Genome-wide association study identifies a susceptibility locus for biliary atresia on 10q24.2.

Biliary atresia (BA) is characterized by the progressive fibrosclerosing obliteration of the extrahepatic biliary system during the first few weeks of life. Despite early diagnosis and prompt surgical intervention, the disease progresses to cirrhosis in many patients. The current theory for the pathogenesis of BA proposes that during the perinatal period, a still unknown exogenous factor meets the innate immune system of a genetically predisposed individual and induces an uncontrollable and potentially self-limiting immune response, which becomes manifest in liver fibrosis and atresia of the extrahepatic bile ducts. Genetic factors that could account for the disease, let alone for its high incidence in Chinese, are to be investigated. To identify BA susceptibility loci, we carried out a genome-wide association study (GWAS) using the Affymetrix 5.0 and 500 K marker sets. We genotyped nearly 500 000 single-nucleotide polymorphisms (SNPs) in 200 Chinese BA patients and 481 ethnically matched control subjects. The 10 most BA-associated SNPs from the GWAS were genotyped in an independent set of 124 BA and 90 control subjects. The strongest overall association was found for rs17095355 on 10q24, downstream XPNPEP1, a gene involved in the metabolism of inflammatory mediators. Allelic chi-square test P-value for the meta-analysis of the GWAS and replication results was 6.94 x 10(-9). The identification of putative BA susceptibility loci not only opens new fields of investigation into the mechanisms underlying BA but may also provide new clues for the development of preventive and curative strategies.

Genome-wide association study identifies NRG1 as a susceptibility locus for Hirschsprung's disease.

Hirschsprung's disease (HSCR), or aganglionic megacolon, is a congenital disorder characterized by the absence of enteric ganglia in variable portions of the distal intestine. RET is a well-established susceptibility locus, although existing evidence strongly suggests additional loci contributing to sporadic HSCR. To identify these additional genetic loci, we carried out a genome-wide association study using the Affymetrix 500K marker set. We successfully genotyped 293,836 SNPs in 181 Chinese subjects with sporadic HSCR and 346 ethnically matched control subjects. The SNPs most associated with HSCR were genotyped in an independent set of 190 HSCR and 510 control subjects. Aside from SNPs in RET, the strongest overall associations in plausible candidate genes were found for 2 SNPs located in intron 1 of the neuregulin1 gene (NRG1) on 8p12, with rs16879552 and rs7835688 yielding odds ratios of 1.68 [CI(95%):(1.40, 2.00), P = 1.80 x 10(-8)] and 1.98 [CI(95%):(1.59, 2.47), P = 1.12 x 10(-9)], respectively, for the heterozygous risk genotypes under an additive model. There was also a significant interaction between RET and NRG1 (P = 0.0095), increasing the odds ratio 2.3-fold to 19.53 for the RET rs2435357 risk genotype (TT) in the presence of the NRG1 rs7835688 heterozygote, indicating that NRG1 is a modifier of HSRC penetrance. Our highly significant association findings are backed-up by the important role of NRG1 as regulator of the development of the enteric ganglia precursors. The identification of NRG1 as an additional HSCR susceptibility locus not only opens unique fields of investigation into the mechanisms underlying the HSCR pathology, but also the mechanisms by which a discrete number of loci interact with each other to cause disease.

iCartiGD: the Integrated Cartilage Gene Database.

BACKGROUND: Diseases of cartilage, such as arthritis and degenerative disc disease, affect the majority of the general population, particularly with ageing. Discovery and understanding of the genes and pathways involved in cartilage biology will greatly assist research on the development, degeneration and disorders of cartilage. DESCRIPTION: We have established the Integrated Cartilage Gene Database (iCartiGD) of genes that are known, based on results from high throughput experiments, to be expressed in cartilage. Information about these genes is extracted automatically from public databases and presented as a single page report via a web-browser. A variety of flexible search options are provided and the chromosomal distribution of cartilage associated genes can be presented. CONCLUSION: iCartiGD provides a comprehensive source of information on genes known to be expressed in cartilage. It will remain current due to its automatic update capability and provide researchers with an easily accessible resource for studies involving cartilage. Genetic studies of the development and disorders of cartilage will benefit from this database.

Structural basis and sequence co-evolution analysis of the hemagglutinin protein of pandemic influenza A/H1N1 (2009) virus.

Severe pandemic influenza A H1N1 (2009) infection, especially in the lower respiratory tract, is often associated with the virus carrying a D222G substitution in the hemagglutinin (HA) protein of the virus. The mechanism for this association has not been fully explored. In the in vitro binding assay, it was found that clinical isolates carrying D222G substitution exhibit higher binding avidity to 2,3-linked sialic acids than the wild-type virus. The receptor binding pocket of the pandemic influenza (H1N1) HA was found to be smaller than those of other influenza A strains, allowing tighter binding of the virus with the receptor, yet also inducing steric stress for the binding. Our homology modeling and molecular docking calculations implicated that residue 222 may affect the positioning of the conserved Q223 residue, hence modulating flexibility of the binding pocket and steric hindrance during receptor binding. The molecular property of residue 222 can also directly influence the 'lysine fence' via the polarity of the amino acid residue where D222G substitution will enhance the electrostatic interactions between the receptor and the protein. The potential importance of residue 222 was illustrated by evolutionary analysis, which showed that this site is under intense selection pressure during adaptation of the virus to human host. Our findings provide a useful reference for follow-up studies in monitoring the ongoing evolution of the pandemic influenza A H1N1 (2009) virus.

In silico analysis of 16S rRNA gene sequencing based methods for identification of medically important aerobic Gram-negative bacteria.

This study provides guidelines on the usefulness of full and 527 bp 16S rRNA gene sequencing and Microseq databases for identifying medically important aerobic Gram-negative bacteria. Overall, full and 527 bp 16S rRNA gene sequencing can identify 26.1 % and 32.6 %, respectively, of medically important aerobic Gram-negative bacteria confidently to the species level, whereas the full-MicroSeq and 500-MicroSeq databases can identify 15.2 % and 26.1 %, respectively, of medically important aerobic Gram-negative bacteria confidently to the species level. Among the major groups of aerobic Gram-negative bacteria, the methods and databases are least useful for identification of Aeromonas, Bordetella and Bartonella species. None of the Aeromonas species can be confidently or doubtfully identified, whereas only 0 % and 0-33.3 % of Bordetella species and 0-10 % and 0-10 % of Bartonella species can be confidently and doubtfully identified, respectively. On the other hand, these methods and databases are most useful for identification of members of the families Pasteurellaceae and Legionellaceae and Campylobacter species: 29.6-59.3 % and 7.4-18.5 % of members of Pasteurellaceae, 36-52 % and 12-24 % of members of Legionellaceae, and 26.7-60 % and 0-13.3 % of Campylobacter species can be confidently and doubtfully identified, respectively. Thirty-nine medically important aerobic Gram-negative bacteria that should be confidently identified by full 16S rRNA gene sequencing are not included in the full-MicroSeq database. Twenty-three medically important aerobic Gram-negative bacteria that should be confidently identified by 527 bp 16S rRNA gene sequencing are not included in the 500-MicroSeq database. Compared with results of our previous studies on anaerobic and Gram-positive bacteria, full and 527 bp 16S rRNA gene sequencing are able to confidently identify significantly more anaerobic Gram-positive and Gram-negative bacteria than aerobic Gram-positive and Gram-negative bacteria.