Val103Ile polymorphism of the melanocortin-4 receptor gene (MC4R) in cancer cachexia

<p>Abstract</p> <p>Background</p> <p>At present pathogenic mechanisms of cancer cachexia are poorly understood. Previous evidence in animal models implicates the melanocortin-4 receptor gene (<it>MC4R</it>) in the development of cancer cachexia. In humans, <it>MC4R </it>mutations that lead to an impaired receptor function are associated with obesity; in contrast, the most frequent polymorphism (Val103Ile, rs2229616; heterozygote frequency approximately 2%) was shown to be negatively associated with obesity. We tested if cancer patients that are homo-/heterozygous for the Val103Ile polymorphism are more likely to develop cachexia and/or a loss of appetite than non-carriers of the 103Ile-allele.</p> <p>Methods</p> <p>BMI (body mass index in kg/m²) of 509 patients (295 males) with malignant neoplasms was determined; additionally patients were asked about premorbid/pretherapeutical changes of appetite and weight loss. Cachexia was defined as a weight loss of at least 5% prior to initiation of therapy; to fulfil this criterion this weight loss had to occur independently of other plausible reasons; in single cases weight loss was the initial reason for seeing a physician. The average age in years (± SD) was 59.0 ± 14.5 (males: 58.8 ± 14.0, females 59.2 ± 14.0). Blood samples were taken for genotyping of the Val103Ile by PCR- RFLP.</p> <p>Results</p> <p>Most of the patients suffered from lymphoma, leukaemia and gastrointestinal tumours. 107 of the patients (21%) fulfilled our criteria for cancer cachexia. We did not detect association between the Val103Ile polymorphism and cancer cachexia. However, if we exploratively excluded the patients with early leucaemic stages, we detected a trend towards the opposite effect (p < 0.05); heterozygotes for the 103Ile-allele developed cancer cachexia less frequently in comparison to the rest of the study group. Changes of appetite were not associated with the 103Ile-allele carrier status (p > 0.39).</p> <p>Conclusion</p> <p>Heterozygotes for the 103Ile-allele are not more prone to develop cancer cachexia than patients without this allele; possibly, Ile103 carriers might be more resistant to cancer cachexia in patients with solid tumors. Further studies of the melanocortinergic system in cachexia of patients with solid tumors are warranted.</p

Genetics Meets Metabolomics: A Genome-Wide Association Study of Metabolite Profiles in Human Serum

The rapidly evolving field of metabolomics aims at a comprehensive measurement of ideally all endogenous metabolites in a cell or body fluid. It thereby provides a functional readout of the physiological state of the human body. Genetic variants that associate with changes in the homeostasis of key lipids, carbohydrates, or amino acids are not only expected to display much larger effect sizes due to their direct involvement in metabolite conversion modification, but should also provide access to the biochemical context of such variations, in particular when enzyme coding genes are concerned. To test this hypothesis, we conducted what is, to the best of our knowledge, the first GWA study with metabolomics based on the quantitative measurement of 363 metabolites in serum of 284 male participants of the KORA study. We found associations of frequent single nucleotide polymorphisms (SNPs) with considerable differences in the metabolic homeostasis of the human body, explaining up to 12% of the observed variance. Using ratios of certain metabolite concentrations as a proxy for enzymatic activity, up to 28% of the variance can be explained (p-values 10−16 to 10−21). We identified four genetic variants in genes coding for enzymes (FADS1, LIPC, SCAD, MCAD) where the corresponding metabolic phenotype (metabotype) clearly matches the biochemical pathways in which these enzymes are active. Our results suggest that common genetic polymorphisms induce major differentiations in the metabolic make-up of the human population. This may lead to a novel approach to personalized health care based on a combination of genotyping and metabolic characterization. These genetically determined metabotypes may subscribe the risk for a certain medical phenotype, the response to a given drug treatment, or the reaction to a nutritional intervention or environmental challenge

Protein Kinase C Iota Regulates Pancreatic Acinar-to-Ductal Metaplasia

Pancreatic acinar-to-ductal metaplasia (ADM) is associated with an increased risk of pancreatic cancer and is considered a precursor of pancreatic ductal adenocarcinoma. Transgenic expression of transforming growth factor alpha (TGF-α) or K-rasG12D in mouse pancreatic epithelium induces ADM in vivo. Protein kinase C iota (PKCι) is highly expressed in human pancreatic cancer and is required for the transformed growth and tumorigenesis of pancreatic cancer cells. In this study, PKCι expression was assessed in a mouse model of K-rasG12D-induced pancreatic ADM and pancreatic cancer. The ability of K-rasG12D to induce pancreatic ADM in explant culture, and the requirement for PKCι, was investigated. PKCι is elevated in human and mouse pancreatic ADM and intraepithelial neoplastic lesions in vivo. We demonstrate that K-rasG12D is sufficient to induce pancreatic ADM in explant culture, exhibiting many of the same morphologic and biochemical alterations observed in TGF-α-induced ADM, including a dependence on Notch activation. PKCι is highly expressed in both TGF-α- and K-rasG12D-induced pancreatic ADM and inhibition of PKCι significantly reduces TGF-α- and K-rasG12D-mediated ADM. Inhibition of PKCι suppresses K-rasG12D–induced MMP-7 expression and Notch activation, and exogenous MMP-7 restores K-rasG12D–mediated ADM in PKCι-depleted cells, implicating a K-rasG12D-PKCι-MMP-7 signaling axis that likely induces ADM through Notch activation. Our results indicate that PKCι is an early marker of pancreatic neoplasia and suggest that PKCι is a potential downstream target of K-rasG12D in pancreatic ductal metaplasia in vivo

Role of Ox-PAPCs in the Differentiation of Mesenchymal Stem Cells (MSCs) and Runx2 and PPARγ2 Expression in MSCs-Like of Osteoporotic Patients

BACKGROUND: Mesenchymal stem cells (MSCs) can differentiate into osteoblasts and adipocytes and conditions causing bone loss may induce a switch from the osteoblast to adipocyte lineage. In addition, the expression of Runx2 and the PPARγ2 transcription factor genes is essential for cellular commitment to an osteogenic and adipogenic differentiation, respectively. Modified lipoproteins derived from the oxidation of arachidonate-containing phospholipids (ox-PAPCs: POVPC, PGPC and PEIPC) are considered important factors in atherogenesis. METHODOLOGY: We investigated the effect of ox-PAPCs on osteogenesis and adipogenesis in human mesenchymal stem cells (hMSCs). In particular, we analyzed the transcription factor Runx2 and the PPARγ2 gene expression during osteogenic and adipogenic differentiation in absence and in presence of ox-PAPCs. We also analyzed gene expression level in a panel of osteoblastic and adipogenic differentiation markers. In addition, as circulating blood cells can be used as a "sentinel" that responds to changes in the macro- or micro-environment, we analyzed the Runx2 and the PPARγ2 gene expression in MSCs-like and ox-PAPC levels in serum of osteoporotic patients (OPs). Finally, we examined the effects of sera obtained from OPs in hMSCs comparing the results with age-matched normal donors (NDs). PRINCIPAL FINDINGS: Quantitative RT-PCR demonstrated that ox-PAPCs enhanced PPARγ2 and adipogenic gene expression and reduced Runx2 and osteoblast differentiation marker gene expression in differentiating hMSCs. In OPs, ox-PAPC levels and PPARγ2 expression were higher than in NDs, whereas Runx2 was lower than in ND circulant MSCs-like. CONCLUSIONS: Ox-PAPCs affect the osteogenic differentiation by promoting adipogenic differentiation and this effect may appear involved in bone loss in OPs

A Snapshot of CNVs in the Pig Genome

Recent studies of mammalian genomes have uncovered the extent of copy number variation (CNV) that contributes to phenotypic diversity, including health and disease status. Here we report a first account of CNVs in the pig genome covering part of the chromosomes 4, 7, 14, and 17 already sequenced and assembled. A custom tiling oligonucleotide array was used with a median probe spacing of 409 bp for screening 12 unrelated Duroc boars that are founders of a large family material. After a strict CNV calling pipeline, 37 copy number variable regions (CNVRs) across all four chromosomes were identified, with five CNVRs overlapping segmental duplications, three overlapping pig unigenes and one overlapping a RefSeq pig mRNA. This CNV snapshot analysis is the first of its kind in the porcine genome and constitutes the basis for a better understanding of porcine phenotypes and genotypes with the prospect of identifying important economic traits

Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits

Mining the LIPG Allelic Spectrum Reveals the Contribution of Rare and Common Regulatory Variants to HDL Cholesterol

Genome-wide association studies (GWAS) have successfully identified loci associated with quantitative traits, such as blood lipids. Deep resequencing studies are being utilized to catalogue the allelic spectrum at GWAS loci. The goal of these studies is to identify causative variants and missing heritability, including heritability due to low frequency and rare alleles with large phenotypic impact. Whereas rare variant efforts have primarily focused on nonsynonymous coding variants, we hypothesized that noncoding variants in these loci are also functionally important. Using the HDL-C gene LIPG as an example, we explored the effect of regulatory variants identified through resequencing of subjects at HDL-C extremes on gene expression, protein levels, and phenotype. Resequencing a portion of the LIPG promoter and 5′ UTR in human subjects with extreme HDL-C, we identified several rare variants in individuals from both extremes. Luciferase reporter assays were used to measure the effect of these rare variants on LIPG expression. Variants conferring opposing effects on gene expression were enriched in opposite extremes of the phenotypic distribution. Minor alleles of a common regulatory haplotype and noncoding GWAS SNPs were associated with reduced plasma levels of the LIPG gene product endothelial lipase (EL), consistent with its role in HDL-C catabolism. Additionally, we found that a common nonfunctional coding variant associated with HDL-C (rs2000813) is in linkage disequilibrium with a 5′ UTR variant (rs34474737) that decreases LIPG promoter activity. We attribute the gene regulatory role of rs34474737 to the observed association of the coding variant with plasma EL levels and HDL-C. Taken together, the findings show that both rare and common noncoding regulatory variants are important contributors to the allelic spectrum in complex trait loci

Global assessment of genomic variation in cattle by genome resequencing and high-throughput genotyping

<p>Abstract</p> <p>Background</p> <p>Integration of genomic variation with phenotypic information is an effective approach for uncovering genotype-phenotype associations. This requires an accurate identification of the different types of variation in individual genomes.</p> <p>Results</p> <p>We report the integration of the whole genome sequence of a single Holstein Friesian bull with data from single nucleotide polymorphism (SNP) and comparative genomic hybridization (CGH) array technologies to determine a comprehensive spectrum of genomic variation. The performance of resequencing SNP detection was assessed by combining SNPs that were identified to be either in identity by descent (IBD) or in copy number variation (CNV) with results from SNP array genotyping. Coding insertions and deletions (indels) were found to be enriched for size in multiples of 3 and were located near the N- and C-termini of proteins. For larger indels, a combination of split-read and read-pair approaches proved to be complementary in finding different signatures. CNVs were identified on the basis of the depth of sequenced reads, and by using SNP and CGH arrays.</p> <p>Conclusions</p> <p>Our results provide high resolution mapping of diverse classes of genomic variation in an individual bovine genome and demonstrate that structural variation surpasses sequence variation as the main component of genomic variability. Better accuracy of SNP detection was achieved with little loss of sensitivity when algorithms that implemented mapping quality were used. IBD regions were found to be instrumental for calculating resequencing SNP accuracy, while SNP detection within CNVs tended to be less reliable. CNV discovery was affected dramatically by platform resolution and coverage biases. The combined data for this study showed that at a moderate level of sequencing coverage, an ensemble of platforms and tools can be applied together to maximize the accurate detection of sequence and structural variants.</p