A Modified Precipitation Method to Isolate Urinary Exosomes

Identification of biomarkers that allow early detection of kidney diseases in urine and plasma has been an area of active interest for several years. ...

Translational Genomics Research Institute (TGen)

Obesity is recognized as one of the most important underlying risk factors for a wide variety of diseases, including heart disease and diabetes. Women are particularly prone to obesity, and approaches that address life transitions across the life span suggest that a number of factors may converge at passage points, such as menopause, that contribute to weight accumulation in the aging woman. The menopausal phase of a woman's life brings a number of changes that may trigger and maintain weight gain. Although the prevalence of overweight and obesity is attributable to each of these factors, it is most likely the interaction among multiple factors that determines an individual's propensity for excess energy intake, sedentary behavior, patterns of fat distribution, and risk of developing obesity. The problem of weight change and obesity in perimenopausal women is best understood from an ecological perspective that can integrate the analysis of factors across levels, from the culture and built environment of the community to family-related factors to individual factors, such as subjective norms, values, attitudes, and beliefs, and biological/genetic predispositions. This review describes the literature relevant to weight change during perimenopause using a multilevel perspective and recommends future directions for the development of translational weight management research to meet the unique needs of women.

Perimenopausal obesity.

Variants in the engulfment and cell motility 1 gene, ELMO1, have previously been associated with kidney disease attributed to type 2 diabetes. The Pima Indians of Arizona have high rates of diabetic nephropathy, which is strongly dependent on genetic determinants; thus, we sought to investigate the role of ELMO1 polymorphisms in mediating susceptibility to this disease in this population. Genotype distributions were compared among 141 individuals with nephropathy and 416 individuals without heavy proteinuria in a family study of 257 sibships, and 107 cases with diabetic ESRD and 108 controls with long duration diabetes and no nephropathy. We sequenced 17.4 kb of ELMO1 and identified 19 variants. We genotyped 12 markers, excluding those in 100% genotypic concordance with other variants or with a minor allele frequency <0.05, plus 21 additional markers showing association with ESRD in earlier studies. In the family study, the strongest evidence for association was with rs1345365 (odds ratio [OR]=2.42 per copy of A allele [1.35-4.32]; P=0.001) and rs10951509 (OR=2.42 per copy of A allele [1.31-4.48]; P=0.002), both of which are located in intron 13 and are in strong pairwise linkage disequilibrium (r(2)=0.97). These associations were in the opposite direction from those observed in African Americans, which suggests that the relationship between diabetic kidney disease and ELMO1 variation may involve as yet undiscovered functional variants or complex interactions with other biological variables.

ELMO1 variants and susceptibility to diabetic nephropathy in American Indians.

A variety of treatment modalities exist for individuals with type 2 diabetes mellitus (T2D). In addition to dietary and physical activity interventions, T2D is also treated pharmacologically with nine major classes of approved drugs. These medications include insulin and its analogues, sulfonylureas, biguanides, thiazolidinediones (TZDs), meglitinides, α-glucosidase inhibitors, amylin analogues, incretin hormone mimetics, and dipeptidyl peptidase 4 (DPP4) inhibitors. Pharmacological treatment strategies for T2D are typically based on efficacy, yet favorable responses to such therapeutics are oftentimes variable and difficult to predict. Characterization of drug response is expected to substantially enhance our ability to provide patients with the most effective treatment strategy given their individual backgrounds, yet pharmacogenetic study of diabetes medications is still in its infancy. To date, major pharmacogenetic studies have focused on response to sulfonylureas, biguanides, and TZDs. Here, we provide a comprehensive review of pharmacogenetics investigations of these specific anti-diabetes medications. We focus not only on the results of these studies, but also on how experimental design, study sample issues, and definition of 'response' can significantly impact our interpretation of findings. Understanding the pharmacogenetics of anti-diabetes medications will provide critical baseline information for the development and implementation of genetic screening into therapeutic decision making, and lay the foundation for "individualized medicine" for patients with T2D.

Pharmacogenetics of Anti-Diabetes Drugs.

Identification of novel genetic markers and improved treatment options for diabetic kidney disease.

Genome-wide association studies (GWAS), in which thousands of single-nucleotide polymorphisms (SNPs) spanning the genome are genotyped in individuals who are phenotypically well characterized, -currently represent the most popular strategy for identifying gene regions associated with common -diseases and related quantitative traits. Improvements in technology and throughput capability, development of powerful statistical tools, and more widespread acceptance of pooling-based genotyping approaches have led to greater utilization of GWAS in human genetics research. However, important considerations for optimal experimental design, including selection of the most appropriate genotyping platform, can enhance the utility of the approach even further. This chapter reviews experimental and technological issues that may affect the success of GWAS findings and proposes strategies for developing the most comprehensive, logical, and cost-effective approaches for genotyping given the population of interest.

Technological issues and experimental design of gene association studies.

More than 99% of genomic DNA sequence is identical among humans, and not surprisingly, slight variations in sequence can often produce a major effect on phenotype. Sequence variants may also mediate the manner in which humans are susceptible to disease or respond to environmental factors such as bacteria, viruses, toxins, chemicals, drugs, and therapeutic interventions. Single-nucleotide polymorphisms (SNPs) are DNA sequence variations that occur when a single base in the genome sequence can be represented by at least two different nucleotides. In the last decade, numerous SNPs have been identified that explain, at least partially, the genetic architecture of complex diseases such as cancer, diabetes, vascular complications, some forms of mental illness, and a multitude of other disorders. Disease-related SNPs are commonly identified through candidate gene approaches, or more recently, through genome-wide association studies. In either case, findings of association require verification in independent, population-based, study samples, usually consisting of several hundreds/thousands of individuals. A convenient technique to genotype a moderate number of markers in this kind of study is available with the TaqMan® platform (Applied Biosystems; Foster City, CA), which utilizes polymerase chain reaction amplification and allelic discrimination to easily and efficiently generate genotype data in a cost-effective way. Here, we introduce and describe this commonly used technique and include protocols that can be directly used in laboratories aiming to perform moderate- to large-scale genotyping studies.

Targeted SNP genotyping using the TaqMan® assay.

CNDP1 is located on 18q22.3, where linkage with diabetic nephropathy has been observed in several populations, including Pima Indians. However, evidence for association between CNDP1 alleles and diabetic nephropathy is equivocal and population-dependent. This study investigated CNDP1 as a candidate for diabetic kidney disease in Pima Indians. Nineteen tag single nucleotide polymorphisms spanning the CNDP1 locus were selected using genotype data from Chinese individuals in the HapMap resource along with 2 variants previously associated with diabetic nephropathy. All variants were genotyped in 3 different samples including a diabetic end-stage renal disease (ESRD) case-control study, a family-based study of diabetic individuals who participated in the linkage study for nephropathy, and a cohort of diabetic individuals in whom longitudinal measures of glomerular filtration rates (GFR) were performed. There was no statistically significant evidence for association with diabetic ESRD. However, nominal evidence for association was found in the family study, where markers rs12957330 (Odds ratio [OR]=0.29 per copy of G allele; p=0.04) and rs17817077 (OR=0.46 per copy of G allele; p=0.05) were associated with diabetic nephropathy. In addition, markers rs12964454, rs7244647, and rs7229005 were associated with changes in GFR (-8.5ml/min per copy of the G allele; p=0.04; 18.8ml/min per copy of the C allele; p=0.03; and -13.4ml/min per copy of the C allele; p=0.001, respectively). These findings provide nominal evidence supporting a role between CNDP1 variants and diabetic kidney disease.

Association of variants in the carnosine peptidase 1 gene (CNDP1) with diabetic nephropathy in American Indians.

We previously observed association between variants in the plasmacytoma variant translocation 1 gene (PVT1) and end-stage renal disease (ESRD) attributed to both type 1 and type 2 diabetes, and demonstrated PVT1 expression in a variety of renal cell types. While these findings suggest a role for PVT1 in the development of ESRD, potential mechanisms for involvement remain unknown. The goal of this study was to identify possible molecular mechanisms by which PVT1 may contribute to the development and progression of diabetic kidney disease. We knocked-down PVT1 expression in mesangial cells using RNA interference, and analyzed RNA and protein levels of fibronectin 1 (FN1), collagen, type IV, alpha 1 (COL4A1), transforming growth factor beta 1 (TGFB1) and plasminogen activator inhibitor-1 (SERPINE1 or PAI-1) by qPCR and ELISA, respectively. PVT1 expression was significantly upregulated by glucose treatment in human mesangial cells, as were levels of FN1, COL4A1, TGFB1, and PAI-1. Importantly, PVT1 knockdown significantly reduced mRNA and protein levels of the major ECM proteins, FN1 and COL4A1, and two key regulators of ECM proteins, TGFB1 and PAI-1. However, we observed a higher and more rapid reduction in levels of secreted FN1, COL4A1, and PAI-1 compared with TGFB1, suggesting that at least some of the PVT1 effects on ECM proteins may be independent of this cytokine. These results indicate that PVT1 may mediate the development and progression of diabetic nephropathy through mechanisms involving ECM accumulation.

Functional characterization of the plasmacytoma variant translocation 1 gene (PVT1) in diabetic nephropathy.

Urinary exosomes are 40-100 nm vesicles containing protein, mRNA, and microRNA that may serve as biomarkers of renal dysfunction and structural injury. Currently, there is a need for more sensitive and specific biomarkers of renal injury and disease progression. Here we sought to identify the best exosome isolation methods for both proteomic analysis and RNA profiling as a first step for biomarker discovery. We used six different protocols; three were based on ultracentrifugation, one used a nanomembrane concentrator-based approach, and two utilized a commercial exosome precipitation reagent. The highest yield of exosomes was obtained using a modified exosome precipitation protocol, which also yielded the highest quantities of microRNA and mRNA and, therefore, is ideal for subsequent RNA profiling. This method is likewise suitable for downstream proteomic analyses if an ultracentrifuge is not available and/or a large number of samples are to be processed. Two of the ultracentrifugation methods, however, are better options for exosome isolation if an ultracentrifuge is available and few samples will be processed for proteomic analysis. Thus, our modified exosome precipitation method is a simple, fast, highly scalable, and effective alternative for the isolation of exosomes, and may facilitate the identification of exosomal biomarkers from urine.

Comparison of protein, microRNA, and mRNA yields using different methods of urinary exosome isolation for the discovery of kidney disease biomarkers.

Diabetic nephropathy, a progressive kidney disease that develops secondary to diabetes, is the major cause of chronic kidney disease in developed countries, and contributes significantly to increased morbidity and mortality among individuals with diabetes. Although the causes of diabetic nephropathy are not fully understood, recent studies demonstrate a role for epigenetic factors in the development of the disease. For example, non-coding RNA (ncRNA) molecules, including microRNAs (miRNAs), have been shown to be functionally important in modulating renal response to hyperglycemia and progression of diabetic nephropathy. Characterization of miRNA expression in diabetic nephropathy from studies of animal models of diabetes, and in vitro investigations using different types of kidney cells also support this role. The goal of this review, therefore, is to summarize the current state of knowledge of specific ncRNAs involved in the development of diabetic nephropathy, with a focus on the potential role of miRNAs to serve as sensitive, non-invasive biomarkers of kidney disease and progression. Non-coding RNAs are currently recognized as potentially important regulators of genes involved in processes related to the development of diabetic nephropathy, and as such, represent viable targets for both clinical diagnostic strategies and therapeutic intervention.

The role of non-coding RNAs in diabetic nephropathy: potential applications as biomarkers for disease development and progression.

Although the causes of diabetic nephropathy are not yet fully known, emerging evidence suggests a role for epigenetic factors in the development of the disease. In particular, microRNAs (miRNAs) are becoming recognized as important mediators of biological processes relevant to diabetic nephropathy. Until recently, investigations of miRNAs in the development of diabetic nephropathy have remained relatively limited; however, the number of reports identifying potential new candidates and mechanisms of impact is presently expanding at a rapid pace. This review seeks to summarize these recent findings, focusing on new candidates and/or novel mechanisms, including the intersection between genetic variation and miRNA function in modulating disease expression, emerging in the field. We also review the latest advances in the diagnostic and therapeutic potential of miRNAs in the treatment of diabetic nephropathy.

Emerging roles for miRNAs in the development, diagnosis, and treatment of diabetic nephropathy.

Individuals with type 2 diabetes have an increased risk of developing non-alcoholic fatty liver disease (NAFLD), and NAFLD patients are also at greater risk for developing type 2 diabetes. Although the relationship between type 2 diabetes and NAFLD is highly interconnected, the pathogenic mechanisms linking the two diseases are poorly understood. The goal of this study was to identify genetic determinants of hepatic lipid accumulation through association analysis using histological phenotypes in obese individuals.

Johanna K. DiStefano

Diabetes,
Cardiovascular and Metabolic Diseases Division,
Diabetes, Cardiovascular and Metabolic Diseases Division

Translational Genomics Research Institute (TGen)

A Modified Precipitation Method to Isolate Urinary Exosomes

Johanna K. DiStefano

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Diabetes,Cardiovascular and Metabolic Diseases Division,Diabetes, Cardiovascular and Metabolic Diseases Division

Translational Genomics Research Institute (TGen)

A Modified Precipitation Method to Isolate Urinary Exosomes

Diabetes,
Cardiovascular and Metabolic Diseases Division,
Diabetes, Cardiovascular and Metabolic Diseases Division