Effect of hepatic lipase -514C->T polymorphism and its interactions with apolipoprotein C3 -482C->T and apolipoprotein E exon 4 polymorphisms on the risk of nephropathy in chinese type 2 diabetic patients

Apolipoprotein C3 genetic polymorphisms are associated with lipids and coronary artery disease in a Chinese population

BACKGROUND

The disorder of triglyceride (TG) metabolism leading to hypertriglyceridemia is an independent risk factor for coronary artery disease (CAD). Variants in the apolipoprotein C3 (APOC3) gene were found to be associated with elevated TG levels. The purpose of this study was to investigate the effect of two polymorphisms (1100 C/T and 3238 C/G) of APOC3 on plasma lipid and risk of CAD in a Chinese population.

METHODS

The study population consisted of 600 patients with CAD and 600 age- and gender-matched controls. The APOC3 gene polymorphism was analyzed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP).

RESULTS

Patients with CAD had a significantly higher frequency of APOC3 3238 GG genotype [odds ratio (OR) =1.64, 95% confidence interval (CI) =1.10, 2.43; P = 0.01] and APOC3 3238 G allele (OR =1.27, 95% CI =1.04, 1.55; P = 0.02) than controls. The findings are still emphatic by the Bonferroni correction. When stratifying by hyperlipidemia, CAD patients with hyperlipidemia had a significantly higher frequency of APOC3 3238 GG genotype (OR =1.73, 95% CI =1.13, 2.64; P = 0.01) than without hyperlipidemia. The APOC3 3238 G allele was significantly associated with increasing plasma TG levels and very-low-density lipoprotein cholesterol (VLDL-C) levels both in cases and controls (P < 0.001).

CONCLUSIONS

The APOC3 3238 G allele might contribute to an increased risk of CAD as a result of its effect on TG and VLDL-C metabolism.

Diabetes and its comorbidities--where East meets West

Fetal programming associated with in utero exposure to maternal stress is thought to alter gene expression, resulting in phenotypes that promote survival in a pathogen-rich and nutrient-poor environment but substantially increase the risk of cardiovascular, metabolic and renal disorders (such as diabetes mellitus) in adults with obesity. These (epi)genetic phenomena are modified by environmental and socioeconomic factors, resulting in multiple subphenotypes and clinical consequences. In individuals from areas undergoing rapid economic development, which is associated with a transition from communicable to noncommunicable diseases, an efficient innate immune response can exaggerate obesity-associated inflammation. By contrast, in individuals with a genetic predisposition to autoimmune or monogenic diabetes mellitus, obesity can lead to atypical presentation of diabetes mellitus, termed 'double diabetes mellitus'. The increasingly young age at diagnosis of diabetes mellitus in developing countries results in prolonged exposure to glucolipotoxicity, low-grade inflammation and increased oxidative stress, which put enormous strain on pancreatic β cells and renal function. These conditions create a metabolic milieu conducive to cancer growth. This Review discusses how rapid changes in technology and human behaviour have brought on the global epidemic of metabolic diseases, and suggests that solutions will be based on using system change, technology and behavioural strategies to combat this societal-turned-medical problem.

Using a multi-staged strategy based on machine learning and mathematical modeling to predict genotype-phenotype risk patterns in diabetic kidney disease: a prospective case-control cohort analysis

Background

Multi-causality and heterogeneity of phenotypes and genotypes characterize complex diseases. In a database with comprehensive collection of phenotypes and genotypes, we compared the performance of common machine learning methods to generate mathematical models to predict diabetic kidney disease (DKD).

Methods

In a prospective cohort of type 2 diabetic patients, we selected 119 subjects with DKD and 554 without DKD at enrolment and after a median follow-up period of 7.8 years for model training, testing and validation using seven machine learning methods (partial least square regression, the classification and regression tree, the C5.0 decision tree, random forest, naïve Bayes classification, neural network and support vector machine). We used 17 clinical attributes and 70 single nucleotide polymorphisms (SNPs) of 54 candidate genes to build different models. The top attributes selected by the best-performing models were then used to build models with performance comparable to those using the entire dataset.

Results

Age, age of diagnosis, systolic blood pressure and genetic polymorphisms of uteroglobin and lipid metabolism were selected by most methods. Models generated by support vector machine (svmRadial) and random forest (cforest) had the best prediction accuracy whereas models derived from naïve Bayes classifier and partial least squares regression had the least optimal performance. Using 10 clinical attributes (systolic and diastolic blood pressure, age, age of diagnosis, triglyceride, white blood cell count, total cholesterol, waist to hip ratio, LDL cholesterol, and alcohol intake) and 5 genetic attributes (UGB G38A, LIPC -514C > T, APOB Thr71Ile, APOC3 3206T > G and APOC3 1100C > T), selected most often by SVM and cforest, we were able to build high-performance models.

Conclusions

Amongst different machine learning methods, svmRadial and cforest had the best performance. Genetic polymorphisms related to inflammation and lipid metabolism warrant further investigation for their associations with DKD.

The Complexity of Vascular and Non-Vascular Complications of Diabetes: The Hong Kong Diabetes Registry

Diabetes is a complex disease characterized by chronic hyperglycemia and multiple phenotypes. In 1995, we used a doctor-nurse-clerk team and structured protocol to establish the Hong Kong Diabetes Registry in a quality improvement program. By 2009, we had accrued 2616 clinical events in 9588 Chinese type 2 diabetic patients with a follow-up duration of 6 years. The detailed phenotypes at enrollment and follow-up medications have allowed us to develop a series of risk equations to predict multiple endpoints with high sensitivity and specificity. In this prospective database, we were able to validate findings from clinical trials in real practice, confirm close links between cardiovascular and renal disease, and demonstrate the emerging importance of cancer as a leading cause of death. In addition to serving as a tool for risk stratification and quality assurance, ongoing data analysis of the registry also reveals secular changes in disease patterns and identifies unmet needs.

Biphasic insulin aspart 30 as insulin initiation or replacement therapy: the China cohort of the IMPROVE study

AIMS

To explore safety and efficacy of BIAsp 30 as initiation or replacement therapy in routine clinical practice in patients with poorly controlled diabetes in the Chinese cohort of the IMPROVE study.

METHODS

In the 26-week, non-interventional, observational study, Chinese subjects with diabetes started BIAsp 30 treatment in routine care. Data from patients' diaries and medical records were transferred to CRFs by participating physicians.

CLINICAL TRIAL REGISTRATION

NCT00659282.

RESULTS

Of the 21,729 subjects enrolled (mean age 54.0 years, BMI 24.6 kg/m 2 , diabetes duration 4.86 years), 32.3% were treatment-naïve, 59.3% were from oral anti-diabetic drugs (OADs) only and 8.1% were from insulin +/- OADs. Overall, mean HbA(1c) and FBG decreased by 2.82% and 5 mmol/L, respectively. In the subgroups, changes were: -3.27% and -6.06 mmol/L (treatment-naïve), -2.57% and -4.54 mmol/L (OADs only), -2.96% and 3.51 mmol/L (insulin +/- OADs) all p < 0.05. HbA(1c) < 7% was achieved by 71.4% of patients. Only 0.1% of subjects reported major hypoglycaemia and 73 SADRs were observed without significant difference compared to those at baseline. Body weight did not change significantly.

CONCLUSIONS

Regardless of previous treatments, insulin initiation or replacement with BIAsp 30 improved glycaemic control without increasing major hypoglycaemia or weight gain in Chinese patients with diabetes.

Phenotype-genotype interactions on renal function in type 2 diabetes: an analysis using structural equation modelling

AIMS/HYPOTHESIS

Cardiovascular and renal diseases share common risk factors. We used structural equation modelling (SEM) to evaluate the independent and combined effects of phenotypes and genotypes implicated in cardiovascular diseases on renal function in type 2 diabetes.

METHODS

1,188 type 2 diabetic patients were stratified into high-risk and low-risk groups according to bimodal distributions of the logarithmically transformed (log(e)) urinary albumin:creatinine ratio and plasma creatinine levels. Models for these groups, comprising continuous and non-ranking categorical data, were developed separately to evaluate the inter-relationships among measured variables and latent factors using non-linear SEMs, Bayesian estimation and model selection as assessed by a goodness-of-fit statistic.

RESULTS

Inter-correlated measured variables (obesity, glycaemia, lipid, blood pressure) and variants of the genes encoding endothelial nitric oxide synthase (NOS), beta-adrenergic receptor (ADRB), components of the renin-angiotensin system (RAS) and lipid metabolism were loaded onto their respective latent factors of phenotypes and genotypes. In addition to direct and indirect effects, latent factors of obesity, lipid and BP interacted with latent factors of ADRB and RAS genotypes to influence renal function. Together with variants of the genes encoding peroxisome proliferator-activated receptor gamma, atrial natriuretic peptide, adducin, G protein beta(3) subunit, epithelial sodium channel alpha subunit and matrix metallopeptidase 3, these parameters explained 39-80% of the variance in renal function in the high-risk and low-risk models.

CONCLUSIONS/INTERPRETATION

SEM is a useful tool for confirming and quantifying multiple interactions of biological pathways with genetic determinants. The combined and interactive effects of blood pressure, lipid and obesity on renal function may have therapeutic implications, especially in type 2 diabetic individuals with genetic risk factors.

The relationship of the apolipoprotein E gene polymorphism Turkish Type 2 diabetic patients with and without nephropathy

OBJECTIVE

Apolipoprotein E (ApoE) genetic variation which is a major constituent of plasma lipoproteins causes diabetic nephropathy progress. Chronic kidney disease is associated with increased E2 allele and the decreased E4 allele risk. The aim of this study was to investigate the association between ApoE gene polymorphism in the development of diabetic nephropathy in Type 2 diabetes Turkish patients.

RESEARCH DESIGN AND METHODS

The objective of the study is to investigate the influence of ApoE gene polymorphism in the development of diabetic nephropathy in Turkish Type 2 diabetes. The ApoE genotypes were determined retrospectively in 46 patients with nephropathy and 56 without nephropathy and a control group of 35 healthy individuals. Genomic DNA was extracted from peripheral leukocytes of the subjects using the High Pure PCR Template Preparation Kit. For the detection of the presence of the three ApoE E alleles epsilon2, epsilon3, and epsilon4 (codon 112 and 158) were analyzed by the commercial LightCycler ApoE Mutation Detection Kit.

RESULTS

No differences in ApoE genotype or the allelic frequencies of epsilon2, epsilon3 or epsilon4 were found between the Type 2 diabetic patient group (with and without nephropathy) and a control group.

CONCLUSIONS

We conclude that the ApoE gene polymorphism is not associated with the development of diabetic nephropathy in Turkish Type 2 diabetic patients. Lack of association between ApoE gene polymorphism and Type 2 diabetic nephropathy might be due to ethnic differences.

Interactions between hepatic lipase and apolipoprotein E gene polymorphisms affect serum lipid profiles of healthy Canadian adults

The purpose of this study was to assess the individual and interactive effects between hepatic lipase (LIPC; C-514T, G-250A) and apolipoprotein E (APOE) (E2, E3, E4) gene polymorphisms on levels of plasma lipoprotein cholesterol and triglyceride among healthy, young, Canadian adults (n = 440). All subjects with at least one APOE2 allele had significantly lower low-density lipoprotein cholesterol, total cholesterol, and total cholesterol – high-density lipoprotein cholesterol ratio when compared with those with the APOE3 or APOE4 allele. There were significant differences in the LIPC allele and genotype frequencies between Caucasian (n = 207) and Asian (n = 211) individuals, but ethnicity did not contribute to the variations in circulating lipids. In addition, the lowest triglyceride levels (0.87 ± 0.27 mmol·mL–1) were found in all APOE2 individuals carrying LIPC-514-CC and LIPC-250-GG genotypes, whereas the highest triglyceride levels (1.29 ± 0.34 –1.32 ± 0.32 mmol·mL–1) were found in APOE2 individuals carrying the opposite genotypes, LIPC-514TT and LIPC-250AA. These observations, distinct from the anti-atherogenic effects of APOE2 through the lowering of low-density lipoprotein cholesterol and LIPC on high-density lipoprotein cholesterol, suggest that there is an interactive effect between APOE and LIPC genotypes on plasma triglyceride levels. These results provide the basis for further studies on establishing which genotype combinations would be the most protective against hypertriglyceridemia.

The effect of APOA5 and APOC3 variants on lipid parameters in European Whites, Indian Asians and Afro-Caribbeans with type 2 diabetes

Common variants in APOA5 and APOC3 have been associated with differences in plasma triglyceride (TG) levels in healthy individuals. The aim of this study was to examine the association of APOA5 (-1131T>C, S19W) and APOC3 (-482C>T, 1100C>T) polymorphisms in patients with type 2 diabetes (T2D) of European White (EW) (n=931), Indian Asian (IA) (n=610) and Afro-Caribbean (AC) (n=167) origin, with lipid and T2D parameters. Rare allele frequencies and linkage disequilibrium differed significantly amongst ethnic groups. Compared to APOA5 -1131T and 19S homozygotes, -1131C and 19W carriers had higher TGs in all groups, but this effect was only statistically significant for the -1131C in the EWs (P=0.04) and 19W in the IAs (P<0.001). APOC3 SNPs showed no significant association with lipid levels in any ethnic group. While haplotypes carrying -1131C allele showed significant TG-raising in the EWs only, the 19W defined haplotype showed significant TG-raising in both IAs and EWs. Comparing all four SNPs in EW T2D subjects with healthy EWs (n=2579), the APOC3 1100C>T frequency was significantly higher in T2D [0.26 (0.24, 0.28)] vs. healthy EWs [0.22 (0.20, 0.23)], P=0.001. While the variable size effects of the two APOA5 SNPs on TG levels may result from ethnically different gene-gene or gene-environment interactions, APOA5 and APOC3 variants did not affect parameters of T2D. However, comparison between EWs with T2D and healthy EWs suggest APOC3 1100C>T is associated with increased risk of diabetes probably through mechanisms other than direct effects on TG.

Association of lipoprotein lipase S447X, apolipoprotein E exon 4, and apoC3 -455T>C polymorphisms on the susceptibility to diabetic nephropathy

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease. In DN patients, triglyceride (TG) level is elevated and lipoprotein lipase (LPL) activity, which hydrolyzes TG, is decreased. The LPL S447X and apolipoprotein E (APOE) exon 4 polymorphisms affect TG levels, and the APOC3 -455T>C polymorphism affects LPL activity. Our aim was to examine the association of these polymorphisms with nephropathy in type 2 diabetes. We examined these polymorphisms in a case-control study of type 2 diabetic patients including 374 with DN and 392 without DN. LPL 447X-containing genotypes (447X+) were significantly decreased in DN patients [18.6 vs 25.6%, odds ratio (OR) = 0.66, p = 0.02], as were APOE epsilon3/epsilon3 genotypes (64.8 vs 73.1%, OR = 0.68, p = 0.01). In addition, combinations of genotypes [APOE epsilon3/epsilon3 and LPL 447X+ (OR = 0.56), APOC3 CC and LPL 447X+ (OR = 0.31), APOE epsilon3/epsilon3 and APOC3 CC (OR = 0.61] were protective for DN compared with the most common combination of the respective polymorphisms. Our findings suggest the importance of interactions among lipid genes in modulating the risk of DN.