Are Genes Associated with Energy Metabolism Important in Asthma and BMI?
ABSTRACT Increased serum leptin levels have been observed in asthmatic patients. Leptin, via proliferation and activation of Th2 cells, may induce inflammation in asthma. It has also been demonstrated that leptin mRNA expression and protein levels increase in response to inflammatory stimuli. We hypothesized that polymorphisms in the leptin receptor, leptin and ghrelin genes, may affect their expression and, therefore, be responsible for altered response to increased leptin levels observed in asthma. To our knowledge, there were no studies on a potential role of LEPR, LEP, and GHRL polymorphisms in asthma.
We analyzed 129 pediatric patients with asthma and 114 healthy children from the control group ranging from 6 to 18 years of age. The diagnosis of allergic asthma was based on clinical symptoms, the lung function test, and the positive skin prick test and/or increased immunoglobulin E (IgE) levels. Polymorphisms were genotyped by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Statistical analyses were performed with Statistica v.7.1 software (Statistica, StatSoft, Poland; available free at http://www.broad.mit.edu/mpg/haploview/index.php). Linkage disequilibrium analysis was performed with Haploview v.4.0.
We observed a statistically significant association of the 3'UTR A/G and the -2549A/G polymorphisms of the leptin gene with asthma. No association with asthma was observed for the K109R and the Q223R polymorphisms of the LEPR gene and the Met72Leu polymorphism of the ghrelin gene. In the analysis of body mass index (BMI) stratified by genotype, we found an association of the -2549A/G LEP, but not of LEPR and GHRL polymorphisms, with higher BMI values in asthmatic patients. We found suggestive evidence for linkage between the two polymorphisms of the LEPR gene (D' = 0.84 CI: 0.71-0.92; r(2) = 0.29) in linkage disequilibrium analysis: The GG haplotype was more frequent in the control healthy group (p = 0.057). No linkage disequilibrium was detected between LEP polymorphisms.
Polymorphisms of the leptin gene may be associated with asthma and higher BMI in asthmatic patients. Polymorphisms of the LEPR and GHRL seem unlikely to be associated with asthma or BMI in our sample. The results of haplotype analysis for the LEPR gene may suggest a protective role of the GG haplotype against asthma; however, studies on larger groups are necessary to confirm the observed trend towards association.
Conference Paper: Low complexity binary description wavelet codec[Show abstract] [Hide abstract]
ABSTRACT: This paper presents a new coding algorithm, called the low complexity binary description (LCBiD) wavelet coder, which has an extremely low implementation complexity yet very rich features. LCBiD encodes wavelet coefficients in blocks of fixed size (16,16). Wavelet coefficients of a block are only taken from a single subband. No inter-subband correlation is exploited so that no specific requirement is imposed on how wavelet coefficients are generated. Each block is encoded using binary context-based bitplane coding. A (16,16) block is usually much smaller than a subband, and a block can become significant much later than a subband. A block skipping technique is employed to bypass one layer of zeros if a block is insignificant at the current quantization threshold. In other words, a separate bitstream is generated to describe the significance of blocks. Because much less zeros are encoded, both the coding speed and efficiency are increased greatly. A separate arithmetic coder set is used for each bitplane, and all coders are reset at the beginning of each subband. Thus, each bitplane of every subband in the compressed file can be directly accessed, and decoded almost independently. The only constraint is that all bitplanes of one subband must be decoded in the correct order. In order to reduce the overall number of arithmetic coders, very simple coding contexts are defined. The image codec has a very good coding performance, and the compressed file is quality and resolution scalable, and resilient to transmission errorsMultimedia Signal Processing, 1999 IEEE 3rd Workshop on; 02/1999
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ABSTRACT: The worldwide pandemic of obesity is creating unique challenges for the diagnosis and treatment of asthma. A wealth of epidemiologic literature has established that whereas asthma can lead to obesity, obesity is a risk factor for asthma, but mechanisms are unclear. This review assesses the current understanding of the relationship between obesity and asthma. Recent studies are developing a more sophisticated understanding of the possible inflammatory, immunologic, genetic, and mechanical mechanisms underlying the association between obesity and asthma. Obese asthma may be a unique phenotype of asthma, with a more difficult clinical course and altered response to asthma controller therapy. Adipokines such as leptin and adiponectin are thought to be important, but there is new interest in other inflammatory mechanisms related to visceral obesity, insulin resistance, and the metabolic syndrome. There are still far more questions than answers as to how obesity might cause or worsen asthma. It is clear that weight gain and obesity are particularly troublesome in asthmatics, and clinicians should target these individuals for aggressive intervention. Randomized controlled trials are needed to determine the best treatment approaches for obese asthma, and prospective studies in which both obesity and asthma are well characterized are needed to better understand the underlying mechanisms.Current opinion in pulmonary medicine 10/2009; 16(1):64-70. DOI:10.1097/MCP.0b013e3283338fa7 · 2.96 Impact Factor
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ABSTRACT: Epidemiologic studies consistently show associations between asthma and obesity. Shared genetics might account for this association. We sought to identify genetic variants associated with both asthma and obesity. On the basis of a literature search, we identified genes from (1) genome-wide association studies (GWASs) of body mass index (BMI; n = 17 genes), (2) GWASs of asthma (n = 14), and (3) candidate gene studies of BMI and asthma (n = 7). We used GWAS data from the Childhood Asthma Management Program to analyze associations between single nucleotide polymorphisms (SNPs) in these genes and asthma (n = 359 subjects) and BMI (n = 537). One top BMI GWAS SNP from the literature, rs10938397 near glucosamine-6-phosphate deaminase 2 (GNPDA2), was associated with both BMI (P = 4 x 10(-4)) and asthma (P = .03). Of the top asthma GWAS SNPs and the candidate gene SNPs, none was found to be associated with both BMI and asthma. Gene-based analyses that included all available SNPs in each gene found associations (P < .05) with both phenotypes for several genes: neuronal growth regulator 1 (NEGR1); roundabout, axon guidance receptor, homolog 1 (ROBO1); diacylglycerol kinase, gamma (DGKG); Fas apoptotic inhibitory molecule 2 (FAIM2); fat mass and obesity associated (FTO); and carbohydrate (N-acetylgalactosamine 4-0) sulfotransferase 8 (CHST8) among the BMI GWAS genes; interleukin 1 receptor-like 1 / interleukin 18 receptor 1 (IL1RL1/IL18R1), dipeptidyl-peptidase 10 (DPP10), phosphodiesterase 4D (PDE4D), V-myb myeloblastosis viral oncogene homolog (MYB), PDE10A, IL33, and especially protein tyrosine phosphatase, receptor type D (PTPRD) among the asthma GWAS genes; and protein kinase C, alpha (PRKCA) among the BMI and asthma candidate genes. SNPs within several genes showed associations to BMI and asthma at a genetic level, but none of these associations were significant after correction for multiple testing. Our analysis of known candidate genes reveals some evidence for shared genetics between asthma and obesity, but other shared genetic determinants are likely to be identified in novel loci.The Journal of allergy and clinical immunology 09/2010; 126(3):631-7.e1-8. DOI:10.1016/j.jaci.2010.06.030 · 11.25 Impact Factor