WLP3 Encodes the Ribosomal Protein L18 and Regulates Chloroplast Development in Rice.

Plastid ribosomal proteins play a crucial role in the growth and development of plants, mainly in the gene expression and translation of key genes in chloroplasts. While some information is known about the regulatory processes of plastid ribosomal proteins in various plant species, there is limited knowledge about the underlying mechanisms in rice. In this study, ethyl methanesulfonate (EMS) mutagenesis was used to generate a new mutant called wlp3 (white leaf and panicle3), characterized by white or albino leaves and panicles, which exhibited this phenotype from the second leaf stage until tillering. Furthermore, after a certain period, the newly emerging leaves developed the same phenotype as the rice variety ZH11, while the albino leaves of wlp3 showed an incomplete chloroplast structure and significantly low chlorophyll content. A transition mutation (T to C) at position 380 was identified in the coding region of the LOC_Os03g61260 gene, resulting in the substitution of isoleucine by threonine during translation. WLP3 encodes the ribosomal L18 subunit, which is localized in the chloroplast. Complementation experiments confirmed that LOC_Os03g61260 was responsible for the albino phenotype in rice. WLP3 has high expression in the coleoptile, leaves at the three-leaf stage, and panicles at the heading stage. Compared to the wild-type (WT), wlp3 exhibited reduced chlorophyll synthesis and significantly decreased expression levels of genes associated with plastid development. Yeast two-hybrid (Y2H) analysis revealed that WLP3 interacts with other ribosomal subunits, to influence chloroplast development. These results contribute to a better understanding of the underlying molecular mechanisms of chloroplast development and plastid gene translation.

GLP1R rs3765467 Polymorphism Is Associated with the Risk of Early Onset Type 2 Diabetes.

Objective: To investigate the relationship between glucagon-like peptide-1 receptor gene polymorphisms and susceptibility to early onset type 2 diabetes. Methods: Samples from 316 type 2 diabetes patients with early onset type 2 diabetes (n = 137) and late-onset type 2 diabetes (n = 179) and 145 nondiabetic individuals were analyzed. Multiplex PCR combined with resequencing Hi-Reseq technology was used to detect single nucleotide polymorphisms of the glucagon-like peptide-1 receptor gene, and the allele frequency, genotype distribution, and clinical parameters were analyzed between each diabetes subgroup and the control group. Results: Sixteen single nucleotide polymorphisms were identified in the exonic region of the glucagon-like peptide-1 receptor gene according to the minor allele frequency (MAF > 0.05) in the participants. Among these, the glucagon-like peptide-1 receptor rs3765467 (G⟶A) mutation was statistically associated with early onset type 2 diabetes. Compared with that of the GG carriers, carriers of genotype AA at rs3765467 had a decreased risk of early onset type 2 diabetes after adjusting for sex and body mass index. In the dominant model, the frequencies of the rs3765467 AA + GA genotype were significantly decreased in the early onset type 2 diabetes group, and carriers of genotype AA + GA at rs3765467 had a decreased risk of early onset type 2 diabetes after adjusting for sex and body mass index. Moreover, fasting C peptide levels were significantly higher in GA + AA genotype carriers than those in GG genotype carriers. Conclusion: The glucagon-like peptide 1 receptor rs3765467 polymorphism was significantly associated with age at type 2 diabetes diagnosis and thus may be used as a marker to screen and detect individuals at risk of developing early onset type 2 diabetes.

RDKG-115: Assisting drug repurposing and discovery for rare diseases by trimodal knowledge graph embedding.

Rare diseases (RDs) may affect individuals in small numbers, but they have a significant impact on a global scale. Accurate diagnosis of RDs is challenging, and there is a severe lack of drugs available for treatment. Pharmaceutical companies have shown a preference for drug repurposing from existing drugs developed for other diseases due to the high investment, high risk, and long cycle involved in RD drug development. Compared to traditional approaches, knowledge graph embedding (KGE) based methods are more efficient and convenient, as they treat drug repurposing as a link prediction task. KGE models allow for the enrichment of existing knowledge by incorporating multimodal information from various sources. In this study, we constructed RDKG-115, a rare disease knowledge graph involving 115 RDs, composed of 35,643 entities, 25 relations, and 5,539,839 refined triplets, based on 372,384 high-quality literature and 4 biomedical datasets: DRKG, Pathway Commons, PharmKG, and PMapp. Subsequently, we developed a trimodal KGE model containing structure, category, and description embeddings using reverse-hyperplane projection. We utilized this model to infer 4199 reliable new inferred triplets from RDKG-115. Finally, we calculated potential drugs and small molecules for each of the 115 RDs, taking multiple sclerosis as a case study. This study provides a paradigm for large-scale screening of drug repurposing and discovery for RDs, which will speed up the drug development process and ultimately benefit patients with RDs. The source code and data are available at https://github.com/ZhuChaoY/RDKG-115.

MDTips: a multimodal-data-based drug-target interaction prediction system fusing knowledge, gene expression profile, and structural data.

MOTIVATION: Screening new drug-target interactions (DTIs) by traditional experimental methods is costly and time-consuming. Recent advances in knowledge graphs, chemical linear notations, and genomic data enable researchers to develop computational-based-DTI models, which play a pivotal role in drug repurposing and discovery. However, there still needs to develop a multimodal fusion DTI model that integrates available heterogeneous data into a unified framework. RESULTS: We developed MDTips, a multimodal-data-based DTI prediction system, by fusing the knowledge graphs, gene expression profiles, and structural information of drugs/targets. MDTips yielded accurate and robust performance on DTI predictions. We found that multimodal fusion learning can fully consider the importance of each modality and incorporate information from multiple aspects, thus improving model performance. Extensive experimental results demonstrate that deep learning-based encoders (i.e. Attentive FP and Transformer) outperform traditional chemical descriptors/fingerprints, and MDTips outperforms other state-of-the-art prediction models. MDTips is designed to predict the input drugs' candidate targets, side effects, and indications with all available modalities. Via MDTips, we reverse-screened candidate targets of 6766 drugs, which can be used for drug repurposing and discovery. AVAILABILITY AND IMPLEMENTATION: https://github.com/XiaoqiongXia/MDTips and https://doi.org/10.5281/zenodo.7560544.

Multimodal reasoning based on knowledge graph embedding for specific diseases.

MOTIVATION: Knowledge Graph (KG) is becoming increasingly important in the biomedical field. Deriving new and reliable knowledge from existing knowledge by KG embedding technology is a cutting-edge method. Some add a variety of additional information to aid reasoning, namely multimodal reasoning. However, few works based on the existing biomedical KGs are focused on specific diseases. RESULTS: This work develops a construction and multimodal reasoning process of Specific Disease Knowledge Graphs (SDKGs). We construct SDKG-11, a SDKG set including five cancers, six non-cancer diseases, a combined Cancer5 and a combined Diseases11, aiming to discover new reliable knowledge and provide universal pre-trained knowledge for that specific disease field. SDKG-11 is obtained through original triplet extraction, standard entity set construction, entity linking and relation linking. We implement multimodal reasoning by reverse-hyperplane projection for SDKGs based on structure, category and description embeddings. Multimodal reasoning improves pre-existing models on all SDKGs using entity prediction task as the evaluation protocol. We verify the model's reliability in discovering new knowledge by manually proofreading predicted drug-gene, gene-disease and disease-drug pairs. Using embedding results as initialization parameters for the biomolecular interaction classification, we demonstrate the universality of embedding models. AVAILABILITY AND IMPLEMENTATION: The constructed SDKG-11 and the implementation by TensorFlow are available from https://github.com/ZhuChaoY/SDKG-11. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Novel ceruloplasmin gene mutation causing aceruloplasminemia with diabetes in a Chinese woman: a case report.

Hereditary aceruloplasminemia (ACP) is a rare adult-onset autosomal recessive disease characterized by a ceruloplasmin (CP) gene mutation and defective or absent CP function. In the present study, we report a case of ACP in a 34-year-old Chinese woman with diabetes, fatigue, anxiety, and progressive membrane loss with low hemoglobin associated with microcytosis. The fasting glucose level was 5.6-7.96 mmol/L. Postprandial blood glucose ranged from 6.8 to 9.6 mmol/L. The Stumvoll first-phase and second-phase insulin secretion disposition indices were very low, and the serum iron content was low, even though transferrin levels were normal. Moreover, the transferrin saturation was low (5%), and the ferritin level was extremely high, above 2,000 µg/L in the patient. Furthermore, her serum CP level was extremely low (<0.0183 g/L). Abdominal computed tomography (CT) examination showed moderate iron overload in the liver. Brain CT also showed a mildly increased density of the bilateral thalami and basal ganglia. Finally, gene analysis showed a rare homozygous mutation (c.146+1G>A) in the CP gene and was diagnosed with ACP. To date, less than 60 family cases of ACP have been reported worldwide, and only two cases of ACP have been reported in China. Here, we report a case of ACP accompanied by diabetes with a novel mutation of the CP gene, which suggests that increased awareness should be highlighted in this disorder as diabetes is an important typical symptom.

Attention-Based Deep Multiple-Instance Learning for Classifying Circular RNA and Other Long Non-Coding RNA.

Circular RNA (circRNA) is a distinguishable circular formed long non-coding RNA (lncRNA), which has specific roles in transcriptional regulation, multiple biological processes. The identification of circRNA from other lncRNA is necessary for relevant research. In this study, we designed attention-based multi-instance learning (MIL) network architecture fed with a raw sequence, to learn the sparse features of RNA sequences and to accomplish the circRNAs identification task. The model outperformed the state-of-art models. Moreover, following the validation of the attention mechanism effectiveness by the handwritten digit dataset, the key sequence loci underlying circRNA's recognition were obtained based on the corresponding attention score. Then, motif enrichment analysis identified some of the key motifs for circRNA formation. In conclusion, we designed deep learning network architecture suitable for learning gene sequences with sparse features and implemented it for the circRNA identification task, and the model has strong representation capability in the indication of some key loci.

SIRT6 controls hepatic lipogenesis by suppressing LXR, ChREBP, and SREBP1.

Fatty liver disease is the most prevalent chronic liver disorder, which is manifested by hepatic triglyceride elevation, inflammation, and fibrosis. Sirtuin 6 (Sirt6), an NAD+-dependent deacetylase, has been implicated in hepatic glucose and lipid metabolism; however, the underlying mechanisms are incompletely understood. The aim of this study was to identify and characterize novel players and mechanisms that are responsible for the Sirt6-mediated metabolic regulation in the liver. We generated and characterized Sirt6 liver-specific knockout mice regarding its role in the development of fatty liver disease. We used cell models to validate the molecular alterations observed in the animal models. Biochemical and molecular biological approaches were used to illustrate protein-protein interactions and gene regulation. Our data show that Sirt6 liver-specific knockout mice develop more severe fatty liver disease than wild-type mice do on a Western diet. Hepatic Sirt6 deficiency leads to elevated levels and transcriptional activities of carbohydrate response element binding protein (ChREBP) and sterol regulatory element binding protein 1 (SREBP1). Mechanistically, our data reveal protein-protein interactions between Sirt6 and liver X receptor α (LXRα), ChREBP, or SREBP1c in hepatocytes. Moreover, Sirt6 suppresses transcriptional activities of LXRα, ChREBP, and SREBP1c through direct deacetylation. In conclusion, this work has identified a key mechanism that is responsible for the salutary function of Sirt6 in the inhibition of hepatic lipogenesis by suppressing LXR, ChREBP, and SREBP1.

Serum Glycated Albumin Levels Are Affected by Alcohol in Men of the Jinuo Ethnic Group in China.

AIM: To investigate the effects of alcohol on serum glycated albumin (GA) levels in Chinese men. METHODS: A total of 2314 male subjects from the Jinuo ethnic group in China were enrolled. Of these, 986 subjects drank alcohol frequently and 404 subjects did not. Lifestyle information was gathered by using a questionnaire, and measurements of blood pressure, body mass index, blood glucose level, liver function, and kidney function were collected. GA was measured by using an enzymatic method. Frequent drinking was defined as a history of drinking ethanol > 80 g/d within the past two weeks. Nondrinking was defined as no alcohol consumption in the past three months. Subjects with an alcohol intake between 0 and 80 g/d in the past two weeks were included in the drinking-occasionally group. Analysis of variance (ANOVA), correlation analysis, and linear regression were used to evaluate the effects of drinking on serum GA levels. Decision tree regression (DTR) algorithm was used to evaluate the effect of features (variables) on GA levels. RESULTS: We found that male subjects who drank frequently had significantly lower serum GA levels than subjects who did not drink (13.0 ± 1.7 vs. 14.1 ± 3.7, p < 0.05). Spearman's correlation analysis calculated a coefficient of -0.152 between drinking and GA (p < 0.005). Linear regression established that drinking was an independent predictor for GA levels with a standardized regression coefficient of -0.144 (p < 0.05). Decision tree regression showed that the effect of drinking on GA levels (0.0283) is five times higher than that of smoking (0.0057). CONCLUSIONS: Frequent alcohol consumption could result in decreased GA levels in men of the Jinuo ethnic group in China.

The 14-3-3 protein YWHAB inhibits glucagon-induced hepatic gluconeogenesis through interacting with the glucagon receptor and FOXO1.

Glucagon antagonism has been reported as a new therapeutic approach to hyperglycaemia. As the 14-3-3 protein YWHAB has been identified as a regulator of the glucagon receptor (GCGR) by affinity purification and mass spectrometry, we examined the role of YWHAB in vivo. Ywhab knockout mice display impaired blood glucose homeostasis only under pyruvate stimulation. Deletion of Ywhab in mouse primary hepatocytes (MPHs) increases hepatocyte glucose production by magnifying the effect of glucagon. Mechanistic analysis indicates that YWHAB forms a phosphorylation-dependent complex with GCGR and directly interacts with forkhead box O1 (FOXO1). Together, these results reveal the inhibitory role of YWHAB in glucagon-mediated hepatic glucose production, which may be a potential target for the control of gluconeogenesis and associated metabolic diseases.

Liraglutide Alleviates Hepatic Steatosis by Activating the TFEB-Regulated Autophagy-Lysosomal Pathway.

Liraglutide, a glucagon-like peptide-1 receptor agonist (GLP-1RA), has been demonstrated to alleviate non-alcoholic fatty liver disease (NAFLD). However, the underlying mechanism has not been fully elucidated. Increasing evidence suggests that autophagy is involved in the pathogenesis of hepatic steatosis. In this study, we examined whether liraglutide could alleviate hepatic steatosis through autophagy-dependent lipid degradation and investigated the underlying mechanisms. Herein, the effects of liraglutide on NAFLD were evaluated in a high-fat diet (HFD)-induced mouse model of NAFLD as well as in mouse primary and HepG2 hepatocytes exposed to palmitic acid (PA). The expression of the GLP-1 receptor (GLP-1R) was measured in vivo and in vitro. Oil red O staining was performed to detect lipid accumulation in hepatocytes. Electron microscopy was used to observe the morphology of autophagic vesicles and autolysosomes. Autophagic flux activity was measured by infecting HepG2 cells with mRFP-GFP-LC3 adenovirus. The roles of GLP-1R and transcription factor EB (TFEB) in autophagy-lysosomal activation were explored using small interfering RNA. Liraglutide treatment alleviated hepatic steatosis in vivo and in vitro. In models of hepatic steatosis, microtubule-associated protein 1B light chain-3-II (LC3-II) and SQSTM1/P62 levels were elevated in parallel to blockade of autophagic flux. Liraglutide treatment restored autophagic activity by improving lysosomal function. Furthermore, treatment with autophagy inhibitor chloroquine weakened liraglutide-induced autophagy activation and lipid degradation. TFEB has been identified as a key regulator of lysosome biogenesis and autophagy. The protein levels of nuclear TFEB and its downstream targets CTSB and LAMP1 were decreased in hepatocytes treated with PA, and these decreases were reversed by liraglutide treatment. Knockdown of TFEB expression compromised the effects of liraglutide on lysosome biogenesis and hepatic lipid accumulation. Mechanistically, GLP-1R expression was decreased in HFD mouse livers as well as PA-stimulated hepatocytes, and liraglutide treatment reversed the downregulation of GLP-1R expression in vivo and in vitro. Moreover, GLP-1R inhibition could mimic the effect of the TFEB downregulation-mediated decrease in lysosome biogenesis. Thus, our findings suggest that liraglutide attenuated hepatic steatosis via restoring autophagic flux, specifically the GLP-1R-TFEB-mediated autophagy-lysosomal pathway.

Long non-coding RNA MALAT1 regulates oxaliplatin-resistance via miR-324-3p/ADAM17 axis in colorectal cancer cells.

BACKGROUND: Colorectal cancer (CRC) is one of the most general malignant tumors. Accumulating evidence implied that long non-coding RNA Metastasis Associated Lung Adenocarcinoma Transcript 1 (MALAT1) participated in the tumorigenesis of CRC. However, the effect of MALAT1 in drug-resistance needed to be further illustrated. METHODS: Levels of MALAT1, microRNA (miR)-324-3p, and a disintegrin and metalloprotease metallopeptidase domain 17 (ADAM17) were detected using quantitative real-time polymerase chain reaction (qRT-PCR) or western blot assay. Cell Counting Kit 8 (CCK-8) was used to assess the half maximal inhibitory concentration (IC50) of oxaliplatin (Ox). Meanwhile, cell proliferation, migration and apoptosis were detected by CCK-8, transwell assay, and flow cytometry, respectively. The interaction between miR-324-3p and MALAT1 or ADAM17 was clarified by dual-luciferase reporter assay. Also, the effect of MALAT1 on tumor growth was detected in xenograft tumor mice treated with Ox. RESULTS: Significant up regulation of MALAT1 and ADAM17, and decrease of miR-324-3p were observed in Ox-resistant CRC tissues and cells. MALAT1 deficiency enhanced the sensitivity of Ox-resistant CRC cells response to Ox, while miR-324-3p repression or ADAM17 acceleration could overturn this effect. Moreover, MALAT1 silencing repressed tumor growth in Ox-treated nude mice. Mechanically, MALAT1 exerted promotion effect on the resistance response to Ox via miR-324-3p/ADAM17 axis in Ox-resistant CRC cells. CONCLUSION: MALAT1 modulated the sensitivity of Ox through ADAM17 in Ox-resistant CRC cells by sponging miR-324-3p, thus MALAT1 might serve as a novel insight for the therapy of CRC.

MicroRNA-1469-5p promotes the invasion and proliferation of pancreatic cancer cells via direct regulating the NDRG1/NF-κB/E-cadherin axis.

Numerous studies demonstrated that microRNAs (miRNAs) were highly involved in pancreatic cancer development. However, the functional roles of many miRNAs remain elusive in pancreatic cancer. In the present study, we analyzed previous published microarray data and found that miR-1469-5p was one of top upregulated miRNAs in pancreatic tumors. Our further study showed that miR-1469-5p was highly expressed in collected pancreatic tumors and its upregulation was associated with lymph node metastasis and tumors of advanced TNM stage. Functional analysis with miR-1469-5p inhibitor showed that downregulation of miR-1469-5p repressed pancreatic cancer cell proliferation and invasion. Mechanistically, miR-1469-5p directly interacted with metastasis suppressor NDRG1 mRNA and downregulated expression of NDRG1 to activate NF-κB pathway in pancreatic cancer cells. It was also found that miR-1469-5p decreased expression of E-cadherin, a metastasis related gene repressed by NF-κB pathway, in pancreatic cancer cells. Transfection of NDRG1 small interference RNA (siRNA) attenuated the function of miR-1469-5p inhibitor in pancreatic cancer cells. Moreover, miR-1469-5p expression was negatively associated with NDRG1 and E-cadherin mRNA levels in pancreatic tumors. Taken together, miR-1469-5p may exert its oncogenic potential in pancreatic cancer via regulating a NDRG1/NF-κB/E-cadherin axis, suggesting that it may be clinically valuable as a prognostic biomarker of pancreatic cancer.

Autonomic function as indicated by heart rate deceleration capacity and deceleration runs in type 2 diabetes patients with or without essential hypertension.

PURPOSE: Sympathovagal imbalance is a common underlying disorder in hypertension and diabetes. This study characterized autonomic nervous system function, indicated by heart rate deceleration capacity (DC) and deceleration runs (DRs), in patients with type 2 diabetes mellitus (T2DM), with or without concomitant essential hypertension. SUBJECTS AND METHODS: We recruited 50 healthy subjects, 50 patients with T2DM, and 95 with T2DM and essential hypertension. DC, DRs (DR2, DR4, and DR8, ie, episodes of 2, 4, or 8 consecutive beat-to-beat heart rate decelerations, respectively), and heart rate variability were determined by dynamic electrocardiogram. Biochemical markers of glucose and lipid metabolism, including glycated hemoglobin (HbA1c) and high-density lipoprotein cholesterol (HDL-C), were measured from blood samples. RESULTS: Both T2DM groups featured lower DC, SD of all normal-to-normal sinus RR intervals over 24 h (SDNN), root mean square of the successive normal sinus RR interval difference, and all DR values, but higher average heart rate (AHR) and acceleration capacity (AC), than healthy subjects. There were significant associations between the following: DC and HbA1c, systolic blood pressure (SBP), AHR, age, and HDL-C; DR2 and AHR, SBP, and HbA1c; DR4 and HbA1c, age, SBP, and HDL-C; and DR8 and HbA1c, AHR, and age. In both T2DM groups, HbA1c correlated negatively with DC, DR2, and SDNN, and positively with AC and AHR; homeostasis model assessment-insulin resistance index correlated negatively with DC, all DRs, and SDNN, and positively with AC. CONCLUSION: Compared with healthy subjects, T2DM patients with or without essential hypertension have lower DC and DRs. DC and DRs correlate negatively with blood glucose and insulin resistance index.

siRNA Targeting of the SNCG Gene Inhibits the Growth of Gastric Carcinoma SGC7901 Cells in vitro and in vivo by Downregulating the Phosphorylation of AKT/ERK.

The aim of the study was to evaluate the effects of synuclein-γ (SNCG) silencing on gastric cancer SGC7901 cells and to elucidate the associated mechanisms. pGCSIL-lentiviral siRNA targeting of the SNCG gene was employed to inhibit SNCG expression. Several experiments such as quantitative real-time PCR, Western blotting, MTT, colony formation, migration assay, and flow cytometry were performed to investigate the biological behavior of infected SGC7901 cells. BALB/c nude mice were used as tumor xenograft models to assess the effects of SNCG silencing on tumor growth. Western blot analysis was carried out to determine the relative levels of AKT, p-AKT, ERK, and p-ERK expression. Our results showed that SNCG was overexpressed in SGC7901 cells as compared to normal gastric mucosal epithelial cells. SGC7901 cells transfected with SNCG siRNA demonstrated significantly decreased gastric cancer growth (p < 0.01), reduced cell migration, cell cycle arrest in the G0/G1 phase, promoted tumor cell apoptosis (p < 0.01), and inhibited tumorigenesis in xenograft animal models. Western blot analysis indicated that the protein levels of p-AKT and p-ERK were much lower in the SNCG siRNA group than in the control groups. The results of the present study suggest that SNCG siRNA plays a significant role in the proliferation, migration, and tumorigenesis of gastric cancer by downregulating the phosphorylation of AKT and ERK. RNA interference-mediated silencing of SNCG may provide an opportunity to develop a novel treatment strategy for gastric cancer.

Knockdown of Latent Transforming Growth Factor-ß (TGF-ß)-Binding Protein 2 (LTBP2) Inhibits Invasion and Tumorigenesis in Thyroid Carcinoma Cells.

Latent transforming growth factor-ß (TGF-ß)-binding protein 2 (LTBP2) is one of four proteins in the LTBP family of proteins (LTBP1-4) and was shown to play a vital role in tumorigenesis. However, little is known regarding the functional role of LTBP2 in thyroid carcinoma. Therefore, the current study aimed to evaluate the effect of LTBP2 expression on the proliferation, invasion, and tumorigenesis in thyroid carcinoma cells and to explore the molecular mechanism of LTBP2 in tumor progression. Our results showed that the expression of LTBP2 is upregulated in human thyroid carcinoma and cell lines. Knockdown of LTBP2 inhibits the proliferation, invasion, and EMT phenotype in thyroid carcinoma cells. Furthermore, knockdown of LTBP2 attenuates thyroid carcinoma growth in nude mice. Finally, knockdown of LTBP2 inhibits activation of the PI3K/Akt pathway in thyroid carcinoma cells. In summary, the present study has provided further evidence that knockdown of LTBP2 inhibits invasion and tumorigenesis in thyroid carcinoma cells. Our findings may help to further elucidate the molecular mechanisms underlying thyroid carcinoma progression and provide candidate targets for the prevention and treatment of thyroid carcinoma.

Factors associated with lower extremity atherosclerotic disease in Chinese patients with type 2 diabetes mellitus: A case-control study.

Early detection and treatment of lower extremity atherosclerotic disease (LEAD), and controlling its risk factors are critical in preventing amputation and death in diabetic patients. This study aimed to investigate the factors associated with LEAD in Chinese diabetic patients.In this case-control study, patients with type 2 diabetes mellitus (T2DM) (N = 1289) were divided into 2 groups according to the ultrasonic Doppler examination: with (LEAD+, n = 737) and without (LEAD-, n = 552) LEAD. In subgroup analysis, the LEAD+ group was divided based on the diameter of lower-extremity arteries: LEAD+A (1%-49% reduction) and LEAD+B (≥50% reduction). Clinical and demographic data of patients were analyzed.Compared with the LEAD- group, serum creatinine levels were significantly increased (P < 0.001), whereas glomerular filtration rate (GFR) was significantly decreased (P < 0.001) in the LEAD+ group. Multivariate analysis results showed that GFR (odds ratio [OR] 0.991, 95% confidence interval [CI] 0.986-0.997, P = 0.003), diabetes duration (OR 1.055, 95% CI 1.026-1.084, P < 0.001), age (OR 1.123, 95% CI 1.104-1.142, P < 0.001), and uric acid (OR 1.002, 95% CI 1.000-1.004, P = 0.031) were independently associated with LEAD in patients with T2DM. Furthermore, multivariate analysis showed that age (OR 1.078, 95% CI 1.048-1.109, P < 0.001) and GFR (OR 0.985, 95% CI 0.975-0.994, P = 0.002) were independently associated with the severity of arterial lesions in patients with T2DM and LEAD.The risk factors of LEAD in Chinese patients with T2DM include age, course of disease, uric acid, and GFR. Patients with T2DM, high uric acid levels, and declined GFR could be listed in the high-risk group for LEAD.

Association of Genetic Variants of SIRT1 With Type 2 Diabetes Mellitus.

SIRT1 has been demonstrated in nutrient-sensing and insulin-signaling pathways in in vivo and in vitro experiments, but there is minimal information concerning the association between gene polymorphisms of SIRT1 and type 2 diabetes mellitus (T2DM) in a Chinese Han population. Using case-control design, we recruited 310 unrelated T2DM patients from inpatients at Shanghai Jiao Tong University Affiliated Sixth People's Hospital, while 301 healthy controls were volunteers from the community for regular medical checkup. All participants were genotyped within the SIRT1 region. The following five SNPs rs10509291, rs12778366, rs10997870, rs10823112, and rs4746720 cover 100% of common genetic variations (minor allele frequency≥0.05) within the SIRT1 gene (r2≥0.8). The genotypes of SIRT1 gene polymorphisms were analyzed by the Snapshot assay and DNA sequencing. The resulting data show that there was significant genetic differentiation in rs10823112 [p=0.003; OR (95% CI)=1.515 (1.152-1.994) for genotype], rs4746720 [p=0.024; OR (95% CI)=1.37 (1.037-1.674) for genotype], and rs10509291 [p=0.002; OR (95% CI)=1.551 (1.179-2.04) for genotype] between T2DM and control subjects. However, the result of rs4746720 was no longer significant after correction for multiple testing (p after Bonferroni correction=0.12); the results of rs10509291and rs10823112 were still significantly different between the two groups (p after Bonferroni correction=0.01 and 0.015, respectively). Linear regression analyses adjusting for age, gender, and body mass index (BMI) showed that HbA1c and HOMA-IR in subjects with rs10509291 AA genotype were higher than those with TT genotype in T2DM group (p=0.045, p=0.035, respectively). Together, our data show that genetic variation of the SIRT1 gene is related to insulin resistance and increase risk of T2DM in Chinese Han population. The risk allele A at SIRT1 rs10509291 was closely associated with T2DM, and subjects who were homozygous of the A allele were more likely to develop T2DM.

Pioglitazone lowers serum retinol binding protein 4 by suppressing its expression in adipose tissue of obese rats.

BACKGROUND/AIMS: Pioglitazone, a peroxisome proliferator-activated receptor γ activator, is clinically used to treat insulin resistance. However, the underlying mechanism of pioglitazone's action remains unclear. We investigated whether, and how, pioglitazone modulates serum level of retinol binding protein 4 (RBP4), an adipocytokine associated with obesity and insulin resistance. METHODS: Insulin sensitivity was determined by oral glucose tolerance test, and RBP4 expression was detected by RT-PCR and Western blotting. RESULTS: Pioglitazone treatment significantly decreased serum RBP4 levels in obese rats, which was correlated with reduced body weight and increased insulin sensitivity. Moreover, pioglitazone greatly decreased RBP4 mRNA and protein levels in adipose tissue but not in the liver. Consistently, pioglitazone treatment significantly reduced RBP4 protein expression in 3T3-L1 adipocytes but not in HepG2 cells. CONCLUSION: These results demonstrate that pioglitazone inhibits the level of serum RPB4 by suppressing RBP4 expression in adipose tissue of obese rats, suggesting that inhibiting RBP4 expression in adipocytes may provide a mechanism by which pioglitazone improves insulin sensitivity in insulin-resistant subjects.

[Expression and regulation of retinol binding protein 4 mRNA in human adipose tissue in obese and type 2 diabetics].

OBJECTIVE: To study the RBP4 mRNA expression between subcutaneous and visceral adipose tissue in obese and type 2 diabetic patients and to investigate the factors that influence RBP4 mRNA expression in Human visceral adipose tissue. METHODS: 9 individuals with normal weight normal glucose regulation subjects, 9 obesity subjects and 9 type 2 diabetes subjects were enrolled. All of the subjects were prepared to undergone an operation because of nondiabetes disease. Subcutaneous and visceral adipose tissue were taken out as soon as cultured. RT-PCR and Real-time PCR were used to assay the relative expression of RBP4 mRNA. RESULTS: RBP4 mRNA level in visceral adipose tissue of obesity group was (2.10 +/- 1.84), and that of type 2 diabetes group was (1.54 +/- 0.46), both were significantly higher than that in normal weight normal glucose group (0.75 +/- 0.28, P < 0.01, P < 0.05). RBP4 mRNA level in subcutaneous adipose tissue of the three groups were (1.05 +/- 0.15 vs 0.99 +/- 0.14 vs 1.13 +/- 0.07), no difference among them(P > 0.05). Insulin, dexamethasone, pioglitazone, free fatty acids can significantly increase RBP4 mRNA expression, compared with the control group, respectively, have an increase of 2.13 times, 0.84 times, 2.04 times, 4.88 times; however, tumor necrosis factor-alpha can significantly lower RBP4 mRNA level, compared with the control group decreased by 38%. CONCLUSION: RBP4 mRNA expression in visceral adipose tissue were significantly higher in obesity and type 2 diabetes subjects. In vitro system, RBP4 gene expression in visceral adipose tissue of normal weight normal glucose subjects was regulated by insulin, dexamethasone, pioglitazone, palmitic acid and TNF-alpha, such factors were also participated in the pathophysiological process of insulin resistance and type 2 diabetes.