Case-control association analysis of rheumatoid arthritis with candidate genes using related cases

We performed a case-control association analysis of rheumatoid arthritis (RA) for several candidate genes using the North American Rheumatoid Arthritis Consortium (NARAC) data provided in Genetic Analysis Workshop 15. We conducted the case-control association analysis using all related cases and unrelated controls and compared the results with those from the analysis of samples using only one randomly selected case from each family and all unrelated controls. For both analyses we used a weighted composite likelihood ratio test based on single-nucleotide polymorphism (SNP) markers or haplotypes accounting for the correlation among samples within a family. Several SNPs, including R620W in the candidate gene PTPN22, showed an association with RA status, which confirmed previously reported results. Several other SNPs in the candidate genes, such as CTLA4, HAVCR1, and SUMO4, also had rather small p-values (<0.05), suggesting the associations between them and RA. Our results showed that the p-values obtained from the analysis including all related cases were generally smaller than those obtained from the analysis including only one randomly selected case per family. These results, together with the results, based on simulated data, showed that higher power could be achieved using all related cases

Effects of Single Nucleotide Polymorphism Marker Density on Haplotype Block Partition

Many researchers have found that one of the most important characteristics of the structure of linkage disequilibrium is that the human genome can be divided into non-overlapping block partitions in which only a small number of haplotypes are observed. The location and distribution of haplotype blocks can be seen as a population property influenced by population genetic events such as selection, mutation, recombination and population structure. In this study, we investigate the effects of the density of markers relative to the full set of all polymorphisms in the region on the results of haplotype partitioning for five popular haplotype block partition methods: three methods in Haploview (confidence interval, four gamete test, and solid spine), MIG++ implemented in PLINK 1.9 and S-MIG++. We used several experimental datasets obtained by sampling subsets of single nucleotide polymorphism (SNP) markers of chromosome 22 region in the 1000 Genomes Project data and also the HapMap phase 3 data to compare the results of haplotype block partitions by five methods. With decreasing sampling ratio down to 20% of the original SNP markers, the total number of haplotype blocks decreases and the length of haplotype blocks increases for all algorithms. When we examined the marker-independence of the haplotype block locations constructed from the datasets of different density, the results using below 50% of the entire SNP markers were very different from the results using the entire SNP markers. We conclude that the haplotype block construction results should be used and interpreted carefully depending on the selection of markers and the purpose of the study

Evolution of rubisco complex small subunit transit peptides from algae to plants

Chloroplasts evolved from a free-living cyanobacterium acquired by the ancestor of all photosynthetic eukaryotes, including algae and plants, through a single endosymbiotic event. During endosymbiotic conversion, the majority of genes in the endosymbiont were transferred to the host nucleus and many of the proteins encoded by these genes must therefore be transported into the chloroplast after translation in the cytosol. Chloroplast-targeted proteins contain a targeting signal, named the transit peptide (TP), at the N-terminus. However, the evolution of TPs is not well understood. In this study, TPs from RbcS (rubisco small subunit) were compared between lower and higher eukaryotes. Chlamydomonas reinhardtii RbcS (CrRbcS) TP was non-functional in Arabidopsis. However, inclusion of a critical sequence motif, FP-RK, from Arabidopsis thaliana RbcS (AtRbcS) TP allowed CrRbcS TP to deliver proteins into plant chloroplasts. The position of the FP-RK motif in CrRbcS TP was critical for function. The QMMVW sequence motif in CrRbcS TP was crucial for its transport activity in plants. CrRbcS TPs containing additional plant motifs remained functional in C. reinhardtii. These results suggest that TPs evolved by acquiring additional sequence motifs to support protein targeting to chloroplasts during evolution of land plants from algae.113Ysciescopu

Genome-wide association analyses of North American Rheumatoid Arthritis Consortium and Framingham Heart Study data utilizing genome-wide linkage results

The power of genome-wide association studies can be improved by incorporating information from previous study findings, for example, results of genome-wide linkage analyses. Weighted false-discovery rate (FDR) control can incorporate genome-wide linkage scan results into the analysis of genome-wide association data by assigning single-nucleotide polymorphism (SNP) specific weights. Stratified FDR control can also be applied by stratifying the SNPs into high and low linkage strata. We applied these two FDR control methods to the data of North American Rheumatoid Arthritis Consortium (NARAC) study and the Framingham Heart Study (FHS), combining both association and linkage analysis results. For the NARAC study, we used linkage results from a previous genome scan of rheumatoid arthritis (RA) phenotype. For the FHS study, we obtained genome-wide linkage scores from the same 550 k SNP data used for the association analyses of three lipids phenotypes (HDL, LDL, TG). We confirmed some genes previously reported for association with RA and lipid phenotypes. Stratified and weighted FDR methods appear to give improved ranks to some of the replicated SNPs for the RA data, suggesting linkage scan results could provide useful information to improve genome-wide association studies

The first Irish genome and ways of improving sequence accuracy

Whole-genome sequencing of an Irish person reveals hundreds of thousands of novel genomic variants. Imputation using previous known information improves the accuracy of low-read-depth sequencing

Region-based analysis in genome-wide association study of Framingham Heart Study blood lipid phenotypes

Due to the high-dimensionality of single-nucleotide polymorphism (SNP) data, region-based methods are an attractive approach to the identification of genetic variation associated with a certain phenotype. A common approach to defining regions is to identify the most significant SNPs from a single-SNP association analysis, and then use a gene database to obtain a list of genes proximal to the identified SNPs. Alternatively, regions may be defined statistically, via a scan statistic. After categorizing SNPs as significant or not (based on the single-SNP association p-values), a scan statistic is useful to identify regions that contain more significant SNPs than expected by chance. Important features of this method are that regions are defined statistically, so that there is no dependence on a gene database, and both gene and inter-gene regions can be detected. In the analysis of blood-lipid phenotypes from the Framingham Heart Study (FHS), we compared statistically defined regions with those formed from the top single SNP tests. Although we missed a number of single SNPs, we also identified many additional regions not found as SNP-database regions and avoided issues related to region definition. In addition, analyses of candidate genes for high-density lipoprotein, low-density lipoprotein, and triglyceride levels suggested that associations detected with region-based statistics are also found using the scan statistic approach

Power of maximum HLOD tests to detect linkage to obesity genes

BACKGROUND: We investigate the power of heterogeneity LOD test to detect linkage when a trait is determined by several major genes using Genetic Analysis Workshop 13 simulated data. We consider three traits, two of which are disease-causing traits: 1) the rate of change in body mass index (BMI); and 2) the maximum BMI; and 3) the disease itself (hypertension). Of interest is the power of "HLOD2", the maximum heterogeneity LOD obtained upon maximizing over the two genetic models. RESULTS: Using a trait phenotype Obesity Slope, we observe that the power to detect the two markers closest to the two genes (S1, S2) at the 0.05 level using HLOD2 is 13% and 10%. The power of HLOD2 for Max BMI phenotype is 12% and 9%. The corresponding values for the Hypertension phenotype are 8% and 6%. CONCLUSION: The power to detect linkage to the slope genes is quite low. But the power using disease-related traits as a phenotype is greater than the power using the disease (hypertension) phenotype

Markedly enhanced intratumoral spread and antitumor effect of oncolytic adenovirus expressing decorin

With the aim of improving viral distribution and tumor penetration, we have engineered decorin expressing replication-incompetent (dl-LacZ-DCNG) and -competent (Ad-[DELTA]E1B-DCNG) adenoviruses. In both tumor spheroids and established solid tumors in vivo, administration of dl-LacZ-DCNG resulted in greater transduction efficiency and viral spread throughout the tumor mass. Ad-[DELTA]E1B-DCNG also enhanced viral distribution and tumor spread, leading to an increased anti-tumor effect and survival advantage. Upon histological analysis, Ad-[DELTA]E1B-DCNG also elicited greater percentage of apoptotic cells and extensive necrosis compared to those from untreated or control virus-treated tumors. Furthermore, Ad-[DELTA]E1B-DCNG substantially decreased extracellular matrix components within the tumor tissue, while normal tissue adjacent to the tumor was not affected. Finally, intratumoral administration of Ad-[DELTA]E1B-DCNG did not enhance but inhibited the formation of pulmonary metastases of B16BL6 melanoma cells in mice. Taken together, these data demonstrate the utility of decorin as a dispersion agent and suggest its utility and potential in improving the efficacy of replicating adenovirus-mediated cancer gene therapy

Antimicrobial peptide from Bacillus subtilis CSB138: characterization, killing kinetics, and synergistic potency

We studied the prospect of synergy between the antimicrobial peptide p138c and non-peptide antibiotics for increasing the potency and bacterial killing kinetics of these agents. The production of p138c was maximized in the late exponential growth phase of Bacillus subtilis CSB138. Purification of p138c resulted in a total of 4800 arbitrary units (AU) with 19.15-fold and 3.2% recovery. Peptide p138c was thermo-tolerant up to 50 &deg;C and stable at pH 5.8 to 11. The biochemical nature of p138c was determined by a bioassay, similar to tricine-SDS-PAGE, indicating inhibition at 3 kDa. The amino acid sequence of p138c was Gly-Leu-Glu-Glu-Thr-Val-Tyr-Ile-Tyr-Gly-Ala-Asn-Met-X-Ser. Potency and killing kinetics against vancomycin-resistant Staphylococcus aureus improved considerably when p138c was synergized with oxacillin, ampicillin, and penicillin G. The minimal inhibitory concentration (MIC) of p138c showed a 4-, 8-, and 16-fold improvement when p138c was combined with oxacillin, ampicillin, and penicillin G, respectively. The fractional inhibitory concentration index for the combination of p138c and oxacillin, ampicillin, and penicillin G was 0.3125, 0.25, and 0.09, respectively. Synergy with non-peptide antibiotics resulted in enhanced killing kinetics of p138c. Hence, the synergy between antimicrobial peptide and non-peptide antibiotics may enhance the potency and bacterial killing kinetics, providing more potent and rapidly acting agents for therapeutic use. [Int Microbiol 20(1):43-53 (2017)]Keywords: Bacillus subtilis &middot; antimicrobial peptides &middot; killing kinetic