56 research outputs found

    Preliminary evidence supports circulating microRNAs as prognostic biomarkers for type 2 diabetes.

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    Background:Circulating microRNAs are emerging as potential prognostic biomarkers for the development of type 2 diabetes. However, microRNAs are also associated with complications from impaired glucose metabolism (e.g. endothelial cell function). Prior studies have not evaluated for associations between trajectories of circulating microRNAs with trajectories of fasting blood glucose over time and the responses to behavioral interventions to reduce risk. This study performed longitudinal assessment of microRNAs and fasting blood glucose and identified relationships between microRNAs and behavioral risk reduction interventions. Methods:MicroRNAs (n = 353) were measured in subsets (n = 10, n = 8) of participants from previously completed clinical trials that studied behavioral risk reduction interventions. Fasting blood glucose trajectories were associated with changes in 45 microRNAs over 12 months. Results:Following a 3-month physical activity and dietary intervention compared with baseline, 13 microRNAs were differentially expressed. Seven microRNAs (i.e. miR-106b, miR-20b, miR-363, miR-486, miR-532, miR-92a and miR-93) were commonly identified between the two analyses. Conclusions:Further studies are needed to determine which microRNAs are prognostic biomarkers of risk for type 2 diabetes versus consequences of impaired glucose metabolism. Additional future directions of this research are to differentiate whether microRNAs are prognostic and/or diagnostic biomarkers for risk for type 2 diabetes and predictive biomarkers of responses to risk reduction interventions

    Relationship between a Novel Polymorphism of the C5L2 Gene and Coronary Artery Disease

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    C5L2 has been demonstrated to be a functional receptor of acylation-stimulating protein (ASP), which is a stimulator of triglyceride synthesis or glucose transport. However, little is known about the variations in the coding region of the C5L2 gene and their association with coronary artery disease (CAD). = 0.047, OR = 2.602, 95% CI: 1.015–6.671).The 698CT genotype of C5L2 may be a genetic maker of CAD in the Han and Uygur population in western China

    A nonsynonymous SNP within PCDH15 is associated with lipid traits in familial combined hyperlipidemia

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    Familial combined hyperlipidemia (FCHL) is a common lipid disorder characterized by the presence of multiple lipoprotein phenotypes that increase the risk of premature coronary heart disease. In a previous study, we identified an intragenic microsatellite marker within the protocadherin 15 (PCDH15) gene to be associated with high triglycerides (TGs) in Finnish dyslipidemic families. In this study we analyzed all four known nonsynonymous SNPs within PCDH15 in 1,268 individuals from Finnish and Dutch multigenerational families with FCHL. Association analyses of quantitative traits for SNPs were performed using the QTDT test. The nonsynonymous SNP rs10825269 resulted in a P = 0.0006 for the quantitative TG trait. Additional evidence for association was observed with the same SNP for apolipoprotein B levels (apo-B) (P = 0.0001) and total cholesterol (TC) levels (P = 0.001). None of the other three SNPs tested showed a significant association with any lipid-related trait. We investigated the expression of PCDH15 in different human tissues and observed that PCDH15 is expressed in several tissues including liver and pancreas. In addition, we measured the plasma lipid levels in mice with loss-of-function mutations in Pcdh15 (Pcdh15av-Tg and Pcdh15av-3J) to investigate possible abnormalities in their lipid profile. We observed a significant difference in plasma TG and TC concentrations for the Pcdh15av-3J carriers when compared with the wild type (P = 0.013 and P = 0.044, respectively). Our study suggests that PCDH15 is associated with lipid abnormalities

    Genome-Wide Association Studies in Atherosclerosis

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    Cardiovascular disease remains the major cause of worldwide morbidity and mortality. Its pathophysiology is complex and multifactorial. Because the phenotype of cardiovascular disease often shows a marked heritable pattern, it is likely that genetic factors play an important role. In recent years, large genome-wide association studies have been conducted to decipher the molecular mechanisms underlying this heritable and prevalent phenotype. The emphasis of this review is on the recently identified 17 susceptibility loci for coronary artery disease. Implications of their discovery for biology and clinical medicine are discussed. A description of the landscape of human genetics in the near future in the context of next-generation sequence technologies is provided at the conclusion of this review

    Interactions of the Apolipoprotein A5 Gene Polymorphisms and Alcohol Consumption on Serum Lipid Levels

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    Little is known about the interactions of apolipoprotein (Apo) A5 gene polymorphisms and alcohol consumption on serum lipid profiles. The present study was undertaken to detect the interactions of ApoA5-1131T>C, c.553G>T and c.457G>A polymorphisms and alcohol consumption on serum lipid levels.A total of 516 nondrinkers and 514 drinkers were randomly selected from our previous stratified randomized cluster samples. Genotyping was performed by polymerase chain reaction and restriction fragment length polymorphism. The levels of serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), ApoA1 and ApoB were higher in drinkers than in nondrinkers (P<0.05-0.001). The genotypic and allelic frequencies of three loci were not different between the two groups. The interactions between -1131T>C genotypes and alcohol consumption on ApoB levels (P<0.05) and the ApoA1/ApoB ratio (P<0.01), between c.553G>T genotypes and alcohol consumption on low-density lipoprotein cholesterol (LDL-C) levels (P<0.05) and the ApoA1/ApoB ratio (P<0.05), and between c.457G>A genotypes and alcohol consumption on TG levels (P<0.001) were detected by factorial regression analysis after controlling for potential confounders. Four haplotypes (T-G-G, C-G-G, T-A-G and C-G-T) had frequencies ranging from 0.06 to 0.87. Three haplotypes (C-G-G, T-A-G, and C-G-T) were significantly associated with serum lipid parameters. The -1131T>C genotypes were correlated with TG, and c.553G>T and c.457G>A genotypes were associated with HDL-C levels in nondrinkers (P<0.05 for all). For drinkers, the -1131T>C genotypes were correlated with TC, TG, LDL-C, ApoB levels and the ApoA1/ApoB ratio (P<0.01 for all); c.553G>T genotypes were correlated with TC, TG, HDL-C and LDL-C levels (P<0.05-0.01); and c.457G>A genotypes were associated with TG, LDL-C, ApoA1 and ApoB levels (P<0.05-0.01).The differences in some serum lipid parameters between the drinkers and nondrinkers might partly result from different interactions of the ApoA5 gene polymorphisms and alcohol consumption

    The role of host genetic factors in respiratory tract infectious diseases:systematic review, meta-analyses and field synopsis

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    Host genetic factors have frequently been implicated in respiratory infectious diseases, often with inconsistent results in replication studies. We identified 386 studies from the total of 24,823 studies identified in a systematic search of four bibliographic databases. We performed meta-analyses of studies on tuberculosis, influenza, respiratory syncytial virus, SARS-Coronavirus and pneumonia. One single-nucleotide polymorphism from IL4 gene was significant for pooled respiratory infections (rs2070874; 1.66 [1.29-2.14]). We also detected an association of TLR2 gene with tuberculosis (rs5743708; 3.19 [2.03-5.02]). Subset analyses identified CCL2 as an additional risk factor for tuberculosis (rs1024611; OR = 0.79 [0.72-0.88]). The IL4-TLR2-CCL2 axis could be a highly interesting target for translation towards clinical use. However, this conclusion is based on low credibility of evidence - almost 95% of all identified studies had strong risk of bias or confounding. Future studies must build upon larger-scale collaborations, but also strictly adhere to the highest evidence-based principles in study design, in order to reduce research waste and provide clinically translatable evidenc

    Multi-Tiered Assessment of Gene Expression Provides Evidence for Mechanisms That Underlie Risk for Type 2 Diabetes

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    Kesava Asam,1 Kimberly A Lewis,2 Kord Kober,2,3 Xingyue Gong,2 Alka M Kanaya,4,5 Bradley E Aouizerat,1,6 Elena Flowers2,7 1Bluestone Center for Clinical Research, New York University, New York City, NY, USA; 2Department of Physiological Nursing, University of California, San Francisco, CA, USA; 3Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA; 4Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA; 5Department of Medicine, University of California, San Francisco, CA, USA; 6Department of Oral and Maxillofacial Surgery, New York University, New York City, NY, USA; 7Institute for Human Genetics, University of California, San Francisco, CA, USACorrespondence: Elena Flowers, University of California, San Francisco, Department of Physiological Nursing, 2 Koret Way, &num;605L, San Francisco, CA, 94143-0610, USA, Tel + 1 415-476-0983, Email [email protected]: Integrated transcriptome and microRNA differential gene expression (DEG) analyses may help to explain type 2 diabetes (T2D) pathogenesis in at-risk populations. The purpose of this study was to characterize DEG in banked biospecimens from underactive adult participants who responded to a randomized clinical trial measuring the effects of lifestyle interventions on T2D risk factors. DEGs were further examined within the context of annotated biological pathways.Methods: Participants (n = 52) in a previously completed clinical trial that assessed a 12-week behavioural intervention for T2D risk reduction were included. Participants who showed > 6mg/dL decrease in fasting blood glucose were identified as responders. Gene expression was measured by RNASeq, and overrepresentation analysis within KEGG pathways and weighted gene correlation network analysis (WGCNA) were performed.Results: No genes remained significantly differentially expressed after correction for multiple comparisons. One module derived by WGCNA related to body mass index was identified, which contained genes located in KEGG pathways related to known mechanisms underlying risk for T2D as well as pathways related to neurodegeneration and protein misfolding. A network analysis showed indirect connections between genes in this module and islet amyloid polypeptide (IAPP), which has previously been hypothesized as a mechanism for T2D.Discussion: We validated prior studies that showed pathways related to metabolism, inflammation/immunity, and endocrine/hormone function are related to risk for T2D. We identified evidence for new potential mechanisms that include protein misfolding. Additional studies are needed to determine whether these are potential therapeutic targets to decrease risk for T2D.Keywords: transcriptome, diabetes, fasting blood glucose, biomarkers, pathway analysi
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