on EEG signals.

Phase Change Behavior of NaCl-H2O Binary Solution Under the Control of AC Electric Field.

Cryopreservation, which refers to preservation of cells or tissues at subzero temperatures, inevitably involves the problem of cryoinjury caused by ice crystals. The application of an external electric field during the freezing process has been shown to be a promising approach to produce miniature ice grains and decrease the fraction of ice crystallization at a slow cooling rate. Thus, the dielectric and thermodynamic properties of NaCl-H2O binary solutions at subzero temperatures were tremendously important for understanding the mechanism of ice formation under the manipulation of an AC electric field in biopreservation. However, there was still a lack of relevant information in the literature. The first objective of this study was to systematically measure the dielectric spectrum of 0.9% NaCl-H2O binary solutions at temperatures ranging from -100°C to 0°C with a cooling/heating rate of 2°C/min. We further measured the thermodynamic properties of a 0.9% NaCl-H2O binary solution while applying a series of electric fields near its dielectric relaxation frequency. The effect of the electric field on the crystal morphology was studied last. Pure water was selected as the control group. The results showed that an AC electric field can alter the thermodynamic process and thus the phase transition and ice crystal structure could be manipulated. It was concluded that the AC electric-assistant preservation method will be a promising technology in cryopreservation.

Interaction of amphotericin B and saturated or unsaturated phospholipid monolayers containing cholesterol or ergosterol at the air-water interface.

The antimicrobial activity of amphotericin B (AmB) depends on its interaction with ergosterol-containing cell membranes of fungus. Cholesterol is a sterol in mammalian cell membrane, and its structure is very similar to ergosterol, which caused to the toxic of amphotericin B to mammalian or human cell membranes. Even so, it is still the gold standard for the treatment of fungal infections. The mechanism of its toxicity to mammalian cell membrane has become a hot topic. The toxicity mechanism of amphotericin B on the cell membrane is also related to the phospholipids on the membrane. The effects of saturated and unsaturated fat chains on the interaction of amphotericin B with phospholipid monolayers containing cholesterol or ergosterol were studied at the molecular level using an air-water interface monolayer model. Both atomic force microscope and Brewster angle microscope were used to observe the surface morphology of the monolayer. The analysis of limiting molecular area suggested that the interaction between AmB and the two kinds of sterol is significantly different on the unsaturated lipid monolayer. According to the elastic modulus, the AmB molecules can increase the compressibility or viscoelasticity of the phospholipid/sterol monolayer. However, this impact of AmB on the DOPC/sterol monolayer containing ergosterol was stronger than that containing cholesterol at 25 ~ 50 mN/m. While this impact of AmB on the DPPC/sterol monolayer containing cholesterol was stronger than that containing ergosterol at 32 ~ 56 mN/m. The excess Gibbs free energy of the monolayer showed that, in the presence of saturated fat chain, amphotericin B could make the molecules of the DPPC/cholesterol monolayer and the DPPC/ergosterol monolayer arrange more closely and make intermolecular interaction stronger. There was no significant difference between DPPC/cholesterol monolayer and DPPC/ergosterol monolayer. However, in the presence of unsaturated chain, the effects of amphotericin B on the DOPC/cholesterol monolayer and the DOPC/ergosterol monolayer were significantly different. Amphotericin B made the molecular arrangement of DOPC/ergosterol monolayer more loosed, and the intermolecular force weakened at 5-35 mN/m. AFM images reflect that AmB can perforate the phospholipid-ergosterol monolayer, which was no significant correlation with saturation of the lipid monolayer. But the areas of dark areas shaped holes on the DPPC/ergosterol monolayer were larger than that on the DOPC/ergosterol monolayer. The adsorption of amphotericin B on lipid/sterol monolayer suggests that the orientation of amphotericin B may be different when it is inserted into the monolayer of phospholipid-sterol in the presence of saturated or unsaturated chains. The results are helpful to understand the complex mechanism of toxicity of amphotericin B to cell membrane.

Reduced high-density lipoprotein 2b in non-obese type 2 diabetic patients analysed by a microfluidic chip method in a case-control study.

BACKGROUND: Alterations in high-density lipoprotein (HDL) subfractions, especially in the HDL2b subfraction, have been reported in type 2 diabetes mellitus (T2DM). However, new methods for convenient and reliable quantitation of HDL2b are yet to be developed. METHODS: Thirty-eight patients with T2DM were enrolled and age-, sex- and body mass index (BMI)-matched controls were selected from the same population. A microfluidic chip method was employed to analyse serum HDL subfractions. RESULTS: The microfluidic chip method revealed a significant reduction in HDL2b and its ratio to total HDL in T2DM patients. There was a reverse correlation for total HDL and HDL2b, and its ratio with triglycerides, homeostasis model assessment-insulin sensitivity index (HOMA-IS) and insulin resistance index (HOMA-IR). CONCLUSIONS: We have shown a reduction of HDL2b and its ratio to total HDL by a novel chip method in T2DM patients. The significant correlation between HDL2b and HOMA-IS and HOMA-IR may have further predictive value in clinical utility.

A case-control study on the relationship between HDL2b and non-alcoholic fatty liver disease in Chinese type 2 diabetic patients.

BACKGROUND: It has been shown that low concentrations of high-density lipoprotein cholesterol (HDL-C) are associated with non-alcoholic fatty liver disease (NAFLD) in patients with type 2 diabetes mellitus (T2DM). HDL2b, a major subfraction of high-density lipoprotein (HDL), is more significantly correlated with coronary heart disease (CHD) compared with total HDL. In this study, we analysed HDL2b in a cohort of Chinese T2DM subjects with or without NAFLD. METHODS: A highly sensitive and reliable microfluidic chip method was adopted to measure HDL2b. In total, 48 T2DM patients with NAFLD diagnosed by a B-ultrasound were enrolled from our Beijing Community Pre-Diabetes (BCPD) study cohort. A total of 48 age and gender matched diabetic controls without NAFLD were selected from the same population. RESULTS: Clinical characteristics and serum biochemical analyses demonstrated a significantly increased body mass index (BMI), waist circumference, homeostasis model assessment-insulin resistant index (HOMA-IR), total cholesterol (TC), and triglyceride (TG) concentrations in the NAFLD group. However, the concentrations of HDL2b and its ratio to total HDL in NAFLD patients was decreased, compared with controls (p<0.01). Significantly increased concentrations of high sensitive C-reactive protein (hs-CRP) (p<0.01) were also found. Multifactor logistic regression analysis showed that BMI and TG were the predominant risk factors for fatty liver, while HDL2b was a protective factor. CONCLUSIONS: T2DM patients with NAFLD have characteristics including obesity, marked insulin resistance, high TG, high hs-CRP, low HDL2b and a low HDL2b ratio to total HDL. These factors may increase the incidence of atherosclerosis as well as the risk of CHD.

High prevalence of impaired fasting glucose in Chinese children and adolescents with prehypertension/hypertension.

AIM: To assess the prevalence of impaired fasting glucose among Chinese children and adolescents with prehypertension/hypertension (PHP/HP), overweight/obesity (OW/OB) or both in the general population. METHODS: In total, 3409 children and adolescents among the age group of 10-18 years were enrolled. These subjects were then divided into four groups: OW/OB, PHP/HP, OW/OB + PHP/HP and a control group. Fasting plasma glucose (FPG) and lipid levels were measured in children with a body mass index > or =85th percentile and/or blood pressure > or =90th percentile and in 100 subjects randomly selected from the control group. The oral glucose tolerance test was performed in all the subjects with fasting glucose > or =5.6 mmol/L. RESULTS: Eighty-one impaired fasting glucose subjects and one girl with type 2 diabetes were identified. The prevalence of impaired fasting glucose in PHP/HP (7.03%) was not significantly different from that in the OW/OB + PHP/HP group (8.59%), but was higher than that in the OW/OB group (3.31%). CONCLUSION: Although the American Diabetes Association does not recommend the FPG test for children and adolescents with PHP/HP, in this study, we found that children and adolescents with PHP/HP have a higher prevalence of impaired fasting glucose than those with OW/OB. Further validation of these findings is warranted and a type 2 diabetes screening protocol for Chinese children and adolescents needs to be established.

Mechanisms of Adsorption of Heavy Metal Cations from Waters by an Amino Bio-Based Resin Derived from Rosin.

Rosin derived from conifer trees is used as the basis for a novel environmentally-friendly adsorbent prepared from a sustainable resource. After treatment with ethylenediamine, ethylenediamine rosin-based resin (EDAR) is produced, which possesses cation exchange capacity that is comparable to that of the best commercial synthetic resins. This is demonstrated by its application to the removal of Pb, Cd, and Cu from water, in single and multicomponent systems. Maximum uptake was obtained at pH 5 and in the order Pb(II) > Cd(II) > Cu(II). The maximum adsorption of Pb was ~1.8 mmol/g, but the adsorption process resembled the Freundlich isotherm, whereas the adsorption of Cd(II) and Cu(II) followed the Langmuir isotherm. In the multicomponent systems, there was direct competition between Pb and Cd for sorption sites, whereas the results with Cu indicated it had a preference for different types of sites compared to Pb and Cd. The EDAR resin could be efficiently regenerated and used repeatedly with only a small decrease in performance. Characterization of EDAR, and investigations of its adsorption mechanisms using physical, spectroscopic, and theoretical techniques, including fourier transform infrared spectroscopy (FTIR), 13C nuclear magnetic resonance (13C NMR), scanning electron microscope (SEM), Brunauer Emmett Teller (BET) method, elemental analysis, thermogravimetric analysis (TGA), and molecular dynamics calculations, showed that amino groups have a critical role in determining the cation adsorption properties. We conclude that this new adsorbent derived from an abundant natural material has the potential to make valuable contributions to the routine removal of heavy metal ions (HMs) from drinking water and wastewater.

[Evaluation of Performance of an Aminated Rosin-based Resin for Adsorption of Norfloxacin from Aqueous Solutions].

An aminated rosin-based resin (ARBR) was synthesized as a novel environmentally-friendly adsorbent for removal of Norfloxacin (NOR) from aqueous solutions. Its features were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and surface area measurements (BET). The effects of resin dosage, pH, and ionic strength on the ARBR adsorption properties of NOR were investigated by batch experiments. Results showed that the NOR adsorption amounts increased with pH in the range from 2.0 to 6.0, but decreased at higher pH (8-10). The adsorption process of NOR followed a pseudo-second rate model and could be fitted to the Langmuir isotherm, with calculated maximum monolayer adsorption capacity of 30.29 mg·g-1 at pH 6.0 and 20℃. Thermodynamic calculations showed that the adsorption of NOR was a spontaneous and endothermic process and could be attributed to a combination of electrostatic interactions and hydrogen bonding. Furthermore, the adsorbed NOR on ARBR could be efficiently desorbed by 0.1 mol·L-1 HCl to regenerate the resin. After five adsorption-desorption recycles, ARBR had a stable adsorption performance and could be recycled. The adsorption performance is better than that of various commercial resins, and these research results contribute to the development of applications of rosin derivatives and their utilization in the environmental control of micro pollutants.

Reanalysis and External Validation of a Decision Tree Model for Detecting Unrecognized Diabetes in Rural Chinese Individuals.

We reanalyzed previous data to develop a more simplified decision tree model as a screening tool for unrecognized diabetes, using basic information in Beijing community health records. Then, the model was validated in another rural town. Only three non-laboratory-based risk factors (age, BMI, and presence of hypertension) with fewer branches were used in the new model. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve (AUC) for detecting diabetes were calculated. The AUC values in internal and external validation groups were 0.708 and 0.629, respectively. Subjects with high risk of diabetes had significantly higher HOMA-IR, but no significant difference in HOMA-B was observed. This simple tool will help general practitioners and residents assess the risk of diabetes quickly and easily. This study also validates the strong associations of insulin resistance and early stage of diabetes, suggesting that more attention should be paid to the current model in rural Chinese adult populations.

Maternal inheritance of severe hypertriglyceridemia impairs glucose metabolism in offspring.

Maternally inherited familial hypercholesterolemia (FH) impairs glucose metabolism and increases cardiovascular risks in the offspring to a greater degree than paternal inherited FH. However, it remains unknown whether hypertriglyceridemia affects glucose metabolism via inheritance. In this study, we sought to compare the impact of maternally and paternally inherited hypertriglyceridemia on glucose and lipid metabolism in mice. ApoCIII transgenic mice with severe hypertriglyceridemia were mated with non-transgenic control mice to obtain 4 types of offspring: maternal non-transgenic control and maternal transgenic offspring, and paternal control and paternal transgenic offspring. Plasma triglycerides (TG), total cholesterol (TC), fasting plasma glucose (FPG) and fasting insulin (FINS) were measured. ApoCIII overexpression caused severe hypertriglyceridemia, but the transgenic female mice had unaltered fertility with normal pregnancy and birth of pups. The 4 groups of offspring had similar birth weight and growth rate. The plasma TG of maternal and paternal transgenic offspring were nearly 40-fold higher than maternal and paternal control mice, but there was no difference in plasma TG between maternal and paternal transgenic offspring. Although the FPG of the 4 groups of animals had no difference, the maternal transgenic mice showed impaired glucose tolerance, increased FINS levels and higher homeostasis model assessment insulin resistance index (HOMA-IR) than the other 3 groups. In conclusion, maternally inherited hypertriglyceridemia in ApoCIII transgenic mice displayed impaired glucose tolerance, hyperinsulinemia and increased HOMA-R, while paternally inherited hypertriglyceridemia did not have such impacts.

Interactions among related genes of renin-angiotensin system associated with type 2 diabetes.

OBJECTIVE: To explore the association between epistasis among related genes of the renin-angiotensin system (RAS) and type 2 diabetes. RESEARCH DESIGN AND METHODS: Gene polymorphisms were genotyped in 394 type 2 diabetic patients and 418 healthy control subjects in this case-control study. We used the multifactor dimensionality reduction method to identify gene-gene interactions. RESULTS: No single locus was associated with type 2 diabetes, except for the insert/deletion (I/D) polymorphism of the ACE gene in female subjects. In multi-locus analyses, in male subjects the model of rs2106809 (ACE2), rs220721 (Mas), rs699 (AGT), and I/D (ACE) was significant (P = 0.043). This combination was associated with a 4.00 times (95% CI 2.51-6.38; P < 0.0001) greater prevalence of type 2 diabetes. In female subjects, the model of rs2106809 (ACE2), I/D (ACE), and rs1403543 (AGTR2) was significant (P = 0.012). This three-locus combination was associated with a 2.76 times (1.91-3.97; P < 0.0001) greater prevalence of type 2 diabetes. CONCLUSIONS: Interactions among RAS-related genes were associated with type 2 diabetes in a Chinese population.

A simple tool detected diabetes and prediabetes in rural Chinese.

OBJECTIVE: To develop and evaluate a simple tool, using data collected in a rural Chinese general practice, to identify those at high risk of Type 2 diabetes (T2DM) and prediabetes (PDM). STUDY DESIGN AND SETTING: A total of 2,261 rural Chinese participants without known diabetes were used to derive and validate the models of T2DM and T2DM plus PDM. Logistic regression and classification tree analysis were used to build models. RESULTS: The significant risk factors included in the logistic regression method were age, body mass index, waist/hip ratio (WHR), duration of hypertension, family history of diabetes, and history of hypertension for T2DM and T2DM plus PDM. In the classification tree analysis, WHR and duration of hypertension were the most important determining factors in the T2DM and T2DM plus PDM model. The sensitivity, specificity, positive predictive value, negative predictive value, and receiver operating characteristic area for detecting T2DM were 74.6%, 71.6%, 23.6%, 96.0%, and 0.731, respectively. For PDM plus T2DM, the results were 65.3%, 72.5%, 33.2%, 90.7%, and 0.689, respectively. CONCLUSION: The classification tree model is a simple and accurate tool to identify those at high risk of T2DM and PDM. Central obesity strongly associates with T2DM in rural Chinese.