The genetic basis of diabetes mellitus

Increased levels of YKL-40 in patients with diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Diabetes mellitus (DM) could be classified as type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), gestational diabetes mellitus (GDM) and others according to etiology and pathology. Diabetic nephropathy (DN) is one of the most serious complications of DM. YKL-40 is a marker of inflammation and some studies have indicated that DM was related with inflammation. The objective of our study is to perform a systematic review and meta-analysis to confirm the relationship between YKL-40 and DM as well as DN.

METHODS

Pubmed, Embase, CNKI and Chinese wanfang databases were searched for eligible studies by two independent authors. Studies were included in this meta-analysis if they fulfilled the following inclusion criteria: (1) a study involving the role of YKL-40 in DM (or DN) designed as a case-control study or cohort study; (2) the data of serum YKL-40 levels were available; (3) studies were published in English or Chinese. Finally, twenty-five studies were included in this meta-analysis.

RESULTS

Compared with healthy controls, DM patients had significantly higher levels of YKL-40 (DM: SMD = 1.62, 95% CI 1.08 to 2.25, P = 0.000; GDM: SMD = 2.85, 95% CI 1.01 to 4.70, P = 0.002). Additionally, DM patients with different degree of albuminuria had significantly higher levels of YKL-40 compared with healthy controls (normoalbuminuria: SMD = 1.58, 95% CI 0.59 to 2.56, P = 0.002; microalbuminuria: SMD = 2.57, 95% CI 0.92 to 4.22, P = 0.002; macroalbuminuria: SMD = 2.69, 95% CI 1.40 to 3.98, P = 0.000) and serum YKL-40 levels increased with increasing severity of albuminuria among DM patients (microalbuminuria vs normoalbuminuria: SMD = 1.49, 95% CI 0.28 to 2.71, P = 0.016; macroalbuminuria vs microalbuminuria: SMD = 0.93, 95% CI 0.34 to 1.52, P = 0.002).

CONCLUSIONS

Our current meta-analysis demonstrates that serum level of YKL-40 is increased in DM and positively associated with the severe degree of albuminuria. Therefore, we suggest that YKL-40 could be considered to be detected, along with other inflammatory markers, if DM, especially DN, is suspected.

Effects of miR‑195‑5p on cell proliferation and apoptosis in gestational diabetes mellitus via targeting EZH2

Gestational diabetes mellitus (GDM) is a type of diabetes mellitus (DM) that occurs during pregnancy. The present study aimed to investigate the roles of microRNA (miR)‑195‑5p and enhancer of zeste homolog 2 (EZH2) in GDM, and their potential association. Human umbilical vein endothelial cells (HUVECs) were collected from healthy and GDM umbilical cords, and the endothelial properties were detected by flow cytometry. mRNA expression levels of miR‑195‑5p and EZH2, and EZH2 protein expression levels were detected by reverse transcription‑quantitative PCR (RT‑qPCR) and western blot analysis, respectively. Cell colony formation and flow cytometry were performed to determine cell proliferation and apoptosis. Furthermore, the target gene of miR‑195‑5p was predicted and assessed using a dual‑luciferase reporter assay. The levels of cell viability, proliferation and apoptosis following the overexpression of miR‑195‑5p, EZH2 or miR‑195‑5p + EZH2, were detected using Cell Counting Kit‑8, colony formation and flow cytometry assays, respectively. In addition, the mRNA expression levels of miR‑195‑59 and EZH2, and EZH2 protein expression levels following transfection with overexpression plasmids were detected using RT‑qPCR and western blot analysis, respectively. It was identified that high mRNA expression of miR‑195‑5p, and low EZH2 mRNA and protein expression levels decreased the level of cell proliferation and the high apoptotic rate of GDM‑HUVECs. In addition, miR‑195‑5p was predicted and identified to target EZH2, and miR‑195‑5p overexpression was identified to inhibit cell proliferation and promote apoptosis. However, it was demonstrated that upregulation of EZH2 could alleviate the inhibition of cell proliferation and the increased apoptotic rate induced by miR‑195‑5p overexpression. Therefore, the present results suggested that miR‑195‑5p may inhibit cell viability, proliferation and promote apoptosis by targeting EZH2 in GDM‑induced HUVECs.

Effect of diabetes mellitus on pharmacokinetic and pharmacodynamic properties of drugs

The effects of diabetes mellitus on the pharmacokinetics and pharmacodynamics of drugs have been well described in experimental animal models; however, only minimal data exist for humans and the current knowledge regarding the effects of diabetes on these properties remains unclear. Nevertheless, it has been observed that the pharmacokinetics and pharmacodynamics of drugs are changed in subjects with diabetes. It has been reported that diabetes may affect the pharmacokinetics of various drugs by affecting (i) absorption, due to changes in subcutaneous adipose blood flow, muscle blood flow and gastric emptying; (ii) distribution, due to non-enzymatic glycation of albumin; (iii) biotransformation, due to regulation of enzymes/transporters involved in drug biotransformation; and (iv) excretion, due to nephropathy. Previously published data also suggest that diabetes-mediated changes in the pharmacokinetics of a particular drug cannot be translated to others. Although clinical studies exploring the effect of diabetes on pharmacodynamics are still very limited, there is evidence that disease-mediated effects are not limited only to pharmacokinetics but also alter pharmacodynamics. However, for many drugs it remains unclear whether these influences reflect diabetes-mediated changes in pharmacokinetics rather than pharmacodynamics. In addition, even though diabetes-mediated pharmacokinetics and pharmacodynamics might be anticipated, it is important to study the effect on each drug and not generalize from observed data. The available data indicate that there is a significant variability in drug response in diabetic subjects. The discrepancies between individual clinical studies as well as between ex vivo and clinical studies are probably due to (i) the restricted and focused population of subjects in clinical studies; (ii) failure to consider type, severity and duration of the disease; (iii) histopathological characteristics generally being missing; and (iv) other factors such as varying medication use, dietary protein intake, age, sex and obesity. The obesity epidemic in the developed world has also inadvertently influenced the directions of pharmacological research. This review attempts to map new information gained since Gwilt published his paper in Clinical Pharmacokinetics in 1991. Although a large body of research has been conducted and significant progress has been made, we still have to conclude that the available information regarding the effect of diabetes on pharmacokinetics and pharmacodynamics remains unclear and further clinical studies are required before we can understand the clinical significance of the effect. An understanding of diabetes-mediated changes as well as of the source of the variability should lead to the improvement of the medical management and clinical outcomes in patients with this widespread disease.

Gene expression microarray studies in polygenic psychiatric disorders: applications and data analysis

Gene expression microarrays have become a mainstream technology that can provide valuable insight into psychiatric disorders. Gene expression studies in post mortem brain samples of schizophrenia and bipolar disorder have the potential to yield novel clues about the pathophysiology of these complex trait disorders. In the present review, a short introduction of the genetic and molecular background of schizophrenia and bipolar disorder is followed by a discussion of the basic concept and limits of gene expression microarray technology, and the complexities surrounding the analysis of thousands of gene transcripts. Although this review is intended for use in most platforms, it has a particular focus on the commercially available Affymetrix system. Various computer programs and their principal features are discussed, and it is shown how these programs can be applied to reveal a biological context of microarray findings. I will demonstrate how the programs can help to judge the results rather than focus on their statistical principles. The strength of gene array experiments is their emphasis on broad, biological themes, rather than on specific genes, and proper biostatistical approaches are important to ensure reproducibility of the findings. All results should be verified by independent means. This review is intended to help brain researchers who want to apply gene expression microarray technology to conceptualize research strategies and sample analysis.

Association between MspI polymorphism of the APO AI gene and Type 2 diabetes mellitus

AIMS

Genes of the Apo AI/CIII/AIV cluster on chromosome 11 have been related to plasma lipid patterns. The close relationship between carbohydrate metabolism and lipid metabolism warrants investigation of the association between this cluster and Type 2 diabetes mellitus. We therefore examined the possible association between polymorphisms of this cluster and Type 2 diabetes mellitus as part of a study of the prevalence of diabetes and the metabolic syndrome in southern Spain.

METHODS

A total of 1224 persons were selected randomly from the town of Pizarra in the province of Malaga, southern Spain. The sample errors for the prevalence of Type 2 diabetes mellitus and the three polymorphisms studied were all < or = 4%. All subjects underwent phenotyping after an oral glucose tolerance test (75 g) (WHO 1998 criteria) and the XmnI and MspI polymorphisms of Apo AI and the SstI polymorphism of Apo CIII were genotyped.

RESULTS

Those subjects with the mutated AA genotype of the MspI polymorphism (-75 G-->A) of Apo AI had a greater risk of impaired glucose tolerance [odds ratio (OR) = 1.95, CI = 1.02-3.8, P = 0.05], Type 2 diabetes mellitus, both known (OR = 7.38, CI = 1.3-39.7, P = 0.02) and unknown (OR = 3.7, CI = 1.4-9.9, P = 0.009). This risk was independent of age, sex, obesity, triglyceride level, HDL cholesterol and pattern of insulin resistance.

CONCLUSIONS

Pending confirmation in prospective studies, the AA genotype of the MspI polymorphism of the Apo AI gene, within the Apo A-I/C-III/A-IV cluster, seems to be a risk factor for Type 2 diabetes mellitus.

Genómica de la regulación del peso corporal: mecanismos moleculares que predisponen a la obesidad

Obesity has become a worldwide public health problem which affects millions of people. Substantial progress has been made in elucidating the pathogenesis of energy homeostasis over the past few years. The fact that obesity is under strong genetic control has been well established. Twin, adoption and family studies have shown that genetic factors play a significant role in the pathogenesis of obesity. Human monogenic obesity is rare in large populations. The most common form of obesity is considered to be a polygenic disorder. New treatments are currently required for this common metabolic disease and type 2 diabetes. The identification of physiological and biochemical factors that underlie the metabolic disturbances observed in obesity is a key step in developing better therapeutic outcomes. The discovery of new genes and pathways involved in the pathogenesis of such a disease is critical to this process. However, identification of genes that contribute to the risk of developing the disease represents a significant challenge since obesity is a complex disease with many genetic and environmental causes. A number of diverse approaches have been used to discover and validate potential new genes for obesity. To date, DNA-based approaches using candidate genes and genome-wide linkage analysis have not had a great success in identifying genomic regions or genes involved in the development of these diseases. Recent advances in the ability to evaluate linkage analysis data from large family pedigrees (using variance components-based linkage analysis) show great promise in robustly identifying genomic regions associated with the development of obesity. Studying rare mutations in humans and animal models has provided fundamental insight into a complex physiological process, and has complemented population-based studies that seek to reveal primary causes. Remarkable progress has been made in both fronts and the pace of advance is likely to accelerate as functional genomics and the human genome project expand and mature. Approaches based on Mendelian and quantitative genetics may well converge, and ultimately lead to more rational and selective therapies.